1.
Unpacking the “Gender Box”:
Integrating Gender in Policy Research and Outreach
Photo credit: Agnes Quisumbing

2.
Some terminology
▪ Gender = socially constructed relationships/differences between
men and women
▪ Includes the roles, responsibilities and opportunities associated with being
male or female in a given culture
▪ These characteristics vary among cultures and change over time.
▪ Gender ≠ Sex (biological differences)
▪ Gender ≠ Women (men are also part of gender)
▪ Refer to “women’s empowerment” or
“gender equality/equity,
NOT “gender empowerment”
▪ Male and Female are adjectives
(need to describe something)
Men and Women refer to adult people

3.
Gender analysis
▪ A set of tools for uncovering differences
between men and women in order to ensure
that our research produces policy
recommendations that are appropriate to the
needs of both men and women
oMay be qualitative, quantitative, or both
▪ Which differences are most important will
depend on the context
▪ Emphasis is not on having “right” answers,
which may be right only in a specific
circumstance, but on asking right questions
Photo: Deborah Rubin

4.
When does it make sense to pay attention to gender in
your research?
▪ When there are systematic gender
differences in…
o Outcomes (yield differentials, health
and nutrition indicators, poverty rates,
etc.)
o Determinants (effects of male and
female schooling, male and female land
ownership, male and female headship,
etc.)
o Processes (when there are differences
in the preferences, motivations, and
behavior of men and women)
Photo credit: Katrin Park / IFPRI

5.
Key questions to ask
▪ What different roles/stakes do women
and men have in XXX?
▪ How might a policy or intervention
affect them differently?
▪ Will both men and women realistically
be able to participate and to benefit?
(look at time, assets)
▪ How might differential participation of
men, women affect project activities
and impact?
▪ How could the research contribute to
gender equity?
Photo credit: Milo Mitchell / IFPRI

6.
Gender in Food Systems
Agriculture is highly “gendered” in developing economies (SOFA 2011):
▪ Women make up a large percentage of the agricultural labor force in developing countries
(average 43%, 50% in Africa).
▪Women are disadvantaged in productive asset
ownership (including land and livestock), control of
productive inputs (including access to credit,
insurance, technology etc.).
▪Gender differences in base education levels,
access to services (extension), natural resource
knowledge.
▪Female farmers produce less than men not
because they are less efficient/able farmers, but
because they lack equal access to resources. Photo credit: Deborah Rubin

7.
Reducing poverty
▪ Women are more constrained than men in terms of
control over and access to resources
▪ Women often lack the assets and income necessary to exit
poverty and are subject to gender-based vulnerabilities,
including:
o Fewer benefits/protections under customary or statutory
legal systems
o Lack of decision-making authority and control of financial
resources
o Greater time burdens
o Social isolation
o Threats or acts of violence
▪ Interventions that don’t anticipate the unique dimensions
of women’s poverty or identify the constraints to women’s
full participation often fail to reach their objectives, or may
have unintended effects
Photo: Tanya Axisa/Department for International
Development

8.
Benefits of closing the gender-resource gap
▪ Productivity boost
▪ Women could increase productivity on their farms by 20-30%
▪ This would raise total output at national level by 2.5-4%
▪ Productivity gains of this magnitude have potential to:
▪ Gender gap (OECD index) associated with higher Global Hunger
Index (esp. education gap in SSA)
▪ Reduce in the number of hungry people in the world by 12-17%
▪ 100-150 million people move out of hunger
▪ Multiplier effects on broader economic and social realms
▪ Women, relative to men, spend more on food for the family
▪ Women’s incomes are more strongly associated with child health
and nutrition
FAO SOFA “Women in Agriculture: Closing the Gender Gap for
Development: http://www.fao.org/3/a-i2050e.pdf

9.
Page 10
Misconceptions about gender research
▪ Gender research is not only about child nutrition or schooling: women are
economic, political and social actors
▪ Gender research is not just about women: Also focuses on men and the
differences/relationship between men and women
▪ Not all women (or men) are the same. Important to consider intersectional
identities:
o Narrow focus on differences between men and women may mask differences
among women, e.g. variations by marital status, age, and the size of women’s
land holdings
o Ethnicity, religion, caste, class, level of education, etc. may be more or less
important in different contexts
o Gender studies show how to analyze this
▪ Gender > female headed households!

