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CGIAR PIM Workshop
Contract farming for rural transformation and
market access to smallholder farmers in the
rice value-chain: A randomized control trial
approach
A. Aminou, J.C. Lokossou, and J.D. Michler
Vancouver, BC, Canada, July 28, 2018
Rice is an important dietary energy source in West
Africa and Madagascar and is becoming important
in the rest of Africa
Demand is growing at more than 6% per year –
faster than for any other food staple in SSA
For Africa Rice, developing the rice value chain is a
key strategy for poverty alleviation and food security
improvement
Background
Background
In SSA, smallholder rice production is mainly for
consumption, low productivity and not integrated
into the commercial value chain
One of factors responsible for this is the weak link
between the different actors in the value chain
Contract farming (CF) is an institutional form that
could strengthen the links between actors and
promote rural transformation
Background
 Contract farming are agreements between different
value chain actors - from production to marketing
including financial and insurance institutions
 Contractual arrangements aim to benefit each party
which may eventually make the chain more efficient
 The objective of this research is to quantify the impact
of different attributes of contractual arrangements on
rural transformation outcomes
Contribution to literature
 One strain of literature claims contract farming has
positive impacts on household welfare
Barrett et al., 2012; Bellemare, 2010; Kirsten and Satorius,
2002; Reardon et al., 2009
 A separate strain is more dubious regarding the
benefits of contract farming to smallholders
Singh, 2002; Guo et al., 2005
 This paper is the first to use a randomized control trial
to explore the impacts of contract farming on
smallholder farmers
Theory of change
 Mighell and Jones (1963) classified contract farming
schemes into three categories:
 market-specifying contract;
 resource-providing contract
 production-management contract
 For rural transformation, three contract farming
attributes can be combined (i) agreement on price
and quantity, (ii) input loans, (iii) training and
backstopping for farmers
Theory of change
Experimental design
 We randomized farmers into either 1 of 3 types of
contracts or into a control group
T1: miller provides an agreement on sale price and
quantity, plus input loans and technical training
T2: miller provides an agreement on sale price and
quantity, plus technical training
T3: miller provides an agreement on sale price and
quantity
C: control farmers with no agreement
Outcomes of interest are 4 rural transformation
indicators: farm size, productivity, market
participation, and income
Data analysis
Baseline data was collected in 2015
Targeted farmers who had grown rice in the previous year
and who expressed interest in growing rice in 2016
Data collected prior to random assignment
Prior to 2016 growing season, farmers randomly
assigned into one of the 4 groups
End-line data was collected at harvest
Econometric method
Simple difference-in-difference and difference-in-difference
with covariates
Results
Impact of CF on farm size
Farm size (ha)
Price and quantity agreement (T3#C)
Using with-without difference 0.23*** (0.07)
Using double difference (DD) 0.20** (0.08)
Using DD with covariates 0.24*** (0.06)
% of increase 31.40
Input loan and training/backstopping agreement (T1#T3)
Using with-without difference 0.14** (0.04)
Using double difference (DD) 0.18** (0.07)
Using DD with covariates 0.23*** (0.08)
% of increase 38.98
Input loan, training/backstopping and price and quantity agreement (T1#C)
Using with-without difference 0.24*** (0.05)
Using double difference (DD) 0.31*** (0.08)
Using DD with covariates 0.34*** (0.09)
% of increase 44.74
Results
Impact of CF on productivity
Productivity (kg/ha)
Price and quantity agreement (T3#C)
Using with-without difference 480.83*** (181.38)
Using double difference (DD) 486.43*** (155.87)
Using DD with covariates 477.99*** (161)
% of increase 28.93
Input loan and training/backstopping agreement (T1#T3)
Using with-without difference 513.37*** (182.44)
Using double difference (DD) 568.39*** (196.33)
Using DD with covariates 578.17*** (175.31)
% of increase 24.77
Input loan, training/backstopping and price and quantity agreement (T1#C)
