Who bears the daily cost of unplanned urban growth in Dar es Salaam?

The cost splits roughly evenly. About TZS 2.9 to 3.3 billion per day falls directly on government through infrastructure retrofit spending and foregone tax revenue from untaxed informal economic activity. A further TZS 3.0 to 3.3 billion per day is absorbed by households, businesses, and the wider city economy through flood-related property damage and disrupted commerce.

Which items got cheaper and which got more expensive in Tanzania in July 2026?

Food staples fell in price month-on-month, including rice, maize grains, maize flour, sweet potatoes, cassava, dried beans and cowpeas. Non-food items that rose included charcoal, diesel, petrol, gas, and clothing materials, pointing to energy costs as the main upward pressure in the month.

How is dollarization connected to market segmentation in Tanzania?

BOT's own Theme 1.3 KPI shows a spread of TZS 57 in the Interbank Foreign Exchange Market (IFEM), which the Plan targets to narrow to TZS 20 or less. A wide, persistent spread between shilling liquidity (IBCM) and foreign-currency liquidity (IFEM) signals inefficient movement of funds between banks, which raises the cost of both shilling and dollar credit and reinforces incentives to hold and lend in dollars.

Why is the number of active taxpayers falling while total registrations rise?

Registration is a cumulative stock — once issued, a Taxpayer Identification Number is rarely removed even if the holder stops filing, closes a business, or never becomes fully compliant. 'Active' status is a flow, measuring who is actually filing and paying in a specific period. A taxpayer can hold a valid TIN for years while being inactive, so the stock keeps growing even as the active flow shrinks.

Is TRA still collecting more tax revenue despite fewer active taxpayers?

Yes. TRA collected TZS 32.26 trillion in 2024/25 (103 percent of target, up 16.7 percent year-on-year) and TZS 37.95 trillion in 2025/26 (105 percent of target), even as the reported active-taxpayer count fell. This is possible because revenue growth has been driven disproportionately by large taxpayers, customs, and digital administration gains rather than by growth in the number of small, active filers.

What does the report recommend to reconcile Tanzania's tax-policy targets?

The report's six recommendations include reconciling the LTPP's 25 percent and the Presidential Commission's 22 percent tax-to-GDP targets, decoupling MSME formalisation from the domestic-revenue agenda, diagnosing the taxpayer-base contraction, applying lessons from the 2021 mobile money levy to future digital-tax design, harmonising central and local revenue instruments, and publishing exemption-by-exemption cost-benefit data.

What is Dira 2050 and what is its economic target for Tanzania?

Dira 2050 is Tanzania's Long-Term Perspective Plan (LTPP) 2026/27–2050/51, which sets out an ambition to become an Upper Middle-Income Country with a one-trillion-dollar economy and a per-capita GNI of at least USD 7,000 by 2050.

How large is Tanzania's informal sector under Dira 2050's own figures?

As of 2023, the informal sector contributed an estimated 55 percent of GDP and absorbed roughly 72 percent of the workforce (about 25.95 million people) according to TICGL's 2024 estimate, though cited estimates range as high as 80 percent of the workforce. Without intervention, the LTPP itself projects informality could rise to 58.5 percent of GDP by 2050.

What is the gap between Tanzania's perceived and formally recognised middle class?

About 12 percent of Tanzanians self-identify as middle-income, but fewer than 3 percent are formally captured as such under internationally comparable consumption-based measures — a gap of roughly nine to one between perception and formal classification.

What are the six Dira 2050 channels for direct citizen economic participation?

The six channels are: formalisation of the informal sector, cooperative transformation, asset-building and middle-class expansion, land and property-rights reform, digital economy and financial inclusion, and decentralised, citizen-led governance.

What is the four-dimensional ownership framework used in this study?

The framework assesses asset ownership, enterprise ownership, income and social-protection ownership, and voice and governance ownership — distinguishing procedural participation (being registered or enrolled) from substantive ownership (holding, controlling, and benefiting from an asset, enterprise, income stream, or decision).

Which Dira 2050 channel rates strongest on ownership, and which rates weakest?

Land and property-rights reform is the only channel rated Strong on any ownership dimension (asset ownership). Voice and governance ownership rates weakest across every channel except decentralisation itself, meaning no channel currently scores Strong on more than one ownership dimension.

TZS 6–8.5 Billion a Day: Dar es Salaam's Hidden Bill for Unplanned Urban Growth

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.

📌

Read this alongside TICGL's flagship Dira 2050 policy-gaps analysis

Unmanaged urban growth in Dar es Salaam is one of the structural constraints standing between Tanzania and Dira 2050's US$1 trillion, US$7,000-per-capita ambition. See TICGL/TERI's wider assessment of the financing, productivity, and institutional gaps that need closing on the road to 2050.

Read: What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050 →

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.

Table: Population and informal settlement growth, 1982–2026
Year	Informal Settlement Area	Region Population (official)	Metro Population (agglomeration)	Informal Share
1982	~52 km²	n/a (pre-boom)	n/a	~60–70% (est.)
2002	growing	~2.5–3.0 million	~3.4 million	~68%
2012	expanding	~4.4 million	~5.1 million	~70%
2022	~379 km²	5,383,728 (census)	~7.4 million	70–80%+
2026	~400 km²+ (est.)	~5.86 million (est.)	~9.0 million (est.)	~70–75% (est.)

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

Table: Major infrastructure and resilience programmes/events, 2018–2026
Programme / Event	Value	Notes
Retrofitting unplanned settlements	~US$250 million/year	If spread over a 30-year horizon (World Bank)
Citywide Action Plan (upgrading target)	~TZS 1.58 trillion (~US$1.2bn)	Multi-year target covering land, basic services, housing, capacity
Msimbazi Basin Development Project	US$200–260 million	2022–2028, World Bank IDA + Spain + Netherlands co-financing
DMDP — Lower Msimbazi phase	US$120 million	World Bank (US$100m) + FCDO (US$20m)
December 2025 government infrastructure injection	TZS 900 billion	Dar es Salaam roads and bridges, incl. flood-driven bridge works
April 2018 flood event — direct losses	US$101–216 million	Single event; 2–4% of city GDP that year
April 2018 flood event — total losses (incl. indirect)	US$107–228 million	Single event, including indirect economic disruption
Recurring flood-related GDP drag	up to ~2% of city GDP/year	When major flood years are averaged across the cycle

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

Table: Total daily economic cost, split by who bears it
Who Bears the Cost	Daily Order of Magnitude	Components
Direct cost to Government	~TZS 2.9–3.3 billion	Component A + Component C
Cost absorbed by households, businesses & city economy	~TZS 3.0–3.3 billion	Component B
TOTAL — Daily Economic Cost	~TZS 6–8.5 billion (~US$2.3–3.3M)	Sum of both groups; wide uncertainty band

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-Usual

Informality 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 Path

Reforms 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.

Table: Indicative trajectory, 2026–2030 (Region boundary)
Year	Region Population	Informal Share	City GDP	Est. Daily Cost (illustrative)	Key Development
2026	~5.86M	~70–75%	~TZS 38T	~US$0.35–0.4B	Baseline
2027	~6.0M	~72–76%	~TZS 43T	~US$0.4–0.45B	Reform measures begin (IDRAS rollout, metropolitan authority discussions)
2028	~6.2M	~73–77%	~TZS 48T	~US$0.45–0.5B	Msimbazi Basin Project completion; BRT Lines 2 & 3 progress
2029	~6.4M	~73–78%	~TZS 54T	~US$0.5–0.55B	Continued land formalisation; housing deficit still growing
2030	~6.6–7.0M	~70–80% (scenario-dependent)	~TZS 60T+	~US$0.55–0.65B	Divergence point: Reform Path vs. Business-as-Usual

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

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.

📌

Read this alongside TICGL's flagship Dira 2050 policy-gaps analysis

Inflation control is one of the macroeconomic conditions Tanzania needs to hold steady on the road to Dira 2050's US$1 trillion, US$7,000-per-capita ambition. See TICGL/TERI's wider assessment of the financing, productivity and institutional gaps that stand between Tanzania and that target by 2050.

