The Effects Of Population Aging On Consumption Structure

Since twenty-first Century, the ageing population in China is more and more outstanding. The sixth census of the National Bureau of Statistics data show that,65years of age or older population reached120million people in2010, accounting for8.9%in the country’s total population. Divided according to international standards, when the China’s fifth census (2000), China has entered the aging society. The proportion of the elderly population aged65and above in the total population was7.1%. By the sixth census data show that the aging process speeds in Sichuan Province only after Chongqing provinces, Sichuan has the serious problem of population aging. It’s proportion of the elderly population aged65and above in the total population increased from7.56%in2000to11.25%in2010, increasing of3.39percentage points in just a decade. In the context of an aging population, more and more elderly population, the consumption of different age groups are different. Elderly special preference for consumption will inevitably have some impact in consumption structure, then will affect in the socio-economic development. Study the impact of aging population on the consumption structure, making us a more accurate grasp of domestic demand growth, pulling the continued growth of the regional economy.The characteristics of the empirical research:First, the sample size is small. Second, they are Multiple dependent variables. These two characteristics led to the traditional classical statistical analysis method is not applicable in this article. This paper attempts to make use of gray relational analysis method and partial least squares regression to deeply study of the impact of population aging on the consumption structure, and the two methods can solve the small sample size and Multiple dependent variables. The gray relational analysis method is a general analysis method for the analysis of the relationship between an aging population and consumption structure, previous literature scholars used. Partial Least Squares Regression in current retrieval literature, no one has ever used. Gray correlation analysis concluded that population aging has maximum influence on health care, then clothing and household equipment and facilities. Squares regression concluded that population aging has maximum influence one education, culture, entertainment, then medical care,finally, transportation and communications. From the results of the two methods, we can know population aging has maximum influence on the cost of healthcare, and the results are consistent with the results from the theoretical analysis. From the results of the theoretical analysis, he results of partial least squares regression are more credible than he results of the gray correlation analysis. The reason may be mat the gray relational analysis method does not remove the income and other factors on the consumption structure. This will lead to the aging of the population having no significant effect on the consumption structure or results being deviation, partial least squares regression Justly makes up for the lack of gray relational analysis method, It studies the impact of income, consumption rates and population age structure to the consumption structure at the same time. Using partial least squares regression study of population aging on the consumption structure after eliminating income or consumption rate, so the result is more accurate and more convincing than the gray relational analysis.This article uses the data belonging to the macroeconomic data, and the data from previous censuses, Statistical Yearbook, and the government work report. As I did not carry out a field survey, I can’t broke down a lot of features, such as the elderly population of gender preferences on the consumption structure. This can be used as follow-up study about the consumption structure effect by the aging of the population.