01 — OverviewExecutive Summary
Financial health — the Welfare dimension — is the newest of NFIF3's four pillars, and the one most directly concerned with outcomes rather than access: can a household or business absorb a shock, meet its obligations, and plan for the future, not merely whether it can reach a bank agent or mobile wallet. The Bank of Tanzania's Mid-Term Evaluation reports that every single Welfare indicator technically exceeded its 2025 target. TICGL/TERI's analysis reads those results in absolute, not only relative, terms — and finds a more sobering picture underneath the "on track" headline.
The starkest number in the entire evaluation sits in this dimension: only 21.5% of adults, and only 11.8% of MSMEs, can reliably pay bills, debts, and other financial obligations on time. Resilience to a single shock is considerably stronger — 67.5% of adults and 76.0% of MSMEs can access emergency funds within 30 days — but the gap between those two figures is itself the story: Tanzanian households and businesses are more able to survive a shock than to avoid needing to. Long-term wealth-building indicators (investment ownership, pension participation) more than doubled off very low bases but remain modest in absolute terms. And institutionally, Welfare holds just 28 of NFIF3's 549 total dimensional activities — 5.1% — the smallest resource allocation of any of the framework's four dimensions, even as stakeholders themselves rated it the dimension where gains have been least "largely achieved."
- Financial stability: adults able to pay obligations on time rose from 14.0% to 21.5%; MSMEs from 3.0% to 11.8% — both technically beat target, both still describe a small minority.
- Resilience to shocks: adults with 30-day emergency-fund access rose from 55.0% to 67.5%; MSMEs from 71.0% to 76.0% — the strongest welfare indicators, but resilience is not the same as health.
- Risk mitigation: MSME insurance coverage rose from 4.4% to 11.4%; MSME contingent financing plans from 50.0% to 56.3% — meaningful growth, still low absolute coverage.
- Long-term wealth: adults with financial/real-asset investments rose from 28.0% to 36.8%; pension account ownership more than doubled from 3.6% to 8.1%.
- Who is left behind: the evaluation explicitly names rural households, smallholder farmers, youth, and persons with disabilities as facing the most constrained financial resilience.
- The resourcing gap: Welfare's 28 activities compare to 181 for Access, 162 for Usage, and 178 for Quality — a five-fold to six-fold difference in institutional attention.
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About TERI — TICGL's Research Institute
This analysis was prepared by the Tanzania Economic Research Institute (TERI), TICGL's dedicated research arm covering financial-sector policy, financial inclusion, and Tanzania's broader economic development. TERI's work spans two complementary strands: collecting and analysing primary data directly from the field — through surveys, key-informant interviews, and site-level data collection, as in TICGL/TERI's own city-level and sector-specific studies — and analysing official statistics published by institutions such as the Bank of Tanzania (BOT), NBS, and the Ministry of Finance, as this page does with the NFIF3 Mid-Term Evaluation. Together, this combination of original fieldwork and rigorous analysis of official data is what allows TERI to produce research that helps policymakers, investors, and development stakeholders make better-informed decisions. This report is part of TERI's ongoing series of Tanzanian economic and financial-policy analysis.
Visit TERI — teri.ticgl.com →02 — At a GlanceEvery Welfare Dimension Indicator
Source: BOT/NCFI, NFIF3 Mid-Term Evaluation Report, Section 5.4 (Welfare Dimension Targets).
Every row here beat its target — read the baseline column too
All eight Welfare indicators are reported as exceeding their 2025 Mid-Term targets. TICGL/TERI's analysis throughout this page reads these results primarily against their absolute level, not only their target, because several of these targets were themselves set low precisely because 2023 baselines were so weak (3.0% of MSMEs able to pay obligations on time, for instance). Beating a modest target and achieving adequate financial health are different claims.
03 — The Central FindingFinancial Stability: Still a Minority Position
The ability to pay bills, debts, and other obligations on time is arguably the single most basic test of financial health there is. On this measure, Tanzania's improvement is real but the destination is still a minority outcome.
Ability to Pay Financial Obligations on Time, 2023 vs. 2025
Percent able to reliably meet obligations, adults vs. MSMEs
TICGL reading
Even after nearly doubling off its baseline, the adult obligation-payment rate means just over one in five Tanzanian adults can reliably meet their financial commitments on time — leaving nearly four in five who cannot. For MSMEs, the picture is starker still: roughly seven out of eight businesses cannot reliably meet their obligations on time, even after a near-quadrupling of the 2023 baseline. This single indicator, more than any access or usage statistic, captures the gap between being financially included and being financially secure.
04 — Shock AbsorptionResilience: The Strongest Welfare Result — With a Catch
Emergency-fund access is where the Welfare dimension shows its most encouraging numbers — and its most important nuance.
30-Day Emergency-Fund Access, 2023 vs. 2025
Percent able to access emergency funds within 30 days without difficulty
Genuine progress, correctly read
Two-thirds of adults and three-quarters of MSMEs can now access emergency funds within 30 days — both figures close to their 2028 end targets already. This is real evidence of "enhanced capacity to absorb financial shocks," in the evaluation's own words, and reflects the broader access and usage gains documented elsewhere in NFIF3.
The gap this section highlights
Compare this section's numbers to Section 03: 67.5% of adults can access emergency funds, but only 21.5% can reliably pay obligations on time. TICGL/TERI reads this gap as evidence that "access to an emergency fund" for many households means the ability to borrow, sell an asset, or draw on social networks when a shock hits — not the underlying cash-flow stability that would reduce how often they need to. Resilience (surviving a shock) and financial health (not needing rescuing as often) are related but distinct outcomes, and Tanzania's current data shows meaningfully stronger performance on the former than the latter.
05 — PreparednessRisk Mitigation: MSME Insurance and Contingency Planning
Beyond emergency funds, the Welfare dimension tracks whether MSMEs are actively preparing for risk, rather than only reacting to it after the fact.
MSME Risk-Mitigation Indicators, 2023 vs. 2025
Percent of MSMEs, insurance coverage and contingent financing plans
MSME insurance coverage nearly tripled off its baseline (4.4% to 11.4%), the fastest relative growth of any Welfare indicator in this analysis — but it is also the lowest in absolute terms alongside the obligation-payment indicators. Contingent financing plans, at 56.3%, show that just over half of MSMEs have some form of pre-arranged financial backstop for disruptions, a meaningfully stronger starting position than insurance coverage suggests, and consistent with the credit-guarantee-scheme activity documented elsewhere in TICGL/TERI's NFIF3 coverage.
06 — Long HorizonLong-Term Wealth Accumulation: Pensions Doubling, Still Small
The final pair of Welfare indicators looks beyond the next shock to longer-horizon financial security — investment ownership and retirement preparedness.
Long-Term Wealth Indicators: 2023 → 2025 → 2028 Target
Percent of adults
TICGL reading
Pension account ownership more than doubled — the single largest relative gain of any Welfare indicator — but even at 8.1%, fewer than one in twelve Tanzanian adults holds a pension account. This aligns closely with the informal-sector social security findings TICGL/TERI documented separately: growth is real and often driven by specific, well-targeted reforms (see Section 09), but the base each of these reforms is building from remains very small.
07 — Distributional GapWho Is Left Behind: Rural Households, Smallholder Farmers, Youth, PWDs
The Mid-Term Evaluation's own summary assessment is explicit that national-level Welfare gains have not reached all groups evenly: "financial resilience remains constrained, particularly among rural households, smallholder farmers, youth, and persons with disabilities." This is a direct, named finding from the evaluation, not an inference — and it matters because none of the eight indicators in Table 1 are disaggregated by these groups in the published report.
The data gap behind the finding
TICGL/TERI flags this as consequential: the evaluation can state that rural households, smallholder farmers, youth, and PWDs have weaker resilience, but the absence of group-disaggregated Welfare indicators in the published Mid-Term Evaluation means policymakers cannot yet see by how much, or track whether targeted interventions are closing that gap over the second half of NFIF3. This mirrors a broader data-disaggregation limitation the evaluation acknowledges elsewhere in its own methodology notes.
This finding is also consistent with the priority-segment implementation data TICGL/TERI has documented separately: smallholder farmers and fisheries recorded the weakest activity-completion rate of any NFIF3 priority segment (22.2%), and persons with disabilities the second-weakest (45.5%) — the same two groups the evaluation names here as having the most constrained financial resilience.
08 — Why Progress Is SlowWelfare Is the Least-Resourced Dimension in NFIF3
Behind the indicator-level results sits a structural explanation the evaluation itself provides: Welfare has consistently received the smallest institutional resourcing of NFIF3's four dimensions.
NFIF3 Activities by Dimension: Total Planned (2023–2028)
Number of dimensional activities submitted by member institutions
Access Activities
181
32.6% of 2023-25 plan completed
Usage Activities
162
63.2% of 2023-25 plan completed
Quality Activities
178
56.2% of 2023-25 plan completed
Welfare Activities
28
52.9% of 2023-25 plan completed
Stakeholders themselves rank Welfare last
In the evaluation's own stakeholder perception survey, 73.5% of respondents said Access had been "largely achieved" — the strongest score of any dimension. Financial health (Welfare) scored lowest: only 35.3% said it was "largely achieved," with 44.1% rating it only "moderately achieved." The evaluation's own conclusion is direct: "gains in access to and usage of financial services are yet to fully translate into broad-based improvements in financial well-being."
TICGL/TERI's reading connects these two facts directly: Welfare activities are implemented at a comparable rate to the other dimensions (52.9%, in the middle of the pack) — the shortfall is not one of execution, but of an activity list that was simply five to six times smaller to begin with. A dimension with 28 planned activities against 181 for Access was always going to move more slowly in absolute national impact, whatever its completion percentage.
09 — What Progress Looks LikeA Household Story Behind the Numbers
From the evaluation's own success stories (Annex 3)
The Mid-Term Evaluation includes first-hand accounts of NFIF3's impact. One describes a market trader in her late fifties who, after a 2023 community outreach programme introduced her to an informal-sector social security scheme, began setting aside small voluntary contributions for the first time — later adding a supplementary savings layer through her local traders' association. She was part of a wave of informal-sector enrolment that grew dramatically over the evaluation period. When a health issue sidelined her for a month, her participation in these schemes let her access care without depleting her business's working capital — resilience, in practice, working as intended. The account also highlights a gender dimension: she is one of roughly 40% of women now represented in informal pension accounts, and describes actively encouraging younger women in her market to start their own savings journeys earlier than she did.
TICGL/TERI includes this account not as statistical evidence but as an illustration of what the resilience indicators in Section 04 look like at the household level — and of the gap this page documents throughout: her story is one of resilience to a single shock, built through voluntary, informal-sector social security participation, of exactly the kind that NFIF3's Welfare dimension is designed to scale, but currently under-resources relative to Access and Usage.
10 — TICGL RecommendationsTurning Access Into Resilience
Rebalance NFIF3's second half toward Welfare
- Welfare holds 5.1% of dimensional activities against 33% for Access — a ratio worth revisiting directly for the 2026–2028 remainder of NFIF3.
- Track affordability and satisfaction (Quality dimension) alongside Welfare indicators — both fell over the review period even as access expanded, a related warning sign.
Close the obligation-payment gap directly
- Design targeted cash-flow and financial-discipline interventions for MSMEs specifically — their 11.8% obligation-payment rate is the weakest indicator in this entire analysis.
- Distinguish resilience-building (emergency funds) from health-building (obligation payment, insurance) in programme design — they responded to different interventions.
Disaggregate Welfare indicators by priority segment
- Publish rural/urban, smallholder-farmer, youth, and PWD breakdowns of the eight Welfare indicators so the evaluation's own qualitative finding can be tracked quantitatively.
- Prioritise smallholder farmers and PWDs specifically — the same two groups already identified as the weakest-performing NFIF3 priority segments overall.
Scale what is already working
- Informal-sector social security schemes (Section 09) are a proven resilience mechanism — expand their reach and voluntary supplementary-savings layers.
- Pair credit-guarantee-scheme expansion (documented in TICGL/TERI's MSME-focused analysis) with contingent-financing-plan take-up, since both indicators move together.
"Tanzania has built the on-ramps to the financial system faster than it has built the shock absorbers. Two-thirds of adults can access emergency funds when something goes wrong — but barely one in five can avoid needing to. Closing that gap, not widening the on-ramps further, should be the defining test of NFIF3's second half."
— TICGL / Tanzania Economic Research Institute (TERI)
11 — SourcesReferences and Data Sources
Primary source
Bank of Tanzania / National Council for Financial Inclusion, The National Financial Inclusion Framework 2023–2028 (NFIF3): Mid-Term Evaluation Report (2023–2025), June 2026. Every figure in this analysis is drawn from that report's Welfare dimension section (5.4), Table 2 (Implementation of Activities by Dimension), the stakeholder perception survey (Section 6), and the illustrative success story in Annex 3, unless otherwise stated.
Framing devices such as the "resilience vs. financial health" distinction (Section 04) and the connection drawn between resourcing levels and outcome data (Section 08) are TICGL/TERI's own interpretation of the source data, clearly marked as such throughout. This is an independent analysis of a Bank of Tanzania publication and is not itself a Bank of Tanzania or NCFI publication.
12 — Quick AnswersFrequently Asked Questions
What share of Tanzanians can pay their bills and debts on time?
Only 21.5% of adults as of December 2025, up from 14.0% in 2023. Among MSMEs, the figure was 11.8%, up from 3.0%.
Can Tanzanian households cope with a financial emergency?
67.5% of adults and 76.0% of MSMEs could access emergency funds within 30 days without difficulty by December 2025 — a stronger result than the obligation-payment indicators.
Why is financial health the weakest dimension in the framework?
Welfare holds only 28 of 549 total dimensional activities (5.1%), versus 181 for Access alone — the smallest resourcing of NFIF3's four dimensions — and stakeholders rated it the least "largely achieved" dimension in the Mid-Term self-assessment.
Which groups have the weakest financial resilience?
The evaluation explicitly names rural households, smallholder farmers, youth, and persons with disabilities as the groups whose financial resilience remains most constrained.
Muhtasari kwa Kiswahili
Je, Watanzania Wanaweza Kulipa Madeni Yao kwa Wakati? — Uchambuzi wa TICGL wa Ustawi wa Kifedha na Resilience ya Kaya — Uchambuzi huu unaangazia kipimo cha "Ustawi wa Kifedha" (Welfare/Financial Health) katika Ripoti ya Tathmini ya Katikati ya NFIF3 iliyotolewa na Benki Kuu ya Tanzania (BOT) na Baraza la Taifa la Ujumuishaji wa Kifedha (NCFI), Juni 2026.
Matokeo makuu: Ni asilimia 21.5 tu ya watu wazima na asilimia 11.8 tu ya MSMEs wanaoweza kulipa madeni na majukumu ya kifedha kwa wakati. Wakati huo huo, asilimia 67.5 ya watu wazima na asilimia 76.0 ya MSMEs wanaweza kupata fedha za dharura ndani ya siku 30 — ikionyesha kuwa Watanzania wana uwezo mkubwa zaidi wa kuhimili mshtuko wa kifedha kuliko uwezo wa kuepuka kuuhitaji mshtuko huo. Umiliki wa akaunti za pensheni uliongezeka zaidi ya mara mbili (kutoka asilimia 3.6 hadi 8.1), lakini bado ni chini sana.
Kipimo cha Ustawi wa Kifedha ndicho kilichopewa rasilimali ndogo zaidi kati ya vipimo vinne vya NFIF3 — shughuli 28 tu kati ya 549 (asilimia 5.1) zililenga moja kwa moja Ustawi, ikilinganishwa na shughuli 181 kwa Upatikanaji. Wadau wenyewe walikadiria Ustawi wa Kifedha kuwa kipimo kilichofanikiwa kidogo zaidi kulinganisha na vipimo vingine. Ripoti inataja wazi kuwa kaya za vijijini, wakulima wadogo, vijana, na watu wenye ulemavu ndio wenye uwezo mdogo zaidi wa kuhimili misukosuko ya kifedha — ingawa takwimu za kina za makundi haya bado hazijachapishwa.
- Uwezo wa kulipa madeni kwa wakati: watu wazima asilimia 21.5; MSMEs asilimia 11.8
- Upatikanaji wa fedha za dharura ndani ya siku 30: watu wazima asilimia 67.5; MSMEs asilimia 76.0
- Umiliki wa akaunti za pensheni: asilimia 8.1 (kutoka 3.6%)
- Shughuli za Ustawi wa Kifedha: 28 tu kati ya 549 (asilimia 5.1) za NFIF3 nzima
- Makundi yenye resilience dhaifu zaidi: kaya za vijijini, wakulima wadogo, vijana, watu wenye ulemavu
Chanzo: Benki Kuu ya Tanzania (BOT) / Baraza la Taifa la Ujumuishaji wa Kifedha (NCFI), Ripoti ya Tathmini ya Katikati ya NFIF3, Juni 2026. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI).
01 — OverviewExecutive Summary
Insurance, capital markets, and social security are the three pillars of NFIF3 most directly concerned with long-run financial resilience — protecting households and businesses against shocks (insurance), building wealth over time (capital markets), and securing income in old age or hardship (social security). TICGL/TERI's analysis of the Mid-Term Evaluation Report finds all three growing at rates that would be remarkable in a mature market, precisely because they are starting from such a low base.
Capital-markets investor numbers grew 140.3% to 2,177,135, driven overwhelmingly by an extraordinary 380.5% surge in collective-investment-scheme investors. Insurance coverage rose from a 10.3% baseline to 23.4% of adults, with premium volume up 31.4% to TZS 1,630.0 billion. Informal-sector social security membership more than doubled (+103.2%) to 522,056 accounts — more than three times the growth rate of formal-sector membership (+30.9%). Each of these is a genuine achievement. But TICGL/TERI's reading is that growth rate and adequacy are different claims: insurance still reaches under a quarter of adults, capital-markets participation sits at 5.8%, and social assistance programmes (TASAF, ZUPS) together reach under 1% of the population. All three sub-sectors also show the same structural pattern — access concentrated in urban areas, low financial literacy constraining deeper participation, and product design not yet matched to the realities of informal, rural, or lower-income households.
- Insurance: coverage up to 23.4% of adults (from 10.3%); premiums up 31.4% to TZS 1,630.0 billion; access points up 26.7% to 2,770 — but constrained by low public trust and outdated micro-insurance regulation.
- Capital markets: investors up 140.3% to 2.18 million (5.8% of adults, above the 5% 2025 target); collective investment scheme investors up 380.5%; but financial literacy and rural outreach remain the binding constraints on further growth.
- Social security: informal-sector membership up 103.2% to 522,056, more than triple formal-sector growth — driven by NSSF's Hifadhi Scheme and Zanzibar's Sharia-compliant products — but a "continued gender disparity, with a large proportion of underserved being women" persists in formal-sector membership.
- Social assistance: TASAF and Zanzibar's Universal Pension Scheme both expanded, but combined outreach remains under 1% of the total population, per the evaluation's own assessment.
- The common thread: every sub-sector cites the same three constraints — urban-concentrated access points, low financial literacy among youth/informal/middle-income groups, and products not yet designed around real household income patterns.
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About TERI — TICGL's Research Institute
This analysis was prepared by the Tanzania Economic Research Institute (TERI), TICGL's dedicated research arm covering financial-sector policy, financial inclusion, and Tanzania's broader economic development. TERI's work spans two complementary strands: collecting and analysing primary data directly from the field — through surveys, key-informant interviews, and site-level data collection, as in TICGL/TERI's own city-level and sector-specific studies — and analysing official statistics published by institutions such as the Bank of Tanzania (BOT), NBS, and the Ministry of Finance, as this page does with the NFIF3 Mid-Term Evaluation. Together, this combination of original fieldwork and rigorous analysis of official data is what allows TERI to produce research that helps policymakers, investors, and development stakeholders make better-informed decisions. This report is part of TERI's ongoing series of Tanzanian economic and financial-policy analysis.
Visit TERI — teri.ticgl.com →02 — At a GlanceKey Numbers Across the Three Pillars
Insurance Coverage
23.4% of adults
26.7 million insured individuals
Capital Markets Participation
5.8% of adults
2,177,135 individual investors
Formal Pension Membership
3,026,303 accounts
+30.9% vs 2023
Insurance Access Points
2,770
+26.7% — agents grew fastest (+35.9%)
Capital Markets Access Points
435
+14.5% — CIS schemes +212.5%
Social Security Access Points
116
+4.5% — digital platforms +181.8%
Certified Capital-Market Professionals
998
Up from 737 in 2023
Insurance, Capital Markets, and Pension Participation: 2023 → 2025 → 2028 Target
Percent of adult population
Source: BOT/NCFI, NFIF3 Mid-Term Evaluation Report, Sections 4.2–4.4 and Annex 2 Measurement Framework.
03 — Pillar 1Insurance: Broader Reach, Still Thin Trust
🛡️ Insurance Services
Coverage: 23.4% of adults
GROWING FAST, STILL URBAN AND TRUST-CONSTRAINEDInsurance access points grew 26.7% to 2,770 between December 2023 and December 2025, led by insurance agents (+35.9% to 1,472), digital platforms (+28.6%), and the bancassurance agent network (+19.5%). The number of licensed insurance companies rose to 37. On the usage side, insured individuals grew 13.8% to 26.7 million — split almost exactly evenly between men (50.3%) and women (49.7%) — and premium volume rose 31.4% to TZS 1,630.0 billion.
Insurance Access Points by Channel: Growth, Dec 2023 → Dec 2025
Percentage growth by distribution channel
Source: BOT/TIRA, NFIF3 Mid-Term Evaluation Report, Table 15.
Why penetration still lags the growth rate
- Low public trust and negative perceptions of insurance continue to weaken uptake, per the evaluation's own diagnosis.
- The Micro Insurance Regulation (2013) is not fully aligned with digital distribution models and newer product innovations.
- Access points remain concentrated in urban areas, leaving rural populations comparatively underserved.
- Limited disaggregated supply- and demand-side data constrains targeted product design.
On the positive side, six new TIRA zonal offices brought services and complaint resolution closer to the public, the 2023 Guidelines on Insurance Digital Platforms and Takaful Operators simplified agent registration, and bancassurance partnerships between insurers and banks expanded cost-effective outreach — all cited by the evaluation as direct drivers of the growth recorded.
04 — Pillar 2Capital Markets: The Fastest-Growing Pillar, Powered by One Product
📈 Capital Markets Services
Participation: 5.8% of adults
COLLECTIVE INVESTMENT SCHEMES ARE DOING MOST OF THE WORKCapital markets access points grew 14.5% to 435, but the usage-side story is the standout number across all three pillars in this report: individual investors more than doubled to 2,177,135, up from 905,946 in 2023 — a 140.3% increase that pushed capital-markets participation to 5.8% of adults, comfortably above the 5% Mid-Term target.
Capital Market Investors by Product Category, 2023 → 2025
Number of investors — note the log-scale-like disparity between categories
Source: CMSA, NFIF3 Mid-Term Evaluation Report, Table 17.
TICGL reading
Collective investment schemes (CIS) — unit trusts and similar pooled vehicles — now account for 66.0% of all capital-market investors, up from 33.0% in 2023, and their investor count grew 380.5% on the back of 17 new schemes launched and technology-enabled platforms (the DSE Mobile Trading Platform, and partnerships such as Sanlam East Africa with M-Pesa). This is a genuinely positive story about retail-accessible pooled investment reaching new savers — but it also means the headline 140.3% growth figure is heavily concentrated in a single, comparatively simple product category, while participation in government securities, corporate bonds, and direct equities — the instruments that typically signal deeper market sophistication — grew far more modestly.
Constraints the evaluation flags
- Emerging cybercrime, fraud, pyramid schemes, and data-breach risk alongside rapid digital-platform growth.
- Limited financial literacy, particularly among youth, informal-sector participants, and middle-income earners.
- A need for inclusive, affordable investment products matched to real household income levels.
- Limited outreach of investment services to the rural population.
On the positive side, the Capital Markets Universities and Higher Learning Institutions Challenge (CMUHLIC) alone created over 180,000 youth investors, and certified capital-market professionals grew from 737 to 998 — both concrete steps toward the literacy and capacity constraints the evaluation names.
05 — Pillar 3Social Security: Informal-Sector Growth Outpacing Formal, But From a Small Base
🏛️ Social Security & Social Assistance
Informal accounts: +103.2%
THE HIFADHI SCHEME IS THE STANDOUT REFORMSocial security access points grew only modestly (+4.5% to 116), entirely driven by a 181.8% expansion in digital platforms, while the number of regional offices actually declined (-12.3%) and supplementary pension schemes fell (-33.3%) — a sector consolidating its physical footprint while digitising service delivery.
Formal vs. Informal-Sector Social Security Membership Growth
Percentage growth in member accounts, Dec 2023 – Dec 2025
Formal-Sector Members
3,026,303
+30.9% — 43.5% women, 48.4% youth
Informal-Sector Members
522,056
+103.2% — 54% women, 42.5% youth
Social Assistance Coverage
<1% of population
TASAF + ZUPS combined, per evaluation
What is driving informal-sector growth
The evaluation credits several concrete reforms: NSSF's Hifadhi Scheme, established specifically for informal-sector workers — boda boda riders, small-scale miners, mama/baba lishe food vendors, small farmers, and street vendors; Zanzibar's Sharia-compliant pension products, which increased trust and participation by aligning with cultural and religious preferences; a reduction in the unemployment-benefit waiting period from 24 months to just 90 days; and the use of accrued pension benefits as collateral for housing finance, adding a tangible near-term value proposition to a traditionally long-horizon product.
Where gaps persist
- Formal-sector membership shows "continued gender disparity, with a large proportion of underserved being women" — even though informal-sector accounts skew female (54%).
- Partial National ID (NIN) coverage limits enrolment, especially in informal employment.
- Pension fund assets are concentrated in illiquid investments (notably large real-estate projects), a mismatch against informal workers' liquidity needs.
- Climate and economic shocks — floods, droughts, disruptions to fishing and seaweed farming — reduce voluntary contributions and increase distress withdrawals.
- No unified legal framework yet bridges formal pension law and social-assistance policy.
Social assistance: TASAF and Zanzibar's Universal Pension Scheme
Under the Productive Social Safety Net (PSSN), TASAF had created 76,070 digital savings groups comprising 1,012,849 members by the end of the evaluation period — 89.0% of them women — mobilising TZS 17.50 billion in group savings and issuing TZS 8.90 billion in loans; 52.9% of beneficiaries had linked bank savings accounts, mostly smallholder farmers. In Zanzibar, the Universal Pension Scheme (ZUPS) reached 33,213 elders by December 2025 (up from 29,636), with the monthly benefit having been raised from TZS 20,000 to TZS 50,000 for those aged 70+. Both programmes are, by the evaluation's own account, constrained by heavy donor-aid dependency and outreach below 1% of the total population.
06 — The PatternWhat All Three Pillars Have in Common
Reading insurance, capital markets, and social security side by side, the same three constraints recur almost verbatim across all three sub-sector chapters of the evaluation — evidence that these are systemic issues, not sub-sector-specific ones.
