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Consistent EM algorithm for a spatial autoregressive probit model

Wei Cheng ()
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Wei Cheng: East China University of Science and Technology

Journal of Spatial Econometrics, 2022, vol. 3, issue 1, 1-23

Abstract: 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.

Keywords: Spatial probit model; EM algorithm; Near-epoch dependence; Consistent estimator (search for similar items in EconPapers)
JEL-codes: C13 C51 C63 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s43071-022-00022-x

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