Estimates of the Economic Effects of Sea Level Rise

Abstract

Regional estimates of direct cost (DC) are commonly used to measure the economic damages of sea level rise. Such estimates suffer from three limitations:(i) values of threatened endowments are not well known, (ii) loss of endowments does not affect consumer prices, and (iii) international trade is disregarded. Results in this paper indicate that these limitations can significantly affect economic assessments of sea level rise. Current uncertainty regarding endowment values (as reflected in two alternative data sets), for example, leads to a 17 percent difference in coastal protection, a 36 percent difference in the amount of land protected, and a 36 percent difference in DC globally. Also, global losses in equivalent variation (EV), a welfare measure that accounts for price changes, are 13 percent higher than DC estimates. Regional EV losses may be up to 10 percent lower than regional DC, however, because international trade tends to redistribute losses from regions with relatively high damages to regions with relatively low damages. Copyright Kluwer Academic Publishers 2001

Full text

Environmental and Resource Economics 19: 113–129, 2001.
© 2001 Kluwer Academic Publishers. Printed in the Netherlands. 113
Estimates of the Economic Effects of Sea
Level Rise
ROY F. DARWIN1and RICHARD S. J. TOL2
1Economic Research Service, U.S. Department of Agriculture, Washington DC, USA; 2Centre for
Marine and Climate Research, Hamburg University, Hamburg, Germany; Institute for
Environmental Studies, Vrije Universiteit, Amsterdam, The Netherlands and Center for Integrated
Studies of the Human Dimensions of Global Change, Carnegie Mellon University, Pittsburgh, PA,
USA
Accepted 28 November 1999
Abstract. Regional estimates of direct cost (DC) are commonly used to measure the economic
damages of sea level rise. Such estimates suffer from three limitations: (i) values of threatened
endowments are not well known, (ii) loss of endowments does not affect consumer prices, and (iii)
international trade is disregarded. Results in this paper indicate that these limitations can significantly
affect economic assessments of sea level rise. Current uncertainty regarding endowment values (as
reflected in two alternative data sets), for example, leads to a 17 percent difference in coastal protec-
tion, a 36 percent difference in the amount of land protected, and a 36 percent difference in DC
globally. Also, global losses in equivalent variation (EV), a welfare measure that accounts for price
changes, are 13 percent higher than DC estimates. Regional EV losses may be up to 10 percent lower
than regional DC, however, because international trade tends to redistribute losses from regions with
relatively high damages to regions with relatively low damages.
Key words: direct cost, economic impacts, equivalent variation, sea level rise
JEL classification: D58, Q00, Q24
1. Introduction
Sea level rise is among the most profound impacts of climate change. Thermal
expansion of ocean waters and melting of land-ice due to higher ambient tempera-
tures would lead to a rise in the average sea level by about 50 cm by the end
of the next century (Warrick et al. 1996). Human activities cluster near low-lying
coasts because of the fertility of land in deltas, proximity of sea food, and transport
opportunities. The coastal zone is also one of the most productive and diverse
natural areas (Vellinga and Leatherman 1989). Even a relatively modest sea level
rise would thus have a substantial effect on human society, unless, perhaps costly,
protective measures are undertaken (Bijlsma et al. 1996). A number of studies have
tried to quantify the impacts of sea level rise (Fankhauser 1994; Hoozemans et al.
1993; Leatherman and Nicholls 1995a, b; Nicholls 1995; Nicholls and Hoozemans