10.
Economic models of the household
Unitary Model Bargaining Model
Household head is
the benevolent
dictator:
He knows all and
makes the best
decisions for
everyone at all times
No differences in
preferences or goals
of individual
household members
Households consist of
individuals with different
preferences
Intra-hh allocation
determined by bargaining
among individuals with
different bargaining
power

11.
Reality is more complex:
▪ Research shows the unitary model of the
household does not apply
▪ Households do not act as one when making
decisions or pooling resources
▪ Neither is the pure bargaining model
accurate
▪ Intra-household decisionmaking is
complex, with degrees of autonomy and
jointness depending on the decision and
the degree of interest alignment

12.
Assets Well-being
Livelihood
strategy Full income
Consumption
Savings/
Investment
Shocks
Men WomenJoint
Context: Ecological, social, economic, and political factors
Source: Meinzen-Dick et al. 2011b
The Gender, Agriculture, and Assets Project
Conceptual Framework

13.
Levels of gender analysis
Household type
(“MHH” “FHH”)
This is a comparison of household types, not a full gender analysis

14.
Levels of gender analysis
Individual
“Men” “Women”
Household type
(“MHH” “FHH”)

15.
Levels of gender analysis
Individual
“Men” “Women”
Household type
(“MHH” “FHH”)
Plot
“Male managed”
“Female managed”
“Jointly managed”

16.
Objectives of gender-sensitive development programs
▪ Three types of gender-sensitive development programs:
▪ The strategies and activities to achieve these aims will be
different
▪ Need indicators to monitor these programs
Reach Benefit Empower
Include women in
program activities
Increase women’s well-
being (e.g. food security,
income, health)
Strengthen ability of women to
make strategic life choices and
to put those choices into action
17

17.
Example: Nutritious crop disseminated through
agricultural extension
Objective
Reach Benefit Empower
• Deliver agricultural
extension services
to women
• Increase women’s
well-being
• Increase women’s agency
in production and nutrition
decisions
Strategies • Provide
transportation
• Conduct training
during convenient
times of the day
Indicators • Proportion of
women attending
training, receiving
extension advise
• Consider women’s
preferences and
constraints in
design and content
of training
• Sex-disaggregated
data for yields,
income, land use,
nutrition, time use, etc
• Decision making power on
production, income, food
consumption
• Reduction of GBV, time burden
• Enhance women’s
decision making power in
households and
communities, especially on
crops to grow
18

18.
Definition of empowerment
The various material,
human, and social
resources that serve to
enhance one’s ability
to exercise choice
The capacity to define
one’s own goals and make
strategic choices in pursuit
of these goals, particularly
in a context where this
ability was previously
denied
The achievement of
one’s goals
Agency
AchievementsResources
Source: Kabeer (1999)
19

19.
Measuring empowerment
Women’s Empowerment in Agriculture Index (WEAI)
▪ Measures inclusion of women in the agricultural sector
▪ Survey-based index - interviews men and women in the same
household
▪ Designed for population-based surveys
▪ Launched in 2012 by USAID, IFPRI, and OPHI
▪ Details on index construction in Alkire et al. (2013)
Project-level WEAI (pro-WEAI)
▪ Survey-based index - interviews men and women in the same
household
▪ Builds on abbreviated WEAI
▪ Adapted to assess impact of agricultural development projects,
with additional indicators (e.g. mobility)
▪ Details on index construction in Malapit et al. (2019)
http://weai.ifpri.info/

20.
Three types of
agency measured
in pro-WEAI
Power to
(instrumental agency)
Power within
(intrinsic agency)
Power with
(collective
agency)

21.
Pro-WEAI is made up of two sub-indices
Three domains
of empowerment
(3DE)
A direct measure of
women’s empowerment in
3 dimensions
Gender parity
Index (GPI)
Women’s achievement’s
relative to the primary
male in household
Project-level
Women’s
Empowerment
in Agriculture
Index
(pro-WEAI)
All range from zero to one;
higher values = greater empowerment
90 % 10 %
22
http://weai.ifpri.info/

22.
12 indicators of empowerment
Each
indicator
receives an
equal
proportion
(1/12) of the
overall
weight
Empowered
if adequate
in 75% of
indicators
http://weai.ifpri.info/

