Presented Simegnew Tamir, Kinde Getnet and Jema Haji at the Nile Basin Development Challenge (NBDC) Science Workshop–2013, Addis Ababa, Ethiopia, 9 – 10 July 2013

1. THE IMPACTS OF BROKERAGE INSTITUTIONS IN THE MARKETING OF
HORTICULTURAL CROPS IN FOGERA DISTRICT
Simegnew Tamir, Kinde Getnet and Jema Haji
Nile Basin Development Challenge (NBDC) Science Workshop
Addis Ababa, Ethiopia, 9–10 July 2013

2. PRESENTATION OUTLINE
INTRODUCTION
RESEARCH METHDOLOGY
RESULTS AND DISCUSSION
CONCLUSION AND RECOMMANDATION

3. 1.INTRODUCTION
1.1. Background
• Ethiopia has highly-diversified agro-ecological conditions
suitable for production of horticultural crops
• Amhara Region is one of the potential area
• Fogera District is an emerging commercial agriculture
• To sustain this well structured market networks and
linkages are required (organization among farmers,
institutions and infrastructure)

4. Background Cont…
• The horticulture market is characterized by imperfect
information
• No cooperatives to coordinate perishable products
• Creates fertile ground for the existence of brokerage
institutions in Fogera District
• ARARI (PRA), brokerage activity in the area is one of the
priority research problem.
• However, the institutions are not studied in the area in terms
of their impact and economic role
• The study focused to fill such knowledge gaps

5. 1.2. Objectives of the Study
The general objective of the study was:
• To assess the economic roles played by the brokerage
institution and identify determinants of decisions on
whether to use brokers or not in the study area
The specific objectives of the study were:
• To identify the determinants of farmers decision whether to
use brokerage institutions or not as a means of market
linkage to wholesalers
• To measure the impact of brokerage institutions on farmers
market participation and income generation capacity

6. 2. RESEARCH METHDOLOGY
2.1. Description of the Study Area
• Fogera District, Amhara Region, South Gondar Zone
• 625 km from Addis Ababa and 55 km from Bahir Dar
• 27 rural and 3 urban PAs
2.2. Methods of Data Collection
• Both primary and secondary data were used
• Primary data: semi-structured questionnaire and check-list
• Trained enumerators were used for data collection
• Pre-testing and rapid market appraisal(RMA)

7. 2.3. Sampling and Data Analysis
Sampling
• 5 kebeles selected randomly
• 143 farmers selected randomly
from participant and non
participant
• Monitoring, 4 months
• Friends with brokers
• Peaceful Café and Pension
(agreement and payment)
• 55 brokers (snowball sampling)
• 52 wholesalers
• 20 rural assemblers and 45
retailers in the main market
Data Analysis
• Descriptive statistics
(Percentages, standard
deviation, t-test and chi
squared test)
• Econometric models
(Propensity score matching
model )

8. 3. RESULTS AND DISCUSSION
3.1. The Brokerage Institutions
Socioeconomic profile of brokers
Variables Category Percent (%)
Sex male 100
female 0
Religion Orthodox 100
others 0
Marital status single 16.4
Married 83.6
Education level Illiterate 3.6
Adults education 16.4
Literate 80
Main occupation Farmer 58.2
Youth 21.8
Trader 20

9. • Most of the brokers are youngsters (18-63)
• Strong brokerage activity in onion marketing
• Only 4.2% of the farmers use brokerage
institutions for marketing of tomato -2
brokers
• Brokers act as rural assemblers in tomato
marketing

10. 3.2. Characteristics and economic roles of
brokerage institutions
• Most of the brokers (98.2%) work the business
informally without having license
• The study characterized brokers in to two ways:
 Based on place:
Rural brokers
Peri-urban brokers (Gumara and Abewana Kokit)
Urban brokers (Woreta)
Based on occupation:
Farmer Brokers-58.2%
Youth Brokers (grade 10 and 12 complete and school
dropouts)-21.8%
Cereal traders (rice)-20%

11. The brokerage institutions main characteristics
and roles in the area include:
• Are better informed
• Are skilled socially to bargain and facilitate linkage
• Create economies of scale
• They stabilize market conditions
• They reduce transaction cost
• Sources of secure market for smallholders
• Provide credit for the wholesalers being as
collateral for the farmer (trust and credit based
transaction)

