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Empowering Parents to Improve Education
Paul Gertler*Harry Patrinos**
Marta Rubio-Codina***
*UC Berkeley, **The World Bank, ***UCL and IFS
20 June 2009
School Based Management (SBM)
Shift responsibility and decision-making powers to end users: parents, teachers, school committees (World Bank, 2007)
SBM reforms can take many different forms:who they devolve decision making powerlevel of decision making they devolve
SBM long popular in the US, UK, Australia and Canada
Developing countries (El Salvador, Nicaragua, Kenya, Nepal, Paraguay, Mexico, Indonesia, etc.)
AID agencies (e.g. WDR 2004)
DebateIncreased participation (voice) of local agents
may result in more effective policies:Allocations better meet local needs and preferences
Better performance through monitoring & accountability
SBM may not improve school quality if:parents lack the ability to make their voices heard,local elites can capture public resources,end users are less technically able to administer
schools. Galiani, Gertler and Schargrodshy (2008)
SBM Evidence in Developing Countries
Most evidence has technical problems
Two exceptions (Mexico and Kenya):
Shapiro and Skoufias (2005) & Murnane et al. (2006) – DID estimates of Mexican PEC (School Quality Program)
Duflo et al (2007) – RCT in Kenya that combines empowering local school committees with contract teacher hiring
Both SBM programs involve many endline users with control over lots of school functions
This Paper: Role of ParentsExamine policy to increase participation of parentsin school matters in rural Mexico: the AGE
1. Does this result in a better and more conducive learning environment for students?
create pressure to influence school management & form of decision making to favor students parent focus groups and school principal interviews
1. Does this improve learning outcomes?impacts on intermediate school quality indicators - grade failure, repetition and intra-year dropout
Outline of the TalkThe AGE Intervention
Mechanisms
Qualitative Evidence on Increased Parental Participation
Quantitative Evidence on Improved Learning Estimation and IdentificationResults
Threats to Identification
Conclusions
7
AGE: Apoyo a la Gestión Escolar
Monetary Grants to Parents Associations US $500-$700 a year depending on school sizeCannot spend money on teacher compensation
or hire new teachers; cannot design curriculumMostly spent on infrastructure and small civil
works
Parents trained in management of the funds transferredparticipatory skills (in school activities)information on measuring student achievements ways parents can help improve learning
AGE role outAGE started in 1996 in rural Mexico
Part of 1992 Compensatory Education Program:Series of interventions designed to strengthen
disadvantaged schools to reduce school inequalitiesSupplies, equipment, teacher training & incentivesExpanded enrollment over time starting in most
disadvantaged areas Broader reform to decentralize educational services
from the federal to the state level
Currently covering 46% of primary schoolsNot a small efficacy trial – at scale
PathwaysPTAs exist by law but are rather dysfunctionalAGE creates a need and a right for parents to:
access schools decide on the allocation of the funds and manage themdirectly participate in the infrastructure works
Parents spend more time in schoolmonitor school activities/performance (e.g. teacher absent,
quality of teaching, children’s attention levels, etc)
better able to voice opinions on school policy and the allocation of resources
AGE may improve communication channel between parents and teachers, and overall school climate
Empowers parents by improving parental “identity”
(Akerlof and Kranton 2000, 2005)
Increased Parental Participation?
Parents focus groups in 10 benef & non-benef schools:improve school maintenance and suppliesfacilitate dialogue amongst parents and with teachers and
directors & promote community participation
motivate teachers & parents to follow students more closelygreater teacher effort: longer hours to help low performing
students
Survey of 100 Principals report that parents:Are more interested in their children’s academic performance
(40%); and interact more with teachers (30%) main change
complain if teachers are absent (82%)accept their children’s poor performance (78%) and
take responsibility (53%)
Better learning environment improved learning outcomes?
Impact on Increased LearningQuasi-Experimental Approach:
Exploit phased rollout of AGE for identification
Treatment Schools: schools intervened between 1998 - 2001
Comparison Schools: schools not (yet) intervened by 2002
AGE Treatment 2,194 (41%)
AGE Comparison 3,158 (59%)
Total Number of Schools 5,352
• Sample of Non-Indigenous Rural Primary Schools
Identification StrategyCompare early to late adopter (benef)
schools
Dif-in-Dif estimation: school FE (s)changes in outcomes as a function of changes in
treatment statusRemove time invariant characteristics that may
vary between early and late beneficiary schools (wealthier, more motivated staff, etc.)
