Full text of DOI:10.1111/0002-9092.00205

Demand, Supply and Willingness-to-Pay
for Extension Services in an
Emerging-Market Setting
Garth John Holloway and Simeon K. Ehui
Although it may be wholly inappropriate to highlands (Nicholson). Previous work with
generalize, the most important resource avail-
able to a subsistence household is the total
amount of time that its members have avail-
able to spend in productive enterprises. In
this context, services that minimize the time
that it takes to perform productive activi-
ties are valuable to the household. Conse-
quently the household is willing to relinquish
quantities of other resources in exchange for
quantities of the time-saving service. These
simple observations motivate a search for the
values that subsistence households place on
time-saving services. This search is especially
important when it is realized that extension
services promote productivity, enhance the
surplus-generating potential of the household
and can, as a consequence, promote immer-
sion into markets that are currently con-
strained by thinness and instability. In this
capacity, extension visitation has the poten-
tial to overcome one of the principal impedi-
ments to economic development, namely lack
of density of market participation. In this arti-
cle, we consider this issue in the context of a
rich data set on milk-market participation by
small-holder dairy producers in the Ethiopian
the data (Holloway et al.) suggests that
extension visitation is a potentially important
catalyst for market expansion. Consequently,
a number of important questions arise con-
cerning the actual impacts of extension on
participating and non-participating house-
holds; the amount that extension-requesting
households would be willing to pay for the
service if it was privatized; the corresponding
demand schedule for extension services; and
the requisite conditions for the existence of
a private market for the service. These ques-
tions are central to the development of mar-
kets, to the issues raised in this session and
are answered in this paper in the context of
our Ethiopian data.
Milk-Market Development in
the Ethiopian Highlands
Small-holder dairy production in the
Ethiopian highlands received an enormous
catalyst when, in 1997, at two sites close to
Addis Ababa, the inauguration of two milk
cooperatives provided incentive for farmer
participation in milk-marketing. Small-holder
dairy producers in the highlands face a num-
ber of barriers to marketing including poor
access to information, low levels of infras-
tructure and problems of transportation and
perishability, leading to low levels of par-
ticipation in markets otherwise constrained
by significant search costs. Along with the
introduction of the milk cooperatives (“milk
groups”) a production innovation with enor-
mous potential for improving productivity
among small-holders is the crossbreeding
of exotic dairy-producing breeds with grade
indigenous stock. Although susceptible to dis-
ease and requiring more labor intensive man-
agement practices than purely indigenous
This paper was presented at the ASSA winter meetings (New
Orleans, LA, January 2001). Papers in these sessions are not sub-
jected to the journal’s standard refereeing process.
Garth John Holloway is visiting scientist and and Simeon K.
Ehui is coordinator, Livestock Policy Analysis Program, Interna-
tional Livestock Research Institute.
The authors are grateful to Chris Barrett, Chris Delgado,
and Ariel Dinar for providing inspiration; Mohammed Ahmed,
Graeme Donovan, and Bill Thorpe for supportive conversations;
Abebe Misgina and Yigezu Atnafe for information about exten-
sion services in the Ethiopian Highlands; and Charles Nichol-
son, who conceived the collection of the data while a postdoc-
toral fellow at the International Livestock Research Institute
under a grant from the Rockefeller Foundation. The authors are
especially grateful to Adugna Mekonnen, Head, North Shewa
Zone Ministry of Agriculture; Fille Kedida, Head, Wouchale
Woreda Ministry of Agriculture; Getachew Kebede, Supervi-
sor, Wouchale Woreda; and Asgedech Eshete, Etenesh Seme,
and Derrese Woyessa, Development Agents, Wouchale Woreda
for information offered in an October 16 interview concerning
extension activities in Wouchale Woreda.
This article is dedicated to U.C. Davis Extension Specialist
Bees Butler.
