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...

Should arbitrators consider authority—such as statutes or case law—external to the collective bargaining agreement when deciding labor grievances? Do they rely on such external authority? If so, do they do so in particular circumstances or in certain types of cases? To provide more insight...

We leverage an event-study research design focused on the seven costliest hurricanes to hit the US mainland since 2004 to identify the elasticity of unemployment insurance filings with respect to search intensity. Applying our elasticity estimate to the state-level Google Trends indexes for the...

We propose an out-of-sample prediction approach that combines unrestricted mixed-data sampling with machine learning (mixed-frequency machine learning, MFML). We use the MFML approach to generate a sequence of now- and backcasts of weekly unemployment insurance initial claims based on a rich...

Predictions of whether newly unemployed individuals will become long-term unemployed are important for the planning and policy mix of unemployment insurance agencies. We analyze unique data on three sources of information on the probability of re-employment within 6 months (RE6), for the same...

We analyze unique data on three sources of information on the probability of re‑employment within 6 months (RE6), for the same individuals sampled from the inflow into unemployment. First, they were asked for their perceived probability of RE6. Second, their caseworkers revealed whether they...

We analyze unique data on three sources of information on the probability of re-employment within 6 months (RE6), for the same individuals sampled from the inflow into unemployment. First, they were asked for their perceived probability of RE6. Second, their caseworkers revealed whether they...