Article
Wei-Shiuen Ng and Robert Mendelsohn
The Economic Impact of Sea-level Rise
on Nonmarket Lands in Singapore
Sea-level rise, as a result of climate change, will likely
inflict considerable economic consequences on coastal
regions, particularly low-lying island states like Singapore.
Although the literature has addressed the vulnerability of
developed coastal lands, this is the first economic study to
address nonmarket lands, such as beaches, marshes and
mangrove estuaries. This travel cost and contingent
valuation study reveals that consumers in Singapore
attach considerable value to beaches. The contingent
valuation study also attached high values to marshes and
mangroves but this result was not supported by the travel
cost study. Although protecting nonmarket land uses from
sea-level rise is expensive, the study shows that at least
highly valued resources, such as Singapore’s popular
beaches, should be protected.
INTRODUCTION AND LITERATURE REVIEW
The consequences of sea-level rise due to global climate change
have significant social and ecological impacts on coastal regions
throughout the world. Global sea-level rise is caused primarily
by thermal expansion of seawater from rising ocean temperatures and also by melting of terrestrial ice, glaciers, and ice
sheets (1, 2, 3, 4). Intergovernmental Panel on Climate Change
(IPCC) has projected that sea levels will rise on average by five
mm per year over the next 100 years and could possibly rise
even faster (5). These changes are important because they have
the potential to alter ecosystems and habitability in coastal
regions, which are home to an increasing percentage of the
world’s population, habitat for much of the world’s fisheries,
and vacation spots across the world (6).
Since the impact of sea-level rise varies among coastal regions,
it is important to assess each nation’s vulnerability to sea-level
change (7). The degree of influence depends on the area that may
be inundated, the cost of potential adaptation measures, and the
ability to adopt such measures. Small island states are among
some of the most vulnerable regions in the world to sea-level rise.
Climate change and sea-level rise will no doubt pose a serious
threat to small island states like Singapore (8).
Global climate change and global sea-level rise are beyond
Singapore’s control (9), but Singapore does have adaptation
options that can reduce damages. IPCC 2001 argued that the
most serious considerations for some small island states is
whether they will have adequate potential to adapt to sea-level
rise within their own national boundaries (5). Singapore has the
financial capacity to protect its developed lands, and it will be
able to carry out effective adaptation measures. In a recent
study, Ng and Mendelsohn (10) demonstrated that Singapore
should protect all of its market lands from inundation. The cost
of protecting Singapore’s developed coast is much less than the
value of the potentially inundated land.
This study focuses on the economic impact of sea-level rise
on nonmarket lands in Singapore. Although the economic
literature on sea-level rise has addressed developed lands, this is
the first study to address land that is not developed. Nonmarket
lands are jointly consumed by many people and include areas
Ambio Vol. 35, No. 6, September 2006
such as beaches, marshes, and mangroves. Because they provide
pleasure to many people, they are often not traded on markets
and have no monetary market value. It is therefore not obvious
how much should be spent to protect these resources from
inundation. This study analyzes whether abandoning natural
areas or protecting them is more efficient. Protection is advised
only if the benefits of protection are higher than the costs (11).
We assess the benefits of protecting each coastal resource using
a willingness-to-pay survey and a travel cost study. These
benefits are then compared with the costs of protection.
The next section describes the physical benefits associated
with preserving beaches, marshes, and mangroves. The section
following that describes the methodology used to value the
benefits of protecting these public resources. Results are
subsequently presented from the travel cost analysis and
contingent valuation survey, and the last section describes the
cost of protection for each resource. The paper concludes with
policy recommendations for Singapore to address desirable
adaptation in natural areas to sea-level rise.
PHYSICAL BENEFITS
The shore zone has natural features that provide considerable
coastal protection. Sand and gravel beaches contribute as wave
energy sinks, and barrier beaches act as natural breakwaters
(12). Coastal vegetation absorbs wind or wave energy, retarding
shoreline erosion. Marshes act as a sea defense (13), and
mangroves are sediment traps (14) that act as a buffer zone
between land and sea and play a significant role in protecting
both the coastal areas and coral reefs at the same time (7). If
these ecological functions of the natural coastal systems are lost,
coastal resilience would decline. As sea level rises, beach
erosion, wetland displacement, and mangrove species inundation will occur, unless adaptation measures are implemented in
time. Beach erosion will move the shoreline, shifting the beach
profile closer inland (15). One method of preventing beach
erosion is continual beach nourishment, which preserves
beaches in their current conditions and discourages further
erosion. Another approach is to build undersea seawalls and
backfill sand behind these hard structures. In both cases, the
beach could continue to be used for recreational purposes.
Singapore has already installed hard undersea structures for
land reclamation (16). Beach protection is expensive, but it is a
feasible option.
