Francisca Richter

Consolidating Rural School Districts: Potential Savings And Effects On Student Achievement

One frequently proposed policy is to consolidate rural school districts in order to save money by obtaining economies of size. The effects of school district size on both expenditures and standardized test scores are estimated for Oklahoma. Results indicate that economies of scale with respect to expenditures per student exist up to an average daily membership (ADM) of 965 students, but that as school districts become larger, tests scores decline. Even if savings in school district administration from consolidation are spent on instruction, state average tests scores would decrease slightly. Thus, school district consolidation can reduce costs, but it will also reduce student learning.

Lending patterns in poor neighborhoods

Concentrated poverty has been said to impose a double burden on those that confront it. In addition to an individuals 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 subprime lending in poor neighborhoods by including a spatial dimension to the analysis, in an attempt to capture social – endogenous and exogenous interaction – effects differences in poor and less poor neighborhoods. The analysis is applied to 2004–2006 census tract level data in Cuyahoga County, home to Cleveland, OH, a region that features urban neighborhoods highly segregated by income and race. The patterns found in poor neighborhoods suggest stronger social effects inducing subprime lending in comparison to less poor neighborhoods.

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 explained by the levels of these characteristics. However, foreclosure rate differences between counties across states are mainly explained by the parameter component, suggesting that state level effects might have contributed to shape foreclosure rate outcomes.

Estimating fees for managed futures: a continuous-time model with a knockout feature

Past research regarding incentive fees based on high-water marks has developed models for the specific characteristics of hedge funds. These theoretical models have used either discrete time or a Black-Scholes type differential equation. However, for managed futures, high-water marks are measured more frequently than for hedge funds, so a continuous-time model for managed futures may be appropriate. A knockout feature is added to a continuous model, which is something unique to managed futures although it could also have some relevance to hedge funds. The procedures allow one to derive the distribution function for the funds survival time, which has not been derived in past research. The distribution of the maximum until ruin is derived as well, and used to provide an estimate of expected incentive fees. An estimate of the expected fixed fee is also obtained. The model shows that the expected incentive fee would be maximized if all funds were invested in margins, but for total fees to be maximized in the presence of a knockout feature, less than half of the funds should be invested. This is precisely what fund managers do. This result suggests that designing a fund with incentive fees only may cause fund managers to adopt the highest leverage, and thus, highest risk possible.

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 in the aggregate had little home price appreciation prior to the crisis, but significant follow-up depreciation. The analysis finds evidence that connectedness, expressed as the relative importance of neighboring housing market conditions in explaining city home prices, increases among submarkets even as they experience varying levels of foreclosure rates, and that foreclosure effects give little sign of receding in the near future. The analysis is relevant to the discussion of economic recovery among city and suburban communities as the nation faces high inventories of soon-to-be foreclosed properties.

Understanding trends in neighborhood child maltreatment rates: A three-wave panel study 1990–2010

This study examines how changes in the social and economic structure of neighborhoods relate to changes in child maltreatment report rates over an extended period. The panel study design allows us to partition the changes in child maltreatment report rates into a portion associated with how the levels of socio-economic risk factors have changed over time, and a portion related to how the relative importance of those factors in explaining maltreatment report rates has changed over time. Through the application of fixed effects panel models, the analysis is also able to control for unmeasured time-invariant characteristics of neighborhoods that may be a source of bias in cross-sectional studies. The study finds that increases in vacant housing, single parent families and unemployment rates are strongly associated with increases in child maltreatment report rates. Changes in racial/ethnic composition did not produce changes in maltreatment report rates except when they reached extreme levels of segregation. Although poverty rates were predictive of cross-sectional variation in child maltreatment, increases in neighborhood poverty became less associated with increases in child maltreatment report rates over time.

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 assessors 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 surveys or among non-surveyed properties in an area subject to a random sample survey.

SROI in the pay for success context: Are they at odds?

The Pay For Success (PFS) and Social Impact Bond (SIB) movements to date have focused heavily on shorter-term outcomes that can be monetized and show clear savings to government entities. In part, this focus derives from the need to specify contract payments based on a narrow set of well measured outcomes (e.g., avoided days in jail and foster care, decreased use of behavioral health services). Meanwhile efforts to measure the social return on investment (SROI) of interventions have sought to expand the view of relevant outcomes to include domains that lend themselves less clearly to monetization. This paper explores the intersection between these two movements with illustrations from a SIB initiative underway focused on homeless families with children in foster care. Challenges and potential for SROI in a third-party payor environment will be discussed as well as opportunities to better leverage the strengths of both types of initiative.

Do Low-Income Rental Housing Programs Complement Each Other? Evidence from Ohio

ABSTRACT We characterise the rental subsidy use in units developed with construction subsidies and explore whether such concurrent subsidy use responds to needs unmet by a tenant-based programme alone. We develop a typology of households to guide our analysis focusing on voucher use in Low Income Housing Tax Credit (LIHTC) units. Findings for Ohio in 2011 suggest that the use of additional rental assistance in LIHTC can be complementary in serving certain high-need populations, particularly when targeted housing services are provided. Very poor households with special housing needs constitute over 60% of the population with additional rental assistance in LIHTC, yet the extent to which additional housing services are provided to them is unclear. However, our analysis identifies a significant portion of households in LIHTC units that could seemingly be housed in the private rental market, signalling some degree of inefficiency in the current subsidy mix. While we find that very low income voucher holders are more likely to use their voucher in an LIHTC unit when facing a tighter market or a potential gain in neighbourhood quality, the effects are small.

Can Local Ordinances Prevent Neighborhood Destabilization

Abstract This article assesses the ability of local housing ordinances to prevent neighborhood destabilization, specifically that arising as a consequence of the most recent housing crisis. We evaluate the degree to which vacancy registrations and point-of-sale inspection requirements influenced housing market outcomes during the housing crisis. With comprehensive real property data from Cuyahoga County, Ohio, we measure outcomes that characterize housing market distress including foreclosures, sales below the tax-assessed value, bulk sales, flipping, and property tax delinquency. We evaluate outcomes across properties in regulated and unregulated municipalities using matching procedures on linked data containing property, neighborhood, loan, and transaction characteristics. We find evidence that vacancy registrations substantially reduce foreclosures. In contrast, we find little evidence that point-of-sale inspections reduce undesirable transactions. Rather, properties in cities with inspection requirements displayed higher levels of foreclosure and tax delinquency relative to the control group during the study period.