Impacts of commercialization of crop and livestock
products on women’s decision making and income
management in Uganda and Malawi
Jemimah Njuki, Susan Kaaria, Angeline Chamunorwa and Wanjiku Chiuri
Introduction
• Different organizations are using different
approaches to link smallholder farmers to
markets
– provision of market information,
– organizing farmers into groups, associations or cooperatives,
– contract farming and out-grower schemes.
• Most of these approaches have been evaluated
based on increases in household incomes,
access to higher value markets and other
potential advantages for farmers including
access to inputs, credit and technological and
extension advice
Introduction
• From a gender perspective
– there is evidence that women face more constraints as
they endeavor to engage with market systems
– Empirical studies on intra-household gender dynamics in
Africa have shown that when a crop enters the market
economy, women may lose control of such crops
• A lot of evaluations of market benefits have used
the household;
– As a single unit that has a welfare function that reflects
the preference of all its members
– That pools resources with the result that all household
members enjoy the same level of welfare
– As one where the head is an altruist who takes into
account the wellbeing of other members of the household
The household and issues of
distributional impact
Unitary
Household Model
Common welfare
function
Pooling of resources
Head is altruist
Collective
Household Model
Co-operative
Individual autonomy
Individual preferences
Sub-economies
Measure outcomes at
household level
Non-Cooperative
Choice of acting as
individuals or joint
“mine, yours, ours”
Measure outcomes at
individual level
The project
• Data from Malawi and Uganda
• Objectives:
– to analyze the gender distributional
impacts of market linkages
• Focus on
– the dichotomy of cash/food crops,
crops/livestock
– what influences women’s management of
income from agricultural markets
Methodology
• Two sets of data
– A cross sectional survey of 457
households
– A panel data set of farmers linked to
beans and potato markets collected
every beginning of the season for 3 years
Description of commodities and their
contribution to household income
Enterprise
Beans
Potatoes
Groundnuts
Soybeans
Rice
Goats
Pigs
Milk
Poultry
Number of
farmers
actively
marketing
80
91
62
14
90
55
40
12
16
Mean average
annual income
(USD)
79.5
270.1
73.6
70.8
232.5
53.4
113.9
906.3
77.8
% contribution
to total
household
income
22.9
37.2
11.9
29.5
43.5
22.2
27.9
31.6
16.1
Income management by men and women
A relatively high proportion of income
managed by women from groundnuts
(43.7%) and beans (35.5%) and
soyabeans (31.7)
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Beans
Groundnuts
Women
Men
More joint management of income
from groundnuts compared to the
other 2 legumes
Soyabeans
Joint
Other Crops
Most income form potatoes
managed jointly, while income
from rice mainly managed by
women (45.1%)
% of income under sole /joint management
% of income under sole /joint management
Legumes
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
potatoes
Women
rice
Men
Joint
Income management by men and women
Livestock and livestock products
% of income under sole /joint management
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Goats
Pigs
Women
Poultry
Men
Dairy milk
Joint
Gendered income control from different livestock and livestock products.
Men controlled 69.1% and 87.3% of the income from goats and pigs respectively. Only 9%
of the income from pigs was controlled by women
Fifty three percent of the income from poultry was managed and controlled by women
with only 14% going to men
Women managed and controlled 39.8% of the income from milk with men managing
29.6% of the income
What influences income management
by women
200
60
•
180
50
160
140
40
120
•
100
30
80
20
60
40
10
20
0
0
Poultry
Rice
Groundnuts
Mean income
Potatoes
Pigs
% income share to women
Goats
•
A general trend of a rise in
income share by women across
the low income commodities
which changes with the higher
income commodities
high income commodities such
as potatoes and pigs showed
lower income share by women
(some exceptions such as rice)
In the lower income categories,
groundnuts and poultry had
average incomes below USD 100
per annum and high income
shares going to women (43.6%
for groundnuts and 52.7% for
poultry)
1600
40
1400
35
1200
30
1000
25
800
20
600
15
400
10
200
5
0
0
2003/4
2004/5
2005/6
Total income
% income share to women
Total income
Income share over time..the influence of
markets
Beans-Malawi
2006/7
Income share to women
Beans -Uganda
• Uganda-Productivity
improvement interventionsSlight changes in income
management by women
80
70
60
50
40
30
20
10
0
2004A
2004B
2005A
2005B
2006A
2006B
Season
Women
Men
• Malawi-Active export market
orientation--decline in
women’s control of income
from the crop as total
income (bar) increased. Thus
as the beans became more
marketable, men tended to
get interested and took over.
