1) The document discusses a project in Mozambique that trained contact farmers (CFs) in sustainable land management (SLM) techniques and had them establish demonstration plots to transfer knowledge to other farmers. 2) The project evaluated the impact of CF training on technology adoption and yields. It found some evidence that CFs adopted SLM techniques in their demonstration plots but little impact on other farmers' adoption or yields. 3) While CFs and farmers interacted and farmers visited demonstration plots, this did not translate to widespread adoption of SLM or perceived productivity gains from the techniques. Overall the CF training approach showed limited success in increasing SLM adoption and agricultural productivity.

1. 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

2. Challenge to Agricultural Growth:
Low Adoption of ImprovedTechnologies
0
10
20
30
40
50
60
70
80
90
100
Chemba Maringue Mopeia Morrumbala Mutarara
Percentage
Crop Rotation
Intercropping
Row planting
Source:TIA (2008)

3. 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)

4. 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)

5. Market-led Smallholders Development
in the ZambeziValley Project (2007-2013)
• GoM andWorld 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

6. CFs trained in SLMTechniques
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)

7. 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

8. 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?

9. 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

10. 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 acrossT & Control
– CFs answer household survey &
separate CF survey
– Extension agent survey

11. 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.

12. CFTraining & CF Retention by Endline
Communities that had at least 1 CF attend training in 2013 (Attendance)
16% Control
63%Treated

13. Intent toTreat (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.

14. 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)

15. 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.

16. 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)

17. 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

18. 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

19. 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

20. Farmers PerceiveTechniques 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

21. 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

22. 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

23. 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

24. 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

25. 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

26. 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)

27. 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 fromCF 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

28. 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