Modern Economy, 2011, 2, 769-779
doi:10.4236/me.2011.25085 Published Online November 2011 (http://www.SciRP.org/journal/me)
769
Valuing Watershed Services in Mexico’s Temperate Forests
Gustavo Perez-Verdin1*, Jose Navar-Chaidez1, Yeon-Su Kim2; Ramon Silva-Flores3
1Instituto Politécnico Nacional, CIIDIR, Sigma 119, Durango, Mexico
2Northern Arizona University, School of Forestry, Flagstaff, USA
3Forest Consultant, Durango, Mexico
Received August 11, 2011; revised Septe mber 14, 2011; accepted October 15, 2011
Abstract
Water resources are highly valuable in arid, semiarid, or high-altitude areas where the sources are restricted
to groundwater or flash floods occurred in short periods of time. In this paper, we present a case study where
water is economically valued through nonmarket valuation techniques. A follow-up review of similarly-
conducted case studies in Mexico was carried out to evaluate the potential relationships that elevation, mois-
ture index, and human development index have over the economic value of water. The main factors influ-
encing the value of water in our case study were income, education, age, and family size. Bivariate correla-
tions of the case studies in the country suggest that there is no a significant relationship between water value
and elevation, although there is some relationship between water value, moisture index, and the human de-
velopment index. Dryer areas and more developed communities tend to pay more for an improvement in
current water resources conditions. These results can help decision-makers to consider regional policies
aimed to improve water management conditions in semiarid and less-developed communities in Mexico.
Keywords: Durango, Contingent Valuation, Non-Market Valuation, Moisture Index, Water Scarcity
1. Introduction
Water scarcity tends to be critical in high-altitude and
semiarid environments [1]. The available water in semi-
arid areas is restricted to groundwater, in the form of
wells or springs, or flash floods during short periods of
time. If natural availability of available water falls below
1000 m3 per capita per year, then critical water scarcity is
observed, and constraints to economic development
emerge [2]. To spatially represent water availability, [3]
modified a moisture measure that Thornthwaite and
Mather created in 1955 to identify water scarcity regions.
This modified, dimensionless climatic moisture index is
a measure of the balance between annual precipitation
and potential evapotranspiration and ranges from +1 to
–1 with wet climates showing positive values and dry
climates negative values. The majority of Mexico’s land
area, dominated by mountain scenarios, is classified as
semiarid with some areas, particularly in southern Mex-
ico, as humid or sub-humid areas [3].
High-elevation areas fulfill important ecological and
economic functions for surrounding lowlands. Highlands,
(e.g., areas situated 1000 meters above sea level, [4]),
provide a range of environmental services to lowlands
including irrigation, drinking water, biodiversity, and
carbon sequestration, among others, but little is used
right there in the highlands [5]. The use of these envi-
ronmental services is even more constrained if an area is
found in low water availability environments. As indi-
cated by Messerli et al., “… the world’s most significant
water towers [mountains] are found in arid and semiarid
environments.” [6, page 30]. This is particularly true in
arid or semiarid areas where the contributions of moun-
tains to total discharge accounts for more than 50%,
while in humid areas this contribution is less than 50%
[4].
Runoff in mountain-based areas is characterized by an
extraordinary heterogeneity of topography, vegetation
and soils, spatially and temporally differentiated levels of
precipitation, as well as annual climate variability [6].
These characteristics make somewhat difficult for high-
land residents to retain and use water for domestic, in-
dustrial purposes. In many cases, these residents have to
pay to bring back products, such as potable water, food,
and electricity, when ironically the main input is gener-
ated where they live. The economic theory suggests that
when more resource inputs are required to supply water
to end users, its price rises. It is therefore necessary to

