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GMM estimation of spatial panels with fixed effects and unknown heteroskedasticity

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  • Moscone, F.
  • Tosetti, E.

Abstract

In this paper we consider the estimation of a panel data regression model with spatial autoregressive disturbances, fixed effects and unknown heteroskedasticity. Following the work by Kelejian and Prucha (1999), Lee and Liu (2006a) and others, we adopt the Generalized Method of Moments (GMM) and consider moments as a set of linear quadratic conditions in the disturbances. As in Lee and Liu (2006a), we assume that the inner matrices in the quadratic forms have zero diagonal elements to robustify moments against unknown heteroskedasticity. We derive the asymptotic distribution of the GMM estimator based on such conditions. Hence, we carry out some Monte Carlo experiments to investigate the small sample properties of GMM estimators based on various sets of moment conditions.

Suggested Citation

  • Moscone, F. & Tosetti, E., 2011. "GMM estimation of spatial panels with fixed effects and unknown heteroskedasticity," Regional Science and Urban Economics, Elsevier, vol. 41(5), pages 487-497, September.
    • Handle: RePEc:eee:regeco:v:41:y:2011:i:5:p:487-497
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    References listed on IDEAS

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    Cited by:

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    3. Luis Eduardo Sandoval, 2018. "Socio-economics characteristics and spatial persistence of homicides in Colombia, 2000-2010," Estudios de Economia, University of Chile, Department of Economics, vol. 45(1 Year 20), pages 51-77, June.
    4. Li, Liyao & Yang, Zhenlin, 2020. "Estimation of fixed effects spatial dynamic panel data models with small T and unknown heteroskedasticity," Regional Science and Urban Economics, Elsevier, vol. 81(C).

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    Keywords

    Spatial panels Fixed effects GMM;

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