Education for Equitable Development (PART I)

Education for all can bring important benefits to society even if it is not very successful in terms of the wider set of goals or even if the quality does not meet international standards. This argument is not to weaken the efforts to improve the quality of, or to reach other goals through education but to stress the importance of enhancing the access to and use of education by all without waiting for notable improvements in its quality or comprehensiveness.

Education for Equitable Development I 1024x683


Educationists prescribe a wide set of goals to be achieved through education. These include critical thinking, democratic values, humanistic ideals along with the skills to improve the status of livelihood. Some educationists and activists can become disenchanted if education does not succeed in the achievement of these goals. Also, there is a general perception that the majority of students, especially in low-income countries, receive poor quality of education. This pervasive lower quality may also encourage some genuine commentators to be less excited about the plans to extend school education to all. This article argues that education for all can bring important benefits to society even if it is not very successful in terms of the wider set of goals or even if the quality does not meet international standards. This argument is not to weaken the efforts to improve the quality of, or to reach other goals through education but to stress the importance of enhancing the access to and use of education by all without waiting for notable improvements in its quality or comprehensiveness.

Education helps people to get out of poverty and underdevelopment

A number of studies have brought out evidence on the relationship between the lack of education and poverty (or that between education and relatively higher incomes) from different parts of the world. Palmer et al (2009)1 report evidence from a set of African countries. They note that investments at all levels of education lift people out of poverty. Analysis based on cross-section datasets confirms that households with a higher level of education are less likely to be poor. Moreover, returns from education rise with the level of education.2 This method of directly comparing households with different levels of education may provide direct and clearer evidence of the contribution than the macro studies linking national estimates of income and education.

Education or even minimal literacy could help in reducing poverty even among those social groups in India, like the Scheduled Castes (SCs) and Tribes (STs), which have been socially and economically deprived historically. Poverty among the illiterate STs was about 56.91 percent whereas that among the same group with primary schooling is only 20.11 percent (Thorat, 2010).3 Similarly, the percentage of poverty among the illiterate SCs is 43.94 percent whereas, it is only 12.86 percent among those belonging to the same group who have acquired primary schooling. Kannan and Raveendran (2011)4 have analysed the consumer expenditure of people who can be classified as poor and vulnerable in different states of India. Here too, education is found to be an important determinant. The odds ratio of being poor and vulnerable due to low education is as high as 4.68 in West Bengal for SC/ST, 6.22 for Other Backward Tribes (OBCs) in Madhya Pradesh and 5.73 for STs in Orissa.

The linkage between poverty and the lack of education prevails in the developed world too. Blandon and Gibbones (2006)5 note that poverty in adulthood in the United Kingdom is associated with low education, lack of employment and employment experience and, for women, single parenthood.6 While considering the long-term persistence of poverty or those who are likely to escape poverty in the United States, it has been noted that about 83 percent of white children living in two-parent households headed by someone with at least a high school education will escape long-term poverty. In contrast, only 10 percent of poor black children in a household headed by a single woman without a high school diploma will avoid it.7

The role of education in enhancing the income of individuals has been recorded in many studies. A review of these studies by Psacharopoulos and Patrinos (2018)8 shows that the rate of return to schooling across countries is about 10 percent. Returns seem higher for low-income countries and for lower levels of schooling, though there can be variations depending on the context. Higher returns to education could be seen even in the informal sectors of the rural areas of India. Education helps a person in rural India to participate in the rural non-farm sector (RNFS) jobs (like the construction of buildings and roads) and earn higher incomes. According to Jatav and Sen, (2013)9 a person with secondary education has nearly 2.3 times higher probability to be in RNFS compared to an illiterate. According to one estimate, the wage premium between farm and rural non-farm sector associated with education was growing over time to 2004 – 5. It was Rs 86 per day for literate workers over illiterate ones and Rs 197 per day for those who had attended middle school (Eswaran et al, 200910).