23.
Data sources (and what you can do with them)
▪ Ways to measure women’s empowerment
with:
o Household-level datasets
o Individual-level datasets
o Individual/plot-level datasets
▪ Existing data sources to look at:
o LSMS-type datasets (plot level, some
individual indicators by household
member)
o Feed the Future datasets (household
and WEAI modules)
o DHS datasets (individual health, some
empowerment indicators)

24.
Indicators for measuring women’s empowerment from existing
datasets - RESOURCES
Sub-categories Examples of Indicators Data required
Natural Capital
Share of women with legally recognized land rights Land ownership by hh member
Share of land managed by women for production Plot manager by hh member
Ownership of livestock and other assets Asset ownership by hh member
Access to productive resources like fertilizer Input data at plot level
Financial Capital
Access to a financial account (sole or joint) Has access, solely or jointly, to a financial account
Share of women with access to credit (hh or
individual level)
Belongs to a household that used a source of credit in the past
year
Government credit Share of women with a loan from a government institution
Social Capital
Number of family members in the village Social network data
Civic/political participation, membership in groups Participation in groups, political participation
Privacy--ability to be interviewed alone Ability to be interviewed alone
Human Capital
Nutritional status of women Sex-disaggregated nutrition indicators (e.g. MDD, anthropometry)
Access to extension/training Contact with extension agents, participation in trainings
Years of education/literacy Years of education/literacy
Physical Capital
Access to sanitation infrastructure (toilet) HH with ventilated/improved latrine
Access to electricity HH has electricity
Access to domestic water Distance/time to domestic water source
Has mobile phone Access to mobile phone
Enabling Environment
Inheritance norms and rights Legal rights to inheritance of land and non-land assets
Reproductive autonomy Legal reproductive rights, access to birth control
Access to services (schools, clinics, markets) Distance to clinics, schools and markets, etc.
Access to health and nutrition services Visited by a health extension worker

25.
Survey module examples: The household roster

26.
Survey module examples: Land and assets

27.
Indicators for measuring women’s empowerment from
existing datasets - AGENCY
Sub-categories Examples of Indicators Data required
Instrumental "power to"
Decision-making Pro-weai indicator
Mobility Pro-weai indicator
Work balance F-to-M ratio, time spent on (1) unpaid care work (2) econ. activities
Control over use of income Pro-weai indicator
Input in productive decisions Pro-weai indicator
Access to and decisions on financial services Pro-weai indicator
Perceived land ownership Percentage of women with perceived tenure security
Ownership of land and other assets Pro-weai indicator
Collective "power with"
Group membership Pro-weai indicator
Membership in influencial groups Pro-weai indicator
Attends meetings Attending a meeting organized by the DA
Intrinsic "power within"
Attitudes about domestic violence Pro-weai indicator
Respect among HH members Pro-weai indicator
Self-efficacy Pro-weai indicator
Autonomy in income Pro-weai indicator
Autonomy in production Weai indicator
Reproductive autonomy Women feel they have autonomy over their pregnancy
Entrepreneurial attitudes WEAI4VC indicator

28.
Survey module examples: Control over income

29.
Indicators for measuring women’s empowerment from existing
datasets - ACHIEVEMENTS
Sub-categories Examples of Indicators Data required
Education
Years of education completed Education at individual level
Enrollment Enrollment rates in primary, secondary and tertiary education
Literacy Literacy at the individual level
Participation in the
economy
Employment rate (sex-disaggregated) Percentage of women and men in paid jobs
Micro enterprises Number of women with their own micro enterprises
Development agents Number of women who work as DAs
Income ratio of men and women Income data at the individual level
Political engagement
Share of women in leadership positions (community,
govt. etc.) Community, government data
Health
Adolescent fertility rate Fertility rates by age
Access to/use of reproductive health services Specific data on reproductive health
Materal mortality rate Maternal (and infant) mortality rates
Diarrhea incidence Individual data for children <5
HIV rates HIV rates (sex disaggregated)
Violence against
women
Incidence of intimate partner violence (IPV) Indicence of domestic violence
Incidence of rape Incidence of rape and sexual harassment
Incidence of FGM Incidence of female genital mutilation
Incidence of early marriage Indicence of marriage before the age of 18
Nutrition
Food security Household or individual indicators (HFIAS)
Dietary diveristy Women's Dietary Diversity (MDD-W)
Incidence of micronutrient deficiencies Testing for anemia, vitamin-A etc.
Anthropometrics Weight-for-height, height-for-age, BMI

