How Much Do Medical Students Know About Physician Income?

Twenty-five cohorts of medical students were asked in their first and fourth year of school to estimate contemporaneous physician income in six different specialties. The students' income estimation errors varied systematically over time and cross-sectionally by specialty and type of student. The median student underestimated physician income by 15 percent, and the median absolute value of the estimation errors was 26 percent of actual income. Students were 35 percent more accurate when estimating market income in their fourth relative to their first year, which indicates medical students learn a considerable amount before choosing a specialty.

Barriers to Entering Medical Specialties

Non-primary care physicians earn considerably more than primary care physicians in the United States. I examine a number of explanations for the persistent high rates of return to medical specialization and conclude that barriers to entry may be creating an economic shortage of non-primary care physicians. I estimate that medical students would be willing to pay teaching hospitals to obtain residency positions in dermatology, general surgery, orthopedic surgery, and radiology rather than receiving the mean residents' salary of $34,000. In the simulation, the quantity of residents in these four specialties would increase by an estimated six to 30 percent, rates of return would fall substantially, and teaching hospitals would save an estimated$0.6 to $1.0 billion per year in labor costs.

Peer Effects in Medical School

Using data on the universe of students who graduated from U.S. medical schools between 1996 and 1998, we examine whether the abilities and specialty preferences of a medical school class affect a student's academic achievement in medical school and his choice of specialty. We mitigate the selection problem by including school-specific fixed effects, and show that this method yields an upper bound on peer effects for our data. We estimate positive peer effects that disappear when school-specific fixed effects are added to control for the endogeneity of a peer group. We find no evidence that peer effects are stronger for blacks, that peer groups are formed along racial lines, or that students with relatively low ability benefit more from their peers than students with relatively high ability. However, we do find some evidence that peer groups form along gender lines.

The Formation and Evolution of Physician Treatment Styles: An Application to Cesarean Sections

Small-area-variation studies have shown that physician treatment styles differ substantially both between and within markets, controlling for patient characteristics. Using a data set containing the universe of deliveries in Florida over a 12-year period with consistent physician identifiers and a rich set of patient characteristics, we examine why treatment styles differ across obstetricians at a point in time, and why styles change over time. We find that the variation in c-section rates across physicians within a market is two to three times greater than the variation between markets. Surprisingly, residency programs explain less than four percent of the variation between physicians in their risk-adjusted c-section rates, even among newly-trained physicians. Although we find evidence that physicians, especially relatively inexperienced ones, learn from their peers, they do not substantially revise their prior beliefs regarding how patients should be treated due to the local exchange of information. Our results indicate that physicians are not likely to converge over time to a community standard; thus, within-market variation in treatment styles is likely to persist.

Physician Income Expectations and Specialty Choice

In spite of the important role of income expectations in economics, economists know little about how people actually form these expectations. We use a unique data set that contains the explicit income expectations of medical students over a 25-year time period to examine how students form income expectations. We examine whether students condition their expectations on their own ability, contemporaneous physician income, and the ex post income of physicians in their medical school cohort. We then test whether a model that uses the students' explicit income expectations to predict their specialty choices has a better fit than a model that assumes income expectations are formed statically, and a model that bases income expectations on ex post income.

Physician Income Prediction Errors: Sources and Implications for Behavior

Although income expectations play a central role in many economic decisions, little is known about the sources of income prediction errors and how agents respond to income shocks. This paper uses a unique panel data set to examine the accuracy of physicians' income expectations, the sources of income prediction errors, and the effect of income prediction errors on physician behavior. The data set contains direct survey measures of income expectations for medical students who graduated between 1970 and 1998, their corresponding income realizations, and a rich summary of the shocks hitting their medical practices. We find that income prediction errors were positive on average over the sample period, but varied significantly over time and cross-sectionally. We trace these results to persistent specialty-specific shocks, such as the growth of health maintenance organizations (HMOs) and other changes across health care markets. Physicians who experienced negative income shocks were more likely to respond by increasing their hours worked, allocating fewer of their work hours to teaching/research and more to patient care, and were more likely to switch specialties.

What Does It Cost Physician Practices to Interact With Health Insurance Plans?

Physicians have long expressed dissatisfaction with the time they and their staffs spend interacting with health plans. However, little information exists about the extent of these interactions.We conducted a national survey on this subject of physicians and practice administrators. Physicians reported spending three hours weekly interacting with plans; nursing and clerical staff spent much larger amounts of time. When time is converted to dollars, we estimate that the national time cost to practices of interactions with plans is at least $23 billion to$31 billion each year. [Health Affairs 28, no. 4 (2009): w533– w543 (published online 14 May 2009; 10.1377/hlthaff.28.4.w533)

Are public managers more risk averse? Framing effects and status quo bias across the sectors

The article of record as published may be found at https://doi.org/10.30636/jbpa.21.3Modern reforms meant to incentivize public managers to be more innovative and accepting of risk are often implicitly based in the longstanding assumption that public employees are more risk averse than their private sector counterparts. We argue, however, that there is more to learn about the degree to which public and private managers differ in terms of risk aversion. In order to address this gap, we field a series of previously validated experiments designed to assess framing effects and status quo bias in a sample of public and private sector managers. Our results indicate that public managers are not more risk averse or anchored to the status quo than their private sector counterparts; in fact, the findings suggest the opposite may be true under some conditions. In addition, our results fail to confirm previous findings in the literature suggesting that public service motivation is associated with risk aversion. We conclude with a discussion of the implications of these results for the study of risky choice in the public sector and for modern public management reforms

The Effects of Medicare Payment Subsidies to Teaching Hospitals

The Medicare program is the nation’s largest single source of funds for graduate medical education. The program pays teaching hospitals for the direct costs of their residency programs and, since 1983, has paid for some of the indirect costs of graduate medical education. The rationale for, and extent of, the payments for indirect costs have been debated for years; recently, Congress has reduced the payments as it attempts to rein in Medicare costs. This Issue Brief reviews the status and recent history behind indirect medical education (IME) payments, and summarizes research that investigates how hospitals have responded to the incentives created by these and other supplemental payments

Does Television Cause Autism?

Autism is currently estimated to affect approximately one in every 166 children, yet the cause or causes of the condition are not well understood. One of the current theories concerning the condition is that among a set of children vulnerable to developing the condition because of their underlying genetics, the condition manifests itself when such a child is exposed to a (currently unknown) environmental trigger. In this paper we empirically investigate the hypothesis that early childhood television viewing serves as such a trigger. Using the Bureau of Labor Statistics' American Time Use Survey, we first establish that the amount of television a young child watches is positively related to the amount of precipitation in the child's community. This suggests that, if television is a trigger for autism, then autism should be more prevalent in communities that receive substantial precipitation. We then look at county-level autism data for three states -- California, Oregon, and Washington -- characterized by high precipitation variability. Employing a variety of tests, we show that in each of the three states (and across all three states when pooled) there is substantial evidence that county autism rates are indeed positively related to county-wide levels of precipitation. In our final set of tests we use California and Pennsylvania data on children born between 1972 and 1989 to show, again consistent with the television as trigger hypothesis, that county autism rates are also positively related to the percentage of households that subscribe to cable television. Our precipitation tests indicate that just under forty percent of autism diagnoses in the three states studied is the result of television watching due to precipitation, while our cable tests indicate that approximately seventeen percent of the growth in autism in California and Pennsylvania during the 1970s and 1980s is due to the growth of cable television. These findings are consistent with early childhood television viewing being an important trigger for autism. We also discuss further tests that can be conducted to explore the hypothesis more directly.