Using a structural life-cycle model and data on school visits from Safegraph and school closures from Burbio, we quantify the heterogeneous impact of school closures during the Corona crisis on children affected at different ages and coming from households with different parental...

We match cell phone data to administrative school records and combine it with information on school learning modes to study effective in-person learning (EIPL) in the U.S. during the pandemic. We find large differences in EIPL for the 2020-21 school year. Public schools averaged less EIPL than...

We propose a model to evaluate the U.K.'s zero-hours contract (ZHC) - a contract that exempts employers from the requirement to provide any minimum working hours, and allows workers to decline any workload. We find quantitatively mixed welfare effects of ZHCs. On one hand they unlock job...

We match cell phone data to administrative school records and combine it with information on school learning modes to study effective in-person learning (EIPL) in the U.S. during the pandemic. We find large differences in EIPL for the 2020-21 school year. Public schools averaged less EIPL than...

We propose a model to evaluate the U.K.’s zero-hours contract (ZHC) – a contract that exempts employers from the requirement to provide any minimum working hours, and allows workers to decline any workload. We find quantitatively mixed welfare effects of ZHCs. On one hand they unlock job...

Using a structural life-cycle model and data on school visits from Safegraph and school closures from Burbio, we quantify the heterogeneous impact of school closures during the Corona crisis on children affected at different ages and coming from households with different parental...

This paper develops a macroeconomic model that combines an incomplete-markets overlapping-generations economy with a job ladder featuring sequential wage bargaining, endogenous search effort of employed and non-employed workers, and differences in match quality. The calibrated model offers a...

The estimation of structural dynamic factor models (DFMs) for large sets of variables is attracting considerable attention. In this paper we briefly review the underlying theory and then compare the impulse response functions resulting from two alternative estimation methods for the DFM....

The estimation of dynamic factor models for large sets of variables has attracted considerable attention recently, due to the increased availability of large datasets. In this paper we propose a new parametric methodology for estimating factors from large datasets based on state space models and...