114 ROY F. DARWIN AND RICHARD S. J. TOL
1996; Nicholls and Mimura 1998; Nicholls et al. 1995; Yohe et al. 1995, 1996;
Yohe and Schlesinger 1998). These studies are far from perfect: data bases are
rough and incomplete, and methods used are crude (Bijlsma et al. 1996). The
studies are also less than satisfactory from an economic point of view. Human
adaptation, for example, is either absent or unrealistically sophisticated (West et al.
1998).
Another shortcoming is that welfare estimates are often confined to direct cost
(DC) – the value of land and/or capital lost plus investments is coastal protection.
Such estimates suffer from three limitations. First, the value of land and capital
located in coastal areas threatened by sea level rise is not well known. Because
of their influence on the optimal level of coastal protection, different assumptions
about land and capital values have an indirect as well as an immediate effect on
DC estimates. Second, DC is only a first order approximation of welfare losses. By
assuming constant prices, it neglects second order effects. Third, DC is generally
estimated for specific regions in isolation. Because of international trade, however,
the economic impacts of sea level rise are likely to spill across regional and national
boundaries and affect areas with little or no immediate damages. The purpose of
this paper is to illustrate and evaluate the extent to which these limitations may
distort estimates of the economic losses that might be generated by sea level rise.
2. Procedures
We illustrate the limitations of the DC method with two models – the Climate
Framework for Uncertainly, Negotiation and Distribution (FUND; cf. Tol 1997,
1999a–e) and the Future Agricultural Resources Model (FARM; cf. Darwin 1999;
Darwin et al. 1995, 1996). By combining values of land and capital with per-unit
costs of coastal quantities and costs of dryland and wetland lost to sea level rise.
We use FUND to estimate and compare the effects of different assumptions about
land and capital values on these optimal levels. FARM contains a twelve-region
geographical information system (GIS) that estimates the type of land lost to sea
level rise and an eight-region computable general equilibrium (CGE) economic
model that estimates DC and equivalent variation (EV), a welfare measure that
also accounts for second order economic effects. Because FARM’s CGE economic
model is global, it also simulates international trade. Hence, we use FARM to
estimate and compare DC with EV and to evaluate cross-boundary spillovers due
to international trade.
2.1. POTENTIAL GEOPHYSICAL IMPACTS OF SEA LEVEL RISE
The impacts of a 0.5-m rise in sea level are evaluated in the twelve regions defined
in FARM’s GIS (see Table I). For each region, Table II presents estimates of the
length of coast at risk, the potential dryland loss without protection, the potential
wetland loss without protection, and the additional potential wetland loss if full

ESTIMATES OF THE ECONOMIC EFFECTS OF SEA LEVEL RISE 115
Table I. Description of the regions.
Acronym Name Description
USA United States of America United States of America
CAN Canada Canada
EC European Community 12 members countries of EC in 1990
JPN Japan Japan
ANZ Australia and New Zealand Australia and New Zealand
OEA other East Asia South Korea, China, Hong Kong, Taiwan
SEA South East Asia Indonesia, Malaysia, Philippines, Thailand
LAaLatin America Latin America
OEaother Europe European countries not in EC and
former Soviet Union
fSUMaformer Soviet Union and Mongolia former Soviet Union and Monoglia
OAOaother Asia and Oceania Middle East, South Asia, and Oceania
AFRaAfrica Africa
aFARM’s Computable General Equilibrium economic model groups these regions into one “Rest
of the World” region. FARM’s Geographical Information System, however, does track some
information about these regions so as to conduct partial equilibrium analyses.
protection for dryland were implemented. The coast length of all countries in the
world was taken from the Global Vulnerability Assessment (GVA) by Hoozemans
et al. (1993), an update of work earlier done for the Intergovernmental Panel on
Climate Change (IPCC CZMS, 1990, 1991). Other sources, such as the proceed-
ings of the 1993 World Coast Conference (Bijlsma et al. 1994), Nicholls and
Leatherman (1995a, b) and Fankhauser (1994) use (occasionally widely) different
estimates of the length of the coast of particular countries. However, the length of
a coast depends on the measurement procedure. The GVA is based on an internally
consistent, globally comprehensive data set and therefore used here. Threatened
coastlines are small portions of the total coastlines of the various regions (cf. Figure
3.1 of Hoozemans et al. 1993). The land area threatened ranges from 0.01 percent
in Canada to 1.03 percent in Southeast Asia for an overall average of 0.25 percent.
Wetland losses for a 0.5-m sea level rise were taken from the GVA and, where
available, replaced with results from country studies as reported by Bijlsma et al.
(1996) and some additional studies reported by Nicholls and Leatherman (1995a,
b) and Beniston et al. (1998). The reasons are this: (i) the GVA is a desk study
which occasionally shows signs of the great haste of its preparation; (ii) the country
studies use local data; and (iii) land lost because of sea level rise is more obviously
estimable than coast length. Bijlsma et al. (1996), however, only report wetland
losses in the absence of coastal protection. The GVA reports wetland losses both
with and without coastal protection for all countries. The country-specific ratio
between the two was used to derive wetland losses with protection according to
Bijlsma et al. (1996).

