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8/2/2019 Gender Gaps in Education - India

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Gender gaps in education - IndiaAnjini Kochar

Stanford Center for InternationalDevelopment

Stanford University

The views expressed in this paper are the views of the author and do not necessarily reflect the views or policies of the AsianDevelopment Bank (ADB), or its Board of Governors, or the governments they represent. ADB does not guarantee the accuracy ofthe data included in this paper and accepts no responsibility for any consequence of their use. The countries listed in this paper donot imply any view on ADB's part as to sovereignty or independent status or necessarily conform to ADB's terminology.


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Overview of talk

Data on gender disparities and trends

National, rural/urban, regional, caste

Gender disparities in achievement/quality

Evidence from within schools, Karnataka

Data on household expenditure on boys, girls

Rural/urban, regional

Theories

Gender differences in returns and costs of schooling

Family / cultural factors (son preference)Changing nature of the family (Karnataka)

Conclusion


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2007: Gender gaps in completed level of schooling, by age group and rural/urban

sector (NSS 64th round, major states)

Age group/

completed educ

Rural Urban

Male Female Male Female

11-13

primary 0.70 (0.46) 0.66 (0.47) 0.80 (0.40) 0.79 (0.41)

Currently - HPS 0.55 (0.50) 0.51 (0.50) 0.59 (0.49) 0.58 (0.49)

14-16

Primary 0.83 (0.37) 0.78 (0.41) 0.89 (0.31) 0.88 (0.32)Upper primary 0.51 (0.50) 0.46 (0.50) 0.65 (0.48) 0.66 (0.47)

Currently enroll -

secondary

0.35 (0.48) 0.30 (0.46) 0.42 (0.49) 0.40 (0.49)

17-19

Primary 0.83 (0.37) 0.72 (0.45) 0.90 (0.30) 0.89 (0.31)

Upper primary 0.63 (0.48) 0.52 (0.50) 0.75 (0.43) 0.76 (0.43)

Sec 0.38 (0.49) 0.31 (0.46) 0.54 (0.50) 0.59 (0.49)

Higher sec 0.12 (0.31) 0.12 (0.30) 0.22 (0.41) 0.28 (0.45)

Currently in Hsec 0.16 (0.37) 0.10 (0.31) 0.22 (0.41) 0.20 (0.40)

Rural: Comparison across cohorts suggests narrowing gaps over timeUrban: insignificant gender gap


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Trends in gender gaps in completed higher secondary (12 years) by region,

Rural India, (NSS), Ages 19-25

Same patterns: Narrowing of gender gaps in all regions; approximately equal gender gaps (2007-08) in

all regions

Greatest reductions in Central and West

With growth, growing disparities in education (male, female) across regions

0

.05

.1

.15

.2

.25

mean

ofchsec

North central East West South

1995 2007 1995 2007 1995 2007 1995 2007 1995 2007

Male Female


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Urban India (NSS) - Trends in gender gaps in completed higher secondary (12

years) by region, Ages 14-18

0

.1

.2

.3

.4

mean

ofchsec

North central East West South

1995 2007 1995 2007 1995 2007 1995 2007 1995 2007

Male Female

Gaps narrowed in all regions, except East

High growth regions are North, West, South


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Most recent data is from ASER 2011

Proportion out-of school children (India, rural)

Narrowing gender gaps, within each cohort


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Even in rural Bihar and Punjab

Rural Bihar Rural Punjab


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Data suggest that gaps appear at primary level, and then

sustained or narrowed at higher level

Ages 20-25, Rural India, 2007

Proportion of ages 20-25 (2007) completed primary: Males: 0.77; Females 0.57

- 20 percentage point difference

1995 survey: Gender gap in primary completions, ages 11-13 (1995): Males

0.63 (0.48); Females 0.47 (0.50) 16 percentage point difference

Gender gap in secondary completions, ages 20-25 (2007): Males 0.33 (0.17);

Females 0.22 (0.10) 11 percentage point difference

Gender gap in higher secondary completions, ages 20-25 (2007): Males 0.18(0.38); females 0.11 (0.31) 7 percentage point difference

Contrary to what one might want: everyone gets at least a primary education,

and gender gaps show up at higher levels here, gender gaps are lowest at low

levels, and then narrow over time


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Pattern is true of all regions

Rural India, ages 20-25 (2007-08, NSS)

Region Completed primary Completed higher secondary

Males Females Males Females

North 0.81

(0.40)

0.61

(0.49)

0.22

(0.41)

0.16

(0.36)

Central 0.71(0.45)

0.45(0.50)

0.15(0.36)

0.08(0.28)

East 0.72

(0.45)

0.59

(0.49)

0.12

(0.32)

0.08

(0.27)

West 0.87

(0.33)

0.72

(0.45)

0.23

(0.42)

