Estimation of Hedonic Single-Family House Price Function Considering "Scenes"

In this study, hedonic house price functions are formulated using the single-family house market in the 23 wards of Tokyo as the subject.  In the formulation of hedonic models, the generation of omitted variable bias is thought to occur in cases when, in addition to locational factors (i.e., factors involved in decision making when buying a property) and building structures which affect the house prices, local environmental variables or “scenes” and the individual characteristics of house buyers, such as their income, are not taken into consideration.  However, since it is difficult to obtain local environmental information in a small neighborhood unit or “scenes” and to observe individual characteristics of house buyers in the property market, these variables have not been sufficiently considered in previous studies.  In the current study, I aim to improve the hedonic model by incorporating local environmental factors or “scenes” and data on family income in a small neighborhood unit using a geographic information system (GIS).  I demonstrate that, without considering these variables, non-negligible levels of omitted variable bias are generated in the variables that are major factors in determining house prices, such as ground area, front road width, distance to the nearest station, and the travel time to the central business district. Results showed that, in the model considering neighborhood effect variables or “scenes”, the explanatory power was improved compared with the simple linear model. At the same time, each of the neighborhood effect variables or “scenes”, which served as subjects of urban policies, was adopted with statistical significance.