Increased Homelessness and Low Rent Housing Vacancy Rates

2000 ◽  
Vol 9 (1-2) ◽  
pp. 76-103 ◽  
Author(s):  
June Ying Shann-Hwa Park
Keyword(s):  
Vacancy Rates ◽  
Housing Vacancy

scholarly journals Spatial Pattern of Housing Sales Vacancy in Guangzhou’s Urban District, China

2021 ◽  
Vol 5 (6) ◽  
pp. 47-51
Author(s):  
Xiaoli Yue ◽  
Yang Wang ◽  
Yabo Zhao ◽  
Hong’ou Zhang
Keyword(s):  
Spatial Pattern ◽  
Real Estate Market ◽  
Urban District ◽  
The Real Estate ◽  
The Core ◽  
The North ◽  
The Real Estate Market ◽  
Vacancy Rates ◽  
Residential Quarters ◽  
Housing Vacancy

Housing vacancy can reflect the destocking degree of the real estate market. Based on the data of 57 opened residential quarters (46,622 units) from 2015 to 2018, this paper constructs a calculation formula of the sales vacancy rate and then analyzes the spatial pattern in Guangzhou’s urban district. The results show that there is obvious differentiation in the spatial pattern of housing sales vacancy in Guangzhou’s urban district, showing a higher spatial pattern in the old area and urban district and a lower spatial pattern in the core area. Subdistricts with high vacancy rates are mainly located in the east of the old area, the south and east of the urban district and near Baiyun Mountain in the north.

Empty houses across North America: Housing finance and Mexico’s vacancy crisis

Urban Studies ◽  
2018 ◽  
Vol 56 (10) ◽  
pp. 2075-2091 ◽  
Author(s):  
Paavo Monkkonen
Keyword(s):  
The United States ◽  
Mortgage Lending ◽  
Housing Finance ◽  
High Rate ◽  
Housing Crisis ◽  
Role Of Government ◽  
Central Cities ◽  
Urban Periphery ◽  
Vacancy Rates ◽  
Housing Vacancy

In the wake of the housing market crash in the United States in the late 2000s, images of abandoned homes on the periphery of American cities dominated international media. Mexico continues to face a housing crisis that began at the same time, and the media similarly focus on the high rate of housing vacancy in the urban periphery. The vacancy rate is extreme in many newly built subdivisions in Mexico, yet it is also high in most central cities. In this article, I describe the role of government mortgage lending in housing vacancy rates, across and within cities in Mexico. I do this using data from the 2010 Census of Population and Housing for the 100 largest cities in the country. Cities with more housing built under the federal housing finance system have higher vacancy rates overall, and the relationship is strong in central areas of cities as well as the urban periphery. These findings imply that policymakers should not only be concerned with vacancy in newly built suburban developments, but they should also consider how the expansion of credit for new suburban housing has played a role in the hollowing out of central cities. The article has direct implications for Mexico and raises questions about the frame for debate about housing policy internationally. The structure of housing finance systems is often under-scrutinised. Scholars working in emerging markets should work to identify incentives in finance systems and how they shape urbanisation.

scholarly journals Estimating Housing Vacancy Rates in Rural China Using Power Consumption Data

2019 ◽  
Vol 11 (20) ◽  
pp. 5722 ◽  
Author(s):  
Jing Li ◽  
Meng Guo ◽  
Kevin Lo
Keyword(s):  
Power Consumption ◽  
Urban Areas ◽  
Spatial Clustering ◽  
Rural China ◽  
National Level ◽  
Scale Up ◽  
Rural Housing ◽  
Consumption Data ◽  
Vacancy Rates ◽  
Housing Vacancy

