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Education in developing countries,. Michael Kremer Economics 1386, Fall 2006. Outline. Background: Education in Developing Countries Methodology Reducing the Cost of Education Changing Education Behavior Improving Provision of Education Inputs Incentives for Providers

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Education in developing countries

Education in developing countries,

Michael Kremer

Economics 1386, Fall 2006


Outline
Outline

  • Background: Education in Developing Countries

  • Methodology

  • Reducing the Cost of Education

  • Changing Education Behavior

  • Improving Provision of Education

    • Inputs

    • Incentives for Providers

  • Changing the Interaction of Consumers and Providers

    • Local Control and Participation

    • Contracting and Choice

  • Conclusion


Background motivation
Background: Motivation

  • Widely held belief that education can play a critical role in development

    • Macro- impact of education on economic growth

      • Lucas (1988), Barro (1991), Mankiw et al. (1992)

      • Causal relationship (Pritchett, Bils & Klenow)

    • Returns: old OLS literature, new IV literature

      • Psacharopoulos 1985; Duflo 2001

    • Adoption of new technologies

      • Foster and Rozenzweig (1996)

    • Means to improve health, reduce fertility

      • Schultz (1997), Strauss and Thomas (1995)

    • Education as an intrinsic good

      • Sen (1999)


Background motivation1
Background: Motivation

  • Development policy makers also enthusiastic about education

    • 2 of the 8 Millennium Development Goals

      • Universal primary education

      • Gender equity at all education levels


Background motivation2
Background: Motivation

  • Rich set of experiences to examine

    • Wide variation in input levels and education systems across developing countries

    • In recent years, dramatic policy changes and reforms in many developing countries

    • In last 10 years: many randomized evaluations of education policies (rare in developed countries)


Background quantity gross enrollment growth
Background: QuantityGross Enrollment Growth


Background quantity ii primary schooling
Background: Quantity (II) Primary Schooling


Background quantity iii average years of schooling age 15
Background: Quantity (III) Average Years of Schooling (Age 15+)

Source: Barro and Lee (2000)


Background quantity iv room for improvement
Background: Quantity (IV)Room for Improvement

  • 1 of 4 adults in developing countries illiterate

    • UNESCO (2002)

  • Today 113M primary age children not in school

    • UNDP (2003); UNESCO (2002)

  • 4 out of 10 primary-age children in sub-Saharan Africa do not go to school

    • In Niger, only 26% of primary-age children go to school

    • UNESCO (2003)



Background educational finance ii government expenditures and teachers
Background: Educational Finance (II) Government Expenditures and Teachers

  • Teacher salaries 74% of recurrent expenditures (Bruns et al. 2003)

  • Teacher salary/ per-capita GDP

  • Sub-Saharan Africa 6.7

  • Latin America 1.4

  • OECD 1.3




Background educational finance v
Background: Educational Finance (V) and Teachers

  • In many developing countries:

    • School systems are highly centralized

    • Teachers’ unions are strong

    • Teacher incentives are weak


Background educational finance vi centralized education heterogeneous needs
Background: Educational Finance (VI) and TeachersCentralized Education, Heterogeneous Needs

  • Heterogeneity within developing countries

    • Educational background

    • School quality

    • Language

  • Makes designing single curriculum for all students difficult


Background educational finance vii households help bear education costs

Sometimes households pay for private schools and Teachers

Sometimes parents pay costs at public schools

Parents must provide basic school inputs (e.g. textbooks, uniforms)

Some costs are collective responsibility of parents (e.g. school roof)

Some costs are passed on through official or unofficial school fees

Background: Educational Finance (VII) Households help bear education costs


Background educational finance viii private funding
Background: Educational Finance (VIII) and TeachersPrivate funding


Quality of education
Quality of Education and Teachers

  • Lack of basic equipment and supplies

    • Textbooks: only 20% of Kenya primary students had their own (recent changes)

