Low-income-rental-housing programs in the Fourth District
In the aftermath of the Great Recession, many policy analysts are rethinking national housing policies, including affordable housing programs. We review the literature to compare the largest tenant-based (housing choice voucher or HCV) and place-based (low-income-housing tax credit or LIHTC) programs with respect to cost efficiency and access to better quality neighborhoods. We also provide an overview of low-income-rental-housing policy trends and perform a rough comparison of neighborhood quality across programs and counties, focusing on four main urban counties in the Fourth Federal ...
Lending patterns in poor neighborhoods
Concentrated poverty has been said to impose a double burden on those that confront it. In addition to an individual's own financial constraints, institutions and social networks of poor neighborhoods can further limit access to quality services and resources for those that live there. This study contributes to the characterization of the relationship between subprime lending and poor neighborhoods by including a spatial dimension to the analysis, in an attempt to capture social effect differences in poor and less poor neighborhoods. The analysis is applied to 2004-2006 census tract level ...
Local average neighborhood effects from moving to opportunity
This paper estimates Local Average Treatment Effects (LATEs) of neighborhood quality from the Moving to Opportunity (MTO) housing mobility experiment in a generalized model with multiple treatment levels. We propose a new approach to identifying parameters that exploits the identification of unobservables in the multi-level model. The variation in neighborhood quality induced by MTO only allows us to identify LATEs of moving from the first to the second decile of the national distribution of quality, but in other applications the approach may allow for the estimation of Marginal Treatment ...
The effect of local housing ordinances
The housing and economic crises have exerted a strong and lingering impact on housing markets across the nation. In this paper, we assess the degree to which local anti-blight policies have infl uenced housing market outcomes following the crises. The analysis is performed for cities in Cuyahoga County, Ohio. We measure outcomes that characterize market distress and that may be influenced by local housing ordinances including foreclosure, bulk sales, flipping, vacancy, and tax delinquency. Using matching procedures on linked data containing property, loan, and transaction characteristics, we ...
Inter-regional home price dynamics through the foreclosure crisis
Overall regional conditions such as employment, geography, and amenities, favor the co-movement of housing prices in central cities and their suburbs. Simultaneously, over half a century of sprawl may induce a negative relation between suburban and central city home prices, with central city values falling relative to suburban home values. What happens to the relationship between subhousing markets when cities are shocked by the foreclosure crisis? This paper builds repeat-sales indices to explore home price dynamics before and after the foreclosure crisis in the Cleveland area, a market that ...
An analysis of foreclosure rate differentials in soft markets
A quantile regression model is used to identify the main neighborhood characteristics associated with high foreclosure rates in weak market neighborhoods, specifically for two counties in Ohio and one in Pennsylvania. A decomposition technique by Machado and Mata (2005) allows separating foreclosure filing rate differentials across counties into two components: the first due to differences in the levels of neighborhood characteristics and the second due to differences in the model parameters. At higher than median rates, foreclosure rate differentials between counties in Ohio are mainly ...
Predictive Modeling of Surveyed Property Conditions and Vacancy
Using the results of a comprehensive in-person survey of properties in Cleveland, Ohio, we fit predictive models of vacancy and property conditions. We draw predictor variables from administrative data that is available in most jurisdictions such as deed recordings, tax assessor?s property characteristics, and foreclosure filings. Using logistic regression and machine learning methods, we are able to make reasonably accurate out-of-sample predictions. Our findings indicate that housing professionals could use administrative data and predictive models to identify distressed properties between ...
Applying Research to Policy Issues in Distressed Housing Markets: Data-Driven Decision Making
A compilation of research published by the Federal Reserve Bank of Cleveland on housing markets experiencing foreclosure and/or a large number of vacant properties which sheds light on a wide range of housing markets. It provides possible policy solutions applicable to both regional and national policy discussions.
Containing a firestorm: adaptive policies needed to address changing foreclosure landscape
Like a wildfire leaving devastation in its path, the foreclosure crisis continues to wreak havoc on many families and communities throughout the Fourth District, especially in the largest urban areas. Only a year ago the primary reason for foreclosures centered on subprime mortgages. Today, the primary driver is unemployment, further widening the consumption arc of this blaze.
Neighborhood Recovery and NSP1: Implementation in Select Fourth District Communities
The housing crisis in the United States has wrought changes to communities in every corner of the nation. Back in 2008, Congress's response was to create the Neighborhood Stabilization Program, or NSP, as part of the Housing and Economic Recovery Act (HERA), authorizing $3.92 billion for the program now known as NSP1 for local governments to mitigate negative impacts of foreclosures and vacancies through acquiring, rehabilitating, demolishing or redeveloping vacant and foreclosed homes. Undoubtedly, NSP1 was a small program compared to the enormous task of neighborhood recovery, and the funds ...