Learning outcomes:Grade failure, grade repetition intra-year drop out rates
Empirical SpecificationEvaluation Period: t = 1998 -2001; Baseline: t=1997
AGE Treatment:Dummy =1 if intervention yearHeterogeneous effects:
by number of periods school has received AGE by grade
School-grade-year observations
Ygst s g t lt ttt EverAGEst
+ 1AGEs ,t1 kXskt gstk2
K
Estimation and IdentificationGrade, Year and School Fixed Effects
control for time invariant unobserved heterogeneity
State * Year Dummies: st demographic trends, changes in govt preferences, etc.
Treatment-Specific Time Trends different evolutions b/w treatment & control schools over time
Time Varying School Characteristics: student-teacher ratio, average class crowding index, other
programs
Robust SE Clustered at the School allow heteroskedasticity and serial correlation within a school
and over time
Treatment Effects: Grade Failure
Model A Model B Model C Model D
AGE =1-0.005*
(0.002)
1 Year of AGE =1-0.005*
(0.002)
> 1 Year of AGE =1-0.006*
(0.003)
AGE * Grade 1 & 2 & 3 =1-0.010*
(0.002)
AGE * Grade 4 & 5 =10.002
(0.002)
AGE 1 Year*Grade 1&2&3=1-0.010*
(0.002)
AGE 1 Year*Grade 4&5=10.001
(0.002)
AGE > 1 Year*Grade 1&2&3=1
-0.011*
(0.003)
AGE 1 > Year*Grade 4&5=10.002
(0.003)
Number of Obs. 133,800 133,800 133,800 133,800
Number of Schools 5,352 5,352 5,352 5,352
Mean Dep. Var. 0.10 0.10 0.10 0.10LS regressions with school FE and robust SE clustered at the school level in parenthesis. Grade, year, state*year dummies, treatment specific trend and time varying school characteristics included; *significant at the 5 percent
Treatment Effects: Grade Repetition
Model A Model B Model C Model D
AGE =1-0.004*
(0.002)
1 Year of AGE =1-0.004*
(0.002)
> 1 Year of AGE =1-0.003
(0.003)
AGE * Grade 1 & 2 & 3 =1-0.008*
(0.002)
AGE * Grade 4 & 5 =10.003
(0.002)
AGE 1 Year*Grade 1&2&3=1-0.007*
(0.002)
AGE 1 Year*Grade 4&5=10.002
(0.002)
AGE > 1 Year*Grade 1&2&3=1
-0.007*
(0.003)
AGE 1 > Year*Grade 4&5=10.004
(0.003)
Number of Obs. 133,800 133,800 133,800 133,800
Number of Schools 5,352 5,352 5,352 5,352
Mean Dep. Var. 0.10 0.10 0.10 0.10LS regressions with school FE and robust SE clustered at the school level in parenthesis. Grade, year, state*year dummies, treatment specific trend and time varying school characteristics included; *significant at the 5 percent; **significant at the 1 percent
Intra-Year Drop Out
Model A Model B Model C Model D
AGE =10.002
(0.002)
1 Year of AGE =10.002
(0.002)
> 1 Year of AGE =10.002
(0.002)
AGE * Grade 1 & 2 & 3 =1-0.003
(0.002)
AGE * Grade 4 & 5 =10.003
(0.002)
AGE 1 Year*Grade 1&2&3=10.001
(0.002)
AGE 1 Year*Grade 4&5=10.003
(0.002)
AGE > 1 Year*Grade 1&2&3=1
0.001
(0.002)
AGE 1 > Year*Grade 4&5=10.003
(0.002)
Number of Obs. 133,800 133,800 133,800 133,800
Number of Schools 5,352 5,352 5,352 5,352
Mean Dep. Var. 0.04 0.04 0.04 0.04
LS regressions with school FE and robust SE clustered at the school level in parenthesis. Grade, year, state*year dummies, treatment specific trend and time varying school characteristics included
Threats to IdentificationEndogenous Program Placement Bias
AGE are non-randomly allocated - balanced pre-intervention trends &
FE: school, grade, state * year, Treatment specific trend
Other Education Interventions Coexisting in School or AreaTime * State dummies – local policy & economic changesexplicit controls: Oportunidades, other Compensatory Education
interventions, Carrera Magisterial scheme results are not affected
Student Learning vs. Parental Pressure< 3% reported parents demanded failed students be allowed to
pass.83% reported parents accepted result and 53% take
responsibility
Student – teacher sorting to/from AGE schools: no evidence
ConclusionsAGE associated with reduction in grade
repetition and grade failure rates in earlier grades (7 to 8 percent decrease)Measures associated with poorer test performance
& higher drop out in later years
Same effect sizes as OPORTUNIDADESVery cheap
Channels seem to be that AGE… …increases parental participation …improves communication b/w parents and
teachers …increases attention to student performance …increased teacher effort
Evaluation of a public program implemented at scale (external validity?)
