This paper studies how the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) affects market outcomes in the yogurt industry, with a focus on distributional effects through equilibrium pricing mechanism. More specifically, I conjecture the WIC benefits transforms the most elastic low-income consumers spread across products into most elastic for few selected products, raising market power to both WIC-approved products and non-WIC products. Using detailed scanner data, I first exploit WIC’s income eligibility cutoff in a regression discontinuity design and perform local randomization inference. I find that WIC participants pay higher unit prices, suggesting they are less price-sensitive for WIC-approved products. This finding is robust to eligibility manipulation, bandwidth choice, and measurement error. To capture equilibrium effects and evaluate alternative program designs, I estimate a structural discrete-choice model of demand and supply, augmented by micro data. The results indicate that the WIC program provides a partial “price relaxation” effect when participants purchase WIC products, making them inelastic to prices in consistent to the reduced-form conclusion. Counterfactual analyses show that the program benefits both WIC households and firms, while imposing costs on non-WIC consumers. Expanding the set of WIC-approved products could substantially improve program effectiveness at a lower efficiency cost.
This paper analyzes the toilet paper run of March 2020 across nine U.S. cities, examining the rationality behind the buying frenzy and evaluating the welfare effects of potential policy interventions. I develop a dynamic demand model that incorporates stockpiling behavior, persistent taste heterogeneity, rational expectations, product differentiation, and availability. Using panel scanner data from retail sales and household purchases (2018–2021), I structurally estimate the model with an innovative algorithm, iteratively updating simulated maximum likelihood estimators from the traditional split estimation procedure designed for homogeneous tastes. The findings suggest that rational consumers participated in the toilet paper run due to anticipated stockouts. Methodologically, I find that ignoring product availability and persistent taste heterogeneity reduces both the efficiency and accuracy of the estimation. Counterfactual simulations show that preemptive warnings about potential stockouts improve consumer welfare; however, such warnings are risky, as a general equilibrium analysis suggests that changes in behavior by a small proportion of consumers could still trigger a run. Surprisingly, increasing the availability of certain product sizes is found to decrease consumer welfare due to excessive stockpiling. Therefore, the autonomous quantity rationing imposed by retailers may have inadvertently reduced consumer welfare.
This paper estimates the household income effects of Xi Jinping’s "Big Bang" anti-corruption campaign in China. Using data from two household panel surveys (2010–2018), I apply a difference-in-difference (DID) framework that leverages temporal variations introduced by the Central Committee of Discipline Inspections. The results indicate a significant decline in household income following the campaign, an effect that remains robust across various specifications and placebo tests. Additionally, I document a post-campaign reduction in the income premium for politically connected groups, including Communist Party members, employees of State-Owned Enterprises (SOEs), and Public Institutions. I explore potential mechanisms behind this income contraction and find suggestive evidence pointing to capital misallocation between SOEs and private firms, likely driven by heightened political scrutiny and information asymmetry in banking. Furthermore, government transfers nearly halved post-campaign, worsening the income decline. However, households partially offset this income shock through reciprocal private transfers within social networks.
This paper aims to examine to what extent venture capitalists are informed about the evolution of start-up value and how predictive ability differ across VCs. The main empirical challenge is the lack of data. Researchers do not observe all the data available at the time of decision-making, nor VC expectations that directly determines decision. We adopt a moment inequality approach to set identify model parameters. We found that predictive accuracy increases with experience and network depth, indicating a potential positive feedback loop when VCs jointly invest.