Using with-without difference 567.45*** (195.56)
Using double difference (DD) 633.90*** (284.86)
Using DD with covariates 608.48*** (288.08)
% of increase 36.83
Results
Impact of CF on market participation
Participation (% rice sold)
Price and quantity agreement (T3#C)
Using with-without difference 30.19*** (5.62)
Using double difference (DD) 34.83*** (6.33)
Using DD with covariates 33.77*** (6.40)
% of increase 135.29
Input loan and training/backstopping agreement (T1#T3)
Using with-without difference 18.61** (4.52)
Using double difference (DD) 11** (5.23)
Using DD with covariates 11.78** (5.23)
% of increase 25.60
Input loan, training/backstopping and price and quantity agreement (T1#C)
Using with-without difference 41.15*** (5.64)
Using double difference (DD) 44.26*** (5.74)
Using DD with covariates 43.67*** (5.79)
% of increase 181.95
Results
Impact of CF attributes on Income
Income (US$/ha)
Price and quantity agreement (T3#C)
Using with-without difference 166*** (84)
Using double difference (DD) 118*** (52)
Using DD with covariates 122*** (54)
% of increase 23.41
Input loan and training/backstopping agreement (T1#T3)
Using with-without difference 120** (56)
Using double difference (DD) 118** (55)
Using DD with covariates 115** (59)
% of increase 26.71
Input loan, training/backstopping and price and quantity agreement (T1#C)
Using with-without difference 187*** (22)
Using double difference (DD) 222*** (82)
Using DD with covariates 218*** (79)
% of increase 46.12
Conclusion
Contract farming has the potential to generate rural
transformation through increasing farm size,
increasing productivity, greater market
participation, and, ultimately more income
Contracts providing all three attributes (access to
market, input loans, and technical training) generated
the largest gains for farmers relative to the control
However, simply providing access to a reliable
market (through price and quantity contract)
generated surprisingly strong impacts
Future research should continue to explore what are
the binding constraints to rural transformation
THANK YOU
MERCI

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Contractual arrangements for rural transformation and market access to smallholder farmers in the rice value-chain: A randomized control trial approach

  • 1. CGIAR PIM Workshop Contract farming for rural transformation and market access to smallholder farmers in the rice value-chain: A randomized control trial approach A. Aminou, J.C. Lokossou, and J.D. Michler Vancouver, BC, Canada, July 28, 2018
  • 2. Rice is an important dietary energy source in West Africa and Madagascar and is becoming important in the rest of Africa Demand is growing at more than 6% per year – faster than for any other food staple in SSA For Africa Rice, developing the rice value chain is a key strategy for poverty alleviation and food security improvement Background
  • 3. Background In SSA, smallholder rice production is mainly for consumption, low productivity and not integrated into the commercial value chain One of factors responsible for this is the weak link between the different actors in the value chain Contract farming (CF) is an institutional form that could strengthen the links between actors and promote rural transformation
  • 4. Background  Contract farming are agreements between different value chain actors - from production to marketing including financial and insurance institutions  Contractual arrangements aim to benefit each party which may eventually make the chain more efficient  The objective of this research is to quantify the impact of different attributes of contractual arrangements on rural transformation outcomes
  • 5. Contribution to literature  One strain of literature claims contract farming has positive impacts on household welfare Barrett et al., 2012; Bellemare, 2010; Kirsten and Satorius, 2002; Reardon et al., 2009  A separate strain is more dubious regarding the benefits of contract farming to smallholders Singh, 2002; Guo et al., 2005  This paper is the first to use a randomized control trial to explore the impacts of contract farming on smallholder farmers
  • 6. Theory of change  Mighell and Jones (1963) classified contract farming schemes into three categories:  market-specifying contract;  resource-providing contract  production-management contract  For rural transformation, three contract farming attributes can be combined (i) agreement on price and quantity, (ii) input loans, (iii) training and backstopping for farmers
