Knowledge that Transforms

A significant amount of work time is lost each year due to worker absence, but evidence on the productivity losses from absenteeism remains scant due to difficulties with identification. We use uniquely detailed data on the timing, duration, and cause of absences among teachers to address many of the potential biases from the endogeneity of worker absence. Our analysis indicates that worker absences have large negative impacts: the expected loss in daily productivity from employing a temporary substitute is on par with replacing a regular worker of average productivity with one at the 10th–20th percentile of productivity.

Research examining the educational attainment of low-income students has often focused on financial factors such as credit constraints. We use unique longitudinal data to provide direct evidence about a prominent alternative explanation—that departures from school arise as students learn about their academic ability or grade performance. Examining college dropout, we find that this explanation plays a very prominent role; our simulations indicate that dropout between the first and second years would be reduced by 40% if no learning occurred about grade performance/academic ability. The article also contributes directly to the understanding of gender differences in educational attainment.

The option to obtain a General Education Development (GED) certificate changes the incentives facing high school students. This paper evaluates the effect of three different GED policy innovations on high school graduation rates. A six point decrease in the GED pass rate due to an increase in passing standards produced a 1.3 point decline in overall dropout rates. The introduction of a GED certification program in high schools in Oregon produced a four percent decrease in graduation rates. Introduction of GED certificates in California increased dropout rates by 3 points. The GED program induces high school students to drop out.

We assess the information spillovers generated by the exchange of job-related information within networks of fellow workers exploiting administrative records covering all employment relationships established in a specific local labor market over 20 years. We recover individual-specific networks of former colleagues for a sample of workers exogenously displaced by firm closures and relate their subsequent unemployment duration to the share of employed contacts at displacement date. Individual-specific networks and the longitudinal dimension of the data allow to account for most plausible sources of omitted variable bias. In particular, identification rests on within-closure within-neighborhood and within-skill comparisons conditional of a wide range of predictors for the displaced and his contacts' employment status, such as lagged wages and labor market attachment. We find that contacts' current employment rate has statistically significant effects on unemployment duration: a one standard deviation increase in the network employment rate reduces unemployment duration by about 8 percent; as a benchmark, a one standard deviation increase in own wage at displacement is associated with a 10 percent lower unemployment duration. These effects are magnified if contacts recently searched for a job and if their current employer is closer, both in space and in skills requirements, to the displaced. We find that stronger ties and lower competition for the available information also speed up re-employment. A number of specification checks and indirect tests suggests the estimated spillover effect of contacts' current employment status is driven by information exchange rather than by other interaction mechanisms.

In this article, we examine optimal job choices when jobs differ in the rate at which they reveal information about workers’ skills. We then analyze how the optimal level of experimentation changes over a worker’s career and characterize job transitions and wage growth over the life cycle. Using the Dictionary of Occupational Titles merged with the National Longitudinal Survey of Youth 1979, we then construct an index of how much information different occupations reveal about workers’ skills and document patterns of occupational choice and wage growth that are consistent with a trade-off between information and wages.

The employment to population rate of high school–aged youth has fallen by about 20 percentage points since the late 1980s. One potential explanation is increased competition from substitutable labor, such as immigrants. I demonstrate that the increase in the population of less educated immigrants has had a considerably more negative effect on employment outcomes for native youth than for native adults. At least two factors are at work: there is greater overlap between the jobs that youth and less educated adult immigrants traditionally do, and youth labor supply appears more responsive to immigration-induced wage changes.

Contingent charges for financial services, such as fees for unauthorized overdrafts, are often controversial. We study the economics of contingent charges in a stylized setting with naive and sophisticated consumers. We contrast situations where the naive benefit from the presence of sophisticated consumers with situations where competition works to subsidize the sophisticated at the expense of the naive, arguably unfairly. The case for regulatory intervention in these situations depends in good part, but not only, on the weight placed on distributional concerns. The economic and legal issues at stake are well illustrated by a case on bank charges recently decided by the U.K. Supreme Court. (JEL D14, D18, G21, G28, L51)

The publication of Daniel Kahneman's book, Thinking, Fast and Slow, is a major intellectual event. The book summarizes, but also integrates, the research that Kahneman has done over the past forty years, beginning with his path-breaking work with the late Amos Tversky. The broad theme of this research is that human beings are intuitive thinkers and that human intuition is imperfect, with the result that judgments and choices often deviate substantially from the predictions of normative statistical and economic models. In this review, I discuss some broad ideas and themes of the book, describe some economic applications, and suggest future directions for research that the book points to, especially in decision theory. (JEL A12, D03, D80, D87)

In the United States, health care technology has contributed to rising survival rates, yet health care spending relative to GDP has also grown more rapidly than in any other country. We develop a model of patient demand and supplier behavior to explain these parallel trends in technology growth and cost growth. We show that health care productivity depends on the heterogeneity of treatment effects across patients, the shape of the health production function, and the cost structure of procedures such as MRIs with high fixed costs and low marginal costs. The model implies a typology of medical technology productivity: (I) highly cost-effective “home run” innovations with little chance of overuse, such as anti-retroviral therapy for HIV, (II) treatments highly effective for some but not for all (e.g., stents), and (III) “gray area” treatments with uncertain clinical value such as ICU days among chronically ill patients. Not surprisingly, countries adopting Category I and effective Category II treatments gain the greatest health improvements, while countries adopting ineffective Category II and Category III treatments experience the most rapid cost growth. Ultimately, economic and political resistance in the United States to ever-rising tax rates will likely slow cost growth, with uncertain effects on technology growth. (JEL H51, I11, I18, O31)

This paper reviews four decades of economics research on the brain drain, with a focus on recent contributions and on development issues. We first assess the magnitude, intensity, and determinants of the brain drain, showing that brain drain (or high-skill) migration is becoming a dominant pattern of international migration and a major aspect of globalization. We then use a stylized growth model to analyze the various channels through which a brain drain affects the sending countries and review the evidence on these channels. The recent empirical literature shows that high-skill emigration need not deplete a country's human capital stock and can generate positive network externalities. Three case studies are also considered: the African medical brain drain, the exodus of European scientists to the United States, and the role of the Indian diaspora in the development of India's information technology sector. We conclude with a discussion of the implications of the analysis for education, immigration, and international taxation policies in a global context. (JEL F02, F22, J24, J61, O15)