Bayesian estimation of spatial externalities using regional production function: the case of China and Japan
AbstractThis 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 InfoArticle provided by AccessEcon in its journal Economics Bulletin.
Volume (Year): 30 (2010)
Issue (Month): 1 ()
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Spatial externalities; Bayesian estimation; Production function;
Other versions of this item:
- Hashiguchi, Yoshihiro, 2009. "Bayesian Estimation of Spatial Externalities Using Regional Production Function: The Case of China and Japan," MPRA Paper 17902, University Library of Munich, Germany.
- R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
- O4 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
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- ERTUR, Cem & KOCH, Wilfried, 2005.
"Growth, Technological Interdependence and Spatial Externalities: Theory and Evidence,"
LEG - Document de travail - Economie
2005-03, LEG, Laboratoire d'Economie et de Gestion, CNRS, Université de Bourgogne.
- 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.
- Cem Ertur & Wilfried Koch, 2005. "Growth, Technological Interdependence and Spatial Externalities - Theory and Evidence," ERSA conference papers ersa05p651, European Regional Science Association.
- 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.
- Koopman, S.J.M. & Shephard, N. & Doornik, J.A., 1998.
"Statistical Algorithms for Models in State Space Using SsfPack 2.2,"
1998-141, Tilburg University, Center for Economic Research.
- 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.
- Neil Shephard & Jurgen Doornik & Siem Jan Koopman, 1998. "Statistical algorithms for models in state space using SsfPack 2.2," Economics Series Working Papers 1998-W06, University of Oxford, Department of Economics.
- 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.
- 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.
- 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.
- Michael Pfaffermayr, 2007.
"Conditional Beta- and Sigma-Convergence in Space: A Maximum Likelihood Approach,"
2007-17, Faculty of Economics and Statistics, University of Innsbruck.
- 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.
- 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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