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Does use of draft animal power increase
economic efficiency of smallholder
farms in Kenya?
P.M. Guthiga
1,
*, J.T. Karugia
2
, and R.A. Nyikal
2
1
Center for Development Research (ZEF), University of Bonn, Walter-Flex Str. 3, 53113 Bonn, Germany.
2
Department of Agricultural Economics, University of Nairobi, PO Box 29053 Nairobi, Kenya.
*Corresponding author: pguthiga@uni-bonn.de
Accepted 5 March 2007 Research Paper
Abstract
Draft animal power (DAP) has been identified as an environmentally friendly technology that is based on renewable energy
and encompasses integration of livestock and crop production systems. Draft animal technology provides farmers with
a possibility to cheaply access and use manure from the draft animals and farm power needed to apply renewable practices
for land intensification. Compared to motorized mechanization, DAP is viewed as an appropriate and affordable technology
especially for small-scale farmers in developing countries who cannot afford the expensive fuel-powered tractor
mechanization. However, it is apparent that there is no consensus among researchers on how it affects crop yields, profit and
production efficiency when applied in farm operations. This study addressed the question of whether using DAP increases
economic efficiency of smallholder maize producers in central Kenya. Results of the study are derived from a sample of
80 farmers, 57% of whom used draft animals while 43% used hand hoes in carrying farm operations. In the study area, draft
animals are almost exclusively used for land preparation and planting, with very few farmers applying them in the
consecutive operations such as weeding. A profit function was estimated to test the hypothesis of equal economic efficiency
between ‘DAP’ and ‘hoe’ farms. The results showed that farmers who used DAP obtained higher yields and operated at a
higher economic efficiency compared to those who used hand hoes. The analysis underscores the viability of DAP in
increasing profitability of small-scale farms; however, other aspects of the technology, such as affordability of the whole
DAP package, availability of appropriate implements and skills of using the technology, must be taken into account when
promoting adoption of DAP technology.
Key words: draft animal power, mechanization, smallholder farmers, profit function, economic efficiency
Introduction
Background information
Use of draft animals is an ancient practice that has persisted to
the present times and its importance in developing countries
as a source of power for carrying out farm operations is likely
to continue in the foreseeable future. Draft animal power
(hereafter referred to as DAP) has been identified as an
environmentally friendly technology that is based on renew-
able energy and encompasses integration of livestock and
crop production systems. Research work has linked the
benefits of using DAP to several aspects such as: enhanced
timeliness of carrying out farming operations, increased yield
through improved seedbed preparation, deeper plowing,
possibility of labor savings, reduced drudgery and possibility
of income generation through off-farm transport and hiring
1
.
Compared to the other parts of the world, sub-Saharan
Africa (excluding Ethiopia) has had a shorter history of
using draft animals
1
. In much of Africa, crop farming
and cattle herding tended to be separate activities carried
out by different tribal groups. In Kenya the use of oxen
for cultivation was introduced in the 1920s by European
settlers from South Africa
2
. The main draft animals used
in Kenya include oxen, donkeys and, to a limited extent,
camels. The use of draft animals for carrying out farm
operations has been spreading rapidly in some areas and
slowly in others in Africa
1
. The extent to which animal
traction is used in Kenya is relatively low. It is estimated
that only about 12% of smallholder farms (smallholder
farms are here defined as farms whose total size is less than
10 ha) are using it, compared to 3% who were using tractors
while over 80% were using hand tools
3
. This observation is
Renewable Agriculture and Food Systems: 22(4); 290–296 doi:10.1017/S174217050700186X
#2007 Cambridge University Press
also mirrored in other parts of Africa where DAP is
adopted; for example in Uganda the contribution of animal
power is estimated at approximately 8–9%
4
while in West
African semi-arid tropics DAP is employed on less than
15% of total area sown
5
. Since its introduction in Kenya,
little attention was given to introducing DAP to smallholder
farmers
6
. On the contrary, the government tried to promote
tractor mechanization which could have led to degrading of
animal traction to a somewhat ‘backward technology’.
