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j PHREE Background Paper SeriesDocument No. PIREE/89/17

Barriers to Female Education in South Asia

byShahrukh R. Khan

(Consultant)

Education and Employment DivisionPopulation and Human Resources Department

May 1989

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FOREWORD

This paper is one of a series of papers that review thefactors influencing women's education in developing countries. Thepapers were commissioned for a project in the Population and HumanResources Department on the determinants and consequences of improvingwomen's education. The review papers examine the importance of family,school and community factors and of education policy in increasing theparticipation of girls and women in school and improving theirachievement levels. They draw on the findings of a large number ofpublished and unpublished studies of individual researchers, on Bankpolicy analysis and research, and on published reports of otherorganizations and of governments.

It is widely recognized that education is a critical factor inimproving opportunities for women and in achieving development goals.Yet many girls and women in Third World countries face serious obstacleswith respect to obtaining education. These barriers must be understoodin order to fashion effective policies and programs to raise theireducation levels. It is hoped the review papers will contribute toimproving that understanding.

Elizabeth M. KingEducation and Employment Division

Population and Human Resources Department

Acknowledgements

Thanks are due to Elizabeth King for very constructive comments andgenerous provision of research materials.

/

IADIERS TO FINALE EDUCANION IN SOUTH ASIA

ABSTRACT

This literature search was conducted to identify the causes of the

large gender differentials in educational enrollments that exist in most South

Asian countries. These differentials are quantified using secondary data, then

a model of household behavior is outlined to guide the literature review. The

evidence corroborates the predictions of the model that the negative household

utility from female education would result in large gender differentials.

Cultural norms are the cae e of this negative utility. In fact, these norms

suggest that female education has costs in addition to its high direct and

indirect, or opportunity, costs.

For example, education can make women less desirable on the marriage

market because many South Asians believe education will make women less

willing to shoulder the tremendous work load expected of wives. Moreover,

education can increase a woman's dowry cost because educated women are

expected to marry more educated males, who command higher dowries. Finally,

the potential monetary benefits from education are viewed as accruing to the

families into which women marry rather than the families that have borne the

educational cost.

Evidence shows these cultural norms are less binding on the more

educated and prosperous families. In fact, education of females is even viewed

as necessary for successful marriage, both to rear children properly and

increasingly to meet the need for double incomes among middle-class families.

Job market discrimination may limit the demand for female education at higher

levels, however. Cultural norms are also important at both the school and

higher level in the kinds of educational facilities parents indicate would

increase the demand for female education.

CONTNSM

page

EXCUTIVE SUMMARY .*..................... i

INTRODUCTION ...... .. . .. . .. . .. . .. . .. . . 1

PATTERNS IN FEMALE EDUCATION IN SOUTH ASIA:SECONDARY DATA ANALYSIS ..... . . . . . . . . . . . . . . . . 2

DETERMINANTS OF FEMALE EDUCATION . . . . . . . . . . . . . . . . 13

LITERATURE SEARCH: CHILD SCHOOLING . . . . . . . . . . . . . . . 20Family and community factors . . . . . . . . . . . . . . . . 20School Factors ...... .. . .. . .. . . .. . .. . . 32

LITERATURE SEARCH: HIGHER EDUCATION . . . . . . . . . . . . . . . 40Barriers to Higher Education .... . . . . . . . . . . . . 40Labor Market Discrimination .... . . . . . . . . . . . . 43

CONCLUSIONS ...... .. .. . .. .. . .. .. . .. .. . . 47

REFERENCES ....... . .. . .. .. . .. .. . .. .. . . 50

GUIDE TO LITERATURE REVIEW . . . . . . . . . . . . . . . . . . . 56

Tables

Table 1: Fema.e Share of Total School Enrollment, by Country, 1975to 1987 (in percent)

Table 2: School Enrollments by Country, Age, Sex and Region(percent of population group)

Table 3: Literacy by Country, Sex, and Region, 1971 and 1981(percent of population group)

Table 4: Literacy Rates by Country, Age, Sex and Region (percent ofpopulation group)

Table 5: Representation of Women in Higher Education by Country,Field of Specialization, and Educational Level (percent oftotal enrollment)

Table 6: Persons Economically Active by Country, Age, Sex andRegion (percent of population group)

Table 7: Minimum Legal Age at Marriage and Age Actually Married byCountry, Sex and Region

Charts

Chart la: Urban Female Literacy RatesChart lb: Rural Female Literacy Rates

EXECUTIVE SUWhRY

School enrollment rates differ widely by gender in South Asia

(except in Sri Lanka), and a wide variety of studies is available that have

some bearing on the causes of this gender gap and on the most effective

policies for rectifying it.

A behavioral model of household decision making about educating

females sets the stage for the literature search of secondary sources dealing

with the sehooling of women. The paper summarizes and comments on the major

specific findings from this literature and suggests approaches for increasing

school enrollment rates for females.

The analysis assumes that family and community factors and school-or

institution-reLated factors determine the demand for female education. Low

family income appears to be the most important barrier of female education.

Poor families find both the direct cost of education and the indirect, or

opportunity, cost burdensome or prohibitive. Opportunity cost appears to be

much greater for school-age females than for males of that age.

Poor families may also perceive additional costs of female

education. First, these families view domestic work as the primary role of

females after marriage; education may act as a spoiler by changing female

aspirations. Thus, families expressed great discontent about the suitability

of the curriculum for girls. Second, educated women may be viewed as less

suitable marriage partners; in educating their daughters, families risk the

social onus of having unmarried daughters of marriageable age. Third, the

marginal returns from female labor may be low because so many females are

a'eilable for family work and because non domestic work opportunities for

women are so limited. Finally, educated females may be require' -z marry

males of a higher education level, which narrows their choice of marriage

partners while raising the dowry cost.

Thus, when education is viewed as a consumption good, poor families

may derive negative utility from the education of females. Viewed as an

investment good, incremental education (for example secondary over primary)

presumably can lead to a higher net stream of earnings over the educated

person's lifetime. Here again, however, cultural practices may reduce the

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incentive to educate females. If females are viewed primarily as an economic

asset for the families into which they marry (rather than their own), then

given limited resources, families will make their human capital or education

investments in males, who are perceived as adding to their own family's income

in later life. Evidence from the survey indicates that such reasoning is

prevalent.

For more prosperous middle- and upper class families, the

consumption motivation for educating females appears to be stronger than it is

for poor families. Considerable evidence indicates that the demand for female

education is positively associated with a family's income and education.

Female education seems to be viewed as a plus on the marriage market insofar

as it improves the quality of a woman's child rearing abilities. Moreover,

middle-income families evidently are expecting women to contribute to the

family income to help cope with the rising cost of living. Thts, for these

families, higher education for females is socially acceptable. Nevertheless,

the expectation of labor market discrimination may hinder higher education for

females. Substantial evidence points to discrimination in jobs, wz.ages, and

positions for women.

Among institutional factors thaw affect families' willingness to

educate girls at both school and higher educational levels, cultural factors

again predominate. Parents indicate that they would respond positively to

separate educational facilities for girls. Special facilities, such as high

boundary walls around schools, latrines, and female teachers, may also

increase demand for female schooling. At the higher level, the shortage of

separate female hostel facilities appeared to deter families from further

educating their daughters.

This literature search is not intended to guide policy directly.

Within a specified analytical framework, however, it does identify some of the

important issues related to female educational attainment. It also suggests

data bases that need to be developed for rigorous policy-oriented examination

of t.ese issues.

The objective of this literature review is to identify specific

changes in education and social policies and in school reforms intended to

increase female education in South Asia. The countries examined are

Bangladesh, India, Nepal, Pakistan, and Sri Lanka. To avoid repetition, this

paper is organized by issue rather than by country.-1 Also, because the

determinants of schooling are different from those at higher levels, these

issues are treated separately. First, the socioeconomic profile of those who

obtain higher education in South Asia may be different from that for lower

levels because access to higher education is more limited. Second, entry

restrictions at the post-secondary level imply a supply constraint. Third,

higher education is more directly related to the labor market than is

schooling and is also more important given the high private and social costs

involved. v

The studies that were reviewed vary greatly. They include general

studies based on secondary materials, village studies, analyses of purposively

selected samples, and studies based on well-designed probability samples.

Thus, some information is more representative of the whole country than is

other information. Appendix A provides more details about the kind of datathese studies used.V

In general, even for data generated from sample surveys, the

analysis in almost all cases does not go beyond one-way cross tabulations.

Like the nonrepresentative studies, these studies essentially generate

hypotheses instead of specific information useful for resource-allocation

decisions.

1 Throughout, "school" refers to primar) and secondary education, while'higher education" refers to post secondary education.

v An implicit assumption here is that the major issues are sufficientlysimilar across countries. Where important differences exist, they will alsobe alluded to.

A/ Material on Sri Lanka is scarce. Three separate data based searchesproduced few current published or unpublished works for Sri lanka. This isunfortunate because Sri Lanka is the clear front runner in educationalprogress in South Asia. A review of studies attempting to explain why this isthe case would be useful, although the explanation is implicit in therecounting of the deterrents to female education in other South Asiancountries in different cultural settings.