0.15

(0.36)

South 0.83

(0.38)

0.67

(0.47)

0.22

(0.42)

0.16

(0.36)

Gender gaps much larger at primary level (those who did not complete primary), then at higher secondary level, suggesting

that gender differences in completed years of schooling is primarily because of gender differences in those completingprimary


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Urban India, ages 20-25 (2007-08, NSS)

Region Completed primary Completed higher secondary


North 0.86

(0.35)

0.80

(0.40)

0.39

(0.49)

0.31

(0.59)

Central 0.82(0.38)

0.72(0.45)

0.33(0.47)

0.34(0.47)

East 0.86

(0.34)

0.78

(0.42)

0.36

(0.48)

0.31

(0.46)

West 0.92

(0.28)

0.88

(0.33)

0.39

(0.49)

0.39

(0.49)

South 0.92

(0.27)

0.87

(0.34)

0.39

(0.48)

0.39

(0.49)

Gender gaps much larger at primary level (those who did not complete primary), then at higher secondary level, suggesting

that gender differences in completed years of schooling is primarily because of gender differences in those completingprimary


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By caste - In North, South and West (high growth regions), gender gaps are

LARGER amongst upper castes, rural India, ages 14-18, 2007-08 (NSS)

Region Upper castes SC/ST


Prop completed

upper primary

North 0.67

(0.47)

0.55

(0.50)

0.44

(0.50)

0.36

(0.48)

Central 0.50

(0.50)

0.43

(0.49)

0.39

(0.49)

0.32

(0.46)

East 0.49

(0.50)

0.52

(0.50)

0.40

(0.49)

0.31

(0.46)

West 0.72

(0.45)

0.59

(0.49)

0.58

(0.49)

0.52

(0.50)

South 0.78

(0.41)

0.71

(0.45)

0.64

(0.48)

0.63

(0.48)


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Alternative way of looking at gender gaps: Of currently enrolled,

percentage who are women (NSS, 2007-08)

Doesnt standardize for age: gender gaps may reflect differences in

acceptable ages at enrollment

Differences across levels reflect cohort effects

Currently

enrolled in

Rural Urban

Primary 45% 46%

Middle 46% 46%

Secondary 42% 46%

Higher

secondary

38% 46%


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Even here, trend is declining gender gaps

MHRD: Number of girls per 100 boys, class IX-XII

Region/State 2001-02 2005-06 Region/state 2001-02 2005-06

South West

A.P. 71 80 Gujarat 68 67

Karnataka 82 89 Maharashtra 76 92

Kerala 107 100

Tamil Nadu 84 97 Central

North Bihar 44 47

Punjab 83 84 MP 52 58

Haryana 68 76 UP 36 58

H.P. 86 88 Chattisgarh 57 65

Rajasthan 38 46 Jharkhand 54 62


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While data suggests narrowing gaps in levels of education, what

is the evidence regarding quality?

Learning gaps less research and data

Current (on-going) study of rural Karnataka schools (720

schools, 11 districts)

Very little evidence of a gender gap in learning in the South,

and, instead, a reverse gap favoring girls.

Government schools only, so results will be biased if

brighter boys go to private schools

Complete picture will require data which surveys all

schools in an area, and conducts same test in all schools

(eg. LEAPS, Pakistan)


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Test score Full

sample

Quartile of District EDI rank

1 (top) 2 3 4

Language (max=100)

Male 33.91

(0.33)

41.17

(0.83)

40.19

(0.60)

33.14

(0.81)

26.83

(0.50)

Female 37.01

(0.34)

45.61

(0.80)

43.57

(0.62)

39.60

(0.80)

26.78

(0.52)

F test for equality

Prob > F

42.39*

(0.00)

14.77*

(0.00)

15.27*

(0.00)

32.75*

(0.00)

0.00

(0.95)

Mathematics

(max=100)

Male 20.49

(0.22)

25.68

(0.64)

21.86

(0.40)

18.45

(0.49)

18.33

(0.33)

Female 21.13

(0.22)

27.79

(0.62)

22.60

(0.42)

18.25

(0.46)

18.44

(0.35)

F test for equality

Prob > F

4.01

(0.05)

5.43

(0.02)

1.64

(0.02)

0.09

(0.77)

0.04

(0.85)

Table 8: Test scores for grade 3 students, by gender and District EDI rank

Note: Language and math test scores based on grade specific curriculum. Sample size=11,447. Standard errors in parentheses.*Statistically significant different at 1% level

Test Scores, Rural Karnataka, Grade 3 2009-10 (Karnataka schooling project data)


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Learning gaps at higher levels

Difficult to interpret, because of greater selectivity of women

into higher education

Eg., MP, results from HSC-12 examinations:

Proportion Division 1: men - 0.24; women - 0.32

Proportion failing: men 0.18; women 0.12

But, proportion of female students (of those appearing for theexam): 0.39


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Possibility of gender gap in quality of schooling comes from data on schooling

expenditures 1995 and 2007 particularly in urban areas

Expenditure on schooling (all items), on children ages 12-15 currently enrolled

in higher primary school or higher (NSS Education Surveys).

