2 Review of Literature - INFLIBNETshodhganga.inflibnet.ac.in/bitstream/10603/6299/11/11...2.2.1...
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TERI University Ph.D. Thesis, 2006
Review of Literature
2.1 Introduction
This chapter reviews the previous published studies and empirical techniques that
have been used to assess customer’s preferences for water services in the context of
welfare change. These studies either use ‘revealed preference’ or ‘stated preference’
methods to quantify change in welfare. Revealed preference methods are subdivided
into two distinct categories – hedonic pricing and averting expenditure; while stated
preference methods use any of the three approaches – open-ended contingent
valuation, contingent ranking and discrete choice methods. Discrete choice methods
are further subdivided into referendum contingent valuation and choice modelling.
The published studies are reviewed keeping in mind this classification. The chapter
concludes with the overall summary of literature review, which is intended to set the
basis for defining objectives of the current research.
2.2 Revealed Preferences
The correspondence of choice and revealed preference is seen as an empirical
matter, and this is indeed how the correspondence is viewed in the classical demand
theory (Sen 1997). Considerable research efforts have been made in public
economics to estimate the demand and choice for public goods with revealed
preference data. These efforts have sufficient theoretical support as they employ
market information for complementary or surrogate goods such as land/housing
markets to assess change in levels of services for valuing monetary impacts of such
changes (Karl-Göran Mäler and Vincent 2005). Haripriya and Kathuria (2005),
Yusuf and Koundouri (2005) use hedonic pricing techniques whereas Dasgupta and
Dasgupta (2004), Kolstad (2000), Abdalla et al. (1992), Akerman et al. (1991),
Harrington and Portney (1987), Courant and Porter (1981) use averting expenditure
for quantifying welfare change in estimation of benefits of better water supply.
2.2.1 Hedonic pricing techniques
Pioneered by Griliches (1971) and formalized by Rosen (1974), this technique uses
the assumption that the price of a non-market good is related to price of the market
good and its associated attributes. The technique is mainly used in property value
studies, where the price of a particular unit of housing is expected to include the
value of environmental amenities, such as good water quality. Various attributes and
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their associated prices of the property reveals the implicit prices of water quality,
known as hedonic prices.
Haripriya and Kathuria (2005) estimated the effect of water availability on house
price and the willingness to pay for a water project that provided reliable water
supply in Chennai using hedonic price technique. The authors argued that quantity
and quality of water supply in a particular zone may affect the preferences of the
households to reside in that area. Using a questionnaire survey of 1416 households
in 13 localities in the city centre of Chennai, the results indicated that the aggregate
WTP for an increase in water supply situation was approximately Rs 2480 million
and for improved water quality the aggregate WTP was Rs 981 million in urban
settlements. The higher price was revealed for piped water and improved water
quality in their premises in comparison to the existing situation of fetching water
through different sources such as ground water, private tankers, metro tanker,
public taps etc. Similarly, Yusuf and Koundouri (2005) investigated how the
decision on house location (urban/rural) affected the household’s valuation of
water-related characteristics of the house through hedonic price analysis. The
empirical analysis used data from the Indonesian housing market and suggested
that households valued access to safe and improved domestic water sources in
selecting housing locations.
Not many case studies are available to value improved water supply through
hedonic pricing technique. The largest problem that hedonic analysis faces is the
requirement that the researcher be able to control all relevant attributes, which is a
difficult task. Even where relevant proxy markets exist, it may be difficult to provide
adequate information about households’ actual willingness to pay for the goods in
question. Other problems with hedonic property valuation include, but are not
limited to, the need for the individuals in question to be aware of the differences in
attributes between potential housing units and jobs, insufficient market data, and
unknown functional forms of the pricing equations (Mitchell and Carson 1989).
According to Bateman et al. (2002), “hedonic pricing technique estimates the value
of a marginal change, in the provision of the good in question. To value discrete
changes, which are often of interest, requires the full ‘two stage’ approach to hedonic
price estimation. This can be complex and resulting estimates can be very uncertain.
Estimates derived from the first stage only, i.e., the change in property price with
respect to small change in the variable affecting the property price, are, however,
thought to be upper bounds to the theoretically complete estimate if one assumes
that there is a variation on the extensive margin (for example, alternative house
size).” Also revealed preference techniques are limited to estimating use value
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associated with goods that are reflected in actual markets, or confined to those
services where there is an associated market.
2.2.2 Averting expenditure
Averting expenditure (AE) analysis captures economic value from customers’ ability
to purchase goods in traditional economic markets that can be used to mitigate
adverse environmental and health impacts. The theoretical foundation is based on
estimation of customers’ ‘production function’ from their demand and consumption
of goods and services as an approximation of benefits stemming from reduced
environmental risks (Dasgupta and Dasgupta 2004, Kolstad 2000, Abdalla et al.
1992, Whittington et al. 1990c, Harrington and Portney 1987, Courant and Porter
1981).
Dasgupta and Dasgupta (2004) estimated WTP in infrastructurally disadvantaged
slums of Delhi using production function approach and found that the averting
expenditure was substantial to secure a safe and reliable water supply. The authors
attempted to provide measure of the households’ minimum willingness-to-accept
for avoiding damages from consuming contaminated water through indirectly
estimating monetary value of health losses borne by households due to diarrhoeal
sickness. The average predicted probability of observing diarrhoeal sickness in the
sampled household was found to be 0.44 whereas the estimated cost of illness for
poor representative household due to diarrhoeal diseases was found to be Rs
1094.31 per annum.
In a revealed preference study carried out in Ukanda, Kenya in 1990 by Whittington
et al. (1990c) it was observed that ‘time’ to collect water and ‘price’ were two major
decision factors responsible for households’ preference for improved water supply.
Choice of different water systems results in different time savings, the service levels
offered from them have to be traded off in terms of increased costs of connection
and the benefits derived from reduced time spent in collecting water. In this study
households placed higher values to time saved due to better water supply sources.
This was roughly equivalent to the wage rate for an unskilled labour, though Asian
Development Bank at that time assumed that time savings should be valued at 50%
of the market wage rate for unskilled labour in the local economy. The households
were already paying 8% of their income on securing water from the vendors. The
authors while using conditional multinomial logit model to study the preference of
water supply systems took two sets of explanatory variables – (i) source attributes
which affect households’ utility such as duration of collection and taste of water, and
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(ii) households’ characteristics that reflect the preference variations such as price of
water and households’ income. This study gave one of the first instances of valuation
benefits from time savings from an improved water supply in a developing country
which was much higher than the commonly held belief.
Many of researchers believe that AE have lower bounds compared to compensating
and equivalent variation, and thus may result in underestimation of customers’
actual expenditure on getting a reliable water supply (Kolstad 2000, Roach 1990,
Shortle and Roach 1989, Courant and Porter 1981). This may be case even if the
value of time that is forgone due to averting behaviour is included in the analysis
(Akerman et al. 1991). This was observed through constructing model of households’
utility function to study their expenditure on averting pollution. Courant and Porter
(1981) considered the response of customers who wish to maximize their utility to
diminutive changes in the levels of water quality, assuming that a better water
quality is preferred mainly because it reduces the need of higher expenditure to
avoid risk of contamination. Harrington and Portney (1987) argue that AE can
produce welfare measures accurately stemming from water quality improvement
project provided information on market mechanisms and customers’ behaviour is
correctly elicited. Hanley et al. (1997) list conditions required for better AE
estimates, such as – (i) AE should not exhibit ‘joint production’ and changes in
expenditure to averting behaviour should be entirely due to changes in quality of
specific goods in question, (ii) increase in AE should also improve the quality of
specific goods, and (iii) the specific goods should directly enter customers’ utility
function, not the inputs required to produce them.
As stated earlier, AE technique is confronted with ‘joint products’ problem, wherein
total expenditure may correspond to spending not only on the specific goods in
question, but also on some other unrelated goods. For example, households may
consume bottled water for drinking purposes not only in an effort to protect them
from contamination, but also because they consider that bottled water tastes better.