12. Brokerage institutions activity in Fogera District
Brokers act in different ways:
1. When the wholesaler comes to Fogera District:
A.When the wholesaler is regular customer or residence in
the District
• Contact the wholesaler with the farmer , 0.10 ETB/Kg as a
commission fee (10%)
B. When the wholesaler is not regular customer (20%):
• No contact between farmer and wholesalers.
• 0.10 ETB/Kg commission fee paid to the broker, there is a
price gap of 0.10 ETB to 1.00 ETB between farm gate
price and wholesale purchase price, (FERQ)

13. 2. Trust based transaction (70%):
• This case happens when the wholesaler did not
come to Fogera District
• Transaction will be made only by wholesaler
telephone order
• No contact between farmers and wholesalers
• in addition to 0.10 ETB commission fee, there is
FERQ (0.10 ETB - 1.00 ETB) depending on the
volume of transaction and customer relationships.

14. Brokers attraction mechanism of wholesalers
• Brokers attract wholesalers by two ways
 Weight cheating from farmers and
 Reducing (FERQ) the price gap between farm gate price
and wholesaler purchase price
• Weight cheating has two advantages for the broker
 obtaining regular wholesaler customers for the future
and
 having his own share from it
• Weight cheating ranges from 6% to 20%

15. 3.3. Market outlets or target markets of
brokerage institutions
 Brokerage institutions base almost all parts of Ethiopia as
market outlets (50%,15%,13%,10%,5%,3%,2%,2%)

16. 3.4. Brokerage Institutions and Smallholder
Market Linkages
• The result is based on 143 (76-participant and 67 non
participant) sample farm households
Descriptive Statistics
• Socioeconomic, demographic and social capital aspects
Variables Category Participant (76) Non participant (67) χ2
Percent (%) Percent (%)
Sex Female 13.16 4.48 2.88*
male 86.84 95.52
Cell phone No 81.58 64.18 31.56***
Yes 18.42 35.52

17. Variables Participant (76) Non participant (67) T-value
Mean Mean
Age 42.54 37.01 -2.86***
Education level 1.52 3.42 3.42***
Family size 3.36 3.26 -0.47
TLU 5.97 5.40 -1.11
Total land (ha) 1.43 1.69 1.43
Irrigable land (ha) 0.77 1.16 2.2**
Exper. in Hort. Pro. 9.18 8.79 -0.61
Distance from DAs 4.41 2.69 -2.92***
Distance from Woreta 14.64 10.49 -3.4***
Distance from asphalt 3.76 1.37 -6.16***
No. regular customers 0.85 2.12 3.29***
No. of trading contact 7.95 8.17 0.18

18. 3.5.Estimation of propensity scores (Logistic
Regression)
– Participation : dependant Variable
Variables Coefficients Z- value
Age 0.056** 2.03
Sex -0.157 -0.16
Marital status -0.308 -0.22
Education level -0.163* -1.90
Family size -0.052 -0.19
Livestock 0.109 1.11
Total land size 0.183 0.31
Irrigable land size -0.022 -0.04
Exp. Hort. production -0.021 -0.33
Distance from DAs 0.156* 1.81
Cell phone -1.710*** -3.09
Distance from Woreta 0.006 0.16
Distance from asphalt 0.631*** 3.67
No. of regular customer -0.331** -2.02
No. trading contacts -0.027 -0.65
constant -2.479 -1.01

19. Common support and matching
• 0.06 - 0.9 (p-score for participants)
• 0.003- 0.89 (p-score for non participants)
• P-score (0.060 - 0.89) are in the common support
region
• Best matching algorithm
 Balances all the observable covariates
 Ends with low pseudo-R2
and
Gives large number of observations in the common
support
• Kernel matching algorism with a band width of 0.25

20. 3.6. Impacts of the Brokerage Institutions
Average treatment effect (Impact)
Sensitivity Analysis
• using Rosenbaum bounding approach
• Shows the effects of unobserved factors
• Resistant up to 200%- pure effect of brokerage
institutions
Outcomes ATT T
Net income (Profit) 4393.62 2.53***
% marketed surplus 13.55 2.86***
Amount of production -5.08 -0.25
Land allocation -0.05 -0.24

21. 4. CONCLUSION AND RECOMMANDATIONS
Brokerage institutions
• Are source of secure market for smallholder
producers
• Play important role in trust and credit based
transaction by creating market linkage and
increasing profit of producers
• Create employment role for youth groups

22. • However, they have problems by providing false
market information and weight cheating
• Thus, this study recommends
formalization of the brokers by forming groups,
providing licenses and training
standardization of weighing balance
training of farmers and
providing market information for farmers