Title: Testing for causal e ffects in a generalized regression model with endogenous regressors
Abstract: A unifying framework to test for causal effects in non-linear models is proposed. We consider a generalized linear-index regression model with endogenous regressors and no parametric assumptions on the error disturbances. To test the significance of the effect of an endogenous regressor, we propose a test statistic that is a kernel-weighted version of the rank correlation statistic (tau) of Kendall(1938). The semiparametric model encompasses previous cases considered in the literature (continuous endogenous regressors (Blundell and Powell(2003)) and a single binary endogenous regressor (Vytlacil and Yildiz(2007)), but the testing approach is the first to allow for (i)multiple discrete endogenous regressors, (ii)endogenous regressors that are neither discrete nor continuous (e.g., a censored variable), and (iii)an arbitrary “mix” of endogenous regressors (e.g., one binary regressor and one continuous regressor). JEL Classification: C14, C25, C13.
Publication Year: 2010
Publication Date: 2010-12-01
Language: en
Type: article
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Cited By Count: 14
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