Also AE includes customers’ long-lasting investments in durable goods and has large
sunk cost such that the full price of such goods cannot be equated as payments for a
change in environmental quality (Bartik 1988). According to Bateman et al. (2002),
WTP estimates from averting expenditure analysis will be upper bounds rather than
the estimates that may be required for policy purposes.
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2.3 Stated preference method
Direct or stated preference method uses survey based approach to valuate
hypothetical changes in levels of service provision by asking customers how much
they would be willing to pay for improved service conditions vis-à-vis existing
service levels (Tietenberg 2005). It is also called contingent valuation (CV) because
the alternate scenario presented to the customers is contingent upon future service
levels enumerated to them. Alternatively, for service failure, they are asked how
much they would be willing to accept compensation for the changed service levels.
The first one is called willingness to pay (WTP) and the second one is referred to as
willingness to accept compensation (WTA). With a strong foundation in
constrained utility maximization theory (McFadden 1974, Johansson 1995), stated
preference technique has become the most widely used tool for estimating benefits
associated with providing non-marketed goods and services, especially in
environmental economics literature. Olsen and Smith (1999) agree that ‘WTP is the
most appropriate way to value benefits provided by imperfectly provided goods and
services in monetary terms’.
Stated preference method is an omnibus for a variety of approaches which use any
of these three techniques – open-ended contingent valuation, contingent ranking
and discrete choice methods. Discrete choice methods are further subdivided into
referendum contingent valuation and choice modelling. The family of stated
preference techniques is shown in the figure 2.1.
Stated preference methods
Open-ended contingent valuation
Conjoint ranking and paired comparison
Discrete choice methods
Referendum contingent valuation
Choice modelling
Figure 2.1 The family of stated preference techniques
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All of these methods approximate the demand curve that would have existed, had
there been a market for valuation of a non-market good like ‘water quality’.
According to (Haab and McConell 2002), stated preference data generated from a
‘questionnaire based survey’ allows estimation of changes in the provision of specific
goods and can be evaluated in the similar way as actual choice and preference
observed in the market. This allows to directly estimate customer’s WTP for water
supply improvements, which is governed by current level of services and coping
mechanisms against unreliable supply, customers’ expectations, and other socio-
economic variables (Haider and Rashid 2002, Raje et al. 2002, Zerah 2001, Asthana
1997). These considerations are taken into designing the survey instruments i.e. the
questionnaire. Questionnaires are deliberated to imitate the behaviour of the
respondents in the marketplace, which are common in all these methods except the
manner in which valuation question is posed to the respondents in assessing the
demand and preference behaviour (Mitchell and Carson, 1989). It basically
confronts the respondents with a given monetary amount under a hypothetical
scenario, resulting into a response. The purpose of appropriate elicitation format in
the valuation of non-market commodities is to present the hypothetical scenario in a
plausible manner so that respondents can express their true preference for them.
This has evolved from the simple open-ended questions to more complex choice
experiments. As respondents’ WTP for an improvement water supply services is a
function of the projected changes in the level of the service, all factors which control
individual’s valuation of the specified change are included in the questionnaire.
According to Whittington et al. (1993), a particular method assumes that a
household’s WTP for an improved water supply depends on several factors such as:
(a) existing levels of service provision and sources of supply; (b) tariff rate and
billing; (c) perceptions of reliability, pressure and quality as water problems ; (d)
Price of other related goods and services; (e) socio-economic characteristics such as
age, gender, family size, education level, occupation, income, expenditures and
assets; (f) housing characteristics; (g) levels of water consumption; and (h) attitudes
of the household which may serve as proxies for taste.
2.3.1 Open-ended contingent valuation
This has evolved from the simple open-ended question of early studies where
respondents are asked to state their maximum WTP amounts as point estimates.
McPhail (1993) in 5 small Moroccan cities found that households were ready to pay
anywhere from 7 to 10 per cent of households’ expenditure for securing residential
water connections even though they were provided with free and reliable standpost
services. Though this finding was not validated by later studies. Altaf (1994)
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described the results of a WTP survey of approximately 1000 households conducted
in Gujranwala, Pakistan to document household response to inadequate water and
sanitation services and to estimate demand for improved public services. The study
showed that demand-side information about household preferences and priorities,
which have traditionally been neglected, could provide important input for
designing public policy aiming at better societal welfare. However, in this study,
respondents were willing to pay 50% less than the price they were currently paying
because they were not convinced from the hypothetical scenario that would result in
savings in procuring water from other sources, mainly private wells. The response
was explained by the fact that private wells were better alternative supply than the
public water supply and so the respondents did not deem promise of an improved
water supply plausible. Raje et al. (2002) presented an approach to quantify the
satisfaction level of consumers relating to water supply services and described the
impact of various factors on WTP through binary logistic regression analysis. Open-
ended elicitation format was employed for getting point estimates of households’
WTP. The study was conducted in Mumbai, one of the mega cities in India, through
a sample of 1000 households selected from 8 zones. Nearly 50% of respondents
were ready to pay partially more than their current bill amounts. The authors
assumed that that consumers’ affordability, satisfaction about water supply services,
and their beliefs in service provider might influence positively on their WTP.
However, it was observed that with increasing level of satisfaction of the consumers,
the probability of WTP decreased. But the change in the probability value of higher
WTP due to change in satisfaction level was insignificant making this variable a
weak indicator of households’ WTP.
Recently, Casey et al (2006) conducted a CV survey of over 1600 residents in the
city of Manaus in Brazil to assess households’ willingness to pay for improved water
services collecting data on their current water needs, health concerns, and
socioeconomic characteristics. Six low-income communities in the eastern area of
Manaus were initially selected for conducting the survey and, households were
randomly selected for in-person survey within these communities. OLS regression
analysis indicated that residents were willing to pay between US$6.12 to US$8.67
per month for improved water services with household size, years living in the
house, employment status, monthly expenses for water outside the home, electricity
bill having positive impact on the WTP whereas income and age of the households
had negative impact on their WTP. The authors used four elicitation techniques to
calculate WTP: open-ended, open-ended with a pre-qualifying statement,
descending and ascending dichotomous choice bidding game. This was done to
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observe for any differences across these four elicitation formats to see if one or any
of them is resulting in significantly different WTP estimates. The open-ended and
augmented open-ended elicitation formats resulted in nearly identical mean WTP.
The descending bid dichotomous choice format gave the highest WTP and the
highest variance around the mean. When used as the dummy variable, this
elicitation format had statistically significant positive sign.
In open-ended direct question formats, respondents express their WTP for
alternative scenario (point estimates), which represents respondents’ maximum
willingness to allocate from income for deriving the same level of utility. No hint is
given to the respondents about the expected charge or expected worth of the
alternative options. Therefore, when the specific goods in question are being
provided ‘free’ or at least cost to them, they may have the difficulty to actually
express true economic value for the services. Consequently, this format is associated
with a large number of non-responses and ‘protests zero bids’. The term ‘protest
zero bids’ refers to a situation where a respondent indicates that his WTP is zero, not
because he has no value for the specific goods, but because he either objects to some
aspect of the survey; or he believes that no monetary value can be placed on the
good in question; or he has very low faith in the service provider’s ability to supply
the stated goods. The method is also associated with ‘strategic overstatements’
wherein the respondents may increase their WTP estimates deliberately so that
goods can be provided to them (NOAA 1993).