TICGL reading: three sub-sectors, one underlying capability gap
The recurrence of nearly identical constraints across three institutionally separate regulators (TIRA, CMSA, PMO-LER/ZSSF) suggests the binding constraint on deepening Tanzania's risk-management ecosystem is less about any single sub-sector's regulation and more about shared, cross-cutting capability gaps — financial literacy infrastructure, rural distribution economics, and disaggregated data systems — that no single regulator can solve alone.
07 — TICGL RecommendationsTurning Growth Into Depth
Modernise regulation to match how these products now reach people
- Update the 2013 Micro Insurance Regulation to reflect digital distribution models and product innovation already in the market.
- Extend the same digital-platform-aware regulatory thinking behind recent capital-markets reforms (crowdfunding guidelines, Sukuk guidelines) to insurance and pensions.
Build a shared financial-literacy infrastructure, not three separate ones
- Scale CMUHLIC-style youth investor programmes (180,000+ reached) as a cross-sector model for insurance and pension literacy, not just capital markets.
- Target literacy efforts specifically at youth, informal-sector workers, and middle-income earners — the group named across all three sub-sector chapters.
Diversify capital-markets growth beyond collective investment schemes
- CIS investors now represent two-thirds of the market; deliberate efforts to grow government-securities, corporate-bond, and equity participation would build a more resilient, diversified investor base.
- Track cyber and fraud risk metrics alongside adoption metrics as digital investment platforms scale.
Match pension-fund asset allocation to informal workers' liquidity needs
- Address the evaluation's own finding of a mismatch between illiquid real-estate-heavy pension portfolios and informal workers' need for liquidity during climate and income shocks.
- Accelerate National ID (NIN) coverage specifically for informal-sector workers — the single most-cited enrolment barrier across social security, insurance, and capital markets alike.
"Insurance, capital markets, and social security all show the fastest growth rates in this entire evaluation — and all three are growing fast for the same reason: they started from almost nothing. The real test for the second half of NFIF3 is whether that growth curve keeps compounding once the easiest wins — mobile-enabled collective investment schemes, a handful of informal-worker pension pilots — are exhausted."
— TICGL / Tanzania Economic Research Institute (TERI)
08 — SourcesReferences and Data Sources
Primary source
Bank of Tanzania / National Council for Financial Inclusion, The National Financial Inclusion Framework 2023–2028 (NFIF3): Mid-Term Evaluation Report (2023–2025), June 2026. Every figure in this analysis is drawn from that report's insurance, capital markets, and social security sections (Sections 4.2–4.4, Tables 14–19, and Annex 2 Measurement Framework) unless otherwise stated. Underlying supply-side data is credited by the source report to TIRA (insurance), CMSA and BOT (capital markets), and PMO-LER and ZSSF (social security).
The cross-cutting constraint comparison (Table 3) and TICGL's reading boxes throughout are TICGL/TERI's own interpretation of the source data, clearly marked as such. This is an independent analysis of a Bank of Tanzania publication and is not itself a Bank of Tanzania or NCFI publication.
09 — Quick AnswersFrequently Asked Questions
How much has insurance coverage grown in Tanzania?
Insurance coverage reached 23.4% of adults by December 2025, up from a 10.3% baseline in 2023. Insured individuals rose 13.8% to 26.7 million, and premium volume rose 31.4% to TZS 1,630.0 billion.
How many Tanzanians now invest in capital markets?
Individual investors more than doubled to 2,177,135 by December 2025 (+140.3%), putting capital-markets participation at 5.8% of adults — driven mainly by a 380.5% surge in collective-investment-scheme investors.
Has social security coverage improved for informal workers?
Informal-sector member accounts grew 103.2% to 522,056 between 2023 and 2025 — more than three times faster than formal-sector growth (30.9%) — driven by reforms including NSSF's Hifadhi Scheme.
Why is penetration still low despite fast growth?
Low public trust, outdated regulation, limited financial literacy, and access points concentrated in urban areas are cited across all three sub-sectors as the binding constraints on deeper participation.
Muhtasari kwa Kiswahili
Bima, Masoko ya Mitaji, na Hifadhi ya Jamii: Uchambuzi wa TICGL wa NFIF3 — Uchambuzi huu unaangazia nguzo tatu za usimamizi wa hatari za kifedha kwa mujibu wa Ripoti ya Tathmini ya Katikati ya NFIF3 iliyotolewa na Benki Kuu ya Tanzania (BOT) na Baraza la Taifa la Ujumuishaji wa Kifedha (NCFI), Juni 2026.
Matokeo makuu: Bima imefikia asilimia 23.4 ya watu wazima (kutoka asilimia 10.3), huku thamani ya malipo ya bima (premiums) ikiongezeka kwa asilimia 31.4 hadi TZS bilioni 1,630. Wawekezaji kwenye masoko ya mitaji waliongezeka mara mbili zaidi (asilimia 140.3) kufikia milioni 2.18, wakichochewa zaidi na ongezeko la asilimia 380.5 la wawekezaji kwenye mifuko ya uwekezaji ya pamoja (collective investment schemes). Akaunti za hifadhi ya jamii kwa sekta isiyo rasmi ziliongezeka kwa asilimia 103.2 kufikia 522,056 — zaidi ya mara tatu ya kasi ya ukuaji wa sekta rasmi (asilimia 30.9), zikichochewa na Mpango wa Hifadhi wa NSSF unaolenga bodaboda, wachimbaji wadogo, mama na baba lishe, na wafanyabiashara wadogo.
Licha ya ukuaji huu wa haraka, uchambuzi wa TICGL/TERI unaonyesha kuwa nguzo zote tatu bado zinakabiliwa na changamoto zinazofanana: vituo vingi vya huduma bado vimejikita mijini, uelewa mdogo wa masuala ya fedha miongoni mwa vijana na sekta isiyo rasmi, na bidhaa ambazo bado hazijaendana kikamilifu na hali halisi ya kipato cha kaya. Mipango ya TASAF na Mpango wa Pensheni wa Zanzibar (ZUPS) bado inafikia chini ya asilimia moja ya watu wote nchini, na inategemea kwa kiasi kikubwa ufadhili wa nje.
- Bima: asilimia 23.4 ya watu wazima; malipo ya bima TZS bilioni 1,630 (+31.4%)
- Masoko ya mitaji: wawekezaji milioni 2.18 (+140.3%); asilimia 5.8 ya watu wazima
- Hifadhi ya jamii — sekta isiyo rasmi: akaunti 522,056 (+103.2%)
- TASAF/ZUPS: chini ya asilimia 1 ya watu wote nchini
- Changamoto za pamoja: upatikanaji wa mijini, uelewa mdogo wa fedha, bidhaa zisizolingana na kipato
Chanzo: Benki Kuu ya Tanzania (BOT) / Baraza la Taifa la Ujumuishaji wa Kifedha (NCFI), Ripoti ya Tathmini ya Katikati ya NFIF3, Juni 2026. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI).
01 — OverviewExecutive Summary
Tanzania's MSME sector sits at the centre of the country's financial-inclusion strategy on paper — it is one of NFIF3's five named priority segments, and MSME-specific indicators are tracked across all four dimensions of the framework (Access, Usage, Quality, and Welfare). TICGL/TERI isolated every one of those MSME-only rows from the June 2026 Mid-Term Evaluation Report to build a picture of the sector on its own terms, rather than as a footnote inside broader Access or Usage numbers.
The resulting picture is genuinely mixed, and more cautionary than the framework's overall "on track" narrative suggests. On one hand, MSME loan accounts in the banking sector more than doubled (+104.8%) in two years, and MSME credit's share of total bank credit rose from 12.0% to 22.7%. On the other hand, the total value of MSME lending fell by 20.7% over the same period, MSME account ownership barely moved (11.0% to 11.6%, against a 2025 target of 13%), and formal business registration — the single foundational indicator for everything else — sits at just 12.5%. Financial-health indicators for MSMEs, while all technically "above target," describe a sector where only around one in eight businesses can reliably pay its obligations on time or carries insurance.
- More borrowers, smaller loans — MSME loan accounts +104.8% to 578,692; total loan value −20.7% to TZS 10,409.1 billion — average loan size per MSME borrower has shrunk substantially.
- Account ownership is nearly flat — MSMEs with an account at a formal financial service provider moved from 11.0% to just 11.6%, even as loan accounts surged — a direct contradiction the evaluation itself flags between two of its own indicators.
- Formalisation remains the binding constraint — only 12.5% of MSMEs are formally registered, against a 2028 end target of just 15%, meaning formalisation itself, not only access to finance, is the deeper structural gap.
- Personal loans are substituting for MSME credit — personal loans used for business purposes grew 189.7% in value, which the evaluation attributes directly to MSMEs avoiding "strict MSME lending requirements."
- Financial health is improving off a very low base — MSMEs able to pay obligations on time rose from 3.0% to 11.8%; insurance coverage from 4.4% to 11.4% — both technically beat target, both still describe a small minority of businesses.
- Institutional attention to MSMEs lags other segments — MSME-targeted activities were only 43.3% complete at the Mid-Term point, and stakeholders rated MSME inclusion at 3.82 out of 5, with over a third of respondents saying MSMEs receive only "moderate attention."
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About TERI — TICGL's Research Institute
This MSME-focused analysis was prepared by the Tanzania Economic Research Institute (TERI), TICGL's dedicated research arm covering financial-sector policy, financial inclusion, and Tanzania's broader economic development. TERI's work spans two complementary strands: collecting and analysing primary data directly from the field — through surveys, key-informant interviews, and site-level data collection, as in TICGL/TERI's own city-level and sector-specific studies — and analysing official statistics published by institutions such as the Bank of Tanzania (BOT), NBS, and the Ministry of Finance, as this page does with the NFIF3 Mid-Term Evaluation. Together, this combination of original fieldwork and rigorous analysis of official data is what allows TERI to produce research that helps policymakers, investors, and development stakeholders make better-informed decisions. This report is part of TERI's ongoing series of Tanzanian economic and financial-policy analysis.
Visit TERI — teri.ticgl.com →02 — At a GlanceEvery MSME Indicator in the Mid-Term Evaluation
Source: BOT/NCFI, NFIF3 Mid-Term Evaluation Report, Annex 2 (Measurement Framework), indicators 1.1.3, 1.1.6, 1.2.2, 2.1.2, 2.2.5, 4.1.2, 4.2.2, 4.2.3, 4.3.3.
Read every "above target" row with the baseline in view
Nearly every MSME indicator in this table is marked "above the 2025 target" — but several of these targets were set low precisely because MSME baselines were so weak (e.g., only 3.0% of MSMEs could pay obligations on time in 2023). Beating a modest target is not the same claim as adequate performance; TICGL/TERI reads these results in absolute terms throughout this analysis, not only against the targets set for them.
03 — The Core FindingMore Borrowers, Smaller Loans: The MSME Credit Paradox
The single most important chart in this analysis is also the simplest: track MSME loan accounts and MSME loan value across the same three reporting dates. Accounts rise steadily. Value peaks in 2024 — and then falls.
MSME Loan Accounts vs. Total MSME Loan Value, Dec 2023 – Dec 2025
Accounts (left axis, thousands) vs. loan value (right axis, TZS billions)
Source: BOT, NFIF3 Mid-Term Evaluation Report, Table 9. Implied average loan size (TICGL calculation) = total value ÷ accounts; not reported directly by BOT.
TICGL reading
On TICGL/TERI's calculation, the average MSME loan size fell from roughly TZS 46.5 million in December 2023 to roughly TZS 18.0 million by December 2025 — a decline of more than 60% in under two years, even as the total number of MSME borrowers more than doubled. This is consistent with two different, non-exclusive explanations: (1) genuine first-time inclusion — a wave of previously excluded, smaller MSMEs entering the formal credit system for the first time, which would mechanically pull the average down even if underwriting stayed constant; or (2) a systemic tightening of MSME loan sizes — banks rationing credit more conservatively per borrower amid the informality-linked risk premiums the evaluation itself cites as a driver of interest-rate rigidity. Distinguishing between these two stories requires loan-size-distribution data the published evaluation does not disaggregate; TICGL/TERI flags this as the single most consequential open question in Tanzania's MSME finance data right now.
04 — A Contradiction in the DataMSME Account Ownership Has Barely Moved
If MSME loan accounts more than doubled, a reasonable expectation would be that MSME account ownership at formal financial institutions — the base layer beneath any loan relationship — grew at a similar pace. It did not.
MSME Account Ownership at Formal Financial Service Providers, 2023 → 2025 → 2028 Target
Percent of MSMEs with an account at an FSP
The evaluation flags this contradiction itself
The Mid-Term Evaluation's own Annex 2 measurement framework notes that indicator 2.1.2 ("% of MSMEs with an active account with FSPs," baseline 31.0%, target 38%) returned no usable 2025 figure because it "contradicts" indicator 1.2.2 (MSME account ownership, 11.6%) — two supposedly related MSME account metrics moving in inconsistent directions in the underlying supply-side data. TICGL/TERI treats this not as a minor data quirk but as a signal that MSME account-level data infrastructure — as distinct from MSME loan-level data, which is comparatively well tracked — needs its own dedicated reconciliation effort before it can support reliable policy conclusions.
Read alongside the credit paradox in Section 03, the pattern that emerges is a formal-credit relationship growing faster than the formal-account relationship beneath it — precisely the reverse of what a healthy formalisation trajectory would look like, where account ownership typically leads credit access, not lags behind it.
06 — A Workaround, Not a SolutionPersonal Loans Are Substituting for MSME Credit
While formal MSME lending value fell, one adjacent category grew sharply: personal loans used for business purposes.
Personal Loans for Business Usage vs. MSME Loan Portfolio Growth, Dec 2023 – Dec 2025
Percentage change in accounts and value
TICGL reading
Personal-loan-for-business value grew nearly 190% — almost the mirror image of formal MSME credit's decline. The evaluation's own text states plainly that "some MSMEs rely on personal loans to finance business activities, to avoid some of the strict MSME lending requirements." This is a rational individual response to onerous underwriting requirements, but it is a policy-relevant workaround, not a solution: personal loans typically carry different (often less favourable) terms, do not build a business's own formal credit history, and are invisible to MSME-specific credit-risk and portfolio monitoring — meaning a meaningful share of Tanzania's actual MSME financing activity may already be occurring outside the data this evaluation, and most MSME policy, is built on.
07 — Welfare DimensionMSME Financial Health: Resilient to Shocks, Not Yet Financially Healthy
NFIF3's Welfare (financial health) dimension tracks MSMEs on the same four measures used for households: obligation payment, emergency-fund access, insurance, and contingency planning. The pattern for MSMEs is more lopsided than for adults generally.
MSME Financial Health Indicators, 2023 Baseline vs. 2025
Percent of MSMEs meeting each welfare indicator
The gap between resilience and health
76.0% of MSMEs can access emergency funds within 30 days — a genuinely strong number, close to its 80% end target. But only 11.8% can reliably pay bills and debts on time, and only 11.4% carry insurance. Read together, this describes a sector that can survive a single shock (by borrowing or drawing down reserves) but lacks the underlying discipline, insurance cover, or cash-flow stability that would let it avoid needing that emergency access in the first place. Emergency-fund access is a resilience metric; obligation-payment and insurance are health metrics — and Tanzanian MSMEs are considerably stronger on the former than the latter.
08 — Institutional AttentionMSMEs Rank Mid-Pack in NFIF3's Own Priority-Segment Delivery
NFIF3 names MSMEs as one of five priority segments, alongside women, youth, smallholder farmers/fishers, and persons with disabilities. On the framework's own activity-completion tracking, MSMEs sit in the middle of that pack — ahead of the weakest-served groups, but well behind the strongest.
Priority-Segment Activity Implementation Rate, 2023–2025
Percentage of planned mid-term activities completed, by segment
MSME Activities Planned (2023–25)
30 of 66
13 completed = 43.3%
Stakeholder Inclusion Rating
3.82 / 5
Behind women (4.24) and youth (3.85)
"Moderate Attention Only"
>1 in 3
Of respondents, re: MSME inclusion
What the evaluation's own stakeholder survey says
Beyond the activity-completion numbers, the evaluation's stakeholder perception survey found MSME inclusion rated 3.82 out of 5 — behind women (4.24) and youth (3.85) — with "over a third of respondents" saying MSMEs receive only moderate attention in NFIF3 implementation. Stakeholders explicitly recommended establishing a dedicated coordination committee for MSMEs (alongside youth and PWDs), mirroring the Women Affairs Committee for Financial Inclusion (WACFI) that is widely credited with driving women's strong performance across every other section of this evaluation.
09 — What Is WorkingCredit Guarantee Schemes: A Genuine, If Small-Scale, Bright Spot
Not everything in the MSME-adjacent data is discouraging. Credit guarantee schemes — designed specifically to solve the collateral problem underlying much of the MSME credit paradox — showed real growth over the Mid-Term period, even if still small relative to the TZS 48.4 trillion national bank loan portfolio.
Source: BOT, NFIF3 Mid-Term Evaluation Report, Sections 4.1.5.1–4.1.5.3.
TICGL reading
These schemes are precisely the instrument that should, in principle, resolve the credit paradox documented in Section 03 — by substituting a guarantee for the collateral an MSME lacks, they should let banks lend larger amounts to smaller businesses with more confidence. The fact that MSME loan values fell even as guarantee schemes grew suggests the schemes, while directionally correct and worth scaling, are not yet operating at a scale that can offset the broader tightening documented above. BOT-CGS and TADB's combined FY2025/26 guaranteed lending (well under TZS 250 billion) remains a rounding error against the TZS 2.7 trillion decline in total MSME loan value over the same two-year window.
10 — TICGL RecommendationsClosing the MSME Credit Paradox
Fix the data before fixing the policy
- Reconcile the contradiction between MSME loan-account growth and flat MSME account ownership (indicators 1.2.2 and 2.1.2) before drawing further policy conclusions from either.
- Publish MSME loan-size distributions, not just totals and averages, so the credit paradox in Section 03 can be attributed to genuine inclusion versus systemic loan-size rationing.
Attack formalisation directly, not just credit access
- Accelerate the TRA/local-government formalisation incentives the evaluation itself recommends — formalisation is the ceiling on every other MSME indicator in this report.
- Expedite the Secured Transactions Law to expand usable collateral for MSMEs lacking traditional assets, as recommended in the evaluation's own Chapter 7.
Scale credit guarantees to match the size of the gap
- BOT-CGS, TADB, SIDO, and PASS Trust are the right instrument but currently too small to offset the TZS 2.7 trillion two-year decline in MSME loan value — scale, not redesign, is the priority.
- Bring personal-loan-for-business substitution (Section 06) into formal MSME credit tracking so its true scale is visible to policymakers.
Give MSMEs the institutional attention women's inclusion received
- Establish a dedicated MSME coordination committee, as stakeholders themselves recommended, modelled on the Women Affairs Committee for Financial Inclusion.
- Target MSME insurance and obligation-payment indicators directly — both sit near 11%, the two weakest MSME welfare indicators in the entire evaluation.
"An MSME sector where loan accounts double while loan value shrinks is not a story of expanding financial inclusion — it is a story of a widening base being served with progressively thinner credit. Tanzania's MSME data doesn't yet tell us why. Answering that question, not celebrating the account-growth number on its own, should be the priority for the second half of NFIF3."
— TICGL / Tanzania Economic Research Institute (TERI)
11 — SourcesReferences and Data Sources
Primary source
Bank of Tanzania / National Council for Financial Inclusion, The National Financial Inclusion Framework 2023–2028 (NFIF3): Mid-Term Evaluation Report (2023–2025), June 2026. Every figure in this analysis is drawn from that report's MSME-specific data rows (Tables 9–10, Annex 2 Measurement Framework, and Chapter 3 priority-segment data) unless otherwise stated.
Implied average MSME loan sizes (Table 2) and the framing of the "credit paradox" are TICGL/TERI's own calculations and interpretation of the source data, clearly marked as such throughout this page. This is an independent analysis of a Bank of Tanzania publication and is not itself a Bank of Tanzania or NCFI publication.
12 — Quick AnswersFrequently Asked Questions
Did MSME access to credit improve under NFIF3?
MSME loan accounts grew 104.8% to 578,692 between December 2023 and December 2025, but total MSME loan value fell 20.7% to TZS 10,409.1 billion — meaning average loan size per borrower shrank considerably.
How many MSMEs in Tanzania are formally registered?
Only 12.5% as of December 2025, up from 10.0% in 2023, against a 2028 end target of just 15%.
Do more MSMEs have bank accounts now than in 2023?
Barely — MSME account ownership moved from 11.0% to 11.6%, even as loan accounts more than doubled, an inconsistency the evaluation itself flags.
How financially healthy are Tanzanian MSMEs?
Only 11.8% can reliably pay obligations on time and 11.4% carry insurance, versus 76.0% that can access emergency funds — suggesting resilience to shocks but not durable financial health.
Muhtasari kwa Kiswahili
Fumbo la Mikopo ya MSMEs: Uchambuzi wa TICGL wa Tathmini ya Katikati ya NFIF3 — Uchambuzi huu umejikita moja kwa moja kwenye takwimu za MSMEs pekee zilizomo kwenye Ripoti ya Tathmini ya Katikati ya NFIF3 iliyotolewa na Benki Kuu ya Tanzania (BOT) na Baraza la Taifa la Ujumuishaji wa Kifedha (NCFI), Juni 2026.
Matokeo makuu: Akaunti za mikopo za MSMEs ziliongezeka mara mbili (asilimia 104.8) kufikia 578,692, lakini thamani ya jumla ya mikopo hiyo ilishuka kwa asilimia 20.7 hadi TZS bilioni 10,409.1 — wastani wa mkopo kwa kila mkopaji ulipungua kutoka takribani TZS milioni 46.5 hadi milioni 18.0. Umiliki wa akaunti za MSMEs katika taasisi rasmi za fedha ulibaki karibu bila kubadilika (asilimia 11.0 hadi 11.6), na ni asilimia 12.5 tu ya MSMEs zilizosajiliwa rasmi. Mikopo binafsi inayotumika kwa biashara iliongezeka kwa asilimia 189.7 katika thamani — ikionyesha wajasiriamali wengi wanakwepa masharti magumu ya mikopo rasmi ya MSME.
Kiafya ya kifedha (welfare), ni asilimia 11.8 tu ya MSMEs zenye uwezo wa kulipa madeni kwa wakati na asilimia 11.4 tu zenye bima — ingawa asilimia 76.0 zinaweza kupata fedha za dharura. Hii inaonyesha kuwa MSMEs zinaweza kuhimili mshtuko mmoja wa kifedha lakini bado hazina afya ya kifedha ya kudumu. Kwenye utekelezaji wa shughuli za NFIF3, MSMEs zilikamilisha asilimia 43.3 tu ya shughuli zilizopangwa — chini ya wanawake (asilimia 78.1) — na wadau wanapendekeza kuanzishwa kwa kamati maalum ya uratibu wa MSMEs, kama ilivyofanyika kwa wanawake kupitia WACFI.
- Akaunti za mikopo za MSME: 578,692 (+104.8%); Thamani ya mikopo: TZS bilioni 10,409 (−20.7%)
- Umiliki wa akaunti za MSME: asilimia 11.6 tu (kutoka 11.0%)
- Usajili rasmi wa MSME: asilimia 12.5 tu
- Uwezo wa kulipa madeni kwa wakati: asilimia 11.8; Bima: asilimia 11.4
- Utekelezaji wa shughuli za NFIF3 kwa MSMEs: asilimia 43.3 tu
Chanzo: Benki Kuu ya Tanzania (BOT) / Baraza la Taifa la Ujumuishaji wa Kifedha (NCFI), Ripoti ya Tathmini ya Katikati ya NFIF3, Juni 2026. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI).
01 — OverviewExecutive Summary
Tanzania's Third National Financial Inclusion Framework (NFIF3, 2023–2028) set out to do something its two predecessors did not fully achieve: move the country's financial-inclusion agenda beyond simply getting people access to a bank agent or a mobile wallet, toward active usage, service quality, and — the dimension that matters most for household welfare — financial health. The Mid-Term Evaluation, covering December 2023 to December 2025, is BOT/NCFI's own scorecard on whether that shift is actually happening.
The Access dimension has essentially been won. Financial service access points grew 60.7% to 2,266,706 nationwide; 93% of adults now live within 5km of an access point, ahead of the 92% mid-term target. Usage is following close behind: active account usage rose from 60% to 72.5% of adults, and active mobile money accounts reached 75.8 million. But TICGL/TERI's reading of the underlying data finds a familiar pattern in financial-inclusion frameworks worldwide — the dimensions that are easiest to build (access points, agent networks) have advanced fastest, while the dimensions that actually determine whether inclusion changes people's lives (Quality and, especially, Welfare/financial health) have moved more slowly, and unevenly across population groups.
- Access and Usage are ahead of target — 93% of adults live within 5km of an access point (target 92%); active account usage is 72.5% (target 70%); mobile money accounts reached 75.8 million (+46.5%).
- Digital payments infrastructure scaled fast — TIPS transaction value more than doubled to TZS 37.2 trillion in the year to April 2025; bank-to-wallet and wallet-to-bank transfers both grew above 20% in a single quarter after charges were harmonised.
- Credit to priority groups is a mixed picture — MSME loan accounts grew 104.8% but the total MSME loan value fell 20.7%; women's credit accounts grew only 4.3% while the value they borrowed fell 45.1%, even as women-targeted activities were the best-implemented of all priority segments.
- Insurance and capital markets both beat their 2025 targets in relative terms (23.4% and 5.8% respectively) but remain shallow in absolute terms, concentrated in urban areas, and constrained by low public trust.
- Smallholder farmers/fishers and persons with disabilities are the clearest laggards — only 22.2% and 45.5% of their planned mid-term activities were completed, against 78.1% for women.
- Structural constraints are unchanged from the framework's stated diagnosis — donor-dependent budgeting, partial National ID coverage, rural connectivity gaps, rising cybersecurity/fraud risk, and interest-rate rigidity linked to informality all continue to cap how far access gains translate into welfare gains.
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About TERI — TICGL's Research Institute
This NFIF3 analysis was prepared by the Tanzania Economic Research Institute (TERI), TICGL's dedicated research arm covering financial-sector policy, financial inclusion, and Tanzania's broader economic development. TERI's work spans two complementary strands: collecting and analysing primary data directly from the field — through surveys, key-informant interviews, and site-level data collection, as in TICGL/TERI's own city-level and sector-specific studies — and analysing official statistics published by institutions such as the Bank of Tanzania (BOT), NBS, and the Ministry of Finance, as this page does with the NFIF3 Mid-Term Evaluation. Together, this combination of original fieldwork and rigorous analysis of official data is what allows TERI to produce research that helps policymakers, investors, and development stakeholders make better-informed decisions. This report is part of TERI's ongoing series of Tanzanian economic and financial-policy analysis.
