Front Cover
 Title Page
 Table of Contents
 List of figures and tables
 List of acronyms
 Executive summary
 Chapter 1: Introduction: Women...
 Chapter 2: The impact of women's...
 Chapter 3: Women producers' contributions...
 Chapter 4: The consequences of...
 Chapter 5: Conclusions and selected...
 Back Cover

Group Title: Technical reports in gender and development ;no. 1 / 1989
Title: Making the case for the gender variable
Full Citation
Permanent Link: http://ufdc.ufl.edu/UF00078688/00001
 Material Information
Title: Making the case for the gender variable women and the wealth and well-being of nations
Series Title: Technical reports in gender and development
Physical Description: xx, 115 p. : ; 28 cm.
Language: English
Creator: Blumberg, Rae Lesser
Clark, Mari H
United States -- Agency for International Development. -- Office of Women in Development
Publisher: Office of Women in Development, U.S. Agency for International Dvelopment
Place of Publication: Washington D.C
Publication Date: <1989>
Subject: Women in development   ( lcsh )
Women -- Economic conditions   ( lcsh )
Women -- Social conditions   ( lcsh )
Genre: federal government publication   ( marcgt )
bibliography   ( marcgt )
Bibliography: Includes bibliographical references (p. 105-115).
Statement of Responsibility: Rae Lesser Blumberg ; edited by Mari H. Clark.
General Note: "October 1989."
General Note: "PN-ABC-454"--P. <1> of cover.
General Note: "WD.21.13.01"--Label on p. <1> of cover.
 Record Information
Bibliographic ID: UF00078688
Volume ID: VID00001
Source Institution: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: aleph - 002765047
oclc - 31418916
notis - ANP3076

Table of Contents
    Front Cover
        Page i
    Title Page
        Page ii
    Table of Contents
        Page iii
        Page iv
        Page v
    List of figures and tables
        Page vi
    List of acronyms
        Page vii
        Page viii
        Page ix
        Page x
        Page xi
        Page xii
        Page xiii
        Page xiv
    Executive summary
        Page xv
        Page xvi
        Page xvii
        Page xviii
        Page xix
    Chapter 1: Introduction: Women and the wealth of nations
        Page 1
        Page 2
        Page 3
        Page 4
        Page 5
        Page 6
    Chapter 2: The impact of women's production and control of income
        Page 7
        Page 8
        Page 9
        Page 10
        Page 11
        Page 12
        Page 13
        Page 14
        Page 15
        Page 16
        Page 17
        Page 18
        Page 19
        Page 20
        Page 21
        Page 22
        Page 23
        Page 24
    Chapter 3: Women producers' contributions and constraints
        Page 25
        Page 26
        Page 27
        Page 28
        Page 29
        Page 30
        Page 31
        Page 32
        Page 33
        Page 34
        Page 35
        Page 36
        Page 37
        Page 38
        Page 39
        Page 40
        Page 41
        Page 42
        Page 43
        Page 44
        Page 45
        Page 46
        Page 47
        Page 48
        Page 49
        Page 50
        Page 51
        Page 52
        Page 53
        Page 54
        Page 55
        Page 56
    Chapter 4: The consequences of women's education: A Cornucopia of human capital
        Page 57
        Page 58
        Page 59
        Page 60
        Page 61
        Page 62
        Page 63
        Page 64
        Page 65
        Page 66
        Page 67
        Page 68
        Page 69
        Page 70
        Page 71
        Page 72
        Page 73
        Page 74
        Page 75
        Page 76
        Page 77
        Page 78
        Page 79
        Page 80
        Page 81
        Page 82
        Page 83
        Page 84
        Page 85
        Page 86
        Page 87
        Page 88
        Page 89
        Page 90
    Chapter 5: Conclusions and selected policy implications
        Page 91
        Page 92
        Page 93
        Page 94
        Page 95
        Page 96
        Page 97
        Page 98
        Page 99
        Page 100
        Page 101
        Page 102
        Page 103
        Page 104
        Page 105
        Page 106
        Page 107
        Page 108
        Page 109
        Page 110
        Page 111
        Page 112
        Page 113
        Page 114
        Page 115
    Back Cover
        Page 116
Full Text

NO. 1/1989
TechnicaRpot in Gender and D lopment

I Making the Case for the Gender Variable :
Women and the Wealth and Well-being
of Nations


Office of Women in Development
Agency for International Development


Making The Case For The Gender Variable:
Women and the Wealth and Well-Being of Nations

Rae Lesser Blumberg
University of California, San Diego

Edited by Mari H. Clark

Office of Women in Development
U.S. Agency for International Development
October 1989

The views and interpretations expressed in this report are those of the author and should not be
attributed to the Agency for International Development.



List of Figures ..................................................... vi

List of Tables ................... ................................. vi

List of Acronym s ................................................... vii

Forew ord . .. . .. . . .. .. . .. . .. .. .. ix

Preface .. . . . . . . . . . . . . . xi

Acknowledgements ................................................. xiii

Executive Summ ary ................................................ xv

1. Introduction: Women and the Wealth of Nations ....................... 1

1.1 Examples of Women's Contributions to National Economic Growth ............ 2
1.2 An Overview of Women's Contributions to the World Economy .............. 4

2. The Impact of Women's Production and Control of Income .................. 7

2.1 Women's Use of Income for Food and Children's Welfare .................. 8
2.2 Effects of Female Control of Income on Decision-Making .................. 11

2.2.1 Women's Income and Fertility Decisions ........................ 11
2.2.2 Women's Income and Economic Decisions ....................... 13

2.3 Women as Providers: Their Response to Incentives ..................... 14
2.4 Ways Development Suffers When Women's Returns to Labor Are Ignored ....... 15

2.4.1 The Cameroon SEMRY I Irrigated Rice Project ................... 16
2.4.2 Other Examples From Africa ................................ 17

2.5 Male/Female Farmers' Responses to a New Road in Cameroon .............. 18
2.6 Neglect of Women Farmers' Micro Level Incentives: Implications for the
African Food Crisis ............................................ 20

3. Women Producers' Contributions and Constraints ........................ 25

3.1 Women's Importance as Producers ............................... 25

3.1.1 Food and Agricultural Labor ................................ 25
3.1.2 The Informal Sector ..................................... 25

3.2 Women's Effectiveness as Producers .............................. 25

3.2.1 Women Farmers' Performance ............................... 25
3.2.2 Women Microentrepreneurs' Performance ........................ 27

3.3 Women's Production Constraints in Low Resource Farming ................. 30

3.3.1 Women's Time Constraints From "Drudgework" .................. 31
3.3.2 Women's Limited Access to Agricultural Extension, Training, Credit and
Inputs .. . . . . . . . . . . . 33

3.4 Easing the Constraints on Women's Productivity ........................ 34

3.4.1 Women Turn Eased Constraints Into Income Generation .............. 34
3.4.2 Computer Simulation of Development Solutions for Yemen ............ 36
3.4.3 Steps Toward Reaching Women Farmers With Extension .............. 39 Women Extension Agents-The Key to Reaching Women Farmers? 40 Women Farmers as Extension Clients-How Much Progress? ...... 47

3.5 African Market Women: A Case Study in Women's Economic Importance,
Effectiveness, and Constraints ................................... 49

3.5.1 Women's Importance and Effectiveness in Marketing ................ 49 Women Traders in Nigeria ............................ 49 Market Women in Ghana ............................ 52 Market Women Elsewhere in Africa ...................... 53

3.5.2 Constraints on Women's Marketing and Trade: Who Pays? ............ 53

4. The Consequences of Women's Education: A Cornucopia of Human Capital ...... 57

4.1 Comparison of Female and Male Access to Education ................... 58

4.2 Age of Marriage: A Prelude to the Education-Fertility Link ................ 60

4.2.1 Evidence From the World Fertility Survey ....................... 60
4.2.2 Schildkrout's Study of Schoolgirls in a Muslim City ................. 61
4.2.3 Effects of Scholarships on Bangladeshi Girls' Marriage Patterns .......... 61

4.3 The Relationship Between Education and Fertility ....................... 65

4.3.1 Cochrane's Synthesis ..................................... 66
4.3.2 Major Patterns From the World Fertility Survey ................... 67
4.3.3 Schultz's Data on the Education-Fertility Link in Thailand ............. 69
4.3.4 Some Speculation on High Fertility in Africa ..................... 70

4.4 The Link Between Education and Lower Infant and Child Mortality ........... 73

4.4.1 Colclough's Overview: Setting the Stage ........................ 73
4.4.2 The W FS Data .............. ......................... 73
4.4.3 Caldwell's Research Among the Yoruba of Western Nigeria ............ 73
4.4.4 LeVine's Research in Urban Mexico ........................... 74
4.4.5 A Finding From Rosenzweig and Schultz's Research in India ........... 76

4.5 Women's Education and Child Health/Nutrition ........................ 76

4.6 Education as a Determinant of Women's Labor Force Participation ............ 77

4.6.1 The Undercounting of Women in Standard National Statistics ........... 77
4.6.2 Ram's Review of Gender Differences in the Education-Labor Force Link .... 78
4.6.3 King's Study of Female Labor Force Participation in Peru ............. 78
4.6.4 Women's Education and Employment: The View From the WFS ........ 80

4.7 Education and Earnings: An Incomplete Sketch ........................ 83

4.8 Some Preliminary Regressions Involving Male/Female Disparities in
Educational Access ........................................... 86

5. Conclusions and Selected Policy Implications ............................ 91

5.1 Findings: Women and the Wealth and Well-Being of Nations ............... 91

5.1.1 Women's Economic Contributions ............................. 92
5.1.2 The Value of Female Education .............................. 94

5.2 Policy Implications: Gender and the "Development Equation" .............. 95

5.2.1 Gender-Disaggregated Tracking and Adaptation of Development Efforts ..... 96
5.2.2 "Women May Be the Single Most Cost-Effective Available Resource to
Alleviate the African Food Crisis" ........................... 97
5.2.3 The "Lessons Learned" From the Most Successful Microenterprise Credit
Projects Must Be Heeded, and Women Recognized as Equal or Better Credit
R isks . . . . . . . . . . . 98
5.2.4 "A Dollar Spent on Boys' Education Must Be Matched by a Dollar Spent
on Girls' Education or Soon Be Lost to the Country by Females' Higher
Fertility" .................................. ........... 98

Appendix Tables From the World Fertility Survey ............................ 101

Bibliography .................................................... 105


Figure Page

1 Relationship Between Women's Industrial Employment and Macroeconomic Growth .. 5

2 Economic Trends in the Yemen Arab Republic ....................... 41

3 The Ga Trading Hierarchy (Ghana) ................................ 54

4 Mean Number of Children Ever Bom to Ever-Married Women Aged 40-45 Years 68

5 Current Work, By Years of Education-Selected Countries ................. 82

6 Partial Regression Coefficients of Variable Indicating Work In a Modem
Occupation, By Gross Enrollment Ratio for Females, 1975 ................. 84


Table Page

1 Effect of Wife's Contribution to Household "Pool" on Her Fertility Leverage ..... 12

2 Marketable Surplus as Percent of Crops Grown ........................ 24

3 Factors Influencing Maize Yields/Acre ............................. 26

4 Men's/Women's Contributions To Economic Activities ................... 32

5 Approximate Daily Labor Time Required For Major Domestic Tasks
Per Average Rural Household ................................... 38

6 Male & Female Extension Personnel In African Agricultural Programs .......... 40

7 Proportion of Girls vs. Boys, 1950-1985, lst-3rd Educational Levels ........... 59

8 Female Enrollment as a Percent of Male, Developing Countries, 1980 .......... 62

9 Regressions of Three Measures of Female Educational Access/Disparity ......... 87



























Association for Development of Microentrepreneurs, Incorporated

Agricultural Development Project

Agency for International Development

Basic Research and Implementation in Developing Education Systems

Children Ever Born

African French Community

Disparity Index

Extension Agents

Economic Commission for Africa

Export Processing Zone

Food and Agriculture Organization

Gross Domestic Product

Gross Enrollment Rate

Gross Enrollment Rate for Females

Gross National Product

High Yield Varieties

International Fund for Agricultural Development

International Labour Organization

International Research and Training Institute for the Advancement of Women

Less Developed Country

Livelihood, Employment and Income Generation

Labor Force Participation Rates



Peruvian Living Standards Survey

RDA Recommended Daily Allowance

SIMME Urban Microenterprise Multiplier System (Guatemala)

SMAM Singulate Mean Age of Marriage

TFR Total Fertility Rate

UN United Nations

UNIDO United Nations Industrial Development Organization

UNESCO United Nations Educational, Scientific and Cultural Organization

UPE Universal Primary Education

USAID United States Agency for International Development

VEWs Village Extension Workers

WFS World Fertility Survey

WID Women in Development

YAR Yemen Arab Republic

2SLS 2-stage least square


A.I.D. was among the first donor agencies to recognize the central role of women in
economic and social development. A.I.D.'s on-going efforts to incorporate consideration of gender
as a critical variable in the development formula are serving as a model to others. The Agency has
supported a wide array of research, technical assistance, training, and information sharing on this
topic over the years, and has begun the sometimes difficult task of gathering and assessing the
impact of improved integration of gender consideration in all phases of the economic development
programming cycle. One effort to document these efforts is presented in this report.

While using and expanding women's productive capacity is seen as a critical, and to some,
necessary condition for sustainable, broad based economic growth and social progress, documenting
clearly the real-world experiences that support this hypothesis is complex and confusing. The
information and data are disparate, of varying quality and statistical purity, and housed in often
incompatible software in organizations that don't usually communicate. The work of attempting to
make consonant the panoply of information and data to make a statement are to be commended.
The findings and conclusions of the study will be of interest to both scholars and practitioners in
the fields of economic development as well as women in development. It seeks to support the
hypothesis that attention to people's gender is a necessary element in meeting project objectives and
contributes significantly to achieving overall development goals.



In 1970, in Woman's Role in Economic Development, Ester Boserup wrote that a lack of
basic information prevented her from drawing some conclusions in her examination of women's
involvement in and contribution to economic development. Her hope was that this book would
"...help to stimulate further study, including the provision of fresh statistical evidence." Today,
nearly 20 years later, the Office of Women in Development finds that it must reiterate this plea in
its own preface. This is not to say progress has not been made in gathering better and more
gender-disaggregated statistics and in the integration of women into national economies. Rather, it
reinforces the continuing need for new and innovative data gathering and assessment activities to
support these processes.
Dr. Rae Lesser Blumberg was given the enormous task of examining developing country
studies and statistics and documenting the benefits of integrating women into national economies.
The result is a document that overflows with rich, diverse examples that clearly "make the case" for
considering gender in economic development. Her case examples, lessons learned, and sectoral
analyses alone make this report a valuable addition to the growing body of knowledge about
women's economic activities in developing countries.
The parallels with Boserup's book continue as neither had the luxury of being able to
compile their own statistics. This report is basically a comprehensive "roundup" of what was
already out there in late 1988 that could be used to substantiate the fact that women's contributions
to national economies are large and rapidly growing larger. Ideally, Blumberg would have found
consonance among the research; in reality, she found less-than-perfect data upon which to base
statements about causal relationships. Thus, in the document's parts lies a revelation about the
weaknesses of our data and information; while as a whole when brought together, its strength is
apparent. The wealth of examples compiled in this report will help to identify these weaknesses
and focus on where rigorous data gathering remains to be done.
Blumberg had to work with what was out there; her assignment was to gather together and
to clean up the data so decision-makers and researchers would have something to work with. Our
challenge now is to recognize what needs fixing and to identify indicators that will facilitate the
gathering of better or more appropriate data for future planning, analysis, and tracking purposes.



This monograph was bor from the best kind of marriage between an action-oriented agency
and academia. The Agency for International Development's Office of Women in Development is
charged with promoting the integration of women into A.I.D.'s development assistance programs
and projects. As a pro-active entity, it continually works to enhance the case for "taking the
gender variable into account" in all phases of A.I..'s development activities, and has been doing
so with steadily increasing success since 1975. It continues to deepen our understanding of why it
is good for a country's development, and not just its women, to fully include them into both the
activities and the benefits of planned development.
In the summer of 1988, the Office of Women in Development (hereinafter, WID Office) was
asked to provide input for a major report being prepared by A.I.D. for Congress. Ron Grosz, who
had been introduced to my work on gender and development through his WID Office colleague,
Bruce Horwith, asked me to undertake what was originally conceived of as a technical report aimed
at two purposes. First, it would serve the immediate objective of the pending report to Congress
and second, it would address the larger goal of presenting the "state of the art" of what was known
about the benefits of integrating women into national economic development. Through the vision
of Kay Davies, head of the Office since 1984, and Ron Grosz' strong and unflagging
encouragement, the report began to expand in scope.
My academic work involves theory as well as research, and I had been working on a theory of
gender and development as the next step beyond my "general theory of gender stratification." I
also was working on a book, Women and the Wealth of Nations, that ties together all my empirical
work on gender and Third World development with my evolving theories. This provided me with
a running start to consider the benefits that accrue to women, their families and ultimately, their
nations, as the result of their productive activities-especially those that generate income under
female control. Ron Grosz encouraged me to expand my approach beyond the economic to
consider human capital as well. Soon, sparked by challenging intellectual exchanges with Ron and
his WID Office colleague, Tulin Pulley, and aided by the first rate logistical and research support
of Laura Raney (then a special assistant in the WID Office), I was delving into terrain I never
before had explored systematically. The consequences that flow from educating girls and women, I
learned, were at least as felicitous as those that emerge from women's production and control of
income-and easier to justify to those uncomfortable with the idea of women as valuable economic
producers-and income managers-in their own right. In short, there was a strong case to be made
not only for women's contribution to wealth but also to well-being.
"Making the case for the gender variable" also was facilitated by the help I received from
everyone in the WID Office. I would like to expand my roster of thanks to include Phillip Boyle,

Mary Herbert, Donna Sidiqui and Jeffery Franklin. Also, it was Ron Grosz who put me in touch
with Scott Moreland of the Research Triangle Institute, who, along with Emesto Cuadra from the
Harvard Institute of International Development, was, by happy coincidence, compiling a data base
on female education for a larger A.I.D. project known as BRIDGES. "Making the case" for
women's education was much advanced thanks to the regressions he ran for me in conjunction with
his colleague, Luis Crouch, and assistant, Luis Cubeddu.
As the report evolved into a full-fledged monograph or short book, two excellent WID Office
editors successively entered the picture: Mari Clark and Kathleen Moran. Mari Clark's
streamlining of my prose transformed my draft into a much more inviting and accessible work, and
Kathleen Moran has turned it into a finely formatted and finished volume.
In addition, I want to thank the many authors of draft reports and works in progress who
discussed their findings and shared their unpublished materials with me, and the many colleagues
and friends who work in Women in Development who have shared their thoughts and writings.
Naming you would present a list about half the length of the bibliography-in which many,
although not all of you, are represented.
Finally, much of the research and writing took place in San Diego, not Washington. I would
like to thank Huma Ahmed Ghosh who did her usual top-notch job in helping me with the
bibliography, and all the University of California, San Diego colleagues who read and reacted to at
least one version of the Executive Summary and/or parts of the draft: Bennett Berger, Mary
Freifeld, Joseph Gusfield, Bennetta Jules-Rosette, Martha Lampland, Lora Lueker, Gershon Shafir,
Barbara Stewart, Carlos Waisman and Jackie Wiseman.


1. Introduction: Women and the Wealth of Nations

A case is made for gender as an essential and critical variable in the "development equation."
Empirical evidence demonstrates that:

Women worldwide make major contributions to the wealth of nations; and

The use and expansion of women's productive capacities is a necessary condition for social
and economic progress.

The discussion focuses on two intertwined ways in which women contribute to the economic
and human resource "wealth" of nations. These are via:

Women's productive activities, which, in many developing countries, contribute
significantly to the food supply, the large informal sector, service and farm labor forces,
and, in some, to the export manufacturing labor force; and

S Women's education, which can lead to lower fertility, better family health, reduced infant
and child mortality, higher formal labor force participation, and greater economic growth.


(1) According to recent estimates, the growing formal labor force participation and rising
female/male earnings ratio of U.S. women between 1890 and 1980 were associated with a
growth in national income per capital that exceeded the growth in male earnings by 28
percent. During this same period, women's teaching for low wages made possible the
mass education that added another 12-23 percent to national income.

(2) In the LDC's specializing in export manufacturing, there is a strong relationship between
increase in female industrial employment, the growth of manufactured exports, and national
economic growth.


Overall, women are estimated to comprise 41 percent of the measured labor force in developed
countries and 32 percent in developing ones. These statistics, however, are now known to
undercount women's productive activities. Women in developing countries play an even greater
role in the sectors of the economy that are poorly measured by national statistics-the urban
informal sector, low resource farming and marketing, and unpaid family productive labor.
Moreover, women's unpaid household labor, if given economic value, would add an estimated four
trillion dollars, or about one-third, to the world's annual economic product.

2. The Impact of Women's Production and Control of Income

A great deal of data support the argument that the development impact of women's productive
activities is heightened where they generate income under female control. The predominant
development model of the household, however, precludes considering gender-disaggregated control

of income, since it treats the household as a shared enterprise described by a single production
function. Therefore, a critique of this "black box" model of the household is presented and
supported by evidence of the widespread existence of an "internal economy of the household" with
a distribution of labor and resources based on age and gender that is not necessarily equitable.
These dynamics vary cross-culturally. But everywhere, it makes a great difference which person in
the household receives information, who does the work, and who gets the income. This has far-
reaching consequences for the success or failure of development efforts at both micro and macro


Many studies support the proposition that income under female control (relative to male-
controlled income) is a major determinant of women's overall status. Moreover, numerous studies
also support hypotheses that income under women's control:

Is most often spent for children's nutrition and the family's "basic human needs,"
especially among women with provider responsibilities; and

Generally enhances women's decision-making power within the household regarding
childbearing, economic issues, and domestic/family welfare.

Additionally, women with provider responsibilities tend to:

Allocate their labor toward activities that put income and/or food under their direct control
and, when feasible, away from activities that do not, even if the latter are more profitable;

Respond more readily than their male counterparts to easing of constraints on own-account
production or modestly increased incentives. (This may be largely because many of these
women urgently need income, but earn less and have fewer resources than men-thereby
having lower opportunity costs.)

Empirical evidence from a wide array of countries provides support for these hypotheses. For
example, studies of the SEMRY I irrigated rice project in Cameroon and various other development
projects in Africa present cases in which women were expected to contribute labor but the direct
returns went to their husbands. In all cases women provided less labor than expected and the
projects suffered. A study of the effects of a new road on a Cameroonian village showed that
women increased their production of own account perishable food much more than men, even
though men's crops brought a sharply higher rate of return.


These findings have serious implications for the food crisis in Africa. African women farmers
could be the single most cost-effective available resource to alleviate this crisis, since they raise as
much as 80 percent of the locally grown food crops. In most ethnic groups, men and women have

at least partially separate income streams and spending obligations. Women typically have heavy
responsibilities to provide for their children and thus need income and/or food under their control.
Accordingly, the model of the household as a unitary pooling unit fits poorly here. Yet it has
guided most development planning, often with negative results. Women are almost always
bypassed by extension, training, inputs, and credit programs. Most food crop development projects
have failed to target women producers. Almost all ignore women's incentives and may unwittingly
undercut their income-often with negative consequences for the project, the women, and their
families. These practices make inefficient use of scarce resources and appear to be an important,
albeit unheralded, factor in the African food crisis.

3. Women Producers' Contributions and Constraints

FARMING AND THE INFORMAL SECTOR: Women are estimated to produce more than
half the food in developing countries. Considering the full farming system (not just the
measured labor force), the UN regional commissions calculate that women do 60-80 percent of
the agricultural labor in Africa and in Asia, and 40 percent in Latin America. The rapidly
growing informal sector in developing countries is absorbing an estimated 40-70 percent of
urban workers, with women predominating in many regions.

WOMEN FARMERS' PERFORMANCE: One econometric study has found that Kenyan
women farmers obtained higher crop yields than males, when women's more limited access to
credit, education, fertile soil, commercial fertilizer, extension, etc., was controlled statistically.
Several less quantitative studies also have found women producing as much as or more than
comparable men. In actual practice, however, few women farm with resources comparable to
men, and their production lags behind men's.

WOMEN MICROENTREPRENEURS' PERFORMANCE: Various quantitative studies of
informal sector, microenterprise credit projects in Latin America and Asia indicate that women
are as good as or better credit risks than men. Further, a study in the Dominican Republic
found that women's clothing/textile businesses were growing faster than men's on several
parameters (e.g., sales, employment). In general, the more successful microenterprise credit
projects have eliminated constraints that prevent women in particular, and poor people in
general, from getting aid.

RURAL WOMENS' PRODUCTION CONSTRAINTS: In low resource agriculture, there is
no comparable reduction of constraints. Women labor under limitations to their productivity
such as the time required for routine domestic tasks (fetching water and firewood, processing
crops and cooking), as well as inadequate access to extension and other farming aids (credit,
inputs, etc.).

EASING THE CONSTRAINTS: Reducing these constraints is a means to tap women's
productivity for development.

Time saving: for example, a computer simulation projected that several looming economic
crises in the Yemen Arab Republic could be averted by reducing the time rural women in
the average household spend fetching water and fuel/wood and cooking from 11.5 to 1.7
hours/day-just through improved water supplies and provision of cooking gas. This
would increase women's agricultural productivity in an economy with declining agriculture
and rising food imports. It would also provide girls time to attend school. Some girls
could then become teachers to replace the foreigners who now teach.


Extension, Credit, and Inputs: Aside from three S.E. Asian nations, only since the mid-
1980s have a few other countries (mainly in Africa) begun to target women farmers. The
number of female extension clients now is growing there. Women farmers have been able
to work well with male extension agents (as well as the few female agents) except in areas
of female seclusion. But many women clients-who have almost no access to formal
credit or subsidized inputs-cannot afford to buy all of an extension "package."
Accordingly, production increases may be inhibited when the new practices are only
partially adopted.