2.3.2 Conjoint ranking and paired comparison
In contingent ranking, several alternative options with different attributes (having
specific cost attribute) are presented to the respondents where respondents are
requested to rank these alternatives according to their preferences and ability to pay
(Roe et al. 1996). Thus a rank-wise preference structure can be obtained depending
upon respondents’ first or second choice with cost tag assigned to each of the
choices (Foster and Mourato 2002). In water supply sector, this technique has been
found to be quite useful especially in low-income areas by Coates et al. (2001) for
‘encouraging exchange of ideas between a water supply organization and community
groups’. Recently, Yang et al. (2006) have used conjoint ranking to evaluate
customers’ demand for alternative water supply system in three coastal towns in
southwestern Sri Lanka. They compared household preferences for four water
supply attributes – price, quantity, safety, and reliability for both poor and non poor
settlements. The authors reported that households possessed heterogeneous
preference structure for quantity, safety, and service options, but not the supply
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duration. It was also observed that households in poor settlements had
comparatively lower capacity to trade-off discretionary income for reliable services
than the non poor households.
Mycoo (1995) attempted to examine the major problems of water supply in urban
Trinidad analyzing factors influencing customers’ willingness to pay for water
service improvements in the early 1990s. The author conducted the survey in 1993
in the capital region of Trinidad using stratified cluster sampling dividing the
sampling into six smaller clusters using a sample size of 360 households. In this
study CVM, contingent ranking and revealed preference method were collectively
used to determine households’ WTP. Reliability, pressure, quality and price
variables were explained using payment card approach in the hypothetical choice.
Since the households were finding it difficult to attach a price to the various
attributes of water supply (reliability, pressure and quality), the contingent ranking
asked them to rank these attributed in the order of priority. Revealed preference
method was based on household’s production function approach. The regression
model indicated that household income, the price of water, number of service hours,
and housing and land tenure influenced positively on WTP amounts, whereas
expenditure on electricity was negatively correlated with increasing WTP.
In this study the application of conjoint ranking was only limited to ranking or
prioritizing the water supply attributes without actually estimating households’
WTP. Therefore, CV method was employed to estimate households’ WTP which
indicated that 80% of the sampled households were willing to pay twice the
currently charged price for a reliable supply. However, this was not validated by the
revealed preference estimates which resulted in lower bounds of value of a reliable
supply. This was explained by the fact that about 75% of the population had already
replicated a water storage and distribution system in their residences by purchasing
and installing tanks and water pumps. This study therefore, gives differing estimates
of customers’ value from revealed and stated preference techniques.
2.3.3 Discrete choice methods
The discrete choice methods for estimating WTP for improved water supply have
been widely employed in both developing and developed countries to determine
affordability and WTP for water and sanitation services (Whittington et al. 2002,
1993, 1992, 1991, 1990ab, Misra 1999, Griffin et al. 1995, Whittington and Swarna
1994, Altaf et al. 1993, McPhail 1993, Whittington and Lauria 1991, Briscoe et al.
1990). These methods have been further sub-divided into referendum contingent
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valuation or choice modelling depending upon the manners in which valuation
questions are posed to the respondents.
2.3.3a Referendum contingent valuation
The referendum CVM format is based on bid levels posed in different manner to the
respondents in the questionnaire – such as single bounded, double bounded or
multi-bounded. This format was introduced by Hoehn and Randall (1987) based
from the single-bounded dichotomous choice (DC) format earlier employed by
Bishop and Heberlin in 1979. This format presents the respondents with the
description of the good, and a single bid, or monetary value, which he may choose to
accept (‘yes’ vote) or reject (‘no’ vote) reflecting whether or not he supports the
provision of a specific good at the stated cost (Cameron and Quiggin 1994). The
single bid value is varied across the sample in the survey. The respondents
hypothetically weigh against their utility in ‘baseline scenario’ to that of utility under
the ‘improved alternative scenario’. These methods are viewed as producing a
hypothetical situation that is quite similar to actual market situations or actual
voting situations; and hence familiar to most individuals. The NOAA Panel on the
CVM recommended the DC referendum format as an appropriate elicitation method
in majority of circumstances (Arrow et al. 1993). However, one drawback of the
traditional DC and referendum formats is that they require the researcher to make
well-built postulation about the statistical distribution of respondents’ stated prices,
so that correct indirect utility function can be constructed to get consistent welfare
estimates (Ready et al. 1995, Mitchell and Carson 1989). This aspect can be met
better with large sample size and careful bid design. Carson et al. (1986) proposed
‘take it or leave it with follow-up’ format to overcome some of the drawbacks of the
traditional approach. In this method, if a respondent aggress to accept the
alternative scenario at the initial bid price, he is asked a follow-up WTP question
that uses a little higher price. On the other hand, the respondent may decline to
undertake the alternative scenario at the initial bid, in which case the follow-up
WTP question uses a lower price. This is very similar to iterative bidding game
which works like true purchasing scene in the market when a buyer tries to bargain
such as those in auction process (Mitchell and Carson 1989).
Whittington et al. (1991) observed that households’ perception of water supplied
from the local authority was generally unsatisfactory in Onitsha, Nigeria and this
resulted in their low willingness to pay. People perceived water quality from those
provided by the tanker trucks and water vendors better than those provided by the
public system. In the absence of reliable supply, households relied upon private
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water vendors. Annually, the payments made to the private vendors were more than
double the O & M cost of supplying water through a piped network. Whereas the
public utility was recovering 1100 US $ from supplying 1.5 MGD water, households
were spending about 28000 US $ to obtain 2.96 MGD from well-organized network
of private water vendors during the dry season. In their study, they found that
households were willing to pay ‘surprisingly high’ amount to secure a reliable
supply. The authors did not use rigorous sampling strategy due to the absence of
appropriate sampling frames; instead biding game approach was employed in a
rapid reconnaissance survey. The study was one of the first examples to show the
scale and magnitude of water vending activities in metropolitan areas of a
developing country. The authors conclude that, “the revenue potential of the public
authority is tremendous and that the population of Onitsha would be much better
served if the utility viewed itself as a regulated utility, not as an agency providing a
social service”.
Two Indian case studies in rural and urban setting can be cited which give different
policy outcomes. In one study in rural Kerala, Singh et al. (1993) used referendum
CVM to study the households’ preference for individual domestic connection with
better quality in comparison to shared yard tap. They observed that households
were willing to share the higher cost for domestic connection if ‘local credit’ facility
was available to them. Vaidya (1995) in a study from urban Baroda reported that 80
% of the households with individual connection were willing to pay 3 times higher
amounts than the current bill if better pressure and quality was ensured to them.
WTP declined with increasing income of the households – households with highest
income were willing to pay just 60% higher than the households with the lowest
income; thereby indicating ‘limited reach for cross subsidization’ across different
categories of the households. The Kerala study indicated that the ‘transferability of
findings from one site to another was likely to lead to erroneous predictions even if
site characteristics, service offered and community characteristics are apparently
alike’.
Asthana (1997) used a multinomial logit model to predict household’s choice of
water supply system (private pipe potable water; public standpost; handpump;
dugwell; surface water) in Bhopal. The in-house piped water supply was found to be
the most preferred alternative option. The perceptions of quality were important
determinants of the choice of water supply source for drinking purposes. The paper
concluded that rather than trying to provide a free or heavily subsidized minimum-
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service to all, the policy makers need to consider an improved service to all and
higher level of service to those who are willing to pay higher amounts.
According to Goldblatt (1999) an improved understanding of customers’ demand
and willingness to pay is not only imperative for financial sustainability of improved
water services, but also for enhanced extension to poorer sections of the urban
society. The author debates the usual effect of providing subsidized water services
without actually studying their demand and consumption pattern resulting into
utility’s decreasing revenue base and its inability to expand to poorer households. As
the author notes “those already with access to water will be paying below-cost prices
while the poorest of the poor households may be denied formal access completely.”
