Advanced Techniques for Incorporating Gender Analysis in Economics Research

www.iita.orgA member of the CGIAR System Office
Advanced Techniques for Incorporating
Gender Analysis in Economics Research
Shiferaw Feleke and Paul Donstop
Ibadan, Nigeria
Nov. 21. 2016
P4D week; 21 November 2016
Ibadan, Nigeria

Outline of Presentation
Motivation and objectives
Analyzing Gender Issues in Agriculture
Developing Research Questions and
Identifying Methodologies
Collecting Sex-Disaggregated Data

Motivation
• Currently, gender research is primarily based on
qualitative analysis
• Qualitative gender analysis provides greater insights
into various gender issues
• However, results of quantitative analysis cannot be
generalized to a broader audience or the public
• As a result, it is difficult to build a case for mobilizing
policy action for addressing gender issues

(Contd.) Motivation
• Therefore, there is an increasing need for a
incorporating gender in CGIAR economics
research
• CGIAR agreed outcomes:
– Increase control over resources and participation
in decision making by women
– Development outcomes
• Expanding the gender research work beyond
anthropology and sociology

(Contd.) Motivation
• However, it has been challenging to generate
insightful analysis of the gender issues
• The gender training in Washington was motivated
by this need.
• Now, the question is:
– What are the challenges to generate insightful
analysis of the gender issues?
– What are the techniques?

Why no insightful analysis?
1. Conceptual: Limited understanding of key
concepts
2. Poor research design (study type, research
question, hypotheses, variables, and data collection
methods)
3. Not integrating quantitative analysis with
qualitative analysis
4. Not using sex-disaggregated data
5. Not taking into account gender during sampling
and power calculations

Conceptual
1. Analyzing Gender Issues in
Agriculture

1.1. Defining gender based on the sex of the
head of the household
• Gender is defined as FHH and MHH
• Comparing FHH and MHH is not gender analysis for a
variety of reasons
• It ignores the women in MHHs and men in FHHs
• It ignores the gender relations and the influence of bargaining
power in the intra-household allocation & distribution
• It fails to account for the unequal access to and control over
resources within the household
• As a result, we can’t assess the effects of gender differentials
on consumption, education and health outcomes
• It perpetuates the assumption of equal consumption (e.g.
poverty analysis)

1.2. Not identifying what gender represents
• When using FHH vs. MHHs, what exactly
are we talking about?
• Are we talking about difference in access
to and control over, mgmt., ownership,
bargaining power imbalance e, etc.?

1.3. Considering women as a homogenous
group
• The effect of gender on an outcome variable may
not be direct but through other variables
• Gender interacts with other attributes such as age,
ethnic background, social class, birth order,
marital status, etc.
• The failure to include interaction terms with
gender may lead to an erroneous conclusion about
the effect of gender

1.4. Not being able to identify the right gender-
sensitive indicators
• The decision of which gender indicators to
use for measurement matter in gender
analysis
• Gender indicator:
– Female plot ownership, relative to male plot ownership –
vs. sex of household head
• Peterman et al. (2011) - JDS finds that the choice of gender
indicator matters

1.5. Not identifying the underlying household
behavior – unitary vs. collective ?
• Unitary models – represent household behavior as
resulting from the decisions of a single individual
• Collective models - represent household behavior as
resulting from the decisions of several individuals within
the household
• However, we usually use unitary models
• This precludes the analysis of intra-household
redistribution of resources and may lead to an erroneous
conclusion about the effect of gender

Some examples of gender analysis in
Economics – bargaining power
• CGIAR agreed outcome: Women empowerment
• Women’s empowerment - policy instrument to improve
children’s welfare.
• Women’s bargaining power - positively related to a
household’s resource allocation pattern in favor of children.
• Women always internalize their children’s interests better
than men (Basu 2006).

