The Econometric SocietyEdited by: Guido W. Imbens • Print ISSN: 0012-9682 • Online ISSN: 1468-0262
August 15, 2022
Econometrica: Sep, 2012, Volume 80, Issue 5
https://doi.org/10.3982/ECTA8291
p. 2303-2319
Hiroyuki Kasahara, Katsumi Shimotsu
This paper considers the estimation problem of structural models for which empirical restrictions are characterized by a fixed point constraint, such as structural dynamic discrete choice models or models of dynamic games. We analyze a local condition under which the nested pseudo likelihood (NPL) algorithm converges to a consistent estimator, and derive its convergence rate. We find that the NPL algorithm may not necessarily converge to a consistent estimator when the fixed point mapping does not have a local contraction property. To address the issue of divergence, we propose alternative sequential estimation procedures that can converge to a consistent estimator even when the NPL algorithm does not.
This zip file contains the replication files for the manuscript.
This supplement contains the following details omitted from the main paper due to space constraints: (A) proof of the results in the paper, (B) auxiliary results and their proof, (C) additional alternative sequential algorithms, (D) the convergence properties of the NPL algorithm for models with unobserved heterogeneity, and (E) additional Monte Carlo results.
