RESUMEN
Physical property investments enhance public safety in communities while alleviating the need for criminal justice system responses. Policy makers and local government officials must allocate scare resources for community and economic development activities. Understanding where physical property investments have the greatest crime reducing benefits can inform decision making to maximize economic, safety, and health outcomes. This study uses Spatial Durbin models with street segment and census tract by year fixed effects to examine the impact of physical property investments on changes in property and violent crime over an 11-year period (2008-2018) in six large U.S. cities. The units of analysis are commercial and residential street segments. Street segments are classified into low, medium, and high crime terciles defined by initial crime levels (2008-2010). Difference of coefficients tests identify significant differences in building permit effects across crime terciles. The findings reveal there is a significant negative relationship between physical property investments and changes in property and violent crime on commercial and residential street segments in all cities. Investments have the greatest public safety benefit where initial crime levels are the highest. The decrease in violent crime is larger on commercial street segments, while the decrease in property crime is larger on residential street segments. Targeting the highest crime street segments (i.e., 90th percentile) for property improvements will maximize public safety benefits.
RESUMEN
Online platforms have become an integral component of the housing search process in the United States and other developed contexts, but recent studies have demonstrated that these platforms offer uneven representation of different neighborhoods. In this study, we use listings covering the largest 50 U.S. metropolitan areas to assess how GoSection8, a platform uniquely focused on affordable housing and voucher-assisted households, compares with "mainstream" alternatives of Craigslist, Apartments.com and Zillow. Through descriptive and regression analyses of the housing and neighborhoods represented on these websites and a new way of measuring the distribution of rental housing opportunities, we advance a multisource perspective on the role of online information exchanges in housing search processes. Specifically, we find that GoSection8 and mainstream alternatives capture spatially-segmented information about housing markets, with GoSection8 ads representing units that are more affordable but also more constrained to higher-poverty neighborhoods where assisted households are already concentrated. The findings suggest that disadvantaged households are potentially funneled toward high-poverty, isolated neighborhoods by the operation of stratified information systems available for online housing searches.
RESUMEN
This paper assesses the asset building of households that take part in shared-equity homeownership (SEH) models. The contribution of this paper is a comparison of outcomes for households participating in shared-equity programs to other low- and moderate-income households who rent or own properties without restrictions on appreciation. We matched participants in SEH programs to households with similar characteristics from the Panel Study of Income Dynamic (PSID) over the 1997-2017 period. The findings indicate that in real terms, median SEH homeowners accumulated about $1,700 in housing wealth annually or around $10,000 during their holding period. This amount is lower than the $2,100 median annual gain in home equity experienced by similar PSID owners but statistically and economically significantly larger than the $16 in annual gain experienced by similar PSID renters. The findings provide evidence that households participating in SEH programs experienced positive, but modest, wealth gains that were slightly lower than homeowners in unrestricted units but substantially higher than renters.
RESUMEN
Research on rental housing markets in the United States has traditionally relied on national or local housing surveys. Those sources lack temporal and spatial specificity, limiting their use for tracking short-term changes in local markets. As rental housing ads have transitioned to digital spaces, a growing body of literature has utilized web scraping to analyze listing practices and variations in rental market dynamics. Those studies have primarily relied on one platform, Craigslist, as a source of data. Despite Craigslist's popularity, the authors contend that rental listings from various websites, rather than from individual ones, provide a more comprehensive picture. Using a mixed-methods approach to study listings across various platforms in five metropolitan areas, this article demonstrates considerable variation in both the types of rental units advertised and the features provided across those platforms. The article begins with an account of the birth and consolidation of online rental platforms and emergent characteristics of several selected websites, including the criteria for posting, search parameters, search results priority, and first-page search results. Visualizations are used to compare features such as the 40th percentile of rent, rent distribution, and bedroom size based on scraped data from six online platforms (Padmapper, Forrent.com, Trulia, Zillow, Craigslist, and GoSection8), 2020 Fair Market Rents, and 2019 American Community Survey data. The analyses indicate that online listing platforms target different audiences and offer distinct information on units within those market segments, resulting in markedly different estimates of local rental costs and unit size distribution depending on the platform.
RESUMEN
Small Area Fair Market Rents (SAFMRs) are calculated at the 40th percentile of the U.S. postal ZIP Code instead of the metropolitan area in an effort to capture localized rents to expand choice for voucher holders to access housing in higher-opportunity neighborhoods. Existing studies on the potential and actual outcomes of SAFMRs demonstrate that findings vary for different types of housing markets. Furthermore, the decisions public housing authorities (PHAs) make in the implementation process affect PHAs' program budget and the rent burden and locational outcomes for voucher households. This study aims to address how these implementation factors are affected by local rental market conditions for three PHAs-Housing Authority of the City of Fort Lauderdale, San Antonio Housing Authority, and Seattle Housing Authority-in diverse housing markets. By comparing different sources of market rent estimates with SAFMRs in each location, we contribute new information about how this rule is likely to produce different residential outcomes in terms of increased access to low-poverty neighborhoods and adjustments to payment standards in low-rent neighborhoods. The findings reveal differences across rent measures in terms of estimated levels and relative differences across ZIP Codes. These findings suggest that housing authorities may face challenges in meeting the objectives of the SAFMR final rule without some form of local adjustments.