We study whether the Swiss short-time work (STW) program reduced unemployment in and after the Great Recession using quarterly establishment-level panel data linking administrative data sources. We compare changes in layoffs into unemployment, employment, and establishment survival between establishments that applied successfully and establishments that applied unsuccessfully for STW at cantonal employment agencies. The unsuccessful establishments provide a valid counterfactual for the successful ones because cantonal approval practices are partly idiosyncratic. We find that STW increases establishment survival and prevents rather than postpones dismissals. The 7,857 establishments treated in 2009 would have dismissed 20,600 additional workers into unemployment (0.47% of the labor force) until 2012. Most workers would have been dismissed in the quarters immediately following the application, and more than a third would have become long-term unemployed. The savings on unemployment benefits may have compensated for the spending on STW benefits.

Women (compared to men) and ethnic minorities (compared to natives) face inferior labor market outcomes in many economies 1,2 , but the extent to-and the channels through-which discrimination is responsible for these effects remains debated 3,4 . While correspondence tests 5 , where researchers send fictitious resumes that are identical except for the randomised minority trait to be tested (e.g. Black vs. White-sounding names), are an increasingly popular method to quantify discrimination in hiring practices 6,7 , they can usually study only a few applicant characteristics in select occupations at a particular point in time. To overcome these limitations, we leverage a new approach to investigating hiring discrimination that combines tracking of recruiters' search behavior on employment websites and supervised machine learning to control for all relevant jobseeker characteristics that are visible to recruiters. We apply this methodology to the online recruitment platform of the Swiss public employment service and find that, depending on their country of origin, ethnic minorities face 4-19% lower contact rates than otherwise identical natives. Women face a penalty of 1 7% in male-dominated professions, and the opposite pattern emerges for men in femaledominated professions. We find no evidence that recruiters spend less time evaluating ethnic minorities' profiles. Our methodology provides a widely applicable, non-intrusive, and costefficient tool that researchers and policy-makers can employ to continuously monitor hiring discrimination, to illuminate some of the drivers of discrimination, and to inform approaches to counter it.Labor market outcomes such as wages and unemployment differ markedly across sociodemographic groups defined by immutable characteristics such as gender, ethnicity, or race. A vast literature has explored how differences in workers' skills, abilities, or preferences contribute to such employment disparities 1, 2 . Because of its fundamental repercussions for equality of opportunity, prior research has paid particular attention to the extent to which these disparities are driven by discrimination 3, 5-7 -understood as the decision to hire a person or pay a wage based not on the individual's merit but on his or her membership of a particular group, defined, e.g., by gender or ethnicity 8 .Earlier studies on discrimination relied on observational data such as labor market surveys to estimate a "minority coefficient" that captures the differences in wage and employment outcomes between, for example, Black and White people, controlling for other observable worker characteristics. The limitation of this regression-based approach is that the minority coefficient typically does not identify the extent of discrimination, since it is plausibly confounded by productivity signals that are unobserved by the researcher 1 . To overcome this limitation, correspondence studies

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