As for marshes and mangrove estuaries, natural inland
migration could be a protection measure. The impact of sealevel rise on marshes and mangrove estuaries depends on
vertical accretion rates and space for horizontal migration,
because increasing sea level will destroy current habitats, hence,
marsh and mangrove species would have to shift to new tidal
areas (5). Coastal ecosystems are threatened when marshes
drown because they do not accrete vertically fast enough (17).
They develop ponds as they drown and eventually can
disappear entirely (6). The vertical accretion of the marsh
surface must occur at a rate at least equal to the rate of relative
sea-level rise, in order to maintain an elevation for marsh
vegetation to survive (17). Sea-level rise could thus easily alter
marsh hydrology and affect the rate of net vertical accretion.
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289
Mangroves go through similar processes when sea level rises.
When the rate of sea-level rise exceeds the rate of sedimentation,
substrate erosion, inundation stress, and increased salinity will
occur (18), mangrove species zones will migrate inland, and
seaward margins will die back (7, 19). These events could
happen to the mangrove estuaries on the western and northern
coasts of Singapore with increasing sea level (20).
Coastal wetlands would naturally migrate inland in response
to relative sea-level rise. However, in Singapore’s case, highly
developed land behind the wetlands will prevent adequate
sediment supply to the mangrove estuaries (20) and will inhibit
the natural migration of mangroves as sea level rises. This
creates a complex problem, since protecting nonmarket lands
will often imply sacrificing developed lands. Previous studies
have estimated that as more developed lands are protected,
there will be a greater loss of wetlands (21, 22, 23, 24). The
extent of the impact of sea-level rise will depend on the decision
to either protect or modify the coastline, therefore allowing
coastal wetlands to migrate inland (25). A tradeoff exists
between preserving nonmarket lands and protecting developed
lands, as human infrastructure will prevent coastal wetlands and
mangroves from migrating inland as sea level rises. In this
study, we assume that the cost of marsh and mangrove
protection is the market value of the property lost due to
inland migration of the marshes and mangroves.
METHODS OF MEASURING THE BENEFITS
OF PROTECTION
Two methods were used to determine the value of the coastal
resources: travel cost and contingent valuation. The travel cost
method is a behavioral technique that deduces values from what
people actually do. Contingent valuation is an attitudinal
approach that measures values from what people say, not what
they do. Each method has its own strengths and weaknesses.
The travel cost method only measures the use value of a site,
whereas the contingent valuation method measures both use
and nonuse. We use both methods in this study to measure a
range of possible values for these coastal nonmarket sites.
Travel Cost Method
The travel cost method (TCM) is a tool that deduces the values
of resources based on the decisions of visitors to travel to the
site from different distances. The travel costs they incur in order
to visit the site is the price of admission (11). The further an
individual lives from the site, the higher the travel cost. By
observing how visitation changes with distance, the analyst can
estimate the demand for visitation. The analyst estimates the
demand to visit each site (beach, marsh, or mangrove estuary)
from these cross-sectional data (26). The demand for visits to a
beach, marsh, or mangrove estuary is given as:
Vi ¼ f ðCi ; X1i ; X2i ; . . . ; Xni Þ;
Eq: 1
where Vi is visits by the ith individual, Ci is the cost of a visit by
individual i, and the X’s are demand shift variables. In this
analysis, we assume that demand has the following form:
Vi ¼ a þ bCi þ ei ¼ a þ bðTi Þ þ ei ;
Eq: 2
where ei is the stochastic component, assumed to be normally
and independently distributed, with zero expectation. Almost
all the sites analyzed in this study had no admission fee, so only
travel costs were taken into account when estimating the
demand function.
The value of a site to an individual is equal to the area under
the individual’s demand curve for that site but above their travel
costs, which can be calculated as:
290
WTP ¼
Z
‘
V ðti Þdt:
Eq: 3
Ti
where willingness to pay (WTP) is the annual value to the
individual of the site. The social value of a site is the sum of the
consumer surplus values of all the individuals who visit that
particular site (26).
Contingent Valuation Method
The contingent valuation method (CVM) uses surveys of public
opinion to estimate the nonmarket values associated with changes
in the environment. Numerous previous studies have applied
CVM in various valuations of natural resources (27, 28, 29, 30).
The contingent valuation method asks the sample population
hypothetical questions about their willingness to pay for a site.
Since this method could cover both use and nonuse values, it
was chosen in this study to measure the nonmarket values of
beaches, marshes, and mangroves in Singapore. The average
willingness to pay observed in the sample was then extrapolated
to the entire adult population in Singapore to obtain an
aggregate valuation:
V ðY WTP; P; QÞ ¼ V ðY ; P; QÞ:
Eq: 4
where V is the indirect utility function of the individual, Y is
income, P is the price of a trip, and Q is the number of trips
taken.
Survey Data
This study employed both a quantitative and qualitative research
design. A survey with a sample size of 338 was conducted over a
period of ten weeks in the summer of 2002 in Singapore.