Read: What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050 →

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)

Table: NCPI index and headline inflation rate, July 2025 – July 2026 (2020=100)
Month	NCPI	Annual Inflation Rate (%)
Jul-2025	119.85	3.3
Aug-2025	119.77	3.4
Sep-2025	119.86	3.4
Oct-2025	119.63	3.5
Nov-2025	120.01	3.4
Dec-2025	121.11	3.6
Jan-2026	121.41	3.3
Feb-2026	122.01	3.2
Mar-2026	123.04	3.2
Apr-2026	124.61	4.0
May-2026	124.90	4.2
Jun-2026	125.04	4.0
Jul-2026	124.85	4.2

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

Table: Food items contributing to the July 2026 month-on-month decrease in the NCPI
Item	Month-on-Month Change	Likely Driver
Sweet potatoes	-6.7%	Seasonal harvest supply
Cocoyams	-4.5%	Seasonal harvest supply
Maize flour	-4.3%	Post-harvest maize supply
Rice	-4.2%	Seasonal supply / import flows
Maize grains	-3.6%	Post-harvest maize supply
Flour of cassava	-3.4%	Seasonal harvest supply
Dried cowpeas	-2.1%	Seasonal harvest supply
Sorghum grains	-2.0%	Seasonal harvest supply
Dried beans	-2.0%	Seasonal harvest supply
Vegetables	-1.9%	Seasonal supply
Cassava dry	-1.4%	Seasonal harvest supply
Groundnuts	-1.3%	Seasonal harvest supply
Poultry, live	-1.1%	Supply / feed cost easing
Bread and bakery products	-0.5%	Wheat flour cost pass-through
Wheat flour	-0.3%	Import price / supply

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

Table: Non-food items contributing to the July 2026 month-on-month increase in the NCPI
Item	Month-on-Month Change	Note
Charcoal	+4.5%	Key household cooking fuel, particularly urban low-income households
Diesel	+3.3%	Dominant fuel for freight, public transport and agricultural transport
Petrol	+2.5%	Private and commercial vehicle fuel
Gas	+1.3%	Household cooking fuel, urban middle-income households
Garments for infants	+0.3%	Non-food, non-energy item
Clothing materials	+0.3%	Non-food, non-energy item

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

Table 1: NCPI by main group, July 2026 (2020=100)
Main Group	Weight (%)	Jul-2025	Jun-2026	Jul-2026	M-o-M (%)	Y-o-Y (%)
Food and non-alcoholic beverages	28.2	130.47	136.92	135.79	-0.8	4.1
Alcoholic beverages and tobacco	1.9	112.50	114.49	114.67	0.2	1.9
Clothing and footwear	10.8	114.89	116.42	116.69	0.2	1.6
Housing, water, electricity, gas and other fuels	15.1	118.77	120.74	120.73	0.0	1.6
Furnishings, household equipment & maintenance	7.9	116.31	118.48	118.90	0.4	2.2
Health	2.5	109.63	111.04	111.12	0.1	1.4
Transport	14.1	119.59	135.98	136.11	0.1	13.8
Information and communication	5.4	106.25	107.17	106.90	-0.3	0.6
Recreation, sport and culture	1.6	110.98	111.72	111.72	0.0	0.7
Education services	2.0	112.16	115.18	115.29	0.1	2.8
Restaurants and accommodation services	6.6	117.35	119.56	120.51	0.8	2.7
Insurance and financial services	2.1	102.39	102.61	102.60	0.0	0.2
Personal care, social protection & misc. goods/services	2.1	118.14	122.34	122.21	-0.1	3.4
TOTAL — ALL ITEMS INDEX	100.0	119.85	125.04	124.85	-0.1	4.2

Other Selected Indices

Table: Supplementary index aggregations, July 2026
Index	Weight (%)	Jul-2025	Jun-2026	Jul-2026	M-o-M (%)	Y-o-Y (%)
Core Index	73.9	115.93	120.17	120.44	0.2	3.9
Non-Core Index	26.1	130.98	138.85	137.38	-1.1	4.9
Energy, Fuel and Utilities Index	5.7	132.57	142.83	141.76	-0.8	6.9
Services Index	37.2	112.70	118.72	119.16	0.4	5.7
Goods Index	62.8	124.09	128.78	128.22	-0.4	3.3
Education services & products ancillary to education	4.1	114.34	116.24	116.24	0.0	1.7
All Items Less Food and Non-Alcoholic Beverages	71.8	115.69	120.37	120.56	0.2	4.2

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 Likely

Headline 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 Closely

Transport 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 Probability

Post-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.

Muhtasari

Muhtasari 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.

🎯

Read TICGL's flagship analysis: the policy gaps keeping Tanzania's $1 trillion Dira 2050 ambition out of reach

Dollarization is one piece of a bigger structural puzzle TICGL has been tracking closely given the current state of Tanzania's economy — what would actually need to change in monetary, fiscal, and structural policy for Dira 2050's ambitions to be reached on schedule.

Read: What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050 →

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.

Where it appears	What BOT says	Why it matters
Theme 1 introduction (Macroeconomic Stability)	"…elevated currency in circulation, rising dollarization tendencies and the persistent threat of imported inflation from global geopolitical and trade disruptions continue to prevail."	Placed alongside inflation risk — BOT itself links dollarization to the same imported-inflation channel it is trying to manage with interest rates.
SWOC Analysis — Challenges	"Structural issues such as dollarization, market segmentation, and high borrowing costs persist."	Confirmed as a standing, unresolved structural weakness — not a one-off shock, and grouped with the credit-cost problem it helps cause.
Theme 1.3 KPI — Spread in the IFEM	Baseline TZS 57, target ≤TZS 20 by 2029/30	The clearest numeric proxy in the entire Plan for how disconnected shilling and dollar liquidity currently are between banks.

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

💵 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.

Table: Credit-to-GDP trajectory against the market-segmentation targets it depends on
Indicator	Baseline, 2021/22	2025/26	Target, 2029/30
Credit to private sector, % of GDP	13.2%	22.8%	≥30%
IFEM spread (TZS)	—	57	≤20
Non-traditional debt issuance share	—	0%	≥10%
GDP growth rate	4.5%	6.2%	≥7.2%

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

BOT Initiative	How It Touches Dollarization	Quantified?
Narrow the IFEM spread	Directly targets the clearest proxy for shilling/dollar market segmentation	Yes — TZS 57 → ≤TZS 20
Adopt Financial Market Master Agreements	Standardises interbank trading, supporting deeper, less segmented liquidity markets	Initiative only
Diversify government debt instruments	Builds local-currency investment alternatives that compete with dollar holdings	Yes — 0% → ≥10% non-traditional issuance
Full capital account liberalization	Double-edged — could deepen markets or accelerate currency substitution depending on sequencing	Initiative only
Modernize Government Securities infrastructure	Improves access and liquidity of shilling-denominated instruments	Initiative only
Track a dedicated "dollarization ratio"	Would directly measure the share of deposits/credit in foreign currency	Not present in the Plan

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.

Muhtasari

Muhtasari 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

🌱 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.

Table: Banking-sector buffers, actual (2025/26) vs regulatory minimum
Indicator	Actual, 2025/26	Regulatory Minimum	Headroom	What the headroom means
Liquidity ratio	26.88%	≥20%	+6.88 pts	Banks hold liquid assets well beyond what is needed to meet withdrawal and settlement obligations
Capital adequacy ratio	21.32%	≥14.5%	+6.82 pts	Banks could absorb substantially more loan risk before breaching capital-safety thresholds
Non-performing loan ratio	2.96%	≤5%	-2.04 pts (better than required)	Loan books are unusually clean — a sign banks may be lending conservatively rather than at their true risk-adjusted capacity

⚠ 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

Table: TICGL's classification of BOT's KPIs
Category	Approx. Count	Example KPIs
Stability & protective buffers	9	Core & headline inflation, IBCM rate stability, foreign reserves, capital adequacy, NPL ratio, liquidity ratio, Financial System Stability Index
Institutional capacity building	10	AI Maturity Index, IT Maturity, data-management maturity, risk maturity, ESG integration, employee satisfaction, expenditure coverage ratio
Service quality & inclusion	7	Payment-system availability, TanFiX, % adults with accounts, customer satisfaction, currency durability and stock, climate-guideline compliance
Market-deepening (indirect generation)	3	Spread in the 7-day IBCM rate, spread in the IFEM, share of non-traditional debt issuance
Direct credit generation	1	Credit to the private sector as a percentage of GDP

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.

Muhtasari

Muhtasari 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.

📌

Read this alongside TICGL's flagship Dira 2050 policy-gaps analysis

This report is best read together with TICGL/TERI's wider assessment of the policy gaps standing between Tanzania and Dira 2050's US$1 trillion, US$7,000-per-capita ambition by 2050 — the financing, productivity and institutional gaps that BOT's monetary and financial-stability mandate must help close from the macro side.

Read: What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050 →

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.