  • 8. Experimental design  We randomized farmers into either 1 of 3 types of contracts or into a control group T1: miller provides an agreement on sale price and quantity, plus input loans and technical training T2: miller provides an agreement on sale price and quantity, plus technical training T3: miller provides an agreement on sale price and quantity C: control farmers with no agreement Outcomes of interest are 4 rural transformation indicators: farm size, productivity, market participation, and income
  • 9. Data analysis Baseline data was collected in 2015 Targeted farmers who had grown rice in the previous year and who expressed interest in growing rice in 2016 Data collected prior to random assignment Prior to 2016 growing season, farmers randomly assigned into one of the 4 groups End-line data was collected at harvest Econometric method Simple difference-in-difference and difference-in-difference with covariates
  • 10. Results Impact of CF on farm size Farm size (ha) Price and quantity agreement (T3#C) Using with-without difference 0.23*** (0.07) Using double difference (DD) 0.20** (0.08) Using DD with covariates 0.24*** (0.06) % of increase 31.40 Input loan and training/backstopping agreement (T1#T3) Using with-without difference 0.14** (0.04) Using double difference (DD) 0.18** (0.07) Using DD with covariates 0.23*** (0.08) % of increase 38.98 Input loan, training/backstopping and price and quantity agreement (T1#C) Using with-without difference 0.24*** (0.05) Using double difference (DD) 0.31*** (0.08) Using DD with covariates 0.34*** (0.09) % of increase 44.74
  • 11. Results Impact of CF on productivity Productivity (kg/ha) Price and quantity agreement (T3#C) Using with-without difference 480.83*** (181.38) Using double difference (DD) 486.43*** (155.87) Using DD with covariates 477.99*** (161) % of increase 28.93 Input loan and training/backstopping agreement (T1#T3) Using with-without difference 513.37*** (182.44) Using double difference (DD) 568.39*** (196.33) Using DD with covariates 578.17*** (175.31) % of increase 24.77 Input loan, training/backstopping and price and quantity agreement (T1#C) Using with-without difference 567.45*** (195.56) Using double difference (DD) 633.90*** (284.86) Using DD with covariates 608.48*** (288.08) % of increase 36.83
  • 12. Results Impact of CF on market participation Participation (% rice sold) Price and quantity agreement (T3#C) Using with-without difference 30.19*** (5.62) Using double difference (DD) 34.83*** (6.33) Using DD with covariates 33.77*** (6.40) % of increase 135.29 Input loan and training/backstopping agreement (T1#T3) Using with-without difference 18.61** (4.52) Using double difference (DD) 11** (5.23) Using DD with covariates 11.78** (5.23) % of increase 25.60 Input loan, training/backstopping and price and quantity agreement (T1#C) Using with-without difference 41.15*** (5.64) Using double difference (DD) 44.26*** (5.74) Using DD with covariates 43.67*** (5.79) % of increase 181.95
  • 13. Results Impact of CF attributes on Income Income (US$/ha) Price and quantity agreement (T3#C) Using with-without difference 166*** (84) Using double difference (DD) 118*** (52) Using DD with covariates 122*** (54) % of increase 23.41 Input loan and training/backstopping agreement (T1#T3) Using with-without difference 120** (56) Using double difference (DD) 118** (55) Using DD with covariates 115** (59) % of increase 26.71 Input loan, training/backstopping and price and quantity agreement (T1#C) Using with-without difference 187*** (22) Using double difference (DD) 222*** (82) Using DD with covariates 218*** (79) % of increase 46.12
  • 14. Conclusion Contract farming has the potential to generate rural transformation through increasing farm size, increasing productivity, greater market participation, and, ultimately more income Contracts providing all three attributes (access to market, input loans, and technical training) generated the largest gains for farmers relative to the control However, simply providing access to a reliable market (through price and quantity contract) generated surprisingly strong impacts Future research should continue to explore what are the binding constraints to rural transformation