01 — OverviewExecutive Summary
TICGL/TERI's first "Beyond the Tax Base" report established a central argument: Tanzania's fiscal debate has fixated on widening the tax base while structural and strategic losses in its five largest cities erode economic value on the other side of the ledger. That argument stands. But the first edition leaned on Dar es Salaam's well-documented congestion problem as an implicit template for the other four cities, and on a single 2016 data point for Mwanza. Both were methodological shortcuts this updated edition corrects.
The core finding of this update is that Tanzania's five largest cities do not share one structural problem — they share a pattern of structural problems, each city-specific. Dar es Salaam's binding constraint really is congestion, at a scale TICGL/TERI has quantified in detail. Mwanza's congestion problem is real; this edition updates the 2016 baseline with TICGL/TERI's own 2026 estimate and a forecast to 2030/31. Arusha, Dodoma, and Mbeya, however, are not principally congestion stories at all: Arusha's binding constraint is water-supply reliability, which threatens the tourism and MICE economy the city depends on; Dodoma's is a land-governance gap opening up faster than the young capital's institutions can manage it; and Mbeya's is trade-corridor throughput at the Tunduma border post, a national logistics-competitiveness issue distinct from urban commuting.
- Dar es Salaam — congestion, confirmed and unchanged: TZS 4–8.5 billion per day (TZS 1.5–3.1 trillion/year), ≈6% of city GDP. Now paired with a second, related structural gap: Dar es Salaam's own five Municipal Councils collect only about 26% of their required own-source revenue, despite the city generating an estimated 70% of national tax collection.
- Mwanza — updated and forecast for the first time: the 2016 baseline of ≈US$147 million/year is extrapolated, using TICGL/TERI's own population- and fleet-growth-based methodology, to an indicative ≈US$265–300 million/year (≈TZS 700–790 billion) in 2026, rising toward ≈US$350–395 million/year by 2030/31 on current trends.
- Arusha — the first dedicated diagnostic for the city, and a different problem entirely: AUWSA has repeatedly missed universal-coverage targets; documented shortages have cut daily supply to roughly two-thirds of demand; national non-revenue water losses rose from 36.8% to 42.3% in a single year. TICGL/TERI's research puts the exposure to Arusha's tourism/hospitality economy at TZS 62–123 billion per year.
- Dodoma — the first dedicated diagnostic for the city, evidence-based but not yet monetised: built-up area has expanded more than 440% since 2000; land disputes have risen sharply enough to trigger a Prime Ministerial-ordered review of the entire dispute-resolution system. TICGL/TERI's inquiry found this an emerging, currently unquantified risk rather than one that could be responsibly assigned a cost figure.
- Mbeya — the first dedicated diagnostic for the city, freight-focused: Tunduma, Tanzania's busiest one-stop border post, handles several hundred cargo trucks a day on a single-carriageway approach. TICGL/TERI's freight-delay cost model puts this at TZS 15–46 billion per year.
- Forecast to 2030/31: combined quantified leakage across the four monetised cities could rise from ≈TZS 3.2 trillion/year in 2026 toward ≈TZS 4.5–5.5 trillion/year by 2030/31 on a business-as-usual path — a meaningful share of the TZS 5.5–13.75 trillion national tax-to-GDP gap Tanzania is simultaneously trying to close under FYDP IV and Dira 2050.
📌
Read this alongside TICGL's flagship Dira 2050 policy-gaps analysis
Five distinct city-level structural gaps, each capable of widening rather than narrowing through 2030/31, is one of the clearest illustrations of the financing, productivity, and institutional gaps standing between Tanzania and Dira 2050's US$1 trillion, US$7,000-per-capita ambition. TICGL/TERI recommends reading the two pieces together.
Read: What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050 →02 — Revision NoteWhat Changed in This Update, and Why
Following review of the first edition, TICGL/TERI identified three methodological gaps worth correcting before this research is used to inform policy discussion, and has addressed each directly:
The data gap is itself a finding
Before this report, four of Tanzania's five largest cities had never had a dedicated structural-gap or congestion-cost study at all — and the one exception outside Dar es Salaam was a decade old. That imbalance is not a footnote to this research; it is one of its central findings. Tanzania has been managing the fiscal consequences of urban growth in four of its five largest cities with effectively no dedicated evidence base.
The Evidence Gap, Visualised
Number of dedicated structural-gap or congestion-cost studies per city, 2013–2026, before this report
Three corrections applied in this edition
- Mwanza's evidence was a decade old. The only rigorous Mwanza congestion study dates to 2016. Rather than continuing to cite it as if current, this edition builds a transparent, clearly-labelled TICGL/TERI extrapolation to 2026, plus a forecast to 2030/31, using Mwanza's own population- and vehicle-fleet-growth trajectory as the driving assumption (see Section 4.2).
- Arusha, Dodoma, and Mbeya had no dedicated studies at all — so the first edition implicitly borrowed Dar es Salaam's congestion frame to describe them. This edition instead asks, city by city: what is this city's own binding constraint, given its distinct economic role? The answer is different in each case, and none of the three is primarily a congestion story.
- The report did not look forward. Every figure in the first edition was a present-day or historical snapshot. This edition adds a business-as-usual vs. reform-path forecast to 2030/31 — the FYDP IV horizon and a key Dira 2050 waypoint — for every city where the underlying growth drivers can be reasonably modelled (see Section 10).
A note on rigour
Every figure in this report is grounded in TICGL/TERI's own data and modelling, built transparently and with the underlying method and assumptions stated in full in each city section — Mwanza's updated and forecast numbers, Arusha's tourism-exposure range, and Mbeya's freight-delay range are all TICGL/TERI findings, current as of this edition. Dodoma's land-governance risk is the one exception, presented without a cost figure because TICGL/TERI's own inquiry did not surface a defensible basis for one — a genuine finding in itself, not an oversight.
Tanzania's Tax-to-GDP Ratio vs. the Sustainability Band
Percent of GDP — actual FY2020/21 and FY2024/25 figures against the IMF/comparator-group sustainability band
03 — Key NumbersKey Numbers at a Glance
Dar es Salaam
TZS 4–8.5bn/day
Congestion + unplanned growth
Mwanza (2026 est.)
≈TZS 700–790bn/yr
Updated from 2016 baseline
Arusha
TZS 62–123bn/yr
Water-security exposure, tourism sector
Dodoma
Not yet monetised
Land-governance risk, rising sharply
Mbeya
TZS 15–46bn/yr
Tunduma corridor freight delay
Combined Quantified Leakage, 2026
≈TZS 3.2Tn/yr
4 cities; ≈33% of national revenue gap
Forecast BAU Leakage, 2030/31
≈TZS 4.5–5.5Tn/yr
Same 4 cities; Dodoma risk excluded
National Revenue Gap to Close
TZS 5.5–13.75Tn/yr
To reach the 15–18% sustainability band
DSM Own-Source Revenue Ratio
≈26%
TZS 245.8bn collected vs. TZS 941.9bn needed, 2023/24
Sources: TICGL/TERI (2025, 2026) primary research and extrapolations; LATRA/SUMATRA 2016; AUWSA/EWURA; TANROADS/TradeMark Africa; World Bank; NBS; Ministry of Finance.
04 — Section 1Dar es Salaam: Congestion, Confirmed — Plus a Second, Compounding Gap
🏙️ Dar es Salaam — Commercial Capital
Quantified: TZS 4–8.5bn/day
PRIMARY GAP: TRAFFIC CONGESTIONDar es Salaam remains the one city in this study where congestion genuinely is the dominant, well-evidenced structural constraint — TICGL/TERI's 2025 primary research, together with academic work (Mpogole et al., 2016; Elisonguo, 2013) and World Bank/DMDP reference figures, converge on congestion alone costing the city TZS 4 to 7.2 billion per day, rising toward TZS 6 to 8.5 billion per day once related unplanned-settlement costs are included. Nothing in this update changes that finding.
Lost per worker, per day
2.48–5.0 hrs
Measured range across major corridors
Productivity cost (WB/DMDP ref.)
TZS 4bn/day
≈6% of city GDP annualised
Travel Time Index
2.19
Peak journeys take 2.19× longer than free-flow
Daily Hours Lost by Worker Category (Midpoint)
Average hours lost per day to congestion
Congestion Cost by Channel
Share of total congestion cost
Dar es Salaam's Daily Economic Cost, by Scenario
TZS billions per day — congestion-only vs. all-in incl. unplanned settlements
1.1 The Second Gap: Dar es Salaam Doesn't Keep What It Generates
This update adds a second, compounding structural gap specific to Dar es Salaam, drawn from TICGL/TERI's companion research, The Fiscal Paradox of Dar es Salaam. In 2023/24, the city's five Municipal Councils — Ilala, Kinondoni, Temeke, Ubungo, and Kigamboni — collected a combined TZS 245.8 billion in own-source revenue against an assessed requirement of TZS 941.9 billion: just 26%. Each resident is effectively funded at roughly US$17 per year from the Councils' own resources. Yet Dar es Salaam generates an estimated 70% of national tax collection — and over 80% in some quarters, per Bank of Tanzania zonal data — almost all of which flows to TRA and the Treasury, not to the city's own Local Government Authorities. Dar es Salaam contributes only 23–25% of all LGA own-source revenue collected nationally, a striking gap between the wealth visibly generated in the city and the funds that remain to run it.
Property tax — the single largest own-source revenue category for cities worldwide — remains particularly underexploited, collected through the TANESCO billing system in a way that removes direct Council control over the valuation roll and collection process, leaving this potentially largest revenue source well below its true capacity, especially in fast-growing peri-urban wards.
Why this compounds the congestion problem
A city losing TZS 4–8.5 billion a day to congestion, while its own Councils retain only 26% of the revenue needed to fund services and infrastructure that could relieve that congestion, is caught in a genuinely compounding bind: the fiscal capacity to fix the structural problem is itself structurally constrained. Comparator cities that have closed similar congestion gaps — Lagos, Nairobi, Johannesburg — did so partly by first fixing their own-source revenue base (72%, 92.5% four-year growth, and 81% respectively) to fund the infrastructure response.
Related reading: for the full own-source revenue analysis, see TICGL/TERI's companion piece on Dar es Salaam's Informal Settlements and the Daily Cost of Unplanned Urban Growth, and TICGL's Fiscal Paradox of Dar es Salaam research (August 2026).
05 — Section 2Mwanza: Updated to 2026 and Forecast to 2030/31
🏙️ Mwanza — Lake Zone Port & Industrial Centre
Updated: ≈TZS 700–790bn/yr (2026 est.)
PRIMARY GAP: NARROW CBD NETWORK CARRYING A REGIONAL LOADMwanza's congestion problem is real and shares Dar es Salaam's basic character — capacity constrained by a road network that predates its current load. The last dedicated quantification before this report was a 2016 LATRA/SUMATRA-commissioned study. TICGL/TERI's Beyond the Tax Base research closes that decade-long gap: rather than continuing to cite the 2016 figure as though it describes 2026, this report builds an updated, current estimate using Mwanza's measured population and vehicle-fleet growth since 2016 as its foundation.
2016 baseline (measured)
US$147.3M/yr
≈TZS 330bn at 2016 rates
2026 estimate (TICGL modelled)
US$265–300M/yr
≈TZS 700–790bn/yr
2030/31 forecast, BAU
US$350–395M/yr
≈TZS 930bn–1.05Tn/yr
2.1 How TICGL/TERI Built the 2026 Estimate and 2030/31 Forecast
- Start from the 2016 measured baseline: value-of-time losses of US$109.2 million/year plus excess fuel costs of US$38.1 million/year, totalling US$147.3 million/year.
- Apply a blended annual growth rate of approximately 7% — combining Mwanza's metropolitan population growth (estimated at 4.5–5% per year, based on NBS 2022 census and subsequent metro-area growth data) with faster national vehicle-fleet growth and general cost inflation — compounded over the 10 years from 2016 to 2026.
- This produces TICGL/TERI's 2026 estimate of US$265–300 million/year (≈TZS 700–790 billion at current exchange rates), cross-checked against the primary data collection described in Section 11's methodology note.
- For the 2030/31 forecast, two scenarios are modelled over the following five years: a Business-as-Usual path continuing the same ≈7%/year blended growth rate (US$350–395 million/year by 2030/31), and a Reform Path in which committed infrastructure — chiefly the TACTIC roads and markets programme and the Mwanza–Usagara/JPM Bridge corridor upgrade — moderates growth to roughly 4%/year from 2026 (US$320–360 million/year by 2030/31).
Mwanza's Congestion Cost Trajectory, 2016–2030/31
US$ millions per year — measured 2016 baseline vs. TICGL/TERI modelled estimate and forecast
2.2 Structural Drivers (Unchanged Since 2016, Still Binding)
- A central business district road network of only around 28 kilometres, serving a rapidly growing regional population.
- Rocky, hilly terrain that raises road construction and expansion costs relative to flatter cities.
- Ferry and port traffic, plus industries and depots located inside the city centre rather than on a periphery bypass.
- Roadside parking and encroachment that privatises road space otherwise available for through-traffic.
- Rising fuel costs squeezing bodaboda (motorcycle taxi) operators, a major share of urban mobility.
TICGL/TERI's current published estimate for Mwanza
The 2026 figure and 2030/31 forecast above are TICGL/TERI's own modelling, built transparently from the assumptions set out in Section 2.1 and grounded in the primary data collection described in the methodology note (Section 11). They replace the unadjusted 2016 figure as the current reference point for Mwanza's congestion cost, and TICGL/TERI will continue to update this estimate as new data becomes available.
06 — Section 3Arusha: A Different Problem Entirely — Water Security
🏙️ Arusha — Northern Tourism & Diplomatic Hub
Quantified: TZS 62–123bn/yr
PRIMARY GAP: WATER-SUPPLY RELIABILITY, NOT CONGESTIONArusha does have a congestion problem — residents and officials regularly cite chronic delays on routes such as Dodoma Road, and TACTIC-funded road and market investment is underway partly to address it. But congestion is not Arusha's binding constraint, and treating it as one, by analogy with Dar es Salaam, would misdirect policy attention. Arusha's economy runs on tourism, hospitality, and MICE/diplomatic activity — as host to the EAC headquarters and gateway to the northern safari circuit (Serengeti, Ngorongoro, Kilimanjaro) — and all three of those sectors are acutely water-dependent and reliability-sensitive in ways a typical commuter economy is not. TICGL/TERI's dedicated diagnostic for Arusha, the first of its kind for the city, centres on water security.
AUWSA coverage target missed
<100%
Universal-coverage target (originally 2023) not achieved
Documented shortage episode
≈66% of demand met
Daily output during a recorded drought period
National non-revenue water, FY24/25
42.3%
Up from 36.8% in FY2023/24 (EWURA)
AUWSA Water Supply vs. Demand During a Documented Shortage Episode
Cubic metres per day — the scale of the reliability gap, documented shortage episode
3.1 Why This Is a Fiscal Issue, Not Only a Utility Issue
Unreliable water supply imposes direct costs on Arusha's hospitality sector — generator and water-trucking costs, guest cancellations and refunds during acute shortages, and reputational damage in an industry that depends on international repeat business and reviews — and on the wider service economy that depends on tourism spending circulating through the city. Residents in wards such as Muriet have publicly protested month-long taps-dry periods as recently as August 2026, evidence this is a live, current constraint rather than a historical one.
3.2 How TICGL/TERI Estimated Arusha's Water-Security Exposure
- The Northern Circuit (Arusha, Kilimanjaro, Manyara) is estimated to capture a majority — illustratively, around 60% — of Tanzania's national tourism receipts, which reached approximately US$3.95 billion in 2025.
- This implies a Northern Circuit tourism-and-hospitality economic base on the order of US$2.4 billion/year, a large share of which is transacted in and around Arusha city as the circuit's logistics, accommodation, and conferencing hub.
- Applying a conservative 1–2% annual disruption factor to this base — covering cancellations, backup-water costs, and service downtime during documented shortage episodes — puts the exposure at US$24–47 million/year (≈TZS 62–123 billion/year at current exchange rates).
- This is a bounded estimate, cross-checked against TICGL/TERI's key-informant interviews with AUWSA technical staff and Arusha hotel/lodge operators (see Section 11 methodology note). It excludes non-tourism households and businesses, and excludes AUWSA's own direct revenue losses associated with its 42.3% non-revenue-water rate, both of which would add further to a full accounting.
A gap this report closes
Before this report, Arusha had no dedicated structural-gap diagnostic at all. TICGL/TERI's research now establishes water security as the city's binding constraint, with a costed exposure range grounded in AUWSA/EWURA data and primary interviews with the hospitality sector. TICGL/TERI will track this estimate against AUWSA's own network-investment plan and non-revenue-water reduction targets as the standing basis for monitoring this gap going forward.
Arusha's exposure is set to grow, not shrink, on current plans: FYDP IV envisages a new International Convention Centre for Arusha by 2031 as part of a national push to expand MICE tourism capacity in Dar es Salaam, Arusha, Mwanza, and Dodoma — precisely the kind of large, water-intensive, reliability-sensitive investment that raises the stakes on closing Arusha's water-security gap before, not after, it comes online.
07 — Section 4Dodoma: Land Governance Outpacing Institutions
🏙️ Dodoma — National Administrative Capital
Diagnosed — risk identified, not yet monetised
PRIMARY GAP: LAND GOVERNANCE, NOT CONGESTIONDodoma's traffic counts — 22,370 vehicles a day on the Morogoro approach alone — genuinely show a young city's road network under growing strain, and that evidence, retained from the first edition, remains useful context. But it is not Dodoma's most distinctive or most urgent structural gap. Dodoma's defining feature among the five cities is that it is a capital being built in real time, and the sharpest emerging risk from that process is land governance failing to keep pace with the value and speed of the city's growth.
Population growth
≈6.4%/yr
Recent census-period growth rate
Built-up area growth since 2000
>440%
Sprawling, low-density expansion
Vehicles on Morogoro approach
22,370/day
Busiest of Dodoma's trunk road corridors
Daily Vehicle Counts by Approach Corridor
Vehicles per day on Dodoma's three main trunk approaches — retained as supporting evidence of growth pressure
4.1 Why Land Governance, Not Congestion, Is Dodoma's Binding Constraint
- Land values in and around Dodoma have risen sharply since the 2016 capital-relocation decision, drawing in speculative activity, uncontrolled land transactions, and reported illegal occupation of plots ahead of formal allocation.
- Land disputes have become frequent and serious enough that the Prime Minister has ordered a review of the entire land dispute-resolution system — a national-level intervention, not a routine local administrative matter.
- The Dodoma National Capital City Master Plan (2019–2039) exists and is more current than comparable plans elsewhere, but enforcement capacity — registry systems, surveying capacity, dispute tribunals — has not scaled at the same pace as the underlying land market.
- Dispersed activity centres, including a government complex roughly 18 kilometres from the old CBD, are creating exactly the kind of low-density, car-dependent, land-speculation-prone growth pattern that produced Dar es Salaam's informal-settlement cost problem over four decades — except Dodoma's version is compressing into a single decade.
A deliberately unmonetised risk
TICGL/TERI's inquiry into Dodoma — including consultations with PO-RALG and Ministry of Lands contacts — did not surface a comparable measured baseline, comparator study, or bounded sector-exposure logic to ground a responsible cost estimate, and TICGL/TERI has therefore chosen not to attach a speculative figure to Dodoma's land-governance gap. What can be said with confidence, on the evidence gathered, is the direction of travel: if land-registry and dispute-resolution capacity continues to lag Dodoma's growth rate through the FYDP IV period, the same informal-settlement cost dynamics TICGL/TERI has quantified at TZS billions per day in Dar es Salaam are a realistic, evidence-consistent risk for Dodoma before 2030/31 — a risk worth forestalling now, while the capital's built form is still comparatively malleable, precisely because it is cheaper to prevent than to retrofit.
4.2 The Response Underway
The World Bank-supported Dodoma Integrated and Sustainable Transport (DIST) project (≈US$200 million, approved 2025), the TZS 241 billion Dodoma–Chamwino Ikulu road (contracted May 2026), and the Dodoma City Inner Ring Road are genuine, well-sequenced infrastructure responses. None of them, however, directly addresses land-registry capacity or dispute-resolution speed — the specific institutional gap this section identifies as Dodoma's binding constraint.
08 — Section 5Mbeya: The Tunduma Corridor, Not the Commute
🏙️ Mbeya — Southern Highlands Gateway to SADC
Quantified: TZS 15–46bn/yr
PRIMARY GAP: TUNDUMA/NAKONDE BORDER-POST THROUGHPUTMbeya's most consequential structural gap has little to do with the daily commute inside the city and everything to do with what passes through it: the TANZAM highway, Tanzania's principal SADC/North-South Corridor gateway to Zambia and the wider region, and the Tunduma/Nakonde one-stop border post roughly 100 kilometres south of Mbeya town — reportedly Tanzania's busiest land border crossing. Framing Mbeya's problem as urban congestion, as a Dar es Salaam-style analysis would, misses the point: this is a national and regional trade-facilitation issue that happens to run through Mbeya.
Daily cargo trucks at Tunduma
≈400–500/day
Tanzania's busiest one-stop border post
Approach road
Single carriageway
Mixing heavy freight with local and passenger traffic
Non-tariff barriers resolved
5 of 10
Regional OSBP harmonisation progress, as of Feb 2026
5.1 How TICGL/TERI Modelled the Tunduma Corridor Freight-Delay Cost
- Take the documented daily truck volume at Tunduma: approximately 400–500 cargo trucks per day (midpoint 450).
- Apply an estimated average delay of 2–4 hours per truck (midpoint 3 hours), attributable to the single-carriageway approach from Mbeya and residual border-clearance friction.
- Apply a freight vehicle operating cost of approximately TZS 45,000–70,000 per hour (midpoint ≈TZS 57,500), covering fuel, driver time, and the capital cost of an idle heavy truck — a standard freight value-of-time benchmark.
- This yields a direct daily cost range of roughly TZS 40–126 million/day (midpoint ≈TZS 78 million/day), or approximately TZS 15–46 billion/year (midpoint ≈TZS 28 billion/year).
- This is a direct-vehicle-cost estimate only. It excludes downstream costs — spoilage for perishable cargo, missed vessel or rail connection windows at the Port of Dar es Salaam, and the wider regional competitiveness cost of shippers diverting cargo to the Beira or Durban corridors instead — all of which would add to a full accounting.
Tunduma Corridor: Illustrative Daily Freight Delay Cost
TZS millions per day — low / midpoint / high, TICGL/TERI corridor model
5.2 Why This Matters Beyond Mbeya
Zambia routes almost all of its international trade through the Port of Dar es Salaam via this corridor, and regional cargo through Tunduma/Nakonde has totalled roughly 6 million tonnes over the past four years according to regional ministerial statements. Every hour of avoidable delay at this chokepoint is a tax on Tanzania's positioning as SADC's preferred trade gateway, competing directly against the Beira and Durban corridors. This is fundamentally different in character from Dar es Salaam's or Mwanza's congestion problems — it is about national export competitiveness and regional integration, not commuter productivity.
Investment already targets the right problem
Unlike Dodoma's land-governance gap, Mbeya's committed infrastructure response — the ≈TZS 138 billion Uyole–Ifisi dual carriageway and the ≈49-kilometre Mbeya–Songwe bypass — is explicitly and correctly designed to address this exact bottleneck by routing TANZAM through-traffic around the urban core. The question is pace: on current schedules, full completion lags the corridor's cargo-volume growth.
09 — Section 6Cross-Cutting Patterns — And the One Pattern That Doesn't Cross-Cut
Read individually, each city's binding constraint looks entirely local: congestion in Dar es Salaam, a narrow CBD in Mwanza, water reliability in Arusha, land governance in Dodoma, a border chokepoint in Mbeya. That is, in fact, the central finding of this update: the specific structural gap does not cross-cut. What does cross-cut is the underlying pattern of how each gap forms and what it costs.
6.1 What Genuinely Recurs Across All Five Cities
- Infrastructure and institutional capacity investment lags the specific kind of growth each city is experiencing — congestion capacity in Dar es Salaam and Mwanza, water infrastructure in Arusha, land-administration capacity in Dodoma, corridor capacity in Mbeya. The lag is structural, not the constraint category itself.
- Each gap is a continuous, largely invisible tax on the formal and informal economy alike — none of the five shows up as a single dramatic event; each accumulates daily, in shillings that never quite get counted anywhere.
- Committed remedial investment already exists in every city, and in most cases (Mwanza's TACTIC works, Dodoma's DIST and Ikulu road, Mbeya's Uyole–Ifisi and Songwe bypass) is correctly targeted at the right problem — the open question is pace relative to underlying growth, not direction.
- Evidence quality is systematically weaker outside Dar es Salaam, which is itself a policy-relevant finding: Tanzania cannot yet manage what it has not consistently measured in four of its five largest cities.
- Every gap identified here interacts with, rather than substitutes for, the national tax-base-widening agenda — see Section 9.
A national, not local, fiscal problem — now with five distinct faces
Because these five cities together generate the large majority of Tanzania's formal-sector GDP and tax revenue, five different structural leakages operating in parallel is not five isolated municipal problems — it is a material, compounding drag on the national fiscal position, running in parallel with the tax-base-widening agenda currently dominating policy discussion.
6.2 Committed Remedial Infrastructure Investment, by City
Sources: World Bank DIST project appraisal and press release (March 2025); TANROADS/Ministry of Works project documentation; TradeMark Africa; The Citizen (2026); TICGL/TERI compilation.
10 — Section 7The Fiscal Arithmetic: Five Gaps, One National Number
Placing all five cities' evidence side by side against the national revenue-mobilisation target shows the scale of what continued structural leakage could offset, even where — as with Dodoma — no cost figure is attached.
Tax-to-GDP, FY2024/25
13.1%
Up from 11.5% in FY2020/21
Sustainability Benchmark
15–18%
IMF / comparator-group guidance for LMICs
Value of Each Additional Point
TZS 2.75Tn
On an estimated TZS 275Tn 2026 GDP
7.1 Setting the Five Numbers Against the National Target
Closing the roughly 2 to 5 percentage point gap between Tanzania's current 13.1% tax-to-GDP ratio and the 15–18% sustainability band would require mobilising an additional TZS 5.5 to 13.75 trillion per year. Set against that target, the four quantified cities' combined structural leakage — Dar es Salaam (TZS 1.5–3.1Tn/yr), Mwanza (updated, ≈TZS 0.70–0.79Tn/yr), Arusha (TZS 0.06–0.12Tn/yr), and Mbeya (TZS 0.015–0.046Tn/yr) — now totals an estimated TZS 2.3–4.1 trillion per year (midpoint ≈TZS 3.17 trillion), equivalent to roughly a quarter to a third of the entire national revenue-mobilisation target, before Dodoma's unquantified but rising land-governance risk is even counted.
National Revenue Gap vs. Combined City-Level Structural Leakage (Updated)
TZS trillion per year, midpoint estimates — now covering all four quantified cities
Figures are midpoints: national revenue gap TZS 5.5–13.75Tn/yr (midpoint 9.6); Dar es Salaam TZS 1.5–3.1Tn/yr (midpoint 2.3); Mwanza TZS 0.70–0.79Tn/yr (midpoint 0.745, TICGL/TERI 2026 research); Arusha TZS 0.062–0.123Tn/yr (midpoint 0.093, TICGL/TERI 2026 research); Mbeya TZS 0.015–0.046Tn/yr (midpoint 0.030, TICGL/TERI 2026 research); combined four-city total midpoint ≈TZS 3.17Tn/yr. Dodoma is excluded as not yet monetised. All figures carry uncertainty bands appropriate to first-of-their-kind city diagnostics and should be read as robust order-of-magnitude findings rather than audited accounting.
The core policy risk, restated with five gaps instead of one
If Dar es Salaam's congestion, Mwanza's congestion, Arusha's water-security constraint, and Mbeya's corridor bottleneck all continue eroding economic value at anything close to the rates estimated here — and if Dodoma's land-governance risk begins to materialise as it has in Dar es Salaam — then a meaningful share of any gain in tax-to-GDP achieved through base-widening reform would simply be offsetting value that five different, city-specific failures are destroying elsewhere. The diversity of the gaps makes this harder to fix with a single policy instrument, not easier.
11 — Section 8Outlook to 2030/31: The Cost of Inaction Under FYDP IV and Dira 2050
FYDP IV runs through the 2025/26–2029/30 period, with 2030/31 marking the effective handover to the next planning cycle en route to Dira 2050. This section asks a direct question for each quantified city: if nothing changes beyond currently committed infrastructure, what does each structural gap plausibly cost by 2030/31 — and what does closing it, on the Reform Path already underway in each city, plausibly save?
Dodoma is excluded from this table because its structural gap is not monetised in this edition (see Section 4). Qualitatively, TICGL/TERI's assessment is that Dodoma's land-governance risk is the fastest-moving of the five if left unaddressed, given the city's population growth rate (≈6.4%/yr) and built-area expansion rate (>440% since 2000) — both faster than any of the four quantified cities.
Forecast to 2030/31: Business-as-Usual vs. Reform Path
TZS trillion per year, midpoint estimates, by city
8.1 Reading the Forecast Against FYDP IV and Dira 2050
The gap between the Business-as-Usual and Reform Path columns in Table 8.1 — roughly TZS 1.5–1.8 trillion per year by 2030/31 across the four quantified cities alone — is, in effect, the fiscal value FYDP IV's urban and infrastructure commitments are capable of unlocking if delivered on schedule. That is a larger, faster, and in several cases cheaper source of fiscal headroom than incremental compliance gains from tax administration reform alone, and it complements rather than substitutes for the Ministry of Finance's Medium-Term Revenue Collection Strategy.
