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xsmle: A Stata command for spatial panel-data models estimation

Author

Listed:
  • Federico Belotti

    (University of Rome "Tor Vergata")

  • Gordon Hughes

    (University of Edinburgh)

  • Andrea Piano Mortari

    (University of Rome "Tor Vergata")

Abstract

Econometricians have begun to devote more attention to spatial interactions when carrying out applied econometric studies. The new command we are presenting, xsmle, fits fixed- and random-effects spatial models for balanced panel data for a wide range of specifications: the spatial autoregressive model, spatial error model, spatial Durbin model, spatial autoregressive model with autoregressive disturbances, and generalized spatial random effect model with or without a dynamic component. Different weighting matrices may be specified for different components of the models and both Stata matrices and spmat objects are allowed. Furthermore, xsmle calculates direct, indirect, and total effects according to Lesage (2008), implements Lee and Yu (2010) data transformation for fixed-effects models, and may be used with mi prefix when the panel is unbalanced.

Suggested Citation

  • Federico Belotti & Gordon Hughes & Andrea Piano Mortari, 2013. "xsmle: A Stata command for spatial panel-data models estimation," German Stata Users' Group Meetings 2013 09, Stata Users Group.
    • Handle: RePEc:boc:dsug13:09
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    References listed on IDEAS

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    1. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2008. "Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large," Journal of Econometrics, Elsevier, vol. 146(1), pages 118-134, September.
    2. Lee, Lung-Fei, 2002. "Consistency And Efficiency Of Least Squares Estimation For Mixed Regressive, Spatial Autoregressive Models," Econometric Theory, Cambridge University Press, vol. 18(2), pages 252-277, April.
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