Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Application of geographical and temporal weighted regression model to the determination of house price

지리시간가중 회귀모형을 이용한 주택가격 영향요인 분석

  • Park, Saehee (Department of Statistics, Chonnam National University) ;
  • Kim, Minsoo (Department of Statistics, Chonnam National University) ;
  • Baek, Jangsun (Department of Statistics, Chonnam National University)
  • Received : 2016.12.30
  • Accepted : 2017.01.19
  • Published : 2017.01.31
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Abstract

We investigate the factors affecting the price of apartments using the spatial and temporal data of private real estate prices. The factors affecting the price of apartment were analyzed using geographical and temporal weighted regression (GTWR) model which incorporates the temporal and spatial variation. In contrast to the OLS, a general approach used in previous studies, and GWR method which is most widely used for analyzing spatial data, GTWR considers both temporal and spatial characteristics of the house price, and leads to better description of the house price determination. Year of construction and floor area are selected as the significant factors from the analysis, and the house price are affected by them temporally and geographically.

본 연구는 아파트 개별 실거래가격에 대한 시공간 자료를 활용하여 아파트 매매가격에 영향을 미치는 요인을 시계열적 흐름과 공간적 변화를 반영한 지리시간가중 회귀모형 (geographical temporal weighted regression; GTWR)모형을 적용하여 분석하였다. 기존 연구에서 활용되었던 일반적인 접근방법인 최소제곱 (ordinary least square; OLS) 회귀모형과 공간 데이터를 분석하기 위한 공간계량 모델 중 가장 많이 활용되고 있는 지리가중 회귀모형 (geographically weighted regression;GWR)과 달리 GTWR은 주택가격 특성을 고려함에 있어서 시간과 공간을 함께 고려함으로써 보다 정밀한 평가모형이 될 것으로 기대되었다. 본 연구에 사용된 주택가격결정 설명 요인들 중에서 건축연도 및 전용면적이 주택가격을 결정하는데 유의적인 영향을 미치는 것으로 나타났으며, 주택가격이 시간적 공간적 특성 모두에 의하여 유의적으로 설명되었다.

Keywords

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