Research Database

Many U.S. households have significant wealth late in life, contrary to the predictions of a simple life-cycle model. In this paper, we document stark differences between U.S. and Sweden regarding out-of-pocket medical and long-term-care expenses late in life, and use them to investigate their role in discouraging the elderly from dissaving. Using a consumption-saving model in retirement with significant uninsurable expense risk, we find that medical expense risk accounts for a quarter of the U.S.-Sweden difference in retirees' dissaving patterns. Furthermore, medical expense risk affects primarily financial assets, while its impact on housing is limited.

While the savings of retired singles tend to fall with age, those of retired couples tend to rise. We estimate a rich model of retired singles and couples with bequest motives and uncertain longevity and medical expenses. Our estimates imply that while medical expenses are an important driver of the savings of middle-income singles, bequest motives matter for couples and high-income singles, and generate transfers to non-spousal heirs whenever a household member dies. The interaction of medical expenses and bequest motives is a crucial determinant of savings for all retirees. Hence, to understand savings, it is important to model household structure, medical expenses, and bequest motives.

We study optimal savings policies when there is a dual concern about undersaving for retirement and income inequality. Agents differ in present bias and earnings ability, both unobservable to a planner with paternalistic and redistributive motives. We characterize the solution to this two-dimensional screening problem and provide a decentralization using realistic policy instruments: mandatory savings at low incomes but a choice between subsidized savings vehicles at high incomes—resembling Social Security, 401(k), and IRA accounts in the US. Offering more savings choice at higher incomes facilitates redistribution. To solve large-scale versions of this problem numerically, we propose a general, computationally stable, and efficient active-set algorithm. Relative to the current US retirement system, we find significant welfare gains from increasing mandatory savings and limiting savings choice at low incomes.

We develop a job ladder model with labor reallocation across firms and regions, and estimate it on matched employer-employee data to study the large and persistent real wage gap between East and West Germany. We find that the wage gap is mostly due to firms paying higher wages per efficiency unit in West Germany and quantify a rich set of frictions preventing worker reallocation across space and across firms. We find that three spatial barriers impede East Germans’ ability to migrate West: migration costs, a preference to live in the East, and fewer job opportunities received from the West. The estimated model highlights that the spatial barriers needed to generate the large wage gap between East and West are small relative to the frictions preventing the reallocation of labor across firms. Therefore, policies that directly promote regional integration lead to smaller aggregate benefits than equally costly hiring subsidies within region.

Why do young firms pay less? Using confidential microdata from the US Census Bureau, we find lower earnings among workers at young firms. However, we argue that such measurement is likely subject to worker and firm selection. Exploiting the two-sided panel nature of the data to control for relevant dimensions of worker and firm heterogeneity, we uncover a positive and significant young-firm pay premium. Furthermore, we show that worker selection at firm birth is related to future firm dynamics, including survival and growth. We tie our empirical findings to a simple model of pay, employment, and dynamics of young firms.

Tracking human activity in real time and at fine spatial scale is particularly valuable during episodes such as the COVID-19 pandemic. In this paper, we discuss the suitability of smartphone data for quantifying movement and social contact. We show that these data cover broad sections of the US population and exhibit movement patterns similar to conventional survey data. We develop and make publicly available a location exposure index that summarizes county-to-county movements and a device exposure index that quantifies social contact within venues. We use these indices to document how pandemic-induced reductions in activity vary across people and places.

Over the last two decades, the literature on comparative development has moved from country-level to within-country analyses. The questions asked have expanded, as economists have used satellite images of light density at night and other big spatial data to proxy for development at the desired level. The focus has also shifted from uncovering correlations to identifying causal relations, using elaborate econometric techniques including spatial regression discontinuity designs. In this survey we show how the combination of geographic information systems with insights from disciplines ranging from the earth sciences to linguistics and history has transformed the research landscape on the roots of the spatial patterns of development. We discuss the limitations of the luminosity data and associated econometric techniques and conclude by offering some thoughts on future research.

Defaults have been shown to have a powerful effect on retirement saving behavior yet there is limited research on who is most affected by defaults and whether this varies based on features of the choice environment. Using administrative data on employer-sponsored retirement accounts linked to survey data, we estimate the relationship between retirement saving choices and individual characteristics – long-term discounting, present bias, financial literacy, and exponential-growth bias – under two distinct choice environments: an opt-in regime and an auto-enrollment regime. Consistent with our conceptual model, we find that the determinants of following the default and contribution behavior are regime-specific. Under the opt-in regime, financial literacy plays an important role in predicting total contributions, active saving choices, and maxing out contributions in the tax-preferred account. In contrast, under the auto-enrollment regime, present bias is the most significant behavioral predictor of contribution behavior. A causal interpretation of the estimates suggests that auto-enrollment increases saving primarily among those with low financial literacy.

We harmonize the results of 42 different data sets and studies dating back to the early 20th century to construct a time series of college attendance patterns for the United States. We find an important reversal around the time of World War II: before that time, family characteristics such as income were the better predictor of college attendance; afterwards, academic ability was the better predictor. We construct a model of college choice that can explain this reversal. The model's central mechanism is an exogenous rise in the demand for college that leads better colleges to become oversubscribed. These colleges institute selective admissions and raise their quality relative to the remaining colleges, as in Hoxby (2009). Rising quality at better colleges attracts high-ability students, while falling quality at the remaining colleges dissuades low-ability students, generating the reversal.

The location of individuals determines their job opportunities, living amenities, and housing costs. We argue that it is useful to conceptualize the location choice of individuals as a decision to invest in a ‘location asset’. This asset has a cost equal to the location’s rent, and a payoff through better job opportunities and, potentially, more human capital for the individual and her children. As with any asset, savers in the location asset transfer resources into the future by going to expensive locations with good future opportunities. In contrast, borrowers transfer resources to the present by going to cheap locations that offer few other advantages. As in a standard portfolio problem, holdings of this asset depend on the comparison of its rate of return with that of other assets. Differently from other assets, the location asset is not subject to borrowing constraints, so it is used by individuals with little or no wealth that want to borrow. We provide an analytical model to make this idea precise and to derive a number of related implications, including an agent’s mobility choices after experiencing negative income shocks. The model can rationalize why low wealth individuals locate in low income regions with low opportunities even in the absence of mobility costs. We document the investment dimension of location, and confirm the core predictions of our theory with French individual panel data from tax returns.