1. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE
Data needs for measuring impacts
on women’s assets and asset
disparities
Nancy Johnson
Agnes Quisumbing
INTERNATIONAL LIVESTOCK RESEARCH INSTITUTE

2. Content
I. Defining asset-related impact indicators
II. Collecting gender disaggregated data on
assets

3. I. Defining Indicators
 Project proposes to measure impacts on
• Women’s assets
• Men’s assets
• Gender asset disparities
 Need to specify what we mean by
• Assets
• “Women’s” assets (assets belonging to
women and/or men)
• Asset disparities
• Changes in assets and asset disparities

4. Page 4
From capitals to assets
Broad definition of assets to
include:
 Natural capital
 Physical capital
 Financial capital
 Human capital
 Social capital
 Political capital

5. Physical capital

6. Natural capital

7. Same asset, many capitals

8. Implications
 Can’t possibly
cover all assets
so need to think
carefully about
which ones really
matter, given the
context and the
objectives of the
intervention
being evaluated.

9. What does it mean to “own” an asset?

10. Use rights
Types of ownership
Decision rights

11. Use rights
 Access
 Extraction
 Commercial
exploitation

12. Decision rights
 Management
 Exclusion
 Alienation

13.  Claims to rights come from multiple sources,
and can overlap and change
Sources and security of rights

14. Implications
 Easy to focus on (and measure) “decision”
rights but in some cases “access” rights
can be important
 For certain kinds of assets (eg land) may
need to include type and security of rights
along with quantity and value of asset as
part of the indicator

15. • Contextual
information on sources
of rights and what can
strengthen and weaken
them is important for
evaluating projects
(implementing them!)

16. Types of owners
 Individuals
 Partners (joint)
 Groups (collective)

17. Implications
 Need to include joint ownership option in
surveys but it may need to be qualified
 Some collectively-owned assets can be
“individualized” but others not

18. How to measure assets & asset changes
 Quantity/quality of specific asset(s)
 Assets index
 Value of assets
 Type or security of rights

19. Asset disparities
 Disparity is the ratio of women’s assets to
men’s assets
 How can the disparity be reduced?
• Increase women’s assets
• Decrease men’s assets
• Increase both, but women’s more
 But remember, changes in rights is not
always zero-sum

20. II. Methods for collecting gender-
disaggregated asset data
 Multiple methods, data sources and
sequencing
 Baseline surveys
 Field implementation issues

21. Page 21
Data collection: national and community
level
• Use of existing
national-level data
(DHS, national
statistics),
administrative data,
existing studies
• Focus groups at
community level, for
example to get at
local norms

22. Page 22
Quantitative methods: household level
 Household and
individual surveys,
particularly panel
surveys
 Take advantage
of existing
gender-
disaggregated
data sets and
build a panel

23. Page 23
Qualitative methods
 Ethnography, case studies, life histories

24. Page 24
Q-squared: Integrated qual and quant
 Sequenced and integrated qualitative and
quantitative data analysis
• For example, quantitative surveys can be used
to draw up the sampling frame for the life
histories work or FGDs

25. How can questionnaire modules can be designed to
look at asset accumulation from a gender perspective?
 In what topics can data collection can be gender-
disaggregated?
 How can the same basic question (say, control of
land and assets) be adapted to specific contexts,
using survey modules on the same topic, but
administered in different settings?
 What issues of survey implementation are
important?

26. What does a baseline questionnaire look like?
Where can we insert/modify modules to look at
gender issues in a standard household survey?
 Basic baseline information: in RED
 Typical module with gender-
disaggregated info ALWAYS collected:
purple cells
 Gender-disaggregated info SOMETIMES
collected: orange cells
 Specialized module with gender-
disaggregated info ALWAYS collected:
green cells

27. Basic and Extended Questionnaire
Design of Socio-economic modules
Module Basic? Gender-
disaggregated
information?
About which hh member?
A Roster—very important, since all
Ids in subsequent modules will
come from here
Yes Yes All!
B Education of head and
household members
Yes Yes All
C Nonfood consumption Depends
on focus of
survey, but
ideal
Partly (clothing,
footwear)
All (typically collected at hh
level)
D Food consumption No (but see
section on
nutrition
modules)
All (typically collected at hh
level)

28. Contents of a household roster
ID Name Sex Age Reln to
head
Marital
Status
Education Main
occupat
ion
1
2
3
4
5
You can also add columns on literacy, migration status, etc.

