Cycling to School: Increasing Secondary School Enrollment ...Cycling to School: Increasing Secondary School Enrollment for Girls in Bihar Karthik Muralidharan & Nishith Prakash University

Cycling to School: Increasing SecondarySchool Enrollment for Girls in Bihar

Karthik Muralidharan & Nishith Prakash

University of California-San Diego & University of Connecticut

June 25, 2012 / University College London/CReAM

Motivation

• Increasing school attainment of girls is one of theMillennium Development Goals

• Improving female education directly contributes to“Inclusive Growth”:

• Growth - by increasing human capital of labor force• Inclusive - by allowing people to participate in the growth

process

• Despite high economic returns to education in developingcountries, there are:

• Low school completion rates• High drop-out rates• Students absenteeism

Education in Bihar

• Girls/Boys enrollment ratio in 2007-08:• 93% in Class 1• 80% in Class 5• 69% in Class 8• 62% in Class 9

• Large gender gap in Bihar in school attendance (growswith age)

Policy Intervention

• In April 2006, the Government of Bihar headed providedbicycles to all girl students studying in Class 9 & 10

• This scheme was called “Cycle Program”• Approximately Rs. 2000 (45 USD) per girl student was

allocated to purchase cycles (currently Rs. 2500)• No direct provision of bicycles - cash was made available

to eligible students through the schools, and receipts forpurchase of cycles were collected

• This was effectively a CCT program and was India’s firstscaled up CCT/CKT program for girl’s secondary education

Policy in Action

Policy in Action

Research Questions & Contributions

• Aim is to evaluate the impact of the MBCY on:• Girl’s Enrollment• Girl’s Educational Attainment• Girls’s Learning Outcomes (for e.g. English and Math test

performance)

• Rigorously evaluates the effectiveness of India’s firstscaled up CCT/CKT program for girls’s secondaryeducation

• Provides an answer if reduction in transportation cost &time reduces gender gap in enrollment and attainment

• Relevant not just for India, but other developing countries

Preview of Main Results

• The program had a positive impact on girl’s enrollment• Positive impact on number of girls appearing for grade 10

exam• Most of the treatment effect appears to be coming from

villages where the nearest secondary school is more than3 km away - suggesting that reducing the distance barrierwas a key mechanism for the program’s impact

• No effect on learning outcomes

Outline of Today’s Talk

• Related Literature• Data & Outcome Measures• Identification and Empirical Framework• Main Findings• Robustness Checks• Discussion

Brief Related Literature

• Reduction in distance to school improves enrollment,reduces dropout, and improves test scores (Lavy, 1996;Bommier & Lambart, 2000; Brown & Park, 2002; Handa,2002)

• Costs of girls traveling long distance may be greater thanfor boys because families may believe girls face uniquerisks to safety (Llyod et al., 2005; Sutlon, 1998)

• More recently is a paper by Burde & Linden (2010)• Uses random placement of school in the treatment village

to look at the effect on children’s academic performance• Increases enrollment, test scores amongst all children and

improves gender disparities• Effect of distance significant on children’s academic

performance• Distance reduces the impact on enrollment and test scores• Effect more pronounced for girls

Data Sources• District Level Household Survey (DLHS) Wave-3 (Year

2007/08)• DLHS represents 1000 to 1500 households per district• Provides additional information on village level

infrastructures (e.g. access and distance to primary,middle, and secondary school etc.)