Questionnaires were evenly distributed to residents above the age
of 19 across the country (the questionnaire designed for this
study is available from the authors upon request). The survey
was conducted personally so as to assure maximum positive
response rate and to obtain reliable results of high quality.
The questionnaire used in this survey consisted of 20
questions and took approximately 10 to 15 minutes to complete.
Questions 1 to 4 were asked to support the travel cost study.
The first question required respondents to mark their residential
area on the map provided. It was then possible to calculate the
distance traveled to each site and, subsequently, the travel cost
of each respondent. Questions 2 to 4 listed 11 specific beach,
marsh, and mangrove sites and asked for the respondents’
frequency of visits within the past year. Questions 5 and 6 tested
respondents’ knowledge of sea-level rise.
Questions 8 to 10 asked attitudinal questions that helped
identify protestors. They asked whether the respondent felt
responsible for protecting natural sites, whether polluters were
responsible for damages from global warming, and whether the
government would actually protect resources if paid. If people
were hostile to these attitudinal questions and offered zero
willingness to pay, they were considered to be protestors.
The contingent valuation questions began with a general
interest question. Question 7 asked: Will you agree to an
increase in your annual personal income tax to be used to
protect each of the following three different types of nonmarket
land in Singapore?
Beaches.......................Yes
Marshlands.................Yes
Mangroves..................Yes
No
No
No
Don’t Know
Don’t Know
Don’t Know
If a respondent chose ‘‘Yes,’’ they were asked three closeended willingness-to-pay questions, with answer categories
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Ambio Vol. 35, No. 6, September 2006
country. The geographical locations of the eleven tested sites are
marked on Figure 2. The four beaches are Changi, East Coast,
Pasir Ris, and West Coast Beach Parks. The beaches are
distributed in the south and east and range from average to very
popular beaches. The four marshes are Kranji Reservoir,
Poyan, Sungei Khatib Bongsu, and Pasir Ris Park Marshes.
The marshes are on the north and west coasts. The final three
sites are mangroves. They are Sungei Buloh Nature Park,
Sungei Mandai, and Sungei Punggol. The mangroves are
located on the north coast.
Travel Cost
The total travel cost for each individual to each of the 11 sites
was calculated using the estimated travel distance and the
transportation cost at 0.33 USD per km. The visitation
regression model was applied to each site, with number of
visits (V) as the dependent variable and travel cost (TC), age
(AGE), gender (GEN), number of children (CHD), educational
level (EDU), family size (FAM), and income level (INC) as the
independent variables:
Figure 1. The geographical location of the 338 survey respondents.
V ¼ b0 þ b1 TC þ b2 AGE þ b3 GEN þ b4 CHD þ b5 EDU
Eq: 5
þ b6 FAM þ b7 INC;
ranging from $0 to more than $500. Each question included a
short description of the solution to beach erosion, marsh, and
mangrove retreat. The willingness to pay was measured in terms
of an increase in income tax.
The remaining questions were demographic (age, gender,
number of children, education level, family size, income level).
These were placed last in the questionnaire, because they involve
private information and respondents are more likely to reveal
such information if other questions have been answered first (31).
ArcView GIS (geographic information system) was used to
calculate the distance between each respondent’s residential
area and each nonmarket land site. LimDep was used to analyze
the data collected from the survey. All estimates in this study
are expressed in terms of 2002 United States dollars (USD)
unless otherwise stated (Singapore dollar: 1 SGD is approximately 0.59 USD).
where bn is a constant.
The visitation regression results are displayed in Table 1.
Only variables that are significant for at least one site are listed.
Age, gender, number of children, and income were only
significant for one or two sites. Age was significant in Changi
Beach Park (t ¼ 2.17) and Kranji Reservoir Marsh (t ¼ 2.33),
but with opposite signs for the coefficient. Gender was only
significant in one site, Changi Beach Park (t ¼ 2.51). Men
tended to visit this beach site more frequently. The number of
children was significant in Sungei Punggol, and income was
significant in West Coast Park.
The travel cost coefficient was negative (the expected sign) and
significant in only five out of the eleven sites. These successful
regressions include all the beaches and one marsh site, Pasir Ris
Park. The travel cost coefficient on the remaining marsh sites and
all the mangroves were either the wrong sign or not significant.
Because valuation is based on this travel cost coefficient, the
results imply that these other sites did not have observable value.
That is, the behavior of visitors was low, effectively random, and
did not reveal statistically significant value for these sites.
Using the travel cost demand functions in Table 1 that had
negative travel cost coefficients, we calculated consumer surplus.
The consumer surplus for Sungei Khatib Bongsu (marsh), Sungei
Buloh Nature Park (mangrove), and Sungei Mandai (mangrove)
could not be estimated. It is reasonable to assume that these sites
with positive travel cost coefficients have low use value.
