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Simultaneous equation models with spatially autocorrelated error components

Author

Listed:
  • AMBA OYON, Claude Marius
  • Mbratana, Taoufiki
Abstract
This paper develops estimators for simultaneous equations with spatial autoregressive or spatial moving average error components. We derive a limited information estimator and a full information estimator. We give the generalized method of moments to get each coefficient of the spatial dependence of each equation in spatial autoregressive case as well as spatial moving average case. The results of our Monte Carlo suggest that our estimators are consistent. When we estimate the coefficient of spatial dependence it seems better to use instrumental variables estimator that takes into account simultaneity. We also apply these set of estimators on real data.

Suggested Citation

  • AMBA OYON, Claude Marius & Mbratana, Taoufiki, 2017. "Simultaneous equation models with spatially autocorrelated error components," MPRA Paper 82395, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:82395
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    File URL: https://mpra.ub.uni-muenchen.de/82395/1/MPRA_paper_82395.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    Panel data; SAR process; SMA process; Simultaneous equations; Spatial error components;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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