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Individual Heterogeneity, Nonlinear Budget Sets, and Taxable Income

Author

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  • Sören Blomquist
  • Anil Kumar
  • Che-Yuan Liang
  • Whitney K. Newey
Abstract
Many studies have estimated the effect of taxes on taxable income. To account for nonlinear taxes these studies either use instrumental variables approaches that are not fully consistent, or impose strong functional form assumptions. None allow for general heterogeneity in preferences. In this paper we derive the expected value and distribution of taxable income, conditional on a nonlinear budget set, allowing general heterogeneity and optimization error in taxable income. We find an important dimension reduction and use that to develop nonparametric estimation methods. We show how to nonparametrically estimate the expected value of taxable income imposing all the restrictions of utility maximization and allowing for measurement errors. We characterize what can be learned nonparametrically from kinks about compensated tax effects. We apply our results to Swedish data and estimate for prime age males a significant net of tax elasticity of 0.21 and a significant nonlabor income effect of about -1. The income effect is substantially larger in magnitude than found in other taxable income studies.

Suggested Citation

  • Sören Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2015. "Individual Heterogeneity, Nonlinear Budget Sets, and Taxable Income," CESifo Working Paper Series 5320, CESifo.
    • Handle: RePEc:ces:ceswps:_5320
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    Cited by:

    1. Claudia Keser & David Masclet & Claude Montmarquette, 2020. "Labor Supply, Taxation, and the Use of Tax Revenues: A Real-Effort Experiment in Canada, France, and Germany," Public Finance Review, , vol. 48(6), pages 714-750, November.
    2. Einav, Liran & Finkelstein, Amy & Schrimpf, Paul, 2017. "Bunching at the kink: Implications for spending responses to health insurance contracts," Journal of Public Economics, Elsevier, vol. 146(C), pages 27-40.
    3. Bertanha, Marinho & McCallum, Andrew H. & Seegert, Nathan, 2023. "Better bunching, nicer notching," Journal of Econometrics, Elsevier, vol. 237(2).
    4. Sören Blomquist & Whitney K. Newey & Anil Kumar & Che-Yuan Liang, 2021. "On Bunching and Identification of the Taxable Income Elasticity," Journal of Political Economy, University of Chicago Press, vol. 129(8), pages 2320-2343.
    5. Einav, Liran & Finkelstein, Amy & Schrimpf, Paul, 2019. "Reprint of: Bunching at the kink: Implications for spending responses to health insurance contracts," Journal of Public Economics, Elsevier, vol. 171(C), pages 117-130.
    6. Liang, Che-Yuan, 2018. "Taxes and Household Labor Supply: Estimating Distributional Effects of Nonlinear Prices on Multidimensional Choice," Working Paper Series 2018:2, Uppsala University, Department of Economics.
    7. Blomquist, Sören & Simula, Laurent, 2019. "Marginal deadweight loss when the income tax is nonlinear," Journal of Econometrics, Elsevier, vol. 211(1), pages 47-60.
    8. Kumar, Anil & Liang, Che-Yuan, 2020. "Estimating taxable income responses with elasticity heterogeneity," Journal of Public Economics, Elsevier, vol. 188(C).
    9. Victor Chernozhukov & Jerry Hausman & Whitney K. Newey, 2019. "Demand analysis with many prices," CeMMAP working papers CWP59/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Soren Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2022. "Nonlinear Budget Set Regressions for the Random Utility Model," Working Papers 2219, Federal Reserve Bank of Dallas.
    11. Daniel Wilhelm, 2018. "Testing for the presence of measurement error," CeMMAP working papers CWP45/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Jerry A. Hausman & Whitney K. Newey, 2016. "Individual Heterogeneity and Average Welfare," Econometrica, Econometric Society, vol. 84, pages 1225-1248, May.
    13. Gregory Cox, 2018. "Almost Sure Uniqueness of a Global Minimum Without Convexity," Papers 1803.02415, arXiv.org, revised Feb 2019.
    14. Sören Blomquist & Whitney K. Newey, 2017. "The Bunching Estimator Cannot Identify the Taxable Income Elasticity," CESifo Working Paper Series 6736, CESifo.
    15. Hernández-Pizarro, Helena M. & Nicodemo, Catia & Casasnovas, Guillem López, 2020. "Discontinuous system of allowances: The response of prosocial health-care professionals," Journal of Public Economics, Elsevier, vol. 190(C).
    16. Chernozhukov, Victor & Fernández-Val, Iván & Newey, Whitney K., 2019. "Nonseparable multinomial choice models in cross-section and panel data," Journal of Econometrics, Elsevier, vol. 211(1), pages 104-116.
    17. Myunghyun Song, 2024. "Identification and Inference in General Bunching Designs," Papers 2411.03625, arXiv.org, revised Nov 2024.
    18. Sören Blomquist, 2023. "Evaluating the Discrete Choice and BN Methods to Estimate Labor Supply Functions," CESifo Working Paper Series 10827, CESifo.
    19. Kumar, Anil & Liang, Che-Yuan, 2015. "The Taxable Income Elasticity: A Structural Differencing Approach," Working Paper Series, Center for Fiscal Studies 2015:1, Uppsala University, Department of Economics.
    20. Leonard Goff, 2022. "Treatment Effects in Bunching Designs: The Impact of Mandatory Overtime Pay on Hours," Papers 2205.10310, arXiv.org, revised Jun 2024.
    21. Liang, Che-Yuan, 2014. "Distribution-Free Structural Estimation with Nonlinear Budget Sets," Working Paper Series, Center for Fiscal Studies 2014:4, Uppsala University, Department of Economics.
    22. Christopher Dobronyi & Christian Gouri'eroux, 2020. "Consumer Theory with Non-Parametric Taste Uncertainty and Individual Heterogeneity," Papers 2010.13937, arXiv.org, revised Jan 2021.
    23. Jerry Hausman & Whitney K. Newey, 2014. "Individual Heterogeneity and Average Welfare," CeMMAP working papers 42/14, Institute for Fiscal Studies.
    24. Richard Blundell, 2017. "What Have We Learned from Structural Models?," American Economic Review, American Economic Association, vol. 107(5), pages 287-292, May.

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    More about this item

    Keywords

    nonlinear budget sets; nonparametric estimation; heterogeneous preferences; taxable income; revealed stochastic preference;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • H30 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - General
    • H31 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Household
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

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