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The purpose of the chapter is to test the hypothesis that food safety (chemical) standards act as barriers to international seafood imports. We use zero-accounting gravity models to test the hypothesis that food safety (chemical) standards act as barriers to international seafood imports. The chemical standards on which we focus include chloramphenicol required performance limit, oxytetracycline maximum residue limit, fluoro-quinolones maximum residue limit, and dichlorodiphenyltrichloroethane (DDT) pesticide residue limit. The study focuses on the three most important seafood markets: the European Union’s 15 members, Japan, and North America.Our empirical results confirm the hypothesis and are robust to the OLS as well as alternative zero-accounting gravity models such as the Heckman estimation and the Poisson family regressions. For the choice of the best model specification to account for zero trade and heteroskedastic issues, it is inconclusive to base on formal statistical tests; however, the Heckman sample selection and zero-inflated negative binomial (ZINB) models provide the most reliable parameter estimates based on the statistical tests, magnitude of coefficients, economic implications, and the literature findings. Our findings suggest that continually tightening of seafood safety standards has had a negative impact on exporting countries. Increasing the stringency of regulations by reducing analytical limits or maximum residue limits in seafood in developed countries has negative impacts on their bilateral seafood imports. The chapter furthers the literature on food safety standards on international trade. We show competing gravity model specifications and provide additional evidence that no one gravity model is superior.

This chapter examines the evolution of the number of days spent on sick leave following the 2011 reform which halved the maximum sick benefit provided by statutory health insurance in Hungary. This policy change sharply decreased benefits for a large group of high earners, while leaving the incentive to claim sickness benefits unchanged for lower earners, providing us with a “quasi-experimental” setup to identify the incentives effect of sickness benefits. We use a difference-in-differences type methodology to evaluate the short-term effect of the reform. We rely on high-quality administrative data and analyze a sample comprised of prime-age male employees with high earnings and stable employment. Our results show that the number of days spent on sick leave fell substantially for those experiencing the full halving of benefits. Estimating the response of the number of sick days with respect to the fall in potential sickness benefits, we find a significant elasticity of −0.45.

With the rise of employer-promulgated mandatory employment arbitration, scholars have become concerned that these policies may reduce the economic viability of lower value employment claims. Of particular worry are claims made under the Fair Labor Standards Act since the FLSA does not include punitive damages. This study empirically tests the relationship between 368 Fortune 1000 companies’ employment arbitration policies and their wage and hour violations discovered during the Department of Labor inspections. Surprisingly, firms that used arbitration were found to have fewer violations and lower back wages for those violation compared to firms that did not use arbitration. This suggests that viewing arbitration merely as a cost-reduction tool may cast the practice too narrowly and instead it may be part of a larger conflict management system that seeks to address conflict at the earliest possible stage.

Measuring the diffusion of protests, or more generally, the diffusion of events, is an ongoing task in social sciences. This paper proposes an inter-event approach to study what types of protests tend to diffuse or decline. We develop a standardized, five-step procedure to measure what we define as “event diffusion momentum” (EDM): (1) employ event-based data containing information on the time, location, and features of each protest; (2) define the temporal and spatial ranges of interest; (3) for each observation, count the number of events before and after it within the defined ranges; (4) predict the numbers of post-event and pre-event protests with appropriate count models; (5) calculate the ratios of predicted values for each predictor and confidence intervals using the delta method. The ratio is the EDM. Applying this method to Dynamics of Collective Action (DoCA) data, we identify several micro- and macro-level factors associated with protest diffusion in the United States, 1960–1995. We conclude with the implications and generalizability of the proposed method.

Purpose – This chapter provides an overview of issues related to analysing crash data characterised by excess zero responses and/or long tails and how to overcome these problems. Factors affecting excess zeros and/or long tails are discussed, as well as how they can bias the results when traditional distributions or models are used. Recently introduced multi-parameter distributions and models developed specifically for such datasets are described. The chapter is intended to guide readers on how to properly analyse crash datasets with excess zeros and long or heavy tails.

Methodology – Key references from the literature are summarised and discussed, and two examples detailing how multi-parameter distributions and models compare with the negative binomial distribution and model are presented.

Findings – In the event that the characteristics of the crash dataset cannot be changed or modified, recently introduced multi-parameter distributions and models can be used efficiently to analyse datasets characterised by excess zero responses and/or long tails. They offer a simpler way to interpret the relationship between crashes and explanatory variables, while providing better statistical performance in terms of goodness-of-fit and predictive capabilities.

Research implications – Multi-parameter models are expected to become the next series of traditional distributions and models. The research on these models is still ongoing.

Practical implications – With the advancement of computing power and Bayesian simulation methods, multi-parameter models can now be easily coded and applied to analyse crash datasets characterised by excess zero responses and/or long tails.

