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Consistency of a method of moments estimator based on numerical solutions to asset pricing models

Burnside, C. (1993) Consistency of a method of moments estimator based on numerical solutions to asset pricing models. Econometric Theory, 9 (4). pp. 602-632. ISSN 0266-4666 (doi:10.1017/S0266466600008008)

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Publisher's URL: http://dx.doi.org/10.1017/S0266466600008008

Abstract

This paper considers the properties of estimators based on numerical solutions to a class of economic models. In particular, the numerical methods discussed are those applied in the solution of linear integral equations, specifically Fredholm equations of the second kind. These integral equations arise out of economic models in which endogenous variables appear linearly in the Euler equations, but for which easily characterized solutions do not exist. Tauchen and Hussey [24] have proposed the use of these methods in the solution of the consumption-based asset pricing model. In this paper, these methods are used to construct method of moments estimators where the population moments implied by a model are approximated by the population moments of numerical solutions. These estimators are shown to be consistent if the accuracy of the approximation is increased with the sample size. This result depends on the solution method having the property that the moments of the approximate solutions converge uniformly in the model parameters to the moments of the true solutions.

Item Type:Article
Status:Published
Refereed:Yes
Glasgow Author(s):Burnside, Prof Craig
Authors: Burnside, C.
Subjects:H Social Sciences > HA Statistics
College/School:College of Social Sciences > Adam Smith Business School > Economics
Journal Name:Econometric Theory
Publisher:Cambridge University Press
ISSN:0266-4666
ISSN (Online):1469-4360
Published Online:11 February 2009
Copyright Holders:Copyright © 1993 Cambridge University Press
First Published:First published in Econometric Theory 9(4):602-632
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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