We measure desired labour supply at the extensive (employment) margin in two representative surveys of the U.S. and German populations. We elicit reservation raises: the percent wage change that renders a given individual indifferent between employment and nonemployment. It is equal to her reservation wage divided by her actual, or potential, wage. The reservation raise distribution is the nonparametric aggregate labour supply curve. Locally, the curve exhibits large short-run elasticities above 3, consistent with business cycle evidence. For larger upward shifts, arc elasticities shrink towards 0.5, consistent with quasi-experimental evidence from tax holidays. Existing models fail to match this nonconstant, asymmetric curve.

Why do cities differ so much in productivity? A long literature has sought out systematic sources, such as inherent productivity advantages, market access, agglomeration forces, or sorting. We document that up to three quarters of the measured regional productivity dispersion is spurious, reflecting the “luck of the draw” of finite counts of idiosyncratically heterogeneous plants that happen to operate in a given location. The patterns are even more pronounced for new plants, hold for alternative productivity measures, and broadly extend to European countries. This large role for individual plants suggests a smaller role for places in driving regional differences.

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.

We study a mentoring program that aims to improve the labor-market prospects of school-attending adolescents from disadvantaged families by offering them a university-student mentor. Our RCT investigates program effectiveness on three outcome dimensions that are highly predictive of later labor-market success: math grades, patience/social skills, and labor-market orientation. For low-SES adolescents, the mentoring increases a combined index of the outcomes by over half a standard deviation after one year, with significant increases in each dimension. Part of the treatment effect is mediated by establishing mentors as attachment figures who provide guidance for the future. Effects on grades and labor-market orientation, but not on patience/social skills, persist three years after program start. By that time, the mentoring also improves early realizations of school-to-work transitions for low-SES adolescents. The mentoring is not effective for higher-SES adolescents. The results show that substituting lacking family support by other adults can help disadvantaged children at adolescent age.

We analyze how skill transferability and the local industry mix affect the adjustment costs of workers hit by a trade shock. Using German administrative data and novel measures of economic distance we construct an index of labor market absorptiveness that captures the degree to which workers from a particular industry are able to reallocate into other jobs. Among manufacturing workers, we find that the earnings loss associated with increased import exposure is much higher for those who live in the least absorptive regions. We conclude that the local industry composition plays an important role in the adjustment processes of workers.

Climate change and inequality are critical and interrelated defining issues for this century. Despite growing empirical evidence on the economic incidence of climate policies and impacts, mainstream model-based assessments are often silent on the interplay between climate change and economic inequality. For example, all the major model comparisons reviewed in IPCC neglect within-country inequalities. Here we fill this gap by presenting a model ensemble of eight large-scale Integrated Assessment Models belonging to different model paradigms and featuring economic heterogeneity. We study the distributional implications of Paris-aligned climate target of 1.5 degree and include different carbon revenue redistribution schemes. Moreover, we account for the economic inequalities resulting from residual and avoided climate impacts. We find that price-based climate policies without compensatory measures increase economic inequality in most countries and across models. However, revenue redistribution through equal per-capita transfers can offset this effect, leading to on average decrease in the Gini index by almost two points. When climate benefits are included, inequality is further reduced, but only in the long term. Around mid-century, the combination of dried-up carbon revenues and yet limited climate benefits leads to higher inequality under the Paris target than in the Reference scenario, indicating the need for further policy measures in the medium term.

We conduct a discrete choice experiment to investigate how the location of a firm in a rural or urban region affects the perceived job attractiveness for university students and graduates and, therewith, contributes to the rural–urban divide. We characterize the attractiveness of a location based on several dimensions (social life, public infrastructure and connectivity) and vary job design and contractual characteristics of the job. We find that job offers from companies in rural areas are generally considered less attractive, regardless of the attractiveness of the region. The negative perception is particularly pronounced among persons of urban origin and singles. In contrast, for individuals with partners and kids this preference is less pronounced. High-skilled individuals who originate from rural areas have no specific regional preference at all.