Inequality in income, consumption, and wealth have all been increasing, but some evidence indicates that increased inequality in the joint distribution of the three measures of economic wellbeing exceeds that of inequality in any of the single distributions. However, to date, no single dataset currently allows researchers to examine rising inequality in the three measures simultaneously over a long period of time. As a result, studies often examine inequality and mobility using income, consumption, or wealth separately, without reference to the other two.
The U.S. labor market has experienced dramatic changes over the last several decades, including increased wage inequality and shifts in the distribution of jobs over time and across geographic regions. These changes raise questions about the associated changes in the tasks that workers perform and how skills applied to different tasks are rewarded. However, it is difficult to analyze the evolving structure of occupations because of limited availability of data measuring the skill requirements and task content of jobs.
The growing availability of digital administrative records combined with new prediction tools developed in machine learning has contributed to increased use of data to inform policy decisions based on predictions. Examples include hiring decisions based on predictions of an employee’s productivity, program services prioritized on predictions of who might benefit the most, allocation of police resources based on predictions about where crime is likely to occur, and pre-trial bail decisions are informed by predictions about risk.
The Great Recession profoundly disrupted local labor markets in the United States, an important destination for Mexican immigrants. If weakened labor demand contributed to increased return migration to Mexico and discouraged potential migrants from leaving, the recession could have also significantly affected the economic conditions in the Mexican regions with the strongest network ties to the hardest-hit U.S. destinations. Economists Brian Kovak and Brian Cadena will examine how losing access to a strong U.S.
Co-funded with the Robert Wood Johnson Foundation
The employer mandate under the Affordable Care Act (ACA) requires businesses that have 50 or more full-time equivalent employees to provide “affordable and adequate” health insurance (defined as covering at least 95 percent of full-time employees and their dependents and at least 60 percent of expected health care expenses, not to exceed 9.5 percent of the employee’s household income) to full-time employees, or to pay a penalty.
Findings: The Impact of Medicaid Expansion on Household Consumption; Sayeh Nikpay, Vanderbilt University; Thomas Buchmueller and Helen Levy, University of Michigan
Co-funded with the Robert Wood Johnson Foundation
The financial burden imposed by illness affects not only health but also standard of living. The Medicaid expansion under the Affordable Care Act (ACA) was expected to improve the financial situation of the uninsured, particularly those with low incomes. Economist Emily Gallagher and public policy expert Stephen Roll will examine the relationship between the ACA and the financial security of households with incomes of below 200 percent of the federal poverty line.
Auto dealers collect loan quotes from many lending institutions, which might lower a customer’s cost of financing. However, dealers’ intermediation role forces car buyers to keep track of relevant car and loan attributes, including the car price, the loan interest rate, any finance charges, the down payment, the repayment period, the trade-in value of their old car, and the price and value of optional add-ons. Online buyer guides and anecdotal evidence suggest that auto dealers may utilize this complexity to obscure the actual price.