G. PEREZ-VERDIN ET AL.
770
estimate the value of water considering the source and
management actions to ensure its supply to end users.
Some studies in Mexico have analyzed the demand of
water by estimating the willingness to pay for water re-
sources in various cities across the country [7-9]. In most
of them, economic factors such as income have been
some of the major factors determining the willingness to
pay for water. Overall, wealthy people tend to state
higher amounts of money than poor [8-10]. However, no
studies have been conducted to analyze the effects of
climatic and altitudinal variations in determining the
value of water. Has precipitation, elevation, or evapora-
tion some effect on the value of water? Answers to this
type of questions have not been addressed, because the
majority of studies put aside the location effect and fo-
cuses on one-time, one-point estimations. Addressing the
temporal scale is currently beyond this study as it would
require panel data that for now are not attainable. Instead,
the study focuses on analyzing the location effect by
looking at different water value estimates conducted in
various parts of the country.
In this study, we present a case study where residents
of a relatively small city located up in the Sierra Madre
in central Durango use water from a small watershed for
domestic purposes. We estimated individual and total
benefits for preserving the forest resources in the water-
shed and identified the main factors affecting willingness
to pay (WTP). We compared the WTP results of this case
study with other works developed in Mexico based on
three exogenous variables: elevation, moisture index, and
the Human Development Index (HDI). Specifically, the
study attempted to 1) estimate the value of water or the
willingness to pay for preserving forest ecosystems in El
Salto, Durango, and 2) analyze the effects of altitude and
moisture variations on the willingness to pay for water
resources. In the first objective, we conducted face-to-
face interviews to a sample of El Salto residents and ap-
plied the contingent valuation technique to determine the
economic value that El Salto residents would pay for
preserving forest resources and protect the watershed
from where they receive the water. In the second objec-
tive, we carried out a review on water value from studies
conducted in Mexico. We evaluated the potential rela-
tionship between expected social benefits and the physi-
cal, economic conditions of the communities, particu-
larly the value of water and its relationship with altitude,
moisture index, and quality of life. This study is the first
to show the location effect on the value of water consid-
ering various moisture, altitude, precipitation, and evapo-
ration conditions, as well as quality of life in Mexico.
2. Study Area
The case study was conducted in the community of El
Salto, Pueblo Nuevo located about 100 km west from
Durango city, the capital and main city of the state of
Durango, Mexico (Figure 1). The El Salto is the biggest
city of the Pueblo Nuevo County and sits at 2540 meters
above sea level. The area is dominated mostly by pine-
oak forests with small holdings where landowners farm
the land. The area receives about 800 mm of annual pre-
cipitation and has an annual mean temperature of 11˚C.
In 2000, the city constructed a dam not only to ensure the
supply of water in critical years, but also to prevent the
community from potential floods and retain soil sedi-
ments. The dam (later known as The Rosilla lake) has a
storing capacity of 1.3 million m3 (Mm3) and was con-
structed at the lowest point of the 944-ha catchment area
[11]. Prior to its distribution to approximately 21,000
users, water is filtered through a chlorine-based system
and transported via plastic tubes. The La Rosilla Lake is
the only water reservoir in the surrounding area and local
residents consider it as a very important source of water.
A much smaller dam was constructed downstream (La
Rosilla dam I) to help water managers and local residents
to deal with the issues of flood protection and water sup-
ply.
While historical records suggest that the lake has
never dried out (Figure 2), the annual available water
per person has been estimated at 109 m3/person [11], a
share that is well below the 1000 m3/person/year thresh-
old marked by several organizations, including the Na-
tional Council of Water (CNA 2008). Current water
consumption in the El Salto community is estimated at
1.5 Mm3 per year1 [11], which gives a 0.2 Mm3 per year
water deficit. To meet total demand, local residents have
to purchase bottled water or haul it from distant springs.
Other issues have jeopardized the supply of water to
local residents. The watershed has been excluded from
timber harvesting and protected against fires and diseases.
These protection and management practices are shared
largely by the landowners and partly by the federal gov-
ernment. Ejidatarios, or landowners where the dam was
constructed, demand a fee to cover their expenses in-
curred in the preservation of the forest ecosystem, while
voluntarily giving up timber production and reducing
grazing. Recently, ejidatarios attempted to modify their
forest management plan and initiate harvest operations
within the watershed if their petition of economical com-
pensation is denied [12]. According to forest managers,
negating their petition could lead to water flow and soil
alterations and eventually reduction of the useful life of
he dam. A final issue is related to the storing capacity of t
1The water balance model estimations are based on year-to-year infor-
mation. Thus, monthly variations can be expected throughout the year.
We sought monthly evaluations, but no information was available at
this time.