Extension planning must take into account women farmer's special skills (e.g., knowledge of
food crops, ability to share knowledge and inputs with other women) and also their special
constraints (e.g., limited time and resources, less and poorer land, gender role ideals that restrict
movement and assertiveness). Cultural practices also must be considered (e.g., in Africa there is a
widespread preference for extension contact in women's groups rather than individually).

WOMEN IN MARKETING: Females often play important roles at all levels of agricultural
commodities distribution, particularly in West Africa. Ghana and Nigeria have long traditions
of women filling important roles in trade. In Ghana, however, recent government policies
severely restricted women's trading activities. This has damaged the country's food distribution
system and its economy. In many countries, women street sellers, especially food vendors, also
suffer from government regulatory pressure which may have reduced food availability in those
nations as well.

In sum, female production and income affect wealth and well-being at levels ranging from the
woman and her family to her nation and even region.

4. The Consequences of Women's Education

There is worldwide evidence that the education of women is associated with (1) a later age of
marriage; (2) increased contraceptive usage; (3) lower fertility (although in some countries, those
with partial primary education have slightly higher fertility than those with no education); (4)
dramatically reduced infant and child mortality; (5) improved child nutrition and general family
health; (6) greater participation in the waged, modem sector labor force; (7) higher earnings; and
(8) increased national development as measured by GNP.
The first seven indicators almost always occur later in the life course than education, so it is
plausible to conclude that female education plays a causal role. Indeed, the evidence indicates that
mothers' education almost invariably has a stronger effect than fathers' (or "education" not
disaggregated by gender) on lowering fertility and infant mortality and improving family health.
New evidence that reductions in fertility enhance national income growth further underline the
importance of giving females the educational and economic resources that facilitate their lower
fertility. The last indicator, national growth and development, is associated with higher levels of
female education and a lower disparity in the proportion of females relative to males in school.
There is not enough evidence at the moment, however, to untangle the direction of causation in
what is clearly an interactive, synergistic process. Nonetheless, education, per se, is a recognized
predictor of national growth.

The enrollment of females in school has increased from 95 million in 1950 to 390 million in
1985 and the disparity between the proportion of boys vs. girls in school has shrunk a little.
However, the gap in the numbers of girls in school, compared with boys, is growing-as are the
numbers of female illiterates and school age girls not in school. Thus, even though education is
the area where females have made the most progress since World War II, the picture is not an
entirely positive one.

5. Conclusions and Selected Policy Implications

The most general conclusion is best expressed by Sivard: "What is good for women is also
good for the society at large." The material presented makes a strong case for the macro and
micro level contributions of women to the wealth and well-being of nations. Even greater future
gains in women's productivity are possible if present constraints to their production, marketing, and
education can be reduced.
Given time and space limitations, only four policy implications are discussed, although more
could be drawn from the data.

Gender must be tracked in projects, programs, and policies, and these should be adapted to
overcome special constraints on women's productivity, participation, and access to benefits.
For projects, gender-disaggregated data should be collected at the baseline, monitoring, and
evaluation phases, so timely adaptations can be made.

Attention to women farmers' skills, incentives, and constraints could be the single most
cost-effective approach to alleviating the African food crisis.

Strong efforts should be made to identify and serve women in microenterprise credit
projects. The "lessons learned" from the most successful of these projects, particularly the
fact that women are as good as or better credit risks than men, must be applied to policies,
programs, and projects.

Female education should be given higher priority, but not in a "zero sum game" manner
which detracts from male education. A dollar spent on boys' education and not matched
by a dollar for girls' education may be lost to a developing nation because of the cost of
the higher fertility of those girls as well as the poorer health and lower infant/child
survival rates of their families and their own reduced productivity.

In summary, despite some gaps in our knowledge, we already know enough to call for and
implement the inclusion of gender as essential and critical to the "development equation."


Introduction: Women and the Wealth of Nations

Few policy issues have had as rapid a rise as that of Women in Development (WID)-
specifically, the integration of women into Third World economic development. It was only in
1970 that Ester Boserup, a Danish economist, published the pathbreaking book, Woman's Role in
Economic Development, that first brought this issue to world attention. In a mere three years, the
United States Foreign Assistance Act of 1973 had been amended to require that henceforth, U.S.
development assistance:

shall be administered so as to give particular attention to those programs, projects and activities
which tend to integrate women into the national economies of foreign countries, thus improving
their status and assisting the total development effort (Section 113, better known as the "Percy

The United Nations proclaimed 1975 as International Women's Year, and sponsored the first
world conference on women in Mexico City. Women's role in development was a major focus-as
it was in the U.N.'s Decade for Women (1976-1985). Within that decade, virtually all the major
international development donors and multilateral development banks and agencies adopted policies
calling for the integration of women into the activities and benefits of economic development.
Despite the meteoric rise of the integration of women in development as a proclaimed policy,
however, implementation has proceeded at a much slower pace.
One reason for the lag has been the persistent perception by many development policymakers,
practitioners and academics that women are not active agents in development-and that resources
targeted to them will have little impact beyond the women themselves. To the contrary, this
monograph argues that enhancing women's productive activities, income, and education results in a
"multiplier effect" that brings benefits to every level from the woman and her family to whole
nations and even regions. In other words, this monograph is aimed at "making the case for the
gender variable."
Gender is both an essential and a critical variable in the "development equation" because:

Women worldwide make major contributions to the wealth of nations; and

The use and expansion of women's productive capacities is a necessary condition for social
and economic progress.

When the gender variable is ignored in development planning, the "development equation" is
"underdetermined." Conversely, inclusion of the gender variable improves development planning
and outcomes (Anderson and Chen 1988; see also Blumberg forthcoming).

This monograph presents empirical support for these assertions, focusing on two important,
intertwined ways in which women contribute to the economic and human resource development, and
hence the "wealth," of their nations. These are via:

Women's productive activities, which often take place in the least measured sectors of their
country's economy (e.g., low resource farming, urban informal/microenterprise sector); and

The education of women, which affects health, fertility, formal labor force participation and
economic growth.

In addition, this monograph presents strong evidence that the development impact of women's
productive activities is intensified where they generate income under women's control.
The following examples serve as an introduction to the larger goal of this monograph-to make
a general case about "women and the wealth of nations" and the need for incorporating gender into
the development equation. Specifically, they demonstrate the link between women's labor and
national economic growth.

1.1 Examples of Women's Contributions to National Economic Growth

There is evidence that women enhance their nations' economic growth and income through the
amount and nature of their participation in the measured labor force.' As a first example, in the
United States, women's labor has significantly contributed to the economic growth that, from 1890-
1980, transformed the country into the world's foremost industrial power. Goldin (1986) provides
compelling empirical documentation for U.S. women's contribution to the wealth of the nation:

S By the definitions of the United States Population Census, the labor force participation rate
of prime-aged females (15-64 years old) rose from 19.6 percent in 1890 to 59.9 percent in
1980, and the female component of the labor force increased from 17 percent to 43
percent. Not only did the labor force participation rate of women expand, but the ratio of
female to male full-time earnings increased as well, from 0.46 to 0.60 over the last

The expansion of the female labor force as conventionally measured and the rise
in the female/male earnings ratio were associated with a growth of national
income per capital that exceeded the growth in male earnings by 28 percent. Had
the female labor force not expanded over this period, national income per capital
would probably have been at least 14 percent lower than it actually was (Goldin
1986, 557).

Goldin's analysis also indicates that 90 percent of U.S. women's contribution to national growth
was made between 1950 and 1980. Moreover, women's work in teaching may have provided the
basis for another source of increase in national income throughout the 20th century (Carter 1986,

SThe nature and extent of undercounting of women's economic activities in current labor force statistics is discussed
in section 4.6.

598). Had women not been willing to teach for low wages, when men generally were not, mass
education might have been too expensive to be politically feasible (Fishlow 1966, 435). The
expansion of mass education raised the stock of education per laborer. This increased real U.S.
national income from 12 percent to 23 percent over this century (Carter 1986, 598, citing Denison
1962). Thus, U.S. women, through their work in general plus the human capital created by their
teaching, have contributed formidably to the "wealth of their nation."
As a second example, the developing countries that have grown the fastest since World War II,
such as Hong Kong, Taiwan, Singapore, and South Korea, gave early and strong emphasis to the
export of manufactured goods produced with a greater reliance on women workers:

Worldwide, women in 1980 constituted 32% of the measured labor force and 26.5 percent
of the industrial labor force-up from 20 percent in 1960 (Hopkins 1983).

In fast-growing Hong Kong and South Korea, women made up 50 percent and 43 percent,
respectively, of paid manufacturing employees (Joekes with Moayedi 1987, 23, based on
the ILO Yearbook of Labour Statistics).

But in slower growing Malawi and Kenya, women formed only 4 percent and 9 percent,
respectively, of the manufacturing labor force.

And in the rapidly expanding export processing zones (EPZs), located mainly in Asia and
the Latin America/Caribbean region, women held 80 percent of the 1,000,000 jobs (UNIDO

Worldwide, there has been a strong relationship between the rate of growth of female industrial
employment, economic growth in general, and growth of manufactured exports in particular (Joekes
1986, 24).2 As in the case of mass education, women's willingness to work for low wages has
helped the growth of their countries. In the EPZs, low female wages have enhanced their
competitive advantage in the world market.3

2 There is disagreement whether these jobs help or exploit women. Joekes with Moayedi (1987) give a thorough
overview. On the negative side, harsh working conditions and health and safety hazards are fairly common. Also, 80%
of female export processing workers are under 25 (ILO/UNCTC 1985), indicating that some women are "cycled out."
Preference for young workers is stronger in electronics than garments. On the positive side, studies show that these
women generally express satisfaction with their jobs and lives (e.g., Kusterer, et al. 1981; Blumberg 1985, 1989a; Tiano
1986; Foo 1987). In most instances, income is higher than in agricultural, domestic, or informal sector occupational
alternatives. In addition, these young women, who generally have above-average education for their countries, tend to
delay marriage and/or childbearing which, in many cases, would jeopardize their jobs.

3 It may well be that developing countries which have chosen protected import substitution industrialization (e.g.,
Argentina) have more masculine, higher wage labor forces in manufacturing compared with those which have chosen
export-oriented industrialization with more female, lower wage labor forces. There is little question that the latter have
performed better since 1950.

1.2 An Overview of Women's Contributions to the World Economy

First we will examine the strongly differentiated regional patterns of women's work and
provider responsibilities. According to ILO 1985 estimates, women constituted 41 percent of the
total labor force in developed countries and 32 percent in developing nations. Since 1950, the rate
of growth of female labor force participation "has outstripped the rise in male workers by two to
one" (Sivard 1985, 12). And this refers only to the measured labor force.
There is strong regional and cultural variation in women's productive labor. Without question,
women in the Eastern European communist countries have the highest rates of labor force
participation, both absolutely and in relation to males. Most are wage earners in the formal sector.
Provider expectations, that they should contribute, are also very high.
Women in the United States, Western Europe, and the other industrial capitalist countries have
somewhat lower levels of labor force participation and provider expectations. But since about 1950,
these women have significantly increased their labor force activity. It is now the statistical norm
for married women to work in the United States and in a number of Western European nations. It
remains to be seen whether a social norm-that married women should contribute to family
sustenance-will follow. Most of women's labor force participation in these nations is in the
formal sector, though less so than in Eastern Europe. Overwhelmingly, these women work in
service jobs (e.g., 78.7 percent of U.S. women in 1982, per ILO/INSTRAW 1985, 28).
Turning to the less developed countries (LDCs), in rural Africa, women generally have strong
provider obligations. They accomplish these via low resource farming and, especially in West
Africa, small-scale trade. In urban Africa, female participation in the formal labor force is quite
Southeast Asia is another region of the developing world with traditionally high female rates of
economic activity. Women have long been involved in agriculture and, in many places, in market
trading. Now these activities are being supplemented and, in some cases, supplanted by modem
sector employment. In a number of Southeast and East Asian countries, there is a great and
increasing amount of women's industrial employment.
In Latin America and the Caribbean, women's labor force participation is increasing especially
rapidly in the urban informal sector which, since the early 1980s, has been the fastest growing
sector. In Latin America, women outnumber men in rural to urban migration, typically entering the
urban informal sector or domestic service. Those who stay in agriculture in the rural areas tend to
be involved in the ill-measured low resource sector. The undercounting of the female labor force
may be most severe in this region (see, e.g., Wainerman and Reccini de Lattes 1981; Dixon 1982,


Relationship Between Women's Industrial Employment
and Macroeconomic Growth

Growth of Women's
Industrial Employment

1985).4 While the ideal of the male breadwinner and the female housewife remains, it is
decreasingly put into practice.
Economic activity rates for women are lowest in South Asia, North Africa, and the Middle
East. In the Islamic countries, in particular, males are expected to fulfill provider obligations.
Moreover, women are restricted to a few "acceptable" occupational choices. In these regions, it is
usually only the poorest women who perform tasks that are socially stigmatized, such as agricultural
day labor and activities involving public contact with male non-relatives. Accordingly, female
economic activity tends to be undercounted by both sexes.
In short, there is dramatic regional variation in the extent to which women make measured
contributions to the wealth of their nations and are expected to contribute to the support of their
families. But, everywhere, women's contributions to national economic growth are more important
than pictured in national accounts or perceived by development planners, husbands, or even the
women themselves.
In addition to their role in the formal labor force, women in developing countries are
universally active in "domestic" activities (such as cooking, looking after family members' health,
and fetching water, fuelwood, and fodder) that are not measured in national accounts. If women's
unpaid work in the household were given economic value, it would add an estimated one-third,
or four trillion dollars, to the world's annual economic product (Sivard 1985, 5). But these
activities are not considered or measured as "economic" or "productive."
Women also predominate in unpaid activities that clearly are considered "economic," such as
subsistence food production and family labor, even though these are inconsistently and incompletely
measured in national accounts (see, e.g., Wainerman and Reccini de Lattes 1981 and Anker 1983).
To date, only Goldin's pioneering effort in the United States has quantified women's
contribution to their country's national product. Much of the remainder of this monograph pulls
together various pieces of evidence that demonstrate women's importance as producers contributing
to the wealth of other nations.

4 Data collection methodology is apparently more to blame than any attempts by women to hide the fact that they
are economically active. See section 4.6.


The Impact of Women's Production and Control of Income

The causal chains that emerge from women's production, where the resulting income is
controlled by women, include consequences ranging from micro to macro levels.5 Where a
woman's production is not unduly constrained or her incentives constricted, the consequences
generally are positive for the woman, the well-being of her family, and for more macro develop-
ment outcomes such as the rate of economic growth in a country or food availability in a region
(e.g., Africa). The opposite holds true when she is constrained or denied expected returns to her
This chapter focuses on the consequences of female control of income and the productive
activities that generate income under the woman's control. In Chapter 3, we will treat women's
importance and effectiveness as producers, as well as the constraints on their productivity.
It should be stressed that mainstream development policymakers and practitioners have seldom
considered the control of income by gender as a development variable, because they embrace the
neoclassical economics notion of the household. It is seen as an indivisible basic unit of analysis, a
"black box" for which a single production function is adequate description (e.g., Becker 1981).
From this perspective, it does not matter who brings in the resources, does the work, or spends the
money. It is assumed that, within this monolithic household, information and resources are pooled
and redistributed equitably. What is not considered is that "income under female control" might be
spent differently than "income under male control" or that this could have distinct and significant
consequences for women's status within the household and the well-being of its members.
In contrast to this view of the household, this monograph attempts to show that there is an
"internal economy" of the household based on age and gender. This is conceptualized as a
continuum ranging from domestic units characterized by almost entirely "separate purses" among
adult male and female members, to those where women have virtually no income-generating
opportunities and are indeed part of a single production function household. Evidence suggests that
the unitary household model fits poorly in much of the world. Instead, the "internal economy of
the household" model applies and its gender division of information, resources, and labor often have
far-reaching consequences for economic development at both the macro and micro levels.

5 "Micro" includes individual, household, and local community levels; "macro" levels range from multi-community to
the nation and even the region.

Thus the relative male/female control of income is a critically important variable for
development. Among the reasons are:

Women tend to devote a higher proportion of such income to children's nutrition and other
family "basic human needs," and hold back a smaller proportion of income under their
control for their own personal needs than do men.

A woman's control of income is often positively related to her say in household decisions
on fertility, economic issues (e.g., production and resource allocation decisions, especially
where her own-account activities give her competence in these spheres), and
domestic/family welfare matters (e.g., which children attend school for how long, health and
nutrition-related practices, etc.).

Relative male/female control of income and other key economic resources appears to be the
most important (although not the sole) variable affecting the overall level of gender
stratification, that is, women's status vis-a-vis men's (see Blumberg 1984 for the theory
and supporting data). This is hypothesized to hold at all levels, from the couple to the

2.1 Women's Use of Income for Food and Children's Welfare

In much of the developing world, women, especially among the poor, have substantial
responsibilities as family provisioners. This is particularly the case in female-headed households-a
large and growing category in developing countries (Buvinic, Youssef, and Von Elm 1978).
Indeed, according to Sivard (1985, 11), "Women are the sole breadwinners in one-fourth to one-
third of the families in the world."
Studies show that, where women have any responsibilities as family provisioners, even as
provisionerss of last resort," their spending patterns differ from that of men's in two significant

Women tend to contribute a higher proportion of their income to family subsistence,
holding back less for personal consumption.

Where women have provider responsibilities, it is generally the mother's, rather than the
father's, income or food production that is more closely related to children's nutrition.
This is not always the case, but evidence presented for Asia, Latin America, and Africa
indicates that it is widespread.

The following examples provide evidence of women's use of their income for family welfare:

South India: Mencher studied samples of desperately poor agricultural laborers in 10 villages
in Tamil Nadu and 10 more in Kerala. In each state, samples were random in 6 of the 10
villages, and about 48 households were sampled in each village. In India, there is such a loss
of status for a woman to do field work for pay that only the poorest do it. But their income is
crucial for their family's survival. Mencher's data reveal the following aggregate picture:
wives earned a median of 55 percent as much as their mates (mean = 58 percent); wives
contributed a median of 94 percent of their earnings (mean = 93 percent) to family subsistence,
compared with a median of only 72 percent of earnings contributed by their husbands (mean =
71 percent). Thus, since wives held back so little for themselves, their contributions to family

subsistence amounted to a median of 84 percent (mean = 92 percent) as much as their
husbands, even though they earned little more than half as much (calculated from Mencher
1988, 108, Table 2A).

Mexico City: Roldan (1982, 1988) studied 140 poor Mexican women who did garment/other
industry piecework in their own homes. In 33 of the 53 households selected for intensive
study, women and men pooled into a common pot for basic household subsistence expenses.
Wives claimed to contribute 100 percent of their earnings, while husbands put in 75 percent or
less. Since nearly half the men withheld income information from their wives, which wives
resentfully viewed as a control technique to keep them dependent, men may have retained an
even higher percentage of their income. Therefore, even though these women earned woefully
little, in 11 of these 33 households, their contributions amounted to 40 percent or more of the
total,common fund. Roldan found that in households where husbands drank heavily, they
commonly "borrowed" from the pool. But even so, by earning their own money, the women in
all 53 households were freer to spend it for their own priorities. And these were clear, as one
women noted: "Of course [working for pay] is important because if you earn your own money,
you yourself distribute it and you do not have to beg for it. You buy food, or a dress for your
daughter, the socks for your son" (Roldan 1988, 245).

Cameroon: Guyer (1980, 1988) studied two Beti farming villages where women grew most of
their family's staple crops; they earned some income primarily from petty trade. Their
husbands grew cocoa as a cash crop. As in much of Africa, men and women had both
separate income streams and separate expenditure responsibilities. Although women farmers
earned only about one-third as much as their spouses, "of total cash expenses for food and
routine household supplies, women contribute two-thirds and men one-third" (Guyer 1988, 51).
Women, it is stressed, provided this in addition to growing their family's main food crops.

The last study emphasizes women's greater earmarking of both subsistence production and cash
income for food for their families. This leads us to consider some evidence for our second
generalization, the contribution of a mother's income to her children's nutrition:

South India: In Kerala, Kumar (1978) found that mothers with gardens or income had better-
nourished children. From an initial stratified random sample of 120 households in three rural
villages, she selected a subsample of 48 desperately poor families with children aged 3-36
months; she studied these families for an entire crop cycle. All these people lived "on the
edge," that is, they were landless or nearly landless (72 percent owned under one-tenth acre).
Her regressions are complex, but show that the single largest contributor to the child's nutrition
was the presence of a home garden tended and distributed by the mother. The data also show
that there was no positive increase in child nutrition as paternal income rose. But increasing
maternal income did benefit their children's nutrition. The regressions show that it was
resources under the mother's control, her home garden, and her earnings (if she worked for
wages) that proved most important in accounting for the level of child nutrition.

Belize: Stavrakis and Marshall (1978) studied the effect of the introduction of commercial
sugarcane on women's economic roles and family nutrition in a Belize village. Sugarcane
generated quite a bit of income, but it was men who controlled and benefited from it ("...money
flowed out of the system as fast as it came in, spent on drink, trucks, travel, and purchased
female companionship. By and large, it did not benefit the women at home tending the
children and animals" ibidd., 158)). Meanwhile, production of corn and other foods declined.
Women had depended on cor for food, exchange with kin (a woman's exchange network
redistributed cor for past favors and provided food to women whose husbands had a bad crop
year), and, most importantly, food for their pigs. Pigs, women's main independent source of
income, were fed the 40 percent of the cor that was spoiled or blighted. As a result of this

change in crop emphasis, women's income fell while men's income rose. But, according to a
nutrition survey (involving a purposive sample of 59 people in 8 households who were surveyed
in both 1973 and 1974), men's higher income did not increase the generally poor level of child
nutrition. While consumption of healthy foods such as fruits, meats, and fish declined,
"consumption of soft drinks and frozen koolaid increased by 255 percent" ibidd., 161).

Rural Philippines: Senauer and associates analyzed 1983-84 longitudinal household survey
data for a random sample of about 800 rural households in three Philippine provinces. Among
these poor farmers, they discovered that husbands came closest to national recommended daily
allowances (RDA) of total calories, with 81 percent; wives averaged 78 percent and children
(aged 1-17) averaged only 64 percent. Among children, boys and children bor earlier in the
birth order got more calories than girls and children bor later. Since only 15 percent of
women and 55 percent of men in the sample were in the formal labor force, wages were
estimated for the rest, using a technique that corrects for the fact that those in the formal labor
force are not a random subsample of the population (Heckman 1974, 1979). "The empirical
results showed that as the wife's value of time (estimated wage rate) rose, both she and her
children did relatively better in terms of the intrahousehold allocation of calories...On the other
hand, as the husband's wage rose, both he and his wife did relatively better, whereas the
relative intrahousehold allocation of calories to the children declined" (Senauer 1988, 14-15).

In another analysis of the same data, Senauer and associates focused on the nutritional status of
preschool children (13-83 months). Only 26 percent of these very poor children had normal
height for age; the rest were stunted-23 percent mildly, 27 percent moderately and 24 percent
severely. Stunting was significantly more prevalent among children whose fathers had a higher
estimated wage, i.e., "The father's wage had a negative impact on his children's long-run
nutritional status...[whereas, i]n general, increases in the mother's value of time tended to
improve the nutritional status of her preschool children" ibidd, 18).

Southwestern Kenya: Kennedy and Cowgill (1987) researched the nutritional impact of the
introduction of commercial sugar into a maize area. They studied three random samples (N =
504): sugarcane farmers (N = 181), nearest-neighbor nonsugar farmers (N = 231), and
merchants and the landless (N = 92). Sugar farmers' incomes were significantly higher than
nonsugar farmers. But sugar was a "man's crop," and the extra income was devoted to
nonfood expenditures (e.g., such male spending obligations as housing and schooling). Women
continued to grow the staple crops, so, unlike the situation in Belize, food production didn't
fall. With respect to children's nutrition, they found "some evidence that income controlled by
women correlates with improved nutritional status, indicating that women are more likely to
spend on food and health care;" and that childrenrn from households headed by females
consistently have better nutritional status than preschoolers from other types of households"
ibidd., 10).

Northern Ghana: Tripp (1981) studied the factors associated with good nutrition among a
non-random sample of 187 children in a Nankane-speaking farm village. Due to uncertain
rainfall and declining soil fertility, cultivation is precarious and the area is marked by both a
pre-harvest "hungry season" and periodic food shortages. Tripp found that, given the poor crop
conditions, although everyone farms, farming variables were not associated with better
nutritional well-being. Rather, it was trading income that affected children's nutritional well-
being. Tripp notes that:

Of all the variables tested, the trading activity of the mother is the one most significantly
associated with the nutritional status of the child. In no case does a woman's trading
generate profits that are equivalent to those of the male long-distance traders, but the
relatively small amount of money that a female trader earns is translated more directly to
the nutrition of her children. The woman has complete control over her earnings, and

although her trading does not provide her with a lot of money, it does furnish a small
steady income which she can use to buy food to augment that provided by the farming
activities of herself and her husband ibidd., 19-20, emphasis added).

These examples clearly indicate that the mother's income is more important for child nutrition
and welfare (also see Carloni 1984). The implications of the examples are clear. Programs and
projects whose objectives or ultimate goals include enhanced nutrition, well-being, and food security
cannot target "the household" or "the small farmer" in an undifferentiated manner. Income and
spending changes must be treated and tracked in a gender-disaggregated manner if
development goals are to be achieved.

2.2 Effects of Female Control of Income on Decision-Making

Blood and Wolfe (1960) were the first to establish that a woman employed outside the home
had more say in a variety of household decisions than her "housewife" counterparts. Since then, a
considerable body of generally supportive empirical evidence has emerged, largely from the U.S.
(Blumberg and Coleman 1989 reviews this literature). Here, we will present evidence from several
Third World countries on how female-controlled income affects their say in (1) fertility, and (2)
economic decisions.


Curbing rates of population growth is an important concern in many LDCs and in much of the
development community. To deal with this effectively, key fertility variables must be
disaggregated by gender. For example, women's education generally has a stronger effect on
reducing fertility than that of their husbands. Similarly, household or husband's income often
increases Third World fertility (United Nations ST/ESA/SER.A/100 1987). But increases in female
income generally, though not always,6 have a negative impact on fertility. A woman's control of
cash income seems linked with her relative say in household fertility decisions, i.e., her ability to
realize her own perceived utilities (expected costs vs. expected benefits) in a given level and pattern
of fertility. Two brief examples will be presented, both from Latin America.

