Learning about Education

Limited human capital investment is a common characteristic of low-income countries despite the fact that estimated returns to educational investment in low-income countries are generally higher than in high-income countries. Empirical evidence suggests that income and credit constraints can only account for a small part of this underinvestment. Recent experimental evidence shows that families' misperceptions about the returns to education play a large role in their low investment levels. This paper builds a model of human capital and growth that incorporates an adaptive learning mechanism to capture the way agents form perceptions about returns to education. In an economy where human capital investments have both private and public returns, we find multiple learnable equilibria, including those which are characterized by low investment and low returns. We also find that even when the rational equilibrium corresponds to a high level of human capital investment, the learning mechanism, influenced by the agents' priors and cultural bias, may impart low human capital investment for extended periods. Policies that can speed up the learning process are examined and it is found that faster rates of growth can be achieved through interventions.growth, education, learning

Are Microloans Bad for Growth?

This paper constructs a two-period overlapping generations model of human capital investment decisions where a microloan program designed to finance entrepreneurial activities is active. It is shown that, in the presence of human capital externalities (social returns to education) there exists a range of microloan amounts that are growth depressing and welfare decreasing through their affect on the opportunity cost of schooling. By increasing the opportunity cost of schooling, microloans divert investment away from human capital: by failing to internalize the social returns to education, households’ individually optimal investment decisions in the face of microcredit availability act to depress the growth of the economy and result in sub-optimal welfare outcomes.microloans, growth, human capital

Medical Concerns About Physician-Assisted Suicide

The November 8, 1994 passage of Oregon\u27s Measure 16, which permits physicians to comply with the request of a competent adult patient with less than six months to live for a prescription for lethal drugs, has intensified the debate over the legalization of physician-assisted suicide following the defeats of similar initiatives in Washington and California. Subsequent legal challenge to Measure 16 and the present preliminary injunction3 has shown that passage and popularity of a public initiative does not ensure its legality. The issue of physician-assisted suicide is most likely headed for the United States Supreme Court. This Article is intended, however, to review the medical concerns of the legalization of physician-assisted suicide and its potential impact on physicians and patients. The issue merits careful study not simply because of the unique concerns of legalized euthanasia, but also because of its critical relationship to physicians and their care of dying patients

Medical Concerns About Physician-Assisted Suicide

The November 8, 1994 passage of Oregon\u27s Measure 16, which permits physicians to comply with the request of a competent adult patient with less than six months to live for a prescription for lethal drugs, has intensified the debate over the legalization of physician-assisted suicide following the defeats of similar initiatives in Washington and California. Subsequent legal challenge to Measure 16 and the present preliminary injunction3 has shown that passage and popularity of a public initiative does not ensure its legality. The issue of physician-assisted suicide is most likely headed for the United States Supreme Court. This Article is intended, however, to review the medical concerns of the legalization of physician-assisted suicide and its potential impact on physicians and patients. The issue merits careful study not simply because of the unique concerns of legalized euthanasia, but also because of its critical relationship to physicians and their care of dying patients

Learning about education

Limited human capital investment is a common characteristic of low-income countries despite the fact that estimated returns to educational investment in low-income countries are generally higher than in high-income countries. Empirical evidence suggests that income and credit constraints can only account for a small part of this underinvestment. Recent experimental evidence shows that families' misperceptions about the returns to education play a large role in their low investment levels. This paper builds a model of human capital and growth that incorporates an adaptive learning mechanism to capture the way agents form perceptions about returns to education. In an economy where human capital investments have both private and public returns, we find multiple learnable equilibria, including those which are characterized by low investment and low returns. We also find that even when the rational equilibrium corresponds to a high level of human capital investment, the learning mechanism, influenced by the agents' priors and cultural bias, may impart low human capital investment for extended periods. Policies that can speed up the learning process are examined and it is found that faster rates of growth can be achieved through interventions

Are microloans bad for growth?

This paper constructs a two-period overlapping generations model of human capital investment decisions where a microloan program designed to finance entrepreneurial activities is active. It is shown that, in the presence of human capital externalities (social returns to education) there exists a range of microloan amounts that are growth depressing and welfare decreasing through their affect on the opportunity cost of schooling. By increasing the opportunity cost of schooling, microloans divert investment away from human capital: by failing to internalize the social returns to education, households' individually optimal investment decisions in the face of microcredit availability act to depress the growth of the economy and result in sub-optimal welfare outcomes

Trace-Driven Simulation for Energy Consumption in High Throughput Computing Systems

High Throughput Computing (HTC) is a powerful paradigm allowing vast quantities of independent work to be performed simultaneously. However, until recently little evaluation has been performed on the energy impact of HTC. Many organisations now seek to minimise energy consumption across their IT infrastructure though it is unclear how this will affect the usability of HTC systems. We present here HTC-Sim, a simulation system which allows the evaluation of different energy reduction policies across an HTC system comprising a collection of computational resources dedicated to HTC work and resources provided through cycle scavenging -- a Desktop Grid. We demonstrate that our simulation software scales linearly with increasing HTC workload

Lincoln at Gettysburg

This is an envelope enclosing four photograph reproductions. Produced for Eastern National Park & Monument Association. It’s front features a photograph image of President Abraham Lincoln. Its verso contains information about each photograph.https://scholarsjunction.msstate.edu/fvw-artifacts/5776/thumbnail.jp

Reducing the number of miscreant tasks executions in a multi-use cluster.

Exploiting computational resources within an organisation for more than their primary task offers great benefits – making better use of capital expenditure and provides a pool of computational power. This can be achieved through the deployment of a cycle stealing distributed system, where tasks execute during the idle time on computers. However, if a task has not completed when a computer returns to its primary function the task will be preempted, wasting time (and energy), and is often reallocated to a new resource in an attempt to complete. This becomes exacerbated when tasks are incapable of completing due to excessive execution time or faulty hardware / software, leading to a situation where tasks are perpetually reallocated between computers – wasting time and energy. In this work we investigate techniques to increase the chance of ‘good’ tasks completing whilst curtailing the execution of ‘bad’ tasks. We demonstrate, through simulation, that we could have reduce the energy consumption of our cycle stealing system by approximately 50%