Further, the acquisition and maintenance of the animal trac-
tion package may require credit, veterinary and extension
services and after sale services of the implements, which
may not be readily available to the farmers. Other con-
straints to the use of animal traction that have been cited
include lack of know-how by the farmers, limited avail-
ability of appropriate implements such as plow and weeders,
potentially high cost of keeping and foddering draft animals
and maintenance and repair of the implements.
In the first two decades after independence, the govern-
ment promoted motorized mechanization through state-
sponsored tractor hire schemes and tractor credit schemes.
The thrust of these initiatives was to enable smallholder
farmers to access tractors either through hire or purchase
respectively. However, these efforts had limited success
and proved unsustainable
1,7
. The government-managed
tractor schemes were bureaucratic and were bogged down
by tractor breakdowns that took too long repair. More
importantly, in the small farms, use of tractors has proved
not to be economically viable because most small-scale
farmers cannot afford the initial cost of purchase, main-
tenance and operation (fuel) cost due to financial con-
straints. Furthermore, the farm sizes are small, scattered
and have irregular shapes which make tractor operations
difficult and in turn increase the operation costs. Sub-
sistence nature of most small-scale farming is also unlikely
to economically justify use of expensive tractors. Due to
the limited success of the government-sponsored tractor
hire services and tractor credit schemes, the use of animal
traction for small farm mechanization has received some-
what more attention in the past two decades; for example,
some government economic planning documents have
highlighted the government’s concern for the need for
more research on the use of DAP
8
. However, there have not
been significant practical efforts by the government to
promote the adoption and widespread use of DAP, but
stakeholders in the private sector have formed a national
network for the promotion of animal draft technology
known as KENDAT (Kenya Network for Draft Animal
Technology).
Kenya’s smallholder agriculture sector is very significant
both in terms of volume and value of domestic production.
According to the national development plan (2002–2008),
the share of small-scale production was projected to av-
erage 54% of total agricultural production by the year
2008
9
. It is estimated that there are 3 million smallholder
farms in Kenya with an average land size of 2 ha
10
. The
dominance of the small farms is bound to continue as
sub-division of larger farms continues due to prevailing
land inheritance patterns. Therefore, given its relative
importance, any strategy for stimulating agricultural growth
in Kenya must inevitably target the smallholder sub-sector.
Smallholder farmers generally use manual labor combined
with low level technologies to carry out their agricultural
production. In the past two decades a decline in agricultural
productivity was shown among the smallholder farmers in
Kenya
11
. Draft animal technology offers a viable potential
to increase agricultural productivity using environmentally
friendly and locally available resources.
Yield, profitability and efficiency effects
of using DAP
The technical aspects of using animal draft technology are
well documented but the user aspects of the technology
have received less attention
12,13
. In Kenya, for example,
several appropriate animal-drawn implements and acces-
sories such as plows, cultivators, a variety of animal-drawn
carts and harnesses have been developed and released
to farmers but studies on profitability aspects of DAP are
not commonplace. The overall low level of use of animal
traction in sub-Saharan Africa has led to doubts being
raised about its profitability and sustainable use. Actually
there is no consensus among researchers on how the ap-
plication of animal traction affects productivity or profit-
ability
7
. This arises partly from the methodologies used in
the studies, and partly due to the differences between the
various study areas with regard to technical and socio-
economic factors. The effects of mechanization on yields
can be viewed as direct effects (higher yields, everything
else being constant) and indirect effects, i.e., increased
timeliness of carrying out farm operations, application of
manure from draft animals. Direct effects of mechanization
have not shown consistent results. The indirect effects of
mechanization are less disputed, for instance timeliness of
carrying out farm operations. Mechanization is seen as
facilitating a more effective use of high yielding inputs.