30.
Survey module examples: IPV

31.
How does having a gender lens enrich policy research?
Examples from PRCI Research Areas:
▪ Healthy Food Systems (Agriculture-Nutrition Pathways)
o Example: Influence of Gender on Irrigation-Nutrition Pathways
▪ Resilience (and Climate Smart Agriculture)
o Example: Gendered Awareness and Adoption of CSA
▪ Inclusive Agricultural Transformation
o Example: Agricultural Value Chains and Gender

32.
Value of “Unpacking the Gender Box”: Example 1
Agriculture to Nutrition Pathways Influenced by Gender
Source: Passarelli et al. 2018;Adapted from Kadiyala et al (2014), Herforth and Harris (2014), Gillespie et al (2012) and
Headey et al (2012).

33.
Policy implications of gender influence on agriculture-
nutrition pathways
▪ What does this mean for policy/programming?
▪ Consider women’s preferences across
agriculture-nutrition pathways
▪ Consider how women access irrigation (what
are the constraints?)
▪ Design agricultural interventions to benefit
both men and women
▪ For more information on ag-nutrition pathways: Kadiyala
et al (2014), Herforth and Harris (2014), Gillespie et al
(2012) and Headey et al (2012).
▪ For information on irrigation-nutrition-gender pathways:
Bryan and Garner (2020), Mekonnen et al. (2019),
Passarelli et al. (2018), Domenech (2015),

34.
Value of “Unpacking the Gender Box”: Example 2
Awareness and Adoption of Climate-Smart Practices is Gendered
Awareness
Adoption (conditional on
awareness)
Men Women P-Value Men Women P-Value
Irrigation 97 97 0.8124 62 55.4 0.0358**
Crop residues 56 54.1 0.5976 44 40.6 0.5581
Compositing 79 70 0.0075*** 37 39.7 0.5341
Manure management 62 60.2 0.5268 52 36.7 0.0009***
More efficient use of fertilizer 88 55.7 0.0000*** 83 64.2 0.0000***
Improved, high yielding varieties 62 41.9 0.0000*** 55 48.1 0.0785*
Stress-tolerant varieties 3.4 1.5 0.0992*
Improved feed management 31 25.7 0.0606* 53 67 0.0393**
Switching to drought or pest tolerant
species/breeds
6.4 1.5 0.0007*** 8.3 16.6 0.5589
Improved stoves 70 70.2 0.9242 6.1 4.1 0.3046
Agroforestry 57 43.7 0.0003*** 8.4 4.8 0.0835*
Integrated pest management (IPM) 79 64.9 0.0000*** 51 48.1 0.5882
Improved grain storage 44 36.3 0.0397** 22 59.8 0.0000***
Source: IFPRI-CCAFS Dataset, Bangladesh

35.
Policy implications of gender
dimensions of CSA
▪ What does this mean for policy/programming?
o Lots of other differences in men’s and
women’s resilience capacities (e.g. different
access to and control over assets, different
bargaining power)
o Understanding gender roles and preferences
in agriculture is essential to designing ag
programs that include and benefit both men
and women
o Women have important contributions to CSA
o Achieve co-benefits other well-being
outcomes
o Cannot achieve scaling with only men farmers
▪ For more information: https://gcan.ifpri.info/

36.
Value of “Unpacking the Gender Box”: Example 3
Agricultural Value Chains and Gender

37.
Policy implications of research and practice on gender
equality in agricultural value chains
▪ Women’s participation in agricultural value chains (beyond production) increases
returns but does not automatically result in social upgrading (Barrientos 2014; Rubin
and Manfre 2014; Markel and Jones 2015)
▪ Agricultural wage work is still an important vehicle for women’s empowerment (IFC
2016; Fintrac 2018)
▪ Gender sensitive interventions (household methodologies, integrated –programs,
VSLPs) are needed to increase women’s participation in, benefits from, and
empowerment effects of agricultural value chains. And to make agribusiness
workspaces safe (Rubin, Manfre, and Nichols Barrett 2009)
▪ Lots of guidance is available to improve value chain program design, gender analysis,
and M&E efforts (e.g., Mutua et al. 2014; Nang’ole et al. 2011; Stoian et al. 2018; USAID
2009)

