# RECORD 1ce55be799df6cb17762fb0541fe95340687f3de
# TITLE: The willingness to pay for access to piped water: a hedonic analysis of house prices in Southwest Sri Lanka
# YEAR: 2012.0  VENUE: nan  DOI: 10.1007/s12076-012-0079-y
# AUTHORS: Caroline van den Berg; Céline Nauges
# PAGES: 16  CANDIDATE TABLE PAGES (1-based): [7, 10, 11]
# ABSTRACT: We apply a hedonic house price analysis to value connection to the piped water network in Southwest Sri Lanka based on a household survey that was conducted in 2003-04. We find that the willingness-to-pay for a piped water connection is on average about 5 percent of monthly household expenditure, which is at the lower end of the range from estimates obtained in case studies in other developing countries. In addition, the willingness-to-pay for piped water decreases as a proportion of income when income goes up. An important policy conclusion is that connection to the piped water system should be considered in relation to the availability and quality of alternative water sources. If alternative sources with good water quality are available, the need for a piped water connection is less urgent.


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Lett Spat Resour Sci (2012) 5:151–166
DOI 10.1007/s12076-012-0079-y
ORIGINAL PAPER
The willingness to pay for access to piped water:
a hedonic analysis of house prices in Southwest
Sri Lanka
Caroline van den Berg · Céline Nauges
Received: 3 January 2011 / Accepted: 2 February 2012 / Published online: 23 February 2012
© The Author(s) 2012. This article is published with open access at Springerlink.com
Abstract We apply a hedonic house price analysis to value connection to the piped
water network in Southwest Sri Lanka based on a household survey that was con-
ducted in 2003-04. We find that the willingness-to-pay for a piped water connection
is on average about 5 percent of monthly household expenditure, which is at the lower
end of the range from estimates obtained in case studies in other developing coun-
tries. In addition, the willingness-to-pay for piped water decreases as a proportion of
income when income goes up. An important policy conclusion is that connection to
the piped water system should be considered in relation to the availability and qual-
ity of alternative water sources. If alternative sources with good water quality are
available, the need for a piped water connection is less urgent.
Keywords Household behavior · Piped water services · Hedonic pricing method ·
Development planning and policy · Sri Lanka
JEL Classification D12 · H4 · O2 · Q25 · Q52
1 Introduction
The World Health Organization and UNICEF’s Joint Monitoring Programme (2010)
estimated that in 2008 about 884 million people in urban areas in developing coun-
tries lacked access to safe water. Yet, these numbers do not capture the often low
The opinions reflected in this paper are the opinions of the authors and not opinions of the World
Bank, the University of Queensland.
C. van den Berg ()
Middle East and North Africa’s Sustainable Development Department, Word Bank,
1818 H Street NW, Washington DC, USA
e-mail: cvandenberg@worldbank.org
C. Nauges
School of Economics, University of Queensland, Brisbane Qld, 4072, Australia


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The willingness to pay for access to piped water: a hedonic analysis
157
Table 1 Descriptive statistics for connected and unconnected households
Non-
connected
households
(mean)
Connected
households
(mean)
Mean com-
parison test
(p-value)
Average house value (in LKR) (ln)
13.01
13.31
0.000
Structural characteristics
Average number of rooms
1.23
1.28
0.033
Average number of sealed toilets
1.17
1.25
0.001
Red bricks/cement used for walls
(proportion)
0.94
0.98
0.000
Tiles used for roof (proportion)
0.82
0.74
0.000
Storage tank (proportion)
0.46
0.41
0.027
Neighborhood characteristics
Average household income in
municipality (in LKR) (ln)
9.7
9.78
0.000
Samurdhi recipients in municipality
(proportion)
0.18
0.20
0.000
Household located in Negombo
(proportion)
0.74
0.26
0.000
Household located in Kalutara
(proportion)
0.72
0.28
0.003
Household located in Galle (proportion)
0.55
0.45
0.000
Average distance to pre-school (km) (ln)
0.57
0.08
0.019
Average distance to hospital (km) (ln)
−0.04
−0.60
0.000
Average distance to road (km) (ln)
1.34
1.02
0.000
Average distance to beach (km) (ln)
1.39
0.77
0.000
Socio-economic characteristics
Average household monthly income (in
LKR) (ln)
9.42
9.58
0.000
Average household per capita monthly
income (in LKR) (ln)
7.93
8.04
0.004
Proportion of Samurdhi recipients
0.21
0.15
0.004
Average number of years of education
by head of household (ln)
1.93
2.12
0.002
Water sources
Piped water (proportion)
0.00
1.00
0.000
Other water sources as main source
(proportion)
1.00
0.00
0.000
4 Empirical results
4.1 Descriptive statistics
Descriptive statistics by connected and unconnected households are presented in Ta-
ble 1. Simple tests of means between both types of households are included (last


