SMU SOE Seminar (Apr 12, 2019, 2-3.30pm): A more powerful subvector Anderson Rubin test in linear instrumental variables regression

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ABSTRACT We study subvector inference in the linear instrumental variables model assuming homoskedasticity but allowing for weak instruments. The subvector Anderson and Ru-bin (1949) test that uses chi square critical values with degrees of freedom reduced by the number of parameters not under test, proposed by Guggenberger et al. (2012), controls size but is generally conservative. We propose a conditional subvector Anderson and Rubin test that uses data-dependent critical values that adapt to the strength of identiﬁcation of the parameters not under test. This test has correct size and strictly higher power than the subvector Anderson and Rubin test by Guggenberger et al. (2012). We provide tables with conditional critical values so that the new test is quick and easy to use. Application of our method to a model of risk preferences in development economics shows that it can strengthen empirical conclusions in practice. Keywords: Asymptotic size, Linear IV regression, Subvector inference, Weak instruments. JEL Codes: C12, C26. Click here to view the paper. Click here to view the CV.
		PRESENTER Patrik Guggenberger Pennsylvania State University
		RESEARCH FIELDS Econometrics
		DATE: 12 April 2019 (Friday)
		TIME: 2pm - 3.30pm
		VENUE: Meeting Room 5.1, Level 5 School of Economics Singapore Management University 90 Stamford Road Singapore 178903