RURAL URBAN

0

1,0

00

2,0

00

3,0

00

4,0

00

5,0

00

meanofedexp

1995 2007

1 2 1 20

1,0

00

2,0

00

3,0

00

4,0

00

5,0

00

meanofedexp

1995 2007

1 2 1 2


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Reflects enrollment in private schools, of far greater significance in urban

areas (NSS education surveys, 1995 and 2007)

Rural Urban

0

.1

.2

.3

.4

mean

ofpvt

1995 2007

1 2 1 2

0

.1

.2

.3

.4

mean

ofpvt

1995 2007

1 2 1 2


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Urban India: regional variation in education expenditure, 1995 & 2007

(ages 12-15, currently enrolled upper primary or higher)

particularly high in North and Central regions (traditional son preference)

0

,

,

,

,

1995 2007

1 2 3 4 5 1 2 3 4 5

1 2

0

,

,

,

1995 2007

1 2 3 4 5 1 2 3 4 5

1 2

Total Educational Expenditure School tuition costs


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Rural India: regional variation in education expenditure, 1995 & 2007

(ages 12-15, currently enrolled upper primary or higher)

Again high in North, but also in South

0

,

,

,

1995 2007

1 2 3 4 5 1 2 3 4 5

1 2

0

200

400

600

800

1995 2007

1 2 3 4 5 1 2 3 4 5

1 2

Total Educational exp. School tuition fees


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Conclusions from data

Reduction in gender gaps in completed schooling

Within cohort analysis suggests that difference in years ofschooling may reflect larger drop out rates by women at lowerlevels of schooling - challenge is at the elementary level

While gender disparities in years of schooling appear to benarrowing, emerging gaps in expenditure on schooling,particularly in regions that have traditionally shown sonpreference

Economic literature suggests that quality gap may influenceincome (and other outcomes) more than quantity gap(Hanushek et al 2007, Heckman and co-authors)


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Theory

Predicting narrowing gaps:

due to higher returns to schooling for women; increases inmaternal education; higher income elasticity of demand forfemale education (Maitra et al, 2012)

Munshi and Rosenzweig (2004) rates of return from pvtschooling are higher for women, but only amongst lower castes

reverse gender gap for lower castes, but no predictions forhigher castes

Increasing gaps:

Transition from agricultural to non-agricultural economy may

initially cause increasing gender gaps which will then benarrowed - inverted U hypothesis (Goldin) diff. in rates ofreturn in transition

Greater credit constraints as incomes rise, causing greatergender inequality in household expenditure.


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In India, general belief that effect of rates of return mediated by

gender differences in returns to parents from sons/daughters

Traditionally believed that this would exacerbate effect of anygender differences in return

May also generate increasing gender gaps

Das Gupta and Bhat (1997): with rising incomes andconsequent decline in fertility, a reduction in the parityeffect (discrimination against girls at higher parities) butincrease in the intensification effect (greaterdiscrimination at lower parities), with latter effectdominating.

Underlying reason: family systems with strongdisincentives against investments in girls


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Problem with that explanation: insufficient attention to changing

nature of the family

(survey data, Karnataka, 2009-10)

father Mother

Grandparents financially dependent

on children

61.55% 61.40%

Parents expect to be financially

dependent on children

49.38% 50.65%

In families which support their

parents, proportion of parents who

expect to depend on their children

58% 57%

Expect to reside by themselves or

with spouse

26% 29%

Expect to reside with children 54% 53%


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Family and gender gaps

Data (Karnataka) also do not suggest greater investment in older son, with who

parents are most likely to live with

Expected years of schooling do not vary across sons (even by caste)

Despite the fact that parents generally claim that older son is brightest

(particularly amongst lower castes)

Alternative explanation: Dependence on son reducedexpenditure on sons,

because of fears regarding commitment to provide support. Widening gaps as

parental dependence on children increases (work in progress).

May particularly take the form of increased expenditures on private

schooling, since returns to private schooling are really in the non-agricultural,

formal sector


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Conclusions and Policy Implications:

Particularly need research on whether gender gap is switching fromquantity of schooling to quality, and reasons for this

If gender gaps reflect family preferences, then programs which relyon community organizations may not be successful (NPEGEL,

operates through community and womens organizations)

If increasing gaps reflect credit constraints, then have to re-structure programs such as Incentive to Girls for SecondaryEducation (2008-09) to address these constraints rather than Rs.

3000 in fixed deposit, withdrawable at age 18,need to providefunds continuously through secondary stage.