不動産購買意思와 土地去來量 및 地價 간의 相互關係에 관한 硏究

Abstract

The purpose of this study is to identify the interrelation among the willingness to purchase real estate reflecting consumer confidence, land transaction volumes, and price of land. That is to systematically analyze the causality, correlation, influence, and effects among the variables. For this, statistical techniques such as the Granger causality test, cross correlation analysis, regression analysis, and path analysis were used. Analysis per region was conducted by dividing the nation into Seoul, six metropolitan cities, and other cities, and Seoul was further divided according to zoning for analysis. As for methods of analysis, causality analysis was firstly performed to identify directions, then cause variable and effect variable, and correlation analysis was performed to investigate lag having the highest correlation coefficient to identify the lead-lag relationship. Based on the analysis, the nationwide willingness to purchase, despite small differences, affected transaction volumes 0 to 1 quarters ahead, and affected the price of land 1 quarter ahead. However, nationwide transaction volumes did not affect the price of land. Meanwhile, a willingness to purchase in Seoul was shown to affect transaction volumes 0 to 1 quarters ahead and price of land 0 to 3 quarters ahead, and transaction volumes in Seoul affected the price of land 1 quarter ahead. This result is significant in that nationwide transaction volumes did not affect the price of land, indicating that transaction volumes could affect price of land in Seoul as a limited region. Given that the population and economic strength are concentrated in Seoul, this result has more than sufficient significance. Also, it is a fact that such a relation was shown at a time difference of 0 to 1 quarters per zoning. Based on the above-mentioned results, the author drew up a diagram of interrelation among the willingness to purchase, transaction volumes, and price of land, and then performed regression analysis and path analysis in order to sufficiently verify the relationship. Regression analysis was conducted in order to compare influences among independent variables that cannot be identified from causality analysis. Because causality analysis showed that both the willingness to purchase and transaction volumes affect price of land, the sizes of influences affecting price of land could be compared with each other by regression analysis in which the willingness to purchase and transaction volumes are independent variables and price of land is regarded as a dependent variable. According to the results of the regression analysis, the willingness to purchase had much more influence than transaction volumes on price of land. However, the influence of the willingness to purchase on price of land is direct, and regression analysis is not able to identify if there is a indirect effect on price of land via transaction volumes. Therefore, the author identified indirect effects by using path analysis. The results of the path analysis showed that the ratio of direct and indirect effects of willingness to purchase on price of land was around 7:3. Based on the results of the empirical analysis, the significance of this study is as follows. First, because consumer confidence is a leading variable for transaction volumes and price of land, there is a need to develop various psychological indexes to be utilized in real estate market forecasting. Second, there are time differences per region in the relation among the willingness to purchase real estate, transaction volumes, and price of land. In particular, there are some time differences in Seoul even based on zoning. Therefore, policy planning and investment should be careful with consideration of time differences per region and zoning. Third, this study is first to use path analysis in explanation of the causality relation model among variables for the real estate market, and it is expected that this study will serve as a reference in path analysis research on the real estate market in the future.