Decidiendo para un Futuro MejorSergio De Marco

Deputy Country Director, IPA Peru, Bolivia and Paraguay

sdemarco@poverty-action.org

The effect of information on school drop-out, time-use and child labor*

Researchers:Francisco Gallego, Universidad Catolica de Chile & J-PALOswaldo Molina, Universidad del Pacifico, LimaChristopher Neilson, Princeton University & J-PAL

* Funding for this project was provided by the United States Department of Labor. This material does not necessarily reflect the views or policies of the United States Department of

Labor, nor does the mention of trade names, commercial products, or organizations imply endorsement by the United States Government.

Motivation (1)

• Around 1.6 million children and adolescents work in the country (National child labor survey, ETI 2015).

• Every year 178,000 students drop out (SIAGIE 2015).

• In 2015, Peruvian Ministry of Education needed to design a cost effective and easily implemented public policy to get children to stay in school and out of work.

Motivation (3)

Investment in human capital usually shows positive returns.

In recent decades, many policies in developing countries have been seeking to increase investment in human capital for the young.

• Supply side: improve access (locals, vouchers, transport facilities)

• Supply side: improve quality (teacher quality, investment in infrastructure)

• Demand side: CCT (Progresa, Juntos, Bolsa Familia)

• Demand side: Information intervention (returns to education, financial support)

Children (and parents) tend to underestimate returns on education

Motivation (4)

• Students underestimate the economic returns to all levels of education.

• They underestimate by 20% the returns to university education and more than 30% technical education.

Perceptions of the returns to education

Motivation (5)

• Evidence that providing information about returns to education effectively informs students on the value of education

• It may thus be a cost-effective way of getting students to stay in school and out of work, and improving educational achievement

• (Nguyen 2008, Jensen 2010, Berry et al. 2017)

• Students’ and families’ education decisions include:

• Whether to continue studying or drop out

• How much effort to put into schooling

• Which courses of study to pursue

• How to finance higher education

• (Hastings & Zimmerman, 2015; Dinkelman & Martínez, 2014)

In 2015, MINEDU, IPA and J-PAL designed an evaluation to test the idea of an informational intervention in Peru and tested its large-scale implementation

Intervention

InterventionInformational campaign provided to students and parents about returns of education

Policy pilot treatment: Information to students at school level

• Telenovelas: informative and persuasive videos shown in class

• (1) Returns on education by level ($)

• (2) Social returns (no-$)

• (3) Scholarship opportunities

• (4) Returns on education by area

Intensive treatment: information provided individually to parents at household level and students at school

• Infographics added to tablet’s in-depth survey

• Additional informative treatments: major-choice app and school-choice app.

Intervention – videos (PP treatment)

Studying for a better life

A scholarship for dreaming

Choosing my major, a major decision

Learning the value of education

We showed videos (policy pilot treatment) during class

… and to a subsample of students and parents we apply a more intensive treatment using tablets.

Intervention – videos (PP treatment)

App: in-depth survey + intensive informational treatment Infographics for students and parents

Intervention – Infographics (Intensive app-based treatment)

Intervention – Infographics (Intensive app-based treatment)

Project Size

Figure 1

School dropout in Peru, 2014-15, according to SIAGIE-MINEDU

The project size

Figure 2

Schools in Peru and School Dropout 2014-15

The project size

2,860 schools considered in this study.

• Urban: 24 regional capitals

• Rural: Southern highland in Peru: Arequipa and Cusco

• 30% of national school population

Project

Figure 3. Sample

Urban:

• Students from 5th grade to 11th grade of school,

• Parents

Rural:

• Students from 5th to 6th grade,

• Parents

Targeting population

The project size

Preliminary results

Preliminary results

1. Perceptions

2. Dropout rates

3. Child labor

4. Test scores

Preliminary results

1. Perceptions — Students’ and parents’ perceptions of the financial benefits to education increased.

2. Drop out

3. Child labor

4. Test score

Effect on Urban Student Perceptions to the Returns to EducationPerceptions on the Returns to Basic Education increase

IDT – Perceptions on the Returns to Basic Education – Urban

988

1565.233

2503.853

1200

1792

2715

0

500

1000

1500

2000

2500

3000

High School Tech Uni

So

les

(Mo

nth

ly)

Control Treatment

+21.5%***

+14.5%***

+8.5%***

*** p

Effect on Rural Student Perceptions on the Returns to EducationPerceptions on the Returns to Basic Education increase

