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Educational attainment differs greatly across the three regions and between countries, ranging from the forerunner country in educational expansion Japan (with on average 13 years of schooling among the population 25+ in 2015) to Afghanistan. As the least educated society in Asia, Afghanistan ranked 13th from the bottom globally with a mere 2.5 years of schooling in 2015.

Cross-country comparisons presented below should be taken with some caution as not only the quantity, but also the quality, of education varies widely between the countries. South Korea and Singapore score top in the PISA testing that measure skills among the students aged about 14 years. The basic quantitative indicators analysed in this report are for the purpose of reflecting the main differences across regions. Although, inequality of access to quality education remains across and within countries, particularly for the poorest and those living in the remote rural regions.

8.3.1 South Asia

South Asia is Asia’s least educated corner with its population 25+ having only on average 5.8 years of schooling in 2015, which places it just above the average for the sub-Saharan Africa (5.3 years) and substantially below the global average (7.9 years). Within the region, Afghanistan stands out, followed by Bhutan, Pakistan and Nepal with less than 4-4.5 years of schooling, while Sri Lanka was the most educated country in the region with 9.9 years in 2015 (and 36 % population 25+ with at least completed upper secondary education).

The average over the whole adult population, however, conceals important improvements that took place in the past decades. These are captured in the differentiated educational compositions of the age groups, as presented in the population pyramid in 2015 for the whole region (see Figure 8.4 at the next page). At the country level, educational attainment of Indian women has improved greatly across younger cohorts, although the country significantly lags behind in achieving universal primary education for boys and girls: 63 % of women 25-39 had completed at least primary education (35 % at least upper secondary), compared to 39 % with at least completed primary at age 40-64. Among men, 77 % had

at least completed primary at age 25-39 (45 % at least upper secondary) compared to only 51 % at age 40-64. In contrast to India, Sri Lanka managed to achieve a 93 % completion of primary schooling among 25-39 year olds (80 % among 40-64 year olds) and 33 % of women compared to 25 % of men had post-secondary education, making it the only country in the region with a reversed gender gap. Among the countries with the lowest educational levels, Pakistan made some progress, yet only 53 % of 25-39 year olds had completed primary (35 % among 40-64 year olds) and women remain heavily disadvantaged compared to men. Very small progress over time occurred in Afghanistan, where only 50 % of men 25-39 had completed at least primary (30 % for age 40-64) compared to only 18 % of women 25-39 (7 % for 40-64).

By 2060, the MYS (mean years of schooling) would increase to 6.3 in South Asia in case of slow development (SSP3) up to 12.5 years in case of fast educational expansion (SSP1). Even though we are projecting a narrowing gender gap, gender disparities will still exist in 2060 and in our CEPAM Medium (SSP2) scenario 64 % of men and 59 % of women 25+ would have achieved upper secondary or higher education in 2060, but still 13 % of women would have no education (8 % men), an artefact of lower education among the old cohorts that were already born by 2015. Educational improvements are projected for younger age groups, so much so that in 2060 all countries in the region except Afghanistan would achieve universal primary education among 25-39 year olds. In the case of swift and successful achievement of the MDGs, as projected in SSP1 scenario, the three regions’ population age structure would stabilise, virtually everyone by age 45 would have completed at least upper secondary education and gender disparities would have diminished. In contrast, SSP3 scenario leads to high population growth with insufficient expansion of the education system, and thus, a large share of the population is left uneducated.

Under the medium scenario 40 % of 25-39 year olds in India and 59 % in Sri Lanka have post-secondary education in 2060, compared to only 27 % in Pakistan (17 % with primary or lower education) and 16 % in Afghanistan (23 % still with no formal education and 19 % with some primary).

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FIGURE 8.4: Population composition of South Asia by age, sex and educational attainment, 2015 and 2060 by scenarios (Source: own calculations) South Asia - 2060 South Asia - 2060 SSP3

CEPAM Medium (SSP2)

South Asia - 2015 South Asia - 2060

SSP1

■ No education ■ Incomplete primary ■ Primary ■ Lower secondary ■ Upper secondary ■ Post-secondary

Male Female Male Female Male Female Male Female

125 62.5 0 62.5 125

Population in Millions Population in Millions Population in Millions Population in Millions

8.3.2 East Asia

In contrast to South Asia, East Asia’s population has been on a fast-track in educational expansion. Japan had some of the world’s best educated population already in the mid-20th century and South Korea is a country that experienced some of the fastest educational, demographic and societal transformations over the past 60 years. On average, the region’s MYS for population 25+ stood at 8.5 years in 2015, but this average reflects the overwhelming weight of China’s 7.9 years (11 % post-secondary educated), while Japan’s population averaged 13.0 years (38 % post-secondary educated) and South Korea’s 11.9 years (40 % post-secondary educated). South Korea’s educational composition shows strong imbalance between the young and old, which reflects a rapid educational expansion: 16 % among 65+ had no education (6 % among men, 24 % among women) and only 10 % post-secondary (17 % among men and 4 % among women), as opposed to 67 % post-secondary educated among 25-39 year olds in 2015. In China, the inter-generational differences are not as pronounced, but also show significant improvements

among the younger age groups: 21 % at ages 25-39 had post-secondary education in 2015 (men and women on par), compared to 7.2 % among 40-64 year olds among whom (30 % had at most primary schooling). Women of older cohorts were less educated than men in all countries in 2015, but a rapid change in women’s education has left younger men slightly behind: in South Korea 69 % of 25-39 year old women and 66 % among men had post-secondary education, with even more pronounced gap in Japan (63 % of women 25-39 and 56 % of men).

