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Estimating the Willingness to Pay for Water Services in Developing Countries: A Case Study of the Use of Contingent Valuation Surveys in Southern Haiti

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Two basic theoretical approaches are available for making reliable estimates of households' willingness to pay: this paper investigates the approach termed the "contingent valuation method' because the interviewer poses questions within the context of a hypothetical market. The preliminary results strongly suggest that contingent valuation surveys are a feasible method for estimating individuals' willingness to pay for improved water services in rural Haiti. This has important policy implications for rural water supply projects because it seems to show that going into a village and conducting a relatively simple household survey can yield reliable information. Contingent valuation surveys may also prove to be a viable method of collecting information on individuals' willingness to pay for a wide range of public infrastructure projects and public services in developing countries. -from Authors
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Estimating the Willingness to Pay for Water Services in Developing Countries: A Case Study
of the Use of Contingent Valuation Surveys in Southern Haiti
Author(s): Dale Whittington, John Briscoe, Xinming Mu, William Barron
Reviewed work(s):
Source:
Economic Development and Cultural Change,
Vol. 38, No. 2 (Jan., 1990), pp. 293-311
Published by: The University of Chicago Press
Stable URL: http://www.jstor.org/stable/1154028 .
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Estimating the Willingness to Pay for Water
Services in Developing Countries:
A Case Study
of the Use of Contingent Valuation Surveys in
Southern Haiti*
Dale Whittington
University of North Carolina at Chapel Hill
John Briscoe
World Bank
Xinming Mu
Asian Development Bank, Manila, Philippines
William Barron
OXFAM, Cambodia
Progress in improving the quality and quantity of water used by people
in rural areas of the developing world has been unsatisfactory in two
respects: (1) supplies that have been built are frequently neither used
correctly nor properly maintained and (2) extension of improved ser-
vice to unserved populations has been slow. Though this poor record is
not the result of a single factor, a major impediment to improved
performance is inadequate information on the response of consumers
to new service options. The behavioral assumptions that typically
underlie most rural water supply planning efforts are simple. It is com-
monly assumed that so long as financial requirements do not exceed
5% of income, rural consumers will choose to abandon their existing
water supply in favor of the "improved" system. Several reviews by
the World Bank, bilateral donors, and water supply agencies in devel-
oping countries have shown, however, that this simple model of behav-
ioral response to improved water supplies has usually proved incor-
rect.1 In rural areas many of those "served" by new systems have
chosen to continue with their traditional water use practices.
? 1990 by The University of Chicago. All rights reserved.
0013-0079/90/3802-0008$01.00
294 Economic Development and Cultural Change
If rural water projects are to be both sustainable and replicable, an
improved planning methodology is required that includes a procedure
for eliciting information on the value placed on different levels of ser-
vice, and tariffs must be designed so that at least operation and mainte-
nance costs (and preferably capital costs) can be recovered. A key
concept in such an improved planning methodology is that of "willing-
ness to pay." If people are willing to pay for the full costs of a particu-
lar service, then it is a clear indication that the service is valued (and
therefore will most likely be used and maintained) and that it will be
possible to generate the funds required to sustain and even replicate
the project. Most attempts to incorporate willingness-to-pay considera-
tions into project design have, however, been ad hoc, in large part
because of the absence of validated, field-tested methodologies for
assessing willingness to pay for water in the context of rural com-
munities in developing countries.
Two basic theoretical approaches are available for making reliable
estimates of households' willingness to pay, but neither has been ade-
quately tested in the field. The first, "indirect" approach, uses data on
observed water use behavior (such as quantities used, travel times to
collection points, perceptions of water quality) to assess the response
of consumers to different characteristics of an improved water system.
Several modeling approaches are possible candidates here, among
them varying parameter demand, hedonic property value, and hedonic
travel cost models.2 The second, "direct" approach, is simply to ask
an individual how much he or she would be willing to pay for the
improved water service, for instance, a public standpost or yard tap.
This survey approach is termed the "contingent valuation method"
because the interviewer poses questions within the context of a hy-
pothetical market.
The focus of this article is on this second approach, the contingent
valuation method. Conventional wisdom has been that contingent valu-
ation surveys are unreliable because of "the pervasive feeling that
interrogated responses by individuals to hypothetical propositions
must be, at best, inferior to 'hard' market data, or, at worst, off-the-
cuff attitudinal indications which might be expected to reflect efforts by
individuals to manipulate the survey to their selfish ends."3 In the
specific case of rural water supplies, the World Bank concluded more
than a decade ago that "the questionnaire approach to estimating indi-
viduals' willingness to pay has been shown to be virtually useless."'
There was, however, little empirical evidence to support this conclu-
sion. Our research objective was to see if contingent valuation surveys
could, in fact, be used in developing countries to develop useful esti-
mates of willingness to pay for water services. A village in southern
Haiti was the field site of our study.
After describing the specific research area in Haiti, we summarize
D. Whittington, J. Briscoe, X. Mu, and W. Barron 295
its existing water supplies and the water use practices of the popula-
tion. We then describe our research design and field procedures. The
results of our analysis of the sample population's contingent valuation
bids lead to general conclusions and remarks on policy implications of
the research.
The Study Area
In August 1986 the research team conducted a contingent valuation
survey and source observations in Laurent, a village in southern Haiti.
One reason that southern Haiti was selected as the research area was
that the United States Agency for International Development was
funding a rural water supply project there. The project was designed to
provide services to about 160,000 individuals in 40 towns and villages.
