Knowledge that Transforms

International transboundary air pollution poses a significant threat to the global economy and health, yet conventional economic analyses seldom incorporate this phenomenon. By integrating transboundary particle trajectory data with individual-level mortality and emergency department visit records, we find that air pollution from China significantly increases mortality and morbidity in South Korea. We evaluate the spillover benefits of recent Chinese environmental regulations and find that a country's environmental policies could generate substantial hidden benefits for neighboring countries. Finally, we demonstrate that China's potentially strategic reductions in pollution could have undermined these benefits, highlighting the implications for additional gains through Coasian bargaining.

We estimate the impacts of temperature on alleged and substantiated child maltreatment among young children using administrative data from state child protective services agencies. Leveraging short-term weather variation, we find increases in the number of young children involved in cases of alleged and substantiated maltreatment during hot periods. Additional analysis identifies neglect as the temperature-sensitive maltreatment type, and we find some evidence that adaptation via air conditioning mitigates this relationship. Given that climate change will increase exposure to extreme temperatures, our findings speak to additional costs of climate change among the most vulnerable.

This paper studies the effects of transitioning from a system of sales taxes to a value-added tax (VAT) on firm-level outcomes. We construct a dataset of product- and state-specific tax rates before and after India gradually switched from a sales tax to a VAT. Exploiting staggered state-level adoptions, we first show that following the transition, effective tax rates declined substantially and complexity as measured by various proxies generally also fell. We then show that sales increased by 57% in the medium run. The reform resulted in increased earnings for workers and higher amounts of capital and digital accounting.

This paper develops a semi-structural model to jointly estimate “stars” — long-run levels of output (its growth rate), unemployment rate, real interest rate, productivity growth, price inflation, and wage inflation. It features links between survey expectations and stars, time-variation in macroeconomic relationships, and stochastic volatility. Survey data help discipline stars' estimates and have been crucial in estimating a high-dimensional model since the pandemic. The model has desirable real-time properties, competitive forecasting performance, and superior fit to the data compared to variants without the empirical features mentioned above. The by-products are estimates of various objects of great interest to the broader profession.

Do people around us influence our personality? We investigate this question through a field experiment where we randomly assign university students to study groups. We find personality spillovers along three dimensions: students become more conscientious when assigned to conscientious peers, more open-minded when assigned to open-minded peers, and more competitive when assigned to competitive peers. We find no effects for peers' extraversion, agreeableness, or neuroticism. Our findings are consistent with students' adopting peer traits that are predictive of academic achievement. Our paper provides novel evidence on spillovers in noncognitive skills and establishes that socialization with peers affects personality development.

We provide evidence on the mechanisms linking resource-related income shocks to conflict, focusing on illegal crops. We hypothesize that the degree of group competition over resources and the extent of law enforcement explain whether opportunity cost or contest effects dominate. Combining temporal variation in international drug prices with spatial variation in the suitability to produce opium, we show that higher prices increase household living standards and reduce conflict in Afghanistan. Analyzing shifts in conflict tactics and using georeferenced data on drug production networks and territorial control highlight the importance of opportunity costs, and reveal heterogeneous effects consistent with our theory.

We propose principled prediction intervals to quantify the uncertainty of a large class of synthetic control predictions (or estimators) in settings with staggered treatment adoption, offering precise non-asymptotic coverage probability guarantees. From a methodological perspective, we provide a detailed discussion of different causal quantities to be predicted, which we call causal predictands, allowing for multiple treated units with treatment adoption at possibly different points in time. We illustrate our methodology with an empirical application studying the effects of economic liberalization on real GDP per capita for Sub-Saharan African countries. Companion software packages are provided in Python, R, and Stata.

Stigma of welfare participation is important for policy and survey design, because it reduces program take-up and increases misreporting. Stigma is also relevant to the literature on social image concerns, yet empirical evidence is scant because stigma is difficult to empirically identify. We use a novel approach to studying stigma by examining the relationship between program participation in a recipient's local network and underreporting program participation in surveys. We find a robust negative relationship and provide evidence against explanations other than stigma. Stigma decreases when more peers engage in the stigmatized behavior and when such actions are less observable.

This paper explores the causal effects of inflation literacy using a two-step randomized controlled trial. The first step shows that qualitative information about inflation and monetary policy (Literacy treatment) enhances knowledge about these issues and raises both the likelihood of providing inflation predictions and trust in the central bank. The second step tests the joint impact of the Literacy treatment and further quantitative treatments. While the level of posterior expectations is affected only by quantitative information, inflation forecast uncertainty and trust react to both qualitative and quantitative information. Moreover, different information types may interact when impacting forecast uncertainty and trust.

A growing literature has shown that people sometimes prefer to randomize between two options. We investigate how prevalent this behavior is in an experiment using a novel and simple method. Subjects face a list of questions in which one of the alternatives is fixed and the other varies, like a Multiple Price List, but in each row they can randomize between the options. We find that the majority of subjects chose to randomize in the majority of questions, and notably, they did so for ranges of values that were “very large.”