GWR모형과 GIS를 이용한 주택가격 추정에 관한 연구

• 발행기관: 한국주거환경학회
• 저자명: 전해정(Chun Hae Jung)
• 간행물 정보: 『주거환경(한국주거환경학회논문집)』住居環境 제14권 제1호 (통권 제31호), 1~12쪽, 전체 12쪽
• 주제분류: 사회과학 > 지역개발
• 파일형태: PDF
• 발행일자: 2016.03.31

영문 초록

In this study, housing price was estimated based on apartment area, number of apartment floor, population density, straight line distance to city hall, subway, 2-lanes, 4lanes and park as explanatory variable by setting actual transaction value of Seoul city apartments as dependent variable using OLS, SAR, SEM (spatial econometrics model) and GWR model (geographically weighted regression model) that is a non-parametric estimation method. As a result of analysis, considering that in case of R2 value and log likelihood, GWR model was higher than OLS but in terms of reference value of both AIC and SC value, GWR model was represented to be lower than OLS, housing price predictability of GWR was proved to be the more reliable than that of OLS model. In addition, as a result of comparing residual distribution, it could be confirmed that while in OLS model, regional spatial correlation was prominent, spatial dependence was considerably moderated in GWR model. As a result of this study, as influence of housing by each features was confirmed to be differently represented spatially, at the time of establishing housing policy, authorities concerned of the government is required to establish and execute regionally differentiated customized housing policy rather than a uniformed policy based on sufficient understanding for the housing sub-market.

목차

Ⅰ. 서 론

Ⅱ. 선행연구 고찰

Ⅲ. 분석모형

Ⅳ. 실증분석

Ⅴ. 결 론

참고문헌

키워드

헤도닉가격결정모형 공간자기회귀모형 공간오차모형 지리가중회귀모형 GIS OLS spatial auto regressive model spatial error model geographically weighted regression GIS