Application Of Markov Chain In Econormic Regional Convergence Of Jiangxi Province

The Markov process,also called the Markov chain when the state and time of the Markov process are both discrete,is a very important branch of stochastic process theory.Markov chain theory can be applied to realistic situation and there are some certain research results in medicine,education,sociology and economics and other disciplines.The Markov chain can be applied to so many areas,mainly because in many areas the characteristic of Markov are met when the system at a moment in the state,you can determine next moment of this system,and it is not necessary to consider the state of the system before that moment.Located in central China,Jiangxi has a very important strategic position in geographical location,mineral resources and ecological environment.However the economic development level of Jiangxi Province stays in the middle and lower stage of the provinces in the central part of China,and there also exist imbalanced,polarized phenomenon between the various prefecture-level cities' economic level in Jiangxi.Therefore,it is a significant means to analyze whether there are the economic regional convergence phenomenon between prefecture-level cities in Jiangxi for studying the coordinated economic development of Jiangxi Province.In the past,the first step of studying the economic convergence problem was to establish the Markov chain model in space to set the spatial lag operator,and constructed the spatial weight matrix to obtain the conditional probability matrix of the lag.Finally,we could reach some conclusions from the analytical of the matrix.This article is based on the specific situation to improve and optimize the model.First of all we conduct the Markov nature test of per capita GDP data of the prefecture-level cities in Jiangxi Province,then we correct the method of classification according to the idea of orderly clustering,and establish the weighting matrix in space,optimize the matrix with the principle of neighboring,then normalize the matrix,and finally we optimize the conditional probability matrix.In the analysis of the actual data,we can find that the matrix obtained by the traditional method mainly shows the state transition in the developed areas,and can not describe the state transition in the backward areas.Using the optimization model to analyze the data,the resulting lag conditional probability matrix can reflect the trend of state transition in economically backward areas.When there is a developed area near the undeveloped area,the probability of moving to the upper state will increase;when the undeveloped areas near the developed areas,the probability of its transfer to the next state will be increase.Different regions are limited by different external factors and the results are not the same,but the analysis of the results show the backwardness of the regional economic development trend which provide a theoretical basis in studying the coordinated development of the city of Jiangxi Province.