We establish currency as an important factor shaping global portfolios. Using a new security-level data set, we demonstrate that investor holdings are biased toward their own currencies to such an extent that countries typically hold most of the foreign-debt securities denominated in their currency. While large firms issue in foreign currency and borrow from foreigners, most firms issue only in local currency and do not directly access foreign capital. These patterns hold broadly across countries except for the United States, as foreign investors hold significant shares of US dollar bonds. The share of dollar-denominated cross-border holdings surged after 2008.

Using a randomized experiment, this study investigates the impact of sustained investment in parenting, from pregnancy until age 5, in the context of extensive welfare provision. Providing the Preparing for Life program, incorporating home visiting, group parenting, and baby massage, to disadvantaged Irish families raised children’s cognitive and socioemotional/behavioral scores by two-thirds and one-quarter of a standard deviation, respectively. There were few differential effects by gender and stronger gains for firstborns and lower-resource households. The program also narrowed the socioeconomic gap in children’s skills. Analyses account for small sample size, differential attrition, multiple testing, contamination, and performance bias.

We study how heterogeneity in performance evaluations across supervisors affects employee and supervisor careers and firm outcomes using data on the performance system of a Scandinavian service sector firm. Supervisors vary widely in how they rate subordinates of similar quality. In our model, this ratings heterogeneity can arise because supervisors can differ in their ability to manage subordinates or in their leniency when rating subordinates. Furthermore, firms might or might not be informed about this heterogeneity. The evidence suggests that supervisor heterogeneity stems, in part, from real differences in managerial ability that firms are partially informed about.

We study the effects of industrial robots on US labor markets. We show theoretically that robots may reduce employment and wages and that their local impacts can be estimated using variation in exposure to robots—defined from industry-level advances in robotics and local industry employment. We estimate robust negative effects of robots on employment and wages across commuting zones. We also show that areas most exposed to robots after 1990 do not exhibit any differential trends before then, and robots’ impact is distinct from other capital and technologies. One more robot per thousand workers reduces the employment-to-population ratio by 0.2 percentage points and wages by 0.42%.

We revisit an old question: does industry labor reallocation affect the business cycle? Our empirical methodology exploits variation in a local labor market’s exposure to industry reallocation on the basis of the area’s initial industry composition and national industry employment trends for identification. Applied to confidential employment data over 1980–2014, we find sharp evidence of reallocation contributing to higher local area unemployment if it occurs during a national recession but little difference in outcomes during an expansion. A multiarea, multisector search-and-matching model with imperfect mobility across industries and downward nominal wage rigidity can reproduce these cross-sectional patterns.

We develop a model of gross capital flows and analyze their role in global financial stability. In our model, consistent with the data, when a country experiences asset fire sales, foreign investments exit (fickleness), while domestic investments abroad return home (retrenchment). When countries have symmetric expected returns and financial development, the benefits of retrenchment dominate the costs of fickleness and gross flows increase fire-sale prices. Fickleness, however, creates a coordination problem since it encourages local policy makers to restrict capital inflows. When countries are asymmetric, capital flows are driven by additional mechanisms—reach for safety and reach for yield—that can destabilize the receiving country.

For many products, platforms enable sellers to transact with buyers. We show that the competitive conditions among sellers shape the market structure in platform industries. If product market competition is tough, sellers avoid competitors by joining different platforms. This allows platforms to sustain high fees and explains why, for example, in some online markets, several homogeneous platforms segment the market. Instead, if product market competition is soft, agglomeration on a single platform emerges, and platforms fight for the dominant position. These insights give rise to novel predictions. For instance, market concentration and fees are negatively correlated in platform industries, which inverts the standard logic of competition.

Older wealth holders spend down assets much more slowly than predicted by classic life-cycle models. This paper introduces health-dependent utility into a model with incomplete markets in which preferences for bequests, expenditures when in need of long-term care, and ordinary consumption combine with health and longevity uncertainty to explain saving behavior. To sharply identify motives, it develops strategic survey questions (SSQs) that elicit stated preferences. The model is estimated using these SSQs and wealth data from the Vanguard Research Initiative. The desire to self-insure against long-term-care risk explains a substantial fraction of the wealth holding of many older Americans.