RISE Insight 2020 Modeling the Long-Run Learning Impact of the COVID-19 Learning Shock

Jul 15, 2026

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The note analyzes how temporary COVID-19 school closures can generate large, persistent learning losses by compounding short-term setbacks into long-run deficits. It calibrates a “pedagogical production function” model to project outcomes from a learning shock affecting students in Grade 3 through Grade 10. Two mitigation strategies are modeled: remediation upon return and long-term reorientation of instruction to match students’ learning levels. Results indicate partial mitigation halves losses, while combined strategies can fully counter the shock and outperform the no-shock counterfactual, informing teacher training and remedial program planning.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages12

Reading Time30 min

AccessFree to download

Introduction

Key Points

Evidence and Mechanism

Modeling Approach and Scenario Design

Mitigation Strategies and Projected Outcomes

INSIGHTS Modeling the Long-Run Learning Impact of the COVID-19 Learning Shock: Actions to (More Than) Mitigate Loss by Michelle Kaffenberger I. Introduction The COVID-19 pandemic has forced 1.7 billion children out of school temporarily. While many education systems are attempting varying degrees of remote learning, it is widely accepted that the closures will produce substantial losses in learning (World Bank, 2020; Kuhfeld et al., 2020) . However, the real concern is not just that a few months of learning will be lost in the short run, but that these losses will accumulate into large and permanent learning losses as many children fall behind during school closures and never catch up. A new study suggests that even temporary school closurescan result in large medium-term lost learning. Andrabi, Daniels, and Das (2020) analyse the impact of the 2005 Pakistan earthquake on children’s learning four years later by comparing households that were close to the fault line with similar households that were farther away and not affected by the quake. Schools in the affected area were closed for an average of 14 weeks, a little more than 3 months. However, four years later children in the affected areas were not just three months behind, they were the learning equivalent of 1.5 years of schooling behind.1 The direct effect of the school closures alone cannot account for such large deficits in later test scores, Key Points • This note uses a calibrated “pedagogical production function” model to estimate the potential long-term losses to children’s learning from the temporary shock of COVID-19 related school closures. It then models possible gains from two mitigation strategies. • Without mitigation, children could lose more than a full year’s worth of learning from a three-month school closure because they will be behind the curriculum when they re-enter school and will fall further behind as time goes on. • Remediation when children return to school reduces the long-term learning loss by half, but still leaves children more than half a year behind where they would have been with no shock. • Remediation combined with long-term reorientation of instruction to align with children’s learning levels fully mitigates the long-term learning loss due to the shock and surpasses the learning in the counterfactual of no shock by more than a full year’s worth of learning. • Systems need to begin planning now for remediation programmes, and as they do so they should build programmes and train teachers in ways that can continue to produce benefits beyond the period immediately following reopening. suggesting affected children learned less each year after they returned to school because of the short-term interruption (Andrabi, Daniels, and Das, 2020) . One possible explanation is that the curriculum and instruction did not adapt to the children’s lower learning levels upon re-entry into school and hence the affected children fell farther and farther behind. 1 Their test scores were 0.24 standard deviations behind unaffected children and the average annual gain is only .15. The study also finds that, due to government and international relief efforts, affected households were no worse off economically than unaffected households (in terms of wealth, consumption, or infrastructure), so the learning affects are not consequences of economic hardships. This note uses a calibrated model with a “pedagogical production function” (Kaffenberger and Pritchett, 2020) to estimate the potential long-term losses to children’s learning from the temporary shock of school closures. The model shows that without mitigation, children could lose more than a year’s worth of learning even from a three-month school closure asthe short-term losses continue to compound after children return to school. Turning to mitigation strategies, the note examines the long-term effects of two strategies, finding that with some mitigation efforts education syst

FAQs

Why does the document emphasize long-run learning losses rather than only short-term losses from closures?

It argues that missed instruction during closures can accumulate as children fall behind during reopening and fail to catch up, turning a temporary disruption into permanent deficits.

What model does the note use to estimate the long-term impact of the COVID-19 learning shock?

It uses a calibrated “pedagogical production function” model to estimate potential long-term losses from temporary school closure shocks, then tracks effects from Grade 3 through Grade 10.

How do the proposed mitigation strategies change the projected learning outcomes?

Remediation upon return reduces long-term learning loss by about half, while combining remediation with long-term reorientation of instruction to fully align with learners’ levels can fully mitigate the loss and exceed the no-shock counterfactual by more than a year’s worth of learning.

Jul 15, 2026

Upload by Liam