In this paper, we seek to understand how changes in product architecture affect the innovation performance of firms in a complex product ecosystem. The canonical view in the literature is that changes in the technological dependencies between components, which define a product’s architecture, undermine the innovation efforts of incumbent firms because their product development efforts are built around existing architectures. We extend this prevailing view in arguing that component dependencies and changes in them affect firm innovation efforts via two principal mechanisms. First, component dependencies expand or constrain the choice set of firm component innovation efforts. From the perspective of any one component in a complex product (which we label the focal component), an increase in the flow of design information to the focal component from other (non-focal) components simultaneously increases the constraint on focal component firms in their choice of profitable R&D projects while decreasing the constraint on non-focal component firms. Second, asymmetries in component dependencies can confer disproportionate influence on some component firms in setting and dictating the trajectory of progress in the overall system. Increases in such asymmetric influence allow component firms to expand their innovation output. Using historical patenting data in the personal computer ecosystem, we develop fine-grained measures of interdependence between component technologies and changes in them over time. We find strong support for the empirical implications of our theory.

A varying number of work hours from week to week creates considerable hardships for workers and their families, like volatile earnings and work–family conflict. Yet little empirical work has focused on racial/ethnic differences in varying work hours, which may have increased substantially in the Great Recession of the late 2000s. We extend literatures on racial/ethnic stratification in recessions and occupational segregation to this topic. Analyses of the Survey of Income and Program Participation show varying weekly hours became significantly more common for White and Black, but especially Latino workers in the late 2000s. The growth of varying weekly hours among White and Latino workers was greatest in predominantly minority occupations. However, the growth among Black workers was greatest in predominantly White occupations. The chapter discusses implications for disparities in varying hours and the salience of occupational composition beyond earnings.

The race concordance hypothesis suggests that matching patients and health providers on the basis of race improves communication and patients’ perceptions of health care, and by extension, encourages patients to seek and utilize health care, which may reduce health disparities. However, relatively few studies have examined the impact of race concordance on the utilization of health services. This chapter is grounded on Andersen’s Emerging Model of Health Services Utilization (Phase 4) and extends that model to include race concordance.

The data were collected from a stratified random sample of adult beneficiaries enrolled in North Carolina Medicaid’s primary care case management delivery system in 2006–2007. Propensity score matching techniques were used to sort respondents on their propensity for race concordance and indices were constructed to generate key control variables. Poisson regression was used to examine the impact of race concordance on the utilization of primary care and emergency room care, under the assumption that race concordance would increase the use of primary care and decrease the use of emergency care for minority patients.

While blacks (compared to whites) used less primary care and had more emergency care visits, race concordance was not a statistically significant predictor of either primary care or emergency room use. However, patients’ satisfaction with their primary care providers was associated with significantly fewer primary care and emergency care visits while trust in one’s provider was associated with more primary care visits.

The study findings suggest that the central premises of the race concordance hypothesis require further study to confirm the assumption that better patient – primary care provider relationships result in less utilization of more costly and resource-intensive forms of health care.

The study makes a valuable contribution by expanding the relatively small body of literature dedicated to exploring the impact of race concordance on health services utilization. Additionally, by virtue of researching the experience of Medicaid enrollees, the study controls for health insurance status.

We distinguish between two forms of local banks that build and maintain legitimacy in different ways: branches and unit banks. Branches gain legitimacy through the parent organization. Unit banks gain legitimacy through the personal reputation and social connections of the founders. Given the different ways in which legitimacy is built by these organizational forms, we think that the rural or urban nature of the community is likely to affect the founding rates of these two forms differently. Rural communities, in which personal and family relationships play an important role in both social and economic life, provide advantages to well-connected founders of unit banks. In these communities social networks serve as a demand buffer for unit banks, making the founding rate of this organizational form less sensitive to fluctuations in the demand for banking services in rural versus urban communities. In contrast, the founding rate of branches may not be greatly affected by the community context because branches gain legitimacy through a sponsoring organization whose legitimating characteristics are not local. Empirical analyses of foundings of local banks between 1976 and 1988 support these predictions. Supplemental empirical analyses also show no evidence of such buffering effect for unit retail establishments, which are expected to be less central in the social networks of rural communities than unit banks. Our results suggest that community organization channels resources to some kinds of organizations at the expense of others and that organizational research in general and organizational ecology in particular will benefit by paying more attention to community context.

A growing literature links oil to conflict, particularly civil war. Greed/opportunity, grievance, and weak state arguments have been advanced to explain this relationship. This chapter builds on the literature on oil and conflict in two important ways. First, I examine a novel dependent variable, domestic terrorism. Much is known about the effect of oil on the onset, duration, and intensity of civil war, though we know surprisingly little about the potential influence of oil on smaller, more frequent forms of violence. Second, I treat oil ownership as a variable, not a constant, coding oil rents based on ownership structure. This is contrary to other related studies that assume oil is necessarily owned by the state. Using a large, cross-national sample of states from 1971 to 2007, several key findings emerge. Notably, publicly owned oil exhibits a positive effect on domestic terrorism. This positive effect dissipates, however, when political performance and state terror are controlled for. Privately owned oil, on the other hand, does not correlate with increased incidences of terror. This suggests that oil is not a curse, per se.