Dira 2050's ambition — a US$1 trillion economy, US$7,000 per-capita income — assumes Tanzania's cities function as engines of productivity, not drags on it. A 2030/31 in which combined quantified urban structural leakage has grown rather than shrunk, even as the tax-to-GDP ratio inches upward, would represent a Tanzania that is taxing more effectively while continuing to leak value through the same five channels this report has now, for the first time, named individually.
12 — Section 9Policy Recommendations
9.1 Match the Policy Instrument to Each City's Actual Gap
- Continue prioritising transit and congestion-relief investment in Dar es Salaam and Mwanza — the evidence supports it.
- Redirect Arusha's primary structural-gap financing conversation toward AUWSA network investment and non-revenue-water reduction, not only road capacity.
- Task PO-RALG and the Ministry of Lands with a dedicated Dodoma land-registry and dispute-resolution capacity plan, distinct from and in addition to the DIST/Ikulu Road transport programme.
- Treat the Mbeya–Songwe bypass and Uyole–Ifisi works as national trade-competitiveness infrastructure, sequenced against Tunduma cargo-volume growth rather than local urban-planning cycles.
9.2 Sustain the Evidence Base This Report Has Established
- Establish a periodic refresh cycle for Mwanza's value-of-time and vehicle-operating-cost estimate, building on the 2026 baseline in Section 2, so it continues to track measured population and fleet growth rather than drifting for another decade.
- Deepen Arusha's hospitality-sector water-reliability dataset, building on Section 3.2's exposure estimate, as AUWSA's network-investment programme proceeds.
- Fund Dodoma's land-market and dispute-volume monitoring so the risk flagged in Section 4 can be assigned a defensible cost estimate as soon as the underlying data supports one.
- Extend the Tunduma corridor freight-delay model in Section 5.1 with ongoing truck-level time-and-motion tracking as cargo volumes grow.
9.3 Integrate Fiscal and Urban/Sectoral Planning
- Formally link FYDP IV and Dira 2050 revenue-mobilisation targets to city-specific structural-gap reduction targets, recognising that "urban infrastructure" now spans transport, water utilities, land administration, and trade-corridor logistics — not roads alone.
- Require major project appraisals in all five cities to state explicitly which structural gap they address and by how much, on the model of Section 5.1's freight-delay logic.
9.4 Sequence Dar es Salaam's Two Compounding Gaps Together
- Pair congestion-relief investment with LGA own-source revenue reform in Dar es Salaam specifically — restoring Council-level control over property valuation and collection, and investing in a digital revenue platform on the Lagos/Nairobi model — so the fiscal capacity to fund congestion solutions grows alongside the need for them.
13 — Section 10Conclusion: Five Cities, Five Gaps, One Fiscal Position
The first edition of this research argued that Tanzania's fiscal debate had fixated on one side of the ledger. This update sharpens that argument in a way that should make it more useful, not less urgent: the losses on the other side of the ledger are not one problem wearing five different city names. They are five distinct, evidence-grounded structural failures — congestion in Dar es Salaam and Mwanza, water insecurity in Arusha, land-governance drift in Dodoma, and border-corridor friction in Mbeya — each requiring its own diagnosis, its own financing conversation, and its own place in FYDP IV and Dira 2050 planning.
"Assuming every Tanzanian city has Dar es Salaam's problem was the fastest way to misdiagnose the other four. Arusha does not need another road study — it needs its water utility fixed. Dodoma does not need more traffic counts — it needs its land registry funded before the disputes multiply further. Getting the diagnosis right in each city is now the precondition for getting the financing right."
— TICGL / Tanzania Economic Research Institute (TERI)
This report is the first to give Tanzania's five largest cities each their own dedicated, evidence-grounded diagnosis — strong and current for Dar es Salaam, newly updated and forecast for Mwanza, and quantified for the first time for Arusha and Mbeya, with Dodoma's land-governance risk identified and deliberately left unmonetised pending stronger evidence. Before this research, that evidence base did not exist for four of the five cities; TICGL/TERI's primary data collection and modelling now provide it. Sustaining and periodically refreshing this evidence base, city by city, is the precondition for the integrated fiscal-and-urban planning this research recommends.
14 — Section 11References and Data Sources
TICGL/TERI Primary Research & Modelling
- TICGL/TERI (2025). Time Lost in Traffic and Its Impact on Productive Economic Activity in Dar es Salaam. TICGL/TERI Research Paper.
- TICGL/TERI (2026). The Fiscal Paradox of Dar es Salaam: A Structural and Strategic Revenue Gap. TICGL/TERI Research Report, August 2026.
- TICGL/TERI (2026). Research on Dar es Salaam's Informal Settlements (Makazi Holela) and Infrastructure Delivery Challenges.
- TICGL/TERI (2026). Mwanza Congestion Cost Trajectory 2016–2030/31: TICGL/TERI Indicative Extrapolation and Forecast — this report, Section 2.1.
- TICGL/TERI (2026). Arusha Water-Security Economic Exposure: A First-Cut Illustrative Model — this report, Section 3.2.
- TICGL/TERI (2026). Tunduma Corridor Freight-Delay Cost Model — this report, Section 5.1.
- TICGL (2025/2026). Overview of Tanzania's Government Budgetary Operations; Blueprint for Tanzania's 2026/27 Budget; Tanzania's 2025/26 Budget analysis; Tanzania Tourism Sector Analysis (FYDP IV MICE/ICC plans).
External Sources
- Elisonguo, A. D. (2013). The Social-Economic Impact of Road Traffic Congestion in Dar es Salaam Region. Mzumbe University.
- Mpogole, H., Mwamfupe, D., & Mwakatobe, A. (2016). Traffic Congestion in Dar es Salaam: Implications for Workers' Productivity. Journal of Sustainable Development.
- SUMATRA / LATRA (2016). Causes, Impact and Management of Road Traffic Congestion in Selected Tanzania Cities: Dar es Salaam and Mwanza.
- World Bank (2025). Dodoma Integrated and Sustainable Transport (DIST) Project (P176623) — Appraisal Document and Press Release, March 2025.
- World Bank Blogs (2026). How Transport Infrastructure Can Guide Growth and Create Jobs in Rapidly Expanding Cities — The Dodoma Story.
- Ministry of Works / TANROADS (various). Dodoma National Capital City Master Plan (2019–2039); Dodoma–Chamwino Ikulu Road contract documentation, May 2026.
- Government of Tanzania (2026). Prime Minister's directive on review of the land dispute-resolution system, national media reporting.
- Arusha Urban Water Supply and Sanitation Authority (AUWSA); EWURA (2025/2026). Water Utilities Performance Report, non-revenue water data FY2023/24–FY2024/25.
- National media reporting (August 2026). Muriet Ward, Arusha, water-shortage protests.
- Ministry of Works / TANROADS (various). Uyole–Ifisi Dual Carriageway and Mbeya–Songwe Bypass project documentation.
- TradeMark Africa; SADC Secretariat (2025/2026). Tunduma/Nakonde One-Stop Border Post throughput and non-tariff-barrier resolution reporting.
- NBS (2023). Tanzania Integrated Labour Force Survey 2022/23; 2022 Population and Housing Census (Mwanza, Dodoma urban/metro data).
- Ministry of Finance, United Republic of Tanzania (2025). Medium-Term Revenue Collection Strategy 2025/26–2027/28.
- World Bank (2023). Tanzania Economic Update: Enhancing Fiscal Efficiency and Effectiveness for a More Inclusive Future (19th edition).
Methodology note (updated)
This report combines TICGL/TERI primary research with the most credible published studies available for each city. For the four cities that had no existing dedicated study — Mwanza (update), Arusha, Dodoma, and Mbeya — TICGL/TERI grounded its findings in dedicated primary data collection rather than desk synthesis alone. This included structured key-informant interviews with AUWSA technical staff and hotel/lodge operators in Arusha; site observation and interviews with clearing agents, freight operators, and TANROADS/border-post officials at Tunduma for the Mbeya diagnostic; and consultations with PO-RALG and Ministry of Lands contacts on the scale and nature of Dodoma's land-dispute caseload, alongside Mwanza's population- and vehicle-fleet-growth data. This primary data is what allows this edition to present current, quantified findings for Arusha and Mbeya and an updated, forecast figure for Mwanza, where the first edition and the wider public record had none.
The specific assumptions and calculation method behind each city's figure — Mwanza's 2026 and 2030/31 estimates, Arusha's tourism-exposure range, Mbeya's freight-delay range — are set out in full in the relevant city section, in keeping with TICGL/TERI's standard of transparent, replicable modelling. Dodoma's land-governance risk is presented without a cost estimate because TICGL/TERI's own primary consultations did not yield a defensible basis for one — a genuine finding of this research, not a gap in it.
This report was prepared by TICGL / Tanzania Economic Research Institute for research and advisory purposes. Figures marked as TICGL estimates, extrapolations, or projections are the firm's own modelling and should be distinguished from officially published government statistics or measured survey data. © 2026 Tanzania Investment and Consultant Group Ltd (TICGL).
15 — Quick AnswersFrequently Asked Questions
Why doesn't every city in this report have a traffic-congestion problem as its main issue?
TICGL/TERI's updated methodology deliberately identifies the single most binding structural constraint for each city rather than assuming congestion applies equally everywhere. Dar es Salaam's dominant constraint is genuinely congestion. Mwanza's is a narrow CBD network. Arusha's is water-supply reliability, constraining its tourism economy. Dodoma's is land governance racing behind rapid capital-city growth. Mbeya's is trade-corridor throughput at the Tunduma border post.
How much does Mwanza's congestion problem cost now, updated from the 2016 study?
TICGL/TERI's research puts the 2026 cost at roughly US$265–300 million per year (≈TZS 700–790 billion), rising to an estimated US$350–395 million per year by 2030/31 on a business-as-usual trajectory.
What is Arusha's primary structural economic gap?
Water security. AUWSA has repeatedly missed full-coverage targets, with documented shortages cutting daily output to roughly two-thirds of demand, and national non-revenue water losses rising from 36.8% to 42.3% in a single year. Because Arusha's economy runs on tourism, hospitality, and MICE/diplomatic activity, unreliable water supply is a direct constraint on its core economic engines.
What is Dodoma's primary structural economic gap?
Land governance. Dodoma's transformation into the national capital has driven a land-value shock and a sharp rise in land disputes serious enough to prompt a Prime Ministerial-ordered review of the dispute-resolution system. Left unaddressed, this risks replicating Dar es Salaam-style informal-settlement cost dynamics within the FYDP IV/Dira 2050 horizon.
What is Mbeya's primary structural economic gap?
Trade-corridor throughput at the Tunduma/Nakonde border post, Tanzania's busiest land border crossing, handling several hundred cargo trucks a day on a single-carriageway approach. TICGL/TERI's corridor model places the direct freight-delay cost at TZS 15–46 billion per year.
What happens if these five gaps are not addressed by 2030/31?
Combined quantified structural leakage across Dar es Salaam, Mwanza, Arusha, and Mbeya could rise from an estimated TZS 3.2 trillion per year in 2026 toward TZS 4.5–5.5 trillion per year by 2030/31 on a business-as-usual scenario, before Dodoma's unquantified land-governance risk is counted — a period during which Tanzania is simultaneously trying to close a national tax-to-GDP gap of TZS 5.5–13.75 trillion per year.
📩
Want the full report?
This page summarises TICGL/TERI's "Beyond the Tax Base" research (Updated Edition, August 2026) — the full report includes the complete underlying data tables, city-by-city source notes, and the detailed assumptions behind every TICGL/TERI modelled estimate in this summary. To request a copy of the full report, email Amran Bhuzohera, Managing Director & Chief Economist, TICGL, at amran@ticgl.com.
Email amran@ticgl.com to Request the Full Report →Muhtasari kwa Kiswahili
Zaidi ya Msingi wa Kodi (Toleo Lililosasishwa): Miji Mitano, Mapengo Matano Tofauti — na Gharama ya Kutochukua Hatua Hadi 2030/31 — Toleo la kwanza la utafiti huu lilionyesha kuwa Dar es Salaam pekee inapoteza mabilioni ya shilingi kila siku kwa msongamano wa magari. Toleo hili lililosasishwa linaenda mbali zaidi: TICGL/TERI imegundua kuwa kila mji mkubwa wa Tanzania una tatizo lake la kipekee la kimuundo — si msongamano wa magari kila mahali.
Mabadiliko matatu makuu: (1) Takwimu za Mwanza za mwaka 2016 zimesasishwa kwa makadirio ya TICGL/TERI kufikia 2026 (Dola milioni 265–300 kwa mwaka, ≈TZS bilioni 700–790) na utabiri hadi 2030/31; (2) Arusha, Dodoma na Mbeya sasa zina tafiti za kwanza kabisa, kila moja ikitambua tatizo lake tofauti; (3) Ripoti sasa ina utabiri wa gharama hadi 2030/31, kipindi cha FYDP IV na njia ya Dira 2050.
Dar es Salaam inaendelea kupoteza TZS bilioni 4 hadi 8.5 kwa siku kwa msongamano, huku Halmashauri zake tano zikikusanya asilimia 26 tu ya mahitaji yake ya mapato ya ndani. Mwanza (iliyosasishwa) inakadiriwa kupoteza TZS bilioni 700–790 kwa mwaka 2026, ikiongezeka hadi TZS trilioni 0.93–1.05 ifikapo 2030/31 bila hatua za ziada. Arusha tatizo lake kuu si msongamano bali uhakika wa maji — AUWSA imeshindwa mara kwa mara kufikia lengo la huduma kamili, na hasara ya maji isiyolipiwa (non-revenue water) imeongezeka kutoka asilimia 36.8 hadi 42.3 mwaka mmoja tu; TICGL inakadiria hasara ya kiuchumi ya utalii ya TZS bilioni 62–123 kwa mwaka. Dodoma tatizo lake kuu ni utawala wa ardhi unaokwenda kasi zaidi ya uwezo wa taasisi — migogoro ya ardhi imeongezeka kiasi cha Waziri Mkuu kuagiza mapitio ya mfumo mzima wa utatuzi wa migogoro ya ardhi; hatari hii bado haijapimwa kifedha. Mbeya tatizo lake kuu ni msongamano wa mizigo kwenye kivuko cha mpaka cha Tunduma, kinachopitisha malori 400–500 kwa siku; TICGL inakadiria gharama ya ucheleweshaji wa TZS bilioni 15–46 kwa mwaka.
Kwa ujumla, hasara ya kimuundo iliyopimwa katika miji minne (bila Dodoma) inakadiriwa kufikia takribani TZS trilioni 3.2 kwa mwaka 2026, na inaweza kupanda hadi TZS trilioni 4.5–5.5 kwa mwaka ifikapo 2030/31 endapo hakuna hatua za ziada — sawa na theluthi moja ya pengo lote la mapato ya taifa linalotakiwa kuzibwa (TZS trilioni 5.5–13.75 kwa mwaka).
- Dar es Salaam: TZS bilioni 4–8.5/siku (msongamano) + asilimia 26 tu ya mapato ya ndani
- Mwanza (2026, makadirio): TZS bilioni 700–790/mwaka; 2030/31: TZS trilioni 0.93–1.05/mwaka (bila hatua)
- Arusha (mpya): uhakika wa maji, TZS bilioni 62–123/mwaka (makadirio ya kwanza)
- Dodoma (mpya): utawala wa ardhi — hatari inayoongezeka, bado haijapimwa kifedha
- Mbeya (mpya): msongamano wa mizigo Tunduma, TZS bilioni 15–46/mwaka (makadirio ya kwanza)
Vyanzo: TICGL/TERI (2025, 2026), LATRA/SUMATRA (2016), AUWSA/EWURA, TANROADS, TradeMark Africa, Benki ya Dunia, NBS, na Wizara ya Fedha. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI), Agosti 2026 (Toleo Lililosasishwa).
01 — OverviewExecutive Summary
Dar es Salaam is Tanzania's undisputed commercial capital and one of the fastest-growing large cities in Africa. Yet the five local government authorities (Halmashauri) that administer the city — Dar es Salaam City Council (Ilala), Kinondoni, Temeke, Ubungo, and Kigamboni — collected only TZS 245.8 billion in own-source revenue (OSR) in 2023/24, equal to roughly US$98 million, or about US$17 per resident per year. That sum financed just 26% of the councils' combined revenue and 33% of their operating revenue; the remainder came from central government transfers — TZS 496.7 billion in operating grants and TZS 199.4 billion in development grants.
This is the central paradox this report examines: the city that generates an estimated 15–20% of national GDP and hosts the headquarters of firms responsible for roughly 70% of Tanzania's tax collections runs municipal councils that are almost as transfer-dependent as councils in far poorer, less commercially active regions. Own funds cover barely a quarter of what Dar es Salaam's Halmashauri need to run schools, clinics, roads, drainage, solid waste management and other devolved services for a population already approaching 6 million on official regional boundaries — and closer to 8–9 million on a wider metropolitan definition. This shortfall is not only structural — a narrow legal revenue base and centralised property tax administration — but also strategic: comparator cities with similar or lower income levels finance two to three times more of their own budgets through deliberate, sustained investment in valuation, digitisation and dedicated revenue institutions.
The report situates this fiscal mismatch within Tanzania's next two policy cycles: the Fourth Five-Year Development Plan (FYDP IV, 2026/27–2030/31), which depends on a 70:22:8 private-government-parastatal investment split to fund a TZS 477.7 trillion national investment programme, and the National Development Vision (Dira 2050), which targets a US$1 trillion economy and roughly US$7,000 per-capita income by mid-century. Neither ambition is achievable if the country's principal engine of urban growth and private investment cannot finance the basic infrastructure and services that make growth liveable, investable, and sustained.
- The gap is TZS 696.1 billion, in a single year. Dar es Salaam's Halmashauri needed TZS 941.9 billion in combined total revenue in 2023/24 but raised only TZS 245.8 billion locally — a gap financed almost entirely by central transfers.
- The headquarters-taxation effect distorts the picture. Firms are taxed where they file, not where their activity occurs — so Dar es Salaam's outsized 70%+ share of national tax revenue is a central-government phenomenon that barely touches municipal budgets.
- Property tax, the obvious fix, has been centralised. Utility-linked billing via TANESCO has improved bill delivery but distanced Halmashauri from valuation, rate-setting and enforcement.
- This is a strategy gap as much as a structural one. Lagos (~72%), Nairobi (50%+ targeted) and South Africa's metros (~81%) all finance far more of their own budgets — through deliberate, multi-year investment in digitisation and dedicated revenue institutions, not because they are richer.
- Neither FYDP IV nor Dira 2050 works without fixing this. Both frameworks assume Dar es Salaam functions as a credible, investable metropolis — an assumption that depends on functioning, adequately financed municipal government.
02 — Key NumbersKey Numbers at a Glance
DSM Own-Source Revenue, 2023/24
TZS 245.8bn
~US$98 million
Total Revenue Need, 2023/24
TZS 941.9bn
Gap: TZS 696.1bn
OSR Share of Total Revenue
26%
33% of operating revenue
Per-Capita OSR / Year
~US$17
Region population 5.3M+
DSM Share of National GDP
15–20%
~TZS 32–36 trillion
DSM Share of National Tax Revenue
~70%
80%+ in some BoT zonal quarters
DSM Share of National LGA OSR
~23–25%
Better than national average
National LGA OSR Target, FY2026/27
TZS 1.977T
Modest share of TZS 62.33T budget
Sources: National Audit Office data compiled in Good Governance Africa, Dar es Salaam African Cities Report (2025); Bank of Tanzania quarterly zonal reports; Ministry of Finance 2026/27 Budget Speech (11 June 2026); TICGL/TERI analysis.
03 — Section 1Dar es Salaam's Demographic and Economic Weight
1.1 Population and Urban Growth
According to the 2022 Population and Housing Census, Dar es Salaam Region recorded 5,383,728 residents, 100% classified as urban — up 23.4% from 4,364,541 in 2012, an average annual growth rate of 2.1%. Official regional projections place the population on course to approach 5.9 million by the mid/late-2020s. Broader metropolitan or agglomeration estimates — capturing continuous built-up areas spilling into neighbouring Coast Region — are substantially higher, commonly cited in the range of 7.8–9 million for 2025–2026, with annual growth nearer 4.5–5% under some analyses.
Dar es Salaam is routinely ranked among the fastest-growing large cities in Africa and globally, and is projected to reach megacity status (over 10 million residents) around 2030, with some projections placing the metropolitan population above 13 million by the mid-2030s. Urban expansion has consistently outpaced population growth, and informal settlements are estimated to account for 70–80% of the built-up area — a pattern that complicates infrastructure planning, service delivery, and, centrally to this report, the administration's ability to identify, register and tax property and economic activity.
1.2 Economic Output and Tax Concentration
Dar es Salaam is estimated to generate roughly 15–20% of Tanzania's GDP — commonly cited around 17%, or on the order of TZS 32–36 trillion in mid-2020s terms — remaining the country's principal commercial, industrial, logistics and services centre and a key hub for the wider East African region.
National tax collection is even more concentrated than GDP. Analyses linking TRA and NBS data indicate that Dar es Salaam accounts for approximately 70% of Tanzania's tax revenue, despite generating a considerably smaller share of GDP; Bank of Tanzania quarterly zonal reports have at times shown the zone contributing over 80% — in specific quarters as high as 85–89%. This largely reflects the concentration of corporate headquarters in the city: firms are taxed where they are registered and file returns, not necessarily where their underlying economic activity is located.
Why this distinction matters
Dar es Salaam's outsized contribution to national tax revenue is a central-government (TRA) phenomenon, and very little of it accrues to the city's own Halmashauri, whose revenue instruments are narrower, more localised, and considerably harder to administer. The city's tax footprint substantially overstates the share of the underlying tax base that is genuinely municipal in character.
GDP Share vs. Tax Revenue Share vs. Own-Source Revenue Share
Dar es Salaam's share of national GDP, national tax collections, and national LGA own-source revenue (%)
Sources: National Bureau of Statistics (2022 Census); Bank of Tanzania quarterly zonal collection reports; TRA/NBS-linked revenue-concentration analyses; TICGL/TERI background analysis.
04 — Section 2The Fiscal Paradox: Local Government Revenue Structure
2.1 Administrative Structure
Dar es Salaam Region is administered through five constituent Halmashauri: Dar es Salaam City Council (based in Ilala), and the municipal councils of Kinondoni, Temeke, Ubungo and Kigamboni. These bodies are responsible for a substantial share of front-line public service delivery — primary and secondary education infrastructure, primary health facilities, local roads and drainage, solid waste management, markets, and local business licensing — but operate under constrained fiscal autonomy.
2.2 Own-Source Revenue by Municipality, 2023/24
Own-Source Revenue by Municipality (TZS billions), 2023/24
National Audit Office data compiled in the Good Governance Africa Dar es Salaam African Cities Report (2025)
Grant figures were disclosed only at the region-level total in the source data (Good Governance Africa, 2025), not broken down by municipality. Source: National Audit Office figures.
Region-Wide Revenue Composition, 2023/24
Own-source revenue vs. operating and development grants
Local taxes, rates, levies and cesses form the largest single category of own-source revenue (around 46% in one breakdown across the five municipalities), followed by service levies, licences and related fees. Property tax collection — historically one of the most promising urban revenue instruments — has often been centralised through utility-linked billing arrangements (notably via TANESCO), which has limited direct municipal control over both the tax base and the collection process.
Source: National Audit Office figures, compiled in Good Governance Africa, Dar es Salaam African Cities Report (2025); TICGL/TERI analysis.
05 — Section 3Root Causes of the Revenue Gap
Halmashauri revenue instruments are legally narrower than those available to the central government, and the instruments they do control are labour-intensive to administer in a context of extensive informality and rapid, often unplanned, urban expansion.
3.1 A narrow, hard-to-administer revenue base
With an estimated 70–80% of Dar es Salaam's built-up area informal, identifying, registering, valuing and billing property owners is a persistent administrative burden that constrains collection regardless of the nominal tax rate.
3.2 Centralisation of high-potential instruments
Property tax — internationally one of the most buoyant urban local-government revenue sources — has in practice been collected through centralised, utility-linked billing, distancing municipal councils from valuation rolls, rate-setting and enforcement.
3.3 The headquarters-taxation effect
Almost none of Dar es Salaam's ~70% share of national tax revenue is assigned to its own Halmashauri; it flows to central government and is redistributed on formulae not calibrated to the city's disproportionate role in generating it.
3.4 Fragmented and inconsistent local taxation
Instruments such as the City Service Levy suffer weak TRA–local coordination, rate and enforcement disparities between neighbouring councils, and compliance burdens on firms operating across multiple LGA jurisdictions.
Read against the national baseline
Across Tanzania's Halmashauri as a whole, own-source revenue has frequently amounted to only a low-single-digit-to-low-teens share of total LGA resources, with dependency on central transfers commonly cited at 70–90%+ of budgets nationally. Dar es Salaam performs considerably better than this average — contributing roughly 23–25% of total national LGA own-source collections — yet still covers only about a quarter to a third of its own resource needs.
Source: Compiled from TICGL/TERI background analysis, National Audit Office / CAG reports, and published academic literature on Tanzanian local government finance and property taxation.
06 — Section 4The Strategic Gap: Lessons from Comparable Cities
The preceding section describes genuine structural constraints — a narrow legal revenue base, centralised property tax administration, a national tax system that credits Dar es Salaam's economic weight to the centre. But structure alone does not fully explain the gap. Other rapidly growing cities, some with lower per-capita incomes than Dar es Salaam, finance a substantially larger share of their own budgets from own-source revenue.
Own-Source Revenue as a Share of Municipal Budget
Dar es Salaam vs. Lagos, Nairobi, and South Africa's major metros (%)
Sources: Lagos State Ministry of Finance ministerial briefings (2025–2026); Nairobi City County Fiscal Strategy Paper 2025 and County revenue reports (2025/26); South African National Treasury / Municipal Money data; TICGL/TERI compilation.
Lagos IGR Growth, 2023–2025
Internally generated revenue, ₦ billions
Nairobi County Own-Source Revenue
KSh billions, 2022 vs. 2025/26 target
4.1 What the comparisons show
Lagos State generated ₦1.87 trillion in internally generated revenue (IGR) in 2025 — about 72% of its ₦2.6 trillion total revenue — up from ₦895 billion just two years earlier, driven by a dedicated Lagos Internal Revenue Service, a digital tax and e-procurement platform, an AI-assisted revenue chatbot, and a Land Use Charge that itself grew over 30% in a single year.
Nairobi County raised own-source revenue from roughly KSh 8 billion in 2022 to a record KSh 15.4 billion in 2025/26 — a 92.5% increase in four years — driven by land rates, hospital revenue, business permits, parking fees and the 'Nairobi Pay' digital platform, achieved largely through enforcement and digitisation rather than new taxes.
South Africa's major metros — Johannesburg, Cape Town, eThekwini and Tshwane — self-generate around 81% of municipal income, principally through property rates and on-sold electricity and water tariffs, reflecting a legal and administrative framework built over two decades of municipal finance reform.
Comparative Takeaway
Dar es Salaam finances about a quarter to a third of its own budget from local revenue. Lagos finances roughly three-quarters, and South Africa's metros over four-fifths. The difference is not primarily that those cities are richer — it is that they have invested for years in valuation, digitisation, and dedicated revenue administration. That is a strategy gap as much as a structural one, and strategy gaps can be closed faster than legal reform.
07 — Section 5National Fiscal Context and Recent Trends, 2024–2026
The national picture provides useful context for interpreting Dar es Salaam's figures. In the first half of 2024/25 (July–December 2024), national LGA own-source collections reached TZS 697.8 billion, equivalent to 103.5% of target for that period, following second-quarter collections of TZS 342.1 billion (99.2% of the quarterly estimate) — evidence of steady, broadly on-target collection performance at the aggregate national level.
For the 2026/27 fiscal year — the first budget year under FYDP IV — the national budget, presented to Parliament on 11 June 2026, totals TZS 62.33 trillion. Of estimated total revenue of TZS 46.79 trillion, TZS 36.99 trillion is projected from tax revenue and TZS 9.24 trillion from other revenue, within which LGA own-source revenue is budgeted at TZS 1.977 trillion nationally — a relatively modest line item against the scale of the overall budget.
The Controller and Auditor General's 2024/25 annual report, presented to the President in early 2026, recorded total government revenue collection of TZS 47.2 trillion against a target of TZS 50.29 trillion (93.11% of target), with domestic revenue reaching 99.4% of projections and TRA collections exceeding goals.
Reading the Trend
National LGA own-source collections are meeting or slightly exceeding their own (modest) targets, which is a genuine administrative achievement — but the targets themselves remain small relative to national revenue and relative to the infrastructure and service needs of a rapidly urbanising population, particularly in Dar es Salaam.
Sources: Ministry of Finance, Budget Execution Report Q2 2024/25; Ministry of Finance 2026/27 National Budget documents and Budget Speech (11 June 2026); Controller and Auditor General 2024/25 Annual Report.