• ASER 2009• Largest household survey undertaken in India by people

outside the government• Annually measures the enrollment, reading and arithmetic

levels of children in the age group of 6-14 years• Has question on bicycle ownership in a household• Has village level characteristics, most importantly, question

on access to secondary school in the village• State Board Examination Data (2003–2010)

• 10th standard board exam records from the State Examauthority in Bihar and Jharkhand

Outcome Measures

• Dependent Variables• Dummy variable for being in high school

• Takes value 1 if completed or currently enrolled in grade 9• Log of number of students appeared for Grade 10 exam

(aggregate at school and block level)• Log of number of students who graduated Grade 10 exam

(aggregate at school and block level)• Dummy variable if child can read words in English• Dummy variable if child can do two digit subtraction

Empirical Strategy

• Difference in Differences Approach:• Single Difference = [(Enroll)Girls

Post − (Enroll)GirlsPre ]

• D-D Bihar = A = [(Enroll)GirlsPost − (Enroll)Girls

Pre ] − [(Enroll)BoysPost − (Enroll)Boys

Pre ]

• This will control for changes in income, tastes and government policies that was targeted towardsschool going children

• Triple Difference Approach:• D-D Jharkhand = B = [(Enroll)Girls

Post − (Enroll)GirlsPre ] − [(Enroll)Boys

Post − (Enroll)BoysPre ]

• D-D-D = [A - B]

• This will control for remaining bias from differential time trend• Jharkhand is particularly compelling as it was part of Bihar till 2000• Border districts share similar socio-economic conditions

Map of border districts ofBihar/Jharkhand

Estimating Equation

• Difference in Differences

yih = αd + β0Treat ∗ Female dummy +

β1Female dummy + β2Treat + γX + eih (1)

whereyih = Completed or currently enrolled in grade 9, educational attainment, andlearning outcomesαd = District Fixed EffectsTreat = Children aged 14 and 15 in BiharX = Control variables (social groups, household level characteristics, andvillage level characteristics)

Estimating Equation

• Difference in Difference in Differences

yihs = αd + β0Treat ∗ Female dummy ∗ Bihar dummy + β1Treat ∗ Female dummy +

β2Treat ∗ Bihar dummy + β3Female dummy ∗ Bihar dummy +

β4Treat + β5Female dummy + β6Bihar dummy + γX + eihs (2)

whereyihs = Completed or currently enrolled in grade 9, educational attainment, andlearning outcomesαd = District Fixed EffectsTreat = Children aged 14 and 15 in BiharX = Control variables (social groups, household level characteristics, andvillage level characteristics)

Children in School

4050

6070

8090

Prob

abilit

y

8 10 12 14 16 18Age

Male Female

By GenderChildren Still in School

Age Profile by Distance & Gender

.4.5

.6.7

.8Pr

obab

ility

0 5 10Distance Group

Male Femalebandwidth = .8

By Distance to Secondary School14-Year Olds In School

Age Profile by Distance & Gender

.3.4

.5.6

.7Pr

obab

ility

0 5 10Distance Group

Male Femalebandwidth = .8

By Distance to Secondary School15-Year Olds In School

Impact on Girls DD (wrt TreatmentStatus, Boys in Bihar)

Treat = Age 14 and 15Control = Age 16 and 17 (1) (2) (3) (4) (5)

VARIABLES No Controls Demographic Controls

HH Level Controls

Vill Level Controls

District Fixed Effects

Treat*Female dummy 0.123*** 0.114*** 0.0906*** 0.0901*** 0.0886***(0.0149) (0.0144) (0.0134) (0.0134) (0.0132)

Treat -0.192*** -0.184*** -0.165*** -0.165*** -0.163***(0.0108) (0.0106) (0.00987) (0.00987) (0.00973)

Female dummy -0.186*** -0.178*** -0.164*** -0.163*** -0.163***(0.0117) (0.0112) (0.0103) (0.0103) (0.0102)

Constant 0.475*** 0.823*** 0.465*** 0.482*** 0.402***(0.00980) (0.0831) (0.0652) (0.0695) (0.0678)

Observations 18,453 18,453 18,353 18,331 18,331R-squared 0.038 0.106 0.230 0.232 0.245Robust standard errors in parentheses*** p<0.01, ** p<0.05, * p<0.1

Standard error clustered at village levelDLHS 3 - 2007/08

Dependent Variable = Dummy for grade 9 and above

Impact on Girls DDD (wrt TreatmentStatus, Boys, and Jharkhand)

