We use Danish administrative data to examine the effects of parental death on labor market outcomes. Leveraging the timing of sudden, first parental deaths and a matched-control difference-in-differences strategy, we find that men’s earnings decline by 2 percent, while women’s earnings decline by 3 percent following a parental death. Both women and men experience mental health deterioration, leading to increased use of psychological assistance and prescriptions for mental health conditions and opioids. Women with young children experience a comparatively larger earnings decline (around 4 percent) likely due to the loss of informal childcare.
A common interpretation of Pareto-efficient policies is that, for some cardinal utility representations of preferences, they maximize utilitarian welfare. We show in the context of income taxation that such cardinalizations are often extreme, requiring unbounded curvature of utility with respect to consumption. Taxes can be justified as utilitarian without these extreme cardinalizations if and only if revenues are decreasing and concave in a class of narrowly targeted tax cuts. We reformulate this condition as a sufficient-statistics test. The test fails whenever elasticities of taxable income are too heterogeneous within some income level, as we argue is empirically likely.
We study how international migrant income prospects affect long-run development in origin areas. We leverage the 1997 Asian Financial Crisis exchange rate shocks in a shift-share identification strategy across Philippine provinces. Initial migrant income shocks are magnified six-fold over time, increasing domestic income, education levels, migrant skills, and high-skilled migration. Remarkably, 74.9 percent of long-run income gains come from domestic rather than migrant income. Trade driven impacts of exchange rate shocks are orthogonal to effects via migrant income. A structural model reveals that 19.7 percent of long-run income gains stem from educational investments. International migration fosters broad economic development in origin communities.
We explore how traders’ equity capitalization influences asset prices in a framework that accounts for market power. In our model, traders with capital constraints engage in transactions in an imperfectly competitive market. We demonstrate that looser capital constraints elevate both asset prices and price impact, the latter diminishing market liquidity. Using Canadian Treasury auction data, we illustrate how to apply our model to quantify these effects. We estimate the shadow costs of capital constraints by leveraging a temporary policy exemption during 2020–2021. We show that while these constraints are only infrequently binding, their relative impact when activated can be sizable.
We develop a simple multilayer network model in which agents allocate effort across layers with heterogeneous structures, subject to an aggregate effort constraint. Incentives are shaped by agents’ network positions within each layer, and equilibrium behavior reflects both within- and cross-layer interactions. We analyze how shocks propagate through the network and characterize optimal targeting interventions. Our results show that effective policy design must account for effort allocation across layers. We also demonstrate that predictions from monolayer models can diverge sharply from those of multilayer models, underscoring the importance of accounting for network complexity in both empirical and policy analyses.
Equal pay laws increasingly require that workers with different group identities doing “similar” work are paid equal wages within firm. We study such “equal pay for similar work” (EPSW) policies theoretically and test our models’ predictions empirically using evidence from a 2009 gender-based Chilean EPSW. Under EPSW, firms segregate their workforce by gender. When there are more men than women in a labor market, EPSW increases the gender wage gap.
We revisit the role of temporary layoffs in the business cycle. While some have emphasized a stabilizing effect due to recall hiring, we quantify from the data an important countercyclical destabilizing effect due to “loss-of-recall,” whereby workers in temporary-layoff unemployment lose their job permanently. We develop a quantitative model allowing for endogenous flows of workers across employment and both temporary-layoff and jobless unemployment. The model captures both pre- and post-pandemic unemployment dynamics, including the contractionary role of loss-of-recall. We use our structural model to show that the Paycheck Protection Program generated sizable employment gains, in part by significantly reducing loss-of-recall.
Captive finance subsidiaries create a channel for trade policy to affect consumer credit. Examining the impact of the Trump administration’s metal tariffs on captive automobile lenders, we find that consumers received higher interest rates from captive lenders after the tariffs relative to unaffected noncaptive lenders. Further, we document a disparate impact on low-income borrowers and in areas with less lending competition. Our results suggest that tariffs may impact not only the price of goods but also the financing terms of purchases. Thus, focusing solely on directly affected product prices may underestimate tariff pass-through significantly.
Principal-agent problems often extend beyond what can be directly addressed through conventional incentive arrangements. We examine a context where physicians are likely under-incentivized to minimize total medical costs until their private financial interests align with those of patients. Leveraging novel data on physician ownership of ambulatory surgery centers——that is, same-day facilities——we show that these equity holdings cause a substitution away from higher cost, rival settings that lowers Medicare spending by 10–40 percent per physician. We find no clear evidence of perverse behavior following these investments. Instead, our findings demonstrate how entrepreneurial activity can indirectly limit principal-agent problems and improve efficiency.
This paper studies which misspecified models are likely to persist when decision-makers compare them with competing models. The main result characterizes such models based on two features that can be derived from primitives: The model’s asymptotic accuracy in predicting the equilibrium distribution of observed outcomes and the “tightness” of the prior around such equilibria. Misspecified models can be robust, persisting against any arbitrary competing model—including the true model—despite decision-makers observing an infinite amount of data. Moreover, simple misspecified models equipped with entrenched priors can be more robust than complex correctly specified models.