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Regression Discontinuity Design with Endogenous Covariates

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Empirical researchers often include observed covariates in theWaldtype implementation of Regression Discontinuity Design (RDD) estimators. When those included covariates are endogenous, we find that the resulting RDD estimator suffers from a larger asymptotic bias than the estimator with exogenous covariates but it is still consistent. We further show that the order of bias increase due to the endogeneity is the same order of bias reduction due to the inclusion of relevant endogenous covariates.

Abstract

1. INTRODUCTION

2. RDD WITH ENDOGENOUS COVARIATES

3. ESTIMATION AND ASYMPTOTIC BIAS

4. CONCLUSION

APPENDIX

REFERENCES

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