Average individual consumer surplus and total consumer
surplus (Table 2) were calculated using the results generated
from the visitation regression equation. The consumer surplus
measured the economic benefits attached to each site. Two of
the beaches had relatively low values per person, whereas Pasir
Ris and East Coast Park beaches were valued at 65 and 426
USD, respectively. The two low-valued beaches were worth an
aggregate value of 140 000 and 1.5 million USD, but the two
most popular beaches were valued at 167 million and 1090
million USD per year. The consumer surplus estimates for
marshes were much less. The most popular marsh was worth
only 240 000 USD in total. The estimates for the mangrove
estuaries were the lowest. The only valued mangrove was worth
just 815 USD per year. This approach suggests that the beaches
are worth far more than the other natural sites and that the
most popular beaches are worth considerably more.
RESULTS
Survey
Figure 1 shows the location of every respondent. As can be seen
from Figure 1, the survey was distributed evenly across the
Figure 2. The geographical location of the 11 natural resource sites
studied.
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291
Table 1. Visitation regression model.
Beach
1
Independent
Variables:
Constant
Travel cost
Age
Gender
Children
Income
R2
Changi
Beach
Park
(CBP)
2.28
(3.61)
–0.04
(2.37)
–0.03
(2.17)
0.48
(2.51)
–0.05(
–0.33)
–0.37E–06
(0.33)
0.06
2
Marsh
3
East Coast Pasir Ris
Park
Park
(PRP)
(ECP)
25.03
(2.12)
–1.48
(3.27)
–0.17
(0.77)
–0.45
(0.13)
–0.004
(0.001)
–0.6E–05
(0.31)
0.04
Mangrove
4
5
6
7
West
Coast
Park
(WCP)
Kranji
Reservoir
Marshes
(KRM)
Ponyan
Marsh
(PM)
Sungei
Khatib
Bongsu
(SKB)
9.87
0.33
–0.10
(1.36)
(0.21)
(0.21)
–0.53
–0.12
–0.02
(2.11)
(2.03)
(1.31)
–0.05
–0.004
0.02
(0.35)
(0.15)
(2.33)
–0.02
0.13
0.10
(0.007)
( 0.29)
(0.75)
–1.39
–0.53
–0.003
(0.88)
(1.63)
(0.03)
–0.2E–04
0.7E–05
0.2E–06
(1.66)
(2.55)
(0.29)
0.04
0.04
0.02
8
9
Pasir Ris
Sungei Buloh
Park
Marshes Nature Park
(SBNP)
(PRPM)
0.16
–0.10
0.85
(1.05)
(0.67)
(1.10)
–0.007
0.01
–0.07
(1.66)
(1.22)
(2.18)
–0.0007
0.002
–0.008
(0.27)
(0.69)
(0.57)
0.08
0.06
0.09
(1.93)
(1.52)
(0.40)
–0.01
–0.03
0.18
(0.48)
(0.95)
(1.04)
–0.2E–07
0.1E–06
0.2E–05
(0.08)
(0.49)
(1.29)
0.03
0.03
0.03
–0.12
(0.42)
0.006
(0.61)
0.004
(0.86)
–0.09
(1.08)
0.03
(0.52)
0.3E–06
(0.61)
0.02
10
11
Sungei
Mandai
(SM)
Sungei
Punggol
(SP)
–0.15
0.34
(1.15)
(2.05)
0.005
–0.006
(0.79)
(0.68)
0.002
–0.0019
(0.81)
(0.63)
0.04
0.008
(1.17)
(0.16)
0.05
0.10
(1.80)
(2.87)
–0.6E–07 –0.2E–06
(0.30)
(0.62)
0.03
0.03
OLS regression model, which estimated the relation between the number of visits, travel cost, and other demographic factors. The t-statistic is in parentheses. There were 338 observations in
these regressions.
Contingent Valuation
Figures 3 to 5 reflect the responses to the questions about
responsibility for protecting natural resources, such as the
beaches, marshes, and mangroves. These questions were aimed
at determining general public attitudes and specifically determining whether people were likely to be hostile to the survey.
Only 24% of the respondents agreed that it was their
responsibility to pay for the protection of beaches, marshes,
and mangrove estuaries (Fig. 3). A significant number, 46%, of
the respondents did not know if it was their responsibility or
not. The remaining respondents, 30%, believed that they were
not responsible for the cost of protecting natural resources.
However, this does not imply that these respondents would not
be willing to pay for the protection of natural resources.
The majority (90%) of the respondents agreed that polluters
should bear the cost of damages resulting from global warming,
and hence, should protect natural resources from inundation
(Fig. 4). Residents of Singapore believe in the ‘‘polluter pays’’
principle. They also believe that resources would not be
protected, even if the public paid, as reported by 44% of the
respondents (Fig. 5). About 25% of the respondents felt that
their payment would not aid in protecting nonmarket lands.
