Sequential Estimation Of Structural Models With A Fixed Point Constraint

Hiroyuki Kasahara and Katsumi Shimotsu

No 1192, Working Paper from Economics Department, Queen's University

Abstract: 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 the conditions under which the nested pseudo-likelihood (NPL) algorithm achieves convergence and derive its convergence rate. We find that the NPL algorithm may not necessarily converge when the fixed point mapping does not have a local contraction property. To address the issue of non-convergence, we propose alternative sequential estimation procedures that can achieve convergence even when the NPL algorithm does not. Upon convergence, some of our proposed estimation algorithms produce more efficient estimators than the NPL estimator.

Keywords: contraction; dynamic games; nested pseudo likelihood; recursive projection method (search for similar items in EconPapers)
JEL-codes: C13 C14 C63 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2008-12
New Economics Papers: this item is included in nep-dcm and nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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https://www.econ.queensu.ca/sites/econ.queensu.ca/files/qed_wp_1192.pdf First version 2008 (application/pdf)

Related works:
Journal Article: Sequential Estimation of Structural Models With a Fixed Point Constraint (2012)
Working Paper: Sequential Estimation of Structural Models with a Fixed Point Constraint (2009)
Working Paper: Sequential Estimation of Structural Models with a Fixed Point Constraint (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:qed:wpaper:1192

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