Treat = Age 14 and 15 (1) (2) (3) (4) (5)Control = Age 16 and 17


HH Level Controls

Vill Level Controls


Treat*Female dummy*Bihar dummy 0.103*** 0.0912*** 0.0517** 0.0514** 0.0486**(0.0302) (0.0294) (0.0252) (0.0252) (0.0242)

Treat*Female dummy 0.0195 0.0235 0.0385* 0.0386* 0.0397*(0.0263) (0.0256) (0.0214) (0.0214) (0.0203)

Treat*Bihar dummy -0.0437** -0.0418** -0.0284* -0.0275* -0.0264*(0.0179) (0.0177) (0.0160) (0.0160) (0.0158)

Female dummy*Bihar dummy -0.0942*** -0.0905*** -0.0654*** -0.0641*** -0.0613***(0.0233) (0.0226) (0.0200) (0.0201) (0.0195)

Treat -0.148*** -0.143*** -0.137*** -0.137*** -0.137***(0.0143) (0.0142) (0.0127) (0.0127) (0.0125)

Female dummy -0.0915*** -0.0880*** -0.0982*** -0.0989*** -0.101***(0.0202) (0.0196) (0.0172) (0.0173) (0.0166)

Bihar dummy 0.0115 -0.0437*** -0.0162 -0.0287* -0.110**(0.0163) (0.0165) (0.0145) (0.0146) (0.0529)

Constant 0.464*** 0.771*** 0.468*** 0.428*** 0.447***(0.0130) (0.0240) (0.0238) (0.0391) (0.0565)


Standard error clustered at village level


Impact on Girls in DDDD (wrt Time,Boys, Jharkhand, Distance to Sec

School)



HH Level Controls

Vill Level Controls


Treat*Female*Bihar*Long distance dummy 0.0940 0.0875 0.0869* 0.0853* 0.0740(0.0578) (0.0560) (0.0500) (0.0499) (0.0486)

Treat*Female*Long distance dummy -0.0788 -0.0803* -0.0731* -0.0718* -0.0638(0.0496) (0.0480) (0.0425) (0.0424) (0.0410)

Treat*Female*Bihar 0.0426 0.0338 -0.00423 -0.00346 0.000665(0.0410) (0.0394) (0.0374) (0.0373) (0.0369)

Female*Bihar*Long distance dummy -0.0826* -0.0746* -0.0695* -0.0692* -0.0598(0.0450) (0.0433) (0.0393) (0.0391) (0.0389)

Treat*Bihar*Long distance dummy -0.0285 -0.0254 -0.00512 -0.00448 -0.00484(0.0363) (0.0356) (0.0327) (0.0326) (0.0324)

Treat*Female dummy 0.0720** 0.0770** 0.0872*** 0.0865*** 0.0824***(0.0349) (0.0334) (0.0321) (0.0321) (0.0318)

Treat*Long distance dummy 0.0367 0.0389 0.0283 0.0272 0.0257(0.0291) (0.0287) (0.0262) (0.0262) (0.0260)

Treat*Bihar dummy -0.0233 -0.0225 -0.0207 -0.0204 -0.0195(0.0274) (0.0267) (0.0251) (0.0251) (0.0249)

Female*Long distance dummy 0.0654* 0.0633* 0.0572* 0.0564* 0.0468(0.0384) (0.0370) (0.0337) (0.0335) (0.0333)

Female*Bihar dummy -0.0419 -0.0426 -0.0210 -0.0200 -0.0235(0.0322) (0.0307) (0.0291) (0.0291) (0.0297)

Bihar dummy*Long distance dummy 0.0136 0.0216 0.00249 0.00270 0.00891(0.0339) (0.0315) (0.0277) (0.0277) (0.0266)

Treat (Age 14 & 15) -0.172*** -0.168*** -0.155*** -0.155*** -0.154***(0.0229) (0.0223) (0.0210) (0.0209) (0.0208)

