A Spatial Econometrical Analysis On China's Economic Growth And Income Distribution Disparities

This dissertation reconsiders the question of Chinese economic convergence club from a spatial econometric perspective and aims at two central objectives. The first is to delineates the trend of Chinese regional disparities and its spatial dynamics over the 1978-2002 period, based on recently developed methods of exploratory spatial data analysis as well as the decomposition techniques of Theil and Gini indices. The second objective is to apply a set of spatial econometric models to examine the growth convergence over the sample period and to explain the performance and mechanism of recent Chinese economic growth from a new growth theory and new economic geography perspective.The dissertation is organized as follows: Chapter 1 indicates the necessity and significance of the research, provides a concise literature review, lists the problematic issues in the existing literature.Chapter 2 is for development of a theoretical framework. The theorizing work begins with the so-called Solow-Swan core model of growth from neoclassical theory, and then it moves beyond the neoclassical model to incorporate the novel ideas of new growth theory and new economic geography. In order to take account of spatial effects as prescribed in the First Law of Geography by Tobler, a GfS-SA platform is devised and a panel database is constructed to facilitate a time-space empirical analysis of Chinese economic growth and convergence patterns.Chapter 3 is devoted to a Chinese regional convergence study from a a-convergence perspective, followed with an exploratory spatial data analysis based on the recent developed methods in the area.Chapter 4 tries to determine the cointegration and causal-effect relationship of economic growth and income disparities using a cointegration model and a Granger causal-effect model, with the results being as expected.In Chapter 5, based on a B -convergence model of Barro andSalad-I-Martin neoclassical theory of growth, the convergence rate of Chinese regional economic growth over the 1978-2002 period is estimated first by ordinary least squares and, then, due to the presence of spatial dependence in the population residual terms, a spatial error model in the line of Anselin's spatial econometrics is specified and re-estimated with maximum likelihood method.Chapter 6 examines the provincial convergence issue and its cause, urban-rural issue and its widening economic gap. Following a Getis-Griffith's approach, a spatial autoregressive filtering technique is adopted and the spatial effects embedded in the panel dataset are filtered out according to a local Gi* measure of each observation. As consequences, a best linear unbiased estimator of ordinary least squares is used in estimating on the panel data. Results show that there is an evidence of conditional convergence in China's provincial economic growth. In other words, regional per capita GDP growth rate is negatively correlated with its initial year's per capita GDP level. Another finding is that the estimated convergence rate of panel data is higher than that estimated using cross-sectional data, implying the possible bias with the cross-sectional data estimation.Chapter 7 is an examination on the sources of Chinese economic growth at a more disaggregated county level from a theoretical perspective of endogenous growth and increasing returns. Empirical estimates show that investment in a county's human capital, urbanization, industrialization and information not only contribute that county's economic growth performance, but also diffuses the momentum of growth to nearby county in the form of economically positive spillovers.Chapter 8 is conclusion, the research results are summarized, conclusions are made, and suggestions for future study are proposed.