Table: BOT thematic areas mapped to national development frameworks
National Framework	Core National Priority	BOT Thematic Area It Feeds
Dira 2050 / Tanzania Vision 2050	Strong, inclusive and competitive economy; human capabilities and social development; environmental integrity and climate resilience	Macroeconomic Stability; Stability of the Financial Sector
FYDP IV 2026/27-2030/31	Re-energising competitiveness and industrialisation for human development	Macroeconomic Stability (credit growth, reserves, market depth)
Zanzibar Development Vision 2050 / ZADEP	Upper-middle-income status via sustainable, inclusive human development; blue economy	Stability of the Financial Sector (inclusion, banking services)
Financial Sector Development Master Plan 2020/21-2029/30	Strengthen science, technology and innovation capacity across production, manufacturing and services	Stability of the Financial Sector
National Financial Inclusion Framework 2023-2028	Broaden access to affordable, quality financial services	Stability of the Financial Sector (inclusion KPIs)
NDC / National Environmental Policy / Climate Change Response Strategy	Climate resilience; ESG principles in supervision and operations; climate-resilient financing	Stability of the Financial Sector (climate objective); Organizational Capacity (ESG, emissions)

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.

04 — The Track RecordHow Did the 2021/22-2025/26 Plan Actually Perform?

Before judging the new Plan's ambition, it helps to see how BOT's previous five-year plan performed against its own targets. The Bank's Corporate Performance Review (Q3 2025/26 data) shows a strong record on macroeconomic and financial-stability metrics, with two notable misses.

Table: Selected KPIs, 2021/22-2025/26 plan — baseline vs target vs actual (Q3 2025/26)
Indicator	Baseline (2021/22)	Target (2025/26)	Actual (Q3 2025/26)	Result
Core inflation	2.1%	3% - 5%	3.4%	Within band ✓
Headline inflation	3.6%	3% - 5%	4.2%	Within band ✓
GDP growth rate	4.5%	≥6%	6.2%	Exceeded ✓
Credit to private sector / GDP	13.2%	≥22%	22.8%	Exceeded ✓
7-day IBCM rate stability	None (n/a)	±200bps of CBR	±200	Met ✓
Months of import cover	6.1	≥4.0	4.7	Met ✓ (but declined)
Capital adequacy ratio	17.20%	≥14.5%	21.32%	Exceeded ✓
Asset quality (NPL ratio)	9.68%	≤5%	2.96%	Exceeded ✓
Liquidity ratio	32.90%	≥20%	26.88%	Met ✓ (but declined)
Payment system reliability	98% (2023/24)	≥98%	99.97%	Exceeded ✓
Financial Inclusion Index	0.69 (2024/25)	≥0.74	0.83	Exceeded ✓
% of adults with bank accounts	60% (2023)	80%	73.80%	Below target ✗
EFT settlement period	T+1	T+0	T+1	Not met ✗
Customer satisfaction, banking & currency services	76%	80%	96.90%	Exceeded ✓
Compliance with BOT climate/sustainability guidelines	31%	40%	40%	Met exactly ✓

⚠ Figures are Q3 2025/26 actuals as reported in BOT's Corporate Performance Review; some Theme 3 (Organizational Capacity) figures in BOT's own summary tables render with partial overlaps and are treated qualitatively rather than quoted precisely in this report.

Previous Plan: Baseline vs Target vs Actual, Core Macro Indicators

GDP growth, credit-to-private-sector, and import cover — 2021/22 baseline vs 2025/26 target vs Q3 2025/26 actual

Inflation: Baseline vs Actual (Q3 2025/26)

Percent — both measures stayed inside the 3-5% target band

Financial Soundness: Baseline vs Actual (Q3 2025/26)

Percent — capital adequacy and NPL ratio, 2021/22 vs Q3 2025/26

The headline takeaway

Of the fifteen indicators tracked here, twelve were met or exceeded, often comfortably. The financial sector's underlying soundness improved sharply — non-performing loans fell from 9.68 percent to 2.96 percent, and total banking assets nearly doubled over the period, according to BOT's own Situation Analysis. That is the strongest evidence in the Plan that BOT can execute what it commits to, and it is the basis on which the new 2029/30 targets should be judged.

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

Table: Theme 1 KPIs — baseline vs 2029/30 target
Objective	KPI	Baseline	Target 2029/30
Monetary Policy Effectiveness	Core inflation rate	2.2%	3% - 5%
Monetary Policy Effectiveness	Headline inflation rate	3.4%	3% - 5%
GDP growth rate	6.2%	≥7.2%
7-day IBCM rate stability	±200 bps	±150 bps of CBR
Credit to private sector / GDP	22.8%	≥30%
Foreign Reserves	Months of import cover	4.7	≥4.0
Foreign Reserves	Foreign investment income	39 bps above SAA target	≥20 bps above SAA target
Domestic Financial Markets	Spread in 7-day IBCM rate	1.6%	≤2%
	Spread in IFEM	TZS 57	≤TZS 20
	Share of non-traditional debt issuance	0%	≥10%

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

Table: Theme 2 KPIs — baseline vs 2029/30 target
Objective	KPI	Baseline	Target 2029/30
Safety, Efficiency, Soundness & Inclusiveness	Capital adequacy ratio	21.32%	≥14.5%
	Asset quality (NPL) ratio	2.96%	≤5%
	Liquidity ratio	26.88%	≥20%
	Financial System Stability Index	0.3	Within ±3
	Availability of Systemically Important Payment Systems	99.97%	99.9%
	Tanzania Financial Inclusion Index (TanFiX)	0.83	≥0.75
	% of adults with transactable accounts	78.3%	87%
Banking & Currency Services	Customer satisfaction level	96.2%	98%
	Currency durability (higher denomination)	2 years	2.4 years
	Currency stock level (unissued)	31 months	≥24 months
Climate Resilience	Compliance with BOT climate/sustainability guidelines	40%	75%

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

Table: Theme 3 KPIs — baseline vs 2029/30 target
Objective	KPI	Baseline	Target 2029/30
Institutional Efficiency	Expenditure coverage ratio	1.9	1
	Strategic Management Maturity Level	Level 3	Level 4
	% achievement of strategic result	81.5%	98%
	AI Maturity Index	1.5	≥3
	IT Maturity Level	Level 3	Level 4
	% employee satisfaction with work environment	78%	90%
Organizational Effectiveness & Sustainability	Risk maturity level	Level 3	Level 5
	Net risk level	Yellow	Green
	% ESG integration	15%	≥50%
	Bank's GHG emissions level	7,594.13 tCO₂e (100%)	4,936.18 tCO₂e (65%)

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.

Table: Discrepancies between BOT's detailed KPI tables and its summary infographic
Indicator	Detailed table (pp. 7-9)	Summary infographic (p. 28)	Implication
GDP growth rate target	≥7.2%	6.0%	A more than one percentage point gap on the Plan's single most-watched macro number
Foreign investment income target	≥20 bps above SAA	10 bps above SAA	Materially different ambition for reserve-management returns
Legal & regulatory compliance target	95%	100%	Minor, but a compliance target should not be ambiguous
Bank's emissions-reduction target	65% of baseline remains (≈35% cut)	≤35% of baseline (≈65% cut)	Nearly doubles the implied ambition depending on which figure is used

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.

Muhtasari

Muhtasari 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.

📌

Read this alongside TICGL's flagship Dira 2050 analysis

This report builds directly on TICGL/TERI's assessment of the policy gaps standing between Tanzania and Dira 2050's US$1 trillion, US$7,000-per-capita ambition by 2050 — including the financing, productivity and institutional gaps that infrastructure and human capital spending must both help close.

Read: What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050 →

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.

Table: Tanzania vs UMIC average, four core human development indicators
Indicator	Tanzania	UMIC Average	Source
Teacher : pupil ratio (primary school)	1 teacher : 50-63 pupils (national average 63:1; some councils such as Kasulu reach 103:1)	1 teacher : 16-24 pupils	World Bank / UNESCO UIS
Government spending per primary pupil	Whole education sector: ~TZS 4.77T (2016/17) to TZS 5.26T (2021/22); no precise per-pupil figure available	Typically 3-5x Tanzania's per-pupil spending	Ministry of Education, Education Policy 2014 (2023 edition)
Doctors per 10,000 people	1.34 (about 1 doctor per 7,460 people)	China 31.1; Brazil 23.6; South Africa 7.9	WHO / World Population Review 2026
Cereal yield (kg per hectare)	1,651 kg/ha (2021)	Brazil 5,003 kg/ha; South Africa 4,562 kg/ha (2024)	World Bank WDI / FAO
Life expectancy at birth	67-68.3 years (2023-25, depending on source)	76.2 years (2023 UMIC average)	World Bank WDI; FYDP IV health sector data
World Bank Human Capital Index Plus (HCI+, out of 325)	133 (Health 37, Education 52, Employment 43)	Sub-Saharan Africa average 126; lower-middle-income average 153; Kenya 171	World Bank Human Capital Project, 2026

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.

