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 co-

operatives, – 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

Common welfare functionPooling of resourcesHead is altruist

Unitary Household Model

Non-CooperativeCo-operative

Collective Household Model

Measure outcomes at household level Measure outcomes at

individual level

Individual autonomyIndividual preferencesSub-economies

Choice of acting as individuals or joint“mine, yours, ours”

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 Number of farmers actively marketing

Mean average annual income (USD)

% contribution to total household income

Beans 80 79.5 22.9Potatoes 91 270.1 37.2Groundnuts 62 73.6 11.9Soybeans 14 70.8 29.5Rice 90 232.5 43.5Goats 55 53.4 22.2Pigs 40 113.9 27.9Milk 12 906.3 31.6Poultry 16 77.8 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)

More joint management of income from groundnuts compared to the other 2 legumes

Most income form potatoes managed jointly, while income from rice mainly managed by women (45.1%)

Beans Groundnuts Soyabeans0%

10%20%30%40%50%60%70%80%90%

100%

Legumes

Women Men Joint

% o

f inc

ome

unde

r sol

e /j

oint

man

agem

ent

potatoes rice0%

10%20%30%40%50%60%70%80%90%

100%

Other Crops

Women Men Joint

% o

f inc

ome

unde

r sol

e /j

oint

man

agem

ent

Income management by men and women

Goats Pigs Poultry Dairy milk0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Livestock and livestock products

Women Men Joint

% o

f inc

ome

unde

r sol

e /jo

int m

anag

emen

t

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 womenFifty 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

Poultry Rice Groundnuts Potatoes Pigs Goats0

20

40

60

80

100

120

140

160

180

200

0

10

20

30

40

50

60

Mean income % income share to women

• 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)

Income share over time..the influence of markets

• 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.

• Uganda-Productivity improvement interventions-Slight changes in income management by women

2004A 2004B 2005A 2005B 2006A 2006B 2007A 2007BSeason

0

10

20

30

40

50

60

70

80

Beans -Uganda

Women Men Joint

2003/4 2004/5 2005/6 2006/70

200

400

600

800

1000

1200

1400

1600

0

5

10

15

20

25

30

35

40

Beans-Malawi

Total income Income share to women

Tota

l inc

ome

% in

com

e sh

are

to w

omen

Other determinants of income managementUnstandardized Coefficients

Standardized Coefficients

t Sig.

B SE Beta(Constant) -6.763 10.957 -.617 .538Enterprise /product Beans 10.108 5.547 .104 1.822 .070 Groundnuts 29.017 7.067 .226 4.106 .000 Soyabeans 1.839 9.762 .010 .188 .851 Goats 9.721 6.375 .090 1.525 .129 Pigs .151 12.159 .001 .012 .990 Poultry -4.087 16.986 -.011 -.241 .810% of enterprise income to total hh income

.042 .092 .022 .452 .652

Who sold (1=Wife 0=Other) 65.588 4.734 .685 13.854 .000Market sold to (1=local or farm gate 0=other)

-4.663 5.740 -.043 -.812 .418

education of men (0=None, 1=Primary and above)

3.673 5.535 .032 .664 .508

education women (0=None, 1=Primary and above)

-5.651 4.571 -.063 -1.236 .218

Family size -1.051 .782 -.064 -1.343 .181Age of household (years) .405 .163 .124 2.480 .014R2 0.606

So what? Do men and women spend income under their control differently?

Expenditure item

Husband Wife Joint

Food 6 23 8Agricultural production

14 22 25

Assets 25 14 15Education 20 7 20Health 5 2 3Clothing 18 22 5Social assistance

2 2 8

Leisure 2 1 2Other 8 7 14Total 100 100 100

• 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