Mexico City: Roldan's study of the women garment/other industry outworkers showed an
unmistakable link between the percent of the total household pool contributed by the wife and
her leverage in fertility decisions (see Table 1). Note that having more children is a decision
made by the woman alone among 50 percent of wives who contribute 40 percent or more of
the common fund; in contrast, it is the woman's sole decision among only 20 percent of those
providing less than 40 percent and whose husbands are main providers.

6 Women's fertility preferences may not always be for fewer children. In many parts of the Third World, especially
sub-Saharan Africa, women want-and seemingly need-more children than family planners would like them to have, to
help fetch water and increasingly scarce firewood and fodder, to help provide for old age, etc.

Guatemala: In 1985, Blumberg followed up a 1980 study by Kusterer, et al. (1981) of the
impact of an agribusiness enterprise on people in four research sites: three villages of poor,
largely Indian, contract growers, and the mainly Ladina women who worked in the firm's
processing plant. The villagers grew broccoli, cauliflower, and snowpeas for the subsidiary of a
U.S.-based multinational corporation. The female processing plant workers froze and packed the
vegetables for export to the U.S. The firm paid these women the minimum wage. During the
8-9 month "high season," shifts of 12-16 hours a day, 6 days a week, were not uncommon.
The result was a wage level as high as an urban male blue collar worker (150 percent-300
percent above female domestics or market traders' earnings). This transformed their lives. The
women controlled their earnings and, by 1985, the fertility impact was unmistakable. Among 15
"1980 veterans" in the 1985 sample (median age = 32.5 years) only 13 babies had been bor
between 1980-1985. These 15 women averaged only 2.2 children each and had taken control
of their fertility: 7 said they will not have any more children (at median age = 37, mean = 2.3
children). In contrast, in 1985, 20 women from the only contract grower village with a
substantial Ladina population (Patzicia) averaged 5.2 children at median age 33.5. Even though
half of these women helped their husbands in the fields, the company's check was for the man.
When asked about further fertility, Patzicia women often replied: "I don't want any more but
my husband does so I'll have to continue" (Blumberg 1985, 1989a).

Table 1: Effect of Wife's Contribution to Household "Pool"
on Her Fertility Leverage

Wife's contribution Use of Have more
to "pool" contraceptives children

1. >40% (N = 11)
wife's decision 50% 50%
joint decision 40% 40%

2. <40% (N = 19)
wife's decision 40% 20%
joint decision 53% 68%

Source: Compiled from Roldan (1982, 1988); missing percent = inferred to be husbands' sole

In summary, an increase or decrease of income in the hands of the woman can be
expected to have more direct consequences for family fertility.
But aggregated family fertility decisions constitute a country's total fertility rate. And new
evidence shows that a falling fertility rate strikingly improves a nation's development prospects. In
particular, Hess (forthcoming) provides strong evidence, from multivariate regressions of a 49-
country sample over two time periods covering the 1960's and 1970's, "that reducing fertility

contributes to economic growth in contemporary LDCs" ibidd., 174). Moreover, the positive impact
of lower fertility on national economic growth increases with time and with socioeconomic
development. His two-stage least squares (2SLS) regression estimates for the response of the
percentage change in real per capital GDP to the percentage change in the national total fertility rate
increase from -1.20 to -1.35 between the first and second time periods. Hess uses infant mortality
as the proxy for socioeconomic development and finds an even stronger impact: the 2SLS
estimates go from -1.26 in his high infant mortality subsample (corresponding to the least developed
countries) to -1.67 in his low infant mortality subsample. We will return to the link between
women's condition, fertility, and national growth in the discussion of women's education (in
Chapter 4).


Nepal: Acharya and Bennett (1981, 1982, 1983) studied 279 households in eight villages,
linking male/female economic contributions to their input on household decisions. These they
describe as "truly subsistence households, consuming more than 86 percent of what they
produce" and getting only 30.6 percent of total income through market intervention (1983, 8).
But it is the extent to which women derive income from the market economy that "gives them
much greater power within the household in terms of their input in all aspects of household
decision-making. [Conversely], confining women's work to the domestic and subsistence sectors
reduces their power vis-a-vis men in the household" (1983, ix). For example, their regression
results show that a woman's involvement in short-term employment or trading outside the
village has a significant, positive impact on her decision-making power over the household's
most important resource allocation decisions (e.g., to buy or sell land or large animals). At the
same time, greater involvement in domestic activities has a significant, negative effect on her
input into those major resource decisions (1983, 39).

Guatemala: Santiago Sacatepequez, one of the three largely Indian villages first studied by
Kusterer, et al. (1981) and then by Blumberg (1985) was unique in several ways. These
included: (1) a co-op which had a master contract with the agribusiness firm, (2) the long
involvement of its women in horticultural field work, and (3) the co-op's cash payments, given
to either men or women (with a receipt). Between the 1980 and 1985 studies, the third feature
changed in a manner that greatly affected household decision-making. Traditionally women
spent three days a week as own-account market traders in the capital and three days a week in
the family fields. But the greater labor intensiveness of the contract crops left them with less
time to do their trading. In 1980, this did not adversely affect their household position but, in
1984, the co-op switched to checks payable solely to the official member (the husband, with the
exception of a handful of widows). In 1985, a purposive sample of 17 women complained that
they had less voice in all kinds of decisions. Before, their own-account food crop trading, in
Guatemala City's large Terminal Market, gave them expertise in prices of different commodities
as well as the leverage provided by their own income. Their husbands used to listen seriously
to their recommendations of how much to plant of which crops. By 1985, their opinions were
little heeded. Their husbands opted to plant more land in the contract crops for which men
received the income. At the same time, the women worked harder but had less autonomy and
less money.

A number of staff members at the co-op worried about the consequences of what they saw as a
clear and rapid drop in women's autonomy and leverage. They noted that income was rising
with the co-op's success, and that the men were acquiring transport vehicles and, sometimes,

more land. But they did not see a corresponding increase in expenditures affecting children's
welfare, especially nutrition. They feared that, with women's decreased status and more limited
access to income, family well-being was not keeping pace (Blumberg 1985, 1989a).

This last example demonstrates the negative consequences of decreasing female control of
income. In the case of the women of Santiago Sacatepequez, the negative impact of less access to
income emerged very quickly. Elsewhere I have hypothesized that, in general, a woman's position
can fall more quickly and directly with a drop in her independently controlled economic resources
than it may rise when income under her control increases (Blumberg 1984).7 Having less access to
income may reduce women's decision-making input in everything from planting crops to purchasing
foods (section 2.4.2 gives still another example-from the Kenyan Mwea resettlement scheme).
When a woman has less money, even if her husband's income goes up and family income is not
hurt, the composition of household spending is likely to tilt away from her preferences and she will
have less income with which to redress the balance. This could mean lower proportionate spending
on children's nutrition, education, and health.

2.3 Women as Providers: Their Response to Incentives

Although there is marked regional/cultural variation, where women have provider
responsibilities, we can hypothesize that:

1. Women will tend to allocate their labor toward activities that put income and/or food under
their direct control and, where culturally feasible, they will attempt to allocate their labor
away from activities that do not, even if the latter are more profitable.

2. The farther down one goes within an economic sector the higher the proportion of women,
especially in the least measured activities such as low resource farming, informal sector
trade, and other microenterprise.

3. The poorer the household within an economic sector, the higher the proportion of their
family's subsistence that these women's economic activities provide.8

4. Poorer women with provider responsibilities may be more responsive than their male
counterparts to either easing of constraints on their production, or new incentives for

Thus far we have focused on micro level consequences of women's self-generated economic
resources, with only passing mention of more macro level effects. Now we will examine evidence
for the first and fourth hypotheses (Blumberg 1989b treats the second and third hypotheses). Our
emphasis is on macro level consequences, including the African food crisis.

7 For more detailed discussion of my general theory of gender stratification, see Blumberg (1984).

' Many of the developing world's female-headed households are found at these levels.

2.4 Ways Development Suffers When Women's Returns to Labor Are

The following African examples illustrate the first hypothesis-that women will try to allocate
labor toward activities under their own control and away from activities that are not, even when the
latter are more profitable. All the examples involve planned development projects that introduced
an intervention which increased women's work load while giving the returns to their husbands. In
terms of the prevailing development view of the household as a monolithic pooling unit, this should
have created no problems. The facts show otherwise. It is no accident that all the examples are
from rural Africa. First, it is here that many studies have found that husbands and wives are most
likely to maintain "separate purses" for most expenditures. Many structural factors encourage them
to do so. Among these are continued high rates of polygyny and, in many instances, marital
instability (see Staudt 1987). There is also the fact that women are, with some exceptions, very
economically active. They raise as much as 80 percent of the locally consumed and marketed food
crops (Sivard 1985, 5) and, especially in West Africa, are frequently active in own-account petty
trading. In addition, both genders typically have separate expenditure obligations, not only vis-a-vis
their own children and household, but also with respect to their natal kin.'
Second, despite African women's importance in the farming system, agricultural projects
typically bypass or undercut them in the allocation of extension, inputs (fertilizer, seeds, etc.) and
credit. Women farmers are also ignored in most non-African countries but almost nowhere else is
there such a wide gap between women's importance in cultivation and their incorporation into
agricultural development schemes. Much of the bypassing of women farmers can be attributed to
the often mistaken assumption that any aid or information that reaches the (male) head of
household will be redistributed internally.10 In addition, the "gender-neutral" approach of the typical
agricultural development project actually results in "gender blindness" to women's productive
activities and the returns that they get from their labor.
Third, the net result of such development efforts in Africa is often an increase in a woman's
workload, coupled with an erosion of the resource base from which she must generate food and/or

Especially where polygyny or marital instability are high, a woman has a strong need to keep up her ties with
natal extended kin. In order to do so, she must uphold her end of traditional obligations and giving.

o1 This assumption is linked to the monolithic, "black box" view of the household. But Fortmann (1982), who has
done field research in Tanzania and other African countries, found that husband-to-wife communication of extension
messages was ineffective. Koons (1988) found the same in Cameroon. An Asian example is provided by the Northeast
Rainfed Agricultural Development project in Thailand. Men were trained to carry out crop trials. But the men were not
full-time farmers. Because the wives received no training, "crops were planted incorrectly and did not grow, the power
tillers provided by the project could not be used, and a nitrogen-fixing crop intended to fertilize rice did not get planted.
Even when the husband was present, advice on crop production was incorrectly transmitted from husband to wife" (Carloni,
1987, 16, emphasis added, reporting on Blanc-Szanton, Viveros-Long and Suphanchainat, 1987).

income." Women are left to raise the bulk of locally grown food crops with little assistance and
worsening factor endowments.


Jones' (1983) sophisticated econometric analysis of this project provides a strong case for the
first hypothesis. Women's own returns to labor strongly affected how much rice they grew. Jones'
study also provides a richly documented case of how a development project suffers when women
are not given sufficient compensation for their labor. Her data (based on a random sample of 102
Massa women from three villages) demonstrate three key findings:

1. The project's long-term prospects are in doubt-since it has not been able to get farmers
to grow enough rice to provide revenues for both operating costs and amortization. Although
SEMRY I encompasses about 5,400 hectares of pump-irrigated rice fields, and both yields and
prices have been good:

Every year many fields go uncultivated for lack of farmer interest...In the 1981 rainy
season...only 3,228 hectares were cultivated, despite [a 45 percent] increase in the producer
price in 1980 ibidd., 30).

To understand why SEMRY cannot find takers for its idle fields, we must examine who works
in contrast to who benefits.

2. Women with more incentive raised more rice. Cultivating rice on irrigated SEMRY fields
was a joint conjugal activity but the husband received all the income. He then compensated his
wife as he saw fit.

In return for [her] sweat, a woman receives about 7,700 CFA [French African francs] and about
9,200 CFA worth of paddy from her husband after the harvest, or about 16,900 CFA in total.
This is less than a quarter of the net returns from rice production-about 70,000 CFA. Valued
at the market wage rates...a woman's labor contribution is worth about 31,200 CFA, so her
husband makes a profit of about 14,300 CFA from her labor ibidd., 51).

Husbands were very aware that their wives' continued participation depended on their own
generosity (i.e., the "wages" they gave them). Although wives had to raise some rice or risk a
beating, wives' rice labor-especially during transplanting season-competed directly with women's
sorghum production and other income-generating activities. In fact, one of Jones' regressions shows
that, during the peak season for rice transplanting, women had to make a one-to-one trade-off
between the number of days they work on rice vs. sorghum planting and weeding:

Days Rice = 28.57 1.04 Days Sorghum; R2 = 0.77; F = 30.93.

This unexpected negative effect of planned development projects was first documented by the Danish economist
Ester Boserup. While it occurs beyond Africa, her data emphasize sub-Saharan "female farming" systems (Boserup 1970).

Married women had good reason to prefer to work on sorghum, which was cultivated on an
individual basis by both women and men in 100 percent of project households. Although a married
woman used her sorghum primarily for feeding her family, it was her own sorghum. Not
surprisingly then, another of Jones' regressions establishes a very strong "relationship between the
amount of compensation women receive from their husbands and the number of days they worked
on their husbands' rice fields" (R2 = 0.70). Yet rice gives the better return ibidd., 52).
So we find that the few independent women, mostly widows, who grew rice on their own
account spent 24.7 days transplanting it. In contrast, married women spent only 16.4 days
transplanting their husbands' rice, a significant difference. The rest of the time they worked on
their own sorghum. In net result, households of independent women transplanted .47 hectare per
adult worker in contrast with only .31 hectare transplanted by married women.

3. Women with more incentives cultivated twice as much land in rice. There was no
difference in rice yields between independent and married women. Both obtained about 4,300
kilos/hectare. The difference was in amount of land cultivated in rice. The independent women
and those married women who received a significantly higher rate of compensation from their
husbands cultivated about double the land. Jones compared independent women with two groups of
married women-those whose households grew more than .75 piquet (1 piquet = .5 hectare) per
household worker and those whose households grew less. The independent women averaged .94
piquet per household worker. Households cultivating .75+ piquet per household worker averaged an
almost identical .95 piquet. Households cultivating less than .75 piquet averaged only half as much
(.47). The secret? Married "women who cultivated .75 piquet or more per household worker were
compensated at the mean rate of 363 CFA/day, while the married women who cultivated less than
.75 piquet per household worker received only 302 CFA/day from their husbands" ibidd., 133). The
difference is significant, as is the result, regardless of the direction of causation.
In summary, although wives were compensated above opportunity costs to work on their
husbands' rice, that payment depended on the husband's uncertain proclivities at the time of the
harvest. Given the competition with sorghum, over which women had direct control, few women
had enough incentive to spend less time on sorghum in order to "take on the cultivation of an
additional rice field" ibidd., 83). And so many of SEMRY's irrigated fields still go untilled.


Kenya-Pyrethrum Project: In an area where Kenyan women traditionally grew pyrethrum
(used in insecticide), sold the dried flowers, and kept the income, a project organized a co-op to
exploit this crop. The co-op gave payments only to formal members who were mainly men.
The disgruntled women reduced their output (Apthorpe 1971).

Kenya-Mwea Resettlement Scheme: Project management failed to provide women with
enough land to grow their own food crops although women previously had been the chief

cultivators in their home villages. Instead, the project necessitated their working long hours on
their husbands' irrigated rice. Earnings from rice, the only project crop, were paid solely to the
husband. Many women deserted their husbands. Many others held back rice from the harvest
and processed and sold it on the black market. Male drunkenness rose as women turned to
beer-brewing for income. All in all, household income rose but nutritional levels fell as
women became very dependent on their husbands for household expenditures. In
comparison with a nearby off-project village (where women farmed their own plots, supplied
much of the family food and traded the surplus on their own account), Mwea women had
considerably less say in family decision-making (Hanger and Moris 1973).

Kenya-Turkana Irrigation Project: Traditionally, Turkana men had been herders and
women had been the cultivators, who controlled the produce from their rainfed sorghum plots.
The project counted on women providing unpaid labor for their husbands' irrigated crops but
paid all cash earnings solely to the male household head. So women neglected the irrigated
project crops for their own off-project rainfed sorghum. As in Jones' Cameroon SEMRY I
study, the few women with their own irrigated plots spent less time on sorghum. Output on
the one-acre irrigated plots was so low, women had to work on off-project activities for their
family to survive. Their children's nutrition was found to be the worst in the area-even lower
than in famine relief camps receiving food rations. Male drunkenness rose as women brewed
and sold more sorghum beer in an attempt to fill their provider role (Broch-Due 1983).

The Gambia-Irrigated Rice: A project developed by male Taiwanese technicians was
targeted to men, even though women were the traditional cultivators and income beneficiaries of
swamp rice. In order to assure women's labor on irrigated rice, men blocked women from
owning and/or cultivating irrigated rice on their own account. As a result, rice production
decreased under the project as women held back their labor (Dey 1981, 1982).

In all of these examples, to the extent they were culturally able, women tended to allocate their
labor away from an activity under their husband's control and toward one from which they could
directly reap food and/or income, even if the former brought a higher rate of return. In short,
incentives for "the household" don't elicit as much of a response from women farmers as incentives
under their own control.
Let us now turn to a positive example that illuminates the fourth hypothesis, that women with
urgent provider responsibilities might be more responsive than their male counterparts to either the
easing of constraints on their production, or the emergence of new incentives. It is relevant that
females are poorer. Women almost invariably earn considerably less than men, hence their
opportunity costs are lower. Therefore, so long as the cash generated is under their control, women
may more zealously go after even a modest increase in cash than their male counterparts.

2.5 Male/Female Farmers' Responses to a New Road in Cameroon

Henn (1988), an economist, studied two Beti villages (Bilik Bindik and Mgbaba) in the cocoa-
growing region of Southern Cameroon. She found that, even though they already were working
over 60 hours a week, women were more responsive to improved marketing conditions and rising

prices for food crops than men, who worked only half as many hours. Henn's random samples
involved 40 households (21 in one village and 19 in the other).12
A major new road opened in 1982, which greatly improved marketing access for the village of
Bilik Bindik. Farmgate prices also rose. Meanwhile, Mgbaba remained quite isolated. Henn found
that both men and women in Bilik Bindik increased their output of marketed food, but women's
response was much greater:

Women in Bilik Bindik reported increasing their food production and processing labor after the
road opened...[spending] 4.6 more hours a week producing food than women in market-isolated
Mgbaba. Women's total work week was nearly sixty-eight hours in Bilik Bindik vs. sixty-one
hours in Mgbaba...[a difference] significant at the 10 percent confidence level. Women in
Mgbaba worked less than five hours a week producing food for the market while women in
Bilik Bindik spend 10.75 hours. The effects of the additional labor on women's incomes,
enhanced by the lower marketing costs in Bilik Bindik were dramatic: women from Bilik
Bindik made an average net income of $570 from sales of processed and unprocessed food,
while women from Mgbaba made only $225 ibidd., 323).

The contrast with men is sharp. Men's main source of income was cocoa. Only 24 percent of
the men sold food crops, in contrast to 94 percent of the women. But this small group of men
received an exceptionally high rate of return (an average of $3.80 per hour) for their production of
plantains and bananas, the only two food crops grown by males. In contrast, cocoa brought them
an average of $1.70 per hour for the 1984 crop. Women received only $0.71 per hour for food
crops grown on their own account (including peanuts, corn, melons, leafy vegetables, onions,
tomatoes, cassava, plantains, bananas and cocoyams).
The Bilik Bindik men devoted nearly one hour per week to increased plantain and, especially,
banana production in contrast to the Mgbaba men's average of only twenty minutes labor per week
on these highly perishable food crops (which were difficult to transport from Mgbaba to the market
without spoilage). At the same time, the men in Bilik Bindik:

...cut back on the amount of time they spent helping their wives produce food for the family.
Women in Bilik Bindik, therefore, were obliged to make up for disappearing male labor in the
subsistence sector ibidd., 324).

Given the small male sample size, these data must be seen as merely preliminary. But it seems
that men, despite an average work week of under 32 hours, proved less responsive than women,
working twice those hours, to fairly lucrative new income opportunities for marketing food crops.
The women, with a crushing work schedule double that of the men, described themselves as
overworked. The women devoted 26 hours/week to agriculture and 31 to "domestic" activities, vs.
their husbands' 12 hours/week in agriculture and 4 in "domestic" tasks. For both genders, the

12 She surveyed each married adult in both villages. In Bilik Bindik, this involved 21 households representing 23%
of total households. In the second village, Mgbaba, her 19 households represented 17% of the village total. She studied
34 men and 47 women. There were more women due to polygyny.

remaining work time was devoted to other income-producing activities. Clearly, the women's
additional labor was approaching physiological limits. Moreover, they ran the risk that their
husbands would shift more of the burden of family maintenance costs onto women as female
income rose-a pattern that was occurring, according to Henn's inference from cross-sectional data.
The women's response speaks for itself. Their need for income was so strong that it outweighed
the constraints of a daunting labor burden.
In light of both African women's importance as own-account food crop cultivators and the
seriousness of the African food crisis, it should be of critical policy importance that these African
women farmers, more than men, seem more willing to grow additional own-account food crops for
the market when their constraints are eased and farmgate prices rise. Thus far, however, the
limitations of the "black box model of the household" seem to have prevented policy makers from
recognizing that gender is a crucially important variable vis-a-vis African food production.

2.6 Neglect of Women Farmers' Micro Level Incentives: Implications for the
African Food Crisis

The next portion of the monograph links micro (individual farmers) and macro (the African
food crisis) levels. It is proposed that lack of attention to women producers and their returns to
labor is an important but neglected cause of the region's persistent food shortfalls.
Television now shows us the endstage of the African food crisis-periodic famine. This is
usually traced to such immediate precipitating causes as severe drought and/or war. But the overall
statistics are grim even in non-famine years:

According to FAO, the sub-Saharan food supply grew about 1.6 percent per annum during
the period 1970-1979, while population grew between 2 and 3.5 percent. More recent
FAO figures indicate that the situation has deteriorated further since then (Raikes 1986,

Food production per capital has fallen over the last decade by up to 15 percent in some
countries and by 6 percent over the whole of the [sub-Saharan Africa] region. Cereal
imports have risen by 117 percent and food aid by 172 percent (World Bank 1985, Annex
Table 6, quoted in Lawrence 1986, 1).

S According to a recent African survey (ECA 1983, pp. 8-9)...Food self-sufficiency ratios
dropped from 98 percent in the 1960s to approximately 86 percent in 1980. This means
that, on average, each African had about 12 percent less home-grown food in 1980 than 20
years earlier (Hyden 1986, 11).

It would seem reasonable to suppose that learned discussions of the African food crisis would
at least acknowledge women's crucial and well-documented role as producers of up to 80 percent of
the locally consumed/marketed food (e.g., Sivard 1985, 5, 17). But a look at two of the most
recent such analyses, Mellor, Delgado, and Blackie 1987 (in the "mainstream" development

paradigm), and World Recession and the Food Crisis in Africa, edited by Lawrence 1986 (in the
more radical paradigm) shows that this is not the case.
Their discussions of the causes of the recent African food shortfalls are complex and cite many
factors. One finds many references to "peasants" and "producers" but little awareness of the
division of labor and resources by gender. Nor is there more than an occasional mention of the
gender of those growing most of the food and doing most of the farm work. Yet, according to the
Economic Commission for Africa (ECA), females account for 60-80 percent of all labor in
agriculture (United Nations 1978, 5).
They are not alone. Despite the empirical reality of the gender division of labor in most
African cultivation, "African farmers" are usually thought of as men, or as households headed by
men and united in a common enterprise. The practices of colonialism, overlaid by several decades
of post-independence development assistance, have created an almost entirely male-oriented approach
to farming in most African countries that ignores the importance of female producers. Schools of
agriculture have overwhelmingly male enrollments and the few females are concentrated in
traditional home economics. In 1986, research in Nigeria found enrollments to be well over 90
percent male, even counting home economics students, in three major Nigerian universities' faculties
of agriculture (Gamble et al. 1988). An estimated 97 percent of all extension agents in Africa are
male (Swanson and Rassi 1981). And, in most countries, the targets of their assistance also are
almost always male, although this is starting to change in a few places, such as Kenya, Malawi,
and Nigeria.
Elsewhere (Blumberg 1989b), I have argued that one reason for this virtually all-male
orientation is that most of the colonialists and the current development experts have come from or
were trained in Western countries with an agrarian13 farming system. The ethnographic data base
amply documents that agrarian farming systems are predominantly male-based (see, e.g., Murdock
1967). But much, albeit not all, of Africa is horticultural.14 And here the ethnographic data base
documents that male-based farming systems are a distinct minority: of 376 horticultural societies
included in Murdock's (1967) 1170-society Ethnographic Atlas, in only about one-fifth were men
the predominant cultivators.
Even more invisible than the gender division of labor in African cultivation is the gender
division of resources. As noted, the unitary household model obscures the reality of men and

"Agrarian" refers to a plow-based farming system that typically involves "mixed farming" (i.e., a combination of
crops and animals, often using animal-drawn traction and animal dung as fertilizer). It can be rainfed or irrigated and is
often well-suited to mechanization. Agrarian cultivation, however, requires soils deep enough to take the plow. This is
often not the case in sub-Saharan Africa, where horticultural cultivation remains dominant.
14 "Horticultural" cultivation generally involves use of the hoe, and slash-and-bum techniques. In much of sub-
Saharan Africa, typically poor tropical soils-thin, acidic, easily leached-predominate, making a transition to mechanized
agrarian cultivation impossible.

women's separate provider obligations, income streams, and expenditure patterns as well as the
prevalence of at least partially "separate purses," rather than pooling in a common household fund.
Consequently, development policy and practice have been largely blind to the possibility of gender-
disaggregated incentives.
Gender-disaggregated incentives and "separate purses" may be particularly important in sub-
Saharan Africa because of three fairly unique regional characteristics: (1) the continued high
prevalence of polygynys' which ranged from 30 to 47 percent in most of the nine sub-Saharan
countries included in the World Fertility Study sample (see United Nations ST/ESA/SER.A/100
1987, 324); (2) the overwhelmingly patrilineal, patrilocal'6 basis of its kinship system, and; (3)
women's importance as farmers.
In such a system, additional wives increase the resources of a man. A woman has a marital
obligation to labor on her husband's fields and/or crops. She also may be allowed to intercrop
own-account crops in the husband's plots on which she is required to work. Typically, she also
receives use rights to plots on which she raises crops for family provisioning and own-account sale
of surplus. Her access to land is tenuous. Her use rights to a plot remain in force only so long as
the plot remains in production. Women generally are assigned poorer, more marginal land in the
first place (Norem 1988). They may try to keep it in production longer than they should because
obtaining new land and/or getting (male) assistance in clearing it is increasingly problematic
(Cashman 1988). This is due to present trends toward population pressure and land scarcity,
environmental degradation," and increasing rural male rates of school attendance and outmigration.
The patrilineal, horticultural, and, often, polygynous system puts a premium on maintenance of
at least partially "separate purses." How much goes into "his, hers, and theirs" varies. Polygyny
typically means separate purses for co-wives. Co-wives may share domestic labor, but almost
always maintain entirely separate economic endeavors and accounts. In a number of ethnic groups,
men and women may pool expenditures for certain items such as children's school fees. But in
many groups, the woman has the obligation to provide part or all the food, or income to purchase
it, for her children. Furthermore, it is very important for her to maintain ties with her natal kin,

"5 Polygyny (where a man marries more than one wife) in Africa generally requires that the groom pay a brideprice.
Therefore, poorer and younger men are less likely to have plural wives.

