Testing for selectivity bias in panel data models
AbstractThe authors discuss several tests to check for the presence of selectivity bias in estimators based on panel data. One approach to test for selectivity bias is to specify the selection mechanism explicitly and estimate it jointly with the model of interest. Alternatively, one can derive the asymptotically efficient Lagrange multiplier test. Both approaches are computationally demanding. In this paper, the authors propose the use of simple variable addition and (quasi-) Hausman tests for selectivity bias that do not require any knowledge of the response process. They compare the power of these tests with the asymptotically efficient test using Monte Carlo methods. Copyright 1992 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.
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Bibliographic InfoPaper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 1990-18.
Date of creation: 1990
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Estimation; Panel Data;
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