ANALYSIS OF PERFORMANCE AND EFFICIENCY OF PEARL MILLET
(Pennisetum glaucum (L.) R .Br. ) MARKET VALUE CHAIN: A CASE OF
MBEERE DISTRICT, KENYA
SILAS OKECH ONGUDI
SUPERVISORSDr. Ngigi, M.
Dr. Kimurto, P.
OUTLINE •Introduction •Statement of the problem •Objectives•Study area •Sample design and sampling procedure •Methodology •Results and discussion •Conclusion and policy recommendation
INTRODUCTION
• Millets 4th important cereal in cultivation and production in the tropics
•Coverage 15 and 12 m ha (Africa and Asia)
• Pearl Millet (Major): Merits;•Hot and dry conditions (200-600 mm p.a); •Requires 25% less rainfall•Diet >500 m households; •Feed source•Fuel and ethanol production
INTRODUCTION CONT’D
•Marketing challenges;
•Poorly developed and fragmented markets with
weak value chains,
•High assembly and processing costs,
•Uncompetitive grain prices,
•Lack of market information
• Limited processing facilities,
•Lags in legal and policy framework
INTRODUCTION CONT’D
•Trends show reduction in acreage and productivity/ha;
•Acreage reduced; 115,302.6 ha (2007) to 100,143.9 ha (2011)
•Yield/Ha decline1,610 kg in (1980) to 200-800 kg
(2008) - potential of 1,500-3,000 kg ha-1
INTRODUCTION CONT’D•Promotional efforts: •Non-traditional crops project - acceptability and consumption (GoK)
•EPHTFC project-income and food security (IFAD & GoK)
•HOPE project- productivity and marketing challenges (ICRISAT)
•INTSORMIL/B&M Gates - millets and sorghum production and marketing ESA
•ASARECA pearl millet productivity project
•However, •<3% pearl millet enters formal production channels•2 m tons pearl millet is fed to animals compared to 30 m tons of sorghum
STATEMENT OF THE PROBLEM
•Despite the efforts, weak supply networks and independent working relationship between actors are major concern. •Yet, improved market value chain, efficient collaboration, networking and coordination are important. •Past studies -efficient coordination has the potential of improving market demand, producers’ output value, stimulate adoption and production •Nevertheless, pearl millet marketing and value chain potential, coordination and collaboration is limited or non existence at all.
GENERAL OBJECTIVE
•To improve the competitiveness and productivity of pearl millet for the benefit of the farming communities in Arid and Semi-Arid Lands of Kenya
SPECIFIC OBJECTIVES
• To conduct value chain mapping of the pearl millet marketing system connecting production areas of Mbeere district and the final markets of Kenya
• To evaluate the marketing channel efficiency of pearl millet and the benefits accruing from farm gate to final consumers
• To identify major marketing constraints affecting pearl millet traders in Mbeere district of Kenya
• To determine consumers’ willingness to pay for value added pearl millet products within markets of Kenya
STUDY AREA: MBEERE DISTRICT, KENYA
•ASAL area
•Rainfall –(640 - 1110 mm; <750 mm p.a)
•Temperature; (20-300C ; >300C (March))
•Major crop failures (maize).
SAMPLING AND SAMPLE SIZE
•255 market actors (120 Farmers; 25Traders; 2 Brokers; 8 Processors; 100 Customers) interviewed
•Purposive sampling technique of Siakago and Evurore -Q-administration•Farmers: simple random sampling •Intermediaries(B/A) ; snowball sampling•Traders: simple random sampling •Processors: MoA records •Consumers: simple random sampling
DATA ANALYSIS
•Objective 1: Value chain mapping - descriptive statistics
•Objective 2: Market channel efficiency –marketing margin and efficiency calculation
•Objective 3: Marketing constraints – descriptive statistics
•Objective 4: Consumers WTP- Semi double bound contingent valuation
RESULTS AND DISCUSSION: SOCIO-ECONOMIC XTS
Percentage Distribution
Variables Farmers Traders Consumers
Mean age in years 52.4 (15.94) 41.56 (11.26) 45.42 (11.74)
Educational level Illiterate 12.5 - 5
Primary 58.9 44 52
Secondary - 56 31
Tertiary 26.6 - 9
University 1.67 - 3
Gender Male 62.5 - 61
Female 37.5 100 39
Respondents Employment
status Full time - 72 18
Part time - 24 21
Unemployed - - 55
Housekeeper - - 4
Retired - - 2
MEANS OF ACCESSING MARKET INFORMATION: PRODUCERS
Percentage of respondents