Joint
2007A
2007B
Other determinants of income management
Unstandardized
Coefficients
(Constant)
Enterprise /product
 Beans
 Groundnuts
 Soyabeans
 Goats
 Pigs
 Poultry
% of enterprise income to total
hh income
Who sold (1=Wife 0=Other)
Market sold to (1=local or farm
gate 0=other)
education of men (0=None,
1=Primary and above)
education women (0=None,
1=Primary and above)
Family size
Age of household (years)
R2
B
-6.763
SE
10.957
Standardi t
zed
Coefficien
ts
Beta
-.617
10.108
29.017
1.839
9.721
.151
-4.087
.042
5.547
7.067
9.762
6.375
12.159
16.986
.092
.104
.226
.010
.090
.001
-.011
.022
1.822
4.106
.188
1.525
.012
-.241
.452
.070
.000
.851
.129
.990
.810
.652
65.588
-4.663
4.734
5.740
.685
-.043
13.854
-.812
.000
.418
3.673
5.535
.032
.664
.508
-5.651
4.571
-.063
-1.236
.218
-1.051
.405
0.606
.782
.163
-.064
.124
-1.343
2.480
.181
.014
Sig.
.538
So what? Do men and women spend
income under their control differently?
Expenditure
item
Husband Wife
Food
Agricultural
production
Assets
Education
Health
Clothing
Social
assistance
Leisure
Other
Total
6
14
23
22
8
25
25
20
5
18
2
14
7
2
22
2
15
20
3
5
8
2
8
100
1
7
100
2
14
100
Joint
• 67% of women’s income
going to food, agricultural
production and clothing
• 45% of men’s income going
to assets and education
compared to women’s 21%
• Joint income mainly going
to agricultural production,
education and assets
• Only 14% of women’s
income going to assets
Conclusions
• Increasing commercialization through linking farmers to
markets will increase farmers’ incomes but with implications
for gender and intra-household dynamics
• The choice of commodity matters. Women seem to control
more income from crops traditionally used for food such as
beans and groundnuts and livestock products rather than sale
of livestock
• As low income commodities start to attract higher prices and
revenues through farmer linkages to higher price markets,
women tend to lose control of these commodities-an often
unplanned outcome of market linkages
• Without a good understanding of what women’s roles and
preferences are and why, market development can undermine
these roles.
• Standard approaches of analyzing value chains can often miss
the gender and intra-household issues.
Conclusions (2)
• Programs aimed at increasing commercialization or using a value chain
approach need to take into account these gender and intra-household
dynamics.
• Gender sensitive value chain or commodity selection and value chain
analysis, monitoring and evaluation helps to develop strategies to
benefit men and women without undermining the control of these
commodities by either
• Skills building and using gender transformative approaches can ensure
that women do not lose control of these commodities as they enter
the market arena.
• Indicators for market and value chain projects need to be ‘gendered’
and to go beyond measuring participation and household incomes and
focus on distributional impacts
• . Working with both men and women in market development, working
on multiple value chains and multiple markets (both formal and
informal) and integrating gender training in market development can
mitigate against negative intra-household effects from value chain and
market development programs
Acknowledgements
• Funding provided by
– Belgian Directorate General for
Development Cooperation
– CIDA and SDC funding to the
Pan Africa Bean Research
Alliance