Village hollowing is a growing policy problem globally, but accurately estimating housing vacancy rates is difficult and costly. In this study, we piloted the use of power consumption data to estimate the vacancy rate of rural housing. To illustrate the method used, we took power consumption data in 2014 and 2017 in an area of rural China to analyze the change in housing vacancies. Results indicated that the rural vacancy rates were 5.27% and 8.69%, respectively, while underutilization rates were around 10% in 2014 and 2017. Second, there was significant spatial clustering of vacant rural housing, and the hotspots were mainly distributed in western mountainous areas, whereas villages near urban areas had lower vacancy rates. Third, rural vacancies increased from 2014 to 2017. Compared with other methods, our method proved to be accurate, very cost-effective and scalable, and it can offer timely spatial and temporal information that can be used by policymakers to identify areas with significant village hollowing issues. However, there are challenges in setting the right thresholds that take into consideration regional differences. Therefore, there is also a need for more studies in different regions in order to scale up this method to the national level.

scholarly journals Influencing Factors of Housing Sales Vacancy in the Guangzhou Metropolitan Area, China

2021 ◽  
Vol 5 (6) ◽  
pp. 49-54
Author(s):  
Xiaoli Yue ◽  
Yang Wang ◽  
Hong’ou Zhang
Keyword(s):  
Influencing Factors ◽  
Metropolitan Area ◽  
Regression Models ◽  
Central Business District ◽  
Vacancy Rates ◽  
Business District ◽  
Housing Vacancy

In this paper, nine indicators selected from three perspectives (convenience, environmental and location characteristics) and three regression models (OLS, SLM and SEM) are used to explore the influencing factors of housing sales vacancy in the Guangzhou Metropolitan Area, China. The results show that subway accessibility, peripheral aversion municipal facilities and distance from the CBD (Central Business District) are consistent with theoretical expectations. Subway accessibility is negatively correlated with the housing sales vacancy rates, while peripheral aversion municipal facilities and distance from the CBD are positively correlated with housing vacancy rates.

scholarly journals Housing Vacancy Rate in Major Cities in China: Perspectives from Nighttime Light Data

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Zhiru Tan ◽  
Donglan Wei ◽  
Zixu Yin
Keyword(s):  
Data Center ◽  
Housing Prices ◽  
Vacancy Rate ◽  
Nighttime Light Data ◽  
Building Information ◽  
Nighttime Light ◽  
Vacancy Rates ◽  
Second Tier ◽  
Nighttime Light Imagery ◽  
Housing Vacancy

In recent years, the phenomenon of housing vacancy rate (HVR) has attracted considerable attention, especially concerning unjustified expansions of Chinese cities. The aforementioned trend is disadvantageous in that it will ultimately lead to tremendous wastage of valuable land that could otherwise be more productively utilized. Consequently, the methods for accurately determining the HVR are of great importance. Based on nighttime light data from the Luojia 1-01 nighttime light imagery provided by Wuhan University in June 2018 and the building data obtained from the Resources and Environmental Sciences Data Center, we estimated the HVRs of 49 cities in China by determining the building areas and considering the floor height. The results revealed that (1) the lowest (15%) and highest (24.3%) HVRs occur in Shenzhen and Nanning, respectively. (2) The urban HVR correlates positively with the three production structures (0.3143) but is significantly negatively correlated with population (0.3841), GDP (0.6139), and urban average housing prices (0.5083). (3) The first-tier, new first-tier, and second-tier cities showed the lowest (16.9%), relatively concentrated (20.5%), and highest (21.3%) average vacancy rates, respectively. (4) The vacancy rate is relatively low in the eastern coastal areas, whereas high in the northeast and western inland areas. The proposed method can help urban planners by identifying vacant areas and providing building information.

Do Housing Vacancies Induce More Crime? A Spatiotemporal Regression Analysis

2019 ◽  
Vol 66 (11) ◽  
pp. 1579-1605 ◽  
Author(s):  
Xiaojin Chen ◽  
Patrick Rafail
Keyword(s):  
Regression Analysis ◽  
Collective Efficacy ◽  
Large Scale ◽  
Spillover Effect ◽  
Property Crime ◽  
Drug Offense ◽  
Community Based Programs ◽  
The City ◽  
Housing Vacancy ◽  
Neighborhood Level

