Rising Concentration of Household Shopping, Superstar Firms, and Implications for Retail Markups (with Justin Leung)
Accepted, American Economic Journal: Applied Economics
Abstract: This paper documents an increase in concentration of household shopping in the US retail sector from 2004-2019. Despite a growing number of stores, households visit fewer stores, do more one-stop shopping, and increasingly shop at different retailers from each other. We find that the increasing availability of superstar retailers, rises in product variety within stores, and the rise of online shopping contribute to these trends. We explore how these trends are linked with rising retail markups. Our calibration suggests a 5-10 percentage point increase in aggregate retail markups during this period.
Previously circulated as "Rising Retail Concentration: Superstar Firms and Household Demand"
Big-Box Store Expansion and Consumer Welfare (with Justin Leung)
Abstract: Supercenters and warehouse clubs have surged in the US, offering many product categories at low prices. Complementing a literature on their competitive effects, we study how these big-box stores affect consumer welfare by impacting shopping behavior. Our event studies show consumers change product categories per trip, adjust spending across store formats, and pay lower prices after store entries. We develop a novel demand model to incorporate these choices across stores and categories, and separately quantify consumption gains and trip-cost savings. We find households benefit substantially from consuming in supercenters relative to competing retailers, highlighting the importance of the store format.
AI for Fairness? The Role of Generative Tools in Shaping Freelancer Success (with Jingman Cao)
Abstract: Online freelance platforms have expanded access to flexible work, but persistent inequalities remain. This paper examines whether generative artificial intelligence (GenAI) tools can help reduce disparities faced by disadvantaged workers, using high-frequency panel data from a major digital labor platform. Among various worker characteristics, language proficiency shows the most significant shifts. Following the launch of ChatGPT, we find that the gap in earnings and job count between native and non-native English speakers narrowed. Non-native speakers gained access to more complex, higher-paying jobs, experienced lower job displacement, and connected more frequently with clients from high-income countries. While overall entry and activity gaps remained, we observe shifts in participation across job categories. Together, the findings suggest that GenAI can help reduce language-based barriers and expand opportunity in digital labor markets.
Period Relief: The Effects of Menstrual Hygiene Tax Exemptions (with Sumit Agarwal, Joysankar Bhattacharya and Xixi Shen)
Abstract: This paper examines the effects of a nationwide tax exemption on menstrual hygiene products in India. Using high-frequency retail data and nationally representative surveys, we find that the exemption reduced prices, spurred product entry, and shifted demand toward lower-cost options. Existing consumers spent more overall while purchasing less frequently. Survey evidence shows broader gains in menstrual hygiene adoption and modest improvements in educational attainment, particularly among disadvantaged women. These findings illustrate how targeted fiscal policy can shape market behavior and potentially support improvements in well-being in a developing country context.
“Vertical Control and Retail Competition: Evidence from Consumer Battery Industry” (with Tiffany Tsai)