BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//UM//UM*Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/Detroit
TZURL:http://tzurl.org/zoneinfo/America/Detroit
X-LIC-LOCATION:America/Detroit
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20070311T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20071104T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260401T090119
DTSTART;TZID=America/Detroit:20260409T103000
DTEND;TZID=America/Detroit:20260409T115000
SUMMARY:Workshop / Seminar:Improved Inference for Nonparametric Regression (joint with G.Cavaliere\, M. Nielsen\, and E. Zanelli)
DESCRIPTION:Nonparametric regression estimators\, including those employed in regression-discontinuity designs (RDD)\, are central to the economist’s toolbox. Their application\, however\, is complicated by the presence of asymptotic bias\, which undermines coverage accuracy of conventional confidence intervals. Extant solutions to the problem include debiasing methods\, such as the widely applied robust bias-corrected (RBC) confidence interval of Calonico et al. (2014\, 2018). We show that this interval is equivalent to a prepivoted interval based on an invalid residualbased bootstrap method. Specifically\, prepivoting performs an implicit bias correction while adjusting the nonparametric regression estimator’s standard error to account for the additional uncertainty introduced by debiasing. This idea can also be applied to other bootstrap schemes\, leading to new implicit bias corrections and corresponding standard error adjustments. We propose a prepivoted interval based on a bootstrap that generates observations from nonparametric regression estimates at each regressor value and show how it can be implemented as an RBCtype interval without the need for resampling. Importantly\, we show that the new interval is shorter than the existing RBC interval. For example\, with the Epanechnikov kernel\, the length is reduced by 17%\, while maintaining accurate coverage probability. This result holds irrespectively of: (a) the evaluation point being in the interior or on the boundary\; (b) the use of a ‘small’ or ‘large’ bandwidths\; (c) the distribution of the regressor and the error term.
UID:143683-21893642@events.umich.edu
URL:https://events.umich.edu/event/143683
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Econometrics,Economics,seminar
LOCATION:North Quad - 4300
CONTACT:
END:VEVENT
END:VCALENDAR