G. PEREZ-VERDIN ET AL.
771
Figure 1. Location of the El Salto community, Durango. The figure also shows the cities with WTP studies on water resource s
in Mexico (see Table 3 for corresponding names).
Figure 2. Historical water balance for the La Rosilla lake,
near El Salto, Dgo., Mexico. The water balance means the
difference between inputs (precipitation) and outputs (eva-
poration, infiltration, runoff, etc.). Source: [2] and authors’
research.
the lake, which is not enough to cover increased water
demand. This concern has been discussed in public meet-
ings and ideas such as elevating the dam have been con-
sidered [12]. So far, no studies or projects to address this
concern have been conducted.
3. Estimating the Value of Water Benefits
Research has focused on how to estimate an economic
value to environmental services to redirect policies ori-
ented for sustainable water management. The intention is
to help landowners to reduce the impact of externalities
by giving monetary resources and implement best man-
agement practices to regulate the quality/quantity of wa-
ter [5,13]. The need of economic valuation of water
benefits stems from their quasi-public and non-rivalry
nature, the presence of externalities, and scales of pro-
duction [14,15]. If economic valuation is absent, water
benefits will not be provided at optimal levels. The non-
exclusive, non-rivalry nature implies that it is difficult, if
not impossible, to exclude an individual from using wa-
ter benefits (e.g. aquatic habitats, recreation), and several
individuals can use the services simultaneously without
diminishing each other’s use values. The presence of
externalities means that the economic profit of users of
these services will not be deviated to compensate pro-
viders. And regarding the scale of production, these ser-
vices are characterized by economies of scale in produc-
tion; the larger the watershed, the lower the marginal
costs [16].
The value of water benefits was estimated using the
Contingent Valuation (CV) approach. CV is a nonmarket
valuation technique used to estimate societal values for
public goods [17]. The CV approach employs survey-
based techniques to directly elicit households’ prefer-
ences and build a contingent market through which re-

