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