The respondent’s attitudes suggested that many of the
respondents might protest against a survey that asked them to
pay to protect Singapore against the damages of sea-level rise.
Twenty respondents, who answered negatively to all of the
above three questions and gave zero as the willingness to pay for
the protection of beaches, mangrove estuaries, and marshes
(Questions 11–13), were identified as protesters. They were
removed from the estimation of contingent valuation (32).
We next estimated the actual WTP of each respondent using
two approaches. A tobit model was used to estimate the
combined probability that someone would pay and how much
he or she would pay. The second approach used a two-equation
model that first used a probit model to determine whether
someone would pay, followed by a conditional Ordinary Least
Squares (OLS) regression to estimate the amount that they
would pay (Tables 3–5). This probit model created a dummy
variable, 0, for respondents who gave a zero willingness to pay
estimate, and 1 for respondents who gave a positive value.
Hence, only respondents who agreed to pay a positive amount
were included in the OLS regression. Both approaches
generated similar results across questions asking about protecting (both 50% and 100% of) the beaches, marshes, and
mangroves. We consequently present only the results from the
100% protection case in Tables 3–5.
In the regression for beaches, Table 3, family size was only
significant in the probit model, where larger families were more
likely to be willing to pay for protection. Gender and income
level were significant in both the conditional OLS and tobit
models. Men and higher-income families were willing to pay
more for protection of beaches. Age, number of children, and
education were not significant in any regression.
The probit results in Table 4 suggest that families with
children are less likely to be willing to pay to protect marshes,
Figure 3–5. The public should bear the responsibility for the protection of natural resources. Polluters should pay to fix the damages from
global warming. The natural resources would not be protected even if the respondents paid.
292
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Ambio Vol. 35, No. 6, September 2006
but larger families are more likely to be willing. According to
the conditional OLS and tobit models, males and higher-income
families are willing to pay more for marsh protection, as with
beach protection. Identical results apply to the mangrove
models in Table 5.
The CVM responses were then used to derive the willingness
to pay of the public for the protection of nonmarket lands
(Table 6). Beach protection had the highest willingness to pay
value. On average, people were willing to pay 23 USD per year
to protect 50% of the beaches and 33 USD for 100% protection.
Mangrove and marsh protection were valued only slightly less.
People were willing to pay about 18 USD per year to protect
50% of the mangroves and marshes and 25 USD for 100%
protection. Summing these results across the entire adult
Singapore population gives the resulting aggregate estimates
of WTP. The CVM results suggest much higher values for the
mangroves and marshes than the TCM results. However, the
CVM generated values for beaches were consistent with the
range of values measured by the TCM.
Table 2. Consumer surplus (CS) values derived from visitation
regression model.
Name
Changi Beach Park
East Coast Park
Pasir Ris Park
West Coast Park
Kranji Reservoir Marshes
Poyan Marshes
Sungei Khatib Bongsu
Pasir Ris Park Marshes
Sungei Buloh Nature Park
Sungei Mandai
Sungei Punggol
Characteristic
Beach
Beach
Beach
Beach
Marsh
Marsh
Marsh
Marsh
Mangrove
Mangrove
Mangrove
CS/
person
Total Value
(2005
USD/year)
*0.053
*140
*426
*1 090 341
*65
*167 106
*0.58
*1 487
0.0059
20
0.0003
N/A
N/A
*0.095
*239
N/A
N/A
N/A
N/A
*0.0003
441
680
714
368
562
686
875
815
Statistically significant values are marked with an asterisk (*). All values are in 2005 USD.
COST OF PROTECTION
Table 3. Probit, OLS, and tobit estimation of WTP for beach
protection.
Beaches
The sea-level rise literature focuses on protecting coastlines by
building sea walls (12, 33). Whereas that is a feasible strategy for
developed land, it is not suitable for beaches, as it would not
provide a continuous transition between the land and sea.
Singapore is actually a frontier leader in reclaiming beach from
the sea. Singapore has long explored building hard structures
under the sea in order to reclaim land for the island. After
constructing the underwater hard structure, engineers raise the
sand levels behind the structure. The result is a beach that
appears natural from the land. This approach requires two
major costs: the hard structure and the sand.
We follow a careful adaptation strategy that builds sea walls
over time as they are needed (34). This approach takes into
account the sea-level rise that has occurred up to each moment
of time and designs the least-cost strategy for the expected
future. The faster sea levels rise, the quicker adaptations must
be taken. However, if the sea rises slowly, decision makers have
more time to act.
We examine applying this strategy to three sea-level rise
scenarios over the next hundred years. The timelines involve a
0.2, 0.49, and 0.86 m increase in sea level by 2100 (1, 35). These
three scenarios span the range of effects predicted by the IPCC.
