This paper builds on the Empirical Monte Carlo simulation approach to study the estimation of Timing-of-Events (ToE) models. We exploit rich Swedish data of unemployed job seekers with information on participation in a training program to simulate placebo treatment durations. We first use these simulations to examine which covariates are key confounders to be included in dynamic selection models for training participation. The joint inclusion of specific short-term employment history indicators (notably, the share of time spent in employment), together with baseline socio-economic characteristics, regional and inflow timing information, is important to deal with selection bias. Next, we omit subsets of explanatory variables and estimate ToE models with discrete distributions for the ensuing systematic unobserved heterogeneity. In many cases the ToE approach provides accurate effect estimates, especially if time-varying variation in the unemployment rate of the local labor market is taken into account. However, assuming too many or too few support points for unobserved heterogeneity may lead to large biases. Information criteria, in particular those penalizing parameter abundance, are useful to select the number of support points. A comparison with other duration models shows that a Stratified Cox model performs well with abundant multiple spells but less well when multiple spells are uncommon. The standard Cox regression model performs poorly in all configurations as it is unable to account for unobserved heterogeneity.

The percentage of people without children over their lifetime is approximately 25% in men and 20% in women. Individual diseases have been linked to childlessness, mostly in women, yet we lack a comprehensive picture of the effect of early-life diseases on lifetime childlessness. We examined all individuals born in 1956–1968 (men) and 1956–1973 (women) in Finland (n = 1,035,928) and Sweden (n = 1,509,092) to the completion of their reproductive lifespan in 2018. Leveraging nationwide registers, we associated sociodemographic and reproductive information with 414 diseases across 16 categories, using a population and matched-pair case–control design of siblings discordant for childlessness (71,524 full sisters and 77,622 full brothers). The strongest associations were mental–behavioral disorders (particularly among men), congenital anomalies and endocrine–nutritional–metabolic disorders (strongest among women). We identified new associations for inflammatory and autoimmune diseases. Associations were dependent on age at onset and mediated by singlehood and education. This evidence can be used to understand how disease contributes to involuntary childlessness.

We document the consequences of losing a job across countries using a harmonized research design and high-quality administrative registers. Workers in Denmark and Sweden experience the lowest earnings declines following job displacement, while workers in Italy, Spain, and Portugal experience losses three times as high. French and Austrian workers face earnings losses somewhere in between. Key to these differences is that Southern European workers are less likely to find employment following displacement. Loss of employer-specific wage premiums accounts for 40% to 95% of within-country wage declines. The use of active labor market policies predicts a significant portion of the cross-country heterogeneity in earnings losses.

Although there is a large gap between Black and White American life expectancies, the gap fell 48.9% between 1990-2018, mainly due to mortality declines among Black Americans. We examine age-specific mortality trends and racial gaps in life expectancy in rich and poor U.S. areas and with reference to six European countries. Inequalities in life expectancy are starker in the U.S. than in Europe. In 1990 White Americans and Europeans in rich areas had similar overall life expectancy, while life expectancy for White Americans in poor areas was lower. But since then even rich White Americans have lost ground relative to Europeans. Meanwhile, the gap in life expectancy between Black Americans and Europeans decreased by 8.3%. Black life expectancy increased more than White life expectancy in all U.S. areas, but improvements in poorer areas had the greatest impact on the racial life expectancy gap. The causes that contributed the most to Black mortality reductions included: Cancer, homicide, HIV, and causes originating in the fetal or infant period. Life expectancy for both Black and White Americans plateaued or slightly declined after 2012, but this stalling was most evident among Black Americans even prior to the COVID-19 pandemic. If improvements had continued at the 1990-2012 rate, the racial gap in life expectancy would have closed by 2036. European life expectancy also stalled after 2014. Still, the comparison with Europe suggests that mortality rates of both Black and White Americans could fall much further across all ages and in both rich and poor areas.

