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Accessing Higher Education in Developing Countries: panel data analysis from India,
Peru and Vietnam
Alan Sánchez (GRADE) Abhijeet Singh (UCL)
CEA 2016
Introduction • Education levels have risen rapidly around the world in recent years.
• Access to higher education has also increased rapidly in the last two decades.
– Deep literature on this topic in developed countries (Cameron and Heckman, 1998; Cameron and Taber, 2004; Cameron and Heckman, 2001; Keane and Wolpin, 2001).
– Yet we know much less about the relevant determinants of access in developing countries.
• We seek to address this gap for three developing countries using rich panel data on a cohort of individuals collected for over a decade preceding college enrolment.
– Comparable longitudinal data for India, Peru and Vietnam for a cohort that just entered into higher education.
Trends in Access to Higher Education
MICS 2010-2011 ENAHO 2012
Trends in Access to Higher Education
IHDS-2 2012
Objectives
1. Analyze patterns of access to higher education in three middle-income countries, focusing on inequalities by (i) socioeconomic characteristics and (ii) gender.
2. Employ panel-based regression analysis.
3. Investigate the extent to which the factors affect access to higher education vary across gender, across urban and rural areas and across parental education.
Data • The Young Lives Study: 4 countries, 2 cohorts, 15 years (2002-2016)
• Ethiopia, India (Andhra Pradesh), Peru and Vietnam
• In each country, two cohorts are tracked (12,000 in total):
– Cohort of 2,000 children born in 2001-2002 (younger cohort).
– Cohort of 1,000 children born in 1994-1995 (older cohort).
• Data from the Older Cohort is used in this study. This cohort has been tracked at ages 7-8, 11-12, 14-15 and 18-19.
R1 R2 R3 R4 6-18 months
4-5 y. 7-8 y. 11-12 y.
R1 R2 R3 R4 7-8 y. 11-12 y. 14-15 y. 18-19 y.
Younger cohort
R5 14-15 y.
R5 21-22 y.
2002 2006 2009 2013 2016
Young Lives Study: Data Structure
Older cohort
2002 2006 2009 2013 2016
R1 R2 R3 R4 6-18 months
4-5 y. 7-8 y. 11-12 y.
R1 R2 R3 R4 7-8 y. 11-12 y. 14-15 y. 18-19 y.
Younger cohort
R5 14-15 y.
R5 21-22 y.
2002 2006 2009 2013 2016
Young Lives Study: Data Structure
Older cohort
2002 2006 2009 2013 2016
Data used in this study
YL study: descriptive statistics (older cohort) India
sample Peru
sample Vietnam sample
Mean Mean Mean
Rural (in 2002) 76% 25% 82%
Wealth Index 0.41 0.48 0.44
Mother´s education level
None 42% 2% 10%
Primary school 29% 32% 27%
Secondary school 22% 47% 68%
Higher education 6% 19% 5%
Empirical specification
Enrolment in higher education, 18-19y , YL study India sample Peru sample Vietnam sample
% n % N % n
Never enrolled in HE 47.8 454 44.6 283 45.9 405
Enrolled in Secondary or lower
9.2 87 9.8 62 18.5 162
Ever enrolled in HE 43.1 409 45.7 290 35.6 312
Technical/vocational post secondary college
7.6 72 21.6 137 16.2 142
University 32.1 305 19.2 122 18.8 165
No longer enrolled 3.4 32 4.9 31 0.6 5
950 635 876
Main results
Results come from OLS estimations. Other controls included: parental education, household size, birth order, age, height-for-age at age 7, cluster fixed effects
Main results 1. There is a pronounced gradient with respect to early-life household wealth
and maternal education. • Moving from bottom to top wealth tercile: access to HE increases by 16.5 pp in India, 16.7 pp in
Peru and 12.4 pp in Vietnam.
• Having a mother with higher education (compared to no education) inceases access to HE by 18.4 pp in India, 20.7 pp in Peru and 22.6 pp in Vietnam.
2. Test scores in Math and Vocabulary at age 12 also predict access to HE (1 S.D. increase in Math scores increases access by 7 pp).
3. Persistent gender differences in access in Vietnam (pro-girl) and India (pro-boy).
Main results 4. Aspirations for higher education at age 12 are an important predictor
of enrolment in HE (by around 10 pp).
5. In India and Vietnam, the caregiver’s aspirations for higher education (measured when child aged 12 years) are also relevant.
Additional results 6. The associations differ by sex, specially in India…
• Wealth has a larger effect for boys compared to girls.
• Parental and child aspirations for higher education have a significant effect only in the case of girls.
7. …associations also differ by area of location (urban vs rural). • In both India and Peru, girls in rural areas are less likely to eventually reach higher
education than boys, but this does not seem to be the case in urban areas.
• In Vietnam, this pattern hold true in the opposite direction; there is a pronounced pro-girl difference in rural areas but no signs of similar differences in urban areas.
Concluding remarks 1. There are steep gradients in HE access across wealth and parental
education.
2. Gender differences in HE access are important.
3. Educational aspirations matter. Moreover, aspirations can act as a protective factor for girls.
Learn more:
www.ninosdelmilenio.org (for Peru, in Spanish)
www.younglives.org.uk
(for the four countries, in English)