Table: Ministerial budget, 2020/21 vs 2026/27 (TZS)
Ministry	2020/21	2026/27	Growth
Agriculture (Kilimo)	TZS 229.8 billion	Not yet fully announced at time of writing (trend: 2024/25 = TZS 1.249T; 2025/26 = TZS 1.242T)	More than 5x, 2020/21-2025/26
Health (Afya)	~TZS 650 billion (Budget Committee report, June 2020)	TZS 1.8 trillion	~2.8x
Education (Ministry / Fungu 46 only)	Not precisely available; whole education sector ~TZS 4.77-5.0T (2016/17-2021/22)	TZS 2.398 trillion (Ministry only; excludes TAMISEMI funding for primary/secondary schools)	Figures are not directly comparable — see note
Water (Maji)	Not precisely available (2021/22 was TZS 680.3 billion)	TZS 1.12 trillion	~65-85%, plus +33% just since 2025/26 (TZS 898bn → 1.12T)

⚠ 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)

2020/21

Low 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.

2022/23-2024/25

Agriculture 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.

2025/26-2026/27

Health 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.

2026/27

FYDP 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

🏥 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)

Table: Infrastructure vs human capital, grouped totals
Group	Ministry	2020/21	2026/27	Growth
Infrastructure	Construction, Works & Communications (combined ministry in 2020/21)	TZS 4.9T	Construction (~2.3-2.5T) + Transport (2.872T) ≈ TZS 5.2-5.4T	Modest / gradual
	Energy	TZS 2.19T	TZS 2.525T	+15%
	Infrastructure Total	All infrastructure ministries	≈ TZS 7.09T	≈ TZS 7.7-7.9T	+10-12%
Human Capital	Health	≈ TZS 650bn	TZS 1.8T	+~177%
	Water	≈ TZS 600-680bn	TZS 1.12T	+~65-85%
	Education (Ministry only)	Not available with confidence	TZS 2.398T	—
Human Capital Total (Health+Water, confirmed)	Confirmed subtotal	≈ TZS 1.25T	≈ TZS 2.92T	+~134%

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.

Muhtasari

Muhtasari 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.

📌

Read this alongside TICGL's full tax-policy study

This piece is a deep dive into one finding from TICGL/TERI's August 2026 report on tax policy under Dira 2050 — which asks whether MSME formalisation can realistically fund Tanzania's US$1 trillion ambition, or whether formalisation and domestic-revenue mobilisation need to be pursued as two separate jobs.

Read: The Price of Formalisation — Tax Policy, MSME Growth & Domestic Revenue under Dira 2050 →

Companion analysis

For the wider structural picture, see What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050, which sets the domestic-revenue question in the context of Tanzania's full Dira 2050 financing gap.

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

✅ "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.

Table: Reported active taxpayer figures and their sources
Period	Active Taxpayers	Source / Citation
2021/22	3.36 million	Cited by the Vice President, April 2025 (as the base year for comparison)
2024 (calendar year)	2.82 million	Vice President's remarks, reported April 2025
2024/25 (fiscal year)	2.18 million	Ministry of Finance data, cited in TICGL/TERI's August 2026 tax-policy report
Change, 2021/22 → 2024/25	-35% approx.	Consistent downward direction across both citations

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)

Table: Total registered taxpayers by fiscal year
Fiscal Year	Registered Taxpayers	YoY Change
2017/18	2,739,000	—
2018/19	2,917,000	+6.5%
2019/20	3,181,000	+9.1%
2020/21	4,107,000	+29.1%
2021/22	4,455,000	+8.5%
2022/23	5,494,000	+23.3%
2023/24	6,272,000	+14.2%
~Dec 2025	~7.7 million	continuing rise
Mid-2026	8.1 million+	TRA 30th-anniversary milestone

~1996

TRA established

Roughly 70,000 taxpayers on record, annual collections around TZS 207 billion.

2017/18–2023/24

NBS-tracked expansion

Register more than doubles, from 2.74 million to 6.27 million, driven by successive registration and formalisation drives.

2021/22–2024/25

The 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-2026

Register 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.

08 — Supporting DataThe Informality Gap Behind the Numbers

Underneath both the register and the active count sits Tanzania's large informal sector, estimated at 45–55 percent of GDP and 70–76 percent of the workforce depending on the source and year. The Tanzania Private Sector Foundation has noted that while roughly 70 percent of businesses in Tanzania are privately owned, only about 30 percent are formally registered with TRA — a gap that helps explain why a growing TIN register does not automatically translate into a growing active, revenue-contributing base.

EFD Compliance Among Business TIN Holders

As of July 2024, per the Controller and Auditor General's April 2025 audit

Formal vs Informal Business Registration

Share of privately owned businesses formally registered with TRA

The CAG's audit found that of 2,056,723 traders holding a business TIN as of July 2024, 1,813,385 — about 88 percent — were not registered to use Electronic Fiscal Devices, despite EFDs being central to VAT compliance and receipt-based revenue verification. TRA management noted that EFD use is not mandatory for all traders due to turnover- and nature-of-business exemptions, but the audit also found TRA's own information systems could not clearly identify which non-EFD traders were actually exempt versus simply non-compliant — a gap in the very administrative data needed to convert "registered" into reliably "active."

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.

Muhtasari

Muhtasari 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.

📌

Before you go further — the bigger picture

Financial inclusion, domestic revenue mobilisation and the depth of Tanzania's formal financial system — all touched on below — sit at the centre of a bigger question TICGL has been tracking: the policy gaps standing between Tanzania's current growth path and its Dira 2050, US$1 trillion ambition.

Read: What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050 →

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

Table: Mobile money accounts by provider, April–June 2026
Provider	April	May	June	Share (June)
M-Pesa (Vodacom)	32,840,183	34,394,537	35,313,186	40.6%
Mixx by Yas	25,928,787	26,882,220	27,853,189	32.0%
Airtel Money	14,164,833	14,331,645	14,307,193	16.4%
HaloPesa	7,932,463	8,473,702	8,796,709	10.1%
T-Pesa (TTCL)	596,453	631,098	686,101	0.8%
Azam Pesa	81,829	106,957	89,711	0.1%
Total	81,544,548	84,820,159	87,046,089	100%

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%)

🏦 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

Table: Tanzania communications sector headline indicators
Indicator	Mar 2026	Jun 2026	Change
Mobile + fixed telephone lines	111.9M	117.0M	+4.51%
Telephone penetration	159.8%	167.0%	+7.2pp
Internet subscriptions	58.97M	62.79M	+6.48%
Data consumed (quarter)	932 PB	1,041 PB	+11.65%
National voice minutes	45.44B	48.82B	+7.44%
Domestic SMS	55.10B	55.05B	-0.05%
Mobile money active accounts	80.98M	87.05M	+7.5%
Mobile money transactions (quarter)	1,991,494,385	2,098,706,145	+5.38%
Paid decoders (DTH+DTT)	2.09M	2.26M	+8.18%
Fraud attempts reported	9,816	7,334	-25.3%
Active telecom licences	—	1,881	n/a

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.

Muhtasari

Muhtasari 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).

Executive Summary

This study examined the tax-policy instruments through which Tanzania's Dira 2050 and its Long-Term Perspective Plan (LTPP) 2026/27–2050/51 intend to fund the country's USD 1 trillion economic ambition while simultaneously formalising an informal sector that contributes an estimated 55 percent of GDP. It asks a narrow but consequential question: are the tax measures aimed at Micro, Small and Medium Enterprises (MSMEs) — the same measures meant to move citizens from survival to ownership — capable of generating the domestic revenue Dira 2050 needs, or are they being asked to do a fiscal job they cannot realistically perform while imposing a real compliance cost on the citizens formalisation is meant to benefit?

The study finds that Tanzania's tax-to-GDP ratio, at approximately 12.9–13.1 percent, remains well below the Sub-Saharan Africa average of 15–18 percent, and that two official processes currently set different 2050 targets for closing that gap: the LTPP targets 25 percent, while the Presidential Commission on Tax Reforms, which submitted 284 recommendations to the President in March 2026, targets 22 percent. Compounding this, Tanzania's own active taxpayer registry contracted from 3.3 million in 2021/22 to 2.18 million in 2024/25 even as formalisation campaigns continued, and comparative evidence from Kenya and Uganda shows that presumptive and turnover-tax regimes aimed at the smallest enterprises typically raise negligible direct revenue relative to the compliance burden they impose.

