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Bayesian Estimation of Spatial Externalities Using Regional Production Function: The Case of China and Japan

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Hashiguchi, Yoshihiro

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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 depend mainly on business conditions.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 17902.

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Date of creation: Oct 2009
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Handle: RePEc:pra:mprapa:17902

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Related research
Keywords: Spatial Externalities; Bayesian Estimation; Production Function;

Find related papers by JEL classification:
E23 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Production
N95 - Economic History - - Regional and Urban History - - - Asia including Middle East
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis

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  1. 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, Blackwell Publishing, vol. 87(3), pages 371-384, 08. [Downloadable!] (restricted)
  2. Pfaffermayr, Michael, 2009. "Conditional [beta]- and [sigma]-convergence in space: A maximum likelihood approach," Regional Science and Urban Economics, Elsevier, vol. 39(1), pages 63-78, January. [Downloadable!] (restricted)
    Other versions:
  3. Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999. "Statistical algorithms for models in state space using SsfPack 2.2," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 107-160.
    Other versions:
  4. Cem Ertur & Wilfried Koch, 2007. "Growth, technological interdependence and spatial externalities: theory and evidence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1033-1062. [Downloadable!]
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  5. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Oxford University Press for Biometrika Trust, vol. 89(3), pages 603-616, August.
  6. Bernard Fingleton & Enrique López-Bazo, 2006. "Empirical growth models with spatial effects," Papers in Regional Science, Blackwell Publishing, vol. 85(2), pages 177-198, 06. [Downloadable!] (restricted)
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