9 years than if we were not using these events, leading to more conservative estimates. **Classification of Industries (N = 10).** The 10 industries are based on revision 3.1 of the International Standard Industrial Classification: 1 = Agriculture, Hunting, Fishing (01-05); 2 = Mining (10-14); 3 = Manufacturing (15-37); 4 = Electricity and Utilities (40-41); 5 = Construction (45); 6 = Commerce (50-55); 7 = Transportation, Storage and Communication (60-64); 8 = Financial, Insurance and Real Estate (65-74); 9 = Services: Public Administration (75); 10 = Other Services & Other/Unspecified Sectors (80-99). **Classification of Occupations (N = 10).** The 10 occupations are based on International Standard Classification of Occupations 88: 1 = Managers; 2 = Professionals; 3 = Technicians and associate professionals; 4 = Clerical support workers; 5 = Service and sales workers; 6 = Skilled agricultural, forestry and fishery workers; 7 = Craft and related trades workers; 8 = Plant and machine operators, and assemblers; 9 = Elementary occupations; 10 = Armed forces occupations/Other/Unspecified occupations.

# **I The COVID-19 Pandemic and Child Labor**

Negative aggregate shocks may increase or decrease child labor (e.g., Ferreira and Schady, 2009; Cogneau and Jedwab, 2012). Given such shocks worsen labor market conditions and reduce the opportunity cost of time for children, children may work less. This substitution effect may even dominate the income effect and result in countercyclical human capital investments, hence _less_ child labor. In HICs, the income effect is typically small so the substitution effect tends to dominate.

The question then is how the income effect and substitution effect compare in both LICs and MICs. In the case of COVID-19, ILO and UNICEF (2021, p. 8) says that “the predicted additional rise in child labour is by no means a foregone conclusion.” The reduction in economic activity due to the pandemic dramatically reduced employment, and youth unemployment increased 2.4 times more than adult unemployment (ILO, 2020, p. 10). Thus, older workers were more protected than younger workers when total employment decreased. As such, it could be child employment did not increase despite falling incomes. More generally, to our knowledge, no studies have quantitatively and rigorously established that COVID-19 increased child labor in developing economies.

# **REFERENCES**

> Alpert, William T., Kenneth A. Couch, and Oskar R. Harmon, “A Randomized Assessment of Online Learning,” _American Economic Review_ , May 2016, _106_ (5), 378–82. Azevedo, Joao Pedro, Amer Hasan, Diana Goldemberg, Syedah Aroob Iqbal, and Koen Geven, _Simulating the potential impacts of COVID-19 school closures on schooling and learning outcomes: A set of global estimates._ , The World Bank, 2020.

> Bauer, Peter, Jonas Brugger, Franz K ̈onig, and Martin Posch, “An international comparison of age and sex dependency of COVID-19 Deaths in 2020 - a descriptive analysis,” _medRxiv_ , 2021. Bettinger, Eric P., Lindsay Fox, Susanna Loeb, and Eric S. Taylor, “Virtual Classrooms: How Online College Courses Affect Student Success,” _American Economic Review_ , September 2017, _107_ (9), 2855–75.