IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v121y2023ics0264999323000299.html
   My bibliography  Save this article

What drives the performance of tax administrations? Evidence from selected european countries

Author

Listed:
  • Milosavljević, Miloš
  • Radovanović, Sandro
  • Delibašić, Boris

Abstract

An effective, efficient, fair, and trusted tax administration is a top priority for every country in the world; however, tax administration faces many issues, such as corruption, tax avoidance, or lack of flexibility. Some countries perform better in this process, and this paper aims to identify the main drivers of tax administration performance. We analyzed 35 European tax administrations by 12 performance dimensions in 2 consecutive years (2018–2019) and created a comprehensive performance measurement indicator using a data-driven neutral-aggregation approach. The findings indicate that (a) digitalization of tax administrations is the most influential driver of the overall tax administration performance, (b) Nordic countries and Switzerland can serve as role models for tax administration performance, and (c) the country-level results can serve as a proxy for the degree of the shadow economy. These findings guide European policymakers regarding the appropriate policy measures required to improve the performance of tax administration.

Suggested Citation

  • Milosavljević, Miloš & Radovanović, Sandro & Delibašić, Boris, 2023. "What drives the performance of tax administrations? Evidence from selected european countries," Economic Modelling, Elsevier, vol. 121(C).
  • Handle: RePEc:eee:ecmode:v:121:y:2023:i:c:s0264999323000299
    DOI: 10.1016/j.econmod.2023.106217
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999323000299
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econmod.2023.106217?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Katzenbach, Christian & Ulbricht, Lena, 2019. "Algorithmic governance," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 8(4), pages 1-18.
    2. M. Chatib Basri & Mayara Felix & Rema Hanna & Benjamin A. Olken, 2021. "Tax Administration versus Tax Rates: Evidence from Corporate Taxation in Indonesia," American Economic Review, American Economic Association, vol. 111(12), pages 3827-3871, December.
    3. Tunyi, Abongeh A. & Ntim, Collins G. & Danbolt, Jo, 2019. "Decoupling management inefficiency: Myopia, hyperopia and takeover likelihood," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 1-20.
    4. Leandro Medina & Mr. Friedrich Schneider, 2018. "Shadow Economies Around the World: What Did We Learn Over the Last 20 Years?," IMF Working Papers 2018/017, International Monetary Fund.
    5. Awasthi, Rajul & Nagarajan, Mohan & Deininger, Klaus W., 2021. "Property taxation in India: Issues impacting revenue performance and suggestions for reform," Land Use Policy, Elsevier, vol. 110(C).
    6. Milosavljević, Milos & Dobrota, Marina & Milanović, Nemanja, 2019. "A New Approach to the Evaluation of Public Procurement Efficiency among European Countries," European Review, Cambridge University Press, vol. 27(2), pages 246-259, May.
    7. Katzenbach, Christian & Ulbricht, Lena, 2019. "Algorithmic governance," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 8(4), pages 1-18.