G. PEREZ-VERDIN ET AL.
772
spondents may state their willingness to pay/accept for a
specified provision change in a particular service [18].
The CV approach first involves describing the current
situation of a non-market service, how it can be im-
proved, and then asking respondents whether or not they
would pay/accept for an improvement/compensation of
the specific good [19]. It is called contingent valuation,
because people are asked to state their willingness to
pay/accept, contingent on a specific hypothetical sce-
nario and description of the environmental good [20].
The willingness-to-pay results can then be used by deci-
sion makers to weigh policy options.
The CV method has been extensively applied to esti-
mate water value in many parts of the world. In Mexico,
only a few cases can be outlined for altitudinal and cli-
mate differences. Among these are the Gutierrez-Villal-
pando work in the city of San Cristobal de las Casas,
Chiapas, located in southern Mexico, in which they
evaluated willingness to pay for an improvement of the
riparian ecosystem that supplies water to the city [21].
Also, López-Paniagua et al. used CV to assess the feasi-
bility of the development of an environmental market for
water in the upper watershed of Rio Tapalpa, Jalisco.
This area is located in the Neovolcanic Axis and sits at
1950 m above sea level [7]. A more recent study was
finished in 2008 in the city of Ciudad Obregon, Son, near
to the Mexico-US border where they evaluated the value
of instream flows in the Yaqui river [22].
3.1. Sample Size and Characteristics of
Respondents
To estimate the social benefit of an improvement of cur-
rent conditions of the Rosilla watershed, we surveyed a
sample of local residents of El Salto city. A sample size
was calculated using the standard equation for variables
subjected to proportions [23]. The sample size was esti-
mated at 242 households, with an error proportion of ±
6% and 95% of confidence. Each household was ran-
domly selected using a city map and in each household a
person, older than 18, was invited to participate in a face-
to-face interview2. The questionnaire included three types
of general questions: level of knowledge of the quality of
the service, willingness to pay (WTP) for a hypothetical
scenario, and socioeconomic background of respondents.
An open-ended question format was used to elicit local
residents’ willingness to pay. The open-ended question
was designed in such a way that each respondent openly
stated their closest preference towards an improvement
of the watershed conditions or not. The reason to use
open-ended question (as opposed to referendum format)
was because it allows zero value responses which often-
times are fairly robust to alternative assumptions made
about respondent beliefs [20]. In addition, while there is
some evidence that referendum format may minimize
hypothetical bias, it is not clear that this format alone can
completely eliminate potential bias [24]. Carson and
Groves suggest that the choice between open-ended or
referendum format, or between bias and variance, comes
down to the researcher’s objectives [20].
After providing with information of the watershed and
hypothetical scenarios of action and no action in the area,
it followed the WTP question, which was stated as fol-
lows: “It is important to protect the forests in the Rosilla
watershed so they can ensure water supply to El Salto
residents. Would you be willing to pay a monthly extra
fee to keep preserving the area and secure water supply?
Yes/No”. Then, respondents provided their WTP amount
of money.
The information was collected in 2007 and some of
the socioeconomic characteristics of respondents are
presented in Table 1. The sample closely resembles the
characteristics of the total population of the city. Differ-
ences were observed in age, sex, occupation, and marital
status. Part of these differences can be explained to sur-
vey procedures including the time when the interviews
were conducted. The questionnaires were applied during
work hours and responded by the person most commonly
found in the household at such time. In the majority of
cases (62%), the respondents were women, whose char-
acteristics increased age and marital status data, but de-
creased percentage of occupation3.
Table 1. Characteristics of sampled and total population of
El Salto residents.
Variable Sample
(n = 242)
El Salto city
(N = 21,793)a
Percentage of women 62.0 51.4
Average age (years) 41.6 26.6
Household family size (# of people) 5.0 4.6
Average household income (MX$/month) 2988 2937
Gini coefficient 0.34 0.482b
Percentage with high school education 21.0 16.7
Percentage of occupation 51.6 68.0
Percentage of married people 73.0 62.9
aSource: Conteo de Población y Vivienda 2005 [25]. bCorresponds to the
2008 national average.
2With random sampling, each household in the city had the same prob-
ability of being selected. This characteristic avoided issues related to
selection bias and enabled use of statistical theory to make valid infer-
ences from the sample to the targeted population [26].
3Occupation in this study was considered as the type of employment
p
rovided by a public institution or private entrepreneur in which a
worker continuously receives a wage.

773 G. PEREZ-VERDIN ET AL.
3.2. Model Specification to Estimate Water
Economic Value
We used the ordinary least squares method to fit the pa-
rameters included in the model. We first analyzed whether
predictors met the restrictions imposed to linear regres-
sion models and found that some variables required loga-
rithm transformations. We then decided to use a log-
linear model to mitigate problems associated with het-
erocedasticity, skewness, and high variability of predic-
tors [26]. The log functional form with k + 1 predictors
was expressed as:
0
Log( )kk wtp x

  (1)
where xk are the predictors, 0

is the intercept, and k

is the parameter associated with xk. The mean WTP
estimate was given by:

1ˆ
m
i
i
WTPeWTP m





(2)
where is the predicted WT P for person i and m is
the number of respondents. Confidence intervals (CI) for
ˆ
WTP
WTP at a 95% confidence level can be calculated using
the standard error and applying the typical formula in
which CI= 1.96WTP se
WTP . Also, for logarithm-trans-
formed predictors, the percentage change (∆) (i.e., semi-
elasticity) of WTP

evaluated at the mean of predictor i
was calculated as k
ˆ
% WTP 

. For non-transformed
predictors, we used the following expression [26]:


ˆ ˆ
% 100exp1
WTPk k
x

 




