This paper argues that an area-specific housing policy that aims to discourage speculators may lead to demand spillovers and increase housing prices in nearby areas. I use Korean administrative transactions, real estate registration, and large online platform data and leverage on a policy that required owner-occupancy for new home purchases. To measure the price changes after the policy, I estimate an empirical model that embeds a difference-in-differences design that compares the regions near the boundaries of the policy-applied neighborhoods, yielding several new results. First, owner-occupancy requirements indeed had significant price suppression effects in the treated areas compared to the untreated by about 6%. Second, the price increased more than the overall increase in the city in the nearby untreated areas, suggesting that speculative demand shifted towards the untreated areas with similar neighborhood characteristics. To quantify this mechanism, I set up a neighborhood sorting model of owner-occupant households and investors making housing purchase decisions, along with quantification plans that include the designation of speculative investors and structural analysis.

We develop a new dynamic continuous-time model of optimal consumption and savings with endogenous liquidity constraints. In addition to exogenously imposed liquidity constraints, we endogenize a liquidity constraint over which individuals can maintain a living standard. We show that the liquidity constraint endogenously determined becomes more tightened with a higher living standard. The optimal strategies with endogenous liquidity constraints are derived in closed form. We find a significant discontinuity and dramatic change in the effect of endogenous liquidity constraints on the optimal strategies, which in turn is determined by levels of current borrowing against future income. We show that consumption changes with respect to changes in wealth are greater with higher living standards when the amount of borrowing is large. However, this result can be reversed when the amount of borrowing is small. These findings are particularly important in addressing the interdependence of consumption and liquidity constraints to maintain a living standard in today's inflation crisis.

We compare the two similar yet distinct early childhood education (ECE) programs while addressing the concerns associated with comparing them. We revisit data from a series of randomized early childhood education interventions to investigate the effects of ECE participation at ages 0 to 3 on a child's cognitive outcome. We document treatment effect heterogeneity in ECE programs by drawing on insights from the causal forest algorithm following Athey and Wager (2018). In particular, children accrue different effects from participation in ECE programs, and the populations differ across programs. Hence, a natural question is what would be the effect of one if randomized into another population. Using a forest built on federal program data and applying state program data to obtain treatment effect estimates for a population resembling each other, we consider treatment heterogeneity and differences between the two program characteristics. The results suggest that when designed and targeted well, ECE programs may be a very effective tool to improve the lives of the disadvantaged population.

We study the rise of non-medical stimulant use for academic performance using a model with relative-performance externalities. Students compete for rank, where taking a stimulant improves effective performance but entails costs. Because payoffs from academic competition depend on others' performance, students' stimulant usage exhibits strategic complementarities: as more individuals use stimulants, others face stronger incentives to follow in order to avoid falling behind. We identify the model using prescription trends and seasonality in the U.S. and South Korea, cross-regional variation in academic competitiveness, and our own survey evidence on students' incentives, beliefs, and perceived costs. The estimated strategic complementarities are substantial and give rise to multiple equilibria: one with relatively low drug use and another with very high usage, in which nearly 90\% of individuals take stimulants. We then use the estimated model to evaluate counterfactual policies that (i) reduce the salience of relative evaluation, (ii) limit the competitive advantage from stimulants, particularly through academic accommodations, or (iii) require stricter prescribing rules to reduce potential misuse. These results highlight that addictive drug use can emerge even among perfectly rational agents when incentives are structured to make stimulant use a rational strategy for competing, and underscore the importance of accounting for these dynamics when designing penalties for stimulant misuse and setting educational accommodations.

We document that during the recent period of a historically high inflation era, the prices of smaller package sizes have increased at significantly faster rates than those of larger packages, even for identical products. We show that because low-income households disproportionately purchase smaller-packaged goods, they have experienced substantially higher perceived inflation. Using detailed store location data and household panels from the Numerator dataset, we find that low-income households face limited access to larger package sizes. Brands that primarily offer large sizes are less prevalent in low-income neighborhoods and, even within the same brand, stores in these areas disproportionately stock smaller packages. Furthermore, conditional on residing in areas with limited package size variety, high-income households are much more likely to travel greater distances to access larger, more cost-effective packages, effectively mitigating their exposure to inflation. In contrast, low-income households tend to shop locally and are less able to hedge against these rising prices. The correlation between package size and household income is considerably weaker for online shoppers, whose geographic access constraints are minimized. Our findings highlight a novel mechanism through which inflation disproportionately burdens low-income households.