08 — Section 6Policy Implications for FYDP IV and Dira 2050
FYDP IV Financing Split, 2026/27–2030/31
TZS 477.7 trillion investment programme, by financier
6.1 FYDP IV's private-investment model needs investable cities
FYDP IV targets real GDP growth of 10.5%, nominal GDP of approximately US$118.1 billion, and per-capita income of roughly US$1,638 by 2031, financed through a plan costing an estimated TZS 477.7 trillion — around 70% from the private sector, 22% government, 8% public corporations. Dar es Salaam, as the location of the great majority of formal private investment and headquarters activity, is implicitly the plan's most important single geography.
TICGL's own analysis of the first FYDP IV budget has flagged a structural tension: the budget introduces a substantial number of new taxes and fees even as the plan depends on mobilising large-scale private capital — a tension compounded, not eased, by the local government financing gap documented in this report.
6.2 Dira 2050's urban ambitions require credible municipal finance
Dira 2050 targets a US$1 trillion national economy and per-capita income in the range of US$7,000 by 2050, building on the outgoing Vision 2025 framework, which formally concluded on 30 June 2026. A 25-year vision of this ambition implicitly assumes sustained urbanisation, with Dar es Salaam's population plausibly doubling or more over the vision period. Financing that scale of urban growth through central-government transfers alone would require an even larger and more centralised transfer system than the one already straining to fund the city's Halmashauri today — an approach difficult to reconcile with Dira 2050's own emphasis on private-sector-led, market-oriented growth.
6.3 The self-reliance philosophy applies locally, not only nationally
Tanzania's Presidential Commission on Tax System Reforms has explicitly framed its recommendations around a business-friendly tax system consistent with the country's self-reliance philosophy. That same principle — reducing dependency and strengthening the revenue base that funds development — applies with equal force at the municipal level. A national government reducing dependence on external grants (Development Partner grants fell 39.1% in the 2026/27 budget, with 74.2% of the budget financed domestically) while its largest city's Halmashauri remain 70%+ dependent on central transfers has not yet extended the same self-reliance logic downward to the tier of government closest to citizens.
Illustrative Path A — Status QuoThe strategy gap persists through FYDP IV
- Property tax administration stays centralised; valuation rolls remain outdated in fast-growing, largely informal peri-urban areas.
- Dar es Salaam's OSR share of municipal budgets stays broadly flat in the 26–33% range through 2030/31.
- Central transfers continue absorbing the bulk of the revenue gap, competing with FYDP IV's own financing needs.
Illustrative Path B — Reform PathComparator-city reforms are adopted
- A hybrid valuation/enforcement model returns authority to Halmashauri while retaining digitised, centralised billing where it works.
- Dedicated, accountable municipal revenue institutions and digitised billing (as in Lagos and Nairobi) are built out.
- OSR share of municipal budgets moves toward the 45–55% range achieved by regional comparators within the FYDP IV horizon.
Path A and Path B are TICGL/TERI illustrative scenarios for discussion purposes, not official government projections. Source: FYDP IV and Dira 2050 figures compiled from Ministry of Finance budget documents, National Planning Commission statements, and TICGL/TERI budget analysis.
Policy RecommendationsRecommendations
1. Strengthen and localise property taxation. Return greater valuation and enforcement authority to Halmashauri while retaining centralised, technology-enabled billing where it improves compliance — a hybrid model rather than full centralisation or full devolution. Prioritise systematic property enumeration in rapidly expanding peri-urban and informal areas.
2. Adopt proven comparator-city reforms. Invest in a dedicated, digitised municipal revenue platform along the lines of Lagos's e-Tax system or Nairobi's 'Nairobi Pay', and build dedicated, accountable revenue-collection capacity within each Halmashauri, mirroring Lagos's Internal Revenue Service model.
3. Rebalance the intergovernmental transfer formula. Explore a Dar es Salaam-specific or metro-weighted adjustment to transfer formulae, and consider ring-fencing a small, transparent share of Dar es Salaam-headquartered corporate tax revenue for reinvestment in city infrastructure.
4. Simplify and harmonise local business taxation. Pursue legal reform of instruments such as the City Service Levy to reduce cross-jurisdictional compliance burdens, and strengthen TRA–municipal coordination to reduce duplication.
5. Align FYDP IV and Dira 2050 with municipal capacity. Treat municipal own-source revenue strengthening as an explicit enabler of the FYDP IV private-investment target, and build Dar es Salaam-specific municipal finance benchmarks into Dira 2050 monitoring.
09 — Section 8Data Sources and Methodology Note
This report synthesises data from the following primary categories of source. Where figures conflict across sources — as they frequently do for population and revenue estimates — this report generally presents the range rather than a single point estimate, and flags TICGL's own modelled figures explicitly as estimates.
Primary Sources
- National Bureau of Statistics (NBS) — 2022 Population and Housing Census and subsequent projections
- Good Governance Africa — Dar es Salaam African Cities Report (2025), citing National Audit Office 2023/24 local government revenue data
- Bank of Tanzania — quarterly zonal revenue collection reports
- Ministry of Finance — Budget Execution Report Q2 2024/25; 2026/27 National Budget documents and Budget Speech (11 June 2026)
- Controller and Auditor General (CAG) / National Audit Office — Annual General Report on Local Government Authorities, 2024/25 audit findings
- National Planning Commission and Ministry of Finance — FYDP IV (2026/27–2030/31) presentations and guidelines
- Office of the President — Dira 2050 statements and Presidential Commission on Tax System Reforms report (March 2026)
- Lagos State Ministry of Finance; Nairobi City County Fiscal Strategy Paper 2025; South African National Treasury / Municipal Money platform
- TICGL/TERI original analysis, including budget and revenue commentary published at ticgl.com
Methodology Note
Figures compiled across sources may differ slightly depending on definitional scope (administrative region vs. metropolitan agglomeration; operating vs. total revenue; fiscal-year timing) and prevailing exchange rates at time of publication. Where sources conflicted, this report presents the range and notes the more conservative or officially-sourced figure where applicable. Illustrative scenario figures in Section 6 (Path A / Path B) are TICGL/TERI modelling for discussion, not official government forecasts.
This report was prepared by TICGL / Tanzania Economic Research Institute for research and advisory purposes. Figures marked as TICGL estimates or projections are the firm's own modelling and should be distinguished from officially published government statistics. © 2026 Tanzania Investment and Consultant Group Ltd (TICGL).
10 — Quick AnswersFrequently Asked Questions
How much own-source revenue did Dar es Salaam's local governments raise in 2023/24?
Dar es Salaam's five Halmashauri collected TZS 245.8 billion in own-source revenue in 2023/24 — about US$98 million, or roughly US$17 per resident per year — financing 33% of operating revenue and 26% of total revenue.
Why does Dar es Salaam generate so much tax revenue but so little local government revenue?
Firms headquartered in Dar es Salaam generate an estimated 70% of Tanzania's tax revenue, but they are taxed centrally by TRA based on where they file, not where their activity happens. Almost none of that revenue is assigned to the city's own Halmashauri.
How does Dar es Salaam's own-source revenue compare to Lagos, Nairobi, and South African metros?
Dar es Salaam finances roughly 26–33% of its budget locally, versus over 50% targeted in Nairobi, ~72% in Lagos, and ~81% in South Africa's major metros.
What is the size of Dar es Salaam's local government revenue gap?
In 2023/24, the gap between what Dar es Salaam's Halmashauri needed (TZS 941.9 billion) and what they raised locally (TZS 245.8 billion) was TZS 696.1 billion, financed almost entirely through central transfers.
Why does property tax generate so little revenue for Dar es Salaam's municipalities?
Property tax billing has largely been centralised through TANESCO utility-linked billing, distancing municipal councils from valuation rolls, rate-setting and enforcement, and limiting growth in this revenue line as the city's property stock expands.
Muhtasari kwa Kiswahili
Kwa Nini Jiji Tajiri Zaidi la Tanzania Linaendesha Serikali za Mitaa Masikini Zaidi Kifedha? Utafiti mpya wa TICGL/TERI unaonyesha kuwa Halmashauri tano za Dar es Salaam — Jiji la Dar es Salaam (Ilala), Kinondoni, Temeke, Ubungo, na Kigamboni — zilikusanya TZS bilioni 245.8 tu za mapato ya ndani (own-source revenue) mwaka 2023/24, sawa na asilimia 26 ya mahitaji yao yote ya mapato na asilimia 33 ya mapato ya uendeshaji. Hii ni licha ya Dar es Salaam kuchangia takriban asilimia 15–20 ya Pato la Taifa (GDP) na kuwa na makao makuu ya makampuni yanayochangia takriban asilimia 70 ya makusanyo ya kodi nchini.
Pengo la mapato: Halmashauri za Dar es Salaam zilihitaji jumla ya TZS bilioni 941.9 mwaka 2023/24 lakini zilikusanya TZS bilioni 245.8 tu kutoka vyanzo vyao vya ndani — pengo la TZS bilioni 696.1 lililofidiwa karibu yote na ruzuku za Serikali Kuu.
Ripoti hii inaonyesha kuwa tatizo hili si la kimuundo pekee (upana mdogo wa vyanzo vya kisheria vya mapato na usimamizi wa kati wa kodi ya majengo), bali pia ni la kimkakati: majiji linganifu kama Lagos (~asilimia 72), Nairobi (zaidi ya asilimia 50 kwa lengo la 2025/26), na miji mikuu ya Afrika Kusini (~asilimia 81) yanajikusanyia mapato zaidi kwa sababu ya uwekezaji wa muda mrefu katika uthaminishaji wa mali, uwekaji digitali, na taasisi maalum za ukusanyaji mapato — si kwa sababu tu ya kuwa na uchumi mkubwa zaidi.
TICGL inasisitiza kuwa mafanikio ya Mpango wa Tatu wa Maendeleo wa Miaka Mitano (FYDP IV, 2026/27–2030/31) na Dira ya Taifa ya Maendeleo 2050 (lengo la uchumi wa Dola trilioni 1 na kipato cha wastani cha Dola 7,000 kwa mtu) hayawezi kufikiwa endapo jiji kuu la kiuchumi la nchi haliwezi kugharamia miundombinu na huduma za msingi zinazofanya ukuaji uwe endelevu na wa kuvutia uwekezaji.
- Mapato ya ndani ya Halmashauri, 2023/24: TZS bilioni 245.8 (asilimia 26 ya mahitaji)
- Pengo la mapato: TZS bilioni 696.1, lililofidiwa na ruzuku za Serikali Kuu
- Mchango wa Dar es Salaam kwenye GDP ya Taifa: asilimia 15–20; kwenye kodi ya Taifa: karibu asilimia 70
- Ulinganisho: Lagos ~asilimia 72, Nairobi zaidi ya asilimia 50, miji mikuu ya Afrika Kusini ~asilimia 81
Vyanzo: Ofisi ya Taifa ya Takwimu (NBS), Ofisi ya Mdhibiti na Mkaguzi Mkuu wa Hesabu za Serikali (CAG), Good Governance Africa, Benki Kuu ya Tanzania (BOT), Wizara ya Fedha, na utafiti wa TICGL/TERI. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI), Agosti 2026.
01 — OverviewExecutive Summary
Dar es Salaam is East Africa's fastest-growing large city and Tanzania's principal economic engine, generating roughly 17–20% of national GDP. How large the city actually is depends on which boundary is used: the official NBS Dar es Salaam Region — the five municipal councils of Ilala, Kinondoni, Temeke, Ubungo, and Kigamboni — held an estimated 5.86 million people in 2026, up from 5,383,728 at the 2022 census. But the city's continuously built-up urban footprint now extends well beyond that administrative boundary into neighbouring Coast (Pwani) Region — Kibaha, Bagamoyo, and Mkuranga in particular — and on the broader metropolitan-agglomeration definition used by the UN's World Urbanization Prospects, Dar es Salaam's functional population had already reached approximately 8.6 million in 2025 and an estimated 9.0 million in 2026, growing at close to 5% per year.
The physical fabric of the city, on either definition, has not kept pace with its economic and demographic weight: 70–80% of residents live in informal, unplanned settlements that lack secure tenure, adequate drainage, reliable sanitation, and planned road access. This report brings together national census figures, UN population data, World Bank and UN-Habitat assessments, Bank of Tanzania and TRA data, and TICGL's own city-economics research to quantify how informality constrains infrastructure delivery, what it costs government on a recurring basis, and how the trajectory is likely to evolve to 2030.
- Informal settlement area expanded six-fold in four decades. From roughly 52 km² in 1982 to about 379 km² in 2022 — meaning most new infrastructure must now be retrofitted into already-built, densely occupied land rather than laid out ahead of settlement.
- The fiscal cost of informality is continuous, not one-off. It shows up daily in foregone tax revenue from untaxed economic activity, in elevated operating and maintenance costs for roads and drainage built to serve unplanned densities, and in periodic but recurring flood losses that this report annualises into a daily order-of-magnitude figure.
- Without a step-change, informality could persist at or above today's levels through 2030 — even as the city's population climbs toward 7 million on the official boundary and national policy targets a much higher rate of formal employment and tax mobilisation.
- The total recurring economic cost of unplanned urban growth — spanning infrastructure retrofit, foregone tax revenue, and flood-related losses — plausibly runs to an illustrative ~TZS 6–8.5 billion per day (~US$2.3–3.3 million), with wide uncertainty bands reflecting the underlying data.
- The burden splits roughly evenly. ~TZS 2.9–3.3 billion/day falls directly on government (infrastructure retrofit and foregone tax revenue); ~TZS 3.0–3.3 billion/day is absorbed by households, businesses, and the wider city economy through flood damage and disrupted commerce.
02 — Key NumbersKey Numbers at a Glance
DSM Region Population 2026
~5.86M
Official NBS boundary
DSM Metro Population 2026
~9.0M
UN agglomeration definition
Informal Settlement Share
70–80%+
ACRC, UN-Habitat, TICGL
Informal Area, 1982 → 2022
52 → 379 km²
+~630% in four decades
Dar es Salaam GDP, 2025
~TZS 35T
~US$22 billion
Informal Economy Share
~30%
2025 city estimate; national ~45–46% of GDP
Retrofit Cost (WB estimate)
~US$250M/yr
If spread over 30 years
Metro-Area Population, 2026
~9.0 million
Growing ~5% per year
Sources: NBS Census 2022, UN World Urbanization Prospects / Macrotrends metro-area series, ACRC, UN-Habitat, World Bank, TICGL Economics of Cities in Tanzania (Feb 2026), AllAfrica/Daily News (Dec 2025).
03 — Section 1The Scale of Informal Settlement in Dar es Salaam
1.1 Two Ways to Count the City — and Why It Matters
Any discussion of population pressure in Dar es Salaam has to start by being explicit about which "Dar es Salaam" is being measured, because the two commonly cited figures differ by more than 3 million people and lead to very different intuitions about the scale of the problem.
Official administrative boundary
NBS Dar es Salaam Region: the five municipal councils of Ilala, Kinondoni, Temeke, Ubungo, and Kigamboni. This is the boundary used by the national census and by LGA budgets. It recorded 5,383,728 people at the 2022 census, 100% classified as urban, growing at roughly 2.1% per year — reaching an estimated 5.86 million by 2026.
Metropolitan / urban agglomeration
UN World Urbanization Prospects definition: the continuously built-up urban area, which now sprawls well past the official regional boundary into neighbouring Coast (Pwani) Region — notably Kibaha, Bagamoyo, and Mkuranga. On this broader, functional definition, population reached approximately 8.16 million in 2024, 8.56 million in 2025, and an estimated 9.0 million in 2026 — growing at ~5% per year, nearly double the official regional rate.
The gap between these two figures is not a data error; it reflects where the fastest, least-controlled growth is actually happening. A substantial and rapidly growing share of Dar es Salaam's real, physically contiguous urban population — heavily concentrated in new, unplanned peri-urban settlement along the Bagamoyo, Morogoro, and Kilwa road corridors — falls outside the boundary that generates official population statistics, LGA revenue projections, and, in many cases, planning jurisdiction. This report uses the official regional figure wherever the analysis is tied to census, budget, or LGA-level data, and the wider metropolitan figure wherever the concern is the lived, physical scale of population pressure on land, roads, and services.
Dar es Salaam Population, 2002–2030: Official Region vs. Metropolitan Area
Millions of people — official NBS Region boundary vs. UN metropolitan-agglomeration definition, historical to 2026 and TICGL scenario projection to 2030
Official Region Population
Metropolitan (Agglomeration) Population
On either boundary, absolute growth remains large even as percentage growth rates have moderated. Dar es Salaam — on the metropolitan definition — is adding roughly 400,000 people a year at present; TICGL's research estimates that 150,000 or more of the region's own new residents each year settle without a formal land claim, a figure that would be materially higher again if the Coast Region fringe were included.
The informal population, in absolute terms
Applied to the larger metropolitan population base, a 70–80% informal share implies that somewhere between 6.3 and 7.2 million people across greater Dar es Salaam were living in informal settlements in 2026 — a materially larger number than the 4.1–4.7 million implied by the official regional population alone, and a more accurate reflection of the true scale of the infrastructure and service challenge.
1.2 Spatial Expansion of Unplanned Areas
Remote-sensing studies place the built extent of informal settlement in Dar es Salaam at approximately 52 km² in 1982, expanding to roughly 379 km² by 2022 — an increase of about 630% in four decades, far outpacing the roughly six-fold growth in population over a similar period. This expansion has been simultaneously a densification process near the city centre and a sprawl process at the periphery, with urban development now extending 40–50 km from the Central Business District along the main transport corridors.
Informal Settlement Area in Dar es Salaam, 1982 → 2026
Square kilometres of built informal settlement — remote-sensing studies and TICGL 2026 estimate
1.3 Housing and Tenure
Roughly 30% of Dar es Salaam residents live in formal housing with secure tenure; the remainder occupy informal plots where perceived security of occupation is common but legal title is rare. Mass land formalisation has made measurable but insufficient progress: over 675,000 land documents were issued nationally between 2020 and 2024, a pace TICGL's research describes as too slow relative to the roughly 150,000+ new informal residents Dar es Salaam absorbs annually. The national annual housing deficit stands at approximately 200,000 units, with the gap projected to exceed 3 million units by 2035 in the absence of a step-change in formal housing delivery.
Sources: NBS Census 1978–2022, UN World Urbanization Prospects / Macrotrends metro-area series, remote-sensing studies of built-up informal area, ACRC (2024), UN-Habitat, TICGL estimates. Pre-2022 population and area figures for intervening years are directional estimates interpolated between census points, not official data points.
04 — Section 2Why Informality Makes Infrastructure Delivery Harder
Unplanned settlement is not merely a housing or welfare issue — it is a direct, structural constraint on how efficiently government can build and maintain infrastructure. The mechanisms are well documented and largely explain why the same kilometre of paved road, drainage channel, or water main costs substantially more, and takes substantially longer, to deliver in an informal Dar es Salaam neighbourhood than on a planned greenfield site.
2.1 Retrofitting Versus Building Ahead of Settlement
In planned development, roads, drainage, water, and power corridors are surveyed and reserved before people build. In Dar es Salaam's informal settlements, the reverse has happened: dense, haphazard construction came first, and infrastructure must now be threaded through existing plots — requiring compensation, negotiated demolition, or complex re-engineering that can stall or derail a project outright if community negotiations break down, as happened with earlier attempts to clear the lower Msimbazi Valley.
2.2 Service Deficits That Compound Over Time
- Formal sewerage reaches a small minority of the city — often cited at 10% or less — with most households relying on pit latrines that overflow in heavy rain.
- Solid waste collection is incomplete because vehicles cannot navigate narrow, unplanned access routes; uncollected waste further blocks drainage and worsens flooding.
- Water access is partial and often informal, with unlicensed private boreholes contributing to aquifer depletion.
2.3 Flood-Prone Occupation of Hazardous Land
A large share of informal settlement has occurred on floodplains and river valleys — most visibly the Msimbazi Basin, home to an estimated 1.6 million people basin-wide and roughly 330,000 in the lower, most flood-exposed reaches. Major flood events have struck in seven of the last ten years, repeatedly disrupting the Bus Rapid Transit corridor at Jangwani Bridge. Earlier attempts to demarcate the valley as non-developable, including two demolition campaigns, were halted due to social opposition.
2.4 The "Build Fast, Open Fast" Problem
Population additions — still averaging well over 100,000 people per year — mean new roads are placed under heavy use almost immediately after opening, compressing the window for design and construction quality control. The effect is faster wear, more frequent resurfacing, and a compounding maintenance backlog, particularly on roads serving dense informal areas with poor drainage.
A direct, costed illustration
This dynamic is visible in government's own recent project list for Dar es Salaam: the Kigogo Bridge (TZS 17.7 billion), Jangwani Bridge (TZS 67 billion), and Mkwajuni Bridge (TZS 11 billion) were all commissioned specifically because flood-driven road closures on routes linking outlying districts to the city centre had become an economically unacceptable, recurring disruption.
05 — Section 3Development and Economic Planning Constraints
Beyond the physical engineering challenge, informality undermines the planning and fiscal instruments government needs to manage urban growth coherently.
3.1 Coordinated Land-Use Planning
Sporadic, self-built growth makes it difficult to sequence infrastructure investment against population distribution, since settlement patterns form organically rather than in response to planned service provision. Densification in informal areas often outpaces the space available for schools, clinics, markets, and drainage reserves, locking in service deficits that are expensive to correct later.
3.2 A Narrow Formal Tax Base
Dar es Salaam contributes an estimated 17–20% of Tanzania's GDP, yet converting that weight into public revenue is constrained by informality. A 2019 survey valued the city's informal economic activity at roughly TZS 6.2 trillion (~22.5% of city GDP then); more recent estimates for 2025 put informality at roughly 30% of the city's economy, even as the national informal economy is estimated at 45–46% of GDP and 76% of the workforce.
3.3 Fragmented Metropolitan Governance
Dar es Salaam is administered as three separate Local Government Authorities — Kinondoni, Ilala, and Temeke — each with its own licensing regime, planning department, development levies, and political leadership. This fragmentation is widely identified — including by the EIU and TICGL's own research — as the single highest-leverage governance reform available, with potential to add 0.5–1.0 percentage points to annual GDP growth if resolved.
3.4 The National Growth Trade-Off
Each percentage-point increase in Tanzania's urbanisation rate is associated with roughly 0.58 additional percentage points of GDP growth — urbanisation itself is a net positive. The risk is unmanaged urban growth: Tanzania's tax-to-GDP ratio improved from 11.8% (2020) to ~13.5–14% (2025/26), still below the government's own 16% target for 2027 and the Sub-Saharan Africa average of 16–17%.
Most Tanzanian LGAs collect less than 20% of their budgets from own-source revenue
Far below benchmarks such as Nairobi County's 50%+, because informal businesses routinely avoid formal registration to escape taxes, fees, and paperwork they perceive as offering limited benefit in return.
06 — Section 4Government Infrastructure and Resilience Spending: A 2018–2026 Snapshot
It is useful to see, side by side, the discrete sums government and its development partners have actually committed to counteracting the effects of informal, unplanned settlement in Dar es Salaam. These figures are not additive in a simple sense — they overlap in scope and timeframe — but together they show a consistent order of magnitude: infrastructure retrofit and flood-resilience spending has run into the hundreds of millions of US dollars, and low trillions of Tanzanian shillings, over the past decade, with no sign of tapering.
Infrastructure & Flood-Resilience Spending, Selected Programmes (US$ millions)
Approximate value of major committed or realised programmes, 2018–2026
Sources: World Bank Msimbazi Basin Development Project appraisal and GFDRR documentation; World Bank DMDP project documents; AllAfrica/Daily News (31 Dec 2025) on the TZS 900bn Dar es Salaam infrastructure allocation; IPS News (24 Jul 2025); Africa Cities Research Consortium; UN-Habitat.
4.1 What This Buys — and What It Doesn't
The Msimbazi Basin Development Project alone is expected to reduce flood exposure for more than 300,000 people and relocate roughly 2,500 households from the highest-risk flood zones by its 2028 completion, while unlocking an estimated US$900 million in real estate investment in the areas made viable by flood protection, according to World Bank-affiliated (GFDRR) analysis.
One basin, most of the city
These are targeted interventions in a single basin; the great majority of Dar es Salaam's 379 km² of informal settlement lies outside the Msimbazi catchment and remains largely unaddressed by any comparable programme, meaning the pattern of retrofit-driven cost overruns and periodic flood losses documented here is likely to persist across most of the city through 2030 even as flagship projects like Msimbazi and the BRT network expansion proceed.
07 — Section 5The Daily Economic Cost of Unplanned Urban Growth
How much does unplanned settlement and informal economic activity cost Dar es Salaam on a day-to-day basis? There is no single official published answer — Tanzania, like most developing-country governments, does not track a daily cost of informality as a discrete line item. What follows is a transparent, bottom-up estimate built by annualising the recurring cost categories identified in Sections 3 and 4 into a daily figure, so the scale of the burden can be compared against familiar reference points. Each component is presented separately, with its own basis and uncertainty, before being combined into the headline figure below.
Component A — Infrastructure Retrofit & Maintenance (Government)
~TZS 1.7–1.9bn/day
~US$685,000/day, from WB's ~US$250M/yr over a 30-year programme; the TZS 900bn Dec 2025 injection alone equates to ~TZS 2.5bn/day if spread over a year
Component B — Flood Losses, Annualised (City Economy)
~TZS 3.0–3.3bn/day
~US$1.2–1.3M/day, from a ~2% annual GDP drag applied to ~TZS 35–38T city GDP; borne mainly by households and businesses
Component C — Foregone Tax Revenue from Informality (Government)
~TZS 1.2–1.4bn/day
~US$460,000–540,000/day; the least precisely measurable component, based on Tanzania's ~13.5–14% effective tax rate applied to a conservative third of DSM's informal economy
Daily Cost by Component (TZS billions/day, midpoint estimate)
Components A, B and C combine into the headline daily cost figure
5.4 The Headline Number: Total Economic Cost, Split by Who Bears It
Reading Components A–C together, and being careful not to double-count, the recurring cost of unplanned urban growth in Dar es Salaam splits cleanly into two groups: costs that fall directly on government (infrastructure retrofit and foregone tax revenue), and costs that are absorbed by households, businesses, and the wider city economy (flood-related losses).
Who Bears the Daily Cost?
Government vs. households, businesses & city economy
Sources: TICGL calculations based on World Bank, Africa Cities Research Consortium, TRA, and TICGL Economics of Cities in Tanzania (2026) data. All daily figures are annualised averages derived from annual or multi-year data points; none reflect an officially published daily cost, and all carry a materially wide margin of error.
An unquantified cost sits on top of this total
Traffic congestion and unreliable logistics arising from an underdeveloped, unplanned road network are not included in the headline figure. The World Bank has described Dar es Salaam's congestion as costing billions of shillings in lost productivity daily, and TICGL/EIU analysis suggests resolving Dar es Salaam's fragmented metropolitan governance alone could add 0.5–1.0 percentage points to annual GDP growth — but no robust, city-specific daily congestion-cost figure has been published to date, so it is flagged here as an upside risk to the total rather than included in it.
Putting the number in context
Even allowing for a wide error margin, the exercise is useful directionally: TRA's 2025/26 target is TZS 36.066 trillion for the full fiscal year, or roughly TZS 99 billion per day on average. On that comparison, the ~TZS 6–8.5 billion/day estimated here would represent roughly 6–9% of average daily national tax collection — a material, continuous drag on the economy rather than an occasional shock, falling on government and on ordinary households and businesses in roughly equal measure.
Caveat
This is a planning-level, order-of-magnitude estimate assembled from the best publicly available data as of August 2026, intended to give decision-makers a sense of scale rather than a precise accounting figure. It should not be cited as an official government cost estimate. A dedicated primary data-collection exercise — ideally led jointly by PO-RALG, TRA, and the Dar es Salaam City Council — would be required to produce a defensible, audited daily or annual figure.
08 — Section 6Forecast to 2030
Two scenarios bound the plausible range for Dar es Salaam through 2030, consistent with TICGL's broader national urban-economics modelling (see TICGL, Economics of Cities in Tanzania, February 2026).
Scenario A — Business-as-UsualInformality drifts at or above today's range
- Metropolitan governance reform, land tenure formalisation, and drainage investment continue at their current, incremental pace.
- Informal settlement share remains at or drifts above today's 70–80% range; informal area continues expanding faster than formal plot supply.
- Annualised cost components grow roughly in line with city GDP: the estimated daily cost of informality could rise from ~TZS 6–8.5 billion in 2026 toward the TZS 9–12 billion per day range by 2030 in nominal terms.
- The national urban informal-settlement rate trends toward the 50% level TICGL flags as a risk by 2050, with Dar es Salaam trending toward the higher end of its historical 70–80% range.
Scenario B — Reform PathReforms already identified are implemented on schedule
- A unified Dar es Salaam Metropolitan Authority, accelerated land titling building on the 675,000 documents issued 2020–2024, and the IDRAS digital tax platform widening the formal tax net.
- Completion of the Msimbazi Basin Development Project and BRT Lines 2 and 3 by around 2028.
- Informal settlement share stabilises or begins a gradual decline by 2030; formal employment climbs toward the government's 38% target; LGA own-source revenue widens materially from today's sub-20% level.
- Even here, the housing deficit and population growth mean the absolute number of people in informal settlements is unlikely to fall before 2030 — the realistic near-term goal is a slower rate of informal expansion, not an outright reversal.