Some research findings suggest that DAP is only pro-
fitable when socio-economic conditions permit a high level
of utilization of animals and equipment
14,15
. Some studies
have shown that use of DAP increased acreage without
having significant impact on yields
16
, while others indicate
that DAP increased economic profitability of crop enter-
prises by smallholder farmers
7,17–19
. Therefore, there is
need to carry out a case-by-case study to ascertain how use
of DAP affects farm profitability. In many areas where
DAP is used in Kenya, it is applied predominantly for
primary tillage, with little or no application in subsequent
operations. When it is applied for primary tillage, DAP has
the potential of achieving expansion of cultivated area
compared to the use of hand tools. Increased acreage implies
that more labor would be needed in subsequent operations
such as planting, weeding and harvesting. Although, in
the context of small and declining farm sizes in Kenya the
potential for significantly increasing acreage is limited, the
Does use of draft animal power increase economic efficiency in Kenya? 291
profitability of DAP in a setting of declining land sizes
would still warrant investigation. As noted by Stevens
20
,
animal traction is rarely applied for weeding in Africa, even
where plowing has been practiced for generations, mainly
due to lack of affordable and readily available weeding im-
plements and inadequate training of both the draft animals
as well as the users. Weeding is recognized as a critical fac-
tor in determining crop yields; uncontrolled weed growth
could reduce crop yields by up to 60%
21
. Weeding
operation is cost intensive especially in terms of labor
requirements. In many cases, farm labor available for
weeding determines the final area that can be harvested.
Given the potential of DAP in increasing farm profitability,
this study attempts to shed light by comparing two groups
of farmers: those using DAP and those using hoes for
growing maize in central Kenya.
Materials and Methods
Study area
The study was conducted in Kirinyaga district, which is
one of the six districts of the Central Province in Kenya.
The district occupies an area of 1478 km
2
with 457,105
inhabitants distributed in four divisions within the district
(Ndia, Gichugu, Mwea and Kerugoya Kutus). The district
has a tropical type of climate with two rainfall seasons,
i.e., the long rains (March to May) and the short rains
(October to December). Usually planting of food crops
is done during these two rainfall seasons because there is
adequate rainfall that makes the district self-reliant in
production of various types of food crops. The general
landscape of the district rises from an elevation of 1480 m
above sea level (ASL) in the south to over 6800 m ASL at
the Mount Kenya peak. Farmers in the upper regions of the
district put large portions of their farms under cash crops
such as coffee and tea and also keep dairy animals for milk
production. Farmers in the lower region do not produce
tea or coffee due to unfavorable climate. Maize–bean inter-
crop is common in both the upper and lower regions. Maize
is the main food crop in the larger part of the district and
a household without maize grain is considered food
insecure
22
. The district has a relatively high intensity of
use of DAP especially for tillage operations. However, the
use of DAP in Kirinyaga district closely follows a regional
pattern. Most farmers who use DAP to carry out farm
operations are concentrated in the lower parts of the district
because it is relatively flat, hence more appropriate for using
draft animals, and land sizes are also larger than in the upper
areas. The traditional zebu oxen are predominantly used
for tillage operations. A pair, or in some few cases two
pairs, of oxen are used to pull a moldboard plow. DAP is
predominantly applied in land preparation with limited
application in weeding operations. There are, however,
many farmers in Kirinyaga district who do not apply DAP
to carry out agricultural operations, with many using hand
tools and very few using tractors. Hiring out traction
animals is a common practice in the study area, hence
farmers who do not own oxen can access DAP through
hiring.
Data sources
Farm level data for this study were collected using
structured questionnaires covering the long rains period of
2001. Information gathered included household character-
istics: acreage under maize, amounts of labor used in
production, cost of hired labor, amounts of fertilizers used
in maize production and their prices, family and hired labor
input into maize production and inter-gender labor time
allocation for farm work, home work and market work.
A combination of multi-stage random and purposive sam-
pling procedures was applied to obtain a sample of 80
farmers that were interviewed in this study. First, three
divisions out of the four divisions were randomly selected,
namely: Gichugu, Mwea and Ndia. In the next stage,
two locations were randomly selected in each division.
The selected locations were Baragwi and Karumandi in
Gichugu division, Mutithi and Murinduko in Mwea
division and Mutira and Inoi locations in Ndia division.
At the location level, purposive sampling was applied to
obtain a sample containing both ‘traction’ and ‘hoe’ groups.
A total of 80 farmers were sampled for interview with 43%
in the ‘hoe’ group and 57% in the ‘DAP’ group.
