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We examine the long-term consequences of teacher discretion in grading of high-stakes tests. Bunching in Swedish math test score distributions reveal that teachers inflate students who have "a bad test day," but do not to discriminate based on immigrant status or gender. By developing a new estimator, we show that receiving a higher grade leads to far-reaching educational and earnings benefits. Because grades do not directly raise human capital, these results emphasize that grades can signal to students and teachers within the educational system, and suggest important dynamic complementarities between students' effort and their perception of their own ability.

Zonder onderwerpscode: economie

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We study the causes of "nutritional inequality": why the wealthy tend to eat more healthfully than the poor in the U.S. Using two event study designs exploiting entry of new supermarkets and households' moves to healthier neighborhoods, we reject that neighborhood environments have economically meaningful effects on healthy eating. Using a structural demand model, we find that exposing low-income households to the same food availability and prices experienced by high-income households would reduce nutritional inequality by only 9%, while the remaining 91% is driven by differences in demand. In turn, these income-related demand differences are partially explained by education, nutrition knowledge, and regional preferences. These findings contrast with discussions of nutritional inequality that emphasize supply-side issues such as food deserts.

Zonder onderwerpscode: economie

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It is standard practice in empirical work to allow for clustering in the error covariance matrix if the explanatory variables of interest vary at a more aggregate level than the units of observation. Often, however, the structure of the error covariance matrix is more complex, with correlations varying in magnitude within clusters, and not vanishing between clusters. Here we explore the implications of such correlations for the actual and estimated precision of least squares estimators. We show that with equal sized clusters, if the covariate of interest is randomly assigned at the cluster level, only accounting for non-zero covariances at the cluster level, and ignoring correlations between clusters, leads to valid standard errors and confidence intervals. However, in many cases this may not suffice. For example, state policies exhibit substantial spatial correlations. As a result, ignoring spatial correlations in outcomes beyond that accounted for by the clustering at the state level, may well bias standard errors. We illustrate our findings using the 5% public use census data. Based on these results we recommend researchers assess the extent of spatial correlations in explanatory variables beyond state level clustering, and if such correlations are present, take into account spatial correlations beyond the clustering correlations typically accounted for.

Zonder onderwerpscode: economie

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The growth of the "gig" economy generates worker flexibility that, some have speculated, will favor women. We explore this by examining labor supply choices and earnings among more than a million rideshare drivers on Uber in the U.S. We document a roughly 7% gender earnings gap amongst drivers. We completely explain this gap and show that it can be entirely attributed to three factors: experience on the platform (learning-by-doing), preferences over where to work (driven largely by where drivers live and, to a lesser extent, safety), and preferences for driving speed. We do not find that men and women are differentially affected by a taste for specific hours, a return to within-week work intensity, or customer discrimination. Our results suggest that there is no reason to expect the "gig" economy to close gender differences. Even in the absence of discrimination and in flexible labor markets, women's relatively high opportunity cost of non-paid-work time and gender-based differences in preferences and constraints can sustain a gender pay gap.

Zonder onderwerpscode: economie