A Study On The Relationship Between Farmers' Income And Consumption In Honghe Prefecture Of Yunnan Province

As the largest developing country in the world,sustained and stable economic growth is essential power. Since the reform and opening-up,our country’s economic development with high speed,and rapidly access to moderate prosperity. But if want to develop the economy on the basis and realize the goal that from a general well-off society to a comprehensive well-off society,nation must narrow the gap between the rich and poor,promote economic development in west area. Thus to improve the economy of the western region needs to stimulate its residents’ consumption level and improve their income level. Therefore in order to ensure the progress of the economy,studying the relation between consumption and income of the western inhabitants is essential.Most of the existing research is basic of the longitudinal data,from two aspects:on the one hand,according to the durability of the Friedman hypothesis,classifying income as persistence income and temporary income,and using different theoretical models to analysis the influence of different sources of income on consumption;on the other hand,basing on the total amount,using the overall national data to study the influence of the regional disparity how to aspect the relationship between rural residents’ income and consumption. Most of them,no matter which one,are based on the traditional estimation method,so the main disadvantage is not taking the structure and heterogeneity between data into account.Overall, multilevel growth model has obvious advantage in analyzing longitudinal data. As a result,this article sets up a two level model changing in time,which taking the resident that drawn from Honghe prefecture of Yunnan province as the main object,probe into the relationship and interaction between income and consumption in this area. In this way,we can not only get a properer model to analyze the connection of the income and consumption with high precision,but aslo analyze the influence of the hierarchy data and do deep studying on the characteristics of the dataset.Accordingly putting forward better advice and suggestions and to have more valuable discovery.