Presentation given by CSISA at GAAP final technical workshop in Addis Ababa, January 2013

1. Gender, Agriculture and Assets Project
(GAAP) Evaluating the Impacts of
Agricultural Development Programming on
Gender Inequalities, Asset Disparities
and Rural Livelihoods
Thelma Paris, Val Pede and Joyce Luis
With assistance from Abha Singh, Raman
Sharma, Donald Villanueva, Jeffrey Estipular and Maria
Theresa Castro
Thanks to Ruth, Nancy and Agnes
Presented at the Final Meeting of GAAP
Jan 8-11, 2013, ILRI, Addis Ababa, Ethiopia

2. Cereal Systems Initiatives for
South Asia (CSISA)
• Reduce poverty and improve the well-being
of poor farm families in South Asia (income
of 60,000 farm households)
– Through development and dissemination of
technologies
• New varieties
• Sustainable crop and resource management
• Direct seeded rice
• Laser land leveler
• Zero tillage (rice and wheat)
• Crop residues for livestock feed
– Policies for economic growth
T.Paris/V.Pede
8th Jan 2013

3. CSISA hub domains
T.Paris/V.Pede
8th Jan 2013

4. Fig 4. Sampling scheme
Household
Hub Level District Level Block Level Village Level
Level
CSISA 18 Households
Block 1 Non-CSISA 18 Households
CSISA 18 Households
Block 2 Non-CSISA 18 Households
District 1
CSISA 18 Households
Block 3 Non-CSISA 18 Households
CSISA 18 Households
Block 1 Non-CSISA 18 Households
Hub District 2 Block 2
CSISA
Non-CSISA
18 Households
18 Households
CSISA
Block 3 18 Households
Non-CSISA
18 Households
CSISA
18 Households
Block 1 Non-CSISA
18 Households
District 3 CSISA 18 Households
Block 2 Non-CSISA 18 Households
18 Households
CSISA
Block 3 18 Households
Non-CSISA
T.Paris/V.Pede
8th Jan 2013

5. CSISA Baseline
• Survey
– Baseline household survey
– September 2010 to May 2011
– 2492 households for all 8 hubs
– Selected findings
• Adoption of CA technologies still very low
• Familiarity with CSISA and the promoted
technologies still weak among farmers
Zero Tillage Direct Seeded Rice Laser Land Leveling
Unfamiliar 64.2 92.6 83.7
Heard About 7.1 2.5 1.5
Seen 24.7 4.3 12
Adopted 4 0.6 2.8

6. Highlights and gaps in CSISA baseline
• Highlights
– Women contribute 32 to 49% to total labor use in
cereal production
– Women from small and marginal farm households
spent more time in animal husbandry, collection of
fuel and animal fodder and graze animals than
men
– Gender inequalities in access to and control of key
assets and resources persist
– Women are generally excluded in project activities
– Labor –saving technologies will have gender-
differentiated impacts on men and women
• Gaps
– Limited information on access to and control of key
assets and resources by gender and social groups

7. Specific objectives of GAAP under
CSISA
• describe what assets are important to men and
women in order to sustain their livelihoods;
• identify who has access to and control over these key
assets/resources;
• assess the current or anticipated effects of the
technologies under CSISA project on men and
women’s access to and control of these key assets and;
• examine how women and men respond or adjust due
to changes in the assets as a result of project
interventions introduced by the CSISA project
T.Paris/V.Pede
8th Jan 2013

8. Methodology
Part 1 – Problem identification
• Documented gender disparities in asset access to and
control using qualitative methods as well as strengthening
methods for measuring men’s and women’s access to and
control over assets.
Part 2 - Impact assessment
• Assessed current or anticipated effects of the technologies
under CSISA project on men and women’ access to and
control of the identified key assets using midline surveys
with gender asset questions.
• Assessed how men and women respond or adjust due to
changes in the assets as a result of project interventions
T.Paris/V.Pede
8th Jan 2013

