Adapting the Women’s Empowerment in Livestock Index (WELI) data collection tool to user demand. Presented by Immaculate Omondi during an online webinar held on 19 September, 2022.

1. Better lives through livestock
Adapting the Women’s Empowerment in Livestock Index (WELI)
data collection tool to user demand
Immaculate Omondi: i.omondi@cgiar.org
Farha Deba Sufian: farha.deba.sufian@gmail.com
Alessandra Galiè: a.galie@cgiar.org
Nils Teufel: n.Teufel@cgiar.org
19 September, Nairobi, Kenya

2. 2
Overview of presentation
- Women’s empowerment in livestock development: an introduction
- Measuring the empowerment of women in livestock
- Overview of WELI
- Adapting WELI to Feedback from WELI Users

3. Women’s empowerment in livestock development

4. 4
Women’s empowerment in livestock
1 in 5 people in the world rely on livestock for their livelihoods (1.3 billion people)
Women are the majority of poor livestock keepers…
 Their empowerment: means for livestock development
 SDG5: Women’s and girls’ empowerment as an end in itself
Women’s empowerment as a
means
Women’s empowerment as an
end

5. 5

6. Measuring the empowerment of women in livestock

7. 7
Measuring the empowerment of women in livestock to…
• Measure whether livestock interventions enhance/hinder women’s empowerment
• Study how livestock-specific interventions affect women's empowerment
• Characterize women’s empowerment through livestock specific activities
• Consider gender differences in roles/activities between livestock species
• Identify sources of disempowerment facing the women participating in livestock production
2 tools in settings where livestock farming is the dominant form of livelihood
Women’s Empowerment
in Livestock Index (WELI)
Women’s Empowerment
in Livestock Business Index (WELBI)

8. 8
WELI: a standardized measure to assess the empowerment of women livestock producers
• Developed by livestock and gender experts from ILRI and Emory University in 2014/2015
• Pilot tested in Tanzania, 2015
• Aligned to pro-WEAI with IFPRI, 2019
WELBI: a standardized measure to assess the empowerment of women livestock agri-preneurs
• Constructed and aligned to pro-WEAI_VC, 2021
A short history of WELI and WELBI
Women’s
empowerment
in the livestock
business node
of livestock
value chains
WELBI
Women’s
empowerment
in the
production
node of the
livestock
sector
WELI
Women’s
empowerment
in the
production node
of crops mostly
WEAI

9. Construction of the Index: comparing pro-WEAI and WELI
9
1 Autonomy in Income
2 Self-efficacy
3 Attitudes about IPV against women
4 Respect among household members
5 Input in household decisions
about Production and Income
6 Ownership of land and other assets
7 Access to and decisions on financial
services
8 Control over use of income
9 Work Balance
10 Visiting Important Locations
11 Group membership
12 Membership in influential groups
Intrinsic
Agency
Instrumental
Agency
Collective
Agency
Pilot version of Pro-WEAI
Additional
Scenarios pertaining
to livestock
Additional options
pertaining to
livestock
Update
scenarios/options
pertaining to
livestock
Input in household
decisions with a
Livestock focus
WELI
New Module
13 Indicators
Weighted average score 3DE
EMPOWERED if
adequate in 75% of indicators

10. 10
• WELI has an elaborate list of livestock activities in decisions making modules: 24 vs 5
• WELI 3DE is estimated from 13 indicators vs 12 indicators
• Empowerment can be assessed for more species and breed-type of livestock
using WELI: 11 vs 6
• WELI integrates more livestock related scenarios/options in several modules
(Autonomy, Domestic violence, Physical mobility etc.)
• Decision making on livestock loops at most 3 times for:
• Specie important to the household
• Specie important to the woman
• Project/target specie
WELI vs Livestock-integrated Pro-WEAI

11. Adapting WELI to feedback from users

12. 12
Adapting to user feedback
User Feedback
• Lengthy interview
• Issues with time module
• High index values
c
Remove questions that
DO NOT go into index
calculation
Recording Time by
ACTIVITY vs 15
minute time slot
Respondent
Participation in
decision making
captured simply
3 main changes to
WELI
WELI-
FullBare

