Home Values Research Articles

How Race Counts for Latinx Homeownership

In recent decades, the racial wealth gap has widened with extant literature reporting that Black and Latinx families hold fewer assets than white families. One such asset that receives substantial attention because of its wealth-generating principles is homeownership. Whereas intergroup homeownership inequalities are found throughout the literature, less is known about racialized inequality within groups. Latinxs provide a novel case for exploring how racialized homeownership inequality is structured within an ethnic group. Using data from the American Community Survey, we examine the odds of homeownership and predicted logged home values among Latinxs. We find that the association between race and housing outcomes varies substantially across Latinx groups. Drawing from theories of Latinx racial identity and the future of racial structures, we discuss the implications of our findings for understanding racial inequality among Latinx groups.

The influence of neighborhood factors on biological measures of stress in home‐dwelling multi‐ethnic older adults with dementia

AbstractBackgroundRecently researchers have begun to examine the possible biological pathways through which neighborhood context may affect the health of vulnerable residents. Although stress is often hypothesized to contribute to the effects of neighborhoods on health, no studies have investigated associations of neighborhood characteristics and stress biomarkers in home dwelling persons living with dementia (PLwD). Identifying these biological pathways is fundamental to increasing our understanding of how neighborhoods can influence health and well being in vulnerable residents including those with dementia.MethodsGuided by the National Institute on Minority Health and Health Disparities Framework, this pilot study examined pathways linking both micro (individual level) and macro (neighborhood) level factors in home dwelling PLwD. The model was used to determine what community level factors (density, total crime index, median home value, and noise index) were associated with measures of salivary cortisol controlling for sociodemographics, dementia stage, and comorbid illnesses. The sample included 100 participants: 30 Whites, 39 African Americans, and 31 Latinos with an average age of 73.6. Saliva samples were collected using Salivette collection tubes over two days and stored at −20 °C until analysis.ResultsResidents of neighborhoods with lower housing value and higher noise and density were disproportionately composed of racial/ethnic minorities (with the patterning for Hispanics more pronounced than for blacks.) Significantly lower levels of cortisol at wakeup and a less steep decline was associated with adverse neighborhood environments (higher noise, crime, density, and lower housing value). The strongest relationship between neighborhood characteristics and cortisol levels was found for neighborhood crime. Individuals with dementia residing in higher crime neighborhoods had significant lower levels of cortisol at wakeup and with less pronounced initial declines than those residing in low crime neighborhoods.ConclusionGiven that lower cortisol at wakening and slower rate of decline in cortisol across the day are associated with adverse health outcomes, our analyses can inform the identification of risky communities that are most likely to benefit from health‐supportive community interventions to minimize the negative impacts of unsupportive community environment. These pilot results suggest that further investigation of the effects of neighborhood contexts on stress biomarkers and health outcomes in PLwD is warranted.

Schumpeter Lecture 2019: Slow Household Deleveraging

AbstractWe use a model of precautionary savings with housing and mortgages to study the effects of a deleveraging shock on consumer spending. We focus on the deleveraging caused by a contraction in home values, and compute numerically the partial-equilibrium effect of the shock. Our simulations show that household deleveraging is associated with a long and protracted weakness in consumption. These effects appear even if we assume, realistically, that housing wealth is illiquid and mortgage debt is long term. We show that housing wealth matters for consumption decisions due to an insurance force: consumers know they can sell their house if they get hit by sufficiently negative shocks in the future. We also show that our slow deleveraging mechanism is amplified when incomes are affected by a weak aggregate consumption demand through general-equilibrium effects.

