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VERSION:2.0
X-WR-CALNAME;VALUE=TEXT:ResearchStats: Peng Ding
PRODID:-//Harvard events data//EN
BEGIN:VEVENT
UID:event_1122118_0
SUMMARY:ResearchStats: Peng Ding
DESCRIPTION:Title: Treatment Effect HeterogeneityAbstract: Applied researchers are increasingly interested in whether and how treatment effects vary in randomized evaluations, especially variation not explained by observed covariates. We propose a model-free approach for testing for the presence of such unexplained variation. To use this randomization-based approach, we must address the fact that the average treatment effect, generally the object of interest in randomized experiments, actually acts as a nuisance parameter in this setting. We explore potential solutions and advocate for a method that guarantees valid tests in finite samples despite this nuisance. We also show how this method readily extends to testing for heterogeneity beyond a given model, which can be useful for assessing the sufficiency of a given scientific theory. We finally apply our method to the National Head Start Impact Study, a large-scale randomized evaluation of a Federal preschool program, finding that there is indeed significant unexplained treatment effect variation.
LOCATION:Science Center Rm. 705
STATUS:CONFIRMED
DTSTART:20150113T170000Z
DTEND:20150113T180000Z
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END:VCALENDAR