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Fixed Effects and Random Effects Estimation of Higher-Order Spatial Autoregressive Models with Spatial Autoregressive and Heteroskedastic Disturbances

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  • Harald Badinger
  • Peter Egger

Abstract

This paper develops a unified framework for fixed and random effects estimation of higher-order spatial autoregressive panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error component. We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM) estimation procedure of the spatial autoregressive parameters of the disturbance process and define both a random effects and a fixed effects spatial generalized two-stage least squares estimator for the regression parameters of the model. We prove consistency of the proposed estimators and derive their joint asymptotic distribution, which is robust to heteroskedasticity of unknown form in the idiosyncratic error component. Finally, we derive a robust Hausman-test of the spatial random against the spatial fixed effects model.

Suggested Citation

  • Harald Badinger & Peter Egger, 2014. "Fixed Effects and Random Effects Estimation of Higher-Order Spatial Autoregressive Models with Spatial Autoregressive and Heteroskedastic Disturbances," CESifo Working Paper Series 4847, CESifo.
  • Handle: RePEc:ces:ceswps:_4847
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    2. Baltagi, Badi H. & Pirotte, Alain & Yang, Zhenlin, 2021. "Diagnostic tests for homoskedasticity in spatial cross-sectional or panel models," Journal of Econometrics, Elsevier, vol. 224(2), pages 245-270.
    3. Harald Badinger & Peter Egger, 2016. "Productivity Spillovers Across Countries and Industries: New Evidence From OECD Countries," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(4), pages 501-521, August.
    4. Badi H. Baltagi & Peter H. Egger & Michaela Kesina, 2022. "Bayesian Estimation of Multivariate Panel Probits with Higher-Order Network Interdependence and an Application to Firms' Global Market Participation in Guangdong," CESifo Working Paper Series 9579, CESifo.
    5. Mitze, Timo & Naveed, Amjad & Ahmad, Nisar, 2016. "International, intersectoral, or unobservable? Measuring R&D spillovers under weak and strong cross-sectional dependence," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 259-272.
    6. Badi H. Baltagi & Peter H. Egger & Michaela Kesina, 2018. "Generalized spatial autocorrelation in a panel-probit model with an application to exporting in China," Empirical Economics, Springer, vol. 55(1), pages 193-211, August.
    7. Simon Bösenberg & Peter H. Egger & Valeria Merlo & Georg Wamser, 2018. "Measuring The Interdependence Of Multinational Firms' Foreign Investments," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 1064-1088, April.

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    More about this item

    Keywords

    higher-order spatial dependence; generalized moments estimation; heteroskedasticity; two-stage least squares; asymptotic statistics;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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