| Regional economic convergence measurement has been the hot spots of the regional economics, and researchers use different empirical methods to measure the regional convergence phenomenon in China, of which the regression method is used most widely. It can determine the how is the convergence situation and what influences the regional development speed. The regression method is based on the linear regression theory which assumes that the random disturbances are independent and are not correlated with the explanatory variable. While, with the speed of the regional integration and the recession of the local protectionism, the connections among the provinces are becoming closer, and provinces cannot be deemed to be an independent unit. The regional spatial correlation disobeys the assumptions of the traditional model which cannot measure the spatial correlation in the model and result in the biased empirical outputs.In this context, it is necessary to introduce new econometric model into the study of the regional convergence. Compared with the cross-sectional regression model, the cross-sectional data spatial econometric model release the independence assumption of the traditional model by means of introducing the spatial lag operator into the model to estimate the spatial effect, the panel data model control the characteristics of heterogeneity among the individuals by way of establishing the variable intercept model. The spatial panel data model gathers the advantages of the cross-sectional data spatial econometric model and panel data model, and it considers the spatial correlation and heterogeneity effects at the same time, which makes it more general and practical.In this paper, we first present the theoretical basis of the spatial econometric model and the spatial panel data model, and then apply them into measuring the economic convergence phenomenon in China. By comparing the empirical results of the econometric models which includes the cross-sectional model, the panel data model, the cross-sectional spatial econometric model and the spatial panel data model, the results indicates that the spatial correlation and heterogeneity effects exists significantly, and the spatial panel data model is the most suitable model to measure the convergence phenomenon in China. And the main contents of this paper are as follows:Chapter 1 is the introductory section, which presents the research background, research purpose and meaning, the framework of the passage, the innovations of the article and literature review on the regional convergence.Chapter 2 presents the theoretical basis of the spatial econometric theory and introduces the cross-sectional spatial model into the regional convergence research. The spatial econometrics is one of the frontiers of the econometric research, this chapter gives a detailed description of the theory and compares with that of the time series econometric model, which can help to comprehend the spatial econometric model deeply. And the empirical outputs show that the cross-sectional data spatial econometric model is influenced greatly by the unusual points, and there exist biased estimates to some extents.Chapter 3 introduces the spatial panel data model and its application in the economic convergence phenomenon. The empirical results of Chapter2 indicates that the spatial heterogeneity exist in the process of regional development, which lead to introducing the panel data model. To test the spatial correlation of the panel data model, we introduce the spatial panel data model. And the result shows that the spatial panel data model fits the phenomenon better than other models.Chapter 4 is the conclusion and the research prospect of the paper, and it summaries the whole paper and puts forward some political inspiration. The main conclusions are that there exist significant spatial correlation and heterogeneity characteristics in the process of regional economic development, and that the spatial panel data model is the best model to fit the regional economic development process. The policy proposals of this paper are that the government should strengthen the regional cooperation, optimize the structure of investment, and promote the development of the non-state business. The independent work and innovations of this paper are listed as follow. (1)Spatial panel data model is one of the hot points of the modern econometrics, this paper organizes and summarizes the spatial econometrics systematically, which contains the building and comparison of the spatial weight matrix, the classification of the spatial econometric model and the spatial panel data model, model estimation and realization. (2)The paper provides an overall summarization on regional economic convergence in China from the stand point of the empirical method, and compares the merits and demerits of each method. (3) Previous research on the measurement of the regional convergence are based on the cross-sectional spatial econometric model or the panel data model, the spatial panel data model is seldom used here, and the result shows that the spatial panel data model is of great use in the regional economics. |
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