116 ROY F. DARWIN AND RICHARD S. J. TOL
Table II. Coastline, dryland and wetland threatened by a 0.5 metre sea level rise.
Region Coastline Dryland Wetland Wetlanda
(km) (km2)(km
2)(km
2)
USA 28,716 10,000 5,700 395
CAN 4,554 485 0 0
ECb32,788 1,962 1,605 451
JPN 4,463 1,150 287 4
ANZ 18,415 1,568 128 92
OEA 27,768 17,694 2,940 890
SEA 29,808 22,907 7,341 2
LA 39,233 28,515 22,892 2,578
OE 28,850 1,089 19 1
fSUM 22,097 7,569 0 0
OAO 77,018 90,129 24,130 0
AFR 34,665 67,477 15,248 173
aAdditional wetland threatened by full protection.
Dryland losses are not reported in the GVA, but they are by Bijlsma et al. (1996).
The GVA reports people-at-risk, which is the number of people living in the one-
in 1000-year flood plain, weighted by the chance of inundation. Combining this
with the GVA’s coastal population densities, area-at-risk results. The relationship
between area-at-risk and land loss for the 18 countries in Bijlsma et al. (1996)
was used to derive land losses from the GVA’s area-at-risk for the other countries.
We used the geometric mean of the ratio between Bijlsma’s area-at-risk and land
loss as a correction factor. This procedure introduces additional uncertainty. The
review of the SCOR Working Group 89 (1991) shows that land loss estimates due
to climate change are not very accurate.
2.2. VALUES OF LAND,CAPITAL,AND COASTAL PROTECTION
Following Fankhauser (1994), the OECD average of dryland value in FUND was
set at 2 million U.S. dollars per km2. Regional values follow from correcting for
GDP per km2(based on population density in the coastal zone, as reported by
the GVA, and income per capita). The OECD average of wetland value was set at
5 million dollars per km2, again following Fankhauser (1994). Regional wetland
values follow from scaling with:
GDP/Capita
20,000 
1+GDP/Capita
20,000 (1)

ESTIMATES OF THE ECONOMIC EFFECTS OF SEA LEVEL RISE 117
Table III. Assumed values of drylands, wetlands, and protection costs.
Region FUND FARM
ProtectionaDrylandbWetlandbDrylandbWetlandbCapitalb
(106$/km) (106$/km2)(10
6$/km2)(10
6$/km2)(10
6$/km2)(10
6$/km2)
USA 3.3 1.56 5.90 0.53 0.013 0.84
CAN 2.8 0.16 5.92 0.02 0.002 0.01
EC 3.4 19.89 5.21 2.91 0.038 10.34
JPN 6.6 21.87 6.22 16.99 0.089 26.33
ANZ 2.0 0.12 5.29 0.08 0.002 0.07
OEA 5.9 0.74 0.34 0.66 0.001 0.49
SEA 1.6 0.31 0.49 0.14 0.012 0.09
LAc4.3 0.26 0.78 0.06 0.009 0.03
OEc1.6 1.49 1.75 0.38 0.005 0.20
FSUMc2.4 0.19 3.10 0.05 0.006 0.03
OAOc4.1 0.43 0.26 0.11 0.001 0.06
AFRc3.0 0.31 0.30 0.08 0.001 0.04
aTotal, undiscounted costs of protection against a 1 metre sea level rise in 100 years, as reported by
Hoozemans et al. (1993).
bNet present value, based on an effective discount rate of 1% and an infinite time horizon; see text
for derivation.
cFARM’s CGE model groups these regions into one ‘rest of the world’. Aggregate net present values
are 0.26, 0.003 and 0.14 million $/km2for dryland, wetland, and capital, respectively. Regional
values are interpolated proportionally to the dryland values of FUND.
which is scaled to unity for the OECD in 1990. The costs of coastal protection
follow from the GVA, again where possible replaced by country study results. Table
III shows the values.
In FARM, land in each region is assigned to up to six climate-defined classes.
Land in each land class is further divided into five major uses and/or covers –
cropland, grazing land, forest land, land used in producing other economic goods
and services (e.g., urban, suburban, and industrial land), and “other” land (i.e.,
deserts, barren wilderness, and wetlands). Total annual regional returns to land
services for cropland and grazing land are derived from cost data in the Global
Trade Analysis Project (GTAP) database (Hertel 1993). These total returns are
distributed to the land classes based on each land class’s respective contributions
to crop and livestock production. Average rents for these two uses by land class are
obtained by dividing returns per use per land class by the number of hectares per
use per land class.
Returns to forest land in FARM are approximately one third the returns to
pasture. Rental values forurban, suburban, and industrial landin the currentversion
of FARM are approximately equal to cropland rents. This assumption is based n the
opportunity cost principle, e.g., that the cost of land used for urban and industrial