The concept of economic efficiency and its
measurement
Efficiency is an elusive concept, defined and therefore
measured differently by different disciplines. The econ-
omist, the engineer and the policy-maker, for example, all
define efficiency differently. Policy implications arising
from economic efficiency are important to both micro- and
macro-level decision-making. Efficiency, as defined by
Farrel
23
in his pioneering work on the subject, is the ability
to produce a given level of output at the lowest cost. Two
concepts of efficiency, technical and price or allocative
efficiency, are clearly distinguished by Farrel
23
. A producer
is said to be technically efficient if there is no possibility of
producing the same amount of output with fewer inputs
or producing more output with the same amount of inputs.
Price efficiency (or allocative efficiency), on the other hand,
refers to the proper choice of input combinations given the
prevailing market prices. Economic efficiency combines
both. It is possible for a firm to be either technically or
allocatively efficient but be economically inefficient
24
.
Technical and allocative efficiencies are necessary con-
ditions, and when they occur together they are sufficient
for achieving economic efficiency
25
.
Many researchers have used the production function
(a mathematical expression that attempts to capture the
relationship between inputs combination and resulting
output) as a tool to study economic efficiency. Some
researchers have used the production function to separately
estimate technical efficiency and allocative efficiency. The
292 P.M. Guthiga et al.
production function approach assumes that all firms have
identical ratios of inputs and outputs, hence only one point
on the production plane would be observable. However, as
noted by Ali and Flinn
26
, a production function approach
may not be appropriate when estimating the economic
efficiency of individual firms because they face different
prices and have different factor endowments. Due to these
differences the firms will have different best practice
production functions and, thus, different optimal operating
points. Production function methods to test for allocative
and economic efficiency have been criticized as suffering
simultaneity bias because input levels are endogenously
determined
26
. Problems of endogeneity can be avoided by
estimating profit or cost function instead of production
functions
27
.
A firm’s profit is a function of prices of inputs, price
of output and the level of fixed inputs, which are all
exogenous from the firms’ point of view. A study by
Yotopoulos and Lau
28
applied a profit function to compare
efficiency of small and large farms in India. They further
suggested that the same reasoning could be applied to
compare different groupings such as owners versus share
tenants or adopters of a new technology versus non-
adopters. As noted by Khan and Maki
29
differences in
economic efficiency among groups of farms (say users of a
given technology and non-users) may result from variations
in technical efficiency (larger output with equal amounts of
inputs) and price efficiency (higher profits). Profit max-
imization is implied if the value of marginal product of
each variable input is equal to its price. Thus we test the
relative economic efficiency of the two groups of firms by
comparing their actual profit functions.
Apart from differences in farm power sources, farms also
differ in fundamental aspects of production such as dif-
ferences in input application levels. This causes a difficulty
in interpreting results. All other factors are not held con-
stant. To overcome this problem two approaches could be
applied: covariance analysis or before and after mechani-
zation yields comparison. The latter method is inappropri-
ate most of the time due to lack of data for comparison.
Covariance analysis is a way of testing whether there are
significant differences in the behavioral relationships
between sets of observations. ‘Covariance’ analysis was
carried out to isolate the direct effects of using animal
traction, i.e. to test whether there are significant differences
in the behavioral relationships between ‘hoe’ group and
‘DAP’ group. The results of the analysis showed that the
two groups are statistically different from each other in the
way the included independent variables explain variation in
the profits from maize production.
The profit function model
In this study a restricted Cobb–Douglas Unit-Output-Price
(UOP) profit frontier was applied in testing the relative
economic efficiency of the effect of using DAP on
economic efficiency of the sample farms in the study area
because it was found to have the best fit of data despite
there being other more flexible functions such as translog
and quadratic functions. Profit functions (like their under-
lying production functions) can either be deterministic or
stochastic in nature
30
. Stochastic functions, unlike determi-
nistic functions, incorporate producer-specific random
shocks besides the common shock that is allowed for all
the producers in deterministic functions. The stochastic
profit function is defined as:
pi=f(Pij,Zik ,Dik )exp(m),
where p
i
is normalized profit of the ith farm defined as the
gross revenue less variable cost divided by farm-specific
output price; P
ij
is the price of the jth variable input faced
by the ith farm divided by output price; Z
ik
is the level of
the kth fixed factor on the ith farm; D
ik
is the dummy for
farm mechanization (D=0 if hoe was used and D=1if
DAP was used); mis an error term; and i=1, ...,n, is the
number of farms in the sample.
m=vi-ui,
where v
i
’s are assumed to be independently and identically
distributed two-sided random errors, independent of the
u
i
’s which are non-negative errors representing profit in-
efficiency.
