Minimum Wage Effects on Labor Market Outcomes under Search,Matching, and Endogenous Contact Rates

Building upon a continuous‐time model of search with Nash bargaining in a stationary environment, we analyze the effect of changes in minimum wages on labor market outcomes and welfare. Although minimum wage increases may or may not lead to increases in unemployment in our model, they can be welfare‐improving to labor market participants on both the supply and demand sides of the labor market. We discuss identification of the model using Current Population Survey data on accepted wages and unemployment durations, and show that by incorporating a limited amount of information from the demand side of the market it is possible to obtain credible and precise estimates of all primitive parameters. We show that the optimal minimum wage in 1996 depends critically on whether or not contact rates can be considered to be exogenous and we note that the limited variation in minimum wages makes testing this assumption problematic.     

An Equilibrium Model of Health Insurance Provision and Wage Determination

We investigate the effect of employer‐provided health insurance on job mobility rates and economic welfare using a search, matching, and bargaining framework. In our model, health insurance coverage decisions are made in a cooperative manner that recognizes the productivity effects of health insurance as well as its nonpecuniary value to the employee. The resulting equilibrium is one in which not all employment matches are covered by health insurance, wages at jobs providing health insurance are larger (in a stochastic sense) than those at jobs without health insurance, and workers at jobs with health insurance are less likely to leave those jobs, even after conditioning on the wage rate. We estimate the model using the 1996 panel of the Survey of Income and Program Participation, and find that the employer‐provided health insurance system does not lead to any serious inefficiencies in mobility decisions.     

Explaining Trends in Body Mass Index Using Demographic Counterfactuals

The United States is experiencing a major public health problem relating to increasing levels of excess body fat. This paper is about the relationship in the United States between trends in the distribution of body mass index (BMI), including trends in overweight and obesity, and demographic change. We provide estimates of the counterfactual distribution of BMI that would have been observed in 2003–2008 had demographics remained fixed at 1980 values, roughly the beginning of the period of increasing overweight and obesity. We find that changes in demographics are partly responsible for the changes in the population distribution of BMI and are capable of explaining about 8.6% of the increase in the combined rate of overweight and obesity among women and about 7.2% of the increase among men. We also use demographic projections to predict a BMI distribution and corresponding rates of overweight and obesity for 2050.     

Returning to the nest: Emerging adults living with parents during the COVID-19 pandemic

Changes in the working, study and social lives of emerging adults due to the COVID-19 pandemic have led to greater need for external supports. Many who lived independently may have sought that support by returning to live with parents. This study identifies factors associated with returns made between 2019 and 2020. It describes supports needed and obtained, relationships between parents and their resident emerging adults and identifies correlates of poor coping and high psychological distress. Data from the Longitudinal Surveys of Australian Youth and the Longitudinal Study of Australian Children were used and showed half of the emerging adults who moved did so due to COVID-19 restrictions. Loss of work and increased need for emotional and financial support were key drivers of moves. Nineteen per cent who returned found spending more time with family difficult and over half did not have their support needs fully met, increasing their odds of poor coping at that time (OR = 2.9, 4.3, respectively) and subsequent psychological distress (OR = 6.0). Families were an important source of support but could not necessarily mitigate all challenges; for some emerging adults, returning to live with parents gave rise to additional difficulties which negatively affected mental health.     

A mixture of experts latent position cluster model for social network data

Social network data represent the interactions between a group of social actors. Interactions between colleagues and friendship networks are typical examples of such data.The latent space model for social network data locates each actor in a network in a latent (social) space and models the probability of an interaction between two actors as a function of their locations. The latent position cluster model extends the latent space model to deal with network data in which clusters of actors exist — actor locations are drawn from a finite mixture model, each component of which represents a cluster of actors.A mixture of experts model builds on the structure of a mixture model by taking account of both observations and associated covariates when modeling a heterogeneous population. Herein, a mixture of experts extension of the latent position cluster model is developed. The mixture of experts framework allows covariates to enter the latent position cluster model in a number of ways, yielding different model interpretations.Estimates of the model parameters are derived in a Bayesian framework using a Markov Chain Monte Carlo algorithm. The algorithm is generally computationally expensive — surrogate proposal distributions which shadow the target distributions are derived, reducing the computational burden.The methodology is demonstrated through an illustrative example detailing relationships between a group of lawyers in the USA.