Research

Since 2009, U.S. hospitals have faced persistent shortages of generic injectable drugs, while their production has shifted toward the Global South. To assess the role of offshoring, I construct a new dataset mapping these drugs to their manufacturing plants and show that offshoring increases shortage incidence and duration. To explain this relationship, I develop and estimate a model of global procurement that quantifies drug manufacturers' trade-off between cost-cutting and supply reliability. Limited transparency makes reliability difficult to reward, while prices and capacity adjust slowly after disruptions. Offshoring magnifies these pre-existing frictions by expanding access to cheaper but riskier plants. To quantify unmet demand and its welfare cost, I develop a censored-demand estimator and derive realized consumer surplus under rationing in closed form. Counterfactuals show that reshoring subsidies and price premia during shortages do little to reduce unmet demand. A failure-to-supply penalty of half the contract price per missing unit induces larger buffers, reducing the expected share of unmet demand by 14 percent while raising contract prices by 9 percent. Improved access nearly offsets the losses from higher prices, with modest gains in consumer surplus when fines are rebated. Procurement contracts that reward resilient capacity before disruptions can therefore reduce shortages without reversing offshoring.

Large language models (LLMs) like ChatGPT have significantly lowered the cost of producing written content. This paper studies how LLMs, through lowering writing costs, disrupt markets that traditionally relied on writing as a costly signal of quality (e.g., job applications, college essays). Using data from Freelancer.com, a major digital labor platform, we explore the effects of LLMs' disruption of labor market signaling on equilibrium market outcomes. We develop a novel LLM-based measure to quantify the extent to which an application is tailored to a given job posting. Taking the measure to the data, we find that employers have a high willingness to pay for workers with more customized applications in the period before LLMs are introduced, but not after. To isolate and quantify the effect of LLMs' disruption of signaling on equilibrium outcomes, we develop and estimate a structural model of labor market signaling, in which workers invest costly effort to produce noisy signals that predict their ability in equilibrium. We use the estimated model to simulate a counterfactual equilibrium in which LLMs render written applications useless in signaling workers' ability. Without costly signaling, employers are less able to identify high-ability workers, causing the market to become significantly less meritocratic: compared to the pre-LLM equilibrium, workers in the top quintile of the ability distribution are hired 19% less often, workers in the bottom quintile are hired 14% more often.

We study the role of newspapers in the migration decisions of rural individuals in the 1870-1940 United States. Contributing to the urban and health economics literature, we offer new insights about how information, specifically newspaper portrayals of public health advancements like water filtration and sewage systems, shapes rural-urban migration patterns. We show that access to information about urban health conditions through newspapers played a crucial role in encouraging rural individuals to move to cities over the turn of the 20th century. By exploiting a novel linkage between full-count U.S. census data and a unique historical newspaper dataset at the county level, which leverages text-mining and Natural Language Processing (NLP) algorithms, we provide novel evidence that rural individuals responded to newspaper narratives on public health investments and disease occurrences. Rural migrants with access to information about public health investments migrated in higher proportion to sanitation-adopting cities compared to rural migrants with no access to such information, and avoided cities affected by epidemics more than their non-informed counterparts. This finding is consistent with the literature suggesting that such investments significantly reduced mortality from waterborne diseases (typhoid and diphtheria) and improved quality of life, making cities more attractive places to live. As policymakers consider strategies to revitalize urban areas in the post-pandemic era, our study highlights the potential importance of information dissemination in promoting urban growth and development.

Enforcement of quality regulations in the Global North may decrease the quality of goods distributed to the Global South, due to the rerouting by manufacturers of "sub-quality" products to less regulated markets. This paper studies the global redistribution of products recalled in highly regulated markets, such as the United States and Europe, when the manufacturers are global firms. Are new global manufacturing forces differentially allocating their products based on differentials in regulatory enforcement among destination markets? To answer these questions, I digitized new U.S. data on pharmaceutical product recalls and warning letters to foreign manufacturing facilities, which I merge with detailed descriptions extracted from Indian customs manifests. Using text mining techniques, I trace global exports of drug produced by Indian drug manufacturers and study what happens to global exports after an Indian product is recalled in the U.S. After a recall, I find evidence that firms reduce U.S. sales and reallocate production to other (less regulated) markets, such as African and South-Asian markets. Such behavior may result in an equilibrium in which high-quality products are traded with the North and sub-optimal quality products are diverted to the South. This may have important policy implications if more stringent quality enforcement in the North widens the differential in regulatory standards with the South. Abilities for global manufacturers to arbitrage exports based on differentials in global regulatory standards may lead to more product differentiation, resulting in lower-quality batches of products being sent to South countries with less regulated markets. This may also have implications for product availability in the North, as suppliers now located in the South may have lower incentives to quickly correct manufacturing quality issues if they can still distribute these products to South markets.

This paper provides a first empirical study of how openness to international trade in news products, a phenomenon largely facilitated by the digitalization of newspapers, may impact the characteristics of the information products available to consumers. Based on a case study of the entry of French media firms in Francophone Africa, I build a new dataset of more than 800 000 newspaper articles over the period 2005 to 2017. Using text mining techniques, I construct a five-dimensional set of newspaper characteristics to qualitatively analyze newspaper data. My evidence suggests that the entry of French digital newspapers, which produce a relatively low share of local news and whose websites are generally uniformly targeting all Francophone African countries, lead to a significant decrease of the diversity of subjects treated by Francophone African newspapers, characterized by a strong and significant increase of the share of local news, and a small decrease of the total number of articles related to France. I also find a slight but significant impact of the penetration of French digital newspapers on two indicators of newspaper format, namely a small increase of the average frequency of publication of Francophone African newspapers, and a very small decrease of the mean wordcount per articles.