The economic impacts of learning losses
Open accessAbstract
The worldwide school closures in early 2020 led to losses in learning that will not easily be made up for even if schools quickly return to their prior performance levels. These losses will have lasting economic impacts both on the affected students and on each nation unless they are effectively remediated. While the precise learning losses are not yet known, existing research suggests that the students in grades 1-12 affected by the closures might expect some 3 percent lower income over their entire lifetimes. For nations, the lower long-term growth related to such losses might yield an average of 1.5 percent lower annual GDP for the remainder of the century. These economic losses would grow if schools are unable to re-start quickly. The economic losses will be more deeply felt by disadvantaged students. All indications are that students whose families are less able to support out-of-school learning will face larger learning losses than their more advantaged peers, which in turn will translate into deeper losses of lifetime earnings. The present value of the economic losses to nations reach huge proportions. Just returning schools to where they were in 2019 will not avoid such losses. Only making them better can. While a variety of approaches might be attempted, existing research indicates that close attention to the modified re-opening of schools offers strategies that could ameliorate the losses. Specifically, with the expected increase in video-based instruction, matching the skills of the teaching force to the new range of tasks and activities could quickly move schools to heightened performance. Additionally, because the prior disruptions are likely to increase the variations in learning levels within individual classrooms, pivoting to more individualised instruction could leave all students better off as schools resume. As schools move to re-establish their programmes even as the pandemic continues, it is natural to focus considerable attention on the mechanics and logistics of safe re-opening. But the long-term economic impacts also require serious attention, because the losses already suffered demand more than the best of currently considered re-opening approaches.
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The results confirm the fears held by many that school closures would cause socioeconomic gaps to widen.
“Our results show that learning loss was particularly pronounced for students from disadvantaged homes, confirming the fears held by many that school closures would cause socioeconomic gaps to widen (51 –55).”
From Learning loss due to school closures during the COVID-19 pandemic (2021) · cites this paper as [51]
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Cites
The effects of cognitive and noncognitive abilities on labor market outcomes and social behavior
Heckman, J. J., Stixrud, J., & Urzua, S. (2006) · Journal of Labor Economics · doi:10.1086/504455 · Cited by 4,427 · see citing works
Are Schools the Great Equalizer? Cognitive Inequality during the Summer Months and the School Year
Downey, D. B., von Hippel, P. T., & Broh, B. A. (2004) · American Sociological Review · doi:10.1177/000312240406900501 · Cited by 853 · see citing works
Lasting Consequences of the Summer Learning Gap
Alexander, K. L., Entwisle, D. R., & Olson, L. S. (2007) · American Sociological Review · doi:10.1177/000312240707200202 · Cited by 763 · see citing works
Flagged first, then by citations
Research works printed but not linked: 47
- Alexander, K. (ed.) (2016), The Summer Slide: What We Know and Can Do About Summer Learning Loss, Teachers College Press., New York, NY.
- Altonji, J. and C. Pierret (2001), "Employer Learning and Statistical Discrimination", Quarterly Journal of Economics, Vol. 116/1, pp. 313-350.
- Baker, M. (2013), "Industrial Actions in Schools: Strikes and Student Achievement", Canadian Journal of Economics, Vol. 46/3, pp. 1014-1036.
- Belot, M. and D. Webbink (2010), "Do Teacher Strikes Harm Educational Attainment of Students?", Labour, Vol. 24/4, pp. 391-406.
- Bowles, S., H. Gintis and M. Osborne (2001), "The Determinants of Earnings: A Behavioral Approach.", Journal of Economic Literature, Vol. 39/4, pp. 1137-1176.
- Bradley, S. and C. Green (eds.) (2020), The Economics of Education: A Comprehensive Overview. 2nd edition, Academic Press, London.
- Burgess, S. (2019), "Understanding Teacher Effectiveness to Raise Pupil Attainment: Teacher Effectiveness Has a Dramatic Effect on Student Outcomes-How Can It Be Increased?", IZA World of Labor, Vol. 46.
- Card, D. (2001), "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems", Econometrica, Vol. 69/3, pp. 1127-1160.
- Card, D. (1999), "The Causal Effect of Education on Earnings", in Ashenfelter, O. and D. Card (eds.), Handbook of Labor Economics ,Vol. 3a, North Holland, Amsterdam, pp. 1803-186.
- Chetty, R. et al. (2011), "How Does Your Kindergarten Classroom Affect Your Earnings? Evidence from Project Star", Quarterly Journal of Economics, Vol. 126, pp. 1593-1660.
