In most disability insurance programs beneficiaries lose some or all of their benefits if they earn above an earnings threshold. While intended to screen out applicants with high remaining working capacity, earnings limits can also distort the labor supply of beneficiaries. We develop a simple...

We revisit the much-investigated relationship between schooling and health, focusing on cognitive abilities at older ages using the Harmonized Cognition Assessment Protocol in the Health & Retirement Study. To address endogeneity concerns, we employ a nonparametric partial identification...

This paper proposes a causal decomposition framework for settings in which an initial regime randomization influences the timing of a treatment duration. The initial randomization and treatment affect in turn a duration outcome of interest. Our empirical application considers the survival of...

We develop an equilibrium model of the labor market to investigate the joint evolution of gender gaps in labor force participation and wages. We do this overall and by task-based occupation and skill, which allows us to study distributional effects. We structurally estimate the model using data...

We use regional variation in the American Recovery and Reinvestment Act (2009-2012) to analyze the effect of government spending on consumer spending. Our consumption data come from household-level retail purchases in the Nielsen scanner data and auto purchases from Equifax credit balances. We...

Contrary to most existing studies of the literature that assumed that the effects of real exchange rate (RE) misalignment on trade flows are symmetric, this paper considers a more general and realistic framework allowing for possible asymmetric effects. We use monthly time-series data over the...

We provide the first analysis of racial in-group bias in Type-I and Type-II errors. Using player-referee matched data from NBA games we show that there is no overall racial bias or in-group bias in foul calls made by referees. Similarly, there is no racial bias or in-group bias in Type-I errors...