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Estimating Nonlinearities in Spatial Autoregressive Models

Author

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  • Nicolas Debarsy

    (CERPE - Centre de Recherches en Economie Régionale et Politique Economique - FUNDP - Facultés Universitaires Notre Dame de la Paix)

  • Vincenzo Verardi

    (ECARES - European Center for Advanced Research in Economics and Statistics - ULB - Université libre de Bruxelles, CRED - Centre de Recherche en Economie du Développement - FUNDP - Facultés Universitaires Notre Dame de la Paix)

Abstract

In spatial autoregressive models, the functional form of autocorrelation is assumed to be linear. In this paper, we propose a simple semiparametric procedure, based on Yatchew's (1998) partial linear least squares, that relaxes this restriction. Simple simulations show that this model outperforms traditional SAR estimation when nonlinearities are present. We then apply the methodology on real data to test for the spatial pattern of voting for independent candidates in US presidential elections. We find that in some counties, votes for "third candidates" are non-linearly related to votes for "third candidates" in neighboring counties, which pleads for strategic behavior.

Suggested Citation

  • Nicolas Debarsy & Vincenzo Verardi, 2010. "Estimating Nonlinearities in Spatial Autoregressive Models," Working Papers halshs-00446574, HAL.
    • Handle: RePEc:hal:wpaper:halshs-00446574
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00446574
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    References listed on IDEAS

    as
    1. Whitney K. Newey & James L. Powell & Francis Vella, 1999. "Nonparametric Estimation of Triangular Simultaneous Equations Models," Econometrica, Econometric Society, vol. 67(3), pages 565-604, May.
    2. Enno Mammen, "undated". "Comparing nonparametric versus parametric regression fits," Statistic und Oekonometrie 9205, Humboldt Universitaet Berlin.
    3. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    4. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    5. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    6. Adonis Yatchew, 1998. "Nonparametric Regression Techniques in Economics," Journal of Economic Literature, American Economic Association, vol. 36(2), pages 669-721, June.
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    More about this item

    Keywords

    Spatial econometrics; semiparametric estimations;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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