26 Years of Tanzania's Financial System, 2000–2026: Who Has Benefited From Its Growth?
How has Tanzania's financial system changed since 2000, and what does that say about how the economy is financed? Credit to the private sector has grown from about TZS 301 billion to TZS 56.4 trillion, and by September 2026 it was growing at 34% a year. This analysis follows credit, deposits, government claims, external assets and currency across six periods, then asks the harder question: whether a bigger system has given the private sector better access to capital, and which sectors and borrowers have gained.
📅 October 2026📍 Tanzania🏛️ TICGL / TERI Economic Research Division📖 Basis: BoT monthly data Jan 2000–Sep 2026; BoT Monthly Economic Review, Sep 2026
Credit to private sector
TZS 56.4 tn187x Jan 2000
Private credit / M3
77.4%from 24.4%
Credit growth, Sep 2026
34.2%M3: 25.9%
Private credit / GDP, 2025
19.1%13.8% in 2018
Source: Bank of Tanzania, Depository Corporations Survey (monthly, nominal TZS) and Monthly Economic Review, September 2026 (Table A1); TICGL calculations. "Credit to the private sector" is the survey line "Claims on non-central government sector", the same series the Review reports.
00 — OverviewExecutive Summary: A System That Grew Fast, Mostly by Lending More to the Private Sector
Four forces shaped 26 years of change. Credit to the private sector outgrew deposits, so its share of broad money (M3) rose from 24% to 77%. Government moved from the banks' main borrower to a net depositor in most years of 2003–2008, and back to a large net borrower from 2010. Net foreign assets grew about 15-fold since 2000 but fell from 60% to 18% of M3. Cash and dollars lost ground to bank deposits in shillings.
Credit growth, 2000–Sep 2026
21.6% a year
nominal CAGR; M3 16.7%
Credit / total domestic credit
81.1%
Sep 2026; 77.9% in 2025
Net claims on Government
TZS 13.1 tn
Sep 2026; −0.1 tn in 2003
Net foreign assets / M3
18.1%
Sep 2026; 62.7% in 2005
Credit to the Private Sector and M3, 2000–2026
TZS billion, year-end (Sep for 2026), logarithmic scale. Source: Bank of Tanzania; TICGL calc.
Private Credit and FX Deposits as % of M3
Percent, year-end. Source: Bank of Tanzania; TICGL calc.
TZS billion unless stated
2000
2005
2010
2015
2020
2025
Sep 2026
Credit to private sector
341
1,654
5,992
15,493
20,308
44,603
56,359
Extended broad money (M3)
1,398
4,251
11,013
22,115
29,921
60,989
72,828
Private credit / M3 (%)
24.4
38.9
54.4
70.1
67.9
73.1
77.4
Government (net)
347
185
807
4,882
5,831
12,627
13,120
Net foreign assets
843
2,665
6,126
8,244
10,722
15,286
13,152
NFA / M3 (%)
60.3
62.7
55.6
37.3
35.8
25.1
18.1
FX deposits / M3 (%)
21.8
30.4
27.0
28.6
23.0
21.7
21.3
Currency / M2 (%)
35.9
30.1
23.6
23.3
19.5
17.8
16.4
M2 / reserve money
1.97
2.30
2.30
2.31
3.21
3.29
3.35
Table 1. Key aggregates at year-end. Source: Bank of Tanzania; ratios are TICGL calculations.
Six periods of change
2000–2003: take-off. Credit tripled; Government turned net depositor in 2003; FX deposits rose to a third of M3 (a reclassification affects Dec 2001).
2004–2008: credit boom. Credit growth of 26–45% a year; Government stayed a net depositor except in 2005.
2009–2015: government returns. Net government claims rose from TZS 0.1 tn to 4.9 tn while credit still grew 10–27% a year.
2016–2021: stall. Credit growth fell to 1.7% in 2017 and 3.1% in 2020; government claims stayed above TZS 3 tn.
2022–2025: recovery. Credit growth of 13–24% a year; credit/GDP rose from 15.3% to 19.1%.
2026: acceleration. Credit grew 34.2% in September; the Bank raised its policy rate to 6.25% in July.
01 — Credit, Deposits & CurrencyMore Money in Banks, Less in Wallets
What the Money Stock Is Made Of
TZS trillion, stacked. Deposits in shillings are M2 minus currency. Source: Bank of Tanzania; TICGL calc.
Currency as % of M2, and the Money Multiplier
Bars: currency in circulation as % of M2 (left). Line: M2 ÷ reserve money (right). Source: Bank of Tanzania; TICGL calc.
Cash fell from 36% to 16% of M2 between 2000 and September 2026, and the M2 multiplier rose from 1.97 to 3.35, a sign of deeper deposit-taking.
Dollarisation peaked then eased. FX deposits reached about 33% of M3 in 2003 and 2006, and are 21.3% in September 2026, though the level is large (USD 6.1 bn in August 2026).
Deposits have not kept pace with lending. Credit grew 34.2% against M3 25.9% in the year to September 2026, so the loan-to-money ratio keeps rising.
Series note
The monthly series has a definitional step in December 2001 (quasi-money jumps from about 64% to 89% of M2), so year-on-year changes for 2001 and composition shifts around it mix real change with reclassification.
02 — Government & ExternalWho Competes With the Private Sector for Bank Funds, and What Protects the System
Banking System's Net Claims on Government
TZS billion, year-end (Sep for 2026). Negative means Government is a net depositor. Source: Bank of Tanzania; TICGL calc.
Net Foreign Assets and Their Share of M3
Bars: TZS billion (left). Line: % of M3 (right). Source: Bank of Tanzania; TICGL calc.
Percent of TZS 40,899.5 bn. Source: Ministry of Finance; BoT Monthly Economic Review, Sep 2026
Crowding out was largely absent in 2003–2008 and is back. Net claims on Government went from −TZS 0.1 tn (2003) to 13.1 tn (Sep 2026), 18.9% of domestic credit.
Banks are major holders of government paper. Commercial banks hold 28.4% of domestic debt and their securities holdings were up 40.3% in the year to August 2026, faster than private credit (33.0%).
The external buffer is thinner relative to money. Net foreign assets of banks turned negative (−TZS 0.99 tn) in September 2026; at end-August the Bank of Tanzania held gross reserves of USD 5.9 bn, 4.2 months of imports.
03 — Who Benefited?Sector, Borrower and Cost of Credit, August 2025–August 2026
Credit grew 33% in the year to August 2026. Its distribution shows where the expansion is going; interest rates show what it costs. Only a year of sector data is in the sources, so these are a snapshot of the latest boom, not a 26-year record.
Share of Bank Credit by Activity
Percent of total credit, selected activities (the remainder, about 15%, is other sectors). Source: Banks and Bank of Tanzania, Review Chart 2.2.6
Annual Credit Growth by Activity
Percent. Source: Banks and Bank of Tanzania, Review Table 2.2.2
What Credit and Deposits Cost, Aug 2026
Percent a year. Source: Banks and Bank of Tanzania computations, Review Tables 2.3.1 and A4
What the numbers say about access
Personal loans lead, and most support MSMEs. At 34.1% of credit they are the largest component, but their share fell from 36.0% in August 2025 and growth (24.9%) is below the 33% average.
The boom is in transport, communication and mining (+77% and +76%), then trade (+47%), construction (+42%) and agriculture (+38%).
Manufacturing is small and volatile: 7.4% of credit; growth recovered to 12.9% after −8.2% in December 2025.
Price of access: the overall lending rate is 15.05% against 11.93% for negotiated (prime) loans, a 3.1-point gap, and a 12-month deposit rate of 9.36%. Short-term lending still costs 15.3%.
What these data cannot show
The sources have no breakdown by firm size beyond personal loans, no regional or gender split, and no financial-inclusion survey data. They show where bank credit went, not who is still without it. Answering "who benefited" fully needs sector and firm-size credit series, and FinScope or Global Findex access data.
04 — The Growth LinkCredit Grew Faster Than the Economy, but the Two Have Not Moved Together
Credit Growth vs Real GDP Growth, and Credit Depth, 2018–2025
Lines: annual % growth of credit to the private sector and of real GDP (left). Bars: credit / GDP, % (right). Source: BoT Monthly Economic Review, Sep 2026, Table A1
Depth rose: credit/GDP went from 13.8% to 19.1%, and credit growth ran at two to five times real GDP growth in 2022–2025.
No visible link in this window. Across these eight years the correlation between credit growth and real GDP growth is about zero (and about zero for M3). With eight points, shocks such as 2020 and nominal credit growth, this neither supports nor refutes a causal link.
Real growth stayed near 5–6% while GDP per head in USD was flat (USD 1,083 in 2018, 1,087 in 2025), so more credit has not yet shown up as faster income growth in these data.
What a full test needs
GDP and prices for 2000–2017, real (deflated) credit, sector value added to match the sector credit data, and controls for investment, trade and the fiscal position, then lagged and error-correction models. TICGL/TERI can run these once the series are assembled.
Extend this analysis
Send sector and firm-size credit series and access surveys, and TICGL/TERI will add the "who benefited" evidence across the full period.
How much has credit to the private sector grown in Tanzania since 2000?
In Bank of Tanzania data, credit to the private sector rose from about TZS 301 billion in January 2000 to TZS 56.4 trillion in September 2026, roughly 187 times in nominal terms or about 21.6 percent a year, and from 24% to 77% of extended broad money.
Which sectors are getting the credit in 2026?
Personal loans, mostly supporting micro, small and medium enterprises, remain the largest part of bank credit at 34.1 percent in August 2026, followed by trade and agriculture. Growth is fastest in transport and communication (77 percent) and mining (76 percent), while manufacturing is only 7.4 percent of credit.
Is a bigger financial system the same as more access to capital?
No. Credit to the private sector is 19.1 percent of GDP in 2025, up from 13.8 percent in 2018, and the overall lending rate is still about 15 percent against a 12-month deposit rate near 9 percent. Data on firm size and access to financial services are needed to say who is reached.
Does the data show that finance has driven growth?
Not on its own. Between 2018 and 2025 annual credit growth and real GDP growth show no visible co-movement in the eight observations available, and GDP is not available before 2018 in the sources used. A causal test needs a longer GDP series and controls.
06 - Explore MoreTICGL Economic: Related Insights & Tools
Related Analysis
Is Tanzania's Economy Growing?
The growth backdrop for credit, trade and incomes.
Miaka 26 ya mfumo wa fedha Tanzania: nani amefaidika? Kwa data ya Benki Kuu (Januari 2000 hadi Septemba 2026) na Mapitio ya Kiuchumi ya Septemba 2026, mikopo kwa sekta binafsi ilipanda kutoka TZS bilioni 301 hadi trilioni 56.4 (mara 187; wastani wa asilimia 21.6 kwa mwaka). Sehemu yake kwenye M3 ilipanda kutoka asilimia 24 hadi 77, na mwezi Septemba 2026 mikopo ilikua asilimia 34.2 (M3 asilimia 25.9).
Serikali na akiba ya nje: Serikali ilikuwa mweka-akiba wa jumla katika miaka mingi ya 2003–2008, lakini madai yake halisi yamepanda hadi TZS trilioni 13.1 (2026), huku benki zikishikilia asilimia 28.4 ya deni la ndani. Mali halisi za kigeni zilikua mara 15 lakini zimeshuka kutoka asilimia 60 hadi 18 ya M3. Fedha taslimu ilishuka kutoka asilimia 36 hadi 16 ya M2.
Nani amefaidika? Mikopo binafsi (zaidi ya biashara ndogo na za kati) ni asilimia 34.1, ikifuatiwa na biashara na kilimo; ukuaji mkubwa upo kwenye usafirishaji na mawasiliano (asilimia 77) na madini (asilimia 76). Viwanda ni asilimia 7.4 tu. Riba ya mikopo ni takriban asilimia 15 dhidi ya asilimia 9.4 ya amana za miezi 12.
Uhusiano na ukuaji: mikopo kwa GDP ilipanda kutoka asilimia 13.8 (2018) hadi 19.1 (2025), lakini ukuaji wa mikopo na wa GDP halisi haujaonyesha mwelekeo mmoja katika miaka hiyo minane. Tunahitaji GDP ya 2000–2017, mikopo kwa sekta na ukubwa wa biashara, na tafiti za upatikanaji wa huduma (FinScope) ili kujibu kikamilifu. Wasiliana: economist@ticgl.com.
07 - SourcesMethod and Sources
Data, calculations and limits
Bank of Tanzania, Depository Corporations Survey, monthly, January 2000–September 2026, millions of TZS (file supplied by TICGL). Year-end values are December; 2026 is September. "Credit to the private sector" is the line "Claims on non-central government sector", which matches the Review's definition (checked against Table A1, 2018–2025).
Bank of Tanzania, Monthly Economic Review, September 2026: Tables 2.2.1, 2.2.2, 2.3.1, 2.6.1–2.6.6, A1, A3, A4; Charts 2.2.6, 2.6.1. Sector shares and growth cover Aug 2025–Aug 2026 only.
TICGL calculations: multiples, CAGR (Jan 2000–Sep 2026), ratios to M3, M2 and domestic credit, correlations (2018–2025, n = 8). All values nominal.
Bankable or Affordable? Who Pays for Tanzania's LGA Projects | TICGL
The Bankability–Affordability Dilemma: Who Pays When Tanzania's Local Government Projects Must Repay Their Lenders?
Local Government Authorities (LGAs) are being encouraged to plan and run revenue-generating projects, from markets and bus terminals to housing, waste, tourism and public transport, to raise own-source revenue and lean less on the centre. To attract private capital those projects must be "bankable": revenue has to repay lenders and reward investors. But the people who use them are often low-income, and an LGA's role is to provide a service, not to maximise profit. This is a general problem for any LGA project that must earn from the people it serves. This page uses markets and bus terminals as case studies: in TICGL/TERI's illustrative case, the rent a lender needs is 3.4 to 7 times what the median user says they can pay. The gap does not disappear when a project is labelled a PPP. It moves, to traders, to citizens, to taxpayers or to investors.
📅 Report: October 2026📍 Tanzania, Local Government Authorities✍️ Author: Amran Bhuzohera🏛️ TICGL / TERI Economic Research Division📖 Basis: case survey, public evidence, three financial models
Required vs affordable rent
3.4–7.0x median TZS 8,300/m²
Yield on cost at stated rents
2.3–4.6% 15-yr bond 10.8%
Anchor rent needed to cross-subsidise
TZS 105k–247k per m² / month
Price rise if rent goes to TZS 300k
+90% at TZS 250k sales
Source: TICGL/TERI, The Bankability–Affordability Dilemma, October 2026, by Amran Bhuzohera (Sections 5–6, Tables 8–12); 15-year Treasury bond yield 10.79%, week to 2 October 2026. Figures come from one anonymised pre-feasibility data set plus explicit assumptions; they show direction and order of magnitude, not statistically precise estimates.
Read first: two TICGL studies that frame this research
This report asks who pays when a project must repay lenders and also serve low-income users. These two companion studies ask why Tanzanian projects fail to reach financial close in the first place, and how the capital stack that sits above the equity should be built.
Project Finance in Tanzania
Tanzania's investment gap stems mainly from weak project preparation, limited long-term debt and shallow capital markets, not from a lack of investor interest. Only about 22% of the USD 7.7 billion of FDI registered in 2024 was disbursed.
Beyond Bankability: Why the Project Finance Capital Stack Is the Root Cause of Investment Failure
The shortfall comes mainly from the inability to assemble the debt and blended-finance layers above equity. It points to pension-fund infrastructure allocations, a viability gap fund and a long-tenor infrastructure lender, the same levers this report tests for LGA projects.
Prepared by TERI for research and strategic-information purposes only. It is not investment, legal, tax or financial advice. The markets and bus terminals discussed are case studies of a wider LGA problem, and the empirical illustrations use an anonymised pre-feasibility case; project, place and respondent names are withheld. Construction-cost, yield and operating-cost inputs are explicit assumptions (listed under Sources & Assumptions) and must be replaced with quantity-surveyor and financial-model figures for any real project. The case evidence is small, non-random and self-reported. Press and public-domain evidence is quoted as reported and is not always like-for-like with a PPP.
00 — OverviewExecutive Summary: Bankable on Paper, Unaffordable in the Market
Tanzania's decentralisation reforms aim to give LGAs more fiscal autonomy, and the current policy push adds private financing and PPPs for revenue-generating assets across sectors, including housing, waste, tourism, public transport, markets, shop complexes and bus terminals. The logic is attractive: the private sector brings capital and management, the LGA keeps the land and earns a share of revenue. The difficulty is structural. When the asset earns only from charges, the only cash flows available are the rents, fees and tariffs paid by the very people the project is meant to serve. TICGL/TERI tested whether bankability and affordability can be met at once, using markets and bus terminals as case studies, with public evidence on Tanzanian and regional experience and data from one illustrative project.
Why markets and bus terminals? They are case studies, not the limit of the argument
The same arithmetic applies to any LGA project planned or operated on user charges: required revenue is set by capital cost, cost of money and operating cost, while affordable revenue is set by what users can pay. Markets and terminals are used here because their rents, fees and bypass behaviour can be observed and counted. The nine-point screen in Tab 9 and the pass-through test in Tab 7 are written to be reused for other LGA projects.
Required rent, base case
TZS 58,200
per lettable m² per month
Median stated affordability
TZS 8,300
upper quartile 16,700; highest 17,100
Gap after 50% grant + cheaper debt
2.3–2.6x
still above the median trader
Public capital needed for affordability
60–70%
at a ~12% hurdle rate
Independent models
3
yield-on-cost, capital-recovery and lender-style (DSCR)
Traders with sales under TZS 500k
76%
16 of 21 existing traders
LGA PPP pipeline vs signed deals
410 : 9
projects in 184 LGAs; 9 contracts nationally by Jun 2026
Magufuli terminal rent arrears
TZS 249 m+
September 2026, Ubungo council
Rent Needed vs Rent Users Can Afford
TZS thousand per lettable m² per month. Teal: stated affordability. Red: required rent on commercial terms (Model A, Annex A). Source: TICGL/TERI case survey and models
Yield on Cost: What Affordable Rent Earns vs What Capital Demands
Percent a year on construction cost. Stated rents earn 2–5%; lenders and investors price off a 10.8% government bond. Source: TICGL/TERI; bond yield week to 2 Oct 2026
Key findings
The gap is large and robust to method. Three independently built models find that on commercial terms the rent needed to repay the building is 3.4 to 7 times what the median respondent says they can pay (median about TZS 8,300 per lettable m² per month; upper quartile TZS 16,700).
Affordable rents carry only a fraction of the building. At stated affordability, rent supports roughly 14–39% of construction cost and yields 2–5% on cost, against about 10.8% on a 15-year government bond. A 50% capital grant plus cheaper long-tenor debt still leaves required rent at 1.3–2.6 times what traders say they can pay.
Cross-subsidy has a hard ceiling. If 50–80% of space is let at affordable rents, anchor tenants would have to pay TZS 105,000–247,000 per m² per month. Half of prospective tenants (8 of 16) can pay more than TZS 200,000, which helps but does not close the gap.
The gap does not disappear; it moves. Whoever closes it (traders, consumers, taxpayers or investors) bears it. Making a project bankable by user charges transfers the cost to traders and, where they can, to the citizen.
For small traders, pass-through is arithmetically impossible. Raising rent from TZS 75,000 to TZS 300,000 would need a 90% price rise at TZS 250,000 of sales (45% even at the top of the band); at TZS 520,000 rent, 178%. In practice traders exit, sub-let or go informal.
For high-volume operators and commuters, pass-through is feasible but regressive. A restaurant adds roughly TZS 50–135 per customer (1–3% of spend); a TZS 1,000–2,000 stand fee is about TZS 35–135 per passenger per trip, and 9 of 12 surveyed customers visit daily.
Tanzania's own terminals show the risk. The TZS 54.6 billion Magufuli terminal (about 93% central-grant funded) struggles with bypass, municipal revenue losses and TZS 249 million of rent arrears, while Morogoro's Msamvu terminal shows what demand-led siting achieves, though its reported takings equal only about 7% of phase-one cost.
The way forward is unbundling, explicit public support and a screening test. Separate the public-good core from the commercial layer, fund the core through VGF, grants or concessional capital, protect sitting traders with a protected tier inside tiered rents, and apply a nine-point affordability–bankability screen at pre-feasibility stage.
Bottom line
Bankability does not remove the subsidy; it moves it from the budget to the wananchi. The question for every LGA market or terminal is who should carry the viability gap: taxpayers through a visible grant, or small traders and commuters through rents, prices and fees. The second route is regressive and is rarely shown in feasibility studies. The next ten tabs show the policy setting, the evidence, the numbers and the options.
01 — Policy & Fiscal ContextA Thin Local Revenue Base, a New PPP Framework and Expensive Money
LGA own-source revenue (OSR) remains a small part of public finances, which is why revenue-generating assets are attractive to councils. At the same time the capital used for the recent generation of terminals has come mainly from the centre, and the PPP pipeline is large but converts slowly. This tab sets out the fiscal and legal backdrop against which the bankability test in Tabs 5–6 should be read.
1.1 A thin local revenue base
Budget
LGA own-source revenue (TZS trillion)
Total budget (TZS trillion)
LGA OSR share of budget
2024/25
1.36
49.35
≈ 2.7% (reported as "about 3%")
2026/27
1.97
62.33
≈ 3.2%
Sources: Ministry of Finance Budget Frame 2024/25 (TZS 1,356,341 m of TZS 49,345,688 m); 2026/27 budget (TZS 1.97 trillion within TZS 62.33 trillion); shares are TICGL/TERI calculations. A UNDP-supported workshop report (June 2025) notes OSR has stayed low, at about 15.5% across three fiscal years, despite electronic collection systems.
LGA Own-Source Revenue and Its Share of the National Budget
Bars: OSR in TZS trillion (left axis). Line: share of total budget, percent (right axis). Source: Ministry of Finance; TICGL/TERI calc.
The PPP Pipeline vs Signed Deals
Count. Identified LGA-level PPP projects are 45 times the contracts signed nationally. Source: PPP Centre (Sept 2025); TanzaniaInvest (June 2026)
Self-reliance is therefore a direction of travel rather than a fiscal reality. Completed terminals, including Magufuli at Mbezi Luis, Dodoma's terminal and Msamvu in Morogoro, are presented in official and press reports as a strategy to reduce councils' dependence on central government, yet their capital came mainly from the centre (Tab 3).
1.2 The PPP framework: what changed in 2023
Feature of the PPP (Amendment) Act No. 4 of 2023 and GN 838A
Why it matters for LGA markets and terminals
"Public funding" defined as support creating fiscal commitments or contingent liabilities
Makes the cost of closing a viability gap visible and countable; it cannot be hidden in optimistic revenue forecasts.
Explicit provision for tax benefits, guarantees and Viability Gap Funding (VGF)
The law already recognises that some socially valuable projects cannot recover their cost from users. VGF exists for exactly this case.
Concept-note stage removed; pre-feasibility studies due at the start of each budget cycle
Pre-feasibility is the right moment to run an affordability–bankability screen (Tab 9).
Contracting authority may hold part ownership of a project company
Enables council-plus-patient-capital structures such as the Msamvu joint company (Tab 3).
Pipeline vs closed deals
The PPP Centre reported in September 2025 that 410 projects had been identified across 184 LGAs in sectors including housing, waste, tourism and public transport, with only a handful at implementation stage. By June 2026 nine PPP contracts had been signed nationally (DART phases, mandatory vehicle inspection, the Kariakoo commercial building, TAZARA and the Dar es Salaam port), mostly national-scale flagships. The gap between the local pipeline and closed deals suggests many local concepts are not yet bankable. An older World Bank-supported municipal PPP presentation (undated; to be checked against current regulations) reached a similar diagnosis: projects were economically attractive but fiscally unaffordable, needing viability-gap or availability payments most municipalities outside Dar es Salaam could not fund.
1.3 The cost of money
Private capital is priced off the government yield curve. The 15-year Treasury bond yield stood at about 10.79% in the week to 2 October 2026, while 20- and 25-year yields were above 14% during 2025. A property investor in a secondary-town market will require a premium over these risk-free rates for construction, letting and regulatory risk. The report uses a base required yield on cost of 16%, with 12% as a concessional-finance case and 18% as a stressed case, and cross-checks with a lender-style model using a debt-service-cover test.
Required Yield on Cost vs Government Bond Yields
Percent per year. Bars in blue are the report's scenarios; grey bars are government bond reference points. The 20–25-year bar is a floor ("above 14%"). Source: TanzaniaInvest week to 2 Oct 2026; The Citizen 2025; TICGL/TERI
02 — Why the Two Logics CollideTwo Roles, a Triangle, a Loop and a Formula
A single LGA project asks the council to be two things at once: a service provider, whose job is access, equity, safety and public health, and an investor and asset owner, whose job is to earn a return and recover the cost of capital. These roles use different customers, different success measures and different views on price.
2.1 Two roles in one project
LGA as service provider
LGA as investor / asset owner
Objective
Access, equity, safety, public health
Own-source revenue; recover cost of capital
The "customer"
Small trader, commuter, resident
Tenant able to pay a market rent
Success measure
People reached, accidents avoided, sanitation, jobs
Cash flow, debt-service cover, investor return
Pricing view
Affordable or subsidised
Cost-reflective rents and fees
Main risk
A project that costs but does not earn
A project that excludes those it should serve
2.2 The triangle: public value, affordability, bankability
Market and stand projects try to deliver three things at once. In practice any two can be achieved, but the third breaks without additional support.
Combination
What is possible
What is lost
Public value + affordability
Good facility, low charges, funded by public capital
Bankability: no cash flow to repay commercial debt
Bankability + affordability
A small, cheap, basic facility
Public value: safety, sanitation and infrastructure are stripped out
Bankability + public value
A modern facility that repays its debt
Affordability: rents and fees exclude small users
2.3 The vicious loop
1 · Capital is dearExpensive capital and a short tenor make the annual capital charge per m² high relative to the building's useful life.
2 · Implied rent is highTo cover the charge, rents per m² and gate fees must sit well above the informal market the facility replaces.
3 · Users will not payLow-turnover traders and commuters with alternatives do not move in, sub-let, or bypass the facility.
4 · Revenue under-deliversVacancy and leakage cut cash flow. The LGA subsidises the shortfall from OSR (crowding out services) or re-prices upward, and the loop repeats.
A lender also prices as cost the objectives an LGA must retain: police post, CCTV, drainage, toilets, inclusion of sitting traders, fee restraint. They are legitimate, but they raise capital cost and common-area ratios while earning little rent.
2.4 The bankability arithmetic
// Required rent per lettable m² per month Rent = [ (Construction cost per gross m² ÷ Net-to-gross efficiency) × Required yield on cost ] ÷ [ (1 − operating-cost ratio) × (1 − vacancy) × 12 ]
// Base case (2,200,000 ÷ 0.70) × 16% ÷ (0.80 × 0.90 × 12) ≈ TZS 58,200 per m² per month
Every term other than construction cost is a lever that bankability pushes up: higher required yield, lower efficiency (more common areas), higher vacancy and operating costs. Lenders also test debt-service cover (commonly 1.2–1.4x), which raises required revenue further. Try your own assumptions below, and see which lever moves the answer most.
Required-rent calculator (Model A)
Change the inputs; results update instantly. Capital contribution scales required rent by (1 − contribution), as in Table 15 of the report.
Required rent
–
TZS per m² per month
× median stated (8,300)
–
multiple of affordability
× upper quartile (16,700)
–
below 1.0x = affordable to top quartile
Rent for an 18 m² shop
–
vs TZS 100,000–200,000 stated
Which Lever Moves the Required Rent Most?
Change in required rent from the TZS 58,200 base case, TZS per m² per month, when one assumption moves to a favourable (teal) or adverse (red) setting. TICGL/TERI calc. from the Model A formula
2.5 Conservation of the gap
The viability gap is conserved: the difference between what the facility must earn and what users can pay does not vanish when a project is structured as a PPP; it is assigned to someone. There are only four candidates.
Who pays
Mechanism
Typical consequence
Traders (tenants)
Higher rents, deposits and service charges
Exit, under-letting, arrears, informal trading outside the building
Consumers / commuters
Higher prices, parking, toilet and stand fees passed through
Regressive burden; reduced footfall
Taxpayers / the LGA
VGF, capital grants, land contribution, guarantees
Fiscal commitments and contingent liabilities
Investors / lenders
Lower returns or higher risk accepted
Project does not reach financial close
2.6 Other mechanisms that bite
Mechanism
How it bites
Price-setting limits
Rents, stand fees and levies are set by by-law and political judgement, not cost recovery; leaders resist fees that hurt small traders. A cost-reflective tariff may be legally or politically unavailable.
Avoidance and bypass
If the fee is the product, users avoid the facility when alternatives exist (Tab 3).
Optimism bias
To look bankable, forecasts of vehicle numbers, occupancy and ability to pay are inflated; when they fail, the LGA is left with direct or contingent liabilities. Support for a project (95% in the case) is not the same as ability to pay.
Long contracts, changing policy
Directives on fees or rent relief can arrive mid-concession; investors price protection into the deal. Clear tariff-indexation and compensation rules are part of bankability.
Maintenance neglect
Without a ring-fenced sinking fund, quality decays and revenue follows.
Displacement
Sitting traders fear losing customers during relocation and higher rent on return; without priority-of-return and rent protection, the project displaces rather than strengthens small business.
2.7 Financial versus economic returns
A project can have a low financial return (FIRR) yet a high economic return (EIRR) once avoided accidents, sanitation, time savings, jobs and council revenue are counted. Where that is so, forcing it to "pay for itself" means redesigning the project to suit the lender rather than designing support that matches its public value.
High EIRR
Low EIRR
High FIRR
Standard PPP: private sector can carry the debt; regulate tariffs
Purely commercial; the LGA need not participate except as landowner
Low FIRR
Deserves support: VGF, concessional loans, availability payments, or public build with private operation
Do not build; reconsider design, site or need
03 — Tanzanian & Regional EvidenceWhat Terminals and Markets Have Actually Done
The public record is mixed in financing structure, so these cases are not like-for-like PPP comparisons. They share the same revenue and affordability logic, and they show what happens when a facility must earn from the people it serves.
3.1 Magufuli terminal, Dar es Salaam: a grant-funded warning
The Magufuli terminal at Mbezi Luis was built at about TZS 54.6 billion, of which TZS 50.9 billion (93%) came from a central-government grant and the balance (about TZS 3.7 billion) from the Ubungo council's own revenue. It is a grant-funded project, not a PPP, but its revenue logic is the one a bankable project would rely on. Press reports describe 70 to 90 buses a day using other stops and a municipal loss first put at more than TZS 50 million a month and later reported as more than TZS 600 million a month in government discussions. The two figures are not reconciled; the earlier is consistent with a report that at least TZS 1.4 million a day was being missed. Bus owners cite distance from the centre, passenger convenience, private terminals with better facilities, and a mandatory entry requirement that conflicts with the regulator's approval of private terminals.
The cost reaches passengers
Passengers to Kigamboni, Mbagala, Temeke and the city centre often pay more for onward transport, and the Prime Minister has himself warned against forcing buses into terminals where this would raise operating costs and fares.
The arrears mechanism is visible
In September 2026 the Ubungo council was pursuing over TZS 249 million of rent arrears from businesses in the passenger building. Traders cited low passenger flow, switched-off lifts and mixed uses, and asked for rent relief.
What the Terminals Cost
TZS billion. Magufuli split between central grant and council funds; other terminals' funding split is not itemised in the sources. Source: TICGL/TERI report, Sections 2.1 and 4
Magufuli: Two Reported Monthly Revenue Losses
TZS million a month. Older reports vs later government discussions; the two figures are not reconciled in the sources
3.2 Dodoma and Morogoro: location and partner structure
Dodoma's terminal, built at over TZS 24 billion, has been reported as under-used, with empty shelves and deteriorating fittings. By contrast, Msamvu in Morogoro, developed by the council and the LAPF pension fund through a joint company, cost about TZS 16 billion for its first phase, and reported takings rose from about TZS 350,000 to about TZS 3 million a day after expansion. Even that success equals roughly TZS 1.1 billion a year, about 7% of phase-one cost before operating expenses and tax. It shows how hard it is for a terminal to repay capital from fees alone, and why siting on a busy corridor and a long-horizon partner matter.
Msamvu: Daily Takings Before and After Expansion
TZS million per day (about 8.6 times higher). Source: press reports cited in the report
Msamvu: A Year of Takings vs Phase-One Cost
TZS billion. About TZS 1.1 billion a year against TZS 16 billion, before operating expenses and tax. TICGL/TERI calc.
3.3 Regional market redevelopments
Kampala (Uganda)
Traders left new stalls because rents were high relative to what they paid before; stalls were sold on after tax holidays ended.
Authorities cut rents in some markets, yet many stalls reportedly stayed vacant.
On 30 September 2026 traders again raised high shop rents with the city authority, which had 550 vacant spaces in government markets.
Kumasi, Kejetia (Ghana)
Traders said store rents were too high; the Assembly arranged bank loans so traders could pay premiums over five years.
Members alleged premiums were inflated to service the construction loan.
Some phase-one shops bought for GH¢25,000 were resold for GH¢100,000–120,000: subsidised space captured by better-connected holders.
Takoradi (Ghana)
A University of Bergen study of a proposed PPP-financed market redevelopment found likely implications for informal traders' access to trading space.
Lesson: displacement is a design risk to be planned for, not an afterthought.
Kejetia, Kumasi: Allocation Price vs Resale Price of a Phase-One Shop
GH¢ thousand. Reported resale at four to five times the allocation price. Source: MyJoyOnline / Adom Online as cited in the report
3.4 Lessons
Case
What happened
Lesson
Magufuli, Dar es Salaam
Large grant-funded terminal; bypass, municipal revenue losses, tenant arrears
Fee-based design fails when users have alternatives; siting, feeders and fee structure matter as much as the building
Msamvu, Morogoro
Council–pension-fund joint company; strong corridor location; takings up about 9x
Demand-led siting and patient capital help, but fees alone still recover only a small share of capex
Kumasi and Kampala
Premiums, rents or stalls priced above traders' means; vacancy, resale and capture
Cost-recovery pricing without allocation rules displaces target users
World Bank-supported urban projects (Tanzania)
Results frameworks target 70–80% recovery of bus-station O&M cost from fees
Even the donor benchmark aimed at operations and maintenance, not full capital recovery
04 — Case: What Users Can PayEvidence from an Illustrative Case: Strong Support, Thin Wallets
The case is a proposed mixed-use complex combining shops and a mini-bus stand in a fast-growing urban ward, used here as a case study of an LGA project that must earn from its users. It draws on structured interviews with institutions and police, prospective tenants, existing traders, and customers and commuters, plus restaurant and market leaders. Respondents' monthly rent ranges were converted to bucket mid-points and divided by the floor area they said they would need. The evidence is small, non-random and self-reported, so results indicate direction and order of magnitude. The full survey detail is available in the full report (see Request the full report).
4.1 Support is high; the issue is price, not demand
All 21 existing traders said they would move into a new building (13 "strongly support", 8 "support"), and 11 of 12 customers said they would use the facility regularly. Local leaders and departments backed the concept and stressed priority for sitting traders, fair compensation, sanitation and security. Demand is not the constraint; the constraint is what that demand can pay.
4.2 Affordability
Maximum Monthly Rent Respondents Say They Can Pay
Number of respondents by band, TZS per month. Source: case survey data; TICGL/TERI analysis
The Affordability Curve: Share Who Can Pay No More Than X
Cumulative percent of respondents whose stated maximum rent is at or below each level. Source: TICGL/TERI calc. from the same survey bands
Indicator
Value
Comment
Existing traders able to pay at most TZS 100,000 / month
11 of 21 (52%)
20 of 21 (95%) cap at TZS 200,000
Prospective tenants capped at TZS 200,000
8 of 16 (50%)
6 in the 200–300k band; 2 above 300k (a financial outlet, a hardware store)
Respondents with usable size and rent data
37
Median stated maximum TZS 150,000; 76% (28 of 37) at or below TZS 200,000
Median stated rent per m²
TZS 8,300 / month
Interquartile range 8,300–16,700; highest 17,100
Existing traders: current rent (median)
TZS 75,000 / month
Mean stated maximum ≈ 1.4x current rent
Existing traders with sales under TZS 500,000 / month
76% (16 of 21)
One preferred not to say
Rent-to-sales at top of sales band (median)
≈ 15%
Rent of 100–200k is 20–40% of top-of-band sales for the lowest band
Table 7. Affordability indicators. Per-m² figures use assumed unit sizes (kiosk 6, small 9, medium 18, large 35, restaurant 40 m²).
4.3 Three observations that matter for design
1 · Unit mix drives revenue density
Small units (under 12 m²) show the highest stated rent per m² (median about TZS 16,700).
Medium units show about TZS 8,300.
A mix weighted towards small units raises revenue per m².
2 · Haircut stated rents
Low reported sales combined with rents already near 15% of sales suggest under-reported turnover or optimistic stated willingness.
Revenue forecasts built on stated rents should be discounted.
3 · Non-revenue needs are large
11 of 21 traders and 8 of 12 customers named missing or dirty toilets and water among main complaints.
Officials and police asked for a police post, CCTV, lighting, separate gates, waste collection, wastewater treatment, drainage and public toilets.
All add capital cost without adding rent.
Advance Rent Prospective Tenants Could Pay
Number of prospective tenants. Source: case survey data
Support, Concerns and Complaints
Percent of the relevant respondent group. Source: case survey data; TICGL/TERI calc. (11/21, 8/12, 29/37, 21/21, 11/12)
05 — The Bankability TestAffordable Rents Earn 2–5% on Cost; Capital Needs 12–18%
Affordable rents deliver a yield on cost of only about 2.3% (median), 3.0% and 4.6% (upper quartile), all below the 10.8% government bond yield. At stated rents the building would be a worse investment than lending to the Government.
Required Rent Rises With Cost and Yield, Far Above What Users Can Pay
Required rent, TZS thousand per lettable m² per month, by construction cost (TZS million per gross m²) at four required yields. Dashed lines: median 8.3k and upper-quartile 16.7k stated affordability. Efficiency 70%, opex 20%, vacancy 10%
How Much of the Building Can Rent Support?
Percent of construction cost supportable by rent, by rent level, at 12% and 16% required yield. Shaded: stated affordability range (TZS 8.3k–17.1k). Base cost TZS 2.2m per gross m²
Across the affordable range of TZS 8,300–17,100, rent supports roughly 14–29% of construction cost at a 16% required yield and 19–39% at 12%. The balance, 61% to 86% of capex, is the viability gap in this illustration.
5.1 Required rent by construction cost and yield
Cost per gross m² (TZS m)
12% yield
14% yield
16% yield
18% yield
1.2
23,800
27,800
31,700
35,700
1.6
31,700
37,000
42,300
47,600
2.0
39,700
46,300
52,900
59,500
2.2 (base)
43,700
50,900
58,200
65,500
2.4
47,600
55,600
63,500
71,400
2.8
55,600
64,800
74,100
83,300
Table 8. Required rent (TZS per lettable m² per month). No cell falls within the stated affordability range (median 8,300; highest 17,100). Cell shading: amber under 35,000; red 35,000–55,000; dark red above 55,000.
5.2 Three models, one conclusion
To test robustness, the gap was estimated with three independently built models: (A) the yield-on-cost model above; (B) a simple capital-recovery model (capital charge over 15 years at 16%, 85% occupancy, no operating costs, so a floor); and (C) a lender-style model requiring 1.3x debt-service cover with 70% debt at 17% over 12 years, operating costs and a maintenance reserve. Models B and C were re-computed independently and reproduce the figures in the working drafts.
Monthly Rent Needed for an 18 m² Shop, Three Models
TZS thousand per month. Shaded band: stated affordability (TZS 100–200k). Source: TICGL/TERI models; case survey data
How Many Times the Median Trader's Affordability?
Multiple of TZS 8,300 per m² per month. Below 1.0x would be affordable at the median. Source: TICGL/TERI, Table 9
Model and capital structure
Rent per m² / month (TZS)
Rent for 18 m² shop (TZS)
Multiple of median affordability (8,300/m²)
A. Yield-on-cost, commercial (2.2m/gross m², 16%)
58,200
1,048,000
7.0x
B. Capital recovery, commercial (1.6m/lettable m², 16%, 15 yrs)
28,100
506,000
3.4x
C. Lender-style, commercial (2.0m/lettable m², DSCR 1.3)
44,600
803,000
5.4x
A. with 50% capital contribution and 12% hurdle
21,800
393,000
2.6x
C. with 50% grant + cheaper debt (10%, 20 yrs)
19,300
347,000
2.3x
C. with fully public capital (rent covers O&M and reserve only)
8,800
159,000
1.1x
Table 9. Triangulation of the viability gap. Model A's cost is per gross m² (≈ TZS 3.1m per lettable m²), so it sits at the high-cost end; Models B and C use cost per lettable m².
Reading the three answers
The conclusions agree. On commercial terms, required rent is 3.4–7 times the median stated affordability. A 50% capital grant with cheaper, longer debt still leaves rent 2.3–2.6 times the median. Only when public capital funds the building does rent fall into the range traders say they can pay (about TZS 159,000 for an 18 m² shop, against TZS 100,000–200,000). The "3x versus 7x" difference between drafts reflects model design, not the data.
06 — Cross-Subsidy & Stand FeesWhy Anchor Tenants and Gate Fees Cannot Close a Gap This Size
6.1 The limits of cross-subsidy
A common response is to cross-subsidise: let anchor tenants (banks, pharmacies, supermarkets, restaurants) pay premium rents so small traders can pay less. The case data show why this has limited reach. The highest stated rents, from large-format tenants, are about TZS 14,000–17,000 per m², not the TZS 58,000 needed. If a social share of space is let at TZS 11,000 per m², the commercial rent required to average out at the Model A rent is shown below.
Anchor Rent Needed to Cross-Subsidise Social Units
TZS thousand per m² per month, by share of space let at the TZS 11,000 social rent. Dashed: highest stated rent (17.1k) and base-case bankable average (58.2k). TICGL/TERI calc.
Share of space at social rent
Rent anchors would need (TZS/m²/month)
Multiple of highest stated rent
50%
105,000
6.1x
70%
168,000
9.8x
80%
247,000
14.4x
Table 10. Anchor rent required to cross-subsidise social units to the base-case bankable average.
What this means
Cross-subsidy and mixed use raise revenue, but they cannot close a gap of this size. Competing private buildings in the same corridor also cap the premium anchors will pay. Half of prospective tenants (8 of 16) can pay more than TZS 200,000, so a protected tier funded by a stronger tier is real, but it is a partial answer.
6.2 Stand economics
The transport officer and regulator indicated 300–600 public vehicles a day and a possible stand fee of TZS 1,000–2,000 per trip, with a proposal for a toll gate. Gross fees would be roughly TZS 110 million (300 vehicles, TZS 1,000) to TZS 438 million (600 vehicles, TZS 2,000) a year. After 15% collection leakage and 30% operating cost, net income is about TZS 65–261 million, which under commercial terms (70% debt at 17% over 12 years, 1.3x cover) supports only about TZS 0.4–1.4 billion of total investment. The terminals actually built cost TZS 16–55 billion.
Stand-fee calculator
Defaults are the low case from the report (300 vehicles, TZS 1,000). Set 600 vehicles and TZS 2,000 for the high case. Investment supported uses 70% debt at 17% over 12 years with 1.3x debt-service cover.
Gross fees a year
–
vehicles × fee × 365
Net income a year
–
after leakage and opex
Investment it can support
–
vs TZS 16–55 bn for built terminals
Fee per passenger per trip
–
charged mostly to low-income users
What Stand Fees Can Fund vs What Terminals Cost
TZS billion of total investment. Fee-supported range (0.4–1.4) vs built terminals (16–55). Source: TICGL/TERI, Section 5.7
Debt Service on a Terminal Component vs Gross Stand Fees
TZS billion a year. Terminal component of TZS 5, 10 or 20 bn financed at 16% over 15 years vs gross fees of TZS 0.11–0.44 bn. Fees cover only 3–49%
A stand fee alone rarely carries the capital cost. Stands rely on cross-subsidy from commercial space, parking and advertising, and survey commuters accept only small charges (Tab 7).
07 — Pass-Through to CitizensFrom the Trader to the Citizen: Who Really Pays
If a facility is made bankable by cost-reflective rents and fees, the cost does not stay with the trader or operator. It travels along the chain below, and the final burden falls on the citizen as consumer, commuter or household member.
Channel
Who is charged first
How it reaches the end user
Constraint on pass-through
Shop and stall rent
Trader
Higher prices, smaller product range, or a shift to higher-margin goods
Competing complexes; customers' low spend; informal street trade outside the building
Service charges, deposits, advance rent
Trader
Same as above; also reduces working capital and stock
Tenants' capacity to pay 1–6 months in advance
Stand and toll fees
Daladala / bajaji operators
Higher fares or lower service quality
Fares and stand fees are regulated; operators absorb first
Parking, toilets, entry fees
Customer / commuter directly
Direct out-of-pocket cost
Stated willingness to pay is low and mostly daily-use
Table 11. Channels of cost pass-through.
7.1 Trader level: how much would prices have to rise?
To keep income unchanged, a trader who absorbs a rent increase through prices must raise sales by the same amount. To a first approximation (ignoring any fall in volume), the required price rise equals the rent increase divided by monthly sales. The baseline is the existing traders' median current rent of TZS 75,000; sales for the lowest band are taken at its mid-point, TZS 250,000.
Price Rise Needed to Keep Income Unchanged
Percent, if rent rises from TZS 75,000 to each level, by monthly sales. Dashed line: 10% flag from the nine-point screen. Source: case survey data; TICGL/TERI analysis
The Pass-Through Curve
Required price rise (%, capped at 400) as rent climbs from TZS 75,000 to 1,050,000, for four monthly sales levels. TICGL/TERI calc.: (new rent − 75,000) ÷ sales
Monthly sales (TZS)
Rent → 150,000
Rent → 300,000
Rent → 520,000
Rent → 1,050,000*
≈ 250,000 (under-500k band)
+30%
+90%
+178%
+390%
≈ 750,000 (500k–1m band)
+10%
+30%
+59%
+130%
≈ 2,000,000 (1m–3m band)
+4%
+11%
+22%
+49%
Table 12. Price rise required to offset a rent increase from TZS 75,000. TZS 520,000 is the simple break-even rent for an 18.5 m² shop at TZS 1.6m per m² (Model B); *TZS 1.05m is Model A's rent for an 18 m² shop. At the top of the lowest sales band (TZS 500,000) the first three columns fall to +15%, +45% and +89%.
Pass-through calculator
Enter a trader's current rent, a proposed new rent and monthly sales to see the price rise needed to keep income unchanged.
Price rise needed
–
to keep income unchanged
New rent as % of sales
–
screen guide: around 15% or less
Extra rent a year
–
TZS, versus current
Screen flag (10%)
–
pass-through above 10% for small traders
Pass-through is not realistic for most existing traders. At 76% reporting sales below TZS 500,000, even doubling rent to TZS 150,000 requires a 30% price rise (15% at the top of the band) in a market where 42% of customers spend under TZS 5,000 a visit and street trade is cheaper. At a bankable rent the arithmetic breaks entirely: rent exceeds monthly sales. The consequence is not that prices rise by hundreds of percent; it is that those traders leave, sub-let or stay informal. The facility is then let to whoever can afford it: larger-format retailers, banks, pharmacies and electronics outlets. This composition effect keeps the building full and the project "bankable" but changes whom it serves. Traders' own worries ("loss of customers" 29 of 37, "rent increase after return", "no guarantee of space") are early signals of it.
7.2 High-volume operators: feasible, but it reaches the consumer
For businesses with many customers, a rent increase is spread thinly. A restaurant with 200 customers a day (surveyed range 150–300) and average spend of about TZS 4,500 adds roughly TZS 50 per customer if rent rises by TZS 300,000, and TZS 133 if it rises by TZS 800,000: between 1% and 3% of the bill.
Restaurant: Extra Cost per Customer
TZS per customer (bars) and share of average TZS 4,500 spend (line, right axis). 200 customers/day, 30 days/month. Source: TICGL/TERI, Table 13
What Customers Accept to Pay for Parking
Number of surveyed customers by the highest parking fee accepted, mean about TZS 830. 9 of 12 visit daily. Source: case survey data
Pass-through is easiest for the tenants who could already pay, and reaches consumers invisibly in small increments. A bankable complex therefore tends to be sustained by high-traffic, higher-income-serving uses while the small-ticket trade that justified the public investment is crowded out.
7.3 Direct charges on commuters and shoppers
Stand, parking and toilet fees fall on users directly. Nine of 12 customers visit daily, so a TZS 1,000 charge is about TZS 26,000–30,000 a month for a daily user, and for the five of 12 who spend under TZS 5,000 a visit, a TZS 1,000 fee is at least a fifth of spending. A stand fee of TZS 1,000–2,000 per vehicle equals about TZS 35–135 per passenger per trip if a vehicle carries 15–30 passengers (assumption). For a daily commuter making two trips on 26 days a month, that is roughly TZS 1,800–7,000 a month, charged mostly to low-income users. Because fares and stand fees are regulated, operators absorb the fee first and pass it on through lower frequency or quality.
Stand Fee per Passenger per Trip
TZS, by fee per vehicle and vehicle load (assumed 15 or 30 passengers). Source: TICGL/TERI calc.
Three outcomes of a cost-reflective tariff
1. Absorption. Traders keep prices flat and eat the rent. Margins collapse, arrears rise and vacancies appear (as in the Magufuli passenger building). The gap returns to the project as revenue risk.
2. Substitution. Rents are paid by higher-turnover tenants; low-income traders move to the periphery or the street. The gap is closed, but the public purpose is diluted.
3. Pass-through. Prices, fares and fees rise. Burdens land on low-income households, with daily users bearing the most, constrained by competition and fare regulation.
Policy implication
Bankability does not remove the subsidy; it moves it from the budget to the wananchi. The question for each project is who should carry the cost: taxpayers through a visible viability-gap grant, or small traders and commuters through prices and fees. The second route is regressive and is rarely shown in feasibility studies. Every pre-feasibility report should therefore include a pass-through table like Table 12.
08 — Closing the GapOptions and Their Numerical Effect: Who Should Pay, and How
Because the gap is conserved, the policy question is not how to eliminate it but who should pay it, and how. There is no single fix; the options below can be combined.
