Impact Story: Tax Gap Work with a Global Impact

Finnish Centre of Excellence in Tax Systems Research FIT
Leader: Prof. Kaisa Kotakorpi, Tampere University
Author of the impact story: Jukka Pirttilä, University of Helsinki.
This note draws on background material shared by Dr Amina Ebrahim of UNU-WIDER.

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Impact objective: Strengthening tax compliance and revenue mobilization in developing countries through evidence-based capacity building

The objective is to enhance the effectiveness of tax administrations in developing countries by improving their capacity to measure, understand, and reduce tax compliance gaps for the benefit of entire societies. This is achieved by embedding rigorous, data-driven tax gap estimation methods into administrative practice and policy processes.

The main elements to reach the desired impact objective are the following:

1. Improving evidence-based revenue administration
   To enable tax authorities to systematically identify and quantify compliance gaps in major tax categories (Value Added Tax VAT, Corporate Income Tax CIT, and Personal Income Tax PIT), thereby supporting more targeted and efficient enforcement strategies.
2. Institutionalizing analytical capacity
   To support the regular production of tax gap estimates within revenue administrations, moving from one-off studies to sustained institutional practices.
3. Enhancing domestic revenue mobilization (DRM)
   To contribute to increased tax collection by informing audit strategies, risk management frameworks, and compliance interventions.
4. Supporting international policy commitments and standards
   To operationalize global initiatives (e.g., Addis Tax Initiative) by providing implementable tools and methodologies aligned with international monitoring frameworks.

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Means

Work on tax gap estimation began in Zambia with the publication of a bottom-up estimate by Kwabena Adu-Ababio and Aliisa Koivisto, in collaboration with the Zambia Revenue Authority, in 2023. At that time, Adu-Ababio was a PhD student at the University of Helsinki, part of the FIT team, and supervised by Jukka Pirttilä, one of the PIs of FIT. The request to conduct such tax gap estimates came from Zambia Revenue Authority, and Adu-Ababio and Pirttilä originally planned the methodology for the analysis, with Koivisto (VATT/FIT and on secondment at UNU-WIDER) joining soon afterwards.

Using administrative tax data, the analysis estimated that between 47 and 56 per cent of potential revenue from corporate income tax and value-added tax was not being collected. It also identified the most pronounced compliance gaps, particularly in the extractives sector for corporate income tax and in wholesale and retail trade for VAT. These findings informed revisions to audit strategies, strengthened the use of data analytics, and supported the creation of specialised capacity to address mining-related risks. The paper was recently published in ITAX Policy Watch journal under the title Estimating audit based tax gaps in Zambia.

Further capacity development and training were conducted in Zambia in person for ZRA staff by Kwabena Adu-Ababio in 2024 and 2025, and re-estimation of the tax gap is underway in Zambia with the aim of institutionalizing and regularizing the analysis.

Following the 2023 tax gap work in Zambia, Sebastián Castillo Ramos (University of Helsinki/FIT post-doctoral researcher) and Amina Ebrahim (UNU-WIDER) studied the VAT gap in Tanzania in collaboration with the University of Dar es Salaam and the Tanzania Revenue Authority. They supervised a research intern at the University of Helsinki, Mostafa Bahbah, who contributed to the study and who subsequently became a PhD student at Tampere University joining the FIT team. The study was later published in the CESifo Economic Studies journal. The results were disseminated through a Research Brief and were featured in the October 2025 IMF Regional Economic Outlook for Sub-Saharan Africa.

The toolkit project included a Training workshop in Dar es Salaam in March 2024 (together with the ATI, World Bank, and IMF) and an online training course in October 2024 on the toolkit’s use. The toolkit was launched in December 2024.

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Impacts

The Addis Tax Initiative Declaration 2025 states that it “will enhance the effectiveness of partner countries’ revenue administrations in curbing non-compliant behaviour by strengthening their capacities and capabilities, including risk management frameworks.” As a result of this commitment, a related indicator was included in the ATI Declaration 2025 monitoring framework, which states: “The number of ATI partner countries that produce regular (at least every two years) tax gap analysis for PIT, CIT, and VAT has increased by 2023/2025.”

This strong and growing demand from governments for practical, implementable tools to measure and reduce tax gaps led to the development of the Tax Gap Toolkit, supported by the International Tax Compact, funded by the German Federal Ministry for Economic Cooperation (BMZ), and co-funded by the European Union.