Visit TERI — teri.ticgl.com →📌
Read this alongside TICGL's flagship Dira 2050 policy-gaps analysis
Financial inclusion is one of the clearest levers Tanzania has for closing the financing and productivity gaps standing between the country and Dira 2050's US$1 trillion, US$7,000-per-capita ambition — but only if inclusion converts into usage, quality, and measurable household welfare, not just access-point counts. TICGL/TERI recommends reading the two pieces together.
Read: What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050 →02 — At a GlanceKey Numbers From the Mid-Term Evaluation
Access Points, Dec 2025
2,266,706
+60.7% vs Dec 2023
Active Mobile Money Accounts
75.8 million
+46.5% vs Dec 2023
TIPS Transaction Value
TZS 37.2 trillion
More than doubled in a year
Adults With a Transacting Account
81.0%
vs 76.0% baseline (2023)
Insurance Coverage of Adults
23.4%
Up from 10.3% baseline
Capital Markets Participation
5.8%
Up from 2.4% baseline
Financial Literacy
66.3%
Up from 60.0% baseline
Adults Able to Meet Obligations on Time
21.5%
Up from 14.0% baseline — still low
Financial Sector Access Points by Sub-Sector: Growth, Dec 2023 → Dec 2025
Percentage growth in access points, by sub-sector
Source: Bank of Tanzania, NFIF3 Mid-Term Evaluation Report (June 2026), Table 1 and Section 1.2.
03 — Theme 1Financial Inclusion, Growth, and Poverty Reduction
The evaluation's own framing is unambiguous about the transmission channel: as more people and MSMEs use formal financial services, monetary policy transmission improves, domestic savings mobilisation reduces reliance on external financing, and the tax base broadens. At the household and MSME level, access to formal savings and credit smooths consumption, reduces dependence on costly informal lending, and — where credit is used for inventory or equipment — expands output, incomes, and employment.
What the Mid-Term data lets TICGL/TERI test is whether the access-side growth is actually reaching the two groups the report singles out as central to this channel: MSMEs and smallholder farmers.
Total Bank Loan Portfolio
TZS 48,434bn
+46.7% in value; +57.3% in accounts
MSME Loan Accounts
578,692
+104.8% accounts, but loan value −20.7%
Smallholder Farmer/Fisher Credit
TZS 467.1bn
+38.2% value; accounts +188.5%
TICGL reading
MSME loan accounts more than doubled while total MSME loan value fell by a fifth — average loan size per MSME borrower has shrunk markedly. That is consistent with more MSMEs being drawn into the formal credit system for the first time (a genuine access win) but being offered smaller, more conservative facilities than before — which limits the growth and employment effect the theory of change is counting on. Smallholder farmer/fisher credit shows the opposite and more encouraging pattern: both accounts and value grew together, roughly in line with each other, consistent with genuine deepening rather than dilution — though off a much smaller base (TZS 467bn vs TZS 48.4 trillion economy-wide).
The report also notes a rise in personal loans used for business purposes (+59.9% in accounts, +189.7% in value) — MSMEs increasingly financing operations through personal rather than business credit lines, which the evaluation itself flags as a sign that formal MSME lending requirements remain too strict for a meaningful share of demand.
04 — Theme 2Digital Financial Services: TIPS, Agency Banking, and Interoperability
This is where NFIF3's Mid-Term period shows its clearest structural achievement: the March 2024 launch of the Tanzania Instant Payment System (TIPS) and the subsequent harmonisation of bank-to-wallet and wallet-to-bank charges. Card payments at merchant POS moved toward zero cost; bank-to-bank transfers were capped at TZS 2,000 for transfers up to TZS 20 million; wallet-to-bank and bank-to-wallet transfers were capped between TZS 10 and TZS 4,500 for amounts up to TZS 0.5 million.
Active Mobile Money Accounts, 2023 → 2025
Millions of active accounts — a straightforward measure of digital-finance reach
TIPS Transaction Value, Year to April 2024 vs. Year to April 2025
TZS billions — total value transacted through the Tanzania Instant Payment System
Source: BOT, NFIF3 Mid-Term Evaluation Report, Tables 20–22.
Efficiency, cost, and formalisation reading
The single-quarter jump of over 20% in both bank-to-wallet and wallet-to-bank volumes immediately after charges were harmonised is about as clean a demonstration of price elasticity in payments as this kind of data provides — cost was a binding constraint on interoperable usage, and removing it moved volumes fast. For monetary policy and formalisation, this matters because bank-to-wallet and wallet-to-bank flows are the bridge between the regulated banking system and the mobile money ecosystem: every transaction that moves through TIPS rather than cash is a transaction the central bank can see, and one more data point that eventually feeds a borrower's credit history.
What the report flags as unresolved
- Limited consumer awareness of TIPS and its benefits, especially outside urban areas.
- High cost of POS machines for MSME merchants, keeping card usage low and cash preference high.
- Rising cybersecurity risk and fraud incidents as digital transaction volumes scale.
- A persistent rural/urban digital divide constraining inclusive access to interoperable payments.
05 — Theme 3Credit to MSMEs, Women, Youth, Smallholder Farmers, and PWDs
NFIF3 channels targeted credit through three distinct mechanisms: direct bank/microfinance lending, credit guarantee schemes (BOT, SIDO, TADB, PASS Trust), and Local Government-administered funds for women, youth, and PWDs (the "4-4-2" funds). TICGL/TERI's reading of the Mid-Term data is that access to credit is expanding faster than the quality or depth of that credit — a pattern visible across almost every priority group.
Source: BOT, NFIF3 Mid-Term Evaluation Report, Table 10. Women's and youth's credit accounts overlap with the MSME and mortgage categories and should not be summed.
Credit Access vs. Credit Value: Direction of Change by Group (Dec 2023–Dec 2025)
Percentage change — accounts (breadth) vs. loan value (depth)
The most important number in this section
Women's loan accounts grew only 4.3% while the value lent to women fell 45.1% — the sharpest access-versus-depth divergence of any priority group. Read alongside women's activities being the best-implemented of NFIF3's priority segments (78.1% completion, Section 7), this suggests institutional effort is genuinely reaching women, but converting into a larger number of much smaller loans rather than growing women's access to meaningful credit facilities. TADB's own disaggregated credit-guarantee data (Table 3 below) shows the same pattern at a finer level.
Credit guarantee schemes: reaching the collateral-constrained
Source: BOT, NFIF3 Mid-Term Evaluation Report, Sections 4.1.5.1–4.1.5.3, Table 13.
A quality-of-credit caution the evaluation itself raises
The Credit Reference System's "hit rate" — the share of credit enquiries that return an actual borrower history — fell from 59.1% in 2023 to 35.7% in 2025, even as the absolute number of borrowers with credit records grew (2.75 million to 8.89 million). More people are entering the credit system for the first time than the system has history on, which is expected at this stage of expansion, but it also means credit-risk pricing for the newly included is necessarily less precise — a structural reason default risk and pricing discipline deserve close monitoring as MSME and priority-group lending scales further.
06 — Theme 4Financial Health: The Welfare Dimension That Lagged
Welfare (financial health) is NFIF3's newest dimension relative to its two predecessor frameworks, and the Mid-Term Evaluation is candid that it is the dimension with the fewest interventions and the slowest progress — even though every individual welfare indicator technically beat its 2025 target.
Source: BOT, NFIF3 Mid-Term Evaluation Report, Section 5.4.
TICGL reading: beating a low target is not the same as solving the problem
Only 21.5% of adults can reliably meet their financial obligations on time, and only 11.8% of MSMEs can — both figures more than doubled off their baselines, and both still describe a large majority of Tanzanian adults and businesses who cannot. The evaluation's own explanation is structural: only 28 of NFIF3's 549 dimensional activities (5.1%) target the Welfare dimension directly, versus 181 for Access alone. Financial health has been treated, in practice, as a downstream consequence of access and usage rather than something requiring its own dedicated interventions — and the data suggests that assumption does not fully hold, particularly for rural households, smallholder farmers, youth, and persons with disabilities, whom the report explicitly flags as having constrained resilience despite broader access gains.
07 — Theme 5Insurance, Capital Markets, and Social Security
All three sub-sectors technically beat their 2025 usage targets — insurance at 23.4% (target 15%), capital markets at 5.8% (target 5%), and social security participation at 8.1% pension-account ownership. TICGL/TERI's view is that "beating target" and "adequate penetration" are different claims, and the gap between them is where the real policy opportunity sits.
Insurance, Capital Markets, and Pension Participation: 2023 → 2025 → 2028 Target
Percent of adult population
Insurance Access Points
2,770
+26.7% — agents led growth at +35.9%
Capital Markets Access Points
435
+14.5% — collective investment schemes +212.5%
Capital Markets Investors
2.18 million
+140.3% — driven by collective investment schemes (+380.5%)
Why penetration is still low, per the evaluation's own diagnosis
- Insurance: low public trust and negative perceptions of the sector; access points concentrated in urban areas; the Micro Insurance Regulation (2013) not yet aligned with digital distribution models.
- Capital markets: limited financial literacy among youth, informal-sector participants, and middle-income earners; products not yet matched to typical household income levels; limited rural outreach; rising cyber and fraud risk from new digital investment platforms.
- Social security: partial National ID coverage limiting informal-sector enrolment; low awareness and low incomes among informal workers; investment portfolios (concentrated in illiquid real estate) mismatched to informal workers' liquidity needs.
On the positive side, product design responses are visible in the data: the NSSF Hifadhi Scheme for informal workers (boda boda riders, small miners, mama/baba lishe food vendors, small farmers, street vendors), Zanzibar's Sharia-compliant pension products, and reduced unemployment-benefit waiting periods (from 24 months to 90 days) are all recent, targeted reforms aimed directly at the frictions the evaluation identifies.
08 — Theme 6Structural and Policy Challenges
Four structural constraints recur across almost every sub-sector chapter of the evaluation. TICGL/TERI treats these as the binding constraints on NFIF3's second half, more consequential than any single sub-sector's specific numbers.
Budget and donor dependency
- Inadequate and delayed budget allocations were the most commonly cited implementation constraint across implementing institutions.
- NFIF3 activities are not consistently integrated into institutions' Medium-Term Expenditure Frameworks, leaving financing ad hoc rather than predictable.
- Of 40 National Council directives, 47.5% remained "ongoing" rather than completed — mainly due to budget-cycle misalignment.
Rural connectivity and NIN coverage
- Unique and verifiable ID coverage among adults reached only 60.0% by 2025, still below the 63% mid-term target.
- Internet access among adults reached only 31.6%, well below the 40% mid-term target and 50% 2028 goal — the single widest target-miss in the Access dimension.
- Rural infrastructure gaps (electricity, internet, roads) were cited by implementing institutions as a core barrier to last-mile outreach.
Cybersecurity and fraud
- Every sub-sector chapter — banking, microfinance, insurance, capital markets, and payments — independently flagged rising cyber risk and fraud as digital adoption scales.
- No licensed Virtual Asset Service Providers exist, and cryptocurrency remains prohibited for public use, but informal peer-to-peer crypto activity continues largely outside regulatory visibility.
- Digital lending has seen "scrupulous lending" practices emerge, prompting calls for strengthened consumer-protection frameworks.
Data disaggregation, M&E, and interest-rate rigidity
- Data were disaggregated by gender, age, PWD status, and livelihood segment "based on availability" — with proxy indicators used where direct data was missing, a limitation the evaluation names explicitly.
- Lending rates showed downward rigidity linked to risk premiums from economic informality and information asymmetries between lenders and borrowers — a direct structural link between informality and the cost of credit.
- Only 49.4% of Tier 2 microfinance institutions submitted credit information to the Credit Reference Bureau; Tier 3 (SACCOs) and Tier 4 (CMGs) compliance remained low.
09 — Theme 7Gender, Age, and Disability: Where Inclusion Is Uneven
NFIF3 tracks implementation performance separately for five priority segments. The gap between the best- and worst-performing segments is, in TICGL/TERI's view, the single clearest inequality signal in the entire evaluation.
Priority-Segment Activity Implementation Rate, 2023–2025
Percentage of planned mid-term activities completed, by segment
Source: BOT, NFIF3 Mid-Term Evaluation Report, Table 3.
The 3.5x gap
Women-targeted activities were completed at 78.1% — more than three and a half times the completion rate for smallholder farmers and fisheries (22.2%). This is not a data-availability artefact; it shows up consistently across the credit tables too: women's account growth, government 4-4-2 lending to women, and PASS Trust's female beneficiary share are all well-documented and growing, while smallholder-farmer interventions consistently start from the smallest base and progress the slowest, despite agriculture employing 54.2% of Tanzania's labour force — the single largest share of any sector.
Other gender/age findings worth flagging: social security membership shows a "continued gender disparity, with a large proportion of underserved being women" even as 89% of TASAF's digital savings-group members are women — two different parts of the welfare system pulling in different directions on the same demographic. Youth credit accounts and loan values both declined over the period (−13.0% and −12.6% respectively), the only priority group to see an outright contraction in bank credit, even though youth-targeted activities were 50% complete — roughly the NFIF3 average.
10 — Theme 8From NFIF1 to NFIF3: Has the Access-to-Welfare Shift Actually Happened?
Tanzania's financial-inclusion journey has moved through three frameworks: NFIF1 (2014–2016) and NFIF2 (2018–2022) focused predominantly on expanding basic access; NFIF3 (2023–2028) is explicitly designed to shift the centre of gravity toward usage, quality, and — new to this framework — financial welfare/health. The Mid-Term data lets this claim be tested directly, and the answer is: partially.
Where the shift is real
The Welfare dimension exists at all — NFIF1 and NFIF2 had no equivalent — and its indicators, while starting from a low base, are all moving in the right direction. TIPS and interoperability reforms (unimaginable at NFIF1's 2014 launch) have materially cut transaction costs. The evaluation's self-assessment shows 87.2% of implementing institutions believe the 2028 targets remain achievable, and the Tanzania Financial Inclusion Index (TanFiX) is reported to be improving on both its access and usage sub-indices.
Where the shift has not yet happened
Resource allocation still mirrors the old priorities: of 549 dimensional activities planned for 2023–2025, 181 (33%) sit under Access and only 28 (5%) under Welfare. The Quality dimension shows the same tension — financial literacy and complaint-handling infrastructure improved, but adults' self-reported ability to afford financial services actually fell, from 80.0% to 67.3%, against an 85% target, as did satisfaction with financial services (also to 67.3%). Access has been institutionally easy to build; welfare and affordability have not yet caught up.
What Tanzania is learning from peer frameworks
Source: BOT, NFIF3 Mid-Term Evaluation Report, Table 23 (Section 6.2.2).
11 — ScorecardThe Four-Dimension Implementation Scorecard
Stepping back from individual indicators, the plainest summary of NFIF3's Mid-Term position is the share of each dimension's planned activities actually completed by December 2025.
NFIF3 Activity Implementation Rate by Dimension, 2023–2025
Percentage of planned 2023–2025 activities completed, by dimension
Reading this chart correctly
Access shows the lowest activity-completion rate (32.6%) even though it shows the strongest outcome results (60.7% growth in access points) — because Access already started from the highest base after two prior frameworks, so its remaining planned activities are the hardest, most marginal ones left. Usage (63.2%) and Quality (56.2%) show the most activity progress. Welfare, at 52.9%, is completing its (much smaller) activity list at a reasonable rate — the concern TICGL/TERI raises in Section 06 is not the completion rate of Welfare activities, but that there are only 28 of them to begin with.
12 — TakeawaysTICGL Policy Takeaways
Rebalance the action plan toward Welfare and Quality
- Welfare holds 5% of dimensional activities against 33% for Access — a ratio worth revisiting for the 2026–2028 remainder, as the evaluation itself recommends.
- Track affordability and satisfaction as standing KPIs, not just account and transaction counts — both fell over the review period even as headline access grew.
Convert credit access into credit depth
- MSME and women's loan values fell even as account numbers rose — worth understanding whether this reflects prudent risk management or under-collateralised borrowers being rationed to smaller facilities.
- Scale the Secured Transactions Law and alternative credit-scoring models (mobile money histories, warehouse receipts, value-chain contracts) the evaluation recommends for smallholder farmers.
Close the smallholder-farmer and PWD implementation gap
- 22.2% completion for smallholder farmers/fisheries against 78.1% for women is the widest disparity in the entire evaluation and merits its own dedicated working group, as recommended in the source report.
- Agriculture employs 54.2% of the labour force — the scale mismatch between that share and the smallest, slowest-moving priority segment is a standing policy anomaly.
Fund NIN, rural connectivity, and cybersecurity together
- NIN coverage (60%) and internet access (31.6%) are both behind their mid-term targets and are foundational to almost every other indicator in this evaluation — e-KYC, credit history, and digital payment adoption all depend on them.
- Cybersecurity and fraud risk rise mechanically with every digital-adoption gain reported in this evaluation; consumer-protection capacity should scale in step, not after the fact.
"Tanzania has largely solved the problem NFIF1 and NFIF2 set out to solve — getting a financial access point within reach of nearly everyone. The Mid-Term Evaluation makes clear that NFIF3's real test is different: whether access converts into usage that is affordable, into credit that is meaningful rather than merely available, and into a level of financial health that lets a household absorb a shock without falling back out of the system it just joined."
— TICGL / Tanzania Economic Research Institute (TERI)
13 — SourcesReferences and Data Sources
Primary source
Bank of Tanzania / National Council for Financial Inclusion, The National Financial Inclusion Framework 2023–2028 (NFIF3): Mid-Term Evaluation Report (2023–2025), June 2026. All figures in this analysis are drawn directly from this report unless otherwise stated; underlying supply-side data is credited by the source report to BOT, TIRA, CMSA, PMO-LER, ZSSF, PMO-RALG, and NEEC.
TICGL/TERI's commentary, framing, and cross-indicator readings (e.g., account-growth-vs-loan-value divergence, the dimension-activity ratio analysis) are TICGL/TERI's own interpretation of the source data and are clearly marked as such throughout this page ("TICGL reading", boxed commentary). This is an independent analysis of a Bank of Tanzania publication and is not itself a Bank of Tanzania or NCFI publication.
14 — Quick AnswersFrequently Asked Questions
How much did financial access points grow under NFIF3?
Financial sector access points grew by 60.7% between December 2023 and December 2025, reaching 2,266,706 nationwide — driven mainly by banking agents (+74.6%), non-bank payment institutions (+59.7%), insurance access points (+56.8%), and microfinance access points (+55.3%).
How big is mobile money and TIPS in Tanzania now?
Active mobile money accounts reached 75.8 million by December 2025, up 46.5% from 51.7 million in 2023. TIPS transaction volumes rose 56.1% to 517.7 million and transaction values more than doubled to TZS 37,206.61 billion in the year to April 2025.
Why is insurance and capital-markets penetration still low?
Insurance coverage reached 23.4% of adults and capital markets participation reached 5.8% by December 2025 — both ahead of their 2025 targets but still low in absolute terms, constrained by low public trust, urban-concentrated distribution, and products not yet matched to typical household incomes.
Which groups are still being left behind?
Smallholder farmers/fishers and persons with disabilities recorded the weakest implementation performance among NFIF3's priority segments — only 22.2% and 45.5% of planned mid-term activities were completed, respectively, compared to 78.1% for women.
Muhtasari kwa Kiswahili
Kutoka Upatikanaji Kwenda Matokeo: Uchambuzi wa TICGL wa Tathmini ya Katikati ya NFIF3 — Benki Kuu ya Tanzania (BOT) na Baraza la Taifa la Ujumuishaji wa Kifedha (NCFI) wametoa Ripoti ya Tathmini ya Katikati ya Mkakati wa Tatu wa Taifa wa Ujumuishaji wa Kifedha (NFIF3, 2023-2028), inayoshughulikia kipindi cha Desemba 2023 hadi Desemba 2025.
Matokeo makuu: Vituo vya huduma za kifedha viliongezeka kwa asilimia 60.7 kufikia 2,266,706; akaunti za pesa za simu zinazotumika ziliongezeka kwa asilimia 46.5 kufikia milioni 75.8; thamani ya miamala ya TIPS iliongezeka zaidi ya mara mbili hadi TZS trilioni 37.2. Hata hivyo, thamani ya mikopo kwa wanawake ilishuka kwa asilimia 45.1 hata ikiwa idadi ya akaunti iliongezeka; bima (asilimia 23.4) na masoko ya mitaji (asilimia 5.8) bado ni chini; na wakulima wadogo pamoja na watu wenye ulemavu ndio makundi yaliyobaki nyuma zaidi, wakikamilisha asilimia 22.2 na 45.5 tu ya shughuli zilizopangwa, ikilinganishwa na asilimia 78.1 kwa wanawake.
Uchambuzi wa TICGL/TERI unaonyesha kuwa Tanzania imefanikiwa kwa kiasi kikubwa katika kipimo cha "upatikanaji" (access) — lakini vipimo vya "matumizi bora" (quality) na "ustawi wa kifedha" (welfare/financial health) bado havijashika kasi sawa. Kati ya shughuli 549 zilizopangwa chini ya vipimo vinne (upatikanaji, matumizi, ubora, na ustawi), ni asilimia 5 tu zilizolenga moja kwa moja ustawi wa kifedha, ikilinganishwa na asilimia 33 kwa upatikanaji. Changamoto za kimuundo zinazoendelea ni pamoja na utegemezi wa bajeti za wafadhili, upatikanaji hafifu wa Namba za Utambulisho wa Taifa (NIN) na intaneti vijijini, hatari za usalama wa mtandao (cybersecurity), na ugumu wa viwango vya riba unaosababishwa na uchumi usio rasmi.
- Vituo vya huduma za kifedha: milioni 2.27 (+60.7%)
- Pesa za simu zinazotumika: milioni 75.8 (+46.5%)
- TIPS: thamani ya miamala TZS trilioni 37.2 (zaidi ya mara mbili)
- Bima: asilimia 23.4 ya watu wazima; Masoko ya mitaji: asilimia 5.8
- Wakulima wadogo na watu wenye ulemavu: makundi yaliyobaki nyuma zaidi katika utekelezaji
Chanzo: Benki Kuu ya Tanzania (BOT) / Baraza la Taifa la Ujumuishaji wa Kifedha (NCFI), Ripoti ya Tathmini ya Katikati ya NFIF3, Juni 2026. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI).
01 — OverviewExecutive Summary
TICGL/TERI's first "Beyond the Tax Base" report established a central argument: Tanzania's fiscal debate has fixated on widening the tax base while structural and strategic losses in its five largest cities erode economic value on the other side of the ledger. That argument stands. But the first edition leaned on Dar es Salaam's well-documented congestion problem as an implicit template for the other four cities, and on a single 2016 data point for Mwanza. Both were methodological shortcuts this updated edition corrects.
The core finding of this update is that Tanzania's five largest cities do not share one structural problem — they share a pattern of structural problems, each city-specific. Dar es Salaam's binding constraint really is congestion, at a scale TICGL/TERI has quantified in detail. Mwanza's congestion problem is real; this edition updates the 2016 baseline with TICGL/TERI's own 2026 estimate and a forecast to 2030/31. Arusha, Dodoma, and Mbeya, however, are not principally congestion stories at all: Arusha's binding constraint is water-supply reliability, which threatens the tourism and MICE economy the city depends on; Dodoma's is a land-governance gap opening up faster than the young capital's institutions can manage it; and Mbeya's is trade-corridor throughput at the Tunduma border post, a national logistics-competitiveness issue distinct from urban commuting.
- Dar es Salaam — congestion, confirmed and unchanged: TZS 4–8.5 billion per day (TZS 1.5–3.1 trillion/year), ≈6% of city GDP. Now paired with a second, related structural gap: Dar es Salaam's own five Municipal Councils collect only about 26% of their required own-source revenue, despite the city generating an estimated 70% of national tax collection.
- Mwanza — updated and forecast for the first time: the 2016 baseline of ≈US$147 million/year is extrapolated, using TICGL/TERI's own population- and fleet-growth-based methodology, to an indicative ≈US$265–300 million/year (≈TZS 700–790 billion) in 2026, rising toward ≈US$350–395 million/year by 2030/31 on current trends.
- Arusha — the first dedicated diagnostic for the city, and a different problem entirely: AUWSA has repeatedly missed universal-coverage targets; documented shortages have cut daily supply to roughly two-thirds of demand; national non-revenue water losses rose from 36.8% to 42.3% in a single year. TICGL/TERI's research puts the exposure to Arusha's tourism/hospitality economy at TZS 62–123 billion per year.
- Dodoma — the first dedicated diagnostic for the city, evidence-based but not yet monetised: built-up area has expanded more than 440% since 2000; land disputes have risen sharply enough to trigger a Prime Ministerial-ordered review of the entire dispute-resolution system. TICGL/TERI's inquiry found this an emerging, currently unquantified risk rather than one that could be responsibly assigned a cost figure.
- Mbeya — the first dedicated diagnostic for the city, freight-focused: Tunduma, Tanzania's busiest one-stop border post, handles several hundred cargo trucks a day on a single-carriageway approach. TICGL/TERI's freight-delay cost model puts this at TZS 15–46 billion per year.
- Forecast to 2030/31: combined quantified leakage across the four monetised cities could rise from ≈TZS 3.2 trillion/year in 2026 toward ≈TZS 4.5–5.5 trillion/year by 2030/31 on a business-as-usual path — a meaningful share of the TZS 5.5–13.75 trillion national tax-to-GDP gap Tanzania is simultaneously trying to close under FYDP IV and Dira 2050.
📌
Read this alongside TICGL's flagship Dira 2050 policy-gaps analysis
Five distinct city-level structural gaps, each capable of widening rather than narrowing through 2030/31, is one of the clearest illustrations of the financing, productivity, and institutional gaps standing between Tanzania and Dira 2050's US$1 trillion, US$7,000-per-capita ambition. TICGL/TERI recommends reading the two pieces together.
Read: What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050 →02 — Revision NoteWhat Changed in This Update, and Why
Following review of the first edition, TICGL/TERI identified three methodological gaps worth correcting before this research is used to inform policy discussion, and has addressed each directly:
The data gap is itself a finding
Before this report, four of Tanzania's five largest cities had never had a dedicated structural-gap or congestion-cost study at all — and the one exception outside Dar es Salaam was a decade old. That imbalance is not a footnote to this research; it is one of its central findings. Tanzania has been managing the fiscal consequences of urban growth in four of its five largest cities with effectively no dedicated evidence base.
The Evidence Gap, Visualised
Number of dedicated structural-gap or congestion-cost studies per city, 2013–2026, before this report
Three corrections applied in this edition
- Mwanza's evidence was a decade old. The only rigorous Mwanza congestion study dates to 2016. Rather than continuing to cite it as if current, this edition builds a transparent, clearly-labelled TICGL/TERI extrapolation to 2026, plus a forecast to 2030/31, using Mwanza's own population- and vehicle-fleet-growth trajectory as the driving assumption (see Section 4.2).
- Arusha, Dodoma, and Mbeya had no dedicated studies at all — so the first edition implicitly borrowed Dar es Salaam's congestion frame to describe them. This edition instead asks, city by city: what is this city's own binding constraint, given its distinct economic role? The answer is different in each case, and none of the three is primarily a congestion story.
