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"Does training AND female representation in extension foster investments?", Florence Kondylis, World Bank, Valerie Mueller, IFPRI (PRESENTER), Siyao Zhu, World Bank, Workshop on Transformation of Agri-food Systems and Commercialization of Smallholder Agriculture in Mozambique: Evidence, Challenges and Implications Maputo, Mozambique, December 9, 2013
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Does training AND female representation in extension foster investments?
Florence Kondylis, World Bank
Valerie Mueller, IFPRI (PRESENTER)
Siyao Zhu, World Bank
TRANSFORMATION OF SMALLHOLDER AGRICULTURE IN MOZAMBIQUE WORKSHOP, 9/12/13
Challenge to Agricultural Growth: Low Adoption of Improved Technologies
0
10
20
30
40
50
60
70
80
90
100
Chemba Maringue Mopeia Morrumbala Mutarara
Pe
rce
nta
ge
Crop Rotation
Intercropping
Row planting
Source: TIA (2008)
Challenge to Agricultural Growth: Delivery of Extension
0 10 20 30 40 50 60 70 80 90 100
Chemba
Maringue
Mopeia
Morrumbala
Mutarara
Source: TIA (2008)
Challenge to Agricultural Growth: Women farm, yet lack access to services
• 95 % of women engaged in agriculture
66% of men engaged in agriculture (Farnsworth, 2010)
48%
21%
31%
Men Women Both
Who has access to extension services: men, women, or both?
Source: TIA (2008)
Market-led Smallholders Development in the Zambezi Valley Project (2007-2013)
• GoM and World Bank
• Several activities in five districts to improve farmer income, soil fertility, and ecosystem resilience to climate change
• As part of the project, 8 extension agents assigned per district
• Project and local authorities nominate main farmer in the community as contact farmer (CF)
• Some CFs trained and given resources to maintain a demonstration plot
CFs trained in SLM Techniques
mulching row planting intercropping micro-basins
contour farming
crop rotation
strip tillage
improved fallowing
*Many of these have been shown to improve yields in Mozambique or elsewhere (Liniger et al., 2011)
What is the impact of training at least 1 CF who manages a demonstration plot within a community?
TRANSFORMATION OF SMALLHOLDER AGRICULTURE IN MOZAMBIQUE WORKSHOP, 9/12/13
Extensions
TRANSFORMATION OF SMALLHOLDER AGRICULTURE IN MOZAMBIQUE WORKSHOP, 9/12/13
Does adding trained female CFs increase SLM adoption?
Do incentives given to CFs increase adoption?
Timeline
October 2010 • Random set of EAs
and CFs trained based on CF census
• Demonstration plots
• Bicycles
November 2012 • EAs and CFs
trained (concentrate on contour farming and mulching)
January 2012 • Midline
survey
April 2013 • Endline
survey
June 2010 • CF census,
baseline survey
Data
Smallholders’ Panel Survey (2012 midline and 2013 endline) – Baseline census of CFs in all 300+ communities to randomize
– 4,000 households in 200 EAs
– Individual adoption/ SLM tech.
– Household productivity
– Retrospective questions to
confirm balance across T & Control
– CFs answer household survey &
separate CF survey
– Extension agent survey
Gendered Barriers to Adoption? Mean Differences within the Control
Male-
Male Female Female
P-value
Number of days spent preparing land per hectare 52.24 37.21 0.09
Grew maize 0.65 0.60 0.34
Grew sorghum 0.12 0.31 0.01
Grew cotton 0.19 0.02 0.00
Grew sesame 0.25 0.09 0.00
Grew cassava 0.20 0.15 0.46
Grew cowpea 0.27 0.38 0.13
Grew pigeon pea 0.20 0.17 0.55
Plot size (hectares) 1.01 0.83 0.01
Plot soil is fertile 0.90 0.88 0.62
Plot has erosion problem 0.10 0.07 0.30
Uses herbicides/pesticides/fungicides on the plot 0.12 0.02 0.00
Uses natural fertilizer on the plot 0.28 0.29 0.83
Uses chemical fertilizer on the plot 0.01 0.00 0.45
Number of crops grown on plot 1.89 1.92 0.30
Number of plots 565 708 1273
Source: Smallholders’ Household Survey (2012) Notes: T statistics based on standard errors clustered at the community level.
