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Drivers of mean reversion bias in the estimation of elasticity of taxable income in an autoregressive framework

Author

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  • Bruno Bosco
  • Paolo Maranzano

Abstract

Mean reversion, the tendency for taxpayers with unusually high or low income in one period to move towards their long-run average, is a key challenge for estimating the elasticity of taxable income (ETI), as it generates bias. We show that this bias can be characterised through the variance of the tax treatment and its covariance with windfall gains in an autoregressive model of taxable income dynamics. We further show that the bias decreases when the tax reaction of marginal treated taxpayers is weaker than that of average treated taxpayers. The paper provides analytical derivations and interpretation for these results.

Suggested Citation

  • Bruno Bosco & Paolo Maranzano, 2026. "Drivers of mean reversion bias in the estimation of elasticity of taxable income in an autoregressive framework," Working Papers 578, University of Milano-Bicocca, Department of Economics.
    • Handle: RePEc:mib:wpaper:578
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    References listed on IDEAS

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    1. Badi H. Baltagi, 2021. "Econometric Analysis of Panel Data," Springer Texts in Business and Economics, Springer, edition 6, number 978-3-030-53953-5, January.
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    4. Gruber, Jon & Saez, Emmanuel, 2002. "The elasticity of taxable income: evidence and implications," Journal of Public Economics, Elsevier, vol. 84(1), pages 1-32, April.
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    Keywords

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    JEL classification:

    • H30 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - General
    • H24 - Public Economics - - Taxation, Subsidies, and Revenue - - - Personal Income and Other Nonbusiness Taxes and Subsidies
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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