Housing Vacancy Rates Research Articles

Abstract 18709: Disparities in Socioeconomic Metrics Associated With Adverse Outcomes Among Medicare Beneficiaries Undergoing Peripheral Endovascular Intervention

Background Low socioeconomic status (SES) is associated with an increased incidence of peripheral artery disease, however there is a lack of granularity in the specific metrics that contribute to this discrepancy. We examine the association of community-level economic distress with adverse outcomes in patients undergoing peripheral endovascular intervention (PVI). Hypothesis: Socioeconomically distressed communities have non-healthcare-related, structural disparities that contribute to incident PVI and adverse outcomes. Methods: Medicare beneficiaries ≥66 years of age from 2016 to 2018 were evaluated to determine the incidence of femoropopliteal PVI. The Distressed Community Index (DCI) was used to categorize adults as distressed (DCI ≥80) or not distressed (DCI <80). Composite outcome of death and major amputation within 1 year of PVI were examined by level of distress using individual community-level metrics. Results: Socioeconomically distressed adults underwent 158 PVIs per 100000 distressed beneficiaries compared with 109 PVIs per 100000 non-distressed beneficiaries (risk ratio, 1.45 [95% CI, 1.42-1.48]; P<0.001). Distressed adults who underwent PVI were more likely to be female (45.5% versus 43.1%; P<0.001) and Black race (21.9% versus 10.1%; P<0.001) (Table I). There was a strong association between distress and the composite outcome at 1 year (incidence rate ratio, 1.11 [95% CI 1.07-1.16; P=0.0001]). Distressed adults lacked high school diplomas (11.88% versus 11.15%; P<0.001), had higher rates of unemployment (24.11% versus 22.76%; P<0.001), and greater housing vacancy rates (9.74% versus 9.31%; P<0.001). Conclusion: Socioeconomic distress is associated with higher rates of PVI-incidence and post-PVI adverse outcomes. This may be driven by structural inadequacies inherent to low SES communities that need to be addressed in order to narrow the gap in care among distressed adults undergoing PVI.

Does high speed railway alleviate housing vacancy rates? Evidence from smart meter data of household electricity consumption

Does high speed railway alleviate housing vacancy rates? Evidence from smart meter data of household electricity consumption

Business Churning and Neighborhood Instability: Is There a Link?

Much of the work concerning economic dynamism has focused on its aggregate-level implications, while there have been rising concerns about business displacement at the community or neighborhood level. In this article, we analyze this important (restructuring) process using detailed establishment-level business information and explore how it manifests itself across space within the Los Angeles—Long Beach—Santa Ana, CA Urbanized Area. We also investigate the association between business churning and neighborhood-level housing vacancy rates to understand the implications of dramatic changes in the business landscape. We find that housing vacancies are more likely to increase in urban neighborhoods with a higher establishment death rate, while the creation of new businesses can mitigate the association to some extent. We also detect substantial variation across decades not only in the spatial distribution of business churning but also in its association with housing vacancy rates, suggesting the evolving nature of business dynamics and their implications.

Analysis of factors affecting the occurrence of vacant houses according to vacant house classification: Shizuoka Prefecture, Japan

This study aimed to analyze factors affecting the occurrence of vacant houses according to vacant house classification across regions of Shizuoka Prefecture, Japan. The analysis considered urban scales, metropolitan areas, and weather data to determine the characteristics of variables that generate vacant houses. The findings showed that housing vacancy rates could be more accurately determined by dividing urban scales into big cities, medium-sized cities, small cities, and towns/villages, rather than merely metropolitan and nonmetropolitan areas. The number of variables affecting the occurrence of vacant houses increased in regions with a high housing vacancy rate and differed according to regional characteristics. The predictive factors for the occurrence of vacant houses in Shizuoka Prefecture were greatly influenced by population, society, and industry. Shizuoka Prefecture needs social policies to stimulate the influx of young people to mitigate the occurrence of vacant houses. Meanwhile, the weather data on daylight hours, number of days with precipitation, and number of days with strong wind showed a correlation with the vacancy rate. Thus, weather data must be considered in urban planning. Our findings can be used for policy making regarding management of housing vacancy rate, urban renewal, and new town planning.

Do social determinants of health impact access to neurosurgical care in the United States? A workforce perspective.

