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Asymptotic Distribution and Finite-Sample Bias Correction of QML Estimators for Spatial Error Dependence Model

Author

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  • Shew Fan Liu

    (School of Economics, Singapore Management University, Singapore, 178903)

  • Zhenlin Yang

    (School of Economics, Singapore Management University, Singapore, 178903)

Abstract
In studying the asymptotic and finite-sample properties of quasi-maximum likelihood (QML) estimators for the spatial linear regression models, much attention has been paid to the spatial lag dependence (SLD) model; little has been given to its companion, the spatial error dependence (SED) model. In particular, the effect of spatial dependence on the convergence rate of the QML estimators has not been formally studied, and methods for correcting finite-sample bias of the QML estimators have not been given. This paper fills in these gaps. Of the two, bias correction is particularly important to the application of this model. Contrary to the common perceptions, both the large and small sample behaviors of the QML estimators for the SED model can be different from those for the SLD model in terms of the rate of convergence and the magnitude of bias. Monte Carlo results show that the bias can be severe and the proposed bias correction procedure is very effective.

Suggested Citation

  • Shew Fan Liu & Zhenlin Yang, 2014. "Asymptotic Distribution and Finite-Sample Bias Correction of QML Estimators for Spatial Error Dependence Model," Working Papers 15-2014, Singapore Management University, School of Economics.
    • Handle: RePEc:siu:wpaper:15-2014
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    References listed on IDEAS

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    4. Christoph Strumann, 2019. "Hodges–Lehmann Estimation of Static Panel Models with Spatially Correlated Disturbances," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 141-168, January.
    5. Wongsa-art, Pipat & Kim, Namhyun & Xia, Yingcun & Moscone, Francesco, 2024. "Varying coefficient panel data models and methods under correlated error components: Application to disparities in mental health services in England," Regional Science and Urban Economics, Elsevier, vol. 106(C).
    6. W. Saart, Patrick & Kim, Namhyun & Bateman, Ian, 2021. "Modeling and predicting agricultural land use in England based on spatially high-resolution data," Cardiff Economics Working Papers E2021/7, Cardiff University, Cardiff Business School, Economics Section.
    7. Liu, Shew Fan & Yang, Zhenlin, 2015. "Improved inferences for spatial regression models," Regional Science and Urban Economics, Elsevier, vol. 55(C), pages 55-67.

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    More about this item

    Keywords

    Asymptotics; Bias Correction; Bootstrap; Concentrated estimating equation; Monte Carlo; Spatial layout; Stochastic expansion;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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