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PATTERNS IN FEMALE EDUCATIOM IN SOUTH ASIA:

SECONDARY DATA ANALYSIS

Two sources of secondary statistics have been used to demonstrate

the nature of gender differentials at the school and higher levels. The first

source is the latest UNESCO data (published in 1988). Although these data

only indicate gender differentials, they do not report enrollments by region

(urban\rural) nor by age. Therefore, this source has been complemented by

census and survey data from the countries themselves, which was compiled on

behalf of the U. S. Department of Commerce, Bureau of the Census, and

distributed as data tapes by the Inter-university Consortium for Political and

Social Research (ICPSR).d/ In addition to disaggregations by region and age,

these tapes contain such information as "age at first marriage" and "labor

force participation," both of which can influence female education. The

drawback in using these data for South Asia is that they are not current. They

do, however, provide useful benchmarks and indicate important trends.

Table 1 shows female shares in total enrollments at the primary and

secondary levels by country and over time. At the primary level, Bangladesh

has made mild progress. Female enrollment increased from 34 percent in 1975

to 44 percent in 1984 but subsequently declined to 40 percent. Nepal showed

the most progress by doubling its enrollment rate from a poor 15 percent in

1975 to a more respectable, but still low, 29 percent in 1985. The remaining

three countries showed little change during the period covered, although

performance differed among the three. Pakistan's female enrollment edged up

from 30 percent in 1975 to 33 percent in 1987. In roughly the same time

period, India's rose from 38 percent to 40 percent, while in Sri Lanka, the

female share of enrollment started at virtual parity with males and remained

so over time.

V Neither the original sources nor the Consortium bear any responsibilityfor the analyses or interpretations presented in the text based on tablesdrawn from these sources.

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Tablg 1: Female Share of Total School EnrolThent, by Country, 1975 to 1987(in percent)

Country 1975 1980 1981 1982 1983 1984 1985 1986 1987

PrimaryBangladesh 34 37 . - 44 40 40 40India 38 39 39 39 39 40 - -Nepal 15 28 - 28 28 28 29 - -Pakistan 30 33 - - 32 32 32 32 33Sri-Lanka 47 48 - - 48 48 48 48 -

SecondaryBangladesh 21 - 24 - - 29 28 21 21India 29 - 32 34 33 33 34 - - -Nepal - 17 20 - 21 22 23 - - -Pakistan 23 - 26 - - 25 26 27 -Sri-Lanka - 51 51 - * 52 52 52 52 -

Source: UNESCO, Statistical Yearbook 1988, pp. 3-131 - 1-139.

At the secondary level, an inverted U-shaped pattern is again

evident for Bangladesh. The female enrollment share increased from 21 percent

in 1975 to 29 percent in 1984 and declined slightly in 1985 and then fell

sharply to 21 percent in 1986 and 1987. Although total enrollment has

increased, female enrollment has not kept pace with male enrollments. India,

Nepal, and Pakistan have experienced steady, but unspectacular, progress in

the female enrollment share at ttie secondary level. Except in Sri Lanka, the

gender differential continues to be very high. The ICPSR data provide gender

differentials by region and age, albeit for an earlier time period. Table 2

clearly indicates that the gender differentials in all cases were dramat.cally

greater in rural areas. In Nepal, the rural female enrollment rate of the 20-

24 age category in 1971 was .4 percent, and the equivalent rates for

Bangladesh and Pakistan were .5 percent and 1.6 percent, respectively. Even

Sri Lanka had a rural female enrollment rate of only 6.8 percent of this age

category; in the 5-9 age category, however, Sri Lanka had no rural gender

differential, and the female enrollment rate was almost 60 percent.

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Table-2: School Enrollments by Country, Age, Sex and Region(percent of population group)

Country/ Total Urban RuralAge Total Male Female Total Male Female Total Male Female

Bax"ladesh (1974)All ages 21.3 27.6 14.5 34.5 38.3 30.2 20.0 26.5 13.05- 9 18.8 22.0 15.5 31.5 33.7 29.3 17.8 21.1 14.410-14 33.8 40.6 25.8 50.7 54.5 46.5 32.1 39.2 23.615-19 18.8 29.1 7.1 34.6 40.7 27.2 16.9 27.6 4.820-24 7.6 14.3 1.1 15.9 21.7 7.0 6.5 13.0 0.5

Nepal (1971) I/All ages 12.7 20.2 4.7 44.3 50.6 36.8 11.3 18.8 3.36- 9 9.7 14.4 4.7 2.3 47.9 36.4 8.4 13.2 3.5

10-14 21.6 32.7 8.5 64.9 72.6 56.0 19.8 31.1 6.515-19 13.4 22.0 3.9 47.4 54.4 38.5 11.7 20.3 2.420-24 4.1 7.5 0.9 21.0 27.2 12.6 3.2 6.2 0.4

Pakistan (1973) 2/All ages 20.9 28.0 12.4 35.8 'i.6 29.1 14.9 22.6 5.65- 9 17.9 23.3 11.8 32.8 36.8 28.4 12.5 18.6 5.810-14 34.6 45.8 20.5 55.1 63.2 45.5 26.1 38.8 9.515-19 18.0 24.6 9.3 32.2 39.1 23.7 11.7 18.4 2.720-24 6.2 8.7 3.3 12.2 16.0 7.6 3.6 5.3 1.6

Sri Lanka (1971) 3/All ages 46.0 47.6 44.4 49.3 49.6 49.0 45.1 47.0 43.2

5- 9 60.9 61.6 60.2 63.8 64.2 63.5 60.2 60.9 59.410-14 69.8 72.2 67.4 75.5 77.0 74.0 68.3 70.9 65.615-19 34.5 36.5 32.4 41.8 43.6 39.7 32.3 34.3 30.420-24 8.6 9.4 7.8 12.2 12.8 11.4 7.4 8.1 6.8

1/ Enrollment refers to all levels of education, presumably at the time of thecensus.2/ Excludes tribal areas and the Malakind Division in the North-West FrontierProvince.3/ Attendance defined as enrolled and regurlarly attending classes during the twomonths preceding the census date.

Sources: Bangladesh--Bangladesh Bureau of Statistics, Population Census ofBangladesh, 1974, National Volume, Report and Tables, Dacca, 1977, tables 4 and 13.Nepal--Nepal Central Bureau of Statistics, Population Census, 1971, Kathmandu, 1975,vol. 2, part 2, table 17, and vol. 5, table 43. Pakistan--Census Organization,Pakistan, Housing, Economic and Demographic Survey, 1973, vol. II, part I, table 5;this survey was the third phase of the 1972 Census Operation antd consisted of a 2pecent rural and 5 percent urban sample of census households. 3ri Lanka--Departmentof Census and Statistics, Census of Population, 1971, vol. 2, part 1, Colombo, 1975,tables 7 and 13.2.

These data were made available by the Inter-university Consortium for Political andSocial Research (U.S. Department of Commerce, Bureau of the Census, ICPSR no. 8155,Women in Development, IV, 1983).

Bangladesh also reveals a good start. Both rural and urban gender

differentials are much smaller for the 5-9 age group than for the other

groups. Similar progress is ind.cated in Nepal and Pakistan, where gender

differences in enrollment ratios for the 5-9 age categories were narrower than

for older groups. The overall rural female enrollment ratios of 3.6 percent

and 5.6 percent were still abysmally low, however, showing the magnitude of

the problem these countries faced.

Changes in literacy, shown in table 3, indicate that these countries

have made some progress in educating women. Rural female literacy rates

climbed frouL 2.7 percent in 1971 to 7.6 percent in 1981 in Nepal and from 4.2

percent to 7.3 percent in Pakistan. Bangladesh and India also made moderate

progress; rural female enrollment rates rose from 11.5 percent to 15.3 percent

and 13.0 percent to 17.6 percent, respectively. (Charts la and lb show the

changes in urban and rural female literacy rates over time.)

Table 3: Literacy by Country, Sex, and Region, 1971 and 1981(percent of population group)

1971 1981Urban Rural Urban Rural

Country Male Female Male Female Male Female Male Female

Bangladesh 57.9 33.2 34.7 11.5 58.0 34.1 35.5 15.3India 72.4 45.5 40.6 13.0 76.4 51.9 47.3 17.6Iepal 62.4 28.0 32.9 2.7 59.7 33.0 29.6 7.6Pakistan 50.1 29.9 22.0 4.2 26.9 34.7 26.6 7.3Sri-Lanka 91.6 80.3 84.5 65.1 95.6 91.1 90.0 79.5

Base period is 1974 for Bangladesh and 1972 for PaVistan.

Source: UNESCO: 1988, pp. 1-19 - 1-21.

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Table 3 clearly indicates that, except for Sri Lanka, gender

differentials are very high and that in absolute terms there are very low

female literacy rates in both urban and rural areas. The extent of progress

is likely to be understated, however, because of the lack of disagbregation by

age categories. This point is clearly brought out in all cases shown in

table 4. Even so, the problem persists.

As indicated by table 5, women continue to be under-represented in

higher education. The pattern of specialization is similar in all the four

countries for which data are available, although the extent of progress in

higher education does differ among them. Sri Lanka is once again clearly the

front runner with women composing 45 percent of those enrolled in Bachelor

degree programs. The share for females enrolled at the postgraduate level in

the professional fields, including law, medicine, engineering, business and

agriculture, is much lower. The same differential exists in India, where

women account for more than 20 percent of total enrollments, and in Bangladesh

and Pakistan, where fewales make up close to 20 percent of total enrollments.

In almost all cases, graduate or postgraduate enrollment in professional

fields is considerably less than 10 percent for these three countries.