The project was executed by CARE, which as the implementing
agency was responsible for site selection, construction, and commu-
nity organization. The CARE project's standard village water supply
project was a gravity-fed system supplied with water captured from a
mountain spring, feeding a few public standposts in a rural community.
CARE provided experienced enumerators for our household surveys,
logistic support, and valuable advice on a wide range of issues, from
questionnaire design and translation to data on local water use cus-
toms. The affiliation of our research effort with the ongoing CARE
project provided us with access to villages and justified our presence to
the local population.5
The village of Laurent is located about 15 kilometers from Les
Cayes, the provincial capital of southern Haiti. The population of Lau-
rent is about 1,500. The region is mountainous, with numerous streams
draining into the Caribbean Sea. The rainy seasons are October-
January and May-June; our study was conducted during the middle of
the July-September dry season.
The population of Laurent consists primarily of small farmers who
cultivate sorghum, beans, corn, rice, manioc, sweet potatoes, plan-
tains, yams, coconuts, mangos, and vetiver (a crop used in the produc-
tion of essential oils for perfume). Few people have regular wage em-
ployment, and remittances from relatives and friends living abroad or
in Port-au-Prince are common. Eighty percent of the population of
Haiti are illiterate; the illiteracy rate in our study area is probably even
higher. Malnourishment is widespread among children in Laurent. The
typical family lives in a three-room mud house with plastered walls and
a thatched or tin roof.
Water Sources and Water Use Patterns and Customs
Inhabitants of Laurent have access to several sources of fresh water.
There are seven sources within approximately 2 kilometers of most of
the population: one protected well and six springs in dry river beds.
296 Economic Development and Cultural Change
The springs provide only modest amounts of water, and individuals
often wait more than an hour to draw supplies. The average 3-
kilometer round trip to a water source can sometimes take several
hours.
The population of Laurent expresses strong preferences for clean
drinking water and sometimes will walk considerable distances past
alternative sources to collect drinking water from sources that are
considered pure. Water for drinking and cooking is usually collected by
women and children and carried home in relatively standard-size con-
tainers (about 20 liters for adults). Although children under 5 years old
are usually bathed at home in basins, adults and older children have a
strong preference for bathing in rivers. Clothes washing is usually done
in rivers. Some individuals actually pay for public transport to make
the roughly 10-kilometer round trip to the nearest river in order to do
laundry.
Research Design
Our research design was developed to test whether contingent valua-
tion surveys could be used to estimate water demand relationships
suggested by consumer demand theory, and thus used reliably to esti-
mate individuals' willingness to pay for improved water services. Eco-
nomic theory suggests that an individual's demand for a good is a
function of the price of the good, prices of substitute and complemen-
tary goods, the individual's income, and the individual's tastes, usu-
ally measured by the individual's socioeconomic characteristics. In
CARE's water supply project, the characteristics of the good-public
standposts or private connections-are the same for everyone. There
is no volumetric charge for water from public standposts; an individual
can use as much water as desired. Whether or not a household de-
mands water from the public water system thus depends on the price
charged for access to the new system or for participation in the project.
If the charge is higher than a given household's maximum willingness
to pay (WTP), the household will elect not to use the new water sys-
tem. Maximum willingness to pay will vary from household to house-
hold and should be a function of all of the variables in the demand
function except the price of the good itself. The households' WTP bids
should thus be positively related to income, the cost of obtaining water
from existing sources, and the education of household members, and
negatively correlated with the individual's perception of the quality of
water at the traditional source used before the construction of the
improved water supply system. We would hypothesize that the WTP
bids of women respondents would be higher than those of men because
women carry most of the water, but alternative interpretations are
certainly possible.6
D. Whittington, J. Briscoe, X. Mu, and W. Barron 297
Our research design attempted to test whether WTP bids are sys-
tematically related to the variables suggested by economic theory. If
the variation in bids cannot be explained by such variables, three logi-
cal explanations can be offered. First, economic theory may not be an
appropriate conceptual framework for explaining the behavior and
preferences involved. Second, economic theory may be correct, but
the contingent valuation method may not be a sound method for col-
lecting information to estimate the water demand relationships sug-
gested by such theory. Third, errors in execution of the research, such
as poor questionnaire design, could lead to invalid inferences about the
relationship between the WTP bids and the independent variables.
Because contingent valuation surveys have seldom been at-
tempted in developing countries, our research design was constructed
to test for the existence and magnitude of several types of threats to the
validity of the survey results. The major problem with the contingent
valuation method is that for a variety of reasons, respondents may not
answer willingness-to-pay questions accurately and thus not reveal
their "true" willingness to pay.7 The question format itself may affect
the bids.8 In our pretest of the questionnaire we tried different ways of
asking the willingness-to-pay questions. We tried both open-ended,
direct questions-for example, "What is the maximum you would be
willing to pay per month to have a public standpost near your
house?"-and two forms of bidding games in which we asked a series
of yes-no questions-for example, "Would you be willing to pay $X
per month for a public standpost near your house?" The Appendix pre-
sents an example of the sequence of questions used in one of these
bidding games.
We also attempted to test for the existence and magnitude of three
types of biases in contingent valuation surveys that have been of par-
ticular concern in the literature: strategic bias, starting point bias, and
hypothetical bias.
