Journal Of The Econometric Society

An International Society for the Advancement of Economic
Theory in its Relation to Statistics and Mathematics

Edited by: Guido W. Imbens • Print ISSN: 0012-9682 • Online ISSN: 1468-0262

Econometrica: May, 2023, Volume 91, Issue 3

A Sieve-SMM Estimator for Dynamic Models
p. 943-977

Jean‐Jacques Forneron

This paper proposes a Sieve Simulated Method of Moments (Sieve‐SMM) estimator for the parameters and the distribution of the shocks in nonlinear dynamic models where the likelihood and the moments are not tractable. An important concern with SMM, which matches sample with simulated moments, is that a parametric distribution is required. However, economic quantities that depend on this distribution, such as welfare and asset prices, can be sensitive to misspecification. The Sieve‐SMM estimator addresses this issue by flexibly approximating the distribution of the shocks with a Gaussian and tails mixture sieve. The asymptotic framework provides consistency, rate of convergence, and asymptotic normality results, extending existing results to a new framework with more general dynamics and latent variables. An application to asset pricing in a production economy shows a large decline in the estimates of relative risk aversion, highlighting the empirical relevance of misspecification bias.

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Supplemental Material

Supplement to "A Sieve-SMM Estimator for Dynamic Models"

Jean-Jacques Forneron

This zip file contains the replication files for the manuscript.

Supplement to "A Sieve-SMM Estimator for Dynamic Models"

Jean-Jacques Forneron

This Supplemental Material consists of Appendices C, D, E, F and G to the main text.

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