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Estimation of Multiequation Cross-Section Models in the Presence of Spatial Autocorrelation

Author

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  • Alexandre Carvalho
  • Daniel da Mata
  • Kenneth M. Chomitz

Abstract

We describe econometric techniques to treat spatial autocorrelation in multiequationcross-section models. The cross-section approaches discussed here are heavily based onthe spatial GMM procedure, proposed by Conley (1999). An extension for fullinformationinstrumental variable models is presented. Monte Carlo simulations areemployed in order to verify some asymptotic properties of the Spatial GMM approach.The simulations suggest that, even in the presence of spatial nonstationarity, the spatialGMM still delivers valid standard errors. Besides, usual t-statistics appear to have astandard normal distribution. An application for estimating labor and wage equationsto study regional growth and development of the Brazilian municipalities, between1991 and 2000, is presented.

Suggested Citation

  • Alexandre Carvalho & Daniel da Mata & Kenneth M. Chomitz, 2005. "Estimation of Multiequation Cross-Section Models in the Presence of Spatial Autocorrelation," Discussion Papers 1111, Instituto de Pesquisa Econômica Aplicada - IPEA.
    • Handle: RePEc:ipe:ipetds:1111
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    Cited by:

    1. Alessandra Faggian & Mark Partridge & Edward J. Malecki, 2017. "Creating an Environment for Economic Growth: Creativity, Entrepreneurship or Human Capital?," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 41(6), pages 997-1009, November.
    2. Alexandre Carvalho & Daniel da Mata & Kenneth M. Chomitz & João Carlos Magalhães, 2005. "Spatial Dynamics of Labor Markets in Brazil," Discussion Papers 1110, Instituto de Pesquisa Econômica Aplicada - IPEA.

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