Economics Research Seminar Series: Tim Neal, UNSW

Research topic: p-Hacking Instrument Selection 

Tim Neil, University of New South Wales 

Topic

p-Hacking Instrument Selection 

abstract

Recent evidence suggests that p-hacking is particularly common in IV research. This article posits that selection across multiple available instruments is a likely cause of this. We study the properties of the 2SLS/GMM estimator when researchers select among multiple instruments to minimize the p-value in either the first or second stage. Due to the mechanical correlation between the coefficients and standard error across samples in 2SLS/GMM, i.e. the power asymmetry problem first outlined in Keane and Neal (2023), p-hacking either stage severely exacerbates both size and median bias towards OLS. We show that the use of robust tests such as the Anderson-Rubin and Conditional Likelihood tests can somewhat alleviate these problems when p-hacking the second stage of the regression, but does not alleviate the problems associated with p-hacking the first stage of the regression. Implications for applied research in IV will be extensively discussed throughout.

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