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

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.

Spatial Characteristics of the Abandonment Degree of Residential Quarters Based on Data of the Housing Sales Ratio—A Case Study of Kunming, China

“…In general, neighborhoods with older buildings and dilapidated houses are prone to abandonment. This finding has been demonstrated by Jeong-II Park [18]. Residential quarters with smaller housing areas are not favored by residents [19,20].…”

“…Housing ages, as the most typical factor in housing physical environment characteristics [18], affect the functionality and living experience of houses, thereby reducing their economic value. Therefore, the general belief is that the older the residential quarter, the higher the abandonment rate.…”

Predicting Detached Housing Vacancy: A Multilevel Analysis

“…These data lack accuracy and specificity in identifying the number and status of vacant properties, thus rendering them ineffective for analyzing the microscopic and accurate causes of vacant properties that take regional heterogeneity into account. In the literature, for example, while Jeon as well as Kim and Park [27,28] conducted their studies at the scale of individual buildings, they failed to identify the spatial distribution or cause of vacant properties across the city; further, they did not consider access to amenities and the presence of nearby vacant properties.…”

Vacancy Dwellings Spatial Distribution—The Determinants and Policy Implications in the City of Sapporo, Japan

“…This figure is expected to continue increasing in the future as the country is facing the stage of a super-aged society and depopulation [22,23]. Further, the unoccupied dwelling problem appears not only in small-and medium-sized cities and suburbs of the metropolises but also spreads into the metropolitan centers [24,25]. As reported in a survey from Japan's Ministry of Internal Affairs and Communications [3], in 2018, the average vacant house ratio in the major metropolis of Japan was about 12.44%, with some cities hitting extremely high value, such as Osaka (17.07%), Kitakyushu (15.80%), or Sapporo (11.93%).…”