Casinos,casino size,and crime: A panel data analysis of Michigan counties

Growth in legal gaming in the United States over the past quarter century or so is well-documented. One important factor fueling this growth was the passage of the Indian Gaming Regulatory Act of 1988, which permitted Native American tribes to establish, under agreements or “compacts” with the states in which they are located, casinos offering what is known as Class III gaming: slot machines, blackjack, roulette, and other games. Since the passage of the Act, there have been 21 Native American casinos established in Michigan. Also, three non-Native American casinos opened in Detroit in 1999 and 2000. This growth in the number of casinos has sparked a wide-ranging debate over the social and economic impacts of casino development.The purpose of this research is to focus on the crime issue in the broader casino debate. We investigate the impact of these Michigan casinos on the rates of burglary, robbery, larceny and motor vehicle theft (property crimes) in casino host counties as well as in nearby counties. We employ a panel data set with annual observations on all 83 Michigan counties for the period 1994–2010. The dataset includes crime rates taken from the FBI crime data series, variables for the presence of a casino in a county or in a nearby county, the scale of a casino's operations as measured by revenues, and a variety of control variables suggested by the broader literature investigating the factors that determine crime rates generally.Our results suggest that in most cases the property crime rates studied are not affected by the presence or size of a casino in a county or in a nearby county. The largest such impact, which is negative, is for motor vehicle theft. The size of a casino does have a small positive effect on the motor vehicle theft rate.     

COMMENT ON "THE IRREDUCIBLE ROLE OF DERIVED MARGINAL UTILITY IN DYNAMIC STOCHASTIC PROGRAMMING"

This comment shows why the Lagrange method can be simpler than dynamic programming in solving dynamic optimization problems.     

Socioeconomic predictors of forest use values in the Peruvian Amazon: A potential tool for biodiversity conservation

Conservation is a crisis discipline requiring rapid action with limited funds. This study examines the potential of socioeconomic variables to predict forest use values. If natural resource use can be predicted from socioeconomic data, conservation planners could rapidly identify and focus conservation programs on the sectors of local populations that most intensively utilize local flora and fauna. Families in three communities in the northern Peruvian Amazon were surveyed over a 6-month period. Data were collected on use of flora and fauna from six locally determined use categories (food, medicine and poisons, wood, weavings, adornments, and “other”) in forest types of three age classes (fallow fields—very young forests, young secondary forests, and old secondary forests). Forest use values were the dependant variables calculated in $/ha/year. Socioeconomic variables included: age, education, family size, residence time, land worked, land owned, number of fishing nets, chickens, pigs, cows, and/or mules owned (all proxies for productive assets), and level of ecological knowledge (ability of informants to correctly identify forest species and answer basic questions about their biology). Ordinary least square multiple regressions were run independently for each forest type. Regressions were also run separately for the two most valuable use categories, food and wood. Low R² adjusted values (all < 0.3) reflect the difficulty in predicting human behavior due to confounding variables and complex interactions. Residence time and a household's community of residence were the most significant predictors of forest use values. Households in Vista Alegre, the community with the highest density of people and smallest landholdings per household, extracted the highest value of forest products per hectare. The longer a family stayed in any community the higher the value of forest goods they extracted. If families that lived in an area longest are the most intensive extractors of forest products, they should be a major focus for conservation programming. In addition, the higher value of products extracted from forests by some families may make them more open to strategies seeking to protect long-term viability of the resources they utilize. The importance of residence time also indicates that planners need to account for changes in the resource use patterns of stakeholders over time.     

Are the new rules relating to disclosures of derivative financial instruments workable?

Accounting for derivatives has created uncertainties for preparers, auditors, regulators, and users of financial statements alike. The complexity and variety of instruments as well as hedging and risk management techniques make derivatives reporting a difficult subject. Developing consistent accounting rules in this area is made even more challenging since derivatives are used in conjunction with assets and liabilities that, under the current accounting system, may be carried at historical cost, fair value, or some hybrid of fair value and historical cost. Further, derivatives are used in connection with portfolios of items as well as with economic assets and exposures that may not be recorded in financial statements under the current model.     

Rates of Return to Schooling in China

This study uses data from a 1988 survey of Chinese individuals to estimate rates of return to schooling in China. The Mincer-type rate of return to schooling was estimated at 4.02 percent in the rural areas and 3.29 percent in the urban areas; these are fairly low estimates compared with similar estimates in other countries. The rate of return to schooling for females was significantly higher than that for males in urban areas. In addition, members of the Communist Party in urban areas had significantly lower returns to schooling compared with non-members.     

DISCOUNT RATES AND ENERGY EFFICIENCY

Empirical studies provide compelling evidence that economic agents do not adopt the complete range of energy-efficient technologies that are cost-effective under prevailing prices and market conditions. Analysts commonly attribute this anomaly to the use of high discount rates in energy-related decisions-an interpretation that is difficult to reconcile with standard models of rational choice. This paper recasts the controversy from the perspective of economic theory and finds that market failures related to asymmetric information, bounded rationality, and transaction costs are major contributors to the so-called "efficiency gap."     

The impact of public investment in medical imaging technology: an interagency collaboration in evaluation

The Canada Foundation for Innovation (CFI) and the Canadian Institutes of Health Research (CIHR) allied to analyze the impact of their investments in medical imaging research. The CFI funds capital and operating programs for research infrastructure, and CIHR's mandate concentrates its funding on research activity. It happens that CIHR-funded research consumes CFI-funded infrastructure as an input in the innovation process. Apart from a few partnered programs, by design there is no coordination between CFI and CIHR funding decisions. Together, these agencies invested $916 million over a 14-year-period. In this paper, we evaluate the economic and health benefits from advancements in one funded area, namely computed tomography perfusion (CTP). CTP is an imaging technique that uses computed tomography to measure blood flow in organs and tissues. It is mostly used to assess acute ischemic stroke. The net social benefits attributable to these investments are substantially positive: the benefit-to-cost ratio is estimated to be between 6.66-to-1 and 9.99-to-1. We review how public investments from multiple funders comingle in the innovation process to deliver social value and improved health outcomes.     

Housing Prices in Urban China as Determined by Demand and Supply

This paper studies the demand for and supply of residential housing in urban China since the late 1980s when the urban housing market became commercialized. Using aggregated annual data from 1987 to 2012 in a simultaneous equations framework we show that the rapid increase in the urban residential housing price can be well explained by the forces of demand and supply, with income determining demand and cost of construction affecting supply. We find the income elasticity of demand for urban housing to be approximately 1, the price elasticity of demand to be approximately ?1.1 and the price elasticity of supply of the total housing stock to be approximately 0.5. The resulting long‐run effect of income on urban housing prices in elasticity terms is approximately 0.7, because the increase in income has shifted the demand curve outward more rapidly than the supply curve.