CF Training & CF Retention by Endline
Communities that had at least 1 CF attend training in 2013 (Attendance)
16% Control
63% Treated
Intent to Treat (ITT) Estimates
Yi,h,j=β0+β1Tj +β2Xi,h,j+εi,h,j
– T=1 for each community j with at least 1 trained, CF who manages a
demonstration plot (150 communities). – X =(midline age, complete primary education, marital status, number of
children, total plot area, number of rooms in house, Incentive treatment, district dummies)
– Two units of analysis: CF and Regular farmer Note: All SEs clustered at community level except for in CF regressions.
Intensity of Extension Agent-CF Interactions
Source: Smallholders’ Panel Household Survey, Panel Contact Farmer Survey
2012 (N=201) 2013 (N=189)
Mean of control ITT (SE)
Mean of control
ITT (SE)
CF says, “Extension agent visited me 1/week”
0.24 0.15* (0.08)
0.17 0.09 (0.08)
CF says, “Extension agent visited me 1/month”
0.30 -0.22*** (0.08)
0.26 -0.07 (0.10)
CF says, “Extension agent visited me 2x/year”
0.13 0.04 (0.08)
0.10 0.15* (0.08)
Do CFs adopt SLM technologies?
Source: Smallholders’ Household Survey, Contact Farmer Survey
Mulching Strip tillage Micro- basins
Contour farming
ITT (Standard Errors)
2012
2013
2012 2013 2012 2013 2012 2013
Demonstration plot
0.10 (0.07)
-0.07 (0.08)
0.17* (0.09)
0.14 (0.10)
0.18* (0.10)
0.11 (0.10)
0.17* (0.10)
0.08 (0.06)
[Mean of control] [0.83] [0.86] [0.57] [0.36] [0.57] [0.29] [0.37] [0.05]
Own farm
0.26*** (0.10)
-0.01 (0.07)
0.09 (0.09)
0.11 (0.10)
0.18** (0.08)
-0.00 (0.10)
0.03 (0.02)
0.07** (0.03)
[Mean of control] [0.45] [0.86] [0.26] [0.38] [0.11] [0.38] [0.00] [0.00]
Note: HH Survey N= 210 in 2012, N=189 in 2013; CF Survey N=201 in 2012, N=189 in 2013.
No evidence that CFs perceive SLM enhances production
Variable Mean of Control ITT (SE) N
Strip Tillage Increases productivity 0.261 0.062 201
(0.087) Reduces land preparation efforts 0.217 0.075 201
(0.080) Reduces planting seed efforts 0.261 0.016 201
(0.082) Reduces harvesting efforts 0.174 -0.103* 201
(0.062)
Source: Smallholders’ Contact Farmer Survey (2012)
CF household yields (kg/ha)
2012 2013
Mean of control
ITT (SE)
Mean of control
ITT (SE)
Maize 155.36 -7.47 (41.98)
262.41 65.17 (100.98)
Sorghum 57.01 -5.88 (29.38)
60.46 -7.32 (14.65)
Cowpea 8.29 -1.65 (4.23)
6.82 -2.99 (1.94)
Pigeonpea 8.86 -1.34 (5.72)
8.15 -5.45 (4.07)
Cassava 12.11 8.13 (10.14)
14.56 -8.34** (4.07)
Cotton 66.57 2.56 (30.29)
18.18 -1.36 (9.35)
Sesame 60.31 -25.36 (18.75)
35.78 -1.56 (12.18)
CF households 210 186
What are the potential channels of CF knowledge transfer to smallholders?
