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Presumptive taxation and firms’ efficiency: an integrated approach for tax compliance analysis

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Listed:
  • ferrara, giancarlo
  • campagna, arianna
  • bucci, valeria
  • atella, vincenzo

Abstract

Presumptive taxation methods are policy tools widespread adopted by fiscal authorities with the aim to improve voluntary tax compliance and to fight tax evasion. Such methods allow authorities to uncover firms’ under-reporting, but face several limits. In particular, presumptive taxation methods do not allow to disentangle when the presence of under-reporting is ascribable to tax evasion behaviour or to the lack of managerial skills and inefficiency. To overcome the main presumptive taxation weakness, we propose combining presumptive frameworks with a measure of technical efficiency, thus developing an integrated approach for tax evasion analysis able to support the audit activities of fiscal authorities. Further, we provide some considerations in terms of tax compliance and support our approach with evidence obtained from an empirical application based on Italian firms.

Suggested Citation

  • ferrara, giancarlo & campagna, arianna & bucci, valeria & atella, vincenzo, 2021. "Presumptive taxation and firms’ efficiency: an integrated approach for tax compliance analysis," MPRA Paper 111516, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:111516
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    References listed on IDEAS

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    1. Francesco Vidoli & Giancarlo Ferrara, 2015. "Analyzing Italian citrus sector by semi-nonparametric frontier efficiency models," Empirical Economics, Springer, vol. 49(2), pages 641-658, September.
    2. Shlomo Yitzhaki, 2007. "Cost-Benefit Analysis of Presumptive Taxation," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 63(3), pages 311-326, September.
    3. Valeria Bucci, 2020. "Presumptive Taxation Methods: A Review Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 34(2), pages 372-397, April.
    4. Lindsay Tedds, 2010. "Keeping it off the books: an empirical investigation of firms that engage in tax evasion," Applied Economics, Taylor & Francis Journals, vol. 42(19), pages 2459-2473.
    5. Godwin Dube, 2018. "The design and implementation of minibus taxi presumptive taxes," The Service Industries Journal, Taylor & Francis Journals, vol. 38(11-12), pages 723-741, September.
    6. Sickles,Robin C. & Zelenyuk,Valentin, 2019. "Measurement of Productivity and Efficiency," Cambridge Books, Cambridge University Press, number 9781107036161, September.
    7. Fan, Yanqin & Li, Qi & Weersink, Alfons, 1996. "Semiparametric Estimation of Stochastic Production Frontier Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 460-468, October.
    8. Kumbhakar, Subal C. & Park, Byeong U. & Simar, Leopold & Tsionas, Efthymios G., 2007. "Nonparametric stochastic frontiers: A local maximum likelihood approach," Journal of Econometrics, Elsevier, vol. 137(1), pages 1-27, March.
    9. Miriam Bruhn & Jan Loeprick, 2016. "Small business tax policy and informality: evidence from Georgia," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 23(5), pages 834-853, October.
    10. Berger, Allen N. & Bonaccorsi di Patti, Emilia, 2006. "Capital structure and firm performance: A new approach to testing agency theory and an application to the banking industry," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1065-1102, April.
    11. Almas Heshmati, 2003. "Productivity Growth, Efficiency and Outsourcing in Manufacturing and Service Industries," Journal of Economic Surveys, Wiley Blackwell, vol. 17(1), pages 79-112, February.
    12. Ms. Milka Casanegra de Jantscher & Mr. Vito Tanzi, 1987. "Presumptive Income Taxation: Administrative, Efficiency, and Equity Aspects," IMF Working Papers 1987/054, International Monetary Fund.
    13. Muggeo, Vito M.R. & Ferrara, Giancarlo, 2008. "Fitting generalized linear models with unspecified link function: A P-spline approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2529-2537, January.
    14. Benno Torgler, 2016. "Tax Compliance and Data: What Is Available and What Is Needed," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 49(3), pages 352-364, September.
    15. Alessandro Santoro, 2008. "Taxpayers’Choices Under Studi Di Settore:What Do We Know And How We Can Interpret It?," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 67(2), pages 161-184, July.
    16. Yu Y. & Ruppert D., 2002. "Penalized Spline Estimation for Partially Linear Single-Index Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1042-1054, December.
    17. Joel Slemrod, 2007. "Cheating Ourselves: The Economics of Tax Evasion," Journal of Economic Perspectives, American Economic Association, vol. 21(1), pages 25-48, Winter.
    18. Joel Slemrod & Shlomo Yitzhaki, 1994. "Analyzing the standard deduction as a presumptive tax," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 1(1), pages 25-34, February.
    19. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    20. Ferrara, Giancarlo & Vidoli, Francesco, 2017. "Semiparametric stochastic frontier models: A generalized additive model approach," European Journal of Operational Research, Elsevier, vol. 258(2), pages 761-777.
    21. Gokalp, Omer N. & Lee, Seung-Hyun & Peng, Mike W., 2017. "Competition and corporate tax evasion: An institution-based view," Journal of World Business, Elsevier, vol. 52(2), pages 258-269.
    22. Dimitris Margaritis & Maria Psillaki, 2007. "Capital Structure and Firm Efficiency," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 34(9‐10), pages 1447-1469, November.
    23. Carlo Fiorio & Stefano Iacus & Alessandro Santoro, 2013. "Taxpaying response of small firms to an increased probability of audit: some evidence from Italy," Working Papers 251, University of Milano-Bicocca, Department of Economics, revised Jul 2013.
    24. Slemrod, Joel, 1990. "Optimal Taxation and Optimal Tax Systems," Journal of Economic Perspectives, American Economic Association, vol. 4(1), pages 157-178, Winter.
    25. Giampaolo Arachi and Alessandro Santoro, 2008. "Tax Enforcement for SMEs: Lessons from the Italian Experience?," Taxation eJournal of Tax Research , ATAX, University of New South Wales.
    26. Joel Slemrod, 2019. "Tax Compliance and Enforcement," Journal of Economic Literature, American Economic Association, vol. 57(4), pages 904-954, December.
    27. Simon N. Wood, 2003. "Thin plate regression splines," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 95-114, February.
    28. Joel Slemrod & Caroline Weber, 2012. "Evidence of the invisible: toward a credibility revolution in the empirical analysis of tax evasion and the informal economy," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 19(1), pages 25-53, February.
    29. Alvarez, Roberto & Crespi, Gustavo, 2003. "Determinants of Technical Efficiency in Small Firms," Small Business Economics, Springer, vol. 20(3), pages 233-244, May.
    30. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    More about this item

    Keywords

    Tax Compliance; Presumptive Taxation; Efficiency; Stochastic Frontier; Business Sector Studies;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion and Avoidance
    • H32 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Firm

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