Female dummy -0.135*** -0.130*** -0.136*** -0.136*** -0.132***(0.0276) (0.0262) (0.0252) (0.0251) (0.0260)

Bihar dummy -0.00856 -0.0658*** -0.0245 -0.0352 -0.118**(0.0264) (0.0243) (0.0213) (0.0215) (0.0555)

Long distance dummy (Sec School > 3 kms) -0.0753*** -0.0733*** -0.0439* -0.0391* -0.0345(0.0277) (0.0257) (0.0228) (0.0227) (0.0217)

Constant 0.513*** 0.816*** 0.494*** 0.451*** 0.471***(0.0228) (0.0279) (0.0270) (0.0409) (0.0574)




Girls Performance in Grade 10 ExamDD (wrt Time, Boys in Bihar)

Learning Outcomes: Performance in Grade 10 Exam

VARIABLES School Level Block Level School Level Block Level

Female dummy * Post dummy 0.118*** 0.0983*** -0.000188 -0.0861(0.0184) (0.0287) (0.0410) (0.0579)

Post dummy 0.233*** 0.238*** -0.124*** -0.115***(0.0231) (0.0276) (0.0347) (0.0354)

Female dummy -0.836*** -0.712*** -0.813*** -0.686***(0.0339) (0.0415) (0.0347) (0.0432)

Constant 4.710*** 5.987*** 4.622*** 5.904***(0.0392) (0.112) (0.0439) (0.112)

Observations 10702 1936 10387 1918R-squared 0.165 0.114 0.147 0.111Robust standard errors in parentheses*** p<0.01, ** p<0.05, * p<0.1

Standard error clustered at district level

Log (Total Appeared) Log (Total Passed)

Bihar and Jharkhand Examination Board Data

Robustness for DD (Border DistrictsOnly, Border Districts & District Fixed

Effects

Treat = Age 14 and 15 (1) (2) (3)

Control = Age 16 and 17

VARIABLES Base District Borders

District Borders &

District Fixed

Effects

Treat*Female dummy 0.0886*** 0.106*** 0.107***

(0.0132) (0.0272) (0.0268)

Treat -0.163*** -0.209*** -0.209***

(0.00973) (0.0217) (0.0212)

Female dummy -0.163*** -0.175*** -0.176***

(0.0102) (0.0205) (0.0201)

Constant 0.402*** 0.378*** 0.408***

(0.0678) (0.0933) (0.0975)

Observations 18,331 3,901 3,901

R-squared 0.245 0.229 0.238

Robust standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1



Difference in Differences

Robustness for DDD (Border DistrictsOnly, Border Districts & District Fixed

Effects

Treat = Age 14 and 15 (1) (2) (3)Control = Age 16 and 17

VARIABLES Base District BordersDistrict Borders &


Treat*Female dummy*Bihar dummy 0.0486** 0.0538 0.0604*(0.0242) (0.0357) (0.0356)

Treat*Female dummy 0.0397* 0.0504** 0.0464**(0.0203) (0.0233) (0.0234)

Treat*Bihar dummy -0.0264* -0.0689*** -0.0722***(0.0158) (0.0266) (0.0264)

Female dummy*Bihar dummy -0.0613*** -0.0552* -0.0616**(0.0195) (0.0296) (0.0299)

Treat -0.137*** -0.139*** -0.136***(0.0125) (0.0158) (0.0158)

Female dummy -0.101*** -0.118*** -0.114***(0.0166) (0.0215) (0.0222)

Bihar dummy -0.110** -0.00615 0.0394(0.0529) (0.0231) (0.0349)

Other controls YES YES YES

Constant 0.447*** 0.268*** 0.333***(0.0565) (0.0591) (0.0550)

Observations 30,112 9,886 9,886R-squared 0.228 0.225 0.236Robust standard errors in parentheses*** p<0.01, ** p<0.05, * p<0.1



Difference in Difference in Differences

Robustness for DDDD (Border DistrictsOnly, Border Districts & District Fixed

Effects

Treat = Age 14 and 15 (1) (2) (3)