Applying a four-dimensional tax-policy framework — revenue yield, compliance burden, formalisation incentive, and equity — to six tax channels under Dira 2050, the study finds that no channel currently rates strongly on both revenue yield and compliance burden simultaneously: the instruments capable of raising material new revenue (exemption rationalisation, large-taxpayer administration) are largely separate from the instruments aimed at MSMEs and formalisation. Tanzania's own 2021 mobile money transaction levy, which cut peer-to-peer transaction volumes by roughly 38 percent within three months before being repeatedly reduced and then largely scrapped, stands as a directly relevant domestic precedent for the risks of miscalibrated digital taxation that Dira 2050's own digital-tax provisions do not reference.

The report concludes with six recommendations centred on reconciling the two conflicting tax-to-GDP targets, decoupling the MSME formalisation agenda from the domestic-revenue agenda, and applying the lessons of Tanzania's own mobile money levy episode to future digital-tax design.

Related TICGL Analysis

What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050

This tax-policy study is one part of a wider structural picture. Read TICGL's flagship analysis of the policy gaps standing between Tanzania and its Dira 2050 ambition — including the financing, institutional, and investment-climate gaps that sit alongside the tax questions raised here.

Read the Full Policy Gap Analysis →

1. Background and Context

Dira 2050 requires financing on a scale far beyond anything Tanzania has previously mobilised: the LTPP estimates investment needs rising from USD 183 billion under the fourth Five-Year Development Plan to USD 1.58 trillion under the eighth, with total investment averaging more than 35 percent of GDP annually. Of this, the LTPP projects that domestic revenue, including tax collection, will cover only around 22 percent of financing needs, with foreign direct investment expected to mobilise roughly 57 percent and the domestic private sector the remaining 21 percent.

How Dira 2050's USD 1.58 Trillion Investment Need Is Expected to Be Financed

Source: LTPP 2026/27–2050/51 financing projections, as reported in the study.

The LTPP is candid that this gap has been long-standing and structural. Tanzania's tax-to-GDP ratio averaged approximately 12 percent between 2018 and 2024, against a Sub-Saharan Africa average of 16.3 percent, and stood at 12.9 percent in 2024. The Plan attributes this partly to administrative inefficiencies, tax exemptions with limited demonstrated impact on growth, and limited taxation of the informal sector and parts of agriculture — the same informal sector that the companion analysis of Dira 2050's citizen-ownership channels found contributes up to 55 percent of GDP while remaining largely outside the formal tax net.

This creates the specific tension this study investigates. The LTPP's own formalisation agenda proposes to bring millions of informal MSMEs into the tax system through a dedicated TRA support wing, a graduated tax system, and simplified compliance. This report asks the fiscal question directly: even if formalisation succeeds on its own terms, can taxing millions of newly formalised micro-enterprises realistically close a tax-to-GDP gap of 12 to 13 percentage points, or does relying on MSME taxation for that purpose risk imposing a real compliance cost on ordinary citizens for a fiscal return that comparative evidence suggests will be marginal?

1.1 Current Situation: Baseline Snapshot

Before assessing Dira 2050's forward-looking targets, this study establishes the current tax-policy baseline, drawing on the LTPP's own data, the Presidential Commission on Tax Reforms' March 2026 report, and Bank of Tanzania and Ministry of Finance data.

Table 1: Tax-policy baseline across six channels
Channel	Current Situation (Baseline)
MSME & informal-sector taxation	The informal sector contributes an estimated 55 percent of GDP and absorbs roughly 72 percent of the workforce (2023–24), largely outside the tax net. Over four million businesses reportedly remain informal, citing complex tax procedures as a primary barrier.
Fiscal sustainability / tax-to-GDP ratio	Tanzania's tax-to-GDP ratio stood at 12.9 percent in 2024 (13.1 percent by some FY2024/25 measures), against a Sub-Saharan Africa average of 15–18 percent and an EAC average of 12.7 percent. The fiscal deficit has averaged around 3.4–3.5 percent of GDP over the past five years.
Taxpayer base	The number of active registered taxpayers fell from 3.3 million in 2021/22 to 2.18 million in 2024/25, even as formalisation campaigns continued over the same period.
Tax exemptions & incentives	Tax exemptions are estimated to cost Tanzania approximately 2–3 percent of GDP in foregone revenue, with limited demonstrated impact on economic growth, and disparities flagged in how incentives are allocated relative to the 2022 Investment Act's guidelines.
Digital & mobile-money taxation	A mobile money transaction levy introduced in July 2021 cut monthly peer-to-peer transaction volumes by roughly 38 percent within three months; reduced by 30 percent in September 2021, a further 43 percent in July 2022, and largely scrapped for most transfers from October 2022.
Institutional reform	The Presidential Commission on Tax Reforms, established October 2024 and chaired by Ambassador Ombeni Sefue, submitted a report to President Samia Suluhu Hassan on 18 March 2026 with 284 reform proposals, including renaming TRA to the Tanzania Revenue Service and a one-year tax grace period for startups.

2. Diagnostic Findings: The Policy Problem

A close reading of the LTPP alongside the Presidential Commission on Tax Reforms' 2026 report and Tanzania's own recent fiscal history surfaces four structural tensions that this study identifies as the central tax-policy problem for Dira 2050's implementation:

Two unreconciled tax-to-GDP targets. The LTPP sets a target of raising Tanzania's tax-to-GDP ratio from 12.9 percent to at least 25 percent by 2050. The Presidential Commission on Tax Reforms separately sets a target of 22 percent for the same year — two different official benchmarks for the same indicator over the same horizon, with no public reconciliation between the two processes.
A contracting taxpayer base alongside expanding formalisation ambitions. Active registered taxpayers fell from 3.3 million in 2021/22 to 2.18 million in 2024/25 — a decline of roughly a third — during the same period formalisation campaigns and digital tax systems were being expanded.
A revenue-yield-versus-compliance-cost mismatch confirmed by regional evidence. Kenya's turnover tax generated only an estimated 0.002 percent of GDP in 2023 despite the compliance obligations it placed on hundreds of thousands of small traders. Uganda's presumptive tax regime imposes compliance costs averaging around USD 510 per year even on firms filing nil returns, and 68 percent of eligible SMEs remain outside the tax net regardless.
An unreferenced domestic precedent on digital taxation. Tanzania's own 2021 mobile money transaction levy cut monthly peer-to-peer transaction volumes by roughly 38 percent within three months. Despite this direct national experience, the LTPP's digital-tax provisions (targeting e-commerce and digital-trade taxation by 2040) do not reference this precedent.

Left unresolved, these four tensions risk a scenario in which Tanzania succeeds at registering enterprises and improving inclusion — without closing the actual tax-to-GDP gap Dira 2050's financing model depends on.

3. Analytical Framework Applied in This Study

To assess Dira 2050's tax-policy instruments consistently, this study applied a four-dimensional working framework, structuring both the channel-level findings and the synthesis matrix below.

3.1

Revenue Yield

The extent to which an instrument is capable of generating material, measurable domestic revenue relative to Tanzania's financing needs — as distinct from the number of taxpayers registered.

3.2

Compliance Burden

The time, cost, and administrative complexity an instrument imposes on taxpayers, particularly MSMEs — frequently a stronger determinant of formalisation behaviour than the statutory tax rate itself.

3.3

Formalisation Incentive

Whether an instrument's net effect, once compliance burden and support are weighed together, makes voluntary formalisation more or less attractive to an informal operator.

3.4

Equity

Whether the burden of an instrument falls proportionately, or disproportionately, on smaller taxpayers, women-led enterprises, and lower-income citizens.

This framework separates two objectives that Dira 2050's own language sometimes treats as one: formalising the informal sector (a structural, inclusion-oriented goal) and closing the tax-to-GDP gap (a fiscal, revenue-oriented goal).

4. Study Objectives and Scope

Overall objective: to analyse the tax-policy instruments Dira 2050 and the LTPP rely on to formalise Tanzania's informal sector and fund the country's fiscal ambitions, and establish whether these instruments can deliver both objectives simultaneously, or should be sequenced separately.