Strategic Bias
Strategic bias may arise when an individual thinks he may influence an
investment or policy decision by not answering the interviewer's ques-
tions truthfully. Such strategic behavior may influence an individual's
answers in either of two ways. Suppose the individual is asked how
much he would be willing to pay to have a public standpost near his
house. If he thinks the water agency or donor will provide the service if
the responses of individuals in the village are positive, but that some-
one else will ultimately pay for the service, he will have an incentive to
overstate his actual willingness to pay. On the other hand, if he be-
lieves the water agency has already made the decision to install public
standposts in the village, and the purpose of the survey is for the water
298 Economic Development and Cultural Change
agency to determine the amount people will pay for the service in order
to assess charges, the individual will have an incentive to understate
his true willingness to pay.
Most attempts to estimate strategic bias have been highly struc-
tured experiments in which one group of respondents is told one set of
factors about a situation that minimizes their incentive for strategic
behavior, and another group receives a different set that maximizes
their incentives for strategic behavior.9 In fact most of the available
evidence from the United States and Western Europe fails to support
the hypothesis that individuals will act strategically in answering con-
tingent valuation questions, but there is no evidence with respect to
developing countries.
Because we were conducting our surveys within the context of
CARE's ongoing rural water supply project, it was impossible to con-
struct a counterfactual situation (it would have entailed deceiving the
study population about CARE policies). We attempted instead to esti-
mate the magnitude of strategic bias in the following way. We divided
our study population into two groups. One group was read the follow-
ing statement that was intended to minimize strategic bias:
Opening
Statement
A: I am going to ask you some questions
in order to
know if you or someone from your household
would be willing
to pay
money
to ensure
that the CARE
Potable
Water
Project
will be successful
in Laurent.
We would like you to answer
these questions
at ease. There
are no wrong answers.
The water system is going to be managed
by a committee
of people
from Laurent.
This committee
will be chosen by the people of Laurent.
CARE has decided to help Laurent
by constructing
a water system in
this community.
Your answers cannot change the fact that CARE has
decided to build this water system. CARE never demands
money from
those people who collect water
from
public
fountains.
You will not have
to pay money at the public fountains.
We need you to tell the truth
in
order
for CARE to construct
the best water system for Laurent.
The second group was read another statement that was accurate
but left more questions about the purpose of the study unanswered:
Opening
Statement
B: I am going to ask you some questions
in order
to
know if you or someone from your household
would be willing
to pay
money so that the CARE Potable Water Project will be successful in
Laurent.
The water system is going to be managed
by a committee
of
people from Laurent.
This committee
will be chosen by the people of
Laurent. The committee will decide the amount each household will
have to pay to operate
and maintain
the water system.
Our hypothesis was that if individuals acted strategically, then bids
from those who received the second statement would be lower than
bids from those who received the first, because the former would fear
D. Whittington, J. Briscoe, X. Mu, and W. Barron 299
that a high bid would result in a higher charge by the community water
committee.'o
Starting-Point Bias
In the bidding-game question format, the interviewer starts the ques-
tioning at an initial price. A respondent who is unsure of an appropriate
answer and wants to please the interviewer may interpret this initial
price as a clue as to the "correct" bid. Starting-point bias exists if this
initial price affects the individual's final willingness to pay. To test for
starting-point bias we distributed three different versions of our ques-
tionnaire, each with different initial prices in the bidding game. The
questionnaires were randomly distributed in the sample population.
Hypothetical Bias
Hypothetical bias may arise from two kinds of reasons.11 First, the
respondent may not understand or correctly perceive the characteris-
tics of the good being described by the interviewer. This has been a
particular problem when the contingent valuation method has been
used to measure individuals' willingness to pay for changes in environ-
mental quality because it may be difficult for people to perceive what a
change, for example, in sulfur dioxide or dissolved oxygen means in
terms of air or water quality. This source of hypothetical bias is not
likely, however, to be significant for most public services in developing
countries. Many rural water systems have already been built in south-
ern Haiti; our respondents were all familiar with public water fountains
and private water connections and readily understood the possibility
that their community would receive a new water system. Moreover,
we showed each respondent two color photographs of public stand-
posts CARE had built in nearby villages. Household members usually
studied these with great interest.
Second, it is often alleged, particularly
in the context of devel-
oping countries, that individuals will not take contingent valuation
questions seriously and will simply respond by giving whatever answer
first comes to mind. Where this type of hypothetical bias is prevalent,
bids will presumably be randomly distributed and not systematically
related to household characteristics and other factors suggested by
economic theory. Our test for hypothetical bias was thus the same as
our test for the applicability of consumer demand theory: were bids
systematically related to the variables suggested by economic theory?
Field Procedures
Fieldwork in the village consisted of two parts: household surveys and
source observations. Eight CARE health education promoters and two
local college students were trained for 2 days to carry out the house-
hold interviews. Prior to field-testing the questionnaire, we held a
300 Economic Development and Cultural Change
"focus group" in which individuals from a nearby community dis-
cussed community water use practices and attitudes. Particular atten-
tion was paid in our focus group to household decision making on
water-related matters and to community expectations about operation
and maintenance costs. The focus group was not intended, however, to
substitute for a pretest of the questionnaire. The Creole questionnaire
was pretested extensively in a nearby village before the CARE
enumerators were trained, and another day of pretesting was carried
out by CARE staff after training. Because microcomputers were avail-
able, revisions to the questionnaire could be incorporated literally
overnight, and new copies made for fieldwork the next day.
The majority of households in Laurent were interviewed. Enu-
merators were instructed to try to interview someone in every house. If
no one was at home, a follow-up visit was usually arranged.