This study attempts to use neurosurgical workforce distribution to uncover the social determinants of health that are associated with disparate access to neurosurgical care. Data were compiled from public sources and aggregated at the county level. Socioeconomic data were provided by the Brookings Institute. Racial and ethnicity data were gathered from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research. Physician density was retrieved from the Health Resources and Services Administration Area Health Resources Files. Catchment areas were constructed based on the 628 counties with neurosurgical coverage, with counties lacking neurosurgical coverage being integrated with the nearest covered county based on distances from the National Bureau of Economic Research's County Distance Database. Catchment areas form a mutually exclusive and collectively exhaustive breakdown of the entire US population and licensed neurosurgeons. Socioeconomic factors, race, and ethnicity were chosen as independent variables for analysis. Characteristics for each catchment area were calculated as the population-weighted average across all contained counties. Linear regression analysis modeled two outcomes of interest: neurosurgeon density per capita and average distance to neurosurgical care. Coefficient estimates (CEs) and 95% confidence intervals were calculated and scaled by 1 SD to allow for comparison between variables. Catchment areas with higher poverty (CE = 0.64, 95% CI 0.34-0.93) and higher prime age employment (CE = 0.58, 95% CI 0.40-0.76) were significantly associated with greater neurosurgeon density. Among categories of race and ethnicity, catchment areas with higher proportions of Black residents (CE = 0.21, 95% CI 0.06-0.35) were associated with greater neurosurgeon density. Meanwhile, catchment areas with higher proportions of Hispanic residents displayed lower neurosurgeon density (CE = -0.17, 95% CI -0.30 to -0.03). Residents of catchment areas with higher housing vacancy rates (CE = 2.37, 95% CI 1.31-3.43), higher proportions of Native American residents (CE = 4.97, 95% CI 3.99-5.95), and higher proportions of Hispanic residents (CE = 2.31, 95% CI 1.26-3.37) must travel farther, on average, to receive neurosurgical care, whereas people living in areas with a lower income (CE = -2.28, 95% CI -4.48 to -0.09) or higher proportion of Black residents (CE = -3.81, 95% CI -4.93 to -2.68) travel a shorter distance. Multiple factors demonstrate a significant correlation with neurosurgical workforce distribution in the US, most notably with Hispanic and Native American populations being associated with greater distances to care. Additionally, higher proportions of Hispanic residents correlated with fewer neurosurgeons per capita. These findings highlight the interwoven associations among socioeconomics, race, ethnicity, and access to neurosurgical care nationwide.

Estimation of Urban Housing Vacancy Based on Daytime Housing Exterior Images—A Case Study of Guangzhou in China

The traditional methods of estimating housing vacancies rarely use daytime housing exterior images to estimate housing vacancy rates (HVR). In view of this, this study proposed the idea and method of estimating urban housing vacancies based on daytime housing exterior images, taking Guangzhou, China as a case study. Considering residential quarters as the basic evaluation unit, the spatial pattern and its influencing factors were studied by using average nearest neighbor analysis, kernel density estimation, spatial autocorrelation analysis, and geodetector. The results show that: (1) The urban housing vacancy rate can be estimated by the method of daytime housing exterior images, which has the advantage of smaller research scale, simple and easy operation, short time consumption, and less difficulty in data acquisition. (2) Overall, the housing vacancy rate in Guangzhou is low in the core area and urban district, followed by suburban and higher in the outer suburb, showing a spatial pattern of increasing core area–urban district–suburban–outer suburb. Additionally, it has obvious spatial agglomeration characteristics, with low–low value clustered in the inner circle and high–high value clustered in the outer suburb. (3) The residential quarters with low vacancy rates (<5%) are distributed in the core area, showing a “dual-core” pattern, while residential quarters with high vacancy rates (>50%) are distributed in the outer suburb in a multi-core point pattern, both of which have clustering characteristics. (4) The results of the factor detector show that all seven influencing factors have an impact on the housing vacancy rate, but the degree of impact is different; the distance from CBD (Central Business District) has the strongest influence, while subway accessibility has the weakest influence. This study provides new ideas and methods for current research on urban housing vacancies, which can not only provide a reference for residents to purchase houses rationally, but also provide a decision-making basis for housing planning and policy formulation in megacities.