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Table 4: Literacy Rates by Country. Age, Sex, and Region(percent of population group)

Country/ Total Urban RuralAge Total Male Female Total Male Female Total Male Female

Bangladesh (1974)"IAll ages 27.7 38.0 16.2 48.7 57.3 36.4 25.5 35.7 14.410-14 35.4 41.0 28.7 51.2 54.3 47.8 33.8 39.7 26.715-19 36.8 46.9 25.2 56.6 61.6 50.5 34.5 45.1 22.420-24 32.4 46.4 19.0 56.8 66.1 42.5 29.2 43.0 16.625-34 25.5 37.8 13.6 49.2 59.8 32.5 22.7 34.5 11.935-44 22.3 33.4 9.6 43.8 54.3 25.9 20.1 30.8 8.445-54 20.3 31.5 6.7 40.9 53.2 19.5 18.4 29.2 5.855-64 18.3 29.6 4.1 34.4 47.3 14.0 17.1 28.1 3.465+ 17.1 27.6 2.8 29.1 43.5 9.8 16.3 26.6 2.3

India (1971)2/All ages 9.6 12.6 6.3 12.1 13.0 11.1 8.9 12.2 5.110-14 18.3 22.0 14.1 24.9 26.5 23.1 16.7 20.9 11.915-19 7.2 8.0 6.3 7.0 6.7 7.3 7.3 8.5 6.020-24 7.3 9.0 5.6 7.5 7.2 7.9 7.3 9.7 4.925-34 7.9 10.8 4.9 9.3 9.5 9.1 7.5 11.2 3.935+ 7.9 11.6 3.7 11.4 13.4 8.9 7.1 11.2 2.5

Unknown 16.1 22.4 10.1 22.1 24.3 18.2 15.0 22.0 9.2

Nepal (1971)All ages 14.3 24.7 3.7 46.9 62.5 27.9 12.9 22.9 2.710-14 23.8 35.8 9.6 68.2 76.1 59.3 22.0 34.2 7.615-19 21.9 35.4 7.1 74.4 74.4 51.3 19.8 33.3 5.120-24 17.0 30.9 4.1 56.3 72.4 34.2 15.0 28.3 2.825-29 13.3 24.4 2.5 46.5 64.4 23.2 11.7 22.3 1.730-34 10.5 20.3 1.6 38.1 59.5 14.5 9.3 18.4 1.135-39 9.8 17.6 1.4 34.9 53.3 12.1 8.8 16.0 1.040-44 8.7 16.4 1.1 32.0 50.5 9.6 7.8 14.9 0.845-54 8.7 15.7 1.0 29.7 47.4 7.8 7.8 14.3 0.755-64 6.8 13.2 0.7 24.1 41.4 5.4 6.2 12.1 0.565+ 6.0 11.7 0.6 19.7 35.9 4.3 5.5 10.8 0.5

Table 4: (continued)

Pakistan (1973)All ages 26.7 37.8 13.4 46.1 57.3 32.4 19.2 30.2 6.010-14 39.3 51.2 24.3 60.7 68.6 51.5 30.4 44.2 12.415-19 39.0 51.1 23.1 60.7 69.2 50.3 29.3 43.4 10.420-24 33.1 47.3 16.6 54.3 65.9 39.9 23.8 38.8 6.825-29 26.6 40.9 11.2 46.2 61.1 29.8 18.9 32.9 4.230-34 22.7 35.7 8.8 40.9 56.4 23.6 15.9 27.7 3.335-39 20.1 32.0 7.6 37.4 52.2 21.0 13.3 23.7 2.540-44 17.0 26.2 6.1 33.7 46.8 17.3 10.8 18.3 2.145-49 16.1 26.1 4.9 32.7 46.9 14.7 9.7 17.5 1.550-54 14.7 21.2 5.6 28.5 39.5 12.0 10.2 15.1 3.655-59 13.6 23.6 3.4 27.1 41.8 10.1 9.1 17.1 1.460-64 11.8 16.6 4.4 22.4 32.1 8.5 8.7 12.2 3.165+ 14.0 19.2 6.1 25.7 35.7 11.0 10.4' 14.2 4.5

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Table 4: (continued)

Sri Lanka (1971)All ages 78.5 85.6 70.9 86.2 90.3 81.5 76.2 84.1 67.910-14 83.0 83.7 82.3 88.0 88.4 87.6 81.7 82.4 80.915-1¢ 86.7 88.3 85.1 91.7 92.4 91.0 85.1 87.0 83.420-24 87.1 91.0 83.1 92.8 94.6 90.5 85.3 89.7 81.025-29 84.7 91.0 78.4 91.6 94.3 88.2 82.4 89.7 75.430-34 82.4 90.4 73.8 89.8 93.5 85.3 79.9 89.3 70.435-39 74.5 86.3 62.5 84.8 90.5 78.1 71.4 84.9 58.240-44 74.9 86.7 61.3 84.3 90.4 76.7 71.9 85.4 56.745-49 70.1 84.0 54.4 81.2 88.6 72.1 66.9 82.5 49.450-54 68.7 83.3 51.3 79.2 87.8 68.6 65.4 81.9 46.055-59 63.9 79.1 45.3 75.2 84.7 63.7 60.6 77.5 39.960-64 60.5 75.7 41.0 71.6 82.5 58.8 57.2 72.8 35.565+ 51.9 68.9 31.6 62.7 75.2 49.7 48.9 67.3 26.3

1/ Definition of Literate conforms to UNESCO standard.

2/ Provisional figures from the 1981 census indicate the following percentagesliterate relative to the entire population (excluding data from Assam andJammu/Kasbmir): Total, 32,6 percent; males 46,7 percent; and females, 24,9 percent.(Source: Registrar General and Census Commissioner for India, "Provisional PopulationTotals, Series-1 India," Census of India, 1981. New Delhi, 1981.)

Sources: Bangladesh--Batigladesh Bureau of Sttistics, Population Census of Bangladesh,1974, National Volume, Report and Tables, Table 11, Dacca, 1977. India--IndiaRegistrar General, Census of India, 1971, Social and Cultural Tables, part II-C(II)K,table C-III, parts A and B, tables C-II and C-Ill, New Delhi, 1976, Nepal--NepalCentral Bureau of Statistics, Population Census, 1971, vol. 1, table 6, and vol. 5,table 42, Kathmandu, 1975. Sri Lanka--Department of Census and Statistics, Census ofPopulation, 1971, vol. 2, part 1, tables 7 and 12, Colombo 1975. Census Organization,Pakistan, Housing, Economic and Demographic Survey, 1973, vol. 2, part 1, table 14.The 1973 Housnig Economic and Demographic Survey was the third phase of the 1972 Censusoperation and consisted over 2% rural and 5% urban sample of census household.Excluded from the universe of the sample were the tribal areas and the Malakanddivision in the northwest frontier province.

These data were made available by the Inter-university Consortium for Political andSocial Research (U.S. Department of Commerce, Bureau of the Census, 1CPSR no. 8155,Women in Development, IV, 1983).

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D_klj : Representation of Women in Higher Education by Country,Field of Specialization, and Educational Level

(percent of total enrollment)

Country/ Level 1/Field Total 5 6 7

Bangladesh (1984)All fields 17.9 17.9 18.1Education science & teacher training 23.2 23.2 --Humanities, religion & theology 20.7 20.8 19.2Fine & applied artsLaw 5.4 5.2 17.4Social & behavioral science 18.7 18.3 26.2Commercial & business administration 15.2 15.7 6.1Mass communications & documentationHome economics (domestic science)Service tradesNatural science 17.0 17.0 17.0Mathematics and computer science 17.9 18.5 10.3Medicine & health-related sciences 15.4 15.4 15.7Engineering 2.6 2.6 2.9Architecture and town planning 6.2 5.8 7.1Trade, craft & industrial programmesTransport & communicationsAgriculture, forestry & fishery 5.7 6.2 2.1Other & not specified 26.1 26.1 --

India (1979)All fields 26.1 24.5 27.5 26.7Education science & teacher training 49.0 50.8 47.2 43.7Humanities, religion & theology 31.4 25.5 39.4 33.1Fine & applied arts 51.4 49.0 52.3 65.2Law 6.5 -- 6.5 8.4Social & behavioral science 18.2 16.7 18.3 20.1Commercial & business administrationMass communications & documentation 38.2 48.6 39.1 26.2Home economics (domestic science)Service tradesNatural science 25.9 24.0 27.2 28.3Mathematics and computer scienceMedicine & health-related sciences 28.9 34.0 22.5 23.2Engineering 8.1 10.1 3.4 4.9Architecture and town planningTrade, craft & industrial programmesTransport & communicationsAgriculture, forestry & fishery 3.1 3.0 2.7 4.5Other & not specified 20.9 14.2 26.7 25.4

- 12 -

TabI§ S: (continued)

Country/ Level 'IField 4ital 5 6 7

Pakistan (1985)All fields 14.7 19.4 23.5Education science & teacher training 34.6 35.6 34.2Humanities, religion & theology 30.9 23.2 34.0Fine & applied artsLaw 4.2 4.3 --Social & behavioral scienceCommercial & business administration 10.3 8.0 12.7Mass communications & documentationHome economics (domestic science)Service tradesNatural science 23.4 21.9 24.8Mathematics & computer scienceMedicine & health-related sciences 28.3 28.8 21.9Engineering 3.2 3.3 --Trade, craft & industrial programmesTransport & communicationsAgriculture, forestry & fishery 1.0 0.9 1.1Other & not specified 14.0 7.8 16.2

Sri Lanka (1985)All fields 37.8 31.9 45.1 45.1Education science & teacher training 60.3 -- -- 60.3Humanities, religion & theologyFine & applied arts 83.3 99.0 77.3 --Law 38.8 -- 39.2 31.6Social & behavioral science 47.9 35.1 51.3 20.4Commercial & business administration 55.7 62.0 42.3 11.1Mass communications & documentationHome economics (domestic science) 100.0 100.0Service tradesNatural science 42.6 34.9 44.0 34.2Mathematics & computer scienceMedicine & health-related sciences 45.8 -- 46.6 27.4Engineering 19.8 20.7 15.0 6.5Architecture & town planning 38.7 -- 45.4 23.4Trade, craft & industrial programmes 4 3 4.3 -- --Transport & communicationsAgriculture, forestry & fishery 50.2 31.7 59.1 27.0Other & not specified

1/ Level 5 Diploma or certificate; Level 6 Bachelors degree;Level 7 Postgraduate degree.