The household interview consisted of four sections. The first dealt
with basic occupational and demographic data for the family members
and summary information on where the family obtained its water. The
second section consisted of additional questions on the location of each
water source that the family used, perceptions of the water quality at
each source, the average number of times each family member went to
each source per day, and the number of containers they carried home
(the enumerator asked to see the containers used to carry water and
estimated their volume). In the third section of the questionnaire, the
enumerator read one of the statements used to test for strategic bias
and showed the respondent photographs of public standposts CARE
had built in other villages. The respondent was then asked for (a) a
WTP bid per month for public standposts (assuming no private connec-
tions) and (b) a private connection (assuming public standposts were
already installed). The fourth section was a series of questions on the
health and education of family members and the household's assets
(such as whether the household had a radio or a kerosene lamp). The
principal investigators and the enumerators had agreed that it was not
possible to obtain accurate information on household income through
interviews (in fact, the enumerators simply refused to ask either in-
come or expenditure questions because of the antagonism such ques-
tions aroused). As a substitute, the enumerator recorded a series of
observations about the construction of the house itself, such as
whether the house was painted, whether the roof was straw or tin, and
whether the floor of the house was dirt or cement.
A detailed map of the village was prepared that indicated the loca-
tion of all houses and major structures, as well as all water sources.
Enumerators who could read maps were given a copy of the village
map and asked to assign a number to each household interviewed and
to record that number on the map. The enumerator also gave each
respondent a ribbon and an index card with the corresponding house-
D. Whittington, J. Briscoe, X. Mu, and W. Barron 301
hold number on it and asked the respondent to wear the ribbon or bring
the index card on a designated day to the water source used.
Enumerators who could not read a map were given a set of ribbons
with preassigned numbers, dropped at specific points in the villages,
and instructed to interview households in clearly specified areas and
assign a number to each household interviewed; one of the senior
members of the research team then recorded on the map which house-
holds were located in the specified areas. Data from household inter-
views were generally entered into the microcomputer on the same day
the interviews were conducted, and processed with dBase III pro-
grams. Summary statistics were continually compiled during the
course of the fieldwork, and discrepancies in the data and problems
with the survey implementation could be quickly detected.
The second part of the fieldwork consisted of observing the quan-
tities of water collected by individuals at all the sources used by the
population of the village. The objective of these observations was to
verify the information individuals provided in household interviews on
the sources they used and the quantities of water collected. Local
residents were hired to serve as source observers; they were typically
secondary school students on summer vacation. All source observers
received one day of training in estimating the volumes of various con-
tainers and in recording data in their notebooks. Each time an individ-
ual arrived at a source, the source observer recorded household num-
ber, name, gender, relative age (adult or child), time of arrival, quantity
of water carried away, and whether the individual bathed or did laun-
dry. All sources were observed on the same day from sunrise to sunset.
Two shifts of source observers were used for each source. The source
observers were monitored closely by the principal investigators to en-
sure the quality of the data collected.
Analysis of the Source Observation Data
The analysis of the source-observation data for Laurent increased our
confidence in the quality of the water-use data obtained from the
household interviews. In Laurent we recorded data on 119 trips to
water sources by individuals (or groups of individuals from the same
household) who identified themselves to our source observers either by
wearing a ribbon or displaying an index card with their household
number. We compared the sources these individuals said they used for
drinking and cooking in the interview with the source they actually
went to on the day of our source observations. Out of the 119 observa-
tions, the interview responses were consistent with the source obser-
vations for 101 households (85%). In the econometric analysis of the
contingent valuation bids, we used the water source selection data
from the household interviews in order to calculate the distance from
the household to its primary source of drinking and cooking water.
302 Economic Development and Cultural Change
TABLE 1
TEST FOR STRATEGIC BIAS
Opening Statement A Opening Statement B
Willingness to pay for
public standposts:
Total observations 77 73
Mean WTP bida 6.0 5.4
Standard deviation 3.8 3.9
Overall mean 5.7
Standard deviation 3.8
t-statistic 1.1
Willingness to pay for
private connections:
Total observations 67 65
Mean WTP bida 7.5 6.7
Standard deviation 9.0 9.8
Overall mean 7.1
Standard deviation 9.4
t-statistic .5
NOTE.-Null hypothesis that the two samples are from the same population cannot
be rejected at any acceptable confidence level.
a Mean WTP bid in gourdes per month. 5 gourdes = US$1.
Analysis of the Contingent Valuation Bids
In Laurent, 170 questionnaires were completed out of approximately
225 households in the village. Our impression from sitting in on many
of the household interviews is that respondents took the contingent
valuation questions, and indeed the entire interview, quite seriously.
Fourteen percent of the households gave an answer of "I don't know"
in response to the WTP question for public standposts; there was a
25% nonresponse rate for the WTP question for private connections.
The mean of the bids in Laurent for the public standposts, 5.7 gourdes
per month (US$1.14; US$1.00 = 5 gourdes) seemed realistic to us. In
our opinion, we never received wildly unrealistic or "protest" bids.
Based on the pretest, we felt that the bidding-game question format
worked better than the direct, open-ended questions. People generally
felt more comfortable with the bidding games, and, in fact, our
enumerators remarked that the bidding game format was very familiar
and easily understood because it was similar to the ordinary kind of
bargaining that goes on in local markets of rural Haiti. Hence in Lau-
rent we used only the bidding-game question format.
