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

Based on data on school visits from Safegraph and on school closures from Burbio, we document that during the Covid-19 crisis secondary schools were closed for in-person learning for longer periods than elementary schools, private schools experienced shorter closures than public schools, and schools in poorer US counties experienced shorter school closures. To quantify the long-run consequences of these school closures, we extend the structural life cycle model of private and public schooling investments by Fuchs-Schündeln et al. (Econ J 132:1647–1683, 2022) to include private school choice and feed into the model the school closure measures from our empirical analysis. Future earnings and welfare losses are largest for children that started public secondary schools at the onset of the Covid-19 crisis. Comparing children from the top to children from the bottom quartile of the income distribution, welfare losses are 0.5 percentage points larger for the poorer children if school closures were unrelated to income. Accounting for the longer school closures in richer counties reduces this gap by about 1/4. A policy intervention that extends schools by 6 weeks generates significant welfare gains for children and raises future tax revenues sufficient to pay for the cost of this schooling expansion.

Research Subject Perceptions Regarding Infection Control Procedures to Reduce COVID-19

Introduction: The COVID pandemic has altered health care delivery, including clinical research, by introduction of measures to reduce COVID. How these measures affect clinical research participation is unclear. Objectives: The purpose of this survey was to document research volunteer's attitudes toward COVID infection control procedures. Methods: Our research program implemented the following: 1. Staff wore masks, disposable gowns, face shields and gloves when with subjects. 2. Subjects were asked if they tested positive or were experiencing COVID symptoms;upon entry their temperature was measured, and hand sanitizer used. 3. Disinfecting was expanded to all scanner room surfaces in contact with humans between each visit. 4. Only 1 subject was allowed in the research office at a time. Staff, when possible, remained > 6 feet away from other persons. As part of a study evaluating total body DXA, community dwelling volunteers completed a self-administered health care delivery preference survey from Dec 2020 to May 2021. A 5-point scale was used to capture responses to 10 questions (Table 1). Responses were tested using Chi Square with age and sex comparisons assessed by ANOVA. Results: Eighty-two adults (41F/41M) mean (SD) age 50.9 (18.3) yrs (range 18-79) without sex difference participated. Participants strongly agreed (84%;p < 0.001) they were more comfortable seeing effort to prevent COVID-19;72% agreed 1 subject, without a companion, should be seen, and 81% strongly agreed masks be required. Seeing staff clean visit space was important to 66%, more so among women (33%) than men (21% (p = 0.007)). Most subjects (83%) reported comfort having elective procedures and did not feel “unclean” or “diseased” (87%) by procedures. Some, 26%, preferred a non-hospital setting, 66% were neutral;those age 50+ (17%) preferred this more (p = 0.004) than younger subjects (5%). Finally, 91% preferred to have a brief test description before visit arrival. Conclusions: In this university-based study, most subjects favored masking, cleaning and limiting personal contact for research visits. Notably, no information regarding vaccination status was exchanged and the study began just as vaccines became available and ended just after all US citizens over age 16 were eligible for vaccination. Thus, it is unknown if vaccination status might alter research participation perception. However, people do prefer that steps are taken to reduce infection in research settings. It seems likely that this would be the case in clinical care settings.

THE LONG-TERM DISTRIBUTIONAL AND WELFARE EFFECTS OF COVID-19 SCHOOL CLOSURES

Using a structural life-cycle model, 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 characteristics. In the model, public investment through schooling is combined with parental time and resource investments in the production of child human capital at different stages in the children's development process. We quantitatively characterise the long-term consequences from a COVID-19-induced loss of schooling, and find average losses in the present discounted value of lifetime earnings of the affected children of 2.1%, as well as welfare losses equivalent to about 1.2% of permanent consumption. Because of self-productivity in the human capital production function, younger children are hurt more by the school closures than older children. The negative impact of the crisis on children's welfare is especially severe for those with parents with low educational attainment and low assets.

Macroeconomic dynamics and reallocation in an epidemic: evaluating the 'Swedish solution'

In this paper, we argue that endogenous shifts in private consumption behaviour across sectors of the economy can act as a potent mitigation mechanism during an epidemic or when the economy is re-opened after a temporary lockdown. We introduce a susceptible-infected-recovered epidemiological model into a neoclassical production economy in which goods are distinguished by the degree to which they can be consumed at home rather than in a social, possibly contagious context. We demonstrate within the model, that the 'Swedish solution' of letting the epidemic play out without much government intervention and allowing agents to reduce their overall consumption as well as shift their consumption behaviour towards relatively safe sectors can lead to substantial mitigation of the economic and human costs of the COVID-19 crisis. We argue that significant seasonal variation in the infection risk is needed to account for the two-wave nature of the pandemic. We estimate the model on Swedish health data and show that it predicts the dynamics of weekly deaths, aggregate as well as sectoral consumption, that accord well with the empirical record and the two-waves for Sweden for 2020 and early 2021. We also characterize the allocation a social planner would choose and how it would dictate sectoral consumption patterns. In so doing, we demonstrate that the laissez-faire outcome with sectoral reallocation mitigates the economic and health crisis but possibly at the expense of unnecessary deaths and too massive a decline in economic activity.