PRESENTED BY:
OLILA Dennis Opiyo1
Nyikal Rose Adhiambo
Otieno David Jakinda
Presentation prepared for the African Economic Research Consortium
(AERC) Thesis Dissemination Workshop Egerton University, 24 – 25th
June 2014







Introduction
Economic Research Problem
Objectives
Hypotheses
Methodology
Results
Contribution to Knowledge

Maize is the most important staple food in Kenya.
•
Production accounts for 20% of the gross farm output from small
scale farming sector (Jayne et al., 2001).
•
Accounts for 40% of the daily calories with per capita
consumption of 98kg.
•
Over 85% of rural population derive livelihood from agric. Most of
whom grow maize.
•
However, production is mainly done under rain-fed agriculture
which is constrained by risk and uncertainty.
•
The result is a decline in staple food production & increase in
poverty level among farmers (De Groote, 2011).

Crop insurance as risk mitigation strategy is in a pilot stage in
Kenya, however;
o
There exists an empirical dearth in Knowledge on farmers’
preferences for the crop insurance programme.

o
i.
ii.
The purpose of this study was to evaluate farmers’
preferences for crop insurance in Kenya.
Specific objectives;
To analyze farmers’ Willingness to Pay for crop
insurance.
To assess factors influencing maize farmers’ WTP for
crop insurance.

o
The hypotheses postulated were:
Maize farmers’ in Trans-Nzoia county are not WTP any
statistical significant amount of money for crop insurance
components.
o
There known factors affecting farmers WTP for crop
insurance features

A multistage cluster random sampling was employed.

Primary data collected through a face-to-face interview in
the three districts of Trans-Nzoia county.

Survey instrument used was a semi-structured
questionnaire.


Sample size; 300 respondents.
Both Choice Experiment (CE) and Socio-demographic
characteristics data were collected.
Crop insurance components Component levels
Level of Coverage
50%, 65%, 70%
Compensation
50%, 60%, 70%
Content design
Joint, Provider only
Risk Cover
Single peril, Multiple peril
Nature of Coverage
Crop only, Crop and Market, Crop and
other social issues such as medical
Cost (Ksh/acre)
110, 170, 280
Insurance
scheme A
Insurance
scheme B
Level of coverage
70%
50%
Compensation
60%
50%
Content design
Provider only
Joint
Single peril
Multiple peril
Crop only
Crop and
medical
110
280
Risk cover
Nature of Coverage
Cost/acre (Ksh)
Which ONE would you
choose?
Neither Scheme A
nor B
(Status quo)

o
o
o

o
Objective 1: Quantification of WTP
A random parameter logit estimated (RPL).
Specification of the utility model by Revelt and Train
(1998) as:
Uint = βnXint + εint .
The Marginal WTP was estimated as specified by Hanemann
(1984).
WTP = -1*(βk/βp).
Variable
Small scale
farmer
Large scale
farmer
Pooled
Mean age (yrs)
42.71
48.94
44.98
Mean educ. (yrs)
10.36
11.39
10.73
Mean income
(Ksh/month)
16, 174.00
81, 860.00
40, 040.00
Access to credit
22.50
(last 12 months, %)
44.00
30.30
Awareness about
crop insurance (%)
31.90
43.10
36.00
Membership to
devpt. group (%)
46.10
53.20
48.70
Average farm size
(acres)
2.53
22.19
9.67
Attribute
Coefficient
Std. Error
P-value
LEVCOVME
1.757
0.619
0.0045
LEVCOVHI
3.249
3.401
0.925
1.119
0.0004
0.0024
CONTJOIN
4.726
1.159
1.266
0.456
0.0002
0.0110
MULTRSK
4.420
1.201
0.0002
CROPMKT
5.965
1.712
0.0005
CROPMED
9.068
2.629
0.0006
PRICE
- 0.021
0.006
0.0009
LL
- 664.556
Pseudo-R2
0.496
COMPENMED
COMPENHI
Attribute
WTP
Std. Error
P-value
LEVCOVME
86
29.49
0.0037
LEVCOVHI
158
21.01
0.0000
COMPENMED
166
33.04
0.0000
COMPENHI
230
25.64
0.0000
CONTJOIN
57
13.79
0.0000
MULTRSK
216
20.83
0.0000
CROPMKT
300
24.10
0.0000
CROPMED
442
39.69
0.0000
Farmer category
Kshs
Small Scale Farmers
16,792
[Compensation, provider
content design, multiple
risk cover & crop and
medical]
Large Scale Farmers
16,640
[Compensation, level of
coverage, joint content
design & single risk cover]
Std.
Error
P-value
1,836.11
0.0000
1,825.03
0.0000

High WTP for nature of coverage; policies that advocate
for both crop, mkt & medical aspects in the design.

Stakeholder engagement in the design; imply a bottom-up
policy formulation approach.
Implementation of programme; creation of an enabling
environment.
Acknowledgment
 The authors acknowledge the African Economic Research
Consortium (AERC) for funding the study.