Source: UNESCO, Stastical Yearbook, 1987.

- 13 -

DETERMINANTS OF FEHAIE EDUCATION

The analytical framework used to guide the literature search is

drawn from a utility maximization model of household choice. The seminal

works in this area are Becker and Lewis (1974) and De Tray (1974). Birdsall

(1985, pp. 25-35), Rosenzweig and Evenson (1977), and Rosenzweig (1980) have

contributed useful expositions and estimations of such a model. Of particular

relevanck is King et al. (1986), in which the model is extended to explain and

subsequently test the intergenerational transmission of gender differentials.

Here, a simple behavioral model of household choice is outlined. The purpose

of doing so is not to offer theoretical innovation but simply to give

structure to the literature review that follows. The reader is referred to

the above sources for the details and complex issues this model involves.

The postulate underlying these behavioral models of household choice

is that households act as rational welfare-maximizing agents and that the

decision-making unit is the Lhousehold rather than the individual, as is

normally the case in the theory of consumer choice. These households are

rational insofar as their behavior reveals that they make consistent choices

to enhance the household welfare. Naturally, the limit on family welfare is

set by family income and leisure. In simple mathematical terms, the

behavioral framework for the family can be depicted as the maximization of a

welfare or utility function subject to income and time constraint; that is,

max U- f(Z). (1)

subject to Y and T.

Z represents a vector of arguments representing mostly consumption,

from which the family can be expected to derive welfare. It would obviously

include consumption of goods and services, in addition to schooling, leisure,

and the intangible cultural or community factors that influence the family's

consumption behavior X represents income from work and unearned income. A

specific form for the family budget could be written as follows:

Y - EW1 + NE (2)

Ti I + Leisure; (3)

where WI - wages for family members including children;

- time spent at work; and NE - unearned income from wealth.

- 14 -

Viewed in the context of developing South Asian economies, a model in which

family members pool their incomes and share consumption decisions seems

reasonable.

This model includes the decision making process concerning how much

schooling females in the family should have. Schooling is viewed as both a

consumption and an investment decision. It is a consumption decision in that

more schooling for both boys and girls may be perceived as improving the

texture of the child's life experience and as transmitting benefits to the

family as well. As an investment good, schooling will probably enhance the

child's future earning ability and hence confer future benefits on the family,

as when an illiterate household head is motivated to educate a child in order

to obtain his/her help in dealing with government forms. The time dimension

this model implies is ignored here, however.

The interaction of culture with family consumption decisions may be

of particular importance in determining gender differentials in the

acquisition of schooling. If uneducated girls are perceived culturally as

better brides or if the future contribution of females' earnings is to the

family they marry into, educating girls would provide less family welfare both

as a consumption and as an investment good. The two sets of diagrams below

indicate the predictions of the model if the family derives negative or zero

utility from schooling for girls. These illustrations are probably more

illustrative of decision making in poor rural households than in those with

higher incomes and education levels. The literature review provides evidence

that preferences are likely to differ with the income and education level of

the family.fi/

I Note that the prediction of the human capital model that less may beinvested in females because labor market discrimination lowers the returns toschooling becomes irrelevant here.

9/ In this framework tastes are considered exogenous. One can get around thisby essentially viewing the schooling decisions of different income groups asseparate problems.

- 15 -

Figug la: Preferences Fijg= lb: Outcome

(Negative Utitlity from (Corner Solution:Girls' Education) Zero Education for Girls)

Bcys' Boys'/Eduati Education

Girls Education Girls' Education

FLi Me 2a: Preferences !igas 2k: Outcome

(Neutral Toiards (Corner Solution:Girls' Education) Zero Education for Girls)

IBoys' BoysEducation Education

Girtst Educatilon Girls* Edchaation

- 16 -

These figures assume a simple two-good model in which only female

and male schooling P-? consumed. Figure la depicts a preference ordering in

which male education sonveys positive utility to the family, while female

education conveys negative utility. Figure lb shows a corner solution

indicating that with such a preference ordering, families would maximize their

welfare by consuming no female education. Figures 2a and 2b show that the

same prediction is achieved with a weaker assumption, that families are

neutral (that is, attain zero utility) about educating girls.V

These are extreme cases and do not conform to average household

behavior patterns, because positive education of girls is observed in all

South Asian countries. Nonetheless, this model is useful in trying to explain

the observed gender differential in enrollments in South Asia. A change in

sociocultural norms can effect household preference ordering in such a way

that it can be depicted in the figures above as the usual convex indifference

curves.

This model is not mere abstract theorizing but has operational

significance. Solving some specific version of the simple general model

represented by equations (1),(2) and (3) would lead to a set of demand

equetions for female and male schooling, among other goods and services, and

also for children and leisure. Because all these equations are functions of

the same exogenous variables, each demand equation can generally be estimated

separately. The exogenous variables include prices, wages, unearned income

(if relevant asset price data are not available), child specific and family

V The precise nature of the trade-off between male and female educationembodied in the preference curves is immaterial. As long as neutrality ofpreference for, or any negative utility from, female education exists, acorner solution would still result.

I/ On this point, see Birdsall (1985, p. 30). The issue of empiricalestimation when a school supply constraint exists is taken Utp in the samesource (pp. 36-39). Rosenzweig (1980, pp.12-13) demonstrates the redundancyinvolved in using the simultaneous equations technique in this case.

- 17-

characteristics, school characteristics, and various community factors,

including social infrastructure and socio-cultural norms.

The cost of schooling is contained witbin the demand equation and

can made explicit as follows:

Cs -W#I + PIT1 (4)

WI in the first term refers to the wage child L can command on thelabor market. This first term therefore captures the opportunity cost of

schooling. Depending on the economic environment, proxy variables could be

used to capture the contribution of children to family productive activity,

either in domestic work or in a family enterprise. The second term represents

the direct cost of schooling measured by price variables, including all fees,

costs of books and uniforms, transportation cost, and other school- related

expenditure. In practice, researchers have often resorted to various proxy

variables for price, including the distance to school.

Certain a pDiori predictions of this theory can be tested by

estimating the demand equations. Thus, an increase in the wages of males in

the household would enlarge the family budget and hence possibly increase

demand for female schooling. The impact of an increase in wages for adult

female members in the household may have a more ambiguous effect. The income

effect may work the same way as for males, but because female child labor can

be viewed as a substitute for female adult labor, the net effect might be a

reduction in the demand for female schooling.

The parallel between the demand for education and that for other

market commodities or services can be overdrawn. This point can be

illustrated in clarifying the role of policy in this framework. Consider the

movement between various points in figure 3 below. Policy can shift the

supply curve by expanding educational capacity. In a normal market, this

should be represented by a movement of the equilibrium point from A to calthough additional policy interventions may be needed to induce this

f See Birdsall (1985, pp. 43-44) for the ideal data requirements and (pp.61-64) for some of the exogenous price variables used in practice.

- 18 -

movement. Policy can also shift fthe demand curve (movement of the equilibrium

from a to 0)-

FLMer 3:

CompositePriceIndex

Enrollments

These movements or shifts in the education "market' are more complex

than those in a commodity or service market. In the case of education, the

price is a composite variable. It is not price in the usual market clearing

sense, but rather, represents the direct and indirect costs of education to

households. The shift in the supply curve reduces the price insofar as

distance is used as one proxy for ;rice. Building more schools, given a

reasi,nable location based on school mapping, would reduce average distance to

school. Distance is only one part of the composite schooling price index,

however. A shift in supply may result in excess capacity, measured as part of

the distance between a and d, if other components of the price index do not

shift as well.

A movement from a to a may be induced by a policy intervention that,

for example, reduces the price or the direct cost of education by providing

attendance scholarships, free textbooks and materials, free uniforms or midday

meals. A policy that reduces the indirect cost of education, such as the

- 19 -

provision of day-care services and labor- and time-saving technologies, could

also cause such a movement. Thus, a supply shift can be viewed as an

expansion of capacity, while cost changes or quality changes, such as

providing more female teachers or more trained teachers which reduces the

composite price index, can be viewed as inducing a mevement along the demand

curve to attain fuller capacity utilization. The literature search should

reveal that this distinction between enhancing capacity and inducing capacity

utilization is very important for increasing female schooling in South Asia.

