The Review of Economic Studies, 91(3), May 2024, pp. 1807–1841. NBER Working Paper, Replication Package.
This paper explores the relationship between the duration of a vacancy and the starting wage of a new job, using linked data on vacancies, the posting establishments and the workers eventually filling the vacancies. The unique combination of large-scale, administrative worker-, establishment- and vacancy-data is critical for separating establishment- and job-level determinants of vacancy duration from worker-level heterogeneity. Conditional on observables, we find that vacancy duration is negatively correlated with the starting wage and its establishment component, with precisely estimated elasticities of -0.07 and -0.21, respectively. While the negative relationship is qualitatively consistent with search-theoretic models where firms use the wage as a recruiting device, these elasticities are small, suggesting that firms’ wage policies can account only for a small fraction of the variation in vacancy filling across establishments.
This paper provides the first systematic analysis of repeated unemployment and its implications for unemployment insurance (UI) design. We document the prevalence of repeated unemployment and that initial unemployment spells differ systematically from subsequent spells in their responses to UI policies. Evidence from Austrian reforms reveals that individuals in repeated spells value higher UI benefits twice as much as first-time unemployed, while the fiscal cost of providing these benefits is three times lower in repeated spells. Our findings highlight significant welfare gains from incorporating unemployment spell dynamics — an aspect largely overlooked in the literature — into UI policy design.
Presentations: ASSA Annual Meeting 2023, NBER SI 2025.
This paper uses large-scale high-frequency data on vacancy flows and matched employer-employee data from Austria to document the cyclicality of vacancy flows and their contribution to variation in the vacancy stock. We document four key facts: (1) Vacancy inflows explain at least one-third of the cyclical variation in the vacancy stock, whereas the remainder is explained by vacancy fillings; (2) vacancy lapses, while accounting for about 20% of vacancy outflows, are acyclical and do not contribute to variation in the stock; (3) replacement vacancies, i.e. vacancies posted following a quit of a worker to another firm, are a key driver of vacancy inflows over the business cycle; and (4) the composition of vacancy inflows varies little over the business cycle and cannot account for the cyclical variation in vacancy filling. We set up a search-and-matching model with fixed costs of vacancy posting and on-the-job search, and calibrate it to match the averages of vacancy flows. The calibrated model highlights the crucial role of on-the-job search — particularly replacement hires — in explaining the observed importance of vacancy inflows for cyclical fluctuations in the vacancy rate.
This paper uses rich matched employer-employee data from the Austrian social security registers to document the short- and long-run effects of short-time work vs. temporary layoffs for workers and firms during the Great Recession. Descriptive evidence points to substantial heterogeneity in short-time work take-up across workers and firms’ observable characteristics. We leverage the rich dataset at hand to estimate a structural model to guide a comparative analysis of short-time work and temporary layoffs policies in terms of efficiency and redistribution. This contributes to the topical debate on whether workers or jobs should be insured during recessions.
This paper demonstrates how worker flows can be used in order to identify administrative firm identifier changes in the Austrian Social Security Data. Relative to the approach used by Fink et al. (2010), the procedure improves by using daily worker flows between different firms in order to identify administrative renames, spinoffs and takeovers. I apply this approach using daily worker flows to the time period 1972-2020, which allows to correctly identify firm-level and aggregate separations as well as hirings in the Austrian Social Security Data.