Estimating housing vacancy rates at block level: The example of Guiyang, China

For the real estate market, housing prices as well as housing vacancy rates (HVRs) are key indicators. However, for the latter indicator, there is no official data set for Chinese cities. Collecting HVR in a traditional way requires enormous personnel efforts and is therefore very expensive and time consuming. In this study, we introduce a framework for estimating the HVR at high spatial resolution (i.e. at block level) for residential areas based on several emerging data sources. The developed framework consists of three steps: 1) we extract residential blocks and map detailed housing data. These data are applied to estimate the population capacity; 2) we spatially distribute the actual census population into residential blocks as a function of night light emission intensity; 3) we estimate the HVR for each residential block according to the gap between its actual distributed population and the estimated population capacity. We find the following main results for our test case of Guiyang in China: 1) the average HVR in the urban area of Guiyang is estimated at 25%; 2) with rising distance to the city center the HVR is increasing; 3) the buildings that have been built more recently feature higher HVRs. We check the plausibility of our approach using water consumption data as proxy information for residency. These checks reveal high accuracies. With this suggested workflow relying on open data sources and the achieved plausibility, the developed framework for HVR estimation has the potential to be applied on a large scale.

Structural indicators of suicide: an exploration of state-level risk factors among Black and White people in the United States, 2015–2019

PurposeDeath by suicide among Black people in the USA have increased by 35.6% within the past decade. Among youth under the age of 24 years old, death by suicide among Black youth have risen substantially. Researchers have found that structural inequities (e.g. educational attainment) and state-specific variables (e.g. minimum wage, incarceration rates) may increase risk for suicide among Black people compared to White people in the USA. Given the limited understanding of how such factors systematically affect Black and White communities differently, this paper aims to examine these relationships across US states using publicly available data from 2015 to 2019.Design/methodology/approachData were aggregated from various national sources including the National Center for Education Statistics, the Department of Labor, the FBI’s Crime in the US Reports and the Census Bureau. Four generalized estimating equations (GEE) models were used to examine the impact of state-level variables on suicide rates: Black adults suicide rate, Black youth (24 years and younger) suicide rate, White adult suicide rate and White youth suicide rate. Each model includes state-level hate group rates, minimum wage, violent crime rates, gross vacancy rates, and race-specific state-level poverty rates, incarceration rates and graduation rates.FindingsAcross all GEE models, suicide rates rose between 2015–2019 (ß = 1.11 – 2.78; ß = 0.91 – 1.82; ß = 0.52 – 3.09; ß = 0.16 – 1.53). For the Black adult suicide rate, state rates increased as the proportion of Black incarceration rose (ß = 1.14) but fell as the gross housing vacancy rates increased (ß = −1.52). Among Black youth, state suicide rates rose as Black incarcerations increased (ß = 0.93). For the adult White suicide rate, state rates increased as White incarceration (ß = 1.05) and percent uninsured increased (ß = 1.83), but fell as White graduation rates increased (ß = −2.36). Finally, among White youth, state suicide rates increased as the White incarceration rate rose (ß = 0.55) and as the violent crime rate rose (ß = 0.55) but decreased as state minimum wages (ß = −0.61), White poverty rates (ß = −0.40) and graduation rates increased (ß = −0.97).Originality/valueThis work underscores how structural factors are associated with suicide rates, and how such factors differentially impact White and Black communities.

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

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.

Abstract 13360: The Association Between Food Insecurity and Cardiovascular Mortality in the United States From 2011 to 2017 - A Longitudinal Analysis

Introduction: Prior analyses suggest a link between food insecurity and cardiovascular (CV) health but are limited by cross-sectional designs. We investigated whether longitudinal changes in food insecurity are independently associated with CV mortality. Methods: Using National Center for Health Statistics data, we determined annual U.S. county-level age-adjusted CV mortality rates for non-elderly (20-64 years old) and elderly (65 years and older) adults. County-level food insecurity rates were obtained from the Map the Meal Gap project. We examined CV mortality trends by quartiles of average annual percent change (APC) in food insecurity. Using a Poisson fixed effects estimator, we assessed the association between longitudinal changes in food insecurity and CV mortality rates after accounting for time-varying demographic (proportion of residents who were male, black, Hispanic), economic (median household income, unemployment, poverty, education attainment, and housing vacancy rates), and healthcare access (insurance coverage, density of healthcare providers and hospital beds) variables. Results: Between 2011 and 2017, mean food insecurity rates decreased from 14.7% to 13.3%. In counties in the highest quartile of APC for absolute value change in food insecurity, non-elderly CV mortality increased from 82.2(SD=33.9) to 87.4(SD=37.3) per 100,000 individuals (p<0.001), while in counties in the lowest quartile of APC, mortality was stable [60.8(SD=22.2) to 60.0(SD=23.0) per 100,000 individuals, p=0.64]. Elderly CV mortality significantly declined in all quartiles [1643.3(SD=315.7) to 1542.7(SD=299.4) per 100,000 (p<0.001) in the highest quartile and 1408.3(SD=225.9) to 1338.6(SD=213.8) per 100,000 (p<0.001) in the lowest quartile). A 1 percentage point increase in food insecurity was independently associated with a 0.83% (95% CI 0.42 - 1.25, P<0.001) increase in CV mortality for non-elderly adults. This was not significant for elderly adults (-0.06%, 95% CI -0.39 - 0.28, P=0.74). Conclusion: From 2011 to 2017, an increase in food insecurity was independently associated with an increase in CV mortality rates for non-elderly adults in the U.S. Interventions targeting food insecurity may play a role in improving community CV health.

