Presentation during IITA R4D week 2015 (23 - 27 Nov. 2015). By: Bola A. Awotide, D.B. Mignouna, T. Abdoulaye, A. Alene and V.M. Manyong

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Yam Participation and Poverty
Bola A. Awotide, D.B. Mignouna, T. Abdoulaye, A. Alene
and V.M. Manyong
27th November 2015
(R4D Week 2015)

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Yam Participation and Poverty
Bola A. Awotide, D.B. Mignouna, T. Abdoulaye, A. Alene
and V.M. Manyong
Workshop on KPI-Poverty: Update on Progress and the Way forward

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Outline
Context
Objective
Methodology
Results
Conclusion

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Context

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Context
Some Basic Facts
 African contribution to the global grains supplies:
 Maize: about 5%
 Rice: 3%
 Wheat: 3% (FAOSTAT 2013)
 Africa is the lead player in the supplies of root & tubers:
 Cassava: 50%
 Yam: 95 % of world production

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Context Ct.
Figure: Yam production from 2003 to 2012 (FAO, 2014)

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Leading yam producing countries: Nigeria & Ghana are
economically engaged in subsistence agriculture (Encyclopedia
2012)
Transforming the yam sector from subsistence to more
marketed oriented production system i.e smallholder
commercialization
Increase productivity and poverty reduction can be achieved
through yam commercialization
Context Ct.

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Objective

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Evaluate the effect of Agricultural
commercialization on productivity
and poverty reduction
Does market participation leads to increase in productivity and by
extension a reduction in poverty?
Objective

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Methodology

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2
2
95.0 )1(
e
PPZ
n

 (n = sample size; Z = value of the standard variate at a given confidence level; P =
sample proportion in the target population estimate to have a particular characteristic, e = accuracy
desired, set at 0.05. )
2
2
)05.0(
55.045.0)96.1( 
n
380n , provided that response rate r is 100%
40095.0/380/380  rn , given 95% response rate
Under simple random sampling, At 95% confident level desired, the sample size n
must satisfy the formula:
csn Design effect   srsn
csn (Ghana)=1.5X 400 =600, given the defaultdesign effect  = 1.5(U.N. Stat.)
csn (Nigeria)=2.0X400 =800,given thedefault design effect  = 2.0 (U.N. Stat.)
Under cluster sampling
Methodology

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States Production
(‘000 metric
tons)
#LGAs
selected &
adjusted
#Com
selected
#Hhs
selected
Niger 6236.2 9 65 260
Nasarawa 2057.1 4 20 80
Benue 2902.8 6 30 120
Ebonyi 1448.3 3 15 60
Enugu 3094.4 7 35 140
Kogi 1361.6 5 15 60
Edo 782.4 3 10 40
Oyo 698.6 3 10 40
Total 18581.4 40 200 800
NIGERIA
Multistage, random
sampling procedure
- 8 states
- 40 LGAs
- 200 communities
- 800 hhs
(Sampling frame as
source list)
Sampling procedure
Methodology Ct.

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District #Com #Com selected #Hhs selected
Mion 30 10 60
East Gonja 71 23 138
Kintampo 93 30 180
Atebubu-Amantin 66 21 126
Ejura 50 16 96
Total 310 100 600
GHANA
Multistage, random
sampling procedure
- 5 districts
- 100 communities
- 600 hhs
(Sampling frame as source
list)
Methodology Ct.

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NigeriaGhana
Methodology Ct.

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- Poverty Measurement FGT
(Foster, Greer and Thorbecke, 1984)
-Propensity Score Matching (PSM)
Analytical model

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Results

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Results & Discussion
Characteristics All (N=600)
Male-headed Hhs (%) 89.8
Average age of Hhs (years) 48.7
Attended school for Hhs (%) 30.0
Average years of schooling for Hhs 2.7
Experience in yam growing for Hhs (years) 23.4

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64.5
35.5
Proportion of Yam Farmers by market
participation
Participants Non-participants
• They sold an average
of 8731.63 kg of yam
per annum
• With an average annual
income of $ US
2596.33
Results & Discussion Ct.

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0 200 400 600 800 1000 1200
Total
Participants
Non-participants
Income per Hectare
Income in $US per Hectare
Results & Discussion Ct.

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0
100
200
300
400
500
600
700
800
900
1000
Total Participants Non-participants
901.09
970.51
774.95
PerCapitaIncome
Per Capita Income
Results & Discussion Ct.

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Poverty indices Total
sample
Participants Non-participants
Poverty Head count 0.6583 0.6331 0.7042
Poverty Gap 0.4646 0.4566 0.4791
Poverty Severity 0.3709 0.3682 0.3758
Results & Discussion Ct.

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Parameter Participants Non-
participants
Difference T-stat.
Unmatched 9089.23 7663.32 1425.90 1.40
ATT 9089.23 6972.59 2116.64* 1.82
ATU 7663.32 9010.45 1347.13 -
ATE - - 1844.35 -
Market participation significantly impacted yam productivity by 2116.64 kg/ha
Note: * significant at 10 %
Results & Discussion Ct.

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Parameter Participants Non-
participants
Difference T-stat.
Unmatched 0.7829 0.8169 -0.0339 1.56
ATT 0.7829 0.8088 -0.0258** 2.44
ATU 0.8169 0.7840 -0.0328 -
ATE - - 0.0283 -
Market participation significantly reduced poverty headcount by 2.6%
Note: ** significant at 5 %
Results & Discussion Ct.

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Conclusion

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Market participation significantly increase yam
productivity in Ghana and generate a reduction in all
the poverty indices
This implies that market participation is essential to
achieve increase agricultural productivity and drastic
reduction in poverty in Ghana
Programs and policies that can link farmers to the
market are highly recommended
Conclusion

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Thank you
D.Mignouna@cgiar.org
www.iita.org