The development of a handbook for Nashua Junior High School students

Thesis (Ed.M.)--Boston Universit

Parameter estimation in softmax decision-making models with linear objective functions

With an eye towards human-centered automation, we contribute to the development of a systematic means to infer features of human decision-making from behavioral data. Motivated by the common use of softmax selection in models of human decision-making, we study the maximum likelihood parameter estimation problem for softmax decision-making models with linear objective functions. We present conditions under which the likelihood function is convex. These allow us to provide sufficient conditions for convergence of the resulting maximum likelihood estimator and to construct its asymptotic distribution. In the case of models with nonlinear objective functions, we show how the estimator can be applied by linearizing about a nominal parameter value. We apply the estimator to fit the stochastic UCL (Upper Credible Limit) model of human decision-making to human subject data. We show statistically significant differences in behavior across related, but distinct, tasks.Comment: In pres

Past, Present, and Future of Wetlands Credit Sales

In this paper we review the evolution of the wetlands credit sales program developed to support the federal wetlands permit program. Then, we explain how the regulatory rules governing the overall permit program, as well as specific rules governing credit sales, have prevented the development of robust markets in credit buying and selling. Based on this review, we identify an alternative institutional structure that would apply marketlike principles to expand the quantity of and lower the prices of credits while ensuring that wetlands credit sales help move the nation toward its goal: no net loss of wetlands acres and functions.wetlands mitigation, wetlands banking, environmental markets, Clean Water Act

Calculated risk : assessing nontraditional mortgage products

Mortgage loans

Satisficing in multi-armed bandit problems

Satisficing is a relaxation of maximizing and allows for less risky decision making in the face of uncertainty. We propose two sets of satisficing objectives for the multi-armed bandit problem, where the objective is to achieve reward-based decision-making performance above a given threshold. We show that these new problems are equivalent to various standard multi-armed bandit problems with maximizing objectives and use the equivalence to find bounds on performance. The different objectives can result in qualitatively different behavior; for example, agents explore their options continually in one case and only a finite number of times in another. For the case of Gaussian rewards we show an additional equivalence between the two sets of satisficing objectives that allows algorithms developed for one set to be applied to the other. We then develop variants of the Upper Credible Limit (UCL) algorithm that solve the problems with satisficing objectives and show that these modified UCL algorithms achieve efficient satisficing performance.Comment: To appear in IEEE Transactions on Automatic Contro

The Future of Wetlands Mitigation Banking

Environmental Economics and Policy, Resource /Energy Economics and Policy,

Credit cycle and adverse selection effects in consumer credit markets -- evidence from the HELOC market

The authors empirically study how the underlying riskiness of the pool of home equity line of credit originations is affected over the credit cycle. Drawing from the largest existing database of U.S. home equity lines of credit, they use county-level aggregates of these loans to estimate panel regressions on the characteristics of the borrowers and their loans, and competing risk hazard regressions on the outcomes of the loans. The authors show that when the expected unemployment risk of households increases, riskier households tend to borrow more. As a consequence, the pool of households that borrow on home equity lines of credit worsens along both observable and unobservable dimensions. This is an interesting example of a type of dynamic adverse selection that can worsen the risk characteristics of new lending, and suggests another avenue by which the precautionary demand for liquidity may affect borrowing.Home equity loans ; Risk