Housing returns, precautionary savings and consumption: Micro evidence from China

We investigate how changes in home prices affect consumption in China via a wealth channel. Examining a panel of 7955 households via fixed effects and instrumental variable methods, we find a marginal propensity to consume out of housing wealth (home-price MPC) that is concentrated on goods consumed for pleasure rather than necessity. This trend is driven by the value of second homes rather than that of primary residences, suggesting a wealth channel. We further examine whether returns on housing investment, including rental income and home appreciation, fund the wealth channel; however, we find little supporting evidence. In contrast, a reduction in health risk increases the home-price MPC, but a reduction in income risk that also relieves precautionary saving motives does not. Our results are robust to alternative data, common-factor progress, expenditure shocks and bequest motives. We contribute by examining second homes, which carry little of the dual nature of housing that primary residences do, to identify a controversial wealth channel, and by studying the relative effects of health and income risks on the wealth channel.

Opioid Crisis and Real Estate Prices

This paper estimates the impact of opioid abuse on real estate prices. We exploit the variation in opioid prescriptions induced by the staggered passage of state laws intending to limit the abuse of opioids. We document a long-term negative relationship between opioid prescriptions and residential real estate prices. For a one standard deviation change in prescriptions we find a 1.36 percentage points change in home values over the following 5 years. We also estimate a positive increase in home prices of 0.54 and 0.91 percentage points respectively in the first and second years following the passage of these laws. One im- portant factor driving this relationship are changes in mortgage delinquency rates. Overall, our results are consistent with opioid abuse having significant long lasting negative economic effects that are mitigated if opioid supply is limited.

Home-Based Locational Accessibility to Essential Urban Services: The Case of Wake County, North Carolina, USA

Accessibility is an important concept in urban studies and planning, especially on issues related to sustainable transportation planning and urban spatial structure. This paper develops an optimization model to examine the accessibility from single family homes to major urban facilities for services or amenities using geographical information systems. The home-based accessibility to facilities is based upon the point to point direct distance from sampled homes to sampled facilities. Descriptive statistics about the accessibility, such as min/max, mean/median, and standard deviation/variance were computed. Variations of accessibility for a range of categories by home price and year built were also examined. Multivariate linear regression models examining the housing value with respect to home-facility accessibility by facility types were implemented. The results show that desirable urban facilities, which are also more frequently used for livability, enjoy better accessibility than undesirable urban facilities. The home-based accessibility’s positive or negative associations with home price along with year built and/or residential lot size exist for most facilities in general, and by confirming to the literature, the home-facility accessibility in particular does strongly impact home values as evidenced by fair to excellent R2 values. Accordingly, this research provides evidence-based recommendations for sustainable urban mobility and urban planning.

Housing at the frontline of the COVID-19 challenge: A commentary on "Rising home values and Covid-19 case rates in Massachusetts".

Housing at the frontline of the COVID-19 challenge: A commentary on "Rising home values and Covid-19 case rates in Massachusetts".

The Case of Cubans: Racial Inequality in U.S. Homeownership and Home Values

Prior research finds that human capital may explain racial housing inequality, whereas others note the historical role that race played in creating unequal housing conditions. This study uses the case of Cubans in the United States to examine whether human capital explains Black–White housing inequalities, or if they are a result of nativity/cohort differences—a proxy for the federal policies that supported Cubans’ economic and social incorporation. Using pooled data from the American Community Survey, I examine how human capital characteristics and nativity/migration cohorts shape odds of homeownership and predicted home values among Cubans. Extended analyses using decomposition methods find that although human capital characteristics are important, they play a smaller role in explaining Black–White differences in homeownership and home values. Indicative of the changing structure of racial stratification in the United States, results reveal substantial inequality among the oldest of Cuban immigrants and U.S.‐born Cubans, despite a trend toward declining inequality among recent arrivals. Supported by the literature of systemic racism, the case of Cubans shows how human capital explanations do not sufficiently explain racial housing inequalities and how the future of racial stratification is one of inter‐ and intra‐ethnic group inequality.

Could equalizing neighborhood socioeconomic status and greenness reduce racial disparities in all-cause mortality among men with prostate cancer?

