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Posterior Average Effects

Bonhomme, S; Weidner, M; (2021) Posterior Average Effects. Journal of Business and Economic Statistics 10.1080/07350015.2021.1984928. (In press). Green open access

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Abstract

Economists are often interested in estimating averages with respect to distributions of unobservables, such as moments of individual fixed-effects, or average partial effects in discrete choice models. For such quantities, we propose and study posterior average effects (PAE), where the average is computed conditional on the sample, in the spirit of empirical Bayes and shrinkage methods. While the usefulness of shrinkage for prediction is well-understood, a justification of posterior conditioning to estimate population averages is currently lacking. We show that PAE have minimum worst-case specification error under various forms of misspecification of the parametric distribution of unobservables. In addition, we introduce a measure of informativeness of the posterior conditioning, which quantifies the worst-case specification error of PAE relative to parametric model-based estimators. As illustrations, we report PAE estimates of distributions of neighborhood effects in the U.S., and of permanent and transitory components in a model of income dynamics.

Type: Article
Title: Posterior Average Effects
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/07350015.2021.1984928
Publisher version: https://doi.org/10.1080/07350015.2021.1984928
Language: English
Additional information: © 2021 The Authors. Published with license by Taylor & Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way
Keywords: Social Sciences, Science & Technology, Physical Sciences, Economics, Social Sciences, Mathematical Methods, Statistics & Probability, Business & Economics, Mathematical Methods In Social Sciences, Mathematics, Empirical Bayes, Latent variables, Model misspecification, Posterior conditioning, Robustness, Sensitivity analysis, PANEL-DATA, CONSUMPTION INEQUALITY, EARNINGS, DECONVOLUTION, NEIGHBORHOODS, SENSITIVITY, INFERENCE, DYNAMICS, IMPACTS
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics
URI: https://discovery.ucl.ac.uk/id/eprint/10140029
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