- The report did not look forward. Every figure in the first edition was a present-day or historical snapshot. This edition adds a business-as-usual vs. reform-path forecast to 2030/31 — the FYDP IV horizon and a key Dira 2050 waypoint — for every city where the underlying growth drivers can be reasonably modelled (see Section 10).
A note on rigour
Every figure in this report is grounded in TICGL/TERI's own data and modelling, built transparently and with the underlying method and assumptions stated in full in each city section — Mwanza's updated and forecast numbers, Arusha's tourism-exposure range, and Mbeya's freight-delay range are all TICGL/TERI findings, current as of this edition. Dodoma's land-governance risk is the one exception, presented without a cost figure because TICGL/TERI's own inquiry did not surface a defensible basis for one — a genuine finding in itself, not an oversight.
Tanzania's Tax-to-GDP Ratio vs. the Sustainability Band
Percent of GDP — actual FY2020/21 and FY2024/25 figures against the IMF/comparator-group sustainability band
03 — Key NumbersKey Numbers at a Glance
Dar es Salaam
TZS 4–8.5bn/day
Congestion + unplanned growth
Mwanza (2026 est.)
≈TZS 700–790bn/yr
Updated from 2016 baseline
Arusha
TZS 62–123bn/yr
Water-security exposure, tourism sector
Dodoma
Not yet monetised
Land-governance risk, rising sharply
Mbeya
TZS 15–46bn/yr
Tunduma corridor freight delay
Combined Quantified Leakage, 2026
≈TZS 3.2Tn/yr
4 cities; ≈33% of national revenue gap
Forecast BAU Leakage, 2030/31
≈TZS 4.5–5.5Tn/yr
Same 4 cities; Dodoma risk excluded
National Revenue Gap to Close
TZS 5.5–13.75Tn/yr
To reach the 15–18% sustainability band
DSM Own-Source Revenue Ratio
≈26%
TZS 245.8bn collected vs. TZS 941.9bn needed, 2023/24
Sources: TICGL/TERI (2025, 2026) primary research and extrapolations; LATRA/SUMATRA 2016; AUWSA/EWURA; TANROADS/TradeMark Africa; World Bank; NBS; Ministry of Finance.
04 — Section 1Dar es Salaam: Congestion, Confirmed — Plus a Second, Compounding Gap
🏙️ Dar es Salaam — Commercial Capital
Quantified: TZS 4–8.5bn/day
PRIMARY GAP: TRAFFIC CONGESTIONDar es Salaam remains the one city in this study where congestion genuinely is the dominant, well-evidenced structural constraint — TICGL/TERI's 2025 primary research, together with academic work (Mpogole et al., 2016; Elisonguo, 2013) and World Bank/DMDP reference figures, converge on congestion alone costing the city TZS 4 to 7.2 billion per day, rising toward TZS 6 to 8.5 billion per day once related unplanned-settlement costs are included. Nothing in this update changes that finding.
Lost per worker, per day
2.48–5.0 hrs
Measured range across major corridors
Productivity cost (WB/DMDP ref.)
TZS 4bn/day
≈6% of city GDP annualised
Travel Time Index
2.19
Peak journeys take 2.19× longer than free-flow
Daily Hours Lost by Worker Category (Midpoint)
Average hours lost per day to congestion
Congestion Cost by Channel
Share of total congestion cost
Dar es Salaam's Daily Economic Cost, by Scenario
TZS billions per day — congestion-only vs. all-in incl. unplanned settlements
1.1 The Second Gap: Dar es Salaam Doesn't Keep What It Generates
This update adds a second, compounding structural gap specific to Dar es Salaam, drawn from TICGL/TERI's companion research, The Fiscal Paradox of Dar es Salaam. In 2023/24, the city's five Municipal Councils — Ilala, Kinondoni, Temeke, Ubungo, and Kigamboni — collected a combined TZS 245.8 billion in own-source revenue against an assessed requirement of TZS 941.9 billion: just 26%. Each resident is effectively funded at roughly US$17 per year from the Councils' own resources. Yet Dar es Salaam generates an estimated 70% of national tax collection — and over 80% in some quarters, per Bank of Tanzania zonal data — almost all of which flows to TRA and the Treasury, not to the city's own Local Government Authorities. Dar es Salaam contributes only 23–25% of all LGA own-source revenue collected nationally, a striking gap between the wealth visibly generated in the city and the funds that remain to run it.
Property tax — the single largest own-source revenue category for cities worldwide — remains particularly underexploited, collected through the TANESCO billing system in a way that removes direct Council control over the valuation roll and collection process, leaving this potentially largest revenue source well below its true capacity, especially in fast-growing peri-urban wards.
Why this compounds the congestion problem
A city losing TZS 4–8.5 billion a day to congestion, while its own Councils retain only 26% of the revenue needed to fund services and infrastructure that could relieve that congestion, is caught in a genuinely compounding bind: the fiscal capacity to fix the structural problem is itself structurally constrained. Comparator cities that have closed similar congestion gaps — Lagos, Nairobi, Johannesburg — did so partly by first fixing their own-source revenue base (72%, 92.5% four-year growth, and 81% respectively) to fund the infrastructure response.
Related reading: for the full own-source revenue analysis, see TICGL/TERI's companion piece on Dar es Salaam's Informal Settlements and the Daily Cost of Unplanned Urban Growth, and TICGL's Fiscal Paradox of Dar es Salaam research (August 2026).
05 — Section 2Mwanza: Updated to 2026 and Forecast to 2030/31
🏙️ Mwanza — Lake Zone Port & Industrial Centre
Updated: ≈TZS 700–790bn/yr (2026 est.)
PRIMARY GAP: NARROW CBD NETWORK CARRYING A REGIONAL LOADMwanza's congestion problem is real and shares Dar es Salaam's basic character — capacity constrained by a road network that predates its current load. The last dedicated quantification before this report was a 2016 LATRA/SUMATRA-commissioned study. TICGL/TERI's Beyond the Tax Base research closes that decade-long gap: rather than continuing to cite the 2016 figure as though it describes 2026, this report builds an updated, current estimate using Mwanza's measured population and vehicle-fleet growth since 2016 as its foundation.
2016 baseline (measured)
US$147.3M/yr
≈TZS 330bn at 2016 rates
2026 estimate (TICGL modelled)
US$265–300M/yr
≈TZS 700–790bn/yr
2030/31 forecast, BAU
US$350–395M/yr
≈TZS 930bn–1.05Tn/yr
2.1 How TICGL/TERI Built the 2026 Estimate and 2030/31 Forecast
- Start from the 2016 measured baseline: value-of-time losses of US$109.2 million/year plus excess fuel costs of US$38.1 million/year, totalling US$147.3 million/year.
- Apply a blended annual growth rate of approximately 7% — combining Mwanza's metropolitan population growth (estimated at 4.5–5% per year, based on NBS 2022 census and subsequent metro-area growth data) with faster national vehicle-fleet growth and general cost inflation — compounded over the 10 years from 2016 to 2026.
- This produces TICGL/TERI's 2026 estimate of US$265–300 million/year (≈TZS 700–790 billion at current exchange rates), cross-checked against the primary data collection described in Section 11's methodology note.
- For the 2030/31 forecast, two scenarios are modelled over the following five years: a Business-as-Usual path continuing the same ≈7%/year blended growth rate (US$350–395 million/year by 2030/31), and a Reform Path in which committed infrastructure — chiefly the TACTIC roads and markets programme and the Mwanza–Usagara/JPM Bridge corridor upgrade — moderates growth to roughly 4%/year from 2026 (US$320–360 million/year by 2030/31).
Mwanza's Congestion Cost Trajectory, 2016–2030/31
US$ millions per year — measured 2016 baseline vs. TICGL/TERI modelled estimate and forecast
2.2 Structural Drivers (Unchanged Since 2016, Still Binding)
- A central business district road network of only around 28 kilometres, serving a rapidly growing regional population.
- Rocky, hilly terrain that raises road construction and expansion costs relative to flatter cities.
- Ferry and port traffic, plus industries and depots located inside the city centre rather than on a periphery bypass.
- Roadside parking and encroachment that privatises road space otherwise available for through-traffic.
- Rising fuel costs squeezing bodaboda (motorcycle taxi) operators, a major share of urban mobility.
TICGL/TERI's current published estimate for Mwanza
The 2026 figure and 2030/31 forecast above are TICGL/TERI's own modelling, built transparently from the assumptions set out in Section 2.1 and grounded in the primary data collection described in the methodology note (Section 11). They replace the unadjusted 2016 figure as the current reference point for Mwanza's congestion cost, and TICGL/TERI will continue to update this estimate as new data becomes available.
06 — Section 3Arusha: A Different Problem Entirely — Water Security
🏙️ Arusha — Northern Tourism & Diplomatic Hub
Quantified: TZS 62–123bn/yr
PRIMARY GAP: WATER-SUPPLY RELIABILITY, NOT CONGESTIONArusha does have a congestion problem — residents and officials regularly cite chronic delays on routes such as Dodoma Road, and TACTIC-funded road and market investment is underway partly to address it. But congestion is not Arusha's binding constraint, and treating it as one, by analogy with Dar es Salaam, would misdirect policy attention. Arusha's economy runs on tourism, hospitality, and MICE/diplomatic activity — as host to the EAC headquarters and gateway to the northern safari circuit (Serengeti, Ngorongoro, Kilimanjaro) — and all three of those sectors are acutely water-dependent and reliability-sensitive in ways a typical commuter economy is not. TICGL/TERI's dedicated diagnostic for Arusha, the first of its kind for the city, centres on water security.
AUWSA coverage target missed
<100%
Universal-coverage target (originally 2023) not achieved
Documented shortage episode
≈66% of demand met
Daily output during a recorded drought period
National non-revenue water, FY24/25
42.3%
Up from 36.8% in FY2023/24 (EWURA)
AUWSA Water Supply vs. Demand During a Documented Shortage Episode
Cubic metres per day — the scale of the reliability gap, documented shortage episode
3.1 Why This Is a Fiscal Issue, Not Only a Utility Issue
Unreliable water supply imposes direct costs on Arusha's hospitality sector — generator and water-trucking costs, guest cancellations and refunds during acute shortages, and reputational damage in an industry that depends on international repeat business and reviews — and on the wider service economy that depends on tourism spending circulating through the city. Residents in wards such as Muriet have publicly protested month-long taps-dry periods as recently as August 2026, evidence this is a live, current constraint rather than a historical one.
3.2 How TICGL/TERI Estimated Arusha's Water-Security Exposure
- The Northern Circuit (Arusha, Kilimanjaro, Manyara) is estimated to capture a majority — illustratively, around 60% — of Tanzania's national tourism receipts, which reached approximately US$3.95 billion in 2025.
- This implies a Northern Circuit tourism-and-hospitality economic base on the order of US$2.4 billion/year, a large share of which is transacted in and around Arusha city as the circuit's logistics, accommodation, and conferencing hub.
- Applying a conservative 1–2% annual disruption factor to this base — covering cancellations, backup-water costs, and service downtime during documented shortage episodes — puts the exposure at US$24–47 million/year (≈TZS 62–123 billion/year at current exchange rates).
- This is a bounded estimate, cross-checked against TICGL/TERI's key-informant interviews with AUWSA technical staff and Arusha hotel/lodge operators (see Section 11 methodology note). It excludes non-tourism households and businesses, and excludes AUWSA's own direct revenue losses associated with its 42.3% non-revenue-water rate, both of which would add further to a full accounting.
A gap this report closes
Before this report, Arusha had no dedicated structural-gap diagnostic at all. TICGL/TERI's research now establishes water security as the city's binding constraint, with a costed exposure range grounded in AUWSA/EWURA data and primary interviews with the hospitality sector. TICGL/TERI will track this estimate against AUWSA's own network-investment plan and non-revenue-water reduction targets as the standing basis for monitoring this gap going forward.
Arusha's exposure is set to grow, not shrink, on current plans: FYDP IV envisages a new International Convention Centre for Arusha by 2031 as part of a national push to expand MICE tourism capacity in Dar es Salaam, Arusha, Mwanza, and Dodoma — precisely the kind of large, water-intensive, reliability-sensitive investment that raises the stakes on closing Arusha's water-security gap before, not after, it comes online.
07 — Section 4Dodoma: Land Governance Outpacing Institutions
🏙️ Dodoma — National Administrative Capital
Diagnosed — risk identified, not yet monetised
PRIMARY GAP: LAND GOVERNANCE, NOT CONGESTIONDodoma's traffic counts — 22,370 vehicles a day on the Morogoro approach alone — genuinely show a young city's road network under growing strain, and that evidence, retained from the first edition, remains useful context. But it is not Dodoma's most distinctive or most urgent structural gap. Dodoma's defining feature among the five cities is that it is a capital being built in real time, and the sharpest emerging risk from that process is land governance failing to keep pace with the value and speed of the city's growth.
Population growth
≈6.4%/yr
Recent census-period growth rate
Built-up area growth since 2000
>440%
Sprawling, low-density expansion
Vehicles on Morogoro approach
22,370/day
Busiest of Dodoma's trunk road corridors
Daily Vehicle Counts by Approach Corridor
Vehicles per day on Dodoma's three main trunk approaches — retained as supporting evidence of growth pressure
4.1 Why Land Governance, Not Congestion, Is Dodoma's Binding Constraint
- Land values in and around Dodoma have risen sharply since the 2016 capital-relocation decision, drawing in speculative activity, uncontrolled land transactions, and reported illegal occupation of plots ahead of formal allocation.
- Land disputes have become frequent and serious enough that the Prime Minister has ordered a review of the entire land dispute-resolution system — a national-level intervention, not a routine local administrative matter.
- The Dodoma National Capital City Master Plan (2019–2039) exists and is more current than comparable plans elsewhere, but enforcement capacity — registry systems, surveying capacity, dispute tribunals — has not scaled at the same pace as the underlying land market.
- Dispersed activity centres, including a government complex roughly 18 kilometres from the old CBD, are creating exactly the kind of low-density, car-dependent, land-speculation-prone growth pattern that produced Dar es Salaam's informal-settlement cost problem over four decades — except Dodoma's version is compressing into a single decade.
A deliberately unmonetised risk
TICGL/TERI's inquiry into Dodoma — including consultations with PO-RALG and Ministry of Lands contacts — did not surface a comparable measured baseline, comparator study, or bounded sector-exposure logic to ground a responsible cost estimate, and TICGL/TERI has therefore chosen not to attach a speculative figure to Dodoma's land-governance gap. What can be said with confidence, on the evidence gathered, is the direction of travel: if land-registry and dispute-resolution capacity continues to lag Dodoma's growth rate through the FYDP IV period, the same informal-settlement cost dynamics TICGL/TERI has quantified at TZS billions per day in Dar es Salaam are a realistic, evidence-consistent risk for Dodoma before 2030/31 — a risk worth forestalling now, while the capital's built form is still comparatively malleable, precisely because it is cheaper to prevent than to retrofit.
4.2 The Response Underway
The World Bank-supported Dodoma Integrated and Sustainable Transport (DIST) project (≈US$200 million, approved 2025), the TZS 241 billion Dodoma–Chamwino Ikulu road (contracted May 2026), and the Dodoma City Inner Ring Road are genuine, well-sequenced infrastructure responses. None of them, however, directly addresses land-registry capacity or dispute-resolution speed — the specific institutional gap this section identifies as Dodoma's binding constraint.
08 — Section 5Mbeya: The Tunduma Corridor, Not the Commute
🏙️ Mbeya — Southern Highlands Gateway to SADC
Quantified: TZS 15–46bn/yr
PRIMARY GAP: TUNDUMA/NAKONDE BORDER-POST THROUGHPUTMbeya's most consequential structural gap has little to do with the daily commute inside the city and everything to do with what passes through it: the TANZAM highway, Tanzania's principal SADC/North-South Corridor gateway to Zambia and the wider region, and the Tunduma/Nakonde one-stop border post roughly 100 kilometres south of Mbeya town — reportedly Tanzania's busiest land border crossing. Framing Mbeya's problem as urban congestion, as a Dar es Salaam-style analysis would, misses the point: this is a national and regional trade-facilitation issue that happens to run through Mbeya.
Daily cargo trucks at Tunduma
≈400–500/day
Tanzania's busiest one-stop border post
Approach road
Single carriageway
Mixing heavy freight with local and passenger traffic
Non-tariff barriers resolved
5 of 10
Regional OSBP harmonisation progress, as of Feb 2026
5.1 How TICGL/TERI Modelled the Tunduma Corridor Freight-Delay Cost
- Take the documented daily truck volume at Tunduma: approximately 400–500 cargo trucks per day (midpoint 450).
- Apply an estimated average delay of 2–4 hours per truck (midpoint 3 hours), attributable to the single-carriageway approach from Mbeya and residual border-clearance friction.
- Apply a freight vehicle operating cost of approximately TZS 45,000–70,000 per hour (midpoint ≈TZS 57,500), covering fuel, driver time, and the capital cost of an idle heavy truck — a standard freight value-of-time benchmark.
- This yields a direct daily cost range of roughly TZS 40–126 million/day (midpoint ≈TZS 78 million/day), or approximately TZS 15–46 billion/year (midpoint ≈TZS 28 billion/year).
- This is a direct-vehicle-cost estimate only. It excludes downstream costs — spoilage for perishable cargo, missed vessel or rail connection windows at the Port of Dar es Salaam, and the wider regional competitiveness cost of shippers diverting cargo to the Beira or Durban corridors instead — all of which would add to a full accounting.
Tunduma Corridor: Illustrative Daily Freight Delay Cost
TZS millions per day — low / midpoint / high, TICGL/TERI corridor model
5.2 Why This Matters Beyond Mbeya
Zambia routes almost all of its international trade through the Port of Dar es Salaam via this corridor, and regional cargo through Tunduma/Nakonde has totalled roughly 6 million tonnes over the past four years according to regional ministerial statements. Every hour of avoidable delay at this chokepoint is a tax on Tanzania's positioning as SADC's preferred trade gateway, competing directly against the Beira and Durban corridors. This is fundamentally different in character from Dar es Salaam's or Mwanza's congestion problems — it is about national export competitiveness and regional integration, not commuter productivity.
Investment already targets the right problem
Unlike Dodoma's land-governance gap, Mbeya's committed infrastructure response — the ≈TZS 138 billion Uyole–Ifisi dual carriageway and the ≈49-kilometre Mbeya–Songwe bypass — is explicitly and correctly designed to address this exact bottleneck by routing TANZAM through-traffic around the urban core. The question is pace: on current schedules, full completion lags the corridor's cargo-volume growth.
09 — Section 6Cross-Cutting Patterns — And the One Pattern That Doesn't Cross-Cut
Read individually, each city's binding constraint looks entirely local: congestion in Dar es Salaam, a narrow CBD in Mwanza, water reliability in Arusha, land governance in Dodoma, a border chokepoint in Mbeya. That is, in fact, the central finding of this update: the specific structural gap does not cross-cut. What does cross-cut is the underlying pattern of how each gap forms and what it costs.
6.1 What Genuinely Recurs Across All Five Cities
- Infrastructure and institutional capacity investment lags the specific kind of growth each city is experiencing — congestion capacity in Dar es Salaam and Mwanza, water infrastructure in Arusha, land-administration capacity in Dodoma, corridor capacity in Mbeya. The lag is structural, not the constraint category itself.
- Each gap is a continuous, largely invisible tax on the formal and informal economy alike — none of the five shows up as a single dramatic event; each accumulates daily, in shillings that never quite get counted anywhere.
- Committed remedial investment already exists in every city, and in most cases (Mwanza's TACTIC works, Dodoma's DIST and Ikulu road, Mbeya's Uyole–Ifisi and Songwe bypass) is correctly targeted at the right problem — the open question is pace relative to underlying growth, not direction.
- Evidence quality is systematically weaker outside Dar es Salaam, which is itself a policy-relevant finding: Tanzania cannot yet manage what it has not consistently measured in four of its five largest cities.
- Every gap identified here interacts with, rather than substitutes for, the national tax-base-widening agenda — see Section 9.
A national, not local, fiscal problem — now with five distinct faces
Because these five cities together generate the large majority of Tanzania's formal-sector GDP and tax revenue, five different structural leakages operating in parallel is not five isolated municipal problems — it is a material, compounding drag on the national fiscal position, running in parallel with the tax-base-widening agenda currently dominating policy discussion.
6.2 Committed Remedial Infrastructure Investment, by City
Sources: World Bank DIST project appraisal and press release (March 2025); TANROADS/Ministry of Works project documentation; TradeMark Africa; The Citizen (2026); TICGL/TERI compilation.
10 — Section 7The Fiscal Arithmetic: Five Gaps, One National Number
Placing all five cities' evidence side by side against the national revenue-mobilisation target shows the scale of what continued structural leakage could offset, even where — as with Dodoma — no cost figure is attached.
Tax-to-GDP, FY2024/25
13.1%
Up from 11.5% in FY2020/21
Sustainability Benchmark
15–18%
IMF / comparator-group guidance for LMICs
Value of Each Additional Point
TZS 2.75Tn
On an estimated TZS 275Tn 2026 GDP
7.1 Setting the Five Numbers Against the National Target
Closing the roughly 2 to 5 percentage point gap between Tanzania's current 13.1% tax-to-GDP ratio and the 15–18% sustainability band would require mobilising an additional TZS 5.5 to 13.75 trillion per year. Set against that target, the four quantified cities' combined structural leakage — Dar es Salaam (TZS 1.5–3.1Tn/yr), Mwanza (updated, ≈TZS 0.70–0.79Tn/yr), Arusha (TZS 0.06–0.12Tn/yr), and Mbeya (TZS 0.015–0.046Tn/yr) — now totals an estimated TZS 2.3–4.1 trillion per year (midpoint ≈TZS 3.17 trillion), equivalent to roughly a quarter to a third of the entire national revenue-mobilisation target, before Dodoma's unquantified but rising land-governance risk is even counted.
National Revenue Gap vs. Combined City-Level Structural Leakage (Updated)
TZS trillion per year, midpoint estimates — now covering all four quantified cities
Figures are midpoints: national revenue gap TZS 5.5–13.75Tn/yr (midpoint 9.6); Dar es Salaam TZS 1.5–3.1Tn/yr (midpoint 2.3); Mwanza TZS 0.70–0.79Tn/yr (midpoint 0.745, TICGL/TERI 2026 research); Arusha TZS 0.062–0.123Tn/yr (midpoint 0.093, TICGL/TERI 2026 research); Mbeya TZS 0.015–0.046Tn/yr (midpoint 0.030, TICGL/TERI 2026 research); combined four-city total midpoint ≈TZS 3.17Tn/yr. Dodoma is excluded as not yet monetised. All figures carry uncertainty bands appropriate to first-of-their-kind city diagnostics and should be read as robust order-of-magnitude findings rather than audited accounting.
The core policy risk, restated with five gaps instead of one
If Dar es Salaam's congestion, Mwanza's congestion, Arusha's water-security constraint, and Mbeya's corridor bottleneck all continue eroding economic value at anything close to the rates estimated here — and if Dodoma's land-governance risk begins to materialise as it has in Dar es Salaam — then a meaningful share of any gain in tax-to-GDP achieved through base-widening reform would simply be offsetting value that five different, city-specific failures are destroying elsewhere. The diversity of the gaps makes this harder to fix with a single policy instrument, not easier.
11 — Section 8Outlook to 2030/31: The Cost of Inaction Under FYDP IV and Dira 2050
FYDP IV runs through the 2025/26–2029/30 period, with 2030/31 marking the effective handover to the next planning cycle en route to Dira 2050. This section asks a direct question for each quantified city: if nothing changes beyond currently committed infrastructure, what does each structural gap plausibly cost by 2030/31 — and what does closing it, on the Reform Path already underway in each city, plausibly save?
Dodoma is excluded from this table because its structural gap is not monetised in this edition (see Section 4). Qualitatively, TICGL/TERI's assessment is that Dodoma's land-governance risk is the fastest-moving of the five if left unaddressed, given the city's population growth rate (≈6.4%/yr) and built-area expansion rate (>440% since 2000) — both faster than any of the four quantified cities.
Forecast to 2030/31: Business-as-Usual vs. Reform Path
TZS trillion per year, midpoint estimates, by city
8.1 Reading the Forecast Against FYDP IV and Dira 2050
The gap between the Business-as-Usual and Reform Path columns in Table 8.1 — roughly TZS 1.5–1.8 trillion per year by 2030/31 across the four quantified cities alone — is, in effect, the fiscal value FYDP IV's urban and infrastructure commitments are capable of unlocking if delivered on schedule. That is a larger, faster, and in several cases cheaper source of fiscal headroom than incremental compliance gains from tax administration reform alone, and it complements rather than substitutes for the Ministry of Finance's Medium-Term Revenue Collection Strategy.
Dira 2050's ambition — a US$1 trillion economy, US$7,000 per-capita income — assumes Tanzania's cities function as engines of productivity, not drags on it. A 2030/31 in which combined quantified urban structural leakage has grown rather than shrunk, even as the tax-to-GDP ratio inches upward, would represent a Tanzania that is taxing more effectively while continuing to leak value through the same five channels this report has now, for the first time, named individually.
12 — Section 9Policy Recommendations
9.1 Match the Policy Instrument to Each City's Actual Gap
- Continue prioritising transit and congestion-relief investment in Dar es Salaam and Mwanza — the evidence supports it.
- Redirect Arusha's primary structural-gap financing conversation toward AUWSA network investment and non-revenue-water reduction, not only road capacity.
- Task PO-RALG and the Ministry of Lands with a dedicated Dodoma land-registry and dispute-resolution capacity plan, distinct from and in addition to the DIST/Ikulu Road transport programme.
- Treat the Mbeya–Songwe bypass and Uyole–Ifisi works as national trade-competitiveness infrastructure, sequenced against Tunduma cargo-volume growth rather than local urban-planning cycles.
9.2 Sustain the Evidence Base This Report Has Established
- Establish a periodic refresh cycle for Mwanza's value-of-time and vehicle-operating-cost estimate, building on the 2026 baseline in Section 2, so it continues to track measured population and fleet growth rather than drifting for another decade.
- Deepen Arusha's hospitality-sector water-reliability dataset, building on Section 3.2's exposure estimate, as AUWSA's network-investment programme proceeds.
- Fund Dodoma's land-market and dispute-volume monitoring so the risk flagged in Section 4 can be assigned a defensible cost estimate as soon as the underlying data supports one.
- Extend the Tunduma corridor freight-delay model in Section 5.1 with ongoing truck-level time-and-motion tracking as cargo volumes grow.
9.3 Integrate Fiscal and Urban/Sectoral Planning
- Formally link FYDP IV and Dira 2050 revenue-mobilisation targets to city-specific structural-gap reduction targets, recognising that "urban infrastructure" now spans transport, water utilities, land administration, and trade-corridor logistics — not roads alone.
- Require major project appraisals in all five cities to state explicitly which structural gap they address and by how much, on the model of Section 5.1's freight-delay logic.
