We build a unified framework to quantitatively examine the demographic transition and industrial policies in contributing to China’s economic growth between 1976 and 2015. We find that the demographic transition and industrial policy changes by themselves account for a large fraction of the...

We provide evidence that graduated driver licensing (GDL) laws, originally intended to improve public safety, impact both high school completion and teen employment. Many teens use automobiles to commute both to school and to employment. Because school and work decisions are interrelated, the...

Scarcity is a ubiquitous experience, and existing evidence largely suggests that people become more myopic when they feel their resources are scarce. Importantly, evidence for this proposition comes primarily from contexts in which scarcity threatens needs that require resources imminently. The...

We specify and estimate a lifecycle model of consumption, housing demand and labor supply in an environment where individuals may file for bankruptcy or default on their mortgage. Uncertainty in the model is driven by house price shocks, education specific productivity shocks, and catastrophic...

We investigate the long-term effects of foreclosure-induced relocations on adolescents and their subsequent use of credit. We ask whether individuals who experience a foreclosure-induced move between the ages of 10 and 17 are more likely to exhibit signs of credit scarring later in life. To...

Replacement hiring—recruitment that seeks to replace positions vacated by workers who quit—plays a central role in establishment dynamics. We document this phenomenon using rich microdata on U.S. establishments, which frequently report no net change in their employment, often for years at a...

This paper examines whether neighborhoods that had been gentrifying lost their appeal during the pandemic because of COVID-induced health risks and increased work-from-home arrangements. By following the mobility pattern of residents in gentrifying neighborhoods in 39 major U.S. cities, we note...

Modeling advances create credit scores that predict default better overall, but raise concerns about their effect on protected groups. Focusing on low- and moderate-income (LMI) areas, we use an approach from the Fairness in Machine Learning literature — fairness constraints via group-specific...

This paper studies how past experiences with privacy shocks affect individuals’ take-up of precautionary behavior when faced with a new privacy shock in the context of credit markets. We focus on experiences with identity theft and data breaches, two kinds of privacy shocks that either...

We study how forcing financially distressed consumer debtors to repay a larger fraction of debt can lead them to misreport data fraudulently. Using a plausibly exogenous policy change that required debtors to increase repayment to creditors, we document that debtors manipulated data to avoid...