Measuring the Sensitivity of Parameter Estimates to Estimation Moments

Isaiah Andrews, Matthew Gentzkow and Jesse Shapiro

The Quarterly Journal of Economics, 2017, vol. 132, issue 4, 1553-1592

Abstract: We propose a local measure of the relationship between parameter estimates and the moments of the data they depend on. Our measure can be computed at negligible cost even for complex structural models. We argue that reporting this measure can increase the transparency of structural estimates, making it easier for readers to predict the way violations of identifying assumptions would affect the results. When the key assumptions are orthogonality between error terms and excluded instruments, we show that our measure provides a natural extension of the omitted variables bias formula for nonlinear models. We illustrate with applications to published articles in several fields of economics.

JEL-codes: C10 C52 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (176)

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Working Paper: Measuring the Sensitivity of Parameter Estimates to Estimation Moments (2014)
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