BackgroundNeighborhood contextual factors are associated with racial disparities among men with prostate cancer (CaP), but studies often separately emphasize socioeconomic status or built environment. We estimated the reduction in mortality disparities following a hypothetical joint intervention to equalize both neighborhood socioeconomic status and greenness across Black and White men with CaP. MethodsBlack and White men diagnosed with CaP from January 2000 to December 2015 were followed for up to 10 years using data from the Pennsylvania and Massachusetts Cancer Registries. Racial disparity was defined as the 10-year all-cause mortality risk difference between Black compared to White men, standardized to age, race, diagnosis year, state, and population density. The racial disparity was estimated using Cox models with 95% confidence intervals obtained using bootstrapping. Neighborhood contextual risk factors included socioeconomic characteristics (census block group income, poverty, racialized economic spatial polarization, educational attainment, home value) and greenness within 250m of residential address. We modeled the impact of modifying neighborhood contextual risk factors by z-scaling neighborhood characteristics to 0.5 standard deviation above or below the mean. This resulted in setting neighborhood poverty=3%, income=$56,000, home value=$164,000, 7% with high school diploma or lower, spatial polarization=0.10, and NDVI=0.60. ResultsThe cohort included 169,195 men (10% Black), with 38,672 deaths over 1,219,552 person-years of follow-up. There were 41.6 (95% CI: 35.6, 47.6) excess deaths per 1,000 over 10 years among Black men. The disparity was attenuated under the hypothetical intervention (17.1 deaths per 1,000, 95% CI: 7.8, 26.4), resulting in a 58.9% reduction in the racial disparity.Discussion An intervention to jointly equalize several neighborhood socioeconomic characteristics and neighborhood greenness among men with CaP could reduce racial disparities in mortality. Though this does not reflect a real-world policy, incorporating environmental improvements alongside efforts to reduce socioeconomic disparities could yield greater gains in reducing racial disparities.

Evaluation of PM2.5 Air Pollution Sources and Cardiovascular Health

Background: Air pollution exposure, notably fine particulate matter (diameter ≤ 2.5 μm, PM2.5), is a global contributor to morbidity and mortality and a known risk factor for myocardial infarctions (MI) and coronary artery disease (CAD). Novel modeling methods can provide source-apportionment, to estimate the source-specific impacts on cardiovascular health. Methods: The Catheterization Genetics (CATHGEN) cohort consists of patients who underwent a cardiac catheterization at Duke University Medical Center (North Carolina, USA) from 2001-2010. History of MI was extracted from medical records. Severity of coronary blockage was determined by coronary angiography and converted into a binary indicator of clinical CAD. PM2.5 source-specific yearly averages were estimated using an improved gas-constrained source apportionment model for North Carolina from 2002 to 2010 at 12x12 kilometer resolution. We tested six PM2.5 source-specific mass estimates for associations with CAD and MI (per 1 µg/m3 increase) using multivariate logistic regression adjusted for age, race, sex, smoking history, home value, urbanity, and education. Results: Of 5681 CATHGEN participants; 2497 (43.9%) had CAD, and 1652 (29.0%) had a history of MI. PM2.5 fractions of ammonium bisulfate and ammonium nitrate were associated with increased prevalence of CAD (odds ratio [OR] 1.52; 95%CI 1.24-1.86 and OR 1.62; 95%CI 1.28-2.05, respectively). PM2.5 from ammonium bisulfate and ammonium nitrate were also associated with increased prevalence of MI (OR 1.57; 95%CI 1.28-1.94 and OR 2.04; 95% CI 1.61-2.58, respectively). MI was associated with PM2.5 from ammonium sulfate (OR 1.44; 95%CI 1.15-1.82). Gasoline source-apportioned PM2.5 was inversely associated with CAD (OR 0.58; 95%CI 0.38-0.90). We did not observe association with diesel or secondary organic carbons PM2.5. Conclusion: Greater PM2.5 fractions of ammonium bisulfate and ammonium nitrate are associated with greater MI and CAD prevalence. Our findings suggest analyses of source-specific PM2.5 mass may reveal novel associations. This abstract does not reflect EPA policy.

