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.

Research on the relationship between teachers' 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. However, most research has examined a relatively small set of characteristics that are collected by school administrators in order to satisfy legal requirements and set salaries. 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 non-traditional 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. Individually, we find that only a few of these predictors have statistically significant relationships with student and teacher outcomes. However, when all of these variables are combined into two primary factors summarizing cognitive and non-cognitive teacher skills, we find that both factors have a modest and statistically significant relationship with student and teacher outcomes, particularly with student test scores. These results suggest that, while there may be no single factor that can predict success in teaching, using a broad set of measures can help schools improve the quality of their teachers.

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No abstract

Inefficiency in the U.S. health care system has often been characterized as "flat of the curve" spending providing little or no incremental value. In this paper, we draw on macroeconomic models of diffusion and productivity to better explain the empirical patterns of outcome improvements in heart attacks (acute myocardial infarction). In these models, small differences in the propensity to adopt technology can lead to wide and persistent productivity differences across countries --or in our case, hospitals. Theoretical implications are tested using U.S. Medicare data on survival and factor inputs for 2.8 million heart attack patients during 1986-2004. We find that the speed of diffusion for highly efficient and often low-cost innovations such as beta blockers, aspirin, and primary reperfusion explain a large fraction of persistent variations in productivity, and swamp the impact of traditional factor inputs. Holding technology constant, the marginal gains from spending on heart attack treatments appear positive but quite modest. Hospitals which during the period 1994/95 to 2003/04 raised their rate of technology diffusion (the "tigers") experienced outcome gains four times the gains in hospitals with diminished rates of diffusion (the "tortoises"). Survival rates in low-diffusion hospitals lag by as much as a decade behind high-diffusion hospitals, raising the question of why some hospitals (and the physicians who work there) adopt so slowly.