Option
How it works
Advantage
Risk / trade-off
A. Full user-pay
Rents and fees set at break-even
Bankable on paper; no public subsidy
Exclusion, vacancy, bypass; political resistance
B. Tiered rents with cross-subsidy
Anchors and parking pay premium rates; protected tier for sitting small traders
Keeps traders in; uses stronger tenants' ability to pay (8 of 16 prospects can pay above 200k)
Needs enough high-paying demand; ceiling shown in Table 10
C. Explicit VGF for public-good components
Government or partner funds drainage, toilets, police post, access roads as grant or availability payment
Separates social cost from commercial cash flow; fits the 2023 PPP framework
Needs a funded LGA window; contingent-liability discipline
D. Unbundle the project
Council builds the public-good core; commercial space let on lease or BOT
Lowers capital the operator must recover; clearer risk allocation
Interface risk; procurement complexity
E. Operator lease with minimum guaranteed rent
Council leases the complex for base rent plus revenue share, with rent bands and service standards
Transfers collection and maintenance risk; predictable council income
Base rent still limited by ability to pay; needs tariff governance
F. Demand-side design
Site on commuter flows, feeder links, separate gates, pre-lets and passenger surveys
Raises volume rather than price
Bypass persists if enforcement is weak (Tab 3)
G. Lower capital cost
Standardised, modest designs; phased construction
Directly lowers break-even rent
May compromise quality and amenities
Table 14. Policy options.
8.1 What combined support does to required rent
Required Rent Falls Only With Large Public or Concessional Capital
TZS thousand per m² per month at each capital contribution, with the hurdle yield falling from 16% to 12%. Dashed: median (8.3k) and upper-quartile (16.7k) stated affordability. Source: TICGL/TERI, Table 15 (Model A)
Capital contribution (grant / land / concessional)
Required yield
Required rent (TZS/m²/month)
× median stated
× upper quartile
0%
16%
58,200
7.0x
3.5x
30%
16%
40,700
4.9x
2.4x
40%
14%
30,600
3.7x
1.8x
50%
12%
21,800
2.6x
1.3x
60%
12%
17,500
2.1x
1.05x
70%
12%
13,100
1.6x
0.8x
Table 15. Effect of public/concessional capital contribution and a lower required yield on required rent (Model A, base cost TZS 2.2m per gross m²).
Reading Table 15
Affordability is reached only at roughly 60–70% public or concessional contribution with a ~12% hurdle, consistent with Model C's finding that a 50% grant plus cheaper debt still leaves rent about 2.3 times the median. At that level the project is, economically, publicly funded infrastructure with private operation, and the relevant question becomes value for money rather than bankability.
8.2 Design principles
1 · Separate the social and commercial layers from the start
Anchor shops, parking and advertising can carry debt; toilets, security, wastewater and small-trader units need grants or availability payments.
2 · Use EIRR to justify support
Quantify avoided accidents, time, health and jobs and use them as the basis for public contribution, rather than hiding the gap behind optimistic revenue forecasts.
3 · Protect sitting traders contractually
Priority of return, a temporary relocation plan and a cap on rent increases during a transition period; allocate subsidised space by published rule to avoid capture and resale.
4 · Build for voluntary demand, not compulsion
Location, services and user cost should attract users; compulsion should be a last resort, not the revenue base. Commission independent demand checks and use verified, lower-bound revenue in the financial model.
5 · Write tariff governance into the contract
A council- and regulator-approved tariff band, indexation rules, an independent review period and compensation rules.
8.3 Raising revenue density without burdening small traders
Unit mix. More small units (higher rent per m²), fewer large low-yield bays; upper floors for offices or services.
Ancillary income. Advertising, private-vehicle parking, logistics and loading space, events, telecom masts, priced for those who can pay.
Collection efficiency. Electronic collection (the council accountant cited 80–95% collection) raises net revenue without raising tariffs.
Advance rent as working capital. 7 of 16 prospective tenants could pay one month in advance, 7 could pay three months and 2 six months.
Mixed income and a ring-fenced maintenance fund from year one, with a tariff review rule.
The Msamvu experience also points to a financing route: a council–pension-fund joint company combines patient long-horizon capital with a commercially managed asset, an arrangement worth testing for market and stand projects with a credible commercial layer.
Stated Rent per m² by Unit Size
TZS thousand per m² per month, median. Small units under 12 m² vs medium units. Source: case survey data; TICGL/TERI calc.
09 — Screen & RecommendationsA Nine-Point Affordability–Bankability Screen for LGA Markets and Stands
TICGL/TERI proposes the following screen for LGA market and stand concepts at pre-feasibility stage. Thresholds are proposals for discussion and should be calibrated on a larger set of projects. Projects should also be judged on economic return (EIRR) alongside financial return (Tab 2, Section 2.7).
Test
Question
Indicative threshold
1. Affordability
Share of target tenants whose stated maximum rent is at or above the proposed rent
At least 70% for the commercial layer; required rent ≤ upper-quartile stated affordability
2. Rent-to-sales
Proposed rent as share of verified monthly sales
Around 15% or less for small traders
3. Capital-recovery gap
Share of annualised capital cost recovered from rent at observed ability to pay
Report the gap explicitly; fund through a named VGF or grant source
4. Public-good cost
Cost of non-revenue components as share of total capital
Separate budget line; not loaded into rent
5. Bypass and demand risk
Alternatives available to operators and traders; enforcement capacity
Pre-lets, letters of intent and passenger surveys; mitigation plan for terminals
6. Pass-through
Price or fare increase needed to cover proposed rent and fees, by sales band and per passenger
Pass-through table in every pre-feasibility report; flag if above 10% for small traders
7. Displacement
Plan for relocation, rent protection, priority of return
Documented, with allocation rule published before approval
8. Sustainability
Maintenance sinking fund and tariff-review rule
Funded from year one
9. Fiscal exposure
Contingent liabilities and VGF commitment as share of LGA OSR
Disclosed in the concept note and within PPP Centre limits
Quick self-check: how many tests does your project pass?
Tick each test your concept already passes with documented evidence. This is a conversation starter, not a substitute for a full feasibility study.
Tests passed
0 / 9
Reading
Tick the tests your project already passes.
9.1 Recommendations by stakeholder
Stakeholder
Recommendation
PPP Centre and Ministry of Finance
Issue guidance for markets and stands that separates social and commercial layers; set clear VGF eligibility rules for LGA projects; require EIRR with FIRR and a pass-through table at pre-feasibility.
PO-RALG and councils
Stop using "self-financing" as the only decision criterion; classify projects by FIRR/EIRR; budget capital and maintenance for non-revenue components; create ring-fenced maintenance funds.
Lenders and development finance institutions
Offer long-tenor, concessional funding for the commercial layer; accept blended revenue; use guarantees to lower the cost of capital.
Advisers and appraisers
Test ability to pay, not just support; present sensitivity and downside cases; show the bankability gap and options to close it.
Traders and communities
Take part early in unit design, rent bands and relocation sequencing; use associations to negotiate priority of return.
Table 17. Recommendations by stakeholder.
Separate the public-good core from the commercial layer; fund the core through a ring-fenced VGF window or grant; let the commercial layer carry tiered rents with a protected tier for sitting traders; and consider public build with private operation where tests 1–3 cannot be met even after realistic public contribution.
TICGL/TERI, The Bankability–Affordability Dilemma, October 2026
9.2 Limitations and further research
Limitations
Small, non-probability case evidence: results indicate the mechanism, not the outcome for every LGA project.
Stated, not revealed, willingness to pay: brackets converted to mid-points and unit sizes assumed; sales probably under-reported (making affordability look worse) while stated rents may be optimistic.
Simplified financial models: scenario costs, not a quantity-surveyor estimate; no taxes, land value, construction-period interest, inflation, indexation or phasing; one cost of capital.
Pass-through assumes unchanged volumes and full recovery through prices and 15–30 passengers per vehicle.
Mixed sources: news reports and an undated programme presentation; legal details such as concession limits for LGA PPPs should be verified against current regulations.
Further research
Compare completed Tanzanian market and stand projects: actual revenue versus feasibility-study forecasts (optimism bias).
Quantify the economic value of the social layer (safety, sanitation, avoided accidents) using recognised SCBA methods.
Design availability-payment and VGF structures suited to LGAs with small own-source revenue.
Track displacement after modern markets open: rents, sales and share of original traders retained.
Analyse contingent liabilities that long-term PPP contracts create for LGAs.
10 — TICGL & Your ProjectFrom Bankability Findings to Feasibility, Market-Entry and Market-Research Decisions
TICGL (Tanzania Investment and Consultant Group Ltd), with its research arm TERI, builds the tests in this report into the studies it delivers: feasibility studies built to withstand a lender, a co-investor or a PPP Centre review, market-entry and setup support, and market research with a named data architecture. The bankability–affordability question is where all three meet, because a market or terminal only works if the financial model, the demand evidence and the entry structure agree. TICGL has delivered feasibility studies for PPP projects including the Boko Dawasa bus terminal and the Msasani Fish Market redevelopment.
10.1 From finding to study test to deliverable
Finding in this report
What a TICGL study tests
Deliverable
Required rent is 3.4–7x stated affordability
Financial model triangulated across yield-on-cost, capital-recovery and lender-style (DSCR) methods; required-rent frontier by cost, yield, efficiency, opex and vacancy; NPV, FIRR and EIRR
Bankability frontier table, break-even rent, viability-gap size in TZS
Stated affordability is not revealed affordability
Structured willingness-to-pay survey with sampling frame, verified sales, haircut on stated rents, comparison with nearby informal and private rents
Verified affordability distribution and a lower-bound revenue case
Cross-subsidy has a ceiling
Tenant-mix and unit-mix optimisation, anchor demand testing, pre-lets and letters of intent, competing-corridor rent comparables
Tiered rent schedule with a protected tier and tested anchor premium
Pass-through lands on citizens
Pass-through table by sales band and per passenger; fare and stand-fee regulation check; elasticity assumptions stated
Pass-through table and a displacement-risk statement
Terminals fail through bypass
Vehicle and passenger counts, bus-owner and operator interviews, alternative-stop mapping, enforcement capacity, regulator position
Demand and bypass-risk assessment with mitigation plan
The public-good core is not bankable
Unbundling of social and commercial capex; EIRR/SCBA of avoided accidents, health, time and jobs; VGF or availability-payment sizing; contingent-liability disclosure against OSR
VGF case and PPP Centre-ready submission
Sitting traders can be displaced
Relocation sequencing, priority-of-return rules, rent-cap during transition, published allocation rule
Displacement and allocation plan
Source: TICGL/TERI analysis; service lines as described on ticgl.com/what-we-do/.
Feasibility studies
Market and demand, technical and operational, financial and economic, legal and regulatory, environmental and social, and risk assessment.
DSCR, NPV and IRR models with downside cases.
PPP structuring: VGF, availability payments, BOT or lease.
Market entry & setup
Entry-mode strategy: council joint company, BOT, lease or operator concession.
Company registration, TIC incentive certificates, sector and local approvals.
Partner and site set-up.
Market research
Primary and secondary data, competitive landscape and demand analysis.
Willingness-to-pay and ability-to-pay surveys.
ARIMA forecasting, regression and trade-data analysis.
Due diligence
Financial, legal, commercial, operational and counterparty checks before a joint venture or new partner.
ESG and land checks.
For LGAs and PPP authorities
Pre-feasibility with the nine-point screen, a pass-through table and a named source for the viability gap, so a concept note can stand up to PPP Centre review.
For developers and operators
Required-rent frontiers, tenant-mix design and pre-let strategy before committing capital, plus entry-mode and approvals support.
For lenders and DFIs
Independent demand checks, lower-bound revenue cases and DSCR stress tests, so blended and concessional structures are sized on evidence.
Talk to TICGL/TERI
Request a feasibility, market-entry or market-research scoping call, or a briefing on this report's findings for your market or terminal project.
The full TICGL/TERI report includes the complete survey detail, all assumptions, the three financial models and the reconciliation notes. Email us and we will send it, or discuss how to apply the nine-point screen to your own LGA project.
12 - Sources & AssumptionsMethod, Assumptions and Reconciliation Notes
Basis
Source report. TICGL/TERI, The Bankability–Affordability Dilemma: Why markets and bus terminals struggle to be both "bankable" and publicly useful in Tanzania's Local Government Authorities, and who ends up paying the difference, comprehensive research report, October 2026, consolidating three TICGL/TERI working drafts. Case data. Anonymised case survey; full detail in the full report on request (economist@ticgl.com). Calculations. Required rent follows the Model A formula in Tab 2; figures on this page marked "TICGL/TERI calc." (cumulative shares, sensitivity bars, anchor-rent curve, pass-through curve, LGA OSR shares) are arithmetic on the report's inputs. Limitations. See Tab 9, Section 9.2.
Key assumptions (Annex A)
Item
Assumption
Note
Model A: construction cost
TZS 2.2m per gross m² (range 1.2–2.8m)
Illustrative; replace with QS estimate
Model A: efficiency, opex, vacancy, yield
70%; 20% of gross rent; 10%; 16% base (12%, 14%, 18% tested)
Yield compares with ≈10.8% 15-year bond (Oct 2026)
Model B
TZS 0.8–3.0m per lettable m²; 16%; 15 years; 85% occupancy
Capital recovery only; ignores opex (a floor)
Model C
TZS 1.5/2.0/2.5m per lettable m²; 70% debt at 17%, 12 years; DSCR 1.3; opex TZS 60,000/m²/yr; reserve 1.5% of cost/yr; occupancy 85%
Concessional: 50% grant, debt at 10% over 20 years; fully public: rent covers opex and reserve
Differences reflect model design, not data. Model B has no operating costs and uses TZS 1.6m per lettable m²; Model A uses TZS 2.2m per gross m² (≈3.1m per lettable m²) with opex and vacancy. All three are shown (Table 9).
Sales mid-point for the lowest band
Earlier draft used TZS 400,000; the band mid-point of TZS 250,000 is now used, with the top of the band as a sensitivity.
Magufuli municipal revenue loss
Press figures differ: more than TZS 50 million a month (older reports) and more than TZS 600 million a month (later government talks). Both are cited; they are not reconciled.
Magufuli cost
Reports range from about TZS 50 billion to 54.6 billion; the report uses TZS 54.6 billion (TZS 50.9 billion central grant).
Kejetia financing
A phase-two loan figure could not be verified and is omitted.
World Bank municipal PPP programme
Source is an undated presentation; used as supporting diagnosis only.
Passengers per vehicle
15–30 used instead of 25.
Share of cost rent can support (this page)
The report text quotes 19–38% at a 12% yield; on this page 17,100 ÷ 43,700 gives about 39% at the top of the stated range, so the web text says 19–39%.
Dodoma terminal name
The report names Dodoma's terminal both Nzuguni and Nane Nane; this page says "Dodoma terminal" (TZS 24 billion or more) pending confirmation of the name.
TICGL/TERI, The Bankability–Affordability Dilemma, October 2026, and underlying working drafts; case survey data (anonymised).
Ministry of Finance, Budget Frame 2024/25; TanzaniaInvest, "Budget proposals 2026/27"; Clyde & Co, "Tanzania's National Budget Speech 2026"; UNDP Tanzania INFF workshop for local governments, 10 June 2025.
Clyde & Co, PPP Act amendments (July 2023) and PPP Regulations Amendments (2023); ICE/ITA, "Tanzania scales up PPP projects", 16 September 2025; TanzaniaInvest, "Tanzania Signs Nine PPP Contracts for DART, Ports and TAZARA Railway" (June 2026).
World Bank PPP Support Programme, "Tanzania's Municipal PPPs" (undated); World Bank results frameworks P159489 and P148974; TanzaniaInvest, "Tanzania Financial Markets Week to 2 October 2026".
Daily News, The Citizen, The Guardian (IPP Media) reporting on the Magufuli, Nane Nane/Dodoma and Msamvu terminals (2018–September 2026); Daily Monitor (Uganda) on Kampala markets; Ghanaian Times, MyJoyOnline, Graphic Online on Kejetia; University of Bergen study on Takoradi.
13 - Quick AnswersFrequently Asked Questions
What is the bankability-affordability dilemma in Tanzania's Local Government Authorities?
To attract private capital, an LGA project (illustrated here by markets and bus terminals) must produce revenue that repays lenders and rewards investors. But its users are often low-income people who cannot pay cost-reflective charges. Public value, affordability and bankability can be achieved two at a time; the third breaks without extra public support.
How much higher is the bankable rent than what traders can afford?
In the TICGL/TERI illustrative case, the rent needed to repay the building on commercial terms is 3.4 to 7 times the median stated affordability of about TZS 8,300 per lettable square metre per month. The base case needs about TZS 58,200 per square metre per month; the highest stated rent in the sample was TZS 17,100.
Can cross-subsidy from anchor tenants close the gap?
Only partly. If 50 to 80 percent of space is let at an affordable social rent of TZS 11,000 per square metre, anchor tenants would have to pay TZS 105,000 to 247,000 per square metre per month, 6.1 to 14.4 times the highest rent any respondent said they could pay.
Who ends up paying the viability gap?
The gap is conserved: it is paid by traders (higher rents, exits, arrears), consumers and commuters (higher prices and fees), taxpayers or the LGA (viability gap funding, grants, guarantees) or investors and lenders (lower returns or no financial close). Making a project bankable through user charges moves the cost from the budget to the citizen.
Can small traders pass a rent increase on to customers?
Not realistically. With 76 percent of existing traders reporting sales under TZS 500,000 a month, raising rent from TZS 75,000 to TZS 300,000 would need a 90 percent price rise at TZS 250,000 of sales. Traders instead exit, sub-let or go informal, and the space goes to higher-turnover tenants.
What does the Magufuli bus terminal show about fee-based terminals?
The TZS 54.6 billion Magufuli terminal at Mbezi Luis was about 93 percent funded by a central-government grant, yet buses bypass it, the municipality loses revenue, and in September 2026 the Ubungo council was pursuing over TZS 249 million of tenant rent arrears. Morogoro's Msamvu terminal, built with a pension-fund partner on a main corridor, performs better but its reported takings equal only about 7 percent of its phase-one cost.
How much public capital makes rents affordable?
In the base case, required rent falls to the range traders say they can pay only at about 60 to 70 percent public or concessional capital contribution with a hurdle rate near 12 percent. At that point the project is economically publicly funded infrastructure with private operation, and the question becomes value for money.
What should an LGA test before taking a project to PPP?
TICGL/TERI proposes a nine-point screen: affordability, rent-to-sales, capital-recovery gap, public-good cost, bypass and demand risk, pass-through, displacement, sustainability and fiscal exposure, with a pass-through table and both financial and economic returns shown at pre-feasibility stage.
14 - Explore MoreTICGL Economic: Related Insights & Tools
Companion Study
Project Finance in Tanzania
Why weak project preparation, scarce long-term debt and shallow capital markets hold back financed projects.
Mradi uwe wa kibenki (bankable) na bei iwe nafuu kwa wananchi: Je, vyote viwili vinawezekana? Halmashauri (LGAs) zinahimizwa kupanga na kuendesha miradi inayozalisha mapato, kama masoko, vibanda vya biashara na vituo vya mabasi, ili kuongeza mapato ya ndani na kupunguza utegemezi kwa Serikali Kuu. Ili kuvutia mitaji binafsi, miradi hiyo lazima ilipe madeni na kutoa faida kwa wawekezaji. Lakini watumiaji wake, kama wafanyabiashara wadogo, madereva wa daladala na wanunuzi wa kila siku, wengi wana kipato kidogo. Hali hii inahusu miradi mingi ya halmashauri (nyumba, taka, utalii, usafiri wa umma, masoko na vituo vya mabasi). Utafiti huu wa TICGL/TERI (Oktoba 2026), ulioandikwa na Amran Bhuzohera, unapima kama mahitaji hayo mawili yanaweza kutimizwa kwa pamoja, kwa kutumia masoko na vituo vya mabasi kama mifano (case studies), pamoja na ushahidi wa Tanzania na kanda.
Pengo ni kubwa: Kodi inayohitajika kulipa jengo kwa masharti ya kibiashara ni mara 3.4 hadi 7 ya kiasi ambacho mfanyabiashara wa kati anasema anaweza kulipa (kodi ya kati ya TZS 8,300 kwa mita ya mraba kwa mwezi, dhidi ya TZS 58,200 inayohitajika katika hali ya msingi). Kwa kodi wanazoweza kulipa, mapato ni asilimia 2.3 hadi 4.6 tu ya gharama ya ujenzi, wakati hatifungani ya miaka 15 inalipa takriban asilimia 10.8.
Ruzuku ya sehemu haitoshi: Hata ruzuku ya asilimia 50 ya mtaji pamoja na mkopo nafuu wa muda mrefu bado inaacha kodi inayohitajika mara 1.3 hadi 2.6 ya uwezo wa wafanyabiashara. Kodi huwa nafuu tu pale mtaji wa umma au wa masharti nafuu unapofikia asilimia 60 hadi 70.
Ruzuku ya ndani kwa ndani ina kikomo: Ikiwa asilimia 50 hadi 80 ya nafasi itapangishwa kwa kodi nafuu, wapangaji wakubwa (benki, maduka makubwa, maduka ya dawa) wangelazimika kulipa TZS 105,000 hadi 247,000 kwa mita ya mraba kwa mwezi, jambo lisilowezekana sokoni.
Pengo halipotei, linahamia: Anayelimaliza pengo ndiye anayebeba mzigo: wafanyabiashara, wateja na abiria, walipakodi, au wawekezaji. Mradi ukifanywa wa kibenki kwa ada za watumiaji, gharama inahamia kwa mwananchi. Kwa mfanyabiashara mdogo, kodi ikipanda kutoka TZS 75,000 hadi 300,000 bei zingepaswa kupanda asilimia 90 (mauzo ya TZS 250,000); kwa hiyo wengi huondoka, hupangisha kwa wengine au hurudi mitaani, na nafasi huchukuliwa na wenye mauzo makubwa. Abiria hulipa TZS 35 hadi 135 kwa safari kwa kila ada ya kituo ya TZS 1,000 hadi 2,000.
Mifano ya Tanzania: Kituo cha Magufuli (TZS bilioni 54.6, takriban asilimia 93 ni ruzuku ya Serikali Kuu) kinakabiliwa na mabasi kukwepa, hasara ya mapato ya manispaa na malimbikizo ya kodi ya zaidi ya TZS milioni 249 (Septemba 2026). Msamvu (Morogoro), kilichojengwa na LAPF kwenye barabara kuu, kinafanya vizuri zaidi lakini mapato yake ya mwaka ni takriban asilimia 7 tu ya gharama ya awamu ya kwanza. Kuna miradi 410 ya PPP katika halmashauri 184, lakini mikataba 9 pekee ndiyo imesainiwa kitaifa hadi Juni 2026.
Mapendekezo: (1) Tenganisha kiini cha huduma za umma (vyoo, mifereji, usalama) na sehemu ya kibiashara; (2) fadhili kiini hicho kwa Ufadhili wa Pengo la Uwezekano (VGF), ruzuku au mtaji nafuu; (3) tumia kodi za ngazi tofauti na linda wafanyabiashara waliopo kwa haki ya kurudi na ukomo wa ongezeko la kodi; (4) jenga kwa mahitaji halisi, si kwa kulazimisha; (5) andika utawala wa ushuru kwenye mkataba; (6) tumia kipimo cha vipengele tisa (uwezo wa kulipa, kodi dhidi ya mauzo, pengo la kurejesha mtaji, gharama za huduma za umma, hatari ya kukwepa, mwitikio wa bei, uhamishaji, uendelevu na mzigo wa kifedha) wakati wa upembuzi wa awali, pamoja na jedwali la mwitikio wa bei. TICGL/TERI hutoa upembuzi yakinifu (feasibility), ushauri wa kuingia sokoni na utafiti wa soko.
Hitimisho: Uwezo wa kibenki hauondoi ruzuku; unaihamisha kutoka bajeti kwenda kwa wananchi. Swali kwa kila mradi wa halmashauri ni nani abebe pengo: walipakodi kupitia ruzuku inayoonekana wazi, au wafanyabiashara wadogo na abiria kupitia bei na ada.
Kodi inayohitajika: mara 3.4 hadi 7 ya uwezo wa kati · TZS 58,200 dhidi ya 8,300 kwa m² kwa mwezi
Mapato kwa kodi nafuu: asilimia 2.3 hadi 4.6 ya gharama · hatifungani ya miaka 15: asilimia 10.8
Mtaji wa umma unaohitajika kufikia unafuu: asilimia 60 hadi 70 · mtaji wa ruzuku ya asilimia 50 bado unaacha mara 2.3 hadi 2.6
Chanzo: TICGL/TERI, The Bankability–Affordability Dilemma (Oktoba 2026), mwandishi: Amran Bhuzohera. Kwa ripoti kamili: economist@ticgl.com.
Tanzania Credit Boom vs SME Capital Access 2026: Who Gets the Loans? | TICGL
Credit Is Growing, But Are Small Businesses Getting Capital? Tanzania, 2025–2026
Mikopo Inaongezeka, Lakini Biashara Bado Zinakosa Mitaji? Private-sector credit grew 31.2% in the year to July 2026 and now equals about 23% of GDP. Yet the IMF's new resident representative still lists access to affordable finance among the reforms Tanzanian businesses most need. This page asks why headline credit growth does not guarantee capital for small traders and SMEs, by looking at credit versus GDP and money growth, where the new lending goes, what it costs and how banks are positioned.
📅 Data: Dec 2024 – Jul 2026📍 Tanzania🏛️ TICGL / TERI Economic Research Division📖 Basis: Bank of Tanzania data as reported, IMF interview
Private credit growth, Jul 2026
+31.2% from 23.5% Dec 2025
Private credit / GDP
23.2% Apr 2026
Personal loans, share of credit
34.0% mostly MSMEs
Overall lending rate, Jul 2026
14.85% prime 12.04%
Source: Bank of Tanzania monthly reviews and reports as published by TanzaniaInvest, The Guardian (IPP), The Citizen and Daily News; IMF resident representative interview, 1 October 2026. Calculations by TICGL/TERI.
00 — OverviewExecutive Summary: Faster Credit, Unchanged Questions for Small Firms
Credit growth is a measure of how much banks lend in total. It does not say who receives the loans, what they pay, how long they have to repay or whether the borrowers are the small firms that report a shortage of capital. In 2026 the Tanzanian numbers are strong on volume and thinner on composition, and that gap in the evidence is the main finding of this page.
Credit stock, May 2026
≈ TZS 49 tn
+22.5% from about TZS 40 tn a year earlier
Credit vs money, Jul 2026
31.2% vs 26.9%
credit now outpaces M3 growth
Manufacturing credit, Jun 2026
+0.9%
while trade grew 59.5%
Dar es Salaam share of loans
51.6%
Dec 2025; 62% of deposits
Private Credit Growth, Year on Year
Percent, selected months. Source: Bank of Tanzania monthly reviews as reported; TICGL/TERI
Rates Small Borrowers Face vs the Policy Rate
Percent. Central Bank Rate for Q4 2026; market rates for July 2026. Source: BoT as reported
Key findings
Credit growth accelerated through 2026. From 23.5% in December 2025 to 28.1% in June and 31.2% in July, now above the 26.9% growth of broad money.
The fastest growth is not in the sectors most associated with small-firm production. Trade (59.5%), transport and communication (46.4%) and agriculture (39.9%) led in June, while manufacturing grew 0.9%. Manufacturing's share of credit fell from 9.7% to 7.2% between February 2025 and February 2026.
SME lending is hidden inside "personal loans". At 34.0% of credit, this category is the largest and is described by the BoT as predominantly MSME lending, so household and business borrowing cannot be separated in the published data.
Borrowing remains expensive. The overall lending rate was 14.85% in July against a 12.04% prime rate and 9.34% on 12-month deposits. After inflation of 4.2% the real lending rate is about 10.6 points.
Banks are healthy but selective. Non-performing loans were 2.8% at end-2025, and bank holdings of Treasury securities rose to TZS 10.27 tn in March 2026. A low NPL ratio is consistent with cautious lending, though it does not prove it.
The IMF flags the issue. Its resident representative says businesses need affordable credit, and welcomes the new secured transactions framework that lets smaller firms use movable assets as collateral.
Bottom line
Rising credit and an SME capital gap are compatible. Volume has grown, but price, concentration, composition and collateral rules decide who benefits. The published aggregates cannot size the gap; a firm-level test (Tab 5) can.
01 — The Credit BoomCredit vs GDP and vs Money: Fast Growth From a Low Base
Private Credit as a Share of GDP
Percent. Bars carry their source: BoT-based Citizen reports (Dec 2024, Dec 2025, Feb 2026) and TanzaniaInvest (Apr 2025, Apr 2026). Not strictly comparable. December 2025 is "more than 21%"; February 2026 "about 22%"
Credit Growth vs Broad Money (M3) Growth
Percent year on year. Source: BoT monthly reviews as reported by TanzaniaInvest; TICGL/TERI
Indicator
Apr 2026
May 2026
Jun 2026
Jul 2026
Private credit growth, y/y
23.6%
23.2%
28.1%
31.2%
M3 broad money growth, y/y
22.0%
25.2%
25.5%
26.9%
Overall lending rate
n/a
15.32%
15.22%
14.85%
Central Bank Rate (quarter)
5.75%
5.75%
5.75%
6.25%
Table 1. Credit, money and rates. Sources: BoT monthly reviews as reported (TanzaniaInvest, The Guardian). The CBR was raised to 6.25% for Q3 2026 and held for Q4. Reported May M3 growth differs slightly between reports (25.2% and 25.5% for June).
At about 23% of GDP, private credit is still modest, so rapid growth partly reflects a low base. That is the main reason to avoid reading 31% growth as proof that capital is abundant. Bank balance sheets are also expanding quickly: total bank assets reached TZS 85.1 tn in March 2026 and TZS 91.3 tn in the first half, with a loan-to-deposit ratio of 87.5%. With credit now growing faster than M3, the room banks have to keep expanding at this pace depends on deposit growth continuing (an inference from the data, not a BoT statement).
02 — Where the Credit GoesGrowth Is Concentrated in Trade, Transport and Mining, While Manufacturing Stalls
Credit Growth by Sector, June 2026
Percent year on year. Source: BoT Monthly Economic Review (July 2026) as reported by TanzaniaInvest
Share of Total Credit, July 2026
Percent. "All other" is derived as the remainder. Source: BoT as reported; TICGL/TERI
Personal Loans vs Manufacturing: Share of Credit
Percent of total private credit. Sources: BoT as reported (TanzaniaInvest, The Citizen)
Bank Deposits by Zone, December 2025
TZS trillion, selected zones (total TZS 42.3 tn). Source: Consolidated Zonal Economic Performance Report as reported
Reading the composition
The SME channel is opaque. The BoT says personal loans are mainly extended to micro, small and medium enterprises through individual facilities. That is useful to know, but the share going to business working capital rather than household spending is not published. Analysts quoted in the press read the high personal-loan share as a sign that credit leans towards consumption.
Fast growth in capital-intensive sectors. In July, transport and communication credit grew 66.0% and mining 65.2% (from only 0.8% a year earlier), which are large-ticket borrowers rather than small traders.
Manufacturing is losing share. Its credit contracted 8.2% in December 2025 and grew 0.9% in June 2026, although manufactured exports rose 46% in the year to July, so firms may be funding themselves another way.
Geography matters. Dar es Salaam held 51.6% of loans and about 62% of deposits (26.0 of 42.3 tn), leaving small firms elsewhere with fewer lenders.
Government programmes are targeted. A TZS 1 trillion special agriculture facility, an SME relief window and credit guarantee schemes have been introduced, which helps explain faster agricultural and mining credit.
03 — Price, Risk & Bank AppetiteCredit Is Available at a Price, and Banks Have Safe Alternatives
Measure (July 2026 unless stated)
Value
Reading
Overall lending rate
14.85%
Down from 15.22% in June
Loans of up to 1 year
15.54%
Up from 15.38%; the short-term loans small firms typically use
Prime (negotiated) lending rate
12.04%
Reserved for the strongest borrowers; 3.5 points below the short-term average
12-month deposit rate
9.34%
Spread to overall lending rate: about 5.5 points
Inflation (headline)
4.2%
Real lending rate about 10.6 points (TICGL/TERI calc.)
Non-performing loans, end-2025
2.8%
Lowest in the East African Community
Bank Treasury holdings, Mar 2026
TZS 10.27 tn
Up from TZS 9.61 tn in December 2025
Table 2. Price and risk indicators. Sources: BoT as reported by The Guardian (IPP), TanzaniaInvest, IPP Media. Differences and the real rate are TICGL/TERI arithmetic.
What the prices imply
A real rate near 10 points is hard to service for a small trader with thin margins. The gap between prime and average rates shows that risk pricing is steep: the borrowers with the best collateral and records get far cheaper money.
What low NPLs may mean
A 2.8% NPL ratio shows a sound banking system. It can also reflect lending concentrated on borrowers that banks already know. Both readings fit the data, so TICGL/TERI treats the ratio as a stability signal, not as evidence that small firms are well served.
Policy rate effect
The BoT raised the Central Bank Rate from 5.75% to 6.25% in July 2026 and held it in the fourth quarter to let the increase transmit. Average market lending rates eased slightly in July, so the policy move had not yet shown up in loan prices in the data available.
04 — SME Constraints & the IMF ViewThe Constraints Are Collateral, Cost, Information and Process
Many Tanzanian businesses need affordable credit to invest, grow, and create jobs.
IMF Resident Representative Jana Bricco, interview with TanzaniaInvest, 1 October 2026 (paraphrased from the published text)
The IMF representative put reforms to credit information, land rights, insolvency procedures and capital markets on the list of measures that can widen access, and welcomed the new secured transactions framework because it can let smaller firms use movable assets as collateral. She also stressed simpler regulation, predictable taxation and faster VAT refunds, which affect the working capital that small firms would otherwise borrow.
Constraint
What the evidence says
Evidence type
Collateral
Lack or low value of collateral appears repeatedly in Tanzanian studies of SME borrowing; the movable-assets framework targets this.
Academic studies (mostly 2012–2020); IMF 2026
Cost of credit
Lending rates of about 15% against 12% for prime borrowers; high interest cited by SME owners as a barrier.
BoT 2026; studies
Tenor and grace
Short repayment and grace periods reported by small-enterprise respondents.
Academic studies
Information and process
Complex loan procedures, informality and weak credit information; the IMF names credit information as a reform area.
Studies; IMF 2026
Financial skills
Limited bookkeeping and financial management lead to rejection or self-financing from retained earnings and relatives.
Table 3. SME constraints. The academic studies are small, dated samples and are cited for the mechanism, not for current magnitudes. Sources: Tanzanian university and research repositories; IMF interview; BoT as reported.
What this evidence cannot do
None of these sources gives a current, representative measure of how many Tanzanian small firms apply for credit and are refused or discouraged. The conclusion that a gap persists rests on the IMF's assessment, the price and composition data and the earlier studies. It should be tested directly (Tab 5).
05 — Closing the Gap & TICGLMeasure the Gap First, Then Match the Instrument
5.1 A test that headline data cannot provide
Question
Indicator needed
Where it would come from
Is the gap real?
Share of SMEs that applied, were approved, rejected or discouraged, by size and region
Firm-level survey with a defined sampling frame
Who gets the credit?
Loan stock by firm size and purpose (working capital vs consumption)
Lender portfolio data; BoT sector detail
Is price the barrier?
Rate, tenor and collateral terms offered to small vs large borrowers
Loan-level sample from banks and microfinance
Is demand matched?
Stated capital need vs approved amount, by sector
Business survey; pipeline of bankable projects
Do guarantees and relief reach SMEs?
Take-up of the SME relief window and credit guarantees
BoT and scheme administrators
Table 4. Proposed diagnostic for the SME capital gap, designed by TICGL/TERI.
5.2 Options and where they act
Lower the collateral barrier
Implement the secured transactions framework for movable assets, expand credit guarantees and improve credit reference coverage.
Lower the price and lengthen tenor
Blended and wholesale lines from development partners and domestic institutions, matched to working-capital and equipment needs.
Improve bankability of the borrower
Bookkeeping, formalisation and project preparation so loan applications meet lender criteria.
Add non-debt capital
The planned USD 50 million venture capital fund, aimed at mobilising USD 180 million for startups and SMEs, would add equity where debt is a poor fit.
TICGL and its research arm TERI design SME demand and access-to-finance surveys, lender portfolio reviews, feasibility studies and investment-readiness support. See what we do or contact economist@ticgl.com.
06 — Sources & MethodMethod and Data Notes
Basis
Primary reports (as relayed): Bank of Tanzania Monthly Economic Reviews (January–August 2026), Monetary Policy Reports (January and October 2026), Financial Stability Report 2025, consolidated zonal economic performance report. Secondary sources: TanzaniaInvest summaries of BoT releases; The Guardian (IPP Media), The Citizen and Daily News reporting; IMF Resident Representative interview (1 October 2026). Calculations: real lending rate (14.85% less 4.2% inflation), spread over deposits, prime premium and "all other" credit share are TICGL/TERI arithmetic. Limits: mixed publication dates, small base effects in sector growth, and no firm-size breakdown. Several figures differ across outlets (credit/GDP, December 2025 growth, personal-loan share); the nearest reported figure is shown with its source. Academic SME studies are older and small-sample.
07 — Quick AnswersFrequently Asked Questions
Why does faster private-sector credit growth not guarantee capital for small businesses?
Aggregate growth measures the total stock of lending, not who receives it, at what price or for how long. In 2026 the fastest growth was in transport, mining and trade, manufacturing credit was almost flat and the average lending rate stayed near 15%.
How fast is Tanzania's private-sector credit growing?
23.5% in December 2025, 23.2% in May 2026, 28.1% in June and 31.2% in July 2026, according to BoT monthly reviews as reported.
What share of credit is personal loans, and why does it matter for SMEs?
34.0% in July 2026. The BoT describes them as predominantly MSME lending, so SME credit is partly hidden in a category that also includes household borrowing.
What does the IMF say about access to finance?
Its resident representative called it very important, said businesses need affordable credit, and pointed to credit information, land rights, insolvency, capital markets and the secured transactions framework.
Can these data prove an SME financing gap?
Not directly. Published aggregates do not separate loans by firm size or show rejection rates. A firm-level survey or lender portfolio data is needed to size the gap.
08 — Explore MoreTICGL Economic: Related Insights & Tools
Companion Analysis
Tanzania Credit and Banking Growth, 2000–2003
The earlier credit expansion, from the Bank of Tanzania monetary survey.
Mikopo inaongezeka, lakini biashara bado zinakosa mitaji? Mikopo kwa sekta binafsi ilikua asilimia 31.2 kwa mwaka hadi Julai 2026 (kutoka asilimia 23.5 Desemba 2025), na sasa ni takriban asilimia 23 ya Pato la Taifa. Hata hivyo kasi ya ukuaji haihakikishi kuwa wafanyabiashara wadogo wanapata mitaji.
Mikopo huenda wapi: ukuaji mkubwa ulikuwa kwenye biashara (asilimia 59.5, Juni), usafirishaji (46.4) na kilimo (39.9), wakati mikopo ya viwanda ilikua asilimia 0.9 tu. Mikopo binafsi ni asilimia 34 ya mikopo yote; Benki Kuu inasema hasa ni ya biashara ndogo na za kati, lakini haitenganishwi na mikopo ya kaya.
Gharama: riba ya jumla ya mikopo ni asilimia 14.85 (Julai 2026), mikopo ya hadi mwaka mmoja asilimia 15.54, wakati wakopaji wakubwa (prime) wanapata asilimia 12.04. Baada ya mfumuko wa bei wa asilimia 4.2, riba halisi ni takriban pointi 10.6.
Benki na hatari: mikopo chechefu ni asilimia 2.8 (mwisho 2025), na benki zimeongeza dhamana za Serikali hadi TZS trilioni 10.27 (Machi 2026). Mkoa wa Dar es Salaam una asilimia 51.6 ya mikopo na takriban asilimia 62 ya amana.
IMF: mwakilishi mkazi wa IMF (Oktoba 2026) anasema upatikanaji wa mikopo nafuu ni muhimu kwa biashara, na anakaribisha mfumo mpya wa dhamana za mali zinazohamishika, taarifa za mikopo, haki za ardhi na sheria za ufilisi.
Tahadhari: takwimu zilizochapishwa hazitenganishi mikopo kwa ukubwa wa biashara wala viwango vya kukataliwa, kwa hiyo pengo la mitaji kwa SMEs halijapimwa moja kwa moja. Tunapendekeza utafiti wa biashara ndogo na uchambuzi wa portfolio za benki.
Chanzo: Bank of Tanzania (kama ilivyoripotiwa), IMF, TanzaniaInvest, The Guardian, The Citizen; hesabu za TICGL/TERI. Ripoti na ushauri: economist@ticgl.com.
Tanzania Oil Dollar Demand vs Mining & Farm Inflows | TICGL
TICGL/TERI - Weekly Markets Deep-Dive, 20 October 2026
TICGL/TERI Economy WatchDollar Flows by SectorOil & EnergyGrowth Impact
Mining and Agriculture Earn the Dollars, Oil Spends Them: What Tanzania's Dollar Gap Means for Growth, Day by Day
In the week to 16 October 2026, banks bought USD 121.35 million more than they sold, and 90.5% of that net inflow came from two sectors: mining (USD 57.36 million) and agriculture (USD 52.47 million). On the other side, oil and energy needed USD 49.33 million net, the largest of any sector. For now the two sides balance with room to spare, with a cover of 2.2 times. A week earlier the cover was 1.25 times. This page uses the Bank of Tanzania's weekly sector data to show who supplies and who uses the dollars, what the oil sector's dollar appetite costs in shillings every day, how it feeds through to prices and growth, and how far mining and agriculture could slow before the cushion disappears.
📅 Data to: 16 October 2026📍 Dar es Salaam, Tanzania🏛️ TICGL / TERI📖 Source: Bank of Tanzania, Domestic Financial Markets Weekly Report
Mining + agriculture, net
USD 109.83 m 90.5% of net
Oil & energy, net need
USD 49.33 m 23.6% of sales
Cover ratio, this week
2.2x 1.25x last wk
Oil dollar bill per weekday
TZS 30.0 bn USD 11.4 m
Source: Bank of Tanzania, Domestic Financial Markets Weekly Report, 12-16 October 2026 (Table 2); TICGL/TERI calculations. Weekday figures divide the weekly total by five. Stress tests are arithmetic scenarios, not forecasts.
Disclaimer & scope
Prepared by TERI for research and strategic-information purposes only. It is not investment, legal, tax or financial advice and does not state the position of the Bank of Tanzania or the Government. All sector figures come from the Bank of Tanzania Domestic Financial Markets Weekly Report for 12-16 October 2026; figures marked "TICGL calc." are our arithmetic on those numbers. The report does not define "purchases" and "sales" in its sector table: we read purchases as dollars banks bought from customers (supply of dollars) and sales as dollars banks sold to customers (use of dollars). Price, import, external-balance and growth evidence in Tab 4 comes from the Bank of Tanzania Monthly Economic Review, September 2026 (data to August 2026). The link from weekly dollar flows to those outcomes is analytical, not a measured causal effect. One week of flow data is a short window: patterns may not persist.
00 — OverviewExecutive Summary
Tanzania's dollar market has a simple structure in the week to 16 October 2026. Two commodity sectors, mining and agriculture, sold banks far more dollars than they bought back. A different group of sectors, led by oil and energy and manufacturing, did the opposite. Trade, the biggest sector by turnover, swung from heavy net buying to small net selling. The result is a banking system that bought USD 121.35 million more than it sold, a shilling that moved only 0.07% to TZS 2,633.12 per dollar, and a question: how dependent is that stability on two sectors?
Mining net supply
USD 57.36 m
bought 65.77, sold 8.41
Agriculture net supply
USD 52.47 m
purchases up 62.4% w/w
Oil & energy net need
USD 49.33 m
bought 57.06, sold 7.73
Cover ratio
2.2x
1.25x the week before
Who Supplies and Who Uses the Dollars
USD million, week to 16 Oct 2026. Left bar: dollars banks bought from customers. Right bar: dollars banks sold to customers. Source: BoT Table 2
Cover Ratio: Mining and Agriculture Net Inflow vs Oil and Energy Net Need
Times covered, two weeks. Above 1.0 means the two supplying sectors more than pay the oil bill. Source: BoT Table 2; TICGL calc.
Key findings
Two sectors supplied nine tenths of the net inflow. Mining and agriculture netted USD 109.83 million, 90.5% of the banks' USD 121.35 million net purchase.
Oil and energy is the largest single net buyer. It bought USD 57.06 million, 23.6% of all dollars banks sold, and netted USD 49.33 million after selling USD 7.73 million back.
The cover is comfortable this week and thin last week. The cover was 1.25 times in the week of 5 October (USD 72.99 million against USD 58.56 million) and 2.2 times in the week of 12 October. It nearly doubled in seven days, which also shows how quickly it can move the other way.
Level and swing have different drivers. Mining and agriculture explain the level of the inflow, but trade explains 54% of the USD 185.29 million swing in net flows from the previous week (TICGL calc.).
The oil dollar bill is large next to the interbank market. Oil's net need alone is 2.5 times the entire weekly interbank FX turnover of USD 19.70 million, so it cannot be met in that market alone.
It costs real shillings every day. Oil bought about USD 11.4 million per weekday, roughly TZS 30.0 billion; each 1% shilling depreciation adds about TZS 1.5 billion a week to that purchase.
The Monthly Economic Review confirms the pressure is real. Petroleum imports rose 51.7% to USD 3,425.6 million in the year to August 2026, transport inflation is 13.8% against 1.4% a year earlier, and the current account deficit widened 45.9% to USD 2,481.8 million. Headline inflation is still 4.3%, inside the 3-5% target, and annual real growth data run to 2025 only (Tab 4).
The stress point is closer than it looks. On the latest week's numbers, mining and agriculture would have to fall 55% before the cushion over oil disappears; on the previous week's numbers, only 20%.
Bottom line
The shilling is being held steady by dollars from two commodity sectors that are spent largely by one import-heavy sector. That works as long as the flow continues, and the report gives no sign it will stop. But the cushion varied by a factor of nearly two in a single week, and the same dollar needs push on prices and costs every working day. The next four tabs show who supplies, what oil needs, how it feeds through to the economy, and where the stress points are.
01 — Who Supplies, Who UsesDollar Flows by Sector: Supply, Use and What Changed
The Bank of Tanzania's retail FX table splits every bank-customer dollar transaction by sector. Reading it as supply (dollars banks bought) and use (dollars banks sold) shows which sectors the shilling depends on. Retail turnover rose to USD 604.89 million; purchases were USD 363.12 million and sales USD 241.77 million.
Sector (USD million)
Bought by banks (supply)
Sold by banks (use)
Net, this week
Net, prior week
Change in net
Mining
65.77
8.41
+57.36
+42.33
+15.03
Agriculture
62.74
10.27
+52.47
+30.66
+21.81
Transport & Communication
29.80
6.03
+23.77
+13.21
+10.56
Tourism
24.81
2.07
+22.74
+17.68
+5.06
Trade
97.56
83.72
+13.84
-86.10
+99.94
Individual Retail Customers
25.38
15.84
+9.54
-0.45
+9.99
NGOs
9.05
2.37
+6.68
+6.45
+0.23
Social Services
10.44
5.31
+5.13
+1.96
+3.17
Constructions (Machine & Equipment)
19.44
19.73
-0.29
-0.32
+0.03
Breweries / Beverages
0.13
2.96
-2.83
-4.70
+1.87
Manufacturing
10.29
27.99
-17.70
-26.11
+8.41
Oil & Energy
7.73
57.06
-49.33
-58.56
+9.23
Total (as published)
363.12
241.77
+121.35
-63.94
+185.29
Source: Bank of Tanzania, Table 2; net and change columns are TICGL calc. Sector nets add to the published total within USD 0.05 million of rounding.
Net Dollar Position by Sector, This Week
USD million, purchases minus sales. Positive = sector supplied more dollars than it took (TICGL calc.)
Share of Dollars Supplied vs Share Used, by Sector
Percent of USD 363.12 m purchases and USD 241.77 m sales (TICGL calc.)
1.1 Net suppliers and net buyers
Eight sectors were net suppliers of dollars, together USD 191.53 million. Four were net buyers: oil and energy (USD 49.33 million), manufacturing (USD 17.70 million), breweries (USD 2.83 million) and construction (USD 0.29 million), together USD 70.15 million (TICGL calc.). Mining and agriculture alone supplied 57% of what the eight supplying sectors netted, and the net buyers are the import-intensive part of the economy: fuel, factory inputs, brewing materials and equipment.
1.2 The level and the swing have different drivers
Net flows moved by USD 185.29 million in one week, from a net sale of USD 63.94 million to a net purchase of USD 121.35 million. Mining and agriculture added USD 36.84 million to that swing (19.9%). Trade added USD 99.94 million (53.9%): it moved from net buying of USD 86.10 million to net selling of USD 13.84 million as purchases more than doubled and sales fell 35.8%. Everything else together added the remaining 26%.
What Drove the USD 185 Million Swing?
Change in net dollar position by sector, this week vs prior week, USD million (TICGL calc.)
Mining + Agriculture Net Inflow vs Oil Net Need, Two Weeks
USD million. Oil shown as a positive amount of need. Source: BoT Table 2; TICGL calc.
TICGL/TERI reading
Two separate risks sit in this table. The first is dependence: the level of the net inflow rests on mining and agriculture. The second is volatility: week to week, the swing rests on trade, where a USD 86 million net outflow one week became a USD 14 million net inflow the next. A stable shilling needs both the commodity inflow to hold and trade flows to stay near balance. The report does not show what trade flows consist of, so the cause of the trade reversal is not known from this data.
02 — Oil & Energy's AppetiteHow Big Is the Oil Sector's Dollar Demand?
Oil and energy bought USD 57.06 million from banks this week, down from USD 66.37 million, and sold back only USD 7.73 million (USD 7.81 million the week before). Sector turnover fell 12.7% to USD 64.78 million. Its net need of USD 49.33 million is below last week's USD 58.56 million but still larger than any other sector's.
Oil & Energy
Week of 5 Oct
Week of 12 Oct
Change
Dollars sold by banks to the sector (USD m)
66.37
57.06
-14.0%
Dollars bought by banks from the sector (USD m)
7.81
7.73
-1.0%
Net need (USD m)
58.56
49.33
-15.8%
Total turnover (USD m)
74.18
64.78
-12.7%
Share of all dollars sold by banks
22.2%
23.6%
+1.4 pts
Gross need per weekday (USD m, weekly / 5)
13.27
11.41
-14.0%
Gross need per weekday at 16 Oct rate (TZS bn)
n.a.
30.05
Net need at 16 Oct rate (TZS bn a week)
n.a.
129.89
Source: Bank of Tanzania, Table 2; shares, per-weekday and TZS conversions are TICGL calc. at TZS 2,633.12 per dollar (the 16 October mean rate). The oil sector's fall in sales went with a fall in turnover; the report does not say whether volumes or prices changed.
Oil & Energy: Supply, Use and Net
USD million, two weeks. Source: BoT Table 2; TICGL calc.
Daily Scale of the Dollar Flows
USD million per weekday (weekly total / 5), week to 16 Oct 2026. Source: BoT; TICGL calc.
2.1 Why oil's dollar need is a macroeconomic issue, not a sector issue
It is large against the wholesale market. Oil's net weekly need of USD 49.33 million is 2.5 times the weekly interbank FX turnover (USD 19.70 million). Mining and agriculture's net supply is 5.6 times it. The sector flows are therefore bigger than the market where banks trade among themselves to even out positions.