    8. Friedrich Schneider & Konrad Raczkowski & Bogdan Mróz, 2015. "Shadow economy and tax evasion in the EU," Journal of Money Laundering Control, Emerald Group Publishing Limited, vol. 18(1), pages 34-51, January.
    9. König, Pascal D. & Wenzelburger, Georg, 2021. "The legitimacy gap of algorithmic decision-making in the public sector: Why it arises and how to address it," Technology in Society, Elsevier, vol. 67(C).
    10. Itf, 2019. "Governing Transport in the Algorithmic Age," International Transport Forum Policy Papers 82, OECD Publishing.
    11. Ernesto Crivelli, 2019. "A basic tool to assess tax administration strength in emerging Europe," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 27(2), pages 425-446, February.
    12. Anders Jensen, 2022. "Employment Structure and the Rise of the Modern Tax System," American Economic Review, American Economic Association, vol. 112(1), pages 213-234, January.
    13. Ning Ding & Xinnan Zhang & Yiming Zhai & Chenglong Li, 2021. "Risk assessment of VAT invoice crime levels of companies based on DFPSVM: a case study in China," Risk Management, Palgrave Macmillan, vol. 23(1), pages 75-96, June.
    14. Õie Renata Siimon & Oliver Lukason, 2021. "A Decision Support System for Corporate Tax Arrears Prediction," Sustainability, MDPI, vol. 13(15), pages 1-23, July.
    15. Gupta, Sanjeev & Jalles, João Tovar, 2022. "Do tax reforms affect income distribution? Evidence from developing countries," Economic Modelling, Elsevier, vol. 110(C).
    16. Svitlana Khalatur & Olena Trokhymets & Oleksandr Karamushka, 2020. "Conceptual Basis Of Tax Policy Formation In The Globalization Conditions," Baltic Journal of Economic Studies, Publishing house "Baltija Publishing", vol. 6(2).
    17. Friedrich Schneider, 2022. "New COVID-related results for estimating the shadow economy in the global economy in 2021 and 2022," International Economics and Economic Policy, Springer, vol. 19(2), pages 299-313, May.
    18. Kim, Eun-Sung, 2020. "Deep learning and principal–agent problems of algorithmic governance: The new materialism perspective," Technology in Society, Elsevier, vol. 63(C).
    19. Nguyen, Trang T.T. & Prior, Diego & Van Hemmen, Stefan, 2020. "Stochastic semi-nonparametric frontier approach for tax administration efficiency measure: Evidence from a cross-country study," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 137-153.
    20. Gordana Savić & Aleksandar Dragojlović & Mirko Vujošević & Milojko Arsić & Milan Martić, 2015. "Impact of the efficiency of the tax administration on tax evasion," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 28(1), pages 1138-1148, January.
    21. Luiz de Mello, 2009. "Avoiding the Value Added Tax," Public Finance Review, , vol. 37(1), pages 27-46, January.
    22. Li, Jianjun & Wang, Xuan & Wu, Yaping, 2020. "Can government improve tax compliance by adopting advanced information technology? Evidence from the Golden Tax Project III in China," Economic Modelling, Elsevier, vol. 93(C), pages 384-397.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Barra, Cristian & Papaccio, Anna & Ruggiero, Nazzareno, 2024. "Are cooperative and commercial banks equally effective in reducing the shadow economy? International evidence," Economic Modelling, Elsevier, vol. 138(C).

