The Varying Effects of Predatory Lending Laws on High-Cost Mortgage Applications

Federal, state, and local predatory lending laws are designed to restrict and in some cases prohibit certain types of high-cost mortgage credit in the subprime market. Empirical evidence using the spatial variation in these laws shows that the aggregate flow of high-cost mortgage credit can increase, decrease, or be unchanged after these laws are enacted. Although it may seem counterintuitive to find that a law that prohibits lending could be associated with more lending, it is hypothesized that a law may reduce the cost of sorting honest loans from dishonest loans and lessen borrowers’ fears of predation, thus stimulating the high-cost mortgage market

The Infosys TIMES, Vol. 5, No. 2

Sagar Bhandari Wins Best Market Potential App Award SCSU Students Win Scholarships Worth Over $144,000 SAP TERP10 Open Web Application Security Project (OWASP) Club Updates IS Club, CSIA Club New Faculty, Anthony Kunkel InfoSys Diaries, Craig Overboe, Abraham Sesay, Swapnika Putta, Paul M. Voeltz, Ouede J. Louan Growing Demand For IS Tutoring Alumni Updates, Khalid Noor, Rosthan Ngomssi Student Faculty Staff Celebration Social Media Engagemen

How High Is Too High? Implications of High-Deductible Health Plans

Assesses high deductible health plans, and the likelihood that they would have a substantial effect on either health costs or coverage. Suggests legislative modifications to protect lower wage adults and ensure access to early preventive and primary care

Learning to play 3 x 3 games : neural networks as bounded-rational players

We present a neural network methodology for learning game-playing rules in general. Existing research suggests learning to find a Nash equilibrium in a new game is too difficult a task for a neural network, but says little about what it will do instead. We observe that a neural network trained to find Nash equilibria in a known subset of games, will use self-taught rules developed endogenously when facing new games. These rules are close to payoff dominance and its best response. Our findings are consistent with existing experimental results, both in terms of subject's methodology and success rates

Stability of sinusoidal responses of marginally stable bandpass sigma delta modulators

In this paper, we analyze the stability of the sinusoidal responses of second order interpolative marginally stable bandpass sigma delta modulators (SDMs) with the sum of the numerator and denominator polynomials equal to one and explore new results on the more general second order interpolative marginally stable bandpass SDMs. These results can be further extended to the high order interpolative marginally stable bandpass SDMs

The variation of invariant graphs in forced systems

In skew-product systems with contractive factors, all orbits asymptotically approach the graph of the so-called sync function; hence, the corresponding regularity properties primarily matter. In the literature, sync function Lipschitz continuity and differentiability have been proved to hold depending on the derivative of the base reciprocal, if not on its Lyapunov exponent. However, forcing topological features can also impact the sync function regularity. Here, we estimate the total variation of sync functions generated by one-dimensional Markov maps. A sharp condition for bounded variation is obtained depending on parameters, that involves the Markov map topological entropy. The results are illustrated with examples