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Girls’ Lower Secondary Education Completion Rate Indicator

Description

This indicator measures a government’s commitment to secondary education for girls in terms of access, enrollment, and completion. MCC uses this indicator for countries with a GNI per capita between $2,146 and $4,465 only.

Relationship to Growth & Poverty Reduction

Access to continued education beyond the primary level solidifies the benefits associated with girls’ primary education. Secondary education for girls ensures they receive both the benefits of primary education and the additional benefits linked to further education. Empirical research consistently shows a strong positive correlation between girls’ secondary education and faster economic growth, higher wages for women, slower population growth, and increased labor productivity.43 According to one estimate, a 1 percent increase in proportion of women enrolled in secondary school will generate a 0.3 percent growth in annual per-capita income.44 A large body of literature also shows that increasing a mother’s schooling has large effect on her children’s health, schooling, and adult productivity.45 The social benefits of female education are also demonstrated through postponed marriage and pregnancy, lower fertility rates, decreased child and maternal mortality, reduced transmission of HIV, and greater educational achievement by children.46 Overall, studies show that increased schooling and gender equality in education lead to poverty reduction and economic growth.47

Methodology

Indicator Institution Methodology

The Girls’ Lower Secondary Education Completion Rate indicator measures the percentage of girls in a particular age cohort that have completed lower secondary school within a few years of their expected graduate date. Lower secondary school is defined as a program typically designed to complete the development of basic skills and knowledge which began at the primary level. In many countries, the educational aim is to lay the foundation for lifelong learning and individual development. The programs at this level are usually on a subject-oriented pattern, requiring specialized teachers for each subject area. The end of this level often coincides with the end of compulsory education. For FY25, MCC will use the most recent UNESCO data from 2018 or later.

MCC Methodology

MCC uses the most recent data point in the past six years

MCC draws upon data from UNESCO’s Institute of Statistics as its exclusive source of data. Specifically, MCC uses the indicator named “Completion rate, lower secondary education, female (%)” which is included in SDG 4.1.2. MCC uses the observed data instead of the modelled data. To receive an FY25 score, countries must have a UNESCO value on “Completion rate, lower secondary education, female (%)” from 2018 or later. MCC uses the most recent year available that is, MCC uses the most recent data from the past six years. If a country does not have UNESCO data at any point from 2018 or later, it does not receive an FY25 score. As better data become available, UNESCO makes backward revisions to its historical data. MCC uses the observed data not the modelled data from UNESCO.

The Girls’ Lower Secondary Education Completion Rate indicator measures the percentage of a cohort of children or young people aged 3-5 years above the intended age for the last grade of each level of education who have completed that grade. The intended age for the last grade of each level of education is the age at which pupils would enter the grade if they had started school at the official primary entrance age, had studied full-time and had progressed without repeating or skipping a grade. This data is gathered from population censuses and household surveys which collect data on the highest level of education or grade completed by children and young people in a household.

In FY24 MCC revised its methodology for this indicator shift from a focus on Girls’ Secondary Education Enrollment to Girls’ Lower Secondary Education Completion. As a result, the scores from FY24 or later are not comparable to scores from FY23 and earlier.