This study aims to investigate the longitudinal associations between patterns of housing vacancies, neighborhood social disorder, and crime in the city of New Orleans. Using large-scale administrative and contextual data collected from the year 2012 to 2018, our spatiotemporal regression analysis provides empirical evidence for the salient effects of housing vacancy on neighborhood level of property crime and violence. In addition, the spillover effect of housing vacancy is observed on the neighborhood level of drug offense, property crime, and violence. These results potentially identify vacant properties as a modifiable target for intervention to reduce urban crime and suggest that community-based programs aiming to enhance informal social control and collective efficacy may be as important as broken window policing programs.

scholarly journals Predicting Detached Housing Vacancy: A Multilevel Analysis

2022 ◽  
Vol 14 (2) ◽  
pp. 922
Author(s):  
Jaekyung Lee ◽  
Galen Newman ◽  
Changyeon Lee
Keyword(s):  
Multilevel Model ◽  
Local Environment ◽  
Critical Issue ◽  
Building Structure ◽  
Model Design ◽  
Vacancy Rate ◽  
City Center ◽  
Individual Housing ◽  
The Individual ◽  
Housing Vacancy

Urban shrinkage is a critical issue in local small- and medium-sized cities in Korea. While there have been several studies to analyze the causes and consequences of vacancy increases, most have only focused on socioeconomic associations at larger scale and failed to consider individual housing level characteristics, primarily due to a lack of appropriate data. Based on data including 52,400 individual parcels, this study analyzes the primary contributors to vacant properties and their spatial distribution through a multilevel model design based on data for each parcel. Then, we identify areas at high risk of vacancy in the future to provide evidence to establish policies for improving the local environment. Results indicate that construction year, building structure, and road access conditions have a significant effect on vacant properties at the individual parcel level, and the presence of schools and hypermarket within 500 m are found to decrease vacant properties. Further, prediction outcomes show that the aged city center and areas with strict regulations on land use are expected to have a higher vacancy rate. These findings are used to provide a set of data-based revitalization strategies through the development of a vacancy prediction model.

scholarly journals International Real Estate Review

2011 ◽  
Vol 14 (2) ◽  
pp. 159-183
Author(s):  
Oliver Bischoff ◽  
Keyword(s):  
Household Income ◽  
Birth Rate ◽  
Flow Model ◽  
Positive Impact ◽  
Data Set ◽  
Rental Market ◽  
East German ◽  
Vacancy Rates ◽  
Stock Flow

We apply the stock flow model for the German residential rental market using a data set that includes the overwhelming majority of nomenclature of territorial units for statistics (NUTS) 3 regions for the 2004-2007 period. Aside from proving conditional rental price convergence, we have detected a turnaround in vacancy stocks between the short and the long term. While East German counties and West German independent cities currently exhibit the highest and lowest vacancy rates, respectively, the opposite holds true at equilibrium. Leaning on theoretical suggestions, landlords in well-developed areas have incentives to hold onto vacancies in view of future rent increases. Our results support this idea, which demonstrates the significantly positive impact of household income and net birth rate on the natural vacancy rate.

When a Country Ignores Its Own Data

2021 ◽  
pp. 175-182
Author(s):  
Rob Kitchin
Keyword(s):  
Local Government ◽  
Census Data ◽  
Housing Crisis ◽  
Policy Makers ◽  
Property Prices ◽  
Property Data ◽  
Public Data ◽  
Construction Activity ◽  
Vacancy Rates ◽  
Quality Issues

This chapter evaluates the benefits of evidence-informed policy over anecdote through an account of the financial crash in Ireland and the effect of creating public data stories. If politicians, policy makers, local government, the banks and property developers had paid proper attention to the data, the crash may not have happened, or at least might have had a softer landing. Instead, the data were ignored. The census data showed that all the way through the boom, vacancy rates were increasing, housing completions were running way ahead of household increase, more land was being zoned than could realistically be developed, and land and property prices were overheating. As a consequence, Ireland was still paying the price and continuing to experience a housing crisis. While some oversupply still existed in parts of the country, over a decade of suppressed construction activity and rising population had led to a shortage of housing in the cities and their commuter belts. Moreover, Ireland still has an issue with property data, with some datasets being discontinued, some having quality issues, some released in non-open formats and some still non-existent.

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