Knowledge that Transforms

This paper examines two behavioral factors that diminish people's ability to value a lifetime income stream or annuity, drawing on a randomized experiment with about 4,000 adults in a U.S. nationally representative sample. We find that increasing the complexity of the annuity choice reduces respondents' ability to value the annuity, measured by the difference between the sell and buy values they assign to the annuity. When we limit narrow choice bracketing by inducing people to think first about how quickly or slowly to spend down assets in retirement, their ability to value an annuity increases.

Inadequate learning is an oft-cited friction impeding the adoption of improved agricultural technology in the developing world. We provide experimental evidence that farmer field days, an approach used throughout the world where farmers meet, learn about new technology, and observe its performance, alleviate learning frictions and increase adoption of an improved seed by 40%. Further analysis demonstrates that these field days are both cost-effective and have a greater impact on poorer farmers. In contrast, we find no evidence that selecting the first adopters of new technology in participatory village meetings has any effect on future adoption.

This paper examines the long-run economic consequences of Russian serfdom. Employing data on the intensity of labor coercion just prior to emancipation in 1861, we document that a 25 percentage point increase in historical serfdom (1 SD) reduces household expenditure today by up to 17%. We then provide evidence on the persistence of this relationship by studying city populations over the period 1800 to 2002. Exploring mechanisms, our findings suggest that less urban agglomeration and slower industrial development in areas with a greater degree of serfdom perpetuated the negative effects of forced labor before, during, and after the Soviet period.

This paper documents large revisions in a widely used series of utilization-adjusted total factor productivity (TFP) by Fernald (2014) and shows that these revisions can materially affect empirical results about the effects of news shocks. We trace these revisions to changes in estimated factor utilization that are evocative of cyclical measurement issues with productivity. We propose an alternative identification that is robust to these measurement issues. Applied to U.S. data, the shock predicts delayed productivity growth while simultaneously generating strong responses of novel indicators of technological innovation and forward-looking variables. The shock does not lead to comovement in macroeconomic aggregates.

For much of the industrialized world, pollution from manufacturing has been falling despite increased output. We examine how air quality standards---a common environmental regulation---have contributed to this cleanup of manufacturing. We develop a general equilibrium model to show how air quality standards can lead to a cleanup by causing reductions in plant emission intensity, relative changes in plant output, and plant entry and exit. We provide quasi-experimental evidence from Canada to highlight the magnitude of these responses. Our results suggest that air quality standards explain just under 40% of the cleanup of manufacturing.

This paper studies the wild bootstrap–based test proposed in Cameron, Gelbach, and Miller (2008). Existing analyses of its properties require that number of clusters is “large.” In an asymptotic framework in which the number of clusters is “small,” we provide conditions under which an unstudentized version of the test is valid. These conditions include homogeneity-like restrictions on the distribution of covariates. We further establish that a studentized version of the test may only overreject the null hypothesis by a “small” amount that decreases exponentially with the number of clusters. We obtain a qualitatively similar result for “score” bootstrap-based tests, which permit testing in nonlinear models.

This paper demonstrates the acute sensitivity of education program effectiveness to the choices of inputs and outcome measures, using a randomized evaluation of a mother-tongue literacy program. The program raises reading scores by 0.64 SD and writing scores by 0.45 SD. A reduced-cost version instead yields statistically insignificant reading gains and some large negative effects (−0.33 SDs) on advanced writing. We combine a conceptual model of education production with detailed classroom observations to examine the mechanisms driving the results; we show they could be driven by the program initially lowering productivity before raising it, and potentially by missing complementary inputs in the reduced-cost version.

We survey a representative sample of U.S. households to study how exposure to the COVID-19 stock market crash affects expectations and planned behavior. Wealth shocks are associated with upward adjustments of expectations about retirement age, desired working hours, and household debt but have only small effects on expected spending. We provide correlational and experimental evidence that beliefs about the duration of the stock market recovery shape households' expectations about their own wealth and their planned investment decisions and labor market activity. Our findings shed light on the implications of household exposure to stock market crashes for expectation formation.

We document how demand shocks in export markets lead French multiproduct exporters to reallocate the mix of products sold in those destinations. In response to positive demand shocks, French firms skew their export sales toward their best-performing products. We develop a theoretical model of multiproduct firms and derive the specific demand conditions (with endogenous price elasticities) needed to generate these product-mix reallocations. Under those demand conditions, the increased competition from demand shocks in export markets also induces productivity changes within the firm. We empirically test for this connection between demand shocks and the productivity of multiproduct firms. We find that this connection is economically substantial.

This paper estimates the impact of police presence on crime using a unique database that tracks the exact location of Dallas Police Department patrol cars throughout 2009. To address the concern that officer location is often driven by crime, my instrument exploits police responses to calls outside their allocated coverage beat. This variable provides a plausible shift in police presence within the abandoned beat that is driven by the police goal of minimizing response times. I find that a 10% decrease in police presence at that location results in a 7% increase in crime. This result sheds light on the black box of policing and crime and suggests that routine changes in police patrol can have a significant impact on criminal behavior.