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

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  • Piras, Gianfranco
  • Sarrias, Mauricio

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.

Suggested Citation

  • Piras, Gianfranco & Sarrias, Mauricio, 2023. "One or two-step? Evaluating GMM efficiency for spatial binary probit models," Journal of choice modelling, Elsevier, vol. 48(C).
    • Handle: RePEc:eee:eejocm:v:48:y:2023:i:c:s1755534523000337
    DOI: 10.1016/j.jocm.2023.100432
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    Cited by:

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    2. de Grange, Louis & González, Felipe & Marechal, Matthieu & Troncoso, Rodrigo, 2024. "A consistent moment equations for binary probit models with endogenous variables using instrumental variables," Journal of choice modelling, Elsevier, vol. 53(C).

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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