Policy also can induce a shift in the demand curve (movement from a

to h) by imposing legislation such as making school attendance compulsory,

forbidding early marriage for girls, or restricting dowries. In this case,

again, quality is interpreted as part of the composite price index -- a

decline in quality Is tantamount to an overall increase in the price of

schooling. A successful drive to increase enrollments without changing

capacity means larger class sizes, which is inversely associated with quality.

One word of caution is in order about the empirical estimation of

demand curves. Several studies have estimated school demand functions and

included a dummy variable for gender. This implicitly assumes that all

quantified exogenous variables have similar effects on both males and females,

which is not necessarily correct.IW For policy purposes, estimating separate

demand equations for females would be imperative in order to identify the

impact on female enrollment of altering a control variable such as some aspect

of the price of schooling or a key social infrastructure variable. Having

estimates of the demand for female education in a situation in which

inadequate supply limits female enrollments may be useful in predicting now

much female enrollments will increase in response to an increase in supply.

DJ This has been established by Rosenzweig nd Evenson (1977, p. 1076) and byRosenzweig (1980, p. 18) using two separate data sets.

- 20 -

LITERATURE SEARCH: CHILD SCROOLING

Although most of the studies reviewed here do not explicitly apply

a conceptual model, the model set forth in the preceding section captures the

implicit behavioral framework underlying these studies. For expositional

convenience, the factors that can affect female schooling have been grouped

into two broad sets: family and community factors and school factors. These

categories are not entirely discreet of course.

Famnily andjeommunitv factors

Most studies mention poverty as the major reason families fail to

enroll or subs,quently withdraw children from primary education.WV This

suggests that families find both the direct and the indirect, or opportunity,

costs of schooling difficult to bear. Related to poverty is the demand for

female child labor to take care of siblings and to do household and farm work.

Moreover, authors writing on this issue emphasize that the demand for girls'

labor for domestic work is much greater than that for boys., Jamison and

Lockheed [1987, p. 283] cite studies indicating that the demand for girls'

labor in Nepal exceeds that for boys' by about 50 percent. However table 6

shows that female economic activity rates in Nepal in the 10-14 age bracket

were much higher than in the rest of South Asia in the mid-1970s but that male

activity rates in this age bracket were equivalent to those of females.

Unfortunately, data for Nepal are not reported by region.

Papanek (1985, p. 334) points out that for Bangladesh the age-

specific female activity rates for the youngest age group (10-14) were the

highest of all age groups and for males in that age group the lowest.

Rozenzweig (1980, p. 18) showed that in India, women's and girls' (but not

boys') work is interchangeable, so a 10 percent rise in female wages reduced

girls' school attendance by about 5 percent.

11 For example, this is mentioned to be the case for Bangladesh by Qasem(1983, p. 21) and Islam (1982, p. 34), for India by Tara (1981, p.178), forPakistan by Anderson (1988, p.1) and Shah and Eastmond (1977, p.14) and forNepal by UNESCO (1980, p.99).

IV For additional evidence on this issue see Chamie (1983, p. 32).

- 21 -

Table 6: Persons Economically Active by Country, Age, Sex, and Region(percent of population group)

Country/ Total U.ban RuralAge Total Male Female Total Male Female Total Male Female

Bangladesh (1974)1/A1l ages 44.3 80.3 4.0 45.8 73.7 5.8 44.2 81.1 3.8

10-14 25.6 41.9 6.3 15.5 23.2 7.1 26.7 43.7 6.315-19 38.3 67.8 4.5 31.8 54.1 4.3 39.0 69.5 4.620-24 42.9 84.0 3.1 47.2 75.1 4.6 42.4 85.6 3.025-34 49.1 96.9 2.8 60.1 94.6 5.6 47.8 97.3 2.635-44 54.4 98.9 3.3 64.1 97.6 6.8 53.4 99.1 3.045-54 55.5 98.4 3.7 63.4 95.9 7.0 54.8 98.6 3.455-64 55.3 95.9 4.0 55.5 87.3 5.4 55.7 96.6 3.965+ 50.1 84.2 3.3 39.3 66.0 3.4 50.8 85.4 3.3

India (1971)All ages 32.9 52.5 11.9 29.3 48.8 6.6 33.8 53.5 13.1

0-14 4.7 6.6 2.6 1.8 2.8 0.8 5.3 7.5 3.015-19 36.6 55.2 15.5 20.5 33.5 5.5 41.4 62.1 18.420-24 49.6 81.3 17.8 41.2 67.4 9.5 52.3 86.3 20.225-29 56.8 94.2 19.7 54.1 90.5 11.6 57.6 95.3 21.830-39 60.4 97.1 21.4 58.8 95.4 13.1 60.8 97.6 23.440-49 62.5 97.1 22.4 61.4 95.1 14.5 62.8 97.6 24.150-59 59.6 90.4 19.4 55.3 87.9 12.7 60.6 95.5 20.860+ 43.2 73.8 10.5 31.5 55.4 6.4 45.5 77.4 11.3Unknown 19.5 34.0 6.0 35.9 52.4 7.6 16.7 29.5 5.9

Nepal (1976)2/All ages 66.6 82.6 50.3

10-14 50.8 51.4 50.115-19 67.9 74.8 60.620-24 72.9 91.8 56.225-29 74.5 96.4 53.930-34 72.5 96.6 50.835-39 75.1 97.8 51.740-44 74.3 98.1 51.445-49 73.5 96.4 48.550-54 70.4 93.5 44.955-59 65.9 90.2 40.260-64 49.8 72.2 28.165+ 34.1 49.2 18.0

- 22 -

,Table 6: (continued)

Country/ Total Urban RuralAge Total Male Female Total Male Female Total Male Female

Pakistan (1973)3/All ages 46.6 77.6 9.1 42.7 70.6 8.7 48.2 80.4 9.310-14 26.6 39.5 10.3 18.8 26.1 10.2 29.8 44.8 10.415-19 42.1 67.7 8.6 32.6 52.7 8.0 46.3 74.1 9.020-24 51.9 87.4 10.8 49.6 81.1 10.9 52.9 90.3 10.825-29 53.1 95.6 8.6 53.0 93.7 7.9 53.2 95.0 8.930-34 54.2 96.3 8.8 54.2 95.9 7.7 54.1 96.5 9.235-39 53.8 97.0 8.2 54.1 96.7 6.9 53.7 97.1 8.740-44 56.3 96.7 8.6 56.4 95.9 7.1 56.3 97.0 9.145-49 54.4 96.3 7.7 56.3 95.1 6.8 53.8 96.8 8.050-54 58.8 94.3 9.5 58.5 91.3 9.7 58.9 95.3 9.455-59 49.3 90.8 7.3 49.0 85.5 7.0 49.4 92.7 7.460-64 55.2 85.6 8.6 48.1 75.1 9.2 57.3 88.5 8.465+ 43.2 65.7 8.9 36.8 55.3 9.9 45.2 68.8 8.6

Sri Lanka (1971)4/All ages 39.0 58.7 18.0 35.9 57.2 11.1 39.9 59.1 19.910-14 3.2 4.0 2.3 3.8 4.8 2.7 3.0 3.8 2.215-19 22.4 29.8 14.9 16.9 25.5 7.2 24.1 31.2 17.020-24 42.8 62.4 23.0 38.4 59.1 12.8 44.3 63.7 25.925-29 54.9 82.9 26.7 52.2 81.1 17.0 55.8 83.6 29.630-34 60.0 90.4 27.4 57.1 88.9 18.0 61.0 91.0 30.235-39 60.7 92.4 28.3 26.7 90.5 17.4 61.9 93.1 31.340-44 62.3 92.7 27.1 57.7 90.2 16.9 63.7 93.6 30.145-49 61.2 92.0 26.2 55.5 88.8 14.9 62.9 93.1 29.350-54 58.2 89.1 21.5 52.7 84.8 13.0 59.9 90.4 24.155-59 49.4 77.9 14.6 41.0 67.7 8.5 51.8 80.8 16.360-64 39.3 63.4 8.4 29.1 48.6 6.2 42.3 67.4 9.165+ 23.5 40.3 3.6 16.6 29.4 3.2 25.4 43.0 3.7

/ The definition of civilian economically active confroms to the ILO standard. Thereference period was the week prior to the census.

2/ Definition of economically active not available. The midterm population samplewas a 3.501 percent sample enumeration conducted in April-June 1976.

3/ Definition of economically active conforms to IID standard. Sample excludestribal areas and the Malakand Division in the North-West Frontier Province.

4/ The economically active population is defined as all persons aged 10 or over whowere engaged in any kind of work for pay or profit on a regular or seasonal basis,including unpaid family workers engaged in profit-making activities at least anaverage of three hours a day, but excluding those engaged in housekeeping; werelooking for work for the first time; were unemployed but actively seekingemployment; or were available for work but not actively seeking employment becausethey felt no work was available.

- 23 -

Table fi: (continued)

Sources: Bangladesh--Bangladesh Bureau of Statistics, PoDulation Census ofBangladesh. 1974, National Volume, Report and Tables, table 14, Dacca, 1977.India--India Registrar General, Census of India. 1971, EconomicCharacteristics of the Population, Series I-India, paper 3, table B-1, part A,tables 17A and 17B, New Delhi, 1972. Nepal--Central Bureau of Statistics,Midterm £Plation Sample SuMvey. 1976, table 11, Kathmandu, 1979. Pakistan--Census Organization, Pakistan, Housing Economic and Demographic Survey. 1973,vol. II, part 1, table 16. Sri Lanka--Department of Census and Statistics,Census of 2poulation. 1971, vol. 2, part 1, tables 7 and 16, Colombo, 1975.

