3rd Africa Rice Congress Theme 4: Rice policy for food security through smallholder and agribusiness development Mini symposium 4: Evidence of impact and adoption of rice technologies Author: Dibba

1. 1
How accessibility to seeds affects the
potential adoption of an improved rice based
technology: The case of New Rice Varieties
for Africa (NERICA) in The Gambia
Varieties for Africa (NERICA) in The
Gambia
Lamin Dibba*, Manfred
Zeller, Aliou Diagne and Thea
Nielsen

2. 2
Outline of the presentation
1. Introduction
2. Objective of the study
3. Methodology
4. Results and discussion
5. Conclusions
6. Acknowledgments
7. Reference

3. Introduction
• The per capita consumption of rice is estimated at
177kg per annum (PSU, 2011)
• Of the 195,811 metric tons of rice consumed in
2011, only 51,137 metric tons was produced locally
(Agricultural census, 2012)
• Out of the 51,137 metric tons of rice produced
locally in 2011, 23,302 metric tons were entirely
attributed
to
NERICA
cultivation
(Agric
census, 2012)
• Past studies that assess NERICA adoption in The
Gambia control only exposure
or awareness
(Dibba et. al., 2012; Diagne et. al., 2012)
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4. Objectives
• Assess NERICA adoption by controlling for both
exposure and seed access
• Provide estimates of actual and potential adoption
rates and their determinants of the NERICA
varieties
• Determine the adoption gap that arises due to
lack of access to adequate supply of NERICA
seeds
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5. 5
Methodology: Sampling procedure and data
• Multi-stage stratified random sampling procedure
to select villages and farmers across the six
agricultral regions
• 5 NERICA seed dessimination and non NERICA
seed dessination villages randomly selected from
each region
• 10 rice farmers randomly selected in each village
• Data collected included both agronomic and
socio-economic information

6. 6
Methodology: Conceptual framework
• This study relies on the potential outcome
framework to assess the effect of exposure and
access to seeds on NERICA adoption
• Every farmer has two potential or counterfactual
outcomes
(Y1 and Y0 ) for each treatment
(Rosenbaum and Rubin, 1983)
• The causal effect of each treatment (Y1 - Y0 )
• In the adoption context Y0 = 0 for any
observational unit whether treated or untreated
• The adoption impact for farmer i is given by Yi1
and the average impact is given by ATE = E(Y1 )

7. 7
Methodology: Estimation of adoption rates
• The Conditional Independence (CI) assumption
(Rosenbaum and Rubin,1983):
• w(s) is independent of Y1 and Y0 conditional of X
• Potential adoption is independent from Zi
conditional on Xi (Diagne and Demont, 2007)
• Exposure or access to seed is independent of Xi
conditional on Zi
• Overlap for all covariates. Then ATE is semiparametrically identified by equation 1
ˆ
ATE e , s
1
n
n
i 1
ˆ
m( xi )
.......... .......... ......( 1)
ˆ
p ( zi )

8. 8
Results and Discussion
Table 1: Comparison of 2006 and 2010 survey results
Variable
2006
(N=600)
2010
(N=515)
Difference
(T-test)
Exposure to NERICA
0.47 (0.02)
0.88 (0.01)
0.41 (0.02)***
Adoption within NERICA
exposed sub-population
0.85 (0.03)
0.77 (0.03)
-0.08 (0.03)***
NERICA sample adoption
0.40 (0.02)
0.66 (0.02)
0.26 (0.03)***
Practice of upland rice
production
0.53 (0.02)
0.78 (0.02)
0.25 (0.03)***
Practice of lowland rice
production
0.80 (0.02)
0.43 (0.02)
- 0.36 (0.03)***
Farmer contact with NARI
0.5 (0.01)
0.21 (0.02)
0.16 (0.02)***
Farmer contact with DAS
0.31(0.02)
0.32 (0.02)
0.01(0.03)

9. 9
Results and Discussion
Table 2: Actual adoption of NERICA varieties in 2010
Description
Regions
WCR LRR
Total
CRS
NBR
CRN
URR
Total number of farmers
89
85
89
92
78
82
515
Proportion of farmers exposed to
99
95
62
100
86
89
88
84
93
38
80
71
68
72
2008
54
69
20
67
31
56
50
2009
65
79
29
67
59
72
61
2010
76
88
35
72
62
65
66
NERICAs in 2010 (%)
Proportion of exposed farmers who
had access to NERICA seeds in
2010 (%)
Proportion of farmers who adopted
at least one NERICA (%)