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C. van den Berg, C. Nauges
column). We only discuss significant differences. Note that 39 percent of the house-
holds are connected.
Average monthly income (including total monthly income of all wage earners in
the household, plus any other income, plus any money remitted to the household
by a family member working outside the country) for connected households is about
30 percent higher than the average of unconnected households. The mean comparison
tests also suggest that connected households tend to live in houses with more rooms
and sealed toilets than unconnected households. Unconnected households are more
likely to have tiles as roof material than connected households, while the opposite
holds for red bricks/cement for walls. Furthermore, a larger proportion of uncon-
nected households have a storage tank.
As far as neighborhood characteristics are concerned, there are significant differ-
ences in terms of distance to pre-school, hospital, beach, and distance to a paved road
between connected and unconnected households. Particularly, unconnected house-
holds tend to be located further away from these amenities. Average municipality
income is higher for connected than for unconnected households. Non-connected
households are concentrated in the Negombo district and connected households in
the Galle district. The Kalutara district is mixed.
As far as socio-economic characteristics are concerned connected households have
higher total and per capita income, and their household heads have more years of
education than unconnected households. In addition, 21 percent of the non-connected
households are Samurdhi recipients, but only 15 percent of the connected households.
Unconnected households mainly collect water from four sources: public taps, pub-
lic wells, neighbors (private tap or private well), and private wells. Nauges and van
den Berg (2009) show that the lowest time cost (to collect water) is borne by house-
holds having private wells, followed by households relying on water provided by
neighbors. It takes on average about 5 minutes to go to community sources (pub-
lic tap or well), and waiting time can be up to 24 minutes. Water from non-piped
sources, except vendors, is free. However households who collect water from wells
need equipment, which can be a bucket and a rope (for the vast majority of house-
holds), a hand pump, or more costly and technically more advanced equipment, such
as an electric pump. Overall, unconnected households are satisfied with the quality
(i.e., taste, color, smell, and safety) and service of non-piped water. More precisely,
90 percent of households collecting water from public taps, neighbors, and private
wells, believe that water from these sources is safe. This percentage is slightly lower
for households relying on public wells: 60 percent of these households think that
there is “no risk” or “little risk” in drinking water from the public well.
Connected households were also questioned about their judgment of the piped
water service. The majority believes that water supplied through the network is safe.
However, there were frequent complaints about piped water being available for less
than 24 hours a day. Indeed, in the rainy (dry) season, only 31 percent (22 percent) of
connected households have 24 hour service; and 36 percent (42 percent) have access
for 12 hours or less a day.
To sum up, satisfaction with access to and quality of water is very high in this part
of Sri Lanka, whether a household has access to a piped water connection, a private
well, or depends on a neighbor for water supply. This means that the willingness


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160
C. van den Berg, C. Nauges
Table 2 OLS estimation results of the conventional hedonic house price model
Dependent variable (ln of house appraisal value)
Coefficient
Std. err.
p value
Constant
7.575∗∗∗
1.013
0.000
Structural characteristics
Number of rooms (ln)
0.640∗∗∗
0.052
0.000
Number of toiletsa (0/1/2)
0.467∗∗∗
0.052
0.000
Wall is made of red bricks or cement (otherwise reference )
0.929∗∗∗
0.113
0.000
Roof is made of tiles (otherwise reference case)
0.143∗∗
0.054
0.008
Overhead storage tank (not available reference case)
0.323∗∗∗
0.048
0.000
Neighborhood characteristics
Mean household income by municipality (ln)
0.355∗∗∗
0.112
0.002
Percentage of Samurdhi recipients by municipality
−1.856∗∗∗
0.414
0.000
Distance to road in km (ln)
−0.071∗∗∗
0.022
0.001
Negombo district (reference case)
Kalutara district (0/1)
−0.208∗∗∗
0.056
0.000
Galle district (0/1)
−0.110∗
0.051
0.032
Water source
Household has access to non-piped sources only (reference)
Household has access to private piped water connection (0/1)
0.195∗∗∗
0.048
0.000
Number of observations
1,523b
Adjusted R-squared
0.41
∗∗∗, ∗∗, ∗Indicate significance at the 1, 5, and 10% level, respectively
aPresence of toilet: 0 = no toilet, 1 = one toilet only, 2 = two or more toilets
bThe sample on which the model is estimated is smaller than the sample of 1,552 households discussed in
Sect. 4, because of non-response in some of the explaining variables, which reduces the total number of
included observations to 1,523
Most of the remaining variables are significant at conventional levels and have
the expected signs. Structural characteristics are highly significant, and so are the
neighborhoods characteristics. Introducing socio-economic characteristics as a proxy
for impact of perceptions and knowledge shows that the connection to the piped water
network has a significant, positive coefficient, but that it is lower than in the traditional
hedonic pricing model (Table 2).8 This tendency of hedonic pricing models to provide
an upper bound of willingness to pay has been noted by different authors (Vaughan
and Ardila 1993; Carson et al. 1996).
In the next subsection we use this piece of information to derive the marginal
willingness to pay for a private piped water connection.
8Note however that the estimated coefficients of a piped water connection in the conventional and adjusted
models are not statistically different, in the sense that the corresponding 95% confidence intervals overlap.