In a CV survey carried in greater Johannesburg in two informal settlements of
Vlakfontein and Finetown to study the water use behaviour of the households and to
study their WTP for improved water supplies, the study employed two controlled
hypothetical bidding approaches whereby households indicated their maximum
WTP for improved water supply scenarios. In the first approach, ‘volumetric bids’
were used in terms of cost per 25 liters of water varied through the sample and the
final amount selected as the maximum WTP. The second bidding approach called as
‘monthly bid’ asked households their maximum monthly water bill as maximum
WTP assigning different low or high starting points selected randomly. This was
done first, to minimize the starting point bias widely cited in the literature, and
second, to later compare the volumetric WTP with the monthly bill based upon the
consumption details provided by the respondents. No parametric models were used;
instead the bids and consumption levels were used to calculate the WTP amounts.
According to the study, Utility’s monthly revenue can be estimated keeping in mind
three attributes – (i) total percentage of households who agree to connect at the
specified price levels, (ii) price of water, and (iii) monthly water consumption. The
results showed that 64% of the households would pay for a reliable piped water
supply if the total monthly bill were 5% of income or below it testifying the
conventional five per cent rule. Volumetric bids and monthly bids yielded similar
results.
Koss and Khawaja (2001) measured customers’ valuation of water supply reliability
using the referendum CV technique. Respondents were asked to indicate their WTP
in order to avoid the occurrence of water shortages of a given frequency and
severity. The authors employed a double bounded dichotomous choice biding game
strategy. The results indicated that customers were willing to pay as much as
$16.92/month to avoid a 50% water shortage occurring over 20 years.
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Whittington et al. (2002) examined household’s demand for improved services in
Kathmandu, Nepal through a randomly selected sample of 1500 households. The
objective was to study the preference for water supply from a private operator or
from existing public water supplier. The valuation section had one CV scenario with
different market segments depending upon the existing supply situation.
Households were presented with one of the eight different prices. The data was
modeled econometrically through discrete choice binomial logit model with linear
utility function. The results indicated that about 70% of the households in 5
municipalities were willing to pay a fivefold increase in the current average water
bill in addition to supporting improved services provided by a private supplier. The
study observed that both poor and non-poor segments of the population were
willing to support privatization plan that would improve water supply.
In a study from rural Bangladesh, Water and Sanitation Program, South Asia (WSP
2002) observed that households place higher value on safe drinking water free from
arsenic in arsenic-affected areas. The demand increased with higher income, and
decreased with higher price quoted for piped water supply. The results also
indicated that the higher the awareness and concern for arsenic contamination, the
greater is the inclination to opt for domestic piped water connections. In particular,
the mean WTP for recurring costs for standposts was 46% higher than the actual
costs, whereas it was 40% higher for domestic connections.
Salman and Emad Al-Karablieh (2004) estimated the willingness of farmers to pay
for groundwater resources under different conditions of water supply regimes using
referendum format. The results showed that the water values in the region were
undervalued as farmers were willing to pay 2.5 times extra than the current price of
groundwater. This finding suggested that decision makers can impose a price level
for groundwater from US$ 0.14 to 0.35/m3 corresponding to farmers’ WTP without
having any impact on the cropping pattern or the planted area. Information
available on water supplies, areas under irrigation and market conditions were the
basis of the calculations. The findings also indicated that there was potential to
decrease water consumption and reallocate it in an optimal way to increase the net
agricultural income in the study area.
Ntengwe (2004) examined the role played by consumer awareness in their
willingness to pay for water supply in two cities in Zambia using referendum design.
Survey conducted in Kitwe and Lusaka revealed that level of awareness, WTP and
cost recovery all varied directly. Whereas awareness might increase consumers’
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WTP assisting service provider’s cost recovery, the research also revealed that
factors such as ability to pay, affordability of bills, quality of water and of the service
provided, as well as good business-consumer relations were important factors
affecting a utility’s ability to recover its costs.
Hensher et al. (2004) assessed household’s WTP to avoid outages (defined in terms
of frequency, timing, and duration) and information (defined in terms of
notification of interruption and telephone response to queries) for water supply and
disposal, in Canberra, Australia. They used a series of conditional logit and mixed
logit models. They observed that people were willing to pay affirmatively higher
amounts to secure less frequently interrupted water supply.
Gloria Soto Montes de Oca et al (2005) estimated willingness to pay for maintained
and improved water services using CV method testing two scenarios in three
residential areas in Mexico city in a split sample on 1424 households, one to
maintain and another to improve the service conditions using probit regression
model. Both the scenarios described the threat of water shortages over the next
decade offering differential benefits to the respondents. The ‘maintenance scenario’
was designed to ensure that the current service levels would be maintained whereas
the ‘improvement scenario’ presented additional reliability improvements. The
elicitation format was typical referendum styled where households were presented
with single bid price selected randomly from ten values to be accepted or rejected.
The WTP question used the referendum format, which presented the respondent
with a single buying price, which was accepted or rejected. Water shortages, water
pressure and water quality were considered as three major attributes to estimate the
service quality standards. The mean differences between the two scenarios were
found to be significant indicating that households were willing to pay more for
improved scenario than the maintenance scenario if income distribution was
ignored. The authors argue that apprehensions on the ability of the poor to pay for
the improved services are justifiable, and reasonable water pricing needed to reflect
the income constraints of poor people further justifying the use of differentiated
water prices between rich and poor segments of the society.
About 10,000 consumers were surveyed to assess coping costs and preferences for
improved water supply services in the Greater Bangalore, where there is currently a
water deficit estimated at about 60% of the demand (WSP 2005). Coping strategies
include private bore wells, sumps and overhead tanks to manage irregular and
inadequate supplies; booster pumps to cope with low pressure; use of storage
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TERI University Ph.D. Thesis, 2006
mechanisms, like earthen pots, small tanks and buckets by low income/poor
households; purchase from vendors and purchase of bottled water; time spent in
queuing up for water collection; use of filter or boiled water etc. Most non-domestic
consumers have their own borewell or purchase water from vendors. The average
coping cost for households is about Rs 24/m3, varying from Rs 3/m3 for high-rise
flats to Rs 13/m3 for low-income group plotted houses, and Rs 7/m3 in slum areas.
According to the study, the expected O&M cost of the upcoming water supply and
sewerage extension project is estimated at Rs 16/m3 suggesting that it would
generate significant savings. A detailed econometric analysis of the survey data was
also carried out to estimate the consumers’ WTP for improved WSS services. Among
household categories, WTP is about Rs 16/m3 for high-rise flats, between Rs 10 and
12/ m3 for low-income group plotted houses and between Rs 7 and 10/m3 for slum
households.
In all the studies cited above one or the other from of referendum bidding game is
employed. It emerges from the review that researchers using bidding game
approach outnumber those using other elicitation formats. Following justification is
given in the literature in support of the bidding game elicitation format:
(i) This format is more familiar to most respondents as they do bargaining
for a marketed good so they emulate true purchasing scene (Bateman et
al. 2002).
(ii) It is less prone to strategic and hypothetical bias (Carson et al. 2000).
The NOAA Panel also favoured dichotomous choice iterative bidding
game over other formats as an appropriate elicitation method (Arrow et
al. 1993).
(iii) The process of bidding helps the respondents to understand the value of
the goods in terms of ‘utility’ better with times to respond (Hoehn and
Randall 1987) and thus it is possible to clearly bring out the respondent’s
maximum WTP with more precise range than that of open ended CV
questions (Cummings et al. 1986).
(iv) It gives more precise estimates of WTP because of lower standard
deviation around mean WTP. According to Chowdhury (1999) the
advantage of iterative bidding games, is that answers often have a lower
standard deviation around the mean as compared with single bid games.
He chose bidding game format to study WTP for improved water supply
in Dhaka’s urban poor settlements because it worked better than direct
and open-ended elicitation formats.
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(v) The approach is more participatory in nature than the other elicitation
formats.
However, there might be a small problem of starting the bid with the specific
amount, i.e. respondents may get overly or unjustifiably influenced by the starting
bid amount. For example, if the first bid is excessively higher than the expected
WTP of the respondents, the last selected bid will be higher than the true WTP.