IDT – Perceptions on the Returns to Basic Education - Rural

1405

2244

3106

1578

2365

3148

0

500

1000

1500

2000

2500

3000

3500

High School Tech Uni

So

les

(Mo

nth

ly)

Control Treatment

+12.4%***

+5.4%***

+1.4%*

*** p

Parents’ perception increase in urban area

Effects on parents’ perceptions of the likelihood of achieving higher education

IDT – Parents’ perceptions of higher education likelihood – Overall

*** p

Preliminary results

1. Perceptions

2. Dropout rates — Information had a significant negative effect on dropout rates in both rural and urban areas

3. Child labor

4. Test scores

Urban and Rural - Reduction of dropout rate

Effect on Dropout Rates

PP – Two Year Dropout Rate - Overall

9.56

7.76

0

2

4

6

8

10

12

14

16

Dro

po

ut

Pe

rce

nta

ge

Urban

Control Treatment

-18.84%***

14.28

7.11

0

2

4

6

8

10

12

14

16

Overall

Dro

po

ut

Pe

rce

nta

ge

Rural

Control Treatment

-50.02%***

*** p

Urban – Reduction of dropout rate

Heterogeneous Effect on Dropout Rates

PP – Two Year Dropout Rate - Urban

9.568.89

9.1439.14

7.82

7.767.51

8.40 6.97

7.12

0

2

4

6

8

10

12

Female Male Grade 1 Grade 2 Grade 3

Dro

po

ut

Pe

rce

nta

ge

Control Treatment

-15.56%***-21.30%***

-19.56%*** -9.05%***

-5.88%***

*** p

Rural – Reduction of dropout rate

Heterogeneous Effect on Dropout Rates

14.6313.95

10.84

7.776.45

4.62

9.38

0

2

4

6

8

10

12

14

16

Female Male With Juntos Without Juntos

Pe

rce

nt

Re

du

cti

on

Control Treatment

PP – Two Year Dropout Rate - Rural

-46.92%***

-53.73%***

-57.38%***

-46.42%***

*** p

Preliminary results

1. Perceptions

2. Drop out

3. Child labor — decreased in some groups, unaffected in others

4. Test scores

Urban and Rural – Negative effect but not significant

Effect on Child Labor

PP - Child labor- Overall

23 21

0

20

40

60

80

100

Overall

Pe

rce

nta

ge

Control Treatment

-0.92%

Urban

88 87.5

0

20

40

60

80

100

Overall

Pe

rce

nta

ge

Control Treatment

-1%

Rural

*** p

Urban – Child labor reduction for girls

Heterogeneous Effect on Child Labor

PP – Child Labor- Urban

2024.9 23.8 20.1 25.217.5

24.8 22.319.4

21.4

0

10

20

30

40

50

60

70

80

90

100

Female Male Grade 1 Grade 2 Grade 3

Pe

rce

nta

ge

Control Treatment

-15%***-0.93%

-0.93%-1.03%

-0.85%

*** p

Urban – Household chores reduction for girls

Effect on household chores

PP – Household chores - Urban

10.74 9.83 10.54 10.61 9.89 11.9510.45 9.18 10.59 10.28 9.94 11.24

0

20

40

60

80

100

Overall Female Male Grade 1 Grade 2 Grade 3

Pe

rce

nta

ge

Control Treatment

+3% -7%* +0% -3% +0% -6%

*** p

Rural – Child labor reduction for 6th graders

Heterogeneous Effect on Child Labor

IDT – Child Labor - Rural

89 8792 8988

82.5

93.582.5

0

20

40

60

80

100

Female Male 5th grade 6th grade

Pe

rce

nta

ge

Control Treatment

-0.4% -5% +1.6% -7.3%**

*** p

Preliminary results

1. Perceptions

2. Drop out

3. Child labor

4. Test scores — standardized test scores increased

Effect on Score in ECEUrban - The effects of treatment on standardized tests at the national level (ECE)

are positive but small.

583 587 578584.87 589.94 578.9

0

200

400

600

800

1000

Overall Female Male

Sco

re r

an

ge

po

ints

Control Treatment

+0.05%*** +0.015%**

PP - Score in ECE - Verbal Test - Urban

+0.03%***

*** p

Effect on Score in ECEUrban - The effects of treatment on standardized tests at the national level (ECE)

are positive but small.