It is repeated every week. Oil's net need was USD 58.56 million and USD 49.33 million in the two weeks of the report: a steady drain rather than an occasional spike.
It does not offset itself. For every dollar oil takes from banks it supplies back only 14 cents (USD 7.73 million against USD 57.06 million). Trade, by contrast, supplied 34 cents per dollar taken in the prior week and USD 1.17 this week, which is why trade's net can swing both ways while oil's stays negative.
It sits alongside other import-heavy sectors. Manufacturing supplied about 37 cents for every dollar it took (USD 10.29 million against USD 27.99 million) and breweries almost nothing. Together with oil these are the structural net buyers.
What this report does not show
The weekly report covers only dollars that pass through banks in the retail market. It does not show fuel import volumes or prices, the share of fuel financed through other channels, the Bank of Tanzania's own foreign-currency operations, or the Government's dollar payments. The oil figures here are the sector's dollar use through the banking system, not the national fuel import bill. Tab 4 checks them against the Monthly Economic Review: annualised, they equal about 87% of the year-to-August petroleum import bill.
03 — Dollars to Daily ImpactHow the Oil Dollar Bill Reaches Prices and Growth
The dollar gap matters because it is paid in shillings. Each day, oil importers need dollars, banks supply them from the dollars mining and agriculture sold, and the price of the dollar sets what that fuel costs at the pump, in the truck and on the factory floor. This tab shows the chain and puts shilling numbers on its first link.
Day 0 · DollarsOil and energy needs about USD 11.4 million a weekday from banks (USD 9.9 million net of its own sales).
Day 0 · Bank positionBanks supply it from the dollars mining and agriculture sold them: about USD 22 million net per weekday.
Days · Exchange rateIf supply falls short or demand rises, the shilling weakens. Each 1% adds about TZS 0.3 billion a weekday to the oil dollar bill.
Weeks · Prices & costsDearer fuel and imports raise transport, food distribution, factory and construction costs.
Quarters · GrowthHigher costs squeeze real incomes, margins and investment, and dollar loans cost more to service.
Tab 3 shows direction and arithmetic. The weekly report has no price, inflation or GDP series; Tab 4 tests the later links against the Monthly Economic Review.
3.1 The first link in numbers: the shilling cost of the oil dollar bill
Gross, per weekday
TZS 30.0 bn
USD 11.41 m x 2,633.12
Net, per weekday
TZS 26.0 bn
USD 9.87 m net need
Gross, per week
TZS 150.2 bn
USD 57.06 m
Cost of 1% depreciation
TZS 1.5 bn/wk
about TZS 78 bn over a year at this pace
Try it: what does a weaker shilling add to the oil dollar bill?
New rate
2,659.45
TZS per USD
Extra cost, per weekday
TZS 0.30 bn
weekly / 5
Extra cost, per week
TZS 1.50 bn
same dollars, higher rate
Extra cost, per year
TZS 78.1 bn
52 weeks, if sustained
Defaults are the report's figures: USD 57.06 million of weekly oil-sector purchases from banks at the 16 October rate. The result is the extra shillings needed to buy the same dollars, a first-round cost before any pass-through to prices.
Extra Weekly Shilling Cost Under the Four Rate Scenarios to 13 November
TZS billion, same USD 57.06 m of weekly oil purchases, vs the 16 Oct rate of 2,633.12. Rates: 2,622.60 / 2,633.12 / 2,640.50 / 2,659.56 (TICGL scenario arithmetic)
3.2 Channels to growth, from days to quarters
Channel
How it works
Who is hit first
In the weekly report
Not in it (see Tab 4)
Exchange rate
Dollar shortfall or rising oil demand weakens the shilling within days
All importers; dollar borrowers
Net flows, sector split, rate +0.07%
Daily rate path
Fuel and transport costs
A weaker shilling raises the shilling cost of the oil dollar bill, then pump prices and freight
Transport, distribution, farmers moving crops
Oil need USD 49.33 m net a week
Pump prices; import volumes (Tab 4)
Production inputs
Manufacturers and brewers pay in dollars for inputs
Manufacturing (net -USD 17.70 m), breweries
Sector nets
Input mix; pass-through to output prices
Consumer prices and demand
Higher transport and import costs feed into prices, eroding real income
Households, especially urban and low-income
Nothing direct
Inflation (Tab 4); spending data
Debt service
Dollar loans cost more shillings to service when the shilling weakens
Borrowers with shilling revenue
Nothing direct
Dollar loan stock
Offsetting gain
A weaker shilling raises shilling income of exporters
Miners, farmers, tourism and transport operators
Mining, agriculture, tourism, transport all net suppliers
Export prices and volumes
Source: TICGL/TERI analysis. The last two columns separate what the BoT weekly report evidences from what it does not.
TICGL/TERI reading
Growth is not hit by the oil dollar bill itself, which is a normal cost of running an economy, but by sudden changes in what it costs. A steady flow of mining and agricultural dollars turns oil into a predictable expense. When that flow weakens, the shilling is the shock absorber, and the same oil volume costs more shillings every day. Sectors that earn dollars gain from that shock and sectors that spend dollars lose, so the net effect on growth depends on whether the economy's weight sits more with exporters or with importers and consumers. The report shows exporters carry the dollar supply and the import-heavy sectors carry the dollar need, which is the setup for an uneven effect.
04 — Evidence: Prices & GrowthWhat the Monthly Economic Review Shows: Fuel, Prices, Imports and Growth
The weekly report shows dollar flows. The Bank of Tanzania's Monthly Economic Review, September 2026 (data to August 2026) shows what has happened to prices, imports, the external balance and growth. Read together they test the chain in Tab 3: oil dollar demand, then the rate, then costs and prices, then growth. The short answer is that the pressure shows up clearly in imports, the external balance and transport prices, while headline inflation and annual growth data have not moved out of range.
Petroleum imports, yr to Aug-26
USD 3,425.6 m
+51.7% from USD 2,257.4 m
Transport inflation
13.8%
1.4% a year earlier; 14.1% of the CPI basket
Current account deficit
USD 2,481.8 m
+45.9% from USD 1,700.9 m
Gold exports
USD 5,625.0 m
+30.2% from USD 4,321.5 m
Petroleum Imports, Gold Exports and Current Account Deficit
USD million, year ending August 2025 vs August 2026 (provisional). Source: BoT Monthly Economic Review, Table 2.7.1 and Chart 2.7.4
4.1 Fuel to prices: visible in fares, not yet at the pump
Group (CPI weight)
Aug-25
Jul-26
Aug-26
Reading
Headline (100.0)
3.4
4.2
4.3
Inside the 3-5% target
Transport (14.1)
1.4
13.8
13.8
Lagged pass-through of earlier fuel price rises to bus, taxi and motorcycle fares
Energy, fuel and utilities (5.7)
2.6
6.9
8.5
Highest since October 2024; driven by charcoal and firewood
Core (73.9)
2.0
3.9
4.1
Rising steadily since March 2026
Services (37.2)
0.8
5.7
5.9
Up from 0.8%
Food (28.2)
7.7
4.1
3.7
Easing; favourable supply
Source: Bank of Tanzania, Monthly Economic Review September 2026, Table 2.1.1.
Pass-through is real and concentrated. Transport inflation jumped from 1.4% to 13.8% and has stayed at 13.8%. By weight (14.1% x 13.8%) transport alone accounts for roughly 1.9 percentage points of the 4.3% headline rate (TICGL rough calc.).
It is not coming from pump prices right now. The Review says petrol and diesel prices in Dar es Salaam are well below their June 2026 levels; the energy index is being lifted by charcoal and firewood. Fares kept the earlier increase.
The upside risk is flagged by the Bank itself. Crude oil averaged USD 84.4 a barrel in August (+5.8% on the month, about 36% above the fourth-quarter 2025 average), and the Review says rising refined-product prices present upside risks to domestic energy inflation.
Core inflation is rising. Core is 4.1% and has risen steadily since March 2026, which the Bank reads as a gradual build-up of underlying pressure.
4.2 Imports and the external balance
Year ending August (USD million)
2025
2026p
Change
Petroleum products imports
2,257.4
3,425.6
+51.7%
Imports of goods and services
n.a.
21,269.2
+21.4%
Exports of goods and services
n.a.
20,216.2
+16.4%
Goods exports
9,981.2
11,960.8
+19.8%
Gold exports
4,321.5
5,625.0
+30.2%
Freight payments
1,300.4
1,683.4
+29.5%
Service payments
3,196.2
3,498.2
+9.4%
Current account deficit
1,700.9
2,481.8
+45.9%
Source: Bank of Tanzania, Monthly Economic Review, September 2026 (Table 2.7.1 and text); p = provisional. Changes for goods exports, gold, freight and service payments are TICGL calc. where the Review gives levels only; "n.a." = prior-year level not shown in the text.
Oil is a third of the import increase. Petroleum accounted for about one third of the increase in the goods import bill, and the Review says higher petroleum and intermediate-input costs pushed import growth above export growth, widening the trade and current account deficits.
Gold is the offset. Gold exports rose USD 1,303.5 million, about 66% of the whole rise in goods exports (USD 1,979.6 million; TICGL calc.), on higher prices and volumes. Gold averaged USD 4,411 an ounce in August, up 8.3% on July. This is the "mining leg" of the dollar cushion in Tab 5.
In shillings. At the August average rate of TZS 2,657.01, the year-to-August petroleum bill is about TZS 9.1 trillion, TZS 3.1 trillion more than a year earlier at the same rate. Each 1% fall in the shilling adds about TZS 91 billion a year to it (TICGL calc.).
The weekly flows are a good proxy. Annualised, the oil sector's bank purchases (USD 57.06 million x 52 = USD 2.97 billion) are about 87% of the Review's year-to-August petroleum import bill, so the weekly sector table captures most of the fuel dollar demand.
4.3 The shilling, the Bank's operations and reserves
The Bank was in the market. In August the Bank sold a net USD 45.4 million in the interbank FX market "to alleviate undue volatility", equal to about 24% of that month's USD 190.3 million of interbank turnover (TICGL calc.). That answers a question the weekly report leaves open: part of the shilling's stability is intervention, not only commodity inflows.
The rate has been steady. The shilling averaged TZS 2,657.01 in August against TZS 2,653.52 in July. Its 6.7% annual depreciation largely reflects a base effect, as August 2025 averaged an unusually strong TZS 2,490.16.
Reserves are a buffer. Gross official reserves were USD 5,888.2 million at end-August, 4.2 months of projected imports (excluding FDI-related imports), above the national benchmark, supported by export earnings and the Bank's gold purchase programme.
Current Account Balance, 2018-2025 and Year to Aug-26
USD million. Last bar is the year ending August 2026 (provisional). Source: BoT Table A1 and Table 2.7.1
Growth has been steady. Real GDP growth was 5.2% in 2023, 5.6% in 2024 and 5.9% in 2025 (provisional), with inflation between 3.1% and 3.8%. The Review's annual series stops at 2025, so any 2026 growth effect of the fuel and import pressure is not yet visible.
The deficit had been narrowing, then turned. The current account deficit fell from USD 5,482.2 million in 2022 to USD 2,049.4 million in 2025, then widened to USD 2,481.8 million in the year to August 2026.
A precedent. In 2022 goods imports jumped 42% (USD 10,003.4 million to 14,208.7 million), the current account deficit reached USD 5.5 billion, growth slowed to 4.6% from 4.9% and inflation rose to 4.3% from 3.7%. The Review does not attribute that episode to one cause, so it is a reference point for what an import-cost shock can look like, not a forecast.
What this means for the question: how does oil dollar demand affect growth?
On the evidence to August 2026, the oil dollar bill is a pressure on the external balance, on transport costs and on core inflation, and the Bank is managing it with reserves and FX operations, while gold earnings pay for most of it. It is not yet a visible drag on headline inflation (4.3%, inside target) or on annual growth (5.9% in 2025). The risk is the combination in Tab 5: if gold prices or volumes soften while crude stays near USD 84 a barrel, the cushion thins, reserves and intervention carry more of the load, and the fare-style pass-through seen in transport spreads to the rest of the basket.
What is still not measured
No source here gives 2026 quarterly GDP, fuel pump prices in shillings per litre (the Review shows them only in a chart), or the share of the transport price rise caused by the exchange rate rather than by global crude prices. The effects are therefore described, not decomposed.
05 — Stress TestWhat If Mining and Agriculture Slow? The Cushion Over Oil
The stress test uses one rule: net surplus = mining and agriculture net inflow x (1 - fall) minus oil net need x (1 + rise). The only inputs are the Bank's weekly numbers. A positive result means the two commodity sectors still more than cover oil. A negative one means other sectors or the Bank would have to fill the gap. The rule ignores everything else in the dollar market, so it measures the cushion, not the exchange rate.
Break-even fall, latest week
55.1%
oil unchanged; 46.1% if oil +20%
Break-even fall, prior week
19.8%
oil unchanged; 3.7% if oil +20%
Surplus now
+USD 60.5 m
109.83 minus 49.33, per week
Surplus, prior week
+USD 14.4 m
72.99 minus 58.56, per week
4.1 Latest week as the base
Fall in mining + agriculture inflow
Oil need unchanged
Oil +10%
Oil +20%
Oil +30%
No fall
+60.5
+55.6
+50.6
+45.7
-10%
+49.5
+44.6
+39.7
+34.7
-20%
+38.5
+33.6
+28.7
+23.7
-30%
+27.6
+22.6
+17.7
+12.8
-40%
+16.6
+11.6
+6.7
+1.8
-50%
+5.6
+0.7
-4.3
-9.2
-60%
-5.4
-10.3
-15.3
-20.2
Net surplus in USD million a week. Base: mining + agriculture USD 109.83 m, oil USD 49.33 m (week of 12 Oct). Red = deficit; TICGL calc.
4.2 Previous week as the base
Fall in mining + agriculture inflow
Oil need unchanged
Oil +10%
Oil +20%
Oil +30%
No fall
+14.4
+8.6
+2.7
-3.1
-10%
+7.1
+1.3
-4.6
-10.4
-20%
-0.2
-6.0
-11.9
-17.7
-30%
-7.5
-13.3
-19.2
-25.0
-40%
-14.8
-20.6
-26.5
-32.3
-50%
-22.1
-27.9
-33.8
-39.6
-60%
-29.4
-35.2
-41.1
-46.9
Net surplus in USD million a week. Base: mining + agriculture USD 72.99 m, oil USD 58.56 m (week of 5 Oct). Red = deficit; TICGL calc.
Net Surplus Over Oil: Latest-Week Base
USD million a week, by fall in mining + agriculture inflow, for three oil-demand cases
Net Surplus Over Oil: Prior-Week Base
USD million a week, same cases; the cushion is far thinner
4.3 What the stress test says
The two weeks give very different answers. The break-even fall is 55% on the latest week and 20% on the previous week. A week of good inflows hides how quickly the cushion can shrink.
Oil demand matters about as much as supply. A 20% rise in oil demand costs about USD 9.9 million a week of cushion on the latest base, the same as a 9% fall in mining and agriculture.
A fall in the surplus is not the same as a fall in the shilling. Other sectors, bank positions and the Bank of Tanzania's operations can fill a gap. The test shows where the pressure would start.
Agriculture is the faster mover. Its purchases rose 62.4% in one week; a seasonal export rise (which the report does not state) could fade as quickly. Mining's purchases rose 29.4% (USD 50.82 million to 65.77 million).
Where the pressure would show first
If the cushion shrinks, the first signs would be a larger net sale of dollars by trade, banks selling more than they buy in the retail market, interbank FX turnover climbing from its USD 4-5 million a day, and a faster weekly rise in the mean rate than the 0.07% seen now.
06 — Risks & PolicyDependence, Volatility and the Policy Options
Risk
Evidence in the BoT report
Likelihood (next 4 weeks)
Impact
Most exposed
Commodity-inflow slowdown
Mining + agriculture supplied 90.5% of net inflow; agriculture purchases +62.4% in one week
Medium
High
Shilling; import-heavy sectors
Oil demand rise
Oil bought USD 57.06 m, 23.6% of dollars sold; supplies back only 14 cents per dollar
Medium
High
Importers; transport; consumers
Thin cushion in weak weeks
Cover 1.25x in the week of 5 Oct; break-even fall 19.8%
Medium
Medium
Exchange-rate stability
Trade flow reversals
Trade drove 53.9% of the USD 185 m swing; net USD -86.10 m to +13.84 m
Medium
Medium
Weekly rate path
Thin interbank market
USD 19.70 m a week vs USD 49.33 m oil net need
Medium
Medium
Price discovery
Manufacturing input squeeze
Manufacturing net -USD 17.70 m; supplies about 37 cents per dollar it takes
Low
Medium
Factories; construction suppliers
Fuel pass-through to consumer prices
Monthly Review: transport inflation 13.8% (14.1% CPI weight), energy and utilities 8.5%, crude USD 84.4 a barrel
Medium
Medium
Households; transport users
Widening current account
Monthly Review: deficit USD 2,481.8 m, +45.9%; petroleum imports +51.7%; reserves 4.2 months of imports
Medium
High
Reserves; the shilling
Dollar debt service
No direct data; weaker shilling raises debt cost
Low
Medium
Borrowers with shilling revenue
Source: TICGL/TERI analysis. Likelihood and impact are analytical judgements (Low/Medium/High), not model outputs.
5.1 Policy options, by horizon
Next four weeks
Monitoring. Track the cover ratio (mining + agriculture net over oil net) weekly; a reading below 1.5 flags a thin cushion.
Transparency. Publish sector flows by commodity (gold, crops, fuel) alongside the weekly report.
Liquidity and FX operations. Keep the Bank's operations flexible while net flows swing by more than USD 150 million a week.
Medium term (1-3 years)
Smooth the oil bill. Payment scheduling and pooled procurement so fuel purchases do not peak with weak export weeks.
Widen dollar supply. Add value in minerals and crops, and grow services exports such as tourism and transport, both already net suppliers.
Hedging. Products for fuel importers and dollar borrowers.
Longer term (to 2030)
Reduce dollar fuel intensity. Energy-mix and efficiency measures that cut the dollar cost per unit of output.
Diversify exports. Lower the share of net inflow from two sectors.
Deeper FX market. Raise interbank volumes so large sector flows are absorbed without moving the rate.
"A stable shilling is not proof of a balanced dollar economy. It can also mean two sectors are paying for a third."
— TICGL / Tanzania Economic Research Institute (TERI)
Conclusion
Mining and agriculture earn most of the dollars that banks took in during the week to 16 October 2026, and oil and energy is the largest sector spending them. The two sides balance with room to spare, but the cover moved from 1.25 to 2.2 times in one week and the cushion would be exhausted by a 55% fall in the two commodity sectors (20% on the earlier week's numbers). The policy task is to keep the cushion thick, make the oil bill predictable, and widen the sources of dollars.
07 — TICGL & Your ProjectFrom Sector Dollar Flows to Project Decisions
TICGL (Tanzania Investment and Consultant Group Ltd), with its research arm TERI, turns market data into feasibility studies, market-entry advisory and market research. Dollar flows matter to each of them, because whether a business earns or spends dollars decides how it fares when the shilling moves.
Source: TICGL/TERI analysis based on the sector nets in BoT Table 2; indicative only.
6.1 Worked example
A transport company with a USD 5 million dollar loan owes TZS 13,166 million at 2,633.12. At 2,659.56 (the faster-depreciation scenario, +1.0% by 13 November) the debt is TZS 13,298 million: TZS 132 million more with no change in the loan. If the same company buys fuel worth USD 1 million a month, a 1% weaker shilling adds TZS 26 million a month to fuel cost. A feasibility or market-entry model puts both in the downside case and tests whether margins survive.
Feasibility studies
Full feasibility across market, technical, financial, institutional, legal and risk components.
Financial models with NPV, IRR and DSCR under exchange-rate scenarios like those on this page.
Funding-currency analysis: dollar or shilling debt for dollar or shilling revenue.
Market entry advisory
Sector screening by dollar position: net suppliers and net buyers.
Entry mode and cost-base design that matches currency of revenue to currency of cost.
Business facilitation from first meeting to registration and start-up.
Market research and intelligence
Weekly tracking of sector dollar flows and the cover ratio.
Scenario models updated with each Bank of Tanzania release.
Research publications and briefs through TERI.
Talk to TICGL/TERI
Request a feasibility, market-entry or market-research scoping call, or a briefing on this analysis.
Source report. Bank of Tanzania, Domestic Financial Markets Weekly Report, 12-OCT-2026 to 16-OCT-2026: Table 1 (exchange rates), Table 2 (retail foreign exchange by sector), interbank FX turnover. TICGL calculations. Net position = purchases minus sales; shares; contribution to the weekly swing = change in each sector's net; cover ratio = mining and agriculture net divided by oil and energy net need; weekday figures = weekly total divided by five; TZS conversions at TZS 2,633.12 per dollar; stress-test surplus = (mining and agriculture net x (1 - fall)) minus (oil net x (1 + rise)). Scenario rates. 2,622.60 / 2,633.12 / 2,640.50 / 2,659.56 are the 16 October mean rate compounded weekly at -0.10%, 0.00%, +0.07% and +0.25% to 13 November 2026. Monthly Economic Review figures. Inflation, petroleum imports, gold exports, freight, current account, reserves, exchange-rate averages and the 2018-2025 growth and current-account series are quoted as published; the transport contribution (about 1.9 points = 14.1% weight x 13.8%), the TZS value of petroleum imports (USD 3,425.6 m at the August average TZS 2,657.01 = TZS 9.10 trillion) and the 87% cross-check (USD 57.06 m x 52 divided by USD 3,425.6 m) are TICGL arithmetic. Limitations. "Purchases" and "sales" are not defined in the weekly report; one week of flow data; the Monthly Review's annual GDP series ends in 2025 (provisional), so any 2026 growth effect is not yet visible; the report covers bank-customer dollar flows, not all central-bank or government operations.
Bank of Tanzania, Domestic Financial Markets Weekly Report, 12-16 October 2026, Dar es Salaam.
Bank of Tanzania, Monthly Economic Review, September 2026 (data to August 2026): inflation (Table 2.1.1), petroleum imports and current account (Table 2.7.1, Chart 2.7.4), exchange rate and interbank market, Statistical Tables A1 and A5.
TICGL/TERI, Tanzania Domestic Financial Markets Weekly, 12-16 October 2026 (companion page).
09 - Quick AnswersFrequently Asked Questions
Which sectors supplied Tanzania's net dollar inflow in the week to 16 October 2026?
Mining (net USD 57.36 million) and agriculture (net USD 52.47 million) supplied USD 109.83 million, 90.5% of banks' total net dollar purchases of USD 121.35 million. Transport and communication (USD 23.77 million) and tourism (USD 22.74 million) were the next largest net suppliers.
How much foreign exchange does the oil and energy sector buy from banks?
Oil and energy bought USD 57.06 million from banks and sold USD 7.73 million to them in the week to 16 October 2026, a net need of USD 49.33 million (USD 58.56 million the week before). That is 23.6% of all dollars sold by banks and about 2.5 times the whole weekly interbank FX market.
Do mining and agriculture dollars cover the oil bill?
Yes in the latest week: mining and agriculture net inflows were 2.2 times oil's net need. The week before the cover was only 1.25 times, so the cushion changes quickly.
How much would mining and agriculture inflows have to fall to cause a net dollar deficit?
On the latest week's numbers, a 55% fall would wipe out the cushion over oil if oil demand were unchanged, or 46% if oil demand rose 20%. On the previous week's numbers, a fall of only 20% would be enough. These are arithmetic stress tests, not forecasts.
How does oil dollar demand affect economic growth day to day?
Through the exchange rate, import and transport costs, production costs for import-dependent sectors, and dollar debt service. The oil sector alone bought about USD 11.4 million a weekday from banks in the latest week, worth about TZS 30 billion a day, so each 1% depreciation adds about TZS 1.5 billion a week to that bill.
What should investors and lenders watch?
Weekly sector net flows from the Bank of Tanzania, the cover ratio of mining and agriculture inflows over oil needs, the interbank FX volume, and whether trade flows keep swinging, since trade drove 54% of the latest week's USD 185 million swing in net flows.
What does the Bank of Tanzania Monthly Economic Review show on fuel, prices and growth?
For the year to August 2026, petroleum imports rose 51.7% to USD 3,425.6 million and the current account deficit widened 45.9% to USD 2,481.8 million. Transport inflation is 13.8% against 1.4% a year earlier, energy and utilities inflation is 8.5%, and headline inflation is 4.3%, within the 3-5% target. Real GDP growth was 5.9% in 2025 (provisional); 2026 growth data are not yet published in the Review.
10 - Explore MoreTICGL Economic: Related Insights & Tools
Companion Analysis
Tanzania Domestic Financial Markets Weekly, 12-16 October 2026
The full weekly picture: shilling, interbank FX, liquidity, Treasury yields and the four-week outlook.
Madini na kilimo vinaleta dola, mafuta yanazitumia. Kwa mujibu wa Ripoti ya Wiki ya Masoko ya Fedha ya Ndani ya Benki Kuu ya Tanzania (BoT) ya wiki ya 12-16 Oktoba 2026, benki zilinunua dola milioni 121.35 zaidi ya zilizouza. Asilimia 90.5 ya ziada hiyo ilitoka sekta mbili: madini (dola milioni 57.36) na kilimo (milioni 52.47). Sekta ya mafuta na nishati ilihitaji dola milioni 49.33 kwa ujumla (ilinunua milioni 57.06, ikauza milioni 7.73), na ndiyo mnunuzi mkubwa zaidi.
Kinga ya sasa: Dola za madini na kilimo ni mara 2.2 ya mahitaji ya mafuta. Wiki iliyotangulia ilikuwa mara 1.25 tu (milioni 72.99 dhidi ya 58.56). Kinga inabadilika haraka.
Kiwango na mshtuko: Madini na kilimo vinaeleza kiwango cha ziada, lakini biashara ilieleza asilimia 54 ya mabadiliko ya dola milioni 185.29 ya wiki moja: kutoka upungufu wa milioni 86.10 hadi ziada ya milioni 13.84.
Gharama ya kila siku: Sekta ya mafuta ilinunua takriban dola milioni 11.4 kwa siku ya kazi, sawa na TZS bilioni 30. Kila shilingi ikidhoofika asilimia 1, gharama ya dola hizo huongezeka TZS bilioni 1.5 kwa wiki (takriban bilioni 78 kwa mwaka kama hali hiyo ikiendelea).
Athari kwa ukuaji (kwa mujibu wa Mapitio ya Uchumi ya Mwezi Septemba 2026): Uagizaji wa mafuta ulipanda asilimia 51.7 hadi dola milioni 3,425.6 kwa mwaka hadi Agosti 2026, nakisi ya akaunti ya sasa iliongezeka asilimia 45.9 hadi dola milioni 2,481.8, na mfumuko wa bei wa usafirishaji ni asilimia 13.8 ikilinganishwa na asilimia 1.4 mwaka mmoja uliopita. Mfumuko wa jumla ni asilimia 4.3, ndani ya lengo la asilimia 3 hadi 5. Ukuaji halisi wa 2025 ulikuwa asilimia 5.9 (awali); takwimu za ukuaji wa 2026 bado hazijachapishwa. Kwa upande mwingine, mauzo ya dhahabu yalipanda asilimia 30.2 hadi dola milioni 5,625.0, na akiba ya fedha za kigeni ni dola milioni 5,888.2 (miezi 4.2 ya uagizaji).
Jaribio la mshtuko: Kwa takwimu za wiki ya hivi karibuni, dola za madini na kilimo zingepaswa kushuka asilimia 55 ndipo kinga ya mafuta iishe (asilimia 46 mahitaji ya mafuta yakipanda asilimia 20). Kwa takwimu za wiki iliyotangulia, kushuka kwa asilimia 20 tu kungetosha. Hizi ni hesabu za mfano, si utabiri.
Mapendekezo: (1) Kufuatilia uwiano wa kinga kila wiki; (2) kuchapisha mtiririko wa dola kwa bidhaa (dhahabu, mazao, mafuta); (3) kulainisha malipo ya mafuta kwa ratiba na ununuzi wa pamoja; (4) kuongeza thamani ya madini na mazao ndani ya nchi na kukuza mauzo ya huduma; (5) bidhaa za kujikinga (hedging) kwa waagizaji na wakopaji wa dola; (6) kupanua soko la dola la benki kwa benki. TICGL/TERI hutoa upembuzi yakinifu (feasibility), ushauri wa kuingia sokoni na utafiti wa soko.
Hitimisho: Shilingi imara ya wiki hii inalindwa na dola za sekta mbili, na mafuta ndiyo yanayozitumia zaidi. Hilo linafanya kazi mradi mtiririko unaendelea. Kazi ni kuweka kinga nene, kufanya gharama ya mafuta itabirike, na kuongeza vyanzo vya dola.
Madini na kilimo: dola milioni 109.83 · asilimia 90.5 ya ziada
Mafuta na nishati: dola milioni 49.33 · asilimia 23.6 ya mauzo ya benki
Uwiano wa kinga: 2.2 (wiki iliyotangulia 1.25) · mahali pa kuvunjika: kushuka asilimia 55 (20)
Chanzo: Benki Kuu ya Tanzania, Ripoti ya Wiki ya Masoko ya Fedha ya Ndani (12-16 Oktoba 2026); TERI/TICGL, Oktoba 2026. Kwa maelezo zaidi: economist@ticgl.com.
Tanzania Financial Markets Weekly 16 Oct 2026 | TICGL/TERI
TICGL/TERI - Weekly Markets Brief, 19 October 2026
TICGL/TERI Economy WatchWeekly Markets 12-16 Oct 2026FX, Rates & BondsFour-Week Outlook
Tanzania's Financial Markets This Week: A Steady Shilling, Heavy Liquidity Support and a 25-Year Bond That Cleared 64 bps Lower
The shilling closed the week at TZS 2,633.12 per US dollar, only 0.07% weaker, while retail foreign-exchange turnover jumped 13.3% to USD 604.89 million. The Bank of Tanzania injected TZS 892.50 billion through 7-day reverse repo, the interbank rate closed at 6.68% against a Central Bank Rate of 6.25%, and the 25-year Treasury bond No. 722 drew TZS 2,495.06 billion of bids for TZS 414.19 billion on offer. This report reads the Bank's Domestic Financial Markets Weekly Report in depth: exchange rates, interbank and retail FX, money market, government securities holders, auction results and the yield curve, then sets out what the next four weeks (to mid-November 2026) are likely to bring.
📅 Data to: 16 October 2026📍 Dar es Salaam, Tanzania🏛️ TICGL / TERI📖 Source: Bank of Tanzania, Domestic Financial Markets Weekly Report
USD/TZS, 16-Oct-26
2,633.12 +0.07% w/w
Retail FX turnover, week
USD 604.89 m +13.3%
7-day IBCM rate, close
6.68% CBR 6.25%
25-yr bond yield, 15-Oct
10.84% -64 bps
Source: Bank of Tanzania, Domestic Financial Markets Weekly Report, 12-16 October 2026; TICGL/TERI calculations. Outlook figures are TICGL scenarios, not forecasts of record.
Disclaimer & scope
Prepared by TERI for research and strategic-information purposes only. It is not investment, legal, tax or financial advice and does not state the position of the Bank of Tanzania or the Government. Historical figures are taken from the Bank of Tanzania Domestic Financial Markets Weekly Report for 12-16 October 2026; where TICGL/TERI computes a figure it is marked "TICGL calc." The four-week outlook (Tab 6) is a set of arithmetic scenarios built on that data, not a forecast of record or a trading recommendation. Currency, rate and yield levels move daily: check live data before any transaction.
00 — OverviewExecutive Summary
Three things defined the week to 16 October 2026. First, the exchange rate barely moved even though customer demand for foreign currency and supply of it both surged: retail turnover reached USD 604.89 million (+13.3%), and banks bought far more dollars from customers than they sold, a net inflow of USD 121.35 million against a net outflow of USD 63.94 million a week earlier (TICGL calc.). Second, the central bank leaned against tight liquidity: it injected TZS 892.50 billion through 7-day reverse repo, 3.5 times the previous week, and the interbank rate stayed 16 basis points above the policy rate on a weekly average. Third, the long end of the Treasury market rallied: the 25-year bond No. 722 attracted a bid-to-cover ratio of 6.02x and cleared at a weighted average yield of 10.84%, 64 basis points below the previous 25-year auction.
USD/TZS mean rate
2,633.12
from 2,631.36; shilling 0.07% weaker
Retail FX turnover
USD 604.89 m
+13.3% w/w; trade, mining, agriculture 54.3%
IBCM 7-day volume
TZS 812.65 bn
+8.6%; weekly average rate 6.41%
Govt securities outstanding
TZS 34.0 tn
bonds 89.84%; banks 34.17%
Interbank FX (IFEM)
USD 19.70 m
-11.7% w/w; four trading days
Reverse repo injected
TZS 892.50 bn
from TZS 252.43 bn; at CBR 6.25%
25-yr bond No. 722
6.02x cover
TZS 610.61 bn allotted; yield 10.84%
Registered securities clients
35,102
3,600 added in the current fiscal year
Week-on-Week Scorecard: What Moved Most?
Percent change, week to 16 Oct 2026 vs week to 9 Oct 2026. Source: BoT weekly report; TICGL calc.
Monthly Retail FX Turnover, January 2024 - October 2026
USD million, total turnover at commercial banks. October 2026 is a part month (lighter bar). Source: BoT Chart 4
Key findings
A stable shilling over a busy market. The mean rate moved from TZS 2,631.36 to TZS 2,633.12 per dollar. All nine currencies in the Bank's table gained on the shilling, from +0.02% (Rwandan franc) to +1.88% (Indian rupee), so the weakness is broad but small.
Interbank trading thinned, retail trading boomed. IFEM turnover fell 11.7% to USD 19.70 million, but only four sessions were recorded, so the daily average actually rose from USD 4.46 million to USD 4.93 million (TICGL calc.). Retail turnover grew 13.3% and equals about 31 times interbank turnover.
Commodity sectors supplied the dollars. Mining (net +USD 57.36 m) and agriculture (net +USD 52.47 m) were the largest net sellers of foreign exchange to banks; oil and energy (net -USD 49.33 m) and manufacturing (-USD 17.70 m) were the largest net buyers (TICGL calc., reading "purchases" as dollars bought by banks).
2026 is already a record year for retail FX. Turnover for January-September 2026 is USD 19.6 billion, 111.8% of the whole of 2025 (USD 17.5 billion) and 64.0% above January-September 2025 (TICGL calc. from Chart 4).
Liquidity support was large. The Bank injected TZS 892.50 billion, more than the entire week's 7-day interbank volume of TZS 812.65 billion, and the weekly interbank rate averaged 6.41% against the 6.25% CBR.
The bond investor base is institutional. Banks (34.17%) and pension funds (29.76%) hold 63.9% of the TZS 34,015.15 billion outstanding; banks took 56.25% of the 25-year allotment while brokers, with 24.4% of subscriptions, received only 1.43%.
The long end is rallying. The 25-year yield fell from 11.48% to 10.84%, leaving only 15 bps between the 10-year (10.69%) and 25-year (10.84%) auction yields, a flat long end against a 116 bps climb from 5 to 10 years.
Market access is widening. Registered securities clients reached 35,102, with 3,600 joining in the current fiscal year alone (10.3% of all clients).
Four-week outlook in one paragraph (to mid-November 2026)
Our central scenario is a shilling that keeps drifting at the latest pace of 0.07% a week, reaching about TZS 2,640 by 13 November 2026 (range TZS 2,623 to TZS 2,660), supported by mining and agricultural dollar inflows that should still be strong in the October-December export season. Interbank rates should stay in the upper half of the 4.75-7.75% corridor while reverse repo support is large, and long-dated Treasury yields have room to stay near 10.8% if demand at the 6x level persists. The 21 October Treasury bill auction is the next test. The main swing factors are oil-import dollar demand, the pace of liquidity injections, and whether the 25-year result repeats at the next long-bond auction. Scenarios and tables are in Tab 6 and the risk register in Tab 7.
Reading notes on the source data
Percentage changes in Table 1 of the Bank's report are rounded from two-decimal rates, so small currencies (Ugandan shilling, Rwandan franc) show larger percentage changes than the displayed levels imply. The Bank describes the shilling as "depreciating slightly (up 0.07%)": we treat that as a 0.07% weaker shilling. The report does not define "purchases" and "sales" in the retail FX table; TICGL reads them as dollars bought from and sold to customers by banks. Fiscal-year labels in Chart 9, numeric values for Chart 5 (retail moving average) and Chart 10 (yield curve) are not in the text of the report, so those series are summarised rather than reproduced. October 2026 monthly figures are part-month. Table 4 prints "Banks" twice (rows 1 and 6); we show both lines as printed.
01 — Shilling & Interbank FXExchange Rates, Cross Rates and the Interbank Foreign Exchange Market
The Bank of Tanzania's official indicative mean rate for the US dollar closed the week at TZS 2,633.12, compared with TZS 2,631.36 at the close of the previous week, a weekly move of TZS 1.76 or 0.07%. The weekly change is small by any standard. What is more informative is that foreign currencies rose against the shilling across the whole table, which means the shilling lost a little ground against everyone, not just against a stronger dollar.
Currency (TZS per unit)
9-Oct-26
16-Oct-26
Change (TZS)
Change (%) as reported
United States Dollar
2,631.36
2,633.12
+1.76
+0.07
British Pound Sterling
3,476.29
3,487.83
+11.54
+0.33
Euro
2,944.49
2,950.67
+6.18
+0.21
Chinese Yuan (Renminbi)
392.59
393.52
+0.93
+0.24
Indian Rupee
27.19
27.70
+0.51
+1.88
Japanese Yen
16.63
16.67
+0.04
+0.23
Kenyan Shilling
20.25
20.25
0.00
+0.03
Ugandan Shilling
0.64
0.65
+0.01
+0.93
Rwandan Franc
1.78
1.78
0.00
+0.02
Source: Bank of Tanzania, Table 1. TZS change is TICGL calc. from the published rates; percentage changes are as published (computed by the Bank on unrounded rates).
Weekly Change Against the Shilling, by Currency
Percent, 16-Oct-26 vs 9-Oct-26. Positive = the foreign currency gained on the shilling. Source: BoT Table 1
Interbank FX Turnover by Day: Two Weeks
USD million, Monday to Friday. No trade recorded on Wednesday 14 Oct. Source: BoT Charts 1 and 2
1.1 Implied cross rates: the dollar was softer, the shilling was softer still
Dividing the published TZS rates gives the cross rates among the major currencies. The euro and sterling gained about 0.14% and 0.26% against the dollar over the week, while the yen and renminbi gained about 0.17% each (dollar-yen and dollar-yuan lower). Because the shilling lost 0.07% to the dollar and the dollar itself was softer against the majors, the shilling's loss against the euro (0.21%) and sterling (0.33%) was larger than against the dollar. For importers paying in euros or sterling, the cost of foreign inputs rose faster than the headline dollar rate shows.
Implied cross rate (TICGL calc.)
9-Oct-26
16-Oct-26
Change
Reading
EUR/USD
1.1190
1.1206
+0.14%
Euro firmer
GBP/USD
1.3211
1.3246
+0.26%
Sterling firmer
USD/JPY
158.23
157.96
-0.17%
Yen firmer
USD/CNY
6.703
6.691
-0.17%
Renminbi firmer
USD/INR
96.78
95.06
-1.78%
Rupee firmer (approximate)
Source: TICGL calc. as ratios of the Bank's published TZS rates. Cross rates derived from two-decimal rates are approximate; the rupee and yen figures carry the largest rounding error.
1.2 Interbank foreign exchange market (IFEM)
IFEM transactions decreased to USD 19.70 million from USD 22.30 million. Trading was recorded on only four days in the latest week because there is no bar for Wednesday 14 October (TICGL note: 14 October is Nyerere Day, a public holiday in Tanzania). Per recorded trading day, turnover was USD 4.93 million against USD 4.46 million, so underlying activity was slightly firmer. Volume built through the week and was heaviest on Friday (USD 8.00 million), whereas in the prior week the peak came on Thursday (USD 8.30 million).
Day
Previous week
Volume (USD m)
This week
Volume (USD m)
Monday
5 Oct 2026
1.10
12 Oct 2026
3.10
Tuesday
6 Oct 2026
3.80
13 Oct 2026
3.60
Wednesday
7 Oct 2026
4.00
14 Oct 2026
no trade shown
Thursday
8 Oct 2026
8.30
15 Oct 2026
5.00
Friday
9 Oct 2026
5.10
16 Oct 2026
8.00
Week total
22.30
19.70
Source: BoT Charts 1 and 2; totals as published in the text of the report.
Monthly Interbank FX Turnover, January 2024 - October 2026
USD million. October 2026 is a part month (lighter bar). Source: BoT Chart 3
Source: TICGL calc. from BoT Chart 3 monthly values. October 2026 (USD 50.9 million, part month) is excluded from the Jan-Sep comparison.
TICGL/TERI reading
The interbank market is a thin layer on top of a large retail market: this week it was 3.3% of retail turnover (4.2% a week earlier), and in 2026 it has ranged from 3.5% (April) to 10.6% (February) of monthly retail turnover. Interbank turnover for January-September 2026 (USD 1.37 billion) already exceeds all of 2025 (USD 1.18 billion) by 15.8%, so depth is improving, but volumes of USD 4-8 million a day are small enough that a single large order can move the price. That is why the stability of the rate this week, in a market where retail flows swung by USD 185 million from net outflow to net inflow, is a signal about central-bank and bank balance-sheet management as much as about market equilibrium.
02 — Retail FX by SectorWho Buys and Who Sells the Dollars? Retail Foreign Exchange at Commercial Banks
Retail foreign-exchange transactions rose to USD 604.89 million from USD 533.81 million, an increase of USD 71.08 million or 13.3%. Trade (USD 181.28 million), mining (USD 74.18 million) and agriculture (USD 73.01 million) contributed the most, together USD 328.47 million or 54.3% of turnover. Over the past month, daily retail transactions averaged USD 124.06 million, with sales averaging USD 61.74 million and purchases USD 62.31 million, a balanced picture over a month that hides this week's large swing in net flows.
Sector (USD million)
Previous week (5-9 Oct)
This week (12-16 Oct)
Turnover change
Purchases
Sales
Total
Purchases
Sales
Total
Trade
44.30
130.40
174.70
97.56
83.72
181.28
+3.8%
Mining
50.82
8.49
59.31
65.77
8.41
74.18
+25.1%
Agriculture
38.64
7.98
46.62
62.74
10.27
73.01
+56.6%
Oil & Energy
7.81
66.37
74.18
7.73
57.06
64.78
-12.7%
Individual Retail Customers
20.31
20.76
41.07
25.38
15.84
41.22
+0.4%
Constructions (Machine & Equipment)
10.41
10.73
21.14
19.44
19.73
39.17
+85.3%
Manufacturing
4.79
30.90
35.69
10.29
27.99
38.28
+7.3%
Transport & Communication
24.08
10.87
34.94
29.80
6.03
35.84
+2.6%
Tourism
20.90
3.22
24.12
24.81
2.07
26.88
+11.4%
Social Services
6.08
4.12
10.20
10.44
5.31
15.75
+54.4%
NGOs
6.79
0.34
7.13
9.05
2.37
11.42
+60.2%
Breweries / Beverages
0.00
4.70
4.70
0.13
2.96
3.09
-34.3%
Total
234.93
298.87
533.81
363.12
241.77
604.89
+13.3%
Source: Bank of Tanzania, Table 2; turnover change is TICGL calc. Published totals are used; sector rows differ from totals by up to USD 0.02 million through rounding.
Total Turnover by Sector: Two Weeks
USD million. Source: BoT Table 2
Net Flow by Sector: Purchases Minus Sales
USD million. Positive = banks bought more dollars than they sold (TICGL calc.)
2.1 The swing from net outflow to net inflow
Total purchases rose 54.6% to USD 363.12 million while total sales fell 19.1% to USD 241.77 million. On TICGL's reading (purchases are dollars bought by banks from customers), the banking system moved from a net sale of USD 63.94 million to a net purchase of USD 121.35 million, a swing of USD 185.29 million in a single week. Three sectors explain most of it: trade, where net flow went from -USD 86.10 million to +USD 13.84 million as purchases more than doubled (+120.2%) and sales fell 35.8%; mining, up USD 15.03 million to a net +USD 57.36 million; and agriculture, up USD 21.81 million to a net +USD 52.47 million, with purchases up 62.4%.
Purchases, Sales and Total: Two Weeks
USD million, all sectors. Source: BoT Table 2
Turnover Growth by Sector, This Week
Percent change vs previous week (TICGL calc.)
Sector Share of Turnover, This Week
Percent of USD 604.89 million (TICGL calc.)
Retail Turnover: Year-on-Year Growth, 2026
Percent, each month of 2026 vs the same month of 2025 (TICGL calc. from BoT Chart 4)
2.2 A record year in the making
Monthly retail turnover rose from USD 740 million in January 2024 to USD 2,822 million in September 2026, the highest month on record in the chart. January-September 2026 turnover totals USD 19,575 million: 111.8% of the full-year 2025 total of USD 17,504 million and 64.0% above January-September 2025 (USD 11,935 million). Growth peaked in February 2026 (+109.0% year on year) and was lowest in May (+39.5%), but has stayed above +46% in every month since, with September at +62.3%.
Retail FX turnover (USD m)
2024
2025
Jan-Sep 2024
Jan-Sep 2025
Jan-Sep 2026
Total turnover
10,931
17,504
6,340
11,935
19,575
Growth y/y
n.a.
+60.1%
n.a.
+88.2%
+64.0%
Source: TICGL calc. from the monthly values in BoT Chart 4 (labels read from the chart). October 2026 (USD 1,385 million, part month) is excluded.
Retail Turnover Cumulative: January-September by Year vs Full Year
USD million. Source: BoT Chart 4; TICGL calc.
TICGL/TERI reading
Sector flows tell a consistent export-and-import story. Dollar supply comes from mining, agriculture, tourism and transport (net inflows in each), while the main users are oil and energy (net -USD 49.33 million, even after a 12.7% fall in turnover), manufacturing (-USD 17.70 million) and breweries (-USD 2.83 million). Oil and energy remains the largest structural buyer of dollars, so fuel-price and import-bill developments (see the zonal report for the pump-price shock earlier in 2026) are the first thing to watch if net inflows fade. For investors and lenders with dollar costs or dollar revenues, the sector table is a ready-made map of who is on which side of the market.
The 7-day Interbank Cash Market (IBCM) weighted average rate (WAR) closed the week at 6.68%, down from 6.75% at the close of the previous week. Total 7-day trading volume increased to TZS 812.65 billion from TZS 748.35 billion (+8.6%). The 7-day weekly WAR averaged 6.41%, within the Central Bank Rate (CBR) corridor of 4.75% to 7.75%, and 16 basis points above the CBR of 6.25%, which the Bank describes as consistent with its policy stance.
Closing WAR
6.68%
from 6.75%; 43 bps above CBR
Weekly average WAR
6.41%
+16 bps vs CBR 6.25%
Reverse repo injected
TZS 892.50 bn
3.5x the TZS 252.43 bn of last week
Corridor headroom
107 bps
close is 107 bps below the 7.75% ceiling
IBCM This Week: Volume and Rate by Day
TZS billion (bars) and weighted average rate, % (line). No trading shown for 14 Oct. Source: BoT Chart 7
IBCM Previous Week: Volume and Rate by Day
TZS billion (bars) and weighted average rate, % (line). Source: BoT Chart 6
Session
Volume (TZS bn)
WAR (%)
Spread to CBR (bps)
Mon 5 Oct
153.1
6.49
+24
Tue 6 Oct
60.5
6.55
+30
Wed 7 Oct
1.0
6.05
-20
Thu 8 Oct
242.5
6.35
+10
Fri 9 Oct
291.3
6.75
+50
Mon 12 Oct
160.1
6.12
-13
Tue 13 Oct
219.0
6.46
+21
Thu 15 Oct
194.5
6.44
+19
Fri 16 Oct
239.1
6.68
+43
Totals: previous week / this week
748.4 / 812.7
6.75 / 6.68 close
Source: Bank of Tanzania, Charts 6 and 7 (daily values read from the chart labels; weekly totals as published in the text: TZS 748.35 bn and TZS 812.65 bn). Spread to CBR is TICGL calc.
Daily IBCM Rate Against the CBR Corridor
Percent. Nine sessions, 5-16 Oct 2026; floor 4.75%, CBR 6.25%, ceiling 7.75% (TICGL chart of BoT data)
Reverse Repo Injection vs IBCM Volume
TZS billion, two weeks. Source: BoT section 2 and Chart 8
3.1 7-day reverse repo: the Bank's operating-target tool
During the week the Bank conducted 7-day reverse repo through main operations at the CBR of 6.25%, injecting TZS 892.50 billion to steer the operating target towards the policy rate, against TZS 252.43 billion in the preceding week. The 24-auction history in Chart 8 shows how unusual the recent run is: the early auctions were TZS 75-110 billion each, injections then rose into the TZS 190-1,061 billion range, and the latest TZS 892.50 billion is 2.2 times the 24-auction average of TZS 403 billion (TICGL calc.) and the third-highest in the series after TZS 1,061.3 billion and TZS 893.0 billion.
7-Day Reverse Repo Injections, Last 24 Main Operations
TZS billion, oldest to latest (auction dates are not in the text of the report). Source: BoT Chart 8
Measure
Previous week
This week
Change
IBCM 7-day volume (TZS bn)
748.35
812.65
+8.6%
IBCM closing WAR (%)
6.75
6.68
-7 bps
Reverse repo injected (TZS bn)
252.43
892.50
+253.6%
Injection / IBCM volume
0.34x
1.10x
+0.76x
Operation rate
CBR 6.25%
CBR 6.25%
unchanged
Source: Bank of Tanzania, section 2; ratios are TICGL calc.
TICGL/TERI reading
Rates are behaving, but liquidity is being actively managed. The weekly average of 6.41% sits 16 bps above the CBR, and daily rates ranged from 6.05% to 6.75% in a thin market (volume was only TZS 1.0 billion on 7 October). When the central bank injects more than the interbank market trades, as it did this week (1.10x), banks are leaning on the central bank for funding, which usually follows tax-payment dates, bond settlements and large retail FX transactions that absorb shilling liquidity. For borrowers it means short-term funding costs are anchored near 6.4-6.7% rather than at the 7.75% ceiling, but it also means lending and bond-pricing assumptions should allow for a funding rate that is 15-45 bps above the policy rate.
04 — Government SecuritiesWho Holds Tanzania's Treasury Bills and Bonds?
Outstanding government securities stand at TZS 34,015.15 billion. Treasury bonds make up TZS 30,560.85 billion (89.84%) and Treasury bills TZS 3,454.30 billion (10.16%), so the stock is dominated by long-dated paper. Banks (34.17%), pension funds (29.76%) and retail investors (17.92%) hold the largest shares.