38.
Conclusions: Integrating gender into the research
process
▪ Priority setting:
o Who participates in setting the research agenda?
o Are women’s issues/concerns reflected in research agendas?
▪ Research (and technology) design:
o Are gender issues considered in research/technology design?
o Are gender experts/end users consulted?
▪ Implementation and conduct of research:
o Are gender dimensions of research adequately budgeted for?
o Do researcher teams have access to tools, data, expertise to
examine gender dimensions?
o Do new technologies reach/benefit women?
▪ Communicating for impact:
o Gender analysis deepens research findings and results with
implications for policymaking, targeting, etc.
Credit: ©2012CIAT/NeilPalmer

39.
Resources: Data
▪ IFPRI Data Repository: https://dataverse.harvard.edu/dataverse/IFPRI
▪ USAID Feed the Future Datasets: https://data.usaid.gov/browse?Data-Asset-
Profile_USAID-Initiative=Feed+the+Future
▪ LSMS Datasets: https://microdata.worldbank.org/index.php/catalog/lsms
▪ DHS Datasets: https://dhsprogram.com/data/available-datasets.cfm
▪ GCAN Harmonized Datasets: https://gcan.ifpri.info/category/outputs/Datasets/

40.
Resources: Toolkits and Frameworks
▪ WEAI Resource Center http://weai.ifpri.info/
▪ Gender, Agriculture and Assets Program website (Methods toolkit, practitioners’ guide, etc.)
http://gaap.ifpri.info/
▪ IFPRI Gender toolbox: www.ifpri.org/themes/gender/gendertools.asp
▪ World Bank/FAO/IFAD Gender & Agriculture Sourcebook: www.worldbank.org/genderinag
▪ FAO State of Food and Agriculture 2011: http://www.fao.org/docrep/013/i2050e/i2050e.pdf
▪ GCAN Framework: https://gcan.ifpri.info/framework-2/
▪ CCAFS Gender Toolkit:
https://cgspace.cgiar.org/bitstream/handle/10568/45955/http://CCAFS_Gender_Toolbox.pdf
▪ http://gender.ifpri.info -- sign up for notifications

41.
Resources: Publications (1)
▪ A. Quisumbing, R. Meinzen-Dick, T. Raney, A. Croppenstedt, J. Behrman, and A. Peterman (Eds.) Gender in
agriculture and food security: Closing the knowledge gap. Dordrecht, The Netherlands: Springer and FAO.
http://link.springer.com/book/10.1007/978-94-017-8616-4.
▪ Quisumbing, A.R., et al. 2014. Reducing the gender asset gap through agricultural development: A
technical resource guide. Washington, D.C.: International Food Policy Research Institute (IFPRI).
http://www.ifpri.org/sites/default/files/publications/gaap_techguide.pdf
▪ Malapit et al. - Development of the project-level Women’s Empowerment in Agriculture Index (pro-
WEAI) https://doi.org/10.1016/j.worlddev.2019.06.018
▪ Blog: Reach, benefit, or empower: Clarifying gender strategies of development
projects http://a4nh.cgiar.org/2016/11/29/reach-benefit-or-empower-clarifying-gender-strategies-of-
development-projects/?utm_source=Email&utm_campaign=GNIE29Nov
▪ Doss CR,Kovarik C, Peterman A, Quisumbing AR, van den BoldM. 2013. Gender inequalities in ownership
and control of land in Africa: myths versus reality. IFPRI Discuss. Pap. 01308, Int. Food Policy Res. Inst.,
Washington, DC Or Doss, C. R., C. Kovarik, A. Peterman, A. Quisumbing, and M. van den Bold.
Forthcoming. “Gender Inequalities in Ownership and Control of Land in Africa.” Journal of Agricultural
Economics. (http://www.ifpri.org/publication/gender-inequalities-ownership-and-control-land-africa).
▪ Ahmed, A.U., J. Hoddinott, P. Menon, A. Quisumbing, S. Roy and M. Younus. 2018. Agriculture, Nutrition,
and Gender Linkages (ANGeL) Evaluation Results. Dhaka: International Food Policy Research Institute
(IFPRI).

