One or two-step? Evaluating GMM efficiency for spatial binary probit models

Gianfranco Piras and Mauricio Sarrias

Journal of choice modelling, 2023, vol. 48, issue C

Abstract: In this article we propose two-step generalized method of moment (GMM) procedure for a Spatial Binary Probit Model. In particular, we propose a series of two-step estimators based on different choices of the weighting matrix for the moments conditions in the first step, and different estimators for the variance–covariance matrix of the estimated coefficients. In the context of a Monte Carlo experiment, we compare the properties of these estimators, a linearized version of the one-step GMM and the recursive importance sampler (RIS). Our findings reveal that there are benefits related both to the choice of the weight matrix for the moment conditions and in adopting a two-step procedure.

Keywords: Spatial dependence; Probit model; Generalized moment estimation; Efficiency (search for similar items in EconPapers)
JEL-codes: C21 C31 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eejocm:v:48:y:2023:i:c:s1755534523000337

DOI: 10.1016/j.jocm.2023.100432

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