    • Blackboards: lacking in 39% schools in rural northern Vietnam

    • Building: lacking in 8% of schools in India


Quality ii pisa study mathematics and reading achievement of 15 year olds
Quality (II) and TeachersPISA Study: Mathematics and Reading Achievement of 15-year-olds


Quality iii quality even lower in low income countries
Quality (III) and TeachersQuality even lower in low-income countries

  • Bangladesh: 58% of rural children 11 and older failed to identify 7 of 8 presented letters

    • Greany, Khandker and Alam (1999)

  • India: 36% of 6th graders unable to answer: “The dog is black with a white spot on his back and one white leg. The color of the dog is mostly: (a) black, (b) brown, or (c) grey”

    • Lockheed and Verspoor (1991)


Quality teacher absence
Quality: Teacher Absence and Teachers

  • Chaudhury, Hammer, Kremer, Muralidharan and Rogers

  • Survey methods

  • Absence rates across countries and sectors

  • Concentration of absence

  • Correlates of absence

  • Institutional forms

  • Conclusion


Teacher absence sampling
Teacher Absence: and TeachersSampling

  • Unannounced visits to public primary schools, health centers

  • Bangladesh, Ecuador, Indonesia, Peru and Uganda:

    •  ~100 schools, ~1000 teachers, 2000+ observations per country

  • India sample is much larger

    •  3,750 schools, 16,500 teachers, ~50,000 observations


Teacher absence survey methodology and absence definition
Teacher Absence: and TeachersSurvey Methodology and Absence Definition

  • Measurement:

    • Direct observation of each teacher, not administrative records

  • Definition of absence:

    • Teacher was considered absent if he/she could not be found anywhere in the school

    • Excluded from the sample: part-time teachers; teachers reported as “on another shift”

    • Exclude cases where the school is closed due to:

      • Official/Scheduled Holidays

      • Bad weather (rain, heat wave)

      • Construction/repairs

      • School Functions (Sports day, picnics, exams)


Absence multi country results on extent of absence
Absence: and TeachersMulti-country Results on Extent of Absence


Absence teacher activity at time of observation in india
Absence: and TeachersTeacher Activity at Time of Observation in India


Absence absence rates vs gdp per capita for sample countries and indian states
Absence: and TeachersAbsence rates vs. GDP per capita(for sample countries and Indian states)

Teachers

Health Workers

60

60

IDN

40

40

UGA

BNG

Absence rate (%)

Absence rate (%)

UGA

PER

IDN

20

20

BNG

ECU

PER

0

0

6.5

7

7.5

8

8.5

6.5

7

7.5

8

8.5

Per-capita income (GDP, 2002, PPP-adjusted)

Per-capita income (GDP, 2002, PPP-adjusted)

Countries

Fitted values

Indian states


Absence raw figures on distribution of absence across teachers
Absence: and TeachersRaw figures on distribution of absence across teachers


Absence estimated distribution of teacher absence
Absence: and TeachersEstimated distribution of teacher absence


Absence stated reasons for teacher absence in india
Absence: and TeachersStated Reasons for teacher absence in India


Absence multicountry correlates of teacher absence hlm estimates
Absence: and TeachersMulticountry Correlates of Teacher Absence – HLM Estimates


Absence indian teachers
Absence: and TeachersIndian teachers

  • More powerful teachers absent more

    • Older teachers (1% more for every 10 years)

    • More educated teachers (2-2.5% more with a college degree)

    • Head teachers (4-5% more)

    • Males (1.5-2% more)

  • Teacher pay (within scale, across states)


Absence multicountry correlates of teacher absence hlm estimates continued
Absence: and TeachersMulticountry Correlates of Teacher Absence – HLM Estimates (continued)


Absence multicountry correlates of teacher absence hlm estimates continued1
Absence: and TeachersMulticountry Correlates of Teacher Absence – HLM Estimates (continued)


Absence school conditions
Absence: and TeachersSchool Conditions

  • Better infrastructure is associated with significantly lower absence

    • Infrastructure Index from 0-5, which includes existence of covered classrooms, non-mud floors, teachers’ toilet, electricity connection, library

