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As fewer younger physicians enter rural practice in the United States, the rural physician workforce is graying and nearing retirement. The uneven distribution of doctors presents serious access problems, exacerbates health needs, and has important equity implications.

A large literature in medicine documents variation across areas in the use of surgical treatments that is unrelated to outcomes. Observers of this phenomenon have invoked “flat of the curve medicine” to explain it and have advocated for reductions in spending in high‐use areas. In contrast, we develop a simple Roy model of patient treatment choice with productivity spillovers that can generate the empirical facts. Our model predicts that high‐use areas will have higher returns to surgery, better outcomes among patients most appropriate for surgery, and worse outcomes among patients least appropriate for surgery, while displaying no relationship between treatment intensity and overall outcomes. Using data on treatments for heart attacks, we find strong empirical support for these and other predictions of our model and reject alternative explanations such as “flat of the curve medicine” or supplier‐induced demand for geographic variation in medical care.

Recent theoretical and empirical advances have renewed interest in monopsonistic models of the labor market. However, there is little direct empirical support for these models. We use an exogenous change in wages at Department of Veterans Affairs (VA) hospitals as a natural experiment to investigate the extent of monopsony in the nurse labor market. We estimate that labor supply to individual hospitals is quite inelastic, with short‐run elasticity around 0.1. We also find that non‐VA hospitals responded to the VA wage change by changing their own wages.

Concerns about physician shortages have led policy makers in the US public and private sectors to advocate for the greater use of nurse practitioners (NPs). We examined recent changes in demographic, employment, and earnings characteristics of NPs and the implications of those changes. In the period 2010-17 the number of NPs in the US more than doubled from approximately 91,000 to 190,000. This growth occurred in every US region and was driven by the rapid expansion of education programs that attracted nurses in the Millennial generation. Employment was concentrated in hospitals, physician offices, and outpatient care centers, and inflation-adjusted earnings grew by 5.5 percent over this period. The pronounced growth in the number of NPs has reduced the size of the registered nurse (RN) workforce by up to 80,000 nationwide. In the future, hospitals must innovate and test creative ideas to replace RNs who have left their positions to become NPs, and educators must be alert for signs of falling earnings that may signal the excess production of NPs.

Importance A better understanding of the association between family structure and sex gaps in physician earnings and hours worked over the life cycle is needed to advance policies addressing persistent sex disparities. Objective To investigate differences in earnings and hours worked for male and female physicians at various ages and family status. Design, Setting, and Participants This retrospective, cross-sectional study used data on physicians aged 25 to 64 years responding to the American Community Survey between 2005 and 2019. Exposures Earned income and work hours. Main Outcomes and Measures Outcomes included annual earned income, usual hours worked per week, and earnings per hour worked. Gaps in earnings and hours by sex were calculated by family status and physician age and, in some analyses, adjusted for demographic characteristics and year of survey. Data analyses were conducted between 2019 and 2022. Results The sample included 95 435 physicians (35.8% female, 64.2% male, 19.8% Asian, 4.8% Black, 5.9% Hispanic, 67.3% White, and 2.2% other race or ethnicity) with a mean (SD) age of 44.4 (10.4) years. Relative to male physicians, female physicians were more likely to be single (18.8% vs 11.2%) and less likely to have children (53.3% vs 58.2%). Male-female earnings gaps grew with age and, when accumulated from age 25 to 64 years, were approximately $1.6 million for single physicians, $2.5 million for married physicians without children, and $3.1 million for physicians with children. Gaps in earnings per hour did not vary by family structure, with male physicians earning between 21.4% and 23.9% more per hour than female physicians. The male-female gap in hours worked was 0.6% for single physicians, 7.0% for married physicians without children, and 17.5% for physicians with children. Conclusions and Relevance In this cross-sectional study of US physicians, marriage and children were associated with a greater earnings penalty for female physicians, primarily due to fewer hours worked relative to men. Addressing the barriers that lead to women working fewer hours could contribute to a reduction in the male-female earnings gap while helping to expand the effective physician workforce.

Nurse practitioners and physician assistants are providing an increasing share of health care services, and education programs have proliferated. These dynamics will have lasting effects on the health care workforce and on relationships among health professionals.

Research on the relationship between teacher characteristics and teacher effectiveness has been underway for over a century, yet little progress has been made in linking teacher quality with factors observable at the time of hire. To extend this literature, we administered an in-depth survey to new math teachers in New York City and collected information on a number of nontraditional predictors of effectiveness, including teaching-specific content knowledge, cognitive ability, personality traits, feelings of self-efficacy, and scores on a commercially available teacher selection instrument. We find that only a few of these predictors have statistically significant relationships with student and teacher outcomes. However, the individual variables load onto two factors, which measure what one might describe as teachers' cognitive and noncognitive skills. We find that both factors have a moderately large and statistically significant relationship with student and teacher outcomes, particularly with student test scores.

Analysis of Current Population Survey data suggests a tightening labor market for registered nurses, licensed practical nurses, and nursing assistants, marked by falling employment and rising wages through June 2021. Unemployment rates remain higher in nonhospital settings and among registered nurses and nursing assistants who are members of racial and ethnic minority groups. With the onset of the COVID-19 pandemic and the immediate shutdown of economic activity in March 2020, overall employment in health care dropped precipitously in all sectors (exhibit 1). As employment gradually resumed (except in nursing facilities), the prevailing dynamic in the health care labor market shifted from furloughs to reports of burnout and nurse shortages.1 Amid this shifting landscape, there has been no systematic analysis of workforce data to increase understanding of the economic impacts on nurses. Using national data from federal government surveys, we provide a snapshot of the pandemic's impacts on employment and earnings across categories of the nurse workforce by major employment setting and by race and ethnicity over the course of the first fifteen months ofthe pandemic. Although we are unable to definitively attribute these impacts to changes in supply of or demand for nurses, the observed trends shed light on broader workforce dynamics affecting this critical workforce.

Over the past four decades, empirical researchers—many of them economists—have accumulated an impressive amount of evidence on teachers. In this paper, we ask what the existing evidence implies for how school leaders might recruit, evaluate, and retain teachers. We begin by summarizing the evidence on five key points, referring to existing work and to evidence we have accumulated from our research with the nation's two largest school districts: Los Angeles and New York City. First, teachers display considerable heterogeneity in their effects on student achievement gains. Second, estimates of teacher effectiveness based on student achievement data are noisy measures. Third, teachers' effectiveness rises rapidly in the first year or two of their teaching careers but then quickly levels out. Fourth, the primary cost of teacher turnover is not the direct cost of hiring and firing, but rather is the loss to students who will be taught by a novice teacher rather than one with several years of experience. Fifth, it is difficult to identify at the time of hire those teachers who will prove more effective. As a result, better teachers can only be identified after some evidence on their actual job performance has accumulated. We then explore what these facts imply for how principals and school districts should act, using a simple model in which schools must search for teachers using noisy signals of teacher effectiveness. The implications of our analysis are strikingly different from current practice. Rather than screening at the time of hire, the evidence on heterogeneity of teacher performance suggests a better strategy would be identifying large differences between teachers by observing the first few years of teaching performance and retaining only the highest-performing teachers.

We study the impact of a public school choice lottery in Charlotte-Mecklenburg schools on college enrollment and degree completion. We find a significant overall increase in college attainment among lottery winners who attend their first-choice school. Using rich administrative data on peers, teachers, course offerings, and other inputs, we show that the impacts of choice are strongly predicted by gains on several measures of school quality. Gains in attainment are concentrated among girls. Girls respond to attending a better school with higher grades and increases in college-preparatory course taking, while boys do not.