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DTSTART:20070311T020000
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DTSTAMP:20260206T110245
DTSTART;TZID=America/Detroit:20260312T103000
DTEND;TZID=America/Detroit:20260312T115000
SUMMARY:Workshop / Seminar:Estimation in linear models with clustered data (joint work with Mikkel Solvsten and Baiyun Jing)
DESCRIPTION:We study linear regression models with clustered data\, high-dimensional controls\, and a complicated structure of exclusion restrictions. We propose a correctly centered internal IV estimator that accommodates a variety of exclusion restrictions and permits within-cluster dependence. The estimator has a simple leave-out interpretation and remains computationally tractable. We derive a central limit theorem for its quadratic form and propose a robust variance estimator. We also develop inference methods that remain valid under weak identification. Our framework extends classical dynamic panel methods to more general clustered settings. An empirical application of a large-scale fiscal intervention in rural Kenya with spatial interference illustrates the approach.
UID:143681-21893640@events.umich.edu
URL:https://events.umich.edu/event/143681
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Econometrics,Economics,seminar
LOCATION:North Quad - 4300
CONTACT:
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