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Family decision-making for educational expenditure: new evidence from survey data for Nigeria

Author

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  • Glenn P. Jenkins
  • Hope Amala Anyabolu
  • Pejman Bahramian

Abstract

This study examines the determinants of educational expenditures by households in Nigeria. Data from the Nigerian General Household Survey, Panel 2012/2013, Wave 2 was used and a double-hurdle model was employed for the analysis. The results suggest household income, the age, education, gender of the household heads and urban versus rural residence have a significant impact on the decision to spend on education. Such expenditures are income elastic overall, but are very different in magnitude for low income compared to higher income families. It is found that the income elasticity of education expenditures are approximately four times greater for households in the bottom two-thirds of the income distribution than for those on the top one-third of the income distribution.

Suggested Citation

  • Glenn P. Jenkins & Hope Amala Anyabolu & Pejman Bahramian, 2019. "Family decision-making for educational expenditure: new evidence from survey data for Nigeria," Applied Economics, Taylor & Francis Journals, vol. 51(52), pages 5663-5673, November.
    • Handle: RePEc:taf:applec:v:51:y:2019:i:52:p:5663-5673
    DOI: 10.1080/00036846.2019.1616075
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    Cited by:

    1. Asmat Ullah & Ijaz Hussain, 2022. "An Empirical Investigation Of Household Head’S Decision For Demand For Education In Pakistan: Evidence From Pakistan Social And Living Standard Measurement (Pslm) Survey," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 11(2), pages 64-73, June.
    2. Asmat Ullah & Saba Shaukat & Bilal Tariq, 2022. "Household Socio-Demographic Characteristics and Out of Pocket Educational Expenditure in Pakistan," Journal of Policy Research (JPR), Research Foundation for Humanity (RFH), vol. 8(4), pages 1-7, December.
    3. Le, Minh Hanh & Afsharian, Mohsen & Ahn, Heinz, 2021. "Inverse Frontier-based Benchmarking for Investigating the Efficiency and Achieving the Targets in the Vietnamese Education System," Omega, Elsevier, vol. 103(C).
    4. Rashmi Rashmi & Bijay Kumar Malik & Sanjay K. Mohanty & Udaya Shankar Mishra & S. V. Subramanian, 2022. "Predictors of the gender gap in household educational spending among school and college-going children in India," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
    5. Yangqi Fu & Yuchun Zhu, 2023. "Internet use and technical efficiency of grain production in China: a bias-corrected stochastic frontier model," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    6. Ye, Juntao & Cai, Liming & Shi, Xinjie & Cheng, Mingwang, 2024. "Pursuing a brighter future: Impact of the Hukou reform on human capital investment in migrant children in China," China Economic Review, Elsevier, vol. 85(C).
    7. Wei, Huaying & Guo, Rui & Sun, Honghao & Wang, Nan, 2021. "Household leverage and education expenditure: the role of household investment," Finance Research Letters, Elsevier, vol. 38(C).
    8. Kang, Chuankun & Fu, Zhengxin & Zhao, Shuchen, 2024. "Maternal relative income, bargaining power, and children's education expenditure," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 1395-1410.

    More about this item

    JEL classification:

    • R29 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Other
    • I10 - Health, Education, and Welfare - - Health - - - General
    • B23 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Econometrics; Quantitative and Mathematical Studies

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