Neighborhood Socioeconomic Status, Long-Term Exposure to Particulate Matter, and Risk of Cardiovascular Disease and Mortality in the Nurses’ Health Study

Background: Although associations between particulate matter <2.5 microns (PM2.5) and cardiovascular disease (CVD) and mortality are well-established, less is known regarding the joint impact of PM2.5 and neighborhood socioeconomic status (nSES). Our objective was to investigate this interaction in a nationwide cohort of U.S. women. Methods: We used time-varying Cox proportional hazards models, conditioned on age and calendar time, to assess main and interaction effects of PM2.5 and nSES on risk of CVD (stroke, myocardial infarction) and mortality among 100,257 women in the Nurses’ Health Study between 1986 and 2008. Incident CVD (n=6,445) and mortality (n=10,186) cases were ascertained from medical or death record reviews. We created Census tract-level nSES scores by summing z-scores (where increasing scores were associated with affluence) of selected nSES metrics (e.g., race, education, income, home value, nativity, unemployment), and calculated time-varying 24-month average PM2.5 exposure using residential address history. Models were adjusted for time-varying demographic, lifestyle (e.g., diet, physical activity, smoking), and individual-level SES factors. Results: In multivariable adjusted models, increases in nSES (Hazard Ratio [HR]CVD: 0.98, 95% Confidence Interval [CI]: 0.97, 0.99; HRmortality: 0.99, 95% CI: 0.99, 1.00, per 1 unit increase) and PM2.5 (HRCVD: 1.03, 95% CI: 0.95, 1.12; HRmortality: 1.04, 95% CI: 0.97, 1.11, per 10 µg/m3 increase) were associated with incident CVD and mortality rates, although the associations with PM2.5 did not reach statistical significance. The interaction between PM2.5 and nSES was statistically significant for CVD risk (p<0.001) and mortality (p<0.013); associations with mortality were strongest among the least affluent neighborhoods, while associations with CVD were weakest in areas of least and greatest affluence. Conclusions: Our results suggest that PM2.5 and nSES exposures are associated with small changes in rates of mortality and CVD incidence. These exposures interact in a complex fashion, even within a relatively demographically homogeneous cohort of women.

The Importance of Micro-Location for Pricing Real Estate Assets: The Case of Hotels

Traditionally, hedonic pricing studies focusing on commercial real estate control for spatial effects with macro-location dummy variables, for example, at the MSA or submarket level, and predominantly rely on OLS regression. This approach ignores the importance of micro-location characteristics for predicting sales prices. Additionally, spatial dependencies in transaction prices and error terms violate OLS assumptions. We propose an alternative approach that replaces macro-location dummy variables with four location area characteristic (LAC) variables, defined as population, median home value, homeownership rate, and average land gradient within a polygon of a 20-minute driving distance around each property in our sample. We compare the location dummy and LAC approach using OLS regression, spatial autoregression (SAR), and spatial autoregression with autoregressive errors (SARAR) for a sample of hotels sold between 2015 and 2017. We find models that include LAC variables to have a superior fit to models with MSA dummy variables, irrespective of estimation method. Additionally, the inclusion of individual LAC variables allows a reduction of spatial lags and errors.

가계경제적 변인과 일만족도가 기혼 직장 여성의 결혼만족도에 미치는 영향

This study set out to investigate the effects of household economic variables and work satisfaction on marital satisfaction. The focus of this study is on married women who work for a living. Data came from the Korean Longitudinal Survey of Women & Families 2016. The final sample size was 2811 working married women in South Korea. Stepwise regression is used for the analysis. The major findings of this study were as follows: First, the highest level of work satisfaction was on security and the lowest was on fringe benefits. Second, marital satisfaction was different according to age of wife, age of husband, educational attainment of wife, educational attainment of husband, income, expenditure, tangible assets, financial assets, savings, value of home, perceived economic status, and work satisfaction. Third, the prominent determinants of marital satisfaction were work satisfaction, age, financial assets, perceived economic status, and expenditure. Work satisfaction was the strongest among them. These findings have an important pragmatical meaning in that they show the determinants of marital satisfaction by working married women. The limitations and implications of the findings from this study were discussed with respect to further studies.

