1. Estimating Consumer
Willingness to Pay
for Aflatoxin-free Food in Kenya
Hugo De Groote 1, Charles Bett 2, Simon Kimenju 3,
Clare Narrod 4, Marites Tionco4, Rosemarie Scott4
1 International Maize and Wheat Improvement Centre (CIMMYT)
2 Kenya Agricultural Research Institute (KARI),
3 University of Kiel, Giessen
5 International Food Policy Research Institute (IFPRI)
Nairobi Aflacontrol Project Meeting
Nairobi, November 30, 2011

2. The Problem
● Aflatoxins are a major health
problem in tropical countries
● New technologies for production,
storage and testing have been
developed,
● These are not cheap: quality costs
money
● How much are consumers willing to
pay for maize of superior quality?
● How do we estimate this WTP?

3. Estimating Consumer
WTP – Stated preferences
(Contingent valuation)
● ask the consumer directly: cheap, but hypothetical
 open question: often hard on respondents
 yes/no question: easier, but limited information
 usually: with one follow-up question
● But:
 hypothetical, no real money (not incentive-compatible)
 respondents reply to what we would like to hear
 overestimation of WTP

4. Consumer WTP –
Revealed preferences
(experimental auctions)
 Real money is exchanged
 Group auctions
 Individual auctions (BDM)
 Bid compared to random number
 incentive compatible: respondents
have no reason not to reveal their
real WTP

5. For aflatoxin: individual auction
● Product: maize grain, in 2 kg bags,
clear plastic
● Type of products
 Clean, untested
 Clean, tested (with no measurable trace
of aflatoxin)
 Moldy poor market quality =
“contaminated”: 5% of moldy, discolored
grain
● Participation fee: twice the estimated
value of the highest quality product
 KShs 110/person ($1.5)

6. Procedure individual auctions
● Participants are offered the
participation fee
● They are asked to bid on different
products
● They draw a number from a random
distribution, from 1 to 80 (40)
● If their bid is higher than the random
number, they purchase the product at
the random price

7. Consumer survey
● Stratified, 2-stage
● Six maize AEZ
● 120 sublocations
● 10 households/ subloc.
● 1 man or woman per
household (1344)

8. Kenya – Premium/discount
● Premium for clean maize over poor quality product:
KSHS 20-30 / 2 kg
● Premium for labeled maize: Kshs 10-15/2 kg

9. Analysis – random effects model
• We estimate the WTP for different product
characteristics through regression
• Dependent variable bij the bid of individual i for product j
• Independent variables: product characteristics, respondent
characteristics, cross effects
• Random effects model (bids of one individual are related)
Where
-i are the different products, j are the different respondents,
- xj is a vector or traits of the product j
- ki is a vector of characteristics of individual I
- C is a vector of cross effects
- i xj s a random error term for the individual
●

10. Kenya – long regression: effect of consumer
characteristics
Direct effects Cross effects x contaminated Cross effects x tested
Variable Coef. Std. Err. P>|z| Coef. Std. Err. P>|z| Coef. Std. Err. P>|z|
Constant 33.9 0.8 0.000
Poor market quality -19.5 3.1 0.000
Tested 11.1 2.8 0.000
Aware of aflatoxins -4.6 1.0 0.000
AEZ 2. Dry mid-altitudes -0.7 1.7 0.671 3.3 1.639 0.045
AEZ 3. Dry transitional 4.6 1.8 0.010 5.2 1.582 0.001
AEZ 4. Moist transitional 1.6 1.6 0.334 1.4 1.432 0.337
AEZ 5. High tropics -0.5 1.7 0.778 0.0 0.001 0.566
AEZ 6. Moist mid-altitudes -1.1 2.3 0.625 7.2 2.146 0.001
Age -0.1 0.1 0.315 -0.1 0.035 0.012
Awareness 1.3 1.4 0.359 0.7 1.358 0.631
Cattle 0.0 0.1 0.862 0.1 0.132 0.688
Experience 0.0 0.1 0.536 0.0 0.005 0.924
Female -0.7 1.0 0.512 -0.4 1.014 0.720
Income 0.0 0.0 0.857 0.0 0.001 0.001
Knowledge 0.4 1.4 0.790 -0.7 1.369 0.628
Land owned (ha) -0.3 0.2 0.142 0.0 0.188 0.964
Schooling -0.1 0.1 0.321 0.3 0.143 0.068

11. Conclusions
● Consumer WTP can conveniently measured with
individual auction
● Consumers are clearly willing to pay a premium
for
 visually clean maize
 maize tested and labeled aflatoxin-free
● WTP is influenced by age (-) and income (+)
● Needs to be clear differentiation in the market
and needs low cost labelling to have credibility
among consumers

12. Thank you