For each scenario, a hard structure is constructed when the sea
level rises to a certain height. In the 0.2 m sea-level rise scenario,
only a single structure will be built and it will be done in 2080.
With the 0.49 m scenario, the first structure will be built in 2040,
and a taller replacement will be built in 2100. In the 0.86 m
scenario, three structures will be built in 2020, 2060, and 2100.
The more rapid the sea-level rise, the earlier the first structure
must be built and the more frequently it must be replaced by a
higher wall.
Although the use of such structures to protect against sealevel rise has not been suggested before, Singapore has had
extensive experience with the approach. Almost all the existing
beaches in Singapore are artificial and have been constructed
with granite stones, which generally have a design life between
50 and 100 years (17). Beach sand is not a scarce resource;
hence, this approach may be a practical and economical option
to protect key beaches from sea-level rise. Beach nourishment
also requires maintenance in the form of constant sand
replenishment, every 5–10 years (36). The current cost of sand
is estimated to be 30 USD per cubic meter, while the present
value of the stream of maintenance costs (MC) is assumed to be
Ambio Vol. 35, No. 6, September 2006
Dependent Variable: Willingness to Pay 100% Protection
Observations
Independent Variables:
Constant
Age
Gender
Children
Education
Family size
Income
R2
318
278
318
Probit
Linear(OLS)
Tobit
0.86
(7.46)
–0.04
(1.69)
–0.05
(1.39)
–0.01
(0.48)
0.01
(0.22)
0.03
(2.51)
0.24E–06
(1.21)
0.06
48.35
(1.41)
–0.01
(0.02)
27.00
(2.45)
5.73
(0.75)
–5.41
(0.33)
–2.43
(0.63)
0.26E–03
(4.32)
0.09
36.02
(1.13)
–0.12
(0.21)
21.73
(2.20)
1.79
(0.27)
–4.17
(0.28)
0.17
(0.05)
0.26E–03
(4.63)
0.12
Figures in parentheses are the t-statistic values.
Table 4. Probit, OLS, and tobit estimation of WTP for marsh
protection.
Dependent Variable: Willingness to Pay 100% Protection
Observations
Independent Variables:
Constant
Age
Gender
Children
Education
Family size
Income
R2
318
242
318
Probit
Linear(OLS)
Tobit
0.45
(2.87)
0.001
(0.39)
0.03
(0.69)
–0.07
(2.16)
0.04
(0.52)
5.6E–02
(3.23)
3.1E–07
(1.15)
0.06
18.8
(0.51)
0.31
(0.45)
37.02
(3.16)
6.49
(0.79)
–2.96
(0.17)
–1.76
(0.42)
2.8E–04
(4.39)
0.13
–8.86
(0.29)
0.42
(0.75)
29.47
(3.15)
–1.88
(0.30)
1.89
(0.13)
2.06
(0.61)
2.4E–04
(4.64)
0.10
Figures in parentheses are the t-statistic values.
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293
Table 5. Probit, OLS, and tobit estimation of WTP for mangrove
protection.
Table 7. Total impact of sea-level rise on beaches in Singapore
until 2100.
Dependent Variable: Willingness to Pay 100% Protection
Observations
318
242
318
Independent Variables:
Probit
Linear(OLS)
Tobit
Benefit of
Assumed Benefit of
Sea-level
Cost of
years of protection protection
rise
(travel cost) protection
(WTP)
scenario Year protection
Constant
0.48
(3.11)
0.002
(0.75)
0.02
(0.32)
–0.07
(2.19)
0.04
(0.6)
0.05
(2.78)
0.12
(0.45)
0.04
Age
Gender
Children
Education
Family size
Income
R2
26.69
(0.73)
0.12
(0.18)
38.32
(3.34)
6.07
(0.74)
–5.19
(0.3)
–2.53
(0.62)
0.34
(5.17)
0.15
–6.96
(0.23)
0.46
(0.83)
29.19
(3.11)
–2.18
(0.34)
2.44
(0.17)
1.15
(0.34)
2.6E–04
(4.94)
0.11
Figures in parentheses are the t-statistic values.
4% of the construction cost. The volume of sand (VS) required
varies from beach to beach and is replenished at different times
according to the different sea-level rise scenarios. We estimate
the cost of protecting each of the four beaches used in the travel
cost study. The cost of beach protection includes the
construction cost of the underwater hard structures (CS), the
cost of sand, and the maintenance cost (MC):
TC ¼ CS þ VS 3 50 þ MC:
Eq: 6
The total cost (TC) ranges from approximately 336 000 USD to
4.37 million USD for the four beaches in the 0.2 m sea-level rise
scenario. The cost of protection increases dramatically together
with the height of the sea wall. In the 0.49 m scenario, the
second wall required in 2100 costs from 1.50 million to 19.51
million USD, depending on the length of the beach. In the 0.86
m scenario, the cost of the third wall ranges from 2.54 million to
32.99 million USD. (Costs of beach, marsh, and mangrove
protection in 0.2, 0.49, and 0.86 m sea-level rise scenarios are
available from the authors upon request.)