In this section we discuss the results of the statistical analysis of
the data obtained from the household surveys in Laurent. Table 1
presents the results of our tests for strategic bias for the WTP questions
both for public standposts and private connections. The 150 total re-
D. Whittington, J. Briscoe, X. Mu, and W. Barron 303
TABLE 2
TEST FOR STARTING-POINT BIAS
STARTING POINT
2 gourdesa 5 gourdes 7 gourdes
Willingness to pay for public
standposts:
Number of observations 56 47 47
Mean WTP bidb 5.4 6.0 5.7
Standard deviation 3.8 3.9 3.9
F = .32
Probability = .73
STARTING POINT
5 gourdes 10
gourdes 15
gourdes
Willingness
to
pay
for
private
connections:
Number of observations 48 41 43
Mean WTP
bidb 6.7 7.4 7.1
Standard deviation 8.3 8.8 11.0
F = .06
Probability
= .94
NOTE.-Null hypothesis that the three samples are from the same population cannot
be rejected at any acceptable confidence level.
a 5 gourdes = US$1.
b Mean WTP bid in gourdes per month.
sponses for public standposts were relatively evenly divided between
statement A (77 responses) and statement B (73 responses), as were
those for the private connections. As anticipated, for respondents who
received statement A, the mean bids both for public standposts and
private connections were higher than for those who received statement
B, but the difference is not statistically significant. On the basis of this
test, we cannot reject the hypothesis that respondents were not acting
strategically when they answered the WTP questions.
Table 2 presents the results of a similar statistical test for starting-
point bias. If starting-point bias were a problem, we would expect that
the low starting point (2 gourdes for public standposts; 5 gourdes for
private connections) would result in a lower bid, and that the high
starting point (7 gourdes for public standposts; 15 gourdes for private
connections) would result in higher bids. The mean bids in table 2 do
not appear to vary systematically with the starting point. The null
hypothesis that the three samples are from the same population (that
there is no difference in the responses from individuals who received
different starting points) cannot be rejected, although the confidence
intervals are wide.
304 Economic Development and Cultural Change
On the basis of these results, there was no reason to attempt to
adjust the WTP bids for strategic or starting-point bias. The mean of
WTP bids for the public standposts was 5.7 gourdes per household per
month. Assuming an average annual household income in Laurent of
4,000 gourdes (US$800), the mean bid is about 1.7% of household
income and is significantly lower than the 5% rule of thumb often used
in rural water-supply planning for maximum "ability to pay" for public
standposts. The mean of WTP bids for private connections, 7.1
gourdes, was not much higher (2.1% of household income), but these
bids are based on the assumption that the public standposts are already
in place.
We next modeled the variations in the bids for public standposts
and private connections as a function of the variables that were the
primary focus of our research design. To measure income we devel-
oped an ordinal measure of the value of household assets, based on
eight questions and observations about the quality of housing construc-
tion and household possessions (WLTH), and supplemented it with
two other indicators of income: (1) whether the household received
remittances from relatives living abroad and (2) the occupations of the
principal members of the household. In the model remittance data were
simply treated as a dummy variable (FINC). Occupation data were
used to group households into two categories (farmers and nonfarmers)
and were also represented by a dummy variable (IOCP). Education
was measured as the sum of the years of school of up to two adults in
the household (HHED). From the village map we measured the dis-
tance of each household to its drinking water source (DIST); these
distances served as a measure of the cost of obtaining water
from the existing source, which we viewed in the model as the "price"
of the close substitute of the improved water service. Our measure of
water quality (QULT) was based on the respondent's answers to seven
questions concerning taste, odor, healthfulness, reliability, color, dirt,
and conflict (quarrels) at the source.
Although the value households place on the proposed water sys-
tem is a continuous variable, we believe the most reliable data gener-
ated from the bidding game are the set of yes/no responses to questions
about specific, discrete prices. Thus, the observed dependent variable
obtained from the bidding game procedure is not the maximum amount
the household would be willing to pay but, rather, an interval within
which the "true" willingness to pay falls. Linear regression is not an
appropriate procedure for dealing with such an ordinal dependent vari-
able because the assumptions regarding the specification of the error
term in the linear model will be violated.12 We have therefore used an
ordered probit model, discussed below, to explain the variations in
WTP bids.
Let Vh be the maximum willingness to pay of household h for the
D. Whittington, J. Briscoe, X. Mu, and W. Barron 305
proposed water system. Based on consumer demand theory, we hy-
pothesize that Vh is a function of the attributes of the new and existing
water sources and the household's socioeconomic characteristics
Vh = a + XhB + eh, (1)
where Xh is a vector of the household's characteristics and the attri-
butes of the sources, a and B are parameters of the model, and eh is a
random term with a standard normal distribution. Since Vh is not ob-
servable from the bidding game, equation (1) cannot be estimated.
However, from the interview responses we know the ranges within
which Vh will fall. Let R1, . . . , Rm be the m prices which divide the
range of WTP space into m + 1 categories, and let yh be a categorical
variable such that
1 if Vh < R
1,
Yh 2 if R1 < Vh < R2, (2)
M + 1 if Vh > Rm.