(3)
Equations (1) and (2) were used to estimate the amount
of money that person i would be willing to pay for im-
proving actual watershed conditions and identify the
main variables influencing the choice. Among the factors
included in the analysis were income, age, family size,
and education. No prior expectations of signs were as-
sumed, except for income, in which literature suggests
that the probability and amount of WTP increase as in-
come also increases [8,9,22].
In order to know not only the expected value of the
WTP but also the distribution of the benefits from this
potential change, we estimated a probability distribution
function of predicted WTP. The fitted probability distri-
bution function also allowed us to identify differences
between the mean and median due to sample distribution
and eventually to choose the best statistics and draw
more general conclusions. If non-normal or asymmetric
probability distribution functions are expected, the choice
between the mean and median has large implications for
the desirability of undertaking the provision of the water
service and the method of financing it [18]. In this case,
the mean WTP was calculated as the area under the
probability distribution function and the median was the
amount of money in which the probability of accepting
such an improvement is 0.5. To do this, we tested various
probability functions for predicted WTP and selected the
best using the Kolmogorov-Smirnov test [26]. Following
Kristrom, the equation that represents the mean for pre-
dicted WTP is given by [27]
 
0
01WTP WTP
WTPFA AFA A



 

 (4)
where is the mean of the predicted WTP, FWTP is
a continuous, non-decreasing function (such as the logit
or log-logistic model) and A the amount to pay. The me-
dian WTP (WTP
M) is obtained by solving for A+ in the
following equation:
WTP


0.5
WTP
WTP
MFA


 (5)
3.3. Review of WTP Studies in Mexico
In recent years, several studies have been conducted in
Mexico to estimate the value of water using non-market
valuation techniques. We searched various information
sources and found that some studies, which covered from
the northern state of Sonora to the southern state of
Chiapas (Figure 1), used the CV method to estimate
social benefits from water resources. The first informa-
tion source involved a literature search from all available
databases (e.g. Web of Science) and the web for non-
market valuation studies. A brief review of the abstracts
and introductions served to select articles directly related
to water values and CV. Second, all articles relating to
the topic were thoroughly reviewed to identify ecological,
social and economic factors that needed to be considered.
We also reviewed the citations of published articles to
find any unpublished data or papers. The factors identi-
fied were coded, georeferenced, and compiled in a data-
base.
The reason to review WTP studies across the country
was to analyze the potential relationship between WTP
and the physical, economic conditions of the community.
These included the location (altitude), natural availability
of water, and quality of life. To the best of our knowl-
edge, no studies have been conducted to analyze these
types of relationships. Attempting to compare WTP
studies was cumbersome due to a diversity of objectives:
some estimate the value of water for recreation amenities,
others for ecosystem preservation and environmental
attributes, and others for improving residential services.
Some even were fussy in terms of defining what specific
public service was being evaluated. We discarded those
studies with multiple objectives and overall WTP esti-
mations, and retained those where water value was inde-

