Weak Instrument Bias in Impulse Response Estimators
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Series
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SpeakersDaniel Lewis (University College London, United Kingdom)
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FieldEconometrics, Data Science and Econometrics
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LocationTinbergen Institute Amsterdam, Roeterseiland campus, E5.07
Amsterdam -
Date and time
April 08, 2026
12:55 - 13:55
Abstract
We approximate the finite-sample distribution of impulse response function (IRF) estimators that are just-identified with a weak instrument using the conventional local-to-zero asymptotic framework. Since the distribution lacks a mean, we assess bias using the mode and conclude that researchers prioritizing robustness against weak instrument bias should favour vector autoregressions (VARs) over local projections (LPs). Existing testing procedures are ill-suited for assessing weak instrument bias in IRF estimates, and we propose a novel simple test based on the usual first-stage F-statistic. We investigate instrument strength in several applications from the literature, and discuss to what extent structural parameters must be restricted ex-ante to reject meaningful bias due to weak identification. Joint paper with Karel Mertens.