By 2060, East Asia’s MYS would increase to 11.7 years (China’s projected value) in the CEPAM Medium (SSP2) scenario (10.2 in SSP3 and 12.0 years in SSP1), with all other countries except China averaging above 12 years, which reflects the fact that virtually everyone would have graduated with at least an upper secondary diploma. For China, the medium scenario suggests that more women (63 % among 25-39 year olds) would have post-secondary education in 2060 compared to men (53 % for the same age group, SSP2) and everyone would complete primary school.

FIGURE 8.5: Population composition of East Asia by age, sex and educational attainment, 2015 and 2060 by scenarios (Source: own calculations)

■ No education ■ Incomplete primary ■ Primary ■ Lower secondary ■ Upper secondary ■ Post-secondary

Male Female Male Female Male Female Male Female

East Asia - 2015 East Asia - 2060

East Asia - 2060 SSP3

CEPAM Medium (SSP2) East Asia - 2060

SSP1

Population in Millions Population in Millions Population in Millions Population in Millions

75 75 37.5 37.5 75 75 37.5

0 0 0 0 37.5 75

94 D E M O G R A P H I C A N D H U M A N C A P I TA L S C E N A R I O S FO R T H E 21S T C E N T U RY 2018 A S S E S S M E N T FO R 201 C O U N T R I E S

8.3.3 ASEAN

ASEAN is a mix of countries with contrasting educational and age compositions. The MYS for population 25+

ranged from 4.6 years in Cambodia to 11.6 in Singapore in 2015. Indonesia carries a lot of weight in the regional average due to its large population (8.3 years for ASEAN, 8.4 years in Indonesia in 2015). Furthermore, Indonesia has nearly succeeded in eradicating illiteracy (2 % uneducated among 25-39 year olds in 2015, as compared to 29 % among 65+) and has made good progress in achieving universal primary education for both boys and girls (95 % of both men and women 25-39 years old have completed primary education, compared to 83 % among 40-64 year olds). These achievements have a significant footprint on the educational composition of ASEAN presented in the Figure 8.6.

Similarly, Malaysia, Philippines, Thailand and Vietnam have made great progress in illiteracy eradication and in achieving universal primary education, while Cambodia

has a long way to go to achieve this considering 20 % of 25-39 year olds were without any education in 2015, and 50 % for 65+. Furthermore, only 65 % of 25-39 year olds had completed primary schooling in 2015.

The three SSPs lead to very different population compositions in ASEAN. In one direction is an aged and well-educated population structure where young cohorts universally achieve upper secondary education, and generational differences in educational attainment are strongly pronounced (SSP1). In another, is a youngish population with a slightly progressive age structure, but sizeable numbers with only a maximum of primary education — estimated at 225 million (40 % of population 25+) compared to 170 million (48 %) in 2015.

In the CEPAM Medium (SSP2) scenario, only 1.2 % of population 25+ would have no formal education, 12 % with a maximum of completed primary and 33 % would have attained post-secondary diploma or a degree. In individual countries, the respective shares vary a great deal (see Appendix 2 for more detail).

FIGURE 8.6: Population composition of ASEAN by age, sex and educational attainment, 2015 and 2060 by scenarios (Source: own calculations)

■ No education ■ Incomplete primary ■ Primary ■ Lower secondary ■ Upper secondary ■ Post-secondary

Population in Millions Population in Millions Population in Millions Population in Millions

40 20 0 20 40 40 20 0 20 40 40 20 0 20 40 40 20 0 20 40

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Crespo Cuaresma, J.C., Lutz, W., and Sanderson, W. (2014), Is the demographic dividend an education dividend? Demography 51 (1): pp.

299–315, doi:10.1007/s13524-013-0245-x

Hesketh, T., Lu, L., and Xing, Z.W. (2011), The consequences of son preference and sex-selective abortion in China and other Asian countries. CMAJ : Canadian Medical Association Journal 183 (12): pp.

1374–1377, doi:10.1503/cmaj.101368

Hudson, V., and Den Boer, A. (2004), Bare branches: Security implications of Asia’s surplus male population. Cambridge. MIT Press.

Jha, P., Kesler, M.A., Kumar, R., Ram, F., Ram, U., Aleksandrowicz, L. et al. (2011), Trends in selective abortions of girls in India: analysis of nationally representative birth histories from 1990 to 2005 and census data from 1991 to 2011. The Lancet 377 (9781): pp. 1921–1928, doi:10.1016/S0140-6736(11)60649-1

Mason, A., and Lee, R. (2006), Reform and support systems for the elderly in developing countries: capturing the second demographic dividend. Genus 62 (2): pp. 11–35.

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2014. Phnom Penh, Cambodia, and Rockville, MA. National Institute of Statistics, Directorate General for Health, andICF International. Available at: https://dhsprogram.com/pubs/pdf/FR312/FR312.pdf

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dhsprogram.com/pubs/pdf/FR294/FR294.pdf

Sahni, M., Verma, N., Narula, D., Varghese, R.M., Sreenivas, V., and Puliyel, J.M. (2008), Missing Girls in India: Infanticide, Feticide and

Made-to-Order Pregnancies? Insights from Hospital-Based Sex-Ratio-at-Birth over the Last Century. PLOS ONE 3 (5): p. e2224, doi:10.1371/journal.

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et al. (2005), Surplus men, sex work, and the spread of HIV in China.

AIDS (London, England) 19 (6): pp. 539–547.

UNFPA (2012), Sex imbalances at birth: Current trends, consequences and policy implications. Bangkok. UNFPA Asia and Pacific Regional Office. Available at: https://www.unfpa.org/sites/default/files/pub-pdf/

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Zhu, W.X., Lu, L. and Hesketh, T. (2009), China’s excess males, sex selective abortion, and one child policy: analysis of data from 2005 national intercensus survey. BMJ 338: p. b1211, doi:10.1136/bmj.

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CHAPTER 9

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