'~ Patrilineal means that descent is reckoned through the male line and that there is a corporate kin group composed of
the descendants of a particular male. Patrilocal means that the young couple traditionally go to live in the village of the
groom's male patrilineall) kin.

If thin tropical soils are not allowed to regenerate (i.e., be put in long, or "bush" fallow) after several seasons of
cultivation, ecological degradation results. Rising population pressure in most of Africa has a strongly negative impact on
the amount of time land is kept in production vs. fallow. Population pressure is intensifying because Africa has the
world's highest rate of population growth-still over 3% per year, based on the world's highest birth rate (49 per 1,000
according to data in Sutcliffe 1986, p. 21).

especially in groups with high marital instability. This entails fulfilling certain financial and
ceremonial obligations to her own extended kin.
As a result of all these factors, most women must have some income of their own, in order to
fulfill their provider and natal kin obligations. This explains why the women, in the examples
discussed earlier, actively attempted to allocate their labor toward activities which put cash and/or
food under their control, and away from activities with more indirect returns, even if these provided
a higher rate of return. Conversely, this is why they did not respond as passive members of
unitary households.
Thus, African women farmers' need for income and their lower opportunity costs appear to
make them more responsive to a reduction of constraints and an increase in prices, as occurred in
Henn's study of the Cameroon villages that did and did not get a new road.18
As such, African women farmers should be-but are not-natural targets for agricultural
programs and projects based on the new emphasis on "structural adjustment." One of the major
aims of the World Bank's structural adjustment programs is "getting the prices right" (World Bank
1981). This involves changing a country's macroeconomic policies to reduce government
interference in markets and "correct" urban-based factor prices. The rationale for these policies is
that, in addition to thereby increasing "tradeables," especially for export, the resulting higher
agricultural prices will provide incentives for small-scale food producers. At the same time, it is
acknowledged that these policies bring immediate hardship to the urban poor, for whom prices of
basic necessities typically skyrocket (see, e.g., Longhurst et al. 1987).
In many African countries, 98 percent of local food output is generated by small scale
producers. Estimates show African women producing up to 80 percent or even 90 percent of
locally grown food (Sivard 1985, 5, 17). We have already seen that at least part of this food
production is typically grown by women farmers on their own account.
While much of female farmers' food is used for family provisioning, the urgent income needs
that drive what Vellenga (1983) terms women's "persistent search for profit" push them to market a
considerable portion of what they raise on their own account, wherever it is feasible and rewarding.
For example, a Nigerian survey (Adeyokennu, 1981), based on a non-random sample of women in
three villages representing the country's three major geographic/ethnic areas, found considerable
dedication to the market (see Table 2).

Even so, there are limits to how much women can be expected to respond to lowered marketing constraints,
increased access to extension, fertilizer and credit, and even increased prices if they are laboring from dawn to dusk.
Time budget studies invariably show longer total workdays for Third World women than men (Sivard, 1985). Much of it
is due to such necessary but largely invisible work as fetching water, fodder and fuel-and cooking with that fuel by
inefficient, low technology forms of combustion. Chapter 3 shows what happens when women's drudgework in such
activities is reduced.

Table 2: Marketable Surplus as Percent of Crops Grown

Percent North West East All
of Crops (N = 32) (N = 35) (N =73) (N = 140)

10-20 -0.95 0.88
20-40 10.00 33.33 15.24 18.67
40-60 80.00 22.00 17.14 37.79
60 + 10.00 44.67 66.67 42.66

Source: Adeyokennu 1981, 20, Table 10.

The proportion of women's marketable surplus found in this Nigerian study may or may not be
higher than elsewhere in Africa; data are sparse. The implication of the Henn study, discussed
earlier, is that where women benefit from increased incentives or reduced constraints, they would
bring more of their food crops to market, over and above whatever they currently were selling.
But if development initiatives target the household as an indivisible unit, and thereby direct
income and incentives to the male head regardless of whose labor and traditionally controlled
income is involved, much of the structural adjustment rise in food prices may result in hardship for
the urban poor without eliciting the hoped for increase in local food production. In other words,
even the "rightest" of prices won't matter if women producers of the bulk of the food crops don't
get enough of the resulting income to provide incentive.
And yet, African women farmers still rarely are targets for agricultural assistance of any sort
and almost never are considered in terms of incentives. At minimum, this is an inefficient use of
scarce development resources. At maximum, this would seem to be an important-albeit
unheralded-factor in the African food crisis. Alternatively stated, we could argue that African
women farmers must be explicitly targeted, because otherwise they don't automatically get either
the information or the incentives to enhance their production. Given incentives, women could be
the single most cost-effective available resource to alleviate the African food crisis (Grosz 1988).


Women Producers' Contributions and Constraints

This portion of the monograph highlights women producers' importance, effectiveness, and
constraints in low resource farming and urban informal sector microenterprises. These activities are
incompletely included in measured labor force participation. African women traders are the focus
of a final case study of a sector in which women are often important and effective-yet the targets
of special constraints that reduce their ability to distribute food.

3.1 Women's Importance as Producers


According to Sivard's estimate (1985, 5): "Rural women account for more than half the food
produced in the Third World; for as much as 80 percent of the food production in Africa." The
older, regional estimates for women's full contributions to agricultural labor were: 60-80 percent in
Africa, 60-80 percent in Asia, and 40 percent in Latin America (see United Nations 1978)."


With the growth of the informal sector's size, importance, and popularity as a locus for
development projects, data are starting to become available. Comia et. al. (1987) argue that the
informal sector may well be the main source of employment in developing countries and its
importance in this respect has been increasing during the past 10 years. It should be noted that
most of the gender data on this sector are estimates. Berger (1985) reckons that the informal sector
absorbs 40-70 percent of those working in the cities of the developing world, with women
predominating. In Latin America, Berger and Buvinic (1988) calculate that women may account for
half or more of those active in the sector.

3.2 Women's Effectiveness as Producers


Data are scarce on relative productivity of males vs. females in low resource farming. The
classic study remains that of Moock (1973; 1976) who measured maize output in a sample of 152
Kenyan farmers (51 of them female household heads). According to his regressions, controlling for

This is based on estimates from the United Nations regional economic commissions-the Economic Commission
for Africa, ECA, the Economic and Social Commission for Asia and the Pacific, ESCAP and the Economic Commission
for Latin America, ECLA. The estimates were aggregated from microlevel studies that examined the full farming system,
not just the measured agricultural labor force.

physical inputs and natural factors, women were technically more efficient maize farmers than were
men. The b coefficient indicates that "a woman obtains 6.6 percent more output at the mean levels
of input use than does a man" (Moock 1976, 833).
The problem is that "the playing field is not level." Women have less schooling and farm with
lower technology, fewer (if any) commercial inputs, less access to credit and extension, and, quite
often, on more marginal soils. For example, Moock found that women farm managers had
significantly less schooling and extension contact than men (r = -0.31 and -0.24, respectively,
N = 160, p < .001). Women also had strikingly fewer purchased inputs (e.g., for nitrogen use,
r = -0.21, N = 160, p < .005). Controlling for these differences, he found:

As anticipated, although this result may come as a surprise to many officials responsible for
policy for this area, the women in Vihiga are better farm managers on average than are the
men. In fact, [the linear] equation suggests that a woman produces an additional bag and a
half of maize with a given package of physical inputs (Moock 1973, 1973).

Table 3: Factors Influencing Maize Yields/Acre

Variable Linear Equation Curvilinear Eq.

Constant 0.540 0.695
Interplanted maize/beans 1.708++ 0.083+
Hybrid maize seeds 1.437+ 0.062
Maize plant population 1.085+++ 0.612+++
Insecticide 0.928 0.066
Rate of phosphate 0.031+ 0.047+++
Rate of nitrogen 0.081+++ 0.064+++
Fallow/fertilize last season 2.181+++ 0.079++
Person hours/acre 0.0017++ 0.062
Hail damage -0.961++ -0.048++
Misc. (erosion) damage -1.961+++ -0.133+++
Schooling 1.244++ 0.067+
Extension index 0.0027 0.010
Project loan 0.537 -0.055
Migration/age 0.864 -0.0013
Female manager 1.508++ 0.080++

R2 0.642 0.663
F 16.279+++ 17.810+++

Source: Moock 1973, adapted from Table VI.4, p. 198. (+, ++, and +++ indicate levels of
significance of .10, .05, and .01 respectively. The dependent variable is maize yields in
bags/acre; mean = 17.6 bags/acre-17.8 for men and 17.1 for women-with minimum = 5
and maximum = 33 bags/acre, std. deviation = 5.7.)

By holding constant most of the factors of which women usually have less (from fertile soil to
credit to commercial fertilizer, etc.), through multivariate regression analysis, we obtain deeper
insight into women's intrinsic abilities as farm managers. The bivariate relationship between gender
and yields (i.e., with no controls for all the factors of which women usually have less) indicated
that women got somewhat lower output. Even though the multivariate analysis showed women's
better performance with a "statistically leveled playing field," in real life, women's lower factor
endowments often mean lower yields.
Two other studies provide corroborative evidence on women's basic competence as farmers:
Staudt (1975-76, 1978) on Kenya and Fortmann (1978) on Tanzania.

Kenya: Staudt found that women managed 40 percent of farms in her Western Kenya
research zone, reflecting high rates of male outmigration. In one area with minimal
agricultural input services such as extension and credit, the most prevalent situation facing
the world's small farmers, she found that women managers were earlier adopters of maize
and grew a more diversified set of crops. But in another area where the level of
agricultural input services was much higher, long-standing, and aimed largely at men,
women lagged behind men in speed of adoption and crop diversification.

Tanzania: Fortmann studied Ujamaa villages and found that women were using improved
farming techniques. There were no significant gender differences in scores indicating "good
maize practices" within groups of purchasers and non-purchasers of improved inputs (seeds,
fertilizers, pesticides, and herbicides). The relative gender composition of the purchasers and
non-purchasers of the improved inputs is not given. However, considering women's much
lower access to cash income, it is a reasonable inference that the men considerably outspent
them. To the extent that these purchased inputs enhanced yields, women's output presumably
lagged behind, "good maize practices" notwithstanding.

These studies, demonstrating women's effectiveness and competence as farmers, indicate that
they perform as well as (and in several cases, better than) their male counterparts once males'
greater access to education, extension, and other production aids is controlled. Otherwise, given
lower access to these boons, and their smaller, poorer land endowments, women's production tends
to lag behind.


Although most discussions of the effectiveness of women vs. men in the informal sector involve
speculation or, at best, estimates, there is one exception where empirical data on relative
male/female performance are increasingly becoming available. Microenterprise credit projects have
been proliferating in the Third World in recent years. Lycette's review (1984) shows that women
have done as well as or better than men in terms of loan performance. More recent case studies,
such as the following Latin American examples, support her findings.

Dominican Republic: In the ADEMI microenterprise project, two types of loans were
given: (1) a bottom stratum of street vendors, recyclers, etc. received "Solidarity Group"
loans; 43 percent of this group was female in 1985; (2) those with some means of

production and perhaps an assistant or two received individual loans; in 1985, 17 percent of
these microentrepreneurs (MEs) were women. Women in both strata performed as well as
or better than men on loan repayment. Also, women MEs created slightly more jobs than
men MEs: 1.5 vs. 1.3. In particular, the women MEs of the clothing/textiles sector merit
special mention. The single most prevalent economic activity among ME loan clients was
clothing/textiles, accounting for 150/847 ME loans. This sector also accounted for about
half of all female ME loan clients. These women MEs had a rate of employment
generation twice as high as their male counterparts (1.4 vs. .64 new jobs created). In fact,
their clothing/textiles businesses were growing faster than those of their male counterparts
on five of six computerized monitoring indicators-sales, profits, savings, salaries,
employees and fixed assets (Blumberg 1985, 1989c).

Guatemala: In the SIMME microenterprise project, 1,623 individual loans averaging $1,300
had been granted by August 1988; 17.68 percent of these were given to women (N = 287). By
that date, 15.3 percent of loans were in arrears (N = 248). Yet, only 26 women were in
arrears. This means that women, who were 17.68 percent of the loan population, constituted
only 10.48 percent of those in arrears (26 out of 248). The difference is significant (Blumberg
and Reibel 1988).

In sum, in each of these cases, women proved to be better entrepreneurs and/or loan
performers than men.
In general, microenterprise credit projects with many women clients were the most successful.
Here are several examples:

Bangladesh: The renowned Grameen Development Bank has a minimal default rate, under
3 percent (Timberg 1988, 11) and, as of 1989, had provided loans to over 500,000
borrowers. These people are among the poorest of the poor, primarily landless and near-
landless. Women receive smaller loans, on average. As of December 31, 1986, the Bank
had 295 branches with 234,000 members. Of these, 69 percent were women, accounting for
55 percent of the cumulative loan amount ibidd., 10). Based on evaluations of relative
male/female loan performance, those proportions rose rapidly, as the Bank's recent
expansion has almost entirely been among women ibidd., 12). Indeed, the most recent
figures (Helmore 1989) indicate that about 82 percent of borrowers are women-and that
the bank is now growing at a rate of 10,000 to 15,000 new borrowers a month. Already it
has reached 9,500 villages, 14 percent of Bangladesh's 68,000 rural communities (ibid.).

Indonesia: The enormous BKK program made 2.7 million loans between 1972 and 1982,
amounting to over $55 million. Loans averaged $20, targeted to "rural families for off-farm
productive purposes." Interest rates were high enough (5.6-10.8 percent per month) for the
program as a whole to make a profit of $333,000 in 1981, a 7 percent return on its portfolio.
Yet delinquency was only 6 percent on current loans. Fully 60 percent of the loan clients were
women, overwhelmingly traders (Timberg 1988, 14).

Meta-evaluation of 100 LEIG (livelihood, employment and income generation) projects:
Tendler's 1987 study found that microenterprise credit projects were among the most successful.
She identified 8 of the 100 grantees as "better performers." As McKee (1988) stresses, 5 of the
8 dealt 100 percent with women and the other three gave serious attention to women clients
from the start. All 8 were narrowly focused on economic rather than social welfare activities.

These cases suggest that: first, experienced female micro-entrepreneurs, given what is usually
their first opportunity to get credit at non-exploitative rates, are at least as good credit risks as men.

Second, as explicated below, the microenterprise credit projects that succeed in reaching women are
those that have eliminated the obstacles and constraints that often not only preclude women from
getting such loans but also reduce the project's chances for success.
Many of the successful mixed-sex microenterprise credit projects did not initially seek out
women as participants. But the better ones seem to have eliminated the "up front" constraints that
typically prevented poor people from receiving credit. When these constraints were eliminated in a
credit program aimed at poor microentrepreneurs, women were able to take advantage of the
Specifically, as in the ADEMI microenterprise project in the Dominican Republic, successful
microenterprise credit efforts managed to incorporate women and poor clients in general because of
the procedures they adopted. ADEMI, for example:

Reduced the number of trips that a person had to make to a credit office in order to
process a loan application (generally, to a single visit);

Did not require collateral for most loans (resorting to a group guarantee scheme, the
"Solidarity Group," for the poorest clients);

Used "streetwise" promoters (college night students who spent much of their time out in
the field and who soon developed deep knowledge about and empathy for the
microenterprise sector) to select loan clients and aid them with the application process
(rather than bank bureaucrats, who tend to intimidate poor, uneducated, potential clients
and who often have a deep-seated negative view of their loan repayment proclivities);

Offered fast turnaround time, so that loans would be approved and issued in days rather
than weeks or months; and

Rewarded on-time payment by offering an immediate, new, slightly larger loan for prompt
and full repayment (Blumberg 1985, 1989c).

These procedures overcome the high "up-front" costs that often place loans, even those at below
market interest rates, beyond the reach of the poorer, less mobile (and frequently female)
microentrepreneurs. In fact, most of the successful micro-enterprise credit projects are not low
interest projects. They charge market rates of interest. But even these can be a great boon to, say,
a market trader who previously had to rely on the moneylender's enormously higher rates for short
term credit. As one woman cloth seller said about ADEMI: "It has freed me from slavery to the
The most successful ME credit projects have almost all been "minimalist" ones that give
virtually nothing except credit (see e.g., Timberg 1988; Tendler 1987). Microenterprise (ME) credit
projects are often more successful than other lending projects that give subsidized loans (below
market rates) to much more affluent clients-an outcome that refutes many stereotypes about

development credit assistance. Development planners should also take seriously the fact that the
most successful ME projects often have large proportions of female clients.'
As a summary hypothesis, one could propose that women entrepreneurs have so little access to
credit of any kind that they make the most of their ME credit project opportunity. This could
explain their better loan performance record, compared with males', and once again indicates that
tapping into women's productive potential enhances development. When given a chance in an
area where they already are economically active, women, spurred by their stronger unmet need for
income-especially where they have provisioning responsibilities toward their children-tend to do
their utmost "not to blow it."
It appears that women's better performance in ME credit projects stems from the same
circumstances and motivations that made them more responsive than their male counterparts to the
opportunity presented by the new road in Bilik Bindik, Cameroon, discussed in section 2.5. Just as
credit access reduces economic constraints, the road drastically reduced women's marketing
constraints for perishable food crops. This brings us to the topic of rural women's constraints to
production and what happens when they are lifted.

3.3 Women's Production Constraints in Low Resource Farming

Three major kinds of constraints act as impediments to the productivity of poor women farmers
in developing countries:

S Time constraints caused by their labor in necessary but "drudgework" tasks such as
fetching water, collecting and utilizing firewood, providing fodder, and processing crops for
cooking, market sale, etc.

Inadequate access to the factors that facilitate agricultural intensification-extension,
training, credit, and inputs.

Less access to land and other factors of production.

The first two sets of constraints (especially the second) involve areas much more frequently
targeted for development assistance than the third. Thus, the present discussion focuses on them.
The third constraint involves redistributional issues frequently thought of as a "zero sum game."
Such issues, rarely addressed by development donors, are beyond the scope of this monograph. For
the first two sets of constraints there is an overview of the severity of each problem and a
consideration of the effects of easing these constraints on women's productivity. The evidence
suggests that lowering women's barriers in these areas adds to economic growth. When

2 This, as we shall see, is a very different experience than that of women's access to agricultural assistance,
extension, and credit. Thus far, very little has been done to reduce the constraints that prevent women farmers from
participating. In fact, agricultural assistance to poor, small farmers, regardless of sex, has proven much more problematic
than assistance to poor microentrepreneurs.

development interventions save much of women's time previously spent in fetching water and
firewood and food processing, this is often translated into enhancement of income generation and/or
output. It is not yet possible to point to a comparable body of evidence on effects of agricultural
aid and extension on women's productivity-targeting women for extension is still too rare or new.


Time constraints resulting from women's labor in providing water, fuel, transport, and
processing crops affect both women who work as unpaid labor in their household or their husband's
holdings, and those who farm partially or fully on their own account. Time budget studies "reveal
the fact that women universally work longer hours than do men" (Carr and Sandhu 1988, 4).
When an expanded definition of productive activities is used, women are often found to provide
more of the household's total labor input than men. Carr and Sandhu illustrate this with data from
Nepal (Bennett and Acharya 1983) and Ivory Coast (FAO 1983) shown in Table 4.
Time budget studies also indicate that in many developing countries, two of the most time
consuming jobs involve:

Fetching water for household humans and animals; and

Foraging for and transporting fuel/wood for cooking. In areas of deforestation,
desertification, and/or increasing population pressure, these tasks have become more
onerous and time-consuming in recent years. Drought lengthens the time needed to
provide even minimal amounts of water, and deforestation makes it more difficult to
provide fuel for cooking. The trek to find firewood becomes longer or crop residues
and/or dung may be used-to the detriment of the soils and the crops. As women resort
to more marginal kinds of fuel materials, the cooking fire may require increased tending
even though it is less efficient.

In general, women bear primary responsibility for both water and fuel/wood provision except in
areas where women are secluded or lose face from being seen in public doing such activities,
and/or where the demand/scarcity situation has resulted in commercialization by males. Where
women are obligated to perform these chores, they often pass along much of this burden to children
(or servants, if any).
Indeed, in many countries, one or more household children may spend the entire work day
fetching water, fuel, or both. This foraging and transporting responsibility has been cited as one
important reason women, in many of the countries most bedeviled by water and fuel/wood
provision, need more children than family planners would like them to have. With more of their
children in school and/or away in seasonal or permanent migration, and often, with water and
fuel/wood harder to get, women may need an extra child or so to help out with these chores.

Table 4: Men's/Women's Contributions To Economic Activities

Average Hours/Day
Male Female

Weighted Work Share
(per sex)1
Male Female

A. Nepal

1. Conventional
(labor force

2. Subsistence

1+2 Enlarged

3. Domestic

1+2 "Productive
+3 work burden"

B. Ivory Coast

1. Conventional

2. Subsistence

1+2 "Enlarged"

3. Domestic
1-3 "Productive"

5h/49m 4h/37m

54m 2h/10m

6h/43m 6h/47m













Source: Carr and Sandhu 1988, tables on pp. 12-13.

1 Weighted work share is not calculated from average hours/day; no explanation is given of the
weighting, however.




















Two other tasks related to production that take an inordinate amount of women's time under
low resource conditions are:

Other transporting tasks--carrying crops from fields to household or farmgate (sometimes,
even a cheap wheelbarrow may greatly ease women's time burden in this regard); and

Processing tasks-from hulling, winnowing, threshing, and pounding to frying (e.g., cassava
flour, or gari) and smoking (e.g., fish). Doing these tasks the traditional way takes great
time and energy


One of the most frequent findings in the women in development literature is how little access
women have to factors that facilitate agricultural modernization and intensification such as:
training/extension, credit, and inputs.
Extension: Only now are a few, mainly African countries, largely in "female farming" zones,
beginning programs to insure that women farmers are served by extension. In some areas, it is
culturally inappropriate for a woman to have contact with a male extension agent in a one-on-one
situation. As shown in Table 6 below, Swanson and Rassi (1981) found that over 97 percent of
extension agents in Africa were males; moreover, it could be inferred that most of the 2.6 percent
female agents at that time actually were home economists whose inputs on farming were extremely
limited. Even where there are no strong cultural prohibitions on cross-sex extension contact,
women still are rarely included in extension, even in token numbers (Wycoff-Baird 1988).
Training: The location and timing of training programs typically preclude women from
participating in them. If the training requires overnight stays or longer and if there are no
culturally appropriate dormitory facilities for females, and/or provision for them to bring their
youngest child, women's attendance is impossible even if they are selected (and, in general they are
not). Sometimes women are even unable to attend courses designed to help them in female tasks.
For example, an A.I.D. Thai sericulture project gave a one-month course on new methods of
silkworm care. Even though this is a distinctly female task, only about half the participants were
women. Many women could not get away to attend, especially at that point in the cropping season
(Blumberg 1982/1983).
Credit: Lacking adequate collateral, especially titles to land, women have had very limited
access to credit, even in agricultural credit projects aimed at small farmers. Women often are
outside the communication networks (e.g., via male extension agents) that spread the word about
new credit projects. Staudt (1979, 1985), for example, found that the women farmers in her
Kenyan sample were 14 times less likely to receive credit information than their male counterparts.
The likelihood of women being recipients of agricultural credit is even lower if the credit is

subsidized (i.e., at below market rates of interest) and the project is "gender neutral." These almost
invariably become "one gender absent" projects.
Inputs: As with credit, where inputs are subsidized, women's likelihood of receiving fertilizer,
planting sets, improved seeds, etc. appears to be even lower than for unsubsidized inputs. With or
without subsidies, if these inputs are not free, women are less likely to be able to afford them.
This is particularly the case if the women intend to use the inputs mainly for a crop used more for
subsistence than for market sale.
The production potential lost from lack of access to these inputs is greatest where the women
are farming at least partially on their own account and are important producers, as is the case in
sub-Saharan Africa. Studies also have documented the bypassing of women cultivators in the
Caribbean (e.g., Knudson and Yates 1981), Southeast Asia (e.g., Blumberg 1982/1983), and
worldwide (Berger, DeLancey and Mellencamp 1984; Ashby 1981).

3.4 Easing the Constraints on Women's Productivity


When the time constraints of water and fuel collection, transportation, and crop processing are
reduced, many women pursue income generating activities. Carr and Sandhu (1988) present
"evidence, for those who require it, of reallocation of time to productive income-generating
activities" ibidd., 44). They also cite a few studies indicating that, when one of the above
constraints was eased, women used the time saved for rest, social activities, or domestic tasks not
normally measured as productive. Combining their examples with my own, here are instances of
income generation outcomes from the easing of each time constraint:
Water: It is often found that when women gain access to more water, closer to home, they
increase their use of water, thus cancelling much of the time saved. While some of this water is
used for domestic purposes such as cooking and better hygiene, women also have found ways to
turn that water into cash.

