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Consistent EM algorithm for a spatial autoregressive probit model

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  • Wei Cheng

    (East China University of Science and Technology)

Abstract

This paper is concerned with the estimation of spatial autoregressive probit models, which are increasingly used in many empirical settings. Among existing estimators, the EM algorithm for spatial probit models introduced by McMillen (J Reg Sci 32(3):335–348, 1992) is a widely used method, but it lacks proof of consistency. In this paper, we formally show that it is inconsistent by applying the law of large numbers for dependent and non-identically distributed near-epoch dependence (NED) random fields. We provide a modification of the EM algorithm to yield a consistent estimator. Monte Carlo experiments show that in finite samples, our new EM algorithm outperforms McMillen’s EM algorithm, especially for medium to high levels of spatial dependence.

Suggested Citation

  • Wei Cheng, 2022. "Consistent EM algorithm for a spatial autoregressive probit model," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-23, December.
    • Handle: RePEc:spr:jospat:v:3:y:2022:i:1:d:10.1007_s43071-022-00022-x
    DOI: 10.1007/s43071-022-00022-x
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    References listed on IDEAS

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    More about this item

    Keywords

    Spatial probit model; EM algorithm; Near-epoch dependence; Consistent estimator;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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