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BEGIN:VEVENT
DTSTAMP:20260427T225312Z
DTSTART;VALUE=DATE-TIME:20251201T140000
DTEND;VALUE=DATE-TIME:20251201T153000
SUMMARY:Econometrics Seminar - Ben Deaner (UCL)
TZID:Europe/London
UID:20251201-8ac672c5990a699f01990fd6b56c5f48@warwick.ac.uk
CREATED:20251124T093307Z
DESCRIPTION:Title: Identification Using Internal Instruments in Large N a
 nd T Panel Models (joint with Andrei Zeleneev). This is preliminary work
  so we do not yet have a complete paper\, here is an abstract . Abstract
  - In order to identify causal effects using panel data\, researchers ma
 y exploit the presence of external instruments in the form of aggregate 
 shocks which vary over time but not between individuals\, e.g.\, policy 
 shocks or cost shocks. By construction\, these shocks are uncorrelated w
 ith any idiosyncratic variation in confounding factors\, and they are un
 correlated with aggregate confounding factors if they satisfy an exclusi
 on restriction. In this work we show that with large N and T panel data\
 , causal effects can be identified and estimated when such exogenous sho
 cks exist\, even if they are not directly observed. Our identification a
 pproach can be summarized as follows. First\, we propose that one form a
  vector of candidate (i.e.\, possibly endogenous) instruments by extract
 ing period-specific factors from the matrix of outcomes and treatments. 
 Second\, we show that with large and panel data\, given a vector of cand
 idate instruments\, one can identify causal effects so long as there exi
 sts some (unknown) linear combination of these candidate instruments tha
 t is exogenous. We propose an estimator whose form is motivated by our i
 dentification results and we provide some simulation evidence of its eff
 icacy.
LOCATION:S2.79
CATEGORIES:Econometrics Seminar
LAST-MODIFIED:20251124T093307Z
ORGANIZER;CN=Gill Gudger:
END:VEVENT
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