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How Much Should We Trust Regression-Kink-Design Estimates?

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  • Ando, Michihito

    (Uppsala Center for Fiscal Studies)

Abstract

In a Regression Kink (RK) design with a finite sample, a confounding smooth nonlinear relationship between an assignment variable and an outcome variable around a threshold can be spuriously picked up as a kink and result in a biased estimate. In order to investigate how well RK designs handle such confounding nonlinearity, I firstly implement Monte Carlo simulations and then study the effect of fiscal equalization grants on local expenditure using a RK design. Results suggest that RK estimation with a confounding nonlinearity often suffers from bias or imprecision and estimates are credible only when relevant covariates are controlled for.

Suggested Citation

  • Ando, Michihito, 2013. "How Much Should We Trust Regression-Kink-Design Estimates?," Working Paper Series, Center for Fiscal Studies 2013:15, Uppsala University, Department of Economics.
    • Handle: RePEc:hhs:uufswp:2013_015
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    Cited by:

    1. Christofzik, Désirée I. & Schneider, Benny, 2019. "Fiscal policy adjustments to budget shocks: Evidence from German municipalities," Working Papers 10/2019, German Council of Economic Experts / Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung.
    2. Sarah H. Bana & Kelly Bedard & Maya Rossin‐Slater, 2020. "The Impacts of Paid Family Leave Benefits: Regression Kink Evidence from California Administrative Data," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(4), pages 888-929, September.
    3. Michihito Ando, 2017. "How much should we trust regression-kink-design estimates?," Empirical Economics, Springer, vol. 53(3), pages 1287-1322, November.
    4. Tomi Kyyrä & Hanna Pesola, 2020. "The Effects of UI Benefits on Unemployment and Subsequent Outcomes: Evidence from a Kinked Benefit Rule," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(5), pages 1135-1160, October.
    5. Chen, Yi & Zhao, Yi, 2022. "The timing of first marriage and subsequent life outcomes: Evidence from a natural experiment," Journal of Comparative Economics, Elsevier, vol. 50(3), pages 713-731.
    6. David Card & David S. Lee & Zhuan Pei & Andrea Weber, 2015. "Inference on Causal Effects in a Generalized Regression Kink Design," Econometrica, Econometric Society, vol. 83, pages 2453-2483, November.
    7. Simona Gamba & Niklas Jakobsson & Mikael Svensson, 2022. "The impact of cost-sharing on prescription drug demand: evidence from a double-difference regression kink design," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(9), pages 1591-1599, December.
    8. Damon Jones & Alexander M. Gelber & Daniel W. Sacks & Jae Song, 2017. "Using Kinked Budget Sets to Estimate Extensive Margin Responses: Method and Evidence from the Social Security Earnings Test," Working Papers 2017-034, Human Capital and Economic Opportunity Working Group.
    9. David Card & David S. Lee & Zhuan Pei & Andrea Weber, 2017. "Regression Kink Design: Theory and Practice," Advances in Econometrics, in: Regression Discontinuity Designs, volume 38, pages 341-382, Emerald Group Publishing Limited.
    10. Alexander M. Gelber & Damon Jones & Daniel W. Sacks & Jae Song, 2017. "Using Non-Linear Budget Sets to Estimate Extensive Margin Responses: Method and Evidence from the Social Security Earnings Test," NBER Working Papers 23362, National Bureau of Economic Research, Inc.
    11. Kyyrä, Tomi & Paukkeri, Tuuli, 2018. "Does experience rating reduce sickness and disability claims? Evidence from policy kinks," Journal of Health Economics, Elsevier, vol. 61(C), pages 178-192.
    12. Alexander Gelber & Timothy J. Moore & Alexander Strand, 2017. "The Effect of Disability Insurance Payments on Beneficiaries' Earnings," American Economic Journal: Economic Policy, American Economic Association, vol. 9(3), pages 229-261, August.
    13. Antti Saastamoinen & Mika Kortelainen, 2020. "When Does Money Stick in Education? Evidence from A Kinked Grant Rule," Education Finance and Policy, MIT Press, vol. 15(4), pages 708-735, Fall.
    14. Ganong, Peter & Jäger, Simon, 2014. "A Permutation Test and Estimation Alternatives for the Regression Kink Design," IZA Discussion Papers 8282, Institute of Labor Economics (IZA).
    15. Peter Ganong & Simon Jäger, 2018. "A Permutation Test for the Regression Kink Design," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 494-504, April.
    16. Jaeger, Simon C & Ganong, Peter Nathan, 2014. "A Permutation Test and Estimation Alternatives for the Regression Kink Design," Scholarly Articles 34222894, Harvard University Department of Economics.

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    More about this item

    Keywords

    Regression Kink Design; Endogenous regressors; Intergovernmental grants; Flypaper effect;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • H71 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Taxation, Subsidies, and Revenue
    • H72 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Budget and Expenditures
    • H77 - Public Economics - - State and Local Government; Intergovernmental Relations - - - Intergovernmental Relations; Federalism

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