Let i = 1, ... , M + 1. From equation (1), we have Yh = i if
Ri-l < a + XhB + eh < Ri (3)
or Ri-1 - a < XhB + eh < Ri - a (4)
or (Ri-1 - a - XhB)/I < eh/I < (Ri - a - XhB)Ia, (5)
where u is the standard deviation of eh. Assuming eh follows a standard
normal distribution, then
P(yh = i) = P(Ri-1 < Vh < Ri)
= P(ui-1 - XhB < eh < ui-1 - XhB) (6)
= F(ui - XhB) - F(uil1 - XhB),
where ui = Ri - a and F(-) is the cumulative standard normal density
function. (Equation [6] is the ordered probit model we have used to
explain the variations in WTP bids.) The maximum likelihood esti-
mates of ui and B are consistent.13
The results of the estimations are presented in tables 3 and 4. The
chi-square statistics illustrate that the overall models are highly sig-
nificant. The adjusted likelihood ratio (1 - {[L(B) - K]/L(0)}) is 0.142
for the model of bids for public standposts and 0.177 for the model of
bids for private connections, where K is the number of independent
variables in the model. The coefficients for all the independent vari-
ables are in the direction expected (e.g., households with higher edu-
cation or wealth tend to bid higher). The t-statistics indicate that the
TABLE 3
WILLINGNESS-TO-PAY BIDS FOR PUBLIC STANDPOSTS
Coefficient t-ratio
Dependent
variable:
Probability
that a household's
willingness
to pay for a public standpost
falls
within
a specified
interval
Independent
variables:
Intercept .841 1.350
Household wealth index
(WLTH) .126 2.939
Household with foreign
income
(FINC = 1 if yes) .064 .232
Occupation
index
(IOCP = 1 if farmer) -.209 -.848
Household education level
(HHED) .157 2.113
Distance
from existing source
(DIST) .001 5.716
Quality
index of existing source
(QULT = 1 if satisfactory) -.072 -2.163
Sex of respondent (male = 1) -.104 - 5.41
Log-likelihood -206.01
Restricted
log-likelihood - 231.95
Chi-square
(freedom = 7) 51.878
Adjusted
likelihood ratio .142
Degrees of freedom 137
TABLE 4
WILLINGNESS-TO-PAY BIDS FOR PRIVATE CONNECTION
Coefficient t-ratio
Dependent
variable:
Probability
that a household's
willingness
to pay for a private
connection
falls
within a specified
interval
Independent
variables:
Intercept -.896 -1.344
Household
wealth index
(WLTH) .217 4.166
Household
with foreign
income
(FINC = 1 if yes) .046 .194
Occupation
index
(IOCP = 1 farmer) - .597 - 2.541
Household
education level
(HHED) .090 1.818
Distance
from existing source
(DIST) .000 1.949
Quality
index of existing source
(QULT = 1 if satisfactory) -.099 - 2.526
Sex of respondent (male = 1) -.045 -.207
Log-likelihood - 173.56
Restricted
log-likelihood - 202.48
Chi-square
(freedom = 7) 57.831
Adjusted
likelihood ratio .177
Degrees of freedom 120
306
D. Whittington, J. Briscoe, X. Mu, and W. Barron 307
TABLE 5
DEMAND SCHEDULES FOR NEW WATER SOURCES, DERIVED FROM THE ORDERED PROBIT
MODELS
(Price vs. Number of Users)
PRICE
(Gourdes per month)
2 5 7 10
Number of users:
Public standposts
(N = 145) 138 97 68 40
PRICE
(Gourdes per month)
5 10 15 20
Number of users:
Private connections
(N = 127) 78 62 40 17
variables for household wealth, household education, distance of the
household from the existing water source, and water quality are all
significant at the 0.05 level in both models. The sex of the respondent
was statistically significant in the model for public standposts, but not
in the model for private connections. The results clearly indicate that
the WTP bids are not random numbers but are systematically related to
the variables suggested by economic theory.
Policy Applications
This ordered probit model can be used to predict the number of house-
holds in a community which will use a new source if various prices
were charged. Since the interval for each category is known, yh (the
category into which household h falls) may be predicted from inequal-
ity (4) by calculating XhB. Summing the number of households in each
category in Laurent yields the demand schedules presented in table 5.
Such demand schedules are precisely the kind of information needed
by planners and engineers to make sound investment decisions, and we
believe this ordered probit model, estimated with WTP bids obtained
from a contingent valuation survey, is a promising approach to model-
ing village water demand relationships.
Summary and Conclusions
The results of this study suggest that it is possible to do a contingent
valuation survey among a very poor, illiterate population and obtain
reasonable, consistent answers. There does not appear to be a major
problem with either starting point or hypothetical bias. The evidence
with regard to strategic bias is less conclusive, but neither the admit-
308 Economic Development and Cultural Change
tedly limited test for strategic bias nor the experience of the enumera-
tors indicated that it was a problem.
From this research we cannot, of course, judge whether individ-
uals in the villages would in fact pay the amounts they indicated in the
contingent valuation survey if a water agency actually tried to collect
the money. To do so we would need to conduct a contingent valuation
survey in a village before a water system is built, then resurvey after
the system is completed and collection efforts are made, and compare
the prior bids with actual behavior.
Nevertheless, we believe that the preliminary results of this re-
search strongly suggest that contingent valuation surveys are a feasible
method for estimating individuals' willingness to pay for improved
water services in rural Haiti. This has important policy implications for
rural water supply projects such as CARE's because it seems to show
that going into a village and conducting a relatively simple household
survey can yield reliable information on the population's willingness to
pay for improved water services. The implications of these preliminary
research findings are not, however, limited to the rural water sector.
Our research suggests that contingent valuation surveys may prove to
be a viable method of collecting information on individuals' willingness
to pay for a wide range of public infrastructure projects and public
services in developing countries.
Appendix
Example of Bidding Game
Here are pictures of CARE public fountains set up in Rosier and Port-a-
Piment.
(a) Do you think your household
would be willing
to pay 5 gourdes
each
month to use a public fountain located in your neighborhood?
Yes__ Go to (b)
No__ Go to (c)
I don't know__ Go to (f)
(b) We do not know how much the water committee
will decide for each
household to pay for using
the public
fountain
each month. If the decision
is for
each household to give 10 gourdes each month, would your household be
willing
to pay this?