118 ROY F. DARWIN AND RICHARD S. J. TOL
purposes is the value that land would have if it were used for other purposes, in this
case, growing crops. Using cropland rents for opportunity costs isolates the biolo-
gically based productive capacity of urban land from its productive capacity due to
the proximity of large capital aggregates. Returns to “other” land are assumed to be
one-tenth the returns to forest land and are added to returns to land in the services
sector. The end result is that each region’s land is treated as a heterogeneous good
and each land-use-land-class combination has its own price.
Each land-use-land-class combination also is associated with an unknown
quantity of homogeneous capital, which also generates an annual return. Total
annual regional returns to capital for 13 commodities are derived from cost data
in the GTAP database (Hertel 1993). Returns by commodity are distributed to the
land classes based on each land class’s share of commodity production. Crop-
land produces three commodities: 1) wheat, 2) other grains, and 3) non-grains.
Pasture and forestland produce livestock and forest products, respectively. Urban,
suburban, and industrial land produces eight commodities: 1) coal, oil, gas, 2)
other minerals, 3) fish, meat, milk, 4) other processed foods, 5) textiles, clothing,
and footwear, 6) other nonmetallic manufactures, 7) other manufactures, and 8)
services. Average per-hectare capital returns by use and land class are obtained by
dividing returns per use per land class by the number of hectares per use per land
class. Because it supports relatively large aggregates of capital, urban, suburban,
and industrial land is associated with greater returns to capital per hectare than
land used for other purposes. Returns to capital on desert, barren wilderness, and
wetlands are zero because capital is assumed to be absent on such land.
The distribution of land at risk due to sea level rise by region, class, and use is
derived with FARM’s GIS by combining 10-minute resolution altitude data (U.S.
Navy, Fleet Navigational Operations Center 1992) with land-use and land-cover
data (Olson 1992) and FARM’s land-class data. We use the land-class-land-use
shares for dryland and wetlands implicit in this data to distribute FUND’s dryland
and wetland losses across FARM’s land uses and land classes. Regional estimates of
wetlands FARM’s coastal land are obtained with FUND’s ratios of wetland to total
land at risk in each region. Wetlands are distributed according to the land-class
shares of “other” land. All other FARM land types are dryland.
FARM’s wetland values in Table III are average values of all wetlands in the
land classes at risk to sea level rise in a given region. They do not reflect the value
of any environmental services that wetlands might provide. Hence they capture
only a small portion (less than 1 percent) of the wetland values considered by
FUND, which do include recreation and nature values. Dryland values are average
values of all land not wetland in the land classes at risk. They reflect only 13
percent to 89 percent of the dryland values assumed by FUND. This is due in part
because FARM’s rental values for urban, suburban, and industrial land only reflect
its biologically-based productive capacity.
FARM’s capital values in Table III are average values of returns to fixed capital
per km2in the land-use-land-class combinations at risk. “Fixed” capital is capital