However, quality’ – whether education really leads to learning achievements – is as important as access to education. There is strong evidence that quality’ matters much more than what we usually think. Cognitive skills of the population – rather than mere school attainment – are significant correlates of individual earnings, distribution of income and economic growth (Hanushek and Wosmann, 200711). Multi-country comparisons incorporating cognitive skills show that the skill deficits in developing countries are much larger than that evident from mere school enrolment and attainment.12

Girls’ education important for addressing issues of underdevelopment

The education of girls could be helpful in breaking the poverty and underdevelopment of current and future generations. Educated girls are likely to delay marriage,13 likely to be able to exercise their reproductive rights and have lesser number of children. Early marriage prevents girls from enrolling for secondary education as evident in many parts of India (Santhakumar et al, 2016).14 It has been noted that an extra year of schooling for girls reduces fertility rates by 5 – 10 percent.15 Herz and Khandker (1991)16 report that women with no education have on average about six children in Brazil and Peru, while women with a secondary education have about three.

This reduction in the number of children itself may lead to a reduction in infant mortality. In addition, literate/​schooled women would be more knowledgeable (or willing to acquire knowledge) on the hygienic and other practices that may reduce infant mortality and morbidity. It would also enhance their ability to understand and respond to risky situations as in a context where the likelihood of HIV infection is higher (Herz and Sperling, 200417). It was estimated that an additional year of schooling for a mother, on an average, results in a reduction in infant mortality by 9 per 1,000 (World Bank 1993).18

The possibility of having fewer and healthier children by educated mothers may lead to better education of the former. A number of studies have noted the positive contribution of mothers’ education to the schooling of their children. Education of women encourages them to send their children to school (Filmer, 1999;19 World Bank 2003). This is more so with regard to the education of the girl child (Kambhapati and Pal 200120; Parker and Pederzini 200021; Bhalla et al, 200322). Mothers’ education is important even for the enrolment and attendance of boys in schools (Santhakumar et al, 2016). On the other hand, fathers’ education does not have a great impact on girls’ education. For all these reasons, girls’ education is an important tool to take generations out of poverty.

Education enables women to participate in paid employment in the formal sector. This has been noted in most parts of the world (Birdsall and Behrman 199123; Cameron, Dowling, and Worsick 200124). There is an argument that the returns to education from formal sector employment are more for women than men (Deolalikar, 199425; Aromolaran, 200226). This is more so with regard to secondary education. Return to secondary education for women in one such estimate is 18 percent whereas that for men is only 14 percent27.

Primary schooling is not adequate to achieve the social benefits of girls’ education. Secondary schooling is important for desirable changes in fertility, infant mortality and participation in paid employment. It is noted in Subbarao and Rainey (1995)28, based on a study of a number of countries, that a woman on an average, is likely to have more than five children if she does not have secondary education and is also more likely to have experienced the loss of a child or two in their infancy. On the other hand, the situation is very different in those countries where half the girls were educated at the secondary level. There, according to the study, would be about three children per women and infant deaths are also rare. Even for achieving other desirable outcomes like the use of child delivery services, secondary education is important (Elo 199229; Bhatia and Cleland 199530; Govindasamy 200031; Malhotra, Pande, and Grown 200332). For the education of children (especially girls) higher levels of education of the mother matters.

Hence, the expansion of schooling to include girls is important for addressing the issues of underdevelopment and poverty. There are two issues here. First, the expansion of education to girls may facilitate education for all’ in the long run. Therefore, there is some merit in the prioritization of girls’ education in the efforts to achieve schooling for all’. Secondly, it is unrealistic to expect that normal efforts to expand education are going to facilitate the education of girls from different sections of society in different parts of the world. There are deep-rooted social and cultural factors that prevent the schooling of girls, and hence, greater efforts in this direction are important.