Footnotes
  • 43.Behrman, Jere R. and Anil B. Deolalikar. 1995. Are there differential returns to schooling by gender? The case of Indonesian labor markets. Oxford Bulletin of Economics and Statistics, 57(1): 97-117. Chen, Derek H. C. 2004. Gender Equality and Economic Development: The Role for Information and Communication Technologies. World Bank Policy Research Working Paper 3285. David Dollar and Roberta Gatti. 1999. Gender inequality, income, and growth: Are good times good for women? World Bank Policy Research Report on Gender and Development Working Paper Series No. 1. World Bank: Washington, D.C. Deolalikar, Anil B. 1993. Gender Differences in the Returns to Schooling and in School Enrollment Rates in Indonesia. Journal of Human Resources 28 (4): 899–932. Klasen, Stephan. 2002. Low Schooling for Girls, Slower Growth for All? World Bank Economic Review 16(3): 345-373. Mathur, Ashok and Rajendra P. Mamgain. 2004. Human capital stocks: Their level of utilization and economic development in India, Indian Journal of Labour Economics 47(4): 655-75. Psacharopoulos, George and Harry Anthony Patrinos. 2004. Returns to investment in education: a further update. Education Economics 12(2): 111-134. Raza, Moonis, and H. Ramachandran. 1990. Schooling and Rural Transformation. New Delhi: Vikas for National Institute of Educational Planning and Administration. Schultz, T. Paul. 1993. Returns to women’s schooling. In Elizabeth King and M. Anne Hill, eds., Women’s Education in Developing Countries: Barriers, Benefits, and Policy. Baltimore: Johns Hopkins Press. Schultz, T. Paul. 1999. Health and schooling investments in Africa. The Journal of Economic Perspectives, 13(3): 67-88. Schultz, T. Paul. 2002. Why governments should invest more to educate girls. World Development 30(2): 212. Self, Sharmistha and Richard Grawbowski. 2004. Does education at all levels cause growth? India, a case study. Economics of Education Review, 23: 47-55. Smith, Lisa C. and Lawrence Haddad. 2002. How potent is economic growth in reducing undernutrition? What are the pathways of impact? New cross‐country evidence. Economic Development and Cultural Change, 51(1): 55-76. Tilak, Jandhyala B. G. 1990. Education and earnings: Gender differences in India, International Journal of Development Planning Literature 5(4): 131-39. Tilak, Jandhyala B. G. Post‐elementary Education, Poverty and Development in India. 1994. World Bank. 2001. Engendering Development: Through Gender Equality in Rights, Resources, and Voice. New York: Oxford University Press.
  • 44. David Dollar and Roberta Gatti. 1999. Gender inequality, income, and growth: Are good times good for women? World Bank Policy Research Report on Gender and Development Working Paper Series No. 1. World Bank: Washington, D.C.
  • 45. Alderman, Harold, and Elizabeth M. King. 1998. Gender Differences in Parental Investment in Education Structural Change and Economic Dynamics 9 (4): 453–68. Filmer, Deon. 2000. The Structure of Social Disparities in Education: Gender and Wealth. Policy Research Working Paper No. 2268, World Bank Development Research Group/Poverty Reduction and Economic Management Network. Washington, D.C.: World Bank. King, Elizabeth, and Rosemary Bellew. 1991. Gains in the education of Peruvian women, 1940-1980. In Barbara Herz and Shahidur Khandkher, Eds. Women’s Work, Education, and Family Welfare in Peru. World Bank Discussion Paper No. 166. Washington D.C.: World Bank. Klasen, Stephan. 2002. Low Schooling for Girls, Slower Growth for All? World Bank Economic Review 16(3): 345-373. Lavy, Victor. 1996. School Supply Constraints and Children’s Educational Outcomes in Rural Ghana. Journal of Development Economics 51 (2): 291–314. Lillard, Lee A. and Robert J. Willis. 1993. Intergenerational Education Mobility: Effects of family and state in Malaysia. RAND Labor and Population Program Working Paper Series 93-38. Mammen, Kristin, and Christina Paxon. 2000. Women’s Work and Economic Development. Journal of Economic Perspectives 14 (4): 141–64. Schultz, T. Paul. 2002. Why governments should invest more to educate girls. World Development 30(2): 212. Thomas, Duncan. 1990. Intra-household allocation: An inferential approach. Journal of Human Resources 25(4): 635-64.
