Gender and Cereal Intensification in
the West African Sahel
V E R O N I Q U E T H E R I AU LT, M E L I N DA S M A L E , H A M Z A H A I D E R
F O O D S E C U R I T Y G R O U P, D E PA R T M E N T O F A G R I C U LT U R A L , F O O D, A N D R E S O U R C E
E C O N O M I C S , M I C H I G A N S TAT E U N I V E R S I T Y
S E M I N A R , F O O D A N D R E S O U R C E E C O N O M I C S , U N I V E R S I T Y O F F LO R I DA
MARCH 11, 2016
Motivation
Population dynamics and climate change exacerbate food insecurity
Household decision-making processes are undergoing changes
◦ More women are planting sorghum- a crop traditionally cultivated by men
Understanding gender differences in the adoption of intensification
strategies is crucial
Previous work
Women play a major role in agriculture, but they face more constraints than men
Gender differentials in farm productivity
◦ Access to inputs and resources
◦ Tenure rights
◦ Household versus plot
Technology adoption
◦ Intensification strategies are context-specific
◦ Gender dimension is often ignored
Hypotheses
1) Female managers adopt intensification strategy sets at lower rates than their male
counterparts on cereals plots
2) Gender differences in the likelihood of adoption depend on the strategy set
3) Determinants of adoption differ between male and female managers of individual plots
Farming Structure & Gender Dynamics
Sorghum, millet, and maize account for over 70% of total cultivated land
Family conducts farm work across numerous plots
◦ Collective plots are managed by the head of the household
◦ Individual plots are managed by different household members
Upon marriage, women may have access to individual plots
Data
Continuous Farm Household Survey (Enquête Permanente Agricole )
◦
◦
◦
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Nationally representative (45 provinces, 826 villages)
2009/10-2011/12
2700 households growing cereals, 11 000 individual cereal plots
Production, area, livestock holding, income and expenditure, input use
NOAA’s Climate Prediction Center
◦ Rainfall variability at the commune level
Empirical Strategy
Perceived benefits derived from adopting an intensification strategy
(1)
𝑦𝑦𝑖𝑖𝑖𝑖∗ = 𝑋𝑋𝑋𝑖𝑖𝑖𝑖 𝛽𝛽 + 𝑢𝑢𝑖𝑖𝑖𝑖 + 𝑐𝑐𝑖𝑖
i=1,….n, and t=1,…,T
The decision to adopt is observable (𝑦𝑦𝑖𝑖𝑡𝑡)
(2)
∗
𝑦𝑦𝑖𝑖𝑖𝑖 =1 if 𝑦𝑦𝑖𝑖𝑖𝑖
>0
=0 Otherwise
Probability of adopting an intensification strategy
(3)
Prob (𝑦𝑦𝑖𝑖𝑖𝑖 = 1⎹ 𝑋𝑋𝑖𝑖𝑖𝑖 ) = F(𝑋𝑋𝑋𝑖𝑖𝑖𝑖 𝛽𝛽 + 𝑐𝑐𝑖𝑖 )
Empirical Strategy
Multivariate Probit Model
◦ Estimating several probit models simultaneously
◦ Allowing the error terms to be correlated
Chamberlain-Mundlak device
◦ Allowing for unobserved heterogeneity (𝑐𝑐𝑖𝑖) to be correlated with observed covariates
(4)
𝑐𝑐𝑖𝑖 = 𝑋𝑋𝑋𝑖𝑖 𝛿𝛿 + 𝛼𝛼𝑖𝑖 + 𝑤𝑤,
𝛼𝛼𝑖𝑖 ⎹ 𝑋𝑋𝑖𝑖 ~ 𝑁𝑁(0, 𝜎𝜎𝛼𝛼2 )
The reduced form
(5)
Prob (𝑦𝑦𝑖𝑖𝑖𝑖 = 1⎹ 𝑋𝑋𝑖𝑖𝑖𝑖 ) = F(𝑋𝑋𝑋𝑖𝑖𝑖𝑖 𝛽𝛽 + 𝑋𝑋𝑋𝑖𝑖 𝛿𝛿 + 𝛼𝛼𝑖𝑖 + 𝑤𝑤)
Defining Adoption
Strategy sets
◦ Yield-enhancing inputs (set 1) - improved seed and inorganic fertilizer
◦ Yield-protecting inputs (set 2) - pesticides, fungicides, and herbicides
◦ Soil and water conservation (set 3) – amendments, anti-erosion, and water-harvesting structures.
Factors affecting adoption of strategy sets
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Gender of the plot manager and household headship
Age, education, marital status
Size, distance to residence, topography, and tenure rights
Labor availability
Total landholding, livestock, non-farm income, cotton hectares
Access to credit and extension service, density of agrodealers
Coefficient of variation in total annual rainfall
Hypothesis 1
Table 1. Adoption Rates
Strategy Sets
All individually-managed
Male-managed
Female-managed
p-value
N=9050
N=3078
N=5972
Yield-enhancement
10.7
15.2
8.2
0.000
Yield-protection
16.7
18.6
15.7
0.000
Soil and water conservation
25.0
29.6
22.6
0.000
Hypothesis 2
Table 2. Pooled Multivariate Probit Model
Gender
Yield-Enhancing
(Set 1)
Yield-Protecting
(Set 2)
SWC
(Set 3)
-0.094
(0.073)
-0.060
(0.064)
-0.129**
(0.057)
The probability of adopting one set is interdependent on the decision to whether to adopt another set
The socio-cultural farming context combined with the economic attributes of technology affect adoption of the
SWC strategy set, not gender per se
Hypothesis 3
◦ The underlying process that explains adoption differs between men and women
◦ Married men are more likely to adopt labor-intensive intensification strategies
◦ Women’s adoption decisions are influenced by variables capturing labor availability
◦ Other household resources affect mostly men’s decisions
◦ Extension services, mostly target male farmers, influencing their decision to adopt modern inputs
◦ Secure tenure rights positively influence the decision to adopt intensification strategy sets that have medium to
long terms benefit
Conclusions
Hypothesis 1
◦ Women are, in average, adopting at lower rates any of the three intensification strategy sets
Hypothesis 2
◦ No difference in the probability of adopting the yield-enhancing and yield-protecting sets between men and
women on their individual cereal plots, after controlling for other covariates.
◦ Women are statistically less likely to adopt the SWC strategy set
economic attribute of the technology affect incentives to adopt.
The socio-cultural farming context and
Hypothesis 3
◦ The determinants of adoption of intensification strategy sets differ across gender
Policy Implications
The interrelatedness of adoption strategy sets
◦ Designing mechanisms to encourage the use of combinations of practices
The variation in input use within strategy sets
◦ Farmers are not best approached with a fixed package in mind
Design policies that respect opportunities and incentives for individuals within multigenerational,
multi-family farms
Thank you
This work receives financial support from the Gates Foundation Global Development Program