Similarly, if starting bid is much less than the expected WTP of the respondents, the
last selected bid will be lower than the true WTP (Roberts et al. 1985). This may be
taken care of by actually calculating the cost of the alternate scenario and reflecting
these costs either in ascending or descending order so that respondents’ stated
maximum WTP from bidding game may lie in the range of the actual costs
previously estimated.
2.3.3b Choice modelling
Choice experiments or choice modelling are multi-attribute stated preference
techniques that which also belong to the family of stated preference method (Ryan
and Wordsworth 2000, Hanley et al. 2001, Adamowicz et al. 1998). This theoretical
construct has been the main starting point for modelling choices in several
applications, such as: transportation (Ben-Akiva and Lerman 1985), marketing
(Louviere 1995, Louviere et al. 2000), energy supply (Goett et al. 2000) and
environmental economics (Boxall et al. 1996). A summary of environmental
applications is given in Hanley et al. (2000). However, there are relatively few
studies that have used choice experiment models to evaluate the service
performance of water companies and customer preferences for attributes of water
supply and quality (Haider and Rasid 2002, Willis et al. 2005, Jalan et al. 2005,
MacDonald et al. 2005). In choice modelling, levels of water service improvements
are valued by their ‘attributes’ and customers are asked to choose between two, or
more than two scenarios having specific attribute bundles (Bennett and Blamey
2001). Price remains the most important attribute and it differs through the
scenario. Having different price levels across the scenarios helps to estimate
marginal utility estimates calculated from choice models which represents social
welfare (Hanley et al. 2005, Train 2003, Hanley et al. 1998). Therefore, choice
modeling approaches allow a more direct route to the valuation of the attributes
(characteristics of the goods), and their marginal changes rather than complete
value of the goods in totality (Bateman et al. 2002). This would mean that the
method would be preferred than the contingent valuation in contexts where it is
necessary to value individual attributes of the goods in question.
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Haider and Rashid (2002) employed discrete choice experiment using a simple
conditional logit model to investigate customer preferences for variations in two
attributes: water pressure and water taste both expressed qualitatively as ‘worse,
same, improved’ in relation to a percentage change in water prices in Thunder Bay,
Ontario. The respondents were asked to choose between different combinations of
water prices, water pressure, and water taste for three alternative sources of water
supply. The survey results suggested that pressure and taste were very important
variable for improved water supply irrespective of the water rates. The questionnaire
had two distinct component in this study: (a) questions relating to important
variables that were responsible for choice of alternate water supply such as water
use, daily consumption of potable water, adoption of water conservation measures,
quality and overall inconvenience (b) set of discrete choice experiments which
presented three alternate sources of water supply. Each of these alternatives
consisted of three attributes having three attribute levels. The households were
asked to choose one of the three options based upon their comparative evaluation of
attribute levels associated with each of the alternatives.
Realizing that very few (one or two percent) respondents had actually suffered any
water service failure over the preceding year, Willis et al. (2005) presented the
respondents with 14 attributes (called as service factors (SF) in the paper) which
changed across all customers in UK. The large number of SFs meant that the 14 SFs
had to be blocked into 5 groups of 3 or 4 SFs to avoid cognitive limitations on
respondents’ ability to simultaneously trade-off large numbers of SFs. The ‘main
block’ permitted customers to trade-off some principal factors in water supply and
quality with wastewater disposal factors; whilst the other blocks investigated
consumers’ marginal rates of substitution (MRS) between different water supply
and quality factors, and wastewater factors. The valuation encompassed use, option,
nonuse, and altruistic utility: that is, the benefit each customer directly derives from
consumption of the SF (use value); the individual’s assessment of the option value of
the SF; the benefit customer derives from knowing that the SF is being improved
even though as a customer may not have been directly affected by it (nonuse value);
and the utility the customer receives from knowing that other customers would
benefit from the SF improvement (altruistic value). The stated choice analysis
estimated the MRS for each SF, and MRS for money. The implicit monetary benefit
of changes in each SF level, or WTP was determined by the ratio of these MRS:
between SFs and money.
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Jalan et al. (2005) estimated WTP for clean water from a multinomial logit model
from a sample of households in Delhi where a household had different choice
available including no purification option. They observed that on an average,
households were willing to pay Rs 25 per month extra for clean drinking water. The
WTP of the richest households were almost twice than that of the poorest
households. Further, increasing the levels of education from illiterate to
matriculation resulted in doubling of expected WTP. Therefore, effect of education
was similar to the wealth effects. The authors studied the impact of different source
of awareness with respect to wealth effects to find out how awareness was impacting
on households’ behaviour towards adopting clean and safe drinking water measures.
The three determinant sources of awareness were – episodes of diarrheal sickness,
exposure to medium of mass communication such as radio, tv, newspaper ads, and
formal schooling.
MacDonald et al. (2005) have used choice modelling approach to highlight the
importance of objective methodologies in standard setting as well as to evaluate
incremental changes in the customer service standards of urban water supply in
Adelaide. They have used ‘water bills’ and ‘frequency of future supply interruptions’
as two important attributes to estimate the implict price of better water supply that
is more reliable using multinomial logit (MNL) and random parameters logit (RPL)
models. The attributes were described in terms of duration of interruption,
frequency of anticipated interruption, communication about interruption (phone
call/knock on door), alternative supply (central location/bottled water) and price
changes. They noted that customers were willing to pay to reduce the frequency and
duration of water interruption depending on the number of interruptions that a
customer faces each year. The households were willing to pay higher amounts for a
water supply that was less frequently interrupted and hence more reliable. In
explaining this positive WTP of households, two variables had no influence on
increasing their WTP. They were – (i) provision of an alternate supply during an
interruption, and (ii) advance notice of interruption or service failure by the utility.
This employs that even if an alternate arrangement of supply were made during a
service failure, or households were told in advance about interruption, their WTP for
a reliable supply would remain same; thereby indicating higher value attached to a
reliable water supply system.
When using the stated preference techniques, the main choice is between using
referendum contingent valuation and choice modelling. According to Bateman et al.
(2002) not all choice modelling techniques are consistent with underlying welfare
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theory; also convincing evidence has not come so far on their superiority over
contingent valuation. However, choice modelling may do better if information is
required on relative values for different attributes of an environmental good (Foster
and Mourato 2003). To study the effectiveness of EU new Water Framework
Directive, Hanley et al. (2005) used choice modelling using mixed logit model to
assess if valuation is sensitive to the bid levels used in bidding game elicitation. They
observed non-significant impact of changing price vector on estimating households’
preference and WTP.
In the stated preference literature cited above, there are basically two steps in
obtaining welfare measure: the estimation step in which one gets parameter
estimates, and the calculation step when the welfare measure is calculated given the
parameters. Discrete choice data is statistically fitted in a specified probability
function and then welfare measures corresponding to the mean and the median
WTP values are computed. However, such measures are sensitive to the distribution
assumption (Carson et al. 1994). WTP when derived from CV studies is random for
several reasons. Frequently, it is a function of a random component of preferences
which is known to the respondent but not to the researcher. When WTP is computed
from the CV survey, same estimated parameters are used, infusing another source of
randomness. Researchers wish to estimate a sample mean WTP because it is a
logical step in the expansion of benefits to the population. The error distribution can
be specified as some parametric form, and the model can be estimated by maximum
likelihood technique (Hanemann and Kanninen 1999). There are also other flexible
formulations and non-parametric methods which can provide alternative fitting of
the observed data dropping scope for some of the biases (Creel and Loomis 1997).