10. 10
Results and Discussion
Table 3: ATE semi-parametric estimation of potential adoption rates
ATE exposure ATE access to
model
seeds model
Adoption
gap due to
lack of
seeds
NERICA population adoption rate (ATE)
0.76 (0.29)***
0.92(0.09)***
16%
Adoption rate within the NERICA-exposed and
0.76 (0.34)**
0.92(0.11)***
16%
0.73 (0.11)***
0.89(0.05)***
16%
0.66(0.28)***
0.66(0.08)***
-0.10 (0.02)***
-0.26(0.01)***
0.01 (0.05)
-0.01 (0.03)
seed accessed subpopulation (ATE1)
Adoption within the NERICA non exposed
and seed accessed subpopulation (ATE0)
Joint exposure and adoption (JEA)
Adoption gap of NERICA (GAP)
Expected population selection bias when
using the within NERICA – exposed and seed
accessed sub-sample estimate (PSB)

11. 11
Results and Discussion
Table 4: Factors affecting exposure, access to seeds and adoption
Age
Years of experience in upland farming
Formal education
Household size
Off-farm labor
Woman
Member of association
Log of rice area in 2006
Farmer contact with extension
Access to credit
Farmer contact with NARI
Practice of upland farming
Practice of lowland farming
West coast region
NERICA introduction village
Coefficients of
Exposure
-0.01 (0.007)
0.01 (0.009)
Coefficient of
Coefficient of
Access to seeds
Adoption
-0.01* (0.005)
-0.01 (0.006)
0.02***(0.006) 0.017** (0.008)
0.49 (0.507)
0.069** (0.030)
-1.705*** (0.491)
-1.017***(0.476)
-0.059 (0.261)
-0.233** (0.118)
0.54** (0.246)
-0.017 (0.250)
0.02 (0.242)
0.02 (0.016)
-0.67* (0.364)
0.03 (0.523)
-0.28 (0.182)
-0.09 (0.077)
0.59*** (0.154)
0.30* (0.169)
0.43*** (0.169)
1.60***(0.226)
-0.07 (0.222)
1.22*** (0.46)
0.22 (0.209)
0.73*** (0.161)
0.06 (0.148)
0.32 (0.208)
0.28**(0.141)
0.16 (0.312)
-0.02 (0.019)
0.449 (0.738)
0.31 (0.289)
-0.28 (0.212)
0.00 (0.089)
0.494***(0.175)
0.45**(0.217)

12. Conclusion
• If every rice farmer is aware of the NERICA
varieties 16% will not be able to adopt due to
insufficient supply of seeds
• For successful dissemination and adoption of
NERICA concerted efforts should be made to
increase farmer contact with extension
• Future studies should focus on measuring the
intensity of NERICA adoption
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13. Acknowledgment
• Global Rice Science Program
• Africa Rice Center
• University of Hohenheim
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14. 14
Thank you!
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15. References
• Agricultural census. 2012: Technical report of the agricultural census of The
Gambia
• Diagne A, Glover S, Groom B and Phillips J. 2012. “Africa’s Green
Revolution? The determinants of the adoption of NERICAs in West Africa”
SOAS Department of Economics Working Paper Series, No. 174, SOAS,
University of London
• Diagne A and Demont M. 2007. Taking a New look at Empirical Models of
Adoption: Average Treatment Effect estimation of Adoption rate and its
Determinants. Agricultural Economics, Vol 37 (2007). 30p.
• Dibba L, Diagne A, Fialor SC and Nimoh F (2012). Diffusion and Adoption of
New Rice Varieties for Africa (NERICA) in the Gambia. African Crop Science
Journal, Vol. 20, No. 1, pp. 141 – 153
• Planning Service Unit. 2011. Rice fact book. Unpublished technical report
• Rosenbaum PR and Rubin DR.1983. “The Central Role of the Propensity
Score in Observational Studies for Causal Effects,” Bometrika 70, 41-55.
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