9. Part 1
• Selection of study sites - Three districts in Maharajganj, Deoria,
and East Champaran in Bihar, India and 18 villages in Eastern
Uttar Pradesh, India
• Focus group discussions - In each district, two villages (one
CSISA village and one non-CSISA village) with separate groups of
men and women from the upper and lower castes were included
in the FGDS.
– Each group was asked to identify what assets are commonly owned by
typical farming households.
– A pre-tested form, developed by the IRRI team of social scientists, was
used to ask asset-related questions.
– Pictures of specific assets in India were developed
• In-depth interviews - 120 respondents (60 principal males and 60
principal females) to rank perceived importance of assets by
gender and social class
• Used of pictures of assets as defined by respondents. Pictures
were used to complement the associated questions.
T.Paris/V.Pede
8th Jan 2013

10. Natural and Physical assets
Rotavator
Rice mill
Irrigation canal
Farm land
Thresher
Draft animals
Water pump Mechanical thresher
Tractor
Dairy animals Small animals Combine
T.Paris/V.Pede
8th Jan 2013

11. Physical assets
Katcha house
Silver jewelry
Expensive clothing
Bicycle
Pucca house
Gold jewelry
Television
Motorcycle
Radio/Cassette
Mobile phones
T.Paris/V.Pede
8th Jan 2013

12. Human, Social and Financial
Farmer’s association
NREGA membership
Trainings
Social Women’s group
Human
Micro-finance
Diploma
Informal groups
Financial
Money lend to others
Savings in bank
Cash on hand
T.Paris/V.Pede
8th Jan 2013

13. COMPARISON OF IMPORTANCE OF ASSETS
- MANN WHITNEY U-TEST
“Do men and women rank assets differently?”
The test determined if there were significant
differences between the importance rating (ordinal
variable) of assets in two independent groups
(men and women):
-Physical
-Human
-Social
-Financial
T.Paris/V.Pede
8th Jan 2013

14. Table 1a. Gendered differences on importance of assets , EUP, India
Male Female
ASSETS p-value
n mean rank n mean rank
Agricultural
Farm land 59 1.10 59 1.86 0.000
Dairy animals 34 3.62 35 4.23 0.095
Small livestock 10 6.30 12 3.75 0.009
Non-Agricultural
Water pump 22 4.23 20 4.85 0.468
Katcha house (mud) 9 4.11 7 3.86 0.667
Pucca house (bricks) 54 2.70 53 2.38 0.082
Television 18 7.94 23 8.00 0.695
Radio/Tape-recorder 5 7.20 9 4.22 0.450
Mobile phone 49 6.24 46 7.04 0.009
Expensive clothing 35 7.26 46 7.22 0.264
Gold Jewelry 37 6.65 57 3.63 0.000
Silver Jewelry 33 6.88 58 5.91 0.002
Bicycle 46 6.24 35 7.69 0.001
Motorcycle 21 5.76 12 8.42 0.003
Legend: 1 – most important;
T.Paris/V.Pede
8th Jan 2013

15. Table 1b. Gendered differences on importance of assets , EUP, India
Male Female
ASSETS p-value
n mean rank n mean rank
Education/Degree 7 4.57 5 5.33 0.330
MNREGA member 12 3.75 11 5.64 0.079
Savings 34 6.53 34 6.00 0.282
Cash on hand 50 4.70 45 5.53 0.124
Money lent to others 18 6.50 16 7.25 0.225
T.Paris/V.Pede
8th Jan 2013

16. Methods of data collection for adoption
of labor saving technologies
Table 4. Distribution of households per village and
per district by classification, EUP, India, 2011.
District Village All
• Study sites
Gorakhpur Aurangabad
Indrapur
25
20
• Number of villages and
Kheria 20 households (Table 4)
Kotwa 20
• Focus group discussion
Kushinagar Mukundpur 20
• Case stories
Maharajganj Agya 20
Pokharbhinda 20
Siddharth Nagar Babhni 21
Basalatpur 20
Biharipur 20
Dhusuri-Laghu 19
Mahdeia 15
Mohnajot 20
Pokharbhinda 21
Saha 20
Sirwat 20
Total 321 T.Paris/V.Pede
8th Jan 2013

