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.

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

Piras, G;
2023-01-01

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/817651
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