570 566 574573.32 571.09 576.21

0

200

400

600

800

1000

Overall Female Male

Sco

re r

an

ge

po

ints

Control Treatment

+0.090%*** +0.039%**

PP - Score in ECE - Mathematics Test - Urban

+0.058%***

*** p

Policy Implications

• The Policy Pilot (PP) was designed for implementation on a large scale and at a low cost.

• The marginal cost of the PP campaign was less than US$0.05 per student.

• At scale and with correct implementation the intervention could reduce the number of students that drop out of school by 70,000 students in two years at a relatively low cost.

Use of evidence

Policy Implications

Policy Implications

Reduction of students drop out and child labor indicator

Informative campaign and collaboration with DoL to further study effect on child labor

Jointly project between researchers, IPA, DoL and MINEDU started in 2015

Scaling-up the intervention

• There is potential to expand to other countries in Latin America & Central America:

• Current effort to conduct an RCT of an informational campaign in illegal market areas in Peru and Colombia: video campaign + a virtual assistant (an SMS or Whatsapp Messenger Bot) that allows dynamic interaction with students and parents.

• Addressing the issue of opportunity cost in vulnerable families. Providing information on the return to education (i.e. the prediction that future income will be lower than that of peers who do remain in school) and disclosing the negative costs of participating in illegal activity (i.e. higher probability of being incarcerated).

• Study the interaction with CCT’s program in both legal and illegal markets.

Use of evidence

Policy Implications and new efforts

Thank you

poverty-action.org

Concept Operational DefinitionChildren Individuals under the age of 18A Working

Child

1. A child, between the ages of 5 to 17, who worked for 1 or more hours in the week

before the survey in any kind of economic activity as defined by ISIC

Economic

Activity

Activities defined by ISIC, International Standard Industrial Classification of All Economic

Activities, Rev.4, and excluding categories 94, Activities of membership organizations, and

98, producing activities of private households for own use. We consider a child to be

involved in an economic activity regardless of being paid.

Child Labor 1. Children 11 years of age and younger:

1.1 Work for 1 or more hours in the week before the survey in any kind of economic

activity (as defined above, excluding regular household chores),

1.2 Work in any kind of activity considered as a hazardous activity (as defined below)

1.3 Any activity which is considered as a worst form of child labor (as defined by ILO

Convention No. 182)

2. Children 12-17 years of age:

2.1 Work for 1 or more hours in the week before the survey in any kind of economic

activity that is considered as a hazardous activity (as defined below), or

2.3 Any activity which is considered as a worst form of child labor (as defined by ILO

Convention No. 182)

Child labor definition

Child labor definitionHazardous

Child Labor

1. Children 5-9 years of age and younger:

1.1 Child works more than 24 weekly hours on any economic activity, or

1.2 Child works in economic activities listed as hazardous, either by nature or conditions,

by Peru’s Ministry of Women and Vulnerable Populations

1.3 Child engages in household chores for more than 18 weekly hours.

2. Children 10-13 years of age:

2.1 Child works for more than 24 weekly hours on any economic activity, or

2.2 Child works more than 4 hours at any given day during the week, or

2.3 Child works in economic activities listed as hazardous, either by nature or conditions,

by Peru’s Ministry of Women and Vulnerable Populations

2.4 Child engages in household chores for more than 18 weekly hours.

3. Children 14 years of age and older:

3.1 Child works for more than 36 weekly hours on any economic activity, or 3.2 Child works more than 6 hours at any given day during the week, or3.3 Child works in economic activities listed as hazardous, either by nature or conditions, by Peru’s Ministry of Women and Vulnerable Populations 3.4 Child engages in household chores for more than 22 weekly hours.

Child labor definition

Worst forms

of Child Labor

Activities defined by the ILO Convention No. 182, Article 3, that compromise 4 distinct

types of worst forms of child labor.

a) All forms of slavery or practices similar to slavery, such as the sale and trafficking of children,

debt bondage and serfdom and forced or compulsory labor, including forced or compulsory

recruitment of children for use in armed conflict,

b) The use, procuring or offering of a child for prostitution, the production of pornography or for

pornographic performances,

c) The use, procuring or offering of a child for illicit activities, in particular for the production and

trafficking of drugs as defined in the relevant international treaties,

d) Work which, by its nature or circumstances in which it is carried out, is likely to harm the

health, safety or morals of children.

e) Dedication to any activity which constitutes commercial sexual exploitation or use of children

for illicit activities.

DFM Treatment and controls school dispersion in rural sample for follow-up (Cuzco and Arequipa)

DFM Treatment and controls school dispersion in urban sample (Metropolitan Lima)