A case for post-purchase support programs as part of Minnesota's emerging markets homeownership initiative

The State of Minnesota’s Emerging Markets Homeownership Initiative (EMHI) seeks to boost homeownership rates among Minnesota’s “emerging markets,” defined as households of color, non-English speaking households, and households in which English is a second language. Many of the implementation strategies in the EMHI Business Plan address general barriers to homeownership and should increase the number of emerging market households that become first-time homeowners. EMHI doesn’t stop there, however. It also recognizes the need to sustain homeownership after initial purchase, in keeping with growing evidence that the cliché “once an owner, always an owner” is far from true, especially for minority and low-income households. In particular, the EMHI Business Plan includes a strategy for developing and implementing a post-purchase services network that will enhance their prospects for successful, sustainable homeownership. As a foundation for the implementation effort, this report explains why Minnesota is in a good position to use post-purchase support programs to pursue EMHI’s goals.

Targeting foreclosure interventions: an analysis of neighborhood characteristics associated with high foreclosure rates in two Minnesota counties

This study examines the statistical association of foreclosure sales with social, economic and housing variables measured at the Census tract level for two purposes of interest to foreclosure mitigation practitioners —- to assess whether it is feasible to identify in advance neighborhoods likely to have high rates of foreclosure, and to explore the socioeconomic traits of high-foreclosure neighborhoods so as to design appropriate mitigation programs. We collected data on foreclosure sales in 2002 from the sheriff’s departments of Hennepin and Ramsey counties, the two core counties that comprise the Minneapolis-St. Paul MSA. We find that several factors commonly associated with high foreclosure sale rates could have correctly identified, in advance, most neighborhoods with high rates of mortgage foreclosure. To guide the design of foreclosure mitigation programs, we also present evidence that foreclosure risks in our two counties were highest in neighborhoods with elevated credit risk indicators and a high proportion of homeowners who are recent minority buyers or young. We show that an accurate credit risk variable is among the best predictors of foreclosure and also critically affects our multivariate analysis of factors associated with foreclosure. To limit social losses associated with foreclosures, we conclude that consideration should be given to enhancing public access to data on mortgages, foreclosures, and foreclosure risk factors, especially the neighborhood distribution of credit scores.

USING CALLING ACTIVITY TO PREDICT CALLING ACTIVITY: A CASE STUDY WITH THE ENDANGERED HOUSTON TOAD (BUFO [ANAXYRUS] HOUSTONENSIS)

Understanding anuran calling activity patterns is important for maximizing efficiency and value of call survey data collection and analyses. Previous studies have primarily focused on identifying and quantifying abiotic variables that influence anuran calling activity, and investigating relationships between calling activity and population estimates. In this study we investigated the use of a predictor pond approach to guide call survey effort. In this approach, calling activity at a subset of breeding sites (e.g., ponds) is used as a predictor of calling activity at additional breeding sites, with the goal being to minimize sampling effort while simultaneously maximizing sampling efficiency. We explored the efficiency of this approach using call survey data collected on the endangered Houston Toad (Bufo [Anaxyrus] houstonensis) at 15 known breeding ponds over 9 survey years. We found that if calling activity at 3 predictor ponds was used to decide if additional call surveys would occur at the remaining 12 ponds, we would have hypothetically correctly assumed calling activity was not occurring at non-predictor ponds on 92.1% of survey nights, and we would have hypothetically detected 93.9% of the total number of detected individuals over the 9 survey years. We found the predictor pond approach performed well in our case study, and believe it could be a valuable tool for many anuran monitoring programs

Reduction in size and unsteadiness of a VTOL ground vortex by ground fences

A ground vortex, produced when a jet impinges on the ground in the presence of cross flow, is encountered by V/STOL aircraft hovering near the ground and is known to be hazardous to the aircraft. The objective of this research was to identify a ground-based technique by which both the mean size and fluctuation in size of the ground vortex could be reduced. A simple passive method was identified and examined in the laboratory. Specifically, one or two fine wire mesh screens (ground fences) bent in a horseshoe shape and located on the ground in front of the jet impingement point proved to be very effective. The ground fences work by decreasing the momentum of the upstream-traveling wall jet, effectively causing a higher freestream-to-jet velocity ratio (V(sub infinity)/V(sub j)) and thus, a ground vortex smaller in size and unsteadiness. At(V(sub infinity)/V(sub j)) = 0.15, the addition of a single ground fence resulted in a 70 percent reduction in mean size of the ground vortex. With two ground fences, the mean size decreased by about 85 percent. Fluctuations in size decreased nearly in proportion to the mean size, for both the single and double fence configurations. These results were consistent over a wide range of jet Reynolds number (10(exp 4) less than Re(sub jet) less than 10(exp 5)); further development and full-scale Reynolds number testing are required, however, to determine if this technique can be made practical for the case of actual VTOL aircraft

Prediction Markets for Corporate Governance

Building on the success of prediction markets at forecasting political elections and other matters of public interest, firms have made increasing use of prediction markets to help make business decisions. This Article explores the implications of prediction markets for corporate governance. Prediction markets can increase the flow of information, encourage truth telling by internal and external firm monitors, and create incentives for agents to act in the interest of their principals. The markets can thus serve as potentially efficient alternatives to other approaches to providing information, such as the Sarbanes-Oxley Act’s internal controls provisions. Prediction markets can also produce an avenue for insiders to profit on and thus reveal inside information while maintaining a level playing field in the market for a firm’s securities. This creates a harmless way around existing insider trading laws, undercutting the argument for the repeal of these laws. In addition, prediction markets can reduce agency costs by providing direct assessments of corporate policies, thus serving as an alternative or complement to shareholder voting as a means of disciplining corporate boards and managers. Prediction markets may thus be particularly useful for issues where agency costs are greatest, such as executive compensation. Deployment of these markets, whether voluntarily or perhaps someday as a result of legal mandates, could improve alignment between shareholders and managers on these issues better than other proposed reforms. These markets might also displace the business judgment rule because they can furnish contemporaneous and relatively objective benchmarks for courts to evaluate business decisions

Variational Trajectory Optimization Tool Set: Technical description and user's manual

The algorithms that comprise the Variational Trajectory Optimization Tool Set (VTOTS) package are briefly described. The VTOTS is a software package for solving nonlinear constrained optimal control problems from a wide range of engineering and scientific disciplines. The VTOTS package was specifically designed to minimize the amount of user programming; in fact, for problems that may be expressed in terms of analytical functions, the user needs only to define the problem in terms of symbolic variables. This version of the VTOTS does not support tabular data; thus, problems must be expressed in terms of analytical functions. The VTOTS package consists of two methods for solving nonlinear optimal control problems: a time-domain finite-element algorithm and a multiple shooting algorithm. These two algorithms, under the VTOTS package, may be run independently or jointly. The finite-element algorithm generates approximate solutions, whereas the shooting algorithm provides a more accurate solution to the optimization problem. A user's manual, some examples with results, and a brief description of the individual subroutines are included