Mapped and analysed the principal tax-policy instruments: the MSME/TRA graduated tax wing, the tax-to-GDP fiscal target, exemption management, digital tax systems, LGA revenue autonomy, and mining/extractive royalty transparency.
Assessed each instrument against the four-dimensional tax-policy framework.
Benchmarked Tanzania against Kenya's turnover tax, Uganda's presumptive tax regime, and Rwanda's digital tax administration, and against Tanzania's own 2021–2022 mobile money levy episode.
Identified the inconsistency between the LTPP's 25 percent and the Commission's 22 percent tax-to-GDP targets, alongside the taxpayer-base contraction running alongside both.
Developed sequenced tax-policy recommendations separating the formalisation objective from the domestic-revenue objective.

6. Comparative Findings: Lessons from Other Economies

Tanzania is not alone in trying to tax its informal and small-business sector into the formal system while also raising material new domestic revenue. A review of comparable regional and cross-country experience offers concrete, quantified lessons for how Dira 2050's tax instruments are designed.

Table 2: Comparative regional tax-policy experience
Country / Region	Relevant Experience	Key Lesson for Dira 2050
Kenya	Turnover tax on small businesses, introduced 2008 at 3 percent on annual turnover between roughly USD 5,000–50,000, generated an estimated 0.002 percent of GDP in 2023.	Presumptive taxes targeted at the smallest enterprises are unlikely to be a meaningful direct revenue source; evaluate on formalisation outcomes, not revenue.
Uganda	Presumptive tax regime (since 1997) imposes average compliance costs of ~USD 510/year even on nil returns; 68 percent of eligible SMEs remain outside the tax net.	Compliance cost and administrative burden, not the statutory rate, are usually the binding constraint on formalisation.
Rwanda	The Rwanda Revenue Authority's e-Tax online filing, paired with SME-targeted training, is associated with improved compliance and revenue collection.	Digitalisation of tax administration works when paired with active taxpayer education; introduced alone, it risks excluding the least digitally literate operators.
Sub-Saharan Africa	An estimated 65 percent of regional tax authorities operate a simplified or presumptive small-business regime; cross-country reviews find these raise little revenue relative to administrative cost.	Design and evaluate Tanzania's MSME tax wing primarily as an inclusion instrument, with a separate revenue plan.

Tanzania's Tax-to-GDP Ratio vs. Regional Benchmarks and 2050 Targets

Figures in percent of GDP. SSA range shown as reported low–high band; Tanzania 2024 figure and both 2050 targets from the LTPP and the Presidential Commission on Tax Reforms.

Tanzania's Active Taxpayer Registry, 2021/22 vs 2024/25

Source: Ministry of Finance data, as cited in the study. Decline of roughly one-third over three years.

7. Findings: Six Tax-Policy Channels under Dira 2050

Applying the framework in Section 3, this study analysed six tax-policy channels through which Dira 2050 and the LTPP intend to formalise the informal sector and mobilise domestic revenue.

7.1 MSME Tax Wing and the Graduated Tax System

The LTPP proposes a dedicated MSME wing within the TRA offering simplified, digitised tax filing, reduced initial tax burden on newly formalised businesses, and tax credits of up to 30 percent for firms creating 500+ jobs, alongside a national digital MSME database by 2030.

Strength identified

Directly targets the compliance-cost barrier that comparative evidence (Uganda) identifies as the single biggest deterrent to formalisation.

Structural gap / risk

Comparable regimes elsewhere (Kenya's 0.002 percent of GDP) generate negligible direct revenue. If Tanzania's 25 percent target implicitly assumes material MSME revenue, that assumption is not supported by comparative evidence.

7.2 Fiscal Sustainability and the Tax-to-GDP Target

The LTPP targets raising the tax-to-GDP ratio from 12.9 percent to at least 25 percent by 2050, alongside reducing public debt to 40 percent of GDP and containing the fiscal deficit to 1–3 percent of GDP.

Strength identified

Directionally consistent with the Tax Reform Commission's own recommendations; both processes agree administrative inefficiency and informality, not statutory rates, are the primary drags on revenue.

Structural gap / risk

The LTPP's 25 percent and the Commission's 22 percent targets for 2050 are not reconciled in any public document reviewed, risking inconsistent Five-Year Development Plan monitoring.

7.3 Tax Base Erosion: The Shrinking Taxpayer Registry

Active registered taxpayers fell from 3.3 million (2021/22) to 2.18 million (2024/25), even as formalisation campaigns and digital tax systems expanded over the same period.

Strength identified

The trend has been acknowledged publicly by senior finance officials, and the Commission's recommendations (simplified registration, a one-year startup grace period) directly respond to the likely cause.

Structural gap / risk

New formalisation drives risk running in place rather than expanding net registration, unless the causes of the existing contraction are diagnosed first.

7.4 Tax Exemptions and Incentive Rationalisation

Tax exemptions are estimated to cost Tanzania approximately 2–3 percent of GDP in foregone revenue, with the LTPP itself noting limited demonstrated growth impact.

Strength identified

The clearest area of consensus between the LTPP and the Tax Reform Commission, and the single largest identified pool of recoverable revenue without raising any statutory rate on MSMEs.

Structural gap / risk

Incentives tend to be allocated to larger, better-connected investors; rationalisation requires sustained political will that multiple years of similar recommendations have not yet delivered.

7.5 Digital Tax Systems and the Mobile Money Levy Precedent

Tanzania has progressively digitalised tax administration since 2013, and the LTPP plans further digitalisation to curb e-commerce tax evasion by 2040 — while the 2021 mobile money levy remains a cautionary domestic precedent.

Strength identified

Rwanda's experience shows digitalisation paired with taxpayer education can materially improve compliance, and Tanzania's 60+ million mobile money accounts provide a strong platform if designed carefully.

Structural gap / risk

The LTPP's digital-tax provisions do not reference the 2021–2022 levy experience or set out safeguards against repeating a sharp, self-defeating drop in transaction volumes.

7.6 Local Government Revenue Autonomy

The LTPP calls for strengthening LGA revenue collection through enhanced fiscal autonomy, while the Tax Reform Commission separately flags overlapping mandates between central (TRA) and local authorities.

Strength identified

Greater LGA fiscal autonomy is consistent with the decentralised, citizen-led governance channel identified as needing strengthening.

Structural gap / risk

Without first harmonising central and local instruments, expanding LGA revenue risks adding another charge layer on the same small, already-overburdened taxpayer pool.

Tanzania's 2021–2022 Mobile Money Levy: Transaction Volume Recovery Path

Illustrative index (100 = pre-levy baseline volume) built from the reported percentage impacts and reductions at each stage; not a precise monthly series.

8. Summary of Key Findings

Synthesising the channel-level findings against the four-dimensional tax-policy framework produces the matrix below. Ratings reflect this study's assessment: Strong (well evidenced to perform on this dimension), Emerging (directed at this dimension but not yet consolidated), and Weak (does not currently address this dimension, or evidence suggests it is unlikely to).

Table 3: Synthesis matrix — six channels against the four-dimensional framework
Channel	Revenue Yield	Compliance Burden	Formalisation Incentive	Equity
MSME tax wing / graduated tax	Weak	Emerging	Emerging	Emerging
Tax-to-GDP fiscal target	Strong (aspiration)	Weak	Weak	Weak
Taxpayer base erosion response	Weak	Emerging	Weak	Emerging
Exemption rationalisation	Strong (potential)	Emerging	Weak	Emerging
Digital tax systems	Emerging	Emerging	Weak	Weak
LGA revenue autonomy	Emerging	Weak	Weak	Weak

Synthesis Matrix Visualised: Rating Score by Channel and Dimension

Scores: Weak = 1, Emerging = 2, Strong = 3 — a visual translation of Table 3 above.

Two patterns stand out. First, the two channels rated Strong on revenue yield — the headline tax-to-GDP target and exemption rationalisation — are macro-level and administrative in nature, not MSME-focused; no MSME-targeted instrument rates above Weak on revenue yield. Second, no channel rates Strong on compliance burden, meaning the barrier comparative evidence identifies as most decisive for formalisation behaviour is not yet the primary design focus of any Tanzanian tax instrument reviewed.

9. Study Approach

This study is based on a structured desk review of the LTPP's fiscal and formalisation chapters, cross-referenced against the Presidential Commission on Tax Reforms' March 2026 report and recent Ministry of Finance and Bank of Tanzania data, combined with a comparative review of published research and policy analysis on MSME and presumptive taxation in Kenya, Uganda, and Rwanda, and documented reporting on Tanzania's own 2021–2022 mobile money levy episode. The four-dimensional tax-policy framework in Section 3 was applied consistently across all six channels to produce the findings in Section 7 and the synthesis matrix in Section 8.