These data were made available by the Inter-university Consortium forPolitical and Social Research (U.S. Department of Commerce, Bureau of theCensus, ICPSR no. 8155, Women in Develo_ment, IV, 1983.

The expectation that poorer rural families will require their sons'

wives to work discourages some households from enrolling girls in school

because they would then become less desirable as wives. Education is

perceived as corrupting the traditional attitudes of females and causing them

to be less willing to do physical labor.W Thus, schooling is perceived to

have a social cost in addition to the direct and opportunity costs. This cost

is the onus of having single daughters of marriageable age in the household.

A related economic cost could also result on the margin if several females are

present in the household (resulting in diminishing returns from household

chores) and if avenues for productive nondomestic work are limited.

Some families may have other reasons to lack interest in or be

openly hostile to the idea of formal education for females.M/ In culturally

LU Seetharamu and Ushadevi (1985, p. 61) and Desai (1987, p.17) reporting forIndia, and Shrestha for Nepal (1986, p. 31). Smock (1981, p. 91) reportsresults of an attitudinal survey in Pakistan in which education was perceivedas making females self-centered, defiant of parental authority, anduninterested in household affairs.

W Singhal (1984, p. 367) cites a study con-aducted by the National Center forEducation Research and Training in India which found that domestic work,marriage, betrothal, and parental indifference account for 55 percent of totalwastage in girls education at the middle level. Clason (1976-77, p.182)reports poor rural parents in Nepal view female education as immoral; asimilar attitude was reported in UNESCO (1975, p. 37).

- 24 -

conservative environments, adolescent girls may be viewed as morally suspect

if they continue going to school. The young age at first marriage and the

importance of preserving a girl's good reputation in such cultures lead to

widespread withdrawal of females from school at puberty, particularly if they

are attending coeducational schools.W Early marriage is perceived to be such

a barrier to female schooling that one writer in a UNESCO study (1980, p. 12)

suggested legislation to forbid early marriage.

Tabla 7 reports minimum legal and actual ages of marriage during the

mid-1970s. The legal minimum age of marriage for females was either fifteen

or sixteen. In Bangladesh, 75 percent of rural ever-married females had

married by the age of seventeen. For Pakistan and India 75 percent were

married by age 22 and 19 respectively. Just as the economic activity rates

for girls in Sri Lanka were the lowest among these countries, only 25 percent

of rural ever-married females married before the age of 21 and 50 percent were

older than 23. In all cases, women in urban areas tend to marry later. Also

in all cases, the legal age of male marriage is higher by a couple of years

than that for females, and the actual age of male marriage in both rural and

urban areas is considerably older. Thus, early marriage may not have deterred

male education as much as it discouraged female education.

Almost all South Asian cultures are conservative, although the way

Islam has been adopted normally leads to a restrictive environment for female

education. According to Gunawardena (1987, p. 8), the Muslim community's

progress in education in Sri Lanka has lagged behind that of the Sinhalese,

Tamils, and Burgers. The importance of cultural conservatism in discouraging

female education can be overstated, however. Cha.mie (1983, p. 2) challenges

the conventional view that Islam contributes to low enrollment rates among

girls by citing the high rates in Libya and Bahrain. Rozfnzweig's results

(1980, table 4) show that being Muslim was not a signifLant barrier to female

enrollments in India. Sarkar (1986, p.88) found mixed evidence and concluded

that the hypothesis that Muslims are opposed to educating both males and

females does not hold. This evidence suggests that unidimensional views are

inadequate in explaining gender differentials in schooling.

W/ See Caldwell et al. (1985, p. 68) for India, Anderson (1988, p. 6) forPakistan and Qasem (1983, p. 6) and Papanek (1985, p. 334) for Bangladesh.

- 25 -

Tablg Z: Minimum Legal Age at Marriage and Age ActuallyMarried by Country, Sex, and Region

Total Urba-. RuralPercent Ever Married Male Female Male Female Male Female

Bangladesh (1974)Minimum legal age 18 15 18 15 18 1525% 21 14 23 15 21 1450% 24 15 26 17 23 1575% 27 17 28 19 27 17

India (1971)Minimum legal ageV/ 18 15 18 15 18 1525% 19 14 21 16 18 1450% 22 17 25 19 22 1675% 26 19 28 21 25 19

Pakistan (1973)2/Minimum legal age 18 16 18 16 18 1625% 22 17 22 18 21 1750% 25 19 26 20 25 1975% 29 22 30 23 29 22

Sri Lanka (1971)Minimum legal age3/ 18 16 18 16 18 1625% 25 20 26 20 24 2050% 28 23 29 24 27 2375% 32 27 34 29 32 27

M/ Minimum legal age revised to 21 in 1976.

2/ Sample excludes tribal areas and the Malakand Division in the North-WestFrontier Province.

3/ Legal marital ages enacted in 1978.

Sorgces: Bangladesh--Bangladesh Bureau of Statistics, Population Census ofBangladesh, 1974, National Volume, Report and Tables, table 5, Dacca, 1977;Population Information Program, series M, no. 4, table 15, November 1979 (Ageat Marriage). India--(minimum legal age) World Health Organization, WorldHealth, Aug.-Sept. 1976, p. 6; (age % ever married) India Registrar General,Census of India, 1971, Social and Cultural Tables, Series 1, part II-c, tablec-il, derived at the U.S. Bureau of the CEnsus by fitting a makeham model todata from the 1971 census. Pakistan--Census Organization, Pakistan, Housing,Economic and Demographic Survey, 1973, vol. II, part 1, table 2; KatherinePeipmeier and Elizabeth Hellyer, "Minimum Age at Marriage: 20 Years of LegalReform," in People, vol. 4, no. 3, 1977. Sri Lanka--Department of Census andStatistics, Census of Population, 1971, vol. 2, part 1, table 8; PopulationInformation Program, Population Reports, Series M, no. 4, table 15, JohnsHopkins University, November 1979.

Data made available by the Inter-university Consortium for Political andSocial Research, (ICSPR no. 8155, Women in Development, IV, 1983, U.S.Department of Commerce, Bureau of the Census).

- 26 -

Cultural norms, as embodied in a father's attitude about educating

his daughters, have been shown to affect enrollment rates. In a careful and

analytically sophisticated study addressing female education (among other

issues) in Asia, King et al. (1986, pp. 56-57) attempted to ascertain how much

of the gender gap in enrollment results from social norms and the attitudes of

parents and how much from differences in individual characteristics. To do

this, the authors computed a family-specific discrimination index. They found

that for families having a positive mean for female schooling, if daughters

were treated similarly to sons, their educational level would rise by 65

percent in middle-class urban Lahore (Pakistan), by 129 percent in lower class

urban Lahore, and by 224 percernt in rural Punjab (pp. 58-59).

Mothers' attitudes also may discourage female education. Smock

(1981, p.61) citing a village survey, reported that only 10 percent of the

village women supported the notion of equality of opportunity for women. Shah

(1986, pp 246-47) citing the results of a survey in Pakistan, reported that

among households that owned no assets, 51 percent of the urban mothers in the

sample and 58 percent of the rural mothers believed that religious education

(about a one year equivalent) was enough for their daughters.

Many studies have reported that rural families perceive the formal

education curriculum as useless.W In one village study in Bangladesh,

Khatun (1979, p. 267) inquired about the parents' perception of a useful

education for girls; an overwhelming majority desired to see child care,

cooking, and handicraft in the curriculum. This is consistent with the role

perceived for females when they marry into another family. In fact, such

training may be perceived as making girl more eligible and hence resulting in

a marriage that is better for her family because they may become allied to a

more economically and socially powerful family.

Because girls are essentially perceived as an economic asset for the

family they marry into, the returns from a family's investment in educating

Lf/ See UNESCO (1980, P. 61).

- 27 -

daughters are viewed as accruing to another ho'usehold rather than to the

investor household.I Under these circumstances, the family has little

potential for viewing female education as an investment good.

Family opposition to secondary education for girls is much greater

than to primary education because the direct costs are higher and the girls

are already of marriageable age. FREPD (1981, p. 109), somewhat unusually,

found little difference in parental attitudes towards the continuation of

daughters' or sons' education at the primary level in Bangladesh. However, 91

percent of the household heads wanted their sons to go on to the lower

secondary level, while only 61 percent wanted their daughters to do so.

In an interesting study, Ashby (1985, pp. 70-72) points out that

poor families develop a strategy of educating one son in the family up to an

upper secondary or higher level so that he may obtain a white-collar job. Her

results show that additional women and young girls in the pool of family labor

significantly increase the amount of schooling male children achieve (p. 78).

In contrast, Caldwell et al. (1985, p. 33) report that in rural

South India the case is sometimes the opposite. Growing pressure on land,

technological change, and a trend toward hiring individual labor rather than

whole families have produced excess labor in families. As a result, girls are

allowed, and are even encouraged, to go to school as a famine-fighting

strategy. Girls with at least some level of education would be a better match

for white-collar husbands, who may help the family during a famine or who at

least would not be a liability. This suggests that changing economic

conditions can alter deep-seated cultural practices.W

IV Such a view is reported by Qasem (1983, p. 21) for Bangladesh (study basedon two purposively selected villages), Shah (1986, p. 253) for Pakistan andSharesta and Jange (1984, p. 70) for Nepal.

