BEGIN:VCALENDAR
PRODID:-//Columba Systems Ltd//NONSGML CPNG/SpringViewer/ICal Output/3.3-
 M3//EN
VERSION:2.0
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20240222T143506Z
DTSTART:20240226T120000Z
DTEND:20240226T130000Z
SUMMARY:Econometrics Seminar - Claudia Noack (University of Bonn)
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}m2wk-lsvxdm
 yf-cu8xp9
DESCRIPTION:Title: Flexible Covariate Adjustments in Regression Discontin
 uity Designs\n\njoint with Christoph Rothe and Tomasz Olma\n\nAbstract:\
 nEmpirical regression discontinuity (RD) studies often use covariates to
  increase the precision of their estimates. In this paper\, we propose a
  novel class of estimators that use such covariate information more effi
 ciently than the linear adjustment estimators that are currently used wi
 dely in practice. Our approach can accommodate a possibly large number o
 f either discrete or continuous covariates. It involves running a standa
 rd RD analysis with an appropriately modified outcome variable\, which t
 akes the form of the difference between the original outcome and a funct
 ion of the covariates. We characterize the function that leads to the es
 timator with the smallest asymptotic variance\, and show how it can be e
 stimated via modern machine learning\, nonparametric regression\, or cla
 ssical parametric methods. The resulting estimator is easy to implement\
 , as tuning parameters can be chosen as ina conventional RD analysis. An
  extensive simulation study illustrates the performance of our approach.
 \n
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:ALB Boardroom\, Arthur Lewis Building\, Manchester
END:VEVENT
END:VCALENDAR