women's invisibility in the workforce census data. The reasons behind this and their reasons for working in Unorganized sectors.

1. Work Participation of Rural
Women in the Third World
By Bina Agarwal
Presented by Medha Bhattacharjee
CIA III
1424517
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2. About the Author and the Article.
• Economic and political weekly 20 (51/52): A 155-64, 21-28 December
1985.
• Bina Agarwal is a Professor of Development Economics and Environment
at the University of Manchester, UK. Until recently she was Director of the
Institute of Economic Growth, Delhi University.
• Among her best known works is A Field of One's Own : Gender and Land
Rights in South Asia (Cambridge University Press, 1994) which was
awarded the A.K. Coomaraswamy Book Prize 1996; the Edgar Graham
Book Prize 1996.In her latest book, Gender and Green Governance (Oxford
University Press 2010), Agarwal explores the impact of women's presence
on forest governance and conservation. Nobel Laureate Elinor Ostrom
endorses the book as follows: ‘Bina Agarwal has crafted a book of central
importance in today's world. … With analytical rigour and originality,
Agarwal bridges major gaps in our understanding of the difference women
can make, when they are actively involved in forest governance.'
• In 2008, Agarwal received a Padma Shri from the President of India for her
contributions to education; and in 2010 the Leontief Prize from Tufts
University ‘for advancing the frontiers of economic thought.'2/9/2015 Medha Bhattacharjee 2

3. BINA AGARWAL
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4. Third world countries
• The term Third World arose during the Cold War to define countries that
remained non-aligned with either NATO, or the Communist Bloc.
The United States, Western European nations and their allies representing
the First World.
• The Soviet Union, China, Cuba, and their allies representing the Second
World. This terminology provided a way of broadly categorizing the
nations of the Earth into three groups based on social, political, cultural
and economic divisions.
• The Third World was normally seen to include many countries
with colonial pasts in Africa, Latin America, Oceania and Asia.
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5. Introduction
• Problems of unemployment, poverty and destitution have long been the
stated concerns of development policy in most Third World countries.
• In many instances these problems are also gender-specific and that any
serious attempt to alleviate these conditions will require a particular focus
on the women of poor households.
• Insights into the micro studies have received very little attention and the
national level statistics which are considered while framing developmental
policies are severally impaired by biases, which leads to an undercounting
of women, both as workers and as those available for work. There are also
lacunae in data coverage which results in faulty conceptualisation based
on which policies are instituted to help the poor are misdirected.
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6. Sections in this Article
• Section II: Why there is a need to focus on
women separately from men in planning rural
employment & income generating schemes and
the inaccurate gender-related information can
lead to faulty schemes.
• Section III: Biases in census information.
• Section IV: Inadequacies in data coverage.
• Section V: Points to some conceptual biases in
data use.
• Section VI: What can be done?
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7. Section II: Need for a Focus on women in
development schemes and Data collection.
• Micro-studies point out the dangers of state – sponsored schemes which
seek to raise the welfare of poor households, based on limited knowledge
of inter-household division of labour and income between women and
men, or of women’ s independent need for employment or economic-
earning opportunities.
• Firstly there is a need to address the coinciding interests of men and
women.
• Secondly in many cultures the programmes for development of
agricultural sectors are planned and these new information and practices
are made available only to the men.
• Thirdly large number of households have women who are the sole bread-
winners but their data is fragmented.
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8. • Inadequate information is not the sole cause of misconceived income
generating schemes, or the failure to pay attention to questions of
women’s poverty and unemployment. The gap between the policy and its
implication can be very crucial. The data available serves as an input into
policy making in Third World countries. Therefore any data inadequacies
has serious repercussions on the effectiveness of economic resources
allocated to development schemes, which are derived from seriously
misconceived notions about the role of women in regards to their
employment and income needs.
• This data shortcomings concerning to rural women and their work stems
from the method of data collection, the concepts and definitions used and
the lastly the analysis of the data.
• Example : women’s work is always discounted on a Priori assumptions of
their lower productivity relative to men’s.
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9. Section III: Biases in Data collection
• A count of those not working but ‘available 'for work would be needed
to measure the number of ‘involuntarily’ unemployed women. This gives
an idea of female underemployment. The information together with
some general characteristics of women workers and those ‘available’
would be necessary for formulating policies to provide income-earning
opportunities.
• The nature and the sources of biases in the existing data which seriously
affect heir accuracy and usefulness.
1. Respondent and Enumerate Biases.
2. Definitional Biases.
3. Changes in Definitions and problems of compatibility.
4. Measurement of female unemployment.
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10. Section IV: Coverage Inadequacies
• The existing macro-data sources are severely limited in their ability to
provide details about the characteristic of employed and unemployed
women, such as their status as household heads, the number of
dependents they have, their economic status and agrarian class , their
levels if skills for which they will work for.
• Family headship is an existing feature of many census in Third World
countries the information is often not available in published census data
and if available it is distorted by cultural and definitional basis.
• The census data tend to under numerate female-headed households.
• The identification of female household heads and their economic means is
clearly important for planning appropriate income –generating schemes.
• The NSS data which consider the time intensity of work effort do not
adequately capture this dimension.
• In this context an important additional dimension is the possible
difference between different socio-economic classes in the sexual division
of labour.
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11. Section V: Some conceptual Biases in
Data Use.
• The available data which is used in economic
analysis reflects a male bias.
• Female labour is assumed to have less efficiency
than male labour. Sometime women are paid
3/4th of what men are paid. Wages paid are not
necessarily indicative of differences in
productivity.
• Sex-typing of tasks is noticed, where there is a
predominance of women in certain tasks and
men in others. Example: cotton-picking and
harvesting of other crops.
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12. Section VI : What can be done?
• Urgent need for taking corrective measures in the data gathering
process and for re-examining analytical concepts as they relate to
women, to overcome their shortcomings.
• A specific attempt can be made to enlist female enumerators and to
seek out female respondents.
• Appropriate modifications of the definitions adopted to identify
women who are employed or unemployed.
• A sounder empirical base for assessing time contribution of rural
women in the agrarian economy is needed.
• A research on understanding the effect of technological innovations
on women belonging to different socio- economic classes. As some
inventions makes life simpler for certain section of women and on
the other deprives the other from their crucial source of livelihood.
• Regional specific research that could focus on the specific needs.
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13. ELA RAMESHBHATT ( Founder of SEWA)
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14. THANK YOU
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