The empirical model
The general form of the UOP profit frontier, dropping the
ith subscript for the farm, is defined as:
P=b
0+b
1ANTRAC +b
2WAGE +b
3FERTZ
+b
4MACR +b
5MSEED +v-u,
where Pis normalized profit in Kenya Shillings (in the year
2001, one US dollar ($) was approximately equal to Ksh
75) defined as total revenue less total variable costs
normalized by the price of maize. ANTRAC is a dummy
variable with value 1 for ‘traction’ farms and 0 for ‘hoe’
farms. WAGE is wage rate in Ksh per person day
normalized by the price of maize and FERTZ is the price
of fertilizers in Ksh normalized by the price of maize.
MACR is the acreage under maize in hectares and MSEED
is the price of seeds in Ksh normalized by the price of
maize. While vis the error term assumed to be inde-
pendently and identically distributed two-sided random
errors, independent of the uwhich is non-negative error
representing profit inefficiency, b
i
’s are the regression
coefficients.
Relative efficiency involves comparing efficiencies of
two or more firms. As noted by Knox et al.
31
, if two classes
of firms have different degrees of technical and price
efficiency and face similar prices in input and output
markets, the firm class with higher profits is considered to
be more economically efficient. The approach is that, given
comparable endowments, identical technology, and normal-
ized input prices, the UOP profit of two firms should be
Does use of draft animal power increase economic efficiency in Kenya? 293
identical if they both maximized profits. If one firm is more
price efficient, or more technically efficient, than the other,
the UOP profits will differ even for the same normalized
input prices and endowments of fixed inputs.
Results and Discussion
There was a significant difference on the land sizes, amount
of hired labor, acreage under maize and value of fertilizers
applied between ‘DAP’ and ‘hoe’ groups (Table 1). But
there was no significant difference on age of the household
head, years of formal schooling, years of farming ex-
perience and the family sizes between the two. Farmers
who used DAP obtained significantly higher profits than
those that used the hoe, as shown in Table 1.
The land sizes in the area of study are generally small
regardless of whether one is in the ‘DAP’ or the ‘hoe’
group. Therefore, there is need to intensify land use through
land augmenting technologies such as using fertilizers, high
yielding crop varieties, nitrogen fixing legumes, cover
crops, conservation tillage and such others. Use of draft
animals could enhance land use intensification through
cheap production and easy transporting of manure on the
farm. Draft animals can also provide power for a wide
range of labor intensive land management and erosion
control systems, such as establishment of ridges along the
contours in hilly areas. As noted by Noodwijk et al.
32
many
renewable practices such as use of compost and green
manures, use of cover crops, pruning of foliage from alley
legumes and bushes are labor intensive, but DAP could help
relieve scarce labor in the farms to perform these practices.
The mean acreage under maize was 1.78 ha for the whole
sample. This means that farmers in the study area on
average put about 74% of their land holdings under maize,
indicating the relative importance of maize crop in the
study area. The average maize yield for the whole sample
was 1074.20 kg ha
-1
. There was a significant difference in
the maize yield between the two groups of farmers. ‘DAP’
group on average obtained 1216 kg of maize ha
-1
while the
‘hoe’ group obtained 883.08 kg of maize ha
-1
. For the
‘hoe’ group yield varied between 441 and 1323 kg ha
-1
while for ‘DAP’ group the maize yield varied between
2190.3 and 1852.2 kg ha
-1
. The above results seem to
concur with the proposition that DAP facilitates timeliness
in land preparation and planting, as well as ensuring deeper
plowing at the onset of rains which later translates to higher
crop yields, all else being constant. The average value
of fertilizers used in the sample farms was Ksh 811.92.