29. Socio-economic modules (cont’d)
Module Basic? Gender-
disaggregate
d
information?
Which hh member?
E Land area and crops grown Yes Yes ID of person who manages the plot
ID of plot owner, if different from
manager
F Major Crop Production Yes, if
ag
survey
Yes ID of plot manager (household
member)
G Agricultural Wage Labor Possibl
y
Yes ID of laborer
H Other Income Possibl
y
Yes ID of people with other incomes,
businesses, ID of people sending
and receiving remittances

30. Socio-economic modules (cont’d)
Module Baseli
ne?
Gender-
disaggregate
d?
Which hh member?
J Assets Ideall
y
Yes ID of asset owner
K Group Membership Ideall
y
Yes ID of group member
L Savings Possi
ble
Yes ID of account owner
M Credit and Lending Ideall
y
Yes ID of borrower

31. Additional consumption, health,
and nutrition-related modules
Module Baseline? Gender-disaggregated? Which hh member?
N 24-hour individual food
recall
Depends
on purpose
of survey
Yes all
O Dietary diversity Depends
on purpose
of survey
Yes all
P Reproductive health Depends
on purpose
of survey
Yes Women
Q Anthropometry and
morbidity
Ideally Yes all
Some of these indicators are more expensive to collect (e.g.
24-hour individual food recall) and will require highly trained enumerators.
Sometimes a good dietary diversity survey will do the trick.

32. Additional gender-related modules
Module Baseline? Gender-disaggregated? Which hh member?
R Labor use and time use by
gender
Yes Yes Main male and female,
could also include children
depending on focus
S Domains of decisionmaking
authority, especially about
assets
Yes Yes Main male and female
T Control of cash income and
use of income
Yes Yes Main male and female
U Level of gender-related
conflict and violence
Ideally Typically only woman is
asked
Main woman
Caveat in fielding questions about domestic violence:
Need to have trained enumerators with knowledge about services available
Need to protect privacy of respondents and not subject them to greater risk

33. Engendering the asset module (simple)
 ID of
owner
 ID of
decision
maker
on sales
Asset (g)
Number
owned
ID of owner
ID of
decisionmaker for
sale
Animal
Cattle
Horses
Sheep/goats
Poultry
Pigs
Domestic assets
Cooker
Kitchen cupboard
Refrigerator
Radio
Television
DVD player
Cell phone
Chairs
Mosquito nets
Gas stove
Spades/shovels
Ploughs

34. What do you do when you don’t
have a baseline?
 Collect information on outcomes that are easy
to recall and “lumpy,” such as land and
assets, and do this retrospectively
 Rely on a combination of qualitative and
quantitative methods
 Use the appropriate impact measurement
techniques

35. Field implementation issues
 Who should be interviewed? “head of
household?”
 Should the head of household answer for all
household members?
 Different people will report different things—
need to reconcile

36. Field implementation issues, cont’d
 Privacy important, but especially important
for asset issues (hidden assets)
 Should field teams employ men and women?
 Examples:
• Pakistan and Bangladesh surveys have teams of
men and women
• Surveys in the Philippines almost always employ
women (trust and safety issues)
• Surveys in Guatemala City employ women to
interviewer (safety issues)
• Most interviewers in our other surveys are men
(small cadre of women to draw on)
 Need to train and employ skilled qualitative
field personnel

37. Concluding remarks
 Context, context, context
 Identify focus of study to avoid getting lost in
details
 Mixed methods: hh survey should ideally be
informed by qualitative work; quantitative
and qualitative work can be iterative
 Learn from experience of others in the field,
especially in the same country