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Development Issues in Africa Spring 2007

5 Education for All


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Contents

  • Investments in education: Concepts

  • Education in Africa: Overview

  • Evaluations of Randomized Experiments

  • Education of Orphans

  • Research Example: “Orphaned children and young adults in rural Uganda”

    by Yamano, Shimamura, and Sserunkumma (2004)


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Investments in Additional Education

Secondary graduates

Earnings

Additional benefits

Primary graduates

Opportunity costs

Age

Completion

Retirement

Direct costs

Beginning of 2nd School

Costs

Source: Todaro & Smith, Economic Development 8th, 2003


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Investments in Additional Education

The decision to make investments in additional education depends on the (expected) additional benefits and the sum of costs in additional education. The additional benefits is the sum of the discounted additional life-time earnings:

The costs of the additional education include the direct costs of

the additional education and the foregone income during the education

period (t=1,.., M).

When B is larger than C, people decide to invest in the

additional education.


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Private vs. Social Benefits and Costs of Education

Expected Private Returns

Private Costs

Years of schooling

Social returns

Social costs

Years of schooling

X*

Source: Todaro & Smith, Economic Development 8th, 2003


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School Supply

  • In the previous figure, the government decides the supply of schools at X*. But because the expected private return is higher than the private cost at this level, there will be more students than the schools can accept. Need to hold entrance exams.

  • Should the government to transfer some of the costs to private (cost-sharing)?


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School Enrollment: Overview

Gross Enrollment rate in primary education:

(Number of pupils in primary education)/ (Number of primary education age children). This number could be higher than 100 if many children repeat the same grade or non-primary education age children enter primary education.

Source: World Bank Development Indicator 2004




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Attainment Profile: Tables

Source: Pritchett (2004)


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Attainment Patterns

Proportion of 15 to 19 years olds who have completed each grade

The enrollment rate is high initially and remains so. The transition is low.

The enrollment rate is high initially; the drop-out is severe.

The enrollment rate is low initially; the drop-out rate is low.

1

Primary Secondary

Primary Secondary

Primary Secondary

Grade

Grade

Grade

Source: Pritchett (2004)


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Attainment Patterns by Wealth

Proportion of 15 to 19 years olds who have completed each grade

The enrollment rate is high for both and remains so. The transition is low for the poor.

The drop-our rate is higher for the poor than the non-poor.

The enrollment rate is low for the poor; the drop-out rate is low for both.

1

Non-Poor

Poor

Primary Secondary

Primary Secondary

Primary Secondary

Grade

Grade

Grade

Source: Pritchett (2004)


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Attainment Patterns in Uganda before and after UPE

Female:

Pre-UPE (age 20-24)

Post-UPE (age 15-19)

Male:

Pre-UPE (age 20-24)

Post-UPE (age 15-19)

Source: Nishimura, Yamano, and Sasaoka (2005)


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Attainment Patterns in Uganda before and after UPE

Female:

Pre-UPE (age 20-24)

Post-UPE (age 15-19)

Solid lines: Least poor

Dashed lines: Poor

Male:

Pre-UPE (age 20-24)

Post-UPE (age 15-19)

Solid lines: Least poor

Dashed lines: Poor

Source: Nishimura, Yamano, and Sasaoka (2005)


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Attainment Profile: Suggestions

  • Different attainment profile suggests different policy implications.

    • If enrollment rates are low, then policies should intend to improve enrollments through increased number of schools.

    • If drop-out rates are high, then efforts should be made to keep students in school.

  • School quality matters!


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Is Education System Efficient?

Production

Frontier

Education Outcome

Gains in efficiency given the same budget

Budget is spend to increase efficiency

Expansion of inefficient education system

If the education system is efficient, then the budget should be spent for expansion

Source: Pritchett (2004)


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Policy Actions

Source: Pritchett (2004)


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Program Evaluations: More complicated than you think


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Schooling as a Self-Selection Mechanism

High Ability People

Earnings

Low Ability People

Assume that they attend

secondary schools and

gain no skills

They do not

attend secondary

schools

Secondary graduates

Earnings

Primary graduates

It appears that the secondary

schooling increased the

Earnings, but this is actually

because of the self-selection.

Age


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Instead we need to control for people’s ability…

High Ability People

Earnings

Assume that some of them attend

secondary schools but some do not,

and that the secondary schooling has

some impacts on earnings.

Secondary graduates

Earnings

Primary graduates

The causal effect of secondary

schooling is much smaller than

the association (previous slide),

which is upward biased because of

the self-selection.

Age


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Another example: Endogenous Program Placement

High Ability People

Earnings

They do not

attend programs

Low Ability People

Assume that the government

provides training programs to them

Others

Earnings

Programs graduates

It appears that the program

graduates have lower earnings

than non-graduates and that

the programs have negative

Impacts. << A Reverse Causality

Age


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The reverse causality was observed because …

Earnings

The reverse causality was observed

because the programs were targeted

to low ability people. The government programs are strategically placed

(called endogenous program placement).


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In econometrics …

  • Econometrically these problems in evaluations are part of d “the omitted variables problem” or more generally “the endogeneity problem.”

  • The problem is created by the correlation between independent variables and the error term:

  • Where i indicates an observation (e.g., individual), y is an outcome variable, X is observed individual characteristics, Z represents the program participation, α is unobserved individual characteristics, such as ability, and e is the error term.

  • If Z is correlated with α, which is part of the error term, then the correlation between Z and αcauses biases. The direction of the bias on the coefficient of Z depends on the correlation between Z and αand between Y and α.


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Corr 2

In general, the direction of the bias is determined by the signs of correlations between the dependent variable (y) and the omitted variable (α) and between the independent variable (Z) and the omitted variable (α).

Corr 1 Corr 2 Bias

Positive Positive Over-estimate

Positive Negative Under-estimate

Negative Positive Under-estimate

Negative Negative Over-estimate

Corr 1


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How can we overcome the endogeneity problems?

  • Use instrumental variables that are correlated with the independent variables (endogenous variables).

  • Use the Difference-in-Differences model: compare changes in an outcome before and after the participation in a program between programs participants and non-participants.

  • Use the Fixed Effects Model: use panel data to eliminate fixed characteristics, such as ability.

  • Use Randomized Experiments: place programs randomly instead of strategically.


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The Difference in Differences Estimation

Earnings

ΔY C: Control Group

Non-Participants

ΔY T: Treatment Group

Participants

The difference-in-differences estimator is

δ= ΔY T - ΔYC

This measures the net impact of the program participation.



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Evaluations through Experiments

  • The Primary School De-worming Project (PSDP) in Busia District, Kenya

    • 75 primary schools (over 30,000 pupils) divided into three

    • 25 Group A schools received free de-worming treatment in both 1998 and 1999

    • 25 Group B schools received free de-worming treatment in 1999

    • 25 Group C schools received free de-worming treatment in 2001



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Evaluations through Experiments

  • PROGRESA in Mexico:

    • Out of 495 localities, 314 localities were randomly selected for PROGRESA

    • In the selected 314 localities, about two-third of households were found “poor” by the previous census and eligible for educational grants.

    • Grants were provided to eligible children who were in grades 3 through 9 grades in elementary school and the next 3 years of junior school.

      T. Paul Schultz (2004). “School subsidies for the poor: evaluating the Mexican Progress poverty program,” Journal of Development Economics.


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Hypothesis 1:D1 = (S1t – S2t) >0 Post program period

Hypothesis 2:D1 = (S1t – S2t) =0 Pre-program period

Hypothesis 3: DD1 = D1(Post) – D1(Pre) > 0

Source: Shultz (2004) Journal of Development Economics




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