Equilibrium Counterfactuals: Joint Estimation and Control in Structural Models
Chemla, Gilles; Hennessy, Christopher A. (2018), Equilibrium Counterfactuals: Joint Estimation and Control in Structural Models, University of Minnesota Finance Department Guest Seminar - Fall 2018, 2018-10, Minneapolis, United States
Type
Communication / ConférenceDate
2018Conference title
University of Minnesota Finance Department Guest Seminar - Fall 2018Conference date
2018-10Conference city
MinneapolisConference country
United StatesMetadata
Show full item recordAuthor(s)
Chemla, GillesDauphine Recherches en Management [DRM]
Hennessy, Christopher A.
London Business School
Abstract (EN)
The objective of applied structural microeconometrics is to identify policy-invariant parameters so alternative policies can be assessed. As we show, the practice of treating policy changes as zero probability "counterfactuals" violates rational expectations: Agents inside the model understand policy changes are positive probability events which the structural estimation isintended to inform. We analytically characterize the implications for moment-based parameter inference. As shown, if a policy change is optimal, inference is biased. Further, the standard identifying assumption, constant partial derivative sign, is neither necessary nor sufficient with policy control. We offer an alternative identifying assumption: constant total differential sign with inference-policy feedback. It is shown that under this assumption, rational expectations can be imposed computationally (algorithmically) to generate unbiased inference and optimal policy.The quantitative importance of these effects in applied settings is illustrated by calibrating theLeland (1994) model to the Tax Cuts and Jobs Act of 2017.Subjects / Keywords
structural models; moments; policy; bias; algorithmRelated items
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