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Revisiting tax effort in emerging markets

Author

Listed:
  • Gustavo Canavire-Bacarreza
  • Maria Cecilia Deza
  • Osmel Manzano
  • Alejandro Puerta

Abstract

Insufficient tax revenues has been one of the most pervasive restrictions on investment in the social and economic infrastructure needed to close the development gaps in emerging markets (EM). To assess the potential for increasing tax collection, the literature has emphasized the concept of tax capacity and tax effort. Conceptually, tax effort is modeled as an inefficiency term with both time-varying and time-invariant components. These are commonly estimated through OLS or stochastic frontier analysis techniques. However, these strategies provide only point estimates and are limited in their ability to break down tax effort into time-varying and time-invariant components. We estimate tax effort for a balanced panel of 108 countries for which data were available from 2002 to 2017, using a Bayesian strategy that allows us to calculate the invariant inefficiency as an upper bound for a country’s tax effort. We also show that the GTRE model from Tsionas and Kumbhakar (2014 ) allows for more precise estimates, providing powerful tools for more informed fiscal planning.

Suggested Citation

  • Gustavo Canavire-Bacarreza & Maria Cecilia Deza & Osmel Manzano & Alejandro Puerta, 2021. "Revisiting tax effort in emerging markets," Public Finance Review, , vol. 49(6), pages 845-873, November.
    • Handle: RePEc:sae:pubfin:v:49:y:2021:i:6:p:845-873
    DOI: 10.1177/10911421221077213
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    References listed on IDEAS

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    9. Mr. Marco Committeri & Ms. Carola Pessino, 2013. "Understanding Countries’ Tax Effort," IMF Working Papers 2013/244, International Monetary Fund.
    10. Musharraf Cyan & Jorge Martinez-Vazquez & VIoleta Vulovic, 2013. "Measuring tax effort: Does the estimation approach matter and should effort be linked to expenditure goals?," International Center for Public Policy Working Paper Series, at AYSPS, GSU paper1308, International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University.
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    Cited by:

    1. Puerta-Cuartas, Alejandro & Ramírez-Hassan, Andrés, 2025. "A spatial one-sided error model to identify where unarrested criminals live," Economic Modelling, Elsevier, vol. 142(C).

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    More about this item

    Keywords

    tax effort; tax revenue; stochastic frontier analysis; bayesian econometrics; JEL CODES: C23; C51; H2; H21;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • H2 - Public Economics - - Taxation, Subsidies, and Revenue
    • H21 - Public Economics - - Taxation, Subsidies, and Revenue - - - Efficiency; Optimal Taxation

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