We study inequality in mortality in Finland using registry data that covers the whole population for years 1990-2018. We create municipality-level indexes of regional deprivation (poverty rate), and show how age-specifc mortality rates have evolved across regions and over time. The inequality in mortality has been remarkably low over the time period for most age groups. However, among young and prime-age males the mortality rates have been persistently higher in the poorer areas. For these age groups the leading causes of death are deaths of despair (alcohol and suicides) and accidents. For the cohorts that were young during the deep early-1990's recession, we also document higher inequality in middle-age mortality than for cohorts entering the labor market in recovery periods.

This paper studies how targeted wage subsidies affect the performance of the recruiting firms. Using Swedish matched employer-employee administrative data from the period 1998–2008, we show that treated firms substantially outperform other recruiting firms after hiring through subsidies, despite identical pre-treatment performance levels and trends in a wide set of key dimensions. The pattern is less clear from 2007 onwards, after a reform removed the involvement of caseworkers from the subsidy approval process. Overall, our results suggest that targeted employment subsidies can have large positive effects on post-match outcomes of the hiring firms, at least if the policy environment allows for pre-screening by caseworkers.

Genome-wide association studies (GWAS) have discovered thousands of replicable genetic associations, guiding drug target discovery and powering genetic prediction of human phenotypes and diseases. However, genetic associations can be affected by gene-environment correlations and non-random mating, which can lead to biased inferences in downstream analyses. Family-based GWAS (FGWAS) uses the natural experiment of random assignment of genotype within families to separate out the contribution of direct genetic effects (DGEs) - causal effects of alleles in an individual on an individual - from other factors contributing to genetic associations. Here, we report results from an FGWAS meta-analysis of 34 phenotypes from 17 cohorts. We found evidence that factors uncorrelated with DGEs make substantial contributions to genetic associations for 27 phenotypes, with population stratification confounding - a form of gene-environment correlation - likely the major cause. By estimating SNP heritability and genetic correlations using DGEs, we found evidence that assortative mating has led to overestimation of SNP heritability for 5 phenotypes and overestimation of the degree of shared genetic effects (pleiotropy) between 22 pairs of phenotypes. Polygenic predictors constructed from DGEs are particularly useful for studying natural selection, assortative mating, and indirect genetic effects (effects of relatives’ genes mediated through the family environment). We validate our meta-analysis results by predicting phenotypes in hold-out samples using polygenic predictors constructed from DGEs, achieving statistically significant out-of-sample prediction for 24 phenotypes with little attenuation of predictive power within-families. We provide FGWAS summary statistics for 34 phenotypes that can be used for downstream analyses. Our study provides both a template for performing FGWAS and an argument for its value for debiasing inferences and understanding the impact of environment and mating patterns.

We study the role of firm productivity in explaining the immigrant-native earnings gap using balance sheet and population-wide employer-employee data. The returns to working in firms with higher persistent productivity are especially high for immigrants, who gain the most from avoiding the least productive firms in which they are strongly over-represented. Immigrant-native skill differences can only partly explain the differential sorting across firms. Taken together, our results suggest group-specific barriers to climbing the productivity ladder. We find that one important barrier operates through manager-worker homophily, which reinforces the unequal access to high-productive firms and differential ability of extracting firm rents.

The paper provides among the first quasi-experimental estimates of the threat of unemployment insurance (UI) benefit sanctions on job-exit rates. Using a difference-in-differences design, I exploit two reforms of the Swedish UI system that made monitoring and sanctions considerably stricter at different points in time for (i) UI claimants and (ii) job-seekers who exhausted their UI benefits and therefore receive alternative “activity support” benefits instead. Results show that men (in particular if long-term unemployed) respond to monitoring and the threat of sanctions by finding jobs faster. By contrast, the existing literature has almost exclusively focused on estimating how job-finding rates respond for those actually receiving a sanction. I estimate such “sanction-imposition effects” and find that they are similar in size for men and women. I further show that properly aggregated sanction-imposition effects explain very little of the overall reform effects for males, and that they are sufficiently small to be consistent with the small and insignificant reform effects found for women. A direct policy implication is that the total impact of monitoring and sanctions may be severely underestimated when focusing only on the sanction imposition effects as is typically done in the literature.