Developments in the Market for Assisted Living: Residential Care Availability in 2017

ObjectivesDescribe how the availability of assisted living (AL) and dementia-specific AL vary across counties and correlate with demographic and socioeconomic characteristics. DesignMaps, univariate statistics, and standardized mean differences show the differences between counties with high and low levels of AL market penetration, and between counties with and without dementia-specific AL. Setting and ParticipantsData collected from state agencies on licensed AL communities, capacity, and geographic location, and population characteristics from the Area Health Resource file. We include novel and previously undescribed data on dementia-specific AL licenses in 21 states. MeasuresAL market penetration is reported as the number of AL units or beds per 1000 persons over age 65 years in a county. ResultsIn comparison to counties with the lowest AL penetration, high-penetration counties had higher high school and college education attainment (mean 25.3% vs 18.5%) and median annual income ($56,000 vs $46,800), and lower poverty (12.8% vs 17.3%) and unemployment rates (3.9% vs 5.1%). Compared to counties with AL but no dementia-specific care, counties with dementia care had substantially higher college attainment (24.6% vs 17.7%) and had higher urbanity index (3.8 vs 5.6 on a 1-9 scale, 1 most urban). Counties with dementia care also had, on average, 16% more in median household income ($54,200 vs $46,400) and 40% greater home value ($159,800 vs. $113,600). Conclusions and ImplicationsLarge socioeconomic disparities persist among counties without any AL or low penetration of AL in their borders in comparison to those with high AL penetration, as well as between counties with and without dementia-specific AL communities. There may be a mismatch in need and availability of residential care options for older adults with Alzheimer's disease and related dementias that contributes to the disproportionate share of racial/ethnic minorities with dementia in nursing homes. Lack of available AL beds in the communities where Medicaid individuals reside could make rebalancing efforts doubly difficult, in that Medicaid enrollees may be reluctant to move out of their neighborhoods.

The Efficacy of Allocating Housing Growth in the Los Angeles Region (2006–2014)

California is known for home values that eclipse U.S. housing prices. To increase housing inventory, California has implemented a regional housing needs allocation (RHNA) to transmit shares of housing growth to cities. However, no study has established RHNA’s efficacy. After examining the 4th RHNA cycle (i.e., 2006–2014) for 185 Los Angeles region cities, this study determined that RHNA directed housing growth to the city of Los Angeles and the region’s outlying cities as opposed to increasing density in the central and coastal cities. Second, RHNA directed 62% of housing growth to the region’s unaffordable cities. Third, the sample suffered a 34% shortfall in housing growth due to the Great Recession but garnered an average achievement of approximately 93% due to RHNA’s transmission of minimal housing growth shares. Lastly, RHNA maintained statistically significant associations with increased housing inventory, housing affordability, and housing growth rates, indicating that RHNA may influence housing development.

The Increasing Effect of Neighborhood Racial Composition on Housing Values, 1980–2015

Abstract Beginning in the 1930s, neighborhood racial composition was an explicit determining factor in the evaluation of U.S. home values. This deliberate practice was outlawed in the 1960s and 1970s, but the correlation between neighborhood racial composition and home values persists. Using Census Bureau data from 1980 to 2015, the present study investigates the changing relationship between neighborhood racial composition and home appraisals, as well as the mechanisms that drive it. Contrary to what is often presumed, neighborhood racial composition was a stronger determinant of appraised values in 2015 than it was in 1980. Results suggest this is primarily due to contemporary appraising practices. Specifically, the use of the sales comparison approach has allowed historical racialized appraisals to influence contemporary values and appraisers’ racialized assumptions about neighborhoods to drive appraisal methods. These findings provide strong evidence that persistent racial inequality is driven in part by perpetual devaluing of communities of color and they suggest further regulation is required to foster equity.

