Knowledge that Transforms

Why aren't there more women in science? This paper begins to shed light on this question by exploiting data from the U.S. Air Force Academy, where students are randomly assigned to professors for a wide variety of mandatory standardized courses.We focus on the role of professor gender. Our results suggest that although professor gender has little impact on male students, it has a powerful effect on female students' performance in math and science classes, and high-performing female students' likelihood of taking future math and science courses, and graduating with a STEM degree. The estimates are largest for students whose SAT math scores are in the top 5% of the national distribution. The gender gap in course grades and STEM majors is eradicated when high-performing female students are assigned to female professors in mandatory introductory math and science coursework.

Abstract Empirical evidence suggests that as much as one-third of the U.S. business cycle is due to nominal shocks. We calibrate a multisector menu cost model using new evidence on the cross-sectional distribution of the frequency and size of price changes in the U.S. economy. We augment the model to incorporate intermediate inputs. We show that the introduction of heterogeneity in the frequency of price change triples the degree of monetary non-neutrality generated by the model. We furthermore show that the introduction of intermediate inputs raises the degree of monetary non-neutrality by another factor of three, without adversely affecting the model's ability to match the large average size of price changes. A single-sector model with a frequency of price change equal to the median, rather than the mean, generates monetary non-neutrality similar to that in our multisector model. Our multisector model with intermediate inputs generates variation in real output in response to calibrated aggregate nominal shocks that can account for roughly 23% of the U.S. business cycle.

We estimate the magnitude of spillovers generated by 112 academic "superstars" who died prematurely and unexpectedly, thus providing an exogenous source of variation in the structure of their collaborators' coauthorship networks. Following the death of a superstar, we find that collaborators experience, on average, a lasting 5% to 8% decline in their quality-adjusted publication rates. By exploring interactions of the treatment effect with a variety of star, coauthor, and star/coauthor dyad characteristics, we seek to adjudicate between plausible mechanisms that might explain this finding. Taken together, our results suggest that spillovers are circumscribed in idea space, but less so in physical or social space. In particular, superstar extinction reveals the boundaries of the scientific field to which the star contributes-the "invisible college." (c) 2010 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology..

Growing concerns over the inadequate achievement of U.S. students have led to proposals to reward good teachers and penalize (or fire) bad ones. The leading method for assessing teacher quality is "value added" modeling (VAM), which decomposes students' test scores into components attributed to student heterogeneity and to teacher quality. Implicit in the VAM approach are strong assumptions about the nature of the educational production function and the assignment of students to classrooms. In this paper, I develop falsification tests for three widely used VAM specifications, based on the idea that future teachers cannot influence students' past achievement. In data from North Carolina, each of the VAMs' exclusion restrictions is dramatically violated. In particular, these models indicate large "effects" of fifth grade teachers on fourth grade test score gains. I also find that conventional measures of individual teachers' value added fade out very quickly and are at best weakly related to long-run effects. I discuss implications for the use of VAMs as personnel tools. (c) 2010 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology..

We use field and natural experiments in online auctions to study the revenue effect of varying the level and disclosure of shipping charges. Our main findings are (1) disclosure affects revenues—for low shipping charges, a seller is better off disclosing; and (2) increasing shipping charges boosts revenues when these charges are hidden. These results are not explained by changes in the number of bidders.

This paper examines how a large conditional grants program influenced school desegregation in the American South. Exploiting newly collected archival data and quasi-experimental variation in potential per-pupil federal grants, we show that school districts with more at risk in 1966 were more likely to desegregate just enough to receive their funds. Although the program did not raise the exposure of blacks to whites like later court orders, districts with larger grants at risk in 1966 were less likely to be under court order through 1970, suggesting that tying federal funds to nondiscrimination reduced the burden of desegregation on federal courts.

The use of stock-based compensation as a solution to agency problems between shareholders and managers has increased dramatically since the early 1990s. We show that in a dynamic rational expectations model with asymmetric information, stock-based compensation not only induces managers to exert costly effort, but also induces them to conceal bad news about future growth options and to choose suboptimal investment policies to support the pretense. This leads to a severe overvaluation and a subsequent crash in the stock price. Our model produces many predictions that are consistent with the empirical evidence and are relevant to understanding the current crisis.

New goods play a central role in many trade and growth models. We use detailed trade and firm-level data from India to investigate the relationship between declines in trade costs, imports of intermediate inputs, and domestic firm product scope. We estimate substantial gains from trade through access to new imported inputs. Moreover, we find that lower input tariffs account on average for 31% of the new products introduced by domestic firms. This effect is driven to a large extent by increased firm access to new input varieties that were unavailable prior to the trade liberalization.

Market size matters for innovation and hence for productivity. Improved access to foreign markets will thus encourage firms to simultaneously export and invest in raising productivity. We examine this insight using the responses of Canadian plants to the elimination of U.S. tariffs. Unique “plant-specific” tariff cuts serve as an instrument for changes in exporting. We find that Canadian plants that were induced by the tariff cuts to start exporting or to export more (a) increased their labor productivity, (b) engaged in more product innovation, and (c) had higher adoption rates for advanced manufacturing technologies. Further, these responses were heterogeneous.