Yes Go to (f)
No Go to (d)
I don't know__ Go to (f)
(c) We do not know how much the water committee
will decide for each
household
to pay for using
the public
fountain
each month.
If the decision
is for
each household to give 0.50 gourdes each month, would your household
be
willing
to pay this?
D. Whittington, J. Briscoe, X. Mu, and W. Barron 309
Yes__ Go to (e)
No__ Go to (f)
I don't know__ Go to (f)
(d) Would your household be willing to pay 7 gourdes each month to use a
public fountain located in your neighborhood?
Yes Go to (f)
No Go to (f)
I don't know Go to (f)
(e) Would your household be willing to pay 2 gourdes each month to use a
public fountain located in your neighborhood?
Yes Go to (f)
No Go to (f)
I don't know__ Go to (f)
(f) Think for a moment, what is the largest amount of money your house-
hold would be willing to pay each month to use a public fountain? If it would
cost your household more than this amount, your household could not afford to
pay and would not be able to use the public fountain.
Amount of money:
I don't know:
Notes
* This research was carried out as part of the Water and Sanitation for
Health (WASH) project, sponsored by the Office of Health, Bureau for Science
and Technology, U.S. Agency for International Development. We would like
to thank our project manager, Dr. Dennis Warner, for his assistance during the
course of this work. We would like to express our appreciation to the following
members of the CARE staff for their support during the fieldwork: Scott Faiia,
Jonathan Mitchell, Ann Raposa, and Louis Jasmine. We would also like to
thank Tom Bourgeois and Jean-Maurice Duval for their assistance with the
fieldwork and David K. Guilkey and Raymond Burby for their comments on an
earlier draft of the article. An earlier version of this article was presented at the
annual meeting of the North American Regional Science Association, Novem-
ber 13-16, 1986, Columbus, Ohio.
1. See, e.g., Canadian International Development Agency, in World
Health Organization, Catalogue of External Support, International Drinking
Water Supply and Sanitation Decade Publication no. 3 (New York, April 1983),
p. 218; IBRD, Water Supply and Urban Development Department, Improving
the Effectiveness of Investment in the Water Sector, UNDP Water Decade
Program (Washington, D.C.: World Bank, June 1986); Anthony A. Churchill,
with the assistance of David de Ferranti, Robert Roche, Carolyn Tager, Alan
A. Walters, and Anthony Yazer, "Rural Water Supply and Sanitation: A Time
for Change," World Bank Discussion Papers 18 (Washington, D.C., 1987); R.
Saunders and J. Warford, Village Water Supply (Baltimore: Johns Hopkins
University Press, 1977).
2. For the varying parameter demand model, see W. J. Vaughn and C. S.
310 Economic Development and Cultural Change
Russell, "Valuing a Fishing Day: An Application of a Systematic Varying
Parameter Model," Land Economics 58, no. 4 (November 1982): 450-63. For
the hedonic property value model, see, e.g., A. M. Freeman, "The Hedonic
Price Approach to Measuring Demand for Neighborhood Characteristics," in
The Economics of Neighborhood, ed. D. Segal (New York: Academic Press,
1979); A. D. Witte, H. J. Sumka, and H. Erekson. "An Estimate of a Struc-
tural Hedonic Price Model of the Housing Market: An Application of Rosen's
Theory of Implicit Markets," Econometrica 47 (1979): 1151-73. For the he-
donic travel cost model, see, e.g., C. J. Cicchetti, V. K. Smith, J. L. Knetsch,
and R. A. Patton, "Recreation Benefits Estimation and Forecasting: Implica-
tions of the Identification Problem," Water Resource Research 8, no. 4 (Au-
gust 1972): 840-50; T. A. Deyak and V. K. Smith, "Congestion and Participa-
tion in Outdoor Recreation: A Household Production Function Approach,"
Journal of Environmental Economics and Management 5, no. 1 (1978): 63-80;
J. A. Sinden, "A Utility Approach to the Valuation of Recreational and Aes-
thetic Experiences," American Journal of Agricultural Economics 56, no. 1
(February 1974): 61-72.
3. R. G. Cummings, D. S. Brookshire, and W. D. Schulze, Valuing Public
Goods: The Contingent Valuation Method (Totowa, N.J.: Rowman & Al-
lanheld, 1986).
4. Saunders and Warford.
5. Another reason southern Haiti was selected was that decisions about
the level of service and the choice of technology for water supply systems are
particularly difficult in Haiti. Per capita incomes in Haiti are the lowest in the
Western Hemisphere: in 1980 more than two-thirds of the population of 5
million people had per capita annual incomes less than US$155. Most individ-
uals simply cannot afford the costs associated with private connections. Haiti
thus provides a field setting similar to the situation in much of Africa and some
parts of Asia, and conditions where an accurate understanding of the willing-
ness of the population to pay for rural water services is likely to be particularly
important for sound investment decisions.
6. For example, a survey in Zimbabwe showed that women were willing
to pay 40% more than men for an improved water supply; see Ministry of
Energy and Water Resources Development, Water Tariff Study, National Mas-
ter Plan for Rural Water Supply and Sanitation, Republic of Zimbabwe (De-
cember 1985), vol. 3, pt. 4.
