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.Foreclosure ; Federal Reserve District, 4th ; Economic conditions - Ohio ; Economic conditions - Pennsylvania

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 data in Cuyahoga County, home to Cleveland, Ohio, a region that features urban neighborhoods highly segregated by income and race. The patterns found in poor neighborhoods suggest stronger social interaction effects inducing subprime lending in comparison to less poor neighborhoods.Poverty ; Bank loans ; Subprime mortgage

MEASURING PRODUCTION EFFICIENCY USING AGGREGATE DATA

This paper develops a measure of efficiency when data have been aggregated. Unlike the most commonly used efficiency measures, our estimator handles the heteroskedasticity created by aggregation appropriately. Our estimator is compared to estimators currently used to measure school efficiency. Theoretical results are supported by a Monte Carlo experiment. Results show that for samples containing small schools (sample average may be about 100 students per school but sample includes several schools with about 30 students), the proposed aggregate data estimator performs better than the commonly used OLS and only slightly worse than the multilevel estimator. Thus, when school officials are unable to gather multilevel or disaggregate data, the aggregate data estimator proposed here should be used. When disaggregate data is available, standardizing the value-added estimator should be considered.Productivity Analysis,

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.Foreclosure

Spatial Differences of Land Use Change within Oklahoma's Wheat Belt

Farm Service Agency acreage data for the nine Oklahoma Agricultural Statistics Service districts is analyzed to determine the degree of price response in wheat acreage allocation decisions. Some critics have stated that land use after Freedom to Farm would change little, however these findings show acreage shifted greatly after the policy throughout the state.Land Economics/Use,

FEEDER CATTLE PRICE SLIDES

A theoretical model is developed to explain the economics of determining price slides for feeder cattle. The contract is viewed as a dynamic game with continuous strategies where the buyer and seller are the players. The model provides a solution for the price slide that guarantees an unbiased estimate of cattle weight. An empirical model using Superior Livestock Auction (SLA) data shows price slides used are smaller than those needed to cause the producer to give unbiased estimates of weight. Consistent with the model's predictions, producers slightly underestimate cattle weights.Demand and Price Analysis,

AIDS VERSUS ROTTERDAM: A COX NONNESTED TEST WITH PARAMETRIC BOOTSTRAP

A Cox nonnested test with parametric bootstrap is developed to select between the linearized version of the First Difference Almost Ideal Demand System (FDAIDS) and the Rotterdam model. The Cox test with parametric bootstrap is expected to be more powerful than the various orthodox tests used in past research. The new approach is then used for U. S. meat demand (beef, pork, and chicken) and compared to results obtained with an orthodox test. The orthodox test gives inconsistent results. In contrast, under the same varied conditions, the Cox test with parametric bootstrap consistently indicates that the Rotterdam model is preferred to the FDAIDS.Demand and Price Analysis,

AIDS VERSUS THE ROTTERDAM DEMAND SYSTEM: A COX TEST WITH PARAMETRIC BOOTSTRAP

A Cox test with parametric bootstrap is developed to select between the linearized version of the First-Difference Almost Ideal Demand System (FDAIDS) and the Rotterdam model. A Cox test with parametric bootstrap has been shown to be more powerful than encompassing tests like those used in past research. The bootstrap approach is used with U.S. meat demand (beef, pork, chicken, fish) and compared to results obtained with an encompassing test. The Cox test with parametric bootstrap consistently indicates the Rotterdam model is preferred to the FDAIDS, while the encompassing test sometimes fails to reject FDAIDS.Research Methods/ Statistical Methods,

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

USING BOTH SOCIOLOGICAL AND ECONOMIC INCENTIVES TO REDUCE MORAL HAZARD

Economists tend to focus on monetary incentives. In the model developed here, both sociological and economic incentives are used to diminish the apparent moral hazard problem existing in commodity grading. Training that promotes graders' response to sociological incentives is shown to increase expected benefits. The model suggests that this training be increased up to the point where the marginal benefit due to training equals its marginal cost. It may be more economical to influence the grader's behavior by creating cognitive dissonance through training and rules rather than by using economic incentives alone.Marketing,