모수적방법과 준모수방법에 의한 주택가격 함수 추정에 관한 연구

A semi parametric estimator is used to analyze the hedonic housing price functions in a sample of 1284 sales prices of apartments in the southern Seoul area. The hedonic price functions are expected to be nonlinear, but theory offers little guidence on the form. of the nonlinearity. Choosing the appropriate functional form is particularly difficult for location variables and time trends because the appropriate form tends to be unique to the place and time. A semiparametric estimation offers important advantages for the hedonic housing price function estimation. It combines the benefits of the parametric and nonparametric estimation. The parametric portion of the model includes standard housing characteristics such as dwelling unit size, the size of the community, age of building, types of heating system and fuel material, school districts, among others. Distances of the CBD, two subcenters, and subway stations are estimated nonparametrically. How the sales price varies with time, which is the critical variable, is modeled nonparametrically, as well. The coefficients have the expected signs and are stable across parametric and semiparametric specifications. The semiparametric estimation has higher coefficient of determination than two parametric OLS estimations. A Hausman (1978) test to determine the specification of the hedonic price function form prefers to the semiparametric estimation.