Amer. J. Agr. Econ. 83(3) (August 2001): 764–768
Copyright 2001 American Agricultural Economics Association

Holloway and Ehui
Willingness-to-Pay for Extension
765
herds, crossbred dairy-producing herds pro- decreasing in extension visitation. Transac-
duce upwards of twice their indigenous coun- tions costs may involve the cost of acquir-
terparts (Kiwuwa et al.). To varying degrees ing transport equipment, of walking (time)
this productivity gain has stemmed increases or, possibly, learning a new production tech-
in marketable surpluses and brought with it nique in order that the selling unit conforms
the potential for market immersion by for- to some market standard. Given estimates
merly subsistence households. In addition, of the impact of extension visitation on
the inauguration of cooperative selling has the transactions costs function, the task of
lowered significantly the remaining barrier retrieving estimates of willingness-to-pay is
to trading and has freed the time absorbed simplified considerably. The quantity that we
by producing transportable products from seek is the amount of income that the house-
fluid milk (butter, cheese, yogurt) to other hold is willing to forgo in order to have one
productive enterprises in the household.
additional unit of the service rendered or, the
With these issues in mind, a comprehen- quantity ω that solves:
sive survey of some sixty-eight households
(3) V (pˆ + δꢁ m − ωꢁ q) = V (pˆꢁ mꢁ q)
was undertaken in 1997 (Nicholson) with the
view to assessing the significance of factors
that impede or promote market participation.
Each household was visited three times and
at each visit sales of milk to the milk group
in the preceding seven days were recorded.
Thus, some (68 × 3 × 7 =) 1428 observations
are available for analysis.
where V (·) denotes indirect utility, δ
≡
ꢃc(z) = ∂c(z)/∂zxꢃzx represents the change
in effective price afforded by the increase
in extension visitation and q denotes other
factors affecting producing and consuming
decisions. Taking a Taylor-series approxima-
tion at an arbitrary expansion point on both
sides of equation (3) an empirically observ-
able (approximation to) the willingness-to-
pay measure is
Transactions Costs Mitigation and
Willingness-To-Pay For
Extension Visitation
(4)
ω ≡ δVp/Vmꢂ
Despite potential complications, the deriva-
tion of household-production willingness-to-
pay estimates shares many similarities with its
derivation in the more traditional consumer
model. We focus most attention on the cash-
income constraint,
Econometric interests focus on the extent
to which the right-hand-side of this expres-
sion is observable and the location and scale
of its posterior distribution. The term in the
numerator is the product of the extension-
service change (which is observable) and the
marginal valuation of one additional unit of
extension (which, in general, is not observ-
able); the term in the denominator gives the
marginal valuation of one additional unit of
income (which, again and in general, is not
observable). However, from a simple applica-
tion of the envelope theorem, Vp ≡ λys and
Vm ≡ λ, where λ denotes the Lagrange mul-
tiplier corresponding to the cash-income con-
straint and ys denotes the amount of the food
product that is sold in equilibrium. Hence, the
right-hand-side of (4) is observable and pro-
vides the basis for the willingness-to-pay cal-
culations that follow.
(1)
z ≤ pˆys + wꢀw + m
where z denotes a (numeraire) purchased
good, pˆ denotes the household’s “effec-
tive price,” w denotes the wage in off-farm
employment, ꢀw denotes labor allocation to
off-farm employment and m denotes exoge-
nous income. Per-unit transactions costs are
conceptualized as the difference between the
per-unit price received in the market, p, and
a per-unit costs function c(z) so that
(2)
pˆ = p − c(z)
denotes the effective (net) return to the
household and z ≡ (z1ꢁ z2ꢁ ꢂ ꢂ ꢂ ꢁ zk)ꢀ denotes
a vector of potentially observable, household-
specific characteristics, one of which we
assume to be extension visitation. Implicit
Estimating Willingness-To-Pay From
Market Participation Data
in what follows, is the assumption that the In estimating the impact of extension on the
transactions costs function is monotonically transactions costs function we infer a direct

766
August 2001
Amer. J. Agr. Econ.
relationship between the household’s effec- Results
tive price and the effect of extension visi-
tation on this price. To this end, household
i’s decision about whether to participate can
be expressed in terms of (indirect) utility
differences
Table 1 reports results. The variables in ques-
tion are “Distance” ≡ return time in minutes
to walk to the milk group; “Education” ≡
years of formal schooling of the house-
hold head; “Crossbred” ≡ number of cross-
bred cows currently being milked; “Local” ≡
number of local-breed cows currently being
milked; “Extension” ≡ number of visits by
an extension agent discussing production or
marketing activities in the twelve months
prior to the survey; “Ilu-Kura” ≡ dummy
variable (= 1 if from the Ilu-Kura peasant
association); “Mirti” ≡ dummy variable (= 1
if from the Mirti peasant association). Num-
bers in parentheses are the ratios of poste-
rior means to their standard deviations in
the Gibbs sample. All of the covariates have
a significant impact on the price differences.
