Earticle

초록

영어

This study investigates the spatial dynamics of apartment sale transaction prices in Busan, South Korea, by applying spatial econometric models to comprehensive real estate and demographic data. Utilizing variables such as exclusive area, floor level, year of construction, and local population density, the analysis identifies significant positive spatial autocorrelation in apartment prices, indicating spatial clustering. To better capture these spatial effects, three spatial econometric models—the Spatial Lag Model (SAR), Spatial Error Model (SEM), and Spatial Durbin Model (SDM)—were employed. The results demonstrate that while all models reveal significant relationships between housing characteristics and prices, the SDM model outperforms the others in terms of model fit, highlighting the influence of unobserved spatial factors.

목차

Abstract
Introduction
Data
Apartment Sale Price Data
Geographic Information System Data
Methods
Moran’s I Test
Spatial Lag Model
Spatial Error Model
Spatial Durbin Model
Result
Spatial Durbin Model
Discussion
Reference

저자

• Sung Je Kim [ Department of Food Science and Nutrition, Pukyong National University ]
• Yongbok Cho [ Department of Management Information Systems, College of Business Administration, Dong-A University ]

참고문헌