- Cooper, H. et al. (1996), "The Effects of Summer Vacation on Achievement Test Scores: A Narrative and Meta-Analytic Review", Review of Educational Research, Vol. 66/3, pp. 227-268.
- Gunderson, M. and P. Oreopoulos (2020), "Returns to Education in Developed Countries", in Steve Bradley, C. (ed.), The Economics of Education: A Comprehensive Overview, Academic Press, pp. 39- 51.
- Hampf, F., S. Wiederhold and L. Woessmann (2017), "Skills, Earnings, and Employment: Exploring Causality in the Estimation of Returns to Skills", Large-scale Assessments in Education, Vol. 5/1, pp. 1-30.
- Hanushek, E. (2014), "The Economic Relevance of Early Childhood Development", in Maas, J., S. Ehmig and C. Seelmann (eds.), Prepare for Life! Raising Awareness for Early Literacy Education, Stiftung Lesen.
- Hanushek, E., M. Piopiunik and S. Simon Wiederhold (2019), "The Value of Smarter Teachers: International Evidence on Teacher Cognitive Skills and Student Performance", Journal of Human Resources, Vol. 54/4, pp. 857-899.
- Hanushek, E. and S. Rivkin (2012), "The Distribution of Teacher Quality and Implications for Policy", Annual Review of Economics, Vol. 4, pp. 131-157.
- Hanushek, E. et al. (2015), "Returns to Skills around the World: Evidence from PIAAC", European Economic Review, Vol. 73, pp. 103-130.
- Hanushek, E., S. Wiederhold and L. Woessmann (2017), "Coping with Change: International Differences in the Returns to Skills", Economics Letters, Vol. 153, pp. 15-19.
- Hanushek, E. and L. Woessmann (2016), "Knowledge Capital, Growth, and the East Asian Miracle", Science, Vol. 351/6271, pp. 344-345.
- Hanushek, E. and L. Woessmann (2015), The Knowledge Capital of Nations: Education and the Economics of Growth, MIT Press.
- Hanushek, E. and L. Woessmann (2012), "Do Better Schools Lead to More Growth? Cognitive Skills, Economic Outcomes, and Causation", Journal of Economic Growth, Vol. 17/4, pp. 267-321.
- Hanushek, E. and L. Woessmann (2011), "How Much Do Educational Outcomes Matter in OECD Countries?", Economic Policy, Vol. 26/67, pp. 427-491.
- Hanushek, E. and L. Woessmann (2011), "The Economics of International Differences in Educational Achievement", in Hanushek, E., S. Machin and L. Woessmann (eds.), Handbook of the Economics of Education, Vol. 3, North Holland, Amsterdam, pp. 89-200..
- Hanushek, E. and L. Woessmann (2008), "The Role of Cognitive Skills in Economic Development", Journal of Economic Literature, Vol. 46/3, pp. 607-668.
- Hanushek, E. and L. Zhang (2009), "Quality-Consistent Estimates of International Schooling and Skill Gradients", Journal of Human Capital, Vol. 3/2, pp. 107-143.
- Harbison, R. and E. Hanushek (1992), Educational Performance of the Poor: Lessons from Rural Northeast Brazil, Oxford University Press.
- Harmon, C., H. Oosterbeek and I. Walker (2003), "The Returns to Education: Microeconomics", Journal of Economic Surveys, Vol. 17/2, pp. 115-155.
- Heckman, J. (2006), "Skill Formation and the Economics of Investing in Disadvantaged Children", Science, Vol. 312 (5782), pp. 1900-1902.
- Heckman, J., L. Lochner and P. Todd (2006), "The Earnings Functions, Rates of Return and Treatment Effects: The Mincer Equation and Beyond.", in Eric A. Hanushek and F. Welch (eds.), Handbook of the Economics of Education, Vol. 1, North Holland, Amsterdam, pp, 307-458..
- Heyns, B. (1978), Summer Learning and the Effects of Schooling, Academic Press, New York.
- Jaume, D. and A. Willén (2019), "The Long-Run Effects of Teacher Strikes: Evidence from Argentina", Journal of Labor Economics, Vol. 37/4, pp. 1097-1139.
- Leuven, E., H. Oosterbeek and H. Ophem (2004), "Explaining International Differences in Male Skill Wage Differentials by Differences in Demand and Supply of Skills", Economic Journal, Vol. 114/495, pp. 466-48.
- Lindqvist, E. and R. Vestman (2011), "The Labor Market Returns to Cognitive and Noncognitive Ability: Evidence from the Swedish Enlistment", American Economic Journal, Vol. 3/1, pp. 101-128.
