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Title:Testing the correlated random coefficient model PDF Logo
Authors:Heckman, James J.
Schmierer, Daniel
Urzua, Sergio
Issue Date:2010
Series/Report no.:cemmap working paper CWP10/10
Abstract:The recent literature on instrumental variables (IV) features models in which agents sort into treatment status on the basis of gains from treatment as well as on baselinepretreatment levels. Components of the gains known to the agents and acted on by them may not be known by the observing economist. Such models are called correlated random coefficient models. Sorting on unobserved components of gains complicates the interpretation of what IV estimates. This paper examines testable implications of the hypothesis that agents do not sort into treatment based on gains. In it, we develop new tests to gauge the empirical relevance of the correlated random coefficient model to examine whether the additional complications associated with it are required. We examine the power of the proposed tests. We derive a new representation of the variance of the instrumental variable estimator for the correlated random coefficient model. We apply the methods in this paper to the prototypical empirical problem of estimating the return to schooling and find evidence of sorting into schooling based on unobserved components of games.
Subjects:correlated random coefficient
testing
instrumental variables
power of tests based on IV
JEL:C31
Persistent Identifier of the first edition:doi:10.1920/wp.cem.2010.1010
Document Type:Working Paper
Appears in Collections:cemmap working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies (IFS)

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