Mexico’s housing crisis: vacancy, limited access & Deaf policy responses

ABSTRACT During the 2000s, millions of Mexicans acquired mortgages to buy homes in the fringes of cities throughout the country. Many such households have faced limited access to services, infrastructure and employment, and have seen their monthly mortgage payments increase while their debt remains virtually unchanged. In parallel, while about a third of Mexicans still live in poor housing conditions, numerous newly built developments have exhibited alarmingly high housing vacancy rates. Such coexistence of housing vacancy and shortages exposes considerable tensions in Mexican housing policy between the social and the economic values of housing. While previous analyses have centred on the financialization of housing policy in Mexico, this paper examines some of the local, political and socioeconomic implications of recent federal housing finance policy and urban development patterns, particularly as they relate to housing access and vacancy. Furthermore, this paper discusses the more recent evolution of Mexico’s housing and urban development policy, as well as the juxtaposition of the institutional and civic responses that have emerged to make front to previous financialization and housing development patterns and their implications.

Estimating Housing Vacancy Rates in Rural China Using Power Consumption Data

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.

Modeling the Census Tract Level Housing Vacancy Rate with the Jilin1-03 Satellite and Other Geospatial Data

The vacant house is an essential phenomenon of urban decay and population loss. Exploration of the correlations between housing vacancy and some socio-environmental factors is conducive to understanding the mechanism of urban shrinking and revitalization. In recent years, rapidly developing night-time remote sensing, which has the ability to detect artificial lights, has been widely applied in applications associated with human activities. Current night-time remote sensing studies on housing vacancy rates are limited by the coarse spatial resolution of data. The launch of the Jilin1-03 satellite, which carried a high spatial resolution (HSR) night-time imaging camera, provides a new supportive data source. In this paper, we examined this new high spatial resolution night-time light dataset in housing vacancy rate estimation. Specifically, a stepwise multivariable linear regression model was engaged to estimate the housing vacancy rate at a very fine scale, the census tract level. Three types of variables derived from geospatial data and night-time image represent the physical environment, landuse (LU) structure, and human activities, respectively. The linear regression models were constructed and analyzed. The analysis results show that (1) the HVRs estimating model using the Jilin1-03 satellite and other ancillary geospatial data fits well with the Census statistical data (adjusted R2 = 0.656, predicted R2 = 0.603, RMSE = 0.046) and thus is a valid estimation model; (2) the Jilin1-03 satellite night-time data contributed a 28% (from 0.510 to 0.656) fitting accuracy increase and a 68% (from 0.359 to 0.603) predicting accuracy increase in the estimate model of the housing vacancy rate. Reflecting socio-economic conditions, the luminous intensity of commercial areas derived from the Jilin1-03 satellite is the most influential variable to housing vacancy. Land use structure indirectly and partially demonstrated that the social environment factors in the community have strong correlations with residential vacancy. Moreover, the physical environment factor, which depicts vegetation conditions in the residential areas, is also a significant indicator of housing vacancy. In conclusion, the emergence of HSR night light data opens a new door to future microscopic scale study within cities.

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

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.

How Vehicle Access Enables Low-Income Households to Live in Better Neighborhoods

ABSTRACTTransportation influences residential location choices generally, but low-income households often face unique constraints because of a lack of access to automobiles. This article examines how vehicle access influences the type of neighborhoods in which low-income households are able to secure housing following a move to a new neighborhood. We rely on data from the Moving to Opportunity program to estimate locational attainment models, including a wide range of variables capturing various dimensions of neighborhood opportunity. Our findings suggest that auto access enables low-income households to secure housing in neighborhoods that exhibit a wide range of positive neighborhood attributes, including lower poverty rates, lower housing vacancy rates, higher median household income, higher labor-force participation, and higher adult high school graduation rates.