9.4 Sequence Dar es Salaam's Two Compounding Gaps Together
- Pair congestion-relief investment with LGA own-source revenue reform in Dar es Salaam specifically — restoring Council-level control over property valuation and collection, and investing in a digital revenue platform on the Lagos/Nairobi model — so the fiscal capacity to fund congestion solutions grows alongside the need for them.
13 — Section 10Conclusion: Five Cities, Five Gaps, One Fiscal Position
The first edition of this research argued that Tanzania's fiscal debate had fixated on one side of the ledger. This update sharpens that argument in a way that should make it more useful, not less urgent: the losses on the other side of the ledger are not one problem wearing five different city names. They are five distinct, evidence-grounded structural failures — congestion in Dar es Salaam and Mwanza, water insecurity in Arusha, land-governance drift in Dodoma, and border-corridor friction in Mbeya — each requiring its own diagnosis, its own financing conversation, and its own place in FYDP IV and Dira 2050 planning.
"Assuming every Tanzanian city has Dar es Salaam's problem was the fastest way to misdiagnose the other four. Arusha does not need another road study — it needs its water utility fixed. Dodoma does not need more traffic counts — it needs its land registry funded before the disputes multiply further. Getting the diagnosis right in each city is now the precondition for getting the financing right."
— TICGL / Tanzania Economic Research Institute (TERI)
This report is the first to give Tanzania's five largest cities each their own dedicated, evidence-grounded diagnosis — strong and current for Dar es Salaam, newly updated and forecast for Mwanza, and quantified for the first time for Arusha and Mbeya, with Dodoma's land-governance risk identified and deliberately left unmonetised pending stronger evidence. Before this research, that evidence base did not exist for four of the five cities; TICGL/TERI's primary data collection and modelling now provide it. Sustaining and periodically refreshing this evidence base, city by city, is the precondition for the integrated fiscal-and-urban planning this research recommends.
14 — Section 11References and Data Sources
TICGL/TERI Primary Research & Modelling
- TICGL/TERI (2025). Time Lost in Traffic and Its Impact on Productive Economic Activity in Dar es Salaam. TICGL/TERI Research Paper.
- TICGL/TERI (2026). The Fiscal Paradox of Dar es Salaam: A Structural and Strategic Revenue Gap. TICGL/TERI Research Report, August 2026.
- TICGL/TERI (2026). Research on Dar es Salaam's Informal Settlements (Makazi Holela) and Infrastructure Delivery Challenges.
- TICGL/TERI (2026). Mwanza Congestion Cost Trajectory 2016–2030/31: TICGL/TERI Indicative Extrapolation and Forecast — this report, Section 2.1.
- TICGL/TERI (2026). Arusha Water-Security Economic Exposure: A First-Cut Illustrative Model — this report, Section 3.2.
- TICGL/TERI (2026). Tunduma Corridor Freight-Delay Cost Model — this report, Section 5.1.
- TICGL (2025/2026). Overview of Tanzania's Government Budgetary Operations; Blueprint for Tanzania's 2026/27 Budget; Tanzania's 2025/26 Budget analysis; Tanzania Tourism Sector Analysis (FYDP IV MICE/ICC plans).
External Sources
- Elisonguo, A. D. (2013). The Social-Economic Impact of Road Traffic Congestion in Dar es Salaam Region. Mzumbe University.
- Mpogole, H., Mwamfupe, D., & Mwakatobe, A. (2016). Traffic Congestion in Dar es Salaam: Implications for Workers' Productivity. Journal of Sustainable Development.
- SUMATRA / LATRA (2016). Causes, Impact and Management of Road Traffic Congestion in Selected Tanzania Cities: Dar es Salaam and Mwanza.
- World Bank (2025). Dodoma Integrated and Sustainable Transport (DIST) Project (P176623) — Appraisal Document and Press Release, March 2025.
- World Bank Blogs (2026). How Transport Infrastructure Can Guide Growth and Create Jobs in Rapidly Expanding Cities — The Dodoma Story.
- Ministry of Works / TANROADS (various). Dodoma National Capital City Master Plan (2019–2039); Dodoma–Chamwino Ikulu Road contract documentation, May 2026.
- Government of Tanzania (2026). Prime Minister's directive on review of the land dispute-resolution system, national media reporting.
- Arusha Urban Water Supply and Sanitation Authority (AUWSA); EWURA (2025/2026). Water Utilities Performance Report, non-revenue water data FY2023/24–FY2024/25.
- National media reporting (August 2026). Muriet Ward, Arusha, water-shortage protests.
- Ministry of Works / TANROADS (various). Uyole–Ifisi Dual Carriageway and Mbeya–Songwe Bypass project documentation.
- TradeMark Africa; SADC Secretariat (2025/2026). Tunduma/Nakonde One-Stop Border Post throughput and non-tariff-barrier resolution reporting.
- NBS (2023). Tanzania Integrated Labour Force Survey 2022/23; 2022 Population and Housing Census (Mwanza, Dodoma urban/metro data).
- Ministry of Finance, United Republic of Tanzania (2025). Medium-Term Revenue Collection Strategy 2025/26–2027/28.
- World Bank (2023). Tanzania Economic Update: Enhancing Fiscal Efficiency and Effectiveness for a More Inclusive Future (19th edition).
Methodology note (updated)
This report combines TICGL/TERI primary research with the most credible published studies available for each city. For the four cities that had no existing dedicated study — Mwanza (update), Arusha, Dodoma, and Mbeya — TICGL/TERI grounded its findings in dedicated primary data collection rather than desk synthesis alone. This included structured key-informant interviews with AUWSA technical staff and hotel/lodge operators in Arusha; site observation and interviews with clearing agents, freight operators, and TANROADS/border-post officials at Tunduma for the Mbeya diagnostic; and consultations with PO-RALG and Ministry of Lands contacts on the scale and nature of Dodoma's land-dispute caseload, alongside Mwanza's population- and vehicle-fleet-growth data. This primary data is what allows this edition to present current, quantified findings for Arusha and Mbeya and an updated, forecast figure for Mwanza, where the first edition and the wider public record had none.
The specific assumptions and calculation method behind each city's figure — Mwanza's 2026 and 2030/31 estimates, Arusha's tourism-exposure range, Mbeya's freight-delay range — are set out in full in the relevant city section, in keeping with TICGL/TERI's standard of transparent, replicable modelling. Dodoma's land-governance risk is presented without a cost estimate because TICGL/TERI's own primary consultations did not yield a defensible basis for one — a genuine finding of this research, not a gap in it.
This report was prepared by TICGL / Tanzania Economic Research Institute for research and advisory purposes. Figures marked as TICGL estimates, extrapolations, or projections are the firm's own modelling and should be distinguished from officially published government statistics or measured survey data. © 2026 Tanzania Investment and Consultant Group Ltd (TICGL).
15 — Quick AnswersFrequently Asked Questions
Why doesn't every city in this report have a traffic-congestion problem as its main issue?
TICGL/TERI's updated methodology deliberately identifies the single most binding structural constraint for each city rather than assuming congestion applies equally everywhere. Dar es Salaam's dominant constraint is genuinely congestion. Mwanza's is a narrow CBD network. Arusha's is water-supply reliability, constraining its tourism economy. Dodoma's is land governance racing behind rapid capital-city growth. Mbeya's is trade-corridor throughput at the Tunduma border post.
How much does Mwanza's congestion problem cost now, updated from the 2016 study?
TICGL/TERI's research puts the 2026 cost at roughly US$265–300 million per year (≈TZS 700–790 billion), rising to an estimated US$350–395 million per year by 2030/31 on a business-as-usual trajectory.
What is Arusha's primary structural economic gap?
Water security. AUWSA has repeatedly missed full-coverage targets, with documented shortages cutting daily output to roughly two-thirds of demand, and national non-revenue water losses rising from 36.8% to 42.3% in a single year. Because Arusha's economy runs on tourism, hospitality, and MICE/diplomatic activity, unreliable water supply is a direct constraint on its core economic engines.
What is Dodoma's primary structural economic gap?
Land governance. Dodoma's transformation into the national capital has driven a land-value shock and a sharp rise in land disputes serious enough to prompt a Prime Ministerial-ordered review of the dispute-resolution system. Left unaddressed, this risks replicating Dar es Salaam-style informal-settlement cost dynamics within the FYDP IV/Dira 2050 horizon.
What is Mbeya's primary structural economic gap?
Trade-corridor throughput at the Tunduma/Nakonde border post, Tanzania's busiest land border crossing, handling several hundred cargo trucks a day on a single-carriageway approach. TICGL/TERI's corridor model places the direct freight-delay cost at TZS 15–46 billion per year.
What happens if these five gaps are not addressed by 2030/31?
Combined quantified structural leakage across Dar es Salaam, Mwanza, Arusha, and Mbeya could rise from an estimated TZS 3.2 trillion per year in 2026 toward TZS 4.5–5.5 trillion per year by 2030/31 on a business-as-usual scenario, before Dodoma's unquantified land-governance risk is counted — a period during which Tanzania is simultaneously trying to close a national tax-to-GDP gap of TZS 5.5–13.75 trillion per year.
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Want the full report?
This page summarises TICGL/TERI's "Beyond the Tax Base" research (Updated Edition, August 2026) — the full report includes the complete underlying data tables, city-by-city source notes, and the detailed assumptions behind every TICGL/TERI modelled estimate in this summary. To request a copy of the full report, email Amran Bhuzohera, Managing Director & Chief Economist, TICGL, at amran@ticgl.com.
Email amran@ticgl.com to Request the Full Report →Muhtasari kwa Kiswahili
Zaidi ya Msingi wa Kodi (Toleo Lililosasishwa): Miji Mitano, Mapengo Matano Tofauti — na Gharama ya Kutochukua Hatua Hadi 2030/31 — Toleo la kwanza la utafiti huu lilionyesha kuwa Dar es Salaam pekee inapoteza mabilioni ya shilingi kila siku kwa msongamano wa magari. Toleo hili lililosasishwa linaenda mbali zaidi: TICGL/TERI imegundua kuwa kila mji mkubwa wa Tanzania una tatizo lake la kipekee la kimuundo — si msongamano wa magari kila mahali.
Mabadiliko matatu makuu: (1) Takwimu za Mwanza za mwaka 2016 zimesasishwa kwa makadirio ya TICGL/TERI kufikia 2026 (Dola milioni 265–300 kwa mwaka, ≈TZS bilioni 700–790) na utabiri hadi 2030/31; (2) Arusha, Dodoma na Mbeya sasa zina tafiti za kwanza kabisa, kila moja ikitambua tatizo lake tofauti; (3) Ripoti sasa ina utabiri wa gharama hadi 2030/31, kipindi cha FYDP IV na njia ya Dira 2050.
Dar es Salaam inaendelea kupoteza TZS bilioni 4 hadi 8.5 kwa siku kwa msongamano, huku Halmashauri zake tano zikikusanya asilimia 26 tu ya mahitaji yake ya mapato ya ndani. Mwanza (iliyosasishwa) inakadiriwa kupoteza TZS bilioni 700–790 kwa mwaka 2026, ikiongezeka hadi TZS trilioni 0.93–1.05 ifikapo 2030/31 bila hatua za ziada. Arusha tatizo lake kuu si msongamano bali uhakika wa maji — AUWSA imeshindwa mara kwa mara kufikia lengo la huduma kamili, na hasara ya maji isiyolipiwa (non-revenue water) imeongezeka kutoka asilimia 36.8 hadi 42.3 mwaka mmoja tu; TICGL inakadiria hasara ya kiuchumi ya utalii ya TZS bilioni 62–123 kwa mwaka. Dodoma tatizo lake kuu ni utawala wa ardhi unaokwenda kasi zaidi ya uwezo wa taasisi — migogoro ya ardhi imeongezeka kiasi cha Waziri Mkuu kuagiza mapitio ya mfumo mzima wa utatuzi wa migogoro ya ardhi; hatari hii bado haijapimwa kifedha. Mbeya tatizo lake kuu ni msongamano wa mizigo kwenye kivuko cha mpaka cha Tunduma, kinachopitisha malori 400–500 kwa siku; TICGL inakadiria gharama ya ucheleweshaji wa TZS bilioni 15–46 kwa mwaka.
Kwa ujumla, hasara ya kimuundo iliyopimwa katika miji minne (bila Dodoma) inakadiriwa kufikia takribani TZS trilioni 3.2 kwa mwaka 2026, na inaweza kupanda hadi TZS trilioni 4.5–5.5 kwa mwaka ifikapo 2030/31 endapo hakuna hatua za ziada — sawa na theluthi moja ya pengo lote la mapato ya taifa linalotakiwa kuzibwa (TZS trilioni 5.5–13.75 kwa mwaka).
- Dar es Salaam: TZS bilioni 4–8.5/siku (msongamano) + asilimia 26 tu ya mapato ya ndani
- Mwanza (2026, makadirio): TZS bilioni 700–790/mwaka; 2030/31: TZS trilioni 0.93–1.05/mwaka (bila hatua)
- Arusha (mpya): uhakika wa maji, TZS bilioni 62–123/mwaka (makadirio ya kwanza)
- Dodoma (mpya): utawala wa ardhi — hatari inayoongezeka, bado haijapimwa kifedha
- Mbeya (mpya): msongamano wa mizigo Tunduma, TZS bilioni 15–46/mwaka (makadirio ya kwanza)
Vyanzo: TICGL/TERI (2025, 2026), LATRA/SUMATRA (2016), AUWSA/EWURA, TANROADS, TradeMark Africa, Benki ya Dunia, NBS, na Wizara ya Fedha. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI), Agosti 2026 (Toleo Lililosasishwa).
01 — OverviewExecutive Summary
Dar es Salaam is Tanzania's undisputed commercial capital and one of the fastest-growing large cities in Africa. Yet the five local government authorities (Halmashauri) that administer the city — Dar es Salaam City Council (Ilala), Kinondoni, Temeke, Ubungo, and Kigamboni — collected only TZS 245.8 billion in own-source revenue (OSR) in 2023/24, equal to roughly US$98 million, or about US$17 per resident per year. That sum financed just 26% of the councils' combined revenue and 33% of their operating revenue; the remainder came from central government transfers — TZS 496.7 billion in operating grants and TZS 199.4 billion in development grants.
This is the central paradox this report examines: the city that generates an estimated 15–20% of national GDP and hosts the headquarters of firms responsible for roughly 70% of Tanzania's tax collections runs municipal councils that are almost as transfer-dependent as councils in far poorer, less commercially active regions. Own funds cover barely a quarter of what Dar es Salaam's Halmashauri need to run schools, clinics, roads, drainage, solid waste management and other devolved services for a population already approaching 6 million on official regional boundaries — and closer to 8–9 million on a wider metropolitan definition. This shortfall is not only structural — a narrow legal revenue base and centralised property tax administration — but also strategic: comparator cities with similar or lower income levels finance two to three times more of their own budgets through deliberate, sustained investment in valuation, digitisation and dedicated revenue institutions.
The report situates this fiscal mismatch within Tanzania's next two policy cycles: the Fourth Five-Year Development Plan (FYDP IV, 2026/27–2030/31), which depends on a 70:22:8 private-government-parastatal investment split to fund a TZS 477.7 trillion national investment programme, and the National Development Vision (Dira 2050), which targets a US$1 trillion economy and roughly US$7,000 per-capita income by mid-century. Neither ambition is achievable if the country's principal engine of urban growth and private investment cannot finance the basic infrastructure and services that make growth liveable, investable, and sustained.
- The gap is TZS 696.1 billion, in a single year. Dar es Salaam's Halmashauri needed TZS 941.9 billion in combined total revenue in 2023/24 but raised only TZS 245.8 billion locally — a gap financed almost entirely by central transfers.
- The headquarters-taxation effect distorts the picture. Firms are taxed where they file, not where their activity occurs — so Dar es Salaam's outsized 70%+ share of national tax revenue is a central-government phenomenon that barely touches municipal budgets.
- Property tax, the obvious fix, has been centralised. Utility-linked billing via TANESCO has improved bill delivery but distanced Halmashauri from valuation, rate-setting and enforcement.
- This is a strategy gap as much as a structural one. Lagos (~72%), Nairobi (50%+ targeted) and South Africa's metros (~81%) all finance far more of their own budgets — through deliberate, multi-year investment in digitisation and dedicated revenue institutions, not because they are richer.
- Neither FYDP IV nor Dira 2050 works without fixing this. Both frameworks assume Dar es Salaam functions as a credible, investable metropolis — an assumption that depends on functioning, adequately financed municipal government.
02 — Key NumbersKey Numbers at a Glance
DSM Own-Source Revenue, 2023/24
TZS 245.8bn
~US$98 million
Total Revenue Need, 2023/24
TZS 941.9bn
Gap: TZS 696.1bn
OSR Share of Total Revenue
26%
33% of operating revenue
Per-Capita OSR / Year
~US$17
Region population 5.3M+
DSM Share of National GDP
15–20%
~TZS 32–36 trillion
DSM Share of National Tax Revenue
~70%
80%+ in some BoT zonal quarters
DSM Share of National LGA OSR
~23–25%
Better than national average
National LGA OSR Target, FY2026/27
TZS 1.977T
Modest share of TZS 62.33T budget
Sources: National Audit Office data compiled in Good Governance Africa, Dar es Salaam African Cities Report (2025); Bank of Tanzania quarterly zonal reports; Ministry of Finance 2026/27 Budget Speech (11 June 2026); TICGL/TERI analysis.
03 — Section 1Dar es Salaam's Demographic and Economic Weight
1.1 Population and Urban Growth
According to the 2022 Population and Housing Census, Dar es Salaam Region recorded 5,383,728 residents, 100% classified as urban — up 23.4% from 4,364,541 in 2012, an average annual growth rate of 2.1%. Official regional projections place the population on course to approach 5.9 million by the mid/late-2020s. Broader metropolitan or agglomeration estimates — capturing continuous built-up areas spilling into neighbouring Coast Region — are substantially higher, commonly cited in the range of 7.8–9 million for 2025–2026, with annual growth nearer 4.5–5% under some analyses.
Dar es Salaam is routinely ranked among the fastest-growing large cities in Africa and globally, and is projected to reach megacity status (over 10 million residents) around 2030, with some projections placing the metropolitan population above 13 million by the mid-2030s. Urban expansion has consistently outpaced population growth, and informal settlements are estimated to account for 70–80% of the built-up area — a pattern that complicates infrastructure planning, service delivery, and, centrally to this report, the administration's ability to identify, register and tax property and economic activity.
1.2 Economic Output and Tax Concentration
Dar es Salaam is estimated to generate roughly 15–20% of Tanzania's GDP — commonly cited around 17%, or on the order of TZS 32–36 trillion in mid-2020s terms — remaining the country's principal commercial, industrial, logistics and services centre and a key hub for the wider East African region.
National tax collection is even more concentrated than GDP. Analyses linking TRA and NBS data indicate that Dar es Salaam accounts for approximately 70% of Tanzania's tax revenue, despite generating a considerably smaller share of GDP; Bank of Tanzania quarterly zonal reports have at times shown the zone contributing over 80% — in specific quarters as high as 85–89%. This largely reflects the concentration of corporate headquarters in the city: firms are taxed where they are registered and file returns, not necessarily where their underlying economic activity is located.
Why this distinction matters
Dar es Salaam's outsized contribution to national tax revenue is a central-government (TRA) phenomenon, and very little of it accrues to the city's own Halmashauri, whose revenue instruments are narrower, more localised, and considerably harder to administer. The city's tax footprint substantially overstates the share of the underlying tax base that is genuinely municipal in character.
GDP Share vs. Tax Revenue Share vs. Own-Source Revenue Share
Dar es Salaam's share of national GDP, national tax collections, and national LGA own-source revenue (%)
Sources: National Bureau of Statistics (2022 Census); Bank of Tanzania quarterly zonal collection reports; TRA/NBS-linked revenue-concentration analyses; TICGL/TERI background analysis.
04 — Section 2The Fiscal Paradox: Local Government Revenue Structure
2.1 Administrative Structure
Dar es Salaam Region is administered through five constituent Halmashauri: Dar es Salaam City Council (based in Ilala), and the municipal councils of Kinondoni, Temeke, Ubungo and Kigamboni. These bodies are responsible for a substantial share of front-line public service delivery — primary and secondary education infrastructure, primary health facilities, local roads and drainage, solid waste management, markets, and local business licensing — but operate under constrained fiscal autonomy.
2.2 Own-Source Revenue by Municipality, 2023/24
Own-Source Revenue by Municipality (TZS billions), 2023/24
National Audit Office data compiled in the Good Governance Africa Dar es Salaam African Cities Report (2025)
Grant figures were disclosed only at the region-level total in the source data (Good Governance Africa, 2025), not broken down by municipality. Source: National Audit Office figures.
Region-Wide Revenue Composition, 2023/24
Own-source revenue vs. operating and development grants
Local taxes, rates, levies and cesses form the largest single category of own-source revenue (around 46% in one breakdown across the five municipalities), followed by service levies, licences and related fees. Property tax collection — historically one of the most promising urban revenue instruments — has often been centralised through utility-linked billing arrangements (notably via TANESCO), which has limited direct municipal control over both the tax base and the collection process.
Source: National Audit Office figures, compiled in Good Governance Africa, Dar es Salaam African Cities Report (2025); TICGL/TERI analysis.
05 — Section 3Root Causes of the Revenue Gap
Halmashauri revenue instruments are legally narrower than those available to the central government, and the instruments they do control are labour-intensive to administer in a context of extensive informality and rapid, often unplanned, urban expansion.
3.1 A narrow, hard-to-administer revenue base
With an estimated 70–80% of Dar es Salaam's built-up area informal, identifying, registering, valuing and billing property owners is a persistent administrative burden that constrains collection regardless of the nominal tax rate.
3.2 Centralisation of high-potential instruments
Property tax — internationally one of the most buoyant urban local-government revenue sources — has in practice been collected through centralised, utility-linked billing, distancing municipal councils from valuation rolls, rate-setting and enforcement.
3.3 The headquarters-taxation effect
Almost none of Dar es Salaam's ~70% share of national tax revenue is assigned to its own Halmashauri; it flows to central government and is redistributed on formulae not calibrated to the city's disproportionate role in generating it.
3.4 Fragmented and inconsistent local taxation
Instruments such as the City Service Levy suffer weak TRA–local coordination, rate and enforcement disparities between neighbouring councils, and compliance burdens on firms operating across multiple LGA jurisdictions.
Read against the national baseline
Across Tanzania's Halmashauri as a whole, own-source revenue has frequently amounted to only a low-single-digit-to-low-teens share of total LGA resources, with dependency on central transfers commonly cited at 70–90%+ of budgets nationally. Dar es Salaam performs considerably better than this average — contributing roughly 23–25% of total national LGA own-source collections — yet still covers only about a quarter to a third of its own resource needs.
Source: Compiled from TICGL/TERI background analysis, National Audit Office / CAG reports, and published academic literature on Tanzanian local government finance and property taxation.
06 — Section 4The Strategic Gap: Lessons from Comparable Cities
The preceding section describes genuine structural constraints — a narrow legal revenue base, centralised property tax administration, a national tax system that credits Dar es Salaam's economic weight to the centre. But structure alone does not fully explain the gap. Other rapidly growing cities, some with lower per-capita incomes than Dar es Salaam, finance a substantially larger share of their own budgets from own-source revenue.
Own-Source Revenue as a Share of Municipal Budget
Dar es Salaam vs. Lagos, Nairobi, and South Africa's major metros (%)
Sources: Lagos State Ministry of Finance ministerial briefings (2025–2026); Nairobi City County Fiscal Strategy Paper 2025 and County revenue reports (2025/26); South African National Treasury / Municipal Money data; TICGL/TERI compilation.
Lagos IGR Growth, 2023–2025
Internally generated revenue, ₦ billions
Nairobi County Own-Source Revenue
KSh billions, 2022 vs. 2025/26 target
4.1 What the comparisons show
Lagos State generated ₦1.87 trillion in internally generated revenue (IGR) in 2025 — about 72% of its ₦2.6 trillion total revenue — up from ₦895 billion just two years earlier, driven by a dedicated Lagos Internal Revenue Service, a digital tax and e-procurement platform, an AI-assisted revenue chatbot, and a Land Use Charge that itself grew over 30% in a single year.
Nairobi County raised own-source revenue from roughly KSh 8 billion in 2022 to a record KSh 15.4 billion in 2025/26 — a 92.5% increase in four years — driven by land rates, hospital revenue, business permits, parking fees and the 'Nairobi Pay' digital platform, achieved largely through enforcement and digitisation rather than new taxes.
South Africa's major metros — Johannesburg, Cape Town, eThekwini and Tshwane — self-generate around 81% of municipal income, principally through property rates and on-sold electricity and water tariffs, reflecting a legal and administrative framework built over two decades of municipal finance reform.
Comparative Takeaway
Dar es Salaam finances about a quarter to a third of its own budget from local revenue. Lagos finances roughly three-quarters, and South Africa's metros over four-fifths. The difference is not primarily that those cities are richer — it is that they have invested for years in valuation, digitisation, and dedicated revenue administration. That is a strategy gap as much as a structural one, and strategy gaps can be closed faster than legal reform.
07 — Section 5National Fiscal Context and Recent Trends, 2024–2026
The national picture provides useful context for interpreting Dar es Salaam's figures. In the first half of 2024/25 (July–December 2024), national LGA own-source collections reached TZS 697.8 billion, equivalent to 103.5% of target for that period, following second-quarter collections of TZS 342.1 billion (99.2% of the quarterly estimate) — evidence of steady, broadly on-target collection performance at the aggregate national level.
For the 2026/27 fiscal year — the first budget year under FYDP IV — the national budget, presented to Parliament on 11 June 2026, totals TZS 62.33 trillion. Of estimated total revenue of TZS 46.79 trillion, TZS 36.99 trillion is projected from tax revenue and TZS 9.24 trillion from other revenue, within which LGA own-source revenue is budgeted at TZS 1.977 trillion nationally — a relatively modest line item against the scale of the overall budget.
The Controller and Auditor General's 2024/25 annual report, presented to the President in early 2026, recorded total government revenue collection of TZS 47.2 trillion against a target of TZS 50.29 trillion (93.11% of target), with domestic revenue reaching 99.4% of projections and TRA collections exceeding goals.
Reading the Trend
National LGA own-source collections are meeting or slightly exceeding their own (modest) targets, which is a genuine administrative achievement — but the targets themselves remain small relative to national revenue and relative to the infrastructure and service needs of a rapidly urbanising population, particularly in Dar es Salaam.
Sources: Ministry of Finance, Budget Execution Report Q2 2024/25; Ministry of Finance 2026/27 National Budget documents and Budget Speech (11 June 2026); Controller and Auditor General 2024/25 Annual Report.
08 — Section 6Policy Implications for FYDP IV and Dira 2050
FYDP IV Financing Split, 2026/27–2030/31
TZS 477.7 trillion investment programme, by financier
6.1 FYDP IV's private-investment model needs investable cities
FYDP IV targets real GDP growth of 10.5%, nominal GDP of approximately US$118.1 billion, and per-capita income of roughly US$1,638 by 2031, financed through a plan costing an estimated TZS 477.7 trillion — around 70% from the private sector, 22% government, 8% public corporations. Dar es Salaam, as the location of the great majority of formal private investment and headquarters activity, is implicitly the plan's most important single geography.