Northeast Thailand: A 1979 evaluation of a potable water project, begun in 1966,
involved a stratified random sample of 52 of 600 village installations. All but 7 were
functioning-a much higher percentage than had been found in evaluations in the early
1970s. The evaluators discovered that the water was not being used for drinking because
the villagers disliked its taste. Gradually the villagers found economic uses for the water
unanticipated in project design. These included irrigation of horticultural crops, small
animal raising, and craft production activities carried on or in the immediate vicinity of the
household. Although the evaluation does not specify which gender was using the water for
economic purposes, these are activities in which women tend to have an important role in
control of resources as well as provision of labor. The evaluation does specify that women
and children gained time and the women used that time: "for activities such as weaving and
gardening to either generate income or raise the household subsistence level. These
activities were said to be less menial than waterbearing. 'Women prefer raising vegetables

and weaving,' it was said, 'because it is not so boring and it lets them use their brains'"
(Dworkin and Pillsbury 1980, p. ii; discussed in Blumberg 1982/1983, 56-57).

Kenya: Tinker (1981; see also Carr and Sandhu 1988, 44) discusses one case where women
with an improved water supply were selling some of it to finance own-account livestock and
vegetable crops.

In fact, a general pattern emerged in a desk review of a random sample of A.I.D.
sanitation/water supply projects. Nieves (1985) "found that reduction of time spent carrying water
did not increase time spent on production unless income-earning opportunities already existed or
were introduced" (Carloni 1987, 31). Finally, it must be pointed out that there are places where
women's water bearing burden is so great that it limits production, whether for women's benefit or
not. For example, Carloni notes that one reason women in Kitui District, Kenya cannot plow and
plant on time (when the rains come) is that half their productive time is spent fetching water from
distant sources.
Fuel: Based on a number of studies, Carr and Sandhu conclude that the total time spent on
fuel provision and cooking is fairly fixed, so that if women spend more time fetching firewood, less
time is left for cooking, and vice versa. But they also cite one study of an income-generating use
engendered by better firewood provision.

Philippines: An ILO study (Cecelski 1984) "found that women were willing to pay more
money for easily used woods so as to reduce the amount of time which needed to be
devoted to tending the fire during meal preparation. This allowed mats to be made at the
same time meals were being cooked. Women sold these-thus earning cash to compensate
for the extra expenditure on fuel" (Carr and Sandhu 1988, 46). It may be inferred that the
women's mat making returned more than just the extra cost of the fuel, although this is not
explicitly stated.

Transport: In much of the developing world, women, unaided by even a cart or wheelbarrow,
transport most of the water and fuelwood and a good deal of the harvest. Women, especially in
Africa, often carry crops on their heads from field to home to market. Carr and Sandhu cite two
studies where the provision of animal transport enabled women to use this saved time for income-
generating activities.

North India: Following the introduction of mules, which freed time women had spent
carrying fuel, they began income-generating activities such as knitting and tomato growing
(Cecelski 1984, in Carr and Sandhu 1988, 46).

Burkina Faso: This example is particularly relevant for the present monograph because both
men and women benefitted. Donkey carts were introduced and men, who traditionally would
not carry wood, water, or harvested crops, used them to transport water and wood for sale.
Women used the freed time to engage in cotton spinning, which is often an income-generating
activity, and for rest ibidd., 46-47).

Processing technology: Sometimes, when machines or mills for grinding, hulling, etc., are
introduced, the poorest women in the community lose an important income source. This occurred
in the well-documented case of the introduction of the electric rice huller in Java, Indonesia (see
Stoler 1977; Milone 1978). At other times, such technology has been introduced to and controlled
by women, for their economic benefit.

West Sumatra, Indonesia: In West Sumatra, the women's clans still own the land, and the
effect of the introduction of the HYVs [high yield varieties, in this case, "Green Revolution"
rice] was entirely different than in Java. In fact, women buy the costly inputs, own the rice
hullers, and employ men with knives and scythes to help in the harvest. Before these
developments, Minangkebau women kept control of earlier technological innovations, such as
mechanized spice grinders and the water driven mills which they still own and use to grind
flour. In Aceh, as well, where women can own the rice fields, they have kept authority over
earlier labor-saving devices, such as mortar and pestle for rice pounding, and now use hullers to
reduce losses and produce a better quality of rice (Milone 1978, 156-157).

Ghana: Carr and Sandhu (1988, 49) discuss an ILO/Netherlands Government (1985) report
concerning the introduction of improved ovens for smoking fish. Processing fish, particularly
through drying and smoking, is an important activity for women in Ghana and elsewhere in
Africa. They don't mention it, but fish smoking is also an income-generating activity for most
of these women. Women with the improved ovens in their compounds were able to smoke
three cycles of fish per day, compared with only one previously. Since the new ovens were
easier to operate, women could combine fish smoking with other household chores. These
women chose to process more fish in the same time rather than the same amount as before in
much less time. Once again, we can infer that, despite heavy work burdens, women opt for
income over leisure when the income is needed and under their own control. Apparently these
women gained extra time for themselves over and above the three smoking cycles per day.
"With the improved smoker, women complete smoking early enough to get time to relax.
Cooking of regular meals for the family has now become a common feature of 56 percent of
the women who before then had no time to cook and therefore bought cooked food from
outside" (ibid.). Carr and Sandhu do not mention whether this adversely affected the incomes
of the women who sell cooked street foods. But they do note that the women fish smokers
used the remaining time saved for: farming, household chores, visiting, and rest.

All of these examples show instances where individual women benefitted because a time
constraint was eased and they were able to turn the time and/or the activity into income under their
own control. The next example suggests how an entire country can benefit when the water and
fuel/cooking time constraints of farm women are eased.


In 1985, Howe analyzed the economic problems and prospects of the Yemen Arab Republic
(YAR) with and without taking women into account. The differences are remarkable. According
to Howe's statistical portrait, the YAR economy receives the bulk of its foreign exchange from
remittances from adult males working outside of the country. At any given moment, one-half of
the working age males have migrated-mainly to neighboring oil-rich Gulf states (where their jobs
depend on the world price of oil). Yemen's exports are negligible. Small-scale, low resource

fanning occupies most of the population. Official statistics indicate that 45 percent of the women
are engaged in agriculture full-time as unpaid family labor. According to Howe, income from
agriculture is controlled by males. In fact, rural Yemeni women have neither provider
responsibilities nor any real income-generating opportunities (Carloni 1988).21
One of the biggest problems facing the YAR is the decline of its agriculture. A six-province
census listed 16.6 percent of the land as permanently abandoned by 1980. The rate of
abandonment is increasing at 2.2 percent per year. Food imports have surged from 0.83 billion
rials to 2.03 billion between 1975 and 1982. With a total 1982 GNP of 17.0 billion, and
remittances totalling 6.94 billion in 1982, this means that almost 30 percent of remittance income
and 12 percent of total GNP are spent on food imports (see Figure 2). The problem is one of food
production shortfalls, not shifts in consumer preferences. If present trends continue, food imports
will jump to 4.4 billion rials (at constant prices) by the year 2000. A food deficit of this size
gravely threatens the viability of the Yemeni development effort.
But present trends need not persist. Howe demonstrates that the food deficit could be almost
entirely eliminated by the year 2000. How? The male farm labor force is highly unlikely to
expand. In fact, the government relies on remittances, sent by male migrants, to fund its
development plans. However, women's agricultural labor could be greatly increased by reducing
time spent fetching water and wood, providing firewood, and cooking.
From available data, Howe took rather conservative figures for the time that the females of a
given household spend in these routine domestic activities. Then he calculated what would be
saved from providing improved water supplies (but not piped-in water) and butagas or kerosene for
cooking. He found that time spent by women in those routine domestic activities would drop
spectacularly from 11.5 to 1.7 hours per household per day.
The estimated 11.5 hours/day for these three tasks includes the efforts of all the adult and
adolescent females of the household. The average Yemeni household has eight members. Howe
arbitrarily estimated the typical composition as: a senior generation adult male and female, a junior
generation adult female, an adolescent (10-14) male and female, and young male and female
children (under 10). The junior generation adult male is assumed to be out-of-country as a
temporary migrant.

2 This example illustrates that peering within the "black box of the household" reveals a diverse continuum vis-a-vis
a gender-disaggregated "internal economy." At one end of this continuum are the partially "separate purses" households
prevalent in much of Africa. At the other end are the more unitary households found, for example, in some Islamic
areas, such as rural Yemen (YAR). The problem has been that households at both ends of this continuum (as well as
those in between) have been conceptualized and treated alike by the prevailing single production function model of the
household. Just where the households of a particular group falls on this continuum should be the subject of empirical.
determination, not a priori assumption.

Howe suggests that if even half the increased time enjoyed by the two adult females were
devoted to agriculture, it would increase the household agricultural labor supply by almost 30

Table 5: Approximate Daily Labor Time Required For Major Domestic Tasks Per Average
Rural Household-Current And Improved Conditions


Task Current Time Improved Time
(hours) (hours)

Cooking 3.0 0.5
Fuel collection 3.0 0.0
Water collection 5.5 1.2

Total 11.5 1.7

Source: Howe 1985, 94, Table 13.

percent and still leave the adolescent girl with half her time free to attend school-something she
currently doesn't have time to do. In the YAR, only 3 percent of the females over age 10 can
read and only 11 percent are enrolled in primary school. Men are 16 times more likely to be
Howe shows that, under the current system, rural Yemeni women are fully occupied.
According to official statistics, 45 percent are engaged in full-time cultivation, which is close to the
calculated maximum (50 percent) that can be achieved given the amount of time women must
spend on the necessary tasks of collecting water and fuelwood as well as cooking. He asserts that
it is not remittance-based "affluence" that restricts the supply of female agricultural labor, it is the
ceiling imposed "by the present organization of domestic reproduction" (Howe 1985, 92).

In sum, providing improved water supplies and cooking fuel to women-and then improving
their agricultural productivity via extension-should be considered investments that can mitigate the
growing crisis in national accounts represented by burgeoning food imports."
Howe also tackles the problem of Yemen's labor shortage, especially in education and health.
Currently, 50 percent of the M.D.s, 66 percent of the nurses, and 87 percent of the teachers are
expatriates (mainly Egyptians). Their numbers are rising, as are the remittances they send out of
the YAR-to the detriment of the country's balance of payments. Even modest increases in female
education, enabling Yemeni women to go into teaching and nursing, could dramatically decrease the
need for expatriates and hence reduce the rising outflow of foreign exchange. The foreign
exchange savings provided, just from reducing needed expatriate teachers from 36,000 to 24,000 by
the year 2000, would amount to about 1.2 billion rials from the cutback in remittances these
expatriates presently send home. Currently, Saudi Arabia pays their salaries as part of its aid
program to the YAR. If this assistance were ended, the ensuing crisis in national accounts would
enormously magnify the problem.
Furnishing the water and cooking fuel that would free time for girls to attend school could be
the first step. Providing enough schools and teachers for increasing female enrollment would come
next. Howe calculates that the short run cost increase this would entail would be greatly
overbalanced by the longer term foreign exchange savings as the YAR would need fewer
expatriates to teach its children and minister to its people's health.
While this is a computer simulation model, the effects are extrapolated from existing data.
Howe's assumptions may strike some as somewhat optimistic about the magnitude of the impact of
reducing women's drudgework constraints. But even a conservative assessment of the data leads to
the conclusion that reducing women farmers' time/labor constraints should have a major impact on
their time available for production and/or education. Thus, easing these constraints should
substantially enhance national accounts and YAR economic development prospects.


There are various means of facilitating agricultural intensification in addition to machinery.
These include: extension, training, credit, and inputs (fertilizer, seeds, chemicals). The present
discussion focuses on extension, particularly the gender of extension agents and extension clients.
Africa is emphasized, since this is where both the food shortfall and the predominance of female
food producers are greatest.

Opening the country's male-based extension system to deal with women cultivators will require planning, and
governmental commitment in the highly traditional, Muslim YAR. Either women extension agents must be used (initially,
expatriates, it must be assumed), or, perhaps, male extension agents could work with suitably convened and chaperoned
groups of women. In short, while reducing women's drudgework burden via improved water supplies and cooking fuel
will free some female labor, that labor must become more productive. Otherwise, Howe's optimistic predictions about the
near-elimination of the food deficit by the year 2000 may be unattainable.

40 Women Extension Agents-The Key to Reaching Women Farmers?

According to the extant data, if attention to women farmers must await the training and
recruitment of sufficient female extension agents, it will be a long time before women cultivators
will be fully served.
A worldwide overview: The most comprehensive, albeit ambiguous, listing of extension
personnel by sex is that of Swanson and Rassi (1981). They use separate categories for agriculture
and home economics. Very few women are classified under agriculture-except in three Southeast
Asian countries. The Philippines lists 35 percent women (3642, vs. 6767 men); Thailand shows 20
percent women (936, vs. 3672 men); and Malaysia 13 percent (383, vs. 2612 men). Presumably,
the women agents facilitate contact with farm women.
But the actual proportion of females who are fully trained agricultural extension agents may be
lower than shown in the table. This is because some countries apparently list women in the
agriculture category who actually are home economists employed in an agricultural division, perhaps
under a title other than "home economist." For example, in Table 6, Nigeria shows nearly

Table 6: Male & Female Extension Personnel In African Agricultural Programs

Country Agriculture Home Economics*

Botswana 186 13 2
Gabon 88 2 -
Gambia 170 6 -
Mauritius 56 -
Namibia 13 -
Nigeria 1106 104 -
Senegal 1088 3 1
Seychelles 11 3 -
South Africa 1107 2
Togo 200 -
Tunisia -
Zimbabwe 1323 13 -

Total 5337 141 (2.6%) 0 5

Only home economists working under agricultural programs are shown.

Source: Swanson, B. E., & Rassi, J. (1981). International Directory of National Extension
Systems. Urbana, IL: University of Illinois, Bureau of Educational Research.


Economic Trends in the Yemen Arab Republic





1980 1985 1990 1995

Legend: Line 1 is demand line 2 is supply at male rate of
increase; line 3 is supply at aggregate male and female rate
of increase; line 4 is supply including productivity rises.




Source: Howe 1985, pp 69, 78


8 percent female agricultural extension personnel (104 out of 1210) and no home economists. As
far as I could ascertain, the first handful of women extension agents, who actually worked in
agriculture with farmers of both sexes, apparently was hired in 1985-1986 in Imo State in Eastern
Nigeria. I found 7 women out of 291 agents in the summer of 1986 and 42/300 in December
1987, as further discussed below. In addition, I found a home economics unit within the
agricultural extension service-as was true in various other states of Nigeria as well.
Swanson and Rassi's data from Africa (Table 6) are cited in all the overviews of gender and
agricultural extension (e.g., Berger, DeLancey and Mellencamp 1984; Walker 1987). Hopefully, the
dismal picture illustrated in this table is now becoming outdated. Indeed, in the last several years,
Cameroon, even more than Nigeria, has aggressively recruited trained female agricultural extension
agents who work on a par with and are paid the same as their male counterparts.
The Cameroon MIDENO Project: According to Walker (1987) and Koons (1988), the
Mission de Developpment de la Province du Nord-Oest has made a strong recent effort to recruit
agriculturally qualified women. As of 1987, it had achieved a higher percentage of women
agricultural agents (18 percent) than anywhere else in Africa (Walker 1987, Table 2, p. 20). This
was accomplished as part of a revamping of extension toward the World Bank-promoted Training
and Visit (T&V) system (Benor and Baxter 1984).
Project funding from IFAD, the International Fund for Agricultural Development,
was used to increase province village extension workers (VEWs) from 189 to 375, providing an
almost unheard of VEW-to-farmer ratio of 1:400. A total of 50 women were hired along with 136
men. There were already 18 women VEWs but, until the project, they were restricted to home
economics and kitchen gardens. All VEWs, both male and female, veterans and newly recruited,
underwent an identical three month intensive training course. All VEWs were supplied with off-
road motorcycles and demonstration equipment, such as chemical sprayers, maize sellers, etc.
(Koons 1988, 7-8). This put women agents on an equal footing with male agents. The plan was
for each of the VEWs to work initially with their own gender, and then gradually phase out the
gender targeting in favor of a geographically based system in which agents would work with groups
of both sexes within their zone. During the initial gender targeting phase, efforts were made to
work with pre-existing groups of farmers. Almost everyone belongs to at least one, almost
invariably single-sex, such group (ranging from cooperatives, church organizations, and rotating
credit societies to various kin-based and neighborhood networks).
The typical African gender division of labor prevails among farmers in the province. According
to one survey, women perform 72 percent of land preparation, 48 percent of planting, 70 percent of
weeding, and 63 percent of harvesting (Walker 1987, 1). As usual, women raise and control the
income from food crops and men concentrate on cash crops such as coffee. With increased access
to urban markets, provincial women have turned potatoes, maize and, to a lesser extent, beans into

"near cash crops." "Women have responded to this opportunity for increased incomes by increasing
production of these crops" ibidd., 7).
Despite some partial successes, reaching women was termed "the weakest aspect of the
MIDENO project" Koons 1988, p. 11). Only 18 percent of the VEWs hired were women rather
than the 33 percent in the project plans. So the initial gender targeting could not be fully
implemented-there were too few VEWs to go around, especially since half the contact farmers
were supposed to be women.
Second, since the female VEWs received the "same training and official agricultural positions as
men, they took on, to some degree, the same elevated status" ibidd., 15). This meant that women
farmers, mindful of cultural norms, were hesitant to ask questions of female, as well as male,
VEWs. Still, the women VEWs were much better able to communicate with women farmers than
their male counterparts, a result also encountered in the Caribbean by Knudson and Yates (1981).
All in all, VEWs often viewed women farmers as passive, traditional, and less willing to adopt
new practices. Where the VEWs formed new groups, rather than working with pre-existing ones,
the problem was compounded because the new groups were mixed in gender. Women were
unlikely to violate cultural norms and speak up in this situation. Yet women were quite willing to
get extension advice. Women's groups were larger than men's and often more women than men
attended mixed groups.
One major difficulty lay in the VEWs' expectations that farmers would adopt the entire
"package" of new practices. Women, who had lower income, tended to adopt only parts of a
"package," or split a bag of fertilizer and seeds among themselves. The VEWs viewed this as
unwillingness to innovate. Also, the VEWs expected farmers to step forward and request further
information or individual farm visits, which often was not culturally appropriate behavior for
women. As a result, surveys conducted by Koons showed that men received eight times more
individual farm visits than women (27 men received 95 visits, whereas 25 women received 12
VEW visits).
Still, women farmers received some benefits. Although, in general, they "knew far fewer of the
extension recommendations than did men" (Koons 1988, 12), more recent research found that they
were twice as likely to follow recommended planting densities of improved maize. Fifty-two
percent of the female contact farmers vs. twenty-four percent of the males used the proper planting
density (Walker 1987, 23; Walker's data is newer, per Weidemann, 1989).
Unfortunately, the data on results of extension were not disaggregated by gender-of either
client or VEW. Therefore, we have no way of knowing whether or to what extent the gender of
the extension agents affected male vs. female clients' adoption rates and subsequent yields.
The shortfalls of this pioneer effort for substantial and rapid "gender integration" of agricultural
extension personnel all seem quite correctable (the newer Walker evidence presented below indicates

that things have improved). And the project's achievement in recruiting and providing equal
training and transport/equipment to women extension agents is considerable.
Innovations in Nigeria: Since the mid-1980s, Nigeria also has started transforming its
extension system via the Training and Visit model. This model of extension has been criticized by
many for its lack of attention to women farmers (e.g. Berger, DeLancey and Mellencamp 1984;
Walker 1987; but see also Benor and Baxtor 1984). However, even critics feel that it could be
implemented to reach women farmers.
Imo State, in the Ibo area of Eastern Nigeria, was the first to make a serious attempt to hire
both women extension agents and reach women farmers. This is a densely populated, classically
"female farming" zone. Until 1985/1986, agricultural extension had been staffed by males to deal
with males. The following incident illustrates the strong male bias of that earlier system. In the
spring of 1986, when I was a member of a research team working in another state in Eastern
Nigeria (not Imo), we visited the farm of a "progressive farmer" who was involved in a variety of
university-based research and outreach activities that we were studying (Gamble et al. 1988).

Imo State, Nigeria: The team and I first interviewed the husband, who enthusiastically
described the many types of help he received from the university and his state's agricultural
development extension staff. The others went to see his yam mounds., I stayed behind with
an interpreter, a male agricultural economics graduate student, to interview the "progressive
farmer's" two wives. Both were full-time farmers who traded bootleg gin in the off season. I
queried the junior wife, a strong, strapping mother of six, about her access to technical
assistance. The extension and university people all dealt with her husband, she explained, but
sometimes she was able to talk with them. Most recently they had been explaining and
promoting fertilizer and chemical application (e.g., pesticides, herbicides, and fungicides). Who
handled this work? She was entirely responsible, hiring labor when she could afford it. Yes,
her husband tried to explain what he had learned. Would she like to deal directly with
extension agents and researchers? A short torrent of words showed clear assent. Then she
paused, looked down, and added another soft phrase. The student translated that she would
indeed like to get this information directly, then had added, "but it's OK the way it is..." He
exclaimed: "Of course she would rather deal directly with the extension people; she's just
being cautious not to offend!" We then accompanied her to the fields to rejoin the rest of the

By the time I arrived in summer 1986, Imo, unlike its neighbor, had already hired about 7
women extension agents (EAs) out of the total of 291 then employed by the statewide Agricultural
Development Project (ADP). These women were trained in agriculture and worked with both males
and females. Like their male counterparts, most of their clients were men, but they did deal with

23 His yam mounds were just then being planted by a mixed-sex labor force. Traditionally, Ibo women did not
participate in the early phases of yam cultivation (mound-making, training the vines), since yams were "men's
business"-the highest prestige, most valued crop. But with male outmigration has come a further "feminization of
farming" in this already "female farming" zone. Despite tradition, we observed many mixed-sex teams making yam
mounds. And, as soil fertility drops in response to shortening of the fallow, yams are increasingly displaced by
cassava-traditionally a female grown/controlled crop.

more women (Blumberg 1986). This was only a drop in the bucket, however, given the
predominance of women in cultivation in the state.
Between summer 1986 and December 1987, the number of women EAs rose to 42 out of
300-a not inconsequential 14%. Moreover, project management made another innovation of
potentially broad applicability in sub-Saharan Africa. It began to reorient its home economics unit
into a "Women in Agriculture" entity. The task was facilitated by two fortuitous circumstances:
(1) all the home economists had trained at the local agricultural school, where they received one
year of general agricultural courses-an atypically strong exposure to agriculture for a Nigerian
home economics curriculum; and (2) all the home economists took advantage of their Ibo female
farmer heritage by part-time own- account farming, to supplement their low salaries. Thus, while
these women would need additional training in order to function as "Women in Agriculture"
specialists, the base already had been laid.
Given that fully qualified female agricultural graduates are few and far between, while home
economists are the most numerous category of women working in African rural/farming activities,
the Imo innovation is potentially widely adoptable." In most other places, the women would
probably require more training before they could begin to transform their functions. It also should
be noted that the Imo State "Women in Agriculture" unit was supposed to concentrate on helping
with the crops in the ADP's agronomicc package" during the growing season, but focus on
revamped home economics activities in the off-season. The new off-season emphasis is to be on
crop-related activities such as processing, storage, and use, as well as on traditionally female-
controlled crops (e.g., vegetables) that are not part of the ADP's "package."
It remains to be seen whether the Imo State "Women in Agriculture" retraining and
reorientation of home economists will achieve its objectives. While a 1987 survey found most male
EAs reacting positively to the idea of the home economists' refocused mission, the women
themselves still had received little retraining and continued to suffer from insufficient transportation.
The dignified, middle-aged and sometimes portly home economists were skeptical about
scooters-the project management's idea of how to provide transport to the female EAs (funds
permitting). Male EAs were supposed to get motorcycles.
A dissenting view on women extension agents: Carloni (1987) has synthesized the findings of
the multi-phased A.I.D. research project measuring progress on women in development. Among the

24 A 1984 FAO study of "trained agricultural personnel" in Africa found that women comprised 3,510 of the 48,200
total for Nigeria, or 7.3%. (Nigeria, with about 105 million people, is by far the most populous state in Africa.)
According to Natalie Hahn of the International Institute of Tropical Agriculture (1986), most of these women are home
economists. Actually, there may be even more home economists in Nigeria. Another survey, involving 11 of Nigeria's
then-19 states (now there are 21), reported 4,530 (Home Economics Association of Africa 1985). These figures further
call into question the accuracy of the widely-cited Swanson and Rassi data presented in Table 6, which reported no home
economists in Nigeria. How many home economists, in Nigeria or elsewhere in Africa, have even basic knowledge of
agriculture is unknown.

ten field studies carried out for the project, five focused on women's access to extension (in
Botswana, the Caribbean, Thailand, Kenya, and Nepal). In all five, some of the extension workers
were female, but Carloni concluded that:

Their contact with female farmers was not necessarily better than that of male extension
workers. On the contrary, both male and female extension workers tended to focus on male
farmers. One reason for the lack of contact with female farmers was the prevailing emphasis
on commercial farming and cash crops. Extension workers had few incentives to spend time
with subsistence farmers. In Botswana, extension workers of both sexes tended to focus on
men because village women's family responsibilities made it more difficult for them to travel to
extension centers. Direct contact by agents of either sex with village women was often
restricted by inadequate transport ibidd., 30; also see Anderson and McBreen 1986).