Investor category
Face value (TZS bn)
Share (%)
Comment (TICGL)
Banks
11,622.51
34.17
Largest holder; also 56.25% of the latest 25-year allotment
Pension Funds
10,121.28
29.76
Long-dated, buy-and-hold demand
Retail Investors
6,094.25
17.92
Largest non-institutional share; 35,102 registered clients
CIS and Other Official Entities
2,715.64
7.98
Collective schemes and official bodies
Insurance Companies
2,484.06
7.30
Liability-matching demand
Others
977.42
2.87
Residual
Total
34,015.15
100.00
Source: Bank of Tanzania, Table 3; comments are TICGL/TERI readings. Banks plus pension funds hold 63.93% (TZS 21,743.79 billion, TICGL calc.).
4.1 Registered clients: a fast-widening retail base
In the current fiscal year, 3,600 new clients have been onboarded, taking total registered clients to 35,102. Annual additions climbed from 153 in the earliest year shown to a peak of 9,899 in the second-latest fiscal year, and the 3,600 recorded so far in the current year (the fiscal year began in July) is 36% of that peak after roughly three and a half months. If that pace held for the rest of the year, additions would be well above the previous peak (TICGL calc., illustrative only). Retail investors already hold 17.92% of outstanding securities, so the client base is large enough to matter at the margin for auction demand.
New Registered Clients by Fiscal Year
Number of clients onboarded. Fiscal-year labels are shown relative to the current year because the report's text does not print them. Source: BoT Chart 9
Cumulative Registered Clients
Running total, ending at 35,102 (TICGL calc. from BoT Chart 9)
TICGL/TERI reading
The investor base is institutional at the core and retail at the margin. Banks and pension funds hold nearly two thirds of the stock, so auction outcomes depend on a few large balance sheets; a rising retail client count (+3,600 this fiscal year) adds a second source of demand for the same paper. The 89.84% bond share also means refinancing risk is spread over long maturities, which is good for debt management but means the bill market is small (TZS 3.45 trillion) and a single large bill auction can move short rates.
05 — Auctions & Yield CurveThe 25-Year Bond No. 722 and Recent Treasury Bond Auctions
The 25-year Treasury bond No. 722 (12.75%, issue 19, redeeming 16 October 2051), auctioned on 15 October 2026, attracted 2,547 bids, of which 1,673 were successful. The amount tendered was TZS 2,495.06 billion against TZS 414.19 billion offered, an oversubscription of TZS 2,080.87 billion. The Bank allotted TZS 610.61 billion, 47% more than the amount offered. The minimum successful price was 115.5000 and the weighted average price 116.3067, giving a weighted average yield to maturity of 10.8422%, against 11.4799% at the previous 25-year auction.
Bid-to-cover
6.02x
highest of the six auctions in Table 5
Allotted
TZS 610.61 bn
147% of the TZS 414.19 bn offered
Weighted avg yield
10.84%
11.48% at previous 25-year auction (-64 bps)
Successful bids
1,673 of 2,547
65.7% of bids; 24.5% of value tendered
5.1 Recent Treasury bond auctions: the full table
Measure
5-yr No. 700 (2)
10-yr No. 711 (2)
15-yr No. 696 (2)
15-yr No. 696 (3)
25-yr No. 695 (3)
25-yr No. 722
Coupon
10.25%
11.25%
12.25%
12.25%
13.25%
12.75%
Redemption date
30-Apr-31
23-Jul-36
19-Feb-41
19-Feb-41
05-Feb-51
16-Oct-51
Bids received
100
165
396
312
2,681
2,547
Successful bids
75
87
235
208
1,671
1,673
Highest bid /100
105.0000
109.0000
117.0314
113.5568
118.8041
118.8765
Lowest bid /100
90.6441
83.3963
86.5544
90.6655
88.6694
85.4033
Minimum successful price /100
100.1576
101.4576
109.2189
109.6647
113.7770
115.5000
Weighted average price (WAP)
102.6275
103.3267
112.4713
110.5120
114.4173
116.3067
Weighted average yield to maturity
9.53%
10.69%
10.55%
10.79%
11.48%
10.84%
Weighted average coupon yield
9.99%
10.89%
10.89%
11.08%
11.58%
10.96%
Amount offered (TZS bn)
145.63
182.90
207.27
207.27
414.19
414.19
Total tendered (TZS bn)
398.06
364.96
689.45
504.13
1,446.83
2,495.06
Oversubscription (TZS bn)
252.43
182.06
482.18
296.86
1,032.64
2,080.87
Successful bids (TZS bn)
143.57
149.60
181.19
196.51
414.20
610.61
Bid-to-cover ratio
2.73x
2.00x
3.33x
2.43x
3.49x
6.02x
Coupon dates
30/10, 30/04
23/01, 23/07
19/02, 19/08
19/02, 19/08
05/08, 05/02
16/04, 16/10
Accrued interest (TZS)
3.9315
1.2945
0.0336
1.4432
0.0363
0.0000
Source: Bank of Tanzania, Table 5. The Bank prints under/oversubscription as negative numbers; we show the absolute oversubscription. Bonds are re-opened across auctions: "(2)" and "(3)" are the second and third issue of the same bond number, as printed.
Weighted Average Yield vs Coupon Yield by Auction
Percent. Source: BoT Table 5
Auction-Implied Yield Curve: Yield by Years to Maturity
Weighted average yield (%) against years from 16-Oct-26 to redemption, one point per auction (TICGL chart of BoT Table 5; the Bank's own curve in Chart 10 is not reproduced numerically in the report text)
5.2 The shape of the curve
The auction results trace a curve that rises steeply and then flattens. From the 5-year bond (9.53%, about 4.5 years to maturity) to the 10-year (10.69%, about 9.8 years) yields rise 116 basis points. Beyond 10 years the curve is nearly flat: the 15-year results were 10.55% and 10.79% across two re-openings and the new 25-year cleared at 10.84%, only 15 bps above the 10-year. The earlier 25-year bond No. 695 had priced at 11.48%, so the new 25-year auction moved the long end down by about 64 bps. The 15-year bond moved the other way between its two re-openings (10.55% to 10.79%, +24 bps), so the rally was not uniform, and the Bank's two yield-curve lines (9 October and 16 October in Chart 10) should be read for the weekly shift.
Bid-to-Cover Ratio by Auction
Times covered. Source: BoT Table 5
Offered, Tendered and Successful Amounts
TZS billion. Source: BoT Table 5
Bids Received vs Successful Bids
Number of bids. Source: BoT Table 5
Price Range Across Each Auction
Price per 100: highest bid, weighted average, minimum successful and lowest bid. Source: BoT Table 5
5.3 Who bid and who won at the 25-year auction?
Banks accounted for 27.51% of subscriptions and were allotted TZS 343.50 billion (56.25%). Individuals and companies accounted for 25.42% of subscriptions and were allotted TZS 191.30 billion (31.33%). Brokers accounted for 24.4% of subscriptions and were allotted only TZS 8.72 billion (1.43%). Collective investment schemes bid for 15.34% and received nothing. Pension funds subscribed 4.32% and were allotted 0.64%.
Investor category
Subscription (%)
Allotment (%)
Allotment / subscription
Allotted (TZS bn)
Banks
27.51
56.25
2.04x
343.50
Individuals and Companies
25.42
31.33
1.23x
191.30
Brokers
24.40
1.43
0.06x
8.72
Collective Investment Schemes
15.34
-
0.00x
0.00
Pension Funds
4.32
0.64
0.15x
3.91
Banks (second line, as printed)
2.20
6.53
2.97x
39.87
Others
0.80
3.81
4.76x
23.26
Total
100.00
100.00
1.00x
610.61
Source: Bank of Tanzania, Table 4. Allotted amounts for banks, individuals and companies and brokers are as published; the other rows are TICGL calc. (allotment share x TZS 610.61 billion). Ratios of allotment to subscription above 1.0x mean the group won more than its share of bids.
Subscription vs Allotment by Investor Category, 25-Year Bond No. 722
Percent of total. Source: BoT Table 4
TICGL/TERI reading
A 6.02x bid-to-cover on a TZS 414 billion offer is exceptional by the standards of the table: the previous best was 3.49x (the earlier 25-year bond), and the 10-year bond covered only 2.00x. The Bank's response was to allot 147% of the amount offered and let the yield fall 64 bps, which tells investors that it values long-term funding at lower yields when demand is deep. The spread between bids and results is wide, with the lowest bid at 85.40 against a minimum successful price of 115.50, so most of the 2,547 bids (including a large share of the brokers' subscriptions) were at prices far below where the auction cleared. The 25-year result is a good benchmark for long-tenor, shilling-denominated funding of infrastructure and PPP projects: a 10.84% base yield, with the question being whether a 6x covered auction can be repeated.
The next Government Securities auction is scheduled for Wednesday, 21 October 2026, when Treasury bills will be offered in line with the issuance calendar (details in the auction prospectus).
06 — Four-Week OutlookWhat Happens Next? 19 October - 13 November 2026
This tab turns the 16 October data into scenarios for the next four weeks (and, for the exchange rate, eight weeks to 11 December 2026). The latest hard data end on 16 October, so each scenario starts from that base and runs on simple, transparent rules that anyone can reproduce from the tables in Tabs 1-5. They are scenarios, not forecasts of record, and should be checked against the Bank of Tanzania's daily and weekly releases as they appear.
6.1 Exchange rate: four weekly-drift scenarios
We project the 16 October mean rate (TZS 2,633.12 per dollar) forward at four constant weekly rates of change. Steady (0.00% a week) holds the rate flat. Base (+0.07% a week) repeats the weekly move just observed. Faster depreciation (+0.25% a week) is a stress case about 3.6 times the latest pace, roughly 1% by mid-November. Appreciation (-0.10% a week) assumes inflows from the export season outweigh dollar demand.
USD/TZS Scenario Paths, 16 October - 11 December 2026
TZS per US dollar, weekly points. 16 Oct = actual. TICGL scenario arithmetic (constant weekly drift), not a forecast
Scenario
Weekly drift
13 Nov 2026
Change vs 16 Oct
11 Dec 2026
Change vs 16 Oct
Cost of USD 10m at 13 Nov (TZS m)
Appreciation
-0.10%
2,622.60
-10.52 (-0.40%)
2,612.13
-20.99 (-0.80%)
26,226.0
Steady
0.00%
2,633.12
0.00
2,633.12
0.00
26,331.2
Base (latest pace)
+0.07%
2,640.50
+7.38 (+0.28%)
2,647.89
+14.77 (+0.56%)
26,405.0
Faster depreciation
+0.25%
2,659.56
+26.44 (+1.00%)
2,686.29
+53.17 (+2.02%)
26,595.6
Source: TICGL calc. from BoT Table 1; compounding weekly from TZS 2,633.12 on 16 October 2026. The last column is a worked example for a project with USD 10 million of dollar-priced cost.
6.2 Money market and bonds: what to watch
Interbank rate. With the weekly average at 6.41% and the close at 6.68%, the base case is a range of about 6.2-6.8% while injections stay large. A move above 7.0% would signal tightening liquidity within 75 bps of the ceiling; a move back towards 6.25% would signal that the injections have worked.
Reverse repo. The latest TZS 892.50 billion is 2.2 times the 24-auction average. If injections drift back towards TZS 250-400 billion, liquidity is easing; if they stay near TZS 900 billion or above, funding pressure is persisting.
Treasury bill auction, 21 October. The first bill auction after the long-bond rally shows whether short yields follow the 64 bps move at the long end.
Long bonds. A repeat of 6x cover would keep the 25-year near 10.8%; cover of 2-3x, the norm in the other five auctions, would imply yields back near 11.0-11.5% (the previous 25-year auction was 11.48%).
Retail FX. Weekly turnover of USD 605 million equals about USD 2.6 billion a month, a little below September's USD 2,822 million; October to date is already USD 1,385 million (part month).
6.3 Four-week outlook matrix
Indicator
Latest (BoT report)
Four-week view (TICGL scenarios)
Swing factor
Direction
USD/TZS
2,633.12 (+0.07% w/w)
About 2,640 by 13 Nov (base); range 2,623-2,660
Oil-import demand; export-season inflows
Stable, mild weakening
Interbank FX
USD 19.70 m; four sessions
USD 4-8 m a day continues; weekly total USD 20-30 m
Bank positioning; public holidays
Stable
Retail FX turnover
USD 604.89 m (+13.3%)
USD 550-650 m a week; Q4 monthly total near USD 2.4-2.8 bn
Trade and commodity flows
High, steady
Net FX position
Net purchases USD 121.35 m
Net purchases in mining and agriculture continue; trade nets near zero
Oil and manufacturing imports
Inflow bias
IBCM 7-day rate
6.68% close; 6.41% average
About 6.2-6.8%, upper half of corridor
Liquidity injections; tax dates
Stable, firm
Reverse repo
TZS 892.50 bn
TZS 300-900 bn per week depending on liquidity
Banks' funding needs
Elevated
T-bill yields
Auction 21 Oct
Direction depends on the 21 Oct result
Bill supply; liquidity
To be tested
Long-bond yields
25-yr 10.84% (-64 bps)
10.6-11.2% if cover stays above 3x
Bank and pension demand
Firm to lower
Securities investor base
35,102 clients; +3,600 this FY
Continued onboarding
Retail participation
Up
Source: TICGL/TERI synthesis of Tabs 1-5; ranges are analytical judgements around the scenario arithmetic, not model outputs.
Bottom line
The most likely four weeks combine heavy but stable foreign-exchange activity, an interbank rate that stays comfortably inside the corridor, and long-dated bond demand deep enough to keep yields near 10.8%. The biggest downside risk for the shilling is a sudden rise in oil and import demand; the biggest upside for yields is a repeat of the 25-year auction.
07 — Risks & PolicyWhat Could Go Wrong and What To Do About It
The week's data show a market that is liquid and calm on the surface and concentrated underneath. A small number of sectors supply the dollars, a small number of sectors use them, banks and pension funds hold two thirds of Treasury paper, and the central bank is carrying a lot of the short-term funding load.
Concentration Map: How Much Rides on a Few Players?
Percent share, week to 16 Oct 2026 (BoT report tables; TICGL selection)
7.1 Risk register
Risk
Evidence in the BoT report
Likelihood (next 4 weeks)
Impact
Most exposed
Dollar demand from oil and imports
Oil and energy net -USD 49.33 m a week; manufacturing -USD 17.70 m
Medium
High
Importers; the shilling; fuel and food prices
Reversal of commodity inflows
Mining +USD 57.36 m and agriculture +USD 52.47 m net inflow; net position swung USD 185 m in one week
Medium
High
Exchange-rate stability; exporters
Thin interbank market
IFEM USD 19.70 m in four sessions; USD 4-8 m a day; 3.3% of retail turnover
Medium
Medium
Price discovery; large single-order impact
Short-term liquidity tightness
Reverse repo TZS 892.50 bn vs IBCM TZS 812.65 bn; weekly WAR 16 bps above CBR
Medium
Medium
Banks; short-term borrowers
Demand concentration in bonds
Banks 34.17% + pension funds 29.76% of holdings; banks 56.25% of 25-yr allotment
Low
Medium
Auction outcomes; yields
One-off auction demand
6.02x cover vs 2.00-3.49x in other five auctions
Medium
Medium
Future long-bond pricing
Uneven curve moves
15-yr yield 10.55% to 10.79% while 25-yr fell 64 bps
Source: TICGL/TERI analysis. Likelihood and impact ratings are analytical judgements (Low/Medium/High), not model outputs.
Upward pressures (rates, exchange rate)
Downward pressures (relief)
Oil and energy remains the largest net buyer of dollars
Mining and agriculture net inflows of about USD 110 m a week
Interbank rate above the CBR; heavy reliance on reverse repo
Weekly average rate only 16 bps above CBR; 107 bps below the ceiling
Faster depreciation in non-USD currencies (INR, UGX, sterling)
Dollar softer against the majors, limiting broad pressure on the shilling
Concentrated bond ownership
Retail client base expanding (+3,600 this fiscal year)
Possible reversal of the 25-year yield rally
Deep demand at the long end (6.02x cover)
7.2 Policy instruments
Next four weeks
FX policy. Keep publishing daily mean rates and weekly flow data; track net sector flows, since the net position swung by USD 185 million in a week.
Liquidity policy. Calibrate reverse repo size to IBCM volume (1.10x this week) so injections steer the rate to the CBR without crowding out interbank trade.
Auction policy. Use the 21 October bill auction to test whether short yields follow the long end.
Communication. Explain the gap between the weekly average rate (6.41%) and the CBR (6.25%).
Medium term (1-3 years)
Market depth. Raise interbank FX volumes beyond the current USD 4-8 million a day by widening the participant base.
Debt management. Build the Treasury bill stock (10.16% of outstanding) to give a deeper short-end benchmark.
Hedging. Develop FX hedging products for the sectors with persistent net dollar needs.
Longer term (to 2030)
Capital market. Use the 25-year benchmark to build a corporate and infrastructure bond curve.
Data. Publish yield-curve values, retail FX moving-average data and fiscal-year labels with the weekly report.
Resilience. Diversify dollar inflows beyond gold and a few crops.
PPP funding. Link long-dated shilling bonds to bankable PPP project financing.
"A calm exchange rate can hide large flows. The question for the next four weeks is whether the dollars that arrived this week keep arriving, and whether the long-bond demand seen at the 25-year auction repeats."
— TICGL / Tanzania Economic Research Institute (TERI)
Conclusion
Tanzania's week to 16 October 2026 shows a shilling at TZS 2,633.12, retail FX turnover of USD 604.89 million, an interbank rate of 6.68% and a 25-year bond yield of 10.84% after a 6.02x-covered auction. For the next four weeks the central scenario is a stable-to-slightly-weaker shilling (about TZS 2,640 by 13 November), money-market rates inside the corridor, and firm long-bond demand. The policy priority is to keep liquidity support and FX flow monitoring ahead of any shift in oil-import demand, and to deepen the interbank and bill markets.
08 — What TICGL DoesFrom Weekly Market Data to Bankable Projects
TICGL (Tanzania Investment and Consultant Group Ltd), with its research arm TERI, turns market data of this kind into decision-grade work for investors, lenders and government: feasibility studies, market-entry advisory, and market research and economic intelligence. This tab shows how the figures in this report become inputs to a financial model or a market study. It does not recommend any investment.
Data point in this report
Value
Where it enters a TICGL deliverable
USD/TZS mean rate
2,633.12
Feasibility study: base exchange rate and depreciation path for dollar-priced capex, equipment and debt service
Weekly drift scenarios
-0.10% to +0.25%
Financial model: FX sensitivity cases on NPV, IRR and DSCR
5-year Treasury yield (auction)
9.53%
Discount-rate build-up for short-life assets: risk-free benchmark
10-year Treasury yield (auction)
10.69%
WACC: risk-free rate for mid-life projects (10-year concessions, plants)
25-year Treasury yield (auction)
10.84%
PPP and infrastructure: long-tenor risk-free rate and domestic bond-funding benchmark
Central Bank Rate and 7-day interbank rate
6.25% / 6.68%
Floating-rate loan pricing and working-capital cost in the model
Retail FX by sector
USD 604.89 m
Market research: sector demand, import and export intensity, hedging needs
Source: TICGL/TERI mapping of BoT weekly data to deliverables; indicative only.
8.1 Worked example: what a four-week FX move does to a dollar-priced budget
A project with USD 10 million of imported equipment costs TZS 26,331 million at the 16 October rate. Under the four scenarios on 13 November the same equipment costs TZS 26,226 million (appreciation), 26,331 million (steady), 26,405 million (base) or 26,596 million (faster depreciation): a spread of TZS 370 million between the best and worst cases in four weeks. A feasibility study turns this into a contingency line, a hedging recommendation and a financing-currency choice (shilling against dollar debt), tested against the sovereign yield levels above.
Feasibility studies
Pre-feasibility and full feasibility across market, technical, financial, institutional, legal and risk components, with PPP structuring for public projects.
Financial models with NPV, IRR and DSCR, stress-tested for exchange-rate, interest-rate and input-cost shocks of the kind shown in Tabs 1, 3 and 6.
Funding-structure analysis against the Treasury curve (5, 10, 15 and 25-year yields) and investor-base data.
Market entry advisory
Sector and market screening, then entry-mode choice: import and distribution, contract partner, joint venture or own plant.
Currency and funding strategy for market entry: dollar costs, shilling revenues and hedging.
Incentives, licensing and site mapping; partner and supplier identification; business facilitation from first meeting to registration and start-up.
Market research and economic intelligence
Demand sizing, price benchmarking and competitor mapping by sector.
Scenario models updated with each Bank of Tanzania release, as in the four-week outlook in Tab 6.
Policy briefs and SEO-ready research publications for institutional clients through TERI.
Why this matters to investors and lenders
The same headline shilling rate can mean very different project economics depending on who holds the dollar risk: an importer in oil and energy sits on the buying side, a miner or farmer on the supplying side, and a PPP sponsor funding with long shilling bonds faces a 10.84% benchmark rather than a policy rate of 6.25%. A short market study and a stress-tested financial model are the low-cost way to avoid using a headline rate for a project-level decision.
Talk to TICGL/TERI
Request a feasibility, market-entry or market-research scoping call, or a briefing on this report and the four-week outlook.
Source report. Bank of Tanzania, Domestic Financial Markets Weekly Report, 12-OCT-2026 to 16-OCT-2026 (Tables 1-5 and Charts 1-10): exchange rates, Interbank Foreign Exchange Market, retail foreign exchange, 7-day Interbank Cash Market, reverse repo, government securities holdings, registered clients, auction results and sovereign yield curve. TICGL calculations. Week-on-week growth rates; shares; implied cross rates (ratios of published TZS rates); net foreign-exchange flows (purchases minus sales); January-September cumulative and year-on-year growth from monthly chart labels; interbank share of retail turnover; spreads to the CBR; allotment-to-subscription ratios; cumulative registered clients; years to maturity for the auction-implied curve. Outlook scenarios. Exchange rate: 16 October mean rate compounded weekly at -0.10%, 0.00%, +0.07% and +0.25%; reverse-repo and interbank ranges: analytical judgement around the observed ranges. Limitations. Daily values in the IBCM and IFEM charts and monthly values in Charts 3 and 4 are read from chart labels; Chart 5 (retail moving average) and Chart 10 (yield curve) have no numeric values in the report text; "purchases" and "sales" in Table 2 are not defined by the Bank; Table 4 prints "Banks" twice; the year labels of Chart 9 are not printed, so fiscal years are labelled relative to the current year; October 2026 monthly values are part-month.
Bank of Tanzania, Domestic Financial Markets Weekly Report, 12-16 October 2026, Dar es Salaam, 2026.
Bank of Tanzania Central Bank Rate (6.25%) and 4.75-7.75% corridor, as stated in the report.
TICGL/TERI, Tanzania Zonal Economic Performance 2025/26 and Six-Month Outlook (for the pump-price and inflation context).
10 - Quick AnswersFrequently Asked Questions
What was the USD/TZS exchange rate in the week to 16 October 2026?
The Bank of Tanzania mean rate closed at TZS 2,633.12 per US dollar on 16 October 2026, from TZS 2,631.36 a week earlier, a 0.07% weakening of the shilling. All nine tracked currencies rose against the shilling, with the Indian rupee up 1.88%, the Ugandan shilling up 0.93% and sterling up 0.33%.
How active were Tanzania's foreign exchange markets?
Interbank FX turnover fell to USD 19.70 million from USD 22.30 million, but retail turnover at commercial banks rose 13.3% to USD 604.89 million. Trade (USD 181.28 million), mining (USD 74.18 million) and agriculture (USD 73.01 million) were the largest sectors, together 54.3% of turnover.
What is the interbank cash market rate versus the Central Bank Rate?
The 7-day interbank cash market weighted average rate closed at 6.68% (from 6.75%) and averaged 6.41% for the week, 16 basis points above the Central Bank Rate of 6.25% and inside the 4.75% to 7.75% corridor. Volume rose to TZS 812.65 billion, and the Bank injected TZS 892.50 billion through 7-day reverse repo.
How much government debt is outstanding and who holds it?
Outstanding government securities are TZS 34,015.15 billion: Treasury bonds TZS 30,560.85 billion (89.84%) and Treasury bills TZS 3,454.30 billion (10.16%). Banks hold 34.17%, pension funds 29.76% and retail investors 17.92%. Registered clients total 35,102, including 3,600 added in the current fiscal year.
What happened at the 25-year Treasury bond auction on 15 October 2026?
Bond No. 722 attracted 2,547 bids and TZS 2,495.06 billion against TZS 414.19 billion offered (bid-to-cover 6.02x). The Bank allotted TZS 610.61 billion at a weighted average yield of 10.84%, down from 11.48% at the previous 25-year auction. Banks took 56.25% of the allotment.
What is the four-week outlook for the shilling and interest rates?
TICGL/TERI scenarios keep the shilling near TZS 2,640 per dollar by 13 November 2026 if the latest weekly drift of 0.07% continues, with a range of TZS 2,623 to 2,660. Interbank rates should stay in the upper half of the 4.75-7.75% corridor while reverse repo support is large, and the 21 October Treasury bill auction is the next test of yields.
11 - Explore MoreTICGL Economic: Related Insights & Tools
Related Analysis
Tanzania's Economy by Zone, 2025/26 and the Six-Month Outlook
The zonal data behind the pump-price shock, inflation and credit picture.
Masoko ya fedha ya Tanzania, wiki ya 12-16 Oktoba 2026. Kwa mujibu wa Ripoti ya Wiki ya Masoko ya Fedha ya Ndani ya Benki Kuu ya Tanzania (BoT), shilingi ilifunga wiki kwa TZS 2,633.12 kwa dola moja ya Marekani, kutoka TZS 2,631.36 wiki iliyotangulia, yaani kushuka kwa asilimia 0.07 tu. Sarafu zote tisa zilizoorodheshwa zilipanda dhidi ya shilingi, kuanzia asilimia 0.02 (faranga ya Rwanda) hadi asilimia 1.88 (rupia ya India).
Soko la fedha za kigeni: Mauzo katika soko la benki kwa benki (IFEM) yalishuka hadi dola milioni 19.70 kutoka milioni 22.30 (asilimia 11.7), lakini siku za biashara zilikuwa nne tu. Soko la rejareja kwenye benki za biashara lilipanda asilimia 13.3 hadi dola milioni 604.89. Biashara (milioni 181.28), madini (milioni 74.18) na kilimo (milioni 73.01) vilichangia asilimia 54.3. Benki zilinunua dola nyingi kuliko zilizouza: ziada ya dola milioni 121.35, ikilinganishwa na upungufu wa milioni 63.94 wiki iliyotangulia. Mwaka 2026 tayari ni wa rekodi: Januari-Septemba ni dola bilioni 19.6, zaidi ya mwaka mzima wa 2025 (bilioni 17.5).
Soko la fedha (money market): Kiwango cha wastani cha siku 7 katika soko la fedha la benki (IBCM) kilifunga kwa asilimia 6.68 (kutoka 6.75), na wastani wa wiki ulikuwa asilimia 6.41, juu ya Kiwango cha Benki Kuu (CBR) cha asilimia 6.25 kwa pointi 16 za msingi, ndani ya ukanda wa asilimia 4.75 hadi 7.75. Kiasi kilifikia TZS bilioni 812.65. BoT ilitoa fedha TZS bilioni 892.50 kupitia reverse repo ya siku 7, mara 3.5 ya wiki iliyotangulia (bilioni 252.43).
Dhamana za serikali: Dhamana zilizobaki ni TZS bilioni 34,015.15: hatifungani asilimia 89.84 na hati fungani za muda mfupi (bills) asilimia 10.16. Benki zinashikilia asilimia 34.17, mifuko ya pensheni asilimia 29.76 na wawekezaji wa rejareja asilimia 17.92. Wateja waliosajiliwa ni 35,102, ambapo 3,600 wameongezwa katika mwaka huu wa fedha.
Mnada wa hatifungani ya miaka 25 (No. 722): Zabuni 2,547 zilipokelewa zenye thamani ya TZS bilioni 2,495.06 dhidi ya bilioni 414.19 zilizotolewa (uwiano wa 6.02). BoT ilikubali TZS bilioni 610.61 kwa wastani wa mapato (yield) ya asilimia 10.84, chini kutoka asilimia 11.48 kwenye mnada wa awali wa miaka 25, yaani punguzo la pointi 64. Benki zilipata asilimia 56.25 ya mgao. Mnada unaofuata ni Jumatano, 21 Oktoba 2026 (hati fungani za muda mfupi).
Wiki nne zijazo (hadi 13 Novemba 2026): Katika hali ya msingi, shilingi inaendelea kudondoka polepole kwa kasi ya sasa ya asilimia 0.07 kwa wiki hadi takriban TZS 2,640 kwa dola (wigo TZS 2,623 hadi 2,660). Viwango vya soko la fedha vinabaki katika nusu ya juu ya ukanda wakati BoT inaendelea kutoa fedha kwa wingi. Mapato ya hatifungani ndefu yanatarajiwa kubaki karibu asilimia 10.8 ikiwa mahitaji yataendelea kuwa makubwa. Mambo yanayoweza kubadilisha mwelekeo ni mahitaji ya dola kwa uagizaji wa mafuta, kasi ya mtiririko wa dola kutoka madini na kilimo, na matokeo ya mnada wa 21 Oktoba.
Mapendekezo: (1) Kufuatilia mtiririko wa dola kwa sekta kila wiki; (2) kulinganisha kiasi cha reverse repo na kiasi cha IBCM; (3) kukuza soko la benki kwa benki la fedha za kigeni; (4) kuongeza hati fungani za muda mfupi ili kupata kigezo cha muda mfupi; (5) kutumia mapato ya hatifungani ya miaka 25 kama kigezo cha kufadhili miradi ya miundombinu na PPP; (6) kuchapisha thamani za yield curve pamoja na ripoti. TICGL/TERI hutoa upembuzi yakinifu (feasibility), ushauri wa kuingia sokoni na utafiti wa soko.
Hitimisho: Soko ni tulivu juu ya uso lakini limejikita kwa wachache: sekta chache zinaleta dola, sekta chache zinazitumia, na benki na mifuko ya pensheni zinashikilia theluthi mbili ya dhamana za serikali. Changamoto ya wiki nne zijazo ni kuhakikisha mtiririko wa dola unaendelea na mahitaji ya hatifungani ndefu yanabaki.
USD/TZS: 2,633.12 · mabadiliko ya wiki: asilimia 0.07
FX ya rejareja: dola milioni 604.89 · asilimia 13.3 · IFEM: dola milioni 19.70
IBCM: asilimia 6.68 · CBR: asilimia 6.25 · reverse repo: TZS bilioni 892.50
Hatifungani ya miaka 25: yield asilimia 10.84 · uwiano wa zabuni 6.02
Chanzo: Benki Kuu ya Tanzania, Ripoti ya Wiki ya Masoko ya Fedha ya Ndani (12-16 Oktoba 2026); TERI/TICGL, Oktoba 2026. Kwa maelezo zaidi: economist@ticgl.com.
Dar es Salaam Output Per Person Is 3.9 Times Simiyu's | TICGL
TICGL/TERI Economy WatchRegional InequalityGDP Per PersonSix-Month Outlook
Dar es Salaam's TZS 6.78 Million Output Per Person Is 3.9 Times Simiyu's TZS 1.74 Million, and the Gap Has Stayed Near 4 Times Since 2019
Output per person was TZS 6.78 million in Dar es Salaam and TZS 1.74 million in Simiyu in 2025, and the ratio has stayed between 3.7 and 4.2 in every year since 2019. Lake zone has 32.0% of Tanzanians but produces 26.1% of GDP, 18% below the national average per person. This report uses the Bank of Tanzania regional series for all 26 regions to show how those numbers are built, whether the gap is closing, what it does and does not mean, and what the six months to March 2027 are likely to change.
📅 Data to: 2025p (regional GDP)📍 Dar es Salaam, Tanzania🏛️ TICGL / TERI📖 Source: Bank of Tanzania, NBS
Dar es Salaam, per person 2025p
TZS 6.78 m +7.5%
Simiyu, per person 2025p
TZS 1.74 m +10.6%
Gap, Dar es Salaam / Simiyu
3.9x 3.7-4.2x since 2019
Lake zone: people / GDP
32.0% / 26.1% -18% per person
Source: Bank of Tanzania, Consolidated Zonal Economic Performance Report, quarter ending June 2026 (Tables 1.1-1.2, Annexes 1-2); NBS; TERI calculations. Outlook figures are TICGL scenarios. Excludes Zanzibar.
Disclaimer & scope
Prepared by TERI for research and strategic-information purposes only. It is not investment, legal, tax or financial advice and does not state the position of the Bank of Tanzania, the National Bureau of Statistics or the Government. "Output per person" is regional GDP divided by population (GDP per capita) as published by NBS; it is not household income. The report does not state the causes of regional differences; the explanations below are TICGL/TERI's reading of the figures, each marked by how well the data support it. The outlook (Tab 6) is a set of scenarios, not a forecast of record. p = provisional.
00 - OverviewThe Short Answer: What the Output-Per-Person Numbers Say
Output per person in Dar es Salaam reached TZS 6.78 million in 2025, 3.9 times the TZS 1.74 million of Simiyu region, the lowest in the country. The gap is not new: the ratio has stayed between 3.7 and 4.2 in every year from 2019 to 2025, and Simiyu has been the lowest region in every one of those years. Lake zone, home to 32% of mainland people, produces only 26.1% of GDP, which puts its output per person 18% below the national average. This report uses the Bank of Tanzania regional series (Annexes 1 and 2, 2019-2025) to show how the numbers are built, whether the gap is closing, what it does and does not mean, and what the next six months are likely to change.
Dar es Salaam, per person
TZS 6.78 m
1.91x the mainland average of TZS 3.54 m
Simiyu, per person
TZS 1.74 m
Lowest of 26 regions, 49% of the average
Gap, Dar es Salaam to Simiyu
3.9x
3.74x to 4.21x in every year since 2019
Lake zone
32.0% / 26.1%
share of people / share of GDP; 18% below average
Regions below the national average
14 of 26
55.4% of people, 39.8% of GDP
Five lowest regions
20.5% of people
but only 11.4% of GDP
Between-zone share of inequality
65%
35% is within zones (Theil, 2025)
Regional Gini, 2025p
0.218
0.205 in 2019; population-weighted
Output Per Person in All 26 Regions, 2025
TZS million per person, current prices. Amber = Dar es Salaam; red = Simiyu; blue = above national average; grey = below. Source: BoT Annex 2
How Far Ahead Is Dar es Salaam? Ratio of Output Per Person, 2019-2025
Dar es Salaam divided by Simiyu, by Kagera, and by the mainland average. Source: BoT Annexes 1 and 2; TICGL calc.
Key findings
The gap has lasted at least seven years. Dar es Salaam to Simiyu was 4.21x in 2019 and 3.89x in 2025p, with a low of 3.74x in 2022. It narrowed slightly in 2025 (from 4.00x), because Simiyu output per person rose 10.6% against 7.5% in Dar es Salaam, but one year does not make a trend.
Regions are not converging. Between 2022 and 2025, regions that started richer grew slightly faster (correlation +0.27), and Simiyu grew 4.8% a year against 6.1% in Dar es Salaam and 5.7% nationally.
It is mainly a zone story. About 65% of regional inequality sits between the six zones and 35% within them. Lake zone shows the within-zone spread most clearly: Mwanza (TZS 4.07 m) is above the national average while Simiyu (1.74 m), Kagera (1.85 m) and Kigoma (2.30 m) are the lowest, and Dodoma (2.11 m), Singida (1.99 m) and Pwani (2.16 m) are also in the bottom six.
Over half of Tanzanians live in regions below the average. 14 regions are below TZS 3.54 million and hold 55.4% of people but 39.8% of output.
These are output figures, not incomes. GDP per person measures what is produced where, divided by residents. Head offices, the port, government and large firms put output in Dar es Salaam that is not earned by its residents alone. The true gap in household incomes is probably smaller, but the report has no household income or poverty data by region to measure it.
Six-month outlook in one paragraph (October 2026 - March 2027)
A gap that has lasted seven years will not close in six months, and the 2026 regional numbers will not be published until well after the period ends. What can change is real purchasing power. Inflation in June 2026 was 6.2% in Dar es Salaam, 8.0% in Southern Highlands, 5.2% in Central, but only 3.0% in Lake and 2.6% in South Eastern. If nominal output per person keeps growing at its 2022-25 pace and prices follow the base case from our zonal economy report, real growth per person stays positive in every zone but is thinnest in Dar es Salaam (about +0.6%); under the stress case it turns negative in four of six zones (Dar es Salaam -1.6%, Southern Highlands -0.7%, Lake -0.3%, Northern -0.2%) (Tab 6).
01 - The NumbersOutput Per Person: Regions, Zones and a Break in the Series
The Bank of Tanzania report reproduces the National Bureau of Statistics regional series for GDP (Annex 1) and GDP per person (Annex 2) for the 26 mainland regions from 2019 to 2025. Dividing one by the other gives the population the statisticians used for each region and year, which is how we derive population shares below. Zanzibar is not included.
1.1 All 26 regions
Region
Zone
2019
2022
2024
2025p
Index (mainland = 100)
Growth 2025
CAGR 2022-25
Rank
Dar es Salaam
Dar es Salaam
4.49
5.67
6.31
6.78
191
+7.5%
+6.1%
1
Iringa
Southern Highlands
3.85
4.73
5.21
5.71
161
+9.5%
+6.4%
2
Kilimanjaro
Northern
3.27
4.29
4.81
5.20
147
+8.1%
+6.6%
3
Mbeya
Southern Highlands
3.65
4.27
4.70
5.06
143
+7.7%
+5.8%
4
Njombe
Southern Highlands
3.06
3.66
4.05
4.53
128
+11.8%
+7.4%
5
Arusha
Northern
3.18
3.58
4.03
4.28
121
+6.1%
+6.2%
6
Ruvuma
South Eastern
3.27
3.64
3.93
4.16
117
+5.9%
+4.5%
7
Mwanza
Lake
2.71
3.48
3.82
4.07
115
+6.4%
+5.4%
8
Tanga
Northern
2.72
3.19
3.54
3.80
107
+7.4%
+6.0%
9
Manyara
Northern
2.58
3.22
3.50
3.73
105
+6.5%
+5.0%
10
Mtwara
South Eastern
2.61
3.02
3.34
3.58
101
+7.2%
+5.8%
11
Lindi
South Eastern
2.74
2.99
3.28
3.57
101
+8.8%
+6.1%
12
Shinyanga
Lake
2.62
2.81
3.16
3.40
96
+7.7%
+6.6%
13
Morogoro
Central
2.51
2.69
3.01
3.27
92
+8.8%
+6.8%
14
Mara
Lake
2.21
2.72
3.03
3.26
92
+7.5%
+6.2%
15
Geita
Lake
2.65
2.73
2.90
3.13
88
+7.9%
+4.6%
16
Songwe
Southern Highlands
2.05
2.42
2.71
2.94
83
+8.7%
+6.7%
17
Rukwa
Southern Highlands
2.43
2.45
2.74
2.88
81
+5.1%
+5.4%
18
Katavi
Southern Highlands
2.44
2.10
2.29
2.46
69
+7.2%
+5.4%
19
Kigoma
Lake
1.44
2.02
2.17
2.30
65
+6.1%
+4.5%
20
Tabora
Central
1.73
1.95
2.16
2.30
65
+6.5%
+5.5%
21
Pwani
South Eastern
2.10
1.78
1.95
2.16
61
+10.9%
+6.6%
22
Dodoma
Central
1.67
1.81
2.00
2.11
60
+5.6%
+5.3%
23
Singida
Central
1.62
1.71
1.84
1.99
56
+7.7%
+5.1%
24
Kagera
Lake
1.14
1.53
1.70
1.85
52
+9.1%
+6.4%
25
Simiyu
Lake
1.07
1.51
1.58
1.74
49
+10.6%
+4.8%
26
Mainland Tanzania
2.56
3.00
3.30
3.54
100
+7.4%
+5.7%
Source: NBS via Bank of Tanzania, Annex 2 (TZS million per person, current prices); index, growth and rank are TICGL calc. Compound growth is measured from 2022 because the series is re-based between 2021 and 2022 (see 1.3).
1.2 The six zones
Zone
People 2025 (m)
Share of people %
GDP 2025 (TZS tn)
Share of GDP %
Per person 2025 (TZS m)
Per person 2019 (TZS m)
Index 2025 (mainland = 100)
Central
12.9
19.5
31.7
13.5
2.46
1.91
69
Dar es Salaam
5.9
8.9
39.8
17.0
6.78
4.49
191
Lake
21.1
32.0
61.0
26.1
2.89
1.97
82
Northern
9.6
14.5
40.3
17.2
4.21
2.94
119
South Eastern
7.3
11.0
24.1
10.3
3.31
2.71
93
Southern Highlands
9.3
14.1
37.2
15.9
3.99
3.01
112
Mainland
66.1
100.0
234.1
100.0
3.54
2.56
100
Source: BoT Annexes 1 and 2; zone figures are the sum of regions (TICGL calc.); people = GDP / GDP per person.
Output Per Person by Zone, 2019-2025
TZS million per person, current prices. Source: BoT Annexes 1 and 2; TICGL calc. from regions
Each Zone as a Percentage of the Mainland Average
Output per person, mainland = 100. Source: BoT Annexes 1 and 2; TICGL calc.
1.3 A break in the series in 2022
The per-person series jumps between 2021 and 2022: Simiyu +23.0%, Kigoma +29.0%, Katavi falls 18.8%. The cause is visible in the implied population. Katavi goes from 0.84 million to 1.15 million people and Kigoma from 2.90 million to 2.47 million in one year, while GDP in both grows smoothly. This is consistent with population estimates being re-based, most likely to the 2022 Census, though the report does not say so. The practical rule is: levels in 2025 are comparable across regions, trends are reliable from 2022 onward, and any comparison that crosses 2021 and 2022 mixes two population bases. This page therefore measures growth and convergence from 2022 and treats 2019-2021 as a separate earlier series.
TICGL/TERI reading
Monthly equivalents make the numbers concrete, though they are output, not take-home pay: TZS 6.78 million a year is about TZS 565,000 per person per month in Dar es Salaam, against about TZS 145,000 in Simiyu and TZS 295,000 on the mainland average. Moving every region to the national average would require about TZS 36.4 trillion of additional output a year (TZS 15.6% of GDP).
02 - People vs OutputLake Zone: 32% of People, 26.1% of Output, and Inequality Within Zones
Lake zone has 32.0% of mainland people (about 21.1 million) but produces 26.1% of GDP (TZS 61.0 trillion). Dividing the two shares gives 82% of the national average, which is the 18% shortfall in the data. The same arithmetic applies to every zone: a zone whose share of GDP is below its share of people is below the average per person.
Zone
Share of people %
Share of GDP %
Difference (points)
GDP share / people share (index)
Output per person (TZS m)
Regions
Dar es Salaam
8.9
17.0
8.1
191
6.78
1
Northern
14.5
17.2
2.7
119
4.21
4
Southern Highlands
14.1
15.9
1.8
112
3.99
6
South Eastern
11.0
10.3
-0.7
93
3.31
4
Lake
32.0
26.1
-5.9
82
2.89
7
Central
19.5
13.5
-6.0
69
2.46
4
Source: BoT Annexes 1 and 2; TICGL calc. Index of 100 = output in line with population.
Share of People vs Share of Output by Zone, 2025
Percent of the mainland total. Source: BoT Annexes 1 and 2; TICGL calc.
Lake Zone Output Per Person Relative to the Mainland, 2019-2025
Percent of the mainland average. Source: BoT Annexes 1 and 2; TICGL calc. (break between 2021 and 2022)
2.1 Inside Lake zone: the gap runs through the middle of it
Region
People (m)
GDP (TZS tn)
Per person (TZS m)
Index (mainland = 100)
Growth 2025
Mwanza
4.12
16.75
4.07
115
+6.4%
Shinyanga
2.48
8.44
3.40
96
+7.7%
Mara
2.65
8.63
3.26
92
+7.5%
Geita
3.36
10.50
3.13
88
+7.9%
Kigoma
2.76
6.34
2.30
65
+6.1%
Kagera
3.32
6.15
1.85
52
+9.1%
Simiyu
2.43
4.23
1.74
49
+10.6%
Lake zone
21.1
61.0
2.89
82
+7.5%
Source: BoT Annexes 1 and 2; TICGL calc. (people = GDP / GDP per person).
Lake Zone Regions: Output Per Person vs the Mainland Average, 2025
TZS million per person. Source: BoT Annex 2
Mwanza (4.07 million, 115% of the average) lifts the zone, while Simiyu, Kagera and Kigoma, with 8.5 million people between them, sit 35-51% below the average. Lake zone also accounts for 69.3% of mineral recovery in 2025/26, yet its output per person is the second lowest of the six zones. Geita, the zone's second-largest regional economy (TZS 10.5 trillion), has output per person at 88% of the national average. The report does not describe how mining value added is allocated to regions, so we cannot say whether this reflects small local value added, profits booked elsewhere, or both.
2.2 How unequal are regions, taken together?
Year
Gini across 26 regions (population-weighted)
Highest / lowest region
2019
0.205
4.21
2020
0.207
4.18
2021
0.208
4.04
2022
0.215
3.74
2023
0.217
3.84
2024
0.218
4.00
2025p
0.218
3.89
Source: TICGL calc. from BoT Annexes 1 and 2. A Gini of 0 means every region has the same output per person.
Lorenz Curve of Output Across Regions, 2025
Cumulative share of GDP (y) against cumulative share of people (x), regions ranked from lowest to highest output per person. Source: BoT Annexes 1, 2; TICGL calc.
The population-weighted Gini across regions is 0.218 in 2025, up from 0.205 in 2019. The ten poorest regions hold 37% of people and 23% of output. A Theil decomposition shows 65% of the inequality is between the six zones and 35% within them. This measures inequality between regional averages, so it understates inequality between households.
TICGL/TERI reading
Lake zone is the clearest example of why a zone average misleads. Its 18% shortfall is the result of a premium pocket (Mwanza) and a low-output belt (Simiyu, Kagera, Kigoma) that together are 21.1 million people. Policy and market-entry choices made at zone level miss this; they need to be made at regional level.
03 - What Sits Behind the GapWhy Output Per Person Differs: Structure, Location and Measurement
Why is output per person so different across regions? The Bank of Tanzania report has no sector breakdown of regional GDP, so the question cannot be answered directly. What it does have is zone-level data on manufacturing, banking, public revenue, power and food, which can be divided by population to see what the high-output zone has that the others do not. The pattern is clear, though the mechanisms are partly inferred.
Zone
GDP per person 2025 (TZS m)
Manufactured output per person 2025/26 (TZS '000)
Bank deposits per person (TZS '000)
Local-government own revenue per person (TZS '000)
Electricity generated per person (kWh)
Food crops per person (kg)
Dar es Salaam
6.78
1,716
5,347
60
730
2
Northern
4.21
299
560
21
47
319
Southern Highlands
3.99
101
203
28
61
757
South Eastern
3.31
522
220
37
905
410
Lake
2.89
70
249
16
11
350
Central
2.46
162
349
18
150
366
Mainland
3.54
322
757
25
213
382
Source: BoT Tables 1.1-1.2, 3.1, 4.3, 5.x, 6.1 and the energy tables; per-person figures are TICGL calc. using population implied by GDP / GDP per person. Electricity and manufacturing are booked where plants are, not where people live.
Kilograms per person. Source: BoT Table 3.1; TICGL calc.
3.1 Six explanations, ranked by how well the data support them
Explanation
What the data show
Evidence
1. Dar es Salaam is where manufacturing, finance and trade concentrate
It has 8.9% of people but 47.4% of manufactured output (index 533), 62.8% of deposits (index 706) and 238% of the average local revenue per person.
Measured
2. Records and headquarters sit there
88.2% of tax collections and 85.4% of port cargo are booked in Dar es Salaam, so part of its GDP is output for the whole country that is attributed to its location.
Measured; the attribution rule is not described
3. Farming alone does not lift output per person
Southern Highlands produces 757 kg of food per person, 2.0x the average, and sits at 112% of national output per person. Central produces 366 kg per person, near the average, but only 69% of the national figure.
Measured
4. Power is generated far from where output per person is highest
South Eastern generates 905 kWh per person (4.2x the average) and sits at 93% of national output per person; Lake generates 11 kWh per person.
Measured
5. Government presence does not raise output per person by itself
Dodoma, the capital, has output per person of TZS 2.11 million, 60% of the national average and fourth lowest of the 26 regions.
Measured
6. Dar es Salaam's workforce partly lives next door
If many people who work in Dar es Salaam live in Pwani region, output is counted in one and people in the other. Pwani has output per person of TZS 2.16 million, fifth lowest of the 26 regions.
Hypothesis; not testable from the report
Source: BoT zonal tables and Annexes 1-2; TICGL calc. "Measured" means the figure is in the report; the interpretation is TICGL/TERI's.
TICGL/TERI reading
The common thread is that output per person tracks where non-farm, non-extractive activity is booked, not where the most food, power or minerals are produced. That is why Dar es Salaam is far ahead, why Southern Highlands (a food surplus zone) is only a little above the average, and why Lake, despite 69.3% of mineral recovery, is not. The way to raise output per person in the lower regions is therefore to add value locally, not simply to produce more raw output.
04 - Is the Gap Closing?Seven Years of Ratios, No Convergence, and the Arithmetic of Catching Up
The seven-year record answers the "how long" question directly: the gap between Dar es Salaam and the lowest region has not closed, and on the evidence of 2022-2025 it is not on a path to close. This tab sets out the year-by-year ratios, tests whether poorer regions grow faster, and then does the arithmetic of catching up.
4.1 Seven years of ratios
Year
Dar es Salaam (TZS m)
Simiyu (TZS m)
Dar es Salaam / Simiyu
Dar es Salaam / mainland
Simiyu as % of mainland
Regional Gini
2019
4.49
1.07
4.21x
1.75x
42%
0.205
2020
4.72
1.13
4.18x
1.76x
42%
0.207
2021
4.98
1.23
4.04x
1.77x
44%
0.208
2022
5.67
1.51
3.74x
1.89x
51%
0.215
2023
5.93
1.54
3.84x
1.92x
50%
0.217
2024
6.31
1.58
4.00x
1.91x
48%
0.218
2025p
6.78
1.74
3.89x
1.91x
49%
0.218
Source: BoT Annex 2; ratios and Gini are TICGL calc. The 2022 step reflects the population re-basing described in Tab 1.
4.2 Year-on-year growth in output per person
Region
2020
2021
2022
2023
2024
2025p
CAGR 2022-25
Dar es Salaam
+5.2%
+5.4%
+13.8%
+4.7%
+6.3%
+7.5%
+6.1%
Simiyu
+6.1%
+9.0%
+23.0%
+1.9%
+2.1%
+10.6%
+4.8%
Kagera
+3.6%
+4.7%
+24.3%
+3.6%
+6.7%
+9.1%
+6.4%
Mainland
+4.4%
+4.8%
+6.8%
+3.3%
+6.6%
+7.4%
+5.7%
Source: BoT Annex 2; TICGL calc. 2022 growth reflects the re-basing; compare years from 2023 onward.