Inequality associated with education 

That education for some and not all is a cause of inequality is well recognized. Early theoretical analysis of personal income distribution was based on education (Becker and Chiswick, 199633). Here inequality in earnings from education is explained by the variations in the supply of funds for investing in education (arising out of income and wealth of parents, the willingness to forego consumption during the time of the study, and the availability of scholarships and loans) and in the demand for such investments (because of differences in ability, attitudes towards risks and other personal characteristics). This indicates the possibility of different equilibriums. The analysis demonstrated that schooling usually explains a not negligible part’ (p.368) of the inequality in earnings in a geographical area and a much greater part of the differences in inequality between areas. Psacharopoulos (1977)34 attempted to relate income inequality (measured in terms of Gini Coefficients) and that in school enrolment and other variables through regression exercises. The results suggest a strong and direct relation between enrolment inequality and income inequality. Winegarden (1979)35 found that inequality in educational attainment has a stronger role in general income disparities than previous studies had revealed.

There were also studies that compared the actual earnings of workers with different levels of skills or education. One such study (Juhn et al, 199336) found that the real average weekly wages for the least skilled workers (as measured by the tenth percentile of the wage distribution) declined by about 5 percent whereas wages for the most skilled workers rose by 40 percent between 1963 and 1989. It notes that a major part of the increase in wage inequality for males over the last 20 years can be explained in terms of the increased returns to the components of skill other than years of schooling and years of employment experience. The divergence in earnings between the most skilled and the least skilled contributes to a substantial increase in wage inequality. These findings are consistent with other studies37. It has been noted that the distribution of incomes within schooling groups has been rising (Levy and Murnane,199238) in the US, but the impact of skills is much more pronounced39. A number of papers in the early nineties have established that the main determinant of the then noted growing inequality was the increase in the relative demand for skill (Bound and Johnson, 199240; Katz and Murphy, 199241. The later evidence, summarized in Acemoglu (2002)42, lead to the conclusion that technological change (and hence, increasing demand for skills) could be the main explanation for the growth in inequality in the US.

De Gregorio and Lee (2002)43 could find only a weak but positive association between inequality in years of schooling and income inequality. In the context of the debates on the potential role of trade unions in income inequality, Nickell (2003)44 saw that while union coverage is statistically significant the bulk of the variation in earnings is generated by skill dispersion.

Changes in the difference between earnings of people with different levels of education are the main driver of income inequality in Mexico (Legovini et al, 200545; Lopes-Acevedo, 200646). Similar evidence is available from Brazil too in the 1980s (Ferreira and Veloso, 200647). Average returns to schooling have been increasing with much higher returns for higher educated people in China (Li et al, 201148). Considering the evidence from India (Pieters, 201149), it was noted that the relative demand shifted to higher-skilled workers in the service sector, and this has caused an increased wage gap between the high- and low-educated workers. There was a widening wage gap between graduate and primary education (for the regular salaried employees) and this has contributed to the increased wage inequality in the 1990s. The increase in wage-inequality was attributable mainly to increases in returns to skills. This was due to the shifts in labour demand within-industry and not so much due to across industries (which would be expected as part of globalization). The wage premium for skilled people is generally attributed to Skill-Based Technological Change (SBTC) and resulting increases in the demand for skilled labour (Krueger, 199350; Berman et al, 199851). It has been noted that wages increase at an increasing rate with years of education (Mincer, 199152; Deschenes, 200253). In fact, as noted in Lamieux (2008: 2954) the enormous increase in the return to post-secondary education accounts for a large share of the overall increase’ in income inequality.


  1. Palmer R, R. Wedgwood and R. Hayman with K. King and N. Thin (2007) Educating out of Poverty? A Synthesis Report on Ghana, India, Kenya, Rwanda, Tanzania and South Africa, Centre of African Studies, University of Edinburgh

  2. http://​www​.csae​.ox​.ac​.uk/​r​e​s​p​r​o​g​s​/​i​n​v​e​s​t​e​d​u​/​d​e​f​a​u​l​t​.html

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  4. Kannan, K. P. and Raveendran, G. (2011) India’s Common People: The Regional Profile, Economic and Political Weekly, 46,38, 60 – 73

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  7. Hoynes, H., Page, M., & Stevens, A. (2006). Poverty in America: Trends and Explanations. The Journal of Economic Perspectives, 20(1), 47 – 68.

  8. Psacharopoulos, G. and H.A. Patrinos. 2018. Returns to Investment in Education: A Decennial Review of the Global Literature.” Education Economic, 26 (5): .445458.