  • 46.Behrman, J.R. and A Deolalikar. 1998. Health and nutrition. In Handbook of Development Economics, eds. H. Chenery and T. N. Srinivasan. Amsterdam: North Holland. Cochrane, S., J. Leslie, and D. O’Hara. 1982. Parental education and child health: Intercountry evidence. Health Policy and Education 2:213-50. De Walque, Damien, J. S. Nakiyingi-Miiro, J. Busingye, and J. A. Whitworth. 2005. Changing Association between Schooling Levels and HIV-1 Infection Over 11 Years in a Rural Population Cohort in South-West Uganda. Tropical Medicine and International Health 10(10): 993-1001. De Walque, Damien. 2004. How does educational attainment affect the risk of being infected by HIV/AIDS? Evidence from a general population cohort in rural Uganda. World Bank Development Research Group Working Paper. Washington, D.C.: World Bank. Dollar, David, Raymond Fisman, and Roberta Gatti. 2001. Are women really the ‘fairer’ sex? Corruption and women in government. Journal of Economic Behavior and Organization 46(4): 423–429. Gage, Anastasia, Elisabeth Sommerfeldt, and Andrea Piani. 1997. Household structure and childhood immunization in Niger and Nigeria. Demography 34(2): 195-309. Herz, Barbara and Gene Sperling. 2004. What works in girls’ education: evidence and policies for the developing world. New York: Council on Foreign Relations. Hill, M. Anne and Elizabeth King. 1995. “Women’s Education and Economic Well-Being.” Feminist Economics 1(2): 21-46. Klasen, Stephan. 1999. Does Gender Inequality Reduce Growth and Development? Evidence from Cross-Country Regressions. Policy Research Report on Gender and Development Working Paper No. 7. Washington, D.C.: World Bank. Malhotra, Anju, Caren Grown, and Rohini Pande. 2003. Impact of investments in female education on gender inequality. Washington, D.C.: International Center for Research on Women. Schultz, T. Paul. 1993. “Returns to women’s schooling,” in Elizabeth King and M. Anne Hill, eds., Women’s Education in Developing Countries: Barriers, Benefits, and Policy. Baltimore: Johns Hopkins Press. Smith, Lisa C., and Lawrence Haddad. 1999. Explaining child malnutrition in developing countries: a cross-country analysis. International Food Policy Research Institute (IFPRI) Food Consumption and Nutrition Division Discussion Paper 60. Washington, D.C.: IFPRI. Subbarao, K., and Laura Raney. 1995. Social gains from female education. Economic Development and Cultural Change 44 (1): 105-28. Summers, Lawrence H. 1994. Investing in all the people: educating women in developing countries. EDI Seminar Paper No. 45, Washington, D.C.: World Bank. Thomas, D., J. Strauss, and M. H. Henriques. 1990. Child survival, height for age, and household characteristics in Brazil. Journal of Development. 33(2): 197-234. Trussell, T. J. and S. Preston. 1982. Estimating the covariates of child mortality from retrospective reports of mothers. Health Policy and Education. 3:1-36. UNESCO. 2000. “Women and Girls: Education, Not Discrimination.” Paris: UNESCO. UNICEF. 2002. Education and HIV Prevention. Citing data from Kenya Demographic and Health Survey. New York: UNICEF. Vandemoortele, J. and E. Delamonica. 2000. Education ‘vaccine’ against HIVAIDS. Current Issues in Comparative Education 3(1).
  • 47. Altuzarra, A., Gálvez-Gálvez, C. and González-Flores, A., 2021. Is gender inequality a barrier to economic growth? A panel data analysis of developing countries. Sustainability, 13(1), p.367. Sarker, M.N.I., Wu, M. and Hossin, M.A., 2019. Economic effect of school dropout in Bangladesh. International journal of information and education technology, 9(2), pp.136-142. Bertay, A.C., Dordevic, L. and Sever, C., 2020. Gender inequality and economic growth: Evidence from industry-level data. International Monetary Fund. Munir, K. and Kanwal, A., 2020. Impact of educational and gender inequality on income and income inequality in South Asian countries. International journal of social economics, 47(8), pp.1043-1062. Bird, K., Chabé-Ferret, B. and Simons, A., 2022. Linking human capabilities with livelihood strategies to speed poverty reduction: Evidence from Rwanda. World Development, 151, p.105728.

Source

  • United National Educational, Scientific, and Cultural Organization Institute for Statistics (UNESCO/UIS)

    UIS compiles education expenditure data from official responses to surveys and from reports provided by education authorities in each country. Specifically, MCC uses government expenditure on education as a percentage of GDP (%) from the SDG database.