Weak identification robust tests in an instrumental quantile model

Sung Jae Jun

Journal of Econometrics, 2008, vol. 144, issue 1, 118-138

Abstract: We develop a testing procedure that is robust to identification quality in an instrumental quantile model. In order to reduce the computational burden, a multi-step approach is taken, and a two-step Anderson-Rubin (AR) statistic is considered. We then propose an orthogonal decomposition of the AR statistic, where the null distribution of each component does not depend on the assumption of a full rank of the Jacobian. Power experiments are conducted, and inferences on returns to schooling using the Angrist and Krueger data are considered as an empirical example.

Date: 2008
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Citations: View citations in EconPapers (29)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:144:y:2008:i:1:p:118-138

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