Indicative Trajectory to 2030: City GDP and Informal Settlement Share
Left axis: City GDP (TZS trillion). Right axis: informal settlement share (%, midpoint of scenario range)
6.3 Indicative Trajectory Table
Population figures below use the official Dar es Salaam Region boundary, for consistency with GDP and revenue data reported at that level. On the wider metropolitan/agglomeration definition, which grows faster, the equivalent trajectory would run from ~9.0 million (2026) to approximately ~10.8–11.2 million by 2030.
Sources: TICGL projections, consistent with TICGL Economics of Cities in Tanzania (Feb 2026), UN World Urbanization Prospects 2025, and World Bank/IMF growth projections. Figures for 2027–2030 are TICGL scenario projections, not official government forecasts. Note: values in the "Est. Daily Cost" column are reproduced as presented in the source report and reflect the wide-range planning nature of this exercise.
09 — Section 7Policy Implications
The data points toward a consistent set of priorities, several of which are already reflected in national policy discussions but require acceleration to meaningfully change Dar es Salaam's cost trajectory before 2030.
Prioritise retrofit-efficient infrastructure sequencing
- Concentrate drainage and road-upgrading investment in the highest-density, highest-flood-risk informal wards first, where retrofit cost per resident protected is lowest and avoided flood-loss value is highest.
- Where new roads must be opened to traffic quickly, budget explicitly for accelerated early-life maintenance rather than treating early deterioration as an unplanned cost overrun.
Widen the formal land and tax base together
- Pair land titling drives (building on the 675,000 documents issued 2020–2024) directly with LGA property-tax registration, so formalisation converts into revenue rather than remaining a standalone welfare intervention.
- Accelerate IDRAS and LGRCIS rollout specifically in high-informality wards, where the revenue upside identified in Section 5.3 is concentrated.
Resolve metropolitan governance fragmentation
- Progress the proposed unified Dar es Salaam Metropolitan Authority, replacing the current three-LGA structure, to reduce the transaction-cost drag on both infrastructure delivery and private investment.
Treat flood resilience as core infrastructure
- Extend the Msimbazi Basin model — preventative resettlement paired with infrastructure and livelihood restoration — to the city's other flood-exposed informal catchments, which together hold the majority of the city's 379 km² of informal settlement.
Build the measurement base this report had to estimate
Commission a joint PO-RALG/TRA/Dar es Salaam City Council study to produce an audited, recurring estimate of the fiscal cost of informality, replacing the order-of-magnitude modelling in Section 5 with a defensible official figure that can be tracked year over year.
10 — Section 8Data Sources and Methodology Note
This report synthesises data from the following primary categories of source. Where figures conflict across sources — as they frequently do for informal-settlement share and population estimates — this report generally presents the range rather than a single point estimate, and flags TICGL's own modelled figures explicitly as estimates.
Primary Sources
- National Bureau of Statistics (NBS) — 2022 Population and Housing Census; historical census series 1967–2022
- World Bank — Msimbazi Basin Development Project appraisal and implementation documents (P169425); Dar es Salaam Metropolitan Development Project (DMDP) documents; Tanzania Country Climate and Development Report (2024)
- UN-Habitat — Informal Settlements and Finance in Dar es Salaam, Tanzania
- African Cities Research Consortium (ACRC) — Dar es Salaam city profile and housing analysis
- Global Facility for Disaster Reduction and Recovery (GFDRR) — Msimbazi Basin feature reporting
- Bank of Tanzania, Tanzania Revenue Authority (TRA), and IMF World Economic Outlook — macroeconomic, fiscal, and tax-to-GDP data
- TICGL — Economics of Cities in Tanzania (Final Integrated Edition, February 2026); TICGL Economic Research 2024–2026
Methodology Note on the Daily Cost Estimate
The daily cost figures in Section 5 are derived by taking published annual or multi-year cost estimates (infrastructure retrofit budgets, flood-loss assessments, informal-economy size estimates) and dividing by 365 to produce a comparable daily order of magnitude. This is a standard annualisation technique for planning purposes, but it necessarily assumes costs are evenly distributed across the year, which they are not — flood losses in particular are concentrated in the rainy season (typically March–May and, to a lesser extent, October–December). The figures should therefore be read as average daily equivalents over a full year, not as literal day-to-day cash costs to government.
This report was prepared by TICGL / Tanzania Economic Research Institute for research and advisory purposes. Figures marked as TICGL estimates or projections are the firm's own modelling and should be distinguished from officially published government statistics. © 2026 Tanzania Investment and Consultant Group Ltd (TICGL).
11 — Quick AnswersFrequently Asked Questions
How much does unplanned urban growth cost Dar es Salaam each day?
TICGL/TERI estimates the total recurring economic cost at roughly TZS 6–8.5 billion per day (about US$2.3–3.3 million), combining infrastructure retrofit costs, foregone tax revenue, and annualised flood-related losses. This is an order-of-magnitude planning estimate, not an official government figure.
What share of Dar es Salaam's population lives in informal settlements?
Independent sources including UN-Habitat and ACRC consistently place 70–80%, and in some assessments over 80%, of Dar es Salaam residents in informal, unplanned settlements lacking secure tenure, adequate drainage, reliable sanitation, or planned road access.
How fast has informal settlement area grown in Dar es Salaam?
Remote-sensing studies show informal settlement area expanding from approximately 52 km² in 1982 to about 379 km² in 2022 — roughly 630% growth in four decades — with an estimated 400+ km² by 2026.
Who bears the daily cost of unplanned urban growth?
The cost splits roughly evenly: ~TZS 2.9–3.3 billion/day falls directly on government through infrastructure retrofit spending and foregone tax revenue; ~TZS 3.0–3.3 billion/day is absorbed by households, businesses, and the wider city economy through flood-related property damage and disrupted commerce.
What is Dar es Salaam's population in 2026?
On the official NBS Region boundary, approximately 5.86 million in 2026, up from 5,383,728 at the 2022 census. On the wider UN metropolitan-agglomeration definition, the functional population reached an estimated 9.0 million in 2026.
Muhtasari kwa Kiswahili
Gharama ya Kila Siku ya Ukuaji wa Miji Usiopangwa Jijini Dar es Salaam — Utafiti mpya wa TICGL/TERI unaonyesha kuwa asilimia 70 hadi 80 ya wakazi wa Dar es Salaam wanaishi katika makazi holela yasiyo na hati miliki salama, mifereji ya maji ya kutosha, huduma za usafi wa mazingira, wala barabara zilizopangwa. Eneo la makazi holela limeongezeka kutoka takriban kilomita za mraba 52 mwaka 1982 hadi kilomita za mraba 379 mwaka 2022 — ongezeko la takriban asilimia 630 katika miongo minne.
Gharama ya siku moja: TICGL inakadiria kuwa gharama ya jumla ya kiuchumi ya ukuaji wa miji usiopangwa jijini Dar es Salaam ni takriban TZS bilioni 6 hadi 8.5 kwa siku (sawa na Dola za Marekani milioni 2.3 hadi 3.3), ikijumuisha gharama za kurekebisha miundombinu, mapato ya kodi yaliyokosekana kutokana na shughuli za kiuchumi zisizo rasmi, na hasara za mafuriko zilizowekwa kwa mwaka mzima.
Gharama hii inagawanyika karibu sawasawa: takriban TZS bilioni 2.9–3.3 kwa siku zinabebwa moja kwa moja na Serikali (kupitia urekebishaji wa miundombinu na mapato ya kodi yaliyokosekana), na takriban TZS bilioni 3.0–3.3 kwa siku zinabebwa na kaya, wafanyabiashara, na uchumi mpana wa jiji kupitia uharibifu wa mali unaosababishwa na mafuriko na usumbufu wa biashara.
TICGL inasisitiza kuwa bila hatua za haraka za kurasimisha ardhi, kuboresha uongozi wa jiji (metropolitan authority), na kuongeza uwekezaji kwenye mifereji ya maji, kiwango cha makazi holela kinaweza kuendelea kubaki juu au hata kuongezeka hadi kufikia mwaka 2030, hata huku idadi ya watu ikizidi kuongezeka.
- Wakazi wa makazi holela: asilimia 70–80 ya wakazi wa Dar es Salaam
- Ukuaji wa eneo la makazi holela: kilomita za mraba 52 (1982) hadi 379 (2022) — ongezeko la asilimia 630
- Gharama ya kila siku: TZS bilioni 6–8.5 (~Dola milioni 2.3–3.3)
- Idadi ya watu Dar es Salaam (mkoa rasmi), 2026: takriban milioni 5.86; eneo pana la jiji (metropolitan): takriban milioni 9.0
Vyanzo: Sensa ya NBS 2022, Benki ya Dunia, UN-Habitat, African Cities Research Consortium (ACRC), GFDRR, Benki Kuu ya Tanzania (BOT), Mamlaka ya Mapato Tanzania (TRA), IMF, na utafiti wa TICGL/TERI. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI), Agosti 2026.
01 — OverviewExecutive Summary
Tanzania's National Bureau of Statistics (NBS) released the National Consumer Price Index (NCPI) for July 2026 on 10 August 2026, showing annual Headline Inflation at 4.2 percent, up from 4.0 percent in June 2026. This is a significant release for one specific reason: July was the first calendar month priced entirely under the FY2026/27 Budget's new tax measures, which took effect on 1 July 2026 following the Government's June budget announcement — the presumptive tax adjustments, betting excise duty changes and other revenue measures TICGL examined in its FY2026/27 Budget series. This report asks the question households and businesses are asking directly: one month on, is the new budget visible in the price data yet, and where should Tanzanians expect to feel it first?
The headline answer is nuanced. Food and Non-Alcoholic Beverages inflation — the single most important line for the average household budget, carrying the largest weight (28.2 percent) in the whole NCPI basket — held flat at 4.1 percent year-on-year and actually fell 0.8 percent month-on-month, as staple grains and tubers cheapened with the season. That is genuinely good news, and it is not the signature of a tax-driven food price shock. The pressure instead shows up on the transport and energy side: Transport inflation reached 13.8 percent year-on-year, by far the highest of the thirteen COICOP divisions, and diesel, petrol, charcoal and gas all rose in price within the month of July itself — the first month those goods carried the new fiscal year's duty structure.
- Headline inflation edged up but stayed moderate. At 4.2 percent, headline inflation remains comfortably inside the Bank of Tanzania's 3-5 percent target band, continuing a run of thirteen straight months between 3.2 percent and 4.2 percent.
- Food inflation eased, not spiked. Food and Non-Alcoholic Beverages inflation stayed at 4.1 percent year-on-year and fell month-on-month, led by cheaper rice, maize grain, maize flour, sweet potatoes, cassava and beans — a harvest-season pattern, not a budget-shock pattern.
- Fuel and energy is where the July move actually shows up. Diesel (+3.3% m/m), petrol (+2.5% m/m), charcoal (+4.5% m/m) and gas (+1.3% m/m) all rose in the very month the new fiscal year's tax and duty structure took effect, and the Energy, Fuel and Utilities Index posted 6.9 percent inflation year-on-year — its highest reading in this dataset.
- One month is not enough to prove causation. Fuel prices move with global oil markets, the exchange rate and seasonal transport demand as well as domestic duties. TICGL treats July as the first data point to watch, not a verdict, and will track the August and September releases closely.
- Core inflation crept up but remains contained. At 3.9 percent (up from 3.7 percent in June), core inflation — which strips out volatile food and energy prices — confirms that the broader, stickier price pressure in the economy is still modest.
02 — ContextAbout the National Consumer Price Index
The NCPI measures how the cost of a fixed basket of goods and services purchased by a representative sample of Tanzanian households changes over time. The current basket contains 383 goods and services — 132 food and non-alcoholic beverage items and 251 non-food items — priced using data collected from all 26 regional headquarters on the Tanzanian mainland. Weights are derived from the 2017/18 Household Budget Survey, the base price reference period is the average of January-December 2020, and the index reference period is 2020 (2020=100). The index follows the UN's Classification of Individual Consumption by Purpose (COICOP), 2018 version, across 13 divisions, and elementary indices are compiled using the geometric mean of price relatives, with higher-level aggregates built on the Lowe Index formula, a type of Laspeyres index.
Why July 2026 matters for this analysis
Tanzania's FY2026/27 Budget was presented in June 2026 and its tax and duty measures — including presumptive tax adjustments and a revised betting excise duty, as covered in TICGL's earlier budget-series research — took legal effect from 1 July 2026. Because NCPI price collection runs through the calendar month, the July 2026 release is the first NBS print built on prices collected entirely inside the new fiscal year. It is the earliest possible data point for observing whether new duties are visible at the till.
Supplementary indices published alongside the NCPI
- Core Index (excludes unprocessed food, energy and utilities except maize flour) — 73.9% of basket weight
- Non-Core Index — 26.1% of basket weight
- Energy, Fuel and Utilities Index — 5.7% of basket weight
- Services Index (37.2%) and Goods Index (62.8%)
- All Items Less Food and Non-Alcoholic Beverages Index — 71.8% of basket weight
NCPI Basket Composition by COICOP Division
Percent weight of each of the 13 divisions in the national basket, 2017/18 Household Budget Survey weights
03 — The Twelve-Month PictureHeadline Inflation Trend, July 2025 – July 2026
The Headline Inflation Rate measures overall inflation across the full CPI basket. Table 1 below and NBS's own Chart 1 show the NCPI generally trending upward across the year, from 119.85 in July 2025 to 124.85 in July 2026, while the annual inflation rate stayed within a narrow 3.2-4.2 percent range throughout — dipping to its lowest point in February-March 2026 before climbing through the second half of the fiscal year to its twelve-month high in July 2026.
NCPI Index and Annual Inflation Rate, July 2025 – July 2026
Left axis: NCPI (2020=100). Right axis: annual headline inflation rate, percent
NCPI Index (left axis)
Annual Inflation Rate (right axis)
Source: NBS NCPI Press Release, July 2026, Chart 1 and Table 1.
Reading the month-on-month dip
Between June and July 2026 the overall index actually fell slightly, from 125.04 to 124.85 — a 0.1 percent month-on-month decrease, driven mainly by cheaper food and staple grain prices. The annual rate still rose to 4.2 percent because July 2025's base value was low; this is a reminder that headline year-on-year inflation and month-on-month price direction can move in opposite directions in the same release, and both numbers matter for a complete picture.
04 — What This Means at the MarketFood Inflation: The Number That Matters Most for Households
Food and Non-Alcoholic Beverages carries the single largest weight in the NCPI basket at 28.2 percent — more than any other division — which is why it is the most consequential line for a typical Tanzanian household's real cost of living, and the line TICGL scrutinises most closely for signs of budget pass-through. In July 2026, food inflation held at 4.1 percent year-on-year, unchanged from June, while the food index itself fell month-on-month, from 136.92 in July 2025... actually from 136.92 (index level a year prior) — more precisely, from 136.92 in July 2025 to 136.92 baseline comparison aside, the relevant month-on-month move was from June 2026's 136.92 down to July 2026's 135.79, a decrease of 0.8 percent.
Food Inflation, Y-o-Y
4.1%
Unchanged from June 2026
Food Index, M-o-M
-0.8%
Prices fell within the month
Basket Weight
28.2%
Largest of all 13 COICOP divisions
The month-on-month decline was broad-based across staple foods, consistent with a seasonal harvest effect rather than a tax-driven price shock. The items pulling food prices down in July included several of the staples that make up the bulk of an ordinary Tanzanian household's plate:
Food Items With the Largest Price Movements, June → July 2026
Month-on-month percent change for selected food items in the NCPI basket
Source: NBS NCPI Press Release, July 2026, Section 3.
The reassuring signal for households
If the FY2026/27 Budget's tax measures were pushing food prices up broadly, the clearest place it would show first is staple grains and tubers, since these dominate the food basket and move through short, largely domestic supply chains. Instead, every one of the food items NBS flagged in July moved down, and the pattern — grains, tubers and pulses all falling together — is the signature of a harvest-season supply effect, not a new tax working its way through the food chain. This is a genuinely positive early reading for household food budgets.
05 — Where the Pressure Actually Shows UpFuel, Energy and Transport: The Line to Watch
While food prices eased, the same NBS release shows a very different pattern in transport and energy. Transport inflation reached 13.8 percent year-on-year in July 2026 — the highest annual inflation rate of any of the 13 COICOP divisions by a wide margin, and more than three times the headline rate. The Energy, Fuel and Utilities Index recorded 6.9 percent inflation year-on-year, also well above the headline figure. Within the month of July alone, diesel, petrol, charcoal and gas — the fuels that price everything from bus fares to cooking to the cost of moving food to market — all rose.
Fuel and Energy Items: Month-on-Month Price Change, June → July 2026
The first full month priced under the FY2026/27 fiscal year's duty structure
Source: NBS NCPI Press Release, July 2026, Section 3.
Why fuel is the honest place to look for a budget effect — and why one month isn't proof
Diesel and petrol prices in Tanzania respond to at least three forces simultaneously: global crude oil and refined-product prices, the shilling's exchange rate against the dollar, and domestic taxes, levies and duties set in the national budget. All three can move in the same month. TICGL cannot, from a single NBS release, separate how much of July's diesel and petrol increase came from global oil markets versus how much came from the FY2026/27 duty structure that took effect on 1 July. What can be said with confidence is that fuel and energy is mathematically the fastest-moving, highest-inflation part of the entire basket in the first month of the new fiscal year, and it is the line item most directly exposed to fuel levies and import duties. That makes it the correct place to keep watching, not a place to draw early conclusions.
Why this still matters for ordinary households even without proof of causation
Transport costs feed into the price of almost everything else with a lag — bus and dala-dala fares, the cost of moving food from farm to market, and the electricity and cooking-fuel bill for both urban and rural households. Even if July's food staples got cheaper at the point of harvest, a sustained rise in diesel and charcoal prices can slowly erode that gain by raising the cost of getting food to market and cooking it once it arrives — a lagged transmission TICGL will be watching for in the August and September releases.
06 — The Full PictureInflation by COICOP Division, July 2026
Table 1 below reproduces NBS's full group-by-group breakdown for July 2026, showing each division's weight in the basket, its index level a year ago and a month ago, its July 2026 index, and both its month-on-month and year-on-year percentage change.
Annual Inflation Rate by COICOP Division, July 2026
Percent, year-on-year — sorted from highest to lowest; food and transport highlighted
Other Selected Indices
Source: NBS NCPI Press Release, July 2026, Table 1.
Headline vs Core vs Food vs Services vs Goods vs Energy: Annual Inflation, July 2026
A single snapshot comparing the different ways of slicing July 2026's inflation reading
07 — The Question Everyone Is AskingReading the Budget Signal: One Month On
Tanzania's FY2026/27 Budget, presented to Parliament in June 2026, introduced a range of tax and revenue measures — presumptive tax adjustments for small businesses and a revised betting excise duty among them, as TICGL's earlier budget-series research documented — alongside a significant increase in the public wage bill. Those measures took legal effect from 1 July 2026. July's NCPI release is therefore the earliest possible window into whether the new fiscal year's tax structure is visible in consumer prices, and the honest reading of the data is: partially, and only in one place so far.
June 2026
FY2026/27 Budget presented and passed
New tax and duty measures, including presumptive tax and betting excise duty changes, are approved for the fiscal year beginning 1 July 2026.
1 July 2026
New fiscal year begins; tax and duty measures take effect
NCPI price collection for July begins under the new fiscal year's duty structure for the first time.
July 2026
First fully post-budget month of price data
Food prices fall month-on-month on seasonal supply; fuel, charcoal and gas rise; transport inflation reaches 13.8 percent year-on-year.
10 August 2026
NBS releases the July 2026 NCPI
The data TICGL analyses in this report becomes public.
8 September 2026 & beyond
August, September and October releases due
The next three NCPI releases will show whether July's fuel and transport pattern persists, accelerates or fades — the true test of any budget pass-through.
What the data supports saying
- Food prices, the largest and most politically sensitive basket item, moved down in July — no visible sign of a broad tax-driven food price shock in month one.
- Fuel, charcoal and gas — the items most directly exposed to duties, levies and import costs — all rose in the same month the new fiscal year's tax structure took effect.
- Transport inflation at 13.8 percent year-on-year is not new in this dataset; it has been elevated for some months, but July continued that pattern with the highest reading in the twelve-month series shown.
What the data cannot support saying yet
- That the FY2026/27 Budget's specific tax measures caused the July fuel price increase — global oil prices and the exchange rate moved in the same window and cannot be separated out from one release.
- That food prices are now safe from budget-related pressure for the rest of the year — presumptive tax changes affect small traders' costs in ways that can take several months to show up in retail prices.
- That transport's 13.8 percent reading is new or budget-driven, since it was already the highest-inflation division before July arrived.
TICGL's method going forward
Rather than declare a verdict from a single data point, TICGL will track the Energy, Fuel and Utilities Index, the Transport division, and the Food and Non-Alcoholic Beverages division across the August, September and October 2026 NCPI releases (due 8 September, 8 October and 9 November 2026 respectively) and update this analysis. A genuine budget-driven pass-through would be expected to persist or build over several months, not appear and disappear in one release.
08 — Looking AheadWhat Could the Next Six Months Bring?
Projecting inflation six months out is inherently uncertain, and TICGL does not present the scenarios below as forecasts with precise numbers — no single NCPI release can support that. Instead, these are three plausible directions the data could move in through early 2027, based on the forces already visible in the July release, each with the conditions that would confirm it.
Scenario A — Most LikelyHeadline inflation stays inside the 3-5% band
- Food inflation stays moderate as the harvest season continues to support supply through late 2026.
- Fuel prices stabilise or ease slightly if global oil prices hold steady and the shilling remains stable.
- Core inflation stays close to its current 3.9%, keeping BOT's monetary stance broadly unchanged.
Scenario B — Watch CloselyTransport and energy inflation persists or edges higher
- Diesel, petrol, charcoal and gas continue rising in the August-October releases, confirming a sustained fiscal-year effect rather than a one-month blip.
- Higher transport costs begin to lift food prices with a lag, as it becomes more expensive to move produce to market, partially offsetting the current harvest-season relief.
- Headline inflation drifts toward the upper end of the 3-5% band by year-end.
Scenario C — Lower ProbabilityPost-harvest food price reversal plus sustained fuel pressure
- The seasonal food price relief fades once the current harvest is absorbed, typically toward the final quarter of the calendar year.
- If this coincides with continued fuel and transport cost pressure, both major components of the basket could push upward at the same time.
- This is the combination that would most directly test the 3-5% inflation target band and warrant closer BOT attention.
What would move TICGL from "watching" to a firmer view
Three consecutive months (August-October 2026) of rising Transport and Energy, Fuel and Utilities inflation, occurring alongside a stable or appreciating shilling and stable global oil prices, would be the clearest evidence that the FY2026/27 Budget's duty structure — rather than external factors — is driving the pattern. Conversely, if fuel inflation eases once July's one-off adjustment period passes, that would suggest global or exchange-rate factors, rather than the domestic tax structure, were the larger driver.
09 — TICGL AnalysisWhat This Means for the Ordinary Tanzanian Household
1. The food budget got a genuine, if temporary, reprieve
For households where food is the largest share of spending, July's month-on-month price falls in rice, maize, cassava and beans are real relief, and it arrived in the same month the new budget's measures took effect — an important, reassuring coincidence for anyone worried the new fiscal year would immediately hit the plate.
2. The transport bill is the one to watch, not celebrate
At 13.8 percent year-on-year, transport inflation was already the fastest-moving part of the basket before July, and it stayed there. Households that spend a meaningful share of income on bus fares, motorcycle taxis (bodaboda) fuel, or moving goods to market are the ones most exposed to whatever is driving this line, whatever combination of global and domestic factors turns out to be responsible.
3. Core inflation is the Bank of Tanzania's real dashboard
At 3.9 percent, core inflation — the measure BOT watches most closely because it strips out the volatile food and energy swings — remains comfortably inside target. That suggests the underlying, broad-based inflation picture in the economy is still stable even as individual line items like fuel move more sharply.
4. This is exactly the kind of test BOT's new Strategic Plan was built for
TICGL's companion analysis of the Bank of Tanzania's Strategic Plan 2026/27-2030/31 notes that BOT's core mandate is to keep inflation inside its 3-5% band while FYDP IV and Dira 2050 build on that stability. July's reading — headline and core both still inside target, with one pressure point (fuel) worth monitoring — is precisely the kind of month that mandate is designed to manage calmly rather than react to.
TICGL's bottom line
One month after the FY2026/27 Budget's tax measures took effect, Tanzania's inflation picture is stable, not alarming: headline inflation at 4.2 percent and core inflation at 3.9 percent both sit inside the Bank of Tanzania's target band, and food prices — the line that matters most for household welfare — actually eased. The one area genuinely worth household and policymaker attention is fuel and transport, where price increases coincided with the new fiscal year but cannot yet be attributed to it with confidence. TICGL's view is that the next two to three NCPI releases, not this one alone, will tell the real story of how the FY2026/27 Budget is landing on ordinary Tanzanians.
10 — TICGL RecommendationsWhat To Watch and What To Do
- Track the Energy, Fuel and Utilities Index monthly, not just the headline rate. It is currently the fastest-moving major index (6.9% y/y) and the most direct channel through which fiscal measures would show up.
- Separate global and domestic drivers of fuel prices by cross-referencing global crude oil price movements and the TZS/USD exchange rate against each month's diesel and petrol price changes, rather than reading NCPI fuel data in isolation.
- Watch for lagged transport pass-through into food prices over the next two to three releases — higher transport costs typically reach the market a month or two after fuel prices move, even when farm-gate food prices are falling.
- Households and small businesses should budget for continued fuel volatility in the near term rather than assume July's food price relief extends automatically to transport and energy costs.
- Policymakers should consider publishing a simple monthly bridge showing how much of any fuel price change is attributable to global price movements, exchange rate movements, and domestic tax/duty changes respectively — this would let households, TICGL and other analysts assess budget impact with far more confidence than the current release format allows.
11 — Quick AnswersFrequently Asked Questions
What is Tanzania's headline inflation rate for July 2026?
Annual Headline Inflation rose to 4.2 percent in July 2026, up from 4.0 percent in June 2026, though the overall index fell slightly month-on-month, from 125.04 to 124.85.
What is Tanzania's food inflation rate in July 2026?
Food and Non-Alcoholic Beverages inflation held at 4.1 percent year-on-year, unchanged from June, while food prices fell 0.8 percent month-on-month on cheaper staples such as rice, maize, sweet potatoes and beans.
Did the FY2026/27 Budget's tax measures push up inflation?
July 2026 is the first NCPI release built entirely on post-budget prices. Food inflation eased, but transport inflation reached 13.8 percent year-on-year and diesel, petrol, charcoal and gas all rose within the month. One month of data cannot prove causation, but fuel and energy is the clearest line to watch over the coming releases.
What is core inflation in Tanzania as of July 2026?
Core inflation, which excludes volatile food, energy and utility prices, rose to 3.9 percent in July 2026 from 3.7 percent in June, remaining within the Bank of Tanzania's 3-5 percent target band.
Which items got cheaper and which got more expensive in July 2026?
Staple foods including rice, maize grain, maize flour, sweet potatoes, cassava and beans got cheaper month-on-month. Charcoal, diesel, petrol, gas and clothing materials got more expensive, with fuel and energy items showing the sharpest increases.
12 — MethodologySources & Notes
- National Bureau of Statistics (Tanzania) — National Consumer Price Index (NCPI) Press Release for July 2026, Ref: AC 334/376/01/381, dated 10 August 2026 (nbs.go.tz).
- TICGL/TERI prior research: TICGL's FY2026/27 Tanzania National Budget analysis series (overall tax measures, presumptive tax, betting excise duty, wage bill increase) and TICGL's Bank of Tanzania Strategic Plan 2026/27-2030/31 analysis.
- Global oil price and exchange-rate context referenced qualitatively; TICGL did not have access to a matched monthly global oil price or exchange-rate dataset at the time of writing and recommends this comparison be made explicitly in a future update.
- This page is an independent analytical summary prepared by TICGL/TERI based on NBS's published NCPI release and does not constitute financial, investment, tax, or legal advice. Figures reflect NBS's own reporting as published.
MuhtasariMuhtasari kwa Kiswahili
Je, Bajeti Mpya ya 2026/27 Imeanza Kuathiri Bei za Chakula na Mafuta? Ofisi ya Taifa ya Takwimu (NBS) imetoa taarifa ya Kielezo cha Bei za Bidhaa Kitaifa (NCPI) kwa mwezi Julai 2026, ikionyesha mfumuko wa bei kwa ujumla (Headline Inflation) umefikia asilimia 4.2, ukiwa umepanda kutoka asilimia 4.0 mwezi Juni 2026. Julai 2026 ni mwezi wa kwanza kamili ambao bei zilikusanywa baada ya hatua za kodi za Bajeti ya 2026/27 kuanza kutumika rasmi tarehe 1 Julai 2026.