9.1 Basis of the Findings

Direct textual analysis of the LTPP's fiscal sustainability and informal-sector formalisation chapters and their target tables.
Cross-referencing against the Presidential Commission on Tax Reforms' March 2026 report and contemporaneous news coverage of its recommendations.
Comparative analysis of published research on MSME and presumptive tax regimes in Kenya, Uganda, and Rwanda, and of documented reporting on Tanzania's 2021–2022 mobile money levy.

9.2 Scope and Limitations

This is a desk-based comparative policy analysis; it does not include new primary fieldwork or key-informant interviews with taxpayers, TRA officials, or MSME associations. The ratings in Section 8 are this study's analytical judgement based on the design of the instruments as written and on comparative evidence, not a direct measurement of Tanzanian outcomes on the ground.
Tax-to-GDP figures for Tanzania vary slightly by source and year (12.8–13.7 percent across sources reviewed) depending on methodology and fiscal year; this study reports the range transparently rather than resolving it to a single figure.
The Presidential Commission's 284 recommendations were reviewed through public reporting of the March 2026 submission rather than the full unpublished report; specific recommendation numbering and detail may be refined as the report is formally released and acted upon.

How Does Tax Policy Shape Ordinary Citizens' Direct Participation in Tanzania's Dira 2050?

Dira 2050's promise is not just macroeconomic growth, but that ordinary citizens move from mere survival to genuine economic ownership. Tax policy is one of the six participation channels through which that promise is meant to be delivered — and this study's findings speak directly to it. Formalisation is often presented as the mechanism that pulls an informal trader into the visible, protected economy: once registered, an MSME can, in principle, access credit, legal protection, and market linkages it could not reach informally.

But this study's channel-level findings (Section 7.1) and the companion 'From Survival to Ownership' report both point to the same caution: the MSME tax wing currently rates only Emerging, not Strong, on formalisation incentive — meaning the pathway from informal survival to formal ownership is directed at, but not yet consolidated for, the ordinary citizen it is meant to serve. For a smallholder trader or micro-entrepreneur, direct participation in Dira 2050 through the tax channel currently means facing simplified — but still real — compliance obligations, in exchange for a formalisation and inclusion benefit that is better evidenced than any revenue benefit to the state. Treating that trade-off honestly, rather than assuming formalisation simultaneously solves both the citizen's inclusion problem and the state's revenue problem, is what this study's separation of the two agendas (Recommendation 2) is designed to protect.

10. Contribution of This Study

A diagnostic assessment of the strengths and structural gaps associated with each of the six tax-policy channels under Dira 2050, organised around the four-dimensional revenue–compliance–formalisation–equity framework.
A synthesis matrix (Section 8) showing that Tanzania's MSME-focused tax instruments and its material-revenue instruments are largely distinct, contrary to the LTPP's narrative framing of formalisation as a primary revenue strategy.
Identification of a specific, previously unreconciled inconsistency between the LTPP's 25 percent and the Presidential Commission's 22 percent tax-to-GDP targets for 2050.
A direct link between Tanzania's own 2021–2022 mobile money levy experience and the design safeguards its future digital-tax measures should adopt.

11. Policy Recommendations

Based on the findings above, this study recommends six actions, sequenced by urgency:

12. Recommended Implementation Roadmap

0–12 months

Phase 1: Immediate Corrective Action

Reconcile the 22 percent / 25 percent tax-to-GDP target inconsistency (Recommendation 1); publish an exemption-by-exemption cost-benefit register (Recommendation 6).

Year 1–2

Phase 2: Diagnosis and Safeguard Design

Diagnose the taxpayer-base contraction (Recommendation 3); design a consultation-and-piloting protocol for any new digital or e-commerce tax measure (Recommendation 4).

Year 2–3

Phase 3: Harmonisation and Rollout

Harmonise TRA and LGA revenue instruments (Recommendation 5); roll out the MSME tax wing evaluated on formalisation and inclusion KPIs rather than revenue KPIs (Recommendation 2).

Ongoing from Year 3

Phase 4: Institutionalisation

Embed transparent exemption reporting and pre-agreed levy-adjustment triggers as standing fiscal governance practice.

13. Conclusion

Dira 2050's financing model depends on closing a persistent, decades-long tax-to-GDP gap, and its formalisation agenda offers a genuine route to bring millions of informal MSMEs into a system that can support them with credit, market linkages, and legal protection. This study finds, however, that the same instruments cannot be assumed to deliver both formalisation and material new domestic revenue at once: comparative regional evidence and Tanzania's own recent taxpayer-base trends both indicate that MSME-focused tax measures are, at best, a modest revenue contributor, while the largest realistic domestic-revenue gains lie in exemption rationalisation and administration of the existing tax base. Recognising this distinction — and applying the direct lesson of Tanzania's own 2021–2022 mobile money levy episode to future digital-tax design — would allow the formalisation agenda to proceed on its real strength, citizen inclusion and ownership, without being asked to also close a fiscal gap it is not well suited to closing alone.

Muhtasari kwa Kiswahili

Lengo la utafiti: Utafiti huu unachunguza kama sera za kodi zinazolenga MSME chini ya Dira 2050 zinaweza kufanikisha malengo mawili kwa wakati mmoja — kurasimisha sekta isiyo rasmi na kuongeza mapato ya ndani — au kama malengo hayo yanapaswa kutekelezwa kwa hatua tofauti.

Matokeo makuu: Uwiano wa kodi kwa Pato la Taifa (tax-to-GDP) wa Tanzania ni asilimia 12.9, chini ya wastani wa Afrika Kusini mwa Jangwa la Sahara (asilimia 15–18). Malengo mawili tofauti ya mwaka 2050 yapo — LTPP inalenga asilimia 25, wakati Tume ya Rais ya Marekebisho ya Kodi inalenga asilimia 22 — bila upatanisho rasmi.

Changamoto ya walipa kodi: Idadi ya walipa kodi waliosajiliwa imepungua kutoka milioni 3.3 (2021/22) hadi milioni 2.18 (2024/25), licha ya kampeni za urasimishaji kuendelea.

Fundisho la tozo ya miamala ya simu: Tozo ya mwaka 2021 ilipunguza miamala ya pesa za simu kwa asilimia 38 ndani ya miezi mitatu, ikapunguzwa mara kadhaa, na hatimaye kufutwa kwa kiasi kikubwa 2022 — somo muhimu kwa kodi za kidijitali zijazo.

Mapendekezo: Ripoti inapendekeza hatua sita, zikiwemo kupatanisha malengo mawili ya tax-to-GDP, kutenganisha ajenda ya urasimishaji wa MSME na ajenda ya mapato ya ndani, kuchunguza sababu za kupungua kwa walipa kodi, na kutumia fundisho la tozo ya simu kwenye kodi za kidijitali zijazo.

Related TICGL Research & Tools

What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach Is Tanzania's Economy Growing? Opportunities and Risks Define Doing Business in Tanzania in 2026 Why Tanzania's Economic Growth Has Not Been Sufficiently Inclusive Invest in Tanzania TICGL Dashboard Tanzania Business Intelligence Dashboard Join TICGL as a Researcher

Frequently Asked Questions

Can MSME formalisation alone close Tanzania's tax-to-GDP gap?

No — this study finds no structural reason to expect Tanzania's MSME tax wing to raise material direct revenue, even if it succeeds as a formalisation tool. Comparable regimes in Kenya (0.002 percent of GDP in 2023) show presumptive taxes aimed at the smallest enterprises typically raise negligible revenue relative to the compliance burden they impose.

What is Tanzania's current tax-to-GDP ratio compared to its 2050 target?

Approximately 12.9 percent in 2024, against an LTPP target of 25 percent and a Presidential Commission target of 22 percent for 2050 — two unreconciled official benchmarks.

Why did Tanzania's taxpayer registry shrink between 2021 and 2025?

Active registered taxpayers fell from 3.3 million to 2.18 million, even as formalisation campaigns expanded. Officials have publicly attributed part of this to the overburdening of a small pool of existing taxpayers.

What happened with Tanzania's 2021 mobile money transaction levy?

It cut monthly peer-to-peer transaction volumes by roughly 38 percent within three months, was reduced three times, and was largely scrapped for most transfers by October 2022 following public and legal pushback.

Which tax-policy instruments generate the most realistic domestic revenue?

Exemption rationalisation (worth an estimated 2–3 percent of GDP) and stronger administration of the existing large-taxpayer base — not MSME-focused instruments.