The price difference is decreasing in the dis-
tance that the household resides from the
milk group and is increasing in each of the
other covariates. Particular interest lies in
the impacts of the extension-visitation covari-
ate. The results suggest that for each unit
increase in extension visitation the effective
price increases (the transactions-costs func-
tion is lowered) by 0.62 Ethiopian birr (EB).
(Currently, $US 1.0 = EB 8.24). Hence, exten-
sion visitation shows promise as a market-
entry catalyst.
(5)
G(pˆiꢁ miꢁ qi) ≡ V p(pˆiꢁ miꢁ qi)
− V n(miꢁ qi)
where V p(·) denotes utility from partic-
ipation, V n(·) denotes utility from non-
participation, G(·) denotes the utility
difference and mi and qi are defined
previously. Given the monotonicity of
G(pˆiꢁ miꢁ qi) in pˆi we can reinterpret the
entry condition (G(·) positive or negative)
c
in terms of a critical price, say pˆ , such that
entry occurs whenever the effectiive price, pˆi,
exceeds the critical price and not conversely.
Given the dependence of G(pˆ ꢁ miꢁ qi) on
mi and qi, it is natural to groupi these terms
into a set of covariates, xi ≡ (miꢁ qi), and
consider the price rule as a transformation
of a standard-normal regression,
c
(6)
σi(pˆi − pˆi ) = σixiꢀ + σiui
where σi is an arbitrary, positive scalar; xi is
a k-vector of observations on the covariates;
ꢀ is a k-vector of unknown coefficients; and
ui ∼ N (0ꢁ 1) is a standard-normal random
variable. Normalizing on the scale parameter,
and assuming independence across house-
holds, we are able to derive estimates of the
quantities we seek from the regression,
Combining the probit regression results
with the willingness-to-pay calculation in
Table 1. Probit Regression Results
Distance
Education
Crossbred
Local
−0ꢂ06
(−9ꢂ27)
0ꢂ56
(9ꢂ94)
2ꢂ87
(14ꢂ78)
1ꢂ14
(7ꢂ22)
0ꢂ62
(10ꢂ66)
−6ꢂ67
(−13ꢂ82)
−11ꢂ31
(−18ꢂ53)
(7)
y = xꢀ + u
(y1ꢁ y2ꢁ ꢂ ꢂ ꢂ ꢁ yn)ꢀ denotes an
where y
≡
n-vector of latent (unobserved) values cor-
responding to the price differences; x
(x1ꢁ x2ꢁ ꢂ ꢂ ꢂ ꢁ xn)ꢀ, x1
(x11ꢁ x12ꢁ ꢂ ꢂ ꢂ ꢁ x1k),
x2 (x21ꢁ x22ꢁ ꢂ ꢂ ꢂ ꢁ x2k)ꢁ ꢂ ꢂ ꢂ ꢁ xn (xn1,
≡
≡
≡
≡
Extension
Ilu-Kura
Mirti
xn2ꢁ ꢂ ꢂ ꢂ ꢁ xnk) are observations on the covari-
ates; and u ∼ N (0nꢁ In). We observe the
participation choice but neither y nor ꢀ.
However, inferences about the locations
and scales of the elements of ꢀ are eas-
ily obtained using a Markov-chain, Monte-
Carlo algorithm (Albert and Chib). In short,
an alternative interpretation of the probit
regression leads to robust estimates of the
impact of extension on the household’s effec-
tive price and its willingness to pay for exten-
sion visitation.
Participants
Pos. Predict.
Neg. Predict.
168
74
94
Non-Participants
Pos. Predict.
Neg. Predict.
