Wage mobility reduces the persistence of wage inequality. We develop a framework to quantify the contribution of employer-to-employer movers to aggregate wage mobility. Using three decades of German social security data, we find that inequality increased while aggregate wage mobility decreased. Employer-to-employer movers exhibit higher wage mobility, mainly due to changes in employer wage premia at job change. The massive structural changes following German unification temporarily led to a high number of movers, which in turn boosted aggregate wage mobility. Wage mobility is much lower at the bottom of the wage distribution, and the decline in aggregate wage mobility since the 1980s is concentrated there. The overall decline can be mostly attributed to a reduction in wage mobility per mover, which is due to a compositional shift toward lower-wage movers.

This paper investigates the critical role of church membership in the process of economic recovery after high-impact natural disasters. We document a significant adverse treatment effect of the 2005 hurricane season in the Southeastern United States on establishment-level productivity. However, we find that establishments in counties with higher rates of church membership saw a significantly stronger recovery in terms of productivity for 2005–10. We also show that church membership is correlated with post-disaster entrepreneurship activities and population growth.

This paper investigates forecast aggregation via the random subspace regressions method (RSM) and explores the potential link between RSM and the Shapley value decomposition (SVD) using the US GDP growth rates. This technique combination enables handling high-dimensional data and reveals the relative importance of each individual forecast. First, it is possible to enhance forecasting performance in certain practical instances by randomly selecting smaller subsets of individual forecasts and obtaining a new set of predictions based on a regression-based weighting scheme. The optimal value of selected individual forecasts is also empirically studied. Then, a connection between RSM and SVD is proposed, enabling the examination of each individual forecast’s contribution to the final prediction, even when there is a large number of forecasts. This approach is model-agnostic (can be applied to any set of predictions) and facilitates understanding of how the aggregated prediction is obtained based on individual forecasts, which is crucial for decision-makers.

Using proprietary data from AngelList Talent, we study how startup job seekers’ search and application behavior changed during the COVID-19 downturn. We find that workers shifted their searches and applications away from less-established startups and toward more-established ones, even within the same individual over time. At the firm level, this shift was not offset by an influx of new job seekers. Less-established startups experienced a relative decline in the quantity and quality of applications, ultimately affecting their hiring. Our findings uncover a flight-to-safety channel in the labor market that may amplify the procyclical nature of entrepreneurial activities.