Three types of formulations are generally discussed in the literature to estimate the
welfare change form WTP studies: (i) Parametric forms (for e.g., Logit, Probit,
Weibull), (ii) Semi-parametric forms (for e.g., Ayer’s and Turnbull’s estimators,
Smoothed Maximum Score (SMS) estimators), and (iii) Non-parametric forms (e.g.,
MSCORE, NPREG). Non-parametric treatment of discrete choice CV deals with
estimating WTP from without the constraint of a given distribution for the
unobserved component of preferences (Haab and McConnel 1997, Creel and Loomis
1997, Carson et al. 1994, Kriström 1990, Cosslett 1983, Turnbull 1976). They allow
only limited or no explanation of the effects of covariates. Therefore, despite of
methodological simplicity, they do not permit integration of explanatory variables in
explaining household’s WTP (Kriström 1990, Carson et al. 1994). While the model is
distribution free, there are many cases when the distribution or the functional form
can have a substantial effect on the estimates of WTP (Salvador and Leandro 2001).
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TERI University Ph.D. Thesis, 2006
Similarly, even though semi-parametric formulations have the advantage of having
more ‘flexible assumption of the true distribution’ observed in the data and allow
inclusion of covariates including the bid levels into the specification, they are
encountered with methodological pitfalls such as failure to provide ‘exact inference
for the predictive probability conditional on a particular observation of the
covariates’ (An 2000, Lewbel and McFadden 1997, Li 1996), misspecification errors
when homoschedasticity and unimodality assumptions do not hold for the collected
data (Chen and Randall 1997, Horowitz 1993). When the pattern of responses is well
behaved, the estimates of WTP will not be especially sensitive to the choice of
distribution assumption for the unobserved random component of preferences, or
for the functional form of the preferences function. Simple parametric formulations
such as logit and probit estimates gives better ‘estimate of the variance of the error
term’ when customers are sure about their choice and preference structure (Li and
Mattson 1995).
Bohara et al. (2001) examined the performance of three alternative distributional
assumptions – normal, lognormal and Weibull in estimating WTP. The normal
distribution provided unbiased and relatively accurate estimates of WTP,
irrespective of the proportion of the population holding negative WTP. According to
the authors, when a relatively small proportion (about 2%) holds negative values,
the lognormal and Weibull give inferior estimates, but they are still reasonably
accurate. As the proportion of the population with negative WTP increases to 14%,
the Weibull, and especially log-normal, distributions give positively biased estimates
of WTP, and appear to have no statistical advantage over the normal model. When
the proportion of the population with negative WTP increases from 14 to 30%, the
use of the lognormal and Weibull become increasingly untenable. They both begin
to grossly overestimate WTP. According to the authors, the Weibull or lognormal
models never out-perform the normal model. They further extended the simulation
to investigate the performance of mixture models of the lognormal and Weibull
distribution. Although mixture modelling decreases bias and reduces errors
compared to the standard models, it fails to out-perform the standard use of the
normal distribution, especially when 30% hold negative WTP values.
2.4 Comparison of stated and revealed preference methods
Stated preference methods can be used to cover a wider range of attribute levels for
the proposed ‘quality’ or ‘quantity’ changes of a good whereas revealed preference
data fails to provide any information about attribute trade-offs (Swait et al. 1994).
Stated preference methods are commonly criticized because the households’
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TERI University Ph.D. Thesis, 2006
behavior they represent may not be actually observed due to several biases (Mitchell
and Carson 1989, Cummings et al. 1986) and their failure to incorporate real market
constraints (Louviere et al. 2000). However, these methods offer the only means for
estimating the value of goods that have no proxy or surrogate markets. There is a
strong case for using revealed preference techniques whenever the relevant
willingness to pay information can be inferred from households’ actual decisions
(Bateman et al. 2002) as decisions actually made in the markets are inferred as
consistent indicator of preference. However, stated preference techniques become
indispensable when the WTP information that is required cannot be inferred from
the markets. On the other hand, revealed preference approaches have to rely on
information from markets for proxy private goods, consumption of which is a
prerequisite for benefiting from the goods in question. Stated preference approaches
may therefore score better over revealed preference approaches. The scope of stated
preference techniques is wider in the sense that they can potentially value all
impacts, both use and non-use values (Bishop et al. 1997).
In literature, comparison of estimates derived from stated and revealed preference
methods are quite common, which is termed as ‘convergent validity test’. Several
researchers have questioned the convergent validity test as they were getting
different value estimates from stated and revealed preference methods (Urama and
Hodge 2006, Bishop 2003, Hanley et al. 2003b, Carson et al. 1996, Mycoo 1995).
Carson et al. (1996) examined the relationship between contingent and revealed
preferences values from 83 studies that estimated the same environmental
amenities. The ratios of contingent values to revealed preference values in these
studies averaged 0.89 with a 95 percent confidence interval of 0.81 – 0.96.
Additional statistical tests confirmed the robustness of this result and the validity of
the approaches involved in the comparisons (Bishop 2003). But some researchers
failed construct validity tests to arrive at similar revealed and stated preference
values (Diamond 1996, Mycoo 1995, Hausman 1993, Diamond and Hausman 1994,
McFadden 1994). The conclusions of Diamond and Hausman (1993, p.4) were
typical of the group: “we conclude that the CV method does not measure an
economic value that conforms with economic preference concept. Thus, we also
conclude that it is not appropriate to include CV measures of stated WTP in either
benefit-cost analysis or compensatory damage measurement”. According to Bishop
(2003), these arguments were not convincing (p. 553) and reason for construct
validity failure was rooted in content validity failures. By computing the indirect
costs incurred by the customers to compensate for the intermittent, irregular, and
unpredictable water supply in Delhi, Zérah (2001) contributed to the ongoing
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TERI University Ph.D. Thesis, 2006
debate on moving to demand-oriented service delivery that addressed the
customers’ needs and their ability to pay for a reliable service. However, no
modelling assessment or behaviour of customers relating to their WTP was done;
instead the implicit cost of water supply unreliability was inferred as their indirect
WTP which was expressed through revealed preference data. Davis (2004) engaged
4 different techniques (a household, “intercept” and telephone survey, and a
sequence of focus group discussions) to estimate households willingness to pay for
better water supply in Odessa, Ukraine. The author observed that a particular data
collection technique can have different outcome, in particular, “social desirability
and time pressures can bias the results obtained in demand-assessment research
and lead to substantively different conclusions and policy recommendations”.
Recently, Urama and Hodge (2006) studied the convergence of stated and revealed
preferences data through two separate experiments conducted in southeastern
Nigeria. They compared irrigators’ stated WTP to mitigate soil and water pollution
problems in their farms with the actual expenditure from revealed preference data
to mitigate the same pollution problems for a river basin restoration scheme. The
authors state that, “we found that the farmers’ stated and revealed preferences were
significantly correlated but yielded significantly different means at 5% level. While
econometric analysis reveals a systematic association between key socioeconomic
variables and farmers’ stated WTP, lending credence to the CVM within its
theoretical framework, analysis of the qualitative follow-ups reveals inconsistencies
in some farmers’ stated and revealed preferences that cannot be satisfactorily
explained on the basis of economic theory alone.” They attributed this behaviour to
farmers’ lack of awareness about the problem, information complexity, risk
aversion, and peer pressure which limit their decision making ability.
Despite prevailing disagreement on accuracy of revealed preference as a true welfare
measure, the estimation of WTP from stated preference technique gives
conceptually convincing yet conservative estimates of actual benefits and costs
derived from improvements in environmental quality. Even though these methods
suffer from a number of problems, their appeal is that they examine customers’
behaviour in actual economic markets related to the provision of goods in question,
as well as establish a hypothetical market for that good by the survey instruments.
The participatory feature of decision-making is clearer in stated preference
techniques where households’ attitudes, motivation, preference and WTP are
assessed which are otherwise omitted in revealed preference studies (Bateman et al.
2002).
