The Fiscal and Welfare Effects of Policy Responses to the Covid-19 School Closures

Abstract

We also thank Burbio and Safegraph for providing us with their data. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

COVID-Induced School Closures in the US and Germany: Long-Term Distributional Effects

“…There are only a handful papers analyzing the consequences of the school closures based on structural models. Besides the two papers by Fuchs-Schündeln et al (2021) andFuchs-Schündeln et al (2022), on which this paper builds, the paper by Jang and Yum (2020) analyzes the long-run economic and welfare consequences of the school closures, focusing on intergenerational mobility and allowing for general equilibrium effects. Agostinelli et al (2020) zoom in on high school students, and model an additional channel for losses from school closures that goes beyond a direct loss of school instruction time, namely the change in peers generated by school closures.…”

“…Given that the decision process was so decentralized in the US for most of the crisis, it is hard to collect systematic evidence on the school closures based on public regulation, and for private schools one necessarily has to collect the evidence school by school. The evidence presented herein thus comes from data on actual school visits presented in Fuchs-Schündeln et al (2021). I describe the basic procedure for generating the data here, and refer the interested reader to the detailed description in Fuchs-Schündeln et al (2021).…”

“…The evidence presented herein thus comes from data on actual school visits presented in Fuchs-Schündeln et al (2021). I describe the basic procedure for generating the data here, and refer the interested reader to the detailed description in Fuchs-Schündeln et al (2021). To calculate school closures, we rely on Safegraph data on cell-phone visits (in minute time intervals) at the physical location of a specific school on the weekly level.…”

“…Children aged 11 to 16 experienced the longest closures I then introduce a two generations life-cycle model to generate an estimate of the long-term losses of the school closures for the affected children. The model comes from Fuchs-Schündeln et al (2021), and features at its core a human capital production function of children. To accumulate human capital, children receive monetary and time inputs from their parents, but also schooling inputs coming either from public or private schools.…”

School Closures and Effective In-Person Learning during COVID-19: When, Where and for Whom

“…The results raise critical questions about the extent of school closings in different parts of the country. The patterns of EIPL that we uncover are also important to understand the impact of in-person learning loss during the pandemic on future educational attainment and income inequality (see Fuchs-Schündeln et al [2021] for an application). At the same time, we emphasize that our analysis does not contribute to the ongoing debate of whether and under what circumstances school closings helped slow down the spread of COVID.…”