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This study contributes to the understanding of the health effects of pesticides exposure and of how pesticides have been and should be regulated.

This study presents literature reviews for the period 2000–2013 on (i) the health effects of pesticides and on (ii) preference valuation of health risks related to pesticides, as well as a discussion of the role of benefit-cost analysis applied to pesticide regulatory measures.

This study indicates that the health literature has focused on individuals with direct exposure to pesticides, i.e. farmers, while the literature on preference valuation has focused on those with indirect exposure, i.e. consumers. The discussion highlights the need to clarify the rationale for regulating pesticides, the role of risk perceptions in benefit-cost analysis, and the importance of inter-disciplinary research in this area.

This study relates findings of different disciplines (health, economics, public policy) regarding pesticides, and identifies gaps for future research.

This chapter revisits the Hausman (1978) test for panel data. It emphasizes that it is a general specification test and that rejection of the null signals misspecification and is not an endorsement of the fixed effects estimator as is done in practice. Non-rejection of the null provides support for the random effects estimator which is efficient under the null. The chapter offers practical tips on what to do in case the null is rejected including checking for endogeneity of the regressors, misspecified dynamics, and applying a nonparametric Hausman test, see Amini, Delgado, Henderson, and Parmeter (2012, chapter 16). Alternatively, for the fixed effects die hard, the chapter suggests testing the fixed effects restrictions before adopting this estimator. The chapter also recommends a pretest estimator that is based on an additional Hausman test based on the difference between the Hausman and Taylor estimator and the fixed effects estimator.

The purpose of this study is to assess the ability of a theoretically motivated statistical model to accurately forecast annual, national counts of terror attacks out-of-sample.

Bayesian multi-level models, classification analysis, marginal calibration plots

We find that the model forecasts reasonably well, but conclude that its overall performance suggests that it is not ready for use in policy planning. This is likely due to the coarse temporal and spatial aggregation of the data.

The implications of this study are that social scientists should devote more effort into evaluating the predictive power of their statistical models, and that annual, national data on violent conflict are probably too coarse to provide useful information for policy planning.

The primary value of our modeling effort is to provide a baseline against which to evaluate the performance of more region- and country-specific models to be developed in the future.

The purpose of this chapter is to explore the intersection of identity, culture, and consumption as it relates to multiracial identity development.

The authors employed a phenomenological approach wherein 21 multiracial women were interviewed to understanding the lived experience and meaning of multiracial identity development.

Findings of this study indicate that multiracial consumers engage with the marketplace to assuage racial discordance and legitimize the liminal space they occupy.

While there is much research related to the variety of ways marketing and consumption practices intersect with identity (re)formation, researchers have focused much of their attention on monoracial populations. This research identifies and fills a gap in the literature related to how multiple racial backgrounds complicate this understanding.

Due to their growing social visibility and recognized buying power, multiracial individuals have emerged as a viable consumer segment among marketers. However, there is a dearth of research examining how multiracial populations experience the marketplace.

This study provides a better understanding of the ways in which multiracial individuals utilize consumption practices as a means of developing and expressing their racial identity.

This chapter examines how public attitudes and judgments about tax fairness reflect distributive justice rules about proportionality/contributions, needs, and equality; fairness issues that influence voluntary tax compliance (Hofmann, Hoelzl, & Kirchler, 2008; Spicer & Lundstedt, 1976). Most public polls and some prior research indicate the general public considers progressive income tax rates as fairer than flat tax rates, a reflection of the Needs rule of distributive justice theory; our 1,138 participants respond similarly. However, two-thirds of our politically representative sample of the American public actually assign “fair shares” of income taxes consistently with fairness-as-proportionality above an exempt amount of income, consistent with the Contributions rule of Equity Theory. We argue experimental assignments of fair shares of income taxes can best be understood as a combination of the Needs rule, applied by exempting incomes below the poverty line from income taxation (via current standard deductions) and taxing incomes above this exempt amount at a single tax rate (i.e., a flat-rate tax) consistent with the Proportionality/Contributions rule. Viewed in combination, these two distributive justice rules explain the tax fairness judgments of 89% of our sample and indicate surprising general agreement about what constitutes a fair share of income taxes that should be paid by US citizens from the 5th percentile to the 95th percentile of the income distribution. The joint application of these fairness rules indicates how seemingly competing, partisan distributive justice concerns can inform our understanding of social attitudes about tax fairness across income classes.