The Tax Gap toolkit is an adaptable set of materials that includes Stata code, readme files, and a technical note to guide users through the estimation process. The technical note of the toolkit is available in English, French, Spanish, and Portuguese to make it widely accessible and user-friendly. The toolkit can be used across various national contexts, making it a valuable resource for countries in the Global South aiming to improve their tax systems. It leverages already collected tax administrative information and uses cutting-edge machine learning techniques to provide a standardized framework for estimating tax gaps, which can be easily applied by tax administrations in several countries.

In connection of the launch of the Toolkit, the Tanzania workshop directly catalysed the creation of the ATI Tax Gap Community of Interest (CoI), which was formally conceptualised in June 2024 with the Zambia Revenue Authority as the inaugural chair. The CoI now holds quarterly meetings (the first on 25 September 2024, featuring the Tanzania and Kenya Revenue Authorities) and Tax Gap clinics (the first on 30 July 2024), plus an online resource depository for peer learning on VAT/CIT/PIT gaps.

In 2025, following the launch of the Toolkit, UNU-WIDER received formal requests from the revenue administrations in South Africa, Zimbabwe, Sierra Leone, and Eswatini for assistance in developing tax gap analysis capacity and producing tax gap estimates for their respective countries. This built directly on work by FIT researchers.

The Ministry of Finance in Indonesia expressed interest in conducting the analysis independently using its own expertise and resources. The MoF Indonesia recently presented its preliminary findings on the VAT gap estimation using the toolkit at the ATI Tax Gap Community of Interest: Quarterly Meeting. The study benefited from input from Sebastián Castillo and Amina Ebrahim on variable selection and ML modelling.

The Toolkit was presented at the UNDP Dialogue on Public Finance and the SDGs in New York in January 2025 where it featured in discussions on data-driven public finance, at the OECD Tax Gap Community of Practice meeting in Paris in February 2025;  at the ATI General Assembly in Addis Ababa in July linking to ATI Declaration 2025 priorities and the new Sevilla declaration; and in a masterclass at the African Tax Research Network (ATRN) congress in Cape Town in September 2025.

Tax gap toolkit materials and studies have also been used by UNU-WIDER for their inputs to the Public Economics course materials under development by VATT and led by Jukka Pirttilä, University of Helsinki. A follow-up Tax Gap Toolkit training was held in May 2025 for 64 ATI officials.

In 2026, Sebastián Castillo and Amina Ebrahim will collaborate with the IMF to produce the VAT gap estimates for Zimbabwe through a project funded by the IMF and in collaboration with the Zimbabwe Revenue Authority (ZIMRA). This includes training for ZIMRA staff, VAT gap estimation, and local engagement on the VAT gap results.

Together with the African Tax Administrations Forum (ATAF), UNU-WIDER will deliver a series of training workshops for ATAF members to improve their capacity to conduct independent tax gap estimations. This includes three online training courses in one in-person training.

The GIZ Good Financial Governance programme in Tunisia has expressed interest in applying the Tax Gap toolkit in Tunisia in collaboration with the Tunisian revenue administration. Amina Ebrahim met with the ATI and GIZ counterparts to develop a roadmap for the analysis.

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Results and publications

The study’s results were presented at a policy event in Zambia in 2023, where the Research Brief was also disseminated. The paper features in the United Nations Economic Commission for Africa Tax Policy manual for Zambia in 2025. Furthermore, the Zambia Tax Gap study shaped how compliance-focused reforms were framed during the 2026 Zambia Budget process, alongside projections showing an increase in ZRA revenue collection out of all revenue from 55.7 per cent in 2020 to 73.1 per cent in 2026. This is captured by Kwabena Adu-Ababio and Amina Ebrahim in the blog post titled “How our tax gap research fed into the Zambia Budget 2026.”

The Tax Gap Toolkit was mentioned in the PCT report to the G20 on DRM capacity development progress: Progress in Strengthening Frameworks for Building Tax Capacity: A Report to G20 Finance Ministers and Central Bank Governors | Platform for Collaboration on Tax

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Current and ongoing work

Sebastián Castillo, in collaboration with Maria Jouste and the Uganda Revenue Authority, is estimating the CIT gap for Uganda, extending the toolkit by testing additional machine learning models. Sebastián Castillo has also commented extensively on the CIT gap study and advised on the VAT gap study in South Africa. The studies in South Africa and Uganda are expected to be published in 2026 following a recent internal presentation to the South African Revenue Service.

The ATI is expected to fund a second phase of work starting Q3 2026 for a period of 2 years, which includes the further development of the Tax Gap toolkit to address challenges of selection bias and incorporate new machine learning models, converting the model to R and Python for broader application, continued dissemination and training, and application in ATI member countries.

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