Control = Age 16 and 17

VARIABLES Base District BordersDistrict Borders &


Treat*Female*Bihar*Long distance dummy 0.0691** 0.0656 0.0577

(0.0334) (0.0491) (0.0487)

Treat*Female*Long distance dummy -0.0607* -0.0454 -0.0423

(0.0335) (0.0433) (0.0430)

Treat*Female*Bihar 0.00356 0.0129 0.0241

(0.0305) (0.0461) (0.0455)

Female*Bihar*Long distance dummy -0.0570* -0.0867* -0.0763

(0.0329) (0.0494) (0.0500)

Treat*Bihar*Long distance dummy 0.0804*** 0.0797** 0.0736**

(0.0282) (0.0349) (0.0347)

Treat*Female dummy 0.0227 0.0174 0.0158

(0.0155) (0.0259) (0.0256)

Treat*Long distance dummy -0.0224 -0.0675** -0.0707***

(0.0159) (0.0268) (0.0266)

Treat*Bihar dummy 0.0450 0.0512 0.0438

(0.0302) (0.0404) (0.0415)

Female*Long distance dummy -0.0252 -0.00211 -0.0148

(0.0271) (0.0388) (0.0397)

Female*Bihar dummy 0.00609 0.0399 0.0343

(0.0188) (0.0317) (0.0303)

Bihar dummy*Long distance dummy -0.152*** -0.150*** -0.147***

(0.0159) (0.0226) (0.0224)

Treat (Age 14 & 15) -0.131*** -0.150*** -0.142***

(0.0245) (0.0295) (0.0314)

Female dummy -0.116** -0.0313 0.0210

(0.0542) (0.0292) (0.0435)

Bihar dummy -0.0328* -0.0496* -0.0400

(0.0180) (0.0267) (0.0252)

Long distance dummy (Sec School > 3 kms) -0.0328* -0.0496* -0.0400

(0.0180) (0.0267) (0.0252)

Other controls YES YES YES

Constant 0.470*** 0.302*** 0.356***

(0.0572) (0.0584) (0.0584)

R-squared 0.228 0.226 0.237

Robust standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1



Difference in Difference in Difference in Differences

Discussion from DLHS Data

• The point estimates suggest that the program did have apositive impact on children aged 14–15 in grade 9 andabove

• Point estimates from Difference in Differences suggests a4-5 percentage point increases. On a base enrollment ofsay 40%, this is a 10% increase

• Point estimates from Triple Differences reduces theDifference in Differences estimates by half

• The point estimates suggest that the program had apositive impact on students who appeared and no impacton passing in grade 10 exam

• Point estimates from Difference in Differences suggest a12% increase in girls who appeared for grade 10 exam

• Estimates suggest a bridging of approximately 20% of thegender gap in students who appeared for grade 10 exam

Main Results from ASER Data -Enrollment

Treat = Age 14 and 15Control = Age 16 and 17 (1) (2) (3) (4) (5)


HH Level Controls

Vill Level Controls


Treat*Female dummy 0.0336 0.0350 0.0384 0.0589* 0.0623**(0.0284) (0.0269) (0.0277) (0.0305) (0.0301)

Treat -0.121*** -0.118*** -0.116*** -0.130*** -0.132***(0.0205) (0.0192) (0.0190) (0.0217) (0.0217)

Female dummy -0.0651*** -0.0766*** -0.0763*** -0.0937*** -0.0935***(0.0243) (0.0224) (0.0234) (0.0254) (0.0254)

Constant 0.661*** 0.527*** 0.473*** 0.431*** 0.385***(0.0175) (0.0196) (0.0210) (0.0398) (0.0947)


Standard error clustered at village levelASER 2009

Dependent Variable = Dummy for grade 9 and aboveImpact on Girls – DD (wrt Treatment Status, Boys in Bihar)