From 2023, Simiyu grew 1.9% and 2.1% while Dar es Salaam grew 4.7% and 6.3%, and the ratio drifted up from 3.74 to 4.00. In 2025 Simiyu grew 10.6% against 7.5% and the ratio fell to 3.89. Over the three years 2022-25, however, Simiyu averaged 4.8% a year, Dar es Salaam 6.1% and the mainland 5.7%. Simiyu is the fastest-growing region in GDP terms in 2025 (+14.7%), so the 2025 improvement may be the start of a catch-up, but it is a single observation after two years of falling behind.
4.3 Do poorer regions grow faster?
If regions were converging, those starting with lower output per person in 2022 would show faster growth to 2025. The opposite holds weakly: the correlation between 2022 output per person (logarithm) and annual growth to 2025 across the 26 regions is +0.27, meaning slightly faster growth among the richer regions. The fastest-growing regions were Njombe (7.4%), Morogoro (6.8%), Songwe (6.7%), Pwani (6.6%) and Shinyanga (6.6%); the slowest were Kigoma (4.5%), Ruvuma (4.5%), Geita (4.6%), Simiyu (4.8%) and Manyara (5.0%). With 26 regions and three years, this is suggestive, not conclusive.
Starting Level vs Growth: No Sign of Convergence, 2022-2025
x = output per person in 2022 (TZS million); y = compound annual growth 2022-25 (%). Each point is a region; colour = zone. Source: BoT Annex 2; TICGL calc.
4.4 How long would catching up take?
The table asks how fast each of the six lowest regions would need to grow, each year, to reach the national average of TZS 3.54 million within 10, 20 or 30 years, assuming the mainland average itself keeps growing at its 2022-25 pace of 5.7% a year. All figures are nominal; they are relative comparisons, so inflation cancels out if it affects all regions equally.
Region
Zone
Output per person 2025 (TZS m)
Needed a year: 10 yrs
20 yrs
30 yrs
Actual 2022-25 pace
Simiyu
Lake
1.74
13.5%
9.6%
8.3%
4.8%
Kagera
Lake
1.85
12.8%
9.2%
8.1%
6.4%
Singida
Central
1.99
12.0%
8.8%
7.8%
5.1%
Dodoma
Central
2.11
11.3%
8.5%
7.6%
5.3%
Pwani
South Eastern
2.16
11.1%
8.4%
7.5%
6.6%
Tabora
Central
2.30
10.4%
8.1%
7.3%
5.5%
Source: TICGL calc. from BoT Annex 2. Needed growth = (national average 2025 / region 2025)^(1/N) x (1 + national growth) - 1.
Growth Needed to Reach the National Average in 20 Years vs Actual Pace
Percent a year, nominal. Needed assumes the national average keeps growing at 5.7% a year. Source: BoT Annex 2; TICGL calc.
At the 2022-25 pace the gap widens. If Simiyu keeps growing at 4.8% and Dar es Salaam at 6.1%, the ratio rises from 3.9x to 4.4x in ten years and 5.0x in twenty.
Simiyu needs about 9.6% a year to reach the national average in 20 years, roughly double its own 2022-25 pace. If it repeated its 2025 pace (10.6%) every year while the mainland grew 5.7%, it would take about 16 years.
All six of the lowest regions are growing below the pace needed even for a 30-year catch-up. Pwani is closest (6.6% a year against 7.5% needed); Simiyu is furthest (4.8% against 8.3%).
What this means for the "how long" question
On the evidence of the series, the honest answer is: more than a generation at current rates, and never if the 2022-25 pattern simply continues. The gap is shaped by structure (where manufacturing, finance and headquarters sit), and structure changes slowly. A six-month window cannot move it; it can only show whether 2025's faster Simiyu growth was a turning point.
05 - What It MeansOutput vs Income, Market Size, Real Growth and Local Public Finance
What do the numbers mean once they are read correctly? Five points follow: what output per person is and is not, what it says about market size, whether people are better off in real terms, what it means for local public finance, and how concentrated demand is.
5.1 Output per person is not income per person
GDP per person divides the value added produced in a region by the people who live there. It includes company profits, depreciation, taxes on products and the pay of workers who live elsewhere, none of which reaches residents as household income. In Dar es Salaam, where headquarters, the port and government are located, the share of output that is not earned by residents is probably larger than in Simiyu. The 3.9-times gap in output is therefore likely larger than the gap in household incomes, and household consumption is the figure that matters for living standards. The report has no household income, consumption or poverty series by region, so the gap in living standards cannot be measured from it. The National Bureau of Statistics household surveys are the right source for that and would be a natural complement to this analysis.
5.2 Market size and purchasing power
For market research, two numbers matter together: how many people, and how much output per person. The table and chart place each zone on both.
Zone
People (m)
GDP (TZS tn)
Per person (TZS m)
Index
Market profile
Dar es Salaam
5.9
39.8
6.78
191
Premium urban market
Northern
9.6
40.3
4.21
119
Upper-middle, tourism-linked
Southern Highlands
9.3
37.2
3.99
112
Above-average, farm-surplus
South Eastern
7.3
24.1
3.31
93
Near-average, energy and ports
Lake
21.1
61.0
2.89
82
Largest volume, mass market with a Mwanza pocket
Central
12.9
31.7
2.46
69
Lowest output per person, farm and livestock
Source: BoT Annexes 1 and 2; TICGL calc. The market profile is TICGL/TERI's reading.
Market Size vs Purchasing Power by Zone, 2025
x = output per person (TZS million); y = zone GDP (TZS trillion); bubble size = people. Source: BoT Annexes 1 and 2; TICGL calc.
Lake zone is the largest market by output (TZS 61 trillion) and by people (21.1 million) but at 82% of national output per person; Dar es Salaam is a market of 5.9 million people with 1.91 times the average output per person. The two require different offers: scale and price in Lake, depth and quality in Dar es Salaam.
5.3 Are people better off in real terms?
Zone
Output per person growth 2025 (nominal)
Average inflation 2025/26
Real growth (indicative)
South Eastern
+7.7%
3.3%
+4.3%
Central
+7.2%
3.0%
+4.1%
Northern
+7.0%
2.9%
+4.0%
Lake
+7.5%
3.6%
+3.7%
Southern Highlands
+8.0%
4.7%
+3.2%
Dar es Salaam
+7.5%
4.8%
+2.5%
Mainland
+7.4%
3.6%
+3.7%
Source: BoT Annexes 1-2 and Table 1.3; TICGL calc. Real growth = (1 + nominal growth) / (1 + average inflation) - 1. The output year is calendar 2025 and the inflation year is 2025/26, so the figures are indicative only.
Real Growth in Output Per Person, 2025 (Indicative)
Percent; nominal growth in 2025 deflated by 2025/26 average zonal inflation. Source: BoT Annex 2, Table 1.3; TICGL calc.
In 2025 every zone had positive real growth in output per person, from 2.5% in Dar es Salaam to 4.3% in South Eastern. Dar es Salaam has the highest level but the lowest real growth, because its prices rose most; this is the only force in the data that narrows the gap, and it narrows it through higher prices in Dar es Salaam, not faster growth elsewhere.
5.4 Local public finance follows the same pattern
Local government authorities collected TZS 60,000 per person in own-source revenue in Dar es Salaam, against TZS 16,000 in Lake (3.7x) and TZS 18,000 in Central. The gap in local revenue per person is wider than the gap in output per person (3.7x against 2.3x for Lake) and it points the same way: the councils that serve the lowest-output people have the least own revenue to spend on them, which is the case for equalising transfers from the centre. South Eastern is the exception: at TZS 37,000 per person it is well above its output-per-person ranking.
Local Government Own-Source Revenue Per Person, 2025/26
TZS thousand per person. Source: BoT Table 4.3; TICGL calc.
5.5 Concentration of demand
Dar es Salaam has 8.9% of people and 17.0% of output. Its 5.9 million residents produce TZS 39.8 trillion, 1.49 times the TZS 26.7 trillion produced by the 13.6 million people in the five lowest regions (Simiyu, Kagera, Singida, Dodoma, Pwani), while the 14 regions below the average combined (36.6 million people) produce 39.8% of GDP. For firms, the largest market by population is not the largest by spending power, and the two overlap only in a few regional cities.
TICGL/TERI reading
The numbers mean three things. First, the gap is mostly structural, set by where non-farm activity is booked, and it is not closing. Second, it overstates the gap in household living standards but cannot be corrected with this report. Third, it matters for decisions today: pricing and format for a Dar es Salaam consumer are different from those for a Simiyu or Kagera consumer, and regional public budgets start from very different revenue bases.
06 - Six-Month OutlookReal Growth Scenarios to March 2027, Watch-List, Policy and Market-Entry Screen
The structural gap cannot change in six months, and the Bank of Tanzania and NBS will not publish 2026 regional output per person until well after March 2027. What can change is real purchasing power, which depends on prices. This tab combines each zone's 2022-25 pace of growth in output per person with the three inflation scenarios from our zonal economy report (Relief, Base, Stress) to show what the next six months could do to real growth per person.
6.1 Real growth per person under three inflation paths
Zone
Nominal growth per person (2022-25 CAGR)
Inflation Mar-27: Relief
Base
Stress
Real growth: Relief
Base
Stress
Dar es Salaam
6.1%
3.1%
5.5%
7.9%
+2.9%
+0.6%
-1.6%
Northern
6.0%
1.5%
3.8%
6.2%
+4.4%
+2.1%
-0.2%
Southern Highlands
5.9%
2.0%
4.4%
6.7%
+3.9%
+1.5%
-0.7%
South Eastern
5.6%
0.1%
2.4%
4.7%
+5.5%
+3.1%
+0.9%
Lake
5.5%
1.1%
3.4%
5.8%
+4.3%
+2.0%
-0.3%
Central
5.8%
0.9%
3.2%
5.6%
+4.9%
+2.5%
+0.2%
Source: TICGL calc. from BoT Annex 2 and the zonal CPI scenarios in "Tanzania's Economy by Zone, 2025/26", Tab 7 (flat, +0.25% and +0.5% a month from June 2026). Real growth = (1 + nominal) / (1 + inflation at March 2027) - 1. Indicative: it pairs an annual output growth rate with a year-on-year inflation rate at the end of the window.
Indicative Real Growth in Output Per Person by Zone, Three Inflation Paths
Percent a year. Nominal growth at the 2022-25 pace minus March 2027 inflation under each scenario. TICGL scenarios
Base case: real growth per person stays positive in every zone, from +0.6% in Dar es Salaam to +3.1% in South Eastern. Dar es Salaam is lowest because it has the highest inflation (5.5% by March 2027).
Stress case: real growth per person turns negative in 4 of six zones (Dar es Salaam -1.6%, Southern Highlands -0.7%, Lake -0.3%, Northern -0.2%), which would mean falling real output per person in zones holding 69% of the mainland population.
Relief case: every zone gains between about 2.9% and 5.5% in real terms, and the gap narrows slightly in real terms because Dar es Salaam's inflation is the highest in every scenario.
What does not change: the nominal ratio of Dar es Salaam to Simiyu. At 2022-25 growth rates it moves from 3.89x to about 3.91x over six months (a rise of 0.03x), too small to measure.
6.2 What to watch
Indicator
Latest
Reassuring signal
Stress signal
Zonal inflation, monthly
Southern Highlands 8.0%, Dar es Salaam 6.2%, Central 5.2% (Jun-26)
Base-case path: 4.4%, 5.5%, 3.2% by Mar-27
Stress path keeps all three above 5%
Food prices and harvest
Central and Southern Highlands food output -8.8% and -11.3%
Recovery at harvest
A second poor season
Regional GDP for 2026
Not published until after this window
Simiyu and Kagera continue to outgrow the average
Return to 2023-24 pace (about 2% a year in Simiyu)
Local-government revenue per person
TZS 60,000 in Dar es Salaam, 16,000 in Lake
Improving collection in low-revenue zones
Widening gap
Household income and poverty data by region
Not in the zonal report
NBS release
No data: the gap in living standards stays unmeasured
Source: BoT zonal report and TICGL calc.
6.3 Policy options
Add value where the output is produced. Processing, packaging and light manufacturing in the lower-output regions (cotton, grain, fish, timber) would put non-farm output where people live; 47.4% of factory output is in Dar es Salaam on 8.9% of the population.
Spread connectivity and trade routes. 85.4% of port cargo passes through one port; secondary corridors and inland logistics hubs reduce the cost of locating outside Dar es Salaam.
Equalise local public finance. Own-source revenue per person is 3.7 times higher in Dar es Salaam than in Lake; a transfer formula that weights output per person or population would reduce the starting gap between councils.
Target the lowest regions by name. Simiyu, Kagera, Singida, Dodoma and Pwani hold 20.5% of people and 11.4% of output; regional programmes and investment incentives can be targeted by region, not by zone.
Close the data gap. Publish household income, consumption and poverty by region, and a regional real-GDP series, so that the gap in living standards can be tracked.
Bring finance closer. Deposits per person in Dar es Salaam are 26 times those in Southern Highlands (see our analysis of the regional credit gap); local deposit mobilisation and agent banking would let low-output regions retain more of their own savings.
6.4 What it means for investors and market-entry decisions
Zone
People (m)
Per person (TZS m)
Index
Growth p.a. 2022-25
Inflation Jun-26
TICGL/TERI reading
Dar es Salaam
5.9
6.78
191
6.1%
6.2%
Premium urban market; highest costs and the highest inflation (6.2%); compete on quality and service.
Northern
9.6
4.21
119
6.0%
3.3%
Upper-middle market with tourism and hospitality links; balanced finance; above-average output per person.
Southern Highlands
9.3
3.99
112
5.9%
8.0%
Above-average output per person but the highest inflation (8.0%) and falling deposits; storage, milling and transport.
South Eastern
7.3
3.31
93
5.6%
2.6%
Lowest inflation (2.6%), energy and port growth; near-average output per person; consumer lending needs care.
Lake
21.1
2.89
82
5.5%
3.0%
Largest volume market (21.1 million people); price-sensitive with a Mwanza premium pocket; Simiyu, Kagera, Kigoma need low-cost formats.
Central
12.9
2.46
69
5.8%
5.2%
Lowest output per person; livestock, tobacco and Dodoma-linked demand; falling food output.
Source: BoT Annexes 1-2, Annex 4; TICGL calc. The reading column is TICGL/TERI's interpretation, not a recommendation to invest.
Feasibility studies
Demand sizing by region, not zone, using output per person, population and local revenue; price-point and format design for each tier of market.
Financial models (NPV, IRR, DSCR) tested for inflation and consumer-spending shocks like the scenarios above.
Market entry advisory
Region screening against the indicators in this report, entry-mode choice and partner identification, from first meeting to start-up.
Matching offers to the market: volume formats for Lake, depth and service in Dar es Salaam.
Market research and economic intelligence
Household surveys and price benchmarking in the lowest-output regions to fill the income gap the report leaves.
Scenario updates with each Bank of Tanzania and NBS release, through TERI.
Talk to TICGL/TERI
Request a feasibility, market-entry or market-research scoping call for a project in any region, or a briefing on this analysis.
Source report. Bank of Tanzania, Consolidated Zonal Economic Performance Report for the Quarter Ending June 2026, Vol. 11 No. 2: Tables 1.1-1.2 and Annexes 1-2 (regional GDP and GDP per person, 2019-2025p, from the National Bureau of Statistics), plus Tables 3.1, 4.3, 5.x, 6.1, 1.3 and Annex 4 for per-person indicators and inflation. TICGL calculations. People = GDP / GDP per person (for regions and, by summation, zones); ratios, shares and compound growth from published values; Gini and Theil measures weight regions by population; the convergence test is the correlation between the logarithm of 2022 output per person and annual growth 2022-25 across 26 regions; the catch-up arithmetic is (national average / region)^(1/N) x (1 + national growth) - 1; per-person structure indicators divide zone totals by implied population; real growth deflates nominal output growth by average inflation. Scenarios. Real growth = (1 + nominal growth at the 2022-25 zone pace) / (1 + zonal year-on-year inflation at March 2027 under the flat, +0.25% and +0.5% a month paths from our zonal economy report) - 1. Limits. Provisional data; population is re-based between 2021 and 2022, so trends are measured from 2022; GDP per person is not household income; the report has no regional sector, income or poverty data; zone averages hide differences between regions; mixing a calendar-2025 output year with a 2025/26 inflation year is indicative only.
Bank of Tanzania, Consolidated Zonal Economic Performance Report, quarter ending June 2026 (Vol. 11 No. 2), Dodoma, 2026.
National Bureau of Statistics: regional GDP and GDP per capita as reproduced in the report.
08 - Quick AnswersFrequently Asked Questions
How much higher is output per person in Dar es Salaam than in Simiyu?
In 2025 (provisional) output per person was TZS 6,776,483 in Dar es Salaam and TZS 1,742,809 in Simiyu, a ratio of 3.9. Simiyu is the lowest of the 26 mainland regions and has been in every year since 2019. The national average is TZS 3,544,124, so Dar es Salaam is 1.91 times the average and Simiyu is 49% of it.
Has the gap between Dar es Salaam and Simiyu narrowed?
Not materially. The ratio was 4.21 in 2019, 3.74 in 2022, 4.00 in 2024 and 3.89 in 2025, so it has stayed between 3.7 and 4.2 for seven years. Between 2022 and 2025 Simiyu grew 4.8% a year against 6.1% in Dar es Salaam and 5.7% nationally. Richer regions grew slightly faster than poorer ones, so there is no sign of convergence. Simiyu grew faster in 2025 (10.6% against 7.5%), but that is one year.
Is GDP per person the same as income per person?
No. It divides the value added produced in a region by its residents, and includes company profits, taxes and the pay of workers who live elsewhere. Dar es Salaam hosts headquarters, the port and government, so its figure likely overstates the gap in household income. The Bank of Tanzania zonal report has no household income, consumption or poverty data by region; NBS household surveys would fill that gap.
Why is Lake zone 18% below the national average?
Lake zone has 32.0% of mainland people but 26.1% of GDP, which puts its output per person at 82% of the national average. The zone is internally divided: Mwanza is at TZS 4.07 million, above the average, while Simiyu (1.74 million), Kagera (1.85 million) and Kigoma (2.30 million), with about 8.5 million people, are 35-51% below it. Lake also accounts for 69.3% of mineral recovery, so output per person is not simply a function of mining.
Which regions have the lowest output per person?
Simiyu (TZS 1.74 million), Kagera (1.85 million), Singida (1.99 million), Dodoma (2.11 million) and Pwani (2.16 million) are the five lowest. Together they have 20.5% of the mainland population and 11.4% of GDP. Fourteen of the 26 regions are below the national average and hold 55.4% of people.
What happens to the gap over the next six months, October 2026 to March 2027?
The structural gap will not change, and 2026 regional figures will not be published until after the window. What can change is real purchasing power. At the 2022-25 pace of growth and base-case inflation, real output per person grows in every zone, thinnest in Dar es Salaam (about +0.6%). Under a stress case with prices rising 0.5% a month it turns negative in Dar es Salaam, Southern Highlands, Lake and Northern.
09 - Explore MoreTICGL Economic: Related Insights & Tools
Companion Report
Tanzania's Economy by Zone, 2025/26: Six-Month Outlook
The full zonal report: GDP, prices, food, industry, tourism, trade, revenue and credit.
Pato kwa kila mtu: Dar es Salaam na Simiyu. Kwa mujibu wa takwimu za NBS zilizomo kwenye Ripoti ya Benki Kuu ya Tanzania ya Utendaji wa Kiuchumi wa Kanda (Juni 2026), pato kwa kila mtu mwaka 2025 lilikuwa shilingi milioni 6.78 Dar es Salaam na milioni 1.74 Simiyu, yaani mara 3.9. Simiyu imekuwa mkoa wa chini kuliko yote kila mwaka tangu 2019. Wastani wa nchi ni milioni 3.54.
Je, pengo linapungua? Hapana kwa kiasi kikubwa. Uwiano umebaki kati ya 3.7 na 4.2 kila mwaka tangu 2019. Mwaka 2022-2025 Simiyu ilikua asilimia 4.8 kwa mwaka, Dar es Salaam asilimia 6.1 na nchi asilimia 5.7. Mikoa tajiri ilikua kwa kasi kidogo zaidi kuliko maskini, kwa hiyo hakuna dalili ya kukaribiana. Kwa kasi ya sasa uwiano ungefikia takriban 4.4 baada ya miaka 10 na 5.0 baada ya miaka 20.
Kanda ya Ziwa: ina asilimia 32.0 ya watu lakini asilimia 26.1 ya pato, kwa hiyo pato kwa kila mtu ni asilimia 18 chini ya wastani. Ndani ya kanda tofauti ni kubwa: Mwanza (milioni 4.07) iko juu ya wastani, wakati Simiyu (1.74), Kagera (1.85) na Kigoma (2.30) ziko chini sana. Mikoa 14 kati ya 26 iko chini ya wastani na ina asilimia 55.4 ya watu.
Kwa nini pengo lipo? Dar es Salaam ina asilimia 47.4 ya uzalishaji wa viwanda, asilimia 62.8 ya amana za benki, asilimia 88.2 ya kodi na asilimia 85.4 ya shehena ya bandari, ikiwa na asilimia 8.9 tu ya watu. Kilimo pekee hakiinui pato kwa kila mtu: Nyanda za Juu Kusini zinazalisha kilo 757 za chakula kwa kila mtu (mara 2 ya wastani) lakini pato kwa kila mtu liko karibu na wastani. Dodoma, makao makuu, iko ya nne kutoka chini.
Maana yake: Pato kwa kila mtu si kipato cha kaya. Linajumuisha faida za kampuni, kodi na malipo ya wafanyakazi wanaoishi mahali pengine. Pengo la kipato halisi cha kaya huenda ni dogo kuliko mara 3.9, lakini ripoti haina takwimu za kipato au umaskini kwa mkoa. Mapato ya halmashauri kwa kila mtu ni mara 3.7 Dar es Salaam kuliko Ziwa, kwa hiyo halmashauri zinazohudumia watu wa pato la chini zina rasilimali kidogo.
Miezi sita ijayo (Oktoba 2026 - Machi 2027): Pengo la muundo halibadiliki. Kinachoweza kubadilika ni nguvu ya kununua. Kwa hali ya msingi ya mfumuko, ukuaji halisi kwa kila mtu unabaki chanya kila kanda, mdogo zaidi Dar es Salaam (takriban +0.6%). Mfumuko ukiongezeka kwa kasi ya Aprili-Juni, unakuwa hasi Dar es Salaam, Nyanda za Juu Kusini, Ziwa na Kaskazini.
Mapendekezo: (1) Kuongeza thamani mahali bidhaa zinapozalishwa; (2) kupanua njia za biashara nje ya bandari moja; (3) kugawa upya mapato kwa halmashauri kwa kuzingatia pato na idadi ya watu; (4) kulenga mikoa ya chini kwa majina (Simiyu, Kagera, Singida, Dodoma, Pwani); (5) kuchapisha kipato, matumizi na umaskini kwa mkoa; (6) kuleta huduma za fedha karibu na wananchi. TICGL/TERI hutoa upembuzi yakinifu (feasibility), ushauri wa kuingia sokoni na utafiti wa soko kwa mkoa wowote.
Hitimisho: Pengo la mara 3.9 ni la muundo wa uchumi, si la bahati: shughuli zisizo za kilimo zinakusanyika Dar es Salaam, na mikoa ya chini haikaribii. Kulifunga kunahitaji kuongeza thamani ndani ya mikoa yenyewe, na kupima kipato cha kaya ili tujue pengo halisi la maisha.
Pato kwa kila mtu 2025: Dar es Salaam TZS milioni 6.78 · Simiyu milioni 1.74 · wastani milioni 3.54
Uwiano Dar es Salaam / Simiyu: 3.74 hadi 4.21 kila mwaka 2019-2025
Kanda ya Ziwa: watu 32.0% · pato 26.1% · pato kwa kila mtu 18% chini ya wastani
Chanzo: Benki Kuu ya Tanzania, Ripoti ya Utendaji wa Kiuchumi wa Kanda (Juni 2026); NBS; TERI/TICGL, Oktoba 2026. Kwa maelezo zaidi: economist@ticgl.com.
Why Do Four Tanzanian Zones Lend More Than They Collect? | TICGL
TICGL/TERI Economy WatchBanking & CreditZonal AnalysisSix-Month Outlook
Why Do Four Tanzanian Zones Lend More Than They Collect?
In four of Tanzania's six zones, banks lent more in 2025/26 than they collected in deposits: 153% in Southern Highlands, 139% in Central, 128% in South Eastern and 127% in Lake. Dar es Salaam holds 62.8% of deposits and lends only 75% of them. This report uses the Bank of Tanzania zonal data to explain why, to show which zones carry real risk, and to set out scenarios for October 2026 to March 2027.
📅 Data to: June 2026📍 Dar es Salaam, Tanzania🏛️ TICGL / TERI📖 Source: Bank of Tanzania, NBS, TRA
Zones with loans > deposits
4 of 6 127-153%
Dar es Salaam share of deposits
62.8% 17.0% of GDP
S. Highlands deposits, 2025/26
-1.4% loans +28.1%
Southern Highlands ratio, Mar-27
~187% Momentum case
Source: Bank of Tanzania, Consolidated Zonal Economic Performance Report, quarter ending June 2026 (Tables 6.1-6.4); TERI calculations. Outlook figures are TICGL scenarios. Excludes Zanzibar.
Disclaimer & scope
Prepared by TERI for research and strategic-information purposes only. It is not investment, legal, tax or financial advice and does not state the position of the Bank of Tanzania, the National Bureau of Statistics or the Government. Deposits and loans are as booked by banks in each zone (not by customer residence). The Bank of Tanzania report does not state the causes of the gap or give non-performing-loan data by zone; the explanations below are TICGL/TERI's reading of the figures, each marked by how well the data support it. The outlook (Tab 6) is a set of scenarios, not a forecast of record. p = provisional.
00 - OverviewThe Short Answer: Five Drivers Behind the Regional Credit Gap
Banks in four of Tanzania's six economic zones lent more in 2025/26 than they collected in deposits there: Southern Highlands (loans equal to 153% of deposits), Central (139%), South Eastern (128%) and Lake (127%). Dar es Salaam, by contrast, holds 62.8% of all deposits but only 51.5% of loans, and carries a loan-to-deposit ratio of 75%. This report takes the Bank of Tanzania zonal data and asks why the gap exists, what it does to the real economy, and how it is likely to move between October 2026 and March 2027.
Borrower zones (loans > deposits)
4 of 6
Southern Highlands, Central, South Eastern, Lake
Dar es Salaam surplus
TZS 7.8 tn
deposits minus loans; 62.8% of deposits
Net funding need, 4 zones
TZS 4.65 tn
loans minus deposits, end-June 2026
Southern Highlands deposits
-1.4%
while loans grew +28.1% (2025/26)
Loans as a Percentage of Deposits by Zone, 2021/22 - 2025/26
Percent; 100% = banks lend exactly what they collect locally. Source: BoT Tables 6.1, 6.2; TICGL calc.
Who Funds Whom? Loans Minus Deposits, End-June 2026
TZS billion. Positive (amber) = zone lends more than it collects; negative (teal) = zone collects more than it lends. TICGL calc.
Why the gap exists: five drivers, ranked by how well the data support them
Driver
What the data show
Evidence
Where
1. Thin local deposit base
Deposits are 5-14% of zone GDP outside Dar es Salaam (79% in Dar es Salaam). Southern Highlands deposits grew 1.7% a year since 2021/22 against GDP growth of 9.6%.
Measured
Tab 2
2. Deposits are booked where institutions sit, not where activity happens
Dar es Salaam has 17.0% of GDP but 62.8% of deposits (3.7 times its weight), 88.2% of tax collections and 85.4% of port cargo.
Measured, with an inferred mechanism
Tab 3
3. Weak local savings capacity in farm zones
Food output fell 8.8% in Central and 11.3% in Southern Highlands; their deposits grew 0.9% and fell 1.4%. Southern Highlands cross-border exports fell from TZS 6.6 tn to 1.1 tn since 2022/23.
Measured; causation not proven
Tab 4
4. Credit demand skewed to households and farming
Personal loans are 49% of lending in Central and Southern Highlands and 66% in South Eastern; agriculture adds 33% in Central.
Measured
Tab 4
5. Funding by bank head offices across zones
The four borrower zones need TZS 4.65 tn more than they collect, and Dar es Salaam plus Northern collect TZS 8.87 tn more than they lend: the arithmetic fits an internal funding flow.
Inferred; the report does not show bank-level flows
Tab 3, 5
Source: BoT Tables 1.1, 1.2, 3.x, 6.1-6.3 and Annex 5; TICGL calc. "Measured" means the figure is in the report; "inferred" means it follows from the figures but the report does not state it.
What it means
A loan-to-deposit ratio above 100% is not the same as over-borrowing. Loans are only 8-20% of GDP in the four borrower zones, compared with 59% in Dar es Salaam. These zones are under-banked, and the gap reflects missing local savings as much as heavy borrowing.
The risk sits in two zones. Central and Southern Highlands combine a ratio above 135%, deposits that barely grew, inflation above 5% and loan books dominated by household and farm credit. Together they are the only zones where all four risk flags in Tab 5 are switched on.
Six-month path. If each zone repeats its 2025/26 growth rates, Southern Highlands moves to about 187% and Central to 154% by March 2027 (Tab 6). If deposit growth halves, Lake also rises to 146%. Dar es Salaam stays below 80% in every case.
Policy angle. The issue is not lending that is too high; it is deposit mobilisation that is too low in the zones where lending is rising fastest, and the absence of published credit-quality data by zone.
01 - The Gap in NumbersDeposits, Loans and the Net Funding Position by Zone
The six zones in the Bank of Tanzania report hold TZS 50.0 trillion of deposits and TZS 45.8 trillion of loans (both exclude Zanzibar). The national loan-to-deposit ratio is 92%, which hides two very different groups: Dar es Salaam and Northern, where deposits exceed loans, and the other four zones, where the reverse is true. The table sets out the stocks, growth rates and net position.
Zone (TZS bn)
Deposits 25/26
Loans 25/26
Loans / deposits 25/26
Loans / deposits 21/22
Loans minus deposits
Deposit growth
Loan growth
Share of deposits
Share of loans
Central
4,498.9
6,244.4
139%
91%
1,746
+0.9%
+16.0%
9.0
13.6
Dar es Salaam
31,412.2
23,578.9
75%
76%
-7,833
+32.0%
+18.7%
62.8
51.5
Lake
5,254.2
6,693.9
127%
119%
1,440
+32.2%
+39.0%
10.5
14.6
Northern
5,361.9
4,322.6
81%
72%
-1,039
+22.6%
+23.6%
10.7
9.4
South Eastern
1,604.4
2,056.3
128%
123%
452
+32.3%
+25.7%
3.2
4.5
Southern Highlands
1,893.8
2,906.1
153%
51%
1,012
-1.4%
+28.1%
3.8
6.3
Total (excl. Zanzibar)
50,025.3
45,802.1
92%
80%
-4,223
+25.9%
+22.3%
100.0
100.0
Source: Banks via BoT Tables 6.1 and 6.2; ratios and net positions are TICGL calc. on zone-booked stocks at end-June 2026 (provisional).
The ratio has risen in Central from 91% to 139% and in Southern Highlands from 51% to 153% over four years, while Dar es Salaam has stayed around 75-83% and Northern has crept up from 72% to 81%. South Eastern and Lake started above 100% and have stayed there (123% to 128%, and 119% to 127%), so for them the gap is a long-standing feature, not a new one. The widening is therefore a Central and Southern Highlands story: loans in Central tripled (x2.95) while deposits did not double (x1.93), and in Southern Highlands loans rose x3.19 while deposits rose only x1.07.
Net Position by Zone, 2021/22 - 2025/26
TZS billion, loans minus deposits. Above zero = zone lends more than it collects. TICGL calc. from BoT Tables 6.1, 6.2
Loans minus deposits (TZS bn)
2021/22
2022/23
2023/24
2024/25
2025/26p
Central
-212
101
722
924
1,746
Dar es Salaam
-3,919
-4,605
-3,604
-3,939
-7,833
Lake
444
936
900
841
1,440
Northern
-863
-1,312
-850
-875
-1,039
South Eastern
192
335
497
424
452
Southern Highlands
-859
-807
-956
348
1,012
All zones
-5,217
-5,353
-3,292
-2,277
-4,223
Source: TICGL calc. from BoT Tables 6.1 and 6.2. Negative = deposits exceed loans.
1.2 The Southern Highlands break in 2024/25
Southern Highlands loans jumped from TZS 1,060.8 billion to TZS 2,268.8 billion in 2024/25 (+114%) while deposits fell by TZS 96.2 billion, taking the ratio from 53% to 118% in a single year. A move of this size looks more like a change in where large loans are booked, or a reclassification, than a sudden rise in household borrowing. It should be confirmed with the Bank of Tanzania before it is used to argue that the zone has become over-indebted. The 2025/26 ratio of 153% is the result of that step plus a further 28.1% rise in loans.
TICGL/TERI reading
Dar es Salaam collects TZS 7.8 trillion more than it lends and Northern TZS 1.0 trillion more; the four borrower zones lend TZS 4.65 trillion more than they collect. That leaves TZS 4.2 trillion of deposits nationwide that were not lent at all. The report does not say where it sits; the usual candidates are reserves and government securities, which links this page to our analysis of the crowding-out problem.
02 - Driver 1A Thin Local Deposit Base
The first and best-supported explanation is that outside Dar es Salaam there is simply not much deposit money booked locally. Depositing needs income left over after consumption, a bank within reach, and an institution that holds its accounts in that zone. All three are weaker in the four borrower zones, and in two of them the deposit base has barely moved in four years.
Zone
GDP per person (TZS m)
Deposits per person (TZS '000)
Loans per person (TZS '000)
Deposits / GDP
Loans / GDP
Deposit growth p.a. 21/22-25/26
GDP growth p.a. 2021-25
Agents per 10,000 people
Central
2.46
349
485
14.2%
19.7%
17.8%
9.8%
20.5
Dar es Salaam
6.78
5,347
4,014
78.9%
59.2%
18.1%
9.7%
102.1
Lake
2.89
249
317
8.6%
11.0%
23.2%
9.7%
18.4
Northern
4.21
560
452
13.3%
10.7%
14.9%
9.7%
29.3
South Eastern
3.31
220
282
6.6%
8.5%
18.2%
9.1%
24.4
Southern Highlands
3.99
203
312
5.1%
7.8%
1.7%
9.6%
26.1
Mainland
3.54
757
693
21.4%
19.6%
17.3%
9.6%
29.6
Source: BoT Tables 1.1, 1.2, 6.1, 6.2, 6.4; population implied by GDP / GDP per capita; per-person and growth figures are TICGL calc. Excludes Zanzibar. Deposits and loans are booked by bank location, not by the residence of the customer.
Deposits and Loans Relative to the Local Economy
Percent of 2025 zone GDP. Source: BoT Tables 1.1, 6.1, 6.2; TICGL calc.
Deposits Have Not Kept Pace With the Economy
Compound annual growth, 2021/22 to 2025/26 (deposits, loans) and 2021 to 2025 (GDP). TICGL calc.
2.1 Income and savings: richer zones do not automatically deposit more
Deposits per person range from TZS 5,347,000 in Dar es Salaam to TZS 203,000 in Southern Highlands, a gap of about 26 times, against a gap in GDP per person of only 1.7 times (TZS 6.78 million against TZS 3.99 million). Southern Highlands and Northern are richer per head than Lake, Central and South Eastern, yet Northern holds nearly three times the deposits per person of Southern Highlands (TZS 560,000 against 203,000). Income alone does not explain where deposits sit; the structure of the local economy does. Much of the output of Southern Highlands and Lake is farm, forest and mining value that is sold to buyers, processors and exporters, and where their accounts are held is not shown in the report.
Output Per Person vs Deposits Per Person
x = GDP per person (TZS million); y = deposits per person (TZS thousand); bubble size = population. Source: BoT Tables 1.1, 1.2, 6.1; TICGL calc.
2.2 Reach: bank agents and access
Agent banking is the main way banks extend deposit-taking beyond branches. Dar es Salaam has 102 agents per 10,000 people; the other zones have between 18 (Lake) and 29 (Northern). Lake, with 21.1 million people and the largest economy, has the lowest agent density. The agent network grew 25.6% nationally in 2025/26, but more points of contact do not guarantee more money held locally: in Central the number of agents grew 29.7% while bank deposits grew 0.9%.
Bank Agents per 10,000 People, 2025/26
Agents per 10,000 residents. Source: BoT Table 6.4; TICGL calc. using implied population
What this driver explains
It explains the level of the ratio in all four borrower zones: with deposits equal to only 5-14% of GDP, even modest local lending pushes the ratio above 100%. It does not on its own explain the rise in Central and Southern Highlands; Tabs 3 and 4 add the other pieces.
03 - Driver 2Where Money Is Booked: Dar es Salaam as the Deposit Centre
The second explanation is about accounting geography. The Bank of Tanzania reports deposits and loans by the zone in which the bank records them, which is where the branch, head office or treasury sits, not necessarily where the customer lives or earns. Dar es Salaam is where the Government, large companies, many banks' head offices, the port and the Revenue Authority are located, so deposits from all over the country are booked there.
How Much of Tanzania Sits in Dar es Salaam?
Dar es Salaam share of the mainland total, percent. Source: BoT Tables 1.1, 1.2, 3.x, 4.1, 5.x, 6.1, 6.2; TICGL calc.
Dar es Salaam share of mainland total
%
Population (implied)
8.9
GDP, 2025
17.0
Manufactured output, 2025/26
47.4
Loans, end-June 2026
51.5
Deposits, end-June 2026
62.8
Port cargo, 2025/26
85.4
Tax collections, 2025/26
88.2
Source: TICGL calc. from BoT Tables 1.1, 1.2, 3.x, 4.1, 5.x, 6.1 and 6.2. Population is implied by GDP / GDP per capita.
3.1 Deposits are worth 3.7 times more to Dar es Salaam than its economy suggests
Dar es Salaam produces 17.0% of mainland GDP and holds 62.8% of deposits: a deposit-to-GDP weight of 3.7. Lake produces 26.1% of GDP and holds 10.5% of deposits (0.40); Southern Highlands 15.9% and 3.8% (0.24); South Eastern 10.3% and 3.2% (0.31); Central 13.5% and 9.0% (0.66); Northern 17.2% and 10.7% (0.62). Loans are less concentrated: Dar es Salaam has 51.5% of loans, a weight of 3.0. The 11-point gap between its deposit share (62.8%) and its loan share (51.5%) is the mirror image of the borrower zones' funding gap, together with the TZS 4.2 trillion that is not lent anywhere.
Share of GDP, Deposits and Loans by Zone
Percent of mainland total, 2025 (GDP) and end-June 2026 (deposits and loans). Source: BoT Tables 1.1, 6.1, 6.2; TICGL calc.
Zone
Share of GDP, %
Share of deposits, %
Share of loans, %
Deposit weight (x GDP share)
Loan weight (x GDP share)
Central
13.5
9.0
13.6
0.66
1.01
Dar es Salaam
17.0
62.8
51.5
3.69
3.03
Lake
26.1
10.5
14.6
0.40
0.56
Northern
17.2
10.7
9.4
0.62
0.55
South Eastern
10.3
3.2
4.5
0.31
0.44
Southern Highlands
15.9
3.8
6.3
0.24
0.40
Source: TICGL calc. from BoT Tables 1.1, 6.1 and 6.2. A weight of 1.0 means the zone holds deposits (or loans) in proportion to its GDP.
3.2 Productive credit also sits in Dar es Salaam
Table 6.3 of the report splits lending by activity and zone. Dar es Salaam accounts for 70% of manufacturing credit, 81% of transport and communication, 80% of building and real estate, 82% of health, education, utilities and finance, and 89% of "other" lending, but only 30% of personal loans and 13% of agriculture. The credit that funds factories, trucks and buildings is booked where the head offices are; the credit that reaches households and farms is the part left for the other zones.
Dar es Salaam Share of National Lending by Activity
Percent of each activity's national total booked in Dar es Salaam, 2025/26. Source: BoT Table 6.3; TICGL calc.
Source note
The zone columns of Table 6.3 add to 99.7% of national lending and place 47.3% of it in Dar es Salaam, whereas Table 6.2 (loans by booking zone) gives 51.5%. The two tables are not on exactly the same basis, so this page uses Table 6.2 for the loan-to-deposit analysis and Table 6.3 only for lending mix, with each zone's mix computed on its own column total.
3.3 What the report cannot show: the inter-zone funding mechanism
The arithmetic is consistent with a simple story. Dar es Salaam and Northern collect TZS 8.87 trillion more than they lend; the four borrower zones lend TZS 4.65 trillion more than they collect; so a flow of about TZS 4.65 trillion must be moving from deposit-rich booking centres to branches that lend locally, most likely inside banks through head-office treasury and inter-branch accounts. The report has no bank-level or inter-branch data, so this cannot be confirmed from it. What can be said is that the ratio above 100% is a bookkeeping outcome of a network that collects centrally and lends regionally, not a sign that those zones are lending money they do not have.
What this driver explains
It explains why the national picture is balanced (92%) while four zones sit above 100%, and why Dar es Salaam's deposit weight is so large. It also explains why a zone's ratio does not by itself measure its credit risk: it measures how much of a bank's funding comes from outside the zone.
04 - Drivers 3 and 4Farm Incomes, Cross-Border Trade and What the Borrowing Is For
The third and fourth explanations are about who is borrowing and how much they earn. Two zones, Central and Southern Highlands, combine rising loans with weak farm incomes and, in the case of Southern Highlands, a collapse in recorded cross-border trade. The remaining borrower zones, South Eastern and Lake, borrow mainly for consumption and trade respectively.
4.1 Farm incomes and local deposits move together in the zones that matter
Food-crop production fell 8.8% in Central and 11.3% in Southern Highlands in 2025/26, the only two zones with a decline. In the same year nominal GDP grew 10.3% and 11.0% there, so recorded activity kept pace while physical output did not. The deposit data tell a clearer story: Central deposits grew 0.9% and Southern Highlands deposits fell 1.4%, against 22.6% to 32.3% in the other four zones. Loans kept growing, by 16.0% and 28.1%.
Zone
Food-crop output 25/26
Nominal GDP 2025
Deposit growth
Loan growth
Inflation Jun-26
Food inflation Jun-26
Central
-8.8%
+10.3%
+0.9%
+16.0%
5.2%
5.0%
Dar es Salaam
+17.1%
+10.0%
+32.0%
+18.7%
6.2%
6.3%
Lake
+41.2%
+11.0%
+32.2%
+39.0%
3.0%
2.2%
Northern
+9.0%
+9.8%
+22.6%
+23.6%
3.3%
3.8%
South Eastern
+14.1%
+10.1%
+32.3%
+25.7%
2.6%
2.3%
Southern Highlands
-11.3%
+11.0%
-1.4%
+28.1%
8.0%
15.1%
Source: BoT Tables 3.1 (food crops), 1.1 (GDP), 6.1, 6.2; Annex 4 (inflation). Growth rates are TICGL calc.; food inflation is year-on-year, June 2026.
4.2 Southern Highlands: trade, deposits and a loan jump
Recorded cross-border exports from Southern Highlands fell from TZS 6.45 trillion in 2021/22 and 6.59 trillion in 2022/23 to TZS 1.28 trillion in 2023/24, and have stayed near that level (TZS 1.09 trillion in 2025/26). The zone's deposits, which had been growing slowly, stopped growing in the same period: TZS 2,016.9 billion in 2023/24, 1,920.7 billion in 2024/25 and 1,893.8 billion in 2025/26. The timing is consistent with a link between lower trade earnings and a smaller local deposit base, but the report does not prove one. Loans moved the other way after 2023/24 (see the 2024/25 step in Tab 1).
Southern Highlands: Deposits vs Cross-Border Exports
TZS billion. Bars = bank deposits (left axis); line = recorded cross-border exports (right axis). Source: BoT Tables 5.x, 6.1
4.3 What the borrowing is for
Within each zone's own lending, personal loans take 49% in Central, 49% in Southern Highlands, 66% in South Eastern, 40% in Lake, 44% in Northern and 22% in Dar es Salaam. Agriculture takes 33% of Central lending and 23% of Southern Highlands lending, against 4% in Dar es Salaam. The report does not say what the personal loans fund (salary-backed credit, housing, consumption or small business), so we cannot tell how many are productive. What the data do show is that credit outside Dar es Salaam is mainly household and farm credit, which depends on incomes that were under pressure from food output and prices in 2025/26.
What Each Zone Borrows For: Mix of Bank Lending, 2025/26
Percent of the zone's own lending. Source: BoT Table 6.3; TICGL calc. on each zone's column total
Zone
Personal
Trade
Agriculture
Manufacturing
Transport, building & real estate
Mining & hotels
Services, finance & other
Central
49%
6%
33%
3%
5%
1%
3%
Dar es Salaam
22%
17%
4%
12%
21%
5%
19%
Lake
40%
22%
18%
6%
5%
7%
3%
Northern
44%
14%
13%
10%
6%
11%
3%
South Eastern
66%
17%
11%
0%
4%
0%
2%
Southern Highlands
49%
14%
23%
3%
3%
4%
3%
Source: BoT Table 6.3; TICGL calc. Zone mix is computed on each zone's own column total (which does not equal the Table 6.2 loan share; see the Tab 3 source note).
4.4 Loans are growing faster than the economy, which is partly a good sign
Loans grew between 16.0% and 39.0% in every zone, against nominal GDP growth of 9.8% to 11.0%. Where credit starts from 8-11% of GDP, as in Lake, South Eastern and Southern Highlands, faster growth than the economy is what financial deepening looks like. Lake is the clearest case: loans +39.0%, deposits +32.2%, with trade (22% of its lending) and mining (7%) both active and the zone's recorded cross-border exports up 75.6% to TZS 12.8 trillion. Deposits there are growing nearly as fast as loans (32.2% against 39.0%), so its ratio has risen only 6 points since 2024/25.
Credit Growth vs Economic Growth by Zone
Percent growth in 2025/26 (loans) and 2025 (nominal GDP). Source: BoT Tables 1.1, 6.2; TICGL calc.
What these drivers explain
They explain why the ratio rose in Central and Southern Highlands (weak farm incomes, flat deposits, loans still growing) and why it is a long-standing feature in South Eastern and Lake (consumption and trade credit on a small deposit base). They do not tell us whether borrowers are repaying; the report has no non-performing-loan data by zone.
05 - Economic EffectsWhat the Gap Does to Growth, Prices and Risk
What does a persistent gap between local lending and local deposits do to the economy? The effects run through four channels: funding dependence, the squeeze on borrowers when prices rise, the allocation of credit between productive and consumption uses, and the unevenness of financial deepening. We then combine four observable conditions into a simple risk screen for each zone.
5.1 Four channels
Funding dependence. A zone that lends TZS 0.5-1.7 trillion more than it collects is relying on funds booked elsewhere. If banks tighten liquidity or reprice head-office funding, the first branches to ration credit are those with a thin local deposit base. This makes regional credit more cyclical than credit in Dar es Salaam.
Price squeeze on borrowers. Fuel prices rose sharply in April-June 2026, and inflation reached 8.0% in Southern Highlands and 5.2% in Central by June. Household and farm borrowers on fixed instalments see real incomes fall just when loans are largest relative to local deposits. The report contains no zonal data on arrears, so the effect cannot be measured, only flagged.
Allocation of credit. Productive lending (manufacturing, transport, building) is concentrated in Dar es Salaam, so the capital that raises output per worker is concentrated with it. Credit to the other zones is dominated by personal and farm loans, which support consumption and seasonal working capital more than they raise capacity.
Uneven deepening. Loans are 59% of GDP in Dar es Salaam and 8-20% elsewhere. Even the four borrower zones are under-banked relative to the economic centre; the problem is not too much regional credit but too little regional saving to support more of it.
5.2 A four-flag risk screen
For each zone we check four conditions that can be read directly from the report: loans above deposits; loans growing at least 10 percentage points faster than deposits; June 2026 inflation above 5%; and personal plus agricultural lending above 70% of the zone's lending. The number of flags is a count, not a credit rating, and it says nothing about actual repayment performance.
Zone
Loans / deposits
Loan minus deposit growth
Inflation Jun-26
Personal + farm share
Flag 1
Flag 2
Flag 3
Flag 4
Flags on
Central
139%
+15.1 pts
5.2%
82%
Yes
Yes
Yes
Yes
4
Dar es Salaam
75%
-13.3 pts
6.2%
26%
No
No
Yes
No
1
Lake
127%
+6.8 pts
3.0%
58%
Yes
No
No
No
1
Northern
81%
+1.0 pts
3.3%
56%
No
No
No
No
0
South Eastern
128%
-6.7 pts
2.6%
77%
Yes
No
No
Yes
2
Southern Highlands
153%
+29.5 pts
8.0%
72%
Yes
Yes
Yes
Yes
4
Flags: (1) loans/deposits above 100%; (2) loan growth exceeds deposit growth by more than 10 points; (3) June 2026 inflation above 5%; (4) personal plus agriculture above 70% of zone lending. Source: BoT Tables 6.1-6.3, Annex 4; TICGL calc.
Funding Gap vs Inflation, With Loan Book Size
x = loans as % of deposits; y = inflation, June 2026 (%); bubble size = loans outstanding. Source: BoT Tables 6.2, 6.1, Annex 4; TICGL calc.
Share of Zone Lending That Is Personal or Farm Credit
Percent of the zone's own lending. Source: BoT Table 6.3; TICGL calc.
Central and Southern Highlands (4 flags). High ratio, loan growth far ahead of deposits, inflation above 5% and a household-and-farm loan book. These are the two zones to watch first in the next BoT zonal release.
South Eastern (2 flags). Ratio of 128% and a 77% personal-and-farm book, but deposits grew 32.3% (faster than loans) and inflation is the lowest of any zone (2.6%).
Lake (1 flag). Above 100%, but deposits and loans are growing together, inflation is 3.0% and trade and mining are well represented in lending.
Dar es Salaam (1 flag). The only flag is inflation (6.2%). Its funding position is the strongest, which is why it can subsidise the rest.
Northern (0 flags). A balanced zone: 81% ratio, deposits and loans growing in step, inflation 3.3%.
What the screen cannot say
The report has no non-performing-loan, interest-rate or loan-size data by zone. A high-flag zone is where stress is most likely to appear first, not where it has appeared. Asking the Bank of Tanzania for zonal NPL data would turn this screen into a measured risk map.
06 - Six-Month OutlookScenarios to March 2027, Watch-List, Policy and Entry Screen
This tab projects each zone's loans and deposits to end-March 2027, nine months after the June 2026 base (a factor of (1+g) to the power 0.75). The three scenarios are mechanical and transparent, so that readers can reproduce them from Tab 1: Momentum (each zone repeats its 2025/26 growth in loans and deposits), Parallel growth (loans and deposits both grow 20% a year in every zone, so ratios stay where they are) and Savings squeeze (loans keep their 2025/26 pace but deposit growth halves, for example because higher living costs cut saving). They are scenarios, not forecasts of record.
