The method of simulated scores for the estimation of LDV models

Hajivassiliou, Vassilis ORCID: 0009-0000-7041-0791 and McFadden, Daniel (1998) The method of simulated scores for the estimation of LDV models. Econometrica, 66 (4). pp. 863-896. ISSN 0012-9682

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Abstract

The method of simulated scores (MSS) is presented for estimating limited dependent variables models (LDV) with flexible correlation structure in the unobservables. We propose simulators that are continuous in the unknown parameter vectors, and hence standard optimization methods can be used to compute the MSS estimators that employ these simulators. The first continuous method relies on a recursive conditioning of the multivariate normal density through a Cholesky triangularization of its variance-covariance matrix. The second method combines results about the conditionals of the multivariate normal distribution with Gibbs resampling techniques. We establish consistency and asymptotic normality of the MSS estimators and derive suitable rates at which the number of simulations must rise if biased simulators are used.

Item Type:	Article
Official URL:	http://eu.wiley.com/WileyCDA/WileyTitle/productCd-...
Additional Information:	© 1998 The Econometric Society
Divisions:	Economics
Subjects:	H Social Sciences > HB Economic Theory
JEL classification:	C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C13 - Estimation C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C15 - Statistical Simulation Methods; Monte Carlo Methods; Bootstrap Methods
Date Deposited:	27 Mar 2008 16:40
Last Modified:	18 Nov 2024 01:51
URI:	http://eprints.lse.ac.uk/id/eprint/3921

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