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- 1. DETERMINANTS OF CONSUMERS CHOICE AND POTENTIAL WILLINGNESS TO PAY HIGHER PRICES: A PEARL MILLET CASE STUDY IN KENYA OKECH, S.O., NGIGI, M. AND KIMURTO, P.K.
- 3. 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
- 4. INTRODUCTION CONTD 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 KENYA Yield/Ha decline1,610 kg in (1980) to 200-800 kg (2008) - potential of 1,500-3,000 kg ha-1
- 5. INTRODUCTION CONTD 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
- 6. GENERAL OBJECTIVE To contribute towards the competitiveness and enhancement of market access of pearl millet for the benefit of the farming communities in Arid and Semi- Arid Lands of Kenya Specific objective: To determine consumers willingness to pay for value added pearl millet products within markets - CVM
- 7. STUDY AREA: MBEERE DISTRICT A total area of 2,097KM2 ;Latitude 00 N and 00 N; Longitude 370 E and 370 E; Altitude - 500-1200m above sea level Unreliable rainfall (640 1,110mm) with most parts receiving less than 750mm annually Average temperature; 20-300C and sometimes -above 300C (March- hottest month)
- 8. Dependent variable Definition Expected sign WTP (Willingness to Pay) If respondent is WTP a price premium for pearl millet products 1-Yes; 0- Otherwise Independent variables Income (Income) What is monthly income level of a household head (Categorical) + Children (Nochildren) The number of children below 12 years in a household + Education (EducLevel) Highest educational level of the respondent (Categorical) - Gender (Gender) Gender of the decision maker (Dummy) +/- Employment (Employmentstatus) Is the household head employed (categorical) + Age (AgeofHH) Age of the decision maker (years) - Household head (HHhead) If the buyer is the head of a household (Dummy) + Awareness (Awareness) The household head level of awareness of pearl millet value added product (Categorical) +/_ Heard (HeardProduct) If a Household have heard of a pearl millet value added product + DATA ANALYSIS: NATURE AND A PRIORI EXPECTED SIGNS OF LOGIT MODEL
- 9. RESULT AND DISCUSSION Variables Consumers Mean age (years) 45.42 (11.74) Educational level (%) Illiterate 5 Primary 52 Secondary 31 Tertiary 9 University 3 Gender (%) Male 61 Female 39 Respondents Employment status (%) Full time 18 Part time 21 Unemployed 55
- 10. ESTIMATES OF MEAN WTP MODEL Variable Coefficient estimate Standard error P- value Constant (留) 9.235 1.662 0.000 Bid () 0.065 0.013 0.000 Mean WTP (留/) 142.077 Number of observations = 100; Log likelihood = -63.862; (Bhatta et al., 2010 40-60% tomatoes; Loureiro and Umberger, 2003 (38-58% certified steak and Hamburger) On average wtp Kshs.142 represented a premium price of 42% over the base price of Kshs 100 of finger millet product.
- 11. ESTIMATED LOGIT MODEL RESULT WTP Coeff Std 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 Employment 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
- 12. CONCLUSION Consumer WTP >42% price premium (income and HH composition and prior knowledge)
- 13. POLICY RECOMMENDATION Fast food marketers should be made aware of price premium to enable them adjust their marketing strategies (consumer classes)
- 14. THANK YOU END