Uchambuzi wa TICGL unaonyesha kuwa bei za chakula hazikupanda kwa kasi — mfumuko wa bei za chakula ulibaki asilimia 4.1 kwa mwaka, na kwa kulinganisha na mwezi uliopita (Juni), bei za chakula zilishuka kwa asilimia 0.8, zikichangiwa na kushuka kwa bei za mchele, mahindi, unga wa mahindi, viazi vitamu, muhogo na maharage — dalili za msimu wa mavuno, si dalili za kodi mpya. Hata hivyo, eneo linaloonyesha ongezeko kubwa ni usafiri na nishati: mfumuko wa bei za usafiri ulifikia asilimia 13.8 kwa mwaka, kiwango cha juu zaidi kati ya makundi yote, huku dizeli (juu kwa asilimia 3.3), petroli (juu kwa asilimia 2.5), mkaa (juu kwa asilimia 4.5) na gesi (juu kwa asilimia 1.3) zote zikipanda bei ndani ya mwezi huo huo.
TICGL inasisitiza kuwa data ya mwezi mmoja haitoshi kuthibitisha kwamba hatua za kodi za bajeti ndizo zilizosababisha ongezeko la bei za mafuta — mabadiliko ya bei za mafuta duniani na thamani ya shilingi dhidi ya dola pia huathiri bei hizi. TICGL itaendelea kufuatilia taarifa za NCPI za miezi ijayo (Agosti, Septemba na Oktoba 2026) ili kuona kama mwenendo huu wa bei za mafuta na usafiri utaendelea, utaongezeka, au utapungua.
- Mfumuko wa bei kwa ujumla: asilimia 4.2 (Julai 2026), ukiwa ndani ya wigo wa lengo la BOT wa asilimia 3-5
- Mfumuko wa bei za chakula: asilimia 4.1 kwa mwaka, lakini bei zilishuka asilimia 0.8 ndani ya mwezi
- Mfumuko wa bei za usafiri: asilimia 13.8 kwa mwaka — kiwango cha juu zaidi cha makundi yote
- Mfumuko wa bei msingi (Core Inflation): asilimia 3.9, bado ndani ya lengo la BOT
Vyanzo: Taarifa ya NCPI ya NBS kwa Julai 2026 (Kumb: AC 334/376/01/381, tarehe 10 Agosti 2026), na utafiti wa awali wa TICGL/TERI kuhusu Bajeti ya 2026/27. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI).
01 — OverviewExecutive Summary
In its Strategic Plan 2026/27–2030/31, the Bank of Tanzania makes a striking admission in passing: introducing its own monetary-policy theme, BOT writes that "the growing complexity of monetary transmission driven by digital financial innovation, elevated currency in circulation, rising dollarization tendencies and the persistent threat of imported inflation" continue to challenge the Bank. Its SWOC self-assessment repeats the point directly under Challenges: "structural issues such as dollarization, market segmentation, and high borrowing costs persist."
TICGL's view is that this single issue deserves far more scrutiny than its brief mention in the Plan suggests. Dollarization sits at the intersection of almost everything else BOT is trying to achieve over the next five years — a 3-5 percent inflation band defended through an interest-rate framework that only works on shilling-denominated transactions, a credit-to-GDP target of ≥30 percent that depends on affordable local-currency lending reaching priority sectors, and a market-deepening agenda built around narrowing the very spreads that dollarization helps widen.
- It is officially recognised, but not yet measured. BOT names dollarization as a persistent challenge but publishes no dedicated KPI, baseline, or target tracking it anywhere in the Plan.
- It has a direct, quantified proxy already inside the Plan. The Interbank Foreign Exchange Market (IFEM) spread — TZS 57, targeted down to ≤TZS 20 — is the clearest numeric signal of how disconnected shilling and dollar liquidity currently are.
- It weakens the exact tool BOT adopted in January 2024. The interest rate-based monetary policy framework transmits through shilling interest rates; the more the economy prices, saves, and borrows in dollars, the less that framework can do.
- It threatens FYDP IV's financing arithmetic directly. FYDP IV counts on private-sector-led industrialization financed substantially in local currency; a dollarized, segmented credit market pushes exactly the wrong incentives onto exactly the firms FYDP IV needs most.
- It is a monetary-sovereignty issue for Dira 2050, not just a technical one. A "strong, inclusive, and competitive economy" by 2050 implies a currency Tanzanians trust and default to — every share of activity that shifts into dollars is a share where BOT's own tools lose reach.
02 — The BasicsWhat Is Dollarization, and Why Does It Happen?
Dollarization (or, more precisely, currency substitution) is the growing use of a foreign currency — almost always the US dollar — alongside or instead of the domestic currency inside a country's own economy. It shows up in three overlapping forms, and Tanzania shows signs of at least two.
1. Payment dollarization
Prices, invoices, or day-to-day transactions — especially for imported goods, real estate, hotel bookings, and some professional services — get quoted or settled in dollars even for domestic buyers, bypassing the shilling entirely for that transaction.
2. Financial (asset/liability) dollarization
Bank deposits, loans, and savings are held in foreign currency rather than shillings. This is the form most directly relevant to BOT's monetary-policy transmission, since it determines how much of the credit and deposit base actually responds to the Central Bank Rate.
3. Real dollarization
Wages, contracts, and long-term commitments get indexed or denominated in dollars as a hedge against inflation or shilling depreciation — a sign that trust in the domestic currency as a stable store of value is eroding at the margin.
Dollarization typically accelerates when a currency has a history of high inflation or sharp depreciation, when trade and remittance flows are dollar-heavy, when residents have easy access to foreign-currency bank accounts, or — as BOT's own Situation Analysis notes for Tanzania — when global geopolitical shocks (the Russia-Ukraine war's effect on food and fuel prices, renewed Middle East conflict pushing oil above US$100/barrel in early 2026) repeatedly demonstrate the shilling's exposure to imported inflation.
03 — The EvidenceWhat BOT's Own Plan Actually Says
Dollarization is mentioned directly in two places in the Strategic Plan, and indirectly via one quantified KPI. TICGL has pulled all three together below because, read separately, their significance is easy to miss.
What's conspicuously absent
Nowhere in the published Plan does BOT report a dollarization ratio — the share of bank deposits or loans denominated in foreign currency — as a tracked indicator. Compare this to the eleven KPIs under financial-sector safety alone (capital adequacy, liquidity, NPL ratio, and so on): dollarization is named as a risk but, unlike almost everything else in the Plan, it is not yet a number BOT has committed to move.
04 — Transmission MechanismWhy Dollarization Blunts BOT's Interest Rate Tool
In January 2024, BOT shifted to an interest rate-based monetary policy framework — using the Central Bank Rate (CBR) to guide the 7-day interbank cash market rate, and from there, bank lending and deposit rates economy-wide. BOT's own Theme 1.1 target narrows the acceptable spread on the 7-day IBCM rate from ±200 bps to ±150 bps of the CBR by 2029/30, a sign of how central this transmission channel now is to Tanzania's entire monetary-policy model.
That model has one structural vulnerability: it only steers shilling-denominated activity. Every loan, deposit, or price that shifts into dollars is a transaction the CBR cannot reach directly. Three consequences follow:
- Weaker pass-through. A CBR change designed to cool or stimulate the economy has a smaller effect the larger the dollarized share of credit and deposits becomes — the Bank is, in effect, steering a shrinking portion of the wheel.
- Currency-mismatch risk shifts onto borrowers. Firms and households that borrow in dollars but earn in shillings absorb exchange-rate risk directly — a shilling depreciation instantly raises their real debt burden, regardless of what BOT does with the CBR.
- Imported-inflation exposure compounds. BOT's own Situation Analysis flags renewed 2026 Middle East conflict pushing oil above US$100/barrel as a live inflation risk; a more dollarized economy transmits global dollar-price shocks into domestic prices faster and more directly than a predominantly shilling economy would.
Inflation vs the 7-Day IBCM Rate Spread: The Transmission Channel BOT Is Tightening
Percent / basis points — the corridor BOT wants monetary-policy signals to move through, which dollarization bypasses by design
05 — The Quantified SymptomMarket Segmentation: IBCM vs IFEM
If dollarization is the underlying condition, market segmentation between the interbank cash market (IBCM, where banks trade shilling liquidity) and the interbank foreign exchange market (IFEM, where banks trade dollar liquidity) is its clearest quantified symptom in BOT's own Plan.
🏦 IBCM — Shilling Liquidity
- 7-day rate spread: baseline ±200 bps, target ±150 bps of CBR
- Spread in the 7-day IBCM interest rate: baseline 1.6%, target ≤2%
- The channel BOT's interest-rate framework depends on
VS
💵 IFEM — Dollar Liquidity
- Spread: baseline TZS 57, target ≤TZS 20 by 2029/30
- A wide spread here signals banks are not moving dollar liquidity efficiently between each other
- Directly shaped by how much of the economy has shifted into dollars
A persistently wide IFEM spread means some banks sit on surplus dollar liquidity while others face shortages, with the cost of bridging that gap passed on to borrowers as a risk premium — on top of, not instead of, ordinary credit risk pricing. That premium falls hardest on smaller, shilling-only borrowers who cannot access dollar financing directly, precisely the businesses FYDP IV is counting on to industrialize.
Market-Deepening Targets: Closing the Segmentation Gap
The three Theme 1.3 KPIs BOT is using as its own proxy for reduced market segmentation between shilling and dollar liquidity
06 — The Growth LinkDollarization, Credit Costs, and the ≥30% GDP Target
BOT's headline growth-adjacent target — credit to the private sector reaching at least 30 percent of GDP by 2029/30, up from 22.8 percent in 2025/26 and just 13.2 percent five years earlier — is the number dollarization threatens most directly.
The mechanism is straightforward: a dollarized, segmented credit market channels the cheapest, most available financing toward larger borrowers who can access and service dollar loans, while shilling-only MSMEs face the full weight of thinner local-currency markets — higher spreads, tighter collateral requirements, and less competitive pricing. Aggregate credit-to-GDP can rise even while the distribution of that credit skews away from exactly the broad-based private-sector growth FYDP IV needs.
Credit to Private Sector as % of GDP, 2021/22 → 2029/30 Target
The trajectory BOT is targeting — and the segmentation gap standing between 22.8% today and the 30% goal
07 — The Bigger StakesWhat This Means for FYDP IV and Dira 2050
FYDP IV: Private-sector-led industrialization needs local-currency credit
FYDP IV's core ambition — re-rising competitiveness and industrialization for human development — is financed substantially through private-sector credit growth. A credit-to-GDP target of ≥30% is only meaningful for that ambition if the credit reaching manufacturers, agro-processors, and MSMEs is affordable and denominated in the currency they earn in. Dollarization risks concentrating credit access among larger, import-linked, or export-earning firms that can naturally hedge dollar exposure, leaving the broader industrial base FYDP IV needs most facing the segmented, more expensive shilling market.
Dira 2050: Monetary sovereignty is part of "strong and competitive"
Dira 2050's vision — "strong, inclusive, and competitive economy" — implicitly assumes a national currency Tanzanians and Tanzanian institutions trust and default to for savings, pricing, and contracts. Every percentage point of economic activity that migrates into dollars is a percentage point where BOT's own policy instruments — the CBR, reserve requirements, open-market operations — lose direct reach. A 2050 vision of economic strength is difficult to reconcile with a domestic currency playing an ever-smaller role in the domestic economy.
The sequencing risk: capital-account liberalization
BOT's Theme 1.3 already lists "adopt a full capital account liberalization" as a strategic initiative — a policy that can deepen markets and attract capital, but that interacts directly with dollarization. Liberalizing capital flows before narrowing the IFEM spread and containing currency substitution risks accelerating dollarization rather than curing it, since it becomes easier, not harder, to move into and hold foreign-currency assets. TICGL's reading is that sequencing here matters as much as the policy itself: market-deepening and de-dollarization measures arguably need to show measurable progress before full liberalization is pushed through, not after.
08 — Comparative EvidenceHow Other Economies Have Handled Dollarization
Tanzania is far from the first economy to confront rising currency substitution. Both cautionary and constructive precedents exist among developing and emerging peers.
🇪🇨 Ecuador & Zimbabwe: Full Dollarization as Last Resort
Both countries eventually abandoned their domestic currencies entirely after hyperinflation destroyed public trust in them — Zimbabwe following inflation that peaked above a billion percent in 2008. Full dollarization stabilised prices but permanently surrendered independent monetary policy, an outcome only relevant to Tanzania as the extreme endpoint to avoid, not a model to follow.
🇵🇪 Peru: A De-Dollarization Success Story
Peru cut financial dollarization from roughly 80 percent of credit in the early 2000s to under 20 percent within about two decades, through sustained inflation-targeting credibility, incentives favouring local-currency lending, and macroprudential limits on unhedged dollar borrowing — evidence that credibility-building and targeted incentives, not capital controls alone, can shift the balance back toward the domestic currency.
🇺🇬 🇰🇪 Uganda & Kenya: East African Peers, Similar Pressure
Both neighbouring central banks report comparable dollarization pressure in deposits and trade-related lending, driven by similar dynamics — import dependence, dollar-denominated regional trade, and periodic shilling/shilling-equivalent depreciation episodes — suggesting the issue is regional in character, not unique to Tanzania's policy choices alone.
🇹🇿 Tanzania: Early-Stage, Named but Unmeasured
BOT's own language — "rising dollarization tendencies" — suggests a trend still in its earlier stages relative to historical extreme cases, which is precisely the window in which credibility-based, incentive-driven de-dollarization (the Peru model) tends to be most effective and least costly to implement.
The pattern worth learning from
The common thread across successful de-dollarization cases is that they were gradual, credibility-based, and incentive-driven — built on sustained low inflation, deeper local-currency capital markets, and macroprudential nudges toward local-currency borrowing — rather than sudden restrictions on foreign-currency access. BOT's existing initiatives (Financial Market Master Agreements, diversified government debt instruments, deepened domestic markets) already point in this direction; the missing piece is simply measuring dollarization directly so progress can be tracked.
09 — What's in the PlanBOT's Response — and the Gap TICGL Sees
TICGL's assessment
To its credit, BOT's Plan does not ignore the underlying problem — the IFEM-spread target and debt-instrument diversification are genuine, quantified responses to market segmentation. What is missing is a direct measure of dollarization itself. Right now, progress can only be inferred indirectly through the IFEM spread; a dedicated KPI would let BOT, government, and the public track de-dollarization on its own terms rather than as a byproduct of a market-depth target.
10 — TICGL RecommendationsA Disciplined Path Toward De-Dollarization
- Publish a standing "dollarization ratio" KPI — foreign-currency deposits and loans as a share of total — as a companion indicator to the IFEM-spread target, with its own baseline and 2029/30 direction of travel.
- Sequence capital-account liberalization behind measurable progress on the IFEM spread, so market opening does not outrun the de-dollarization tools meant to accompany it.
- Study Peru's incentive-based de-dollarization model specifically — macroprudential limits on unhedged dollar borrowing, and incentives favouring local-currency lending, layered on top of continued inflation-targeting credibility.
- Disaggregate the private-sector-credit target by currency of denomination, not just by sector, so BOT and stakeholders can see whether the path to 30% credit-to-GDP is being financed in shillings or dollars.
- Use the new debt-instrument diversification agenda deliberately as a de-dollarization tool — local-currency government securities that are liquid, accessible, and competitively priced give savers and institutions a shilling-denominated alternative to holding dollars.
11 — Quick AnswersFrequently Asked Questions
What is dollarization and is it happening in Tanzania?
Dollarization is the growing use of a foreign currency — typically the US dollar — for savings, borrowing, pricing, or invoicing, alongside or instead of the domestic currency. BOT's own Strategic Plan names "rising dollarization tendencies" as a persistent structural challenge, confirming the trend is real and officially recognised, even without a published dollarization ratio.
Why does dollarization weaken Tanzania's monetary policy?
Tanzania's interest rate-based framework (adopted January 2024) works by moving shilling interest rates. The more borrowing, saving and pricing shift into dollars, the less grip a change in the Central Bank Rate has on those decisions.
How is dollarization connected to market segmentation?
BOT's own Theme 1.3 KPI shows a TZS 57 spread in the Interbank Foreign Exchange Market, targeted down to TZS 20 or less. A wide, persistent spread signals inefficient movement of dollar liquidity between banks — raising credit costs and reinforcing incentives to hold and lend in dollars.
What does dollarization mean for FYDP IV and Dira 2050?
FYDP IV's private-sector-led industrialization depends on affordable local-currency credit reaching priority sectors. Dollarization risks concentrating credit toward larger, dollar-capable borrowers, leaving broader industrial ambitions under-financed — while Dira 2050's vision of a strong, competitive economy assumes a currency Tanzanians trust and use by default.
What is BOT doing about dollarization?
BOT targets a narrower IFEM spread (≤TZS 20), Financial Market Master Agreements, diversified government debt instruments (≥10% non-traditional issuance), and capital-account liberalization — but has not published a standalone KPI tracking dollarization itself.
12 — MethodologySources & Notes
- Bank of Tanzania — Strategic Plan 2026/27-2030/31 (June 2026): Situation Analysis, SWOC Analysis, and Theme 1 (Macroeconomic Stability) objectives, KPIs, baselines and targets (bot.go.tz).
- TICGL/TERI companion analysis: "Does BOT's 2026/27-2030/31 Strategic Plan Support FYDP IV and Dira 2050?" and "What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050."
- Comparative dollarization experience: publicly documented accounts of Ecuador's and Zimbabwe's full dollarization episodes, and Peru's financial de-dollarization programme since the early 2000s, cited for illustrative comparative purposes.
- All interpretation connecting BOT's KPIs to dollarization, market segmentation, FYDP IV and Dira 2050 is TICGL/TERI's own analysis, not BOT's stated framing.
- This page is an independent analytical summary prepared by TICGL/TERI and does not constitute financial, investment, tax, or legal advice.
MuhtasariMuhtasari kwa Kiswahili
Dollarization Tanzania: Maana Yake kwa Uchumi, FYDP IV na Dira 2050. Ndani ya Mpango Mkakati wa Benki Kuu ya Tanzania (BOT) wa 2026/27-2030/31, BOT yenyewe inakiri kuwepo kwa "mwelekeo unaokua wa dollarization" (matumizi makubwa ya dola badala ya shilingi) kama changamoto kubwa ya kimuundo inayoendelea kuikabili nchi. Suala hili linatajwa mara mbili kwenye mpango — kwenye uchambuzi wa hali ya sasa (Situation Analysis) na kwenye uchambuzi wa SWOC chini ya sehemu ya Changamoto (Challenges).
TICGL inaona hii ni miongoni mwa masuala muhimu zaidi yasiyoshughulikiwa vya kutosha kwenye mpango huu. Dollarization inaathiri moja kwa moja uwezo wa BOT kudhibiti uchumi kupitia kiwango cha riba (mfumo uliopitishwa Januari 2024), kwani mfumo huo unafanya kazi kwenye mikopo na akiba za shilingi tu. Kadri shughuli za kiuchumi zinavyohamia kwenye dola, ndivyo uwezo wa BOT wa kudhibiti mfumuko wa bei na ukuaji wa uchumi kupitia riba unavyopungua.
Kiashiria pekee cha kiasi (quantified proxy) kilichopo kwenye mpango kinachohusiana moja kwa moja na tatizo hili ni pengo la soko la fedha za kigeni baina ya benki (IFEM spread), ambalo kwa sasa ni TZS 57 na linalengwa kupungua hadi TZS 20 au chini ifikapo 2029/30. Hata hivyo, BOT haijaweka kiashiria maalum (KPI) kinachopima moja kwa moja kiwango cha dollarization — yaani asilimia ya amana na mikopo iliyo kwenye fedha za kigeni.
TICGL inapendekeza: (1) BOT iweke KPI mahususi ya "kiwango cha dollarization"; (2) uwekaji huru wa mtaji (capital account liberalization) usitangulie kabla ya maendeleo ya wazi kwenye kupunguza dollarization; (3) Tanzania ijifunze kutoka mfano wa Peru wa kupunguza dollarization kwa kutumia motisha badala ya vikwazo vikali; na (4) lengo la mikopo kwa sekta binafsi (30% ya GDP) ligawanywe kulingana na sarafu inayotumika, ili kujua kama ukuaji huo unafadhiliwa kwa shilingi au dola. Bila hatua madhubuti, malengo makubwa ya FYDP IV na Dira 2050 ya kuwa na uchumi imara, jumuishi na wenye ushindani ifikapo 2050 yanaweza kukwamishwa na tatizo hili la kimuundo.
- Pengo la soko la IFEM: TZS 57 kwa sasa, lengo ni TZS 20 au chini ifikapo 2029/30
- KPI maalum ya dollarization kwenye Mpango wa BOT: haipo
- Lengo la mikopo kwa sekta binafsi linalotegemea suluhu ya tatizo hili: angalau 30% ya GDP
- Mfumo wa sera ya fedha unaotegemea shilingi pekee: tangu Januari 2024
Vyanzo: Mpango Mkakati wa Benki Kuu ya Tanzania 2026/27-2030/31 (Juni 2026), uchambuzi wa TICGL/TERI kuhusu FYDP IV na Dira 2050. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI).
01 — OverviewExecutive Summary
Tanzania needs its economy to grow faster than it is growing now — FYDP IV's own ambition is 10.5 percent real GDP growth by 2030/31, well above the 6.2 percent Tanzania achieved in 2025/26. The question this report asks is uncomfortable but necessary: is the Bank of Tanzania's new five-year Strategic Plan built to help deliver that faster growth, or mainly to guard against the things that could go wrong along the way?
The evidence points to a plan weighted heavily toward protection. Tanzanian banks currently hold liquidity and capital well above what regulators require — headroom that, in principle, could support significantly more lending to the real economy. Yet across the roughly 31 measurable targets in BOT's Plan, only one — credit to the private sector as a share of GDP — directly targets the expansion of credit into the economy. The remainder measure inflation control, reserve adequacy, capital buffers, payment-system reliability, and institutional capacity: all legitimate, all necessary, but all defensive in character rather than generative.
- Idle balance-sheet capacity is real and measurable. A liquidity ratio of 26.88 percent against a 20 percent floor, and a capital adequacy ratio of 21.32 percent against a 14.5 percent floor, both in 2025/26, suggest Tanzanian banks could safely extend meaningfully more credit than they currently do.
- BOT's own target mix is protection-heavy. TICGL's classification of the Plan's KPIs finds roughly nine targets built purely around stability buffers, ten around institutional capacity, seven around service quality and inclusion, and only one squarely aimed at credit generation.
- Stability has genuinely enabled credit growth before. Tanzania's own recent history — inflation averaging 3.7 percent while credit to the private sector rose from 13.2 percent to 22.8 percent of GDP between 2021/22 and 2025/26 — shows protection and generation are not mutually exclusive; stability was a precondition, not a substitute, for credit growth.
- But other developing economies show a more actively developmental model is possible. China, India and Rwanda all pair conventional stability tools with structural instruments — priority-sector lending quotas, credit guarantee schemes, targeted refinancing — that Tanzania's Plan does not yet feature in any quantified way.
- The risk of over-correcting is real and documented. Zimbabwe's hyperinflation and more recent inflation and currency stress in Argentina and Turkey show what happens when growth-oriented pressure overrides monetary discipline — the answer is not to abandon protection, but to add structure, not disorder, to generation.
📌
Read this alongside TICGL's full review of BOT's Strategic Plan 2026/27-2030/31
This report builds directly on TICGL/TERI's line-by-line review of the Bank of Tanzania's Strategic Plan — its alignment with FYDP IV and Dira 2050, its five-year performance record, and the internal inconsistencies TICGL found in the Plan's own published targets.
Read: Does BOT's 2026/27-2030/31 Strategic Plan Support FYDP IV and Dira 2050? →02 — Framing the QuestionTwo Models of Central Banking
Central banks worldwide sit somewhere on a spectrum between two broad philosophies, and BOT's Plan is a useful lens for locating Tanzania on that spectrum.
🛡️ The Protective Model (Conventional Inflation-Targeting)
- Growth is treated as an outcome of stability, not a direct policy target
- Primary tools: interest rates, reserve requirements, capital and liquidity buffers
- Success is measured by inflation staying in-band and the financial system remaining sound
- Assumes markets will allocate credit efficiently once stability conditions are met
- Model followed by most Western central banks and, per this Plan, largely by BOT
VS
🌱 The Developmental Model (Structural / Directed Credit)
- Growth is treated as a co-equal objective alongside stability
- Additional tools: priority-sector lending quotas, credit guarantee schemes, targeted refinancing windows, differentiated reserve requirements
- Success is measured partly by whether credit actually reaches strategic sectors (agriculture, MSME, industry)
- Assumes markets under-allocate credit to high-growth, high-risk-perception sectors without active direction
- Model associated with China, India, South Korea (historically) and, increasingly, Rwanda
Where BOT's Plan sits
BOT's stated mission — to maintain price stability and financial-system integrity "for" inclusive growth — places it firmly in the protective camp, with growth positioned as a downstream consequence rather than a direct target. That is not unusual or wrong by international standards. The question TICGL raises is whether, given Tanzania's specific starting point — comfortable capital and liquidity buffers, an ambitious FYDP IV growth target, and a financing gap FYDP IV is counting on the private sector to close — a purely protective posture is still the right calibration, or whether a modest shift toward structural, disciplined generative tools would serve Tanzania better.
03 — The EvidenceTanzania's Banks Are Holding More Capacity Than Required
The clearest quantitative evidence for the "protect over generate" critique sits inside BOT's own Corporate Performance Review. Two of the financial sector's core soundness indicators are running well above their regulatory floors — capacity that, in principle, represents room for additional lending without breaching safety thresholds.
⚠ Headroom figures are illustrative, calculated directly from BOT's own published baseline and target/floor figures; they indicate directional capacity, not a precise lending multiplier, since capital and liquidity requirements interact with asset-quality and risk-weighting rules not fully disclosed in the Plan.
Idle Balance-Sheet Capacity: Actual vs Regulatory Floor
Percent — the gap between what banks hold and what regulation requires is capacity that is not being converted into credit
A caveat TICGL wants to be clear about
Excess liquidity and capital are not automatically "wasted" capacity — some buffer above the regulatory minimum is normal and prudent, especially given Tanzania's exposure to external shocks (commodity prices, geopolitical disruption to trade routes) documented elsewhere in BOT's own Situation Analysis. The point is not that banks should run at the regulatory floor, but that a gap this wide, sustained across a full plan period, is worth actively investigating rather than treated as a given.
04 — Counting the TargetsHow Many of BOT's Own Targets Actually Aim at Growth?
To move this argument beyond impression, TICGL classified all measurable KPIs in BOT's Strategic Plan (excluding the GDP growth rate itself, which is an outcome indicator rather than a policy lever) into five categories, based on what each target is actually designed to achieve.
Classification of BOT's ~31 Measurable KPIs by Function
TICGL's own categorisation, based on the stated intent of each KPI in the Strategic Plan
The honest reading of this mix
This is not necessarily a design flaw — a central bank's core job genuinely is disproportionately about safeguarding rather than allocating capital, and most of Tanzania's peers show a similar KPI mix. But it does mean that if Tanzania wants BOT to play a larger role in actively generating growth, that would require a deliberate expansion of the market-deepening and direct-generation categories, not something that happens automatically from the stability targets already in place.
05 — The Other Side of the ArgumentStability Has Genuinely Enabled Credit Growth Before
Before concluding that BOT should pivot hard toward a developmental model, it is worth acknowledging what Tanzania's own recent record shows: the protective approach has not been a drag on credit growth — if anything, it appears to have been a precondition for it.
Inflation Stability and Private-Sector Credit Growth, 2021/22-2029/30
Left axis: headline inflation (%, stayed within the 3-5% band); right axis: credit to private sector as % of GDP (rose steadily as inflation stabilised)
The case for the protective model
Between 2021/22 and 2025/26, inflation averaged 3.7 percent, well inside target, while credit to the private sector nearly doubled as a share of GDP. Non-performing loans fell from 9.68 percent to 2.96 percent over the same period. A bank confident that inflation and asset quality are under control is more willing to lend — stability arguably did more for credit growth than any single directed-lending scheme could have, by making lending itself less risky.
The limit of that argument
Correlation is not the whole story. Credit growth from 13.2 percent to 22.8 percent of GDP, while real, still leaves Tanzania well below the 30-45 percent typical of fast-growing lower-middle-income peers, and well below what FYDP IV's private-financing ambitions ultimately require. Stability created the conditions for credit growth; it did not, on its own, close the gap to where Tanzania needs to be — which is exactly where structural, targeted tools could plausibly add something stability alone has not yet delivered.
06 — Comparative EvidenceHow Other Central Banks Balance Protection and Generation
Tanzania is not choosing between two untested extremes. Both cautionary and constructive examples exist among developing and emerging economies.
🇿🇼 Zimbabwe: The Cautionary Extreme
Zimbabwe's central bank financed government deficits and directed lending without monetary discipline through the 2000s, producing hyperinflation that peaked above a billion percent in 2008. It stands as the clearest warning that growth-oriented monetary tools without fiscal and institutional discipline can destroy the very economy they aim to grow.
🇦🇷 🇹🇷 Argentina & Turkey: Political Pressure on Rate Policy
Both countries saw central banks pressured to cut interest rates to stimulate growth even as inflation ran high, contributing to currency instability and elevated inflation that ultimately hurt the lower-income households growth-oriented policy was meant to help. The lesson: generation without disciplined sequencing undermines itself.
🇨🇳 China: Structural Directed Credit
The People's Bank of China pairs conventional tools with structural monetary-policy instruments — targeted relending facilities, differentiated reserve requirements for banks that lend to small firms, and directed credit toward strategic sectors such as green industry and technology — layered on top of, not instead of, price and financial stability management.