  9. Jatav, M. & Sen, S. (2013). Drivers of Non-Farm Employment in Rural India: Evidence from the 2009-10 NSSO Round. Economic & Political Weekly, Vol. XLVIII Nos. 26 & 27, 14 – 21

  10. Eswaran, M., Kotwal, A., Ramaswami, B. and Wadhwa, W. 2009. Sectoral labour flows and agricultural wages in India, 1983 – 2004: Has growth trickled down? Economic and Political Weekly 44(2): 46 – 55

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  12. http://​www​.unicef​.org/​g​e​n​d​e​r​/​f​i​l​e​s​/​B​a​s​i​c​E​d​u​c​a​t​i​o​n​_​L​a​y​o​u​t​_​W​e​b.pdf

  13. Women with seven or more years of schooling marry five years later than women with no education in Africa. See, World Bank (1993a). Women’s education in developing countries: Barriers, benefits, and policies, The World Bank, Washington DC, http://​eli​brary​.world​bank​.org/​d​o​i​/​a​b​s​/​10​.​1596/0 – 8018-4534 – 3 (opened on 2012016)

  14. Santhakumar, V., Gupta, N. and Murthy, S.R. (2016) Schooling for All: Can We Neglect the Demand? New Delhi: Oxford University Press.

  15. https://​www​.unicef​.org/​s​o​w​c​96​/​n​g​i​r​l​s.htm

  16. Herz, B. K and Khandker, S R (1991) Women’s Work, Education, and Family Welfare in Peru. Discussion Papers 116, World Bank, Washington, DC.

  17. Herz, B. K and Khandker, S R (1991) Women’s Work, Education, and Family Welfare in Peru. Discussion Papers 116, World Bank, Washington, DC.

  18. World Development Report, 1993, World Bank, Washington, D.C.

  19. Filmer, D. 1999. The Structure of Social Disparities in Education: Gender and Wealth.” Policy Research Report on Gender and Development, Working Paper Series No. 5, World Bank Development Research Group/​Poverty and Human Resources. Washington, D.C.

  20. Kambhapati, U S, and Pal, S. 2001. Role of Parental Literacy in Explaining Gender Difference: Evidence from Child Schooling in India, European Journal of Development Research 13 (2): 97 – 119

  21. Parker, S. W., and Pederzini, C. 2000. Gender Differences in Education in Mexico.World Bank Departmental Working Paper 21023. Washington, D.C

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  23. Birdsall, N., and J. Behrman. 1991. ―Why Do Males Earn More than Females in Urban Brazil: Earnings Discrimination or Job Discrimination? In N. Birdsall and R. Sabot, eds., Unfair Advantage: Labor Market Discrimination in Developing Countries. Washington, D.C.: World Bank

  24. Cameron, L. A., M. J. Dowling, and C. Worsick. 2001. ―Education and Labor Market Participation of Women in Asia: Evidence from Five Countries. Economic Development and Cultural Change 49 (3): 459 – 77.

  25. Deolalikar, A. 1994. ―Gender Differences in the Returns to Schooling and in School Enrolment Rates in Indonesia. Journal of Human Resources 28 (Fall): 889 – 932

  26. Aromolaran, A. 2002. Private Wage Returns to Schooling in Nigeria: 1996 – 1999. New Haven, Conn.: Yale University Press.

  27. According to this estimate, women experience lower returns (13 percent) to primary education than do men (20 percent.

  28. This is a cross-country study of fertility and secondary school attainment among women in 65 low- and middle-income countries which covered 93 percent of the population of the developing world. Subbarao, K., and Rainey, L. 1995. ―Social Gains from Female Education. Economic Development and Cultural Change 44(1): 105 – 28

  29. Elo, I. 1992. Utilization of Maternal Health-Care Services in Peru: The Role of Women’s Education. Health Transition Review 2 (1): 49 – 69

  30. Bhatia, J. C., and J. Cleland. 1995. Determinants of Maternal Care in a Region of South India. Health Transition Review 5 (2): 127 – 42

  31. Bhatia, J. C., and J. Cleland. 1995. Determinants of Maternal Care in a Region of South India. Health Transition Review 5 (2): 127 – 42

  32. Malhotra, A., R. Pande, and C. Grown. 2003. ―Impact of Investments in Female Education on Gender Equality. International Center for Research on Women, Washington, D.C.