Access to the City Center and Housing Vacancies in the Suburbs

How does access to the center of a city affect the housing vacancy rate in the suburbs? Using data on housing for French municipalities, I first document the disparities and evolution of housing vacancy rates in France. A particular attention is paid on the Paris metropolitan area, where housing vacancies are surprisingly large. Next, I develop a theoretical model which emphasizes the link between proximity to the city center and housing vacancies in suburban locations. Finally, I empirically test the predictions of the model using information on transport and housing in the Paris urban area. The findings show that proximity to the city is associated with lower vacancy rates. This result is consistent with a positive association between distance and frictions in the real estate market.

Empty homes, longer commutes: The unintended consequences of more restrictive local planning

We investigate the impact of land use regulation on housing vacancy rates. Using a 30-year panel dataset on land use regulation for 350 English Local Authorities (LAs) and addressing potential reverse causation and other endogeneity concerns, we find that tighter local planning constraints increase local housing vacancy rates: a one standard deviation increase in restrictiveness causes the local vacancy rate to increase by 0.9 percentage points (23%). The same increase in local restrictiveness also causes a 6.1% rise in commuting distances. The results underline the interdependence of local housing and Labour markets and the unintended adverse impact of more restrictive planning policies.

Adolescent Mental Health

The purpose of this article is to explore the role of neighborhood characteristics, specifically economic disadvantage/advantage, residential instability, and racial/ethnic heterogeneity on emotional distress (depressed affect, anxiety, hopelessness) among youth. Using a regional sample of adolescents and matching their data to census tracts, we use hierarchical linear modeling to examine the relationship of neighborhood spatial factors on distress while controlling for individual, family, peer, and school factors. Results show neighborhood effects for adolescent distress are consistent with a stress process model where economic disadvantage and residential instability are positively associated with emotional distress, and indicators of economic advantage are negatively related. Specifically, we find neighborhood unemployment and housing vacancy rates are associated with increased distress, while the percentage of college graduates and foreign-born residents in the neighborhood is associated with reduced distress. We discuss the implications of our findings for ongoing research on neighborhood contextual effects and adolescent health.

Race, class, unemployment, and housing vacancies in Detroit: an empirical analysis

ABSTRACTThis paper is an analysis of the spatial distribution of housing vacancies in Detroit in four census years: 1980, 1990, 2000, and 2010. Our analysis is largely grounded in the contexts of race and class. We use both cartographic and statistical methods to illustrate the distribution of vacancies at the census tract level and to model the conditions that contribute to vacancy rates. A cartographic analysis of the spatial distribution of housing vacancies over time in Detroit indicates that a weak general pattern of outward diffusion occurred from 2000 to 2010. A regression analysis indicates there is a structural pattern of race and class characteristics at the tract level, as measured respectively by percent White—tied to the potential for White flight—and by unemployment rates—tied to financial factors of housing abandonment, that are good predictors of housing vacancy rates over fairly long time periods. Other good predictors are a tract’s percentage of rental housing and, to a lesser degree, the age of a tract’s population.

Wohnungsleerstand in Deutschland. Zur Konzeptualisierung der Leerstandsquote als Schlüsselindikator der Wohnungsmarktbeobachtung anhand der GWZ 2011

At present the housing market in Germany is characterized by contrary trends: Strained markets with partly distinct housing shortage are facing each other with relieved markets even with very high vacancies. For both situations the vacancy rate is a decisive indicator for evaluation. However, the vacancy rate so far is not systematically investigated and elaborated as an indicator but rather is quantified and qualified differently by various scientific and political debates. Against this background the paper suggests a systematic categorization of vacancy rates based on relevant literature. Additionally it develops a heuristic for a differentiated evaluation of housing vacancy rates from different perspectives. This heuristic is then backed up empirically by data from the building and housing census (GWZ) 2011. Thus, it can be demonstrated that the majority of German municipalities has indeed a moderate vacancy rate between 3 and 5 %, but also that substantially regional and spatial-structural differences appear. In respect of the analysis of vacancy rates no spatially-extensive generalization or simple conclusions for housing and urban renewal policies can be drawn. This underlines that a qualification of vacancy rates is necessary in order to be utilized for planning and political decisions.