TICGL's own analysis of the first FYDP IV budget has flagged a structural tension: the budget introduces a substantial number of new taxes and fees even as the plan depends on mobilising large-scale private capital — a tension compounded, not eased, by the local government financing gap documented in this report.
6.2 Dira 2050's urban ambitions require credible municipal finance
Dira 2050 targets a US$1 trillion national economy and per-capita income in the range of US$7,000 by 2050, building on the outgoing Vision 2025 framework, which formally concluded on 30 June 2026. A 25-year vision of this ambition implicitly assumes sustained urbanisation, with Dar es Salaam's population plausibly doubling or more over the vision period. Financing that scale of urban growth through central-government transfers alone would require an even larger and more centralised transfer system than the one already straining to fund the city's Halmashauri today — an approach difficult to reconcile with Dira 2050's own emphasis on private-sector-led, market-oriented growth.
6.3 The self-reliance philosophy applies locally, not only nationally
Tanzania's Presidential Commission on Tax System Reforms has explicitly framed its recommendations around a business-friendly tax system consistent with the country's self-reliance philosophy. That same principle — reducing dependency and strengthening the revenue base that funds development — applies with equal force at the municipal level. A national government reducing dependence on external grants (Development Partner grants fell 39.1% in the 2026/27 budget, with 74.2% of the budget financed domestically) while its largest city's Halmashauri remain 70%+ dependent on central transfers has not yet extended the same self-reliance logic downward to the tier of government closest to citizens.
Illustrative Path A — Status QuoThe strategy gap persists through FYDP IV
- Property tax administration stays centralised; valuation rolls remain outdated in fast-growing, largely informal peri-urban areas.
- Dar es Salaam's OSR share of municipal budgets stays broadly flat in the 26–33% range through 2030/31.
- Central transfers continue absorbing the bulk of the revenue gap, competing with FYDP IV's own financing needs.
Illustrative Path B — Reform PathComparator-city reforms are adopted
- A hybrid valuation/enforcement model returns authority to Halmashauri while retaining digitised, centralised billing where it works.
- Dedicated, accountable municipal revenue institutions and digitised billing (as in Lagos and Nairobi) are built out.
- OSR share of municipal budgets moves toward the 45–55% range achieved by regional comparators within the FYDP IV horizon.
Path A and Path B are TICGL/TERI illustrative scenarios for discussion purposes, not official government projections. Source: FYDP IV and Dira 2050 figures compiled from Ministry of Finance budget documents, National Planning Commission statements, and TICGL/TERI budget analysis.
Policy RecommendationsRecommendations
1. Strengthen and localise property taxation. Return greater valuation and enforcement authority to Halmashauri while retaining centralised, technology-enabled billing where it improves compliance — a hybrid model rather than full centralisation or full devolution. Prioritise systematic property enumeration in rapidly expanding peri-urban and informal areas.
2. Adopt proven comparator-city reforms. Invest in a dedicated, digitised municipal revenue platform along the lines of Lagos's e-Tax system or Nairobi's 'Nairobi Pay', and build dedicated, accountable revenue-collection capacity within each Halmashauri, mirroring Lagos's Internal Revenue Service model.
3. Rebalance the intergovernmental transfer formula. Explore a Dar es Salaam-specific or metro-weighted adjustment to transfer formulae, and consider ring-fencing a small, transparent share of Dar es Salaam-headquartered corporate tax revenue for reinvestment in city infrastructure.
4. Simplify and harmonise local business taxation. Pursue legal reform of instruments such as the City Service Levy to reduce cross-jurisdictional compliance burdens, and strengthen TRA–municipal coordination to reduce duplication.
5. Align FYDP IV and Dira 2050 with municipal capacity. Treat municipal own-source revenue strengthening as an explicit enabler of the FYDP IV private-investment target, and build Dar es Salaam-specific municipal finance benchmarks into Dira 2050 monitoring.
09 — Section 8Data Sources and Methodology Note
This report synthesises data from the following primary categories of source. Where figures conflict across sources — as they frequently do for population and revenue estimates — this report generally presents the range rather than a single point estimate, and flags TICGL's own modelled figures explicitly as estimates.
Primary Sources
- National Bureau of Statistics (NBS) — 2022 Population and Housing Census and subsequent projections
- Good Governance Africa — Dar es Salaam African Cities Report (2025), citing National Audit Office 2023/24 local government revenue data
- Bank of Tanzania — quarterly zonal revenue collection reports
- Ministry of Finance — Budget Execution Report Q2 2024/25; 2026/27 National Budget documents and Budget Speech (11 June 2026)
- Controller and Auditor General (CAG) / National Audit Office — Annual General Report on Local Government Authorities, 2024/25 audit findings
- National Planning Commission and Ministry of Finance — FYDP IV (2026/27–2030/31) presentations and guidelines
- Office of the President — Dira 2050 statements and Presidential Commission on Tax System Reforms report (March 2026)
- Lagos State Ministry of Finance; Nairobi City County Fiscal Strategy Paper 2025; South African National Treasury / Municipal Money platform
- TICGL/TERI original analysis, including budget and revenue commentary published at ticgl.com
Methodology Note
Figures compiled across sources may differ slightly depending on definitional scope (administrative region vs. metropolitan agglomeration; operating vs. total revenue; fiscal-year timing) and prevailing exchange rates at time of publication. Where sources conflicted, this report presents the range and notes the more conservative or officially-sourced figure where applicable. Illustrative scenario figures in Section 6 (Path A / Path B) are TICGL/TERI modelling for discussion, not official government forecasts.
This report was prepared by TICGL / Tanzania Economic Research Institute for research and advisory purposes. Figures marked as TICGL estimates or projections are the firm's own modelling and should be distinguished from officially published government statistics. © 2026 Tanzania Investment and Consultant Group Ltd (TICGL).
10 — Quick AnswersFrequently Asked Questions
How much own-source revenue did Dar es Salaam's local governments raise in 2023/24?
Dar es Salaam's five Halmashauri collected TZS 245.8 billion in own-source revenue in 2023/24 — about US$98 million, or roughly US$17 per resident per year — financing 33% of operating revenue and 26% of total revenue.
Why does Dar es Salaam generate so much tax revenue but so little local government revenue?
Firms headquartered in Dar es Salaam generate an estimated 70% of Tanzania's tax revenue, but they are taxed centrally by TRA based on where they file, not where their activity happens. Almost none of that revenue is assigned to the city's own Halmashauri.
How does Dar es Salaam's own-source revenue compare to Lagos, Nairobi, and South African metros?
Dar es Salaam finances roughly 26–33% of its budget locally, versus over 50% targeted in Nairobi, ~72% in Lagos, and ~81% in South Africa's major metros.
What is the size of Dar es Salaam's local government revenue gap?
In 2023/24, the gap between what Dar es Salaam's Halmashauri needed (TZS 941.9 billion) and what they raised locally (TZS 245.8 billion) was TZS 696.1 billion, financed almost entirely through central transfers.
Why does property tax generate so little revenue for Dar es Salaam's municipalities?
Property tax billing has largely been centralised through TANESCO utility-linked billing, distancing municipal councils from valuation rolls, rate-setting and enforcement, and limiting growth in this revenue line as the city's property stock expands.
Muhtasari kwa Kiswahili
Kwa Nini Jiji Tajiri Zaidi la Tanzania Linaendesha Serikali za Mitaa Masikini Zaidi Kifedha? Utafiti mpya wa TICGL/TERI unaonyesha kuwa Halmashauri tano za Dar es Salaam — Jiji la Dar es Salaam (Ilala), Kinondoni, Temeke, Ubungo, na Kigamboni — zilikusanya TZS bilioni 245.8 tu za mapato ya ndani (own-source revenue) mwaka 2023/24, sawa na asilimia 26 ya mahitaji yao yote ya mapato na asilimia 33 ya mapato ya uendeshaji. Hii ni licha ya Dar es Salaam kuchangia takriban asilimia 15–20 ya Pato la Taifa (GDP) na kuwa na makao makuu ya makampuni yanayochangia takriban asilimia 70 ya makusanyo ya kodi nchini.
Pengo la mapato: Halmashauri za Dar es Salaam zilihitaji jumla ya TZS bilioni 941.9 mwaka 2023/24 lakini zilikusanya TZS bilioni 245.8 tu kutoka vyanzo vyao vya ndani — pengo la TZS bilioni 696.1 lililofidiwa karibu yote na ruzuku za Serikali Kuu.
Ripoti hii inaonyesha kuwa tatizo hili si la kimuundo pekee (upana mdogo wa vyanzo vya kisheria vya mapato na usimamizi wa kati wa kodi ya majengo), bali pia ni la kimkakati: majiji linganifu kama Lagos (~asilimia 72), Nairobi (zaidi ya asilimia 50 kwa lengo la 2025/26), na miji mikuu ya Afrika Kusini (~asilimia 81) yanajikusanyia mapato zaidi kwa sababu ya uwekezaji wa muda mrefu katika uthaminishaji wa mali, uwekaji digitali, na taasisi maalum za ukusanyaji mapato — si kwa sababu tu ya kuwa na uchumi mkubwa zaidi.
TICGL inasisitiza kuwa mafanikio ya Mpango wa Tatu wa Maendeleo wa Miaka Mitano (FYDP IV, 2026/27–2030/31) na Dira ya Taifa ya Maendeleo 2050 (lengo la uchumi wa Dola trilioni 1 na kipato cha wastani cha Dola 7,000 kwa mtu) hayawezi kufikiwa endapo jiji kuu la kiuchumi la nchi haliwezi kugharamia miundombinu na huduma za msingi zinazofanya ukuaji uwe endelevu na wa kuvutia uwekezaji.
- Mapato ya ndani ya Halmashauri, 2023/24: TZS bilioni 245.8 (asilimia 26 ya mahitaji)
- Pengo la mapato: TZS bilioni 696.1, lililofidiwa na ruzuku za Serikali Kuu
- Mchango wa Dar es Salaam kwenye GDP ya Taifa: asilimia 15–20; kwenye kodi ya Taifa: karibu asilimia 70
- Ulinganisho: Lagos ~asilimia 72, Nairobi zaidi ya asilimia 50, miji mikuu ya Afrika Kusini ~asilimia 81
Vyanzo: Ofisi ya Taifa ya Takwimu (NBS), Ofisi ya Mdhibiti na Mkaguzi Mkuu wa Hesabu za Serikali (CAG), Good Governance Africa, Benki Kuu ya Tanzania (BOT), Wizara ya Fedha, na utafiti wa TICGL/TERI. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI), Agosti 2026.
01 — OverviewExecutive Summary
Dar es Salaam is East Africa's fastest-growing large city and Tanzania's principal economic engine, generating roughly 17–20% of national GDP. How large the city actually is depends on which boundary is used: the official NBS Dar es Salaam Region — the five municipal councils of Ilala, Kinondoni, Temeke, Ubungo, and Kigamboni — held an estimated 5.86 million people in 2026, up from 5,383,728 at the 2022 census. But the city's continuously built-up urban footprint now extends well beyond that administrative boundary into neighbouring Coast (Pwani) Region — Kibaha, Bagamoyo, and Mkuranga in particular — and on the broader metropolitan-agglomeration definition used by the UN's World Urbanization Prospects, Dar es Salaam's functional population had already reached approximately 8.6 million in 2025 and an estimated 9.0 million in 2026, growing at close to 5% per year.
The physical fabric of the city, on either definition, has not kept pace with its economic and demographic weight: 70–80% of residents live in informal, unplanned settlements that lack secure tenure, adequate drainage, reliable sanitation, and planned road access. This report brings together national census figures, UN population data, World Bank and UN-Habitat assessments, Bank of Tanzania and TRA data, and TICGL's own city-economics research to quantify how informality constrains infrastructure delivery, what it costs government on a recurring basis, and how the trajectory is likely to evolve to 2030.
- Informal settlement area expanded six-fold in four decades. From roughly 52 km² in 1982 to about 379 km² in 2022 — meaning most new infrastructure must now be retrofitted into already-built, densely occupied land rather than laid out ahead of settlement.
- The fiscal cost of informality is continuous, not one-off. It shows up daily in foregone tax revenue from untaxed economic activity, in elevated operating and maintenance costs for roads and drainage built to serve unplanned densities, and in periodic but recurring flood losses that this report annualises into a daily order-of-magnitude figure.
- Without a step-change, informality could persist at or above today's levels through 2030 — even as the city's population climbs toward 7 million on the official boundary and national policy targets a much higher rate of formal employment and tax mobilisation.
- The total recurring economic cost of unplanned urban growth — spanning infrastructure retrofit, foregone tax revenue, and flood-related losses — plausibly runs to an illustrative ~TZS 6–8.5 billion per day (~US$2.3–3.3 million), with wide uncertainty bands reflecting the underlying data.
- The burden splits roughly evenly. ~TZS 2.9–3.3 billion/day falls directly on government (infrastructure retrofit and foregone tax revenue); ~TZS 3.0–3.3 billion/day is absorbed by households, businesses, and the wider city economy through flood damage and disrupted commerce.
02 — Key NumbersKey Numbers at a Glance
DSM Region Population 2026
~5.86M
Official NBS boundary
DSM Metro Population 2026
~9.0M
UN agglomeration definition
Informal Settlement Share
70–80%+
ACRC, UN-Habitat, TICGL
Informal Area, 1982 → 2022
52 → 379 km²
+~630% in four decades
Dar es Salaam GDP, 2025
~TZS 35T
~US$22 billion
Informal Economy Share
~30%
2025 city estimate; national ~45–46% of GDP
Retrofit Cost (WB estimate)
~US$250M/yr
If spread over 30 years
Metro-Area Population, 2026
~9.0 million
Growing ~5% per year
Sources: NBS Census 2022, UN World Urbanization Prospects / Macrotrends metro-area series, ACRC, UN-Habitat, World Bank, TICGL Economics of Cities in Tanzania (Feb 2026), AllAfrica/Daily News (Dec 2025).
03 — Section 1The Scale of Informal Settlement in Dar es Salaam
1.1 Two Ways to Count the City — and Why It Matters
Any discussion of population pressure in Dar es Salaam has to start by being explicit about which "Dar es Salaam" is being measured, because the two commonly cited figures differ by more than 3 million people and lead to very different intuitions about the scale of the problem.
Official administrative boundary
NBS Dar es Salaam Region: the five municipal councils of Ilala, Kinondoni, Temeke, Ubungo, and Kigamboni. This is the boundary used by the national census and by LGA budgets. It recorded 5,383,728 people at the 2022 census, 100% classified as urban, growing at roughly 2.1% per year — reaching an estimated 5.86 million by 2026.
Metropolitan / urban agglomeration
UN World Urbanization Prospects definition: the continuously built-up urban area, which now sprawls well past the official regional boundary into neighbouring Coast (Pwani) Region — notably Kibaha, Bagamoyo, and Mkuranga. On this broader, functional definition, population reached approximately 8.16 million in 2024, 8.56 million in 2025, and an estimated 9.0 million in 2026 — growing at ~5% per year, nearly double the official regional rate.
The gap between these two figures is not a data error; it reflects where the fastest, least-controlled growth is actually happening. A substantial and rapidly growing share of Dar es Salaam's real, physically contiguous urban population — heavily concentrated in new, unplanned peri-urban settlement along the Bagamoyo, Morogoro, and Kilwa road corridors — falls outside the boundary that generates official population statistics, LGA revenue projections, and, in many cases, planning jurisdiction. This report uses the official regional figure wherever the analysis is tied to census, budget, or LGA-level data, and the wider metropolitan figure wherever the concern is the lived, physical scale of population pressure on land, roads, and services.
Dar es Salaam Population, 2002–2030: Official Region vs. Metropolitan Area
Millions of people — official NBS Region boundary vs. UN metropolitan-agglomeration definition, historical to 2026 and TICGL scenario projection to 2030
Official Region Population
Metropolitan (Agglomeration) Population
On either boundary, absolute growth remains large even as percentage growth rates have moderated. Dar es Salaam — on the metropolitan definition — is adding roughly 400,000 people a year at present; TICGL's research estimates that 150,000 or more of the region's own new residents each year settle without a formal land claim, a figure that would be materially higher again if the Coast Region fringe were included.
The informal population, in absolute terms
Applied to the larger metropolitan population base, a 70–80% informal share implies that somewhere between 6.3 and 7.2 million people across greater Dar es Salaam were living in informal settlements in 2026 — a materially larger number than the 4.1–4.7 million implied by the official regional population alone, and a more accurate reflection of the true scale of the infrastructure and service challenge.
1.2 Spatial Expansion of Unplanned Areas
Remote-sensing studies place the built extent of informal settlement in Dar es Salaam at approximately 52 km² in 1982, expanding to roughly 379 km² by 2022 — an increase of about 630% in four decades, far outpacing the roughly six-fold growth in population over a similar period. This expansion has been simultaneously a densification process near the city centre and a sprawl process at the periphery, with urban development now extending 40–50 km from the Central Business District along the main transport corridors.
Informal Settlement Area in Dar es Salaam, 1982 → 2026
Square kilometres of built informal settlement — remote-sensing studies and TICGL 2026 estimate
1.3 Housing and Tenure
Roughly 30% of Dar es Salaam residents live in formal housing with secure tenure; the remainder occupy informal plots where perceived security of occupation is common but legal title is rare. Mass land formalisation has made measurable but insufficient progress: over 675,000 land documents were issued nationally between 2020 and 2024, a pace TICGL's research describes as too slow relative to the roughly 150,000+ new informal residents Dar es Salaam absorbs annually. The national annual housing deficit stands at approximately 200,000 units, with the gap projected to exceed 3 million units by 2035 in the absence of a step-change in formal housing delivery.
Sources: NBS Census 1978–2022, UN World Urbanization Prospects / Macrotrends metro-area series, remote-sensing studies of built-up informal area, ACRC (2024), UN-Habitat, TICGL estimates. Pre-2022 population and area figures for intervening years are directional estimates interpolated between census points, not official data points.
04 — Section 2Why Informality Makes Infrastructure Delivery Harder
Unplanned settlement is not merely a housing or welfare issue — it is a direct, structural constraint on how efficiently government can build and maintain infrastructure. The mechanisms are well documented and largely explain why the same kilometre of paved road, drainage channel, or water main costs substantially more, and takes substantially longer, to deliver in an informal Dar es Salaam neighbourhood than on a planned greenfield site.
2.1 Retrofitting Versus Building Ahead of Settlement
In planned development, roads, drainage, water, and power corridors are surveyed and reserved before people build. In Dar es Salaam's informal settlements, the reverse has happened: dense, haphazard construction came first, and infrastructure must now be threaded through existing plots — requiring compensation, negotiated demolition, or complex re-engineering that can stall or derail a project outright if community negotiations break down, as happened with earlier attempts to clear the lower Msimbazi Valley.
2.2 Service Deficits That Compound Over Time
- Formal sewerage reaches a small minority of the city — often cited at 10% or less — with most households relying on pit latrines that overflow in heavy rain.
- Solid waste collection is incomplete because vehicles cannot navigate narrow, unplanned access routes; uncollected waste further blocks drainage and worsens flooding.
- Water access is partial and often informal, with unlicensed private boreholes contributing to aquifer depletion.
2.3 Flood-Prone Occupation of Hazardous Land
A large share of informal settlement has occurred on floodplains and river valleys — most visibly the Msimbazi Basin, home to an estimated 1.6 million people basin-wide and roughly 330,000 in the lower, most flood-exposed reaches. Major flood events have struck in seven of the last ten years, repeatedly disrupting the Bus Rapid Transit corridor at Jangwani Bridge. Earlier attempts to demarcate the valley as non-developable, including two demolition campaigns, were halted due to social opposition.
2.4 The "Build Fast, Open Fast" Problem
Population additions — still averaging well over 100,000 people per year — mean new roads are placed under heavy use almost immediately after opening, compressing the window for design and construction quality control. The effect is faster wear, more frequent resurfacing, and a compounding maintenance backlog, particularly on roads serving dense informal areas with poor drainage.
A direct, costed illustration
This dynamic is visible in government's own recent project list for Dar es Salaam: the Kigogo Bridge (TZS 17.7 billion), Jangwani Bridge (TZS 67 billion), and Mkwajuni Bridge (TZS 11 billion) were all commissioned specifically because flood-driven road closures on routes linking outlying districts to the city centre had become an economically unacceptable, recurring disruption.
05 — Section 3Development and Economic Planning Constraints
Beyond the physical engineering challenge, informality undermines the planning and fiscal instruments government needs to manage urban growth coherently.
3.1 Coordinated Land-Use Planning
Sporadic, self-built growth makes it difficult to sequence infrastructure investment against population distribution, since settlement patterns form organically rather than in response to planned service provision. Densification in informal areas often outpaces the space available for schools, clinics, markets, and drainage reserves, locking in service deficits that are expensive to correct later.
3.2 A Narrow Formal Tax Base
Dar es Salaam contributes an estimated 17–20% of Tanzania's GDP, yet converting that weight into public revenue is constrained by informality. A 2019 survey valued the city's informal economic activity at roughly TZS 6.2 trillion (~22.5% of city GDP then); more recent estimates for 2025 put informality at roughly 30% of the city's economy, even as the national informal economy is estimated at 45–46% of GDP and 76% of the workforce.
3.3 Fragmented Metropolitan Governance
Dar es Salaam is administered as three separate Local Government Authorities — Kinondoni, Ilala, and Temeke — each with its own licensing regime, planning department, development levies, and political leadership. This fragmentation is widely identified — including by the EIU and TICGL's own research — as the single highest-leverage governance reform available, with potential to add 0.5–1.0 percentage points to annual GDP growth if resolved.
3.4 The National Growth Trade-Off
Each percentage-point increase in Tanzania's urbanisation rate is associated with roughly 0.58 additional percentage points of GDP growth — urbanisation itself is a net positive. The risk is unmanaged urban growth: Tanzania's tax-to-GDP ratio improved from 11.8% (2020) to ~13.5–14% (2025/26), still below the government's own 16% target for 2027 and the Sub-Saharan Africa average of 16–17%.
Most Tanzanian LGAs collect less than 20% of their budgets from own-source revenue
Far below benchmarks such as Nairobi County's 50%+, because informal businesses routinely avoid formal registration to escape taxes, fees, and paperwork they perceive as offering limited benefit in return.
06 — Section 4Government Infrastructure and Resilience Spending: A 2018–2026 Snapshot
It is useful to see, side by side, the discrete sums government and its development partners have actually committed to counteracting the effects of informal, unplanned settlement in Dar es Salaam. These figures are not additive in a simple sense — they overlap in scope and timeframe — but together they show a consistent order of magnitude: infrastructure retrofit and flood-resilience spending has run into the hundreds of millions of US dollars, and low trillions of Tanzanian shillings, over the past decade, with no sign of tapering.
Infrastructure & Flood-Resilience Spending, Selected Programmes (US$ millions)
Approximate value of major committed or realised programmes, 2018–2026
Sources: World Bank Msimbazi Basin Development Project appraisal and GFDRR documentation; World Bank DMDP project documents; AllAfrica/Daily News (31 Dec 2025) on the TZS 900bn Dar es Salaam infrastructure allocation; IPS News (24 Jul 2025); Africa Cities Research Consortium; UN-Habitat.
4.1 What This Buys — and What It Doesn't
The Msimbazi Basin Development Project alone is expected to reduce flood exposure for more than 300,000 people and relocate roughly 2,500 households from the highest-risk flood zones by its 2028 completion, while unlocking an estimated US$900 million in real estate investment in the areas made viable by flood protection, according to World Bank-affiliated (GFDRR) analysis.
One basin, most of the city
These are targeted interventions in a single basin; the great majority of Dar es Salaam's 379 km² of informal settlement lies outside the Msimbazi catchment and remains largely unaddressed by any comparable programme, meaning the pattern of retrofit-driven cost overruns and periodic flood losses documented here is likely to persist across most of the city through 2030 even as flagship projects like Msimbazi and the BRT network expansion proceed.
07 — Section 5The Daily Economic Cost of Unplanned Urban Growth
How much does unplanned settlement and informal economic activity cost Dar es Salaam on a day-to-day basis? There is no single official published answer — Tanzania, like most developing-country governments, does not track a daily cost of informality as a discrete line item. What follows is a transparent, bottom-up estimate built by annualising the recurring cost categories identified in Sections 3 and 4 into a daily figure, so the scale of the burden can be compared against familiar reference points. Each component is presented separately, with its own basis and uncertainty, before being combined into the headline figure below.
Component A — Infrastructure Retrofit & Maintenance (Government)
~TZS 1.7–1.9bn/day
~US$685,000/day, from WB's ~US$250M/yr over a 30-year programme; the TZS 900bn Dec 2025 injection alone equates to ~TZS 2.5bn/day if spread over a year
Component B — Flood Losses, Annualised (City Economy)
~TZS 3.0–3.3bn/day
~US$1.2–1.3M/day, from a ~2% annual GDP drag applied to ~TZS 35–38T city GDP; borne mainly by households and businesses
Component C — Foregone Tax Revenue from Informality (Government)
~TZS 1.2–1.4bn/day
~US$460,000–540,000/day; the least precisely measurable component, based on Tanzania's ~13.5–14% effective tax rate applied to a conservative third of DSM's informal economy
Daily Cost by Component (TZS billions/day, midpoint estimate)
Components A, B and C combine into the headline daily cost figure
5.4 The Headline Number: Total Economic Cost, Split by Who Bears It
Reading Components A–C together, and being careful not to double-count, the recurring cost of unplanned urban growth in Dar es Salaam splits cleanly into two groups: costs that fall directly on government (infrastructure retrofit and foregone tax revenue), and costs that are absorbed by households, businesses, and the wider city economy (flood-related losses).
Who Bears the Daily Cost?
Government vs. households, businesses & city economy
Sources: TICGL calculations based on World Bank, Africa Cities Research Consortium, TRA, and TICGL Economics of Cities in Tanzania (2026) data. All daily figures are annualised averages derived from annual or multi-year data points; none reflect an officially published daily cost, and all carry a materially wide margin of error.
An unquantified cost sits on top of this total
Traffic congestion and unreliable logistics arising from an underdeveloped, unplanned road network are not included in the headline figure. The World Bank has described Dar es Salaam's congestion as costing billions of shillings in lost productivity daily, and TICGL/EIU analysis suggests resolving Dar es Salaam's fragmented metropolitan governance alone could add 0.5–1.0 percentage points to annual GDP growth — but no robust, city-specific daily congestion-cost figure has been published to date, so it is flagged here as an upside risk to the total rather than included in it.
Putting the number in context
Even allowing for a wide error margin, the exercise is useful directionally: TRA's 2025/26 target is TZS 36.066 trillion for the full fiscal year, or roughly TZS 99 billion per day on average. On that comparison, the ~TZS 6–8.5 billion/day estimated here would represent roughly 6–9% of average daily national tax collection — a material, continuous drag on the economy rather than an occasional shock, falling on government and on ordinary households and businesses in roughly equal measure.