1260
24
1236

Holloway and Ehui
Willingness-to-Pay for Extension
767
equation (4), we can estimate the quantities is “normal demand” (November–December)
of interest in terms of the Ethiopian birr average visits amount to about 100 per week
that the households are willing to give up per agent. The extension department of the
for one additional extension visit. Figure 1 administrative unit in question has a total of
presents the estimates across the 168 partic- 29 Development Agents and in the produc-
ipating households. The point estimates are
virtually indistinguishable from their 95%
highest-posterior-density values (confidence
intervals) and the estimates appear credible
in terms of the operations under considera-
tion. Average sales in the sample are 3.9 l
milk per day and the prices received are EB
1.00 and EB 1.25 per liter, respectively, at the
Ilu-Kura and Mirti milk groups. The maxi-
mum (standard deviation) willingness-to-pay
estimate is 6.77 (0.50) EB and the minimum
(standard deviation) willingness-to-pay esti-
mate is 0.62 (0.05) EB. These estimates pro-
vide relatively precise information to which
supply considerations should be targeted.
Complicating supply estimates are prob-
lems arising in the allocation of fixed costs
(educating field representatives, housing a
base of personnel and equipment, updat-
ing and revising communication techniques)
and estimating the variable costs of visitation
(wages and variable expenditures incurred
in travel). However, rough estimates about
the per-unit costs can be made by divid-
ing the annual extension budget of the local
administrative unit by the number of vis-
its made to each household. During the
“peak season” for visitation (April–August)
extension agents typically visit with 180
farmers per week; during the “slack seasons”
(September–October and January–March)
average visits amount to 18 per week per
agent; and during the seasons in which there
tion year 1998–99 (Ethiopian calendar year
1991) incurred running costs amounting to
EB 294,748 (Wouchale Woreda Extension
Personnel). Dividing this amount by the total
number of visits, which is ((180 × 20) + (18 ×
20)+(100×8))×29 = 138ꢁ040 visits per year,
we arrive at a rough estimate of the marginal
cost of each visit—EB 2.14 per visit. Using
the willingness to pay estimates in figure 1,
it appears that some sixty-five “households”
(observations in the sample) would be will-
ing to purchase extension services. Hence, net
of fixed costs, and in the context of milk-
market development in the Ethiopian high-
lands, the privatization of extension services
is an intriguing possibility.
Conclusions
Extension visitation is a potent catalyst stim-
ulating entry into emerging milk-markets.
This article has analyzed willingness to pay
for extension visitation in the context of data
collected from two sites close to Addis Ababa
and has assessed the conditions necessary for
a private market to prevail. Although a pre-
cise response must hinge on the magnitude
of any fixed costs, variables costs cannot pre-
clude the possibility that privatization may be
currently possible. Future work should aim at
strengthening confidence in our estimates by
overcoming limitations of the analysis, includ-
ing the assumption of unit variance in the
pricing model, the assumption of indepen-
dence across time periods and the arbitrary
assignment of covariates to the transactions
costs function.
References
Albert, J., and S. Chib. “Bayesian Analysis of
Binary and Polychotomous Data.” J. Amer.
Stat. Assoc. 88(1993):669–79.
Holloway, G., C. Nicholson, C. Delgado, S. Ehui,
and S. Staal. “Agroindustrialization Through
Institutional Innovation: Transactions Costs,
Cooperatives and Milk-Market Development
in the East African Highlands.” Agric. Econ.
23(2000):279–88.
Figure 1. Willingness-to-pay estimates for a
one unit increase in extension visitation

768
August 2001
Amer. J. Agr. Econ.
Kiwuwa, G.H., J.C.M. Trail, M.Y. Kurtu, G. Worku,
F.M. Anderson, and J. Durkin. Cross-Breed
Dairy Cattle Productivity in Arsi Region,
Ethiopia. International Livestock Center for
Africa (ILCA) Research Report No. 11,
Addis Ababa: ILCA, 1983.
Shewa and Arsi Regions of Ethiopia: Project
Description, Survey Methodology, and Collec-
tion Procedures.” Mimeograph, Livestock Pol-
icy Analysis Project, International Livestock
Research Institute, Addis Ababa, 1997.
Wouchale Woreda Extension Personnel. Personal
communication, October 14, 2000.
Nicholson, C.F. “The Impact of Milk Groups in the