VoxEU Column COVID-19 Education

The long-term effects of school closures

According to the World Bank, around 1.6 billion school children were affected by Covid-related school and childcare centre closures at their peak. This column uses a model that features public schooling as an input into the human capital production of children, as well as the monetary and time investment of parents into their children. The results suggest that school and childcare closures have significant negative long-term consequences on the human capital and welfare of the affected children, especially those from disadvantaged socioeconomic backgrounds. The loss in schooling and associated human capital accumulation is harder to offset the longer the crisis lasts.

After the outbreak of the COVID-19 crisis in the spring of 2020, politicians around the world closed schools and childcare centres together with businesses in an effort to contain the virus. According to the World Bank, around 1.6 billion school children were affected by these closures at their peak (World Bank 2020). While the economic costs of closing businesses arise immediately and are thus very salient, closed schools and childcare centres have negative economic effects on the human capital accumulation of children that only arise in the long run. Education is a crucial determinant of future wages, and schools are an important driver of intergenerational mobility (Kotera and Seshadri 2017, Lee and Seshadri 2019). In the short run, parents, and especially mothers, are struggling with combining work and childcare while schools are closed (Alon et al. 2020, Dingel et al. 2020, Fuchs-Schündeln et al. 2020a), but what are the long-run economic impacts of Covid-related school closures on the affected children? 

A model of schooling and parental investment into children

To answer this question, in a recent paper (Fuchs-Schündeln et al. 2020b), we build a model that features public schooling as an input into the human capital production of children, as well as the monetary and time investment of parents into their children. At the core of the model, there is a human capital production function that features self-productivity (i.e. human capital builds on itself) and complementarity (i.e. the higher the human capital, the more productive is investment into human capital) (Cunha and Heckman 2007, Cunha et al. 2010). From the age of 4 to the age of 16, children reside with their parents who invest time and resources into their education, which, combined with public expenditures, governs the evolution of human capital of the children from kindergarten through high school. At the age of 16, high-school students decide whether to stop schooling and start working, to complete high school, or to study for a college degree. At that time, parents endow their children with intra-vivo transfers that can be used to finance higher education. The terminal school degree (college, high-school, high-school dropout) as well as the human capital accumulated during their schooling period determines wages of the children once they enter the labour market. 

We calibrate the model to data from the US. Parents are heterogeneous with respect to marital status, education, income, and assets. Parental characteristics affect not only the innate ability of their children, but also the optimal investment into their children. We model the school and childcare closures as a drop in government investment in children corresponding to school closures of six months. In addition, the COVID-19 shock comprises a fall in parental income through increased unemployment, with a larger incidence for less-educated parents (Bick and Blandin 2020). We then use the model as a laboratory to ask how parents react to these shocks, and what the ultimate labour market and welfare effects are on the children. 

Our main results are summarised in Table 1. We find that the children affected by the school closures suffer long-run average wage losses of -1%. These wage losses lead to a reduction in welfare corresponding to a consumption equivalent variation of -0.7%. An important driver of the long-term wage losses are changes in the final educational attainment of the children; the table summarises the percentage point changes in the education shares. Translated into percent changes, the share of college-educated children falls by -2.6% and the share of high school dropouts increases by 4.1%, due to the fact that the children impacted by COVID-19 school closures early in their life arrive at the age of 16 with significantly less human capital than in the absence of COVID-induced school closures. Thus, there are significant permanent negative effects associated with a purely temporary shock. For the children, the negative effects of the temporary school closures are much more important than the negative effects caused by the temporary income drop of their parents: school closures account for 90% of their overall welfare loss.

Table 1 Aggregate outcomes of school closures and income recession


Notes: share s ∈ {no, hs, co}: education share in respective education category s = no: less than high school, s = hs: high school, s = co: college; PDV gross earn: present discounted value of gross earnings assuming labour market entry at age 22 and retirement at age 66 and an annual average return on wealth of 4.2%; CEV: consumption equivalent variation. Columns for average ages of children and biological ages 4, 6 and 14 show the respective percentage point changes of education shares, the percent changes of the present discounted value of earnings, and the CEV expressed as a percent change, for children of the respective age at the time of the school closures. The CEV is the consumption equivalent variation of the aggregate welfare accruing to children.

These negative effects emerge despite the optimal efforts of parents to offset the impact of school closures through increased parental time and resource inputs into their children’s education. On average, parents increase their time investment into children by 3.8% and their monetary investment by 5.1%. However, due to their own income loss, parental intra-vivo transfers fall by -0.3%. These changes imply welfare losses of -0.3% for the parents themselves.

The average long-term gross earnings loss of -1% for the children translates into a net earnings loss of -0.8%, assuming no changes in the tax and transfer system. Given the progressivity of labour income taxes, the lower average earnings lead to disproportionally lower tax payments. Thus, while the tax system to some degree shelters children from the future negative income effects, the flip side is that future government revenues fall by more than the gross earnings loss endured by these future workers, namely by -1.8%. Thus, COVID-19 school closures in the short-run foreshadow a substantial fiscal crisis in the long run.