IV It is also possible to find economic imperatives underlying culturalpractices.

- 28 -

Uniform cultural practices cannot be viewed as prevailing

universally across all cross sections of society. A definite class difference

exists in parental attitudes toward education and marriage prospects. Middle-

class families may view some education of girls as promoting a good marriage,

because the women can then manage their households more efficiently.)2

Because marriages are perceived as an alliance of families rather than as a

commitment of two individuals to each other, some education for females may

confer positive welfare if it raises the probability of a strong social

alliance. Thus, the expectations from a girl's marriage can be expected to

differ by income group.

Lower middle-class families have reason to perceive education

negatively. Women in South lAsia are usually expected to marry men with more

education than they have. However, to find a husband for a more educated

woman would require a larger dowry in cultures in which dowries are

customary.3&l This is then another example of a "hidden" cost of educating

females. Seetharamu and Ushadevi (1985, p. 61) recommend an antidowry

campaign in the media and a policy linking a dowry subsidy to the educational

attainment of girls.

A family's income level and the education level of the parents or

other adult family members appear to be positively related to the education of

the girls in the family. In the analytical framework used here, a higher

income level enables the family to bear both the direct and indirect costs of

education. A higher income level, but even more so the family education level,

W See for example Jange and Sharesta (1984, p. 70) for Nepal and Ahmad etal. (1978, p.7) for Bangladesh. Also, a change in norms in the upper-incomegroups may eventually filter down, possibly in conjunction with economicchanges. A country study of India in UNESCO (1980, p. 67) reports that evenpoor villagers view female education as a means of enhancing security andmarriage prospects. This is not however the opinion expressed by mostauthors.

20/ See Sharesta (1986, p.31) for Nepal, however Seetharamu and Ushadevi(1985, p. 61.) and Desai (1987, p. 10) for India, and Lavador (1986, p. 92)for Bangladesh. The most frequent references to this phenomenon were forIndia.

- 29 -

can also lead to higher female educational attainment because those families

tend to have a more enlightened attitude or provide a more stimulating

environment for education.W

Rosenzweig, (1980, p.19) using multivariate analysis and the

appropriate separate equations by gender, found land size and unearned income

to be positively and significantly associated with rural female enrollments.

Abmed and Hasan (1984, pp. 2-3), using data from a probability sample survey,

performed simple two-way cross tabulations to show that girls' education

varies positively with their family's income and land ownership. For

Bangladesh, Islam (1982, p.35) reported a high correlation between girls'

enrollment and the proportion of adult hourehold members who are educated.

This evidence is corroborated by Ahmed and Hasan (1984, pp. 2-3), wh%; reported

that 91 percent of children from the most educated families in their sample

survey, those with eight years of education or more (4 percent of the families

sampled), were enrolled in school, while only 12 percent of boys and 7 percenL

of girls from illiterate families were in school. For Pakistan, Shah (1986,

pp. 246-4) cites a study indicating that about two-thirds of illiterate rural

women wanted only religious education for girls, while approximately the same

proportion of rural women with up to six years of education desired up to

higher secondary education for their daughters and 17 percent wanted them to

get a college education.

To ascertain whether education has a "snowballing effect," a study

should control for income in the cross tabulations. Irfan, (1985) using a

large 1979 data set for Pakistan, explored this issue as well as several other

schooling issues for the 10-14 age group. Cross tabulations demonstrated that

within all income groups the relationship between the education of the head of

the household and the enrollment rate for girls in the family was positive (p.

W Even if such children are not consciously nurtured to be betterperformers, they are likely to have a competitive edge over students in harshfamily circumstances.

- 30 -

33). M/ In a multivariate analysis, Irfan used enrollment ratios as the

dependent variable in separate regressions by gender to explore both demand

and supply factors in education (p.36).

On the supply side, the existence of a middle school or a high

school proved significant for nonfarm households but not for farm households.

On the demand side, for both farm and nonfarm households, income of parents

was a significant variable. For farm households, land ownership was

significant, whereas for nonfarm households, the educational level of the

household head was significant. For both kinds of households, the literacy

ratio in the village during the last census period (1972) was a significant

variable. That education generates education is evident not only from the

significance of the variable representing the education level of the head of

the household but also from the independent influence of the general level of

literacy of the village.

This finding is also confirmed by elasticities estimated at means by

King et al. (1986, p. 52) from equations estimating the determinants of

education. In a cross section of families in Pakistan, the father's education

had significant impact and was among the most powerful influences on the

education of both males and females. Although the elasticities are

approximately equal for the sexes in middle-class urban families in Lahore (.3

and .29 for males and females, respectively), they are disproportionately

higher for females than for males in lower class urban families in Lahore (.32

and .18) and in rural Punjab families (.32 and .12).Wh Thus, an educated

father may play a more important role in the education of females than of

males in lower class urban and rural families. The mother's schooling was not

as influential as the father's; the elasticity for mother's education was

significant only for females belonging to middle-class urban families in

VJ The page references given in this paragraph conform to the revised versionof Irfan's report and hence may not tally exactly with the citation in thebibliography.

ZU All the elasticity coefficients are significantly different from zero atthe 10 percent level.

- 31 -

Lahore (.14). Although the conservatism of a lower class urban or a rural

family may oe gauged by male attitudes (or male educational level as a proxy),

the social attitudes of middle- and upper class families may well be

determined by the educational level of the mother. Thus, the significance of

the elasticity for females bel3nging to middle-class urban families is

interesting.

In summary, among family and community factors affecting girls'

education, poverty is reported as the major barrier. Both the direct and

indirect costs of education discourage poor families from educating their

daughters. Evidence suggests that girls are much more heavily involved than

boys in domestic chores. The importance of costs of education in

understanding low female enrollments is borne out both by the direct responses

of poor families in survey studies and indirectly by cross tabulations and

multivariate analyses, which indicate that female enrollments vary inversely

with family income.

For poor families, the prevailing cultural norms impose further

costs. First, they may have to give a higher dowry to more educated daughters

because women traditionally marry better educated men, who command a higher

dowry. Second, education is perceived as making females "uppity" and averse

to the hard labor that is their life role; also education beyond puberty may

make them suspect of being unchaste. Both factors can prejudice a woman's

marital prospects, and families desire to avoid the stigma of having daughters

at home beyond marriageable age.

For these reasons, female education may provide negative utility to

families as a consumption good. Educating females may also be a poor

investment strategy, because culturally induced job market discrimination

reduces the rate of return to their education. Moreover, any returns to their

education would accrue to their husbands' families.

The requirements for a desired bride vary with the socioeconomic

status of the family. A more educated girl would enable the family to forge

- 32 -

through marriage a more powerful social link. A middle- or upper class family

may be more concerned than a poor family with the quality of child rearing and

hence would require a more educated bride for their son. The positive

association of female education and the educational and income level of

families supports this supposition.W Although the role of cultuxe is

critical in family decision making, autonomous economic forces can bring about

cultural changes; for example, in a South Indian region, economic developments

made female education more desirable as a famine fighting strategy.

Family and community factors are undoubtedly important in gender

differentials in schooling. These factors are also amenable to policy cbarges

such as the reforming of dowry and marriage practices. Tara (1981, p. 74),

noting that taking care of siblings usurps much of a young girl's time,

recommends the development of some form of community day care. In addition,

labor-saving technologies, in principle, can make time for schooling.

Seetharamu and Ushadevi (1985, p.101) suggest that the provision of safe and

continuous water should be a priority, because bringing water can occupy up to

four hours of a girl's day. These policy recommendations typically are not

viewed as directly in the domain of education policy as are recommendations

that emerge from a study of the school factors as determinants of female

schooling.

School Factors

School location, female-specific facilities, and examination

policies are among the various school-related factors that can contribute to

gender differential in enrollments. These factors influence parents'

decisions to educate their female children.

The importance of school location may vary within and among

countries. In the analytical framework guiding this literature review,

24/ Marriage of females is a major concern in all families in South Asia. Thisof course does not preclude an enlightened attitude as the main motivation ineducating girls in some cases.

- 33 -

location, or the distance to the nearest school, is often used as a school

price variable in studies estimating school demand functions. The hypothesis

is that, other factors held constant, enrollments should have a inverse

relationship with distance; that is, the shorter the distance to school, the

greater the likelihood that females will attend. Many authors have reported

distance to school to be an important barrier of female education. W

Islam (1982, p.36), on the basis of evidence for Bangladesh, argued

that increasing the number of schools will not necessarily foster greater

enrollments. She cited a survey that interviewed 208 female drop-outs, 84

percent of whom lived within a mile of the school. Similarly, Sattar (1984,

p.13) argued that access is not the issue for India, because 90 percent of the

children have access to a primary school or to a primary section in a

secondary school within a kilometer of their homes.

Even a short distance may seem long to some parents however. Ahmed

and Hasan (1984, p.26) reported that enrollment is negatively associated with

distance in Bangladesh because parents may be unwilling to allow girls even to

cross a major road or a river. For Nepal, with its rugged terrain, Clason

(1975-76, p.182) reported that the remoteness of schools can be a major cause

of low female enrollment. Jamison and Lockheed (1987, pp. 298, 301) did not

find distance to be an important determinant of school participation. They

admitted, however, that school availability for the sample they were using was

atypical for Nepal as a whole; also, they were not estimating separate

equations by gender, hence constraining the effect to be identical for males

and females.