Marshes and Mangroves
In many countries, the most efficient method to preserve
marshes and mangroves in their natural state is to allow them to
migrate inland as sea level rises. This requires that inlanddeveloped land be sacrificed to advancing mangroves and
marshes. The cost of this approach is the lost value of the inland
area. In Singapore, the inland spaces are mostly developed,
which makes this approach too expensive to be feasible.
BENEFITS AND COSTS
In this section, we compare the costs and benefits of different
adaptation strategies to deal with sea-level rise for each
resource. We compare the two different estimates of benefits
from the travel cost and contingent valuation study respectively.
The benefits of protection derived from the travel cost study are
Table 6. Willingness to pay (WTP) for 50% and 100% protection of
natural resource.
Beaches
Willingness to Pay
Average WTP/person
Total WTP
(millions of 2005 USD/year)
294
Marshes
Mangroves
50% 100% 50% 100% 50%
100%
23
33
18
25
18
26
58
83
45
64
47
65
0.2 m
0.49 m
0.86 m
2080
2040
2100
2020
2060
2100
80
60
60
40
40
40
5
4
13
2
5
11
352
002
132
841
220
526
81
60
199
43
79
174
236
750
324
130
234
952
7.37
8.99
32.88
6.41
31.16
55.62
Both cost and benefit of protection are shown in millions of USD, discounted to present
values, using a 4% discount rate. The frequency of protection measures depends on the
sea-level rise scenario.
significantly higher, due to the high frequency of visits made to
the beach sites. In Table 7, we examine beach adaptation
choices. With each sea-level rise scenario, there is a moment
when building a hard structure is required to protect the beach.
For each construction choice, we look at the present value of
benefits for that project evaluated at the moment the project is
to be executed. We assume that without the protection, the
beach would lose its annual recreation value. For example, the
first sea wall built to protect against the 0.49 m sea-level rise
increase must be built in 2040. The structure is supposed to last
until 2100. We take the construction costs in 2040 and compare
them to the stream of benefits from 2040 to 2100 evaluated in
2040 Singapore dollars. The present value in 2040 of the stream
of benefits is:
h
Z 2100
i
Bt
3 1 erð21002040Þ :
Bt erðt2040Þ dt ¼
PV ðBt Þ ¼
r
2040
Eq: 7
The results in Table 7 reveal that the benefits of beach
protection far outweigh the costs. Every single beach
adaptation project is justified whether one uses travel cost or
contingent valuation. Singapore should protect its more
valuable beaches against sea-level rise, regardless of the
scenario. Since the time line applied in this study is from the
present to 2100, protection cost and benefit values are only
estimated until 2100. The discount rate used in the benefit
estimation for all three resources is 4%. A lower rate of 2% will
result in higher benefit values, but these would not be
substantial enough to alter the predicted year or frequency of
sea-level rise protection, particularly in the cases of marshes and
mangroves.
For marshes and mangroves, we take a decadal approach to
analyze protection decisions. Every decade, we examine what it
would cost to move the marsh or mangrove back into land that
is now developed. If the resource is allowed to move back, we
assume that it will provide another decade of benefits. The cost
of protection is the value of lost developed land. Both the costs
and benefits are evaluated as though the decision must be made
at the beginning of each decade.
The decadal costs and benefits of marsh and mangrove
protection are shown in Table 8. The consumer surplus values
derived from the travel cost method are minimal for marshes
and almost negligible for mangrove protection. The costs of
protecting both resources exceed the estimated benefits using
travel cost analysis, due to the high value of land in Singapore.
The travel cost analysis suggests that Singapore should not
allow either resource to migrate inland. The contingent
valuation values in Table 8 for marsh and mangrove protection
are much higher. These analyses suggest that it is reasonable to
pay for inland migration at least initially, if sea level increases
follow the lower scenarios. However, with the 0.86 m sea-level
rise, inland migration eventually becomes very expensive, and
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Ambio Vol. 35, No. 6, September 2006
Table 8. Total impact of sea-level rise on marshes and mangroves
in Singapore.