Google Search Queries, Foreclosures, and House Prices

We study whether Google search behavior for “mortgage assistance” and “foreclosure help” aggregated in the mortgage default risk indicator (MDRI) of Chauvet et al. (2016) helps predict future house prices and foreclosures in local residential markets. Using a long-run equilibrium model, we disaggregate house prices into their fundamental and bubble components, and we find that MDRI dampens both components of house prices. This negative relationship is robust to various model specifications and time horizons. A higher intensity of search online, however, is associated with lower future foreclosure rates. We also find that foreclosure rates increase after a decline in the fundamental component of home values, but are not sensitive to their transitory (bubble) component. Foreclosure rates are higher in metropolitan areas located in non-recourse states. We interpret these findings as evidence for strategic household behavior. Our paper sheds new light on the predictive power of household sentiment derived from Google searches on prices and foreclosure rates in local housing markets.

MIXED GEOSPATIAL METHODS BASELINE STUDY TO EVALUATE AND MODEL GENTRIFICATION ALONG THE WESTSIDE ATLANTA BELTLINE, USA

Abstract. There is a need for sustainable infrastructure planning that includes environmental, social, economic, and transportation management consideration. A portion of a former railway corridor around Atlanta, Georgia was converted to a multi-use trail called the Atlanta BeltLine to provide walking and bicycling access to businesses and homes. Although the pedestrian-transit trail brings renewed development and services, it also triggers increases in home values and displaces existing communities. This study uses remote sensing and geospatial analysis to focus on changes in the structural conditions of housing along the Westside segment of the Atlanta BeltLine. The first segment of the Beltline, the Eastside Trail completed in 2007, demonstrated an alarming influx of development. Increases in property values opened the doors for private investors to purchase properties and open new businesses in communities adjacent to the BeltLine. The proposed Westside segment of the BeltLine has raised concerns by community members who fear the impacts of gentrification. An assessment of housing conditions was conducted by researchers ranking the structural conditions of homes adjacent to the Westside BeltLine. To conduct an estimate of green spaces along both segments of BeltLines, Sentinel-2 Earth Observation Satellite was used to calculate the percentage of green spaces in. A preliminary concept agent-based simulation model (ABM) is being developed to forecast human movement and housing condition around the BeltLine. Combined, the housing survey, green space inventory, and ABM model provides a baseline method to record and identify social and the environmental impacts.

Eco-gentrification and who benefits from urban green amenities: NYC’s high Line

This study estimates the impact of the introduction of New York’s High Line, an elevated walkway in Manhattan by relating the increase in housing values to the issue of eco-gentrification in urban areas. Studies have shown that increasing the amount of green space can lead to gentrification: rising property values, displacement of existing residents, and a large in-migration of wealthy populations. We utilize Geographic Information Systems (GIS) to spatially model the effects of the High Line on residential property values. We exploit spatial and temporal differences of the High Line’s opening to estimate its impact on residential home values. We find that homes closest to the High Line experienced a 35.3% increase in housing values. We estimate the driving force behind this premium by using a triple difference approach by analyzing elevation levels and find that homes with relatively the same height as the High Line receive the largest premium. This study serves to inform policy makers regarding potential inequality of green space provisions. We provide policy recommendations for minimizing the housing price impact of green space creation.

Rising home values and Covid-19 case rates in Massachusetts.

We explore whether housing displacement pressure could help explain place-based disparities in Massachusetts COVID-19 prevalence. We use qualitative data from the Healthy Neighborhoods Study to illustrate how rising and unaffordable housing costs are experienced by residents in municipalities disproportionately affected by COVID-19. We then predict municipal-level COVID-19 case rates as a function of home value increases and housing cost burden prevalence among low-income households, controlling for previously identified community-level risk factors. We find that housing value increase predicts higher COVID-19 case rates, but that associations are ameliorated in areas with higher home values. Qualitative data highlight crowding, “doubling up,” homelessness, and employment responses as mechanisms that might link housing displacement pressure to COVID-19 prevalence.