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Regression Discontinuity Designs with Clustered Data: Variance and Bandwidth Choice

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  • Bartalotti, Otávio C.
  • Brummet, Quentin O.

Abstract

Regression Discontinuity designs have become popular in empirical studies due to their attractive properties for estimating causal effects under transparent assumptions. Nonetheless, most popular procedures assume i.i.d. data, which is unreasonable in many common applications. To fill this gap, we derive the properties of traditional local polynomial estimators in a fixed-G setting that allows for cluster dependence in the error term. Simulation results demonstrate that accounting for clustering in the data while selecting bandwidths may lead to lower MSE while maintaining proper coverage. We then apply our cluster-robust procedure to an application examining the impact of Low-Income Housing Tax Credits on neighborhood characteristics and low-income housing supply.

Suggested Citation

  • Bartalotti, Otávio C. & Brummet, Quentin O., 2016. "Regression Discontinuity Designs with Clustered Data: Variance and Bandwidth Choice," ISU General Staff Papers 201608010700001001, Iowa State University, Department of Economics.
    • Handle: RePEc:isu:genstf:201608010700001001
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    1. David Card & David S. Lee & Zhuan Pei, 2009. "Quasi-Experimental Identification and Estimation in the Regression Kink Design," Working Papers 1206, Princeton University, Department of Economics, Industrial Relations Section..
    2. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    3. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    4. Baum-Snow, Nathaniel & Marion, Justin, 2009. "The effects of low income housing tax credit developments on neighborhoods," Journal of Public Economics, Elsevier, vol. 93(5-6), pages 654-666, June.
    5. Lee, David S. & Card, David, 2008. "Regression discontinuity inference with specification error," Journal of Econometrics, Elsevier, vol. 142(2), pages 655-674, February.
    6. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, vol. 69(1), pages 201-209, January.
    7. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    8. Guido Imbens & Karthik Kalyanaraman, 2012. "Optimal Bandwidth Choice for the Regression Discontinuity Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 933-959.
    9. Lee, David S., 2008. "Randomized experiments from non-random selection in U.S. House elections," Journal of Econometrics, Elsevier, vol. 142(2), pages 675-697, February.
    10. Bhattacharya, Debopam, 2005. "Asymptotic inference from multi-stage samples," Journal of Econometrics, Elsevier, vol. 126(1), pages 145-171, May.
    11. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs," Econometrica, Econometric Society, vol. 82, pages 2295-2326, November.
    12. Matthew Freedman & Tamara McGavock, 2015. "Low‐Income Housing Development, Poverty Concentration, and Neighborhood Inequality," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 34(4), pages 805-834, September.
    13. David Card & David S. Lee & Zhuan Pei, 2009. "Quasi-Experimental Identification and Estimation in the Regression Kink Design," Working Papers 1206, Princeton University, Department of Economics, Industrial Relations Section..
    14. Moulton, Brent R, 1987. "Diagnostics for Group Effects in Regression Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(2), pages 275-282, April.
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    1. Ari Hyytinen & Jaakko Meriläinen & Tuukka Saarimaa & Otto Toivanen & Janne Tukiainen, 2018. "When does regression discontinuity design work? Evidence from random election outcomes," Quantitative Economics, Econometric Society, vol. 9(2), pages 1019-1051, July.

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