Tracking the Progress of a Child from Enrolment to Completion of Secondary Education in India



Using both rounds of India Human Development Survey (2004-05 and 2011-2012) data, this study has tracked the progress of students from enrolment to completion of the secondary level of education in India. Using a logit model, we have examined how in addition to family attributes the ‘access to school resources,’ and ‘learning activities’ of a child associated with the secondary and higher secondary school completion, post-enrolment. We find that household assets, parental education, and ‘computer or Internet usage by any household member’ are major determinants of secondary and higher secondary school completion by a student. The chances of completing both levels of schooling increase with the increase in the level of household assets and parental education, but the marginal effect of both is higher for government school children relative to private school children. We also find that the stumbling block (as a backward caste and Muslims) for most students lies at the entry to secondary school particularly for government school students. We also find that the completion of higher secondary school is robust to changes in caste and religion of the student. Moreover, the probabilities of completing higher secondary school by government and private school students are almost similar for children from the ‘wealthy families.’


  1. Amemiya, T. (1981). Qualitative response models: A survey. Journal of Economic Literature, 19(4), 1483–1536.Google Scholar
  2. Aslam, M., & Atherton, P. (2013). The shadow education sector in India and Pakistan: the determinants, benefits and equity effects of private tutoring. In: Macpherson, I., Robertson, S., Walford, G. (Eds.), Education Privatisation and Social Justice: Case Studies from Africa, South Asia and South-East Asia. Symposium Books: Oxford. 137–156.Google Scholar
  3. Azam, M. (2014). Private tutoring: Evidence from India. SSRN Electronic Journal.
  4. Barro, R. J. (2001). Human capital and growth. The American Economic Review, 91(2), 12–17.CrossRefGoogle Scholar
  5. Battle, P. A. (1999). Home computers and school performance. The Information Society, 15(1), 1–10. Scholar
  6. Becker, G. S. (1964). Human Capital: A theoretical and empirical analysis, with special reference to education. National Bureau of Economic Research, New York.Google Scholar
  7. Behrman, J. R., & Rosenzweig, M. R. (2002). Does increasing women’s schooling raise the schooling of the next generation? American Economic Review, 91(1), 323–334.CrossRefGoogle Scholar
  8. Bhorkar, S., & Bray, M. (2018). The expansion and roles of private tutoring in India: From supplementation to supplantation. International Journal of Educational Development, 62, 148–156. Scholar
  9. Biswal, K. (2011). Secondary education in India: Development policies, programmes and challenges. Brighton: Consortium for Research on Educational Access, Transitions and Equity.Google Scholar
  10. Björklund, A., & Salvanes, K. G. (2011). Education and family background: Mechanisms and policies. Handbook of the Economics of Education, 3(3), 201–247.CrossRefGoogle Scholar
  11. Borooah, V. K. (2001). Do children in India benefit from having mothers who are literate? New Delhi: National Council of Applied Economic Research, (No. 77).Google Scholar
  12. Buchmann, C., & Hannum, E. (2001). Education and stratification in developing countries: A review of theories and research. Annual Review of Sociology, 27(1), 77–102.CrossRefGoogle Scholar
  13. Business Standard. (2018). Primary level dropout rate in India was 4.13% in 2014–15: Prakash Javadekar, Business Standard (January 4).
  14. Cameron, S. V., & Heckman, J. J. (1998). Life cycle schooling and dynamic selection bias: Models and evidence for five cohorts of American males. Journal of Political Economy, 106(2), 262–333.CrossRefGoogle Scholar
  15. Checchi, D. (2006). The economics of education: Human capital, family background and inequality. Cambridge University Press.Google Scholar
  16. Conger, R. D., & Donnellan, M. B. (2007). An interactionist perspective on the socio-economic context of human development. Annual Review of Psychology, 58, 175–199.CrossRefGoogle Scholar
  17. Duncan, G., & Murnane, R. (2011). Whither opportunity? Rising inequality, schools, and children’s life chances. New York: Russell Sage Foundation.Google Scholar
  18. Duraisamy, P. (1998). Morbidity in Tamil Nadu: Levels, differentials and determinants. Economic and Political Weekly, 982–990.Google Scholar
  19. Filmer, D., & Pritchett, L. (1999). Educational enrollment and attainment in India: Household wealth, gender, village, and state effects.  Journal of Educational Planning and Administration,13(2), 135–164.Google Scholar
  20. Government of India. (2008). School Education Statistics 2007–08. New Delhi: Ministry of Human Resource Development.Google Scholar