- Hanushek, E., S. Machin and L. Woessmann (eds.), Handbook of the Economics of Education, Vol. 4, North Holland, Amsterdam, pp. 183-282..
- McEachin, A. and A. Atteberry (2017), "The Impact of Summer Learning Loss on Measures of School Performance", Education Finance and Policy, Vol. 12/4, pp. 468-491.
- Mulligan, C. (1999), "Galton Versus the Human Capital Approach to Inheritance", Journal of Political Economy, Vol. 107/(6, pt. 2), pp. S184-S224.
- Murnane, R. et al. (2000), "How Important Are the Cognitive Skills of Teenagers in Predicting Subsequent Earnings?", Journal of Policy Analysis and Management, Vol. 19/4, pp. 547-568.
- Murnane, R., J. Willett and F. Levy (1995), "The Growing Importance of Cognitive Skills in Wage Determination", Review of Economics and Statistics, Vol. 77/2, pp. 251-266.
- Neal, D. and W. Johnson (1996), "The Role of Pre-Market Factors in Black-White Differences", Journal of Political Economy, Vol. 105/5, pp. 869-895.
- OECD (2010), The High Cost of Low Educational Performance: The Long-run Economic Impact of Improving PISA Outcomes, PISA, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264077485-en. · DOI
- OECD, E. Hanushek and L. Woessmann (2015), Universal Basic Skills: What Countries Stand to Gain, OECD Publishing, Paris, https://doi.org/10.1787/9789264234833-en. · DOI
- Oreopoulos, P. and K. Salvanes (2011), "Priceless: The Nonpecuniary Benefits of Schooling.", Journal of Economic Perspectives, Vol. 25/1, pp. 159-184.
- Pischke, J. (2007), "The Impact of Length of the School Year on Student Performance and Earnings: Evidence from the German Short School Years", Economic Journal, Vol. 117/523, pp. 1216-1242.
- Psacharopoulos, G. and H. Patrinos (2018), "Returns to Investment in Education: A Decennial Review of the Global Literature", Education Economics, Vol. 26/5, pp. 445-458.
- Schultz, T. (1961), "Investment in Human Capital", American Economic Review, Vol. 51/1, pp. 1-17.
- Woessmann, L. (2016), "The Economic Case for Education", Education Economics 24, Vol. 1, pp. 3-32.
- Woessmann, L. (2016), "The Importance of School Systems: Evidence from International Differences in Student Achievemen", Journal of Economic Perspectives, Vol. 30/3, pp. 3-32.
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Learning loss due to school closures during the COVID-19 pandemic
Engzell, P., Frey, A., & Verhagen, M. D. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2022376118 · Cited by 1,848 · see citing works
Learning loss due to school closures during the COVID-19 pandemic
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The impact of Covid-19 on student achievement: Evidence from a recent meta-analysis
Di Pietro, G. (2023) · Educational Research Review · doi:10.1016/j.edurev.2023.100530 · Cited by 173 · see citing works
“Second, following Hanushek and Woessmann (2020), a learning deficit of about 0.186 standard deviations can be considered to be equivalent to the loss of just over half of a school year.”
InfluentialBlaskó, Z., Costa, P. D., & Schnepf, S. V. (2022) · Journal of European Social Policy · doi:10.1177/09589287221091687 · Cited by 87 · see citing works
Blanden, J., Doepke, M., & Stuhler, J. (2022) · National Bureau of Economic Research · doi:10.3386/w29979 · Cited by 47 · see citing works
Kim, L. E., Leary, R., & Asbury, K. (2020) · doi:10.31234/osf.io/m8scj · Cited by 13 · see citing works
Borzino, N., Otto, M., Kjellstrom, T., & Kai Wei Lee, J. (2026) · Environmental Research: Climate · doi:10.1088/2752-5295/ae8320
- Authors
- Hanushek, E. A., & Woessmann, L.
- Venue
- OECD Education Working Papers
- Published
- 2020-09-10
- ISSN
- 1993-9019 (ISSN-L)
- OpenAlex
- W3086390437
- Cited by
- 409
- References
- 3
- Citations by year
- 2026: 30 · 2025: 48 · 2024: 62 · 2023: 81 · 2022: 73 · 2021: 104 · 2020: 10
- Type
- report
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- OECD education working papers (publishedVersion)
- OECD eBooks
- Topics
- Social Sciences › Education › Education during COVID-19 pandemic
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › COVID-19 Pandemic Impacts
- Social Sciences › Education › School Choice and Performance
- Keywords
- learning loss, school closures, COVID-19 pandemic, lifetime earnings, GDP growth, disadvantaged students, out-of-school learning, school reopening, video-based instruction, individualised instruction
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