References

United Republic of Tanzania. Long-Term Perspective Plan (LTPP) 2026/27–2050/51: Pathways to Prosperity (Dira 2050).
The Citizen (Tanzania). Tax commission proposes 284 changes to reform Tanzania's tax system, 18 March 2026.
TanzaniaInvest. Presidential Commission Proposes 284 Measures to Overhaul Tanzania Tax System, March 2026.
The EastAfrican. Tanzania tax review warns of trust erosion, proposes sweeping overhaul, March 2026.
PwC Tanzania. Broadening Tanzania's Tax Base (press release).
TICGL. Why Tanzania Must Expand Its Tax Base; Tanzania Tax Revenue, Government Role & Private Sector-Driven Development.
Brookings Institution. Designing Simplified Tax Regimes to Work for Women's Economic Empowerment.
UNU-WIDER Working Paper 2021/163. An Assessment of Presumptive Tax in Uganda.

Channel	Current Situation (Baseline)
Informal sector	Contributes an estimated 55% of GDP (2023) and absorbs roughly 72% of the workforce — about 25.95 million people (TICGL, 2024); other cited estimates range as high as 80% of the workforce. Without intervention, the LTPP projects informality could rise to 58.5% of GDP by 2050.
Cooperatives	A long-established sector across agriculture, fisheries, mining, housing, and finance, but currently constrained by governance inefficiencies, outdated management practices, and limited market-access capacity. Coop Bank Tanzania has only recently been established.
Middle class	About 12% of Tanzanians self-identify as middle-income, but fewer than 3% are formally captured as such under internationally comparable consumption-based measures (2023) — roughly a nine-to-one gap between perception and formal classification.
Land and property rights	Only about 20% of land nationally is surveyed or titled, and only 30% of the population lives in planned settlements. Of Tanzania's 94.5 million hectares of land, 44 million hectares are suitable for agriculture, yet only 24% of that suitable land is currently utilised.
Digital economy & financial inclusion	2023: financial inclusion 76% vs exclusion 24%; formal bank account ownership 22%; mobile money account ownership 72%; broadband coverage 83%; over 67 million mobile subscriptions; 34.5 million internet users; mobile money transactions of roughly TZS 155 trillion (BoT).
Decentralised governance	Local Government Authorities operate with constrained fiscal autonomy and uneven capacity; participatory planning and citizen scorecard mechanisms remain at an early, largely pilot stage rather than a standing national system.

Country / Region	Relevant Experience	Key Lesson for Dira 2050
Rwanda	Long-standing citizen-centred governance built on home-grown participatory instruments (community-based savings, performance contracts, community courts) alongside a UMIC-by-2035 ambition.	Citizen ownership is easier to sustain when anchored in durable, locally owned institutions rather than one-off national campaigns.
South Africa	One of the most significant reductions in non-agricultural informal employment recorded on the continent (2001–2015), through sustained labour-market and social-protection reform.	Formalisation is a multi-decade structural process; Dira 2050's 2030 milestones should be read as intermediate steps, not a stand-alone target year.
Indonesia	Roughly a third of GDP and well over half the workforce remain informal; policy has shifted toward industrialising rural informal activity rather than registration incentives alone.	Formalisation succeeds when paired with productivity-raising investment; incentives alone risk formalising firms that cannot survive the added compliance cost.
Vietnam	Despite steady UMIC-oriented reform, informal employment has remained above two-thirds of the workforce, partly due to very small, low-capacity firms.	A segmented approach is needed: the smallest operators may require social protection and productivity support before formalisation is realistic.
Kenya & Ethiopia	Multiple studies find agricultural cooperative membership raises smallholder income, market bargaining power, and women's economic empowerment.	Cooperative-led ownership models work, but require deliberate design (capacity-building, governance safeguards) so smallholder and women members share proportionally in the gains.

Channel	Asset Ownership	Enterprise Ownership	Income / Social Protection	Voice / Governance
Formalisation of the informal sector	Weak	Emerging	Weak	Weak
Cooperative transformation	Weak	Emerging	Emerging	Emerging
Middle-class / asset-building	Emerging	Weak	Emerging	Weak
Land and property-rights reform	Strong	Weak	Weak	Weak
Digital economy & financial inclusion	Weak	Emerging	Emerging	Weak
Decentralised, citizen-led governance	Weak	Weak	Weak	Emerging

01 — OverviewExecutive Summary

Read this alongside TICGL's flagship Dira 2050 policy-gaps analysis

02 — Key NumbersKey Numbers at a Glance

03 — Section 1The Scale of Informal Settlement in Dar es Salaam

1.1 Two Ways to Count the City — and Why It Matters

Official administrative boundary

Metropolitan / urban agglomeration

Dar es Salaam Population, 2002–2030: Official Region vs. Metropolitan Area

1.2 Spatial Expansion of Unplanned Areas

Informal Settlement Area in Dar es Salaam, 1982 → 2026

1.3 Housing and Tenure

04 — Section 2Why Informality Makes Infrastructure Delivery Harder

2.1 Retrofitting Versus Building Ahead of Settlement

2.2 Service Deficits That Compound Over Time

2.3 Flood-Prone Occupation of Hazardous Land

2.4 The "Build Fast, Open Fast" Problem

05 — Section 3Development and Economic Planning Constraints

3.1 Coordinated Land-Use Planning

3.2 A Narrow Formal Tax Base

3.3 Fragmented Metropolitan Governance

3.4 The National Growth Trade-Off

06 — Section 4Government Infrastructure and Resilience Spending: A 2018–2026 Snapshot

Infrastructure & Flood-Resilience Spending, Selected Programmes (US$ millions)

4.1 What This Buys — and What It Doesn't

07 — Section 5The Daily Economic Cost of Unplanned Urban Growth

Daily Cost by Component (TZS billions/day, midpoint estimate)

5.4 The Headline Number: Total Economic Cost, Split by Who Bears It

Who Bears the Daily Cost?

08 — Section 6Forecast to 2030

Informality drifts at or above today's range

Reforms already identified are implemented on schedule

Indicative Trajectory to 2030: City GDP and Informal Settlement Share

6.3 Indicative Trajectory Table

09 — Section 7Policy Implications

Prioritise retrofit-efficient infrastructure sequencing

Widen the formal land and tax base together

Resolve metropolitan governance fragmentation

Treat flood resilience as core infrastructure

10 — Section 8Data Sources and Methodology Note

Primary Sources

Methodology Note on the Daily Cost Estimate

11 — Quick AnswersFrequently Asked Questions

How much does unplanned urban growth cost Dar es Salaam each day?

What share of Dar es Salaam's population lives in informal settlements?

How fast has informal settlement area grown in Dar es Salaam?

Who bears the daily cost of unplanned urban growth?

What is Dar es Salaam's population in 2026?

12 — Explore MoreTICGL Economic: Related Insights & Tools

What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050

Is Tanzania's Economy Growing?

What Opportunities and Risks Define Doing Business in Tanzania in 2026?

Why Tanzania's Economic Growth Has Not Been Sufficiently Inclusive

Tanzania Business Intelligence Dashboard

Invest in Tanzania

Muhtasari kwa Kiswahili

01 — OverviewExecutive Summary

Read this alongside TICGL's flagship Dira 2050 policy-gaps analysis

02 — ContextAbout the National Consumer Price Index

Why July 2026 matters for this analysis

Supplementary indices published alongside the NCPI

NCPI Basket Composition by COICOP Division

03 — The Twelve-Month PictureHeadline Inflation Trend, July 2025 – July 2026

NCPI Index and Annual Inflation Rate, July 2025 – July 2026

04 — What This Means at the MarketFood Inflation: The Number That Matters Most for Households

Food Items With the Largest Price Movements, June → July 2026

05 — Where the Pressure Actually Shows UpFuel, Energy and Transport: The Line to Watch

Fuel and Energy Items: Month-on-Month Price Change, June → July 2026

06 — The Full PictureInflation by COICOP Division, July 2026

Annual Inflation Rate by COICOP Division, July 2026

Other Selected Indices

Headline vs Core vs Food vs Services vs Goods vs Energy: Annual Inflation, July 2026

07 — The Question Everyone Is AskingReading the Budget Signal: One Month On

FY2026/27 Budget presented and passed

New fiscal year begins; tax and duty measures take effect

First fully post-budget month of price data

NBS releases the July 2026 NCPI

August, September and October releases due

What the data supports saying

What the data cannot support saying yet

08 — Looking AheadWhat Could the Next Six Months Bring?