In der ökonomischen Forschung fehlt bislang gesamtwirtschaftlich repräsentative empirische Evidenz zu der Frage, ob offene Stellen als Vorlaufindikator für die Beschäftigungsentwicklung gelten können. Bei der Interpretation der aktuellen Entwicklung des Stellenangebots wird dies häufig...

In der ökonomischen Forschung fehlt bislang gesamtwirtschaftlich repräsentative empirische Evidenz zu der Frage, ob offene Stellen als Vorlaufindikator für die Beschäftigungsentwicklung gelten können. Bei der Interpretation der aktuellen Entwicklung des Stellenangebots wird dies häufig...

Using data from a 1998 establishment-level survey in the telecommunications industry, the authors examine the predictors of aggregate quit rates. They draw on strategic human resource and industrial relations theory to identify the sets of employee voice mechanisms and human resource practices...

We collect rich establishment-level data about advance layoff notices filed under the Worker Adjustment and Retraining Notification (WARN) Act since January 1990. We present in-sample evidence that the number of workers affected by WARN notices leads state-level initial unemployment insurance...

Many large and small companies in the tech and startup sector have been laying off an unusually high number of workers in 2022 and 2023. We are interested in predicting when this period of layoffs might end, without resorting to economic forecasts. We observe that a sample of layoffs up to March...

We propose a local adaptive multiplicative error model (MEM) accommodating timevarying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time....

We propose a local adaptive multiplicative error model (MEM) accommodating timevarying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time....

Public programs often use statistical profiling to assess the risk that applicants will become long-term dependent on the program. The literature uses linear probability models and (Cox) proportional hazard models to predict duration outcomes. These either focus on one threshold duration or...