Empirical Likelihood for Mixed Regressive, Spatial Autoregressive Model Based on GMM

Yongsong Qin () and Qingzhu Lei ()
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Yongsong Qin: Guangxi Normal University
Qingzhu Lei: Guangxi Normal University

Sankhya A: The Indian Journal of Statistics, 2021, vol. 83, issue 1, No 14, 353-378

Abstract: Abstract For the parameters in a mixed regressive, spatial autoregressive (MRSAR) model, it is shown, in this article, that for every generalized method of moments (GMM) estimator, there is an empirical likelihood (EL) estimator which has the same asymptotic variance as the GMM estimator. Specifically, we show that there exists an EL estimator which is asymptotically efficient as the best GMM estimator and the EL confidence region for the parameters in the MRSAR model is constructed without estimating the asymptotic variance.

Keywords: Confidence region; Empirical likelihood; GMM; Mixed regressive; Spatial autoregressive model; Primary 62G05; Secondary 62E20 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s13171-019-00190-3

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