A Spatial Investigation of σ-Convergence in China
Using techniques of spatial econometrics, this paper investigates σ-convergence of provincial real per capita gross domestic product (GDP) in China. The empirical evidence concludes that spatial dependence across regions is strong enough to distort the traditional measure of σ-convergence. This study focuses on the variation of per capita GDP that is dependent on the development processes of neighboring provinces and cities. This refinement of the conditional σ-convergence model specification allows for analysis of spatial dependence in the mean and variance. The corrected measure of σ-convergence in China indicates a lower level of dispersion in the economic development process. This implies a smaller divergence in real per capita GDP, although convergence across regions is still a challenging goal to achieve in the 2000s.
|Date of creation:||Mar 2006|
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- Harry H. Kelejian & Ingmar R. Prucha, 1999.
"On the Asymptotic Distribution of the Moran I Test Statistic with Applications,"
Electronic Working Papers
99-002, University of Maryland, Department of Economics.
- H. Kelejian, Harry & Prucha, Ingmar R., 2001. "On the asymptotic distribution of the Moran I test statistic with applications," Journal of Econometrics, Elsevier, vol. 104(2), pages 219-257, September.
- Chen, Jian & Fleisher, Belton M., 1996. "Regional Income Inequality and Economic Growth in China," Journal of Comparative Economics, Elsevier, vol. 22(2), pages 141-164, April.
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