When women extension agents are the only solution: In all of the examples, extension
agents of both sexes had at least some contact with farmers of both sexes-i.e., cultural sensitivity
did not preclude a male agent from dealing with women farmers (although in the Cameroon
MIDENO project this was not supposed to occur until the women had been initiated into extension
by a woman agent who had built trust and paved the way with possibly reluctant husbands). There
are many areas, however, where it is not culturally appropriate for a male agent to deal one-on-one
with a woman farmer. For example, in areas where seclusion is practiced to some degree, it would
be shameful for all concerned. Here the only choice is to have women agents.
The danger, however, is that they will be cast in the home economics mold, rather than the
"Women in Agriculture" role. All too often, even women home economists recognize that their
clients would rather learn about income-generating activities within the farming system (e.g., raising
small livestock and high value specialty crops in/around the household compound, processing staple
crops and oil seeds for saleable end products) than about embroidery, making face cream, or other
domestic science pursuits. But the home economists lack the training and/or transport needed to
help women with these higher gain, but riskier, ventures. So they stick to low risk, low gain home
economics activities that require less guidance.
Conclusions about women extension agents: Women extension agents may be a necessity
where contact with unrelated males is culturally proscribed, and the evidence indicates that they can
more empathetically communicate with women farmers. But merely hiring women agents is not
enough. If the women agents: (1) remain in the home economics mold, (2) lack transport to get
to women clients who might not be able to reach them, (3) are only rewarded for dealing with
male-dominated cash crops, and/or (4) are not trained to overcome poor women farmers' reluctance
to be forthcoming with high status people, their gender may be irrelevant and women farmers'
productivity may not be enhanced. Women Farmers as Extension Clients-How Much Progress?

Between Ashby's (1981) first major overview of women's access to extension and that of
Berger, Delancey, and Mellencamp in 1984, progress was apparently slow and uneven. The latter
study presents summaries of roughly a dozen projects, worldwide, where women farmers were
ignored. Since the mid-1980s, however, a few governments, especially in Africa, have begun
dealing with women farmers. Their aim is not to help women in particular, but rather to face the
reality that women are the producers of crops crucially important to national development.
Especially where scarce foreign exchange is being expended to import food crops, female food crop
farmers would seem to be an increasingly appealing target.
One common element in several countries' recent approaches to women farmers is working with
them in groups. There are several advantages: (1) lower costs, (2) less cultural sensitivity if the
extension agent is a male, and (3) preference for working in groups on the part of the extension
agents and the women themselves (Blumberg 1986, 1989d). In contrast, men farmers may be less
willing to work in groups.
Here are some examples of increased contact with women as extension clients:

Kenya: Carloni and Horenstein (1986) found a dramatic increase in outreach to female farmers
when extension workers began contacting local self-help groups instead of individual contact
farmers. As other studies also will soon report, since the mid-1980s, there has been a push in
Kenya to reach women's groups as collective "contact farmers" for extension.

Nigeria: At the same time that traditionalists among the management in the Imo State
Agricultural Development Project claimed that male extension agents' (EAs) contact with
women farmers would be culturally inappropriate and resisted by both the male agents and the
women's husbands, a 1986 survey involving a 42% sample (N = 122) of the state's extension
agents showed otherwise (Blumberg 1986). Unexpectedly, an astounding 90% of the male EAs
and all of the females had already begun to work with at least one woman contact farmer.
Only 3 EAs (all male) reported problems with husbands as the result of working with a woman
contact farmer. In this area, extension contact was more likely to begin with individual women
than with women's groups. Only about 12% of the EAs (all of them males) objected to
working with women as contact farmers. All but a handful of EAs claimed that at least some
of their male contact farmers' wives, daughters, and/or female neighbors came to listen to their
instructions at least some of the time.

How well did these women do? Of EAs who worked with at least one woman contact farmer,
52% thought the females) did as well as the males. Moreover, 20% thought their females)
did better than the males. Another 19% had mixed results with their women contact farmers.
Only 9% reported that their females) did worse than their men.

Did women farmers want to be included? Here, the traditionalists among project management
weren't sure, but the women interviewed were. Consensus was high among the 53 women
queried, mostly in a series of five group meetings (about a dozen of the pioneer contact farmers
were included in this purposive sample). All the women wanted to be included in the project's
extension programs. "Only please," they asked, "let us listen to the extension agent in groups,
not just individually." They explained that they were not literate and were afraid that they
might miss part of the message in individual contact. In a group they could help each other

and make sure that they understood properly. They also noted that they were accustomed to
working in traditional women's groups, such as rotating credit societies.

The project management subsequently decided to encourage their EAs to increase the number of
women farmer clients. As noted above, they also decided to transform their home economists
into "Women in Agriculture" specialists. One important reason for these decisions was
management's deepening realization that all three crops in the project "package" (cassava,
cowpeas, and maize) were traditionally female grown/controlled crops. A second reason was
their understandable response to the strong interest, shown by the donor agency, in increasing
attention to women farmers. A second survey was conducted 18 months later (December 1987).
Analysis of responses from 128 out of 300 extension agents (42%) showed that, on the average,
the EAs claimed that at least 25% of the farmers with whom they worked were women.
Further, 86% of the EAs reported that the number of women farmers with whom they worked
had increased in the last year. These 1987 findings should be viewed with a bit of caution,
however, because the EAs were aware of management's increased emphasis on reaching women
farmers and some may have overstated the proportion of women among their extension clients.
Still, responses to a number of the questions remained almost identical in the second survey
(e.g., the proportions saying that their women farmers were doing as well as, better than, mixed,
or worse than men). This fact bodes well for the validity of the data (Blumberg 1989d).

Cameroon: Two studies of the MIDENO project (Walker 1987 and Koons 1988), discussed
earlier, contrast in their assessments of attention to women-even though both note considerable
progress. Walker is more optimistic than Koons and it is significant that Walker's is the more
recent research (Weidemann 1989). For example, while Walker notes that women were twice
as likely as men (52% vs. 24%) to follow recommended planting densities of the improved
maize, Koons points out that women knew far fewer of the extension recommendations than
men. Further, while Walker states that women were just as likely as men to receive visits from
the extension agent, Koons indicates that men received eight times more individual extension
follow-up visits than women (95 vs. 12, received by 27 men and 25 women, respectively)."

The point is that descriptive statistics on increased extension contact with women farmers may
mask more subtle problems involved in successfully incorporating women into extension efforts.
As Koons points out, women are more than farmers. They have multiple roles. And cultural
expectations about their behavior may act as a constraint that prevents full and effective
communication between extension agents (regardless of gender) and female clients. Still, the
fact that Walker's much more positive findings are the more recent indicates that initial
problems in working with women farmers can be worked out. All in all, then, both the Imo
State, Nigeria, and the Province du Nord-Oest, Cameroon, efforts must be considered innovative
successes vis-a-vis use of agriculturally trained women extension agents as well as attention to
women farmers.

An apt conclusion to this section is that pioneering attempts at making extension available to
women farmers must not focus exclusively on women's importance as producers. Rather, both
women's special constraints and their special skills also must be taken into account in designing
successful extension for women farmers. One example is African women's clear preference for

Part of the discrepancy (over and above the difference in timing of research) may be due to different
methodologies and objectives. Koons was examining problems in communication vis-a-vis women farmers. Walker was
documenting the rapid hiring, training, and field posting of what he asserts to be the highest proportion of female
extension agents on the whole continent of Africa (18%).

working in groups. This preference seems related to women's special constraints and special skills.
On the "special constraints" side, lower literacy, and cultural norms of appropriate cross-sex contact
may militate toward group contact. On the "special skills" side, prior organizational experience
may also predispose women toward receiving extension in groups. More generally, women's
"special constraints" include their lower levels of available time, resources (income, credit), good
quality land, culturally appropriate assertiveness, and freedom of movement. Women's "special
skills" include their greater knowledge of food crops, experience with single sex groups (especially
in Africa), and ability to share knowledge and farming inputs with other women, so as to make a
little stretch a long way.

3.5 African Market Women: A Case Study in Women's Economic
Importance, Effectiveness, and Constraints

The market women of West Africa are legendary. There are even stereotypes of flamboyant
entrepreneurs who have never been to school but are canny enough in their trading to merit a
chauffeur-driven Mercedes. Some women do fit the image, and some have achieved an
international scale of operation. For example, women traders/wholesalers were a very visible
component of the passengers filling the jets to and from Lagos, Nigeria during the heady days of
the oil boom and the $1.70 naira. But the overwhelming number of market women deal in small
quantities, in markets overcrowded with competitors, and for low profits. Moreover, women are
traders in many other countries in addition to those of West Africa. Some of the countries where
women's trading is most visible include the Caribbean nations, Guatemala, the South American
Andean nations and much of Southeast Asia, as well as various other African states.


Concerning African market women, the data demonstrate two central points, according to Spring
and Trager (1988, 3): (1) in much of the continent, women play major roles in the internal
distribution of agricultural commodities, and (2) for many African women, trade and marketing are
important components of their income.
In Ghana and Nigeria, in particular:

Women comprise the central participants at all levels of distribution for most of the major
commodities. These areas historically had high levels of urbanization with intermediate towns
and cities that functioned as regional market centers ... In these systems, women traders are
"middlemen" who are responsible for organizing the distribution of goods from one rural region
to another and from rural to urban areas (ibid.). Women Traders in Nigeria

Women traders of a number of Nigeria's 200-odd ethnic groups have been described (e.g., the
Nupe long distance traders studied by Nadel (1942)). But the women in each of the three main

ethnic groups-Yoruba, Ibo, and Hausa-play such distinct and important roles in marketing that
the commonalities and contrasts in their approach to trade are worth describing.
Yoruba women-600 years of pursuing comparative advantage: For at least 600 years, the
Yoruba, in the southwestern part of Nigeria, have lived in their unique "urban farmer" pattern of
large, occupationally diverse towns surrounded by 3-15 miles of fields. Men have been the primary
farmers and women the traders. Women not only dominated town markets but, for centuries, have
engaged in often far-flung itinerant inter-urban trade. Even during the 19th century civil wars,
when travel and trade relied on armed caravans, many of the long-distance traders were women
(Suderkasa 1973, 26). Today, Wipper (1984) estimates, 80% of all Yoruba traders are women.
Trager (1976-77) emphasizes that Yoruba women's trading is basic to the urban and regional
distributive network. They function as: (1) rural traders, selling locally-produced commodities in
rural periodic markets; (2) intermediaries who bulk and arrange for the transport of agricultural
commodities along the rural-urban chain; (3) intermediaries who break bulk by resale to retailers in
the urban markets; and (4) retailers in intermediate and large cities.
Yoruba women are known for their financial independence and for keeping "separate purses."
The classic economic study, Galletti, et al. (1956, 77) found less than 5% who were fully supported
by their husbands. Their strong commitment to entrepreneurial activities is reflected in the fact that
a common greeting among Yoruba women is: "How are you selling?" In recent years, these
dedicated entrepreneurs seem to be pursuing profit and comparative advantage in a new
direction--own-account farming.
Although Yoruba women have been considered farmers only secondarily (mainly as helpers to
their husbands), recent trends of rising prices for certain food crops and falling profits from many
branches of trade have drawn many of them into agriculture. Spiro, for example, found that 34%
of the women randomly sampled in three rural villages were own-account farmers-and 56% of
those had begun farming only in the three years before her study. Rising food prices enabled
women to earn more money by farming and trading than by trading alone (Spiro 1981, 21).
More recent studies (Gamble et al. 1988, and Cashman 1986) have corroborated this trend.
Women stressed declining trading profits as the reason they wanted to begin or expand own-account
farming. But not surprisingly, given 600 years of tradition, most want to combine farming with
Ibo women-farmers first, traders second: Even though Ibo women of the southeastern part
of Nigeria view themselves primarily as farmers, working for both their husbands and on their own
account, they are active traders. Wipper (1985) estimates that 50% of Ibo trading is done by
women. Typically, Ibo women sell surplus produce in the market during the agricultural season
and then focus on trade-possibly in non-agricultural commodities-during the off season. In

common with Yoruba women, Ibo traders rely on rotating credit societies, members of their
kinship/friendship networks, and, sometimes, husbands as sources of capital.
Hausa women-hidden trade from seclusion: One of the world's most unique trading
patterns is that of Hausa women, almost all of whom sell agricultural commodities, prepared snack
foods, handicrafts, etc. from the confines of seclusion in their compounds. Theirs is one of the
most restrictive systems of female seclusion in the world. Premenopausal women are not supposed
to leave their compound during daylight hours. Young, newly married women may go for months
or longer without leaving.
In "Hidden Trade in Hausaland," Hill (1969) first described this pattern. She found that women
engaged in two types of trade from their homes: (1) retailing of farmer-husband's grain and other
produce, primarily on the husband's behalf; and (2) own-account trading (involving about 2/3 of the
women studied). Other studies indicate that, although secluded women deal in everything from
bulked grains to essential spices and household items such as kerosene, their most prevalent "hidden
trade" activity is the processing and sale of cooked foods. For example, Simmons (1976, 8) found
that of 465 women in three sample villages, 398 (86%) reported at least one food-processing
activity as sana'a (an acceptable occupation for a Muslim married woman). Hawking of these
cooked foods is carried out primarily via still unsecluded preadolescent daughters.
Hausa husbands are obligated by Islam to support their wives. Any income that women make,
without breaking the rules of seclusion, is completely under their own control. Thus women are
able to fund a virtually autonomous female economic sphere through clever use of the money their
husbands give them for food. As a result of their seclusion, women gain the time to pursue their
independent economic activities because they have no formal obligation to work in the fields or
fetch water and firewood. Various studies have shown that women get a higher return from their
trading activities than they could from fieldwork, which is not only lower status but much harder.
In this setting, husband-wife relations become highly monetized:

Despite their virtual incarceration for the first 35 years of their married lives, women of the
[village] enjoy a considerable degree of economic independence-thus having more in common
with their sisters in the southern forest country than might be supposed. [Just as other kin
interactions] often involve cash transactions identical to those between non-kin...a husband will
pay his wife at (or near) the standard rate for 'threshing' groundnuts, her obligations being
confined to domestic duties, mainly cooking...[And] a wife who makes groundnut oil for sale
will pay her husband the proper 'market price' for any groundnuts she buys from him.
Although, of course, husbands and wives are apt to help each other in numerous different ways,
a wife's economic autonomy is often sufficient to insulate her from her husband's poverty-as
shown by examples of prominent house-traders whose husbands are notably poverty-stricken
(Hill 1969, 398). Market Women in Ghana

Even more so than in Nigeria, womenmn in Ghana play the central role in nearly all marketing
and distribution activities" (Spring and Trager 1988, 3-4). Women wholesalers are the most
important sources of farm produce sold in urban markets, and women's marketing range extends
from farmgate to final retail sale. Although there are more women in the lower reaches of the
trade hierarchy than at its pinnacle, especially since the 1970s, Ghanaian women traders are found
at all levels.
Robertson's (1984) study of market women in Accra, Ghana presents a number of life histories
from women who are extremely knowledgeable about business in general and market trade in
particular. Most of these women are lower class and uneducated. They move in an essentially all-
female world-one that Adam Smith would have recognized:

Accra, Ghana: A woman in her late 60s who smoked and traded fish until she turned to a
less strenuous activity-making and trading corn wine-when she got old: "If I were giving
advice to a young woman starting out in trade now I would tell them not to waste capital,
concentrate on their work, and keep track of their profit position at all times. You have to
watch the market constantly since it fluctuates all the time. We are all at its mercy. My own
profits went up and down" ibidd., 74).

A woman in her 80s: "My stepmother taught me a lot about business strategy...It was a
lucrative business. I did not specialize in any one type of goods but tried out various
commodities to see what sold best. You have to be constantly alert to seize opportunities and
deal in as many goods as one possibly can. As a result one gets profits from many angles and
will not feel worse off at any one time, especially in the case of farm produce which you can
also use yourself. For example, once I was on my way to a women's church meeting when I
happened upon an auction at the offices of the Accra Town Council. I bought L100 [pounds]
worth of goods there which I then resold immediately in a batch for L107. L7 was a nice
profit then" ibidd., 130).

Other women operated on a considerably larger scale. One wholesaler of imported cloth, for
example, by the 1950s, when she was in her 50s, was turning over between L4000 and L6000
a month. By then she no longer went to the villages herself, but had 10 other women selling
the cloth for her. They got the profits, and she got the commission. In this way, she educated
her five sons, even sending one to Britain ibidd., 102).

Another woman in her 80s: "The main thing I liked about the bead trade was that it was
profitable. Profit is what every person in business looks for, as long as the profits keep coming
you stick to the enterprise" ibidd., 235).

Finally, the women's tradition creates backward linkages and employment, and tends to be
transmitted from one generation to the next. Here is an example from a woman in the fish trade:

"Since fish decomposes easily and there is much competition in the market, I find that the best
strategy is to minimize your per unit profit to outsell your competitors and achieve a fast
turnover. That way in the end you get more customers and more profits. Now I have a canoe
and a fishing crew who fish for me. Sometimes they return from the sea empty-handed. As
an employer I must provide them with money to tide them and their families over. This is, of

course, given against further catches. It is a worrisome responsibility sometimes...Now my
daughter is carrying on with the fish trade" ibidd., 172). Market Women Elsewhere in Africa

Spring and Trager (1988) note that, in various countries, men dominate certain levels of
marketing and/or commodities, while women dominate others (e.g., fruits and vegetables in the
Shona-speaking area of Zimbabwe, vegetables in Burkina Faso). As in Nigeria, within many
countries regional variation is strong. In other areas where markets had not been well developed
before colonialism, women have played a very small role in rural market trade but are now
becoming increasingly important in market activities (e.g., in Tanzania, Zambia, and Uganda).
Spring and Trager generalize that women are important in urban retail market trade, especially
in the informal sector even in countries where their overall role in the market system is less
central. They may sell farm produce in the market, process food for sale, or sell cooked foods,
especially as street vendors. Particularly in the cities of southern and eastern Africa, they may
brew/sell beer. As Jules-Rosette (1988) and others have noted, unlicensed beer brewing provides
both the greatest profits and the greatest legal risks. In fact, she found that in Lusaka, Zambia,
many women's occupations were classified as illegal and/or severely regulated and restricted. This
greatly hindered women's efforts at making a livelihood, and also inhibited the operation of various
sectors of trade (Jules-Rosette 1988). This brings us to the topic of constraints on women.


Women in marketing and trade face numerous constraints already discussed in this paper,
ranging from lack of access to formal credit to having to juggle the "double day" of productive and
reproductive (domestic/childcare) activities. They often face additional constraints as well, since
they frequently pursue the areas of trade that are most commonly the target of state regulatory
policies. For example, in many countries, women often predominate among the street vendors of
cooked foods. One study found that women constitute 94% of these sellers in the Yoruba city of
Ile-Ife, Nigeria and 53% in Ziguinchor, Senegal (Cohen 1986, 5, cited in Spring and Trager 1988,
6). Street vendors, especially of cooked foods, are disproportionately likely to be the object of
state regulatory policies, prohibitions, and day-to-day harassment. For example, most cities have
laws banning street selling in central city locations, even though enforcement and/or harassment
may be intermittent. Other rules about trading also may be on the books and subject to periodic
Evading harassment takes time and money that might otherwise have been invested in trade.
Small scale women traders are more vulnerable to regulatory pressure, since they have less money
for fines or bribes. Sometimes states target trading sectors dominated by women, or women traders


The Ga Trading Hierarchy (Ghana)

ca. 1950s-1960s
'Wholesaleis-cloth, provisions.
hardware store owners

Wholesalers-fish and produce
Market stallhoklers.
kiosk owners

Imported goods sellers
at fixed street and
home locations
Prepared food makers and
sellers at fixed locations-
markets, streets, homes

Occasional traders
-fixed locations
(renters, etc.)

-prepared foods
-petty items


'Wholesalers-cloth, provisions.

hardware store owners

-fish and produce

Market stallholders,
kiosk owners

Retailers at
fixed street and
home locations

Large-scale tbeed
and kenkey sellers

Other prepared food llers,
occasional traders,
-fixed locatis
(renters, etc.)
-prepared feeds
-petty items

* Since most women perform multiple functions.
a cumulative point system might be necessary to rank women within groups.

Robertson 1984, 121

as a group, accusing them of being price gougers who reap huge profits from food and imported
goods.26 But the (apparently) lone study on African consumer exploitation concludes that "charges
of price gouging and other exploitative practices [by] Cameroon food crop vendors are largely
unfounded" (Boyer and Davis 1988, cited in Spring and Trager 1988). The most extreme and
dramatic examples of the persecution of market women have occurred in Ghana, where much of the
private sector distribution system, as we have seen, remains largely in female hands. Robertson
charges that:

In fact, gender identity is increasingly being used by the governments of Ghana in an ideology
which objectifies women traders into a class which can be blamed and persecuted for causing
the enormous economic problems ibidd., 243).

During the 1970s, price controls (begun under Nkrumah) were ever more stringently applied,
mainly to such imported canned "essential" foods as sardines, tomato paste, and condensed milk.
During the Acheampong government years, "its newspapers headlined charges against petty traders
of violating price controls and hoarding essential goods while people starved" ibidd., 244).2
Another government policy toward traders could be called "malevolent neglect" (ibid.). While
market vendors paid substantial revenue to the Accra City Council, successive governments (from
the late colonial era onwards) put very little back into the markets and allowed them to decay
Without a doubt, the most spectacular single act of harassment was the bulldozing of Makola
No. 1 Market, "the center of trade in Ghana, and the chief wholesale and retail market [out of 19]
in Accra" (ibid.). This occurred in 1979, under the first Rawlings government, and soldiers leveled
Makala to a pile of rubble. As Robertson describes it:

'That will teach Ghanaian women to stop being wicked,' a soldier said (ibid.)...Sexist rhetoric
was evident in the campaign against Makola. The Ghanaian Times described the bulldozing as
a 'happy tragedy' producing 'tears of joy' for the 'worker, the common man [who] was
helpless at the hands of the unfeeling Makola conspirators' ibidd., 245). [At the time of the
bulldozing, Makola remained the country's most important hub of trade], despite many efforts
by various [post-Independence] governments to remove control of the distributive system from
the women traders ibidd., 244).

26 Ethnic "middlemen" minorities, such as Asians in certain African countries, may also be singled out in this regard.

According to Robertson, "A typical gesture was the Acheampong government decree of 1976 ordering the street
sellers to buy kiosks from the government; only the larger traders could afford one at an annual rate of C10 [cedis] to
C150. Even some of them went underground) when the government ordered all kiosks abolished in a move worthy of
Catch-22" (ibid.).

2 "In Salaga Market the fishsellers have been evicted from the sole building due to its poor condition; it now echoes
emptily the play of a few children and youthful hawkers inside to escape the broiling sun. There are virtually no
adequate restroom facilities and the aisles are littered with chunks of broken cement and even ordure, on occasion" (ibid.).

Successive governments have been particularly repressive on traders of imported goods. The
cloth market on the street next to Makola No. 1 had been largely abolished even before Makola
was bulldozed. Under the second Rawlings government, mobs attacked the main markets in three
other Ghanaian cities. According to Robertson, the combination of Draconian measures of
oppression of traders (at times even including their summary execution for price control violations),
and the overvalued currency, have "made the best places to buy Ghanaian manufactured cloth the
markets in Abidjan [Ivory Coast] and Lome [Togo]" ibidd., 245).

The upshot? "By [1984], even the produce markets have been severely damaged...
Government repression has mainly hurt the small traders, because they cannot afford
to pay bribes, and the distribution system as a whole, to the further detriment of the
economy" (ibid.).

While the Ghanaian case is extreme, the burden of state regulation and repression has fallen
heavily on the sorts of marketing activities most often done by women. Those activities, as we
have seen, most frequently revolve around food. So once again, the undercutting of women's
activities may well have worsened food availability in a number of African countries.
In summary, the neglect of women food crop farmers and the excessive constraints on the
operations of private sector female food traders and marketers seem to combine in a case of
"negative synergy." Together, these two acts of omission and commission may have an even
stronger impact on food availability in sub-Saharan Africa than either alone. The contrast with the
two examples at the beginning of this monograph is clear: countries that have adopted development
strategies which draw on-and enhance-women's role in production (e.g., the United States, and
the newly industrialized export-oriented Asian countries discussed in section 1.1) seem to have
enjoyed higher national growth. Countries whose development strategies ignore or undercut
women's economically productive roles seem to have suffered-most visibly so in Africa.
This concludes the discussion of the first "chain" of women's impact on the wealth and well-
being of nations-that forged from women's productive activities, especially those that generate
income under female control. Based on the above, the case for integrating women into economic
development seems very strong. Now we turn to the second intertwined "chain," whereby women
contribute to the wealth and well-being of nations via education. Here, "the case for the gender
variable" seems unimpeachable.


The Consequences Of Women's Education:
A Cornucopia Of Human Capital

All the evidence about the consequences of women's productivity-especially where it produces
income under women's control-makes a strong case for Sivard's statement that, "What is good for
women is also good for the society at large" (1985, 7). The data concerning the results of
educating women are even more dramatic. They reveal what a cornucopia of human capital and
positive outcomes ensue from providing schooling to girls and women.
Worldwide, female education is generally associated with:

Later age of marriage,

Lower fertility,29

Lower infant and child mortality,

Improved health for their families and better nutrition for their children,

Greater participation in the measured, waged, modem sector labor force,30

Increased earnings, and

Increased national development, as measured by Gross National Product.

The first six items almost always occur later in the life course than education, so it is plausible
to conclude that female education plays a causal role. The evidence for lower fertility, lower infant
and child mortality, and improved health and nutrition indicates that mother's education has a
stronger effect than either fathers' or an education variable not disaggregated by gender.
The expansion of national growth and development is associated with both higher levels of
female education and a lower disparity in the proportion of males vs. females in school. It is not
yet possible to muster enough evidence to disentangle the direction of causation of what is clearly
an interactive, synergistic process. Nevertheless, in section 1.1, we saw that the evidence for the
United States (based on a series of aggregate production function studies) suggested that an
appreciable part of the growth of the nation's economy since the turn of the century was

29 There are some countries where those with partial primary school education have slightly higher fertility than
those with no education.