  21. Greene, W. H. (2003). Econometric analysis. Upper Saddle River. NJ: Prentice Hall.Google Scholar
  22. Hanushek, E. A., & Woessmann, L. (2015). The knowledge capital of nations: Education and the economics of growth. MIT Press.Google Scholar
  23. Haveman, R., & Wolfe, B. (1995). The determinants of children’s attainments: A review of methods and findings. Journal of Economic Literature, 33(4), 1829–1878.Google Scholar
  24. Huang, J. (2013). Inter-generational transmission of educational attainment: The role of household assets. Economics of Education Review, 33, 112–123.CrossRefGoogle Scholar
  25. Huang, J., Guo, B., Kim, Y., & Sherraden, M. (2010). Parental income, assets, borrowing constraints and children’s post-secondary education. Children and Youth Services Review, 32(4), 585–594.CrossRefGoogle Scholar
  26. Kerawalla, L., & Crook, C. (2002). Children’s computer use at home and at school: Context and continuity. British Educational Research Journal, 28(6), 751–771.CrossRefGoogle Scholar
  27. Kim, Y., & Sherraden, M. (2011). Do parental assets matter for children’s educational attainment? Evidence from mediation tests. Children and Youth Services Review, 33(6), 969–979.CrossRefGoogle Scholar
  28. Kingdon, G. G. (2007). The progress of school education in India. Oxford Review of Economic Policy, 23(2), 168–195.CrossRefGoogle Scholar
  29. Lee, S., Brescia, W., & Kissinger, D. (2009). Computer use and academic development in secondary schools. Computers in the Schools, 26(3), 224–235.CrossRefGoogle Scholar
  30. Lewin, K. M. (2011). Expanding access to secondary education: Can India catch up? International Journal of Educational Development, 31(4), 382–393.CrossRefGoogle Scholar
  31. Lillard, L. A., & Willis, R. J. (1994). Inter-generational educational mobility: Effects of family and state in Malaysia. Journal of Human Resources, 1126–1166.Google Scholar
  32. Long, J., & Freese, J. (2006). Regression Models for Categorical Dependent Variables Using Stata (2nd ed.). College Station, TX: Stata Press.Google Scholar
  33. Maitra, P. (2003). Schooling and educational attainment: Evidence from Bangladesh. Education Economics, 11(2), 129–153.CrossRefGoogle Scholar
  34. Maitra, P., & Sharma, A. (2009, November). Parents and children: Education across generations in India. In 5th Annual Conference on Economic Growth and Development. Delhi: Indian Statistical Institute, Delhi.Google Scholar
  35. Majumdar, M. (2014). The shadow school system and new class divisions in India. Working Paper Series, TRG Poverty & Education, Max Weber Stiftung, London.Google Scholar
  36. Majumdar, M. (2018). Access, success, and excess: debating shadow education in India. In: Kumar, K. (Ed.), Routledge Handbook on Education in India: Debates, Practices and Policies. Routledge: New York. 273–284.Google Scholar
  37. Nam, Y., & Huang, J. (2009). Equal opportunity for all? Parental economic resources and children’s educational attainment. Children and Youth Services Review, 31(6), 625–634.CrossRefGoogle Scholar
  38. NCRWC. (2002). Report of the National Commission to Review of the Working of the Constitution. New Delhi, Government of India.Google Scholar
  39. NSSO [National Sample Survey Office]. (2016). Education in India (NSS 71st Round, January-June 2014, No.575 [75/25.2/1]. Government of India, Ministry of Statistics and Programme Implementation. New Delhi. http://admin.indiaenvironmentportal,
  40. OECD. (2010). Education at a Glance 2010: OECD Indicators. Paris.
  41. Salovaara, I. M. (2017). The work of tuitions: Moral infrastructure in a Delhi neighbourhood. Asian Anthropology, 16(4), 243–260.CrossRefGoogle Scholar
  42. Sengupta, P., & Guha, J. (2002). Enrolment, drop-out and grade completion of girl children in West Bengal. Economic and Political Weekly, 1621–1637.Google Scholar
  43. Srinivasan, J. (2010). Demand for education in India: Sub regional study. New Delhi: Well Publication.Google Scholar
  44. Tilak, J. B. G. (2002). Determinants of household expenditure on education in rural India. New Delhi: National Council of Applied Economic Research.Google Scholar
  45. Tilak, J. B. G. (2003). Public Expenditure on Education in India: A Review of Trends and Emerging Issues, In: J. B. G. Tilak (ed.) Financing in India: Current Issues and Changing Perspectives (pp. 3–54). New Delhi: Ravi Books for National Institute of Educational Planning and Administration.Google Scholar
  46. UNESCO. (2013). Education for All Global Monitoring Report 2013/4 Teaching and Learning: Achieving Quality for All.Google Scholar
  47. White, G., Ruther, M., & Kahn, J. (2016). Educational inequality in India: An analysis of gender differences in reading and mathematics. Working Paper No. 2016-2, India Human Development Survey.Google Scholar

Copyright information

© Council for Social Development  2020

Authors and Affiliations

  1. 1.Centre for Economic Studies and PlanningJawaharlal Nehru UniversityNew DelhiIndia

Personalised recommendations