(contd.…)
• Hypothesis: A woman's bargaining power
has effect on children educational outcome
• Finding a good proxy for bargaining power
– Ownership of current assets held by the H and W
– Assets brought to marriage
– The expected level of assets upon divorce
– Shares of income earned

1.1. Testing whether bargaining power has differential
effects on children’s educational outcome?
At levels
𝐸𝑖𝑗 = 𝛽0 + 𝜷 𝟏 𝑮 𝒊𝒋 + 𝛽2 𝑋 𝑐𝑗 + 𝜷 𝟑 𝑿 𝒎𝒋 + 𝜷 𝟒 𝑿 𝒇𝒋
+ 𝜷 𝟓 𝑮 𝒊𝒋. 𝑿 𝒎𝒋 + 𝜷 𝟔 𝑮 𝒊𝒋. 𝑿 𝒇𝒋 + 𝜋 𝑠𝑖 𝑍 𝑠𝑖𝑗 + 𝜀𝑖𝑗
𝐸𝑖𝑗 : Educational outcomes of child 𝑖 in household 𝑗;
𝐺𝑖𝑗 : Dummy variable=1 if daughter; 𝑋 𝑐𝑗 : Vector of
child characteristics including age, age-squared; 𝑍 𝑠𝑖𝑗 :
Dummy variables indicating characteristics such as
location, survey round, and ethnicity
𝑿 𝒇𝒋 and 𝑿 𝒎𝒋 : vectors of husband’s and wife’s
characteristics, including age, education, assets

1.2. Testing whether bargaining power has differential
effects on children’s educational outcome, controlling
household-level unobservables

Takeaways
• Conduct your analysis at different levels of aggregation
(household, individual, plot)
• Use appropriate indicators of gender differences, allowing for
different degrees of sole-ness or joint-ness
• Use appropriate statistical comparisons and econometric
techniques (levels, fixed effects estimates)
• Note that just because there are differences does not
necessarily constitute proof of an association. Even worse
don’t give causal interpretation

(Contd.) Takeaways
• Explore the gender differences within the
context of the available data
• Look for intervening variables (find the
causal link - variable that explains the found
r/ship)
• Eliminate an extraneous variable (find r/ship
not understood)
• Find a variable that suppresses a relation
(expect a r/ship but none exists)

Poor research design
2. Developing research questions
and identifying methodologies

2.1. Good research design
• A good research design has to begin with
incorporating conceptually well-grounded research
questions about gender into the research design
• Research Question ____Method ____Data ___ Analysis
• Given the research question, what methods and data
are needed to answer the question in a convincing
way?

(Contd.) Developing research
questions…
 Too often, we design questionnaires before
thinking through what methods and data we
require to answer our research questions
Research process??
Data------Question-----Methods-----Analysis
Research process??
Method------Question-----Data-----Analysis

Example: Research questions
 Does adoption of maize technology lead to differential
poverty reduction between men and women?
 If so, what accounts for the gap? characteristics effect or
returns effect?
• Gender, causality, IV-variable, decomposition method
• Based on the research question and the method, identify
which explanatory and outcome variables are needed as
well as others needed for IV or to correct for selection

Takeaways
 Begin with a research question – and
determine if and how gender is relevant
 Then choose methods that allow you to
answer the question
 Then identify the variables and collect
the DATA that allow you to answer the
question

Data
3. Collecting Sex-Disaggregated
Data

Collecting Sex-Disaggregated Data
What are sex-disaggregated data?
• Data that are collected and analyzed
separately on men and women
• For agricultural household surveys, this usually
involves asking the “who” questions: Who
provides labor? Who makes decisions? Who
owns and controls resources?

Asking the right questions: Consider
the context
• Both research and survey questions must be adapted to
the context
• Those collecting and analysing sex-disaggregated data
need to understand gender roles and other dimensions of
identity
• Conducting qualitative research prior to survey
development can help identify most useful research
questions
• Understanding the context will allow researchers to:
o Develop survey questions that are culturally sensitive
o Ensure that survey questions are relevant

Gender differences in technology adoption:
What data are needed?
• How do you identify male and female farmers?
Individual plotholders or managers; joint farming?
• Requires data on plots (size, irrigation status, soil
quality, tenure status, etc.), inputs (fertilizer, labor,
agricultural tools and equipment, education,
livestock, credit, etc.), and other potential barriers
to production (risk preferences, childcare
responsibilities, gender norms, etc.)