🇮🇳 India: Mandated Priority-Sector Lending
The Reserve Bank of India requires banks to direct a fixed share of total lending to designated priority sectors — agriculture, MSMEs, affordable housing, export credit — regardless of where banks would otherwise choose to lend, converting balance-sheet capacity into targeted credit by regulation rather than by hoping the market allocates it there.
🇷🇼 Rwanda: Credit Guarantees at Tanzania's Own Income Level
The National Bank of Rwanda has backed dedicated credit-guarantee facilities for SMEs and agriculture, directly addressing the collateral and risk-perception barriers that keep banks from lending to exactly the sectors Tanzania's own FYDP IV prioritises — a lower-middle-income example closer to Tanzania's starting point than China or India.
🇹🇿 Tanzania: Structural Tools Are Named, Not Yet Quantified
BOT's own Plan references an "Independent Credit Guarantee Co-operation of Tanzania" it intends to help operationalise, and a new "Strategic Investment Subsidiary" for balance-sheet diversification — both structurally similar to the Rwanda and China models above. Neither, however, carries a quantified target, baseline, or KPI in the published Plan, leaving their scale and ambition undefined.
The pattern across all six cases
Every example where directed credit worked — China, India, Rwanda — paired it with continued, disciplined attention to inflation and financial stability; it was never a substitute for the protective mandate, only an addition to it. Every example where growth-oriented pressure overrode monetary discipline — Zimbabwe, Argentina, Turkey — ended in currency and price instability that hurt growth more than it helped. For Tanzania, the evidence points toward addition, not replacement: keep the protective architecture BOT already runs well, and add quantified, disciplined structural tools on top of it.
07 — TICGL AnalysisSo, Should BOT Do More to Generate Growth?
TICGL's answer is yes, with a specific and disciplined scope — not a wholesale rewrite of BOT's mandate.
1. The credit-to-GDP target should not stand alone
BOT's target of credit to the private sector reaching 30 percent of GDP by 2029/30 is a genuinely strong ambition, but it is a single aggregate number that says nothing about which sectors receive that credit. Without sub-targets — agriculture, MSME, health and education-adjacent enterprise — the headroom identified in Section 3 could just as easily flow toward low-risk, already-well-served corporate borrowers as toward the sectors FYDP IV and Dira 2050 most need financed.
2. Quantify the two structural tools already named in the Plan
The Independent Credit Guarantee Co-operation of Tanzania and the Strategic Investment Subsidiary are the closest things in BOT's Plan to genuine developmental instruments. Both currently have implementation initiatives but no KPI, baseline, or target — the single highest-value addition BOT could make to this Plan without changing its core mandate.
3. Idle capacity deserves its own tracked metric
TICGL recommends BOT publish and track a simple "lending headroom" indicator — the gap between actual and required liquidity and capital ratios — as a standing KPI. Making idle capacity visible is the first step to deciding, transparently, whether it should be converted into credit, and for whom.
4. Tanzania's own history argues for addition, not replacement
The 2021/22-2025/26 record shows stability and credit growth moved together, not in tension — the strongest evidence in the Plan that a purely protective posture is not actively hostile to growth. The case for change is not that protection has failed, but that it has already done its job well enough that Tanzania can now afford to layer targeted, disciplined generative tools on top of it without repeating Zimbabwe's or Argentina's mistakes.
TICGL's bottom line
BOT should not choose between protecting and generating — the evidence from both Tanzania's own record and its developmental-central-bank peers shows the two are complementary when generation is structural and disciplined, not when it substitutes for monetary discipline. The specific, actionable shift TICGL recommends is narrow: quantify the credit-guarantee and strategic-investment vehicles already named in the Plan, disaggregate the private-sector-credit target by priority sector, and publish idle-capacity as a tracked metric — three additions that would move BOT from a purely protective posture toward a disciplined developmental one, without touching its core price-stability mandate at all.
08 — TICGL RecommendationsA Disciplined Path Toward a More Generative BOT
- Set a quantified target and timeline for the Independent Credit Guarantee Co-operation of Tanzania — currently named as an initiative with no KPI, this is the single clearest gap between BOT's stated intentions and its measurable commitments.
- Disaggregate the 30-percent credit-to-GDP target by priority sector (agriculture, MSME, health/education-adjacent enterprise, green industry), so the target's success can be judged on reach as well as scale.
- Publish a standing "lending headroom" indicator tracking the gap between actual and required liquidity and capital ratios, to make idle balance-sheet capacity visible and debatable rather than implicit.
- Give the Strategic Investment Subsidiary a defined mandate and KPI for balance-sheet diversification into strategic projects, rather than leaving its scale undefined in the published Plan.
- Study Rwanda's credit-guarantee model specifically, given its closer income-level comparability to Tanzania than China or India, as the most directly transferable example of disciplined, structural directed credit.
09 — Quick AnswersFrequently Asked Questions
Is the Bank of Tanzania's mandate to protect the economy or to grow it?
Formally, to protect: BOT's mission treats growth as an outcome of price and financial-system stability rather than a direct policy target. Only about one in thirty of its measurable KPIs directly targets credit expansion into the economy.
Do Tanzanian banks have spare capacity to lend more?
The numbers suggest yes — a liquidity ratio of 26.88 percent against a 20 percent regulatory floor, and capital adequacy of 21.32 percent against a 14.5 percent floor, both in 2025/26, indicate headroom that is not fully converted into credit.
What is developmental central banking?
An approach where central banks add structural tools — priority-sector lending quotas, credit guarantees, targeted refinancing — to their conventional stability mandate, actively directing credit toward strategic sectors, as practised to varying degrees by China, India and Rwanda.
What are the risks of a central bank pushing growth too aggressively?
Zimbabwe's hyperinflation and inflation/currency stress in Argentina and Turkey show that growth-oriented pressure without monetary discipline can destabilise the economy it aims to grow — the case for generative tools depends on them being structural and disciplined, not a substitute for stability management.
10 — MethodologySources & Notes
- Bank of Tanzania — Strategic Plan 2026/27-2030/31 (June 2026): Corporate Performance Review, Plan at a Glance KPI tables, and Theme 1-3 objectives and initiatives (bot.go.tz).
- TICGL/TERI companion analysis: "Does BOT's 2026/27-2030/31 Strategic Plan Support FYDP IV and Dira 2050?" and "What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050."
- Comparative central-bank practice: publicly documented approaches of the People's Bank of China (structural monetary policy tools), the Reserve Bank of India (priority-sector lending norms), and the National Bank of Rwanda (SME and agriculture credit-guarantee facilities).
- Historical reference cases: documented accounts of Zimbabwe's 2007-2009 hyperinflation episode and central-bank rate-policy pressure in Argentina and Turkey, cited for illustrative comparative purposes.
- KPI classification (Section 4) is TICGL/TERI's own analytical categorisation of BOT's published targets and is presented as interpretation, not as BOT's own framing.
- This page is an independent analytical summary prepared by TICGL/TERI and does not constitute financial, investment, tax, or legal advice.
MuhtasariMuhtasari kwa Kiswahili
Je, BOT Inalinda Uchumi wa Tanzania, au Inausaidia Kuzalisha Ukuaji? Benki za Tanzania zinashikilia mtaji na ukwasi zaidi ya kiwango kinachohitajika kisheria — uwiano wa ukwasi ni asilimia 26.88 dhidi ya kiwango cha chini cha asilimia 20, na uwiano wa mtaji ni asilimia 21.32 dhidi ya kiwango cha chini cha asilimia 14.5. Kati ya malengo zaidi ya 31 yaliyowekwa kwenye Mpango Mkakati wa BOT, moja tu — mikopo kwa sekta binafsi kama asilimia ya GDP — linalenga moja kwa moja kuongeza mikopo kwenye uchumi. Mengine yote yanahusu ulinzi wa uthabiti, uwezo wa taasisi, na huduma bora, si "kuzalisha" moja kwa moja.
Uchambuzi wa TICGL unaonyesha kwamba uthabiti wa fedha umekuwa msingi muhimu uliowezesha ukuaji wa mikopo hapo awali — mfumuko wa bei ulipobaki thabiti kati ya 2021/22 na 2025/26, mikopo kwa sekta binafsi yaliongezeka kutoka asilimia 13.2 hadi 22.8 ya GDP. Hii inaonyesha kulinda na kuzalisha si mambo yanayopingana — lakini historia ya nchi kama Zimbabwe (mfumuko wa bei uliozidi asilimia bilioni moja mwaka 2008) na shinikizo la kisiasa kwenye benki kuu za Argentina na Uturuki zinaonyesha hatari za kusukuma ukuaji bila nidhamu ya kifedha.
Nchi kama China, India na Rwanda zinaonyesha njia ya kati — zinatumia zana za "directed credit" (mikopo inayoelekezwa kimkakati kwa sekta maalum kama kilimo na MSME) sambamba na uthabiti wa fedha, si badala yake. BOT tayari imetaja vyombo viwili vinavyofanana na mifano hii — Independent Credit Guarantee Co-operation ya Tanzania na Strategic Investment Subsidiary — lakini bado havina malengo ya kiasi (targets) yaliyowekwa wazi. TICGL inapendekeza BOT iweke malengo dhahiri kwa vyombo hivi, igawe lengo la mikopo kwa sekta binafsi kulingana na sekta za kipaumbele, na ichapishe kiashiria cha "uwezo wa mikopo usiotumika" kama sehemu ya ufuatiliaji wa umma.
- Uwiano wa ukwasi wa benki: 26.88% (zaidi ya kiwango cha chini cha 20%)
- Uwiano wa mtaji wa benki: 21.32% (zaidi ya kiwango cha chini cha 14.5%)
- Malengo ya "kuzalisha" moja kwa moja kwenye Mpango wa BOT: 1 tu kati ya 31
- Mikopo kwa sekta binafsi: kutoka 13.2% (2021/22) hadi 22.8% (2025/26), lengo la 30% ifikapo 2029/30
Vyanzo: Mpango Mkakati wa Benki Kuu ya Tanzania 2026/27-2030/31, uchambuzi wa awali wa TICGL/TERI kuhusu FYDP IV na Dira 2050, na mifano ya kimataifa ya benki kuu za maendeleo. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI).
01 — OverviewExecutive Summary
Every national development plan needs a stable macroeconomic floor to stand on. FYDP IV's ten-sector transformation agenda and Dira 2050's US$1 trillion, US$7,000-per-capita ambition both assume low inflation, a credible exchange rate, adequate reserves, and a financial sector willing and able to lend. That floor is precisely what the Bank of Tanzania's (BOT) Strategic Plan 2026/27-2030/31, published June 2026 to mark the Bank's 60th anniversary, is designed to deliver. This report reads the Plan against two questions: does it genuinely align with FYDP IV and Dira 2050, and is it ambitious and credible enough to protect Tanzania's growth over the next five years.
On alignment, the answer is a clear yes on paper — BOT's own strategy map lines its three thematic areas up directly against Dira 2050's pillars and FYDP IV's competitiveness agenda. On ambition and credibility, the picture is more mixed. BOT's five-year track record from 2021/22 to 2025/26 was strong: most monetary and financial-stability targets were met or exceeded, sometimes by a wide margin. But several of the new 2029/30 targets are set below levels BOT has already achieved, several key figures are inconsistent between different tables in BOT's own document, and the headline GDP growth target sits below what FYDP IV itself is asking for.
- The previous plan mostly over-delivered. Inflation stayed inside the 3-5 percent band, GDP growth hit 6.2 percent against a 6 percent target, and credit to the private sector reached 22.8 percent of GDP, just above target — while capital adequacy, non-performing loans, and payment-system reliability all beat their targets comfortably.
- The new plan's boldest number is private-sector credit. BOT wants credit to the private sector to climb from 22.8 percent to at least 30 percent of GDP by 2029/30 — a genuinely stretching target that, if achieved, would materially expand the financing available to the private investment FYDP IV is counting on.
- Some targets are floors, not stretch goals. Capital adequacy (target ≥14.5% vs an actual 21.32%), the non-performing loan ratio (≤5% vs an actual 2.96%), and foreign reserve cover (≥4.0 months vs an actual 4.7) are all set below what BOT already achieved in 2025/26 — sensible as regulatory minimums, but not evidence of rising ambition on their own.
- The document contradicts itself on two important numbers. The detailed KPI table sets GDP growth at ≥7.2 percent and foreign investment income at ≥20bps above the Strategic Asset Allocation (SAA) target; BOT's own summary infographic later in the same document shows 6.0 percent and 10bps respectively — a gap TICGL flags for BOT and readers alike.
- Institutional and climate capacity building is the least visible but most structural theme — AI maturity, data governance, ESG integration and emissions reduction targets that matter for whether BOT can execute the rest of the Plan at all.
02 — ContextWhat Is the BOT Strategic Plan 2026/27-2030/31?
The Plan is BOT's fifth-generation corporate strategy, published in June 2026 under Governor and Board Chairman Emmanuel Mpawe Tutuba, coinciding with the Bank's 60th anniversary (1966-2026). It restates BOT's mission — to maintain price stability and the integrity of the financial system for inclusive economic growth — and sets out a results-based framework built predominantly on the Management by Objectives (MBO) methodology, partly supplemented by the Balanced Scorecard (BSC) technique and a Performance Measurement Process (PuMP®) for tracking execution.
Seven Key Strategic Focus Areas
- Enhancing Monetary Policy and Price Stability
- Deepening Domestic Financial Markets and Foreign Reserve Opportunities
- Strengthening Financial Stability, Inclusion, Payment Systems and Regulation
- Enhancing Digital Transformation, Data Governance and Operational Resilience
- Promoting Climate Change Resilience and Sustainability
- Enhancing Institutional Excellence
- Improving Gender Equality and Diversity
Three Thematic Areas, Six Strategic Objectives
- Theme 1 — Macroeconomic Stability: monetary policy effectiveness, foreign reserves, deepening domestic financial markets.
- Theme 2 — Stability of the Financial Sector: financial-sector safety and inclusiveness, banking and currency services, climate resilience.
- Theme 3 — Organizational Capacity: institutional efficiency, organisational effectiveness and sustainability.
Each objective carries defined intended results, KPIs, a 2026/27 baseline, a 2029/30 target, and a named strategic initiative with an assigned departmental "champion" responsible for delivery.
The Governor's framing
In his foreword, Governor Tutuba reports that the outgoing 2021/22-2025/26 plan achieved and, in his words, surpassed its objectives: core and headline inflation averaged 2.9 percent and 3.1 percent respectively, the exchange rate was managed through external pressure, foreign reserves were strengthened partly through domestic gold purchases, and real GDP growth averaged 5.5 percent. The new Plan is framed as building on that record while adding a new Artificial Intelligence and Data Management strategy and a stronger climate-resilience agenda, developed against a backdrop of rising global geopolitical risk.
Structurally, the document also discloses BOT's capital works pipeline: two multi-year construction projects (Bank Officers' Apartments and Senior Staff Housing Apartments, both in Kigoma, on a design-and-build basis) plus a further sixteen new projects for 2026/27 alone, split evenly between construction and ICT — a reminder that institutional capacity building sits alongside monetary policy as a genuine budget line, not an afterthought.
03 — Policy AlignmentHow the Plan Maps Onto FYDP IV and Dira 2050
BOT's own alignment diagram is unusually explicit for a central bank strategy document: it draws direct lines from each of its three thematic areas to specific national frameworks, rather than gesturing at alignment in prose alone.
Where the alignment is strongest
The clearest link runs through Theme 1. FYDP IV's growth and industrialisation agenda depends on a stable shilling, contained inflation, adequate reserves, and — critically — a banking sector willing to extend credit at scale. BOT's monetary-policy and financial-market-deepening objectives target exactly those inputs, and its 70 percent-private-financing assumption for FYDP IV infrastructure (documented in TICGL's companion analysis on infrastructure and human-capital spending) is only credible if private-sector credit genuinely expands the way BOT's Plan targets it to.
Where the alignment is more implicit than operational
Human capital and social development is one of FYDP IV's five co-equal national priorities, yet BOT's Plan engages with it only indirectly, through financial inclusion (percentage of adults with accounts, the Tanzania Financial Inclusion Index) rather than through any direct link to health, education or skills financing. That is a reasonable division of labour for a central bank, but it means BOT's Plan alone cannot answer the infrastructure-versus-human-capital budget question TICGL examines elsewhere — it only sets the financing conditions under which that debate plays out.
05 — The New CommitmentsWhat BOT Is Targeting by 2029/30
The new Plan resets baselines to 2026/27 opening figures and sets fresh targets for 2029/30 (the Plan's fourth year, one year short of its formal 2030/31 close, per BOT's own "Plan at a Glance" tables). The clearest way to read these is theme by theme.
Theme 1 — Macroeconomic Stability
Credit to the Private Sector: The Plan's Boldest Target
Credit to private sector as a percentage of GDP — 2021/22 baseline, 2025/26 actual, 2029/30 target
Theme 2 — Stability of the Financial Sector
Financial Sector Soundness Targets vs Current Position
Percent — capital adequacy, NPL ratio and liquidity ratio: baseline (already achieved) vs the regulatory-minimum 2029/30 target
Financial Inclusion: Baseline vs 2029/30 Target
Percent of adults with transactable accounts and TanFiX index (scaled ×100 for comparability)
Theme 3 — Organizational Capacity
Digital & Institutional Maturity: Baseline vs Target
Maturity levels (approx. 1-5 scale) — AI, IT and data-management maturity
Governance & ESG: Baseline vs Target
Percent — legal/regulatory compliance, stakeholder satisfaction and ESG integration
Bank of Tanzania's Own Carbon Footprint: Reduction Target
Tonnes of CO₂-equivalent (tCO₂e) — baseline vs 2029/30 target, per BOT's Theme 3 KPI table
06 — Reading the Fine PrintWhere BOT's Own Tables Disagree With Each Other
A close read of the Plan turns up several places where the detailed "Plan at a Glance" KPI tables (pages 7-9) do not match the summary infographic later in the same document ("Bank's Key Performance Indicators and Targets by 2030/31", page 28). TICGL flags these not to discredit the Plan — its underlying direction is sound — but because published targets should be internally consistent, and readers relying on any single page of the source PDF could come away with a different number.
Why this matters for external readers
Investors, development partners and researchers who cite a single BOT target risk quoting the wrong one. TICGL recommends BOT publish a single reconciled KPI annex — the Plan's own Companion Document, referenced but not included in the main Plan, may already resolve some of these gaps, and TICGL will update this analysis if and when that document becomes publicly available.
07 — Institutional Self-AssessmentBOT's Own SWOC Analysis
BOT's Situation Analysis includes a candid Strengths-Weaknesses-Opportunities-Challenges (SWOC) assessment, which is useful context for judging how realistic the Organizational Capacity targets are.
Strengths
- Strong working environment supporting staff productivity and retention
- Competent, experienced, committed personnel with solid governance practices
- Reliable ICT systems and interoperable payment infrastructure
- Strategically located branches and robust operational frameworks
- Proactive monetary policy framework and diversified foreign reserves
Weaknesses
- Inadequate risk-management culture and handling of strategic-project and sustainability risks
- ICT infrastructure insufficient to fully support operations
- Slow adoption of global standards and technological innovation
- Aging infrastructure, limited office space and security concerns
- Inefficient processes and generational-diversity challenges causing delays
Opportunities
- Stable political and economic environment supports policy implementation
- Technological innovation and expanding financial-service networks
- Strong government support and stakeholder collaboration
- Access to international training and global best practice
- Gold reserves, diversified investments and rising investor participation
Challenges
- Rising cyber threats and fraud risk to financial stability
- Global financial-market volatility and external shocks complicating policy
- Data unreliability and rapid technological change
- Structural issues: dollarization, market segmentation, high borrowing costs
- Climate-change risk and still-limited financial inclusion
The connecting thread
Nearly every listed weakness and challenge — inadequate risk culture, insufficient ICT, dollarization, cyber risk, data unreliability — maps directly onto a Theme 3 KPI in the new Plan (risk maturity, IT maturity, AI maturity, data-management maturity). That is a good sign: BOT appears to be building its 2029/30 targets around problems it has itself already diagnosed, rather than setting generic aspirational goals.
08 — TICGL AnalysisSo, Will This Plan Protect Tanzania's Growth?
Putting the pieces together — the alignment mapping, the strong prior track record, the new targets and the internal inconsistencies — TICGL's assessment is that the Plan is a credible, well-aligned foundation for FYDP IV and Dira 2050, with three qualifications that matter for how it should be read.
1. Macro stability is necessary but not sufficient for FYDP IV
Low inflation, adequate reserves and deep financial markets are the conditions private capital needs before it will commit to the PPPs and FDI that FYDP IV's 70:30 financing model depends on, as TICGL's companion infrastructure-versus-human-capital analysis sets out. BOT's Plan supplies those conditions; it cannot, on its own, guarantee the PPP pipeline or private appetite actually materialises.
2. The credit-to-GDP target is the single biggest lever
Lifting credit to the private sector from 22.8 percent to 30 percent of GDP by 2029/30 would be a genuine structural shift for an economy where dollarization and market segmentation still push up borrowing costs, per BOT's own SWOC. If achieved, it materially widens the pool of financing available for both infrastructure and human-capital-adjacent private investment (health facilities, ed-tech, agribusiness) — arguably a more powerful lever for inclusive growth than any single BOT KPI.
3. The GDP growth target undershoots FYDP IV's own ambition
FYDP IV's headline target is 10.5 percent real GDP growth by 2030/31 (per TICGL's FYDP IV research); BOT's detailed table targets ≥7.2 percent — and its own summary infographic shows just 6.0 percent. Central-bank growth targets are typically set conservatively to preserve credibility, but the gap between BOT's figures and FYDP IV's headline number is wide enough that either FYDP IV's growth ambition, or BOT's own monetary stance, may need to be reconciled publicly.
4. Several "targets" are really floors, and that is fine — but should be labelled as such
Capital adequacy, NPL ratio, liquidity ratio and import cover are all set at levels BOT has already surpassed. These read less as ambition for 2029/30 and more as regulatory minimums BOT will not allow itself to fall below — a legitimate risk-management stance, but worth distinguishing clearly from genuinely stretching targets like the credit-to-GDP or AI-maturity goals, so external readers do not mistake a floor for a forecast.
TICGL's bottom line
BOT's Strategic Plan 2026/27-2030/31 is structurally well-aligned with FYDP IV and Dira 2050 and builds on a genuinely strong five-year delivery record. It is likely to protect — rather than drive — Tanzania's growth: its job is to keep inflation, the exchange rate and the financial system stable enough that FYDP IV's growth and private-financing ambitions have a fighting chance, not to generate that growth itself. Whether Tanzania hits FYDP IV's 10.5 percent growth ambition depends far more on fiscal policy, the PPP pipeline, tax-to-GDP expansion and human-capital investment — the levers examined in TICGL's other FYDP IV research — than on anything within BOT's own mandate.
09 — TICGL RecommendationsGetting the Most Out of BOT's Plan
- Publish a single reconciled KPI table resolving the GDP growth, foreign-investment-income, compliance and emissions discrepancies between the detailed tables and the summary infographic, ideally as a published erratum or via the referenced Companion Document.
- Distinguish regulatory floors from stretch targets in future public communication — capital adequacy, NPL and liquidity minimums serve a different purpose than the credit-to-GDP or AI-maturity targets and should be presented differently to avoid understating the Plan's genuine ambition.
- Publish an explicit reconciliation between BOT's GDP growth target and FYDP IV's 10.5 percent headline ambition, so investors and development partners are not left guessing which growth figure is the operative national target.
- Track private-sector credit growth by sector (agriculture, MSME, infrastructure-adjacent, health/education-adjacent) so the 30-percent-of-GDP target can be assessed not just on scale but on whether it reaches the sectors FYDP IV and Dira 2050 most need financed.
- Report AI Maturity Index and Risk Maturity Level progress annually and publicly, given how directly these targets map onto the cyber, data-reliability and risk-culture weaknesses BOT itself identified in its SWOC analysis.
10 — Quick AnswersFrequently Asked Questions
What is the Bank of Tanzania's Strategic Plan 2026/27-2030/31?
BOT's five-year corporate strategy covering monetary policy, foreign reserves, financial markets, financial-sector stability, banking services, climate resilience and organisational capacity, explicitly aligned with FYDP IV and Dira 2050.
Does BOT's Strategic Plan align with FYDP IV and Dira 2050?
Yes, structurally — BOT's own alignment diagram maps its three thematic areas directly onto Dira 2050's pillars and FYDP IV's competitiveness agenda, with BOT's price and financial-stability mandate forming the macroeconomic base those plans depend on.
What GDP growth does BOT's plan target by 2029/30?
The detailed KPI table sets a target of at least 7.2 percent, though BOT's own summary infographic later in the document shows a lower 6.0 percent figure for the same indicator — an inconsistency TICGL flags for clarification.
Did BOT meet its previous five-year targets from 2021/22 to 2025/26?
Largely yes. Inflation stayed within target, GDP growth and credit to the private sector both beat target, and capital adequacy, NPL and payment reliability were all exceeded. The EFT settlement-time target and the share of adults with bank accounts were the two clear misses.
What is the biggest target BOT has set for credit to the private sector?
Credit to the private sector reaching at least 30 percent of GDP by 2029/30, up from 22.8 percent in 2025/26 — one of the most consequential targets in the Plan for private financing of FYDP IV.
11 — MethodologySources & Notes
- Bank of Tanzania — Strategic Plan 2026/27-2030/31 (June 2026), including the Foreword, Situation Analysis, Corporate Performance Review 2021/22-2025/26, SWOC Analysis, Plan at a Glance KPI tables, and Bank's Key Performance Indicators and Targets by 2030/31 summary (bot.go.tz).
- TICGL/TERI prior research: "What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050," "Infrastructure vs Human Capital: Where Is Tanzania's Budget Really Going?," and TICGL's FYDP IV budget series.
- Ministry of Finance Tanzania — FY2026/27 Budget context and FYDP IV framework documents, as cross-referenced in TICGL's related analyses.
- This page is an independent analytical summary prepared by TICGL/TERI based on BOT's published Strategic Plan document and does not constitute financial, investment, tax, or legal advice. Figures reflect BOT's own reporting as published; where BOT's document contains internal inconsistencies, both figures are disclosed.
MuhtasariMuhtasari kwa Kiswahili
Je, Mpango Mkakati wa BOT wa 2026/27-2030/31 Unaunga Mkono FYDP IV na Dira 2050? Benki Kuu ya Tanzania (BOT) imezindua Mpango Mkakati wa miaka mitano (2026/27-2030/31) unaolenga kudumisha uthabiti wa bei, kuimarisha mfumo wa fedha, na kuongeza mikopo kwa sekta binafsi kutoka asilimia 22.8 hadi angalau asilimia 30 ya Pato la Taifa (GDP) ifikapo 2029/30. Mpango huu umeunganishwa moja kwa moja na Dira 2050 na Mpango wa Nne wa Maendeleo wa Taifa (FYDP IV), ukiwa msingi wa kiuchumi unaohitajika ili malengo ya uwekezaji na ukuaji yaweze kufikiwa.
Uchambuzi wa TICGL unaonyesha kuwa katika miaka mitano iliyopita (2021/22-2025/26), BOT ilifanikiwa kufikia — na mara nyingi kuzidi — malengo yake mengi: mfumuko wa bei ulibaki ndani ya wigo wa asilimia 3-5, ukuaji wa GDP ulifikia asilimia 6.2 (zaidi ya lengo la asilimia 6), na mikopo kwa sekta binafsi ilifikia asilimia 22.8 ya GDP. Hata hivyo, malengo mapya ya 2029/30 yana changamoto kadhaa: baadhi ya malengo (kama uwiano wa mtaji wa benki na akiba ya fedha za kigeni) ni chini ya kiwango ambacho BOT tayari imekifikia, na kuna tofauti kati ya jedwali la kina la malengo (linaloonyesha ukuaji wa GDP wa angalau asilimia 7.2) na muhtasari wa mwisho wa hati hiyo (unaoonyesha asilimia 6.0 tu) — jambo ambalo TICGL inapendekeza BOT ilifafanue.
Uchambuzi wa TICGL unahitimisha kuwa Mpango wa BOT ni msingi imara na unaoendana vizuri na Dira 2050 na FYDP IV, lakini jukumu lake ni "kulinda" ukuaji wa uchumi kwa kudumisha uthabiti wa fedha, si "kuuzalisha" ukuaji huo. Kufikiwa kwa lengo kuu la FYDP IV la ukuaji wa asilimia 10.5 kunategemea zaidi sera za kibajeti, mfumo wa ubia wa umma na binafsi (PPP), upanuzi wa mfumo wa kodi, na uwekezaji kwenye maendeleo ya watu — maeneo yanayochambuliwa kwa kina katika tafiti nyingine za TICGL kuhusu FYDP IV.
- Mikopo kwa sekta binafsi: kutoka asilimia 22.8 (2025/26) hadi lengo la angalau asilimia 30 ifikapo 2029/30
- Ukuaji wa GDP: lengo la angalau asilimia 7.2 (jedwali la kina) dhidi ya asilimia 6.0 (muhtasari wa mwisho) — tofauti inayohitaji ufafanuzi
- Mfumuko wa bei: lengo la kubaki ndani ya wigo wa asilimia 3-5
- Akiba ya fedha za kigeni: lengo la miezi angalau 4.0 ya uagizaji bidhaa
Vyanzo: Mpango Mkakati wa Benki Kuu ya Tanzania 2026/27-2030/31 (Juni 2026), na utafiti wa awali wa TICGL/TERI kuhusu FYDP IV na Dira 2050. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI).