3 This occurs over a threshold effect for education that differs within and between countries and over time.

attributable to increases in the stock of human capital-to which women's teaching made a
significant contribution. In fact, not only is the principle of educating females less controversial
than enhancing their production and own-account income, it is hard to find data that show any
negative consequences from the education of females.3
Before examining the consequences of educating girls, let us first look at its prevalence and the
extent of the enrollment gap between females and males. Next we will explore data for each of
the outcomes of female education (from age of marriage through increasing earnings) listed above.
Then we will examine simple regressions, based on a new and preliminary data set on the results
of females' differential access to primary education. The regressions indicate that parity in
male/female enrollments is associated with (among other effects) sharply reduced infant mortality,
lower fertility, and higher GNP per capital. The discussion highlights the importance of females'
education to their nation's wealth and well-being. At the policy level, the data presented indicate
that investment to achieve male/female parity in education at primary and secondary levels may
stimulate a cost-effective and powerful "multiplier effect" of positive economic and social benefits
for the girl, her future husband and children, her community, and her country.

4.1 Comparison of Female and Male Access to Education

The inescapable fact about education in much of the Third World is that, despite a great post-
World War II increase in girls' access to education, the gender gap in schooling is very wide.
Two thirds of the women over the age of 25, compared with about half the men, have never
attended school (Sivard 1985, 5). Even now, females in South Asia are only about half as likely
as males to be literate or schooled, with their prospects only slightly better in the Middle East,
Oceania, and Africa (see Table 8, below). A closer examination of the educational gender gap
reveals statistics showing that in some aspects it is worsening, in other aspects it is little changed,
and in still other aspects it is improving.
First, on the negative, side, the gap in numbers of girl vs. boy students is getting bigger as
enrollment increases, despite the postwar increase in girls' enrollment. For example, Sivard (1985)
found that:

In 1950 there were 27 million more boys than girls enrolled in first and second levels of
education. Currently boys outnumber girls by 80 million. In South Asia alone, where the
male advantage is most pronounced, there would have to be 38 million more school places
just to bring girls' enrollment up to boys' at the present time ibidd., 19).

3 At worst, we find that in a few countries, largely in Africa, increased education is not consistently associated with
lower fertility or higher formal labor force activity. All other positive effects seem to be found worldwide, albeit in
varying degrees.

Moreover, the numbers/gap also is growing among girls:

Combining first and second level education, the gap between girls' enrollment and school-
age population widens. "In developing countries, almost 60% of girls 5-19 are not
inschool. The ratio of enrollees to population is higher than it was in 1950 but, in
absolute numbers, the difference between the population of girls and the number in school
amounts to 350 million, 100 million more than in 1950" (ibid.).

Second, in other aspects, the gap has changed little since World War II, although more girls
attend school than in the past. Here are three such aspects:
(1) Examining the worldwide figures on gender differences in enrollments (Table 7), we see that
the proportion of girls has risen appreciably only for the third educational level (i.e., post-secondary

Table 7: Proportion of Girls vs. Boys, 1950-1985, lst-3rd Educational Levels

First Level

Second Level

Third Level









Source: Sivard (1985, 19).

(2) Girls continue to be more disadvantaged when countries cannot educate all the school-age

According to the UN, school systems in at least one in three developing countries cannot
yet accommodate all the children who should attend school. In Africa, four out of ten
eligible children could not be enrolled in 1980 (Sivard 1985, 18). In almost all LDCs with
such limitations in education facilities, girls are more likely to be left out than boys.

(3) The story is similar for literacy. The wide gap between males and females has not declined
significantly in recent years.

In developing countries, "a literacy average of 50% for women contrasts with 68% for
men," even though there is no literacy gap between men and women in developed
countries ibidd., 19).

Third, on the more positive side, UNESCO data and projections indicate that the enrollment of
girls in the world's schools and universities is about 300 million higher in 1985 than in 1950 ibidd.,
18). "Girls' enrollment quadrupled during this period, rising from 95 million in 1950 to a projected
390 million in 1985" (ibid.). At all age levels, an increasing proportion of girls is able to attend
school. In absolute numbers, since 1960, nearly 500 million more women around the world have
become literate, so the total is now over one billion.
Even Sivard, who compiled the educational gender gap statistics presented above, concludes
that: "Education may well be the area where women have made the greatest gains in recent
decades" (ibid.). Since the consequences of education for girls and women are so positive, it is
good news that girls' Gross Enrollment Rates (GER) are growing worldwide and gender disparity in
education is declining in a number of developing countries."
Table 8 presents a more precise picture of the gender gap in education in developing countries.
The extent of the gap varies greatly by region and country. It is narrowest in the Latin
America/Caribbean Region and widest in South Asia.3 Not surprisingly, the gap is narrowest in the
countries of the developed world, both capitalist and socialist.3

4.2 Age of Marriage: A Prelude to the Education-Fertility Link


The World Fertility Survey (WFS, see United Nations 1987) will be the primary data source in
explicating the positive consequences of educating women. The WFS sample involved 38
developing countries, fairly evenly divided among three regional classifications: (1) Latin America
and the Caribbean, (2) Africa, and (3) Asia and Oceania. Although its primary purpose was to
explain fertility patterns, it presents information on a number of variables associated with education.
One of these is age of marriage, which proves to be strongly related to education. The "singulate
mean age of marriage" (SMAM) for women with seven or more years of education is nearly four
years higher than for women with no schooling. Women with no education marry, on average, at
age 19.2; those with seven or more years of schooling marry at 23.0. This effect is found in all
three regional classifications and at all four development levels (from low to high) into which the
sample is divided. Education has the strongest effect on the age of marriage in the less developed

3 In section 4.8 there are some preliminary regression results for primary education for over 50 countries showing
the relationship of an index of girls' primary school GER and the boy/girl education disparity ratio, on a number of
development indicators.

In fact, data not shown in Table 8 demonstrate that the gender gap in education in Latin America is narrower than
in the least developed European countries-Albania, Greece, Malta, Portugal, Spain, and Yugoslavia.

For example, in the United States since 1985 women have received over half of all bachelor's and master's

of the 38 countries (4.8 years), particularly in the African region (5.2 years). The most dramatic
case is Benin, where women with no education marry at an average age of 16.9 in contrast to those
with seven or more years of schooling who marry at age 24.1-a difference of 7.2 years.


What do these national level data mean in human terms? As part of a larger project that also
researched female seclusion and "hidden trade" in the Northern Nigerian city of Kano, Schildkrout
(1982, 1984) conducted a study of 100 Muslim Hausa children. She studied them in 1976, and
again in 1981, and found that education was very important for their life chances.
In 1976, the same year Schildkrout began the study, the Nigerian government began
implementation of the Universal Primary Education (UPE) Law. In 1976, the only girls enrolled in
school were those whose fathers had some Western education, and whose secluded mothers did not
engage in occupations requiring the constant assistance of children.3 Most people indicated that
their daughters would not go to post-primary school. But the 1981 follow-up study found
that-surprisingly-most of these girls were still in school. Furthermore:

This first generation of school attenders had not only enrolled in secondary school but had
passed the traditional age of marriage [12-14]...With boarding schools [built by the government]
many families were able to accept the risk of delaying marriage. Moreover, the increase of
Western education for men meant that many men were interested in women with some
education (ibid.).

In families where women's trade is carried out with the assistance of preadolescent daughters,
resistance to their schooling continues. The contrast in the lives of the schooled and unschooled
girls is extreme:

Five years after our original study of one hundred children, we found that every girl who had
not been enrolled in primary school was married and in seclusion by age twelve ibidd., 47-48).


Female seclusion, or purdah, is also practiced in Bangladesh, where female educational
disadvantage is great and girls marry early. According to Martin (1987), in 1984 girls comprised
41% of primary school enrollment and only 32% at the secondary level, where most schools are
private and fees are charged. Further:

Data from the 1975 Bangladesh Fertility Survey...indicate that among ever married women...
20-49, those with no schooling married on average at age 12.8 years, those with some primary
schooling at 13.6 years, and those with more than primary at 14.7 years. Unpublished census
data from 1974 show that among females of ages 15 to 19, 81.0% of those with no schooling

5 As noted earlier, many secluded Hausa women's "hidden trade" was conducted via the help of their still-
unsecluded preadolescent daughters, who delivered needed materials and hawked final products.

Table 8

Female Enrollment as a Percentage of Male, Developing Countries, 1980

Adult Numbers Enrolled:
Literacy 1st & 2nd 3rd
Rate Levels Level Average

Developing World 72 76 52 67

Latin America 94 96 77 89
Argentina 99 101 102 101
Barbados 98 97 76 91
Bolivia 73 86 47 69
Brazil 96 100 102 99
Chile 97 99 65 87
Columbia 98 100 66 88
Cuba 100 96 87 94
Dominican Rep. 97 100 85 94
Ecuador 93 98 57 82
El Salvador 90 96 51 79
Guatemala 73 82 40 65
Guyana 97 99 88 95
Haiti 73 85 38 65
Honduras 97 95 59 84
Jamaica 103 104 76 94
Mexico 93 92 50 79
Nicaragua 98 105 48 84
Panama 99 98 119 105
Paraguay 93 92 76 87
Peru 81 91 52 75
Trinidad/Tobago 96 99 65 86
Uruguay 100 100 109 103
Venezuela 93 102 85 94

Middle East 57 69 41 56
Bahrain 69 85 67 74
Cyprus 89 96 71 85
Iran 54 65 48 56
Iraq 47 74 45 55
Jordan 68 87 84 80
Kuwait 75 86 134 98
Lebanon 77 91 34 68
Saudi Arabia 35 63 36 45
Syria 49 70 43 54
Turkey 62 73 33 56
U. Arab. Emir. 63 88 81 77
Yemen, Arab Rep. 11 14 15 13
Yemen, Peoples Dem. 33 55 39 42

Table 8 (cont.)

Adult Numbers Enrolled:
Literacy 1st & 2nd 3rd
Rate Levels Level Average

South Asia 52 56 34 47
Afghanistan 23 20 22 22
Bangladesh 46 49 16 37
India 53 59 35 49
Nepal 16 33 22 24
Pakistan 46 34 36 39
Sri Lanka 87 96 54 79

Far East 82 84 57 74
Brunei 98 96 142 112
Burma 74 90 104 89
Cambodia 50 70 25 48
China 80 30 55
Indonesia 75 83 42 67
Korea, South 92 89 32 71
Laos 71 80 40 64
Malaysia 78 92 55 75
Mongolia 92 104 144 113
Philippines 98 104 113 105
Singapore 80 96 74 83
Thailand 90 90 77 86
Vietnam 91 37 64

Oceania 72 76 25 58
Fiji 88 99 33 73
Papua New Guinea 62 66 21 50

Africa 61 75 36 58
Algeria 40 70 33 48
Angola 53 62 58
Benin 42 52 21 38
Botswana 98 120 62 93
Burundi 38 63 25 42
Cameroon 58 81 21 53
Cent. Afric. Rep. 40 55 17 37
Chad 24 36 7 22
Congo 63 85 18 55
Equatorial Guinea 64 10 37
Egypt 50 71 47 56
Ethiopia 46 54 22 41
Gabon 71 91 30 64
Gambia 41 49 31 40
Ghana 63 74 16 51
Guinea 40 49 26 38
Ivory Coast 53 60 26 46

Table 8 (cont.)

Adult Numbers Enrolled:
Literacy 1st & 2nd 3rd
Rate Levels Level Average

Africa, cont.
Kenya 58 88 23 56
Lesotho 140 140 162 149
Liberia 43 57 38 46
Libya 47 83 30 53
Madagascar 81 88 52 74
Malawi 52 69 31 51
Mali 42 54 14 37
Mauritania 53 14 34
Mauritius 84 93 33 70
Morocco 44 59 32 45
Mozambique 52 71 60 61
Niger 43 56 27 42
Nigeria 50 82 19 50
Rwanda 64 92 7 54
Senegal 45 64 30 46
Sierra Leone 52 63 20 45
Somalia 30 57 11 33
Sudan 37 66 37 47
Swaziland 91 100 57 83
Tanzania 90 88 21 66
Togo 44 56 21 40
Tunisia 56 68 49 58
Uganda 62 71 32 55
Upper Volta 28 59 33 40
Zaire 50 77 20 49
Zambia 73 85 17 58
Zimbabwe 80 83 56 73

Source: Adapted from Sivard (1985, 22-23).

Notes: Where a statistic is not available (-), the average is based on the remaining data.

The data for Brunei are from the early 1970s.

and 70.5% of those with some primary education had already married, but only 36.5% of those
with some secondary education had married (Ahmed and Chaudhury 1981, cited in Martin
1987, 2).

Given this situation, it is worth reviewing the dramatic results of a USAID pilot project which
provided secondary school scholarships to girls in two zones in Bangladesh (Shahrasti Upazilla, in
Chandpur District and Gopalgonj Upazilla, in Gopalgonj District). Begun in 1982, the project had
granted scholarships to over 6,000 girls by 1985. These were awarded solely on the basis of
residence in the project areas. The stipends covered about one-half of a girl's annual total
educational costs, including tuition, texts, supplies, uniforms, and rainy season transportation. In the
Shahrasti Upazilla area, only 27.3% of secondary students were females in 1981, before the project.
This rose to 43.5% by 1984, while dropout rates fell from 23.3% in 1981 to under 5% in 1984
(Ather 1983, 1984).
A remarkable shift in marriage patterns followed this increase in female education. In 1985,
USAID sponsored a survey (Ather 1985) of four groups of girls matched on age (mean = 17.2
years, including both married and unmarried females): (a) 383 scholarship recipients who had
completed secondary school; (b) 58 recipients who had dropped out; (c) 200 nonrecipients who had
completed primary school only; and (d) 200 girls with no schooling. Only 30% of the secondary
completers had married (at mean = 16.5), compared to 76% of the secondary dropouts, 77% of the
primary completers, and 62% of those with no education. The average age of marriage was 15.8
for the secondary dropouts, 14.6 for the primary completers, and 14.7 for the uneducated.
Even the secondary dropouts, most of whom left for marriage, showed one crucial change in
behavior increased contraceptive use. Rates of contraceptive usage were 53% among secondary
completers and 48% among secondary dropouts. This compared with usage rates of only 12% and
14%, respectively, among primary completers and those with no schooling. According to the 1983
Contraceptive Prevalence Survey (cited in Martin 1987, 3), 42.1% of Bangladeshi women with more
than primary school used contraceptives, in contrast to only 21.0% of those with some primary
education, and 16.0% of those with none.
Not just in Bangladesh, but throughout the developing world, female education results in a
higher likelihood of using contraception. The World Fertility Survey found about 25% higher
contraceptive usage among women with seven or more years of schooling (post-primary in most
countries) than with those with no education (United Nations 1987, 214, 237). This brings us to
what many consider the key education linkage for development.

4.3 The Relationship between Education and Fertility

The literature on this topic is enormous. Most of the studies find some kind of a negative
relationship, although it may be non-linear, with slightly higher fertility found among those with

partial primary education than among those with no schooling (the peak seems to occur at about 3-
4 years, per Cochrane (1979a, 36-39)). Until the recent publication of the full World Fertility
Survey findings (United Nations 1987), Cochrane's was the "state of the art" review of the evidence
(Cochrane 1979a).


She found that females' education indirectly affects their fertility in three main ways:

By affecting the "biological supply" of children,

By lowering the demand for children,

By increasing knowledge of contraception.

Education affects the "biological supply" of children by raising women's age of marriage and
reducing the proportion who marry, thus reducing females' exposure to pregnancy. Conversely,
however, education also tends to raise fecundity by improving health and by breaking down
traditional post-partum abstinence taboos, particularly in Africa.
Education lowers the demand for children mainly via enhanced earnings and attractiveness of
job prospects for educated women. Thus, their opportunity costs in raising children rise. More
generally, the perceived benefits of more children diminish, while the perceived costs increase.
Education increases the knowledge of how to regulate fertility via contraception. This better
enables parents to achieve fertility goals.
It should also be noted that Cochrane found an inverse relationship between schooling and
number of children for the husbands as well. But this relation was weaker to begin with and was
reduced greatly when income was held constant. In contrast, the relationship between women's
schooling and fertility became stronger when income was held constant, indicating that it is not
just a function of their economic position. In other words, within a given economic level, more
educated women have fewer children than their less educated counterparts (Cochrane 1979a; LeVine
1980, S81).
These findings were tentative, primarily because of data limitations. The more recent final
report on the World Fertility Survey (WFS) data (United Nations 1987) provides support for all
three major patterns identified by Cochrane. In addition, it offers much needed clarification and
more precise specifications via a series of multiple regressions.


The long-awaited WFS results show that education is strongly and inversely related to fertility
in most countries, but the form and size of the relationship vary considerably. Findings are based
on both Total Fertility Rate (TFR) and Children Ever Born (CEB; to women 40-49), and bivariate
relationships include the following:36

S At current fertility rates, averaged over all countries, women with seven or more years of
education will bear 3.9 children while women with no schooling will bear nearly 80%
more, 6.9 on average. The effect of education is strongest in Latin America and the
Caribbean-3.2 vs. 6.8 children for women with 7+ and 0 years of education, respectively.
The effect is weakest for Africa-5.0 vs. 7.0 children for 7+ vs. 0 education. ibidd., 214;
see also WFS Table 112, in the Appendix).

S The fertility differential by education has increased over time in many countries, due to
greater fertility decline among the better educated.

S Although highly educated women generally have the lowest fertility, women with a few
years of schooling often have slightly higher levels than those with no education, as found
by Cochrane. This pattern is common in the least developed countries, and, regionally, in
Africa. The inverse relation of education and fertility is stronger and more linear in the
relatively more developed WFS countries.

The contrast in the number of surviving children between the most and least educated
women is considerably smaller than the contrast in number of births. This is due to the
lower infant and child mortality among educated women. Averaged over all countries,
women with seven or more years of education had 91% of their children surviving vs.
79% for women with no education. As a result, in the least developed countries, the
number of surviving children is about the same-4.6--for women with 7+ vs. 0 years of
education. Similarly, in tropical Africa, the region with the highest fertility, where the
great majority of the least developed countries are concentrated, women with 7+ years of
education had 4.4 surviving children, vs. 4.8 for women with no education (see WFS Table
113, in the Appendix).

Comparing the impact of wife's vs. husband's education on fertility, fertility differentials
by wife's education tend to be somewhat larger and less often curvilinear than with
husband's education. In the Latin America/Caribbean region, husband's education is
similar in pattern to wife's and almost as strong; in the other two regions, however, the
husband's pattern is weaker and more curvilinear (i.e., wife's fertility is higher when their
husbands have intermediate levels of education). In Africa, a woman whose husband has
7+ years of education has as many or more children than a woman whose husband has
never been to school (see WFS Tables 112 and 114, in the Appendix, and Figure 4

Education differentials are similar in rural and urban areas of most countries, but in a
sizeable minority, the education effect is larger in urban areas.

6 There is a lively literature on the biases, advantages and disadvantages of the various measures of fertility.
Reviewing this literature is beyond the scope of this monograph, but a good discussion of TFR and CEB is found in the
report on the WFS (United Nations 1987, Chapter I).



Mean Number of Children Ever Born to Ever-Married Women Aged 40-45
Years By Husband's and Respondent's Education and By Region

astd faimty reu.
by ,wapodt'Is mducatlo
Ou to Four Sewm
th, to st or more Dffernct:
Zero s wi yu () (4)
_________ W W W ffl

A. Country
Beninb ................... 7.7 6.5 5.6 5.1 2.6
Cameroone ................. 8.1 8.4 8.2 6.4 1.7
C6te d'Ivoired.............. 8.6 8.2 7.5 6.3 2.3
Egypt ..................... 4.5 3.9 3.5 2.6 1.9
Ohanab .................. 6.6 5.8 5.9 5.2 1.4
Kenya.................... 7.6 7.0 6.9 6.5 1.1
Lesotho .................. 6.4 6.3 6.0 5.7 0.7
Mauritaniae.................... 9.0 8.6 7.1 6.0 3.0
Moroccob ................ 5.1 4.0 3.9 3.4 1.7
Senegalb................... 8.5 8.3 6.7 5.0 3.5
Sudanb................... 6.5 6.1 5.4 5.0 1.5
Tunisia................... 4.3 4.0 3.6 3.2 1.1
Latin America
and the Caribbean
Colombia ................... 4.7 4.2 3.8 3.5 1.2
Costa Rica................ 5.7 5.6 4.6 3.7 2.0
Dominican Republic ......... 4.8 4.9 4.5 4.1 0.7
Ecuador .................. 4.7 4.5 4.0 3.3 1.4
Guyana.................... 5.0 4.6 4.9 4.5 0.5
Haiti..................... 3.6 3.4 3.2 3.2 0.4
Jamaica .................. 4.9 4.7 4.3 3.9 1.0
Mexico ................... 5.0 4.8 4.3 3.4 1.6
Panama .................. 4.6 4.9 4.4 3.8 0.8
Paraguay ................. 5.9 5.8 5.0 4.1 1.8
Peru ..................... 4.1 3.9 3.7 3.4 0.7
Trinidad and Tobago ........ 4.0 4.5 4.0 3.7 0.3
Venezuela................... 4.9 4.6 4.1 3.6 1.3
Asia and Oceania
Bangladeshb .............. 4.1 4.0 4.1 4.0 0.1
Fijic ...................... 4.4 4.4 4.3 3.9 0.5
Indonesia................ 4.1 4.3 4.1 4.0 0.1
Jordan ................... 7.2 6.3 5.9 4.7 2.5
Malaysia................... 4.6 4.4 4.3 3.9 0.7
Nepal ........ ............. 3.9 3.7 3.6 3.1 0.8
Pakistanc ................. 4.2 3.7 3.6 3.3 0.9
Philippines............. ... 5.4 4.9 4.6 3.9 1.5
Republic of Korea ........... 3.6 3.5 3.2 2.8 0.8
Sri Lanka.............. .... 4.2 4.0 3.9 3.3 0.9
Syrian Arab Republic ........ 7.0 4.7 4.7 3.9 3.1
Thailand.................. 3.9 3.9 3.7 3.2 0.7
Yemenb .................. 5.4 .. 4.5 ..
B. Averages by region and level of development
Africa........................ 6.9 6.4 5.9 5.0 1.9
Sub-Saharar................ 7.7 7.2 6.6 5.7 2.0
Other ................... 4.7 4.0 3.7 3.1 1.6
Latin America and the Caribbean 4.8 4.7 4.2 3.7 1.1
Asia and Oceania.............. 5.4 4.3 4.2 4.0 1.4
I. High ................... 4.7 4.6 4.2 3.7 1.0
II. Middle-high............. 5.2 4.7 4.3 3.7 1.5
III. Middle-low .............. 6.4 6.0 5.8 5.0 1.4
IV. Low..................... 5.9 5.5 4.9 4.3 1.6
Excluding Sub-Saharan
Africa '
III. Middle-low ............ 4.6 4.1 3.8 3.4 1.2
IV. Low..................... 4.2 3.7 3.6 3.4 0.8
TOTAL 5.4 5.1 4.7 4.1 1.3

Source: World Fertility Survey standard recode tapes.
NOTES: Means are adjusted for the effects of age differences between
educational groups. Desired size not shown for cells containing fewer
than 10 observations. Averages exclude values for such cells.
'Years of schooling completed.

Source: UN 1987, p. 228

Within countries, desired family size is always lower for better educated women, but actual
fertility differentials do not simply reflect desires. Women with 7+ years of education
desired an average of 1.3 fewer children than women with no education. Differences in
number of children desired were most strongly related to education in Africa, which is the
opposite of the actual fertility pattern. In the least developed (largely African) countries,
where the education difference in number of living children is minimal, older women with
moderate to high levels of education are the most likely to have exceeded their desired
family size. In the more developed countries, the proportion with excess fertility decreases
with education.

Regional (or cultural) differences in desired fertility are stronger than differences by level
of development. Thus, women in most countries desire between three and five children;
this rises to five to six in Western Asia, and six to nine in sub-Saharan Africa (see ibid.,

Turning to multivariate analysis, the great advance represented by the WFS permits more
sophisticated specification of the education-fertility linkage. The regressions successively control for
demographic variables such as age of marriage, rural-urban residence, and other socio-economic
factors. Controlling only for the demographic variables, the fertility of women with ten or more
years of education is about 1.5 children lower than women with no education. Adding controls for
rural-urban residence reduces the differential to 1.1 children, and probably provides the best
indication of the overall effect of female education on fertility.
In the regressions comparing the strength of effect of wife's and husband's education on
fertility, wife's education proved stronger. The contrast was -39 births per 1,000 woman years of
marriage for most vs. least educated wives, as compared with only -24 births for most vs. least
educated husbands. In a number of countries, husband's education even had a significant positive
relation with fertility.


In a study utilizing the 1981/82 Socioeconomic Household Survey (SES), 12,620 women
between 15-49 were sampled. Schultz found that: "If the woman's education is one year higher
than average, her fertility rate at the sample mean is 6.4% lower...A standard deviation change in
education (3.4 years) is thus associated with a 21% change (inverse) in fertility" (Schultz 1988, 15;
see also Table 1). Although Schultz later adjusts this figure downward due to an income effect
that is not broken down by gender, this result gives an idea of the kind of impact that education
can have in a population already undergoing rapid fertility decline, as is the case in Thailand.
Between 1960 and 1980, Schultz reports ibidd., 1), total fertility rates in the country dropped 45%,
while the country grew at a rapid 7-8% per year.


Although fertility rates are clearly lower among the most educated African women (with seven
or more years of education), many have puzzled over why most sub-Saharan African women want
and bear so many more children than women in almost any other part of the globe. Other than to
say that Africa is just at an earlier stage of the demographic transition, how can this state of affairs
be explained? Several clues can be found in:

SThe "spillover effect" of low literacy;

The collapse of traditional post-partum sexual abstinence taboos among those with some
education; and

The horticultural, rather than agrarian, "techno-economic heritage" of Africa, which make it
different in ways that may be relevant for fertility.