13. 13
• HH roster dropped
• Rows with items that do not go into the index
• Some columns that do not go into the index
• Questions asking for more than 1 decision maker
• Time allocation consolidated
• Intrahousehold relationships reviewed hence fewer non-response cases
Major changes to WELI to produce the FullBare version

14. 14
Restructure in WELI-FB: MODULE G2
WELI WELI-FB
• Livestock and productive activities decisions restructured
in WELI-FB
• Rows reduced to only activities/items that contribute to
the index

15. 15
WELI
• G3.10
restructured
in WELI-FB
WELI-FB
Restructure in WELI-FB: MODULE G3

16. 16
WELI Time Module (by time
slot)
WELI-FB Time Module (by
Activity)
• Calculate time_work: minutes
spent on work in 24 hours
• Calculate time_childcare:
minutes spent on childcare
as secondary activity
Restructure in WELI-FB: MODULE G4

17. 17
WELI WELI-FB
• Relations expanded in WELI-FB
Restructure in WELI-FB: MODULE G7

18. WELI Full bare validation

19. 19
1. Pilot study using WELI-FB questionnaire on 16 dual adult households
(16 women and 16 women) in Ethiopia
WELI-Full Bare Validations: pilot study
ETHIOPIA Women Men
Number of observations 16 16
3DE score 0.84 0.86
Disempowerment score (1 – 3DE) 0.16 0.14
% achieving empowerment 0.56 0.56
% not achieving empowerment 0.44 0.44
Mean 3DE score for not yet empowered 0.64 0.67
Mean disempowerment score (1 – 3DE) 0.36 0.33
Gender Parity Index (GPI) 0.95
% achieving gender parity 0.69
% not achieving gender parity 0.31
Average empowerment gap 0.16
WELI score 0.85

20. 20
2. Simulations using existing data on WELI to run WELI-FB syntax
TANZANIA WELI
WELI-FB
Simulated
Number of observations 210 210
WELI (3DE score) 0.86 0.86
Disempowerment score (1 – 3DE) 0.14 0.14
% achieving empowerment 62 62
% not achieving empowerment 38 38
Mean 3DE score for not yet empowered 0.63 0.63
Mean disempowerment score (1 – 3DE) for not yet
empowered
0.37 0.37
Same
results
WELI-Full Bare Validation: simulations on existing data

21. 21
3. Length of the interviews
Survey time comparison
• Challenge: Recoded Survey time includes review time
• Comparing Mean survey time across projects (restricting to survey
duration less than 7 hours)
• Full Bare records the lowest time on average
WELI-Full Bare Validation: focus on length of interviews
Estimate source
Mean
(hrs)
Min
(hrs)
Max
(hrs)
Full WELI (Tanzania) 5.2 1.9 6.9
Full WELI (Ethiopia) 5.6 4.0 6.9
WELI – FB (Ethiopia) 4.8 2.0 6.8

22. WELI next steps

23. 23
Thoughts on next steps for (WELI-xs)
Objective: Shorter interview (20-30 minutes) by reducing questions that form indicators
(rather than no. of indicators that go into WELI)
How:
• Assess time required for questions and modules
• Assess correlations between questions/items or activities within questions
• Assess variation between questions/items or activities within questions
• Theoretical background of these questions
o Drop redundant questions/items or activities within questions (if any)
• Analysis of 'candidate" indicators to dropped from WEAI
o Variation/contribution to overall indicator and correlation with other indicators

24. 24
Challenges and doubts
• High index values
• Meaning of the indices vs general use of the results in light of ‘high index values’ observation
o Interpreting absolute vs relative values of the index
TANZANIA WELI
Number of observations 210
WELI (3DE score) 0.86
Disempowerment score (1 – 3DE) 0.14
% achieving empowerment 62

25. 25
Questions for discussion
• How others have dealt with the length of the surveys
e.g.
• Creating and validating shorter versions of the main tools
• Using qualitative research in shortening the tools
• Usefulness of additional questions that do not contribute to the index calculation
• How others have dealt with ‘seemingly high’ index values

26. Acknowledgement
• CGIAR GENDER Impact
Platform Methods Module
• Innovation Lab for Small-
scale Irrigation (ILSSI)
project

27. THANK YOU