| Housing price has the direct bearing on people's living quality and social harmony. The discussion of measurement methods of housing prices has been an important research topic in the theory circle and the practice circle. Housing is typically a heterogeneous commodity, not only in terms of housing structure, but also in location, neighborhood and environment, these characteristics are very different, and have effects on the level of housing prices. A large number of foreign literatures have confirmed that, if we adopt the simple average price to measure the law of housing prices fluctuations, the results appear bias. Therefore, relying on the in-depth study of housing price measurement methods, on the one hand, we can accurately define the housing price differences caused by different characteristics; the other hand, by stripping the influence of housing characteristics, we may analyze housing pure price volatility. This has important practical significance to reveal the rule of housing price changes.As an analytical tool for the price measurement of heterogeneous commodity, hedonic price model has been highly appreciated by foreign scholars in the past 40 years, and a large number of literatures have been appeared in housing price studies. These studies cover both public policy evaluation, and housing demands analysis, also include compilation of housing price indexes. However, due to the regional attribute of housing market, there exhists a significant difference across countries or regions in analytical methodology, model specification and so on. There are no uniform criteria and standards, and there are many problems to be further studied both in the aspect of theory and methodological. Hedonic method has been introduced to China with only 10 years old, the domestic studies are only a briefly introduction of hedonic approach or an application of abroad model to China's data, lack of depth exploration and innovation integrated with the background of China's housing market. In view of the above considerations, this dissertation from the perspective of housing characteristics implicit price, taking China's housing market as study area, using hedonic price model, studies the relationship between housing prices and housing characteristics, by hedonic quality adjustment, peeling off an impact of housing characteristic over housing price, reveals the real housing price fluctuations. Thesis work and innovation are reflected in:â‘ On the basis of overseas research, taking second-hand housing market of Baoding city Hebei province as research object, this dissertation constructed a hedonic price model of China's housing market. The paper made a detailed analysis of variable definition and assignment, in addition to conventional characteristics such as building, location and neighborhood, the model introduced trading characteristics variables to delineate the features of our housing market. With Box-Cox transformation technique, the functional forms commonly used at home and abroad, such as linear function, semi-logarithmic function, log-log function and Box-Cox function have been compared, the above regression function perform well both in fitting accuracy and the significance of the variable parameters. Further, log-likelihood ratio test and Theil U statistic for out-of-sample forecasting were implemented to test the best functional form. Test results show that, Box-Cox function is superior to other commonly used functions.â‘¡By sorting and analyzing the concepts and ideas of quality adjustment, this paper made an in-depth analysis of the difference between time dummy variable method, characteristic price index method, and hedonic imputation price index method, and demonstrated the derivation process of calculation formulas of time dummy variable method. Applying mixed cross-section, adjacent-period and single-period cross-section of hedonic price model, the paper calculated mixed time dummy variable housing price index, adjacent period time dummy variable housing price index, and characteristics housing price index. Wald test showed that characteristics price index method is the best one with model stability and robustness. By way of comparison of differences between different methods, research finds that chain price index calculated with adjacent period function parameters is similar with Fisher characteristics price index. The results show that, with hedonic quality control, the chain price index can be better reflect housing price dynamic fluctuations than fixed base price index, in particular, such difference is more significant where there is large change between sample's compositions at different periods. When the sample size is large, the hedonic price index is the best choice, but when the sample size is limited, then the adjacent period time dummy variable price index or even mixed time dummy variable price index may be an alternative option.â‘¢From the perspective of housing characteristics'implicit price difference, applying housing sub-market hedonic price model, the paper analyzed housing price change across spatial-temporal. Baoding housing market is divided into three sub-markets by space dimension, Wald test showed that the three sub-market model defined by administrative districts were significantly different, further test with Tiao-Goldberger statistics explored the housing characteristics implicit price differences among sub-market. results show that among 26 explanatory variables, the differences between each coefficient is significant at the 5% level up to 19 variables, reflecting the difference of consumer demand for housing characteristics in different regions. Study showes that there exist spatial differences intra-urban housing markets, even in the same city, a single hedonic house price model cannot precisely describe the relationship between housing prices and housing characteristics. Finally, using sub-market hedonic housing price model, the paper calculated the housing price differences between each sub-market, and established a second-hand housing price index of Baoding city ranging from the fourth quarter of 2006 to second quarter of 2009. |
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