Empirical study of the relationship between population structure and housing prices

Based on the supply-demand theory and consumption function theories, the transmission mechanism between population structure and housing prices was analyzed, and the mutual ties among various population sub-structures was interpreted. In order to find out the relationship between those population sub-structure and housing prices, the econometric model was set by using a set of data on the statistical indicators of population structure and common residential prices from 1990 to 2006 in Beijing. Through Granger causality test on these indicators and housing prices, the remarkable indicators in the test were used to further establish a linear logarithm model to give a quantitative relationship. As the most remarkable indicator in the logarithm regression, the proportion of working population was studied in detail by dividing into different age groups. The results indicate that population structure has an impact on consumer's demand for housing, thus affecting the changes of housing prices. The population age structure, education structure, labor force structure and the household structure are the Granger cause of residential prices. The proportion of working population, the proportion of population who attain college and higher level education, together with the proportion of unmarried population and average household size, all has significant influences on residential prices. Working population in different age stages has different degree in influencing housing prices, with the population in the group (age from 25 to 44-year-old) having the most significant impact. According to the impact of population structure on housing prices, suggestions proposed include: 1) to identify the change of people's housing demand and develop a reasonable policy of housing supply by researching and controlling population structure, in order to balance supply and demand in the housing market as well as prevent housing prices rising too fast; 2) through the forecast of changes in population structure, to analyze future housing price movements and foresee the real estate cycle; and 3) for achieving a reasonable demand for housing, to establish a correct guidance of housing consumption concept for the 25 to 44-year-old population to help them make housing consumption decisions from their own real demands.