IDEAS home Printed from https://ideas.repec.org/p/unu/wpaper/wp-2024-66.html

Estimating the value-added tax gap in Tanzania: A study of small, medium, and micro enterprises

Author

Listed:
  • Amina Ebrahim
  • Sebastián Castillo
  • Vincent Leyaro
  • Ezekiel Swema
  • Oswald Haule
  • Massaga Fimbo
  • Ephraim Mdee

Abstract

This study measures the VAT compliance gap for small and medium-sized entities in Tanzania. Specifically, the study measures the under-reporting component of the VAT compliance gap. This study uses VAT declaration and audit data to conduct a bottom-up estimation to measure the extent of VAT misreporting in small, medium, and micro enterprises. The study's objective is to examine the extent of VAT under-reporting from 2014 to 2020 and identify the behaviour of firms that contribute to the VAT gap.

Suggested Citation

  • Amina Ebrahim & Sebastián Castillo & Vincent Leyaro & Ezekiel Swema & Oswald Haule & Massaga Fimbo & Ephraim Mdee, 2024. "Estimating the value-added tax gap in Tanzania: A study of small, medium, and micro enterprises," WIDER Working Paper Series wp-2024-66, World Institute for Development Economic Research (UNU-WIDER).
    • Handle: RePEc:unu:wpaper:wp-2024-66
    as

    Download full text from publisher

    File URL: https://www.wider.unu.edu/sites/default/files/Publications/Working-paper/PDF/wp2024-66-estimating-value-added-tax-gap-Tanzania.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kwabena Adu-Ababio & Aliisa Koivisto & Eliya Lungu & Evaristo Mwale & Jonathan Msoni & Kangwa Musole, 2023. "Estimating tax gaps in Zambia: A bottom-up approach based on audit assessments," WIDER Working Paper Series wp-2023-25, World Institute for Development Economic Research (UNU-WIDER).
    2. Sendhil Mullainathan & Jann Spiess, 2017. "Machine Learning: An Applied Econometric Approach," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 87-106, Spring.
    3. José M. Durán-Cabré & Alejandro Esteller Moré & Mariona Mas-Montserrat & Luca Salvadori, 2019. "The tax gap as a public management instrument: application to wealth taxes," Applied Economic Analysis, Emerald Group Publishing Limited, vol. 27(81), pages 207-225, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Juergen Deppner & Marcelo Cajias, 2024. "Accounting for Spatial Autocorrelation in Algorithm-Driven Hedonic Models: A Spatial Cross-Validation Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 68(2), pages 235-273, February.
    2. Naguib, Costanza, 2019. "Estimating the Heterogeneous Impact of the Free Movement of Persons on Relative Wage Mobility," Economics Working Paper Series 1903, University of St. Gallen, School of Economics and Political Science.
    3. Dang, Hai-Anh & Carleto, Gero & Gourlay, Sydney & Abanokova, Kseniya, 2023. "Addressing Soil Quality Data Gaps with Imputation: Evidence from Ethiopia and Uganda," 2023 Annual Meeting, July 23-25, Washington D.C. 335648, Agricultural and Applied Economics Association.
    4. Tobias Götze & Marc Gürtler & Eileen Witowski, 2020. "Improving CAT bond pricing models via machine learning," Journal of Asset Management, Palgrave Macmillan, vol. 21(5), pages 428-446, September.
    5. Sascha O. Becker & Thiemo Fetzer, 2018. "Has Eastern European Migration Impacted UK-born Workers?," CAGE Online Working Paper Series 376, Competitive Advantage in the Global Economy (CAGE).
    6. Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2017. "Econom\'etrie et Machine Learning," Papers 1708.06992, arXiv.org, revised Mar 2018.
    7. Crespo, Cristian, 2020. "Two become one: improving the targeting of conditional cash transfers with a predictive model of school dropout," LSE Research Online Documents on Economics 123139, London School of Economics and Political Science, LSE Library.
    8. Ioanna Arkoudi & Carlos Lima Azevedo & Francisco C. Pereira, 2021. "Combining Discrete Choice Models and Neural Networks through Embeddings: Formulation, Interpretability and Performance," Papers 2109.12042, arXiv.org, revised Sep 2021.
    9. Yucheng Yang & Zhong Zheng & Weinan E, 2020. "Interpretable Neural Networks for Panel Data Analysis in Economics," Papers 2010.05311, arXiv.org, revised Nov 2020.
    10. Erik Heilmann & Janosch Henze & Heike Wetzel, 2021. "Machine learning in energy forecasts with an application to high frequency electricity consumption data," MAGKS Papers on Economics 202135, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    11. Suriyan Jomthanachai & Wai Peng Wong & Khai Wah Khaw, 2024. "An Application of Machine Learning to Logistics Performance Prediction: An Economics Attribute-Based of Collective Instance," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 741-792, February.
    12. Tranos, Emmanouil & Incera, Andre Carrascal & Willis, George, 2022. "Using the web to predict regional trade flows: data extraction, modelling, and validation," OSF Preprints 9bu5z, Center for Open Science.
    13. Kristoffer B. Birkeland & Allan D. D'Silva & Roland Füss & Are Oust, 2021. "The Predictability of House Prices: "Human Against Machine"," International Real Estate Review, Global Social Science Institute, vol. 24(2), pages 139-183.
    14. Johannes König & Christian Schluter & Carsten Schröder, 2025. "Routes to the Top," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 71(2), May.
    15. Christian Posso & Jorge Tamayo & Arlen Guarin & Estefania Saravia, 2024. "Luck of the Draw: The Causal Effect of Physicians on Birth Outcomes," Borradores de Economia 1269, Banco de la Republica de Colombia.
    16. Bryan T. Kelly & Asaf Manela & Alan Moreira, 2019. "Text Selection," NBER Working Papers 26517, National Bureau of Economic Research, Inc.
    17. Manuel J. García Rodríguez & Vicente Rodríguez Montequín & Francisco Ortega Fernández & Joaquín M. Villanueva Balsera, 2019. "Public Procurement Announcements in Spain: Regulations, Data Analysis, and Award Price Estimator Using Machine Learning," Complexity, Hindawi, vol. 2019, pages 1-20, November.
    18. Md Mohsan Khudri & Kang Keun Rhee & Mohammad Shabbir Hasan & Karar Zunaid Ahsan, 2023. "Predicting nutritional status for women of childbearing age from their economic, health, and demographic features: A supervised machine learning approach," PLOS ONE, Public Library of Science, vol. 18(5), pages 1-31, May.
    19. Ratzanyel Rincón, 2023. "Quarterly multidimensional poverty estimates in Mexico using machine learning algorithms/Estimaciones trimestrales de pobreza multidimensional en México mediante algoritmos de aprendizaje de máquina," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 38(1), pages 3-68.
    20. Kwabena Adu-Ababio & Aliisa Koivisto & Eliya Lungu & Evaristo Mwale & Jonathan Msoni & Kangwa Musole, 2023. "Estimating tax gaps in Zambia: A bottom-up approach based on audit assessments," WIDER Working Paper Series wp-2023-25, World Institute for Development Economic Research (UNU-WIDER).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:unu:wpaper:wp-2024-66. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Siméon Rapin (email available below). General contact details of provider: https://edirc.repec.org/data/widerfi.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.