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Weak identification robust tests in an instrumental quantile model

  • Jun, Sung Jae

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.

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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 144 (2008)
Issue (Month): 1 (May)
Pages: 118-138

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Handle: RePEc:eee:econom:v:144:y:2008:i:1:p:118-138
Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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