Daily prices
Buyer
information
Market
days
Mobile phones 39.17 5.83 32.5
Internet 0.83 2.5 0
Magazine 1.67 6.83 0
Radio 16.67 10.83 17.5
Via fellow farmers 1.67 5.83 9.17
Television 39.17 0 0
Limited access 1.83 74.17 40
Total 100 100 100
MAPPING OF THE PEARL MILLET VALUE CHAIN AND MARKETING CHANNELS
Producer
Final consumer
Rural agents
Traders
Small scale processorsBrokers
Large processors
Supermarket
Channel 1:- Producer- Rural agents- Traders- small processors- Consumers; Channel 2:- Producers-Traders- Brokers- Large processors- Final consumers; Channel 3:- Producers- Rural agents- Traders- Brokers- Large processors- Final consumers; Channel 4: producers- rural agent- traders- final consumers; Channel 5:- Producers- Final consumers
MARKETING EFFICIENCY OF DIFFERENT PEARL MILLET MARKETING CHANNELS
Prices/Costs Channel I Channel II Channel IIIChannel IV
Value added 6,080 11,600 15,200 4,060Cost of marketing
Traders 1,392.60 1,392.60 1,392.60 1,392.60
Brokers - 1,914 1,914 - Large
processors - 940 940 - Small
processors 415 - - -Total cost of marketing 1,807.60 4,246.60 4,246.60 1,392.60
Marketing Efficiency index 3.36 2.70 3.54 2.90Channel 1:- Producer- Rural agents- Traders- small processors- Consumers; Channel 2:- Producers-Traders- Brokers- Large processors- Final consumers; Channel 3:- Producers- Rural agents- Traders- Brokers- Large processors- Final consumers; Channel 4: producers- rural agent- traders- final consumers; Channel 5:- Producers- Final consumers
MARKET UPGRADING CONSTRAINTS: TRADERS
Insurance
Forward contracts
Warehouse receipts
Precautionary savings
0 10 20 30 40 50 60
20
44
20
12
56
24
20
24
8
32
28
20
4
32
44
12
Upgrading constraints
Most effective Effective Neither-norModerately effective Ineffective
Percentage respondents
Sp
ecif
ic c
onst
rain
ts
ESTIMATES OF MEAN WTP MODEL
Variable Coefficient
estimate
Standard
error
P- value
Constant (α) 9.235 1.662 0.000
Bid (ρ) 0.065 0.013 0.000
Mean WTP
(α/ρ)
142.077Number of observations = 100; Log likelihood = -63.862
• On average wtp Kshs.142 represented a premium price of 42% over the base price of Kshs 100 of finger millet product.
ESTIMATED LOGIT MODEL RESULT
WTP Coefficie
nt
Standard
error
Z P>|z| Marginal
Effects
HHhead -0.555
0.716 -0.78 0.438 -0.056
AgeofHH 0.080 0.029 2.76 0.006* 0.008
Gender 1.252 0.728 1.72 0.086*** 0.127
EducLevel -0.102 0.348 -0.29 0.769 -0.010
NoChildren 0.558 0.244 2.29 0.022** 0.057
Employmentstatus 0.238 0.277 0.86 0.390 0.024
Income 1.029 0.388 2.65 0.008* 0.105
Awareness 1.351 0.420 3.22 0.001* 0.138
HeardProduct 0.229 0.455 0.50 0.615 0.023
Constant -10.540
3.136 -3.36 0.001 -
CONCLUSION•Channel levels: three level (channel 1st, 2nd and 3rd); a two level (4th channel); one level (5thchannel) and a zero level (6th channel) •Most efficient channel: channel III (3.54) while the least channel II (2.70) •Higher transport costs (brokers and traders)- (police bribes, municipal cess and import taxes)•Major procurement constraints: lack of targeted insurance products (56%) and limited use of contract (44%)•Consumer WTP >42% price premium (income and HH composition and prior knowledge)
POLICY RECOMMENDATION
•Government to enact policies -linking producers’ to processors for chain efficiency and profitability
•Municipal cess, border taxes and police bribes be removed
•Targeted insurance products (crop insurance) be introduced
•Fast food marketers should be familiar with price premium and adjust their marketing strategies (consumer classes)
ACKNOWLEDGEMENT
•Egerton University
•AERC (CMAAE program)
•ASARECA pearl millet project (Field data collection)
•Supervisors (Dr. Ngigi and Dr. Kimurto)
•Lecturers
•Classmates and friends
PUBLICATIONS UNDER REVIEW
•Okech, S.O, Ngigi, M. and Kimurto, P.K. (2013). Value chain mapping on pearl millet in Kenya. ASARECA regional conference (Nakuru, February 2013)
•Okech, S.O, Ngigi, M. and Kimurto, P.K. (2013). Consumers’ Willingness to Pay for Value Added Pearl Millet Products within the Markets of Kenya: A One and One Half Bound Dichotomous Choice Contingent Valuation- (Asian Journal of Agricultural Sciences)
THANK YOU END