Limitations and next stepsLimited school outcomesDespite a scaled program
Non-indigenous schoolsRural communitiesPrimary schoolsLATE
New evaluation just coming out of fieldSecondary schoolsCross-over design with demand-side
(OPORTUNIDADES)Randomized design
Thank you!
Extra Slides
Data SourcesData Sources
CONAFE admin data on AGE coverage (1996 - 2002)
School Census data, Censo Escolar 911 (1995 – 2003)
2000 Mexican Census & 1995 ConteoAdmin data on coexisting educational
interventions
Two Types of Analysis
Dif in Dif estimates of impact on school outcomes: failure, repetition and dropout
Qualitative analysisParent focus groups in 10 beneficiary and non-
beneficiary schoolsSchool director surveys in 115 beneficiary
schools
0.2
.4.6
De
nsity
4 6 8 10 12Targeting Index
CONAFE Treatment Schools CONAFE Control Schools
CONAFE Treatment and CONAFE Control SchoolsFigure 1: Distribution of the 2000 Targeting Index
Increased Parental Participation –most important change
The most important change induced by increased parental participation
30
40
30
0
5
10
15
20
25
30
35
40
45
Better interactin with teachers More interested in the school More interested in children's academicprogress
Parental Attitude Towards Teacher Absenteeism
Parents' attitudes about teacher absenteeism
4
14
82
0
10
20
30
40
50
60
70
80
90
Other Not interested in this issue Complain if teachers are absent
Do parents pressure teachers to pass their children?
Parental attitudes about prospects their child will repeat a year or receive very poor grades
23
7
10
25
53
0
10
20
30
40
50
60
Don't know Do not accept andpressure teacher
Other Accept it but blameteacher
Accept it Accept it and takeresponsibility
DID Identifying Assumption Pre-intervention trends are equal between treatment
and control schools: t’ = 1995 -1997
EverAGEs*Yeart’=1 if s is a potential treatment school (i.e. receives AGE for all or some of the treatment years)
t’ =0 is a test of equality of pre-intervention trendsbetween treatment and comparison schools
K
kstsktk
tts
tttt
ltgsgst
uXYREverAGEYR
Y
2''
''
''''
''
*
Balanced Pre-Intervention Trends
Failure Rate
Failure Rate
Repetition Rate
Repetition Rate
Intra Drop
Out Rate
Intra Drop
Out Rate
Ever AGE * Year 1996 =10.005*
(0.002)
0.002
(0.002)
0.001
(0.002)
Ever AGE * Year 1997 =1-0.001
(0.003)
-0.001
(0.003)
0.001
(0.002)
Ever AGE * Year 1996 *
Grade 1 & 2 & 3 =1
0.003
(0.003)
0.000
(0.003)
-0.001
(0.002)
Ever AGE * Year 1996 *
Grade 4 & 5 =1
0.008*
(0.003)
0.005
(0.003)
0.003
(0.002)
Ever AGE * Year 1997 *
Grade 1 & 2 & 3 =1
-0.004
(0.003)
-0.004
(0.003)
-0.001
(0.002)
Ever AGE * Year 1997 *
Grade 4 & 5 =1
0.005
(0.003)
0.003
(0.003)
0.004
(0.002)
Number of Observations 80,280 80,280 80,280 80,280 80,280 80,280
Number of Schools 5,352 5,352 5,352 5,352 5,352 5,352
LS regressions with school FE and robust SE clustered at the school level in parenthesis. Grade, year, state*year dummies and time varying school characteristics included; *significant at the 5 percent
Student/Teacher Sorting to Better Schools
Total Student
Enrolment
Total Student
Enrolment
Student Teacher
Ratio
Student Teacher
Ratio
Prop High Edu
Teachers
Prop High Edu
Teachers
AGE =10.045
(0.071)
0.151
(0.162)
0.000
(0.009)
AGE 1 Year =10.050
(0.073)
0.128
(0.163)
-0.000
(0.009)
AGE > 1 Year =10.176
(0.144)
-0.462
(0.263)
-0.013
(0.014)
Number of Observations 113,800 113,800 113,800 113,800 113,800 113,800
Mean Dep Var 23.65 23.65 26.05 26.05 0.53 0.53
Changes in the denominator: better/worse students/teachers attracted to treatment schools
No changes on total enrolment nor the prop of higher qualified teachers in AGE schools over evaluation period