Zone
Loans / deposits Jun-26
Mar-27 Momentum
Mar-27 Parallel
Mar-27 Squeeze
Loans minus deposits, Momentum (TZS bn)
Loans minus deposits, Squeeze (TZS bn)
Central
139%
154%
139%
155%
2,451
2,467
Dar es Salaam
75%
69%
75%
76%
-11,862
-8,292
Lake
127%
132%
127%
146%
2,091
2,693
Northern
81%
81%
81%
87%
-1,181
-744
South Eastern
128%
123%
128%
136%
461
646
Southern Highlands
153%
187%
153%
186%
1,625
1,615
All zones
92%
89%
92%
97%
-6,415
-1,615
Source: TICGL calc. from BoT Tables 6.1 and 6.2 (June 2026 base). Excludes Zanzibar. Momentum extends 2025/26 growth rates for nine months and is a mechanical extrapolation, not an expectation: the Southern Highlands result in particular reflects the 2024/25 loan step and a falling deposit base.
Loans as a Percentage of Deposits: June 2026 and End-March 2027
Percent, by zone, under three scenarios. TICGL calc.
Funding Gap by Zone, June 2026 vs March 2027 (Momentum)
TZS billion, loans minus deposits. TICGL calc.
6.1 Reading the scenarios
Under Momentum the ratio rises where deposits are weakest. Southern Highlands moves from 153% to about 187% and Central from 139% to 154%; Lake goes from 127% to 132%. South Eastern drifts down from 128% to 123% and Dar es Salaam from 75% to 69% because their deposits are growing faster than loans.
Parallel growth freezes the picture. If banks and savers grow together, no zone gets worse and the four borrower zones stay above 100%. This is the benign case; it needs deposit growth in Central and Southern Highlands to jump from near zero to 20%, which the 2025/26 data do not suggest.
A savings squeeze is a Lake and Northern story as well. If deposit growth halves, Lake rises to 146% and Northern from 81% to 87%, so the fuel-price shock can push the funding gap into zones that look comfortable today.
Nationally the effect is small. The all-zone ratio would be 89% under Momentum, 92% under Parallel growth and 97% under a squeeze, against 92% in June 2026. The story is about distribution between zones, not the system total.
6.2 What to watch between October 2026 and March 2027
Indicator
Latest
Reassuring signal
Stress signal
Deposit growth in Central and Southern Highlands
+0.9% and -1.4% in 2025/26
Still near zero by the next zonal report
Ratio rises toward the Momentum case
Inflation in Southern Highlands, Dar es Salaam and Central
8.0%, 6.2%, 5.2% (June 2026)
Base-case path eases to 4.4%, 5.5% and 3.2% by March 2027 (zonal economy report, Tab 7)
Stress path keeps all three above 5%
Harvest and food prices in Central and Southern Highlands
Output -8.8% and -11.3%; NFRA purchases -68.5%
A recovery in output and NFRA buying
A second poor season
Zonal non-performing loans
Not published in the report
Publication, and stable ratios
No data: treat as a risk until shown otherwise
Southern Highlands loan booking
Loans +114% in 2024/25
Bank of Tanzania clarification
Further steps without a matching deposit change
Fuel and transport costs
Pump prices up sharply in April-June 2026 (approximate, from Chart 1.2)
Prices ease as the harvest arrives
Prices stay high through the dry season
Source: BoT zonal report and TICGL calc.
6.3 Policy options
Publish zonal credit quality. Non-performing loans, average loan size and interest rates by zone would show whether a ratio above 100% is a risk or just a funding pattern.
Mobilise deposits where lending is growing. Link agent-banking incentives to balances held, not only to transactions, in Central, Southern Highlands and Lake.
Share the risk on farm credit. Credit guarantees and crop insurance for lending in zones with falling food output (Central, Southern Highlands), so that a poor season does not turn into arrears.
Route crop and trade proceeds through local accounts. Cooperative and warehouse-receipt payments that settle into zone-based accounts would keep more of the value chain's deposits where the output is produced.
Watch consumer credit. Personal loans are two-thirds of South Eastern lending and about half of Central and Southern Highlands lending; affordability checks matter most when inflation is rising.
Disclose inter-zone funding. A simple statistic on bank funding flows between zones would settle the question the report cannot answer.
6.4 What it means for investors and lenders: a zone entry screen
Zone
Deposits per person (TZS '000)
Loans per person (TZS '000)
Loans / deposits
Agents per 10,000
Risk flags
TICGL/TERI reading
Central
349
485
139%
20
4
Deposit mobilisation, agri-credit with risk-sharing, livestock and tobacco value chains; verify repayment before scaling consumer lending.
Dar es Salaam
5,347
4,014
75%
102
1
Deep, institution-led market with the lowest ratio; competition is high and price pressure is the highest of any zone.
Lake
249
317
127%
18
1
Trade- and mining-linked SME finance, payments and cold-chain; lowest agent density (18 per 10,000) for the largest economy.
Northern
560
452
81%
29
0
Balanced funding position; hospitality and tourism supply chains (11% of its lending).
South Eastern
220
282
128%
24
2
Fast agent growth and low inflation; consumer-credit discipline needed (66% personal lending).
Southern Highlands
203
312
153%
26
4
Deposit gathering and storage-linked finance; confirm the 2024/25 loan step before extending credit.
Source: BoT Tables 6.1, 6.2, 6.4 and TICGL calc. as in Tabs 2 and 5. The reading column is TICGL/TERI's interpretation of these indicators, not a recommendation to lend or invest.
Feasibility studies
Full feasibility for branches, agent networks, microfinance and fintech products by zone, with demand sized on deposits and loans per person and local income.
Financial models (NPV, IRR, DSCR) stress-tested for fuel, inflation and deposit-growth shocks like the scenarios above.
Market entry advisory
Zone screening against the indicators in this report, entry-mode choice (partnership, agent model, own branch) and licensing support.
Introductions to local institutions and partners, from first meeting to start-up.
Market research and economic intelligence
Regional credit-demand studies, borrower surveys and price benchmarking.
Scenario updates with each Bank of Tanzania and NBS release, through TERI.
Talk to TICGL/TERI
Request a feasibility, market-entry or market-research scoping call for a financial-services or regional-credit project, or a briefing on this analysis.
Source report. Bank of Tanzania, Consolidated Zonal Economic Performance Report for the Quarter Ending June 2026, Vol. 11 No. 2: Tables 1.1-1.2 (GDP, GDP per capita), 3.x (food crops), 4.1 (tax), 5.x (cross-border trade, ports, manufacturing), 6.1-6.4 (deposits, loans, lending by activity, agent banking) and Annexes 3-5 (CPI, agents). Underlying sources cited in the report: banks, the National Bureau of Statistics, TRA, TPA and the Ministry of Agriculture. TICGL calculations. Loan-to-deposit ratio = zone loans / zone deposits; net position = loans minus deposits; deposits and loans per person and as a share of GDP use population implied by GDP / GDP per capita; agents per 10,000 = agents / implied population; the lending mix by zone is Table 6.3 divided by each zone's own column total (the columns add to 99.7% and place 47.3% of lending in Dar es Salaam, against 51.5% in Table 6.2, so the two tables are not on exactly the same basis); the four-flag screen counts conditions in Tab 5. Scenarios. End-March 2027 stocks = June 2026 stocks x (1+g)^0.75, with g = 2025/26 growth (Momentum), 20% for both loans and deposits (Parallel growth) and loan growth at 2025/26 pace with deposit growth halved (Savings squeeze). Limits. Provisional data; zone-booked figures; no zonal NPL, interest-rate or bank-level data; the Southern Highlands 2024/25 loan step is unexplained; mechanical scenarios are not forecasts.
Bank of Tanzania, Consolidated Zonal Economic Performance Report, quarter ending June 2026 (Vol. 11 No. 2), Dodoma, 2026.
National Bureau of Statistics: regional GDP and zonal CPI as reproduced in the report.
08 - Quick AnswersFrequently Asked Questions
Why do some Tanzanian zones lend more than they collect in deposits?
Four things line up in the Bank of Tanzania data. Outside Dar es Salaam deposits are only 5-14% of zone GDP (79% in Dar es Salaam); deposits are booked where banks' head offices and institutions sit, so Dar es Salaam holds 62.8% of deposits with 17.0% of GDP; farm incomes were weak in Central and Southern Highlands, where deposits barely grew; and credit outside Dar es Salaam is mostly personal and farm lending. The gap is probably funded inside banks by money moving from Dar es Salaam, though the report does not show bank-level flows.
Which zones have loans above deposits?
At end-June 2026 loans were 153% of deposits in Southern Highlands, 139% in Central, 128% in South Eastern and 127% in Lake. Northern was at 81% and Dar es Salaam at 75%. The national ratio was 92%.
Is a loan-to-deposit ratio above 100% a sign of over-borrowing?
Not by itself. Loans are only 8-20% of GDP in the four borrower zones, against 59% in Dar es Salaam, so these zones are under-banked. The ratio shows how much bank funding comes from outside the zone. The risk is concentrated in Central and Southern Highlands, where loans grew far faster than deposits, inflation is above 5% and lending is mainly household and farm credit. The report has no zonal non-performing-loan data.
Where does the extra money in Dar es Salaam go?
Dar es Salaam and Northern hold TZS 8.9 trillion more deposits than they lend. About TZS 4.65 trillion of that is consistent with funding the four borrower zones; the remaining TZS 4.2 trillion is not lent anywhere in the data, and is most likely held in reserves and government securities, although the report does not say.
What is the outlook for the gap between October 2026 and March 2027?
If every zone repeats its 2025/26 growth, the Southern Highlands ratio rises to about 187% and Central to 154%, while Dar es Salaam falls to 69%. If loans and deposits both grow 20% a year, ratios stay where they are. If deposit growth halves, Lake rises to 146%. The national ratio stays between 89% and 97% in all three cases, so the issue is distribution between zones.
Why did Southern Highlands deposits fall in 2025/26?
The report does not say. Deposits were TZS 2,016.9 billion in 2023/24, 1,920.7 billion in 2024/25 and 1,893.8 billion in 2025/26, after recorded cross-border exports from the zone fell from TZS 6.6 trillion in 2022/23 to 1.3 trillion in 2023/24. Food output also fell 11.3% in 2025/26. The timing fits, but it is not proof of a link.
09 - Explore MoreTICGL Economic: Related Insights & Tools
Companion Report
Tanzania's Economy by Zone, 2025/26: Six-Month Outlook
The full zonal report this analysis builds on: GDP, prices, food, industry, tourism, trade and revenue.
Kwa nini kanda zinakopesha zaidi ya zinavyokusanya? Kwa mujibu wa Ripoti ya Benki Kuu ya Tanzania (BoT) ya Utendaji wa Kiuchumi wa Kanda (Juni 2026), mwishoni mwa 2025/26 mikopo ilikuwa asilimia 153 ya amana Nyanda za Juu Kusini, asilimia 139 Kati, asilimia 128 Kusini Mashariki na asilimia 127 Ziwa. Dar es Salaam ina asilimia 62.8 ya amana zote lakini inakopesha asilimia 75 tu ya amana zake. Kanda nne zinakopesha TZS trilioni 4.65 zaidi ya zinavyokusanya, wakati Dar es Salaam na Kaskazini zinakusanya TZS trilioni 8.87 zaidi ya zinavyokopesha.
Sababu 1: Amana ndogo za ndani. Nje ya Dar es Salaam, amana ni asilimia 5-14 ya pato la kanda (Dar es Salaam: asilimia 79). Amana za Nyanda za Juu Kusini zimekua asilimia 1.7 tu kwa mwaka tangu 2021/22, wakati pato lilikua asilimia 9.6.
Sababu 2: Fedha zinarekodiwa mahali taasisi zilipo. Dar es Salaam ina asilimia 17 ya pato lakini asilimia 62.8 ya amana, asilimia 88.2 ya kodi na asilimia 85.4 ya shehena ya bandari. Mikopo ya viwanda (asilimia 70) na usafirishaji (asilimia 81) pia inarekodiwa Dar es Salaam.
Sababu 3: Mapato dhaifu ya kilimo. Uzalishaji wa chakula ulipungua asilimia 8.8 Kati na asilimia 11.3 Nyanda za Juu Kusini; amana zilikua asilimia 0.9 na zilishuka asilimia 1.4, wakati mikopo iliongezeka asilimia 16.0 na asilimia 28.1. Mauzo ya nje ya mipakani ya Nyanda za Juu Kusini yalishuka kutoka TZS trilioni 6.6 hadi trilioni 1.1.
Sababu 4: Mikopo ya matumizi na kilimo. Mikopo binafsi ni takriban asilimia 49 ya mikopo ya Kati na Nyanda za Juu Kusini na asilimia 66 Kusini Mashariki; kilimo kinaongeza asilimia 33 Kati.
Sababu 5 (hitimisho la kimantiki): Pengo linafadhiliwa ndani ya benki kwa fedha kutoka Dar es Salaam. Ripoti haionyeshi mtiririko wa benki, kwa hiyo hili halijathibitishwa.
Je, ni hatari? Uwiano zaidi ya asilimia 100 si lazima uwe kukopa kupita kiasi: mikopo ni asilimia 8-20 tu ya pato katika kanda hizo nne (Dar es Salaam: asilimia 59). Hatari iko Kati na Nyanda za Juu Kusini, ambako mikopo inakua haraka kuliko amana, mfumuko ni zaidi ya asilimia 5 na mikopo ni ya kaya na kilimo. Ripoti haina takwimu za mikopo chechefu kwa kanda.
Miezi sita ijayo (Oktoba 2026 - Machi 2027): Kama kila kanda itaendelea na kasi ya 2025/26, uwiano wa Nyanda za Juu Kusini unafika takriban asilimia 187 na Kati asilimia 154. Amana zikikua nusu ya kasi, Ziwa linafika asilimia 146. Uwiano wa taifa unabaki kati ya asilimia 89 na 97, kwa hiyo tatizo ni mgawanyo kati ya kanda.
Mapendekezo: (1) Kuchapisha mikopo chechefu kwa kanda; (2) kuhamasisha amana katika kanda zinazokopa; (3) dhamana za mikopo ya kilimo na bima ya mazao; (4) malipo ya mazao kupitia akaunti za kanda; (5) kufuatilia mikopo ya matumizi wakati wa mfumuko; (6) kuweka wazi mtiririko wa fedha kati ya kanda. TICGL/TERI hutoa upembuzi yakinifu (feasibility), ushauri wa kuingia sokoni na utafiti wa soko kwa huduma za fedha kwa kanda.
Hitimisho: Pengo la mikopo na amana linaonyesha benki zinakusanya katikati na kukopesha pembezoni. Tatizo si mikopo mingi, bali akiba ya ndani ndogo katika kanda ambako mikopo inakua kwa kasi.
Uwiano Juni 2026: Nyanda za Juu Kusini 153% · Kati 139% · Kusini Mashariki 128% · Ziwa 127%
Dar es Salaam: amana 62.8% · pato 17.0% · kodi 88.2%
Hali ya kasi Machi 2027: Nyanda za Juu Kusini ~187%, Kati ~154%
Chanzo: Benki Kuu ya Tanzania, Ripoti ya Utendaji wa Kiuchumi wa Kanda (Juni 2026); TERI/TICGL, Oktoba 2026. Kwa maelezo zaidi: economist@ticgl.com.
Tanzania Economy by Zone 2025/26: Six-Month Outlook | TICGL/TERI
TICGL/TERI Economy WatchZonal Performance 2025/26Prices & CreditSix-Month Outlook
Tanzania's Economy by Zone, 2025/26: Strong Growth, a Fuel-Price Shock and What Comes Next
Nominal GDP reached TZS 234.1 trillion, tax collections beat target by 7.1%, bank credit grew 22.3% and gold lifted mineral recovery 43.3%. Then fuel prices jumped and inflation re-accelerated in five of six zones. This report reads the Bank of Tanzania's zonal data in depth: GDP, prices, food, industry, mining, energy, tourism, trade, revenue and banking, and projects what the next six months (October 2026 to March 2027) are likely to look like.
📅 Data to: June 2026📍 Dar es Salaam, Tanzania🏛️ TICGL / TERI📖 Source: Bank of Tanzania, NBS, TRA, Mining Commission, TANAPA
Nominal GDP 2025p
TZS 234.1 tn +10.4%
Tax revenue 2025/26p
TZS 36.25 tn +18.3%
Inflation range, Jun-26
2.6-8.0% by zone
Avg-zone inflation, Mar-27 (base)
3.8% peak 5.4%
Source: Bank of Tanzania, Consolidated Zonal Economic Performance Report, quarter ending June 2026; NBS; TRA; TERI calculations. p = provisional. The outlook figures are TICGL scenarios.
Disclaimer & scope
Prepared by TERI for research and strategic-information purposes only. It is not investment, legal, tax or financial advice and does not state the position of the Bank of Tanzania, the National Bureau of Statistics or the Government. Historical figures are taken from the Bank of Tanzania Consolidated Zonal Economic Performance Report (quarter ending June 2026, Vol. 11 No. 2); where TICGL/TERI computes a figure it is marked "TICGL calc." The six-month outlook (Tab 7) is a set of scenarios built on that data, not a forecast of record. p = provisional.
00 — OverviewExecutive Summary
Tanzania entered the second half of 2026 with a broad-based expansion and a new price shock. Nominal GDP reached TZS 234.1 trillion in 2025 (+10.4%), tax collections beat their target by 7.1%, bank credit grew 22.3%, gold pushed mineral recovery up 43.3% to USD 5.6 billion, and a 133% food self-sufficiency ratio gives the country a cushion that most of its neighbours lack. The weak spots are visible too: fuel pump prices jumped from around TZS 2,800-2,900 a litre in February 2026 to around TZS 4,200-4,400 by June 2026 (read from Chart 1.2 of the report), headline inflation re-accelerated in five of six zones, Dar es Salaam inflation (6.2%) and Southern Highlands inflation (8.0%) are above the 3-5% band, and growth is concentrated in a few places and a few commodities.
Nominal GDP, 2025p
TZS 234.1 tn
+10.4% on 2024; Lake zone 26.1% share
Tax revenue, 2025/26p
TZS 36.25 tn
+18.3% y/y; 107.1% of target
Food self-sufficiency
133%
25.2 m tonnes, +6%; surplus 6.3 m t
Mineral recovery
USD 5.6 bn
+43.3%; gold 86.3% of value
Bank deposits
TZS 50.0 tn
+25.9%; Dar es Salaam 62.8%
Bank loans
TZS 45.8 tn
+22.3%; personal loans 35%
Cross-border surplus
TZS 11.8 tn
+80.9%; Lake zone gold exports
Headline inflation, Jun-26
2.6-8.0%
Dar es Salaam 6.2%; S. Highlands 8.0%
Growth Scorecard: How Fast Did Each Indicator Move?
TZS trillion, stacked by zone. Source: NBS via BoT Table 1.1
Key findings
Growth is broad but shallow in per-capita terms. Nominal GDP per capita reached TZS 3.54 million in 2025 (+7.4%), but Dar es Salaam (TZS 6.78 m) is 3.9 times Simiyu region (TZS 1.74 m) and the Central, Lake and South Eastern zones remain below the national average.
Prices are the main near-term risk. Pump prices of petrol, diesel and kerosene rose 4.5%, 7.8% and 0.4% on annual averages, but monthly data show a sharp jump in April-June 2026 that fed through to zonal CPI: Central inflation went from 2.6% (Mar-26) to 6.6% (Apr-26) and Southern Highlands from 2.7% to 7.6%.
Food security is strong on paper, uneven in practice. National production reached 25.2 million tonnes (SSR 133%), yet Central and Southern Highlands production fell 8.8% and 11.3%, Lake zone cereals are in deficit (SSR 96%) and NFRA purchases fell 68.5% to 137,612 tonnes.
Gold is a price story. Gold recovery rose 57.3% to USD 4.83 bn on a 5.7% volume gain; TICGL calc. shows roughly 90% of the increase came from higher unit values. Non-gold minerals fell 8.2%.
Manufacturing and trade are surging from a narrow base. Manufactured goods grew 18.9% (cured tobacco +65.8%, wheat flour +57.0%) and port cargo grew 26.6%, but 47.4% of factory output is still in Dar es Salaam and 85.4% of cargo passes through Dar es Salaam port.
The power system has changed shape. Hydro rose from 33.5% of generation in 2023/24 to 67.0% in 2025/26 as Julius Nyerere output lifted South Eastern zone to 46.8% of national generation, while natural-gas production is 22.1% below its 2022/23 level.
Finance is deepening, but the money sits in Dar es Salaam. Dar es Salaam holds 62.8% of deposits at a loan-to-deposit ratio of 75%, while Southern Highlands (153%), Central (139%) and South Eastern (128%) lend more than they collect locally.
The tax base is geographically narrow. Dar es Salaam collects 88.2% of TRA revenue; direct taxes were the fastest-growing category (+32.5%).
Six-month outlook in one paragraph (October 2026 - March 2027)
Our central case is a strong real economy with a bumpy price path. Headline inflation in the average zone peaks near 5.4% in October-November 2026 before base effects pull it toward 3.8% by March 2027 if monthly price growth stays at +0.25%; a repeat of the April-June pace (about +0.5% a month) keeps it above 6%, while a flat price level takes it to 1.5%. Tax collection, deposits and credit keep growing at double-digit rates, peak-season tourism and the typical cashew and coffee marketing months support external earnings, and hydrology and gold prices are the two swing factors. Full scenarios, tables and a risk register are in Tab 7 and Tab 8.
Reading notes on the source data
Some published totals in the BoT report differ slightly from the sum of their parts (for example 2021/22 tax revenue, where the published total is TZS 21,926.9 bn and the zone rows add to TZS 21,595.0 bn, and some tourism earnings totals); TICGL uses the published totals and flags where it computes. Population by zone is derived as GDP divided by GDP per capita. Zone inflation rates use different CPI weights, so the simple average of zones shown in the outlook is not the national rate. Fuel-price levels for April-June 2026 are read from Chart 1.2 of the report and are approximate.
01 — Growth & ZonesWho Produces Tanzania's Output? GDP by Zone and Region
The Bank of Tanzania report groups the 26 mainland regions into six economic zones. Nominal GDP increased in every zone in 2025, from TZS 211.97 trillion to TZS 234.10 trillion, with Lake zone the largest block (26.1% of output) followed by Northern (17.2%) and Dar es Salaam (17.0%). Because zones differ in size, the per-capita and regional views below matter more for investment screening than the headline totals.
Zone (TZS billion)
2021
2022
2023
2024
2025p
Share 2025
Growth 2025
CAGR 2021-25
Central
21,822
24,234
25,884
28,725
31,677
13.5
+10.3%
+9.8%
Dar es Salaam
27,517
30,515
33,236
36,198
39,808
17.0
+10.0%
+9.7%
Lake
42,092
46,557
50,089
54,987
61,033
26.1
+11.0%
+9.7%
Northern
27,796
30,871
33,273
36,671
40,282
17.2
+9.8%
+9.7%
South Eastern
17,013
18,856
20,281
21,917
24,131
10.3
+10.1%
+9.1%
Southern Highlands
25,752
28,377
30,597
33,477
37,173
15.9
+11.0%
+9.6%
Mainland Tanzania
161,992
179,410
193,360
211,975
234,104
100.0
+10.4%
+9.6%
Source: National Bureau of Statistics via Bank of Tanzania, Table 1.1; shares and growth rates are TICGL calc. Data revised 2021-2024; p = provisional.
Growth by Zone: 2025 vs 2021-25 Average
Percent. Nominal growth, TICGL calc. from BoT Table 1.1
GDP per Capita by Zone, 2021-2025
TZS million per person, current prices. Source: BoT Table 1.2
1.1 Per-capita output and derived population
Dividing zonal GDP by zonal GDP per capita gives an implied population of about 66.0 million for mainland Tanzania in 2025. Lake zone holds 21.1 million people (32% of the total) but produces only 26.1% of GDP, which is why its per-capita output (TZS 2.89 m) sits 18% below the national average of TZS 3.54 m. Dar es Salaam, with 5.9 million people (8.9%), produces 17.0% of GDP and reaches TZS 6.78 m per head, 1.91 times the national average.
Zone (TZS per person)
2021
2022
2023
2024
2025p
Growth 2025
Implied pop. (m)
Index (nat.=100)
Central
2,083,356
2,074,378
2,125,386
2,292,522
2,458,479
+7.2%
12.88
69
Dar es Salaam
4,978,938
5,668,023
5,934,722
6,306,638
6,776,483
+7.5%
5.87
191
Lake
2,132,585
2,464,426
2,531,037
2,689,743
2,891,028
+7.5%
21.11
82
Northern
3,231,974
3,537,727
3,663,858
3,931,570
4,208,017
+7.0%
9.57
119
South Eastern
3,033,980
2,813,249
2,910,795
3,074,748
3,311,954
+7.7%
7.29
93
Southern Highlands
3,310,930
3,352,379
3,467,292
3,689,386
3,986,380
+8.0%
9.32
112
Mainland Tanzania
2,806,299
2,997,593
3,096,626
3,299,637
3,544,124
+7.4%
66.05
100
Source: BoT Table 1.2; implied population = GDP / GDP per capita (TICGL calc.); index = zone GDP per capita as a percentage of the national figure.
1.2 The regional picture: 26 regions, 10 carry 60% of output
Annexes 1 and 2 of the report give regional GDP. Output is concentrated: the five largest regions (Dar es Salaam, Mwanza, Mbeya, Morogoro, Arusha) produce 39.3% of mainland GDP and the ten largest 60.3%, while the ten smallest produce 20.2%. Growth in 2025 was fastest in Simiyu (+14.7%), Njombe (+13.9%), Pwani (+13.5%), Kagera (+12.4%) and Songwe (+11.8%), and slowest in Dodoma and Ruvuma (+8.5% each). Per-capita output ranges from TZS 6.78 m in Dar es Salaam, followed by Iringa (TZS 5.71 m), Kilimanjaro (TZS 5.20 m) and Mbeya (TZS 5.06 m), to TZS 1.74 m in Simiyu and TZS 1.85 m in Kagera.
Percent change 2024 to 2025, all 26 regions; teal = 11.8% or more, red = below 9.2% (TICGL calc.)
GDP per Capita by Region, 2025
TZS million per person; teal = above national average (TZS 3.54 m)
Full regional table
Region
Zone
GDP 2025 (TZS bn)
Share of GDP
Growth 2025
GDP per capita (TZS m)
Index (nat.=100)
Dar es Salaam
Dar es Salaam
39,808
17.0
+10.0%
6.78
191
Mwanza
Lake
16,749
7.2
+9.8%
4.07
115
Mbeya
Southern Highlands
12,924
5.5
+10.3%
5.06
143
Morogoro
Central
11,410
4.9
+11.4%
3.27
92
Arusha
Northern
11,101
4.7
+9.1%
4.28
121
Tanga
Northern
10,864
4.6
+10.1%
3.80
107
Geita
Lake
10,495
4.5
+11.7%
3.13
88
Kilimanjaro
Northern
10,489
4.5
+10.4%
5.20
147
Tabora
Central
8,668
3.7
+10.0%
2.30
65
Mara
Lake
8,627
3.7
+10.9%
3.26
92
Shinyanga
Lake
8,445
3.6
+10.9%
3.40
96
Ruvuma
South Eastern
8,445
3.6
+8.5%
4.16
117
Manyara
Northern
7,828
3.3
+9.8%
3.73
105
Iringa
Southern Highlands
7,335
3.1
+11.8%
5.71
161
Dodoma
Central
7,168
3.1
+8.5%
2.11
60
Kigoma
Lake
6,343
2.7
+9.6%
2.30
65
Mtwara
South Eastern
6,342
2.7
+9.3%
3.58
101
Kagera
Lake
6,147
2.6
+12.4%
1.85
52
Rukwa
Southern Highlands
5,015
2.1
+9.0%
2.88
81
Pwani
South Eastern
4,749
2.0
+13.5%
2.16
61
Lindi
South Eastern
4,596
2.0
+10.8%
3.57
101
Singida
Central
4,431
1.9
+10.9%
1.99
56
Songwe
Southern Highlands
4,371
1.9
+11.8%
2.94
83
Njombe
Southern Highlands
4,337
1.9
+13.9%
4.53
128
Simiyu
Lake
4,228
1.8
+14.7%
1.74
49
Katavi
Southern Highlands
3,191
1.4
+11.0%
2.46
69
Source: NBS via BoT Annexes 1 and 2; shares, growth and index are TICGL calc. Regional GDP excludes Zanzibar.
TICGL/TERI reading
Two patterns matter for the next six months. First, the fastest-growing regions (Simiyu, Njombe, Pwani, Kagera, Songwe) start from low or mid-sized bases, so their growth is a catch-up signal rather than a sign of rising output weight. Second, per-capita growth of 7.4% in 2025 compares with national average headline inflation of 3.6% in 2025/26 (different year definitions, so indicative only): households gained in real terms last year, but Tab 2 shows that the April-June 2026 price jump erodes part of that gain in Central, Dar es Salaam and Southern Highlands.
02 — Prices & InflationInflation, Food Prices and Fuel: The 2026 Price Shock
Headline inflation averaged 3.6% nationally in 2025/26, up from 3.1% in 2024/25 and still inside the 3-5% target range. Averages hide the trend, however. Month by month, year-on-year inflation was drifting up through the first half of 2026 and then jumped in April-June, when pump prices of petrol, diesel and kerosene rose sharply on higher global oil prices amid Middle East tensions. By June 2026 inflation was above 5% in Dar es Salaam (6.2%), Central (5.2%) and Southern Highlands (8.0%), within the band in Lake (3.0%) and Northern (3.3%), and below it in South Eastern (2.6%).
Annual average headline inflation, %
2021/22
2022/23
2023/24
2024/25
2025/26
National
4.0
4.6
3.1
3.1
3.6
Central
2.3
5.0
2.5
1.5
3.0
Dar es Salaam
3.5
4.0
5.4
4.9
4.8
Lake
6.7
5.0
1.2
2.4
3.6
Northern
2.7
4.5
3.6
1.7
2.9
South Eastern
3.7
3.8
2.4
2.0
3.3
Southern Highlands
4.2
5.0
3.7
3.6
4.7
Source: National Bureau of Statistics via Bank of Tanzania, Table 1.3. Zonal CPIs use different weights, so a simple average of zones is not the national rate.
Year-on-Year Headline Inflation by Zone, June 2024 - June 2026
Percent. Dashed lines = 3% and 5% bounds of the national target range. Source: BoT Annex 4
Average Inflation by Zone: 2024/25 vs 2025/26
Percent. Source: BoT Table 1.3
Food vs Non-Food Inflation, June 2026
Year-on-year, percent. Food June 2025 shown for comparison. Source: BoT Annex 4
Zone
Headline Mar-26
Headline Jun-26
Food Jun-26
Non-food Jun-26
vs 3-5% band
Central
2.6
5.2
5.0
5.4
Above band
Dar es Salaam
4.5
6.2
6.3
6.2
Above band
Lake
4.7
3.0
2.2
3.4
Within band
Northern
2.2
3.3
3.8
3.0
Within band
South Eastern
3.3
2.6
2.3
2.8
Below band
Southern Highlands
2.7
8.0
15.1
5.0
Above band
Source: BoT Annex 4 (twelve-month changes). Band status is TICGL classification against the 3-5% national target range.
2.1 Why inflation jumped in April 2026: a price shock on top of a low base
Annex 3 gives the headline CPI index for each zone, which lets us split the April 2026 jump in year-on-year inflation into two parts: the actual monthly price rise in April 2026, and a base effect because prices fell in April 2025 (in Central and Southern Highlands the index dropped 1.5% and 3.2% in that month). In Central the monthly rise was 2.3% and the base effect added a further 1.5 percentage points; in Southern Highlands the figures are 1.4% and 3.2 points. Base effects work in both directions: the April 2026 step is now in the index, so year-on-year inflation stays elevated until April 2027 unless prices fall back, which is the core of the six-month outlook in Tab 7.
Decomposing the April 2026 Jump in Year-on-Year Inflation
Percentage points. Monthly CPI rise in April 2026 plus base effect from the April 2025 monthly move (TICGL calc. from BoT Annex 3)
Southern Highlands paradox
Southern Highlands has the highest food self-sufficiency in the country (SSR 222%) yet recorded 15.1% food inflation in June 2026. Part of the answer is the low base (food inflation was only 1.7% in June 2025 after a price fall in April 2025); part is transport cost, since fuel prices feed into the cost of moving crops from farm to market; and part is the fall in zonal food production (-11.3%). It is a good reminder that surplus production does not translate into local price stability when logistics costs move.
2.2 Wholesale food prices
Average wholesale prices of selected food crops rose in 2025/26 for every crop except beans (Table 1.4), reflecting depletion of household stocks from the 2024/25 season and higher transport costs. Finger millet (+35.8%), bulrush millet (+14.8%) and rice (+12.6%) rose most. Maize, the staple that matters most for household budgets, rose 9.9% to TZS 83,236 per 100 kg, back to its 2023/24 level after a fall in 2024/25.
Crop (TZS per 100 kg, national avg)
2023/24
2024/25
2025/26
Change 2025/26
Beans
270,402
272,038
255,597
-6.0%
Bulrush millet
123,653
148,375
170,272
+14.8%
Finger millet
159,068
178,569
242,475
+35.8%
Maize
83,739
75,724
83,236
+9.9%
Round potatoes
95,751
100,058
111,644
+11.6%
Rice
254,615
223,302
251,436
+12.6%
Sorghum
135,722
133,158
144,034
+8.2%
Wheat
182,351
164,038
172,882
+5.4%
Source: Ministry of Industry and Trade via BoT Table 1.4; change is TICGL calc. Simple average of zonal prices where available.
Wholesale Prices of Major Food Crops
TZS thousand per 100 kg, three crop years. Source: BoT Table 1.4
Maize Price by Zone
TZS per 100 kg. Source: BoT Table 1.4
2.3 Fuel pump prices
Annual average pump prices rose in 2025/26: petrol +4.5% to TZS 3,202 a litre, diesel +7.8% to TZS 3,194 and kerosene +0.4% to TZS 3,354. Those averages understate the 2026 shock. Chart 1.2 of the report shows pump prices running at about TZS 2,800-3,000 a litre through February 2026 and then climbing to roughly TZS 4,200-4,400 by June 2026 in every zone, with petrol, diesel and kerosene converging. Diesel, the transport and farm-machinery fuel, rose most (+9.2% in South Eastern and +8.1% in Lake and Northern on annual averages).
Average Pump Prices, 2021/22 - 2025/26
TZS per litre, average across zones. Source: BoT Table 1.5
Pump-Price Change by Zone, 2024/25 to 2025/26
Percent change in annual average. Source: BoT Table 1.5
Average pump price (TZS per litre)
2021/22
2022/23
2023/24
2024/25
2025/26
Change 2025/26
Petrol
2,670.2
3,034.9
3,244.8
3,065.4
3,202.0
+4.5%
Diesel
2,559.3
3,160.3
3,229.0
2,961.8
3,194.2
+7.8%
Kerosene
2,522.5
3,365.3
3,243.3
3,340.6
3,353.9
+0.4%
Source: BoT Table 1.5 (National Bureau of Statistics).
TICGL/TERI reading
For businesses, the combination of a fuel-price step and a food-price recovery means transport-intensive and food-processing margins are the first place the shock appears; for households, it means non-food inflation (5.4% in Central and 6.2% in Dar es Salaam in June 2026) is now as important as food. The report attributes the Dar es Salaam slowdown in annual-average inflation to housing, utilities and clothing, which is the opposite of the current trend in monthly data.
03 — Food, Agriculture & LivestockFood Security, Cash Crops, Livestock, Fish and Forests
Food and agriculture are where the 2025/26 numbers look best and where the regional detail is most uneven. National food-crop production is estimated at 25.2 million tonnes (16.4 m tonnes of cereals and 8.8 m of non-cereals), 6% above the previous season, on favourable long rains, subsidised fertiliser, extension services and pest-control campaigns, and on a larger cultivated area (12.06 million hectares against 11.86 million). Production exceeds 2026/27 food requirements by 6.3 million tonnes, lifting the self-sufficiency ratio (SSR) to 133% from 128%.
Zone (tonnes)
2024/25
2025/26p
Change
Requirement 2026/27
Surplus (+) / deficit (-)
SSR
Central
5,167,635
4,710,865
-8.8%
3,701,837
1,009,028
127%
Dar es Salaam
7,577
8,870
+17.1%
1,632,058
-1,623,188
1%
Lake
5,228,890
7,385,377
+41.2%
5,739,908
1,645,469
129%
Northern
2,802,375
3,053,436
+9.0%
2,615,038
438,398
117%
South Eastern
2,621,611
2,990,087
+14.1%
2,007,983
982,104
149%
Southern Highlands
7,955,040
7,056,172
-11.3%
3,183,720
3,872,452
222%
National (total)
23,783,128
25,204,807
+6.0%
18,880,544
6,324,263
133%
Source: Ministry of Agriculture via BoT Table 2.1; change is TICGL calc.; surplus = 2025/26 production less 2026/27 requirement, as published. SSR 0-99% = inadequate, 100-119% = adequate, 120% and above = surplus.
National Food Production, 2021/22 - 2025/26
Million tonnes, cereals and non-cereals. Source: BoT Table 2.1
Production vs Requirement by Zone
Thousand tonnes: 2025/26 production vs 2026/27 requirement (Dar es Salaam is a non-agricultural zone)
Lake zone drove the national gain (+41.2% to 7.39 m tonnes) while Central (-8.8%) and Southern Highlands (-11.3%) produced less than in 2024/25. Lake zone is also the only agricultural zone with a cereal deficit (cereals SSR 96%), and Dar es Salaam, with a requirement of 1.63 million tonnes, produces almost nothing (SSR 1%). Food therefore has to move from Southern Highlands (surplus 3.87 m tonnes) and Central to Dar es Salaam and the Lake zone, which makes logistics and fuel costs central to food prices (Tab 2).
3.1 National Food Reserve Agency stocks
NFRA closing stocks of maize and paddy rose 2.5% to 489,998 tonnes, but the flow behind that figure changed sharply: purchases fell 68.5% to 137,612 tonnes (from 436,382 t) and releases to private traders and the World Food Programme fell to 125,537 tonnes (from 298,937 t). About 95% of the stock sits in two zones, Southern Highlands (278,216 t) and South Eastern (187,404 t), against only 19,721 t in Dar es Salaam, where requirements are largest.
Year (tonnes)
Purchased
Released
Closing balance
2023/24
297,421.0
3,605.8
340,478.9
2024/25
436,381.8
298,937.4
477,923.4
2025/26
137,612.0
125,537.4
489,998.0
Source: National Food Reserve Agency via BoT Table 2.2. Stock excludes food in transit.
NFRA Purchases, Releases and Closing Stock
Thousand tonnes. Source: BoT Table 2.2
Where the Reserve Sits, End 2025/26
Thousand tonnes closing stock by zone (BoT Table 2.2)
3.2 Cash crops
Procurement rose for cashew nuts (+6.9% to 439,639 t, with South Eastern zone handling 437,459 t), coffee (+2.7%), cotton (+33.7%) and tobacco (+28.4%), and fell for sisal (-24.1%) and tea (-15.2%). The report attributes the gains to higher global prices, favourable weather, input distribution and extension services, and the losses to weak global demand and weather-affected processing for sisal.
Crop (tonnes procured)
2023/24
2024/25r
2025/26p
Change 2025/26
Sisal
51,812.6
72,409.1
54,922.4
-24.1%
Coffee
69,350.0
71,717.4
73,622.5
+2.7%
Cotton (seed)
282,218.0
149,809.8
200,231.8
+33.7%
Tobacco
155,538.4
127,149.7
163,275.5
+28.4%
Tea
21,062.5
16,267.1
13,795.3
-15.2%
Cashewnut
244,797.0
411,158.9
439,639.4
+6.9%
Source: respective crop boards via BoT Table 3.1; r = revised, p = provisional.
Cash-Crop Procurement, Three Seasons
Thousand tonnes. Source: BoT Table 3.1
3.3 Livestock, hides, fish and forest products
Livestock traded in registered markets grew 16.5% to TZS 3,505.2 billion, with cattle at 88.6% of value. Central zone is the largest market (34.4% of value, after a 27.9% rise) ahead of Lake (23.6%) and Northern (18.0%), and Northern (-1.2%) was the only zone to fall. Raw hides and skins rose 12.1% to TZS 13.2 billion, led by Dar es Salaam (TZS 3.84 bn, 29.1%). Fish sold stayed flat in value at TZS 656.4 billion but quantity fell 12.6% to 85,237 tonnes, so the implied price per tonne rose 13.5% to TZS 7.7 million. Forest-product value rose 16.6% to TZS 1,306 billion, with Southern Highlands at 95.7% of the total.
Livestock value (TZS m)
2023/24
2024/25r
2025/26p
Change
Share 2025/26
Central
669,878
941,504
1,204,414
+27.9%
34.4
Dar es Salaam
354,449
407,539
426,543
+4.7%
12.2
Lake
537,455
660,842
827,828
+25.3%
23.6
Northern
534,670
638,075
630,535
-1.2%
18.0
South Eastern
148,375
147,230
185,207
+25.8%
5.3
Southern Highlands
192,974
214,644
230,717
+7.5%
6.6
Total
2,437,800
3,009,833
3,505,244
+16.5%
100.0
Source: Regional Administrative Secretary Offices via BoT Table 3.2. Species 2025/26: cattle TZS 3,107.0 bn (3.64 m head), goats TZS 273.6 bn (2.30 m head), sheep TZS 124.6 bn (1.46 m head).
Source: Regional Administrative Secretary Offices via BoT Table 3.4. Declines in Dar es Salaam and South Eastern were attributed to strong winds in the Indian Ocean, in Central to lower water levels in Singida and Morogoro.
TICGL/TERI reading
Agriculture supports the six-month outlook through three channels. It lowers the risk that food drives inflation above the target band (SSR 133%, NFRA stock of 0.49 m tonnes), it supports export earnings through cashew, coffee, tobacco and cotton, and it feeds demand for processing capacity. The offsetting concerns are distribution (surplus in Southern Highlands, deficits in Dar es Salaam and Lake) and the collapse in NFRA buying, which removes a price floor at harvest time.
04 — Industry, Mining & EnergyManufacturing, Gold and Minerals, Electricity and Gas
This tab covers the three sectors that move the external accounts and the power bill: manufacturing, mining and energy. All three grew in 2025/26, but each is concentrated in one zone and one or two products, and each has a clear six-month swing factor.
4.1 Manufacturing
The value of selected manufactured products grew 18.9% to TZS 21,250.7 billion, on stronger domestic and external demand. Growth was broad-based across zones except Northern (-13.2%, on plastics, textiles, coffee and tea products), and Dar es Salaam, with 47.4% of the total, rose 33.5%. Cured tobacco (+65.8%), wheat flour (+57.0%), vegetable oils and fats (+52.2%), cigarettes (+52.1%) and ceramics (+26.4%) grew fastest; textiles (-6.6%), plastic articles (-25.0%) and corrugated iron sheets (-7.6%) fell. Six products (cured tobacco, wheat flour, bottled beer, beverages, vegetable oils and cigarettes) account for 44.7% of value.
Zone (TZS billion)
2021/22
2022/23
2023/24
2024/25
2025/26p
Share
Change
Central
995.5
958.3
1,450.9
1,616.2
2,087.2
9.8
+29.1%
Dar es Salaam
6,634.0
7,229.4
8,439.2
7,550.5
10,081.6
47.4
+33.5%
Lake
750.7
955.7
1,077.5
1,236.9
1,470.7
6.9
+18.9%
Northern
1,594.7
1,647.6
2,237.0
3,295.9
2,861.5
13.5
-13.2%
South Eastern
1,970.5
2,222.2
2,950.1
3,232.2
3,805.0
17.9
+17.7%
Southern Highlands
702.4
743.5
770.0
936.1
944.7
4.4
+0.9%
Total
12,647.8
13,756.6
16,924.8
17,867.8
21,250.7
100.0
+18.9%
Source: National Bureau of Statistics and respective industries, BoT Table 3.6a.
Manufactured Output by Zone
TZS trillion, stacked. Source: BoT Table 3.6a
Product Growth, 2025/26
Percent change in value vs 2024/25 (BoT Table 3.6b)
Product (TZS bn)
2023/24
2024/25r
2025/26p
Change
Share of growth, %
Share of total, %
Bottled beer
1,233.7
2,228.8
2,631.1
+18.1%
11.9
12.4
Beverages
2,324.6
2,341.9
2,622.5
+12.0%
8.3
12.3
Cement
2,122.7
2,332.6
2,406.7
+3.2%
2.2
11.3
Wheat flour
1,060.1
939.8
1,475.2
+57.0%
15.8
6.9
Cured tobacco
782.0
855.6
1,418.8
+65.8%
16.6
6.7
Rolled steel
1,158.5
1,123.6
1,298.1
+15.5%
5.2
6.1
Sugar
923.6
796.3
889.2
+11.7%
2.7
4.2
Textiles
505.5
934.4
872.8
-6.6%
-1.8
4.1
Vegetable oils and fats
651.2
463.0
704.9
+52.2%
7.2
3.3
Cigarettes
266.7
424.4
645.4
+52.1%
6.5
3.0
Ceramics
459.0
505.2
638.6
+26.4%
3.9
3.0
Soap and detergents
500.5
539.4
618.1
+14.6%
2.3
2.9
Mattresses
365.4
360.4
353.2
-2.0%
-0.2
1.7
Plastic articles
420.3
315.6
236.7
-25.0%
-2.3
1.1
Corrugated iron sheets
294.7
154.5
142.8
-7.6%
-0.3
0.7
Others
3,856.1
3,552.2
4,296.4
+21.0%
22.0
20.2
Total
16,924.8
17,867.8
21,250.7
+18.9%
100.0
100.0
Source: BoT Table 3.6b; share of growth = product increase / total increase (TICGL calc., agrees with the BoT contribution column).
Volume Check: Quantity Change by Product
Percent change in quantity, 2025/26 vs 2024/25 (BoT Table 3.6c)
Where the TZS 3.4 Trillion Increase Came From
Increase in value 2024/25 to 2025/26, TZS billion (TICGL calc.)
TICGL/TERI reading
Value growth of 18.9% is partly price: in volume terms cement rose 11.1%, wheat flour 11.9%, beverages 5.5% and beer 9.8%, and steel (-2.7%) and sugar (-6.6%) fell. The strongest value-and-volume combinations are cured tobacco (volume +65.1%) and cigarettes (+22.8%); a policy or crop-season shock would hit both. For market entry, the 2025/26 pattern favours food and beverage processing, tobacco, building materials and ceramics, and flags import-competing plastics, textiles and iron sheets as segments under pressure.
4.2 Mining
The value of mineral recovery rose 43.3% to USD 5,598.5 million, led by gold (USD 4,833.5 m, 86.3% of the total). The report attributes the gold gain to quantity and price: volume rose 5.7% to 54.5 tonnes, helped by small-scale miners selling through the Bank of Tanzania domestic gold purchase programme and the Mining (Technical Support for Small Scale Miners) Regulations, 2025, while world gold prices rose 50.4% to an average USD 4,249.6 per troy ounce on safe-haven demand. TICGL calc. on the report data shows the implied unit value of recovered gold rose 48.7%, so about USD 1.58 billion of the USD 1.76 billion increase (90%) is price and only USD 0.18 billion is volume. Everything else fell: coal -24.9%, diamond -21.1%, gemstones -62.4% and tanzanite -62.1%, while limestone (+80.1%), graphite (+39.9%) and nickel (USD 13.3 m from 1.8 m) grew from small bases.
Mineral (USD million)
2023/24
2024/25r
2025/26p
Change
Share
Gold
2,552.1
3,073.5
4,833.5
+57.3%
86.3
Coal
313.7
376.0
282.5
-24.9%
5.0
Building materials
119.0
183.2
182.0
-0.7%
3.3
Limestone
37.9
51.8
93.3
+80.1%
1.7
Diamond
47.4
55.0
43.5
-20.9%
0.8
Graphite
9.3
29.7
41.5
+39.7%
0.7
Industrial minerals
32.1
36.2
32.2
-11.0%
0.6
Gypsum
10.2
12.5
18.1
+44.8%
0.3
Nickel
1.8
1.8
13.3
---
0.2
Gemstones
27.2
29.0
10.9
-62.4%
0.2
Tanzanite
9.1
9.9
3.7
-62.6%
0.1
Total (incl. others)
3,179.4
3,906.7
5,598.5
+43.3%
100.0
Source: Mining Commission via BoT Table 3.7a (selected minerals shown; total includes copper, salt and other items). "---" = change above 100% or not meaningful.
Mineral Recovery by Type
USD million, stacked. Source: BoT Table 3.7a
Gold: Volume Effect vs Price Effect
Change in gold recovery value, USD million (TICGL calc.: volume at prior-year unit value)
Gold Quantity and Implied Unit Value
Tonnes (bars) and USD thousand per kg (line). Unit value = value / quantity (TICGL calc.)
Mineral Recovery by Zone
USD million. Source: BoT Table 3.7c
Mineral market centres show the same picture in shillings: minerals traded in registered markets rose 73.3% to TZS 6,852.1 billion, with gold 98% of the total, Lake zone 58.6% and Southern Highlands 28.1%. Central (+112%), South Eastern (+104%) and Southern Highlands (+84%) grew fastest from smaller bases, while Dar es Salaam (tanzanite and gemstones) fell 56.5%.
Minerals Sold at Market Centres by Zone
TZS billion, 2024/25 vs 2025/26. Source: BoT Table 3.8
4.3 Energy
Domestic electricity generation grew 10.4% to 14,080.1 GWh as hydro output (Julius Nyerere, Mtera, Kidatu and New Pangani Falls) and new solar plants in Lake zone (Ushetu, Bukombe, Kishapu) came on stream. The shape of the system has changed: hydro supplied 67.0% of generation in 2025/26 against 33.5% two years earlier, South Eastern zone now produces 46.8% of the national total (from 8.3% in 2023/24), and Dar es Salaam, once 63.6% of generation, is down to 30.5%. Imports more than doubled to 613.0 GWh (4.4% of supply), mainly from Kenya (350.8 GWh) after the 400 kV interconnector was energised in December 2024, while exports to Kenya fell 79.1% to 7.0 GWh.
Share of domestic generation, percent (TICGL calc. from BoT Table 3.12)
Natural gas moved the other way. Production rose 3.2% to 63,440.5 million standard cubic feet in 2025/26, but is 22.1% below its 2022/23 level because Songo Songo output has fallen from 47,565 to 26,544 MMSCF; Mnazi Bay (+9.7%) now supplies 58.2% of production. Consumption rose 3.6% to 61,956.7 MMSCF: power plants (70.1% of use) burned 3.5% less, as hydro displaced gas, while industry took 19.9% more (17,126 MMSCF) and compressed natural gas for vehicles more than doubled to 1,393 MMSCF as the CNG fleet grew from 7,000 to 16,354 vehicles and filling stations from 9 to 19.