Benefit of protection
Year
Marsh
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
Mangrove
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
Cost of protection
Sea-level rise scenario
WTP
Travel cost
0.2 m
0.49 m
0.86 m
1823
2192
2616
3087
3579
4027
4298
4128
3013
3673
7.44
8.94
10.67
12.60
14.60
16.43
17.53
16.85
12.30
14.99
40.66
99.53
143.94
184.71
222.06
256.19
287.31
315.59
341.22
364.35
99.53
143.94
184.71
222.06
256.19
287.31
315.59
341.22
364.35
385.15
174.79
252.78
324.37
389.96
449.91
504.57
554.24
599.24
639.86
676.37
0.02
0.03
0.03
0.04
0.05
0.05
0.05
0.05
0.04
0.05
41.84
60.50
77.63
93.34
110.98
124.00
135.76
146.41
156.01
164.64
102.81
150.48
194.33
234.51
267.93
301.49
332.06
359.77
381.98
404.55
185.29
264.23
340.20
409.87
473.56
531.62
584.41
629.30
672.54
711.47
1
2
2
3
3
4
4
4
3
3
841
212
641
116
612
064
338
167
041
707
All estimates are presented in millions of USD adjusted to present values using a discount
rate of 4%. The benefit of protection remains the same regardless of sea-level scenario,
while the cost of protection changes according to different scenarios. WTP is willingness
to pay.
further migration beyond 2070 is not economically justifiable.
With the remaining milder scenarios, the contingent valuation
analysis suggests that Singapore should fully protect both
marshes and mangroves.
DISCUSSION AND CONCLUSION
In general, knowledge regarding sea-level rise among the public
in Singapore was found to be low. Further, there was a strong
belief that producers and the government should bear the
responsibility of paying for any form of environmental
protection. Almost 90% of the respondents believed that
polluters should pay, and only 24% agreed that they, as
consumers, should pay for protection measures for natural
resources. About 44% of the respondents were skeptical
regarding the ultimate use of their payment, because they felt
that natural resources would not be protected even if they paid.
Although these negative attitudinal responses led us to drop 20
protestors, most of the population was willing to pay for
protecting beaches, marshes, and mangroves.
This study explored two measures of the benefits of
protecting natural sites from damage caused by sea-level rise.
The travel cost measure relied on people’s behavior to infer
values by examining where they choose to visit. The contingent
valuation method directly asked respondents for their values.
The two methods provided somewhat consistent measures of
values for beaches. The travel cost method differentiated
between some popular beaches that were highly valued and
some more remote beaches that were not. The contingent
valuation questions led to only one value of beaches. Overall,
the average value from the CVM was not that different from the
TCM. However, the contingent valuation method suggested
that mangroves and marshes were far more valuable than the
travel cost method implied. The CVM placed almost the same
value on all three coastal resources. The travel cost method
suggested that the marshes and mangroves had very little use
value. People did not enjoy visiting the sites. However, the
CVM revealed that the sites nonetheless may have had
Ambio Vol. 35, No. 6, September 2006
substantial nonuse value. People may have enjoyed simply
knowing that they were there.
The study also examined the costs of protection. All these
resources can be protected with underwater hard structures and
additional sand. In the long run, mangroves and marshes can
also survive by migrating inland as the sea rises. Although in
most tropical countries, migration may be the least-cost
alternative, the high level of development in Singapore makes
hard structures more attractive. Examining three sea-level rise
scenarios, we calculated what the costs will be to save the 11
sites examined in the travel cost study.
We compared the present value of the benefits of protection
from the travel cost and contingent valuation studies against the
costs. Both the travel cost and contingent valuation methods
suggested that it would be worthwhile to protect the beaches in
every sea-level rise scenario. The travel cost analysis, however,
revealed that it would not be worthwhile to protect the marshes
and mangroves. The cost of protection was orders of magnitude
more expensive than the benefits of the lost resources. In
contrast, the contingent valuation analysis suggested that
protection was worthwhile as long as sea-level rise was limited.
Once sea-level rise exceeded approximately 0.6 m, however, the
cost of protection became too high. However, for milder sealevel rise outcomes, the contingent valuation analysis suggested
that it would be worthwhile for Singapore to protect its marshes
and mangroves. The results of the travel cost and contingent
valuation analyses for marshes and mangroves were thus in
conflict with each other. This is an important methodological
issue to resolve in future studies.
Vulnerable coastal nations need to begin analyzing their
adaptation options against sea-level rise. They must weigh the
benefits of their nonmarket coastal resources against the cost of
protection. Although it may be too early for countries to
institute adaptation measures, it is not too soon to begin
planning. Adaptive strategies require time to implement.
Countries with important coastal resources need to start
planning the strategies that they will adopt to reduce the
impacts of sea-level rise.
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37. First submitted 1 August 2005. Accepted for publication 25 January 2006.
Wei-Shiuen Ng is a research analyst at the World Resources
Institute. Her address: 10 G Street NE Suite 8000, Washington, DC 20008, USA. Fax: 1-202-729-7775; Telephone
Number: 1-202-729-7722.
wng@wri.org.
Robert Mendelsohn is a professor of economics at Yale
University School of Forestry and Environmental Studies. His
address: 230 Prospect Street, New Haven, CT 06511, USA.
Fax: 1-203-387-0766; Telephone Number: 1-203-432-5128.
robert.mendelsohn@yale.edu.
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