01 — OverviewExecutive Summary
Every Tanzanian budget season revives the same quiet argument inside ministries, in Bunge debate, and among development partners: does the next shilling build a road, a railway and a power plant, or does it build a classroom, a clinic and a water point? This report puts numbers behind that argument. It compares Tanzania's spending on infrastructure (construction, transport, energy) against its spending on human capital (health, education, water) from 2020/21 through the 2026/27 budget — the opening year of the Fourth Five-Year Development Plan (FYDP IV, 2026/27-2030/31) — and benchmarks Tanzania's underlying human development indicators against upper-middle-income countries (UMIC), the income class Dira 2050 aims to reach by 2050.
The picture is not a simple story of neglect. Health and water budgets have grown far faster than infrastructure budgets in percentage terms since 2020/21. But infrastructure still commands the larger absolute share of Tanzania's development spending, and the underlying human capital deficit — a 63:1 teacher-pupil ratio, 1.34 doctors per 10,000 people, a World Bank Human Capital Index Plus score of 133 out of 325 — remains severe enough to threaten the productivity gains FYDP IV and Dira 2050 are counting on. This report also looks outward: how did South Korea, China, Vietnam, Rwanda and Ethiopia sequence their own infrastructure and human-capital investments on the way to faster growth, and what, if anything, should Tanzania borrow from their experience.
- Infrastructure still leads in absolute terms. Construction, transport and energy ministries together commanded roughly TZS 7.09 trillion in 2020/21 and an estimated TZS 7.8-7.9 trillion in 2026/27 — still larger than confirmed health, water and education-ministry spending combined.
- Human capital is growing faster, from a smaller base. Confirmed health and water spending rose from about TZS 1.25 trillion in 2020/21 to about TZS 2.92 trillion in 2026/27 — growth of roughly 134 percent, against roughly 10-12 percent for infrastructure ministries over the same period.
- The underlying gaps are still wide. Tanzania's teacher-pupil ratio, doctor-population ratio, cereal yield per hectare and life expectancy all remain well below UMIC averages — the income class Dira 2050 targets by 2050.
- FYDP IV's financing model may make this less of a binary choice. With roughly 70 percent of FYDP IV's resource needs expected from private capital and PPPs — concentrated in infrastructure, ports, energy and roads — public fiscal space may be freer than the raw numbers suggest to prioritise human capital, provided the PPP pipeline actually delivers.
02 — The DataTanzania vs Upper-Middle-Income Countries: The Human Capital Gap
Dira 2050 aims to move Tanzania into the upper-middle-income bracket by mid-century, with a US$1 trillion economy and roughly US$7,000 GDP per capita. Comparing Tanzania today against the average UMIC country shows how much ground human capital indicators still need to cover — regardless of how the infrastructure-versus-human-capital budget question is eventually resolved.
Teacher-Pupil Ratio: Tanzania vs Upper-Middle-Income Countries
Pupils per primary-school teacher — lower is better
Doctors per 10,000 People
Tanzania vs selected UMIC comparators
Cereal Yield (kg per hectare)
Agricultural productivity, Tanzania vs UMIC comparators
Life Expectancy at Birth
Years, Tanzania vs UMIC average
Human Capital Index Plus (HCI+) Score
Out of 325 — Tanzania vs regional and income-group averages
⚠ Teacher-pupil and doctor-population ratios are the most recent figures publicly available (2018-2024) from differing sources; not all indicators are updated annually by the World Bank or WHO.
What the HCI+ score actually means
The World Bank's Human Capital Index Plus estimates how productive a child born in Tanzania today can expect to become by the end of their working life, given current health and education outcomes. Tanzania's score of 133 means a Tanzanian child today can expect to reach only 41 percent of the productivity they could achieve with complete education and full health. Closing the gap with high-performing countries at a similar income level would raise future incomes by an estimated 66 percent — a bigger single lever than almost any infrastructure project on Tanzania's books.
03 — The DataSectoral Budget Trends: Agriculture, Health, Education and Water, 2020/21-2026/27
Comparing ministerial budgets for agriculture, health, education and water between 2020/21 and the most recent 2026/27 estimates shows consistent, and in some cases dramatic, nominal growth — though starting from a low base in several sectors.
⚠ Education and Health figures shown are Ministry (Fungu) budgets only, not whole-sector spending. Most primary and secondary education and primary healthcare services are financed through TAMISEMI (President's Office - Regional Administration and Local Government), so the true "sector" total is larger than what appears here. The whole education sector reached TZS 5.26 trillion in 2021/22 alone.
Human-Capital-Adjacent Ministerial Budgets: 2020/21 vs 2026/27
TZS trillions — Agriculture, Health and Water (Education excluded due to non-comparable base years; see table above)
2020/21Low base across all four sectors
Agriculture at TZS 229.8bn, health at roughly TZS 650bn, water below TZS 700bn — all a small fraction of infrastructure ministries' combined TZS 7.09 trillion that year.
2022/23-2024/25Agriculture budget multiplies
Kilimo's budget rises from TZS 294bn (2021/22) to TZS 751.1bn (2022/23) to TZS 970.78bn (2023/24) to TZS 1.249 trillion (2024/25) — a more than fivefold increase in four years, before flattening in 2025/26.
2025/26-2026/27Health and water accelerate again
Water's budget jumps from TZS 898bn to TZS 1.12 trillion in a single year (+33%); health reaches TZS 1.8 trillion, roughly 2.8 times its 2020/21 level.
2026/27FYDP IV's opening year
The national budget rises to TZS 62.33 trillion (+10.3% year-on-year), explicitly framed as the first operational budget of FYDP IV and Dira 2050.
04 — The Core ComparisonInfrastructure vs Human Capital: The Full Reckoning
Putting construction, transport and energy spending side by side with health, water and education-ministry spending gives the clearest single picture of Tanzania's budget priorities across the FYDP III-to-FYDP IV transition.
🏗️ Infrastructure (Construction + Transport + Energy)
- ~TZS 7.09 trillion in 2020/21 (Construction, Works and Communications was a single combined ministry at the time)
- ~TZS 7.7-7.9 trillion in 2026/27 — Transport TZS 2.872T (approved), Energy TZS 2.525T (approved), Construction estimated TZS 2.3-2.5T
- Growth of roughly 10-12 percent over six years — modest relative to human capital's growth rate
- Still the single largest category of sectoral development spending in absolute TZS terms
VS
🏥 Human Capital (Health + Water + Education-Ministry)
- ~TZS 1.25 trillion in 2020/21 for confirmed Health + Water alone
- ~TZS 2.92 trillion in 2026/27 for confirmed Health + Water; adding the Education ministry's TZS 2.398T brings the total to roughly TZS 5.3 trillion
- Health + Water growth of roughly 134 percent since 2020/21 — over ten times infrastructure's growth rate
- Still smaller in absolute terms than infrastructure, even after the fastest six years of growth on record
Infrastructure vs Human Capital: Total Ministerial Budgets, 2020/21 vs 2026/27
TZS trillions — infrastructure (Construction + Transport + Energy) vs confirmed human capital (Health + Water)
1. Growth rate favours human capital
Between 2020/21 and 2026/27, human-capital budgets (health and water) grew by more than 2.3 times, versus roughly 10-12 percent for infrastructure. This is a genuine acceleration in the direction of Dira 2050's human-development ambitions.
2. Absolute scale still favours infrastructure
In raw TZS terms, infrastructure still commands the larger share of Tanzania's development budget: roughly TZS 7.8 trillion against roughly TZS 2.9-5.3 trillion for confirmed human capital, depending on whether the Education ministry is included.
3. The trend line, not the snapshot, is the story
The direction of travel shows government accelerating investment in social services, even though infrastructure still leads in overall scale of funding — a rebalancing in progress rather than a completed shift.
⚠ The Ministry of Works, Transport and Communications that existed in 2020/21 has since been split into separate Construction and Transport ministries. Comparisons combine functionally equivalent ministries and are therefore approximate, not exact.
05 — Supporting DataWhere the Whole TZS 62.33 Trillion Budget Goes
Infrastructure and human capital spending sit inside a much larger national budget. Understanding the full FY2026/27 envelope — TZS 62.33 trillion, up 10.3 percent on 2025/26 — shows how much fiscal room genuinely exists for either priority once debt service, subsidies, wages and pensions are accounted for.
Total FY2026/27 Budget
TZS 62.33T
+10.3% vs 2025/26 (TZS 56.49T)
Domestically Financed
74.2%
Of total budget, from domestic revenue
Projected Revenue
TZS 46.79T
Tax revenue TZS 36.99T; other revenue TZS 9.24T
Budget Deficit
TZS 7.71T
Financed via domestic and external borrowing
FY2026/27 Budget Composition
TZS trillions, by expenditure category (excludes debt principal repayment)
Note: "Subsidies" (ruzuku, TZS 25.32T) is the largest single category and includes transfers to public institutions, LGAs, and sector programmes — this is the pool from which much of both infrastructure PPP support and human-capital service delivery (schools, hospitals) is actually funded, beyond the ministries' own direct development votes shown in earlier sections.
Why this matters for the infrastructure-vs-human-capital question
Interest payments alone (TZS 6.86 trillion) are now larger than either the entire health ministry or water ministry budget, and personnel costs (TZS 10.13 trillion) dwarf both combined. This is the fiscal reality within which any reprioritisation between infrastructure and human capital must happen — it is not simply a question of moving money from one ministry's vote to another, but of managing debt service, wage bill growth, and subsidy commitments that already claim the majority of the budget before a single road or classroom is funded.
06 — Policy ContextWhat FYDP IV and Dira 2050 Actually Prioritise
Tanzania's Long-Term Perspective Plan (LTPP) 2050 — Dira 2050 — is implemented through five successive Five-Year Development Plans, the first of which, FYDP IV, runs from 2026/27 to 2030/31 under the theme "Reforms for Inclusive Economic Growth and Employment Creation." TICGL's prior analysis frames FYDP IV's underlying philosophy as the "4Rs": Reform, Reconciliation, Rebuilding and Resilience.
FYDP IV's Five Core Priorities
- Building a strong, inclusive and competitive economy through nine transformation sectors
- Promoting human capital and social development
- Strengthening environmental conservation and climate resilience
- Advancing economic transformation drivers
- Reinforcing governance, peace, security and stability
Human capital is formally listed as one of five co-equal national priorities — not subordinate to infrastructure or economic transformation, at least on paper.
FYDP IV's Headline Targets by 2030/31
- Nominal GDP of US$118.052 billion
- Real GDP growth of 10.5 percent
- A step toward Dira 2050's US$1 trillion economy and US$7,000 per-capita income by 2050
- 70:30 private-to-public financing architecture — the private sector expected to provide 70 percent of resources needed for Plan implementation
FYDP IV's Planned Financing Architecture
Share of total resource needs expected from private capital vs public budget
Why the 70:30 split matters for this debate
If PPPs, FDI and blended finance genuinely deliver 70 percent of FYDP IV's resource needs — targeted at construction, transport, energy, ports and industrial infrastructure — then a meaningful share of Tanzania's infrastructure ambition does not have to compete directly with health, education and water for scarce public shillings. Public and Statutory Corporations, holding assets exceeding TZS 92.3 trillion, are being restructured specifically to attract this private capital. The Plan targets PPPs contributing 10 percent of GDP by June 2030, with 6-8 projects reaching commercial close, mobilising TZS 4.0-5.0 trillion in private capital.
The catch: Tanzania's PPP track record to date has been described as modest by independent analysts, and development-budget execution rates run around 52 percent versus 93 percent for recurrent spending — meaning this fiscal-space argument is currently more of a plan than a proven mechanism.
The tax-to-GDP constraint underneath everything
Tanzania's tax-to-GDP ratio is estimated at roughly 12.9-13.1 percent for 2024 by TICGL/TERI's own research, below the Sub-Saharan Africa average commonly cited in the 15-18 percent range, and well below FYDP IV's own 2030 target of 18 percent. Independent analysts have gone further, suggesting a ratio closer to 22 percent may be needed to sustainably finance Vision 2050's full ambitions without over-relying on debt. Until the tax base widens, every additional shilling for either infrastructure or human capital increasingly has to come from borrowing, subsidy reallocation, or genuinely successful PPP mobilisation — not fresh domestic revenue.
07 — Comparative LessonsWhat Did Other Developing Countries Prioritise First?
Tanzania is not the first country to face this choice. Looking at how South Korea, China, Vietnam, Rwanda and Ethiopia sequenced infrastructure and human-capital investment on their own development paths offers some grounding — though, as the evidence below shows, there is no single formula that guarantees success.
🇰🇷 South Korea: Human Capital First, Infrastructure Followed
In the 1950s and early 1960s, Korea used more than US$100 million in foreign aid for education, dedicating roughly US$70 million to building and repairing classrooms and a further US$19 million to Seoul National University and other institutions, even while the country was still recovering from war and had scarce infrastructure. Only from the 1960s-1980s did the state pivot toward capital-intensive, infrastructure-heavy heavy industry. Korea's total domestic investment from 1960-1990 averaged 26.3 percent of GDP, with about a third of that going to infrastructure — but the education base built in the 1950s is widely credited as the precondition that let later industrial investment pay off.
🇨🇳 China: Infrastructure-Led, Investment-Driven Growth
China's growth since 1978 has been defined by sustained, investment-led infrastructure development — averaging around 8 percent of GDP annually in the early 2000s — layered on top of rural land reforms and foreign direct investment that together cut poverty from 60 percent of the population in 1980 to 8 percent by 2009. Chinese policymakers have historically treated rapid infrastructure investment growth as a precondition for sustaining high GDP growth, rather than a reward for it.
🇻🇳 Vietnam: Following the Infrastructure-First Playbook
Vietnam's Doi Moi reforms, launched in 1986 (eight years after China's own reform), consciously mirrored China's development path, including its emphasis on infrastructure as a growth driver. Vietnam still needs an estimated US$25 billion a year in infrastructure investment, and continues to rely heavily on foreign capital and technical partners — including a cautious, security-conscious relationship with Chinese infrastructure financing — to close the gap.
🇷🇼 Rwanda: Trying to Run Both Tracks in Parallel
Rwanda's Vision 2020 and Vision 2050 explicitly targeted human capital development, growth-enhancing infrastructure, and higher-value economic activity simultaneously, with public investment averaging around 10 percent of GDP. The results are mixed: Rwanda built over 40 microhydro plants in 15 years and posted some of the region's best logistics performance, yet a persistent skills gap remains, with around 22 percent of the manufacturing workforce reporting limited technical proficiency and over 90 percent needing soft-skills training — a caution that infrastructure gains alone do not automatically produce a workforce able to use them.
🇪🇹 Ethiopia: Pragmatic, Sector-Specific Infrastructure
Ethiopia's modernisation drive focused on large agricultural plantations, industrial parks, and pragmatic energy solutions tailored to rural realities, evoking classic mid-20th-century infrastructure-led modernisation. Independent reviews credit Ethiopia's energy-access gains as a genuine driver of progress, while noting that, as with Rwanda, execution capacity and complementary human capital investment remain the binding constraints on translating infrastructure into broad-based productivity gains.
🇹🇿 Tanzania: Currently Closer to the Infrastructure-First Model
On the numbers in this report, Tanzania's actual spending pattern — infrastructure still commanding roughly 1.5-2.5 times the confirmed human-capital budget in absolute terms — sits closer to the China/Vietnam/Ethiopia infrastructure-led tradition than to Korea's education-first sequencing or Rwanda's declared dual-track approach, even though FYDP IV's stated priorities read more like Rwanda's parallel-track framing.
The one consistent warning across all five cases
No country in this comparison achieved sustained high growth through infrastructure investment alone, without a workforce capable of using that infrastructure productively. Korea's heavy-industry boom depended on a workforce Korea had already educated. China and Vietnam paired infrastructure-led growth with large, continuous investments in basic education and health that are easy to overlook next to the more visible infrastructure story. Rwanda and Ethiopia's experience shows that even genuinely impressive infrastructure gains can be undercut by skills shortages that leave new capacity under-utilised. For Tanzania, the lesson is less "infrastructure or human capital" and more "infrastructure without human capital is a stranded asset."
08 — TICGL AnalysisSo What Should Tanzania Prioritise?
TICGL's reading of the evidence is that Tanzania does not face a clean either/or choice, but it does face a sequencing and intensity choice — and the data in this report suggests the intensity needs to shift further toward human capital than current budget trends have managed so far, for four reasons.
1. The productivity return on closing human capital gaps is larger and faster
The World Bank's own HCI+ modelling suggests closing Tanzania's human capital gap with high-performing income-peers would raise future incomes by roughly 66 percent — a bigger single national productivity lever than any individual infrastructure corridor currently on Tanzania's books, including the SGR or the Julius Nyerere hydropower station.
2. FYDP IV's own financing model frees room for exactly this shift
If the 70:30 private-to-public financing architecture works as designed, most new infrastructure capital should come from PPPs, FDI and restructured public corporations rather than the recurrent budget — precisely the mechanism that should let public shillings concentrate more on health, education and water, which are far harder to finance through private capital because their returns are diffuse, long-term, and non-excludable.
3. Existing infrastructure commitments should be completed, not abandoned
SGR, port modernisation, and the National Water Grid represent large sunk investments with genuine growth payoffs once complete; halting them to redirect funds would likely destroy more value than it creates. The choice is not to strip infrastructure funding, but to ensure its growth rate does not continue to outpace human capital's as FYDP IV progresses.
4. Regional and global evidence favours running both tracks, but weighting toward people
Korea's experience — foundational education investment before the infrastructure-heavy industrial push — is the closest historical analogue to a country starting, as Tanzania is, from a low human-capital base with an ambitious multi-decade income target. Rwanda's parallel-track approach, while imperfect, shows dual investment is achievable at Tanzania's income level; its remaining skills gap is itself an argument for weighting the human-capital side of that balance more heavily than Rwanda has.
TICGL's bottom line
Tanzania should treat FYDP IV's 70:30 private-public financing target for infrastructure as a binding commitment to actively pursue, not an assumption to bank passively — because its success is what creates the fiscal space for the second half of this argument. At the same time, given that human capital's growth in Tanzania's budget over 2020/21-2026/27, while rapid in percentage terms, has still not closed the absolute gap with infrastructure, TICGL's assessment is that the marginal shilling of new public spending through 2030/31 should tilt toward human capital — particularly toward closing the teacher-pupil and doctor-population ratios that most directly limit how much value Tanzania's citizens, and its completed infrastructure, can ultimately generate.
09 — TICGL RecommendationsGetting the Balance Right Under FYDP IV
- Publish a consolidated, comparable annual infrastructure-vs-human-capital scorecard that nets out ministry restructuring (such as the Works/Transport split) so the trend is auditable year over year, not just within isolated ministry budget speeches.
- Make the 70:30 PPP financing target a tracked, published commitment, with quarterly disclosure of PPP projects reaching commercial close against the 6-8 project, TZS 4.0-5.0 trillion target — the credibility of this target is what determines whether infrastructure can be funded without crowding out human capital.
- Prioritise teacher and doctor recruitment and retention as a headline FYDP IV human-capital target with the same visibility currently given to SGR kilometres completed or megawatts connected to the grid.
- Fund TAMISEMI-administered primary education and primary healthcare transparently alongside ministry-level figures, so public debate is not distorted by comparing partial (Fungu-only) human-capital budgets against full infrastructure ministry totals.
- Treat tax-to-GDP expansion as the precondition for both priorities — closing the gap toward FYDP IV's own 18 percent target (and the 22 percent some analysts argue is truly needed) reduces the degree to which infrastructure and human capital have to compete for the same limited pool of domestic revenue.
10 — Quick AnswersFrequently Asked Questions
Does Tanzania spend more on infrastructure or on human capital?
In absolute terms, infrastructure still leads — roughly TZS 7.8-7.9 trillion in 2026/27 across construction, transport and energy, versus roughly TZS 2.9 trillion in confirmed health and water spending. But human-capital budgets have grown over ten times faster in percentage terms since 2020/21.
What is Tanzania's teacher-to-pupil ratio compared to upper-middle-income countries?
About 63 pupils per teacher nationally, reaching over 100:1 in some councils, versus 16-24:1 in upper-middle-income countries.
What is Tanzania's doctor-to-population ratio?
About 1.34 doctors per 10,000 people — roughly 1 doctor per 7,460 residents — compared with 31.1 per 10,000 in China, 23.6 in Brazil, and 7.9 in South Africa.
What does FYDP IV say about infrastructure and human capital?
Human capital and social development is one of FYDP IV's five core priorities, alongside a competitive economy across nine transformation sectors. The Plan expects the private sector to fund roughly 70 percent of total resource needs, largely for infrastructure, which could free public resources for social spending if the financing model succeeds.
Did other developing countries prioritise infrastructure or human capital first?
There is no single formula. South Korea invested heavily in education before its infrastructure-heavy industrial push. China and Vietnam pursued infrastructure-led growth. Rwanda has tried to pursue both in parallel, though a persistent skills gap remains despite strong infrastructure gains.
11 — MethodologySources & Notes
- World Bank Open Data (World Development Indicators) and UNESCO Institute for Statistics — teacher-pupil ratios, cereal yield, life expectancy.
- WHO Global Health Observatory and World Population Review 2026 — doctor-population ratios.
- World Bank Human Capital Project — Tanzania's Human Capital Index Plus (HCI+) brief, 2026.
- Ministry of Finance Tanzania — FY2026/27 Budget Speech and Mapendekezo ya Ukomo wa Bajeti 2026/27-2028/29 (mof.go.tz).
- Sectoral budget speeches and parliamentary approvals, 2025/26-2026/27: Ministry of Agriculture, Ministry of Health, Ministry of Water, Ministry of Energy, Ministry of Transport, Ministry of Construction.
- TICGL/TERI prior research: "Tanzania's 2026/27 Budget: The First Blueprint of FYDP IV," "Tanzania Budget 2026/27: Can It Mobilize USD 121 Billion GDP by 2030/31?," "Tanzania's Health Economy Under FYDP IV," and "The Price of Formalisation" tax-policy report.
- ODI (Overseas Development Institute) — "Moving from vision to delivery: implementing Tanzania's Vision 2050."
- TanzaniaInvest — FYDP IV PPP framework, financing targets and Vision 2050 overview.
- International comparisons drawn from published academic and multilateral sources on South Korea, China, Vietnam, Rwanda and Ethiopia's development strategies, including World Bank Human Capital Project country studies and IMF/AfDB country papers.
- This page is an independent analytical summary prepared by TICGL/TERI and does not constitute financial, investment, tax, or legal advice.
MuhtasariMuhtasari kwa Kiswahili
Miundombinu Dhidi ya Maisha ya Watu: Bajeti ya Tanzania Inaelekea Wapi? Kati ya 2020/21 na 2026/27, bajeti za afya na maji zimeongezeka kwa zaidi ya asilimia 134, ikiwa ni zaidi ya mara kumi ya kasi ya ongezeko la bajeti za miundombinu (ujenzi, uchukuzi na nishati) ambazo zimeongezeka kwa asilimia 10-12 tu katika kipindi hicho hicho. Hata hivyo, kwa thamani halisi, miundombinu bado inachukua fedha nyingi zaidi — takribani shilingi trilioni 7.8 mwaka 2026/27 — ikilinganishwa na takribani trilioni 2.9 za afya na maji zilizothibitika.
Tanzania bado inakabiliwa na pengo kubwa la maendeleo ya watu: uwiano wa mwalimu kwa mwanafunzi wa 1:63 (ukilinganisha na 1:16-24 katika nchi za kipato cha kati cha juu), daktari 1.34 kwa kila watu 10,000, na alama ya Human Capital Index Plus ya 133 kati ya 325 — ikimaanisha mtoto anayezaliwa Tanzania leo anatarajiwa kufikia asilimia 41 tu ya uwezo wake kamili wa uzalishaji. Mpango wa Nne wa Maendeleo wa Taifa (FYDP IV, 2026/27-2030/31) umeweka maendeleo ya watu (human capital) kama mojawapo ya vipaumbele vitano vikuu, na unategemea asilimia 70 ya fedha za utekelezaji kutoka sekta binafsi (PPP), hasa kwa miundombinu — jambo ambalo, likifanikiwa, laweza kuachia fedha zaidi za umma kwa ajili ya elimu, afya na maji.
Kwa kulinganisha na nchi nyingine: Korea Kusini iliwekeza kwanza kwenye elimu kabla ya kuingia kwenye miundombinu mikubwa ya viwanda; China na Vietnam zilifuata mkondo wa miundombinu-kwanza; Rwanda inajaribu kuchanganya vyote viwili kwa wakati mmoja, ingawa bado ina pengo kubwa la ujuzi wa wafanyakazi licha ya mafanikio makubwa ya miundombinu. Uchambuzi wa TICGL unaonyesha kuwa Tanzania haihitaji kuchagua kimoja tu — bali inahitaji kuhakikisha mfumo wa ubia wa umma na binafsi (70:30) unafanya kazi kikamilifu ili kuachia nafasi zaidi ya kibajeti kwa maendeleo ya watu, hasa katika kuongeza idadi ya walimu na madaktari.
- Bajeti ya afya na maji: ongezeko la asilimia 134 (2020/21-2026/27)
- Bajeti ya miundombinu: ongezeko la asilimia 10-12 tu, lakini bado ni kubwa zaidi kwa thamani halisi (~trilioni 7.8)
- Uwiano wa mwalimu-mwanafunzi: 1:63 Tanzania dhidi ya 1:16-24 UMIC
- Alama ya Human Capital Index Plus: 133/325 — chini ya wastani wa nchi za kipato cha kati cha chini (153)
Vyanzo: Wizara ya Fedha, Benki ya Dunia, WHO, UNESCO, hotuba za bajeti za wizara husika, na utafiti wa awali wa TICGL/TERI. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI).
01 — OverviewExecutive Summary
Two numbers about Tanzania's tax base are both accurate, and both keep making headlines for opposite reasons. The first: TRA's cumulative taxpayer register — everyone ever issued a Taxpayer Identification Number (TIN) — has grown from around 70,000 at TRA's founding in 1996 to over 8.1 million by mid-2026, a milestone TRA itself celebrated at its 30th anniversary. The second: the number of "active" registered taxpayers — those the Ministry of Finance counts as actually filing and paying in a given period — fell from 3.36 million in 2021/22 to 2.18 million in 2024/25, a decline of roughly a third, even as formalisation campaigns continued over the same period.
This report, building on TICGL/TERI's earlier tax-policy research, digs into what sits underneath both numbers: how a shrinking "active" base and a growing "registered" base can be simultaneously true, why TRA's revenue collections have kept setting records regardless, and what the gap means for Tanzania's Dira 2050 ambitions to widen its domestic revenue base.
- The register keeps growing because it almost never shrinks. A TIN, once issued, is rarely cancelled — so the cumulative count rises even when many holders stop filing.
- "Active" is a stricter, shrinking flow measure. Reported active-taxpayer snapshots show a consistent downward trend across three independent citations between 2021/22 and 2024/25.
- Revenue has grown anyway — TZS 32.26 trillion in 2024/25, TZS 37.95 trillion in 2025/26 — driven disproportionately by large taxpayers, customs, and digital administration, not by growth in the number of small active filers.
- Compliance infrastructure lags registration: 88 percent of business-TIN holders were not registered for Electronic Fiscal Devices as of July 2024, per the Controller and Auditor General.
02 — The Core TensionRegistered vs Active: Tanzania's Two Taxpayer Numbers
Ask "how many taxpayers does Tanzania have?" and the honest answer is: it depends which of two very different numbers you mean.
📇 Total Registered (TIN Holders)
- 8.1 million+ as of mid-2026 — up from 70,000 at TRA's 1996 founding
- A cumulative stock: once a TIN is issued, it is rarely cancelled, even if the holder stops trading or filing
- Grew from 4.46 million (2021/22) to 6.27 million (2023/24) to roughly 7.7 million (late 2025), per NBS Tax Statistics data and subsequent reporting
- Reflects registration drives, digital onboarding, and formalisation campaigns pulling more people and businesses into the system
VS
✅ "Active" Taxpayers (Filing & Paying)
- 2.18 million in 2024/25 — down from 3.36 million in 2021/22
- A flow measure: counts who is actually filing returns and making payments in a given period
- An intermediate snapshot of 2.82 million was cited by Tanzania's Vice President as of 2024, consistent with a continuing downward trend
- Ministry of Finance and senior officials have publicly linked the decline to overburdening of the existing taxpayer pool
Why both numbers can be true
Think of the register as a bathtub that almost never drains: TINs flow in continuously through new registrations, but very few flow out through cancellation, even for businesses that have closed or gone dormant. "Active" status measures something different — who is actually turning up to file and pay in a specific tax year. It's entirely possible, and is exactly what Tanzania's data shows, for the bathtub to keep filling while the share of taxpayers actively transacting with TRA in any one period shrinks.
03 — The DataThe Decline in Active Taxpayers: Three Data Points, One Direction
3.36M active, 2021/22
2.82M active, 2024
2.18M active, 2024/25
Three independent public citations, spaced roughly a year apart, all point the same way. In April 2025, Tanzania's Vice President expressed concern that registered active taxpayers had dropped from 3.36 million in 2021–2022 to 2.82 million in 2024, urging renewed efforts to expand the base. TICGL/TERI's own August 2026 tax-policy research, citing Ministry of Finance data, put the 2024/25 active count at 2.18 million — continuing the same downward trajectory into the most recent fiscal year on record.
