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Bayesian estimation of spatial externalities using regional production function: the case of China and Japan

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  • Yoshihiro Hashiguchi

    ()
    (Kobe University)

Abstract

This paper used regional panel data for Chinese provinces from 1979 to 2003, and for Japanese prefectures from 1955 to 1998, to estimate the spatial externalities (or spatial multiplier effects) using a production function and Bayesian methodology, and to investigate the long-run behavior of the spatial externalities of each country. According to the estimation results, China's spatial externalities increased its domestic production significantly after 1994, which tended to increase until 2003. Before 1993, however, its spatial externalities were not significant. Japan's spatial externalities showed fluctuating values throughout the sample period. Furthermore, the movement of the spatial externalities was correlated with Japan's business conditions: the externalities showed a high value in the economic boom, and a low value in the economic depression. This could mean that spatial externalities correlate mainly with business conditions.

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Bibliographic Info

Article provided by AccessEcon in its journal Economics Bulletin.

Volume (Year): 30 (2010)
Issue (Month): 1 ()
Pages: 751-764

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Handle: RePEc:ebl:ecbull:eb-09-00630

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Keywords: Spatial externalities; Bayesian estimation; Production function;

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  1. Michael Pfaffermayr, 2007. "Conditional Beta- and Sigma-Convergence in Space: A Maximum Likelihood Approach," Working Papers 2007-17, Faculty of Economics and Statistics, University of Innsbruck.
  2. Cem Ertur & Wilfried Koch, 2005. "Growth, Technological Interdependence and Spatial Externalities - Theory and Evidence," ERSA conference papers ersa05p651, European Regional Science Association.
  3. Koopman, S.J.M. & Shephard, N. & Doornik, J.A., 1998. "Statistical Algorithms for Models in State Space Using SsfPack 2.2," Discussion Paper 1998-141, Tilburg University, Center for Economic Research.
  4. Esther Vaya Valcarce & Enrique Lopez Bazo & Rosina Moreno Serrano & Jordi Surinach Caralt, 2000. "Growth and externalities across economies. An empirical analysis using spatial econometrics," Working Papers in Economics 59, Universitat de Barcelona. Espai de Recerca en Economia.
  5. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
  6. Alicja Olejnik, 2008. "Using the spatial autoregressively distributed lag model in assessing the regional convergence of per-capita income in the EU25," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 371-384, 08.
  7. Bernard Fingleton & Enrique López-Bazo, 2006. "Empirical growth models with spatial effects," Papers in Regional Science, Wiley Blackwell, vol. 85(2), pages 177-198, 06.
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Cited by:
  1. Seya, Hajime & Tsutsumi, Morito & Yamagata, Yoshiki, 2012. "Income convergence in Japan: A Bayesian spatial Durbin model approach," Economic Modelling, Elsevier, vol. 29(1), pages 60-71.

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