Source: Smallholders’ Household Survey
2012 2013
ITT (Standard Errors)
Women Men Women Men
Farmer says, “Most important source of info. is from demo plot”
0.01 (0.02)
0.02 (0.03)
0.01 (0.02)
0.01 (0.03)
[Mean of control] [0.04] [0.07] [0.09] [0.12]
Farmer says, “Most important source of info. is from CF visit to my plot”
0.05** (0.02)
0.06** (0.03)
0.01 (0.02)
-0.00 (0.03)
[Mean of control] [0.09] [0.11] [0.25] [0.28]
Observations 3,599 2,477 2,632 1,980
Intensity of CF-Farmer Interactions
2012 2013
ITT (Standard Errors)
Women Men Women Men
Farmer says, “I visit demo plot at least 1/month”
0.01 (0.01)
0.01 (0.01)
0.01 (0.02)
0.03* (0.01)
[Mean of Control] [0.01] [0.02] [0.05] [0.04]
Farmer says, “CF gave me advice on my plot 2x/year”
0.02 (0.01)
0.03 (0.02)
0.02 (0.02)
0.02 (0.02)
[Mean of Control] [0.03] [0.04] [0.08] [0.06]
Farmer says, “CF gave me advice on my plot 1/year”
0.04* (0.02)
0.06* (0.03)
0.04 (0.03)
0.01 (0.04)
[Mean of Control] [0.10] [0.12] [0.19] [0.26]
Observations 3,599 2,477 2,632 1,980
CF says, “I gave advice on farmer’s plot 2x/year”
0.09* (0.05)
0.08 (0.08)
[Mean of Control] [0.04] [0.14]
Observations 201 189
Farmers Perceive Techniques As Labor-Saving
Variable Specification Mean of Control
ITT (SE) N
Mulching Female 0.131 -0.032 3599 (0.033)
Male 0.142 -0.025 2477 (0.033)
Strip Tillage Female 0.157 -0.019 3599 (0.038)
Male 0.177 -0.044 2477 (0.042)
Micro-Basins Female 0.009 0.011** 3599 (0.005)
Male 0.008 0.019** 2477 (0.008)
Contour Farming Female 0.004 0.008 3599 (0.005)
Male 0.008 -0.003 2477 (0.005)
Source: Smallholders’ Household Survey
Farmer Adoption
– Micro-basins: men (midline), women (endline)
2012 2013
ITT (Standard Errors)
Women Men Women Men
Mulching adoption -0.05 (0.05)
-0.02 (0.05)
0.03 (0.05)
-0.02 (0.06)
[Mean of Control] [0.25] [0.25] 0.39 0.52
Strip tillage adoption -0.03 (0.05)
-0.04 (0.04)
-0.01 (0.04)
-0.03 (0.05)
[Mean of Control] [0.16] [0.16] [0.18] [0.23]
Micro-basins adoption 0.02 (0.02)
0.06*** (0.02)
0.04* (0.03)
-0.01 (0.03)
[Mean of Control] [0.04] [0.04] [0.09] [0.15]
Contour farming adoption 0.00 (0.00)
0.00 (0.00)
-0.01 (0.01)
-0.01 (0.01)
[Mean of Control] [0.00] [0.00] [0.01] [0.02]
Observations 3,599 2,477 2,632 1,980
Farming household yields (kg/ha)
– Micro-basins: men (midline), women (endline)
2012 2013
Mean of control
ITT (SE)
Mean of control
ITT (SE)
Maize 155.36 2.84 (21.76)
262.41 65.17 (100.98)
Sorghum 57.01 -1.07 (9.95)
60.46 -7.32 (14.65)
Cowpea 8.29 0.89 (1.44)
6.82 -2.99 (1.94)
Pigeonpea 8.86 -4.80 (5.70)
8.15 -5.45 (4.07)
Cassava 12.11 9.69* (5.16)
14.56 -8.34** (4.07)
Cotton 66.57 2.01 (10.00)
18.18 -1.36 (9.35)
Sesame 60.31 8.03 (6.68)
35.78 -1.56 (12.18)
Households 3,864 3,338
No Differences in Inputs and Crop Choice by Treatment
Source: Smallholders’ Household Survey (2013)
Variable Name Treated Control Mean Diff. Mean Mean (* for PV) Total labor day 67.215 61.394 5.821 Uses herbicides/pesticides/fungicides on the plot 0.024 0.020 0.004 Uses natural fertilizer on the plot 0.427 0.431 -0.004 Uses chemical fertilizer on the plot 0.006 0.006 0.000 Number of crops grown on plot 2.471 2.458 0.013 Grew maize 0.604 0.616 -0.012 Grew sorghum 0.262 0.268 -0.005 Grew cotton 0.059 0.050 0.008 Grew sesame 0.148 0.123 0.024 Grew cassava 0.137 0.132 0.005 Grew cowpea 0.327 0.337 -0.010 Grew pigeon pea 0.203 0.175 0.027 Plot size (hectares) 1.151 1.078 0.073 Plot is flat 0.596 0.544 0.052 Plot lays in the high zone 0.412 0.378 0.034 Main source of water for this plot is rain 0.982 0.977 0.005 Plot has erosion problem 0.122 0.108 0.014 Plot is burnt 0.251 0.254 -0.003 Number of plots 4795 1647 6442
District level effects?