The "spillover effect": This refers to the effect that others' education, at the community or
even national level, may have on individual women's and couples' fertility. Cochrane noted that:
"If women in general have very little education, an educated woman can afford massive child care
substitutes and thus can combine the benefits of education with high fertility" (Cochrane 1979a, 76).
In general, in countries with high levels of illiteracy, the education-fertility inverse relationship is
both weaker and more likely to be curvilinear. This fits the African situation.
The breakdown of traditional post-partum sexual abstinence taboos: The classic method of
birth spacing in sub-Saharan Africa involves long periods of sexual abstinence after the birth of a
child. Many have argued that the traditional system of polygyny (where men may have more than
one wife) facilitated husbands' compliance with such a taboo. Wives were under strong communal
pressure to maintain at least three year spacing between births, on the grounds that anything closer
would endanger the health of the nursing child. Long lactation was the norm (see, e.g., Page and
Lesthaeghe 1981). Women were further motivated to maintain widely spaced births because of
their own strong tradition of economic activity in farming and, in many instances, trading. These
are more easily accomplished if a woman does not have two tiny children to carry and worry about
at the same time.
Empirical studies presented in Page and Lesthaeghe show that these traditional practices are
breaking down, especially among those who are urban and/or have at least some education. They
are not only less likely to observe long post-partum abstinence, they are breastfeeding for shorter
intervals. The WFS data confirm this pattern. Moreover, urban/educated women are likely to be
healthier and thus more fecund. Studies by Lesthaeghe, et al., (1981) and Caldwell and Caldwell
(1981) conducted in the two biggest cities in Black Africa-Lagos and Ibadan, Nigeria-show that
certain categories of women have begun to respond to this new situation by deliberate contraceptive
practice. "The most important element in the characteristic profile of these women is that most of

them have reached at least a secondary level of education" (Page and Lesthaeghe 1981, 307). The
problem is that so few African women attain it and only with this level of schooling is the
association with fertility almost invariably negative.
The horticultural tradition: Nolan (1988) finds that a horticultural vs. agrarian "techno-
economic heritage" has a direct effect on fertility in a sample of 57 societies. All of his
horticultural societies, however, are in Africa, while the agrarian ones are scattered around Latin
America, Asia, and the Middle East. He invokes ecological-evolutionary theory (developed by
Lenski 1970; see Lenski and Lenski 1987 for the most recent version) to account for this pattern.
Worldwide, women in horticultural societies typically play a much more important role in
cultivation than their counterparts in agrarian societies."
Nolan finds that contemporary "industrializing horticultural societies" have higher levels of child
mortality, smaller service sectors, and larger proportions of their labor forces female than their
industrializing agrarian counterparts. The first two features indirectly raise fertility, while the third
indirectly lowers it" (Nolan 1988, 26, emphasis in original). His analysis controls for the above
factors, as well as the level of development and family planning effort, but the regressions indicate
that he has not specified all the factors pertaining to horticultural societies that account for their
higher fertility.
The patrilineality/patrilocality of most African horticultural societies is one such additional
element that should be taken into account. Even educated, urban women are only minimally
integrated into their husband's patrilineage and have a tenuous relation to resources within their
own. Investing in children may be seen as a rational and, indeed, best strategy if the woman has
few other sources of assistance for crises and old age. Cain, et al. (1979) have found this for
Bangladesh as well. If urban women still can count on "massive child care substitutes," then their
fertility is facilitated. And rural women may have even stronger incentives for high fertility than
their urban counterparts-their need for labor as well as old age/crisis help.
Combining these explanations with some of the constraints on female horticultural cultivators,
reviewed earlier, provides the following possible scenario. First, the fact that the WFS found that
even the most educated category of African women desired 5.0-6.5 children (United Nations 1987,
230), while African women with no education wanted 6-9, needs to be disaggregated by rural/urban.
Although fertility differentials are not great between rural and urban areas, women's reasons and
incentives for observed patterns (as mentioned above) may differ.
Less educated rural women farmers may want high fertility because of the high perceived cost-
benefit ratio. With more of their children in school and so many of the men migrating, extra

This is particularly the case if horticulture is being compared to rainfed (dry) agrarian cultivation; irrigated agrarian
cultivation, especially of wet rice, is so labor-intensive that everyone works (Blumberg 1978, 1981, 1984).

children are useful, from a remarkably early age, for everything from caring for younger siblings, to
fetching water and fuelwood and helping with many farm tasks. The future cost-benefit ratio is
also expected to be positive. Rural women with more education presumably would not have many
non-farming, non-trading economic opportunities that might prove incompatible with high
fertility-and they, too, have a positive cost-benefit ratio and ample child-care substitutes.
Second, even African urban women are infrequently found in modem occupations that are
incompatible with high fertility (discussed in 4.6 below). Uneducated women are likely to be in
the informal sector and thereby have a positive perceived cost-benefit ratio for children. Urban
women with some education are most likely to be caught in the situation described by Page and
Lestheaghe-their fertility enhanced by a reduction in breastfeeding and post-partum abstinence
without a corresponding increase in contraception. Urban women with high education may want
fewer children than their less educated counterparts but because they still can find abundant child-
care assistance and find children an effective hedge against the vagaries of the patrilineal system for
future support, they may continue to want more of them than in other regions.
It must be stressed that, even in Africa, fertility is almost invariably lower among women with
the most education. Over all 38 WFS countries, women, more than men, "show an overall pattern
of decreasing fertility with increasing education...[indeed, i]n roughly 40% of the countries with
available information, women with seven or more years of schooling will have under half as many
children as women with no education at current rates of childbearing" (United Nations 1987, 248).
Given that Hess (forthcoming) found "strong evidence that reducing fertility contributes to
economic growth in contemporary LDCs" ibidd., 174), it is not only women's lives that stand to be
enriched when education opens up life options that reduce their needs for high fertility. The final
results are societal. As Hess traces the process, "lower fertility can 'free up' resources (including
expenditures that would have been used for capital widening and social welfare maintenance) for
human and physical capital deepening. The consequent capital formation combined with a labor
force that, for at least a decade, is no smaller and likely larger, can increase national output" (ibid.).
His data base (49 countries for two time periods encompassing the 1960's and 1970's) shows that
there was a statistically significant increase in real per capital Gross Domestic Product when the
total fertility rate fell ibidd., 173).

4.4 The Link Between Education and Lower Infant and Child

The evidence indicates a strong relationship between mother's education and the survival rates
of her children. But why should this be so? LeVine (1980) proposes a provocative explanation.
In most developing countries, he notes, a girl is socialized:

...to take [her] place at the bottom of a family hierarchy in which she follows parental
commands, rarely seeks the attention of adults, and does not expect her expressed thoughts or
feelings to be taken seriously by them. Participation in the school classroom represents entry
into a new world of values and becomes a form of assertiveness training...The consequences of
this training in adulthood...is a greater tendency to take one's own opinions seriously, act upon
them, believe in the efficacy of one's own actions and refuse to be intimidated by others.
Additional years in the classroom [enhance these effects]. This leads educated mothers to
pursue the health and survival of their children (a traditional goal) more persistently and with
greater determination than women of the same age with less schooling (LeVine 1980, S85-S86).


His (1982) review of the literature showed that:

With regard to data relating to up to 29 developing countries, both bivariate analysis (Cochrane
1979a) and multivariate studies (O'Hara 1979) show that infant and child mortality are lower
the higher the mother's level of schooling. The evidence indicates that a wife's education has a
larger total effect on mortality than that of her husband, but that the combined effects of both
parents being literate (as compared to having no schooling) may be such as to reduce mortality
by up to 27/1000. Finally, there is evidence that maternal education not only reduces child
mortality, but also improves the health of the survivors: children of more schooled mothers
tend to be better nourished (Colclough 1982, 179).


We have already seen that women with higher education have more surviving children. In the
least developed countries-particularly in Africa-this so flattens out the educational differential in
number and percentage of children living at the time of the interview that the mean number of
living children is actually highest for women with intermediate levels of education (1-6 years)
(United Nations 1987, Table 113, 227). Averaged over all 38 countries, the WFS found that:
"Among women aged 40-49, those with seven or more years of schooling average 2.2 fewer
children ever born than women with no education, but the difference in number of children living
is only 1.0" ibidd., 249).


According to Caldwell (1979), although little attempt has been made to explain the observed
negative relationship between maternal education and infant/child mortality, it frequently seems to
have been assumed that mother's education merely reflects the standard of living ibidd., 396; see
also LeVine 1980, S84, from which much of this discussion is taken).

Caldwell challenges the validity of this assumption. In a large-scale research project among the
Yoruba in Western Nigeria in 1973, he and his associates sampled 6,606 women in Ibadan and
another 1,499 in surrounding areas. They found that there was an inverse relationship between
education of the mother and infant/child mortality within age/socioeconomic groups. For example,
among females 40-49 years of age, 29.6% of the children of mothers with no education were
reported to have died, compared to 24.8% of the children of mothers with primary education, and
only 11.8% of those of mothers with some secondary schooling. Younger women had fewer
children who died, presumably because health facilities had improved over time. But within each
age category of women the inverse education-child/infant mortality relationship emerged.
Depending on the age cohort of the mother, the life expectancy of a child whose mother had some
secondary education was between 10 and 17 years greater than the child of a woman who had
never been to school.
Caldwell finds that these differences in child/infant mortality by mother's education are not
related to more educated women's better material circumstances. For example, the link between
mother's education and child's mortality remains strong even among the wives of high status men,
with secondary education and white collar occupations. Not even ease of access to health facilities
and area of residence were important predictors of child/infant mortality in comparison with
mother's education. Caldwell concludes that, "in terms of child mortality, a woman's education is a
good deal more important than even her most immediate environment" ibidd., 405).
Caldwell's analysis included five control variables. Even with all five controlled, the inverse
relation between mother's schooling and child's mortality emerged, "so that children of mothers
with secondary schooling average little more than half the chance of dying than children with
mothers similar in terms of the other five characteristics but who have not had any schooling"
ibidd., 407).
Caldwell concludes that maternal education is, by far, the single most powerful determinant of a
child's survival chances, and that: "Clearly maternal education cannot be employed as a proxy for
general social and economic change but must be examined as an important force in its own right"
ibidd., 408).


LeVine (1980, S85), who presented the above synopsis of Caldwell's work in a paper
describing his own research on maternal education and behavior among the Gusii of Kenya, later
studied the same topic in central Mexico (LeVine et al. 1987). He conducted the research in a
state capital with over 200,000 inhabitants. The sample included 300 women (294 in the final
analysis) who: (a) had 1-9 years of education, (b) had a child under 48 months, and (c) lived in

either a poor squatter settlement on the outskirts of town (N = 73/294) or the crowded vecindades
(one-room flats sharing courtyards and toilets) of the central city (N = 221/294). The mean age
was 25 and the mean number of children was 2.5 and rising.
There had been only 15 child deaths among these 294 mothers; 10 of them involved the 73
mothers in the squatter town. Part of the reason for the high death rate in the shacktown was
exposure to risk combined with limited access to health protection. For example, this shacktown
lacked most urban services found in the vecindades, was far from the municipal general hospital,
and had poor sanitation and water supply. In contrast, the inner city neighborhood was within easy
walking distance of the hospital. In addition, 66% of the inner city mothers had access to one of
the government social security clinics (which provide the best public medical service), compared
with only 45% of the mothers from the squatter settlement.
Nevertheless, maternal education still proved to be important in both locations. Not one of the
15 child deaths occurred to mothers with more than six years of schooling. More educated mothers
were generally more pro-active about children's health. First, even before their baby's birth,
educated mothers were more likely to seek health services: regression analyses in both the
shacktown and vecindades samples showed that mother's education was a significant predictor of
prenatal care even when other household variables were controlled-including social security
membership (which gives access to the government-run healthcare/hospital system). Second, more
educated mothers were more likely to seek quick health intervention for a sick baby: among the
mothers whose infants had had a serious health crisis in the preceding month (e.g., fever, vomiting,
diarrhea), those with at least six years of education were significantly more likely to take their child
to a clinic within three days of the onset of symptoms.
In this study, few of the better educated wives (6-9 years of schooling) earned any money
because they had married men who were in a position to enforce the traditional machista norm that
the wife remains in the home. In contrast, a significantly larger number of the least educated
women were earning income. They worked mostly in the urban informal sector as laundresses,
street vendors, domestic servants, etc. Given that these jobs are not incompatible with high fertility
and that the expected cost/benefit ratio of children is often found to be positive for poor urban
informal sector workers, it should not be surprising that these uneducated women had higher
fertility than the more educated mothers who did not work.
In exploring the consequences of female production/income under the woman's control, section
2.2 presented data on a sample of Mexico City outworkers' whose decision-making power on
fertility was substantially related to the proportion of the household common fund that they
provided. In contrast, in LeVine's sample, the better educated women not only were unlikely to
contribute any income, they also were at a relative disadvantage vis-a-vis their husbands even with
respect to education-they married men with very significantly better educations than their own.

Thus, it is not surprising that among such women over 25 years of age, husband's education proved
much more strongly correlated with fertility than the wife's. Nevertheless, when the husband's
schooling was controlled, wife's fertility was still significantly correlated with her education-she
still had some impact on her own fertility.
In short, the fertility of a better educated woman, who is not likely to work but is likely to
marry a man with the educational and financial resources to enforce the cultural ideal of male
domination, depends more heavily on what her husband wants than her own level of schooling.
Without the clout that independently controlled income gives, these women are less likely to realize
their own fertility objectives if they conflict with their husbands'. But these women are not
powerless; their education also "counts."


They found (1982) that the survival rate of female infants in relation to male babies was higher
in areas where there were better employment opportunities for adult women. In other words, we
can disaggregate infant mortality by gender. In doing so, we find that female infant mortality is
associated with mother's education and the overall economic opportunities for women in an area.
Where these are high, girl babies receive better care.

4.5 Women's Education and Child Health/Nutrition

LeVine argues that more self-confident, assertive, educated mothers pursue their children's
health and survival (including nutrition) more relentlessly than less educated women (LeVine 1980,
S86). Colclough's literature overview (1982, 179) also showed that mother's education improved
the health of surviving children, who tended to be better nourished.
Providing further corroboration of the maternal education-child nutrition link is a study by
Behrman and Wolfe (1984), whose title is quite germane to the points made in this monograph:
"More evidence on nutrition demand: [household] income seems overrated and women's schooling
underemphasized" (1984). The fact that they found household income overrated is in line with the
findings presented in section 2.2 on the greater weight of mother's-as opposed to father's or
household-income on child nutrition. Also, given the mother's much more direct role in food
selection and preparation, her increased education would be expected to translate more directly into
better child nutrition. These findings, no doubt, will be often replicated once studies begin to
disaggregate by gender.
Thus far, however, such disaggregation by gender is uncommon. Many studies merely note that
both parents' education affects child nutrition, without discussing the relative impact of mother's vs.
father's schooling. One such case is Senauer's studies of mother's estimated wage and
intrahousehold food allocation and children's nutrition, presented in section 2.1. He and his

associates also found that "both the mother's and father's education level had a positive impact on
their children's long-run nutritional status. The children whose mothers and fathers had more years
of schooling suffered less stunting" (Senauer 1988, 19).3 This conclusion contrasts strongly with
his results involving income, which showed that increased mother's income helped children's
nutrition but increased father's income hindered it."

4.6 Education as a Determinant of Women's Labor Force Participation

It is important here to distinguish between the standard, census-type measurements of the labor
force, and the more expanded definitions that have begun to appear in the literature in the last
decade (e.g., ILO 1977; Dixon 1982; Anker 1983). The standard approach emphasizes work for
wages in the formal sector and places various methodological restrictions on counting many of the
forms of economic activity in which women are most likely to be engaged (e.g., unpaid family
labor, income generated in the informal sector). The more expanded definitions incorporate these
activities. When only the standard measures are used, women's labor force participation is often
strikingly undercounted.


As a first example, census takers may ask a woman for her "primary occupation" in a Latin
American country where she is culturally constrained to answer "housewife"-even if she has a
strong role in the household's farming operations or engages in various informal sector income-
generating endeavors. Deere (1977) analyzed census data for the Cajamarca, Peru, area. When
women were first asked about their principal occupation, a majority identified themselves as
"housewives"-a status not classified as part of the labor force. But when women were first asked
about their income-generating activities, a majority of rural women reported themselves as
economically active. A thorough analysis of the shortfall in counting female labor force
participation in Latin America due to problems of this sort is undertaken by Wainerman and
Recchini de Lattes (1981). In fact, they estimate that the undercounting of economically active
women may be most severe in Latin America.
As a second example, in a survey in Kenya in 1974, the percentage of women (aged 20-49)
counted as being in the labor force varied from 20% to 90%-depending on whether respondents
were asked about a "job" (eliciting the 20% response) or "work" (producing the 90% response)
(Anker 1983).

~1 Strauss (1987) also concluded that both parents' education level had a significant positive impact on child's
nutritional status.

39 This brief discussion of the link between mother's education and child's health/nutrition is far from definitive. It
was not possible, given the time constraints involved, to delve more deeply into the literature on this topic.

As a third and final example, the 1981 Peruvian National Census included unpaid workers in
the labor force only if they worked 15 hours a week or more. No such hours test was applied to
paid workers. In contrast, the 1985-86 Peruvian Living Standards Survey (PLSS) randomly sampled
5,648 women, aged 20-59, in urban and rural households. It defined "labor force participation...as
any amount of work in paid or unpaid employment" (King 1988, 10). Accordingly, the 1981
Peruvian census recorded a female labor force participation rate of only 21%, while the PLSS
counted 55% of women in the labor force.


Ram (1980) presents a summary of the literature on "labor market situations involving wage or
salary payments." Ram's point of departure is the "human capital framework" prediction that
women's education should be (with some exceptions) directly linked to their market-participation
rates. This is based on the premise that education raises the market earning power (potential wage)
for both genders, and thus provides a stronger incentive for them to seek market work. He also
presents Standing's (1976) approach, within the "discrimination framework," that proposes the
"sexual dualism" hypothesis. This proposition "suggests that a dualistic structure of the labor
market could result in education having different effects on the market-activity rates of men and
women" (Ram 1980, S63).
Turning to the data, Ram establishes that for men, the education-labor force participation link is
positive in both developed and developing countries. For women, he sees it as positive for women
in the United States and possibly in other high income market economies. In the developing world,
the picture is much more complicated. Although there is a tendency for the female market-
participation rate to increase with education, there are numerous exceptions and other variables that
must be taken into account. Moreover, he found, "in several cases, that the relationship between
education and female participation rate seems to be 'curvilinear' in the sense that at low levels of
schooling (e.g., a change from illiteracy to bare literacy) the effect of education on female market-
activity rate is small or negative, while at somewhat higher educational levels the effect is more
clearly positive" (ibid.). Otherwise, he found that the effect of women's education on their labor
force participation rates (LFPR) seems to vary with rural-urban residence, marital status, presence of
children, and husband's or family's income.


Her paper (1988) begins with a review of five recent studies that have estimated labor force
participation equations for Latin American women. One principal finding is that education has a
positive impact on the female labor force participation rate (LFPR). In four of the studies, the
relationship rises with education, although in a nonlinear fashion. But in the fifth (Castaneda 1986,

on Chile), a strongly U-shaped relationship emerges-women with more than 13 years of education
and those who have no schooling are more likely to participate in the labor market than those with
primary and secondary education. In three of these studies, young children (in one study, under
age 3; in another between 1 and 2 years old) have a strong negative impact on women's LFPR
(e.g., one more toddler, age 1-2, in the home reduces a mother's LFPR by 27%).
Of the 5,648 women in King's sample (that of the Peruvian Living Standards Survey), 31%
lived in Lima, 37% in other urban areas, and 32% in rural areas. Using the expanded definition of
labor force participation mentioned above (any amount of work in paid or unpaid employment),
King finds that the overall participation rate was highest in the rural areas-at 85%. The rate was
lowest in Lima at 64% and intermediate in "other urban areas," at 68%. In short, 70% of the
women in the total sample were in the labor force. The breakdown between paid and unpaid work
is particularly relevant:

But, whereas 71% of employed Lima women reported receiving compensation for their work,
only 30% of employed rural women were paid workers while the rest reported themselves as
unpaid workers. Hence, although 84% of rural women were employed during the survey week,
we observe wages, salaries, and/or payment in kind for only 25% of them. [Moreover], 60% of
the paid workers in our sample are self-employed. [Geographically, 60% of paid workers in
Lima are salaried, as are 35% of those in other urban areas and only 15% in rural areas. The
rest are self-employed-and in the rural areas, almost 70% of the self-employed work in
agriculture.] This suggests the overwhelming importance of own and family enterprises as a
source of employment for women, particularly for those residing in rural areas. Private sector
employment is most important in Lima [70% of the 60% who are salaried work in the private
sector, this is more than five times as many as in rural areas] ibidd., 11-12).

Turning to the relation between education and full labor force participation, we find that the
mean education of those in the labor force is lower (5.0 years) than that of individuals outside of
the labor force (6.6 years of schooling). This is due to the fact that rural women, who are the
least educated, have much higher participation rates at all ages than urban women.
If we confine our attention only to paid workers, however, we find that remunerated workers
have higher education (6.3 years) than unpaid workers (3.4 years). Much of this gap is due to
more rural women engaging in unpaid work. In fact, in rural areas, where only one-fourth of the
labor force is in paid employment, an additional year of schooling has the greatest effect on the
probability of being a paid worker, increasing it by 2% ibidd., 28). This is calculated at the mean
schooling level of about 2 years in rural areas.
Another noteworthy finding is that having a diploma greatly increases the likelihood of paid
employment (vs. overall labor force participation, as measured in this study). Women in urban
areas outside Lima increase their chances of paid employment by 27% with a diploma, and women
in rural areas are 21% more likely to work at a paid job. Finally, King found that being married

decreases the likelihood of paid employment for women by about 10%. Paid employment, which
typically has fixed hours and is done away from home, may be less compatible with childcare and
domestic tasks.
All the studies from which Ram and King drew their inferences about the relationship between
labor force participation and education were based on single countries. Synthesizing these findings
is problematic because of noncomparable measurements of labor force participation, measures of
education, and selection/measures of other variables included in the research. What sort of patterns
emerge when we look at the 38-country sample of the World Fertility Survey? As in the case of
the education-fertility link, we can take a large stride forward because "all the data come from the
same drawer."


Noteworthy here is the WFS approach to increasing the precision of the labor force participation
measure. This is part of the push to measure full labor force participation, noted earlier, by
including unpaid family labor, especially in agriculture, and by eliciting women's informal sector
income-generating activities.
The results of an expanded labor force definition are commendable from many perspectives.
But including so many more activities that seldom require educational qualifications raises the
possibility that the new measure will be inversely related to education. This is precisely what
occurred in King's study: due to the broader labor force definition used, the mean educational
attainment of those in the labor force is lower than of those out of it: by -1.6 years for the whole
country (-1.3 years in Lima, -1.1 years in other urban areas, and -0.9 years for rural women) (King
1988, 14). King resolved this problem by differentiating between the paid and the unpaid labor
force. The WFS takes another tack-a dual-faceted approach including: (1) a broad definition to
ascertain if a respondent is currently working, and; (2) a recorded version of the standard categories
of the international occupational code.
A broad definition of "work": The standard question in the WFS questionnaire, used to
ascertain if a respondent is currently "working," is:

As you know, many women work-I mean aside from doing their own housework. Some take
up jobs for which they are paid in cash or kind. Others sell things, or have a small business
or work on the family farm. Are you doing any such work at the present time? (United
Nations 1987, 258).

The data generated by this query show strong regional contrasts:

In Latin America/Caribbean, 23-68% of women were currently working. In Asia and
Oceania, the range is wider, from 11% in Jordan to almost 85% in Thailand. And the
average is somewhat higher at about 45%. In Africa, the variation in labour force
participation is also very broad; the percentage of women currently working ranges from
18 in Egypt to over 90 in Ghana. In addition, the level of women's work was consistently

low in countries with a predominantly Muslim population, such as Bangladesh, Egypt,
Jordan, Pakistan, and the Syrian Arab Republic, where cultural restrictions that discourage
women from doing most types of work are common (United Nations 1987, 259).

With the use of this broad definition of work, the WFS data reveal that a relationship between
education and labor force participation does, in fact, exist. "The data strongly suggest that labour
force participation among women is highly correlated with education" ibidd., 262). But there
actually are three major variations among the 38 countries (shown in Figure 5).
The first, and most typical, is the pattern where work is curvilinearly related to education. In
most of the WFS countries, the most highly educated women and those with no education are most
likely to work, while women in the middle educational categories are least likely to do so. This
pattern is represented by Senegal in Figure 5.
The second major pattern is where the most educated women are by far the most likely to
work. The percentage of women with no education who work is only slightly higher than that of
women in the middle categories (illustrated by the Dominican Republic and Jordan).
A third variation involves a few exceptions (e.g., Cameroon, Nepal, and the Republic of
Korea), where participation declines with increasing education.
Revision of the international occupational code categories: As a second tack, the WFS report
has reordered the standard Edwards-type categories of the international occupational code into four
occupational subgroups: (1) Modem (professional, clerical); (2) Transitional (domestic household
employee, service); (3) Mixed (skilled, unskilled, and sales); and (4) Traditional (agricultural). The
object of this regrouping is to better delineate the relationship between education and the sort of
labor force participation that, presumably, would be most enhanced by it-paid occupations in the
modern formal sector.
According to Cochrane (1979a, 76), such jobs have two important characteristics: (1) they are
"more attractive" in the sense that, "the more attractive a job, the higher the satisfaction derived and
the higher the benefits from work" ibidd.); and (2) they are likely to be less compatible with
childrearing. Often this is because these jobs are done outside the home in a setting to which one
cannot bring children and/or they have irregular and frequently heavy time commitments.
Comparable data should be available for future studies from virtually any one-digit (or more
detailed) coding of occupation.
From the standpoint of the theoretical literature on women's labor force participation, the only
major problem with this recoding of occupational categories is that the "mixed" category blurs the
formal and informal sectors and combines manufacturing labor with other kinds of jobs. Women's
labor force participation in export-oriented manufacturing jobs is an increasingly important variable

University of Florida Home Page
© 2004 - 2010 University of Florida George A. Smathers Libraries.
All rights reserved.

Acceptable Use, Copyright, and Disclaimer Statement
Last updated October 10, 2010 - - mvs