Micro-Econometric Analysis On Driving Mechanism Of Urbanization

An appropriate level of urbanization is of great importance to theeconomic development for each country's economy. Since the implementationof reform and opening policies, China's urbanizing process has beenaccelerated greatly. But it is still lagging far behind the economicdevelopment level. In order to provide some beneficial policy advice to speedup China's urbanization process, the thesis make a deep investigation andstudy on the driving mechanism of urbanization, specially focusing on thearea of Zhujiang River Delta.China's academic circles lay particular stress on qualitative analysis andmacro-analysis over the driving mechanism of urbanization. Differently, thisthesis carries out quantitative micro-analysis on the issue by questionnaireinvestigation and econometric methods. It studies the characteristics ofindividual peasant's decision-making on urbanization and interprets itsinfluence factors quantitatively from micro-aspects.During the spot investigation period, a total of 500 survey questionnaireswere sent to the area and 394 completed questionnaires were returned. Byanalyzing the questionnaire data statistically, the thesis indicates that gender,age, education, distance, income, relative network, urban structure, industrialstructure, international economic connection and government policyrespectively play important roles in the process of individual urbanizationdecision-making. This process turns out to be very complicated so that onlyindustrialization and the development of the tertiary industry are not enoughto form the whole driving mechanism of urbanization.According to the characteristics of the survey data, the thesis conductsanalysis with econometric tools. The dependent variable in the data includes 0and 1, respectively representing two choices of urbanizing decision-making.That type of variable is discrete, so classical multivariate linear regression cannot be applied to it. Currently, scholars all over the world usually adopt utilityfunction to transform the discrete dependent variable into continuous variable.Then they use ML (Most Likelihood) method to estimate the parameters toestablish the Binary Choice Model. This thesis is going to utilize this model toanalyze the factors of the driving mechanism of urbanization and provide aquantitative predicting framework over the issue of individual urbanizationdecision-makingThe main contribution of the thesis is setting up a general framework forthe micro-driving mechanism of urbanization. In the end, the thesis comes tothe conclusion that many individual micro-factors, which are neglected for along time, play very important roles in the mechanism. It is very necessary topay more attention to them.