Distanc.e is usually related to the supply of schools. UNESCO (1978,

p.36) reported distance to be perceived as a greater for secondary education

of girls, because one school must serve several villages. As public education

facilities increase in South Asia, the variation in school distance will

continue to decline. This suggests that researchers may need to look for more

W See Caldwell et al. (1985, p.41) for India, Shah (1986, p. 255) forPakistan, and UNESCO (1980, p. 99) for Nepal.

- 34 -

refined proxies for the price of schooling when the actual price data are not

available.

A lack of some basic facilities may affect girls' school attendance

more than boys'. Qasem (1983, p. 38) pointed out that 71 percent of rural

schools and 53 percent of urban schools in Bangladesh had no latrines, a

problem that could discourage female attendance. Ahmed and Hasan (1984, p.

58) also noted that families have withdrawn girls from schools lacking

latrines. In Pakistan, according to Anderson (1988, p.6), many parents feel

uncomfortable about enrolling girls in institutions without solid and high

boundary walls, which provide privacy.

Another cultural concern relating to school characteristics is the

need for separate institutions. Anderson has pointed out that coeducation is

a oe facto reality in Pakistan at the primary level and that the expense of

segregated schools with separate administrations is unwarranted.20 Islam

(1982, p. 67) indicated that after the nationalization of schools in

Bangladesh, the educational administration strongly discouraged segregated

schools, and the statistics support a downward trend in such institutions.

Other studies from Bangladesh and elsewhere, however, indicate that

parents are concerned about a lack of separate schools for girls.W Parents

desire segregation even at the primary level, so the lack of segregated

facilities at the secondary level may be an even more serious barrier to

continued female education. Testing for the effect of separate schooling

facilities, boundary walls, and latrines on the reduction of female

enrollments at puberty would be of great value for policy.

If See Nayar (1985) on this issue for India.

av See for example FREPD (1981, p.89) and UNESCO (1980, p. 44) forBangladesh, the latter source for India (p. 61), and Shah (1986, p. 255) forPakistan.

35 -

The same cultural forces that require special educational facilities

for females also provide universal support for female teachars.W The

Government of Nepal in conjunction with several international donors since the

early 1970s has undertaken an extensive project to provide women with equal

access to education. The key strategy of this project has been recruiting and

training female teachers from various regions, including remote areas, where

they could then serve as teachers after their training. A mid-evaluation

report (UNICEF 1978, pp. 25-33) indicated that the program appeared to be

having some success in encouraging and retaining female enrollments.

Pakistan has also experimented with training local teachers. Marker

and Gah (1985) describe a "mohalla" (home) school project in Baldia, a large

squatter settlement in Pakistan. In addition to training teachers with a high

school education chosen among women from within the community, the project

emphasizes cost-cutting by holding classes in homes, and not requiring

uniforms or even shoes. At least initially, the project has been a great

success. By the time the report was written (p. 8), the number of schools had

multiplied to sixty-four and enrollments had exceeded 16,000. The success of

the project was attributed to the hard work of the project team of two members

in involving and gaining the support and participation of the local

communities (p. 9).W

The wisdom of recruiting female teachers locally is not universally

accepted, however. A monitoring study by Qadir in Bangladesh (1986, pp. 18-

19) indicated that, although local women are able to communicate with and gain

acceptance by villagers, local teachers (including women) are chronically

absent in order to carry out household chores; the tenure policies of

nationalized schools probably encourage such absenteeism. In addition, they

21 This issue has probably achieved the greatest consensus in the literature.See for example UNESCO (1980, p. 15).

2V Also see UNESCO (1980, pp. 112-116) for a description of the mohallaprogram. Anderson (1988, p.7) is currently investigating this program andanother one involving mosque schools partly to see whether they provide accessto groups currently excluded or under-represented.

- 36 -

are primarily concerned with the income from giving private tuition to their

own students and practice favoritism toward these students.1/ Also, well-

connected women continually pester the local administration for a transfer to

town schools. Perhaps for these reasons, villagers indicated they opposed

local area teachers (pp.36-38). Drawing and retaining females from outside

the village poses another set of problems, however, such as gaining local

acceptance and, in particular, finding suitable accommodations.Al

Another school issue is the rigid examination policy, which may

affect girls more adversely than boys.W Because girls are under more

pressure to carry out household and farm work, they are more often absent than

boys. Their subsequent failure in examinations causes the family to perceive

that the educational investment has soured and to withdraw them.H' Repeating

a grade also makes them overage which, along with late entrance and withdrawal

at puberty, results in low schooling attainment.H1 Sattar (1984, p.17) has

suggested compulsory er.ollment at the prescribed age to ensure more years of

schooling. Possibly, forced withdrawal may become more difficult the greater

the number of years of schooling females attain; certainly, this hypothesis is

worth testing.

-" This is also a problem in Pakistan. Policymakers may consider legalizingtuition but restricting teachers to provide tuition to students from otherthan their own schools.

H/ Marker and Gah (1985, p.6) make this point for Pakistan. In fact, notonly is adequate accommodation not provided but female teachers are denied arent allowance. The Indian government has tried special allowances to attractrural female teachers and provided accommodation for them (UNESCO, p. 58, 65).No account was available about the success of this scheme.

AY See Chamie (1983).

P-U Sattar (1984, p.15) makes this point for India. This does not indicatethat girls are poorer performers. In fact Khan et al. (1986, p. 19) provideoverwhelming evidence from secondary data that girls in Pakistan haveconsistently been outperforming boys at the secondary level.

V/ See Abmad (1987, p.28).

- 37 -

In its campaign to increase girls' school enrollments, India has

experimented with a host of school-related incentives. In the analytical

framework being used here, these are aimed at reducing the direct cost of

education. These policies include providing attendance scholarships for

girls, free text books, stationery, uniforms, and midday meals. Seetharamu

and Ushadevi (1985, p. 68) suggested that the public has limited awareness of

these incentives.2' Bangladesh has experimented with free uniforms and is

currently disbursing scholarships to girls attending secondary schools to

defray part of their direct cost.&/ Qadir reported (1986, p.20) several

times, however, that both rural and urban households in Bangladesh felt a

midday meal also would help increase enrollments.

Some special programs for female education also have been attempted

in South Asia. One such program, which has been evaluated by Sattar (1981)

and viewed as very successful, is Bangladesh's Shawniwar movement. Although

this program was not exclusively designed for increasing female education,

that and augmenting other forms of female activity were among its major

objectives (p. 2). Shawniwar emphasizes local participation to create demand

for various governmental social services such as education (p. 1). The

statistics recounted indicate that in the Shawniwar villages the girls' share

in total enrollment was 44 percent at the primary level, a significantly

higher rate than the national average of 38 percent (p.4). Also, village

opinion leaders reported that the average enrollment of primary and secondary

N These policies started with the Second Five Year Plan and continued untilthe Fifth Five Year Plan. The current policy is universal elementaryeducation which, it is argued, will necessarily focus more on females sincetheir enrollments are lower. An evaluation study of the special program forgirls' education, undertaken by the Programme Evaluation Organization of thePlanning Commission, concluded that where the special programs were wellplanned and implemented, they did have considerable impact on femaleenrollments (UNESCO, 1980, p. 67).

See Qadir (1986, p. 83) on the distribution of free uniforms, a policyreported to have been discontinued. Several organizations are involved in thescholarship scheme including Bangladesh Association for Community Education.Over twenty thousand fellowships have been dispersed; the donor USAID, iscurrently having the pilot project evaluated.

- 38 -

female students in the Shawniwar villages increased by more than 50 percent

after the movement beg4n (p. 29).

Local participation, apparently the key to the Shawniwar movement's

success, was also emphasized in another study on Bangladesh. In a survey to

evaluate Bangladesh's drive towards universal primary enrollment, Qadir (1986,

p.18) noted that villagers were suspicious of corruption in the way contracts

were issued for building schools and other social infrastructures. The

villagers were willing and believed they were able to participate in building

such infrastructures themselves. A

Two experimental projects have highlighted the special importance of

flexible school hours for encouraging female enrollment. The idea is that if

hours for schooling do not conflict with the time girls are needed for

domestic chores, the opportunity cost of female schooling for the family would

be reduced .r eliminated. Naik (1982, pp. 152-172) reported that in a village

school project near Pune in Maharashtra State in India, the key feature was

holding classes between 7 and 9 o'clock in the evening after household chores

and dinner. The project had parental support, and the community provided

rent-free accommodations. Teachers were local primary school graduates with

some secondary education, intensively trained for one week after every six-

week period. Learning was based on small-group teaching, with peer teaching

heavily encouraged. In this accelerated program, flash cards were used for

word recognition. Within one year, 75 percent of the children in the school

could read fairly well, write a little, and do the expected arithmetic. The

dropout rate was much lower than average. Although marriage or betrothal

still proved to be one of the main reasons for dropping out, 8 percent of

girls who dropped out did so to enter a regular school (p. 169).

Junge and Shrestha (1984) have reported on a similar project aimed

at low-caste girls in Nepal. School took place from 7:30 to 9:30 in the

morning-- before household chores began. Also like the Indian project, this

W See also UNESCO (1980, p.18) on the provision of low cost schooling builtwith community participation.

- 39 -

one recruited and trained local teachers, and students started reading by

learning whole words from their own life experience by using cards, rather

than by memorizing the alphabet; enrollees were expected to read at the third

or fourth class level in one year. Some girls did drop out from the project,