Transcript Gratuidad - World Bank

The Effects of User Fee Reductions on
Enrollment: Evidence from a quasi-experiment
Felipe Barrera-Osorio (HDNED World Bank)
Leigh L. Linden (Columbia University)
Miguel Urquiola (Columbia University)
The objective of the study

What are the effects of user fee
reductions on enrollment?
 It
is possible to see differential responses
to the program from different groups of
populations
 Specifically, we can analyze the different
responses between females and males
Gratuidad program
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Each year the government issues a resolution that stipulates which
items schools may charge for and the maximum fee for each.
These expenses are equivalent to between 7 and 29 monthly dollars,
(between 6 and 25 percent of the minimum wage)
The Gratuidad program subsidizes some of these fees.
The program is targeted using the Sisben index that identify the most
vulnerable households in Colombia.

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
The system is implemented with a survey about households’ infrastructure,
demographics and human capital characteristics.
Based on these, each household receives an score between 0 and 100
Based on the score, it places households into six different levels, 1 being the
most poor, and 6 the richest.
Households with scores below a cutoff score of 11 are given a Level of 1;
those between 11 and a cutoff of 22 receive a Level 2; Level 3—22 and
43, and so on
The extent to which students benefit from these reductions is a
function of their Sisben level.
Gratuidad
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For basic education (grades 1-9) Sisben 1 children
enjoy a 100 percent reduction of complementary
service charges, while those in Sisben levels 2 and
above receive no reduction.
For high school (grades 10-11), Sisben 1 children
benefit from the elimination of both academic and
complementary services fees, while Sisben 2
households receive roughly a 50 percent reduction
Households in levels 3 and higher receive no benefit.
Gratuidad: items of charges
Category
1. Academic fees
Frequency
Annual or monthly
2. Complementary services
Annual, monthly,
or when event takes place
3. Periodic charges
Monthly
4. Other
When event takes place
Items
Registration
Board
Report cards
School handbook
ID cards
Pedagogical materials
Maintenance of infraestructure
Field trips
Transportation
Food services
Certifications
Replacement of ID cards
Replacement of school handbook
Graduation fees
Direct cost of education
Distribution of cost across
items
Items charged
Percentage of cost, average all levels
Sisben 1
Sisben 2
Sisben 3
Annual
Registration
Uniform
Text books
20%
17%
23%
22%
16%
20%
24%
15%
19%
Board
Transportation
Food services
Materials (paper, pencils, etc)
Others
2%
1%
0%
30%
6%
2%
2%
1%
28%
9%
3%
3%
1%
28%
7%
100%
100%
100%
Monthly
Total
Source: ECV, 2003
Identification and Estimation
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
Whether or not students benefit from the program is a discrete
function of their score.
Characteristics of the household (observable and
unobservable) are similar for students just above and
below the cutoff scores.
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Under this assumption, discrete differences in attendance
rates between treated and untreated students close to the
cutoff can be attributed to the fee reductions.
 Students with scores of 21.5 might provide an adequate
control group for students with scores of 22.5
In short, close to the cutoffs the RD design resembles a
(localized) randomized experiment
Data
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The information comes from two sources.
First, data collected (in 2004 and 2005) directly
through the Sisben survey.
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Demographic characteristics (gender, age, household
composition, pregnancy, and marital status).
Educational attainment (grades completed), type of
enrollment (public/private), labor force participation,
and income.
Second, we use administrative enrollment
records (October 2006) kept by the District
Education Department (SED)
Descriptive statistics
Full
Sample
(1)
Panel A: Household variables
Household income
Number of people in hhld.
Number of children under 18
Household head yrs. of sch.
Age of household head
Panel B: Individual variables
Age
Years of schooling
Male %
N
Basica
Sisben 1
(2)
High sch.
Sisben 1
(4)
High sch.
Sisben 2
(6)
485.8
(340.1)
5.3
(2.0)
2.6
(1.3)
6.6
(3.5)
43.5
(10.2)
440.8
(284.7)
5.4
(2.0)
2.7
(1.4)
6.2
(3.2)
42.8
(10.5)
452.3
(290.4)
5.4
(2.0)
2.6
(1.4)
5.8
(3.1)
46.2
(9.5)
524.4
(350.6)
5.1
(1.8)
2.4
(1.2)
6.8
(3.4)
46.2
(9.5)
12.0
(3.4)
3.4
(2.9)
0.51
(0.50)
570,648
11.0
(2.6)
2.3
(2.2)
0.51
(0.50)
388,238
17.0
(0.8)
6.9
(2.0)
0.51
(0.50)
118,481
17.0
(0.8)
7.3
(1.8)
0.50
(0.50)
97,450
Validation of the exercise
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First, properties of the assignment variable:
 We verified that the students’ Sisben score is a good
predictor of their level
 And we verified that households were not able to
influence their Sisben score

Second, we investigated that the characteristics of
individuals are smoothly related to the Sisben score at
the cutoff points (e.g., that the control and treatment
groups are similar)
 The treatment and control groups are similar. For
example:
2400
Example, Validation of similarity between
treatment and control groups: Income
0
400
800
1200
1600
2000
Basic Grades
High School Grades
1
6
11
16
SISBEN Score
2122
26
31
Results
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We present regressions’ coefficients between
enrollment and level of Sisben (controlling by
cube on the score)
We present results for several subpopulations
(e.g., gender, public / private students, etc)
We discuss results with a band of 1 point
Results
Effects of the program on the probability of Enrollment
% increase on Enrolment
Basic education
Sisben 1 - 2
Grades 10 - 11
Sisben 1 - 2
Grades 10 - 11
Sisben 2 - 3
All students
2.9**
(1.4)
0.7
(2.3)
6.1**
(3.0)
Males
4.3**
(1.9)
-0.1
(3.1)
4.7
(4.2)
Females
1.5
(1.9)
1.7
(3.3)
7.6*
(4.4)
4.8***
(1.7)
-0.1
(2.4)
7.7**
(3.7)
Old for grade
.7
Results
.2
.3
.4
.5
.6
Basic Grades
High School Grades
1
6
11
16
2122
Enrollment by SISBEN Score
26
31
Results
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Results suggest that the program had a significant impact.
 The program raises the probability of enrollment for basic-aged
Sisben 1 students by about 3 percent, and for high school-aged
Sisben 2 students by about 6 percent.
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These positive effects seem to be larger for at-risk students.
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The program also seems to display a substantial degree of
heterogeneous impacts for different populations.
 The program seems to increase the probability of attendance for
males in the first grades and for girls in the higher grades