    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. Tironi, Martín & Rivera Lisboa, Diego Ignacio, 2023. "Artificial intelligence in the new forms of environmental governance in the Chilean State: Towards an eco-algorithmic governance," Technology in Society, Elsevier, vol. 74(C).
    2. Cowls, Josh & Morley, Jessica & Floridi, Luciano, 2023. "App store governance: Implications, limitations, and regulatory responses," Telecommunications Policy, Elsevier, vol. 47(1).
    3. BRICI Iulia & ACHIM Monica Violeta, 2023. "Does The Digitalization Of Public Services Influence Economic And Financial Crime?," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 18(2), pages 67-85, August.
    4. Arzhenovskiy, Sergey, 2023. "Estimate of shadow economy dynamics in Russia and regions: The inflationary aspect," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 69, pages 121-140.
    5. Ulbricht, Lena, 2020. "Algorithmen und Politisierung [Algorithms and politicization]," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 0, pages 255-278.
    6. Kniep, Ronja, 2022. ""Herren der Information" - Die transnationale Autonomie digitaler Überwachung ["Masters of information" - The transnational autonomy of digital surveillance]," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 32(2), pages 457-480.
    7. Nguyen, Canh Phuc & Nguyen, Binh Quang, 2023. "Environmental foe or friend: The influence of the shadow economy on forest land," Land Use Policy, Elsevier, vol. 124(C).
    8. Eduard Hartwich & Alexander Rieger & Johannes Sedlmeir & Dominik Jurek & Gilbert Fridgen, 2023. "Machine economies," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-13, December.
    9. Lena Ulbricht & Karen Yeung, 2022. "Algorithmic regulation: A maturing concept for investigating regulation of and through algorithms," Regulation & Governance, John Wiley & Sons, vol. 16(1), pages 3-22, January.
    10. Sebastián Bustos & Dina Pomeranz & Juan Carlos Suárez Serrato & José Vila-Belda & Gabriel Zucman, 2022. "The Race Between Tax Enforcement and Tax Planning: Evidence From a Natural Experiment in Chile," NBER Working Papers 30114, National Bureau of Economic Research, Inc.
    11. Martina Bazzoli & Paolo Di Caro & Franceso Figari & Carlo V. Fiorio & Marco Manzo, 2020. "Size, heterogeneity and distributional effects of self-employment income tax evasion in Italy," Working Papers wp2020-8, Ministry of Economy and Finance, Department of Finance.
    12. Sætra, Henrik Skaug, 2020. "A shallow defence of a technocracy of artificial intelligence: Examining the political harms of algorithmic governance in the domain of government," Technology in Society, Elsevier, vol. 62(C).
    13. Apeti, Ablam Estel & Edoh, Eyah Denise, 2023. "Tax revenue and mobile money in developing countries," Journal of Development Economics, Elsevier, vol. 161(C).
    14. Achim, Monica Violeta & Postea, Mihaela Maria & Noja, Gratiela Georgiana, 2024. "New estimate of shadow economy based on the total energy consumption. Evidence from the European Union countries," Energy Economics, Elsevier, vol. 130(C).
    15. Oanh Tran Thi Kim & Quoc Huynh Van & Nha Lam Tuan & Chau Nguyen Thi Bao & Phat Nguyen Huu, 2024. "The Relationship Between the Shadow Economy, Corruption, and Taxes: Empirical Evidence from Countries with High and Low Financial Development," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 34(4), pages 78-104.
    16. Dolata, Ulrich, 2020. "Internet – Plattformen – Regulierung: Koordination von Märkten und Kuratierung von Sozialität," Research Contributions to Organizational Sociology and Innovation Studies, SOI Discussion Papers 2020-01, University of Stuttgart, Institute for Social Sciences, Department of Organizational Sociology and Innovation Studies.
    17. Garriga, Pablo & Tortarolo, Dario, 2024. "Firms as tax collectors," Journal of Public Economics, Elsevier, vol. 233(C).
    18. Dolata, Ulrich, 2020. "Internet – Platforms – Regulation: Coordination of Markets and Curation of Sociality," Research Contributions to Organizational Sociology and Innovation Studies, SOI Discussion Papers 2020-02, University of Stuttgart, Institute for Social Sciences, Department of Organizational Sociology and Innovation Studies.
    19. Md. Harun Ur Rashid & Afzal Ahmad & Muhammad Saleh Abdullah & Monir Ahmmed & Serajul Islam, 2022. "Doing Business and Tax Evasion: Evidence from Asian Countries," SAGE Open, , vol. 12(4), pages 21582440221, October.
    20. Ligita Gasparėnienė & Rita Remeikienė & Colin C. Williams, 2022. "Unemployment and the Informal Economy," SpringerBriefs in Economics, Springer, number 978-3-030-96687-4, June.

    More about this item

    Keywords

    Tax administration; Performance measurement; Algorithmic governance; Machine learning; Multi-criteria decision-making;
    All these keywords.

    JEL classification:

    • C69 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Other
    • H21 - Public Economics - - Taxation, Subsidies, and Revenue - - - Efficiency; Optimal Taxation
    • H11 - Public Economics - - Structure and Scope of Government - - - Structure and Scope of Government

    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:eee:ecmode:v:121:y:2023:i:c:s0264999323000299. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    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.