Caveat
This is a planning-level, order-of-magnitude estimate assembled from the best publicly available data as of August 2026, intended to give decision-makers a sense of scale rather than a precise accounting figure. It should not be cited as an official government cost estimate. A dedicated primary data-collection exercise — ideally led jointly by PO-RALG, TRA, and the Dar es Salaam City Council — would be required to produce a defensible, audited daily or annual figure.
08 — Section 6Forecast to 2030
Two scenarios bound the plausible range for Dar es Salaam through 2030, consistent with TICGL's broader national urban-economics modelling (see TICGL, Economics of Cities in Tanzania, February 2026).
Scenario A — Business-as-UsualInformality drifts at or above today's range
- Metropolitan governance reform, land tenure formalisation, and drainage investment continue at their current, incremental pace.
- Informal settlement share remains at or drifts above today's 70–80% range; informal area continues expanding faster than formal plot supply.
- Annualised cost components grow roughly in line with city GDP: the estimated daily cost of informality could rise from ~TZS 6–8.5 billion in 2026 toward the TZS 9–12 billion per day range by 2030 in nominal terms.
- The national urban informal-settlement rate trends toward the 50% level TICGL flags as a risk by 2050, with Dar es Salaam trending toward the higher end of its historical 70–80% range.
Scenario B — Reform PathReforms already identified are implemented on schedule
- A unified Dar es Salaam Metropolitan Authority, accelerated land titling building on the 675,000 documents issued 2020–2024, and the IDRAS digital tax platform widening the formal tax net.
- Completion of the Msimbazi Basin Development Project and BRT Lines 2 and 3 by around 2028.
- Informal settlement share stabilises or begins a gradual decline by 2030; formal employment climbs toward the government's 38% target; LGA own-source revenue widens materially from today's sub-20% level.
- Even here, the housing deficit and population growth mean the absolute number of people in informal settlements is unlikely to fall before 2030 — the realistic near-term goal is a slower rate of informal expansion, not an outright reversal.
Indicative Trajectory to 2030: City GDP and Informal Settlement Share
Left axis: City GDP (TZS trillion). Right axis: informal settlement share (%, midpoint of scenario range)
6.3 Indicative Trajectory Table
Population figures below use the official Dar es Salaam Region boundary, for consistency with GDP and revenue data reported at that level. On the wider metropolitan/agglomeration definition, which grows faster, the equivalent trajectory would run from ~9.0 million (2026) to approximately ~10.8–11.2 million by 2030.
Sources: TICGL projections, consistent with TICGL Economics of Cities in Tanzania (Feb 2026), UN World Urbanization Prospects 2025, and World Bank/IMF growth projections. Figures for 2027–2030 are TICGL scenario projections, not official government forecasts. Note: values in the "Est. Daily Cost" column are reproduced as presented in the source report and reflect the wide-range planning nature of this exercise.
09 — Section 7Policy Implications
The data points toward a consistent set of priorities, several of which are already reflected in national policy discussions but require acceleration to meaningfully change Dar es Salaam's cost trajectory before 2030.
Prioritise retrofit-efficient infrastructure sequencing
- Concentrate drainage and road-upgrading investment in the highest-density, highest-flood-risk informal wards first, where retrofit cost per resident protected is lowest and avoided flood-loss value is highest.
- Where new roads must be opened to traffic quickly, budget explicitly for accelerated early-life maintenance rather than treating early deterioration as an unplanned cost overrun.
Widen the formal land and tax base together
- Pair land titling drives (building on the 675,000 documents issued 2020–2024) directly with LGA property-tax registration, so formalisation converts into revenue rather than remaining a standalone welfare intervention.
- Accelerate IDRAS and LGRCIS rollout specifically in high-informality wards, where the revenue upside identified in Section 5.3 is concentrated.
Resolve metropolitan governance fragmentation
- Progress the proposed unified Dar es Salaam Metropolitan Authority, replacing the current three-LGA structure, to reduce the transaction-cost drag on both infrastructure delivery and private investment.
Treat flood resilience as core infrastructure
- Extend the Msimbazi Basin model — preventative resettlement paired with infrastructure and livelihood restoration — to the city's other flood-exposed informal catchments, which together hold the majority of the city's 379 km² of informal settlement.
Build the measurement base this report had to estimate
Commission a joint PO-RALG/TRA/Dar es Salaam City Council study to produce an audited, recurring estimate of the fiscal cost of informality, replacing the order-of-magnitude modelling in Section 5 with a defensible official figure that can be tracked year over year.
10 — Section 8Data Sources and Methodology Note
This report synthesises data from the following primary categories of source. Where figures conflict across sources — as they frequently do for informal-settlement share and population estimates — this report generally presents the range rather than a single point estimate, and flags TICGL's own modelled figures explicitly as estimates.
Primary Sources
- National Bureau of Statistics (NBS) — 2022 Population and Housing Census; historical census series 1967–2022
- World Bank — Msimbazi Basin Development Project appraisal and implementation documents (P169425); Dar es Salaam Metropolitan Development Project (DMDP) documents; Tanzania Country Climate and Development Report (2024)
- UN-Habitat — Informal Settlements and Finance in Dar es Salaam, Tanzania
- African Cities Research Consortium (ACRC) — Dar es Salaam city profile and housing analysis
- Global Facility for Disaster Reduction and Recovery (GFDRR) — Msimbazi Basin feature reporting
- Bank of Tanzania, Tanzania Revenue Authority (TRA), and IMF World Economic Outlook — macroeconomic, fiscal, and tax-to-GDP data
- TICGL — Economics of Cities in Tanzania (Final Integrated Edition, February 2026); TICGL Economic Research 2024–2026
Methodology Note on the Daily Cost Estimate
The daily cost figures in Section 5 are derived by taking published annual or multi-year cost estimates (infrastructure retrofit budgets, flood-loss assessments, informal-economy size estimates) and dividing by 365 to produce a comparable daily order of magnitude. This is a standard annualisation technique for planning purposes, but it necessarily assumes costs are evenly distributed across the year, which they are not — flood losses in particular are concentrated in the rainy season (typically March–May and, to a lesser extent, October–December). The figures should therefore be read as average daily equivalents over a full year, not as literal day-to-day cash costs to government.
This report was prepared by TICGL / Tanzania Economic Research Institute for research and advisory purposes. Figures marked as TICGL estimates or projections are the firm's own modelling and should be distinguished from officially published government statistics. © 2026 Tanzania Investment and Consultant Group Ltd (TICGL).
11 — Quick AnswersFrequently Asked Questions
How much does unplanned urban growth cost Dar es Salaam each day?
TICGL/TERI estimates the total recurring economic cost at roughly TZS 6–8.5 billion per day (about US$2.3–3.3 million), combining infrastructure retrofit costs, foregone tax revenue, and annualised flood-related losses. This is an order-of-magnitude planning estimate, not an official government figure.
What share of Dar es Salaam's population lives in informal settlements?
Independent sources including UN-Habitat and ACRC consistently place 70–80%, and in some assessments over 80%, of Dar es Salaam residents in informal, unplanned settlements lacking secure tenure, adequate drainage, reliable sanitation, or planned road access.
How fast has informal settlement area grown in Dar es Salaam?
Remote-sensing studies show informal settlement area expanding from approximately 52 km² in 1982 to about 379 km² in 2022 — roughly 630% growth in four decades — with an estimated 400+ km² by 2026.
Who bears the daily cost of unplanned urban growth?
The cost splits roughly evenly: ~TZS 2.9–3.3 billion/day falls directly on government through infrastructure retrofit spending and foregone tax revenue; ~TZS 3.0–3.3 billion/day is absorbed by households, businesses, and the wider city economy through flood-related property damage and disrupted commerce.
What is Dar es Salaam's population in 2026?
On the official NBS Region boundary, approximately 5.86 million in 2026, up from 5,383,728 at the 2022 census. On the wider UN metropolitan-agglomeration definition, the functional population reached an estimated 9.0 million in 2026.
Muhtasari kwa Kiswahili
Gharama ya Kila Siku ya Ukuaji wa Miji Usiopangwa Jijini Dar es Salaam — Utafiti mpya wa TICGL/TERI unaonyesha kuwa asilimia 70 hadi 80 ya wakazi wa Dar es Salaam wanaishi katika makazi holela yasiyo na hati miliki salama, mifereji ya maji ya kutosha, huduma za usafi wa mazingira, wala barabara zilizopangwa. Eneo la makazi holela limeongezeka kutoka takriban kilomita za mraba 52 mwaka 1982 hadi kilomita za mraba 379 mwaka 2022 — ongezeko la takriban asilimia 630 katika miongo minne.
Gharama ya siku moja: TICGL inakadiria kuwa gharama ya jumla ya kiuchumi ya ukuaji wa miji usiopangwa jijini Dar es Salaam ni takriban TZS bilioni 6 hadi 8.5 kwa siku (sawa na Dola za Marekani milioni 2.3 hadi 3.3), ikijumuisha gharama za kurekebisha miundombinu, mapato ya kodi yaliyokosekana kutokana na shughuli za kiuchumi zisizo rasmi, na hasara za mafuriko zilizowekwa kwa mwaka mzima.
Gharama hii inagawanyika karibu sawasawa: takriban TZS bilioni 2.9–3.3 kwa siku zinabebwa moja kwa moja na Serikali (kupitia urekebishaji wa miundombinu na mapato ya kodi yaliyokosekana), na takriban TZS bilioni 3.0–3.3 kwa siku zinabebwa na kaya, wafanyabiashara, na uchumi mpana wa jiji kupitia uharibifu wa mali unaosababishwa na mafuriko na usumbufu wa biashara.
TICGL inasisitiza kuwa bila hatua za haraka za kurasimisha ardhi, kuboresha uongozi wa jiji (metropolitan authority), na kuongeza uwekezaji kwenye mifereji ya maji, kiwango cha makazi holela kinaweza kuendelea kubaki juu au hata kuongezeka hadi kufikia mwaka 2030, hata huku idadi ya watu ikizidi kuongezeka.
- Wakazi wa makazi holela: asilimia 70–80 ya wakazi wa Dar es Salaam
- Ukuaji wa eneo la makazi holela: kilomita za mraba 52 (1982) hadi 379 (2022) — ongezeko la asilimia 630
- Gharama ya kila siku: TZS bilioni 6–8.5 (~Dola milioni 2.3–3.3)
- Idadi ya watu Dar es Salaam (mkoa rasmi), 2026: takriban milioni 5.86; eneo pana la jiji (metropolitan): takriban milioni 9.0
Vyanzo: Sensa ya NBS 2022, Benki ya Dunia, UN-Habitat, African Cities Research Consortium (ACRC), GFDRR, Benki Kuu ya Tanzania (BOT), Mamlaka ya Mapato Tanzania (TRA), IMF, na utafiti wa TICGL/TERI. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI), Agosti 2026.
01 — OverviewExecutive Summary
Tanzania's National Bureau of Statistics (NBS) released the National Consumer Price Index (NCPI) for July 2026 on 10 August 2026, showing annual Headline Inflation at 4.2 percent, up from 4.0 percent in June 2026. This is a significant release for one specific reason: July was the first calendar month priced entirely under the FY2026/27 Budget's new tax measures, which took effect on 1 July 2026 following the Government's June budget announcement — the presumptive tax adjustments, betting excise duty changes and other revenue measures TICGL examined in its FY2026/27 Budget series. This report asks the question households and businesses are asking directly: one month on, is the new budget visible in the price data yet, and where should Tanzanians expect to feel it first?
The headline answer is nuanced. Food and Non-Alcoholic Beverages inflation — the single most important line for the average household budget, carrying the largest weight (28.2 percent) in the whole NCPI basket — held flat at 4.1 percent year-on-year and actually fell 0.8 percent month-on-month, as staple grains and tubers cheapened with the season. That is genuinely good news, and it is not the signature of a tax-driven food price shock. The pressure instead shows up on the transport and energy side: Transport inflation reached 13.8 percent year-on-year, by far the highest of the thirteen COICOP divisions, and diesel, petrol, charcoal and gas all rose in price within the month of July itself — the first month those goods carried the new fiscal year's duty structure.
- Headline inflation edged up but stayed moderate. At 4.2 percent, headline inflation remains comfortably inside the Bank of Tanzania's 3-5 percent target band, continuing a run of thirteen straight months between 3.2 percent and 4.2 percent.
- Food inflation eased, not spiked. Food and Non-Alcoholic Beverages inflation stayed at 4.1 percent year-on-year and fell month-on-month, led by cheaper rice, maize grain, maize flour, sweet potatoes, cassava and beans — a harvest-season pattern, not a budget-shock pattern.
- Fuel and energy is where the July move actually shows up. Diesel (+3.3% m/m), petrol (+2.5% m/m), charcoal (+4.5% m/m) and gas (+1.3% m/m) all rose in the very month the new fiscal year's tax and duty structure took effect, and the Energy, Fuel and Utilities Index posted 6.9 percent inflation year-on-year — its highest reading in this dataset.
- One month is not enough to prove causation. Fuel prices move with global oil markets, the exchange rate and seasonal transport demand as well as domestic duties. TICGL treats July as the first data point to watch, not a verdict, and will track the August and September releases closely.
- Core inflation crept up but remains contained. At 3.9 percent (up from 3.7 percent in June), core inflation — which strips out volatile food and energy prices — confirms that the broader, stickier price pressure in the economy is still modest.
02 — ContextAbout the National Consumer Price Index
The NCPI measures how the cost of a fixed basket of goods and services purchased by a representative sample of Tanzanian households changes over time. The current basket contains 383 goods and services — 132 food and non-alcoholic beverage items and 251 non-food items — priced using data collected from all 26 regional headquarters on the Tanzanian mainland. Weights are derived from the 2017/18 Household Budget Survey, the base price reference period is the average of January-December 2020, and the index reference period is 2020 (2020=100). The index follows the UN's Classification of Individual Consumption by Purpose (COICOP), 2018 version, across 13 divisions, and elementary indices are compiled using the geometric mean of price relatives, with higher-level aggregates built on the Lowe Index formula, a type of Laspeyres index.
Why July 2026 matters for this analysis
Tanzania's FY2026/27 Budget was presented in June 2026 and its tax and duty measures — including presumptive tax adjustments and a revised betting excise duty, as covered in TICGL's earlier budget-series research — took legal effect from 1 July 2026. Because NCPI price collection runs through the calendar month, the July 2026 release is the first NBS print built on prices collected entirely inside the new fiscal year. It is the earliest possible data point for observing whether new duties are visible at the till.
Supplementary indices published alongside the NCPI
- Core Index (excludes unprocessed food, energy and utilities except maize flour) — 73.9% of basket weight
- Non-Core Index — 26.1% of basket weight
- Energy, Fuel and Utilities Index — 5.7% of basket weight
- Services Index (37.2%) and Goods Index (62.8%)
- All Items Less Food and Non-Alcoholic Beverages Index — 71.8% of basket weight
NCPI Basket Composition by COICOP Division
Percent weight of each of the 13 divisions in the national basket, 2017/18 Household Budget Survey weights
03 — The Twelve-Month PictureHeadline Inflation Trend, July 2025 – July 2026
The Headline Inflation Rate measures overall inflation across the full CPI basket. Table 1 below and NBS's own Chart 1 show the NCPI generally trending upward across the year, from 119.85 in July 2025 to 124.85 in July 2026, while the annual inflation rate stayed within a narrow 3.2-4.2 percent range throughout — dipping to its lowest point in February-March 2026 before climbing through the second half of the fiscal year to its twelve-month high in July 2026.
NCPI Index and Annual Inflation Rate, July 2025 – July 2026
Left axis: NCPI (2020=100). Right axis: annual headline inflation rate, percent
NCPI Index (left axis)
Annual Inflation Rate (right axis)
Source: NBS NCPI Press Release, July 2026, Chart 1 and Table 1.
Reading the month-on-month dip
Between June and July 2026 the overall index actually fell slightly, from 125.04 to 124.85 — a 0.1 percent month-on-month decrease, driven mainly by cheaper food and staple grain prices. The annual rate still rose to 4.2 percent because July 2025's base value was low; this is a reminder that headline year-on-year inflation and month-on-month price direction can move in opposite directions in the same release, and both numbers matter for a complete picture.
04 — What This Means at the MarketFood Inflation: The Number That Matters Most for Households
Food and Non-Alcoholic Beverages carries the single largest weight in the NCPI basket at 28.2 percent — more than any other division — which is why it is the most consequential line for a typical Tanzanian household's real cost of living, and the line TICGL scrutinises most closely for signs of budget pass-through. In July 2026, food inflation held at 4.1 percent year-on-year, unchanged from June, while the food index itself fell month-on-month, from 136.92 in July 2025... actually from 136.92 (index level a year prior) — more precisely, from 136.92 in July 2025 to 136.92 baseline comparison aside, the relevant month-on-month move was from June 2026's 136.92 down to July 2026's 135.79, a decrease of 0.8 percent.
Food Inflation, Y-o-Y
4.1%
Unchanged from June 2026
Food Index, M-o-M
-0.8%
Prices fell within the month
Basket Weight
28.2%
Largest of all 13 COICOP divisions
The month-on-month decline was broad-based across staple foods, consistent with a seasonal harvest effect rather than a tax-driven price shock. The items pulling food prices down in July included several of the staples that make up the bulk of an ordinary Tanzanian household's plate:
Food Items With the Largest Price Movements, June → July 2026
Month-on-month percent change for selected food items in the NCPI basket
Source: NBS NCPI Press Release, July 2026, Section 3.
The reassuring signal for households
If the FY2026/27 Budget's tax measures were pushing food prices up broadly, the clearest place it would show first is staple grains and tubers, since these dominate the food basket and move through short, largely domestic supply chains. Instead, every one of the food items NBS flagged in July moved down, and the pattern — grains, tubers and pulses all falling together — is the signature of a harvest-season supply effect, not a new tax working its way through the food chain. This is a genuinely positive early reading for household food budgets.
05 — Where the Pressure Actually Shows UpFuel, Energy and Transport: The Line to Watch
While food prices eased, the same NBS release shows a very different pattern in transport and energy. Transport inflation reached 13.8 percent year-on-year in July 2026 — the highest annual inflation rate of any of the 13 COICOP divisions by a wide margin, and more than three times the headline rate. The Energy, Fuel and Utilities Index recorded 6.9 percent inflation year-on-year, also well above the headline figure. Within the month of July alone, diesel, petrol, charcoal and gas — the fuels that price everything from bus fares to cooking to the cost of moving food to market — all rose.
Fuel and Energy Items: Month-on-Month Price Change, June → July 2026
The first full month priced under the FY2026/27 fiscal year's duty structure
Source: NBS NCPI Press Release, July 2026, Section 3.
Why fuel is the honest place to look for a budget effect — and why one month isn't proof
Diesel and petrol prices in Tanzania respond to at least three forces simultaneously: global crude oil and refined-product prices, the shilling's exchange rate against the dollar, and domestic taxes, levies and duties set in the national budget. All three can move in the same month. TICGL cannot, from a single NBS release, separate how much of July's diesel and petrol increase came from global oil markets versus how much came from the FY2026/27 duty structure that took effect on 1 July. What can be said with confidence is that fuel and energy is mathematically the fastest-moving, highest-inflation part of the entire basket in the first month of the new fiscal year, and it is the line item most directly exposed to fuel levies and import duties. That makes it the correct place to keep watching, not a place to draw early conclusions.
Why this still matters for ordinary households even without proof of causation
Transport costs feed into the price of almost everything else with a lag — bus and dala-dala fares, the cost of moving food from farm to market, and the electricity and cooking-fuel bill for both urban and rural households. Even if July's food staples got cheaper at the point of harvest, a sustained rise in diesel and charcoal prices can slowly erode that gain by raising the cost of getting food to market and cooking it once it arrives — a lagged transmission TICGL will be watching for in the August and September releases.
06 — The Full PictureInflation by COICOP Division, July 2026
Table 1 below reproduces NBS's full group-by-group breakdown for July 2026, showing each division's weight in the basket, its index level a year ago and a month ago, its July 2026 index, and both its month-on-month and year-on-year percentage change.
Annual Inflation Rate by COICOP Division, July 2026
Percent, year-on-year — sorted from highest to lowest; food and transport highlighted
Other Selected Indices
Source: NBS NCPI Press Release, July 2026, Table 1.
Headline vs Core vs Food vs Services vs Goods vs Energy: Annual Inflation, July 2026
A single snapshot comparing the different ways of slicing July 2026's inflation reading
07 — The Question Everyone Is AskingReading the Budget Signal: One Month On
Tanzania's FY2026/27 Budget, presented to Parliament in June 2026, introduced a range of tax and revenue measures — presumptive tax adjustments for small businesses and a revised betting excise duty among them, as TICGL's earlier budget-series research documented — alongside a significant increase in the public wage bill. Those measures took legal effect from 1 July 2026. July's NCPI release is therefore the earliest possible window into whether the new fiscal year's tax structure is visible in consumer prices, and the honest reading of the data is: partially, and only in one place so far.
June 2026
FY2026/27 Budget presented and passed
New tax and duty measures, including presumptive tax and betting excise duty changes, are approved for the fiscal year beginning 1 July 2026.
1 July 2026
New fiscal year begins; tax and duty measures take effect
NCPI price collection for July begins under the new fiscal year's duty structure for the first time.
July 2026
First fully post-budget month of price data
Food prices fall month-on-month on seasonal supply; fuel, charcoal and gas rise; transport inflation reaches 13.8 percent year-on-year.
10 August 2026
NBS releases the July 2026 NCPI
The data TICGL analyses in this report becomes public.
8 September 2026 & beyond
August, September and October releases due
The next three NCPI releases will show whether July's fuel and transport pattern persists, accelerates or fades — the true test of any budget pass-through.
What the data supports saying
- Food prices, the largest and most politically sensitive basket item, moved down in July — no visible sign of a broad tax-driven food price shock in month one.
- Fuel, charcoal and gas — the items most directly exposed to duties, levies and import costs — all rose in the same month the new fiscal year's tax structure took effect.
- Transport inflation at 13.8 percent year-on-year is not new in this dataset; it has been elevated for some months, but July continued that pattern with the highest reading in the twelve-month series shown.
What the data cannot support saying yet
- That the FY2026/27 Budget's specific tax measures caused the July fuel price increase — global oil prices and the exchange rate moved in the same window and cannot be separated out from one release.
- That food prices are now safe from budget-related pressure for the rest of the year — presumptive tax changes affect small traders' costs in ways that can take several months to show up in retail prices.
- That transport's 13.8 percent reading is new or budget-driven, since it was already the highest-inflation division before July arrived.
TICGL's method going forward
Rather than declare a verdict from a single data point, TICGL will track the Energy, Fuel and Utilities Index, the Transport division, and the Food and Non-Alcoholic Beverages division across the August, September and October 2026 NCPI releases (due 8 September, 8 October and 9 November 2026 respectively) and update this analysis. A genuine budget-driven pass-through would be expected to persist or build over several months, not appear and disappear in one release.
08 — Looking AheadWhat Could the Next Six Months Bring?
Projecting inflation six months out is inherently uncertain, and TICGL does not present the scenarios below as forecasts with precise numbers — no single NCPI release can support that. Instead, these are three plausible directions the data could move in through early 2027, based on the forces already visible in the July release, each with the conditions that would confirm it.
Scenario A — Most LikelyHeadline inflation stays inside the 3-5% band
- Food inflation stays moderate as the harvest season continues to support supply through late 2026.
- Fuel prices stabilise or ease slightly if global oil prices hold steady and the shilling remains stable.
- Core inflation stays close to its current 3.9%, keeping BOT's monetary stance broadly unchanged.
Scenario B — Watch CloselyTransport and energy inflation persists or edges higher
- Diesel, petrol, charcoal and gas continue rising in the August-October releases, confirming a sustained fiscal-year effect rather than a one-month blip.
- Higher transport costs begin to lift food prices with a lag, as it becomes more expensive to move produce to market, partially offsetting the current harvest-season relief.
- Headline inflation drifts toward the upper end of the 3-5% band by year-end.
Scenario C — Lower ProbabilityPost-harvest food price reversal plus sustained fuel pressure
- The seasonal food price relief fades once the current harvest is absorbed, typically toward the final quarter of the calendar year.
- If this coincides with continued fuel and transport cost pressure, both major components of the basket could push upward at the same time.
- This is the combination that would most directly test the 3-5% inflation target band and warrant closer BOT attention.
What would move TICGL from "watching" to a firmer view
Three consecutive months (August-October 2026) of rising Transport and Energy, Fuel and Utilities inflation, occurring alongside a stable or appreciating shilling and stable global oil prices, would be the clearest evidence that the FY2026/27 Budget's duty structure — rather than external factors — is driving the pattern. Conversely, if fuel inflation eases once July's one-off adjustment period passes, that would suggest global or exchange-rate factors, rather than the domestic tax structure, were the larger driver.
09 — TICGL AnalysisWhat This Means for the Ordinary Tanzanian Household
1. The food budget got a genuine, if temporary, reprieve
For households where food is the largest share of spending, July's month-on-month price falls in rice, maize, cassava and beans are real relief, and it arrived in the same month the new budget's measures took effect — an important, reassuring coincidence for anyone worried the new fiscal year would immediately hit the plate.
2. The transport bill is the one to watch, not celebrate
At 13.8 percent year-on-year, transport inflation was already the fastest-moving part of the basket before July, and it stayed there. Households that spend a meaningful share of income on bus fares, motorcycle taxis (bodaboda) fuel, or moving goods to market are the ones most exposed to whatever is driving this line, whatever combination of global and domestic factors turns out to be responsible.
3. Core inflation is the Bank of Tanzania's real dashboard
At 3.9 percent, core inflation — the measure BOT watches most closely because it strips out the volatile food and energy swings — remains comfortably inside target. That suggests the underlying, broad-based inflation picture in the economy is still stable even as individual line items like fuel move more sharply.
4. This is exactly the kind of test BOT's new Strategic Plan was built for
TICGL's companion analysis of the Bank of Tanzania's Strategic Plan 2026/27-2030/31 notes that BOT's core mandate is to keep inflation inside its 3-5% band while FYDP IV and Dira 2050 build on that stability. July's reading — headline and core both still inside target, with one pressure point (fuel) worth monitoring — is precisely the kind of month that mandate is designed to manage calmly rather than react to.
TICGL's bottom line
One month after the FY2026/27 Budget's tax measures took effect, Tanzania's inflation picture is stable, not alarming: headline inflation at 4.2 percent and core inflation at 3.9 percent both sit inside the Bank of Tanzania's target band, and food prices — the line that matters most for household welfare — actually eased. The one area genuinely worth household and policymaker attention is fuel and transport, where price increases coincided with the new fiscal year but cannot yet be attributed to it with confidence. TICGL's view is that the next two to three NCPI releases, not this one alone, will tell the real story of how the FY2026/27 Budget is landing on ordinary Tanzanians.
