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Empirical Likelihood for Spatial Autoregressive Models with Spatial Autoregressive Disturbances

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  • Yongsong Qin

    (Guangxi Normal University)

Abstract

The empirical likelihood ratio statistics are constructed for the parameters in spatial autoregressive models with spatial autoregressive disturbances. It is shown that the limiting distributions of the empirical likelihood ratio statistics are chi-squared distributions, which are used to construct confidence regions for the parameters in the models.

Suggested Citation

  • Yongsong Qin, 2021. "Empirical Likelihood for Spatial Autoregressive Models with Spatial Autoregressive Disturbances," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 1-25, February.
  • Handle: RePEc:spr:sankha:v:83:y:2021:i:1:d:10.1007_s13171-019-00166-3
    DOI: 10.1007/s13171-019-00166-3
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    References listed on IDEAS

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    1. Song Chen & Ingrid Van Keilegom, 2009. "A review on empirical likelihood methods for regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(3), pages 415-447, November.
    2. H. Kelejian, Harry & Prucha, Ingmar R., 2001. "On the asymptotic distribution of the Moran I test statistic with applications," Journal of Econometrics, Elsevier, vol. 104(2), pages 219-257, September.
    3. Jin, Fei & Lee, Lung-fei, 2019. "GEL estimation and tests of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 208(2), pages 585-612.
    4. Lung-Fei Lee, 2004. "Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models," Econometrica, Econometric Society, vol. 72(6), pages 1899-1925, November.
    5. Liu, Xiaodong & Lee, Lung-fei & Bollinger, Christopher R., 2010. "An efficient GMM estimator of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 159(2), pages 303-319, December.
    6. Wu, Changbao, 2004. "Weighted empirical likelihood inference," Statistics & Probability Letters, Elsevier, vol. 66(1), pages 67-79, January.
    7. Song Chen & Ingrid Van Keilegom, 2009. "Rejoinder on: A review on empirical likelihood methods for regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(3), pages 468-474, November.
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