Younger children and children from disadvantaged households suffer more

The earnings and welfare effects of the school closures depend significantly on the age at which they happen. For children aged 6 who are about to start primary school when the COVID-19 school closures occur, long-term earnings losses amount to -1.2%, with associated welfare losses of -0.8%. By contrast, for children aged 14, these losses are approximately one third lower, amounting to -0.8% and -0.5%, respectively. The reason for this age pattern is that human capital builds on itself, and lower human capital leads to lower optimal investments in the future. Thus, for children aged 6, parents optimally increase their investments at the time of the closures but cannot completely offset the human capital loss on impact. This leads to lower parental investments in future periods, relative to a world without the school closures. Compared to children of age 6, younger pre-school children are somewhat sheltered from the negative effects of the closures, because at that age parental investments play a more important role in human capital accumulation than government investments. 

In addition to the age of the child, parental characteristics are a crucial determinant of the magnitude of the earnings and welfare losses for children from the COVID-19 crisis. The welfare losses of the school closures for children are decreasing in parental education as well as in parental assets. Well-off parents have more resources to help out their children during the school closures, and also have a higher incentive to do so. Their children have on average higher human capital than the children of less well-off parents, and thus, given the complementarity of investments and human capital, larger investment increases after the school closures subside are optimal for them. Therefore, the role of parental characteristics for the school success of children is amplified by the COVID-19 school closures.

Prolonged school closures make the effects worse

The current second Covid-19 wave in the autumn of 2020 makes prolonged school closures a reality in some school districts, and renewed school closures a possibility in many more. We find that the welfare effects of one-year school closures are more than twice as large as the welfare effects of six-month school closures. The loss in schooling and associated human capital accumulation is harder to offset the longer the crisis lasts. 

Hybrid and digital teaching

Many schools relied on various forms of digital teaching during the school closures, and nowadays implement hybrid teaching formats, combining in-person instruction and remote teaching. The literature thus far provides only scant evidence on the effectiveness of online versus in-person instruction, and thus it is hard to gauge the long-run consequences of digital teaching. Yet, there is evidence that children from disadvantaged households have less access to and/or make less use of digital forms of teaching during the current crisis. Opportunity Insights (Chetty et al. 2020) reports that student participation in online maths work decreased immediately for all children at the start of the school closures, but ultimately decreased by 41% for children from low-income ZIP codes by the end of the school year compared to January 2020, by 32% for children from middle-income ZIP codes, and not at all for children from high-income ZIP codes. It is plausible that both the equipment for digital teaching among teachers as well as the equipment and the provision of quiet learning spaces for the students depend on socioeconomic characteristics. While we cannot put hard numbers on the differential use of online learning by parental characteristics, our model allows us to trace out the heterogeneous wage and welfare effects, by parental background, when the length of school closures is negatively correlated with socioeconomic characteristics of the parents. For example, if one assumes that the school closures in combination with distance learning opportunities correspond to a complete school closure of three months for children of college-educated parents, but of six months for children of high school dropouts, then the welfare impact is -0.7% for the latter group, but only -0.3% for the former group.


School and childcare closures have significant negative long-term consequences on the human capital and welfare of the affected children, especially those from disadvantaged socioeconomic backgrounds. This reduction in human capital accumulation is likely slowing the long-run growth prospects of countries, especially those whose economies are relatively human capital intensive, such as the US and Europe.

Thus, school and childcare closures are potentially very costly measures to avoid the spread of the Covid-19 virus. This point was initially largely lost in the political debate, likely because these negative effects arise only in the long run and thus are not immediately measurable. Medical research now also indicates that children are not the primary drivers of the COVID-19 pandemic, in contrast to pandemics caused by the influenza virus. During the current second wave of the crisis in the autumn of 2020, governments seem more committed to keeping schools and childcare centres open as long as possible. For example, Germany and France are closing restaurants, bars, and the entertainment industry during their ‘lockdown light’ in November 2020, but not schools or childcare centres. Our research suggests that this policy choice has the potential to pay significant long-run dividends for future generations, even though it might contribute to a more rapidly evolving second wave of Covid-19 infections in the short run.


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Bick A and A Blandin (2020), “Real-Time Labor Market Estimates During the 2020 Coronavirus Outbreak”, Working Paper. 

Chetty, R, J N Friedman, N Hendren, M Stepner and the Opportunity Insights Team (2020), “The Economic Impacts of COVID-19: Evidence from a New Public Database Built Using Private Sector Data”, mimeo.  

Cunha, F and J Heckman (2007), “The Technology of Skill Formation”, American Economic Review 97(2): 31-47.

Cunha F, J Heckman and S Schennach (2010), “Estimating the Technology of Cognitive and Noncognitive Skill Formation”, Econometrica 79(3): 883-891.

Dingel, J I, C Patterson and J Vavra (2020), “Childcare obligations will constrain many workers when reopening the US economy”, Becker Friedman Institute Working Paper No 2020-46.

Fuchs-Schündeln, N, M Kuhn and M Tertilt (2020a), “The Short-Run Macro Implications of School and Child-Care Closures”, CEPR Discussion Paper 14882.

Fuchs-Schündeln, N, D Krueger, A Ludwig and I Popova (2020b), “The Long Term Distributional and Welfare Effects of Covid-19 School Closures”, CEPR Discussion Paper 15227.

Kotera, T and A Seshadri (2019), “Educational Policy and Intergenerational Mobility”, Review of Economic Dynamics 25: 187-207. 

Lee, S Y and A Seshadri (2019), “On the Intergenerational Transmission of Economic Status", Journal of Political Economy 127(2): 855-921.

World Bank (2020), The Human Capital Index 2020 Update: Human Capital in the Time of COVID-19.

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