Active Registered Taxpayers: The Downward Trend, 2021/22–2024/25
Millions of active (filing/paying) taxpayers, as reported at each citation point
Note: these three figures come from separate public citations (Vice President's April 2025 remarks; TICGL/TERI's August 2026 report citing the Ministry of Finance) rather than a single continuous published series, so treat the connecting line as an illustrative trend rather than a precise quarterly series. All three, however, are consistent in direction and rough magnitude.
Whichever exact endpoint one uses — 2.82 million or 2.18 million — the direction and rough scale of the decline are corroborated by two independent sources roughly a year apart, which strengthens confidence that this is a genuine trend rather than a one-off data anomaly or reporting quirk.
04 — The DataThe Register Keeps Growing: 70,000 to 8.1 Million
Set against the active-taxpayer decline, the cumulative TIN register tells an almost opposite story. NBS's Tax Statistics Report series shows the total registered taxpayer count rising every year on record, and TRA's own 30th-anniversary figures put the milestone at over 8.1 million by mid-2026.
Total Registered Taxpayers, 2017/18–2023/24
Thousands of TIN holders, per NBS Tax Statistics Report data, with year-on-year growth
The Long Run: TRA's Register Since 1996
Selected milestones, thousands of registered taxpayers (log scale)
~1996TRA established
Roughly 70,000 taxpayers on record, annual collections around TZS 207 billion.
2017/18–2023/24NBS-tracked expansion
Register more than doubles, from 2.74 million to 6.27 million, driven by successive registration and formalisation drives.
2021/22–2024/25The active-count divergence begins
Even as the total register keeps climbing, active filing-and-paying taxpayers fall from 3.36 million to 2.18 million.
Mid-2026Register crosses 8.1 million
TRA marks its 30th anniversary; operational offices have grown from 95 to 323, and staff from 924 to 8,790, over the same broad period of expansion.
05 — TICGL AnalysisReconciling the Numbers: Stock, Flow, and What Gets Missed
The headline tension — "taxpayers are disappearing" versus "the register just hit a record 8.1 million" — dissolves once the two figures are read as what they actually measure, but that doesn't make the underlying compliance problem any less real.
1. TINs are sticky by design
A TIN functions as a permanent identity number, similar to a national ID, rather than a subscription that lapses. Businesses that close, individuals who die or emigrate, and duplicate or dormant registrations from earlier drives all remain in the cumulative count unless specifically cleaned up — something TRA's own systems, per the CAG's 2025 audit, do not yet do systematically.
2. "Active" is where the real story sits
The active-taxpayer figures — however imperfectly tracked across different citations — are the ones that actually matter for whether Dira 2050's formalisation and domestic-revenue goals are being met. A shrinking active base, even alongside a growing register, means TRA is working harder to extract the same or more revenue from a narrower, potentially more strained pool of genuinely compliant filers.
3. Both trends can share one cause
Complex procedures and compliance costs can simultaneously push existing filers toward inactivity or informality (shrinking the active count) while registration drives continue adding new TINs faster than genuine compliance grows behind them (expanding the register) — precisely the dynamic TICGL/TERI's Price of Formalisation report flags as a risk of formalisation drives "running in place."
Why this matters for policy
If policymakers cite only the growing 8.1 million register, the taxpayer-base story looks like unambiguous success. If they cite only the falling active count, it looks like unambiguous failure. Neither framing alone is accurate — and a formalisation strategy built on the register number risks overstating how much of Dira 2050's domestic-revenue gap it is actually closing, exactly the caution TICGL/TERI's tax-policy research raises about relying on MSME-focused instruments for material new revenue.
06 — The DataRevenue Keeps Rising — So Who Is Actually Paying?
Despite the active-taxpayer decline, TRA has posted record collections and beaten its target for 24 consecutive months through mid-2026. That is not a contradiction of the taxpayer-decline story — it is a clue to where Tanzania's tax revenue actually comes from.
TRA Annual Tax Collections vs Target
TZS trillions, selected fiscal years
Where December 2025 Revenue Came From
Share of TZS 4.13 trillion collected in December 2025, by source
In December 2025 alone, TRA collected TZS 4.13 trillion, of which large taxpayers contributed roughly TZS 1.9 trillion and customs roughly TZS 1.2 trillion — together well over 70 percent of that month's total — while small and medium traders contributed around TZS 838 billion. This composition is consistent with the study's broader finding: material revenue growth is concentrated among large taxpayers, customs, and administrative efficiency gains, not among the millions of small, actively-registered filers whose numbers have been shrinking.
FY2021/22 Collections
TZS 22.2T
Baseline year for active-taxpayer comparison
FY2023/24 Collections
TZS 26.73T
~85% of that year's domestic revenue
FY2024/25 Collections
TZS 32.26T
103% of target, +16.7% YoY
FY2025/26 Collections
TZS 37.95T
105% of target, 24th consecutive month above target
07 — Supporting DataTax-to-GDP in Context: Progress, But Still Below Regional Peers
Tanzania's tax-to-GDP ratio has been reported at different points between roughly 11.5 percent and 14.9 percent depending on the source, methodology, and fiscal year — reflecting genuine improvement over time as well as differences in how domestic revenue is measured. TICGL/TERI's own Price of Formalisation report puts the 2024 figure at approximately 12.9–13.1 percent. Across nearly every measure, however, Tanzania remains below the Sub-Saharan Africa average, most commonly cited in the 15–18 percent range.
Tanzania's Tax-to-GDP Ratio: The Range Across Sources
Percent of GDP, as reported by different sources and time periods (2023–2025)
Figures vary because different institutions use different fiscal-year definitions, revenue scopes (tax-only vs total domestic revenue), and GDP rebasing assumptions. TICGL reports the range transparently rather than resolving it to a single figure, consistent with the approach in the companion Price of Formalisation report.
09 — TICGL ViewWhat This Means for Tanzania's Domestic Revenue Strategy
For TRA and the Ministry of Finance
A public "active" taxpayer metric — tracked consistently over time, and reconciled with the total register — would let policymakers monitor the compliance trend directly, rather than relying on periodic public citations that vary in scope and vintage as this report's own sourcing had to work around.
For the formalisation agenda
New registration drives should be judged on whether they convert into sustained active filing, not just TIN issuance. Diagnosing why an existing pool of taxpayers is lapsing into inactivity may matter more for Dira 2050's revenue target than continuing to add new registrations to an already fast-growing stock.
For investors and the private sector
The concentration of revenue growth among large taxpayers and customs, documented above, suggests Tanzania's near-term domestic-revenue gains will keep depending disproportionately on a relatively small number of large, well-administered taxpayers rather than broad-based small-business compliance — a dynamic worth factoring into market-entry and partnership planning.
10 — TICGL RecommendationsClosing the Registered–Active Gap
- Publish a consistent, dated "active taxpayer" series alongside the total TIN register, so the two figures are never read as competing claims about the same thing.
- Audit and clean the TIN database to separate genuinely dormant, closed, or duplicate registrations from taxpayers who are simply non-compliant — the distinction the CAG's 2025 audit found TRA's own systems could not make.
- Diagnose the causes of inactivity among the roughly 1.2–1.4 million taxpayers who appear to have moved from active to inactive status since 2021/22, before launching further large-scale registration drives.
- Close the EFD compliance gap among the 88 percent of business-TIN holders not yet registered for EFDs, prioritising traders TRA's own data cannot currently classify as exempt or non-compliant.
- Evaluate formalisation campaigns on active-filing conversion, not registration counts alone, so success is measured by sustained compliance rather than by how many new TINs are issued.
11 — Quick AnswersFrequently Asked Questions
Is the number of taxpayers in Tanzania rising or falling?
Both, depending on which figure you look at. The total register has grown from about 70,000 to over 8.1 million, but "active" taxpayers — those actually filing and paying — fell from 3.36 million (2021/22) to 2.18 million (2024/25).
How many people are registered with TRA in Tanzania?
Over 8.1 million taxpayers were on TRA's register as of mid-2026, up from about 6.27 million in 2023/24 and 4.46 million in 2021/22.
Why is the active-taxpayer count falling while total registrations rise?
Registration is a cumulative stock that rarely shrinks; "active" status is a flow measuring who is actually filing and paying in a given period. A taxpayer can hold a valid TIN for years while being inactive.
What is Tanzania's EFD compliance rate?
As of July 2024, about 88 percent of business TIN holders (1,813,385 of 2,056,723) were not registered for Electronic Fiscal Devices, per a Controller and Auditor General audit tabled in April 2025.
Is TRA still collecting more revenue despite fewer active taxpayers?
Yes — TZS 32.26 trillion in 2024/25 and TZS 37.95 trillion in 2025/26, driven disproportionately by large taxpayers, customs, and administrative efficiency gains rather than growth in the active small-taxpayer base.
12 — MethodologySources & Notes
- Ministry of Finance data on active registered taxpayers (3.3–3.36 million, 2021/22; 2.18 million, 2024/25), as cited in TICGL/TERI's "The Price of Formalisation" report, August 2026.
- Vice President's remarks on active taxpayers declining from 3.36 million (2021/22) to 2.82 million (2024), reported by TanzaniaInvest, April 2025.
- National Bureau of Statistics (NBS), Tax Statistics Report, 2023/24 — registered taxpayer counts by fiscal year, 2017/18–2023/24.
- Tanzania Revenue Authority (TRA) 30th-anniversary corporate communications, July 2026 — total register (8.1 million+), office and staffing expansion.
- TRA corporate announcements on 2024/25 (TZS 32.26 trillion, 103% of target) and 2025/26 (TZS 37.95 trillion, 105% of target) revenue performance.
- Controller and Auditor General (CAG) performance audit on Electronic Fiscal Devices, tabled in Parliament 16 April 2025 (EFD non-registration among business TIN holders, as of July 2024).
- Tanzania Private Sector Foundation (TPSF) remarks on formal vs informal business registration shares, reported April 2025.
- Tax-to-GDP ratio figures compiled from multiple sources (PwC Tanzania, World Bank/Trading Economics, TICGL prior research, and TanzaniaInvest), reflecting the range across methodologies and fiscal years discussed in Section 7.
- This page is an independent analytical summary prepared by TICGL/TERI and does not constitute financial, investment, tax, or legal advice.
MuhtasariMuhtasari kwa Kiswahili
Kitendawili cha Walipa Kodi Tanzania: Milioni 8.1 Wamesajiliwa, Lakini Ni Wangapi Wanaolipa Kweli? Orodha ya walipa kodi waliosajiliwa (wenye TIN) imeongezeka kutoka takribani 70,000 mwaka TRA ilipoanzishwa hadi zaidi ya milioni 8.1 kufikia katikati ya mwaka 2026. Wakati huo huo, idadi ya walipa kodi "active" — wanaolipa na kuwasilisha taarifa zao kwa ukawaida — imepungua kutoka milioni 3.36 (2021/22) hadi milioni 2.18 (2024/25), kulingana na takwimu za Wizara ya Fedha.
Takwimu hizi mbili zinaweza kuwa kweli kwa wakati mmoja kwa sababu zinapima vitu tofauti. Usajili (TIN) ni orodha inayoongezeka tu — mara chache TIN hufutwa hata kama biashara imefungwa au mtu hajalipa kodi kwa miaka. "Active" ni kipimo cha wale wanaofanya malipo na kuwasilisha taarifa kwa wakati fulani — na hapa ndipo tatizo halisi la kupungua kwa msingi wa kodi linapoonekana. Licha ya hali hii, TRA imeendelea kuvunja rekodi za makusanyo — Sh trilioni 32.26 (2024/25) na Sh trilioni 37.95 (2025/26) — kwa sababu ukuaji mkubwa wa mapato unatokana zaidi na walipa kodi wakubwa na forodha, si ongezeko la walipa kodi wadogo wanaofanya kazi kikamilifu.
- Walipa kodi waliosajiliwa (TIN): zaidi ya milioni 8.1 (2026), kutoka 70,000 (1996)
- Walipa kodi "active": milioni 2.18 (2024/25), kutoka milioni 3.36 (2021/22) — punguzo la takribani asilimia 35
- Asilimia 88 ya wafanyabiashara wenye TIN hawajasajiliwa kutumia EFD (Julai 2024, Ripoti ya CAG)
- Ni asilimia 30 tu ya biashara binafsi zilizosajiliwa rasmi TRA, licha ya asilimia 70 kuwa za watu binafsi
Vyanzo: Wizara ya Fedha, Ripoti ya Takwimu za Kodi ya NBS, TRA, na Mdhibiti na Mkaguzi Mkuu wa Hesabu za Serikali (CAG). Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI).
01 — OverviewExecutive Summary
In the quarter ending June 2026, Tanzania's mobile money accounts grew 7.5% to 87.05 million — more active wallets than Tanzania has adults — and processed over 2.1 billion transactions, up 5.38% on the prior quarter. That scale, reached in barely a decade since mobile money's launch, now rivals or exceeds the customer reach of the entire formal banking sector by transaction count and active-user footprint, even though banks still hold more total assets and issue the bulk of formal credit.
This report asks a direct question: as mobile money keeps growing faster than bank account penetration, is it complementing Tanzania's banking sector — feeding it new customers and float — or substituting for it, pulling everyday cash flow away from deposit accounts banks rely on to fund lending? The answer, based on TCRA's own data, is: both, and the balance between the two is now one of the more consequential open questions in Tanzania's financial-sector policy.
- Mobile money's transaction growth is real but decelerating — from 21.6% quarter-on-quarter growth in late 2025 to 5.38% now, signalling a shift from an acquisition phase to a maturity phase.
- Three providers control 89% of accounts — M-Pesa, Mixx by Yas and Airtel Money — concentrating both commercial power and systemic risk in a handful of telecom-linked platforms.
- Fraud attempts fell 25.3% quarter-on-quarter even as volumes rose, a sign the payment rails underpinning this growth are becoming more trustworthy, not less.
- The rest of the telecom sector — cheap data, expanding 4G, near-universal mobile coverage — is the infrastructure that made this possible, and continues to expand it.
Companion analysis
This piece complements TICGL's Is Tanzania's Economy Growing?, which examines the macro numbers behind Tanzania's growth story. Read the two together for the full picture of how digital finance connects to headline GDP growth.
02 — The DataMobile Money in Numbers: Accounts, Transactions, Providers
87.05M active accounts
2.10B transactions this quarter
89% held by 3 providers
22.9% 4-yr account CAGR
Tanzania's mobile money ecosystem processed 2,098,706,145 transactions in the quarter ending June 2026, through 87.05 million active accounts — up from 80.98 million just three months earlier. For a population of roughly 68–69 million, this means the average adult effectively holds more than one active mobile money wallet.
Mobile Money Accounts by Provider
Share of 87.05 million active accounts, June 2026
Mobile Money Transactions by Provider
Share of June 2026 transactions
Mobile Money Accounts — Quarterly Trend
Active accounts, September 2025 – June 2026 (millions)
Mobile Money Transaction Growth Rate
Quarter-on-quarter transaction growth, June 2025 – June 2026 (%)
Mobile Money: Five-Year Account Growth
Active accounts by year, 2021–2025 (millions)
Mobile Money: Five-Year Transaction Volume
Total transactions by year, 2021–2025 (billions)
The five-year picture explains why this matters for banking. Active mobile money accounts grew from 35.29 million in 2021 to 76.47 million in 2025 — a compound annual growth rate of roughly 22.9% — while annual transaction volumes grew from 3.75 billion to 6.31 billion, a CAGR of about 13.8%. But look closely at the growth-rate chart: quarter-on-quarter transaction growth has decelerated sharply, from 21.60% (Sep 2025) to 9.40% (Dec 2025), 7.40% (Mar 2026) and now 5.38% (Jun 2026) — the classic signature of a market shifting from acquiring new users to deepening usage among existing ones. That shift is exactly where the mobile-money-vs-banking question becomes sharpest: what do 87 million wallet-holders do next — keep transacting only in mobile money, or graduate into savings, credit and insurance products that connect them to the formal financial system?
03 — The Core QuestionMobile Money vs Banks: Who's Really Winning Tanzania's Wallet?
Tanzania's central bank and commercial banking system do not publish transaction-level statistics inside TCRA's communications report, so a precise, apples-to-apples comparison isn't possible from this dataset alone. What TCRA's numbers do make clear is the order of magnitude gap in reach and transaction frequency between the two systems — and that gap is the real story.
📱 Mobile Money
- 87.05 million active accounts (used in the last 90 days)
- 2.1 billion+ transactions in one quarter (roughly 23 million transactions per day)
- Accessible via any basic phone — no minimum balance, no branch visit, no ID-heavy onboarding
- Near-universal reach: 167% telephone penetration, mobile money agents in almost every ward
- Growth rate: transactions still expanding, but decelerating (5.38% QoQ, down from 21.6%)
VS
🏦 Formal Banking
- Bank account penetration remains a fraction of mobile money's reach, concentrated in urban centres
- Physical branch and agent-banking footprint far smaller than mobile money's agent network
- Requires documentation, and often a minimum balance, to open and maintain an account
- Holds the bulk of formal savings, term deposits and long-term credit — mobile money largely does not replace this function
- Increasingly linked to mobile money via bank-to-wallet transfers, but interoperability is still maturing
Reading the comparison correctly
Mobile money and banks are not fighting over exactly the same product. Mobile money dominates payments and transfers — the high-frequency, low-value transactions that make up most people's day-to-day financial life. Banks still dominate savings mobilisation, term deposits and formal credit — the lower-frequency, higher-value functions that fund investment and business lending. The risk is not that mobile money "replaces" banking outright, but that it captures and holds liquidity that would otherwise flow into bank deposits, without that liquidity being efficiently recycled back into the formal credit system.
Illustrative: Transaction Frequency, Mobile Money vs a Typical Bank Account
Indicative comparison based on TCRA transaction data and typical retail-banking transaction patterns — illustrative, not an official Bank of Tanzania statistic
This chart is illustrative: TCRA does not publish comparable bank-transaction-frequency data in this report, so the "typical bank account" bar reflects general retail-banking usage patterns rather than an official Bank of Tanzania figure. It is included to visualise the scale gap in transaction frequency, not transaction value — banks still process far higher-value transactions on average.
Where mobile money may be squeezing banks
- Deposit disintermediation: wages, remittances and trading proceeds increasingly settle in e-wallets rather than bank current/savings accounts, shrinking the low-cost deposit base banks use to fund lending.
- Float sitting outside formal credit markets: unless mobile money trust-account float is efficiently swept into interest-bearing, lendable bank deposits, large sums of liquidity can sit idle relative to their productive potential.
- Concentration risk: 89% of accounts sit with three private telecom-linked providers — an operational failure at any one of them would have near-systemic effects on household liquidity.
- Weaker monetary-policy transmission: the more money that moves through e-wallets rather than the banking system, the harder it becomes for interest-rate policy to reach households and small businesses quickly.
Where mobile money may be building banks
- A ready-made customer funnel: 87 million verified, transacting mobile money users are a natural pipeline for banks and fintechs to convert into savings, micro-credit and insurance customers.
- A built-in credit-scoring dataset: transaction histories from mobile money are already used by several Tanzanian lenders to underwrite micro-loans for people with no formal credit history.
- Falling fraud, rising trust: a 25.3% drop in fraud attempts this quarter, even as volumes rose, is precisely the kind of trust-building that makes people comfortable moving larger balances and formal products onto digital rails.
- Bank-linked wallets already exist: several banks now offer direct mobile-money-to-bank transfers and savings products, meaning growth in mobile money usage can translate into growth in linked bank products if interoperability keeps improving.
04 — TICGL ViewImplications for Tanzania's Financial Sector
On balance, TICGL reads this quarter's data as a net positive for financial inclusion, but one that raises the urgency of specific policy and industry actions to make sure mobile money's growth strengthens, rather than substitutes for, formal financial deepening.
For regulators (BOT & TCRA)
Treat mobile money interoperability, trust-account transparency and outage resilience as macro-financial policy, not just telecom policy. With 89% of 87 million accounts concentrated in three providers, this is now systemically important payments infrastructure that deserves banking-grade prudential oversight alongside TCRA's technical regulation.
For commercial banks
The addressable market is not shrinking — it is moving. Banks that build genuinely seamless wallet-to-account products, mobile-money-based credit scoring, and low-friction savings sweeps stand to convert mobile money's 87 million users into deposit and credit customers rather than losing them to the informal float economy.
For investors & fintechs
With account-acquisition growth decelerating (5.38% QoQ, down from 21.6%), the next wave of value creation sits in merchant payments, embedded credit, savings products and cross-border remittances layered on top of the existing mobile money base — not in signing up more wallet-holders.
For a broader view of how financial-sector deepening fits into the wider debate on Tanzania's growth trajectory and the policy gaps standing between the country and its US$1 trillion, US$7,000-per-capita 2050 ambition, see TICGL's dedicated analysis linked above and in the related reading section below.
05 — Supporting DataFull Communications Sector Dashboard
Mobile money doesn't grow in isolation — it rides on the back of Tanzania's broader telecom expansion. The table below sets the mobile money numbers in the context of the full sector, quarter ending June 2026 vs March 2026.
Mobile + fixed lines
117.0M
+4.51% QoQ, 167.0% penetration
Internet subscriptions
62.79M
+6.48% QoQ, 89.7% penetration
Smartphones in use
31.34M
+5.16% QoQ — 44.7% penetration
Data consumed (quarter)
1,041 PB
+11.65% QoQ
06 — Supporting DataThe Connectivity Behind the Mobile Money Boom
Mobile money's growth is only possible because of cheap, widely available mobile data and near-universal phone ownership. In June 2026, the average in-bundle data tariff across all five mobile operators was TZS 2.05 per MB (roughly US$0.81 per GB) — cheap enough to place Tanzania among Africa's more affordable data markets and under the global "1-for-2" affordability benchmark (data costing 2% or less of average monthly income). Out-of-bundle pricing, at TZS 9.35 per MB (roughly US$3.68/GB), remains far more expensive and disproportionately affects casual, lower-income users — often the same users most dependent on mobile money precisely because they lack a bank account.
Mobile & Internet Subscriptions: Trend
Total mobile+fixed lines and internet subscriptions, quarterly (millions)
Smartphone vs Basic Phone Penetration
June 2026 — the device gap behind uneven mobile money usage patterns
Notably, only 44.7% of the population owns a smartphone, while mobile penetration overall (including basic/feature phones) is 83.4% — a reminder that most mobile money transactions in Tanzania still happen over USSD on basic handsets, not banking apps. This is precisely why mobile money has outpaced formal banking in reach: it was built to work on the cheapest, most widely owned device in the country.
Infrastructure headroom
Tanzania's international internet gateway capacity stands at 17,690 Gbps, of which only 15.4% is in use — leaving 84.6% spare capacity. Average mobile download speed across 22 measured locations is 14.26 Mbps, with average latency of 76.79ms. 5G population coverage reached 34.18%, but geographic coverage is only 11.34% of Tanzania's land area — meaning both connectivity and mobile-money agent networks remain concentrated where people already live, not evenly across the country.
07 — Supporting DataTrust in the System: Fraud & Network Reliability
Trust is the currency mobile money runs on — and this quarter's data is encouraging. Reported fraud attempts fell 25.3% quarter-on-quarter to 7,334 cases, even as transaction volumes rose. Network quality-of-service compliance averaged 96.6% across operators, with TTCL (98.1%) leading and Halotel (94.5%) trailing.
Fraud Attempts: Quarterly Trend
Total reported fraud attempts across all operators
Fraud Attempts by Region
June 2026 quarter, top 8 regions by volume
Rukwa (2,495) and Morogoro (2,129) recorded by far the highest fraud-attempt counts nationally — together over 63% of all reported cases — concentrated in specific districts (Sumbawanga, Rukwa; and Kilombero, Morogoro), useful intelligence for both operators' fraud teams and financial-sector regulators monitoring emerging risk hotspots.
08 — Supporting DataBroadcasting & Postal: Brief Context
Broadcasting
Paid decoder subscriptions rose 8.18% to 2.26 million, with satellite (DTH) now 75.8% of decoders versus 24.2% terrestrial (DTT). Cable TV connections fell 8.18% to 16,347 as households migrate to satellite and streaming. All monitored TV and radio broadcasters met the 60% local-content quota, though only 38% of TV channels fully adhered to their submitted programme schedules.
Postal & Courier
Domestic mail volumes softened (-9.9% sent, -1.6% received) as digital channels substitute for physical mail, while cross-border parcel volumes surged (+40.8% sent, +52.2% received) — a clear signature of rising cross-border e-commerce, itself increasingly paid for via mobile money.
09 — TICGL ViewOutlook: A Fork in the Road for Tanzania's Financial System
Tanzania's mobile money sector has already answered the "access" question — nearly every adult with a phone can now transact digitally. The question this data leaves open is a "depth" question: will the 87 million active wallets, and the transaction data they generate, become the foundation for deeper formal savings, credit and insurance markets — or will they remain a parallel, largely self-contained payments economy that banks struggle to fully connect to? The direction of travel over the next few quarters — interoperability rules, bank-fintech partnerships, and how effectively e-money float is channelled into the formal credit system — will determine which path Tanzania takes, with direct consequences for the depth and resilience of its financial sector, and by extension its Dira 2050 growth ambitions.
10 — Quick AnswersFrequently Asked Questions
Is mobile money bigger than banking in Tanzania?
By transaction count and active-user reach, yes — 87.05 million active accounts processed over 2.1 billion transactions in the quarter ending June 2026, a footprint far exceeding Tanzania's commercial bank account base. By total assets held and formal credit issued, banks remain larger.
How many mobile money accounts does Tanzania have in 2026?
87.05 million active accounts as of June 2026, up 7.5% from 80.98 million in March 2026. M-Pesa, Mixx by Yas and Airtel Money together hold about 89% of the market.
Does mobile money growth hurt bank deposits in Tanzania?
It creates a structural risk of deposit disintermediation if e-money float isn't efficiently channelled back into the formal banking system through trust-account arrangements. As more routine cash flow settles in mobile wallets, banks can see slower deposit growth unless interoperability with banks is strong.
Is mobile money transaction growth slowing down in Tanzania?
Yes — quarter-on-quarter transaction growth decelerated from 21.6% in September 2025 to 5.38% in June 2026, signalling the market is moving from rapid account acquisition to a more mature, usage-intensity phase.
11 — MethodologySources & Notes
- Primary data: Tanzania Communications Regulatory Authority (TCRA), Ripoti ya Hali ya Sekta ya Mawasiliano — Robo Mwaka Inayoishia Juni 2026 ("State of the Communications Sector Report, Quarter Ending June 2026").
- The "mobile money vs bank" transaction-frequency comparison chart is TICGL's own illustrative estimate, clearly labelled, since TCRA's report does not include comparable bank-transaction statistics.
- USD conversions use an indicative exchange rate of approximately TZS 2,600 = US$1 (August 2026).
- This page is an independent analytical summary prepared by TICGL/TERI and does not constitute financial, investment or legal advice.
MuhtasariMuhtasari kwa Kiswahili
Je, Pesa Mtandao Inazidi Mabenki Tanzania? Katika robo mwaka iliyoisha Juni 2026, akaunti za pesa mtandao ziliongezeka kwa asilimia 7.5 kufikia milioni 87.05 — idadi kubwa kuliko watu wazima wote nchini — na kufanya miamala zaidi ya bilioni 2.1 ndani ya robo moja tu. Kasi hii ni kubwa kuliko ukuaji wa akaunti za benki za kawaida, jambo linaloibua swali muhimu: je, pesa mtandao inasaidia kukuza mfumo rasmi wa kifedha, au inauondolea mabenki fedha ambazo zingeweza kuwa amana za benki?
Uchambuzi wa TICGL unaonesha kuwa jambo hili lina pande mbili. Kwa upande mmoja, pesa mtandao imefanikisha ujumuishaji mkubwa wa kifedha (financial inclusion) kwa kasi ambayo mabenki ya kawaida hayajawahi kufikia — watu wengi wanaweza kutuma, kupokea na kuhifadhi fedha bila kuhitaji akaunti ya benki. Kwa upande mwingine, fedha nyingi zinazopita kwenye mitandao ya simu badala ya mabenki zinaweza kupunguza amana (deposits) ambazo mabenki hutegemea kutoa mikopo, hasa ikiwa hakuna muunganiko mzuri (interoperability) kati ya mifumo ya pesa mtandao na mabenki. Watoa huduma watatu — M-Pesa, Mixx by Yas na Airtel Money — wanamiliki asilimia 89 ya soko, hali inayoongeza umuhimu wa usimamizi imara wa Benki Kuu (BOT) na TCRA katika eneo hili.
- Akaunti za pesa mtandao: milioni 87.05 (ongezeko la asilimia 7.5)
- Miamala ya robo mwaka: zaidi ya bilioni 2.1 (ongezeko la asilimia 5.38)
- Watoa huduma watatu wanamiliki asilimia 89 ya soko
- Majaribio ya ulaghai yalipungua kwa asilimia 25.3 — ishara ya kuimarika kwa uaminifu wa mfumo
Chanzo: TCRA, Ripoti ya Hali ya Sekta ya Mawasiliano, Robo Mwaka Inayoishia Juni 2026. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI).