G. PEREZ-VERDIN ET AL.
774
4. Results pendently, explicitly estimated. We recognized that com-
parison across water-related valuation studies may not be
appropriate if WTPs from these studies were payments
for different purposes (e.g., improving residential service
or environmental attributes). But, our goal was to con-
sider the diversity of water benefits and compare use and
non-use values [28].
4.1. Willingness to Pay
Survey results indicate that the vast majority of respon-
dents (90% of the sample) were willing to pay for pre-
serving watershed conditions. The amounts ranged from
MEX$ 5 to MEX$ 200 per month. The main variables
affecting the probability of paying for an improvement
were education, age, family size, water bill, and income
(Table 2). Older and richer people were more likely to
pay more for an improvement of the watershed whereas
the amount decreased as respondents had bigger families.
Though not significant, there was a slight, positive cor-
relation between monthly income and water bill, which
suggests in part that people who are now paying more
are willing to pay even more, that is, the WTP amount
increases as the water bill increases too. Contrary to
other studies [8,9], the WTP amount decreased as people
are more educated. A possible explanation of this finding
is that 70% of the sample reported secondary education
as their maximum level of education. In this community,
many people drop off school to get a job to contribute to
their family’s economy. Being this a rural community,
many of these jobs are directly or indirectly related to the
forest. We believe that high levels of perception of wa-
tershed protection to ensure water supply in less edu-
cated people are due to the living experiences in forest-
related jobs. During the survey, we asked respondents
about the importance of forests in providing the water
they consume; the answer, on a scale from 1 (not impor-
tant) to 10 (very important), was 4% higher in those who
had low-levels of education than those with higher lev-
els.
In reviewing these works, we tried to find out the
value of water benefits based on the main priorities of
users and non-market valuation techniques. We focused
on the characteristics of local (physical and economic)
conditions and the stated amount of money residents
gave to water for personal or environmental uses. The
physical and socioeconomic conditions were grouped
into three variables: elevation, moisture index, and a
Human Development Index (HDI). Elevation is meas-
ured in meters above sea level while the moisture index
is based on both monthly precipitation (PT) and evapora-
tion (EV) data [3]. The expression used to calculate the
moisture index (MI) was:
1vT
M
IEP (6)
The closer the MI gets to +1, the wetter the area. Data
of elevation and moisture index were obtained from a
spatially-published database by the National Institute of
Geography.
The HDI is a common measure used to rank societies
as a function of life expectancy, education, and per capita
gross domestic product [29,30]. Even though the HDI
measure has been criticized because it fails to address
ecological factors, it has been used as a standard measure
to classify economies based on their individual perform-
ance [31]. The HDI index goes from 0 to 1, where higher
values mean higher economic development. The HDI
data were taken from the National Council of Population
[32].
To have a better perspective of the model, we esti-
mated the elasticity of predictors. These coefficients are
Table 2. Ordinary least squares estimates of the log-linear functional form for El Salto residents.
Variable MeanCoefficient t-ratio Elasticity (%)
Constant –0.905 –0.856
Age (# of years) 41.010.013 2.52 1.34
Education (1 primary; 2 secondary: 3 high school; 4 college; 5 posgrade) 2.48–0.112 –2.41 –10.62
Family size (# of individuals) 4.98–0.071 –2.08 –6.84
Water bill (MX$) 33.180.008 2.92 0.803
Log Income (MX$) 7.850.455 3.41 0.455
Number of observations 242
Adjusted R2 0.14

775 G. PEREZ-VERDIN ET AL.
interpreted as percentages of change of the independent
variable on WTP (Equation (3)). For example, a one per-
cent increase in family size, ceteris paribus, the WTP
amount decreased by 6.8%. Also, one percent increase in
the age of respondents also increased the amount by
1.3%. Increases or decreases in the water bill have a mar-
ginal impact on WTP. The income effect is also signifi-
cant but marginal; after taking off the logarithm effect, a
unit increase in the mean income, holding all else con-
stant, increases the WTP amount by 0.45%.
Mean WTP estimated through Equation (2) resulted in
MEX$ 19.24 with a confidence interval of MEX$ 17.86
to 20.61 per month. Other statistics showed that pre-
dicted WTP values had some asymmetric distribution
(skewness = 3.7 and kurtosis = 21.5), which strengthened
our idea of taking a closer look at the measures of central
tendency. To get the best probability distribution func-
tion of predicted WTP, we simulated various probability
functions and obtained the best fit using the Kolmo-
gorov-Smirnov test. Results indicate that the best fit was
obtained through the log-logistic model. Using Equations
(4) and (5), mean and median WTP for predicted WTP
were MEX$ 19.20 and 17.11 per month, respectively
(Figure 3). The mean WTP is the area under the distribu-
tion function whereas the median WTP represents the
probability that half of the sample accept an improve-
ment, i.e. when the probability of saying yes is 50%.
Note that the mean WTP is practically the same in both
procedures.
Differences between the mean and median are due to
an asymmetric distribution of benefits of the water ser-
vice improvement [33]. In this case, a portion of the sam-
ple did not see substantial benefits with the policy
change, but the rest is willing to pay considerable
amounts to keep preserving the ecosystem watershed.
There have been various studies debating about which
measure should be used in contingent valuation studies
[34-37]. The mean is very sensitive to the right tail of the
distribution; that is, to responses of higher bidders [35].
Hanemann suggests that if the mean is to be used, a
probability distribution function estimation such as the
one used here, is to be applied [36]. In addition, the mean
WTP is recommendable when it is necessary to estimate
a total value and when benefits are being compared with
opportunity costs [33]. Due to these reasons, the WTP
for this study was based on the mean value (Figure 3).
The total benefits for the whole city, considering 5689
occupied households [25], was MEX$ 1.31 million/year
(US$ 100,826/year) with a confidence interval of MEX$
1.22 and MEX$ 1.41 million/year.
4.2. The Value of Water in Other Environments
We found some differences between our WTP results and
those obtained elsewhere in Mexico. The overall WTP
mean was MEX $73 while El Salto gave MEX $19.
Figure 3. Log-logistic probability distribution function of predicted WTP for El Salto Residents. The Kolmogorov-Smirnov
statistics was 0.036 with p = 0.95, thus the null hypothesis of data coming from the specified distribution cannot be rejected.
lso shown the values of the three parameters estimated in the fitting. A

