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Vietnam’s educational development: Consolidating and building on success

Ian Coxhead, University of Wisconsin-Madison

MOET and UNICEF, 23 April 2019(Revised, May 2019)

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Overview

• Vietnam has made great progress in increasing average years of education

• However, large achievement gaps remain—relative to SDGs, national growth goals, and among age peers

• Economic growth & globalization have changed composition of employment and returns to schooling– Most new jobs still require only basic education

• Increasing rate of progression to upper secondary school (and beyond) is still a major challenge

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Base +5 +10 +15 +20 +25 +30 +35 +40 +45 +50 +55

China

South Korea

Vietnam

Philippines

Singapore

Malaysia

Thailand

Indonesia

Source: Authors’ calculations using data from www.barrolee.com (accessed 7/20/2018). Country-specific base years (using comparable per capita GDP) are: Vietnam 1990; China 1985, Indonesia 1970, Thailand 1965, Philippines 1960, and Malaysia, Singapore, and South Korea 1955.

Development-stage comparable mean years of schooling for population aged 15+

Average years of schooling: big gains relative to peer economies

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Net enrollment rate by age, 2004 and 2014 (Source: VHLSS)

Al l households 2004 Al l households 2014

Net enrollment rate has improved, esp. for preschool and tertiary

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Unequal progressNet enrolment rate

from age 5 – 25by income quintile

2012

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NER @

age:All Q5 Q1

12 92 98 88

18 46 70 20

Vietnam:net enrolment rate from age 5 – 25,

by ethnicity2012

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NER @

age:All Kinh EM

12 92 96 88

18 46 50 32

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Grade progression in 2006 and 2016: Top 20% households by expenditures

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Grade progression in 2006 and 2016: Bottom 20% households by expenditures

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Moving up: progression to 10th grade

• Almost all adolescents now complete grade 9– Completion rate has improved since 2004

• Who continues beyond grade 9?– Strong evidence of selection by vulnerability (e.g., ethnicity,

economic status of parents)– Strong evidence of “pull” from the labor market

• 10th grade entrance exam: why we care– Goal of universal 12-year education (SDG 4)– Different school dropout points:

• No test taken• Test taken, but poor result• High school “undermatch” (don’t select best possible school)

– Each may require a different policy approach

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Progression to 10th grade: evidence from data

• Data source: 10th grade exam candidates and scores by province and year (2014 – 2017)

• Source: provincial DoET– Dong Thap– Ninh Thuan– Lao Cai– HCM City (not used in this study)

• Dataset includes student’s place of residence, lower secondary school, school where test taken, age, ethnicity, test scores

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Q1. What fraction of children take the 10th grade entrance examination?

• We count the number of test-takers in each province and year, by district

• By district, we calculate the size of the 15-year old cohort from the 2014 Intercensal Survey of Population (GSO)

• We can then calculate district-level ratio of test-takers to total cohort

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G10 entrance exam: test-taking rate in 2014-15(district average fraction of children in cohort taking G10 exam)

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Province Sample Mean S.D. Min Max

Lao Cai (9 districts) All 0.418 0.213 0.147 0.691

Male 0.466 0.195 0.207 0.740

Female 0.380 0.238 0.105 0.733

Ninh Thuan (7 dist.) All 0.591 0.166 0.415 0.897

Male 0.469 0.181 0.237 0.778

Female 0.750 0.175 0.527 1.033

Dong Thap (12 dist.) All 0.547 0.067 0.450 0.649

Male 0.495 0.049 0.400 0.577

Female 0.616 0.125 0.431 0.826S.D.: Standard deviation

Q2. What explains fraction of children taking G10 exam?

• We calculate district-level measures of well-being:– Real per capita household expenditure– Poverty headcount – Poverty severity

• We use regression methods to test statistical relationship of these variables to the test-taking rate

• Any one of these variables explains about half the variation in test-taking rate

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Strong relation between income, poverty and test-taking rate

15District average test-taking rate and several measures of poverty and well-being, with fitted regression lines 16

(1) (2) (3) (4)

VARIABLES

Headcount poverty -0.606***

(0.130)

Log of per cap exp. 0.369***

(0.080)

Poverty gap -1.502***

(0.394)

Pov. severity index -2.934***

(0.907)

Urban = 1 0.084** 0.030 0.108*** 0.120***

(0.037) (0.044) (0.038) (0.038)

Constant 0.716*** -3.143*** 0.652*** 0.610***

(0.077) (0.771) (0.076) (0.076)

Observations 66 66 66 66

R-squared 0.541 0.538 0.496 0.467

Explaining district-level test-taking rate: detailed regression results

Dependent variable: fraction of cohort taking G10 exam. Standard errors in parentheses. Province and year dummy variables also included. *** p<0.01, ** p<0.05, * p<0.1

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Q3. What are the sources of variation in scores, among children taking the exam?

• Early, descriptive results with available data

• Calculate distribution of test scores by:– Province– Sex– Ethnicity– Urban/rural

• Lots of variation in each of these measures!

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Test scores: unequal within and between provinces

10th grade examinationscores by ethnicity,

urban/rural locationand gender

Summary and policy directions

• Middle-income challenge: deepen & broaden school attainment to achieve equity and sustain growth

• Current policy: increase supply, improve curricula– Better teachers, schools and affordability– More relevant curriculum– These are important measures

• Demand failures also matter (labor market)• More than one dropout point• Improved school persistence and performance may

require more than one policy treatment

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Grade 10 entrance exam analysis: next steps

• Test score datasets contain little information about students• We know their middle school and test-taking school• More information about schools will help us to understand

contribution of class sizes and other school-specific characteristics to test-taking rate and test scores

In order to learn more, we need more data:• District or province level labor market data

à Measures of opportunity cost of time spent in school

• Test scores from more provinces – better coverage• School-level data (available places, teacher/student ratios,…)• Admissions cutoff scores for individual schools

à Insights relevant to the design of education policy-- Including special measures directed at poor and ethnic minorities

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Thank you for listening!

Today’s talk comes from several research projects• Diep Phan and Ian Coxhead, 2019: Educational development in

Vietnam. Chapter forthcoming in J. London, ed: Handbook of Contemporary Vietnam.

• Ian Coxhead and Rashesh Shrestha, 2017. Globalization and school-work choices in an emerging economy: Vietnam. Asian Economic Papers

• Diep Phan and Ian Coxhead, 2018: Persistent privilege? Institutional educational achievement gaps in Vietnam (working paper)

• Research in progress, in collaboration with Mr. Nguyen Phong and Dr. Valerie Kozel (formerly World Bank/Hanoi)

All these papers are available for download at https://bit.ly/2W70ea2

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