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The willingness to pay for access to piped water: a hedonic analysis
161
Table 3 OLS estimation results of the adjusted hedonic house price model
Dependent variable (ln of house appraisal value)
Coefficient
Std. err.
p value
Constant
5.818∗∗∗
1.096
0.000
Structural characteristics
Number of rooms (ln)
0.556∗∗∗
0.052
0.000
Number of toiletsa (0/1/2)
0.334∗∗∗
0.052
0.000
Wall is made of red bricks or cement (otherwise reference )
0.847∗∗∗
0.111
0.000
Roof is made of tiles (otherwise reference case)
0.138∗∗
0.053
0.009
Overhead storage tank (not available reference case)
0.219∗∗∗
0.048
0.000
Household socio-economic characteristics
Monthly household income (ln)
0.267∗∗∗
0.033
0.000
Household is Samurdhi recipient
−0.271∗∗∗
0.060
0.000
Education of head of household in number of years (ln)
0.031∗
0.018
0.086
Neighborhood characteristics
Mean household income by municipality (ln)
0.310∗∗∗
0.109
0.005
Percentage of Samurdhi recipient by municipality
−1.553∗∗∗
0.406
0.000
Distance to road in km (ln)
−0.071∗∗∗
0.021
0.000
Negombo district (reference case)
Kalutara district (0/1)
−0.175∗∗∗
0.055
0.001
Galle district (0/1)
−0.094∗
0.050
0.062
Water source
Household has access to non-piped sources only (reference)
Household has access to private piped water connection (0/1)
0.152∗∗∗
0.047
0.001
Number of observations
1,491b
Adjusted R-squared
0.45
∗∗∗, ∗∗, ∗Indicate significance at the 1, 5, and 10% level, respectively
aPresence of toilet: 0 = no toilet, 1 = one toilet only, 2 = two or more toilets
bThe sample on which the model is estimated is smaller than the sample of 1,552 households discussed in
Sect. 4, because of non-response in some of the explaining variables, which reduces the total number of
included observations to 1,491
4.4 The marginal willingness-to-pay for a private connection
We now turn to the derivation of the marginal willingness-to-pay for connection to
the public water system. Coefficient ˆβ in Tables 2 and 3 denote the difference in ln
value between connected and unconnected houses and the absolute increase in house
value from the connection to the piped network is V NC(e ˆβ −1) or in percentages:
V NC(e ˆβ −1) × 100
V NC
= (e ˆβ −1) × 100.


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C. van den Berg, C. Nauges
Table 4 Predicted increase in house value after connection according to the basic hedonic pricing model
(overall, monthly equivalent, % of monthly household income)
Predicted increase in house value (LKR)
Monthly equivalent of
increase in house value
(LKR)
As % of monthly
household income
(non-connected)
Mean
[95% confidence
interval]
Median
[95% confidence
interval]
Mean
[95%
confidence
interval]
Median
[95%
confidence
interval]
Mean
[95%
confidence
interval]
Median
[95%
confidence
interval]
97,149
[47,839;151,437]
100,430
[49,454;156,550]
810
[399;1,262]
837
[412;1,305]
6.6%
[3.2%;10.2%]
7.0%
[3.4%;10.9%]
In the conventional hedonic pricing model, ˆβ = 0.195 (0.152 in the adjusted model),
which translates into a relative increase in house value (after connection) of about 22
(in the adjusted model reduced to 16) percent. However, ˆβ is estimated with error.
The 95% confidence interval for ˆβ is [0.061 and 0.247], which corresponds to a 95%
interval of [6% and 25%] in percentages when the basic hedonic pricing model is
used.
4.5 The average monthly income equivalent
We define the average monthly equivalent of the increase in house value due to con-
nection as 1/12 of the discounted annualized increase. We use a discount rate of
10 percent, which is the rate charged by a self-help group or microfinance institution.
In Table 4 we report in the first column the predicted increase in house value after
connection to the piped network (based on the estimated parameter ( ˆβ = 0.195) of
the connection dummy variable), and the monthly equivalent, in absolute terms and
as a percentage of monthly household income. We find that non-piped households
on average would be willing to pay each month about LKR 810 (median LKR 837),
which is about 6.6 percent of their monthly household income, to get a connection to
the piped network.9 When using the adjusted model that takes a better account of the
perceptions and knowledge, the results are significantly lower and non-piped house-
holds are on average willing to pay only LKR 614 (median LKR 701) which is about
5 percent of their monthly household income as shown in Table 5. These numbers
are in the range of North and Griffin (1993) for the Philippines, De Oca et al. (2003)
for Mexico, Nauges et al. (2009) for Central America, and Suparman et al. (2009) for
Indonesia.
In Table 6 we show the monthly equivalents for different income groups. The first
quartile is the 25 percent of households with the lowest per capita income, and so on.
Table 6 shows that the expected willingness-to-pay for access to a private connec-
tion decreases as a proportion of income when income goes up, although there is a
kink whereby the expected willingness-to-pay decreases from the first to the second
quartile, but it increases in the third quartile, after which it decreases in the fourth
9The total increase in house value due to the water connection is on average LKR 97,149, which translates
into a monthly value of LKR97, 194 × 1/12 × 10 percent = LKR 810; and an annual value of LKR 9,715.