17. Adoption of labor saving technologies
by caste groups
Table 5. Percentage of farmers who are using specific machines by caste, EUP, India, 2011.
Caste
Machine Upper Other Backward Scheduled Others
(n=56) (n=186) (n=59) (n=20)
Combine 89 53 27 70
Rotavator 50 29 8 25
Laser Leveler 2 3 2
Rice thresher 1
Reaper 7 4 2
Transplanter 5 1 2
Zero till machine 9 5 3 10
Source: Thelma Paris, Val Pede, Joyce Luis, Abha Singh and Donald Villanueva. 2011. Assessing the effects of labor
saving technologies on employment of men and women agricultural workers in selected villages of Eastern Uttar
Pradesh (on-going project)
T.Paris/V.Pede
8th Jan 2013

18. Adoption of labor saving technologies
by farm size groups
Table 6. Percentage of farmers who are using specific machines by size of landholdings, EUP,
India, 2011.
Farm category
Machine Marginal (<1ha) Small (1-2 ha) Medium and Large (>2 ha)
(n=248) (n=49) (n=24)
Combine 45 94 92
Rotavator 21 51 67
Laser Leveler 2 2 4
Rice thresher 4
Reaper 2 6 17
Transplanter 2 2 4
Zero till machine 2 12 29
Source: Thelma Paris, Val Pede, Joyce Luis, Abha Singh and Donald Villanueva. 2011. Assessing the effects of labor
saving technologies on employment of men and women agricultural workers in selected villages of Eastern Uttar
Pradesh (on-going project)
T.Paris/V.Pede
8th Jan 2013

19. Fig. 1 Labor reduction in harvesting and post-
harvest activities by using combine machine
30.00
Non-user (n=142)
25.00 User (n=179)
Labor (days/ha)
20.00
15.00
10.00
5.00
0.00
Male Female Male Female
Family Hired
Type and source of labor
Note: Figures represent the labor used for harvesting and post-harvest activities in rice production.
T.Paris/V.Pede
8th Jan 2013

20. Other farm and non-farm activities of
women
Cleaning Winnowing Making cow dung cake Grazing of goat
Knitting cloth Washing cloths
Making of basket
Taking care of children
T.Paris/V.Pede
8th Jan 2013

21. Effects of combine on female workers
Effects Before After
Loss of access to non- 20-25 days (rice harvesting); 30-35 No more employment
farm employment days wheat harvesting (only 5 to 8 days of work within
the village); Only 20-25 days in
transplanting
Food (cereal) insecurity 2-3 months food (share from Reduced food share from
wages); 1-2 quintals per season harvesting; only from
(costs Rs1000-1500) transplanting
Loss of income Rs 1000-1500 from rice harvesting Rs 500 to 800 from rice
per season; Rs 1500 -1800 from harvesting per season (earlier
wheat harvesting per season wages were lower only Rs 40-
50per day and now Rs100-120
per day); No income from wheat
harvesting
Labor displacement Assured employment of 30-35 Assured employment only in
days during rice harvesting and transplanting
20-25 days during wheat
harvesting
Economic dependency Men and women both work as More dependent on MNREGA,
hired labor in farming activities non farm income, and
during rice and wheat season and remittances from migrant
most are dependent on off farm husband as to pay for rental fee
labor wages and selling of of machines,
animal products T.Paris/V.Pede
8th Jan 2013

22. Fig 3. Effects of labor saving technology
adoption on women from farming households
Better-off farming
households
(Landlords,
Medium to Large
land holders)
Effects of labor
saving technology
adoption on
women
Poor, landless and
marginal faming
households
(off-farm workers,
marginal to small
land holders)
T.Paris/V.Pede
8th Jan 2013

23. Empowering women
as entrepreneurs in
transplanting rice
Tamil Nadu, India CSISA project

24. Part 2
Midline Surveys with Gendered Asset
Access Information
T.Paris/V.Pede
8th Jan 2013

25. Midline survey
• Survey
– Period: June to August 2012
– 324 households were re-surveyed in EUP
– More gender-disaggregated data than baseline
• Detailed asset information
– Who has “access to” and “control”
• Income sources
• Decision making
• Labor participation in crop production
• Access to credit and training
• Household composition

