Knowledge that Transforms

Abstract This paper estimates the size of the media multiplier, an easily generalizable model-based measure of how far media coverage magnifies the economic response to shocks. We combine monthly aggregated and anonymized credit card activity data from 114 card-issuing countries in 5 destination countries with a large corpus of news coverage in issuing countries reporting on violent events in the destinations. To define and quantify the media multiplier, we estimate a model in which latent beliefs, shaped by either events or news coverage, drive card activity. According to the model, media coverage can more than triple the economic impact of an event. We document, through our model, that this effect is highly heterogeneous and depends on the broader media representation of countries in each other’s news. We speculate about the role of the media in driving international travel patterns.

Abstract This paper describes how to reparametrize low-dimensional factor models with one or two factors to fit weak identification theory developed for generalized method of moments models. Some identification-robust tests, here called “plug-in” tests, require a reparametrization to distinguish weakly identified parameters from strongly identified parameters. The reparametrizations in this paper make plug-in tests available for subvector hypotheses in low-dimensional factor models with one or two factors. Simulations show that the plug-in tests are less conservative than identification-robust tests that use the original parametrization. An empirical application to a factor model of parental investments in children is included.

Abstract We report the results of two experiments designed to better understand the mechanisms driving decision making under ambiguity. We elicit individual preferences over different sources of uncertainty, entailing different degrees of complexity, from subjects with different sophistication levels. We show that (1) ambiguity aversion is robust to sophistication, but the strong relationship previously reported between attitudes toward ambiguity and compound risk is not and (2) Ellsberg ambiguity attitude can be partly explained by attitudes toward complexity for less sophisticated subjects only. Overall, regardless of the subject’s sophistication level, the main driver of Ellsberg ambiguity attitude is a specific treatment of unknown probabilities.

Abstract Urban forests are ubiquitous, yet their impacts and values remain largely unknown. We study a massive urban afforestation policy in Beijing that planted 1/3 of a million acres of greenery in less than a decade. We conduct a remote-sensing audit of the program, finding that it contributes to a substantial greening up of the city. This causes significant downwind air quality improvement, reducing average PM2.5 concentration at city population hubs by 4.2%. Rapid vegetation growth unexpectedly led to a 7.4% increase in pollen exposure. Analysis of medical claims data shows that increased aeroallergens triggered emergency room visits, mirroring pollution effects though much less severe. Monetized net health benefits of the program amount to 1.5% of the city’s GDP. Urban forests are only partially capitalized in housing values, with buyers mainly appreciating proximity to green spaces but not the air quality improvements they bring.

Abstract This study examines the impact of school choice on academic achievement. I use differences in the number of schools across similar Romanian towns, generating variation in school choice for local students, who compete for seats via test scores. I find that more school choice results in increased sorting of students by admission scores across different schools. Sorting widens achievement gaps between high- and low-admission score students. High-scorers having access to better teachers and peer effects are the primary factors explaining these widening gaps. Last, between-school competition via school choice does not increase average achievement levels.

Abstract Migrants shape market access: They reduce international trade frictions and they affect the geographical location of demand. This article incorporates both effects in a model of inter- and intranational trade and migration calibrated to U.S. states. It estimates the elasticity of exports and imports to migrants and shows that reducing U.S. migrant population shares to 1980s levels would increase import (export) trade costs by 7% (2.5%) and decrease U.S. natives’ real wages by more than 2%. States with higher exposure to migrant consumer demand than to migrant labor competition would suffer more, as would states with higher export and import exposure.

Abstract P-hacking is prevalent in reality but absent from classical hypothesis-testing theory. We therefore build a model of hypothesis testing that accounts for p-hacking. From the model, we derive critical values such that, if they are used to determine significance, and if p-hacking adjusts to the new significance standards, then spurious significant results do not occur more often than intended. Because of p-hacking, such robust critical values are larger than classical critical values. In the model calibrated to medical science, the robust critical value is the classical critical value for the same test statistic but with one-fifth of the significance level.

Abstract I investigate the social costs imposed by poor implementation of public infrastructure. Focusing on the period from 2005 to 2015 in Peru, when the government embarked on a nationwide initiative to expand sewerage systems, I leverage quasirandom variation in initiation of the implementation phase. By combining several sources of administrative data, I find that infrastructure development increased infant and under-5 mortality. These effects are driven by health and safety hazards associated with construction work, leading to increased deaths from accidents and waterborne diseases. The severity of these effects is more pronounced in areas where construction activity was more intense.

Abstract This paper connects changes in employer characteristics through job transitions to employee earnings following mergers and acquisitions. Using firm balance sheet data linked to individual earnings data in Canada and a matched difference-in-differences design, we find that earnings of workers at target firms decrease after M&As relative to control workers, largely driven by those who move to other firms. Workers leaving targets move to larger and more profitable firms, but still experience wage declines. These decreased earnings are also concentrated among workers with longer tenure. These results are consistent with workers losing valuable match-specific premia after M&A-induced job transitions.

Abstract We examine the impact of firearm violence on newborn health in the U.S. using two approaches. First, we analyze the “beltway sniper” attacks in 2002, leveraging both temporal and spatial variation to compare birth outcomes of exposed children to those unexposed. Second, we investigate in-utero exposure to mass shootings using national data. We find that exposure to these incidents during pregnancy increases the likelihood of very low-birthweight and very premature birth. These events carry a significant economic burden, with the beltway sniper attacks costing at least $155 million and mass shootings resulting in annual costs exceeding $75 million.