- Titel
- Regression Discontinuity Design with Covariates
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:15-qucosa2-879098
- Datum der Einreichung
- 18.04.2023
- Abstract (EN)
- This thesis studies regression discontinuity designs with the use of additional covariates for estimation of the average treatment effect. We prove asymptotic normality of the covariate-adjusted estimator under sufficient regularity conditions. In the case of a high-dimensional setting with a large number of covariates depending on the number of observations, we discuss a Lasso-based selection approach as well as alternatives based on calculated correlation thresholds. We present simulation results on those alternative selection strategies.
- Freie Schlagwörter (EN)
- Regression Discontinuity Design, Covariates, Average Treatment Effect Estimation, Local Polynomial Regression
- Klassifikation (DDC)
- 510
- BetreuerIn Hochschule / Universität
- Jun.-Prof. Dr. Alexander Kreiß
- Den akademischen Grad verleihende / prüfende Institution
- Universität Leipzig, Leipzig
- Version / Begutachtungsstatus
- angenommene Version / Postprint / Autorenversion
- URN Qucosa
- urn:nbn:de:bsz:15-qucosa2-879098
- Veröffentlichungsdatum Qucosa
- 07.11.2023
- Dokumenttyp
- Diplomarbeit
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
CC BY 4.0- Inhaltsverzeichnis
1. Introduction 2. Preliminaries 3. Regression Discontinuity Designs 4. Setup and Notation 5. Computing the Bias 6. Asymptotic Behavior 7. Asymptotic Normality of the Estimator 8. Including Potentially Many Covariates 9. Simulations 10. Conclusion