26. Location of households in EUP
T.Paris/V.Pede
8th Jan 2013

27. Table 9. Owning and Renting Machines
Baseline (n=324) Midline (n=318)
Machines
own rent-in own Rent-in
Electric submersible pump 3 11 2 2
Diesel pump 95 223 85 214
4-wheel tractor 7 110 20 229
2-wheel tractor 7 110 1 1
Tine cultivator 13 297 19 282
Disc harrow 7 75 1 42
Rotavator 1 20 4 72
Seed drill 0 3 3 2
Mechanical transplanter 0 0 0 1
Mechanical pesticide sprayer 1 1 0 2
Knapsack sprayer 29 129 45 108
Thresher (power) 20 224 15 185
Thresher (pedal) 1 0 1 34
Combine harvester 2 82 2 85
Fodder chopper 166 0 84 8
T.Paris/V.Pede
8th Jan 2013

28. Table 10. Percentage of households who have access to asset
Upper Lower
Type of assets *
Baseline (77) Midline (77) Baseline (247) Midline (241)
Agricultural
Farm Land 98.7 98.7 93.1 95.4
Dairy Animals 48.1 50.6 41.3 45.2
Small livestock 10.4 11.7 11.3 16.2
Tractor 15.6 15.6 2.4 2.5
Cultivator 15.6 15.6 2.4 2.1
Rotavator 2.6 2.6 0.4 0.0
Combine 5.2 5.2 0.0 0.0
Thresher 9.1 9.1 0.8 0.8
Rice mill/huller 2.6 2.6 1.2 1.2
Water pump 28.6 29.9 23.9 24.5
Non-Agricultural
House with thatched roof 39.0 39.0 36.8 36.1
House with concrete floor 79.2 83.1 74.9 78.0
Mobile phone 39.0 42.9 32.8 33.2
Television 10.4 10.4 11.3 10.8
Radio tape-recorder 72.7 83.1 65.2 80.1
Expensive clothing 53.2 59.7 27.1 33.2
Gold Jewelry 87.0 87.0 75.7 77.2
Silver Jewelry 87.0 88.3 79.4 80.5
Bicycle 75.3 85.7 74.5 80.1
Motorcycle 40.3 48.1 16.6 19.1
Own shop 9.1 10.4 7.3 8.3

29. Table 12. Number of lower caste household farmers who owns assets
Baseline (n=247) Midline 2012 (n=241)
Assets
Husband Wife Both Husband Wife Both
Agricultural
Farm land 147 5 78 147 5 78
Dairy animals 55 6 41 56 7 46
Small livestock 6 7 15 11 9 19
Tractor 6 0 0 6 0 0
Cultivator 5 0 0 6 0 0
Combine 0 0 0 0 0 0
Thresher 2 0 0 2 0 0
Rice mill/ huller 3 0 0 3 0 0
Water pump 52 0 7 51 0 7
Non-Agricultural
House with thatched roof 37 3 51 35 3 49
house with concrete floor 101 3 81 101 3 84
TV 48 5 28 47 5 28
Radio/tape 18 1 9 16 1 9
Mobile phones 121 4 36 138 6 49
Expensive clothes 5 35 27 7 36 37
Gold jewelry 6 166 15 6 165 15
Silver jewelry 7 176 13 7 174 13
Bicycle 172 5 6 181 5 6
Motorcycle 38 0 3 44 0 2
Shop 13 1 4 15 1 4
T.Paris/V.Pede
8th Jan 2013

30. Table 3.2 Number of lower caste household farmers who uses assets
Baseline (n=247) Midline 2012 (n=241)
Assets
Husband Wife Both Husband Wife Both
Agricultural
Farm land 50 6 174 49 6 175
Dairy animals 20 1 81 20 2 87
Small livestock 1 7 20 3 9 27
Tractor 5 0 1 5 0 1
Cultivator 6 0 0 0 0 0
Thresher 2 0 0 2 0 0
Combine 0 0 0 0 0 0
Rice mill/ huller 3 0 0 3 0 0
Water pump 46 0 12 45 0 13
Non-Agricultural
House with thatched roof 10 2 79 9 2 76
house with concrete floor 27 3 155 27 3 158
TV 10 4 67 10 4 66
Radio/tape 4 1 23 4 1 21
Mobile phones 60 4 97 70 6 117
Expensive clothes 2 34 31 4 35 41
Gold jewelry 4 165 18 4 164 18
Silver jewelry 6 174 16 6 172 16
Bicycle 165 6 12 174 6 12
Motorcycle 37 0 4 43 0 3
Shop 11 1 6 13 1 6
T.Paris/V.Pede
8th Jan 2013