Main Results from ASER Data -Enrollment



HH Level Controls

Vill Level Controls


Treat*Female dummy*Bihar dummy 0.0501 0.0466 0.0531 0.0946* 0.0958*(0.0462) (0.0444) (0.0451) (0.0513) (0.0515)

Treat*Female dummy -0.0165 -0.0120 -0.0158 -0.0376 -0.0347(0.0365) (0.0353) (0.0356) (0.0411) (0.0413)

Treat*Bihar dummy -0.0793** -0.0751** -0.0773** -0.0764** -0.0728**(0.0328) (0.0320) (0.0321) (0.0364) (0.0359)

Female dummy*Bihar dummy -0.0856** -0.0795** -0.0828** -0.137*** -0.126***(0.0410) (0.0388) (0.0395) (0.0445) (0.0448)

Treat -0.0418 -0.0424* -0.0388 -0.0528* -0.0605**(0.0257) (0.0256) (0.0261) (0.0294) (0.0287)

Female dummy 0.0205 0.00334 0.00768 0.0457 0.0341(0.0330) (0.0317) (0.0320) (0.0367) (0.0368)

Bihar dummy 0.0894*** 0.0513* 0.0571* 0.0618* 0.0382(0.0298) (0.0289) (0.0297) (0.0342) (0.0340)

Constant 0.571*** 0.473*** 0.412*** 0.354*** 0.304***(0.0241) (0.0246) (0.0263) (0.0372) (0.0662)



Dependent Variable = Dummy for grade 9 and aboveImpact on Girls – DDD (wrt Treatment Status, Boys, and Jharkhand)

Main Results from ASER Data -English



HH Level Controls

Vill Level Controls


Treat*Female dummy*Bihar dummy 0.0136 0.0135 0.0180 0.0144 0.0141(0.0208) (0.0207) (0.0222) (0.0266) (0.0270)

Treat*Female dummy 0.00488 0.00495 -0.00254 0.00776 0.00893(0.0181) (0.0181) (0.0195) (0.0240) (0.0244)

Treat*Bihar dummy 0.00813 0.00775 0.00984 0.0149 0.0168(0.0123) (0.0122) (0.0128) (0.0151) (0.0152)

Female dummy*Bihar dummy -0.0163 -0.0165 -0.0202 -0.0183 -0.0195(0.0181) (0.0180) (0.0192) (0.0231) (0.0230)

Treat 0.00279 0.00266 0.00180 -0.00384 -0.00593(0.0106) (0.0105) (0.0112) (0.0135) (0.0137)

Female dummy 0.00379 0.00572 0.0108 0.00478 0.00515(0.0164) (0.0163) (0.0175) (0.0215) (0.0214)

Bihar dummy -0.0169 -0.0115 -0.0119 -0.0192 -0.0147(0.0114) (0.0113) (0.0119) (0.0146) (0.0150)

Constant 0.0528*** 0.0719*** 0.0780*** 0.0879*** 0.0460***(0.0100) (0.0106) (0.0114) (0.0149) (0.0166)



Impact on Girls – DDD (wrt Treatment Status, Boys, and Jharkhand)Dependent Variable = Dummy if Child can read words in English

Discussion from ASER 2009 Data

• The point estimates suggest that the program did have apositive impact on children aged 14–15 in grade 9 andabove

• Both Difference in Differences and Triple Differencesestimates similar in magnitude and economic significance

• No effect on learning outcomes (e.g. child can read wordsin English)

Next Steps

• We plan to further use data from ASER (PRATHAM)sources to examine the impact of the Cycle Program

• Has data from 2006 to 2009. Two pre and two post years• Decompose the effect by access to secondary school in the

village• Has question on bike ownership• Has questions on learning outcomes for children aged

5–16. Some examples includes:• Can read simple sentence• Knows meaning of English sentences• Can do division, and• Can do two-digit substraction, etc.

Documents

Cycling to School: Increasing Secondary School Enrollment ...Cycling to School: Increasing Secondary School Enrollment for Girls in Bihar Karthik Muralidharan & Nishith Prakash University