Arthshastra Indian Journal of Economics & Research

Open Access Open Access  Restricted Access Subscription Access

The Differential Effects of the Determinants of Household Education Expenditure in India : Quantile Regression Estimation


Affiliations
1 Formerly Professor, Department of Econometrics, University of Madras, Chennai - 600 005, Tamil Nadu, India

   Subscribe/Renew Journal


Despite substantial government expenditure on education, scholarships, and financial aid to students to provide affordable education, the household education expenditure on children is sizable and varies widely on account of gross differences in the socioeconomic, demographic, religious, and cultural factors. This paper attempted to identify such determinants and analyze the differential effects of the determinants of household education expenditure on children in India using the 2014 NSSO 71st Round survey data by applying the quantile regression method. Unlike the standard regression method, the quantile regression method allows estimation beyond the average effects at different points of the distribution of household expenditure on education. The quantile regression estimates revealed that low-income households were more sensitive to changes in household income and government programmes than upper-income households. The proportion of household income spent on the education of children increased more in the lower quantiles than in the higher quantiles. Gender bias existed at the lower quantiles and was considerably less at the higher quantiles. The SC/ST households spent less than the non-SC/ST communities at the lower quantiles and the difference got reduced at higher quantiles. Compared to scholarships, the provision of educational materials had a higher impact on household education expenditure. More children from lower quantiles attended government institutions, and a substantial difference existed in household education expenditure between the students attending government and private educational institutions. Despite government policies and programmes for affordable education, the study observed that the lower-income households still incurred a considerable proportion of their income on the education of their children.

Keywords

Household Education Expenditure, Socioeconomic Determinants, Differential Effects, Gender Bias, Quantile Regression.

JEL Classification : B23, C21, C31, C61, H52, I22.

Paper Submission Date : December 18, 2020; Paper Sent Back for Revision : December 7, 2020; Paper Acceptance Date : February 15, 2021.

User
Subscription Login to verify subscription
Notifications
Font Size

  • Bayar, A. A., & Ilhan, B. Y. (2016). Determinants of household education expenditures: Do poor spend less on education ? Topics in Middle Eastern and African Economies, 18(1), 83–111.

  • Chandrasekhar, S., Geetha Rani, P., & Sahoo, S. (2019). Household expenditure on higher education : What do we know and what do recent data have to say ? Economic and Political Weekly, 54(20), 52–60.

  • Chatterji, M., Mohan, S., & Dastidar, S.G. (2015). Determinants of public education expenditure : Evidence from Indian states. International Journal of Education Economics and Development, 6(1), 1–19. https://doi.org/10.1504/IJEED.2015.068355

  • Jana, S. K., & Maiti, A. (2019). State-wise public expenditure on higher education in India : An empirical analysis. Arthashastra Indian Journal of Economics & Research, 8(2), 7–20. https://doi.org/10.17010/aijer/2019/v8i2/145222

  • Khan, B. M. (2013). Public expenditure on education in Karnataka. Arthashastra Indian Journal of Economics & Research, 2(6), 31–39. https://doi.org/10.17010/aijer/2013/v2i6/54538

  • Koenker, R.W., & Bassett, G. (1978). Regression quantiles. Econometrica, 46(1), 33–50. https://www.jstor.org/stable/1913643

  • Koenker, R. W., & Hallock, K. F. (2001). Quantile regression. Journal of Economic Perspectives, 15(4), 143–156. https://doi.org/10.1257/jep.15.4.143

  • Motiram, S., & Osberg, L. (2012). Demand or supply for schooling in rural India? Electronic International Journal of Time Use Research, 9(1), 1–27.

  • NSSO. (2014). 71s t Round - Key indicators of social consumption in India: Education. http://mospi.nic.in/sites/default/files/national_data_bank/ndb-rpts-71.htm

  • Ota, M., & Moffatt, P. G. (2007). The within-household schooling decision: A study of children in rural Andhra Pradesh. Journal of Population Economics, 20(1), 223–239. https://doi.org/10.1007/s00148-005 0033-z

  • Rajalakshmy, G. (2012). Higher education in India : Challenges and prospects. Arthashastra Indian Journal of Economics & Research, 1(4), 25–32. https://doi.org/10.17010/aijer/2012/v1i4/54534

  • Sarkar, N. (2017). Determinants of household expenditure on higher education in India. International Education and Research Journal, 3(6), 12–14.

  • Steinberg, M. B. (2015). On the demand for education in India (Doctoral dissertation). Department of Economics, Harvard University.

  • Tilak, J. B. (1996). How free is free primary education in India ? Economic and Political Weekly, 31(5), 355–366.

  • Tilak, J. B. (2002). Determinants of household expenditure on education in rural India (Working Paper Series No. 88). National Council of Applied Economic Research.


Abstract Views: 515

PDF Views: 0




  • The Differential Effects of the Determinants of Household Education Expenditure in India : Quantile Regression Estimation

Abstract Views: 515  |  PDF Views: 0

Authors

T. Lakshmanasamy
Formerly Professor, Department of Econometrics, University of Madras, Chennai - 600 005, Tamil Nadu, India

Abstract


Despite substantial government expenditure on education, scholarships, and financial aid to students to provide affordable education, the household education expenditure on children is sizable and varies widely on account of gross differences in the socioeconomic, demographic, religious, and cultural factors. This paper attempted to identify such determinants and analyze the differential effects of the determinants of household education expenditure on children in India using the 2014 NSSO 71st Round survey data by applying the quantile regression method. Unlike the standard regression method, the quantile regression method allows estimation beyond the average effects at different points of the distribution of household expenditure on education. The quantile regression estimates revealed that low-income households were more sensitive to changes in household income and government programmes than upper-income households. The proportion of household income spent on the education of children increased more in the lower quantiles than in the higher quantiles. Gender bias existed at the lower quantiles and was considerably less at the higher quantiles. The SC/ST households spent less than the non-SC/ST communities at the lower quantiles and the difference got reduced at higher quantiles. Compared to scholarships, the provision of educational materials had a higher impact on household education expenditure. More children from lower quantiles attended government institutions, and a substantial difference existed in household education expenditure between the students attending government and private educational institutions. Despite government policies and programmes for affordable education, the study observed that the lower-income households still incurred a considerable proportion of their income on the education of their children.

Keywords


Household Education Expenditure, Socioeconomic Determinants, Differential Effects, Gender Bias, Quantile Regression.

JEL Classification : B23, C21, C31, C61, H52, I22.

Paper Submission Date : December 18, 2020; Paper Sent Back for Revision : December 7, 2020; Paper Acceptance Date : February 15, 2021.


References





DOI: https://doi.org/10.17010/aijer%2F2021%2Fv10i1%2F159883