Written by Kobe Yip - UCL BSc Economics
Education is an investment in human capital accumulation, involving skills and knowledge that determine an individual’s earnings (Becker, 1962). Weiss (2015) links education's impact on earnings to productivity, as also evident in the strong positive correlation (+0.7207) between productivity and average years of education in Asia (Fig.1). However, the ongoing COVID-19 pandemic caused disruptions in education, resulting in "lost learning", where the learning progress of reading was 2 to 3 months slower than usual (Fig.2). This disruption highlights the need to explore its potential impact on future labour market
One consequence of "lost learning" is a rise in unemployment, diminishing living standards for those unemployed. Maisonneuve et al. (2022) estimate up to 32% of future labour force could be affected by school closures between 2020 with recovery as late as 2080. This implies a decrease in future labour productivity, depicted by a downward shift in the average product of the labour curve to λ1 (Fig.3). Assuming market competitiveness remains, the markup (μ= λ-PS) stays unchanged. Then, the price-setting curve shifts down to PS1 to restore markup, resulting in a fall in real wage to W1. The equilibrium will then move from X to Y, increasing unemployment to U’. Those unemployed with lower incomes tend to consume less with Ganong and Noel (2016) reporting a 6% reduction in spending. This would lead to a decrease in living standards below those employed (Bradshaw et al., 1983).
Another impact is increase in inequality, causing inequality in education attainable. The growing number of unemployed workers (Fig.3) shifts the Lorenz curve downward (Fig.4). While the percentage division of output between workers and owners remains, the Gini coefficient increases. Rising income inequality further limits education opportunities for children from poor backgrounds (Ingraham, 2018), who may become less productive employees with lower wages. Thus, the impact of "lost learning" extends to children from unemployed families arising from schooling inequality.
The final impact is a fall in consumption of those employed, which lowers the living standard. This can stem from two reasons. First, a rise in unemployment will affect those employed as they are uncertain about their future employment status and therefore income uncertainty increases. This will result in precautionary savings (Malley and Moutos, 1996). Second, a decrease in real wages (Fig.3) indicates both an income and substitution effect (Fig.5). Income effect (A to B) shrinks the feasible set to dotted FF1, reducing consumption at each free time level. Thus, workers would work less. Substitution effect (B to C) flattens the feasible set to FF2 as the opportunity cost of free time decreases, motivating workers to work more. Assuming a vertical labour supply, substitution effect offsets income effect, resulting in a decrease in consumption to Y3 only. Both consumption falls would lower living standards for those employed (Bradshaw et al., 1983).
In conclusion, the government should implement post-COVID-19 recovery policies, with one key focus on educating future workforce affected by "lost learning", given its impact on the employed, unemployed, and descendants of the unemployed. However, policymakers need to acknowledge the opportunity cost, recognizing the need for other areas like training the current labour force. Strategic compromises are vital for maximising overall labour market recovery.
Sources:
Becker, G. S. (1962). Investment in Human Capital: A Theoretical Analysis. Journal of Political Economy, 70(5), 9–49. http://www.jstor.org/stable/1829103
Bradshaw, J., Cooke, K. and Godfrey, C. (1983). The Impact of Unemployment on the Living Standards of Families. Journal of Social Policy, 12(4), pp.433–452. doi:https://doi.org/10.1017/s0047279400013076.
Education Endowment Foundation. (2022). The Impact of COVID-19 on Learning: A review of the evidence [Review of The Impact of COVID-19 on Learning: A review of the evidence ]. https://d2tic4wvo1iusb.cloudfront.net/production/documents/guidance-for-teachers/covid-19/Impact_of_Covid_on_Learning.pdf?v=1706397296
Feenstra et al. (2015), Penn World Table (2021) – with major processing by Our World in Data. “Productivity” [dataset]. Feenstra et al. (2015), Penn World Table (2021), “Penn World Table” [original data]. Retrieved January 31, 2024, from https://ourworldindata.org/grapher/productivity-vs-educational-attainment
Ganong, P., & Noel, P. (2016). How Does Unemployment Affect Consumer Spending? [Review of How Does Unemployment Affect Consumer Spending?]. https://scholar.harvard.edu/files/ganong/files/ganong_jmp_unemployment_spending.pdf
Ingraham, C. (2018). How rising inequality hurts everyone, even the rich. The Washington Post. [online] 6 Feb. Available at: https://www.washingtonpost.com/news/wonk/wp/2018/02/06/how-rising-inequality-hurts-everyone-even-the-rich/.
de la Maisonneuve, C., B. Égert and D. Turner (2022), "Quantifying the macroeconomic impact of COVID-19-related school closures through the human capital channel", OECD Economics Department Working Papers, No. 1729, OECD Publishing, Paris, https://doi.org/10.1787/eea048c5-en.
Malley, J. and Moutos, T. (1996). UNEMPLOYMENT AND CONSUMPTION. Oxford Economic Papers, 48(4), pp.584–600. doi:https://doi.org/10.1093/oxfordjournals.oep.a028586.
Weiss, Y. (2015). GARY BECKER ON HUMAN CAPITAL. Journal of Demographic Economics, 81(1), 27–31. https://www.jstor.org/stable/26422358
Comments