  33. Becker, G. S., & Chiswick, B. R. (1966). Education and the distribution of earnings. American Economic Review, 56, 358 – 369.

  34. Psacharopoulos, G. (1977) Economics of education: An assessment of recent methodological advances and empirical results, Social Science Information, Volume: 16 issue: 3 – 4, page(s): 351 – 371

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  37. For a review, see Sawhil (1988)

  38. Levy, Frank, and Richard J. Murnane. 1992. U.S. earnings levels and earnings inequality: A review of recent trends and proposed explanations. Journal of Economic Literature 30 (3): 1333 – 81.

  39. They found that for a given level of schooling attainment, the income distribution is more dispersed reflecting growing rewards to individual skills.

  40. Bound, John, and George Johnson. 1992. Changes in the structure of wages during the 1980s: An evaluation of alternative explanations. American Economic Review 82 (3): 371 – 92

  41. Katz, Lawrence F., and Kevin M. Murphy. 1992. Changes in relative wages, 1963 – 1987: Supply and demand factors. Quarterly Journal of Economics 107:35 – 78

  42. Katz, Lawrence F., and Kevin M. Murphy. 1992. Changes in relative wages, 1963 – 1987: Supply and demand factors. Quarterly Journal of Economics 107:35 – 78

  43. De Gregorio, J. D., and J. W. Lee. 2002. Education and Income Inequality: New Evidence from Cross-Country Data.” Review of Income and Wealth 48 (3): 395 – 416

  44. Nickell S (2003) Labour market institutions and unemployment in OECD countries. CESifo DICE Rep 1(2):13 – 26

  45. Legovini, A., C. Bouillon, and N. Lustig (2005). Can Education Explain Changes in Income Inequality in Mexico.’ In F. Bourguignon, F.H.G. Ferreira, and N. Lustig (eds), The Microeconomics of Income Distribution Dynamics. Washington, DC: World Bank and New York, NY: Oxford University Press

  46. Lopez-Acevedo, G. (2006). Mexico: Two Decades of the Evolution of Education and Inequality’. World Bank Policy Research Working Paper 3919. Washington, DC: World Bank

  47. Ferreira Sérgio G. and Fernando Veloso (2006): Intergenerational Mobility of Wages in Brazil”, Brazilian Review of Econometrics, 26 (2)

  48. Li, F., Y. Zhao & W. John Morgan (2011): The rate of return to educational investment in China: a comparative commentary, Education, Knowledge and Economy, 5:1 – 2, 45 – 52

  49. Pieters, J. (2011) Education and Household Inequality Change: A Decomposition Analysis for India, The Journal of Development Studies, 47:12, 1909 – 1924

  50. Krueger, Alan B. (1993), How computers changed the wage structure: evidence from microdata”, Quarterly Journal of Economics 108: 33 – 60

  51. Berman, Eli, John Bound and Zvi Griliches (1994), Changes in the demand for skilled labour within U.S. manufacturing industries: evidence from the annual survey of manufactures”, Quarterly Journal of Economics 109: 367 – 397

  52. Mincer, Jacob (1991), Human capital, technology and the wage structure: what do time series show?” Working paper no. 3581 (NBER, Cambridge, MA)

  53. Deschênes, Olivier. Unobserved Ability, Comparative Advantage and the Rising Return to Education in the United States: A Cohort-Based Approach.” Princeton University Industrial Relations Section, Working Paper No. 4652001

  54. Lemieux T. (2008), The Changing Nature of Wage Inequality’, Journal of Population Economics, vol. 21, pp. 21


V Santhakumar, Professor, Azim Premji University, Bangalore

Featured photo by Nikhita S on Unsplash

This article is published in two parts. To read PART II, click here.