Skip to main content

Advertisement

SpringerLink
Log in

Socio-economic inequalities in spending on various levels of education across Indian households: an update

  • Article
  • Published:
Indian Economic Review Aims and scope Submit manuscript

Abstract

The study examines potential channels of socio-economic inequalities in education expenditure by Indian households at three different levels of education using National Sample Survey Data (2018). Based on Heckman’s two-step model estimates, the inequalities are evident in the participation choice and education expenditure by social groups, place of residence and religious minorities for education up to the secondary level. Nevertheless, the economic status of the household is less critical. Gender inequality is more evident in the expenditure incurred than the enrollment choice at the secondary level. For education at higher secondary and above levels, the crucial channel of social inequality lies in choosing a subject specialization and subsequent expenditures. As per multinomial logit estimates, the choice of streams is highly selective, favoring those with the capacity and willingness to pay. The selection corrected expenditure based on Lee correction reveals the extent of socio-economic inequalities in education expenditures at these levels of education. The apparent disparity in participation choice and expenditure can only be addressed through calibrated policy interventions, especially at higher levels of education. Failing to resolve this may exacerbate inequalities in education and labor market participation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Source: Authors’ calculation from NSS (2018), 75th round

Fig. 2

Source: Authors’ calculation from NSS (2018), 75th round

Fig. 3

Source: Authors’ calculation from NSS (2018), 75th round

Fig. 4

Source: Authors’ calculation from NSS (2018), 75th round

Similar content being viewed by others

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Notes

  1. Up to secondary level refers to Classes from I to X.

  2. Various streams are different courses that students opt for such as Humanities, Commerce and Science.

  3. Higher secondary refers to Class XI and XII, whereas above Higher secondary means classes above XII, Graduation and Post-graduation.

  4. NER is the number of students of the age of a particular level of education that are enrolled in that level of education, expressed as a per centage of the total population in that age group (Eurostat/Glossary: https://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:Net_enrolment_rate).

  5. \(Total\, household \,expenditure\,=\,\left(Monthly\, consumption\, expenditure*12\right)\).

  6. Per-student expenditure is obtained from the unit level data and calculated as \(\frac{Expenditure\, on \,education\, for \,respective\, levels}{Total \,number \,of \,individuals\,in\, the\, household\, who\, attending\, that \,particular\,level \,of \,education}\)

References

  • Acar, E. Ö., Günalp, B., & Cilasun, S. M. (2016). An empirical analysis of household education expenditures in Turkey. International Journal of Educational Development, 51, 23–35. https://doi.org/10.1016/j.ijedudev.2016.03.007

    Article  Google Scholar 

  • Agrawal, T. (2014). Educational inequality in rural and urban India. International Journal of Educational Development, 34, 11–19.

    Article  Google Scholar 

  • Ahmadzai, H. (2018). Tests for separability and factor market participation in Afghanistan. CREDIT Research Paper.

  • Al-Samarrai, S., Gangwar, M., & Gala, P. (2020). The Impact of the COVID-19 Pandemic on Education Financing. World Bank Other Operational Studies 33739, the World Bank.

  • Asadullah, M. N., & Chaudhury, N. (2009). Reverse gender gap in schooling in Bangladesh: insights from urban and rural households. Journal of Development Studies, 45(8), 1360–1380.

    Article  Google Scholar 

  • Aslam, M., & Kingdon, G. G. (2008). Gender and household education expenditure in Pakistan. Applied Economics, 40(20), 2573–2591. https://doi.org/10.1080/00036840600970252

    Article  Google Scholar 

  • Azam, M., & Kingdon, G. G. (2013). Are girls the fairer sex in India? Revisiting intra—household allocation of education expenditure. World Development, 42, 143–164.

    Article  Google Scholar 

  • Bairagya, I. (2018). Why is unemployment higher among the educated. Economic & Political Weekly, 53(7), 43–51.

    Google Scholar 

  • Bohindar, S. (2019). Corporate route of higher education. Frontline, 36(14), 8–11.

    Google Scholar 

  • Castelló-Climent, A., & Mukhopadhyay, A. (2013). Mass education or a minority well educated elite in the process of growth: The case of India. Journal of Development Economics, 105, 303–320. https://doi.org/10.1016/j.jdeveco.2013.03.012

    Article  Google Scholar 

  • Chaudhuri, K., & Roy, S. (2006). Do parents spread educational expenditure evenly across the two genders? Evidence from two North Indian states. Economic and Political Weekly, 5276–5282.

  • Chiplunkar, G., & Weaver, J. (2021). Marriage markets and the rise of dowry in India. Available at SSRN 3590730.

  • Das, U., & Sarkhel, P. (2020). Does more schooling imply improved learning? Evidence from a conditional cash transfer programme in India (SSRN Scholarly Paper ID 3703566). Social Science Research Network. https://doi.org/10.2139/ssrn.3703566

    Article  Google Scholar 

  • Datta, S., & Kingdon, G. G. (2019b). Gender Bias in Intra - Household Allocation of Education in India: Has It Fallen over Time? IZA Discussion Papers.

  • Datta, S., & Kingdon, G. G. (2021). Gender Bias in Intra - Household Allocation of Education in India: Has it fallen over time? In DoQSS Working Papers (No. 21–06; DoQSS Working Papers). Quantitative Social Science - UCL Social Research Institute, University College London. https://ideas.repec.org/p/qss/dqsswp/2106.html

  • Deaton, A. (1989). Looking for boy-girl discrimination in household expenditure data. The World Bank Economic Review, 3(1), 1–15.

