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Regression Discontinuity Design with Covariates

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اقرأ أكثر حفظ في قائمتي
  • نوع التسجيلة:
    Electronic Resource
  • معلومة اضافية
    • Publisher Information:
      2023-04-18 2023-11-07
    • Added Details:
      Universität Leipzig
      Kramer, Patrick
    • نبذة مختصرة :
      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.: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
    • الموضوع:
      Regression Discontinuity Design, Covariates, Average Treatment Effect Estimation, Local Polynomial Regression; info:eu-repo/classification/ddc/510; ddc:510; info:eu-repo/semantics/acceptedVersion; doc-type:masterThesis; info:eu-repo/semantics/masterThesis; doc-type:Text
    • Note:
      English
    • Other Numbers:
      SUUSL oai:qucosa:de:qucosa:87909
      urn:nbn:de:bsz:15-qucosa2-879098
      https://ul.qucosa.de/id/qucosa%3A87909
      https://ul.qucosa.de/api/qucosa%3A87909/attachment/ATT-0/
      1409794585
    • Contributing Source:
      STAATS U UNIV
      From OAIster®, provided by the OCLC Cooperative.
    • الرقم المعرف:
      edsoai.on1409794585
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