INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE
Data needs for measuring impacts
on women’s assets and asset
disparities
Nanc...
Content
I. Defining asset-related impact indicators
II. Collecting gender disaggregated data on
assets
I. Defining Indicators
 Project proposes to measure impacts on
• Women’s assets
• Men’s assets
• Gender asset disparities...
Page 4
From capitals to assets
Broad definition of assets to
include:
 Natural capital
 Physical capital
 Financial cap...
Physical capital
Natural capital
Same asset, many capitals
Implications
 Can’t possibly
cover all assets
so need to think
carefully about
which ones really
matter, given the
contex...
What does it mean to “own” an asset?
Use rights
Types of ownership
Decision rights
Use rights
 Access
 Extraction
 Commercial
exploitation
Decision rights
 Management
 Exclusion
 Alienation
 Claims to rights come from multiple sources,
and can overlap and change
Sources and security of rights
Implications
 Easy to focus on (and measure) “decision”
rights but in some cases “access” rights
can be important
 For c...
• Contextual
information on sources
of rights and what can
strengthen and weaken
them is important for
evaluating projects...
Types of owners
 Individuals
 Partners (joint)
 Groups (collective)
Implications
 Need to include joint ownership option in
surveys but it may need to be qualified
 Some collectively-owned...
How to measure assets & asset changes
 Quantity/quality of specific asset(s)
 Assets index
 Value of assets
 Type or s...
Asset disparities
 Disparity is the ratio of women’s assets to
men’s assets
 How can the disparity be reduced?
• Increas...
II. Methods for collecting gender-
disaggregated asset data
 Multiple methods, data sources and
sequencing
 Baseline sur...
Page 21
Data collection: national and community
level
• Use of existing
national-level data
(DHS, national
statistics),
ad...
Page 22
Quantitative methods: household level
 Household and
individual surveys,
particularly panel
surveys
 Take advant...
Page 23
Qualitative methods
 Ethnography, case studies, life histories
Page 24
Q-squared: Integrated qual and quant
 Sequenced and integrated qualitative and
quantitative data analysis
• For e...
How can questionnaire modules can be designed to
look at asset accumulation from a gender perspective?
 In what topics ca...
What does a baseline questionnaire look like?
Where can we insert/modify modules to look at
gender issues in a standard ho...
Basic and Extended Questionnaire
Design of Socio-economic modules
Module Basic? Gender-
disaggregated
information?
About w...
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 al...
Socio-economic modules (cont’d)
Module Basic? Gender-
disaggregate
d
information?
Which hh member?
E Land area and crops g...
Socio-economic modules (cont’d)
Module Baseli
ne?
Gender-
disaggregate
d?
Which hh member?
J Assets Ideall
y
Yes ID of ass...
Additional consumption, health,
and nutrition-related modules
Module Baseline? Gender-disaggregated? Which hh member?
N 24...
Additional gender-related modules
Module Baseline? Gender-disaggregated? Which hh member?
R Labor use and time use by
gend...
Engendering the asset module (simple)
 ID of
owner
 ID of
decision
maker
on sales
Asset (g)
Number
owned
ID of owner
ID ...
What do you do when you don’t
have a baseline?
 Collect information on outcomes that are easy
to recall and “lumpy,” such...
Field implementation issues
 Who should be interviewed? “head of
household?”
 Should the head of household answer for al...
Field implementation issues, cont’d
 Privacy important, but especially important
for asset issues (hidden assets)
 Shoul...
Concluding remarks
 Context, context, context
 Identify focus of study to avoid getting lost in
details
 Mixed methods:...
Upcoming SlideShare
Loading in …5
×

Data needs presentation nov 5 final

961 views

Published on

Published in: Technology, Business
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
961
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
22
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Data needs presentation nov 5 final

  1. 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. 2. Content I. Defining asset-related impact indicators II. Collecting gender disaggregated data on assets
  3. 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. 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. 5. Physical capital
  6. 6. Natural capital
  7. 7. Same asset, many capitals
  8. 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. 9. What does it mean to “own” an asset?
  10. 10. Use rights Types of ownership Decision rights
  11. 11. Use rights  Access  Extraction  Commercial exploitation
  12. 12. Decision rights  Management  Exclusion  Alienation
  13. 13.  Claims to rights come from multiple sources, and can overlap and change Sources and security of rights
  14. 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. 15. • Contextual information on sources of rights and what can strengthen and weaken them is important for evaluating projects (implementing them!)
  16. 16. Types of owners  Individuals  Partners (joint)  Groups (collective)
  17. 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. 18. How to measure assets & asset changes  Quantity/quality of specific asset(s)  Assets index  Value of assets  Type or security of rights
  19. 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. 20. II. Methods for collecting gender- disaggregated asset data  Multiple methods, data sources and sequencing  Baseline surveys  Field implementation issues
  21. 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. 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. 23. Page 23 Qualitative methods  Ethnography, case studies, life histories
  24. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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

×