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Jumpy or Kinky? Regression Discontinuity without the Discontinuity

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  • Yingying Dong

    (Department of Economics, University of California-Irvine)

Abstract

Regression Discontinuity (RD) models identify local treatment effects by associating a discrete change in the mean outcome with a corresponding discrete change in the probability of treatment at a known threshold of a running variable. This paper shows that it is possible to identify the RD model treatment effect without a discontinuity. In particular, identification can come from a slope change (a kink) instead of a discrete level change (a jump) in the treatment probability. The intuition is based on L'hopital's rule. The identification results can also be interpreted using instrumental variables models. Estimators are proposed that can be applied in the presence or absence of a discontinuity, by exploiting either a jump, or a kink, or both. The proposed estimators are applied to investigate the "retirement-consumption puzzle." In particular, I estimate the impact of retirement on household food consumption by exploiting changes in the retirement probability at 62, the early retirement age in the US.

Suggested Citation

  • Yingying Dong, 2011. "Jumpy or Kinky? Regression Discontinuity without the Discontinuity," Working Papers 111207, University of California-Irvine, Department of Economics.
  • Handle: RePEc:irv:wpaper:111207
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Richard Murphy & Gill Wyness, 2023. "Testing Means-Tested Aid," Journal of Labor Economics, University of Chicago Press, vol. 41(3), pages 687-727.
    2. Engels, Barbara & Geyer, Johannes & Haan, Peter, 2017. "Pension incentives and early retirement," Labour Economics, Elsevier, vol. 47(C), pages 216-231.
    3. Yingying Dong, 2012. "Regression Discontinuity Applications with Rounding Errors in the Running Variable," Working Papers 111206, University of California-Irvine, Department of Economics.
    4. Fe, Eduardo & Hollingsworth, Bruce, 2012. "Estimating the eect of retirement on mental health via panel discontinuity designs," MPRA Paper 38162, University Library of Munich, Germany.
    5. Hansen, Benjamin & Nguyen, Tuan & Waddell, Glen R., 2017. "Benefit Generosity and Injury Duration: Quasi-Experimental Evidence from Regression Kinks," IZA Discussion Papers 10621, Institute of Labor Economics (IZA).
    6. Camille Landais, 2015. "Assessing the Welfare Effects of Unemployment Benefits Using the Regression Kink Design," American Economic Journal: Economic Policy, American Economic Association, vol. 7(4), pages 243-278, November.
    7. Zhongjun Qu & Jungmo Yoon, 2019. "Uniform Inference on Quantile Effects under Sharp Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 625-647, October.
    8. Jan Fidrmuc & J. D. Tena, 2013. "National Minimum Wage and Employment of Young Workers in the UK," CESifo Working Paper Series 4286, CESifo.
    9. Martin González-Rozada & Hernan Ruffo, 2022. "The welfare effects of unemployment insurance in Argentina. New estimates using changes in the schedule of transfers," Department of Economics Working Papers 2022_01, Universidad Torcuato Di Tella.
    10. Rhys Llewellyn Thomas & Emmanouil Mentzakis, 2024. "The direct and spillover effects of diabetes diagnosis on lifestyle behaviours," Health Economics, John Wiley & Sons, Ltd., vol. 33(5), pages 952-970, May.
    11. 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).
    12. 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.
    13. Sebastian Garmann, 2014. "The causal effect of coalition governments on fiscal policies: evidence from a Regression Kink Design," Applied Economics, Taylor & Francis Journals, vol. 46(36), pages 4490-4507, December.
    14. Yingying Dong & Arthur Lewbel, 2011. "Regression Discontinuity Marginal Threshold Treatment Effects," Working Papers 111205, University of California-Irvine, Department of Economics.

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    More about this item

    Keywords

    Regression discontinuity; Fuzzy design; Local average treatment effect; Identification; Jump; Kink; Threshold; Retirement; Consumption;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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