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
TypeCommunication / Conférence
Conference titleUniversity of Minnesota Finance Department Guest Seminar - Fall 2018
Conference countryUnited States
MetadataShow full item record
Dauphine 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 / Keywordsstructural models; moments; policy; bias; algorithm
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