The value ranged from Ksh 0.00 to Ksh 6250 with a median
of Ksh 655. The ‘hoe’ group applied more fertilizers for
maize production than the ‘DAP’ group on average. The
mean value of fertilizers was Ksh 2061.38 and Ksh 1103.02
for the ‘hoe’ and the ‘DAP’ group respectively. ‘DAP’
group on average used less fertilizer than ‘hoe’ group but
they still obtained higher yields on average. There is no
straightforward explanation for this observation but there
is a possibility that the yield increasing effect of using
DAP overshadowed those of using fertilizers. Farmers in
the ‘DAP’ group had a ready source of manure from the
draft animals that they applied in their farms. Furthermore,
crop rotation was more possible among ‘DAP’ farmers
because some areas of the farm were set apart as non-
cropped fallow for grazing the animals.
Regression analyses of the profit function are summari-
zed in Table 2.
The signs of coefficients and their significance are
consistent with the expectations of the profit function apart
from the land size. As expected, the prices of variable
inputs (wage rate, seeds and fertilizers) had a negative co-
efficient in the profit function. It is expected that the higher
the price of variable inputs of production the less the profit
that a farmer can attain. All the prices of variable inputs are
significant in the model. This result to a large extent
concurs with those of several others
24,26,28,29
. The coeffi-
cient of land is negative and significant, which implies that
farmers with larger pieces of land were less efficient
than those with smaller pieces of land. This observation
could be attributed to the fact that farmers with smaller
farm tend to intensify their production thereby making
better use of inputs than those with larger farmers. The
coefficient of mechanization was found to be positive and
significant. This result indicates that use of animal traction
Table 1. Descriptive statistics for the sample farmers.
Variable
‘Hoe’
group
‘DAP’
group
Land size (ha)*** 1.06 2.81
Hired labor (person days)*** 5.84 10.97
Acreage under maize (ha)*** 0.96 2.40
Maize yield (kg/ha)*** 883.03 1216
Value of fertilizer applied (in Ksh†)*** 2061.38 1103.02
Age of household head 50.38 51.33
Farming experience (years) 26.03 29.81
***Significant at 1% level.
†Ksh =Kenya Shillings where 1 US $ =Ksh 75.
Table 2. Maximum likelihood estimates (MLE) of stochastic
profit function regression.
Variable Coefficient
Standard
error t-value
Constant*** 804.86 108.57 7.41
ANTRAC (dummy)*** 229.24 63.09 3.63
WAGE*** -1.28 0.29 -4.39
FERTZ*** -1.06 0.14 -7.75
MACR*** -10.16 24.28 3.17
MSEED -0.09 0.08 -1.17
Log likelihood function -487.51
s
u
2
+s
v
2
211.19 66.59 3.172***
***Significant at 1% level.
s
u
2
,s
v
2
, variance of the error term components uand v.
294 P.M. Guthiga et al.
had a significant effect on increasing maize enterprise
profits. Testing whether the coefficient of a dummy variable
that differentiates the two groups of farms, is significantly
different from zero we can test the hypothesis of relative
economic efficiency. The results indicated that the co-
efficient of the dummy variable was significantly different
from zero.
Conclusions
The present study examined profitability aspects of using
animal traction as a strategy for small farm mechanization
in Kirinyaga district in Kenya. The results indicated
that use of animal traction (both owned and hired) all else
being equal, increased both the yield and profits in maize
production. This observation seems to concur with the
proponents of use of DAP who say that if applied in farm
operations animal traction can facilitate a more efficient use
of other production inputs. DAP has a potential to enhance
farmer’s ability to adopt and use renewable practices
such as use of animal manure, crop rotation, ridging and
other renewable practices. Therefore, government and
other stakeholders should promote use of animal traction
as a way of increasing farm efficiency. For effective pro-
motion of DAP as a source of farm power and its uptake by
farmers various constraints that farmers face in adoption
of animal traction, such as lack of capital and know-how,
should be addressed. This is particularly important given
the current status of low levels of adoption of a seemingly
profitable technology.
Acknowledgements. The authors gratefully acknowledge the
International Food Policy Research Institute (IFPRI) who
provided the funds to carry out this research under the MSc.
Competitive grant of 2001. The support received from the
Principal and other staff members of Kamweti Farmers Train-
ing Centre, Kirinyaga, during the fieldwork is greatly appre-
ciated. The authors are fully responsible for the contents of the
paper.
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