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Functional-Coefficient Spatial Durbin Models with Nonparametric Spatial Weights: An Application to Economic Growth

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  • Mustafa Koroglu

    (Department of Economics and Finance, University of Guelph, Guelph, ON N1G2W1, Canada
    Department of Economics, Süleyman Şah University, Istanbul 34956, Turkey)

  • Yiguo Sun

    (Department of Economics and Finance, University of Guelph, Guelph, ON N1G2W1, Canada)

Abstract

This paper considers a functional-coefficient spatial Durbin model with nonparametric spatial weights. Applying the series approximation method, we estimate the unknown functional coefficients and spatial weighting functions via a nonparametric two-stage least squares (or 2SLS) estimation method. To further improve estimation accuracy, we also construct a second-step estimator of the unknown functional coefficients by a local linear regression approach. Some Monte Carlo simulation results are reported to assess the finite sample performance of our proposed estimators. We then apply the proposed model to re-examine national economic growth by augmenting the conventional Solow economic growth convergence model with unknown spatial interactive structures of the national economy, as well as country-specific Solow parameters, where the spatial weighting functions and Solow parameters are allowed to be a function of geographical distance and the countries’ openness to trade, respectively.

Suggested Citation

  • Mustafa Koroglu & Yiguo Sun, 2016. "Functional-Coefficient Spatial Durbin Models with Nonparametric Spatial Weights: An Application to Economic Growth," Econometrics, MDPI, vol. 4(1), pages 1-16, February.
    • Handle: RePEc:gam:jecnmx:v:4:y:2016:i:1:p:6-:d:63356
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