Weak identification robust tests in an instrumental quantile model

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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.

Original languageEnglish (US)
Pages (from-to)118-138
Number of pages21
JournalJournal of Econometrics
Volume144
Issue number1
DOIs
StatePublished - May 1 2008

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

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