42.
▪ Cheryl Doss: "If women hold up half the sky, how much of the world's food do they produce?"
(http://www.fao.org/docrep/013/am309e/am309e00.pdf)
▪ "Standards for collecting sex disaggregated data for gender analysis"
(http://www.pim.cgiar.org/2014/07/31/standards-for-collecting-sex-disaggregated-data-for-gender-
analysis/)
▪ Doss C. 2014 "Data needs for gender analysis in agriculture"
(http://www.ifpri.org/sites/default/files/publications/ifpridp01261.pdf)
▪ Meinzen-Dick, R., A. Quisumbing, J. Behrman, P. Biermayr-Jenzano, V. Wilde, M. Noordeloos, C. Ragasa,
and N. Beintema. (2011a). Engenderingagriculturalresearch. IFPRI Monograph. Washington, D.C.:
IFPRI. http://www.ifpri.org/sites/default/files/publications/rr176.pdf
▪ Meinzen-Dick, R., N. Johnson, A. Quisumbing, J. Njuki, J. Behrman, D. Rubin, A. Peterman, and E.
Waithanji. (2011b). Gender, assets, and agricultural development programs: A conceptual
framework. CAPRi Working Paper 99. Washington, DC: IFPRI. 2008.
http://www.capri.cgiar.org/pdf/capriwp99.pdf.
▪ Meinzen-Dick, R., Q. Bernier, and E. Haglund. (2013). The six “ins” of climate-smart agriculture:
Inclusive institutions for information, innovation, investment, and insurance. CAPRi Working Paper No.
114. Washington, D.C.: International Food Policy Research Institute.
http://dx.doi.org/10.2499/capriwp114
Resources: Publications (2)

43.
▪ Quisumbing, A., Meinzen-Dick, R., and Njuki, J. (Eds). 2019. Gender Equality in Rural Africa: From
Commitments to Outcomes. ReSAKSS 2019 Annual Trends and Outlook Report. Washington, DC:
International Food Policy Research Institute.
http://www.ifpri.org/cdmref/p15738coll2/id/133470/filename/133685.pdf
▪ Chapter 1 Introduction [Download]
Chapter 2 Gender and social norms in agriculture: A review [Download]
Chapter 3 Gender and leadership in Africa: Exploring the nexus, trends, and opportunities [Download]
Chapter 4 Women’s land rights in Africa [Download]
Chapter 5 Beyond access: Gender-transformative financial inclusion in agriculture and entrepreneurship [Download]
Chapter 6 Building an inclusive agriculture: Strengthening gender equality in agricultural value chains [Download]
Chapter 7 Building livelihoods for rural youth: A gendered perspective [Download]
Chapter 8 Gender and trade in Africa: Case study of Niger [Download]
Chapter 9 Addressing gender and social dynamics to strengthen resilience for all [Download]
Chapter 10 Toward gender equality: A critical assessment of evidence on social safety nets in Africa [Download]
Chapter 11 Women’s control over income: Implications for women’s empowerment and the agricultural sector [Download]
Chapter 12 The promise and challenges of gender data [Download]
Chapter 13 Tracking key CAADP indicators and implementation processes [Download]
Chapter 14 Concluding remarks [Download]
▪ Case Study 1: Cultural Institutions and Gender Norms in Matrilineal and Patrilineal Kinships of Malawi
Case Study 2: Engaging Men in Creating New Gender Norms and Practices: Lessons from CARE
Case Study 3: Why Gender Matters for Agricultural Productivity in Africa
Case Study 4: Developing Gender-Inclusive Products and Programs: The Role of Gender in Adoption and Consumption of
Biofortified Crops
Case Study 5: The Role of Men in Nutrition: Reflections from Malawi
Case Study 6: How Empowered Are Women in African Agriculture?
Resources: Publications (3)

44.
THANK YOU!
Follow up with more questions:
Ruth Meinzen-Dick, https://www.ifpri.org/profile/ruth-meinzen-dick
Elizabeth Bryan, https://www.ifpri.org/profile/elizabeth-bryan