A Multilevel Model Approach for Assessing the Effects of House and Neighborhood Characteristics on Housing Vacancy: A Case of Daegu, South Korea

Jeong-Il Park

doi:10.3390/su11092515

Abstract

Previous studies on housing vacancy mostly focused on variables representing regional characteristics while overlooking the characteristics of individual houses. This is due to the limitations of available data. Using the house-level Housing Vacancy Database, this study aims to identify the spatial clustering pattern of vacant houses by examining single-family houses in Daegu, South Korea, and analyze the factors affecting housing vacancy. The Housing Vacancy Database built in this study provides accurate location information of vacant houses, making it possible to analyze the clustering pattern of vacant houses in a more detailed spatial unit. Furthermore, the Housing Vacancy Database considered various physical and neighborhood factors at the house level. The result of hot spot analysis showed that vacant houses were spatially concentrated in the city center. As a result of analyzing the factors affecting housing vacancy at the house level and neighborhood level using a multilevel model, it was found that the physical environment characteristics of individual houses were key factors affecting housing vacancy. Additionally, the probability of housing vacancy tended to increase when the land prices were higher, the houses were located in redevelopment zones, and there were more neighboring vacant houses nearby. Meanwhile, population decline and the ratio of old houses were the only significant variables at the neighborhood level. Thus, this study addresses that policies are needed to improve housing and physical environment characteristics that contribute to housing vacancy.

Highlights

Housing vacancy has emerged as a major urban issue in South Korea along with urban shrinkage
It was possible to determine the intra-class correlation (ICC), which is the variance ratio explained by the difference in the neighborhood level, among the house-level variance, neighborhood-level variance, and total variance of housing vacancy that affected the probability of housing vacancy [37]
The ICC calculated in Model 1 was 0.345, which indicates that the probability was explained by the difference in the neighborhood level by 34.5%

Summary

Introduction

Housing vacancy has emerged as a major urban issue in South Korea along with urban shrinkage. According to the 2015 Population and Housing Census, the number of vacant houses in South Korea exceeded 1 million, which accounts for 6.5% of all houses [1]. Vacant housing may spoil urban aesthetics, destroy neighborhood housing conditions, and increase the risk of fire or crime [2,3,4,5,6]. Deterioration of the neighborhood environment due to housing vacancy leads to the decline of housing satisfaction and prices, resulting in population outflow and additional vacant houses [7]. To develop measures to address housing vacancy, it is necessary to determine where it occurs the most and what factors cause its occurrence. Accurately diagnosing the factors that cause housing vacancy provides important information for developing suitable policy alternatives

Objectives

Methods

Results

Conclusion