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Social and Behavioral Sciences Commons™
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Articles 1 - 5 of 5
Full-Text Articles in Social and Behavioral Sciences
Smart Sentencing Guidelines: The Effect Of Marginal Policy Changes On Recidivism, Sarah M. Estelle, David C. Phillips
Smart Sentencing Guidelines: The Effect Of Marginal Policy Changes On Recidivism, Sarah M. Estelle, David C. Phillips
Faculty Publications
Public appeals regarding criminal justice have shifted somewhat from “tough on crime” to “smart justice” that is more lenient when tradeoffs merit it. Among other considerations, smart sentencing policy depends on how sentence severity affects recidivism. Using administrative data on two common non-violent felonies committed by adults in Michigan, we measure the effect of sentences on offenders' future criminal activity. Discontinuities in the legislative guidelines that constrain sentences chosen by Michigan judges provide exogenous variation in sentence severity. Harsher sentences generated by sentencing guidelines significantly reduce recidivism by felony shoplifters but not repeat drunk drivers. Recidivism falls most for young, …
Social Entrepreneurship In China: Driving Institutional Change, Tonia Warnecke
Social Entrepreneurship In China: Driving Institutional Change, Tonia Warnecke
Faculty Publications
In the aftermath of the Great Recession, the concern with exclusionary and unethical business practices has led to the growing popularity of social entrepreneurship, which focuses on the creation of social value, not wealth. In this article, I reflect on social entrepreneurship in China, a unique context given the strong Communist party leadership and the transition to a market economy. To begin, I discuss the legal and political framework for social entrepreneurship in China, followed by an overview of the sector’s characteristics, including age, size, social issues emphasized, leader characteristics, and the role of women. Next, I provide examples of …
Factors Influencing Corn Fungicide Treatment Decisions, Alicia Rosburg, Luisa Menapace
Factors Influencing Corn Fungicide Treatment Decisions, Alicia Rosburg, Luisa Menapace
Faculty Publications
Fungal disease management in U.S. corn production has undergone a major shift in the last 2 decades. The decision to apply fungicide, a management practice that was once rarely considered, is now contemplated annually by many U.S. corn producers. We investigate potential factors underlying the fungicide treatment decision. We use economics, agronomy, and plant pathology literature to develop a conceptual model of the fungicide treatment decision and test the model using a survey of Midwest corn producers. We find the treatment decision is positively related to perceived economic gains, but heuristic factors also have a strong influence.
Country And Industry-Level Performance Of Nasdaq-Listed European And Asia Pacific Adrs, Mark Schaub
Country And Industry-Level Performance Of Nasdaq-Listed European And Asia Pacific Adrs, Mark Schaub
Faculty Publications
This study examines the 3-year performance of NASDAQ-Listed Asia Pacific and European ADRs versus the NASDAQ Index and their respective regional indexes from 1990-2010. Country specific performance results show ADRs from China, Japan and Ireland performed best versus the US and regional benchmarks. Industry-level results show the best industry performers were in the Technology Hardware & Services industry and in Energy companies.
On Using Interval Response Data In Experimental Economics, James Mcdonald, Olga B. Stoddard, Daniel Walton
On Using Interval Response Data In Experimental Economics, James Mcdonald, Olga B. Stoddard, Daniel Walton
Faculty Publications
Many empirical applications in the experimental economics literature involve interval response data. Various methods have been considered to treat this type of data. One approach assumes that the data correspond to the interval midpoint and then utilizes ordinary least squares to estimate the model. Another approach is to use maximum likelihood estimation, assuming that the underlying variable of interest is normally distributed. In the case of distributional misspecification, these estimation approaches can yield inconsistent estimators. In this paper, we explore a method that can help reduce the misspecification problem by assuming a distribution that can model a wide variety of …