Source: Smallholder Household Survey
2012 2013
Microbasins Adoption Female Male Female Male
Treatment 0.023 0.071*** 0.045 -0.001
(0.021) (0.021) (0.027) (0.037)
Mopeia -0.127*** -0.079** -0.233*** -0.250***
(0.028) (0.034) (0.034) (0.051)
Treatment*Mopeia 0.004 -0.062** -0.012 -0.019
(0.019) (0.031) (0.028) (0.044)
N 3599 2477 2632 1980
Mean of control 0.041 0.039 0.090 0.146
Treatment Effects DON’T vary with CF Education, Age, and Land
TRANSFORMATION OF SMALLHOLDER AGRICULTURE IN MOZAMBIQUE WORKSHOP, 9/12/13
2012 2013 2012 2013 2012 2013
Microbasins’ Adoption Female Male Female Male Female Male Female Male Female Male Female Male
Treatment 0.032 0.050** 0.031 0.005 0.062 0.096* 0.134 0.099 0.017 0.051** 0.010 -0.011
(0.021) (0.024) (0.028) (0.037) (0.068) (0.050) (0.086) (0.105) (0.029) (0.024) (0.043) (0.068)
Treatment*CF Ed -0.016 0.023 0.024 0.004
(0.027) (0.031) (0.036) (0.050)
Treatment*CF Age -0.001 -0.001 -0.002 -0.002
(0.001) (0.001) (0.002) (0.002)
Treatment*CF Land 0.003 0.002 0.008 0.005
(0.006) (0.004) (0.011) (0.018)
Observations 3395 2348 2261 1723 3395 2348 2261 1723 3395 2348 2261 1723
Mean of control 0.039 0.039 0.089 0.141 0.039 0.039 0.089 0.141 0.039 0.039 0.089 0.141
Does Female Representation in Extension Affect Adoption Rates?
2012 2013
Mean of Control MCF FCF
Mean of Control MFC FFC
Mulching Female 0.249 -0.080* -0.018 0.393 -0.005 0.059
(0.046) (0.050) (0.058) (0.059)
Male 0.248 -0.040 0.005 0.518 -0.048 0.003
(0.047) (0.052) (0.060) (0.060)
Strip tillage Female 0.157 -0.024 -0.027 0.184 -0.044 0.019
(0.051) (0.046) (0.037) (0.042)
Male 0.161 -0.038 -0.036 0.231 -0.069 0.018
Microbasins Female 0.041 0.019 0.029 0.090 0.034
0.052**
(0.019) (0.020) (0.029) (0.025)
Male 0.039 0.063*** 0.052** 0.146 -0.009 0.000
(0.023) (0.022) (0.036) (0.033)
Contour farming Female 0.000 0.003 0.001 0.007 -0.005 -0.009*
(0.002) (0.001) (0.006) (0.006)
Male 0.000 0.006* 0.001 0.019 -0.008 -0.016
(0.003) (0.002) (0.012) (0.011)
Policy Implications
– CF is an effective, scalable way to deal with information market failures
– Peer learning manifested into increased micro-basin adoption
– Demonstration plots used as a commitment device for CFs to learn by doing • Farmers benefit more from CF visits than demonstration plot exposure
• Needs to be a clear mandate for “seed adopters” to actively advise other farmers on new techniques
– Complementarities between men and women CFs further increases adoption and requires further scrutiny
– Extension agents were actively helping CFs, but the intervention lost traction over time • Retention of trained “peer farmers” can be a problem, but mechanisms like performance
incentives prove difficult to implement
• Still need to adjust ITT estimates for CF (ATT) and hh survey attrition
– Need more studies of this size to learn from, using other technologies which produce visible results in the short term
TRANSFORMATION OF SMALLHOLDER AGRICULTURE IN MOZAMBIQUE WORKSHOP, 9/12/13
Thank you!
TRANSFORMATION OF SMALLHOLDER AGRICULTURE IN MOZAMBIQUE WORKSHOP, 9/12/13
• Jose Caravela, Isabel Cossa, Destino Chiar, Beatriz
Massuanganhe (National Directorate of Rural Development)
• Pedro Arlindo, Siobhan Murray, Patrick Verissimo,
Cheney Wells (World Bank) • 3ie, USAID