    Article  Google Scholar 

  • Hjortsberg, C. (2003). Why do the sick not utilise health care? The Case of Zambia. Health Economics, 12(9), 755–770.

    Article  Google Scholar 

  • Humphreys, B. R. (2013). Dealing with zeros in economic data. University of Alberta Department of Economics, 1, 1–27.

    Google Scholar 

  • Johnson, N. L., Kovarik, C., Meinzen-Dick, R., Njuki, J., & Quisumbing, A. (2016). Gender, assets, and agricultural development: Lessons from eight projects. World Development, 83, 295–311.

    Article  Google Scholar 

  • Kim, J.-H., & Park, D. (2010). The determinants of demand for private tutoring in South Korea. Asia Pacific Education Review, 11(3), 411–421.

    Article  Google Scholar 

  • Kingdon, G. G. (2005). Where has all the bias gone? Detecting gender bias in the intra—household allocation of educational expenditure. Economic Development and Cultural Change, 53(2), 409–451.

    Article  Google Scholar 

  • Lancaster, G., Maitra, P., & Ray, R. (2008). Household expenditure patterns and gender bias: evidence from selected Indian states. Oxford Development Studies, 36(2), 133–157.

    Article  Google Scholar 

  • Lee, L.-F. (1983). Generalized econometric models with selectivity. Econometrica: Journal of the Econometric Society, 51, 507–512.

    Article  Google Scholar 

  • Madden, D. (2008). Sample selection versus two-part models revisited: The case of female smoking and drinking. Journal of Health Economics, 27(2), 300–307.

    Article  Google Scholar 

  • Maertens, A. (2013). Social norms and aspirations: age of marriage and education in rural India. World Development, 47, 1–15.

    Article  Google Scholar 

  • Majumder, A., & Mitra, C. (2017). Gender bias in household education expenditure: the case of West Bengal. Indian Growth and Development Review.

  • Sachar Commission, R. of. (2015, August 8). Sachar Committee Report | Ministry of Minority Affairs | Government of India. https://minorityaffairs.gov.in/reports/sachar-committee-report

  • Saha, A. (2013). An assessment of gender discrimination in household expenditure on education in India. Oxford Development Studies, 41(2), 220–238.

    Article  Google Scholar 

  • Sekher, T., & Ram, F. (2015). Conditional cash transfers for girls in India: Assessment of a girl child promotion scheme from beneficiary perspective. International Institute for Population Sciences.

  • Sengupta, A. (2020). Rapid growth of private universities. Economic and Political Weekly, 55(22), 7–8.

    Google Scholar 

  • Singh, S., & Sridhar, K. S. (2002). Government and private schools: Trends in enrolment and retention. Economic and Political Weekly, 4229–4238.

  • Tansel, A., & Bircan, F. (2006). Demand for education in Turkey: a tobit analysis of private tutoring expenditures. Economics of Education Review, 25(3), 303–313. https://doi.org/10.1016/j.econedurev.2005.02.003

    Article  Google Scholar 

  • Tilak, J. B. G. (2002). Elasticity of household expenditure on education in rural India. South Asia Economic Journal, 3(2), 217–226. https://doi.org/10.1177/139156140200300206

    Article  Google Scholar 

  • von Weizsäcker, R. K., & Wigger, B. U. (1999). Risk, resources, and education: public versus private financing of higher education. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.880829

    Article  Google Scholar 

  • Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data. Cambridge: MIT press.

    Google Scholar 

  • You, X., & Kobayashi, Y. (2011). Determinants of out-of-pocket health expenditure in China. Applied Health Economics and Health Policy, 9(1), 39–49.

    Article  Google Scholar 

Download references

Acknowledgements

We thank the anonymous reviewers for the fruitful comments and remarks to improve the initial version of the manuscript

Funding

We declare that no funds, grants, or other support were received during the preparation of this manuscript.

Author information

Authors and Affiliations

  1. Department of Applied Economics, Cochin University of Science and Technology (CUSAT), Cochin, Kerala, 682022, India

    Aswathy Rachel Varughese

  2. Institute for Social and Economic Change (ISEC), Centre for Human Resource Development, Dr. V K R V Rao Road, Nagarbhavi, Bengaluru, 560072, India

    Indrajit Bairagya

Authors
  1. Aswathy Rachel Varughese
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Indrajit Bairagya
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by ARV and IB. The first draft of the manuscript was written by ARV and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Aswathy Rachel Varughese.

Ethics declarations

Conflict of interest

We combinedly declare that no conflicting interest (financial or non- financial) are directly or indirectly related to the work submitted for publication. We have no relevant financial or non-financial interests to disclose.

Ethical approval

We combinedly declare that all ethical standards of the journal are met while preparing the manuscript.

Consent to participate and publish

As per the requirement of the journal, we combinedly give the consent for the same.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

See Tables 8 and 9.

Table 8 Summary Statistics—Mean
Full size table
Table 9 Proportion of enrolled students attending private educational institutions (in percentage).
Full size table

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Varughese, A.R., Bairagya, I. Socio-economic inequalities in spending on various levels of education across Indian households: an update. Ind. Econ. Rev. 58, 197–229 (2023). https://doi.org/10.1007/s41775-023-00186-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41775-023-00186-9

Keywords

JEL Classification

Search

Navigation