Abstract
Uncertainty in societies is increasing. Therefore, good quality information by which people can understand trends in the property market is necessary. The price of real estate property in a region is chiefly determined by the distance from the closest station. However, the influences between estates cannot be disregarded when real estate properties are concentrated. Patterns that influence properties are likely reflected in the peculiar geographical and historical characteristics of the existing region. The spatial autocorrelation model is a statistic method that can test for the existence of mutual influences between plural objects. However, there is little research on the features of interrelated influences of real estate compared with the features of a region. Therefore, we analyzed newly built apartments in a specific region in a metropolitan area to determine the patterns of social interactions based on the sale price, and evaluate the characteristics of the region.
The following three points were indistinct in the previous researches.
(1) the existence of partial space which has autocorrelations,
(2) the existence of inherent characteristics possessed by the partial space,
(3) the possibility of distinguishing between the interrelated influence of the construction apartments the same period and the influence from the already constructed apartment.
In this study, we focused on Kawaguchi Station with 143 apartments and Kawasaki Station with 130 apartments (each total of 16 years) . The results showed that apartments near the Kawaguchi Station are more competitive and influenced by apartments built at the same time, while the circle region around Kawasaki Station has different features along with directions from the center. Hereafter, we will semi-automate the calculation routine to utilize a computer to analyze the data, reflect on interviews with the concerned persons, and try to establish a marketing area with high consent.
JEL Classification: R12, R14, C31, C18, D85
