USING THE PARETO DISTRIBUTION TO IMPROVE ESTIMATES OF TOPCODED EARNINGS

Inconsistent censoring in the public‐use March Current Population Survey (CPS) limits its usefulness in measuring labor earnings trends, as previous approaches for imputing topcoded earnings systematically understate top earnings. Using Pareto estimation methods with less‐censored internal data, we create an enhanced cell‐mean series to capture top earnings in the public‐use data. Annual earnings inequality trends since 1963 using our series largely mirror those found by Kopczuk, Saez, and Song using social security administration data for commerce and industry workers. When we extend our analysis to 2013 and consider all workers, earnings inequality levels are higher but its growth is more modest. (JEL C81, D31, J01)     

Predictive Hierarchic Modeling of Operational Characteristics in Clinical Trials

An analytic methodology for patient enrollment modeling using a Poisson-gamma model is developed by Anisimov & Fedorov (2005–2007). For modeling hierarchic processes associated with enrollment, a new methodology using evolving stochastic processes is proposed. This provides rather general and unified framework to describe various operational processes associated with enrollment. The technique for calculating predictive distributions, mean, and credibility bounds for evolving processes is developed. Some applications to modeling operational characteristics in clinical trials are considered with focus to modeling events associated with incoming and follow-up patients in different settings. For these models, predictive characteristics are derived in a closed form.     

Social Entrepreneur: Same or Different from the Rest?

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - A social business responds to social problems usually ignored by institutions, mobilizing resources and generating...     

The racialized patterns of police violence: The critical importance of research as praxis

The tragic killing of George Floyd at the hands of the police resulted in hundreds of thousands of protestors marching in the streets demanding change. The call for change criticized the killing of Blacks by law enforcement and challenged White supremacy as an institution of social control and racial violence. A key component of the marches and protests was a message to the residents of the United States: “Black Lives Matter.” As society grapples with a reckoning, researchers studying police violence for the past 6 decades have been empirically and theoretically debating the reasons why use of force by law enforcement continues to have a higher proportion of Black and Brown victims compared to Whites. Although the research on fatal police killings was studied by only a small number of individuals prior to 2014, after the killing of Michael Brown in Ferguson, Missouri the research in different areas of the country increased rapidly as did the forms of analysis and research disciplines making their own contributions. The Washington Post and Guardian news agencies established that deaths at the hands of the police were occurring for at least 900 to 1100 individual deaths per year for which firearms resulted in the greatest cause of death. As US government agencies failed to produce a national data source on police involved killings, the media took a leading role in providing greater national understanding. The authors examine what role academic researchers contribute to the discussion for solutions, particularly those from marginalized backgrounds. As protestors march, lawyers sue and defend, and politicians create new forms of legislation, researchers need to play a more important role initiating critical studies, making sense of the data, and providing a theoretical framework for which police violence can be understood. This article will provide an overview of the literature on racialized police violence, point out key patterns involving racial and ethnic disparities, and emphasize how researchers can play a more important role in advocating for change.     

Analysis of California propositions: An experiment in the empirical revelation of shared mental models

This paper uses factor analysis to analyze Californians’ voting on 12 propositions considered during the 2008 general election. The result is to create quantitative representations of shared mental models. After generating two county-level shared mental model indices, the indices are further examined to explain their variation across counties and to evaluated their performance as substitutes for previous presidential voting as an independent variable in a presidential voting model.     

Campylobacter QMRA: A Bayesian Estimation of Prevalence and Concentration in Retail Foods Under Clustering and Heavy Censoring

A Bayesian statistical temporal‐prevalence‐concentration model (TPCM) was built to assess the prevalence and concentration of pathogenic campylobacter species in batches of fresh chicken and turkey meat at retail. The data set was collected from Finnish grocery stores in all the seasons of the year. Observations at low concentration levels are often censored due to the limit of determination of the microbiological methods. This model utilized the potential of Bayesian methods to borrow strength from related samples in order to perform under heavy censoring. In this extreme case the majority of the observed batch‐specific concentrations was below the limit of determination. The hierarchical structure was included in the model in order to take into account the within‐batch and between‐batch variability, which may have a significant impact on the sample outcome depending on the sampling plan. Temporal changes in the prevalence of campylobacter were modeled using a Markovian time series. The proposed model is adaptable for other pathogens if the same type of data set is available. The computation of the model was performed using OpenBUGS software.     

Paired comparisons analysis: an axiomatic approach to ranking methods

In this paper we present an axiomatic analysis of several ranking methods for general tournaments. We find that the ranking method obtained by applying maximum likelihood to the (Zermelo-)Bradley-Terry model, the most common method in statistics and psychology, is one of the ranking methods that perform best with respect to the set of properties under consideration. A less known ranking method, generalised row sum, performs well too. We also study, among others, the fair bets ranking method, widely studied in social choice, and the least squares method.     

Mobility and Professional Networks in Academia: An Exploration of the Obligations of Presence

This article explores the obligations of presence behind work-related mobility for academics in internationalizing higher education systems. By further developing John Urry’s concept of ‘meetingness’, the article reveals how academics depend on corporeal and virtual mobility to create and maintain a networked professional life outside their own institution, which is crucial in the context of changing work conditions. Our insights are drawn from original qualitative research (42 interviews) in a Flemish and Danish context. The data reveal obligations of presence associated with an interrelated mix of functionality, and the construction of dense and sparse social networks that together support career success and work at the frontiers of academic knowledge. Despite the now well-recognized costs of corporeal mobility, obligations of presence result in virtual and corporeal mobility coexisting, rather than the former substituting for the latter. Virtual mobility is mainly used when conflicting obligations of presence exist, and as a means of sustaining networks over time given the processual nature of meetingness, rather than as a means to reduce levels of corporeal mobility.     

An Ecological Model for Quantitative Risk Assessment for Schistosomiasis: The Case of a Patchy Environment in the Coastal Tropical Area of Northeastern Brazil

We developed a stochastic model for quantitative risk assessment for the Schistosoma mansoni (SM) parasite, which causes an endemic disease of public concern. The model provides answers in a useful format for public health decisions, uses data and expert opinion, and can be applied to any landscape where the snail Biomphalaria glabrata is the main intermediate host (South and Central America, the Caribbean, and Africa). It incorporates several realistic and case‐specific features: stage‐structured parasite populations, periodic praziquantel (PZQ) drug treatment for humans, density dependence, extreme events (prolonged rainfall), site‐specific sanitation quality, environmental stochasticity, monthly rainfall variation, uncertainty in parameters, and spatial dynamics. We parameterize the model through a real‐world application in the district of Porto de Galinhas (PG), one of the main touristic destinations in Brazil, where previous studies identified four parasite populations within the metapopulation. The results provide a good approximation of the dynamics of the system and are in agreement with our field observations, i.e., the lack of basic infrastructure (sanitation level and health programs) makes PG a suitable habitat for the persistence and growth of a parasite metapopulation. We quantify the risk of SM metapopulation explosion and quasi‐extinction and the time to metapopulation explosion and quasi‐extinction. We evaluate the sensitivity of the results under varying scenarios of future periodic PZQ treatment (based on the Brazilian Ministry of Health's plan) and sanitation quality. We conclude that the plan might be useful to slow SM metapopulation growth but not to control it. Additional investments in better sanitation are necessary.