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Nonparametric regression with spatially dependent data

Author

Listed:
  • Stefano Magrini

    (Department of Economics, University Of Venice C� Foscari)

  • Margherita Gerolimetto

    (University Of Venice C� Foscari)

Abstract

In this paper we present a new procedure for nonparametric regression in case of spatially dependent data. In particular, we extend usual local linear regression (along the lines of Martins-Filho and Yao, 2009) and propose a two-step method where information on spatial dependence is incorporated in the error covariance matrix, estimated nonparametrically. The finite sample performance of our proposed procedure is then shown via Monte Carlo simulations for various data generating processes.

Suggested Citation

  • Stefano Magrini & Margherita Gerolimetto, 2009. "Nonparametric regression with spatially dependent data," Working Papers 2009_20, Department of Economics, University of Venice "Ca' Foscari".
    • Handle: RePEc:ven:wpaper:2009_20
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    Citations

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    Cited by:

    1. Margherita Gerolimetto & Stefano Magrini, 2010. "Convergence analysis as distribution dynamics when data are spatially dependent," Working Papers 2010_12, Department of Economics, University of Venice "Ca' Foscari".
    2. Hasan Engin Duran, 2011. "Short run dynamics of income disparities and regional cycle synchronization," ERSA conference papers ersa11p937, European Regional Science Association.
    3. Paul Evans & Ji Uk Kim, 2016. "Convergence analysis as spatial dynamic panel regression and distribution dynamics of $$\hbox {CO}_{2}$$ CO 2 emissions in Asian countries," Empirical Economics, Springer, vol. 50(3), pages 729-751, May.
    4. Eduardo A. Souza-Rodrigues, 2016. "Nonparametric Regression with Common Shocks," Econometrics, MDPI, vol. 4(3), pages 1-17, September.

    More about this item

    Keywords

    nonparametric smoothing; spatial dependence;

    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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