Unit of analysis
• Individual
• Household
• Intrahousehold
• Community
• Region or nation
• Land area
• Asset
• Resource unit
• Formal or informal organizations
• Value chain

Who to interview?
 When unit of analysis is the individual, it should be
collected from the individual farmer, worker, consu
 When the unit of analysis is the household, farm, or
intrahousehold dynamics, then who should be
interviewed?
• Options include:
– One household member who is a proxy respondent
for all members
e.g. person most knowledgeable about the relevant subject
– Principal couple, husband and wife
– An adult man and an adult woman
– Randomly select one or more individuals
– All adultsmer, etc.

• For some research questions, one person can
provide information on everyone in the
household.
• Some questions, individuals must answer for
themselves
Intrahousehold analyses
• Some analyses are based on responses from
one person
• For other analyses, need to interview multiple
people per household.

So who to interview?
• It depends on the research question.
• And depends on the budget.
• Researchers must also be aware of how gender
and other social norms might inform responses.
(who is most knowledgeable, who is the farmer)
• The setting of the data collection can also inform
responses
• Always note who the respondent is, with basic
identifying information (sex, age, marital status,
education, etc.)

Designing surveys for gender analysis
Household Roster
• For household surveys, those sampling by
household, rather than individual, it is useful to
have a household roster.
• List all members of the household
• Include some basic information on each: sex, age,
marital status, relationship to head or respondent
• Assign each an id number that allow you to refer
to them in the coding throughout the survey.

Ask the “who” questions
• The key to gender analysis: know the sex of the people
involved in various tasks such as the owner of the land,
the farm manager, the laborer, or the decision-maker
• Changing a question from “Does the household…?” to
“Who in the household…?” can generate a wealth of data
• Coding the “who” questions:
o Code by sex (man, woman, boy, or girl) OR
o Code by household member ID (this approach
facilitates additional analysis through disaggregation across a
range of characteristics)

Costs of collecting sex-disaggregated data
• Simply adding a few of the “who” questions will not
significantly increase the cost
• Randomizing the respondent should not alter costs
• Interviewing multiple people within the same
household. The amount depends on the length of the
survey, the number of respondents, and the survey
setting
• It is important to identify who must be interviewed and
the appropriate sample size to sufficiently answer your
research questions before finalizing the project budget

Good practices
 Work with gender expert early in process to define
research question(s) and methodology
 All data collection methods must be context specific:
• Conducting qualitative research prior to survey development
can:
O Clarify useful research questions and best approach for
quantitative data collection
O Ensure that researchers, enumerators, facilitators, and
respondents have same understanding of questions
• Interview context: It may – or may not – be necessary for
O Enumerators or facilitators to be the same sex as respondents
O Interviews to be conducted in private
O Interviews to be conducted with men and women separately

Good practices (continued)
Begin by having a household roster
Collect information about men and women
and record who responded
Ask “who” questions
When possible, connect information to
member ID codes to allow for disaggregation
by sex, age, etc.
Budget for additional costs of collecting sex-
disaggregated data

Thank you

Advanced Techniques for Incorporating Gender Analysis in Economics Research

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Viewers also liked

Viewers also liked (20)

Similar to Advanced Techniques for Incorporating Gender Analysis in Economics Research

Similar to Advanced Techniques for Incorporating Gender Analysis in Economics Research (20)

More from International Institute of Tropical Agriculture

More from International Institute of Tropical Agriculture (20)

Recently uploaded

Recently uploaded (20)

Advanced Techniques for Incorporating Gender Analysis in Economics Research