7. See, e.g., Cummings, Brookshire, and Schulze; R. C. Mitchell and
R. T. Carson, "Will Respondents Answer Honestly? Observations on Strate-
gic Bias and Contingent Valuation Surveys," in "Using Surveys to Value
Water Quality Benefits: The Contingent Valuation Method," draft manuscript
for USEPA Resources for the Future (Washington, D.C., January 29, 1985),
chap. 3, and Using Surveys to Value Public Goods: The Contingent Valuation
Method (Washington, D.C.: Resources for the Future, 1989).
8. See A. Randall, B, Ives, and C. Eastman, "Bidding Games for the
Valuation of Aesthetic Environmental Improvements," Journal of Environ-
mental Economics and Management 1 (1979): 132-49; A. Randall, J. P.
Hoehn, and G. S. Tolley, "The Structure of Contingent Markets: Some Re-
sults of a Recent Experiment" (paper presented at the American Economic
Association annual meeting in Washington D.C., 1981).
9. P. Bohm, "Estimating Demand for Public Goods: An Experiment,"
European Economic Review 3 (1972): 111-30; see also Mitchell and Carson,
Using Surveys to Value Public Goods.
10. This is not in fact a strong test for strategic bias because the differ-
ences in the two statements are quite subtle. In an ongoing field test in Brazil
D. Whittington, J. Briscoe, X. Mu, and W. Barren 311
we are testing for strategic bias by comparing WTP bids from two different
villages, one in which the water utility has already promised to construct a new
water system and another in which the water utility has not yet determined
whether to build a new system. A comparison of WTP bids from these two
villages should be a more conclusive test for strategic bias, assuming it is
possible to control for other differences between the two villages. In future
research it would also be useful to have follow-up interviews with selected
repondents to see whether the differences that we wished to suggest were
understood. An in-depth anthropological research effort might also elicit infor-
mation on what types of strategic "thoughts" passed through respondents'
minds during the interview process. If strategic behavior is found to exist,
anthropological research might also yield insights into how to minimize it dur-
ing the interview.
11. Cummings et al. (n. 3 above).
12. See G. S. Maddala, Limited-Dependent and Qualitative Variables in
Econometrics (New York: Cambridge University Press, 1983); D. McKelvey
and W. Zavorina, "A Statistical Model for the Analysis of Ordinal Level
Dependent Variables," Journal of Mathematical Sociology 4 (1975): 103-20.
13. See Maddala.
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PAUL BAIROCH
Translated
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... In these areas, some households often resort to alternative sources of improved water supply such as privately investing in water infrastructure and treating water at home. However, the cost of collecting water from alternative sources is significantly higher and less efficient than that of a collectively provided safe tap water system (Whittington et al. 1990). For instance, the price per unit of bottled water is typically up to 1,000 times more expensive than tap water (Ferrier 2001). ...
... A MIXL model is used as a highly flexible model to accommodate unobserved heterogeneity in estimation and to approximate any random utility model. It is widely applied in modeling for improved water demand choice using the stated preference method (Whittington et al. 1990;Hensher et al. 2005). In the MIXL model, unobservable factors can be decomposed into two additive parts (1 n ¼ h n þ d n ): stochastic (h n ), which is correlated over alternatives and heteroscedastic over consumers and alternatives and stochastic part (d n ), which is IID over alternatives and consumers (Train 2009). ...
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... In recent years economists are inclined to solve problem of water resource management applying the tools of economic theory and econometrics. There are two basic theoretical approaches a) indirect -uses data on observed water use behavior; b) direct -to ask an individual how much he or she would be willing to pay for the improved water services, are popularly used to estimate economic value of natural water resources like water (Whittington et al., 1990). His preliminary investigation in Haiti, proved contingent valuation method (CVM) surveys to be viable method of collecting information on individuals' willingness to pay for a wide range of public infrastructure projects and public services in developing countries. ...
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Valuing Public Goods: The Contingent Valuation Method Rowman & Allanheld , 1986). 4. Saunders and Warford. 5. Another reason southern Haiti was selected was that decisions about the level of service and the choice of technology for water supply systems are particularly difficult in Haiti
  • R G Cummings
  • D S Brookshire
  • W D Schulzetotowa
R. G. Cummings, D. S. Brookshire, and W. D. Schulze, Valuing Public Goods: The Contingent Valuation Method (Totowa, N.J.: Rowman & Allanheld, 1986). 4. Saunders and Warford. 5. Another reason southern Haiti was selected was that decisions about the level of service and the choice of technology for water supply systems are particularly difficult in Haiti. Per capita incomes in Haiti are the lowest in the Western Hemisphere: in 1980 more than two-thirds of the population of 5
Valuing a Fishing Day: An Application of a Systematic Varying Parameter Model For the hedonic property value model, see, e.g., A. M. FreemanThe Hedonic Price Approach to Measuring Demand for Neighborhood Characteristics
, "Valuing a Fishing Day: An Application of a Systematic Varying Parameter Model," Land Economics 58, no. 4 (November 1982): 450-63. For the hedonic property value model, see, e.g., A. M. Freeman, "The Hedonic Price Approach to Measuring Demand for Neighborhood Characteristics," in The Economics of Neighborhood, ed. D. Segal (New York: Academic Press,
111-30; see also Mitchell and Carson, Using Surveys to Value Public Goods. 10. This is not in fact a strong test for strategic bias because the differences in the two statements are quite subtle
  • P Bohm
P. Bohm, "Estimating Demand for Public Goods: An Experiment," European Economic Review 3 (1972): 111-30; see also Mitchell and Carson, Using Surveys to Value Public Goods. 10. This is not in fact a strong test for strategic bias because the differences in the two statements are quite subtle. In an ongoing field test in Brazil