Spatial segregation of low- and high-wage workers is a persistent economic issue with broad social implications. Using social security data and an AKM wage decomposition, this paper examines spatial wage inequality in West Germany. Spatial inequality in log wages rose sharply between 1998 and 2008, mainly due to increased variance in worker pay premiums across regions (48%) and stronger positive spatial assortative matching of workers and establishments (40%), i.e. colocation. Changes in establishment wage premia are mostly unrelated to rising colocation whereas labor mobility even reduced it. Instead, growth in worker pay premiums among stayers was concentrated in regions where high-wage workers and high-wage establishments were overrepresented already in the 1990s and, thus, magnified pre-existing colocation leading to ‘colocation without relocation’. Germany’s rising trade surplus, especially with Eastern Europe, boosted stayers’ worker pay premiums in those ex-ante high-wage regions and fully explains rising colocation.

We examine employment and patient outcomes at hospitals acquired by private equity (PE) firms and PE-backed hospitals. While employment declines at PE-acquired hospitals, core medical workers (physicians, nurses, and pharmacists) increase significantly. The proportion of wages paid to core workers increases at PE-acquired hospitals whereas the proportion paid to administrative employees declines. These results are most pronounced for deals where the acquirers are publicly traded PE-backed hospitals. Non-PE-backed acquirers also cut employment but do not increase core workers or reduce administrative expenditures. Finally, PE-backed acquirers are not associated with worse patient satisfaction or mortality rates compared to their non-PE-backed counterparts.

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.

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.

Firm training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of automation risk based on tasks performed at work. Our analysis reveals substantial within-occupation variation in automation risk, overlooked by existing occupation-level measures. To assess whether firm training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without firm training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that training reduces workers’ automation risk by 3.8 percentage points, equivalent to 8% of the average automation risk. The training-induced reduction in automation risk accounts for 15% of the wage returns to firm training. Firm training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Training is similarly effective across gender, age, and education groups, suggesting widely shared benefits rather than gains concentrated in specific demographic segments.