Natural Gas Production by Field
Million standard cubic feet, stacked. Source: BoT Table 3.13
Natural Gas Consumption by Use
Million standard cubic feet, stacked. Source: BoT Table 3.13
Swing factors for the next six months
Gold: with price accounting for about 90% of the 2025/26 increase, every 10% move in gold prices shifts annual gold recovery value by roughly USD 0.5 billion (TICGL calc.). Power: the system now depends on hydrology (67% hydro), so a weak short-rains season would raise thermal burn and imports at a time when Songo Songo gas output is falling. Manufacturing: fuel and input costs are the main pressure on margins in the months ahead.
Trade, tourism and logistics are the external-facing engines of the 2025/26 expansion. Park visitors rose 7.5% to 2.45 million and park earnings 8.4% to TZS 823.9 billion; the cross-border trade surplus widened 80.9% to TZS 11.8 trillion as gold, rough diamonds and fish exports through the Lake zone surged; port cargo grew 26.6% to 39.4 million tonnes; and air passengers rose 8.8% to 5.25 million.
5.1 Tourism
Growth came entirely from non-resident visitors (+9.9% to 1.87 million, 76.5% of the total). Resident visitors were flat (+0.3% to 575,420) and remain 46.5% below the 2022/23 level of 1.08 million, so domestic tourism has not recovered. Earnings per visitor were flat (TZS 336,400, +0.9%), which means the 8.4% earnings gain is a volume story rather than a pricing story. Northern zone takes 64.9% of visitors and 59.7% of earnings, but Lake zone earns far more per visitor (TZS 533,300 against TZS 309,100 in the Northern zone), reflecting its mix of entry and other fees. Earnings here are park and Ngorongoro fee revenue, not total tourism receipts.
Zone
Visitors 2024/25
Visitors 2025/26
Change
Earnings 2025/26 (TZS bn)
Change
Earnings per visitor (TZS)
Central
187,672
194,259
+3.5%
12.2
+18.5%
62,856
Lake
525,341
555,011
+5.6%
296.0
+10.3%
533,282
Northern
1,462,529
1,590,367
+8.7%
491.5
+7.0%
309,057
South Eastern
76,543
81,840
+6.9%
16.4
+1.6%
200,868
Southern Highlands
26,773
27,438
+2.5%
7.8
+20.9%
282,703
Total
2,278,858
2,448,915
+7.5%
823.9
+8.4%
336,434
Source: TANAPA and NCAA via BoT Tables 3.9a and 3.9b; earnings per visitor is TICGL calc. (zone totals use published zone rows).
Park Visitors: Residents vs Non-Residents
Thousands, stacked. Source: BoT Table 3.9a
Park Earnings and Earnings per Visitor
TZS billion (bars) and TZS thousand per visitor (line, TICGL calc.). Source: BoT Table 3.9b
Visitors and Earnings by Zone, 2025/26
Share of national total, percent
Earnings per Visitor by Zone, 2025/26
TZS thousand per visitor (TICGL calc.)
Museums continued to recover in visitors (+13.9% to 153,695) but not in revenue: earnings fell 11.0% to TZS 909.2 million, concentrated in Dar es Salaam (-19.9% despite 10.3% more visitors), so revenue per museum visitor dropped from about TZS 7,570 to TZS 5,920.
5.2 Cross-border trade
Trade with neighbouring countries recorded a surplus of TZS 11,811.7 billion, 80.9% above the previous year. Exports rose 49.6% to TZS 14,964.4 billion, with Lake zone alone exporting TZS 12,811.3 billion (85.6% of the total, +75.6%) on unrefined gold, rough diamonds and fish products. Imports fell 9.1% to TZS 3,152.7 billion, driven by Lake zone (floor tiles, electronics, fish feed, mining equipment) and Northern zone (animal feed, pharmaceuticals, soap and detergents, lubricants), a substitution the report attributes to higher domestic production. Southern Highlands slipped into deficit (TZS -155.3 bn) as exports fell 20.2% and imports rose 22.3%.
Year (TZS billion)
Exports
Imports
Trade balance
2021/22
12,312.1
5,074.0
7,238.1
2022/23
12,359.3
6,714.6
5,644.8
2023/24
6,545.2
2,654.2
3,891.0
2024/25
10,000.4
3,469.6
6,530.8
2025/26p
14,964.4
3,152.7
11,811.7
Zone 2025/26 (TZS bn)
Exports
Change
Imports
Change
Balance
Lake
12,811.3
+75.6%
1,065.0
-29.7%
11,746.3
Northern
1,018.3
-21.3%
833.1
-10.6%
185.2
South Eastern
42.9
+2.9%
7.4
+311.1%
35.5
Southern Highlands
1,091.8
-20.2%
1,247.1
+22.3%
-155.3
Source: Tanzania Revenue Authority via BoT Table 5.1. Cross-border trade covers land and lake trade with neighbouring countries only; Dar es Salaam and Central zones have no recorded cross-border trade in the table.
Cross-Border Exports, Imports and Balance
TZS billion. Source: BoT Table 5.1
Exports by Zone
TZS billion, stacked. Lake zone drives the surge. Source: BoT Table 5.1
5.3 Ports and airports
Cargo handled at major sea and lake ports grew 26.6% to 39.4 million tonnes. Dar es Salaam handled 33.6 million tonnes (+26.5%, 85.4%), Tanga 2.17 million (+63.3%) and Mtwara 2.22 million (-13.7% on weak global coal demand). Bagamoyo and Mafia appear for the first time (377,300 and 69,500 tonnes), and lake ports on the DRC route grew strongly: Kigoma +54.9%, Karema +54.2% and Mwanza more than doubled, with clinker for cement the main export to DRC. Kilwa (+36.5%) and Lindi (+22.8%) benefited from seafood exports.
Port ('000 tonnes)
2023/24
2024/25r
2025/26p
Change
Share
Dar es Salaam
24,547.9
26,596.6
33,641.6
+26.5%
85.4
Tanga
1,191.5
1,326.4
2,165.4
+63.3%
5.5
Mtwara
1,727.3
2,577.3
2,223.2
-13.7%
5.6
Bagamoyo
n.a.
n.a.
377.3
new
1.0
Kigoma
195.9
216.6
335.6
+54.9%
0.9
Karema
183.3
213.6
329.4
+54.2%
0.8
Mwanza
97.0
91.6
196.4
+114.4%
0.5
Mafia
n.a.
n.a.
69.5
new
0.2
All ports (incl. minor)
28,182.9
31,109.1
39,381.2
+26.6%
100.0
Source: Tanzania Ports Authority via BoT Table 5.2. Minor ports (Kilwa, Lindi, Mbamba Bay, Itungi, Kasanga, Matema) are included in the total but not listed.
Port Cargo by Port, 2021/22 - 2025/26
Million tonnes, stacked: Dar es Salaam, Tanga, Mtwara, others. Source: BoT Table 5.2
Port Cargo Growth, 2025/26
Percent change in tonnes vs 2024/25 (BoT Table 5.2)
Airports handled 148,636 flights (+4.2%), 5.25 million passengers (+8.8%) and 39,483 tonnes of cargo (+6.6%). Domestic passengers grew fastest (+12.8% to 3.00 million) against +3.9% for international passengers (2.25 million). Dar es Salaam accounts for 57.4% of passengers and 75.9% of cargo, the Northern zone for 26.7% of passengers.
Air Passengers, 2021/22 - 2025/26
Million passengers, stacked. Source: BoT Table 5.3
The data point to a trade-and-logistics cycle that is strengthening ahead of the next six months: cargo growth of 26.6% and new ports (Bagamoyo, Mafia) widen capacity, regional cargo for DRC supports lake ports, and tourism growth is entirely foreign. The vulnerabilities are concentration (Dar es Salaam is 85.4% of cargo, Lake zone 85.6% of cross-border exports) and the gold dependency of the surplus, which links this tab back to the price swing in Tab 4.
06 — Revenue, Banking & CreditTax Collection, Local Revenue, Deposits, Loans and Agent Banking
Public revenue and the financial system both finished 2025/26 well ahead of their prior-year levels, and both are heavily centred on Dar es Salaam. Tax revenue reached TZS 36.25 trillion (107.1% of target), local-government own-source revenue reached TZS 1.66 trillion (99.4% of target), bank deposits rose 25.9% to TZS 50.0 trillion and loans 22.3% to TZS 45.8 trillion, and the bank-agent network grew 25.6% to 195,345 agents.
6.1 Tax revenue
Collections beat the annual target in every zone, from 106.5% in Dar es Salaam to 116.0% in Southern Highlands. The report credits economic expansion, taxpayer education and the Integrated Domestic Revenue Administration System. Taxes on local goods and services were the largest component (42.1%), followed by import taxes (39.0%) and direct taxes (18.9%), which grew fastest (+32.5%). Dar es Salaam accounts for 88.2% of the total because it is where large taxpayers and the port are registered, so zonal tax shares measure where tax is collected rather than where income is earned. Tax revenue equals about 15.5% of 2025 mainland GDP (TICGL calc., indicative because fiscal and calendar years differ).
Zone (TZS billion)
2024/25r
Target 2025/26
Actual 2025/26p
Actual / target, %
Growth y/y
Share
Central
405.9
433.7
488.2
112.6
+20.3%
1.3
Dar es Salaam
27,269.4
30,037.4
31,990.2
106.5
+17.3%
88.2
Lake
812.9
845.7
953.3
112.7
+17.3%
2.6
Northern
1,174.4
1,327.9
1,459.4
109.9
+24.3%
4.0
South Eastern
430.1
599.4
662.9
110.6
+54.1%
1.8
Southern Highlands
546.6
600.1
696.3
116.0
+27.4%
1.9
Total
30,639.3
33,844.3
36,250.4
107.1
+18.3%
100.0
Source: Tanzania Revenue Authority via BoT Table 4.1. Gross of refunds; excludes revenue collected by TANAPA, NCAA and TAWA. Growth and ratios are TICGL calc. (the published 2021/22 total does not equal the sum of the zone rows).
Category (TZS billion)
2023/24
2024/25r
2025/26p
Growth y/y
Share
Tax on imports
10,516.6
12,334.7
14,142.3
+14.7%
39.0
Tax on local goods & services
11,146.1
13,137.1
15,260.3
+16.2%
42.1
Direct tax
4,634.8
5,167.5
6,847.8
+32.5%
18.9
Total
26,297.5
30,639.3
36,250.4
+18.3%
100.0
Source: BoT Table 4.2.
Tax Revenue by Category
TZS billion, stacked. Source: BoT Table 4.2
Actual vs Target by Zone, 2025/26
Actual as percent of target (100 = target met). Source: BoT Table 4.1
6.2 Local government revenue
Local Government Authorities collected TZS 1,656.4 billion from own sources (+14.5%), 99.4% of target, supported by point-of-sale devices and online trading of some cash crops. The shortfall sits in the largest urban base: Dar es Salaam reached only 90.1% of target (TZS 349.9 bn) and Central 93.1%, while South Eastern (109.7%), Southern Highlands (107.4%) and Lake (102.0%) exceeded targets. Local revenue equals about 4.6% of TRA collections.
Zone (TZS billion)
2024/25r
Target 2025/26
Actual 2025/26p
Actual / target, %
Growth y/y
Share
Central
213.8
248.3
231.3
93.2
+8.2%
14.0
Dar es Salaam
338.6
388.3
349.9
90.1
+3.3%
21.1
Lake
293.5
337.1
344.0
102.0
+17.2%
20.8
Northern
181.4
208.4
204.9
98.3
+13.0%
12.4
South Eastern
226.8
245.4
269.3
109.7
+18.7%
16.3
Southern Highlands
192.9
239.2
257.0
107.4
+33.2%
15.5
Total
1,447.0
1,666.8
1,656.4
99.4
+14.5%
100.0
Source: Regional Administrative Secretary Offices via BoT Table 4.3; ratios and growth are TICGL calc.
Local Government Own-Source Revenue: Target vs Actual
TZS billion by zone, 2025/26. Source: BoT Table 4.3
6.3 Bank deposits and loans
Deposits rose 25.9% to TZS 50,025.3 billion and loans 22.3% to TZS 45,802.1 billion (both exclude Zanzibar), so the national loan-to-deposit ratio eased from 94.3% to 91.6%. Credit equals about 19.6% of mainland GDP and deposits about 21.4% (TICGL calc., indicative). The zonal split is the interesting part. Dar es Salaam holds 62.8% of deposits (+32.0%) but only 51.5% of loans (+18.7%), a loan-to-deposit ratio of 75%. By contrast, deposits in Central (+0.9%) and Southern Highlands (-1.4%) stalled while loans grew 16.0% and 28.1%, taking their local loan-to-deposit ratios to 139% and 153%. Lake zone loans grew fastest (+39.0%). Banks are therefore moving Dar es Salaam funding into the regions, which is positive for regional investment but also a funding-concentration exposure.
Zone (TZS bn)
Deposits 24/25
Deposits 25/26
Change
Loans 24/25
Loans 25/26
Change
Loans/ deposits
Central
4,457.0
4,498.9
+0.9%
5,381.3
6,244.4
+16.0%
139%
Dar es Salaam
23,800.9
31,412.2
+32.0%
19,861.6
23,578.9
+18.7%
75%
Lake
3,973.0
5,254.2
+32.2%
4,814.4
6,693.9
+39.0%
127%
Northern
4,372.8
5,361.9
+22.6%
3,497.5
4,322.6
+23.6%
81%
South Eastern
1,212.4
1,604.4
+32.3%
1,636.2
2,056.3
+25.7%
128%
Southern Highlands
1,920.7
1,893.8
-1.4%
2,268.8
2,906.1
+28.1%
153%
Total (excl. Zanzibar)
39,736.8
50,025.3
+25.9%
37,459.9
45,802.1
+22.3%
92%
Source: Banks via BoT Tables 6.1 and 6.2; loan-to-deposit ratios are TICGL calc. on zone-booked deposits and loans.
Percent: loans booked in the zone / deposits booked in the zone (TICGL calc.)
Growth in Deposits vs Loans by Zone
Percent change 2024/25 to 2025/26 (TICGL calc.)
Who Gets the Credit? Lending by Activity
Share of total bank lending, 2025/26, percent. Source: BoT Table 6.3
Personal loans take 35.0% of lending, wholesale and retail trade 15.7%, and agriculture 12.9%; manufacturing gets 8.3%, transport and communication 5.4%, building and construction 3.7% and mining 2.6%. Agriculture is the main borrower in Central (4.9% of total lending is booked there), manufacturing and transport in Dar es Salaam, and mining in Dar es Salaam and Lake (1.1% each). Personal and trade lending together are 50.7% of the book, which is consistent with strong household and trading demand but is not the same as investment finance.
6.4 Agent banking
The agent network grew 25.6% to 195,345 agents, with the fastest growth in South Eastern zone (+46.6% to 17,778) and Central (+29.7%). Cash deposits through agents rose 12.6% to TZS 103.3 trillion and cash withdrawals 30.2% to TZS 45.4 trillion, but transaction counts barely moved for deposits (+1.3% to 108.0 million) and rose 7.0% for withdrawals (66.9 million), so the growth is in the size of transactions (average deposit TZS 956,000, up 11.1%; average withdrawal TZS 679,000, up 21.7%), not in more customers served. Transactions per agent fell about 18% (from 1,087 to 895), a sign that the network is expanding faster than usage. Dar es Salaam has about 102 agents per 10,000 people against 18 in Lake zone and 20 in Central (TICGL calc. on implied zonal population).
Zone
Agents 24/25
Agents 25/26
Change
Cash deposits 25/26 (TZS bn)
Cash withdrawals 25/26 (TZS bn)
Agents per 10,000 people
Central
20,340
26,378
+29.7%
12,801.0
6,048.0
20.5
Dar es Salaam
48,144
59,966
+24.6%
32,644.0
12,549.1
102.1
Lake
33,112
38,885
+17.4%
24,099.1
9,672.5
18.4
Northern
22,019
28,038
+27.3%
12,618.6
5,642.5
29.3
South Eastern
12,127
17,778
+46.6%
6,727.1
3,894.8
24.4
Southern Highlands
19,833
24,300
+22.5%
14,397.1
7,629.5
26.1
Total
155,575
195,345
+25.6%
103,286.9
45,436.3
29.6
Source: Bank of Tanzania, BoT Table 6.4 and Annex 5 (excludes Zanzibar); agents per 10,000 people is TICGL calc. using zone population implied by GDP / GDP per capita.
Bank Agents by Zone
Number of agents, stacked. Source: BoT Table 6.4
Agent Cash Deposits and Withdrawals
TZS trillion. Source: BoT Table 6.4
Financial Access Gap: Agents per 10,000 People
Agents per 10,000 residents, 2025/26 (TICGL calc.)
TICGL/TERI reading
The revenue and credit data point to a system with momentum going into the next six months: tax collections 18.3% higher, deposits growing faster than loans, and a wider regional footprint. The two watch-points are funding concentration (the regions lend more than they collect) and credit quality, because personal and trade loans make up half the book while agent-banking usage per agent is falling. Neither the report nor TICGL has non-performing-loan data by zone, so credit risk is a data gap to monitor in Tab 7.
07 — Six-Month OutlookWhat Happens Next? October 2026 - March 2027 Scenarios
This tab turns the June 2026 data into scenarios for October 2026 - March 2027, the six months after this page was prepared. The latest hard data in the BoT report end in June 2026, so each scenario starts from the June base and is projected forward on simple, transparent rules that anyone can reproduce from the tables in Tabs 2-6. They are scenarios, not forecasts of record, and they should be checked against NBS and BoT releases for July-September 2026 as those become available.
7.1 Inflation: base effects and the April 2026 fuel step
We project each zone's CPI index forward from June 2026 at three monthly rates and divide by the index twelve months earlier (Annex 3). The three rates are anchored to the data: Relief (0.0% a month: prices plateau at the June level as fuel eases and the harvest arrives), Base (+0.25% a month, below the 24-month average of about 0.37% because of the 133% food self-sufficiency ratio) and Stress (+0.5% a month, the April-June 2026 pace). The April 2026 step is already in the index, so year-on-year inflation does not fall back automatically: it only declines as the low-inflation months of late 2025 and early 2026 drop out of the base.
Average Zonal Inflation Outlook, July 2026 - March 2027
Percent, year-on-year; simple average of six zones (not the national rate). June 2026 = 4.7%. Dashed lines = 3-5% target band. TICGL scenarios
Zone
Jun-26 actual
Relief Dec-26
Relief Mar-27
Base Dec-26
Base Mar-27
Stress Dec-26
Stress Mar-27
Central
5.2
3.3
0.9
4.9
3.2
6.5
5.6
Dar es Salaam
6.2
4.4
3.1
6.0
5.5
7.6
7.9
Lake
3.0
2.2
1.1
3.7
3.4
5.3
5.8
Northern
3.3
3.3
1.5
4.9
3.8
6.5
6.2
South Eastern
2.6
2.3
0.1
3.8
2.4
5.4
4.7
Southern Highlands
8.0
3.4
2.0
5.0
4.4
6.5
6.7
Simple average of zones
4.7
3.1
1.5
4.7
3.8
6.3
6.1
Source: TICGL calc. from BoT Annex 3 (CPI index) and Annex 4. Year-on-year % = projected index / index twelve months earlier. Zonal CPIs have different weights, so the simple average is indicative only.
Dar es Salaam is the outlier. It starts at 6.2% and stays above 5% through March 2027 in the base case (5.5%) and above 7% in the stress case, because its index has risen every month since late 2025 and the base keeps rising slowly.
Central and Southern Highlands normalise fastest. Their April 2025 price falls created low bases that disappear in April 2026; in the base case Central drops from 5.2% to 3.2% and Southern Highlands from 8.0% to 4.4% by March 2027.
The band is at risk in October-November. In the base case the average zone peaks near 5.4% in those two months, because the flat-price months of late 2025 form the base while the post-shock level keeps rising; a flat price level keeps it at or below 4.4%.
What would change the path: pump-price direction (diesel moves transport and food costs), the pace at which Southern Highlands and Central surplus grain reaches deficit zones, and any non-food pass-through in Dar es Salaam, where non-food inflation is already 6.2%.
7.2 Public revenue: another strong half-year
Tax collections averaged TZS 3,021 billion a month in 2025/26 (TZS 36,250.4 bn, +18.3%). Applying three growth rates to that run-rate, with flat seasonality (a simplification), gives the six-month collection for October-March shown below. Even the low case (+8%) means about TZS 19.6 trillion over six months, because the 2025/26 outturn already sits TZS 2.4 trillion above target.
Scenario (TZS billion)
FY2026/27 total
Monthly average
Six months Oct-Mar
Low (+8% on 2025/26)
39,150
3,263
19,575
Central (+12%)
40,600
3,383
20,300
High (+18%, repeat of 2025/26)
42,775
3,565
21,388
Source: TICGL calc. on BoT Table 4.1; scenarios are run-rate illustrations, not Ministry of Finance or TRA projections.
Tax Revenue: Outturn and Scenarios
TZS trillion. 2025/26 target and actual; FY2026/27 scenarios (TICGL calc.)
7.3 Credit and deposits: growth continues, funding gets tighter
Loans grew 22.3% and deposits 25.9% in 2025/26. Projecting the end-March 2027 stock (nine months after the June 2026 base, so a factor of (1+g) to the power 0.75) at three annual growth rates gives the ranges below. A key watch-point is the loan-to-deposit ratio: if loans grow 25% while deposits grow 15%, the national ratio rises from 91.6% to about 98% by March 2027.
Scenario (TZS billion, end-Mar 2027)
Loans
Deposits
Loans / deposits
Cooling (loans +15%, deposits +15%)
50,864
55,554
91.6%
Central (loans +20%, deposits +22%)
52,514
58,071
90.4%
Hot (loans +25%, deposits +30%)
54,146
60,904
88.9%
Funding squeeze (loans +25%, deposits +15%)
54,146
55,554
97.5%
Source: TICGL calc. from BoT Tables 6.1 and 6.2 (June 2026 base: loans 45,802.1, deposits 50,025.3). Excludes Zanzibar.
7.4 Gold, tourism and electricity: the external and energy swing factors
Gold. Applying the 2025/26 volume growth (+5.7%) and a range of unit-value changes to 2025/26 gold recovery of USD 4,833.5 million gives the annual sensitivity below. Because price explained about 90% of the 2025/26 gain, the outlook for mining revenue, the Lake zone and the cross-border surplus is mostly a gold-price call.
Gold scenario (USD million a year)
Gold recovery value
Change vs 2025/26
Growth
Unit value -20%
4,087
-746
-15.4%
Unit value -10%
4,598
-235
-4.9%
Unchanged
5,109
276
+5.7%
Unit value +10%
5,620
786
+16.3%
Source: TICGL calc. on BoT Table 3.7a; 12-month illustration with volume +5.7%. Half of each annual figure approximates a six-month value.
Tourism. If visitors grow 5%, 7.5% or 10% in 2026/27 (2025/26: +7.5% to 2.449 million), arrivals reach 2.57, 2.63 or 2.69 million, and park earnings at constant TZS 336,400 per visitor reach TZS 865 bn, 886 bn or 906 bn. The risk is that growth depends on non-resident arrivals (76.5% of visitors) and on air and road capacity into the Northern zone.
Electricity. With hydro at 67% of generation and gas production 22% below its 2022/23 peak, the short-rains season is the main variable: a weak season would lift thermal burn and imports (already 613 GWh, 4.4% of supply), while good rains would keep the 2025/26 pattern of surplus hydro and falling gas use at power plants.
7.5 Six-month outlook matrix
Indicator
Latest (BoT report)
Six-month view (TICGL scenarios)
Swing factor
Direction
Headline inflation
Zones 2.6-8.0% (Jun-26)
Average zone peaks near 5.4% in Oct-Nov (base), easing to 3.8% by Mar-27; Dar es Salaam stays above 5%
Pump prices; base effects
Rises, then eases
Food prices
Maize +9.9%, rice +12.6%, millets +15-36%
Easing at harvest as SSR is 133% and NFRA holds 0.49 m t; logistics keep deficit zones higher
Fuel; NFRA buying (-68.5%)
Easing
Tax revenue
TZS 36.25 tn, +18.3%, 107.1% of target
Six-month collection of TZS 19.6-21.4 tn; strong direct-tax growth (+32.5%)
Import prices; compliance
Up
Bank credit
TZS 45.8 tn, +22.3%
Loans of TZS 51-54 tn by Mar-27; loan/deposit ratio 89-98%
Deposit growth; credit quality (no NPL data)
Up, funding tighter
Mining and gold
USD 5.6 bn, +43.3%; gold 86.3%
Value tracks gold price; volume +5-6% trend; non-gold minerals soft
World gold price; small-scale supply
Price-driven
Manufacturing
TZS 21.25 tn, +18.9%
Food, beverage, tobacco and cement lead; plastics, textiles, sheets weak
Fuel and input costs
Up, narrow
Tourism
2.45 m visitors, +7.5%; TZS 823.9 bn
Peak-season gains of +5-10% in arrivals, led by non-residents
Air capacity; resident demand (-46% from peak)
Up
Electricity and gas
14.1 TWh, +10.4%; hydro 67%
Stable if short rains hold; imports and thermal rise if not
Hydrology; Songo Songo decline
Stable, weather-dependent
Trade and ports
Surplus TZS 11.8 tn; cargo 39.4 m t, +26.6%
Cargo growth continues with Bagamoyo and Mafia ports; surplus tied to gold
Gold price; DRC corridor
Up
Source: TICGL/TERI synthesis of Tabs 2-6; directions are analytical judgements on the scenario ranges above.
Bottom line
The most likely six months combine strong real activity (revenue, credit, trade, tourism and manufacturing all growing at double-digit or high single-digit rates) with a price path that stays near or above the top of the 3-5% band until the base effects roll off in spring 2027. The largest downside risks are a repeat of the April-June fuel pace and a fall in the gold price; the largest upside is a harvest-driven easing of food prices.
08 — Risks & PolicyWhat Could Go Wrong and What To Do About It
The previous tabs show an economy that is growing fast and is heavily concentrated. This tab pulls the risks together, ties each to evidence in the BoT report, and sets out the policy instruments that would reduce them. Concentration is the common thread: on the 2025/26 data one zone, one port, one commodity or one product group carries most of the weight in a dozen areas.
Concentration Map: How Much Rides on One Zone, Port or Commodity?
Percent share of the national total, 2025/26 (BoT report tables; TICGL selection)
8.1 Risk register
Risk
Evidence in the BoT report
Likelihood (next 6 months)
Impact
Most exposed
Fuel-price pass-through
Pump prices from about TZS 2,800-2,900 (Feb-26) to 4,200-4,400 (Jun-26); April CPI step of 0.8-2.3% in five zones
High
High
Households in Dar es Salaam, Central and Southern Highlands; transport and food processors
Gold-price reversal
Gold 86.3% of mineral value; about 90% of the gain is price; Lake zone 85.6% of cross-border exports
Medium
High
Mining revenue, external surplus, Lake zone incomes
Hydrology and power supply
Hydro 67% of generation; Songo Songo gas output -44% since 2022/23; imports up 111%
Medium
High
Industry, Dar es Salaam, South Eastern generation zone
Regional food distribution
Surplus 3.87 m t in Southern Highlands vs deficits in Dar es Salaam (1.62 m t) and Lake cereals; NFRA purchases -68.5%
Medium
Medium
Deficit-zone consumers; farmers at harvest
Funding concentration in banking
Dar es Salaam 62.8% of deposits; Central and Southern Highlands loan/deposit ratios of 139% and 153%
Medium
Medium
Regional borrowers; banks
Credit mix and quality
Personal and trade loans 50.7% of the book; no zonal NPL data in the report
Medium
Medium
Banks, retail borrowers
Narrow tax base
Dar es Salaam 88.2% of collections; direct tax 18.9% of total
Low
Medium
Fiscal planning; local governments (Dar es Salaam LGA revenue 90.1% of target)
Logistics bottleneck
Dar es Salaam port 85.4% of cargo growing 26.5%; Mtwara cargo -13.7%
Northern-zone suppliers, tea and sisal growers, import-competing manufacturers
Source: TICGL/TERI analysis. Likelihood and impact ratings are analytical judgements (Low/Medium/High), not model outputs.
Upward pressures (growth, prices)
Downward pressures (relief)
Pump prices above TZS 4,000 a litre feed transport and food costs
Harvest-driven easing of cereal prices (SSR 133%, surplus 6.3 m t)
Rising non-food inflation in Dar es Salaam (6.2% in Jun-26)
Base effects as the April 2026 step passes into the index (spring 2027)
Electricity imports and thermal burn if rains disappoint
More hydro and solar capacity, and the Kenya interconnector, widening supply
Credit growth outpacing deposits in the regions
Deposits growing faster than loans nationally (+25.9% vs +22.3%)
Gold-linked exports and revenue exposed to price reversal
New ports (Bagamoyo, Mafia) and rising cargo volumes diversify trade
8.2 Policy instruments
Next six months
Monetary and price policy. Track the pump-price path and the zonal CPI baskets monthly; the Dar es Salaam non-food trend is the early warning.
Food policy. Restore NFRA buying at harvest in surplus zones and rebalance stocks toward Dar es Salaam and the Lake zone (only 19,721 t in Dar es Salaam).
Power policy. Publish reservoir and short-rains contingency plans; protect gas supply to industry (+19.9%) and CNG (+152%).
Revenue policy. Maintain compliance gains; review the 90.1% LGA outturn in Dar es Salaam.
Medium term (1-3 years)
Credit policy. Publish zonal credit-quality and loan-to-deposit data; steer lending from personal and trade toward manufacturing (8.3%) and agro-processing.
Logistics policy. Scale Tanga, Bagamoyo, Mtwara and the lake ports so Dar es Salaam is not 85% of cargo.
Industrial policy. Target import-substituting segments that are shrinking (plastics, textiles, iron sheets) with input-cost and quality support.
Domestic tourism. Recover resident visits (575,000 vs 1.08 m peak) with pricing and packages.
Longer term (to 2030)
Mining value chain. Convert gold-price windfalls into processing, local content and savings rules; grow non-gold minerals (limestone, graphite, nickel).
Regional growth poles. Close the per-capita gap (Dar es Salaam 3.9x Simiyu) with infrastructure and finance in Central, Lake and South Eastern zones.
Data. Add zonal GDP deflators, employment and non-performing-loan series to the BoT zonal report.
Energy mix. Keep hydro, solar, gas and interconnection balanced to reduce weather risk.
"Tanzania's 2025/26 numbers show growth that is real and fast. The question for the next six months is whether prices, power and logistics stay stable enough for that growth to reach the regions that produce the least per person."
— TICGL / Tanzania Economic Research Institute (TERI)
Conclusion
Tanzania ended 2025/26 with nominal GDP of TZS 234.1 trillion, tax revenue of TZS 36.25 trillion, TZS 50.0 trillion in deposits, a TZS 11.8 trillion cross-border surplus and a 133% food self-sufficiency ratio. For October 2026 to March 2027 the central scenario is continued strong activity with inflation near the top of the 3-5% band until base effects fade, a stable-to-tighter funding position in the regions, and two swing factors that matter most: the gold price and the short rains. The policy priority is to keep the price shock from spreading into non-food items while diversifying away from single zones, ports and commodities.
09 — What TICGL DoesFrom Zonal Data to Bankable Projects
TICGL (Tanzania Investment and Consultant Group Ltd), with its research arm TERI, turns national data of this kind into decision-grade work for investors, lenders and government: feasibility studies, market-entry advisory and market research and economic intelligence. This tab applies the zonal data in the BoT report as a first screen. It does not rank zones or recommend investments; it shows which indicators a feasibility or market study would need to test in each zone.
Zone
GDP 2025 (TZS tn)
GDP growth
Per-capita index
Pop. (m)
Loan growth
Loans / deposits
Tax growth
Mfg growth
Inflation Jun-26
Central
31.7
+10.3%
69
12.9
+16.0%
139%
+20.3%
+29.1%
5.2%
Dar es Salaam
39.8
+10.0%
191
5.9
+18.7%
75%
+17.3%
+33.5%
6.2%
Lake
61.0
+11.0%
82
21.1
+39.0%
127%
+17.3%
+18.9%
3.0%
Northern
40.3
+9.8%
119
9.6
+23.6%
81%
+24.3%
-13.2%
3.3%
South Eastern
24.1
+10.1%
93
7.3
+25.7%
128%
+54.1%
+17.7%
2.6%
Southern Highlands
37.2
+11.0%
112
9.3
+28.1%
153%
+27.4%
+0.9%
8.0%
Source: BoT zonal report (Tables 1.1, 1.2, 3.6a, 4.1, 6.1, 6.2, Annex 4); growth rates, ratios and implied population are TICGL calc.
Zone Screen: Income Level vs Credit Momentum
x = GDP per capita index (national = 100); y = loan growth 2025/26, %; bubble size = GDP 2025 (TICGL calc.)
9.1 What the data raises for each zone
Dar es Salaam
47.4% of manufacturing (TZS 10.1 tn, +33.5%), 62.8% of deposits, 102 agents per 10,000 people.
Highest income (index 191) but also highest price pressure: inflation 6.2%.
To test: consumer and industrial demand at higher unit costs; port-linked logistics capacity; margin sensitivity to fuel and power.
Lake
Largest economy (26.1%), 69.3% of mineral recovery, TZS 12.8 tn of cross-border exports, fish value TZS 302.9 bn.
Loans +39.0% but only 18 agents per 10,000 people; per-capita income at 82% of national.
To test: mineral-linked services, cold chain and fish processing, cereal supply (cereal SSR 96%), financial access.
Northern
64.9% of park visitors, 59.7% of park earnings, tax +24.3%; manufacturing -13.2%.
Income index 119; inflation 3.3%, inside the band.
To test: hospitality and tourism-supply chains, air capacity, and why plastics, textiles and coffee-and-tea products shrank.
Central
Largest livestock market (34.4%, TZS 1.2 tn), cured tobacco TZS 1.42 tn (+65.8%), mineral recovery +86.8%.
Deposits flat (+0.9%) while loans rose 16.0% (loans/deposits 139%); inflation 5.2%.
To test: livestock and tobacco value chains, local funding depth, Dodoma-driven demand.
South Eastern
46.8% of national electricity, 437,459 t of cashew procured, manufacturing 17.9% share, tax +54.1%, agents +46.6%.
New Bagamoyo and Mafia ports; mineral recovery -6.6%; inflation 2.6%, below the band.
To test: cashew processing, power-intensive industry, port-linked logistics, ceramics, steel and beverages demand.
Southern Highlands
95.7% of forest-product value (TZS 1.25 tn), SSR 222% (3.87 m t surplus), 278,216 t of NFRA stock, minerals traded +83.7%.
To test: storage, milling and transport, wood-products processing, and why a surplus zone has the highest food inflation.
9.2 How TICGL/TERI works with this evidence
Feasibility studies
Pre-feasibility and full feasibility across market, technical, financial, institutional, legal and risk components, with PPP structuring for public projects.
Financial models with NPV, IRR and DSCR, tested for fuel, power, exchange-rate and input-cost shocks of the kind shown in Tabs 2 and 7.
Demand and offtake analysis calibrated on zonal data such as GDP per capita, credit depth and cargo flows.
Market entry advisory
Zone and sector screening against indicators like those in the table above, then entry-mode choice: import and distribution, contract partner, joint venture or own plant.
Incentives, licensing and site mapping; partner and supplier identification.
Business facilitation from first meeting to registration and start-up.
Market research and economic intelligence
Demand sizing, price benchmarking and competitor mapping by zone and sector.
Scenario models updated with each Bank of Tanzania and NBS release, as in the six-month outlook in Tab 7.
Policy briefs and SEO-ready research publications for institutional clients through TERI.
Why this matters to investors and lenders
The same national growth rate can mean very different unit economics by zone: a plant in Dar es Salaam faces 6.2% inflation and the highest incomes, one in Southern Highlands faces 8.0% inflation and the lowest local deposit base, and one in the Lake zone faces the fastest credit growth with the thinnest agent network. A zone-level feasibility or market study is the low-cost way to avoid applying a national average to a local decision.
Talk to TICGL/TERI
Request a feasibility, market-entry or market-research scoping call for a project in any zone, or a fuller briefing on this report and the six-month outlook.
Source report. Bank of Tanzania, Consolidated Zonal Economic Performance Report for the Quarter Ending June 2026, Vol. 11 No. 2 (Tables 1.1-6.4 and Annexes 1-6). Underlying sources cited in the report: National Bureau of Statistics (GDP, CPI), Ministry of Agriculture and Ministry of Industry and Trade, National Food Reserve Agency, crop boards, Regional Administrative Secretary Offices, Tanzania Forest Services Agency, Mining Commission, TANAPA and NCAA, TANESCO, TPDC, Tanzania Revenue Authority, Tanzania Ports Authority, Tanzania Airports Authority, and commercial banks. TICGL calculations. Growth rates and shares from published values; implied population = GDP / GDP per capita; loan-to-deposit ratios from zone-booked stocks; gold unit value = value / quantity with volume effect valued at prior-year unit value; April 2026 inflation decomposition from Annex 3 index levels; earnings per visitor, fish price per tonne, transactions per agent and agents per 10,000 people. Outlook scenarios. Inflation: June 2026 zonal CPI index projected at 0.0%, +0.25% and +0.5% a month and divided by the index twelve months earlier; tax: 2025/26 run-rate with +8%, +12% and +18% growth; credit: stock at end-March 2027 at the stated annual growth rates (factor of 0.75 years); gold: 2025/26 volume growth (+5.7%) with unit value -20% to +10%; tourism: visitor growth of +5%, +7.5% and +10% at constant earnings per visitor. Limitations. Provisional data are subject to revision; some published totals differ slightly from the sum of rows (2021/22 tax revenue and some tourism earnings totals); zonal CPIs are not nationally weighted; Chart 1.2 fuel prices are read visually and are approximate; the report has no zonal non-performing-loan, employment or real-GDP series.
Bank of Tanzania, Consolidated Zonal Economic Performance Report, quarter ending June 2026 (Vol. 11 No. 2), Dodoma, 2026.
National Bureau of Statistics: regional GDP (Annexes 1-2) and zonal CPI (Annexes 3-4) as reproduced in the report.
World Bank commodity price data as cited in the report (gold: USD 4,249.6 per troy ounce, +50.4%).
11 - Quick AnswersFrequently Asked Questions
How big is Tanzania's economy and which zone is largest?
Mainland nominal GDP was TZS 234.1 trillion in 2025, up 10.4% from TZS 212.0 trillion in 2024. Lake zone is the largest at 26.1% of output, followed by Northern (17.2%) and Dar es Salaam (17.0%). Dar es Salaam has the highest GDP per capita at TZS 6.78 million, 1.91 times the national average of TZS 3.54 million.
What is inflation in Tanzania by zone?
Average headline inflation was 3.6% in 2025/26, inside the 3-5% target. Monthly data show a jump in April-June 2026 after pump prices rose sharply: by June 2026 year-on-year inflation was 8.0% in Southern Highlands, 6.2% in Dar es Salaam, 5.2% in Central, 3.3% in Northern, 3.0% in Lake and 2.6% in South Eastern.
What is the six-month outlook for Tanzania's economy, October 2026 to March 2027?
TICGL/TERI scenarios point to continued strong activity with inflation near the top of the 3-5% band. In the base case the average zonal inflation rate peaks near 5.4% in October-November 2026 and eases to about 3.8% by March 2027; a repeat of the April-June price pace keeps it above 6%. Tax collection, credit and trade keep growing at high single-digit to double-digit rates, with gold prices and the short rains as the main swing factors.
How much tax did Tanzania collect in 2025/26?
Tax revenue reached TZS 36,250.4 billion, 7.1% above the annual target and 18.3% above 2024/25. Direct taxes grew fastest (+32.5%). Dar es Salaam accounted for 88.2% of collections. Local government own-source revenue was TZS 1,656.4 billion, 99.4% of target.
Is Tanzania food secure?
Food crop production was 25.2 million tonnes in 2025/26, 6% higher, with a self-sufficiency ratio of 133% and a 6.3 million tonne surplus over 2026/27 requirements. Distribution is uneven: Dar es Salaam produces almost none of its 1.6 million tonne requirement, Lake zone has a cereal deficit, and National Food Reserve Agency purchases fell 68.5% to 137,612 tonnes.
What drove mineral and trade growth in 2025/26?
Mineral recovery rose 43.3% to USD 5.6 billion, with gold 86.3% of the total. A TICGL calculation shows about 90% of the gold increase came from higher unit values rather than volume (+5.7%). The cross-border trade surplus widened 80.9% to TZS 11.8 trillion on Lake zone exports of gold, rough diamonds and fish, and port cargo grew 26.6% to 39.4 million tonnes.
12 - Explore MoreTICGL Economic: Related Insights & Tools
Related Analysis
What Opportunities and Risks Define Doing Business in Tanzania in 2026?
Investment-climate assessment: the risks and opportunities behind this zonal picture.
Uchumi wa Tanzania kwa kanda, 2025/26. Kwa mujibu wa Ripoti ya Benki Kuu ya Tanzania (BoT) ya Utendaji wa Kiuchumi wa Kanda (robo iliyoishia Juni 2026), Pato la Taifa kwa bei za soko lilifikia shilingi trilioni 234.1 mwaka 2025, ongezeko la asilimia 10.4. Kanda ya Ziwa ndiyo kubwa kuliko zote (asilimia 26.1), ikifuatiwa na Kaskazini na Dar es Salaam. Pato kwa kila mtu ni shilingi milioni 3.54 kwa wastani, na Dar es Salaam inafikia milioni 6.78.
Bei na mfumuko wa bei: Mfumuko wa bei wa wastani ulikuwa asilimia 3.6 mwaka 2025/26, ndani ya lengo la asilimia 3-5. Hata hivyo, kuanzia Aprili hadi Juni 2026 bei za mafuta zilipanda kutoka takriban TZS 2,800-2,900 hadi TZS 4,200-4,400 kwa lita, na ifikapo Juni 2026 mfumuko ulikuwa asilimia 8.0 Nyanda za Juu Kusini, 6.2 Dar es Salaam na 5.2 Kati.
Chakula: Uzalishaji wa mazao ya chakula ulifikia tani milioni 25.2 (ongezeko la asilimia 6), na uwiano wa kujitosheleza ni asilimia 133. Hata hivyo, uzalishaji ulipungua Kati (asilimia 8.8) na Nyanda za Juu Kusini (asilimia 11.3), na ununuzi wa NFRA ulishuka kwa asilimia 68.5.
Viwanda, madini na nishati: Thamani ya bidhaa za viwandani iliongezeka asilimia 18.9 hadi TZS trilioni 21.25. Madini yalipanda asilimia 43.3 hadi dola bilioni 5.6, na dhahabu ni asilimia 86.3; takriban asilimia 90 ya ongezeko la dhahabu ilitokana na bei, si wingi. Uzalishaji wa umeme ulikua asilimia 10.4, na umeme wa maji sasa ni asilimia 67 ya uzalishaji.
Utalii, biashara na bandari: Wageni wa hifadhi walifikia milioni 2.45 (asilimia 7.5) na mapato TZS bilioni 823.9. Ziada ya biashara na nchi jirani ilifikia TZS trilioni 11.8 (asilimia 80.9), na shehena ya bandari ilipanda asilimia 26.6 hadi tani milioni 39.4.
Mapato na benki: Makusanyo ya kodi yalifikia TZS trilioni 36.25 (asilimia 107.1 ya lengo). Amana za benki zilikua asilimia 25.9 hadi TZS trilioni 50.0 na mikopo asilimia 22.3 hadi trilioni 45.8. Dar es Salaam ina asilimia 62.8 ya amana na inakusanya asilimia 88.2 ya kodi.
Miezi sita ijayo (Oktoba 2026 - Machi 2027): Katika hali ya msingi, mfumuko wa bei wa wastani wa kanda unafikia kilele cha takriban asilimia 5.4 Oktoba-Novemba na kushuka hadi takriban asilimia 3.8 ifikapo Machi 2027; ikiwa bei zitaendelea kupanda kwa kasi ya Aprili-Juni, utabaki juu ya asilimia 6. Kodi, mikopo, biashara na utalii vitaendelea kukua. Mambo mawili yanayoweza kubadilisha mwelekeo ni bei ya dhahabu na mvua fupi (kwa umeme wa maji).
Mapendekezo: (1) Kufuatilia bei za mafuta na mfumuko wa bei wa bidhaa zisizo za chakula kila mwezi; (2) kurejesha ununuzi wa NFRA wakati wa mavuno na kusogeza akiba kwenye kanda zenye upungufu; (3) mpango wa dharura wa umeme kwa mvua fupi; (4) kuchapisha takwimu za ubora wa mikopo kwa kanda; (5) kupanua bandari ili Dar es Salaam isibebe asilimia 85 ya shehena; (6) kutumia faida ya dhahabu kujenga viwanda vya kuchakata na akiba. TICGL/TERI hutoa upembuzi yakinifu (feasibility), ushauri wa kuingia sokoni na utafiti wa soko kwa kanda yoyote.
Hitimisho: Uchumi unakua kwa kasi na kwa upana, lakini unategemea maeneo machache (Dar es Salaam, bandari moja, dhahabu). Changamoto ya miezi sita ijayo ni kuzuia mshtuko wa bei za mafuta usisambae kwenye bidhaa zisizo za chakula na kupunguza utegemezi wa kanda, bandari na bidhaa moja.
Pato la Taifa 2025: TZS trilioni 234.1 · ukuaji asilimia 10.4
Mfumuko Juni 2026: asilimia 2.6 hadi 8.0 kwa kanda · uwiano wa chakula: asilimia 133
Hali ya msingi Machi 2027: mfumuko wa wastani wa kanda takriban asilimia 3.8
Chanzo: Benki Kuu ya Tanzania, Ripoti ya Utendaji wa Kiuchumi wa Kanda (Juni 2026); NBS; TRA; TERI/TICGL, Oktoba 2026. Kwa maelezo zaidi: economist@ticgl.com.
Tanzania Medicine Import Bill: USD 295 Million a Year | TICGL/TERI
TICGL/TERI Health Economy & TradePharmaceutical ImportsLocal ManufacturingOutlook to 2030
What Does Tanzania Pay Abroad for Medicines? The USD 295 Million Import Bill
Tanzania imports most of the medicines its hospitals, clinics and pharmacies dispense. On Bank of Tanzania data the bill is about USD 295 million a year, or USD 24.6 million (about TZS 65 billion) every month. It has been flat in dollars since 2021 but not in shillings, India supplies over half of it, and local factories meet only 10-20% of demand. This report sets out the bill, why published figures range from USD 130 million to USD 1 billion, who supplies the medicines, what local production could save, and where the bill is heading to 2030.
📅 Data to: August 2026📍 Dar es Salaam, Tanzania🏛️ TICGL / TERI📖 Source: Bank of Tanzania, UN COMTRADE/UNCTAD, MoH and industry sources
Annual bill (YE Aug 2026p)
USD 295.0 m +0.8% y/y
Monthly bill
USD 24.6 m ≈ TZS 65 bn
Share of goods imports
1.66% from 2.57% in 2022
2030 bill range
237-469 m USD a year
Source: Bank of Tanzania, Monthly Economic Review, September 2026 (Table A7); TERI calculations. p = provisional. Shilling values use the August 2026 average rate of TZS 2,657 per USD.
Disclaimer & scope
Prepared by TERI for research and strategic-information purposes only. It is not investment, legal, tax, medical or financial advice and does not state the position of the Bank of Tanzania, the Ministry of Health, the Medical Stores Department or the Government. Where TICGL/TERI computes a figure it is marked "TICGL calc." Projections and import-substitution figures are illustrations, not forecasts of record. Figures for 2015-2020 and some COMTRADE values come from TICGL working notes and have not been independently re-verified.
00 — OverviewExecutive Summary
Tanzania pays about USD 295 million a year for imported pharmaceutical products. That is large in health terms and modest in macro terms: it is 1.7% of goods imports, about one-twelfth of the petroleum bill and 5% of gold export earnings. The binding constraint is health security and supply reliability, not foreign exchange alone.
Annual bill
USD 295 m
≈ TZS 784 bn a year
Monthly bill
USD 24.6 m
≈ TZS 65 bn a month
India's share
54-59%
of imports by value
Local share of demand
10-20%
Targets: 50-80% by 2030
Central finding
The medicine bill is flat in dollars (USD 280-340 million since 2021) but not in shillings: the dollar bill fell from USD 340 million (2022) to USD 295 million (2024) while the shilling weakened from about TZS 2,300 to TZS 2,600 per USD, so the shilling bill stayed in a TZS 680-785 billion band. Exchange-rate moves, not volumes, dominate what the Treasury and the Medical Stores Department (MSD) feel. Over 2021-2025 the country spent more than USD 1.5 billion on pharmaceutical imports.
Three Measures of the "Medicine Bill"
USD million: official BoT line vs customs-based HS 30 vs government/media "medicines" headline
Monthly Bill in 2030 by Scenario
USD million a month; today = 24.6 (TERI scenarios)
Key findings
Large in health terms, modest in macro terms. USD 295 million is 1.7% of goods imports (USD 17.8 bn), equal to about 5% of gold export earnings (USD 5.6 bn) and 5% of gross official reserves (USD 5.9 bn).
India dominates supply. India supplies roughly 54-59% of imports by value; India's own export data record USD 283 million of pharmaceutical exports to Tanzania in 2025. China, Kenya, South Africa and Europe follow.
Local production is thin. Domestic factories meet an estimated 10-20% of demand. 2030 targets (80% of health products, at least 65% of medicines, at least 50% of hospital medicines) are ambitious and not yet mutually consistent.
Projections to 2030 span USD 237 to 469 million a year. In the 5.4% mid-case the 2030 bill is USD 405 million (USD 33.7 million a month) and 2025-2030 spending is USD 2.14 billion. Observed data so far track the flat path.
Import substitution is worth real money, but not all of it is saved. Moving the local share from about 15% to 50% cuts finished-product imports by about USD 122 million a year, of which about USD 73 million is a net foreign-exchange saving once imported active ingredients and packaging are netted off; at 80% the net saving is about USD 135 million.
Two corrections to earlier working notes
1. The mid-case cumulative 2025-2030 spend is USD 2,138.5 million, not USD 1,900.0 million; the annual figures were right and only the sum was mis-added. 2. The 5.4% growth rate attributed to 2017-2022 is a market-size growth rate from sector reports; BoT's import series grew only about 0.9% a year over that period (USD 326 million to USD 340 million). TERI keeps 5.4% as a deliberately stressed mid-case but does not present it as the observed trend.
