Bayesian modelling of catch in a north-west Atlantic fishery

Summary. We model daily catches of fishing boats in the Grand Bank fishing grounds. We use data on catches per species for a number of vessels collected by the European Union in the context of the Northwest Atlantic Fisheries Organization. Many variables can be thought to influence the amount caught: a number of ship characteristics (such as the size of the ship, the fishing technique used and the mesh size of the nets) are obvious candidates, but one can also consider the season or the actual location of the catch. Our database leads to 28 possible regressors (arising from six continuous variables and four categorical variables, whose 22 levels are treated separately), resulting in a set of 177 million possible linear regression models for the log-catch. Zero observations are modelled separately through a probit model. Inference is based on Bayesian model averaging, using a Markov chain Monte Carlo approach. Particular attention is paid to the prediction of catches for single and aggregated ships.     

Happiness has traitlike and statelike properties: A reply to Veenhoven

Veenhoven (1994) contrasted hypotheses of whether happiness is a trait or state, concluding that it is a state variable. This article critiques the conceptual foundation of Veenhoven's paper, and examines technical deficiencies in his review of evidence. Based on previous findings and new analyses, we conclude that happiness has both traitlike and statelike properties, but that individual differences in happiness endure despite its situational reactivity, and explain greater variance than situational effects.     

An Assessment of Change in Risk Perception and Optimistic Bias for Hurricanes Among Gulf Coast Residents

This study focuses on levels of concern for hurricanes among individuals living along the Gulf Coast during the quiescent two‐year period following the exceptionally destructive 2005 hurricane season. A small study of risk perception and optimistic bias was conducted immediately following Hurricanes Katrina and Rita. Two years later, a follow‐up was done in which respondents were recontacted. This provided an opportunity to examine changes, and potential causal ordering, in risk perception and optimistic bias. The analysis uses 201 panel respondents who were matched across the two mail surveys. Measures included hurricane risk perception, optimistic bias for hurricane evacuation, past hurricane experience, and a small set of demographic variables (age, sex, income, and education). Paired t‐tests were used to compare scores across time. Hurricane risk perception declined and optimistic bias increased. Cross‐lagged correlations were used to test the potential causal ordering between risk perception and optimistic bias, with a weak effect suggesting the former affects the latter. Additional cross‐lagged analysis using structural equation modeling was used to look more closely at the components of optimistic bias (risk to self vs. risk to others). A significant and stronger potentially causal effect from risk perception to optimistic bias was found. Analysis of the experience and demographic variables’ effects on risk perception and optimistic bias, and their change, provided mixed results. The lessening of risk perception and increase in optimistic bias over the period of quiescence suggest that risk communicators and emergency managers should direct attention toward reversing these trends to increase disaster preparedness.     

Social Distance and the Formerly Obese: Does the Stigma of Obesity Linger?*

Research has documented the stigma of obesity extensively, but little attention has been given to the study of stigma toward formerly obese individuals. The present study examines whether the stigma of obesity in romantic relationships carries over to formerly obese individuals by using primary data collected from a Midwestern university in the United States (N = 363). We consider how an individual's own body weight, demographic characteristics, familiarity, and attitudes affect the willingness to form a romantic relationship with a formerly obese person. Results suggest that obese individuals are less likely to hesitate about engaging in a romantic relationship with a formerly obese person than underweight or normal weight individuals, but only when attitudes toward obese and formerly obese individuals are controlled. In terms of demographic characteristics, men and African Americans are more likely to hesitate about forming a romantic relationship than their respective counterparts. More familiarity with currently obese family members and formerly obese close friends appears to reduce the stigma minimally. Greater social distance is also desired if weight loss is believed to be temporary.     

Reducing poverty and inequality through tax-benefit reform and the minimum wage: the UK as a case-study

Atkinson’s book Inequality: What Can Be Done? (Harvard University Press, 2015) sets out a range of concrete proposals aimed at reducing income inequality, which cover a very broad span but include major changes to the income tax and social transfers system and the minimum wage. These are framed with specific reference to the UK but have much broader relevance in demonstrating how substantial the impact on inequality of such measures could be. This paper assesses the first-round effects of these tax, transfer and minimum wage reforms on income inequality and poverty based on a microsimulation approach using EUROMOD. The reforms involve a significantly more progressive income tax structure, a major increase in the minimum wage to the level which is estimated to represent the ‘Living Wage’, and alternative routes to reforming social transfers – either to strengthen the social insurance element or to restructure the entire system as a Participation Income (a variant of Basic/Citizen’s Income). The results show how the first-round effects of either set of tax and transfer proposals would be to substantially reduce the extent of income inequality and relative income poverty and the paper draws out how the two approaches differ in their effects. The additional impact of raising the minimum wage to the Living Wage is modest, reflecting in particular the position of beneficiaries in the household income distribution and the offsetting effects on household income of the withdrawal of means-tested cash transfers.     

Discussion of “Nonparametric Bayesian Inference in Applications”: Bayesian nonparametric methods in econometrics

The use of Bayesian nonparametrics models has increased rapidly over the last few decades driven by increasing computational power and the development of efficient Markov chain Monte Carlo algorithms. We review some applications of these models in economic applications including: volatility modelling (using both stochastic volatility models and GARCH-type models) with Dirichlet process mixture models, uses in portfolio allocation problems, long memory models with flexible forms of time-dependence, flexible extension of the dynamic Nelson-Siegel model for interest rate yields and multivariate time series models used in macroeconometrics.     

Measuring stakeholder identification with nonprofit causes: the development and validation of the identification with social causes scale

Nonprofit organizations (NPOs) achieve desired outcomes by fostering organizational identification. However, little research has explored how identification with the cause or the recipients of support relates to identification with the NPO. This study developed the Identification with Social Causes Scale as a mechanism for distinguishing organizational identification from identification with a social group or cause. Data were collected using two groups: the homeless (n = 318) and HIV positive (n = 314) individuals. Exploratory factor analysis and multigroup confirmatory factor analysis yielded a 9-item scale measuring two dimensions: attachment and consubstantiality. Initial construct validity of the scale was established.     

Struggle as opportunity: making sense of U.S. migration experiences through Buddhist practice

Recent scholarship demonstrates how immigrants rely on religion for resources and psychological and social support at various stages of migration. Many studies of religion focus on the institutional role of faith-based organisations, with little regard for the social importance of religious experiences in daily life. Using interviews with U.S. immigrants who identify as Buddhists, I examine how migrants use Buddhist philosophies as a lens for finding meaning in the struggles associated with migration, including language acquisition, employment, and legal status. Through their practice, migrants gain a sense of agency amid vulnerable circumstances. I also explore the potentially negative consequences of the practice’s individual focus, including the propensity to mask structural causes of inequality and impede possibilities for collective action.