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TERI University Ph.D. Thesis, 2006
Table 2.1 Some major case studies in water supply sector with goods being valued and signs of major explanatory variables Study area with goods being valued
Method of estimation Important variables and their sign with respect to preference and/or WTP
Reference
Ukanda, Kenya; Value of ‘time’ to collect water and households’ preference for water supply options amongst wells, kiosks, and vendors
Revealed preferences, and discrete choice modelling to study the households’ preference of different water systems through conditional multinomial logit model
Time savings (+), price of water charged by the vendor (–), taste (–), income, women (+), education (+)
Whittington et al. 1990c
Onitsha, Nigeria; Preference for securing a reliable water supply as against water secured from vendors and unreliable supply from the local authority
Rapid reconnaissance survey using bidding game, surveys could not be carried out as per strict contingent valuation approach due to absence of well defined sample frames
Quality of water (+), price (–)
Whittington et al. 1991
Trinidad; Customers’ willingness to pay for water service improvements
CVM, contingent ranking and revealed preference method using stratified cluster sampling and OLS regression. Reliability, pressure, quality and price vectors were explained using payment card approach in the hypothetical choice
Income (+), price of water (+), number of service hours (+), housing and land tenure (+), expenditure on electricity (−)
Mycoo M 1995
Vlakfontein and Finetown, Greater Johannesburg; Demand and willingness to pay for improved water supplies in informal settlements
CV study employed two hypothetical bidding processes where households indicated their WTP for improved water supply scenarios - Volumetric bids and monthly bids, distribution of bid amounts was used to estimate WTP
Utility’s monthly revenue can be estimated keeping in mind three attributes – (i) total percentage of households who agree to connect at the specified price levels, (ii) price of water, and (iii) monthly water consumption levels.
Goldblatt M 1999
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TERI University Ph.D. Thesis, 2006
Mexico city; Willingness to pay for maintained and improved water services
CV method testing two scenarios in three residential areas in a split sample, one to maintain and another to improve the service conditions using probit regression model
Income (+), bid amount (–), knowledge of the water bill, water bill (–), water quality (–), family members (+)
Gloria Soto Montes de Oca et al 2005
Manaus, Amazonas, Brazil; Willingness to pay for improved water services
CV experiment using OLS regression through four elicitation techniques: open-ended, open-ended with a pre-qualifying statement, descending and ascending dichotomous choice bidding game on a randomly selected households
Income (–), Age (–), household size (+), energy bill (+), water expenditure (+), owned house (+)
Casey et al 2006
Kanye in southern Botswana; Willingness to pay for private water connection
CV approach through iterative bidding game from randomly selected households
Household income (+), level of education (+), employment status of the head of the household (+) and level of consumers’ awareness (+)
Mbata J N 2006
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Table 2.2 Summary of case studies using CVM in water supply sector with different
options and prices
Study area with number of options
Sequencing of scenarios and eliciting procedures
Reference(s)
Anambra State in Nigeria. Public taps and private connections.
1 – described public taps, asked to bid. 2 – described private connections, asked to bid on unlimited quantity of water for fixed rate.
Whittington et al. 1990b
Willingness to pay for Water in Onitsha, Nigeria
Rapid reconnaissance survey of private water vendors and households’ willingness to pay for improved level of services, survey could not follow strict protocols, sample frames could not be constructed appropriately, valuation through bidding game procedure
Whittington et al. 1991
Improved Sanitation Services in Kumasi, Ghana
Two improved scenarios – water closets and a latrine connected to the city sewer systems, on 1200 randomly selected households
Whittington et al. 1993
Kerala, India. CVM to determine demand for piped connections
Two samples. Households with connections asked if they were willing to pay higher tariffs. Others were asked willingness to pay for connection and monthly charges. Yes/no type answers for quoted bid levels
Griffin et al. 1995
Willingness to pay for four water supply options in small towns in Uganda
Describe each option, setting out the institutional environment and a fixed capital cost contribution for each option. Options are described simultaneously. Then respondents are asked referendum style questions for O&M contribution for all four options starting with the most expensive option.
Nostrand 1997
Jakarta, Indonesia. One water supply option to determine value of piped water option only.
1 – asked whether wanted a connection based on three types of charges. 2 – offered connection charge in installments plus monthly charge for ordinary water quality. 3 – offered connection charge in installments plus monthly charge for better quality water. 4 – offered real water authorities connection and monthly rates. All yes/no answers. 5 – repeated the above but with reverse ordering of all questions.
McGranahan et al. 1997
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Small towns water supply in Uganda. Two options with two payment methods. Option 1a – Public taps by jerry can. 1b – Public taps fixed monthly charge. 2 – Private connection with various public taps prices.
1 – Each option was described and bids elicited for paying by jerry can 2- Bids elicited for monthly metered charge 3 – Respondents asked to choose between monthly charge for private connection or pay by jerry can at taps (various prices). No lowering or raising of bids
Whittington et al. 1998
Estimation of demand and willingness to pay for improved water supplies in two informal settlements in Johannesburg
Done through two different bidding games in which respondents indicate whether they would be willing to pay specified amounts differing across samples. The final amount arrived at via this process was referred to as the ‘volumetric bid’ or ‘monthly bid’
Goldblat 1999
Dar es Salaam, Tanzania. Two Water Supply options – Piped connection or public kiosks.
1 – both options described in detail. Respondents asked to select preferred option. Split sample bidding on chosen option only.
Wedgwood 2000
Mombasa, Kenya. Six water supply option to three different market segments
High starting point bids for assessing demand for each option
Njiru and Sansom 2000
Bushenyi, Uganda. Five Water Supply Options
1 – All five options described in detail, respondents chooses one without knowing exact price but knows relative prices. 2 – Various bidding techniques on preferred option. 3 – Respondents allowed to choose option (not obligatory), bidding takes place.
Wedgwood et al. 2001
Kathmandu, Nepal. One main CV scenario with different market segments depending on existing supply.
Respondents were asked specific amounts to connect to the water supply scheme. Eight different prices were used in the questionnaire varied across households, only one price per household, no bidding
Whittington et al. 2002
Willingness to pay for improved water
Administration of two scenarios through a split sampling procedure: The first scenario
Gloria et al. 2005
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supplies in Mexico City for two supply options concerning risk of water shortfalls and quality
(maintenance scenario) was presented to the respondents that would avoid the risk of shortfall and ensure current service level would be maintained. The second scenario (improvement scenario) would avoid this risk of shortfall as well as improve the service conditions. The WTP question employed referendum format, which presented the respondent with a single buying price selected randomly from ten values, which was accepted or rejected.
2.5 Bias1 in WTP studies: construction and specification of the
contingent market
WTP responses from the stated preference techniques are going to remain
hypothetical and there is always a risk of bias, size and direction of which may not
be all so easy to determine (Bateman et al. 2002). Misleading answers by the
respondents introduce bias in the survey that compromises the validity and
consistency of the welfare estimates (Cummings et al. 1995, Diamond and Hausman
1994, Neill et al. 1994). The CVM has been criticized in the literature for context
effects, framing effects and embedding effects mainly resulting into various types of
biases such as strategic bias, hypothetical bias, compliance bias, information bias,
and scenario mis-specification bias. According to Whittington (2004), three main
ways may result in bias during the CV survey: (i) background information in the CV
scenario is poorly and inaccurately provided; (ii) the description of the hypothetical
market is not done in a plausible manner, and (iii) complex referendum elicitation
formats and split-sample experiments. In the literature, several ways have been
devised to reduce the bias and extent of estimation inconsistencies through survey
design and implementation. There are few CV studies on evidence of accuracy in
developing countries as compared to what exists in developed countries
(Whittington et al. 2002).
1 Biased responses are defined as those final WTP values that differ systematically from the ‘true’ values placed by respondents on the good in question.
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Table 2.3 Frequently cited biases in CV with examples from case studies Bias-type Description References Strategic bias Respondent deliberately expresses his WTP
amount to influence the decision to provide the goods resulting in under-representation or over-representation of the true WTP. Therefore he gets maximum share of ‘consumer surplus’ by being ensured provision of the good at a less price than he would actually be willing to pay.
Johannesson 1996, Mitchell and Carson 1989
It depends upon how meaningful CV scenario is described to the respondents. Bias is substantially reduced ‘if careful attention is paid to making the valuation scenario realistic.’