10 — TICGL RecommendationsWhat To Watch and What To Do
- Track the Energy, Fuel and Utilities Index monthly, not just the headline rate. It is currently the fastest-moving major index (6.9% y/y) and the most direct channel through which fiscal measures would show up.
- Separate global and domestic drivers of fuel prices by cross-referencing global crude oil price movements and the TZS/USD exchange rate against each month's diesel and petrol price changes, rather than reading NCPI fuel data in isolation.
- Watch for lagged transport pass-through into food prices over the next two to three releases — higher transport costs typically reach the market a month or two after fuel prices move, even when farm-gate food prices are falling.
- Households and small businesses should budget for continued fuel volatility in the near term rather than assume July's food price relief extends automatically to transport and energy costs.
- Policymakers should consider publishing a simple monthly bridge showing how much of any fuel price change is attributable to global price movements, exchange rate movements, and domestic tax/duty changes respectively — this would let households, TICGL and other analysts assess budget impact with far more confidence than the current release format allows.
11 — Quick AnswersFrequently Asked Questions
What is Tanzania's headline inflation rate for July 2026?
Annual Headline Inflation rose to 4.2 percent in July 2026, up from 4.0 percent in June 2026, though the overall index fell slightly month-on-month, from 125.04 to 124.85.
What is Tanzania's food inflation rate in July 2026?
Food and Non-Alcoholic Beverages inflation held at 4.1 percent year-on-year, unchanged from June, while food prices fell 0.8 percent month-on-month on cheaper staples such as rice, maize, sweet potatoes and beans.
Did the FY2026/27 Budget's tax measures push up inflation?
July 2026 is the first NCPI release built entirely on post-budget prices. Food inflation eased, but transport inflation reached 13.8 percent year-on-year and diesel, petrol, charcoal and gas all rose within the month. One month of data cannot prove causation, but fuel and energy is the clearest line to watch over the coming releases.
What is core inflation in Tanzania as of July 2026?
Core inflation, which excludes volatile food, energy and utility prices, rose to 3.9 percent in July 2026 from 3.7 percent in June, remaining within the Bank of Tanzania's 3-5 percent target band.
Which items got cheaper and which got more expensive in July 2026?
Staple foods including rice, maize grain, maize flour, sweet potatoes, cassava and beans got cheaper month-on-month. Charcoal, diesel, petrol, gas and clothing materials got more expensive, with fuel and energy items showing the sharpest increases.
12 — MethodologySources & Notes
- National Bureau of Statistics (Tanzania) — National Consumer Price Index (NCPI) Press Release for July 2026, Ref: AC 334/376/01/381, dated 10 August 2026 (nbs.go.tz).
- TICGL/TERI prior research: TICGL's FY2026/27 Tanzania National Budget analysis series (overall tax measures, presumptive tax, betting excise duty, wage bill increase) and TICGL's Bank of Tanzania Strategic Plan 2026/27-2030/31 analysis.
- Global oil price and exchange-rate context referenced qualitatively; TICGL did not have access to a matched monthly global oil price or exchange-rate dataset at the time of writing and recommends this comparison be made explicitly in a future update.
- This page is an independent analytical summary prepared by TICGL/TERI based on NBS's published NCPI release and does not constitute financial, investment, tax, or legal advice. Figures reflect NBS's own reporting as published.
MuhtasariMuhtasari kwa Kiswahili
Je, Bajeti Mpya ya 2026/27 Imeanza Kuathiri Bei za Chakula na Mafuta? Ofisi ya Taifa ya Takwimu (NBS) imetoa taarifa ya Kielezo cha Bei za Bidhaa Kitaifa (NCPI) kwa mwezi Julai 2026, ikionyesha mfumuko wa bei kwa ujumla (Headline Inflation) umefikia asilimia 4.2, ukiwa umepanda kutoka asilimia 4.0 mwezi Juni 2026. Julai 2026 ni mwezi wa kwanza kamili ambao bei zilikusanywa baada ya hatua za kodi za Bajeti ya 2026/27 kuanza kutumika rasmi tarehe 1 Julai 2026.
Uchambuzi wa TICGL unaonyesha kuwa bei za chakula hazikupanda kwa kasi — mfumuko wa bei za chakula ulibaki asilimia 4.1 kwa mwaka, na kwa kulinganisha na mwezi uliopita (Juni), bei za chakula zilishuka kwa asilimia 0.8, zikichangiwa na kushuka kwa bei za mchele, mahindi, unga wa mahindi, viazi vitamu, muhogo na maharage — dalili za msimu wa mavuno, si dalili za kodi mpya. Hata hivyo, eneo linaloonyesha ongezeko kubwa ni usafiri na nishati: mfumuko wa bei za usafiri ulifikia asilimia 13.8 kwa mwaka, kiwango cha juu zaidi kati ya makundi yote, huku dizeli (juu kwa asilimia 3.3), petroli (juu kwa asilimia 2.5), mkaa (juu kwa asilimia 4.5) na gesi (juu kwa asilimia 1.3) zote zikipanda bei ndani ya mwezi huo huo.
TICGL inasisitiza kuwa data ya mwezi mmoja haitoshi kuthibitisha kwamba hatua za kodi za bajeti ndizo zilizosababisha ongezeko la bei za mafuta — mabadiliko ya bei za mafuta duniani na thamani ya shilingi dhidi ya dola pia huathiri bei hizi. TICGL itaendelea kufuatilia taarifa za NCPI za miezi ijayo (Agosti, Septemba na Oktoba 2026) ili kuona kama mwenendo huu wa bei za mafuta na usafiri utaendelea, utaongezeka, au utapungua.
- Mfumuko wa bei kwa ujumla: asilimia 4.2 (Julai 2026), ukiwa ndani ya wigo wa lengo la BOT wa asilimia 3-5
- Mfumuko wa bei za chakula: asilimia 4.1 kwa mwaka, lakini bei zilishuka asilimia 0.8 ndani ya mwezi
- Mfumuko wa bei za usafiri: asilimia 13.8 kwa mwaka — kiwango cha juu zaidi cha makundi yote
- Mfumuko wa bei msingi (Core Inflation): asilimia 3.9, bado ndani ya lengo la BOT
Vyanzo: Taarifa ya NCPI ya NBS kwa Julai 2026 (Kumb: AC 334/376/01/381, tarehe 10 Agosti 2026), na utafiti wa awali wa TICGL/TERI kuhusu Bajeti ya 2026/27. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI).
01 — OverviewExecutive Summary
In its Strategic Plan 2026/27–2030/31, the Bank of Tanzania makes a striking admission in passing: introducing its own monetary-policy theme, BOT writes that "the growing complexity of monetary transmission driven by digital financial innovation, elevated currency in circulation, rising dollarization tendencies and the persistent threat of imported inflation" continue to challenge the Bank. Its SWOC self-assessment repeats the point directly under Challenges: "structural issues such as dollarization, market segmentation, and high borrowing costs persist."
TICGL's view is that this single issue deserves far more scrutiny than its brief mention in the Plan suggests. Dollarization sits at the intersection of almost everything else BOT is trying to achieve over the next five years — a 3-5 percent inflation band defended through an interest-rate framework that only works on shilling-denominated transactions, a credit-to-GDP target of ≥30 percent that depends on affordable local-currency lending reaching priority sectors, and a market-deepening agenda built around narrowing the very spreads that dollarization helps widen.
- It is officially recognised, but not yet measured. BOT names dollarization as a persistent challenge but publishes no dedicated KPI, baseline, or target tracking it anywhere in the Plan.
- It has a direct, quantified proxy already inside the Plan. The Interbank Foreign Exchange Market (IFEM) spread — TZS 57, targeted down to ≤TZS 20 — is the clearest numeric signal of how disconnected shilling and dollar liquidity currently are.
- It weakens the exact tool BOT adopted in January 2024. The interest rate-based monetary policy framework transmits through shilling interest rates; the more the economy prices, saves, and borrows in dollars, the less that framework can do.
- It threatens FYDP IV's financing arithmetic directly. FYDP IV counts on private-sector-led industrialization financed substantially in local currency; a dollarized, segmented credit market pushes exactly the wrong incentives onto exactly the firms FYDP IV needs most.
- It is a monetary-sovereignty issue for Dira 2050, not just a technical one. A "strong, inclusive, and competitive economy" by 2050 implies a currency Tanzanians trust and default to — every share of activity that shifts into dollars is a share where BOT's own tools lose reach.
02 — The BasicsWhat Is Dollarization, and Why Does It Happen?
Dollarization (or, more precisely, currency substitution) is the growing use of a foreign currency — almost always the US dollar — alongside or instead of the domestic currency inside a country's own economy. It shows up in three overlapping forms, and Tanzania shows signs of at least two.
1. Payment dollarization
Prices, invoices, or day-to-day transactions — especially for imported goods, real estate, hotel bookings, and some professional services — get quoted or settled in dollars even for domestic buyers, bypassing the shilling entirely for that transaction.
2. Financial (asset/liability) dollarization
Bank deposits, loans, and savings are held in foreign currency rather than shillings. This is the form most directly relevant to BOT's monetary-policy transmission, since it determines how much of the credit and deposit base actually responds to the Central Bank Rate.
3. Real dollarization
Wages, contracts, and long-term commitments get indexed or denominated in dollars as a hedge against inflation or shilling depreciation — a sign that trust in the domestic currency as a stable store of value is eroding at the margin.
Dollarization typically accelerates when a currency has a history of high inflation or sharp depreciation, when trade and remittance flows are dollar-heavy, when residents have easy access to foreign-currency bank accounts, or — as BOT's own Situation Analysis notes for Tanzania — when global geopolitical shocks (the Russia-Ukraine war's effect on food and fuel prices, renewed Middle East conflict pushing oil above US$100/barrel in early 2026) repeatedly demonstrate the shilling's exposure to imported inflation.
03 — The EvidenceWhat BOT's Own Plan Actually Says
Dollarization is mentioned directly in two places in the Strategic Plan, and indirectly via one quantified KPI. TICGL has pulled all three together below because, read separately, their significance is easy to miss.
What's conspicuously absent
Nowhere in the published Plan does BOT report a dollarization ratio — the share of bank deposits or loans denominated in foreign currency — as a tracked indicator. Compare this to the eleven KPIs under financial-sector safety alone (capital adequacy, liquidity, NPL ratio, and so on): dollarization is named as a risk but, unlike almost everything else in the Plan, it is not yet a number BOT has committed to move.
04 — Transmission MechanismWhy Dollarization Blunts BOT's Interest Rate Tool
In January 2024, BOT shifted to an interest rate-based monetary policy framework — using the Central Bank Rate (CBR) to guide the 7-day interbank cash market rate, and from there, bank lending and deposit rates economy-wide. BOT's own Theme 1.1 target narrows the acceptable spread on the 7-day IBCM rate from ±200 bps to ±150 bps of the CBR by 2029/30, a sign of how central this transmission channel now is to Tanzania's entire monetary-policy model.
That model has one structural vulnerability: it only steers shilling-denominated activity. Every loan, deposit, or price that shifts into dollars is a transaction the CBR cannot reach directly. Three consequences follow:
- Weaker pass-through. A CBR change designed to cool or stimulate the economy has a smaller effect the larger the dollarized share of credit and deposits becomes — the Bank is, in effect, steering a shrinking portion of the wheel.
- Currency-mismatch risk shifts onto borrowers. Firms and households that borrow in dollars but earn in shillings absorb exchange-rate risk directly — a shilling depreciation instantly raises their real debt burden, regardless of what BOT does with the CBR.
- Imported-inflation exposure compounds. BOT's own Situation Analysis flags renewed 2026 Middle East conflict pushing oil above US$100/barrel as a live inflation risk; a more dollarized economy transmits global dollar-price shocks into domestic prices faster and more directly than a predominantly shilling economy would.
Inflation vs the 7-Day IBCM Rate Spread: The Transmission Channel BOT Is Tightening
Percent / basis points — the corridor BOT wants monetary-policy signals to move through, which dollarization bypasses by design
05 — The Quantified SymptomMarket Segmentation: IBCM vs IFEM
If dollarization is the underlying condition, market segmentation between the interbank cash market (IBCM, where banks trade shilling liquidity) and the interbank foreign exchange market (IFEM, where banks trade dollar liquidity) is its clearest quantified symptom in BOT's own Plan.
🏦 IBCM — Shilling Liquidity
- 7-day rate spread: baseline ±200 bps, target ±150 bps of CBR
- Spread in the 7-day IBCM interest rate: baseline 1.6%, target ≤2%
- The channel BOT's interest-rate framework depends on
VS
💵 IFEM — Dollar Liquidity
- Spread: baseline TZS 57, target ≤TZS 20 by 2029/30
- A wide spread here signals banks are not moving dollar liquidity efficiently between each other
- Directly shaped by how much of the economy has shifted into dollars
A persistently wide IFEM spread means some banks sit on surplus dollar liquidity while others face shortages, with the cost of bridging that gap passed on to borrowers as a risk premium — on top of, not instead of, ordinary credit risk pricing. That premium falls hardest on smaller, shilling-only borrowers who cannot access dollar financing directly, precisely the businesses FYDP IV is counting on to industrialize.
Market-Deepening Targets: Closing the Segmentation Gap
The three Theme 1.3 KPIs BOT is using as its own proxy for reduced market segmentation between shilling and dollar liquidity
06 — The Growth LinkDollarization, Credit Costs, and the ≥30% GDP Target
BOT's headline growth-adjacent target — credit to the private sector reaching at least 30 percent of GDP by 2029/30, up from 22.8 percent in 2025/26 and just 13.2 percent five years earlier — is the number dollarization threatens most directly.
The mechanism is straightforward: a dollarized, segmented credit market channels the cheapest, most available financing toward larger borrowers who can access and service dollar loans, while shilling-only MSMEs face the full weight of thinner local-currency markets — higher spreads, tighter collateral requirements, and less competitive pricing. Aggregate credit-to-GDP can rise even while the distribution of that credit skews away from exactly the broad-based private-sector growth FYDP IV needs.
Credit to Private Sector as % of GDP, 2021/22 → 2029/30 Target
The trajectory BOT is targeting — and the segmentation gap standing between 22.8% today and the 30% goal
07 — The Bigger StakesWhat This Means for FYDP IV and Dira 2050
FYDP IV: Private-sector-led industrialization needs local-currency credit
FYDP IV's core ambition — re-rising competitiveness and industrialization for human development — is financed substantially through private-sector credit growth. A credit-to-GDP target of ≥30% is only meaningful for that ambition if the credit reaching manufacturers, agro-processors, and MSMEs is affordable and denominated in the currency they earn in. Dollarization risks concentrating credit access among larger, import-linked, or export-earning firms that can naturally hedge dollar exposure, leaving the broader industrial base FYDP IV needs most facing the segmented, more expensive shilling market.
Dira 2050: Monetary sovereignty is part of "strong and competitive"
Dira 2050's vision — "strong, inclusive, and competitive economy" — implicitly assumes a national currency Tanzanians and Tanzanian institutions trust and default to for savings, pricing, and contracts. Every percentage point of economic activity that migrates into dollars is a percentage point where BOT's own policy instruments — the CBR, reserve requirements, open-market operations — lose direct reach. A 2050 vision of economic strength is difficult to reconcile with a domestic currency playing an ever-smaller role in the domestic economy.
The sequencing risk: capital-account liberalization
BOT's Theme 1.3 already lists "adopt a full capital account liberalization" as a strategic initiative — a policy that can deepen markets and attract capital, but that interacts directly with dollarization. Liberalizing capital flows before narrowing the IFEM spread and containing currency substitution risks accelerating dollarization rather than curing it, since it becomes easier, not harder, to move into and hold foreign-currency assets. TICGL's reading is that sequencing here matters as much as the policy itself: market-deepening and de-dollarization measures arguably need to show measurable progress before full liberalization is pushed through, not after.
08 — Comparative EvidenceHow Other Economies Have Handled Dollarization
Tanzania is far from the first economy to confront rising currency substitution. Both cautionary and constructive precedents exist among developing and emerging peers.
🇪🇨 Ecuador & Zimbabwe: Full Dollarization as Last Resort
Both countries eventually abandoned their domestic currencies entirely after hyperinflation destroyed public trust in them — Zimbabwe following inflation that peaked above a billion percent in 2008. Full dollarization stabilised prices but permanently surrendered independent monetary policy, an outcome only relevant to Tanzania as the extreme endpoint to avoid, not a model to follow.
🇵🇪 Peru: A De-Dollarization Success Story
Peru cut financial dollarization from roughly 80 percent of credit in the early 2000s to under 20 percent within about two decades, through sustained inflation-targeting credibility, incentives favouring local-currency lending, and macroprudential limits on unhedged dollar borrowing — evidence that credibility-building and targeted incentives, not capital controls alone, can shift the balance back toward the domestic currency.
🇺🇬 🇰🇪 Uganda & Kenya: East African Peers, Similar Pressure
Both neighbouring central banks report comparable dollarization pressure in deposits and trade-related lending, driven by similar dynamics — import dependence, dollar-denominated regional trade, and periodic shilling/shilling-equivalent depreciation episodes — suggesting the issue is regional in character, not unique to Tanzania's policy choices alone.
🇹🇿 Tanzania: Early-Stage, Named but Unmeasured
BOT's own language — "rising dollarization tendencies" — suggests a trend still in its earlier stages relative to historical extreme cases, which is precisely the window in which credibility-based, incentive-driven de-dollarization (the Peru model) tends to be most effective and least costly to implement.
The pattern worth learning from
The common thread across successful de-dollarization cases is that they were gradual, credibility-based, and incentive-driven — built on sustained low inflation, deeper local-currency capital markets, and macroprudential nudges toward local-currency borrowing — rather than sudden restrictions on foreign-currency access. BOT's existing initiatives (Financial Market Master Agreements, diversified government debt instruments, deepened domestic markets) already point in this direction; the missing piece is simply measuring dollarization directly so progress can be tracked.
09 — What's in the PlanBOT's Response — and the Gap TICGL Sees
TICGL's assessment
To its credit, BOT's Plan does not ignore the underlying problem — the IFEM-spread target and debt-instrument diversification are genuine, quantified responses to market segmentation. What is missing is a direct measure of dollarization itself. Right now, progress can only be inferred indirectly through the IFEM spread; a dedicated KPI would let BOT, government, and the public track de-dollarization on its own terms rather than as a byproduct of a market-depth target.
10 — TICGL RecommendationsA Disciplined Path Toward De-Dollarization
- Publish a standing "dollarization ratio" KPI — foreign-currency deposits and loans as a share of total — as a companion indicator to the IFEM-spread target, with its own baseline and 2029/30 direction of travel.
- Sequence capital-account liberalization behind measurable progress on the IFEM spread, so market opening does not outrun the de-dollarization tools meant to accompany it.
- Study Peru's incentive-based de-dollarization model specifically — macroprudential limits on unhedged dollar borrowing, and incentives favouring local-currency lending, layered on top of continued inflation-targeting credibility.
- Disaggregate the private-sector-credit target by currency of denomination, not just by sector, so BOT and stakeholders can see whether the path to 30% credit-to-GDP is being financed in shillings or dollars.
- Use the new debt-instrument diversification agenda deliberately as a de-dollarization tool — local-currency government securities that are liquid, accessible, and competitively priced give savers and institutions a shilling-denominated alternative to holding dollars.
11 — Quick AnswersFrequently Asked Questions
What is dollarization and is it happening in Tanzania?
Dollarization is the growing use of a foreign currency — typically the US dollar — for savings, borrowing, pricing, or invoicing, alongside or instead of the domestic currency. BOT's own Strategic Plan names "rising dollarization tendencies" as a persistent structural challenge, confirming the trend is real and officially recognised, even without a published dollarization ratio.
Why does dollarization weaken Tanzania's monetary policy?
Tanzania's interest rate-based framework (adopted January 2024) works by moving shilling interest rates. The more borrowing, saving and pricing shift into dollars, the less grip a change in the Central Bank Rate has on those decisions.
How is dollarization connected to market segmentation?
BOT's own Theme 1.3 KPI shows a TZS 57 spread in the Interbank Foreign Exchange Market, targeted down to TZS 20 or less. A wide, persistent spread signals inefficient movement of dollar liquidity between banks — raising credit costs and reinforcing incentives to hold and lend in dollars.
What does dollarization mean for FYDP IV and Dira 2050?
FYDP IV's private-sector-led industrialization depends on affordable local-currency credit reaching priority sectors. Dollarization risks concentrating credit toward larger, dollar-capable borrowers, leaving broader industrial ambitions under-financed — while Dira 2050's vision of a strong, competitive economy assumes a currency Tanzanians trust and use by default.
What is BOT doing about dollarization?
BOT targets a narrower IFEM spread (≤TZS 20), Financial Market Master Agreements, diversified government debt instruments (≥10% non-traditional issuance), and capital-account liberalization — but has not published a standalone KPI tracking dollarization itself.
12 — MethodologySources & Notes
- Bank of Tanzania — Strategic Plan 2026/27-2030/31 (June 2026): Situation Analysis, SWOC Analysis, and Theme 1 (Macroeconomic Stability) objectives, KPIs, baselines and targets (bot.go.tz).
- TICGL/TERI companion analysis: "Does BOT's 2026/27-2030/31 Strategic Plan Support FYDP IV and Dira 2050?" and "What's Next for Tanzania's Economy? The Policy Gaps Keeping $1 Trillion Out of Reach by 2050."
- Comparative dollarization experience: publicly documented accounts of Ecuador's and Zimbabwe's full dollarization episodes, and Peru's financial de-dollarization programme since the early 2000s, cited for illustrative comparative purposes.
- All interpretation connecting BOT's KPIs to dollarization, market segmentation, FYDP IV and Dira 2050 is TICGL/TERI's own analysis, not BOT's stated framing.
- This page is an independent analytical summary prepared by TICGL/TERI and does not constitute financial, investment, tax, or legal advice.
MuhtasariMuhtasari kwa Kiswahili
Dollarization Tanzania: Maana Yake kwa Uchumi, FYDP IV na Dira 2050. Ndani ya Mpango Mkakati wa Benki Kuu ya Tanzania (BOT) wa 2026/27-2030/31, BOT yenyewe inakiri kuwepo kwa "mwelekeo unaokua wa dollarization" (matumizi makubwa ya dola badala ya shilingi) kama changamoto kubwa ya kimuundo inayoendelea kuikabili nchi. Suala hili linatajwa mara mbili kwenye mpango — kwenye uchambuzi wa hali ya sasa (Situation Analysis) na kwenye uchambuzi wa SWOC chini ya sehemu ya Changamoto (Challenges).
TICGL inaona hii ni miongoni mwa masuala muhimu zaidi yasiyoshughulikiwa vya kutosha kwenye mpango huu. Dollarization inaathiri moja kwa moja uwezo wa BOT kudhibiti uchumi kupitia kiwango cha riba (mfumo uliopitishwa Januari 2024), kwani mfumo huo unafanya kazi kwenye mikopo na akiba za shilingi tu. Kadri shughuli za kiuchumi zinavyohamia kwenye dola, ndivyo uwezo wa BOT wa kudhibiti mfumuko wa bei na ukuaji wa uchumi kupitia riba unavyopungua.
Kiashiria pekee cha kiasi (quantified proxy) kilichopo kwenye mpango kinachohusiana moja kwa moja na tatizo hili ni pengo la soko la fedha za kigeni baina ya benki (IFEM spread), ambalo kwa sasa ni TZS 57 na linalengwa kupungua hadi TZS 20 au chini ifikapo 2029/30. Hata hivyo, BOT haijaweka kiashiria maalum (KPI) kinachopima moja kwa moja kiwango cha dollarization — yaani asilimia ya amana na mikopo iliyo kwenye fedha za kigeni.
TICGL inapendekeza: (1) BOT iweke KPI mahususi ya "kiwango cha dollarization"; (2) uwekaji huru wa mtaji (capital account liberalization) usitangulie kabla ya maendeleo ya wazi kwenye kupunguza dollarization; (3) Tanzania ijifunze kutoka mfano wa Peru wa kupunguza dollarization kwa kutumia motisha badala ya vikwazo vikali; na (4) lengo la mikopo kwa sekta binafsi (30% ya GDP) ligawanywe kulingana na sarafu inayotumika, ili kujua kama ukuaji huo unafadhiliwa kwa shilingi au dola. Bila hatua madhubuti, malengo makubwa ya FYDP IV na Dira 2050 ya kuwa na uchumi imara, jumuishi na wenye ushindani ifikapo 2050 yanaweza kukwamishwa na tatizo hili la kimuundo.
- Pengo la soko la IFEM: TZS 57 kwa sasa, lengo ni TZS 20 au chini ifikapo 2029/30
- KPI maalum ya dollarization kwenye Mpango wa BOT: haipo
- Lengo la mikopo kwa sekta binafsi linalotegemea suluhu ya tatizo hili: angalau 30% ya GDP
- Mfumo wa sera ya fedha unaotegemea shilingi pekee: tangu Januari 2024
Vyanzo: Mpango Mkakati wa Benki Kuu ya Tanzania 2026/27-2030/31 (Juni 2026), uchambuzi wa TICGL/TERI kuhusu FYDP IV na Dira 2050. Uchambuzi umeandaliwa na Idara ya Utafiti ya TICGL / Tanzania Economic Research Institute (TERI).
05 — Pillar 3Social Security: Informal-Sector Growth Outpacing Formal, But From a Small Base
🏛️ Social Security & Social Assistance
Informal accounts: +103.2%Social security access points grew only modestly (+4.5% to 116), entirely driven by a 181.8% expansion in digital platforms, while the number of regional offices actually declined (-12.3%) and supplementary pension schemes fell (-33.3%) — a sector consolidating its physical footprint while digitising service delivery.
Formal vs. Informal-Sector Social Security Membership Growth
The evaluation credits several concrete reforms: NSSF's Hifadhi Scheme, established specifically for informal-sector workers — boda boda riders, small-scale miners, mama/baba lishe food vendors, small farmers, and street vendors; Zanzibar's Sharia-compliant pension products, which increased trust and participation by aligning with cultural and religious preferences; a reduction in the unemployment-benefit waiting period from 24 months to just 90 days; and the use of accrued pension benefits as collateral for housing finance, adding a tangible near-term value proposition to a traditionally long-horizon product.
Social assistance: TASAF and Zanzibar's Universal Pension Scheme
Under the Productive Social Safety Net (PSSN), TASAF had created 76,070 digital savings groups comprising 1,012,849 members by the end of the evaluation period — 89.0% of them women — mobilising TZS 17.50 billion in group savings and issuing TZS 8.90 billion in loans; 52.9% of beneficiaries had linked bank savings accounts, mostly smallholder farmers. In Zanzibar, the Universal Pension Scheme (ZUPS) reached 33,213 elders by December 2025 (up from 29,636), with the monthly benefit having been raised from TZS 20,000 to TZS 50,000 for those aged 70+. Both programmes are, by the evaluation's own account, constrained by heavy donor-aid dependency and outreach below 1% of the total population.