G. PEREZ-VERDIN ET AL.
776
Mean elevation, MI, and HDI were 1498 m, 0.781, and
0.117, whereas for El Salto were 2540 m, 0.774, and
0.25, respectively (Table 3). To evaluate a potential rela-
tionship between water value and each of the factors, and
considering the low number of case studies, we per-
formed simple bivariate correlations (Figure 4). Overall,
no significant association was found between WTP and
elevation (r = –0.27, p = 0.37). The lack of significant
correlation between elevation and WTP can be explained
in part by the great diversity of topographic conditions
where large cities, such as Mexico City, located in high
altitude areas, have high levels of demand, and probably
are willing to pay large amounts of money for the water
they use. Mexico City residents for example consume
water at a rate of 64 cubic meters per second (m3/s) while
the supply has been estimated at 54 m3/s [8]. Their WTP
estimates suggest a high latent demand and value percep-
tion over policies aimed to improve water service4.
The moisture index (MI), a measure of dryness, had a
significant inverse correlation with WTP (r = –0.64, p =
0.02). Cities located in dryer environments tend to pay
higher values for water services than wetter cities. This
finding coincides with that of the economic theory in
which individuals pay higher amounts of money for
scarce resources. In contrast, the HDI, a measure of the
quality of life, has a direct relationship with WTP (r =
0.64, p = 0.02). Cities with better quality of life standards
tend to give higher values than less-developed cities.
Figure 4 shows individual relationships between WTP
and each factor. The exploratory results of these types of
relationships can help resource managers to consider
regional-aimed policies to improve water management
conditions in arid and less-developed communities in
Mexico.
5. Conclusions
This research presented a case study where water is eco-
nomically valued using non-market valuation methods.
Residents of a rural community in Durango, Mexico par-
ticipated in face-to-face interviews to help estimating
total social benefits about the preservation of the forest
ecosystem from which they obtain their potable water.
Contingent valuation was used to estimate the amount of
money residents were willing to pay for preserving the
forests of the Rosilla watershed. A log-linear model and
probability density function were used to estimate mean
WTP. Results showed that the majority of respondents
(90% of the sample) are willing to pay for preserving
watershed conditions. Mean WTP estimated using Equa-
tion (2) was estimated at MEX$ 19.2/month (US$ 1.5/
month) with a confidence interval of MEX$ 17.86 to
20.61. The main factors influencing acceptance of the
payment were income, education, age, family size, and
water bill. The total benefit for the entire population was
estimated at MEX$ 1.31 million/year (US$ 100,826/
year).
Based on the analysis of WTP studies developed so far
in Mexico, there was no significant relationship between
elevation and WTP. The analysis was based on several
cities distributed in an altitudinal gradient from 10 to
2540 m above sea level including Mexico City, the
world’s third largest metropolitan area, located at 2240 m.
According to the national water agency, a moderate pro-
portion of high-altitude areas in Mexico shows similar
deficits of water supply [2] and their residents, as evi-
denced by the Mexico City case, are probably willing to
pay large amounts of money to compensate for these
deficits. Large WTP amounts were also registered in low-
altitude cities such as La Paz and Alamos. Based on our
analysis, the topographic heterogeneity of the country,
where almost 55% of the total population lives above the
1000-m elevation line [25], made elevation not impor-
tant to determine the value of water.
Results provided evidence that the moisture and hu-
man development indexes are statistically correlated with
WTP. Dryer areas and more developed communities tend
to pay more for improved water resources. The moisture
index finding coincides with basic economic theory
which suggests that scarce resources are more appreci-
ated. Regarding HDI finding, there is an increasing de-
bate whether communities with better quality of life are
more likely to contribute to ecosystem preservation.
Some argue that economic growth and conservation are
incompatible goals, but others say that wealthier com-
munities have the luxury of investing more heavily in
efforts to ecosystem conservation [44,45]. To have a
more comprehensive conclusion it is necessary more
studies that analyze the relationship between WTP and
human development index or other type of economic
growth metrics.
The analysis presented in this explorative study moti-
vates us to continue investigating the relationship be-
tween water value and exogenous variables based on
non-market valuation methods in Mexico. Adding more
studies should reinforce the decision-making process of
correctly allocating financial resources for different pur-
poses such as improving current management and distri-
bution systems, protecting high-value watersheds, or
providing water to low-income families.
6. Acknowledgements
4Water in Mexico City is pumped from a 1600-m to 2200-m elevation
differential to reach users [2]. We thank CONACYT and the Instituto Politecnico Na-