    • In India, each measure significant on its own, average impact of 1.4% for each 1 point increase in the index

    • In multicountry sample, correlation is even larger quantitatively and highly significant, at over 2% for each 1 point increase


Absence multicountry correlates of teacher absence hlm estimates continued2
Absence: and TeachersMulticountry Correlates of Teacher Absence – HLM Estimates (continued)


Absence private schooling and teacher absence in india
Absence: and TeachersPrivate Schooling and Teacher Absence in India

  • Surveyed private schools in villages visited

    • Teachers have much lower pay

    • More likely to be fired for absence

  • Indian private school absence about 2 percentage points lower in sum stats, baseline multivariate regression.

  • 8 percentage points lower with village fixed effects

  • Absence in public schools high in villages with private schools. Explanations?


Absence private schooling and teacher absence in india continued
Absence: and TeachersPrivate Schooling and Teacher Absence in India (continued)


Absence correlation with education outcomes in india
Absence: and TeachersCorrelation with education outcomes in India

  • Teacher absence is a significant (but weak) predictor of lower student attendance

    • A 10% increase in teacher absence is associated with a 1.8% decrease in student attendance

  • Teacher absence is also a significant predictor of lower student test scores

    • We conducted a simple 14-question test (2 Verbal, 12 Math) to a randomly selected sample of 10 4th grade children in the schools that we covered

    • A 20% decrease in teacher attendance is associated with a 2% decrease in test scores


Absence multi country correlates of health worker absence
Absence: and TeachersMulti-country correlates of health worker absence


Absence why is absence so high
Absence: and TeachersWhy is Absence So High?

  • High levels of absence are not efficient – no coordination

  • Technically possible to monitor attendance

    • Logbook/HM/inspection system

    • Duflo and Hanna (2005) cameras

  • Political economy

    • In some authoritarian, colonial regimes, absence reportedly been less of a problem

    • Not an electoral issue

    • Powerful often outside public system

    • Tradeoff between political and civil service systems


Absence conclusions
Absence: and TeachersConclusions

  • One in five teachers is absent, on average

  • Institutional failure

  • Evidence from randomized evaluations

    • Teacher incentives in Kenya (Glewwe, Ilias, Kremer)

    • Merit scholarships (Kremer, Miguel, Thornton)

    • Cameras in Indian NGO schools (Duflo and Hanna)

  • Range of interventions could be tested:

    • Improve facilities

    • Intensify and upgrade inspections

    • Empower school committees

    • Publicize absence statistics

    • Increase choice


Outline1
Outline and Teachers

  • Background: Education in Developing Countries

  • Methodology

  • Reducing the Cost of Education

  • Changing Education Behavior

  • Improving Provision of Education

    • Inputs

    • Incentives for Providers

  • Changing the Interaction of Consumers and Providers

    • Local Control and Participation

    • Contracting and Choice

  • Conclusion


113 million children not in school
113 million children not in school and Teachers

  • How expensive to address?

  • Is their labor needed by household?

  • Debate on user fees in health and education

    • Impact on provider

    • Impact on consumer

  • Strong ideological component to debate, need for evidence


Methods problem omitted variable bias
Methods and TeachersProblem: Omitted Variable Bias

  • yi = α+δdi+Xiβ+εi

    • We want to know δ, the effect of di on yi

    • Xi is a vector of observable factors, and εi contains the unobserved factors determining yi

  • If εi is correlated with di, OLS estimate of δ will be biased.

    • Its impossible to be certain because we can’t observe εi!


Methods ii solution instrumental variables
Methods (II) and TeachersSolution: Instrumental Variables

  • Instrumental variables (IV) can address the omitted variables problem

  • An instrument zi must be correlated with di and uncorrelated with εi


Methods iii solution iv with random assignment
Methods (III) and TeachersSolution: IV with Random Assignment

  • Randomly altering di for some individuals provides an instrument we can be confident in

  • zi = 1 for individuals who had their di randomly decreased and zi = 0 otherwise.

  • We know E(ziεi)=0 because randomization ensures it