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The bunching estimator cannot identify the taxable income elasticity

Author

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  • Soren Blomquist

    (Institute for Fiscal Studies)

  • Whitney K. Newey

    (Institute for Fiscal Studies and MIT)

Abstract

Saez (2010) introduced an influential estimator that has become known as the bunching estimator. Using this method one can get an estimate of the taxable income elasticity from the bunching pattern around a kink point. The bunching estimator has become popular, with a large number of papers applying the method. In this paper, we show that the bunching estimator cannot identify the taxable income elasticity when the functional form of the distribution of preference heterogeneity is unknown. We find that an observed distribution of taxable income around a kink point in a budget set can be consistent with any taxable income elasticity if the distribution of heterogeneity is unrestricted. If one is willing to assume restrictions on the heterogeneity density some information about the taxable income elasticity can be obtained. We give bounds on the taxable income elasticity based on monotonicity of the heterogeneity density and apply these bounds to the data in Saez (2010). We also consider identification from budget set variation. We find that kinks alone are still not informative even when budget sets vary. However, if the taxable income specification is restricted to be of the parametric isoelastic form assumed in Saez (2010) the taxable income elasticity can be well identified from variation among linear segments of budget sets.

Suggested Citation

  • Soren Blomquist & Whitney K. Newey, 2017. "The bunching estimator cannot identify the taxable income elasticity," CeMMAP working papers CWP40/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:cemmap:40/17
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    1. Soren Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2014. "Individual heterogeneity, nonlinear budget sets, and taxable income," CeMMAP working papers CWP21/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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    Cited by:

    1. Vincent Dekker & Karsten Schweikert, 2021. "A Comparison of Different Data-driven Procedures to Determine the Bunching Window," Public Finance Review, , vol. 49(2), pages 262-293, March.
    2. Zhao Chen & Zhikuo Liu & Juan Carlos Suárez Serrato & Daniel Yi Xu, 2021. "Notching R&D Investment with Corporate Income Tax Cuts in China," American Economic Review, American Economic Association, vol. 111(7), pages 2065-2100, July.
    3. Alinaghi, Nazila & Creedy, John & Gemmell, Norman, 2020. "Do Couples Bunch More? Evidence from Partnered and Single Taxpayers in New Zealand," Working Paper Series 9366, Victoria University of Wellington, Chair in Public Finance.
    4. Hargaden, Enda Patrick, 2020. "Taxpayer responses in good times and bad," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 653-690.
    5. Glogowsky, Ulrich, 2021. "Behavioral responses to inheritance and gift taxation: Evidence from Germany," Journal of Public Economics, Elsevier, vol. 193(C).
    6. Stuart Adam & James Browne & David Phillips & Barra Roantree, 2021. "Frictions and taxpayer responses: evidence from bunching at personal tax thresholds," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 28(3), pages 612-653, June.
    7. Felix J. Bierbrauer & Pierre C. Boyer & Andreas Peichl, 2021. "Politically Feasible Reforms of Nonlinear Tax Systems," American Economic Review, American Economic Association, vol. 111(1), pages 153-191, January.
    8. Bertanha, Marinho & McCallum, Andrew H. & Seegert, Nathan, 2023. "Better bunching, nicer notching," Journal of Econometrics, Elsevier, vol. 237(2).
    9. Nazila Alinaghi & John Creedy & Norman Gemmell, 2023. "Do couples bunch more? Evidence from partnered and single taxpayers," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(4), pages 1137-1184, August.
    10. Tuomas Kosonen & Tuomas Matikka, 2019. "Discrete earnings responses to tax incentives: Empirical evidence and implications," Working Papers 326, Työn ja talouden tutkimus LABORE, The Labour Institute for Economic Research LABORE.
    11. Rema Hanna & Benjamin A. Olken, 2019. "Tax Administration vs. Tax Rates: Evidence from Corporate Taxation in Indonesia," CID Working Papers 361, Center for International Development at Harvard University.
    12. Matthew Gudgeon & Simon Trenkle, 2024. "The Speed of Earnings Responses to Taxation and the Role of Firm Labor Demand," Journal of Labor Economics, University of Chicago Press, vol. 42(3), pages 793-835.
    13. Marx, Benjamin M., 2018. "Dynamic Bunching Estimation with Panel Data," MPRA Paper 88647, University Library of Munich, Germany.
    14. Massenz, Gabriella, 2023. "On the behavioral effects of tax policy," Other publications TiSEM eb44a9f7-b859-480d-b2e4-4, Tilburg University, School of Economics and Management.
    15. Bohne, Albrecht & Nimczik, Jan Sebastian, 2018. "Information Frictions and Learning Dynamics: Evidence from Tax Avoidance in Ecuador," IZA Discussion Papers 11536, Institute of Labor Economics (IZA).
    16. Alinaghi, Nazila & Creedy, John & Gemmell, Norman, 2020. "Do Couples Bunch More? Evidence from Partnered and Single Taxpayers in New Zealand," Working Paper Series 21094, Victoria University of Wellington, Chair in Public Finance.
    17. He, Daixin & Peng, Langchuan & Wang, Xiaxin, 2021. "Understanding the elasticity of taxable income: A tale of two approaches," Journal of Public Economics, Elsevier, vol. 197(C).
    18. Homonoff, Tatiana & Willage, Barton & Willén, Alexander, 2020. "Rebates as incentives: The effects of a gym membership reimbursement program," Journal of Health Economics, Elsevier, vol. 70(C).
    19. Helen Miller & Thomas Pope & Kate Smith, 2024. "Intertemporal Income Shifting and the Taxation of Business Owner-Managers," The Review of Economics and Statistics, MIT Press, vol. 106(1), pages 184-201, January.
    20. Nicole Bosch & Vincent Dekker & Kristina Strohmaier, 2020. "A data-driven procedure to determine the bunching window: an application to the Netherlands," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 27(4), pages 951-979, August.
    21. Asatryan, Zareh & Peichl, Andreas, 2016. "Responses of firms to tax, administrative and accounting rules: Evidence from Armenia," ZEW Discussion Papers 16-065, ZEW - Leibniz Centre for European Economic Research.
    22. Daniel M. Hungerman & Mark Ottoni-Wilhelm, 2021. "Impure Impact Giving: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 129(5), pages 1553-1614.
    23. Aronsson, Thomas & Jenderny, Katharina & Lanot, Gauthier, 2021. "Maximum Likelihood Bunching Estimators of the ETI," Umeå Economic Studies 987, Umeå University, Department of Economics.

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