Jones-Lee 1989, Milon 1989, Groves 1973, Clarke 1971, Groves and Ledyard 1977, Smith 1979, Rowe et al. 1980, Bohm 1972, Brookshire et al. 1976
Discrete questionnaires can reduce the incentive for strategic bias.
Carson 1991, Mitchell and Carson 1989
Overall, empirical evidence suggests only weak forms of strategic bias occur
Morrison et al. 1996
The WTP question based on referendum style, which presents the respondent with a single bid price to be accepted or rejected, minimizes strategic bias and it is incentive compatible.
Bateman et al. 2005, Carson et al. 2000, Hoehn and Randall 1987
Hypothetical bias
Attitude-behaviour difference – respondents systematically overestimate their WTP in many CV studies due to their ‘hypothetical nature’. Cited as biggest drawback in the literature resulting in significant different welfare estimates between an individual’s stated WTP and his true WTP. In general, revealed WTP actually in the market when goods are provided may be less than the committed WTP during the survey.
Cummings and Taylor 1999, Johannesson 1996, Diamond and Hausman 1993
“a single purchase of an unfamiliar commodity represents a guess as to what the commodity might be worth, rather than an evaluation based on experience”
Diamond and Hausman 1993
Respondents have no underlying information or preference upon which to base their decision concerning goods’ value to them. Therefore, hypothetical bias is highly likely because it is rational for respondents to overstate their WTP values
Harrison and Rutström 1999, Seip and Strand 1991, Duffield and Patterson 1992, Loomis et al. 1994, Neill 1995, Cummings et al. 1995,
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Bias-type Description References in a hypothetical scenario Brown et al. 1996, Fox et
al. 1998 “Respondents must be reminded of his
budget constraint; otherwise, he may exaggerate the value that he places on the hypothetical good”
Cropper and Oates 1992
Non-commitment – intention and behaviour is cross-checked when the customers are actually provided with the goods and services. “Survey responses do not require the same level of financial commitment as a ‘real’ purchase done in the market”.
Kemp and Maxwell 1993, Bishop and Heberlein 1986
Some of the studies could not find any convincing evidence of significant hypothetical bias. Particularly, it is difficult to attribute discrepancies between responses to hypothetical and real valuation questions to hypothetical bias alone, as combination of factors may be at work.
Brookshire and Coursey 1987, Dickie et al. 1987, Smith and Mansfield 1997
“problems due to the hypothetical nature of CVM questions arise more frequently and are more serious when the choices are between goods with which people are not familiar”
Chowdhury 1999
Compliance bias
Respondent tries to fulfill his perceived expectations of the interviewer or the purpose of the study unconsciously or consciously, i.e. they give responses which they believe the interviewers are looking for.
Mitchell and Carson 1989
This bias can be reduced by taking care not to provide respondents with any additional instructions beyond those that are carefully prepared in advance and given to all.
The extent of these types of biases will depend in part on whether or not the method for eliciting individuals’ true preferences is “incentive-compatible”. A demand revelation method is incentive-compatible if it creates a situation where it is in the individual’s best interests to reveal his true preferences for the good, and he will not be tempted to engage in free-riding behaviour.
Griffin et al. 1995, Mitchell and Carson 1989
Information Similar to the hypothetical bias. The WTP Loomis et al. 2000
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TERI University Ph.D. Thesis, 2006
Bias-type Description References bias estimates will depend upon how much and
what type of information is presented to the respondents in the description of the hypothetical non-market scenario.
Reduced variations in the results of final bids with increasing information
Pearce and Morgan 1994
Elements of a hypothetical scenario such as the payment vehicle and the amount of information provided to the respondents influence WTP values, since respondents are not valuing an abstract amenity, but a policy package.
Arrow 1986, Kahneman 1986, Randall 1986
Effect of information bias is very less compared to the other forms of bias.
Mitchell and Carson 1989
Scenario misspecification bias
Such biases can be a problem if the respondent perceives some aspect of the contingent market incorrectly. This bias may stem from either theoretical or methodological problems.
Loomis et al. 1996
Theoretical misspecification bias occurs if the scenario described by the researcher is incorrect from a theoretical standpoint or is contrary to established facts. In such a case, although the respondent may understand the presented scenario perfectly, his indicated WTP values are not valid
Mitchell and Carson 1989
Methodological misspecification occurs when some aspect of the contingent market is inadequately described, and thus respondent perceives the scenario in a different way unintended by the researcher
Cooper 1997
Elements of the hypothetical scenario that may be misinterpreted include descriptions of risk, the payment vehicle, and the implied budget constraint
Mitchell and Carson 1989
Giving respondents more time to think about their responses leads to a lowering of bids
Whittington et al. 1993
Non-response bias
Sample non-response leads to inconsistent welfare estimates and a vague mean WTP presenting a vexing problem in the CV studies
Seung-Hoon Yoo and Hee-Jong Yang 2001, Schuman 1996, Whitehead et al. 1993, Mattsson and Li 1994, Whitehead 1994
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2.6 Conclusion: synthesizing common thread
The review has seen that most applications in the literature involve creative
blending of theory with the application to an empirical framework in diverse
situations using either revealed or stated preference techniques. It emerges from the
review that site and purpose-specific situations are crucial in the choice of a
particular valuation technique. Even though revealed preference methods reflect
real choices and take into account various constraints on households’ decisions,
such as market imperfections, budgets and time, they fail to provide the value of
changes in the quality or quantity provided by the policy change in the provision of
the good (Louviere et al. 2000). The improvement in service conditions of an
environmental good can be better estimated directly from stated preference
techniques, which are estimated from assessing customers’ choice through
administering specially designed questionnaires (Hensher et al. 2005, Louviere et
al. 2000). These techniques have emerged as the most widely used methods to
estimate customer’s preferences for non-market goods that have no well-defined
market price or market is imperfect or incomplete2. Several researchers have
effectively implemented the outcome of stated preference studies to design
appropriate public policy to determine affordability and WTP affecting water service
improvements and the price levels to achieve them (Mbata 2006, Casey et al. 2006,
Gloria et al. 2005, Ntengwe 2004, Davis 2004, Whittington et al. 2002, 1990ab,
1991, Goldblatt 1999, Asthana 1997, Griffin et al. 1995, McPhail 1993, Altaf et al.
1993). More advanced and recent studies are those by MacDonald et al. (2005),
Willis et al. (2005), Ahmad et al. (2005) and Hanley et al. (2005). The common
thread of these studies was on valuation of water supply improvements in terms of
customer’s WTP. Overall, the available literature indicates that the amount that
customers are willing to pay for improved water services varies widely depending
upon the scope, context and extent of reliability improvements. While using stated
preference techniques, bidding game elicitation formats outscore than the other
formats.
In the literature, most studies conducted in developing countries treat water as a
homogenous good even though there is a clear preference for quality differentiated
supply. Households are willing to pay higher amounts for better water quality and
assured reliability. People have different preference structure for water supply
services and they differ in their willingness to pay depending upon their quality,
taste, perception and other socio-economic characteristics. The service attributes for
2 According to Bishop (2003), CV is by far the most widely applied nonmarket valuation technique the world over. He writes – “without stated preference methods, there would still be an environmental economics, but its usefulness would be much diminished”.
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TERI University Ph.D. Thesis, 2006
urban water supply being provided by either markets or government institutions are
‘heterogeneous in their degree of marketability’ because of heterogeneous
customers’ preference and socio-economic settings, and, therefore, a site-specific
approach is required to assess demand and to provide adequate supply.
It emerges from the literature review that customers’ preferences and choice of
water supply options in a diverse planning environment has immense potential for
improvement by understanding their demand and preference structures. There is a
need to fill this gap by studying preference heterogeneity for quality and reliability
improvements in a mega city in heterogonous planning environments in both
planned and unplanned settlements.