777 G. PEREZ-VERDIN ET AL.
Table 3. Cities with WTP estimations for water in Mexico.
Study site Water
attributea
Elevation
(meters)
Moisture
indexb
Human Development
Indexc
Adjusted WTP
(US$/month)d
Source of WTP
estimations
1. Ciudad Obregon, SON E, R 35 0.146 0.834 6.12 [22]
2. San Luis Rio Colorado, SON E 40 0.055 0.826 6.39 [38]
3. Parral, CHIH R 1,620 0.089 0.810 8.915e [9]
4. El Salto, DGO E 2,540 0.250 0.733 2.08 This study
5. Tapalpa, JAL E 1,950 0.135 0.732 9.10f [7]
6. Mexico City, DF R 2,240 0.064 0.849 15.81g [8]
7. San Cristobal de las Casas, CHIS R, E 2,120 0.306 0.752 1.82 [21]
8. Tepetlaoxtoc, EDOMEX E 2300 0.088 0.751 4.98 [39]
9. Oaxaca, OAX E 1555 0.105 0.834 3.11 [40]
10. Tlaxco, TLAX E 2588 0.074 0.743 1.83 [41]
11. Metztitlan, HGO E 2080 0.091 0.686 0.45 [42]
12. Alamos, SON E 400 0.046 0.706 8.23 [43]
13. La Paz, BCS R 10 0.048 0.817 10.15 [10]
aWater use: E: Environmental/protection; R: Residential service. bBased on average precipitation and evaporation data. cBased on county-level estimations by
CONAPO (National Council of Population). dFebrurary-2010 price levels (US$ 1 = MEX$ 13, average annual inflation rate = 4.4%). eOpen-ended question. No
certainty correctionf Includes domestic sector only. gAverage across five income groups and improvement scheme.
(a) (b) (c)
Figure 4. Relationships between WTP and (a) elevation, (b) moistur e inde x, and (c) human development index.
cional for partially funding this study. The ejido La Vic-
toria and CNA provided valuable forest inventory and
climatic data, respectively. Our thanks also go to El Salto
residents for participating in the interviews. Part of this
study was presented at the 2010 ACES conference in
Phoenix, AZ. We thank attendees for constructive inputs.
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