01 — What Tanzania SpendsThe Bill: Annual, Monthly and in Shillings
BoT's September 2026 Monthly Economic Review reports pharmaceutical imports of USD 295.0 million in the year ending August 2026 (provisional), up slightly from USD 292.8 million a year earlier and USD 278.2 million in 2024. Dividing by twelve gives USD 24.6 million a month. "Pharmaceutical products" is the line in BoT's import table (Table A7), valued f.o.b., within "other consumer goods".
Pharmaceutical Imports, 12 Months to August
USD million (bars) and share of total goods imports, % (line). Source: BoT Table A7; TERI calc.
Year ending Aug
Annual (USD m)
Monthly avg
Total goods imports
Share of goods imports
YoY change
2022
329.1
27.4
12,829.4
2.57%
n/a
2023
295.2
24.6
13,869.1
2.13%
-10.3%
2024
278.2
23.2
14,141.5
1.97%
-5.8%
2025
292.8
24.4
14,321.2
2.04%
+5.2%
2026p
295.0
24.6
17,771.7
1.66%
+0.8%
Source: Bank of Tanzania, Monthly Economic Review, September 2026, Table A7; TERI calculations. p = provisional.
1.1 Calendar-year view and the shilling
BoT's calendar-year series gives USD 329.9 million (2021), USD 340.4 million (2022), USD 286.2 million (2023) and USD 295.3 million (2024). Adding a provisional USD 269.9 million for the year to September 2025 (as quoted in coverage of the Ministry of Health's local-manufacturing directive), five years of data sum to more than USD 1.5 billion, the figure The Citizen reported from the same BoT review.
Calendar-Year Bill in Dollars and Shillings
USD million (bars) and TZS billion (line), 2021-2024
Average Exchange Rate
TZS per USD, annual average (BoT Table A1)
Year
USD million
Avg TZS per USD
TZS billion (approx.)
2021
329.9
2,297.8
758
2022
340.4
2,303.0
784
2023
286.2
2,382.1
682
2024
295.3
2,597.4
767
Source: BoT MER Oct 2025 (imports) and Sep 2026 Table A1 (annual average exchange rate); TERI calculations. 2025 average rate: TZS 2,537.6.
Why the Treasury and MSD see little relief
The shilling depreciated 6.7% year on year to August 2026, so a flat dollar bill implies a rising shilling bill. Holding the USD 295 million bill constant, every move of 100 shillings per dollar changes the annual shilling cost by about TZS 29.5 billion (TICGL calc.).
Shilling Cost of a Constant USD 295 Million Bill
TZS billion a year at different exchange rates (TICGL calc., illustrative sensitivity, not a forecast)
1.2 Perspective: how big is the bill?
The Medicine Bill Against Other Large Flows
USD million, 12 months to August 2026 (BoT; logarithmic scale)
Item
USD million
Pharma bill as share/multiple
Pharmaceutical imports
295.0
—
Total goods imports (f.o.b.)
17,771.7
1.7% of goods imports
Petroleum products imports
3,425.6
Petroleum is 11.6 times larger
Insecticides and similar products imports
177.8
Pharma is 1.7 times larger
Gold exports
5,625.0
Pharma equals 5.2% of gold exports
Gross official reserves (Aug 2026)
5,888.2
Pharma equals 5.0% of reserves
Source: BoT MER September 2026 (Tables A7, A6, text); TERI calculations. For the gold-export side of the picture see TICGL's analysis of gold dependence in the related insights below.
02 — TriangulationWhy Published Figures Range From USD 130 Million to USD 1 Billion
Anyone searching for "how much Tanzania spends on medicine imports" will find figures from USD 130 million to more than USD 1 billion. They are not all measuring the same thing. TERI ranks sources as follows: (1) Bank of Tanzania publications, because they are official, current and revised openly; (2) UN COMTRADE and UNCTAD, for cross-checks and partner breakdowns; (3) ministry, MSD and press statements, for policy and context; (4) commercial shipment databases, which cover only part of trade and are not used in totals.
Competing Figures for the Medicine Import Bill
USD million, by source and period (see table for what each measures)
Source / series
Period
USD m
What it measures
BoT, pharmaceutical products (rolling)
YE Aug 2026
295.0
Official f.o.b. import line; latest provisional
BoT, calendar year
2024
295.3
Revised; was first published at 258.2
BoT, fiscal year
2024/25
285.6
Year to June 2025, provisional
WITS / COMTRADE, HS 30
2025
385.3
Customs-based, all of Chapter 30 (TICGL note)
WITS / COMTRADE, HS 30
2023
444.4
Customs-based (TICGL note)
UNCTAD / CEIC, "Medicament"
2025
253.9
Narrower: finished medicines only (343.7 in 2024)
UNCTAD / CEIC, "Medicinal and pharma. product"
2025
129.3
Narrower class (197.7 in 2024)
India-reported exports to Tanzania, HS 30
2025
282.9
Partner (mirror) data from the supplier side
Media and government, "medicines"
Annual
~1,000
Includes medical devices, consumables, other health products
Commercial shipment databases, HS 3004
Apr 2025-Mar 2026
~118
Partial shipment coverage; not used in totals
Sources: BoT MERs; CEIC/UNCTAD; TradingEconomics (UN COMTRADE); The Citizen; TICGL working notes. YE = year ending. HS 30 covers medicaments (HS 3003 and 3004), vaccines, blood products, wadding and bandages; medical devices and consumables sit mostly in Chapter 90 and are outside these figures.
2.1 TERI's reading
BoT is the best official anchor. It is current to August 2026, revised in public and consistent with the balance of payments. TERI uses USD 295 million a year (USD 24.6 million a month) as the central estimate; the plausible range is USD 280-400 million a year.
Customs-based HS 30 totals run higher. India's reported exports to Tanzania alone (USD 283 million) are about 96% of BoT's whole pharmaceutical line. That suggests the BoT line is narrower than Chapter 30 or captures consignments differently (for example duty-exempt and donor-funded imports, vaccines and blood products). This is an interpretation, not a reconciled fact.
Revisions are material. The 2024 figure was first published at USD 258.2 million (January 2025) and now stands at USD 295.3 million, a 14% upward revision. Early provisional readings of the latest year should be treated as lower bounds.
The USD 1 billion headline is not comparable. It is roughly 3.4 times the BoT pharmaceutical line. The published sources reviewed do not decompose it, so TERI treats the gap (about USD 700 million) as medical devices, consumables, reagents and other health products plus coverage differences, and recommends that the Ministry of Health and MSD publish the breakdown.
Aggregator sites that list pharmaceutical products at about USD 650 million (4.3% of imports) were reviewed and rejected: the figure is not corroborated by BoT, COMTRADE or UNCTAD.
03 — The TrendTen-Year Trend: Growth, Plateau, Soft Landing
Longer-run values combine BoT figures for 2021-2026 with indicative earlier estimates from TICGL's working notes. The earlier years rest on older mirror data and approximate ranges and should be read as orders of magnitude, not exact values.
Pharmaceutical Import Bill, 2015-2026
USD million a year. Light bars = indicative ranges (TICGL working notes); solid bars = point values (2017 indicative; 2021-2026 Bank of Tanzania)
Year
Annual bill (USD m)
Monthly equivalent
Confidence
2015
~155-200
13-17
Indicative
2016
~168-220
14-18
Indicative
2017
~326
27
Indicative
2018-2020
~300-450
25-38
Indicative (wide range)
2021
329.9
27.5
BoT
2022
340.4
28.4
BoT
2023
286.2
23.9
BoT
2024
295.3
24.6
BoT (revised)
12m to Aug 2026
295.0
24.6
BoT, provisional
Sources: BoT MERs (2021-2026); TICGL working notes (2015-2020). Calendar-year basis except last row.
Monthly Equivalent of the Bill
USD million a month, BoT calendar years and latest 12 months
Year-on-Year Change, 12 Months to August
Percent (TICGL calc., Table A7)
Rolling 12-Month Readings Reported by BoT
USD million. The September 2025 reading was an early provisional figure; early provisionals tend to be revised up
3.1 Three phases
Rapid growth, 2015-2017
Bill rises from roughly USD 155-200 million to about USD 326 million.
Demand for malaria, antibiotic, HIV and chronic-disease medicines expands as public health programmes scale up.
Plateau, 2018-2022
Volatile but broadly USD 300-340 million on BoT data.
Peaks at USD 340.4 million in 2022.
Soft landing, 2023-2026
Falls to USD 278 million (12 months to Aug 2024), recovers to about USD 295 million.
A lower dollar bill does not mean lower need: it can reflect procurement timing, price and product mix, stock drawdowns, or more local and donor-funded supply.
Caution on growth rates
From 2021 to 2024 the BoT calendar series fell at about 3.6% a year; from the indicative 2017 level of USD 326 million to 2022 it grew only about 0.9% a year. Neither supports automatic extrapolation. The data available cannot separate price, volume, stock and local-supply effects: this is the main open research question.
04 — Supply & DemandWhere the Medicines Come From and What Drives the Bill
Tanzania's High Commissioner to India said in July 2025 that 85% of Tanzania's pharmaceuticals and 60% of its medical equipment are imported, with India the main source. MSD says it sources about 80% of medicines and 90% of medical supplies from abroad. The concentration creates a single-supplier exposure: a rupee, shipping or export-policy shock in India is a Tanzanian health-supply shock.
Largest supplier by far: generics, antibiotics, cardiovascular medicines, ARVs. India-reported exports to Tanzania USD 282.9m in 2025 (medicaments USD 251.0m; vaccines, blood products USD 25.3m).
Kenya
~6%
Regional supplier; about 6.3% in earlier TMDA data
China
2nd-3rd
Raw materials (APIs), consumables and health supplies; also generics
South Africa, South Korea
Smaller
Among the main HS 30 sources in WITS data
Germany and Europe
Smaller
Specialty and high-value products, some chronic-disease and oncology medicines
United States
Small
Niche and specialist products
Sources: TradingEconomics/UN COMTRADE; CEIC; TMDA data as cited in TICGL working notes; TanzaniaInvest.
What India Reports Selling to Tanzania, 2025
USD million, HS 30 (other = TICGL calc.: 282.9 less 251.0 less 25.3)
Top Import Classes, Mainland Tanzania 2013/14
USD million (PLOS ONE 2019, private-sector import study; dated but indicative)
4.1 What drives the bill
Anti-infectives, pain relief and antimalarials. In the most detailed published import study the top class was worth USD 180 million, followed by analgesics (USD 132 million) and antimalarials (USD 97 million): high-volume essential medicines carry much of the import value.
HIV, TB and chronic disease. ARVs and the growing burden of hypertension, diabetes and heart disease keep demand for long-term therapies rising.
Oncology and specialty medicines. Few patients but very high unit prices, so they weigh heavily in value even where volumes are small.
Procurement architecture. MSD annual spending of about TZS 590 billion (an older Citizen estimate), roughly 80% on imports, shows that public procurement alone is a large part of the bill. Private pharmacies and facilities add to it.
Exchange rate and freight. The shilling and rising freight costs (Middle East disruptions pushed national freight payments up about 29% year on year to USD 1.68 billion) raise the landed cost of every consignment.
05 — Import SubstitutionLocal Production, 2030 Targets and What They Are Worth
Local manufacturers meet an estimated 10-20% of national demand (The Citizen; Daily News), with up to 30% cited in some studies for essential medicines depending on method. TICGL's working notes count about 36 factories producing medicines, devices and health products, of which 11 make medicines. A national strategy for local manufacturing was launched by Ministry of Health directive on 24 November 2025, and the President committed to guaranteed MSD offtake for local producers when opening the 13th Parliament on 14 November 2025.
Local share today
10-20%
Up to 30% in some studies
Factories (TICGL notes)
~36
11 make medicines
Interested investors
50+
Reported; PIAT created
Bagamoyo land secured
1,000 acres
Via TISEZA
Local Share of Demand: Today, Targets and a Peer
Percent. Tanzania today shown at 15% (mid-point of the 10-20% estimate); targets are official statements on different bases; Egypt as reported
Statement on 2030 local-production targets
Source
80% local production of health products by 2030
Daily News; TMDA/MoH-linked reporting
At least 65% of medicines consumed made locally by 2030; 65% of medical equipment next year
Daily News (Deputy PS, Medicines)
At least 50% of hospital medicines and equipment made locally
The Citizen, Jan 2026 investment forum
Reduce dependence on imported medicines and equipment by 85% by 2030
Daily News
Cut imports from 80% to 50% by 2030 (earlier Chief Pharmacist target)
The Citizen (older statement)
Sources as listed; TERI compilation. Targets are not defined on a common basis (value vs volume, medicines vs all health products). TERI recommends one definition: share of national medicine demand by value, essential medicines list, tracked annually.
5.1 Delivery pipeline
More than 50 investors have reportedly expressed interest in pharmaceutical manufacturing, and the Pharmaceutical Investment Acceleration Taskforce (PIAT) was created to remove approval bottlenecks.
The Mloganzila Pharmaceutical Manufacturing Hub is hosting new plants (including products for HIV prevention, diabetes and hepatitis); 1,000 acres in Bagamoyo have been secured through TISEZA for a larger future development.
Peers show the scale of the task: Egypt reports meeting about 91% of its market domestically after decades of build-up; Algeria has nearly 230 pharmaceutical factories.
Reality check
Going from about 15% to 80% in four years would be an exceptional industrial achievement. TERI's scenarios therefore treat the targets as upside cases, not baselines.
5.2 What local production could change
Holding the 2024 market constant (about USD 347 million at import prices, assuming a 15% local share today) TERI asks what the import bill would be at higher local shares. It assumes 40% of the value of local output is itself imported (active ingredients, excipients, packaging), so only 60% of displaced imports is a net foreign-exchange saving. These two assumptions are TERI's and should be replaced with factory-level data as it becomes available.
Implied Import Bill and Savings at Different Local Shares
USD million a year, constant market (TERI illustration)
Local share of demand
Implied import bill
Gross import saving
Net FX saving (60%)
15% (today)
295.3
0.0
0.0
30%
243.2
52.1
31.3
50%
173.7
121.6
73.0
65%
121.6
173.7
104.2
80% (target)
69.5
225.8
135.5
Source: TERI illustration. Assumes constant market value (USD 347.4m), local share measured by value, and 40% import content of local output. USD millions.
How Much of the Saving Leaks Back Out as Imported Inputs?
USD million a year: net FX saving vs gross saving lost to imported active ingredients and packaging (gross minus net, TICGL calc.)
Two conclusions
First, the prize is real: a 50% local share is worth roughly USD 70 million of net foreign exchange a year and the 80% target more than USD 130 million. Second, it is smaller than the headline import bill suggests, because local manufacturing still depends on imported active ingredients. A pharmaceutical API and packaging strategy must sit alongside factory incentives.
06 — OutlookThe Medicine Import Bill to 2030: Four Scenarios
From the 2024 base of USD 295.3 million, TERI projects four paths: Low (-3.6% a year, the 2021-2024 trend), Flat (0%), Mid (+5.4% a year) and High (+8% a year, driven by chronic-disease growth and global price increases). The Flat path is included because observed data to August 2026 (USD 295.0 million) track it almost exactly. Formula: Bill(t) = 295.3 × (1+g)^(t-2024).
Scenario Paths for the Medicine Import Bill, 2024-2030
USD million a year; observed BoT 12-month readings (to August 2025 and 2026) shown as points
USD million
Low (-3.6%)
Flat (0%)
Mid (+5.4%)
High (+8%)
2025
284.7
295.3
311.2
318.9
2026
274.4
295.3
328.1
344.4
2027
264.5
295.3
345.8
372.0
2028
255.0
295.3
364.4
401.8
2029
245.8
295.3
384.1
433.9
2030
237.0
295.3
404.9
468.6
Monthly in 2030
19.8
24.6
33.7
39.1
Change 2024-2030
-19.7%
0%
+37.1%
+58.7%
Cumulative 2025-2030
1,561.4
1,771.8
2,138.5
2,339.6
Source: TERI calculations on BoT 2024 base (USD 295.3m). Scenarios are illustrative, not forecasts of record.
Cumulative Spend, 2025-2030
USD million
2030 Bill in Shillings
TZS billion a year at the Aug-2026 rate of TZS 2,657 per USD (TICGL calc., constant rate)
TICGL/TERI reading
Even in the low case Tanzania spends over USD 1.5 billion on medicine imports in the next six years; in the mid case, over USD 2.1 billion. The 2030 bill ranges from USD 237 million (about USD 20 million a month) to USD 469 million (about USD 39 million a month). Observed data so far sit closer to the low-to-flat scenarios than to the high one. These are dollar figures at a constant exchange rate; any further shilling depreciation would raise the shilling bill on top.
07 — Risks & PolicyWhat Could Push the Bill Up or Down, and What To Do
Upward pressures
Downward pressures
Population growth and rising chronic-disease burden (diabetes, hypertension, cancer)
Local production rising from 10-20% towards 30% or more
Higher global drug and raw-material prices; freight costs from Middle East disruption
MSD procurement preference and multi-year contracts for local producers
Shilling depreciation (6.7% year on year to August 2026) raises the TZS bill
Lower duties on active ingredients and inputs for local manufacturers
Supplier concentration: dependence on India and China exposes costs to their policies and currencies
GMP-certified plants winning durable market share and regional exports
Upward revisions to provisional data (2024 was revised up 14%)
Pooled procurement and price negotiation in the EAC and SADC
Source: TERI synthesis.
Recommendations
Immediate (next 12 months)
One authoritative dataset. BoT, TRA, MSD and TMDA agree a reconciled series for pharmaceuticals, devices and consumables, with a public bridge to the "USD 1 billion" headline.
One local-production target. Replace the 50/65/80/85% statements with one definition and an annual scorecard.
Predictable demand. Set a minimum local share in MSD and public-hospital procurement for essential medicines, reserved by value.
Hedge the shilling. MSD forward purchasing and diversified supplier currencies on a bill of about TZS 780 billion.
Medium term (1-3 years)
Finance manufacturers. Low-cost, long-tenor credit for equipment, GMP upgrades and working capital.
Cut input costs. Reduce duties and VAT friction on active ingredients and packaging.
Build the cluster. Complete Mloganzila and Bagamoyo with shared utilities, QC laboratories and testing services.
Diversify suppliers. Second-source qualification for critical medicines (Kenya, Egypt, Algeria, South Africa).
Longer term (to 2030)
Start where the volumes are. Antimalarials, antibiotics, ARVs and chronic-disease generics.
Train the workforce. Pharmacy, biotechnology and quality-control graduates with universities.
3-5 year offtake agreements with qualified local manufacturers so investors can finance plants against contracted demand.
Track five indicators: local share by value; import bill in USD and TZS; top-supplier share; number of WHO-prequalified or GMP-certified local plants; API import share.
"The question is not only how much Tanzania pays for medicines, but how much of that bill is set by decisions in Mumbai and the exchange rate rather than by decisions in Dodoma and Dar es Salaam."
— TICGL / Tanzania Economic Research Institute (TERI)
Conclusion
On the best official data Tanzania spends about USD 295 million a year (USD 24.6 million a month, roughly TZS 65 billion) importing pharmaceutical products, with customs-based measures as high as USD 385-445 million and the all-in health products bill near USD 1 billion. If current trends hold, Tanzania will spend between USD 1.6 and 2.3 billion on pharmaceutical imports between 2025 and 2030. Achieving the 2030 local-production targets would retain USD 70-135 million a year in net foreign exchange, but it requires more than factories: predictable public demand, affordable inputs, quality certification, skilled people and credible data to track progress.
08 — What TICGL DoesFrom Import Data to Bankable Pharmaceutical Projects
A USD 295 million import bill, a 10-20% local share and 2030 targets that range from 50% to 85% create a concrete investment question: which pharmaceutical projects are bankable, in which segments and with which entry route? TICGL (Tanzania Investment and Consultant Group Ltd), with its research arm TERI, turns the numbers in this report into decision-grade work in three technical service lines.
Feasibility Studies
Pre-feasibility and full feasibility for pharmaceutical plants (oral solids, liquids, injectables) and cluster infrastructure, including PPP structuring.
Financial models with NPV, IRR and DSCR, FX and input-cost escalation, and a factory-level import-content test replacing the 40% assumption used here.
Offtake and demand-risk analysis against MSD and public-hospital procurement.
GMP, regulatory and WHO-prequalification cost and timeline assessment; sensitivity on exchange rate, API prices and payment delays.
Market Entry Advisory
Segment screening by therapeutic class (antimalarials, antibiotics, ARVs, chronic disease) against import value and substitution potential.
Entry-mode choice: import and distribution, contract manufacturing, joint venture or own plant.
Incentives and site mapping (Mloganzila, Bagamoyo/TISEZA), registration pathway and tender-readiness.
Partner, API-supplier and second-source identification beyond India.
Market Research
Demand sizing and price benchmarking by product class, reconciling BoT, customs and procurement data.
Scenario models of the import bill and local share, updated with each Bank of Tanzania release.
Supplier-concentration and supply-risk studies; stakeholder and willingness-to-pay surveys.
Policy briefs and SEO-ready research publications for institutional clients.
Why this matters to investors and funders
The report shows the opportunity is real but narrower than the headline: of a USD 225.8 million gross saving at an 80% local share, only USD 135.5 million is a net foreign-exchange gain on current assumptions. Feasibility models that rely on the gross figure overstate the prize; a project-level import-content and offtake analysis is the low-cost way to avoid it.
Talk to TICGL/TERI
Request a feasibility, market-entry or market-research scoping call for a pharmaceutical or health-supply project, or a fuller briefing on this report.
Bank of Tanzania series. Table A7 in each Monthly Economic Review (f.o.b., USD million). Year-ending series: September 2026 MER (YE Aug), October 2025 MER (calendar 2021-2024 and YE Sep 2025p), July 2025 MER (fiscal years to June), January 2025 MER (first 2024p estimate of 258.2). Additional rolling readings: YE Jan 2026 = 298.9; YE Feb 2026 = 305.5. Exchange rates. Annual average TZS/USD from BoT Table A1 (2021: 2,297.8; 2022: 2,303.0; 2023: 2,382.1; 2024: 2,597.4; 2025: 2,537.6); August 2026 average 2,657.01. Import substitution. Market value M = 295.3 / (1 - 0.15) = USD 347.4 million; imports at local share s = M × (1 - s); net FX saving = (295.3 - imports) × 0.6. Not independently re-verified: 2015-2020 indicative values; WITS/COMTRADE 2023 and 2025 totals and India's USD 228.5 million; HS 3004 shipment data (about USD 118 million); the count of 36 factories and 11 medicine manufacturers. Limitations. Provisional data are subject to revision; BoT and HS 30 coverage differ; the split between public and private procurement, and between volume and price effects, is not available in the sources reviewed.
Bank of Tanzania, Monthly Economic Review, September 2026 (Tables A1, A6, A7; Sections 2.4, 2.7); October 2025; July 2025; January 2025; January, February and March 2026 issues.
CEIC / UNCTAD, Tanzania imports of medicament and medicinal and pharmaceutical products (2024, 2025); TradingEconomics / UN COMTRADE, India exports of pharmaceutical products to Tanzania, 2025.
The Citizen (local drug production strategy; investor forum Jan 2026; MSD and manufacturers); TanzaniaInvest (Nov 2025 directive; Tanzania-India Business Forum 2025); Daily News (local manufacturing strategy, Mloganzila hub, 2030 targets).
PLOS ONE (2019), Pharmaceuticals imports in Tanzania: overview of private sector imports (2013/14 data); TICGL working notes (Kiswahili research report on medicine import costs and 2025-2030 scenario note, Oct 2026).
10 — Quick AnswersFrequently Asked Questions
How much does Tanzania spend on imported medicines each year?
About USD 295 million in the 12 months to August 2026 (provisional), or USD 24.6 million a month (roughly TZS 784 billion a year, TZS 65 billion a month). Customs-based HS 30 data run higher: USD 385 million in 2025.
Is the medicine import bill USD 1 billion?
Not for medicines alone. The roughly USD 1 billion (TZS 2.6 trillion) headline covers medicines plus medical devices, consumables and other health products; pharmaceuticals are about 30% of it.
Which country supplies most of Tanzania's medicines?
India, with roughly 54-59% of imports by value (USD 282.9 million reported by India for 2025). China, Kenya, South Africa and Europe follow.
How much demand is met by local factories?
An estimated 10-20%, with up to 30% for essential medicines in some studies. Targets for 2030 range from 50% of hospital medicines to 80% of health products and are not defined on a common basis.
What will the bill be in 2030?
Between USD 237 million (low) and USD 469 million (high); the mid case is USD 405 million (USD 33.7 million a month). Cumulative 2025-2030 spending ranges from USD 1.56 to USD 2.34 billion.
How much foreign exchange would local production save?
At a 50% local share, about USD 73 million a year net; at 80%, about USD 135 million, after netting imported active ingredients and packaging (TERI assumption: 40% import content).
11 — Explore MoreTICGL Economic: Related Insights & Tools
Related Analysis
What Opportunities and Risks Define Doing Business in Tanzania in 2026?
Investment-climate assessment including import, currency and supply-chain risks.
Bili ya Uagizaji wa Dawa Tanzania. Kwa mujibu wa Benki Kuu ya Tanzania (BoT), Tanzania ilitumia takriban dola milioni 295 za Marekani kuagiza bidhaa za dawa kutoka nje katika miezi 12 hadi Agosti 2026 (takwimu za awali). Hii ni takriban dola milioni 24.6 kwa mwezi, au karibu shilingi bilioni 784 kwa mwaka (shilingi bilioni 65 kwa mwezi) kwa kiwango cha wastani cha TZS 2,657 kwa dola.
Kwa nini takwimu zinatofautiana: Takwimu za forodha (HS 30) zinaonyesha hadi dola milioni 385 (2025) na milioni 444 (2023). Kiasi cha “dola bilioni 1” kinachotajwa na serikali na vyombo vya habari kinahusu dawa pamoja na vifaa tiba, bidhaa za matumizi na bidhaa nyingine za afya; dawa pekee ni takriban asilimia 30. Kati ya mwaka 2021 na 2025 nchi ilitumia zaidi ya dola bilioni 1.5.
Imetulia kwa dola, haijatulia kwa shilingi: Bili ilishuka kutoka dola milioni 340 (2022) hadi milioni 295 (2024), lakini shilingi ilidhoofika kutoka takriban TZS 2,300 hadi TZS 2,600 kwa dola, hivyo bili ya shilingi ilibaki kati ya TZS bilioni 680 na 785. Kushuka kwa thamani ya shilingi kwa asilimia 6.7 kwa mwaka kunaongeza gharama bila kuongeza kiasi cha dawa.
Wauzaji: India ndiyo muuzaji mkuu kwa mbali (takriban asilimia 54-59 ya thamani); kisha China, Kenya, Afrika Kusini na Ulaya. Tegemeo hili kwa nchi moja ni hatari ya usalama wa upatikanaji wa dawa.
Uzalishaji wa ndani: Viwanda vya ndani vinakidhi asilimia 10-20 tu ya mahitaji. Malengo ya 2030 ni pamoja na asilimia 65 ya dawa na asilimia 80 ya bidhaa za afya kuzalishwa nchini, lakini hayana ufafanuzi mmoja. Kupandisha sehemu ya ndani kutoka asilimia 15 hadi 50 kungeokoa takriban dola milioni 73 kwa mwaka (fedha za kigeni halisi), na hadi asilimia 80 takriban dola milioni 135, baada ya kuondoa malighafi na vifungashio vinavyoagizwa.
Makadirio hadi 2030: Bili ya mwaka 2030 inaweza kuwa kati ya dola milioni 237 (kiwango cha chini) na milioni 469 (kiwango cha juu); hali ya kati ni dola milioni 405 (milioni 33.7 kwa mwezi). Matumizi ya jumla 2025-2030 ni dola bilioni 1.56 hadi 2.34. Takwimu halisi hadi sasa zinakaribia njia ya “tulivu”.
Mapendekezo: (1) Kuwa na takwimu moja rasmi ya uagizaji wa dawa; (2) lengo moja la uzalishaji wa ndani lenye ufafanuzi wazi; (3) uhakika wa soko kwa wazalishaji wa ndani kupitia MSD na mikataba ya miaka 3-5; (4) kupunguza kodi za malighafi (APIs) na vifungashio; (5) mikopo nafuu ya muda mrefu kwa viwanda; (6) kupanua wauzaji zaidi ya India; (7) kudhibiti hatari ya sarafu. TICGL/TERI hutoa upembuzi yakinifu (feasibility), ushauri wa kuingia sokoni na utafiti wa soko kwa miradi ya dawa.
Hitimisho: Bili ya dawa ni kubwa kwa afya ya umma lakini ndogo kwa uchumi mpana (asilimia 1.7 ya uagizaji wa bidhaa). Changamoto kuu ni usalama wa upatikanaji wa dawa, tegemeo kwa muuzaji mmoja na thamani ya shilingi, siyo fedha za kigeni peke yake.
Bili ya mwaka: dola milioni 295.0 · kwa mwezi: milioni 24.6 · TZS bilioni 784
Sehemu ya India: asilimia 54-59 · uzalishaji wa ndani: asilimia 10-20
Makadirio 2030: dola milioni 237 hadi 469 kwa mwaka
Akiba halisi ya fedha za kigeni (asilimia 50 / 80 ya soko la ndani): dola milioni 73 / 135
Chanzo: Benki Kuu ya Tanzania, Mapitio ya Kila Mwezi ya Uchumi, Septemba 2026; UN COMTRADE/UNCTAD; TERI/TICGL, Oktoba 2026. Kwa maelezo zaidi: economist@ticgl.com.
Tanzania Government Securities Market October 2026: TZS 33.6 Trillion Outstanding, 15-Year Bond 10.79% | TICGL/TERI
TICGL/TERI — Reading the Bank of Tanzania Weekly Financial Markets Reports, 28 Sep to 9 Oct 2026
TICGL/TERI Markets Series · Part 3 of 3Government SecuritiesTreasury Bonds & BillsYield Curve
Tanzania's Government Securities Market: Strong Bond Demand, a Weak Bill Auction
Outstanding government securities reached TZS 33.56 trillion on 9 October 2026, up TZS 0.16 trillion in a week, with banks (34.1%) and pension funds (30.1%) holding almost two thirds. At the 30 September auction the 15-year bond still drew 2.4 times the amount on offer, but its yield rose to 10.79%. A week later the Treasury bill auction was undersubscribed, with banks supplying 99.98% of bids. This final report in the series reads the two weekly reports to ask who is funding the Government, at what price, and what the yield curve says about the next auctions.
📅 Weeks: 28 Sep – 9 Oct 2026📍 Dar es Salaam, Tanzania🏛️ TICGL / TERI📖 Source: Bank of Tanzania, Domestic Financial Markets Weekly Reports
Outstanding securities
33.56 tn +0.16 tn w/w
15-yr bond yield (30 Sep)
10.79% +24 bps
T-bill auction cover (7 Oct)
0.80x undersubscribed
Banks' share of holdings
34.06% +0.44 pp w/w
Source: Bank of Tanzania, Domestic Financial Markets Weekly Reports (28 Sep–2 Oct and 5–9 Oct 2026), Section 3 and Tables 3–5. Stocks are shown in TZS trillions (tn) and auction flows in TZS billion (bn). Figures marked "TICGL calc." are derived from the published data.
Disclaimer & scope
Prepared by TERI for research and strategic-information purposes only. It is not investment, legal, tax or financial advice and does not state the position of the Bank of Tanzania. Holdings in the weekly reports are at face value and use the Bank's investor categories, so they differ from the Ministry of Finance domestic-debt figures in the Monthly Economic Review, which use a different basis and include non-securitised debt. Yields in the "yield curve" tab are weighted average yields from the latest auction of each tenor; the weekly reports do not state auction dates for every tenor, and the Bank's own secondary-market curve (Chart 10) is only shown graphically.
00 — OverviewExecutive Summary
The market is deep but concentrated. Bonds are 89% of the stock; banks and pension funds hold 64%; and in the latest bill auction banks were practically the only bidders. Demand is healthy at long maturities, but the price of long money is edging up.
Treasury bonds
29.99 tn
89.35% of stock
Treasury bills
3.57 tn
+4.3% in a week
Registered clients
34,605
+3,103 this fiscal year
Bank share of T-bill bids
99.98%
Retail: 0.02%
Central finding
Strong long-end demand (25-year bond cover of 3.49x, 15-year cover of 2.43x) coexists with a thin bill market (cover 0.80x), and one plausible link (not confirmed by the data) is that banks prefer longer paper to bills yielding well below the policy rate, while pension funds, which already hold 30% of the stock, were allotted only 7.2% of the last 15-year bond and their holdings did not grow in the week. The Government's funding therefore depends on a small group of buyers.
Stock: TZS 33.41 tn (2 Oct) → TZS 33.56 tn (9 Oct); bills rose TZS 0.15 tn to TZS 3.57 tn while bonds were roughly flat (+TZS 0.01 tn).
Investors: banks added TZS 0.20 tn in a week; retail investors (-0.03 tn) and insurers (-0.02 tn) reduced holdings (TICGL calc.).
Price: 15-year bond WAY 10.79% vs 10.55% at the previous auction; the 364-day bill WAY 6.28%, almost exactly the 6.25% Central Bank Rate.
Next: a 25-year bond auction on Wednesday 14 October; its previous result was 11.48% at 3.49x cover.
01 — HoldingsWho Owns Tanzania's Government Securities
Outstanding government securities were TZS 33.56 tn at face value on 9 October: Treasury bonds TZS 29.99 tn (89.35%) and Treasury bills TZS 3.57 tn (10.65%). The previous week they were TZS 33.41 tn (bonds 89.74%, bills 10.26%).
Holdings by Investor Category
TZS trillions, face value
Weekly Change in Holdings
TZS billion, 2 Oct → 9 Oct (TICGL calc.)
Investor category
2 Oct (TZS bn)
9 Oct (TZS bn)
Share 9 Oct
Change (bn)
Banks
11,232.82
11,432.15
34.06%
+199.33
Pension funds
10,117.52
10,117.34
30.14%
-0.18
Retail investors
5,908.68
5,883.12
17.53%
-25.56
CIS & other official entities
2,713.71
2,714.81
8.09%
+1.10
Insurance companies
2,464.98
2,446.86
7.29%
-18.12
Others
970.26
970.04
2.89%
-0.22
Total
33,407.97
33,564.32
100%
+156.35
Source: Bank of Tanzania, Table 3 of each weekly report. Change column is TICGL/TERI calculation. CIS = collective investment schemes.
Bonds vs Bills in the Stock
TZS trillions
Registered Clients Added per Fiscal Year
Number; FY-1 = last completed year, current FY to 9 Oct (Chart 9, labels relative)
1.1 What the holdings tell us
Two-thirds in two hands. Banks and pension funds hold TZS 21.55 tn, 64.2% of the stock. Insurers add 7.3%. Together the three institutional groups hold 71.5%.
Retail is meaningful but flat. Retail investors hold TZS 5.88 tn (17.5%) and the Bank has onboarded 3,103 new clients this fiscal year (total 34,605), already 31% of the 9,899 added in the last full year, after about three months.
Pension funds are not adding. Their holdings were unchanged at TZS 10.12 tn (-TZS 0.18 bn in the week), even as banks bought TZS 199 bn.
The week's growth was mainly bills held by banks. The stock rose TZS 156 bn; bills rose TZS 146 bn. Banks' rise of TZS 199 bn exceeds the net increase, as other holders sold or redeemed.
02 — BondsTreasury Bond Auctions: Strong Demand, Rising Yield
The 15-year Treasury bond No. 696 was auctioned on 30 September 2026. It attracted 312 bids, of which 208 succeeded. Bids totalled TZS 504.13 bn against TZS 207.27 bn offered, an oversubscription of TZS 296.86 bn (cover 2.43x), and TZS 196.51 bn was allotted. The weighted average yield to maturity was 10.7907%, up from 10.5515% at the previous auction of the same tenor.
Tendered
504.13bn
Offered 207.27bn
Allotted
196.51bn
94.8% of offer
WAY
10.79%
+24 bps vs 10.55%
Bid-to-cover
2.43x
Prev. 15-yr: 3.33x
Bond auction (latest per tenor)
2-yr No.712
5-yr No.700
10-yr No.711
15-yr No.696 (prev)
15-yr No.696 (30 Sep)
25-yr No.695
Coupon
9.50%
10.25%
11.25%
12.25%
12.25%
13.25%
Redemption date
30-Jul-28
30-Apr-31
23-Jul-36
19-Feb-41
19-Feb-41
05-Feb-51
Bids received / successful
93 / 45
100 / 75
165 / 87
396 / 235
312 / 208
2,681 / 1,671
Offered (TZS bn)
138.95
145.63
182.90
207.27
207.27
414.19
Tendered (TZS bn)
438.45
398.06
364.96
689.45
504.13
1,446.83
Allotted (TZS bn)
111.49
143.57
149.60
181.19
196.51
414.20
Bid-to-cover
3.16x
2.73x
2.00x
3.33x
2.43x
3.49x
Weighted avg yield (%)
8.40
9.53
10.69
10.55
10.79
11.48
WAP (per 100)
101.9580
102.6275
103.3267
112.4713
110.5120
114.4173
Lowest / highest bid
82.15 / 104.59
90.64 / 105.00
83.40 / 109.00
86.55 / 117.03
90.67 / 113.56
88.67 / 118.80
Source: Bank of Tanzania, Table 5 of the 2 October report. Auction dates are not stated for tenors other than the 15-year. Allotted = "successful bids" in the Bank's table.
Bid-to-Cover by Auction
Times; tendered ÷ offered
15-Year Bond: Offered, Tendered, Allotted
TZS billion, previous auction vs 30 September
Who Bid and Who Was Allotted
Share of subscriptions and allotments, percent, 15-year bond of 30 September (Table 4)
Investor category
Subscription %
Allotment %
Allotted (TZS bn)
Gap (pp)
Banks
51.05
48.17
94.66
-2.88
Individuals & companies
22.87
28.35
55.71
+5.48
Collective investment schemes
12.24
10.97
21.56
-1.27
Pension funds
8.75
7.18
14.1
-1.57
Insurance companies
5.08
5.33
10.5
+0.25
Source: Bank of Tanzania Table 4. Allotted amounts for pension funds and insurers are TICGL/TERI calculations (allotment share × TZS 196.51 bn).
2.1 Reading the bond results
Demand weakened, not collapsed. The 15-year cover fell from 3.33x to 2.43x and tendered volume fell 27% (TZS 689.45 bn → 504.13 bn), yet the Treasury allotted 94.8% of what it offered and paid 24 bps more.
Bank-led. Banks put in 51% of bids, more than double the next category. Individuals and companies were allotted 5.5 points more than their share of subscriptions; the report does not say why.
Pension funds took little. Only 8.75% of bids and 7.18% of allotments (about TZS 14 bn), despite holding 30% of the stock. Either their appetite is saturated or they prefer other assets.
The long end clears at a premium. The 25-year bond drew 2,681 bids and TZS 1.45 tn against TZS 414 bn offered, accepting the full offer at 11.48%, a sign that investors will lend long at around 11.5%.
03 — BillsTreasury Bill Auction No. 1208: Undersubscribed
The Treasury bills auction on 7 October 2026 offered the 35-, 91-, 182- and 364-day tenors. It drew 54 bids, of which 49 succeeded. Bids totalled TZS 309.50 bn against TZS 388.70 bn offered, an undersubscription of TZS 79.20 bn (cover 0.80x), and TZS 279.40 bn was allotted.
Cover
0.80x
309.50 ÷ 388.70
Allotted
279.40bn
71.9% of offer
Bids
54
49 successful
Bank share of bids
99.98%
Allotment 99.97%
T-bill auction, 7 Oct
35-day
91-day
182-day
364-day
Total
Maturity date
12-Nov-26
07-Jan-27
08-Apr-27
07-Oct-27
—
Bids received / successful
2 / 2
10 / 10
24 / 19
18 / 18
54 / 49
Offered (TZS bn)
49.9
69.9
99.9
169.0
388.7
Tendered (TZS bn)
10.0
42.0
130.0
127.5
309.5
Allotted (TZS bn)
10.0
42.0
99.9
127.5
279.4
Bid-to-cover
0.20x
0.60x
1.30x
0.75x
0.80x
Weighted avg yield (%)
3.36
3.49
5.63
6.28
—
WAP (per 100)
99.6790
99.1372
97.2696
94.1029
—
Source: Bank of Tanzania, Table 5 of the 9 October report. Total cover is TICGL/TERI calculation (309.5 ÷ 388.7). Only the 182-day tenor was oversubscribed (TZS 30.1 bn).
Offered vs Tendered vs Allotted
TZS billion by tenor
Bill Yields: August vs 7 October
Percent; August from BoT Table A4
3.1 Why the bill market is shallow
Banks only. Banks supplied 99.98% of subscriptions and received 99.97% of allotments (TZS 279.33 bn); individuals and companies got TZS 0.07 bn. Bills are effectively an interbank-liquidity instrument.
Short bills pay far less than the policy rate. The 35-day yield of 3.36% is almost 3 points below the 6.25% CBR; only the 364-day (6.28%) matches it. Bids concentrated in the 182- and 364-day tenors (TZS 257.5 bn of 309.5 bn), leaving the 35- and 91-day tenors at 0.20x and 0.60x cover.
The bill curve flattened. Versus the August monthly averages, the 35-day yield rose 125 bps (2.11% → 3.36%) while the 364-day fell 42 bps (6.70% → 6.28%), shrinking the 35-to-364-day spread from 4.59 to 2.92 percentage points (TICGL calc.).
Link to liquidity. The 7 October auction day coincided with a one-day collapse in interbank volume to TZS 1.0 bn and a 6.05% rate (Part 2), consistent with banks holding back cash for the auction or settling it.
Why an undersubscribed bill auction matters
Undersubscription means the Government could not raise the full TZS 388.70 bn planned. Given bills are only 10.7% of the stock, the funding impact is small, but a bid-to-cover of 0.80x compares with 1.7x for the August auctions (Bank's September review) and is a warning that the bank base for bills is narrow.
04 — Yield CurveThe Curve and What to Watch
Combining the latest auction result for each tenor gives a picture of the curve from 35 days to 25 years. It is steep at the short end, flatter in the middle and runs from 3.4% to 11.5%.
Tanzania Government Securities Yield Curve (Auction-Based)
Weighted average yield, percent. Bills: 7 Oct auction; bonds: latest auction per tenor. Dashed line = CBR 6.25% (TICGL assembled)
Tenor
Yield (%)
vs CBR 6.25 (bps)
Source
35-day
3.36
-289
Auction 7 Oct
91-day
3.49
-276
Auction 7 Oct
182-day
5.63
-62
Auction 7 Oct
364-day
6.28
+3
Auction 7 Oct
2-year
8.40
+215
Latest auction
5-year
9.53
+328
Latest auction
10-year
10.69
+444
Latest auction
15-year
10.79
+454
Auction 30 Sep
25-year
11.48
+523
Latest auction
Slope of the Curve
Percentage points (TICGL calc.)
Bond Yields: August vs Latest Auction
Percent; August from BoT Table A4
4.1 What the curve says
Upward sloping and credible. The 25-year yield is 308 bps above the 2-year and 523 bps above the CBR. Investors demand a clear term premium but do not price a sharp policy shock.
The 2-year to 364-day jump of 212 bps. There is a sizeable step between the bill and bond segments of the curve.
Rates are close to August for most tenors. The 2-year (8.40%), 5-year (9.53%) and 25-year (11.48%) match August levels; the 10-year is 18 bps lower (10.87% → 10.69%) and the 15-year 24 bps higher (10.55% → 10.79%).
4.2 Outlook and risks
14 October 25-year auction. The last 25-year cleared the full TZS 414 bn at 11.48% with 3.49x cover. A cover below about 3x or a yield above 11.8% would be a warning that long-end demand is cooling alongside the 15-year softening. This is a TICGL/TERI threshold for monitoring, not a forecast.
Concentration. Banks are the marginal buyers of both bills (99.98%) and bonds (51%); a shift in bank liquidity, as shown in Part 2, hits the Treasury directly.
Pension-fund saturation. If pension funds, 30% of the stock, stop adding, new supply must be absorbed by banks and retail or by higher yields.
Crowding-out. With the Government borrowing heavily at 10–11.5% in the long end, private firms seeking local-currency bonds face a high benchmark. Banks hold TZS 11.43 tn of government paper while private credit grows 33%.
For investors and pension managers
Treat 11.5% as the 25-year benchmark and 10.8% as the 15-year benchmark for discounting.
Use auction cover and the allotted-to-offered ratio as demand signals, not only yield.
Bills below the CBR suit liquidity management, not return; ladder into 182- and 364-day bills.
For corporates and project sponsors
Price local-currency debt off the government curve plus a credit spread of 2–4 points (illustratively about 13.5–15.5% for long tenors).
Consider infrastructure bonds or pension-fund co-investment where pension funds are saturated.
Time issuance away from heavy government auction weeks.
"The Treasury can still borrow long at about 11 percent, but it is borrowing from the same few hands. The real depth test is whether pension funds, insurers and retail investors take more of the next auctions."
— TICGL / Tanzania Economic Research Institute (TERI)
05 — What TICGL DoesFrom Market Data to Financing Strategy
The government yield curve is the benchmark for every local-currency financing decision. TICGL (Tanzania Investment and Consultant Group Ltd), with its research arm TERI, combines original economic research with practical advisory outputs across Tanzania and East Africa. Three technical service lines use the analysis in this report directly.
Feasibility Studies
Pre-feasibility and full feasibility studies for PPP and private projects.
Discount-rate and cost-of-capital build-ups anchored on the government curve.
Financing-structure options: bank debt, infrastructure bonds, pension-fund and PPP funding.
Sensitivity to yields, inflation and exchange rates, with DSCR and affordability tests.
Market Entry Advisory
Sector screening including local-currency financing availability and cost.
Treasury and working-capital planning for new entrants.
Entry-mode choice, incentives and capital-market access routes.
Partner, lender and investor identification.
Market Research
Weekly, monthly and quarterly capital-market monitoring from official sources.
Investor-base, pension and capital-market depth studies.
Primary surveys and stakeholder interviews with issuers, banks and fund managers.
Policy briefs, training materials and SEO-ready publications.
Why this matters to clients
A project discount rate set off the CBR (6.25%) understates the cost of long-term local money by about 4.5 to 5 points. Refreshing the curve inputs in a feasibility model, PPP proposal or bond plan takes little time and avoids mispriced risk.
Talk to TICGL/TERI
Request a feasibility, market-entry or market-research scoping call, or a fuller briefing on this series.
Source: Bank of Tanzania, Domestic Financial Markets Weekly Reports for 28 September–2 October 2026 and 5–9 October 2026 (Section 3: Tables 3–5, Chart 9), plus the Monthly Economic Review, September 2026 (Table A4 yields; Section 2.4 auction cover). Weekly changes in holdings, per-category allotments for pension funds and insurers, total T-bill cover, curve spreads versus the CBR and the August-to-October yield comparisons are TICGL/TERI computations. "Latest auction" tenors in the bond table carry no dates in the weekly report. The monitoring thresholds for the 14 October auction are TICGL/TERI judgements, not forecasts. This is Part 3 of a three-part series; Part 1 covers the foreign exchange market and Part 2 the money market.
07 — Quick AnswersFrequently Asked Questions
How much government debt is outstanding in the securities market?
TZS 33.56 trillion at face value on 9 October 2026: bonds TZS 29.99 trillion (89.35%) and bills TZS 3.57 trillion (10.65%).
Who holds Tanzania's government securities?
Banks 34.06%, pension funds 30.14%, retail investors 17.53%, CIS and other official entities 8.09%, insurers 7.29% and others 2.89%.
What was the latest Treasury bond auction result?
The 15-year bond of 30 September drew TZS 504.13 billion against TZS 207.27 billion offered, allotted TZS 196.51 billion at a weighted average yield of 10.79%, up from 10.55%.
Was the 7 October Treasury bill auction successful?
It was undersubscribed: TZS 309.50 billion tendered against TZS 388.70 billion offered (0.80x), TZS 279.40 billion allotted, banks 99.98% of bids. Yields were 3.36%, 3.49%, 5.63% and 6.28% for 35-, 91-, 182- and 364-day bills.
What happens next?
A 25-year Treasury bond will be offered on Wednesday 14 October 2026. The previous 25-year auction yielded 11.48% at 3.49x cover.
08 — Explore MoreTICGL Economic: Related Insights & Tools
Soko la Dhamana za Serikali la Tanzania. Kwa mujibu wa ripoti mbili za wiki za Benki Kuu ya Tanzania (28 Sep – 9 Okt 2026), dhamana za serikali zilizopo sokoni zilifikia TZS trilioni 33.56 tarehe 9 Oktoba, kutoka trilioni 33.41 wiki iliyotangulia. Hati fungani ni TZS trilioni 29.99 (asilimia 89.35) na hati za muda mfupi (T-bills) ni trilioni 3.57 (asilimia 10.65).
Wamiliki: Benki asilimia 34.06, mifuko ya pensheni asilimia 30.14, wawekezaji wa rejareja asilimia 17.53, bima asilimia 7.29. Mifuko ya pensheni haikuongeza dhamana wiki hii (TZS trilioni 10.12), wakati benki ziliongeza takriban TZS bilioni 199.
Mnada wa hati fungani ya miaka 15 (30 Sep): Zabuni zilikuwa TZS bilioni 504.13 dhidi ya bilioni 207.27 zilizotolewa (mara 2.43). Mapato ya wastani (yield) yalipanda hadi asilimia 10.79 kutoka asilimia 10.55. Benki zilitoa asilimia 51 ya zabuni, mifuko ya pensheni asilimia 8.75 tu.
Mnada wa T-bills (7 Okt): Zabuni zilikuwa TZS bilioni 309.50 dhidi ya bilioni 388.70 zilizotolewa (mara 0.80), yaani haukujazwa. Benki zilitoa asilimia 99.98 ya zabuni. Yield: siku 35 asilimia 3.36, siku 91 asilimia 3.49, siku 182 asilimia 5.63, siku 364 asilimia 6.28.
Mkunjo wa yield: Kutoka asilimia 3.4 (siku 35) hadi asilimia 11.48 (miaka 25). Yield ya siku 364 ni sawa na CBR ya asilimia 6.25. Mnada ujao ni wa hati fungani ya miaka 25 tarehe 14 Oktoba; mnada uliopita ulikuwa asilimia 11.48 kwa mara 3.49.
Ushauri: Wawekezaji watumie asilimia 11.5 kama kigezo cha miaka 25 na asilimia 10.8 kwa miaka 15. Miradi isipime gharama ya mtaji kwa CBR ya asilimia 6.25 pekee. TICGL/TERI hutoa upembuzi yakinifu (feasibility), ushauri wa kuingia sokoni na utafiti wa soko.
Hitimisho: Mahitaji ya dhamana ndefu ni mazuri, lakini yanatoka kwa wanunuzi wachache. Kina cha soko kitapimwa na kama mifuko ya pensheni, bima na wawekezaji wa rejareja watachukua sehemu kubwa ya minada ijayo.