31. Formula for WEI
n
xj
j 1
WEI _ all
d
Where:
WEI_all = women empowerment index for all decisions per respondent
x = value of decision maker
j = code for the specific decision matter
d = total number of decisions replied by the respondent
N = number of decisions
T.Paris/V.Pede
8th Jan 2013

32. Table 17a. Involvement of upper caste women in decisions making and activities, EUP
Midline
Activities Husband only H>W Both W>H Wife only
Choice of Crop
What crop to grow
What variety to use
Crop Management
When to apply fertilizer
Amount to fertilizer use
When to apply pesticide/insecticide to use
Amount of pesticide/insecticide to use
When to irrigate crops
When to weed
When to hire laborer
When to harvest
When to thresh rice
Post harvest operations
Which seeds/variety should be grown next
season
Amount of rice to store
When to sell rice or other crops
T.Paris/V.Pede
8th Jan 2013

33. Table 17b. Participation of husband and wife in decision making activities
Midline
Activities Husband only H>W Both W>H Wife only
Livestock/poultry rearing
Number of large animals to raise
When to sell animals
Investments
How much money to spend on farm inputs
How much money to spend on food
How much money to spend on capital
investments
Whether to buy livestock
Whether to buy land
Expenditure on children’s education
House construction
Allocation of remittances
Politics
Who decides whom you should vote for
T.Paris/V.Pede
8th Jan 2013

34. Table 19. Women Empowerment Index by caste
Midline 2012
Activities for decision making
Upper (n=77) Lower (n=241)
Choice of Crop 1.91 2.07
Crop Management 1.90 2.10
Post harvest operations 2.01 2.41
Livestock/poultry rearing 2.12 2.55
Investments 2.32 2.51
Politics 2.35 2.40
Overall 2.08 2.30
H 1
H>W 2
H=W 3
W>H 4
W 5
T.Paris/V.Pede
8th Jan 2013

35. Lessons learnt
o Individual level data on assets is essential to capture intrahousehold asset
gaps.
• Access to asset may mean “ownership” or renting. Rather than asking
“which of the assets you own or possess?” it will be better also ask the
question “if you do not own or possess this asset, do you have access to
this asset?”
o Asset ownership and acquisition depends on whether the household is a
nuclear or extended/joint family with more number of family members.
o There are conceptual issues not only in sorting out who owns property
within married couples, but also in an individual’s perceptions of
ownership within marriage and social norms which may not conform to
legal norms..
o It is also important to ask when the asset was acquired – whether before or
after marriage.
o The direct benefits from the point of view of the male and female
respondents) of collecting detailed personal information on asset
ownership and control is difficult to justify to the respondents.
o CSISA require more strategic planning. It is crucial that the leaders of
CSISA objectives are responsive to gender issues.
o More resources from the CSISA project should be provided to reduce the
gender gaps in assets

36. How CSISA interventions can impact gender
inequality and empower women
• Targeting women with development interventions, improving their involvement in
farmer participatory experiments on crop and livestock, and post-harvest
technologies.
• Post harvest technologies for rice, wheat and other crops will reduce post harvest
losses and provide women with income opportunities.
• Promoting and validating technologies that enhance crop-livestock interactions
e.g production of dual purpose crops for food and animal fodder will directly
benefit women who take care of crop production and dairy animals.
• Providing women with new knowledge and skills in production techniques e.g.
raising nursery rice seedlings for paddy mechanical transplanter through “hands-
on” training can be an opportunity for income generating activities for poor women
displaced by labor-saving technologies.
• Increasing women’s access to seeds of improved varieties of non-rice crops to
increase cropping intensity and cropping diversification should be given more
attention.
• Thus, seed distribution for distribution trials and participatory experiments should
include women farmers and not only give to male heads of households.
• To provide women access to agricultural machinery, NGOs can help tap existing
Self Help Groups to organize themselves run a microenterprise e.g. providing
custom services for post harvest and processing crops or renting out an
agricultural equipment or machinery. T.Paris/V.Pede
th
8 Jan 2013