Recent studies have shown that idiosyncratic labor income risk becomes more left-skewed during recessions. This procyclical skewness arises from a combination of higher downside risk and lower chances of upward surprises during recessions. While this much is known, some important open questions remain. For example, how robust are these patterns across countries that differ in their institutions and policies, as well as across genders, education groups, and occupations, among others? What is the contribution of wages versus hours to procyclical skewness of earnings changes? To what extent can skewness fluctuations in individual earnings be smoothed within households or with government policies? Using panel data from the United States, Germany, Sweden, and France, we find four main results. First, the skewness of individual income growth (before-tax/transfer) is procyclical while its variance is flat and acyclical in all three countries. Second, this result holds even for full-time workers continuously employed in the same establishment, indicating that the hours margin is not the main driver; additional analyses of hours and wages confirm that both margins are important. Third, within-household smoothing does not seem effective at mitigating skewness fluctuations. Fourth, tax-and-transfer policies blunt some of the largest declines in incomes, reducing procyclical fluctuations in skewness.

In 2015-2016 Germany experienced a wave of predominantly low-skilled refugee immigration. We evaluate its macroeconomic and distributional effects using a quantitative overlapping generations model calibrated using German micro data to replicate education and productivity differentials between foreign born and native workers. Workers are modelled as imperfect substitutes in aggregate production leading to endogenous wage differentials. We simulate the dynamic effects of this refugee wave, with specific focus on the welfare impact on low skilled natives. Our results indicate that the small losses this group suffers can be compensated by welfare gains of other parts of the native population.

We develop a novel empirical approach to identify the effectiveness of policies against a pandemic. The essence of our approach is the insight that epidemic dynamics are best tracked over stages, rather than over time. We use a normalization procedure, built around making the pre-policy paths of the epidemic identical across regions, to uncover regional variation in the stage of the epidemic at the time of policy implementation. This variation delivers clean identification of the policy effect based on the epidemic path of a leading region that serves as a counterfactual for other regions. We apply our method to evaluate the effectiveness of the nationwide stay-home policy enacted in Spain against the Covid-19 pandemic. We find that the policy saved 15.9% of lives. Its effectiveness evolves with the epidemic and is larger when implemented at earlier stages.

Observed wage dynamics are the result of both exogenous factors, such as productivity shocks, and workers’ choices. Using data from administrative German social security records, I document that the extent of occupational switching upon changing jobs is high, and that the choice to change occupations is of major relevance for realized wage changes. I develop a structural model in which workers optimally switch occupations in response to idiosyncratic productivity shocks. In the model, switching occupations entails a cost, because workers can only imperfectly transfer human capital. The degree of transferability depends on the distance in the task space. Disentangling the role of choices and shocks, I find that the endogenous choice of occupations accounts for 26% of the dispersion of wage changes after controlling for human capital changes.