ESTIMATES OF THE ECONOMIC EFFECTS OF SEA LEVEL RISE 119
that could not be economically moved as sea leave rises. It consists primarily of
buildings, roads, piers, and similar items found near the seashore. Returns to fixed
capital are assumed to be equal to 0.5 total capital returns. The quantity per unit
area (and hence its value per unit area) is assumed to increase at the same rate
as land values in this analysis. Combining FARM’s capital and dryland values
together yields values that reflect 19 percent to 198 percent of FUND’s dryland
values. The relatively large differences between these values and the wetland
values clearly indicates that there is considerable uncertainly about the values of
endowments threatened by sea level rise.
2.3. ESTIMATING THE LEVEL OF COASTAL PROTECTION
Given values of land and protection, FUND calculates optimal levels and costs of
coastal protection as well as optimal quantities and costs of dryland and wetland
lost to sea level rise. The fraction of land protected against sea level rise follows:
L=max 0,1−1
2PC +WL
DL  (2)
Lis the fraction of the coastline to be protected. WL is the net present value of
wetland lost due to full coastal protection. DL is the net present value of dryland
lost to sea level rise. PC is the net present value of the protection if the whole
coast is protected. See Fankhauser (1994) for the derivation of (2). He uses a very
simple, large linear model so as to be able to express the optimal level of protection
in closed-form. Below, we use simple expressions for the growth of dryland losses,
wetland losses and protection costs so that their net present values can be expressed
in closed form too.
The GVA reports average protection costs per year over the next century (see
Table III). PC is calculated assuming annual costs to be constant. This is based on
the following. First, the coastal protection decision makers anticipate a linear see
level rise. Second, coastal protection entails large infrastructural works which last
for decades. Third, the considered costs are direct investments only, and techno-
logies for coastal protection are mature, that is, technologies and prices will not
change substantially in the future.
WL is the net present value of the wetlands lost due to full coastal protection.
Wetland values are assumed constant relative to income, reflecting how much
current decision makers care about the non-marketed services and goods that get
lost. The amount of wetland lost is assumed to increase linearly over time. DL
denotes the net present value of the dryland lost if no protection takes place.
Dryland values are assumed to rise at the same pace as the economy grows. The
amount of dryland lost is assumed to increase linearly over time.

120 ROY F. DARWIN AND RICHARD S. J. TOL
Throughout the analysis, a pure rate of time preference, ρ, of 1.0 percent per
year is used. The actual discount rate lies thus 1.0 percent above the growth rate of
the economy, g. The net present costs of protection PC are thus equal to:
PC =
∞
X
t=11
1+ρ+gt
PCa=1+ρ+g
ρ+gPCa(3)
where PCais the average annual costs of protection.
The net present costs of wetland loss WL follow from:
WL =
∞
X
t=1
t1
1+ρ+gt
WL
0=1+ρ+g
(ρ +g)2WL
0(4)
where WL0denotes the value of wetland loss in the first year.
The net present costs of dryland loss DL are:
DL =
∞
X
t=0
t1+g
1+ρ+gt
DL0=(1+g)(1+ρ+g)
ρ2DL0(5)
where DL0is the value of dryland loss in the first year.
2.4. ESTIMATING THE COSTS OF SEA LEVEL RISE
As land and fixed capital are lost to sea level rise or as resources are diverted from
other pursuits to coastal protection, the supply of consumer goods and services
in a region declines relative to a no-sea-level-rise scenario. This results in lower
production levels and higher prices. Direct cost is the value of land and/or capital
lost plus investments in coastal protection. Direct cost is also equal to the value of
consumer goods and service foregone (assuming constant prices) and so it provides
an estimate of welfare change. This and the fact that it is relatively easy to calculate
ensures its popularity in the literature (Cline 1992; Fankhauser 1994; Jansen et al.
1991; Nicholls and Leatherman 1995a, b; Nordhaus 1991; 1994; Rijsberman 1991;
Titus 1992; Titus et al. 1991; Tol 1995, 1996; Yohe 1990, 1995, 1996).
In FUND, DC is calculated as the amount of wetland and dryland land lost
times their respective values plus the length of coast protected times the costs of
protection per km. FUND’s DC estimates are annuitised. Direct cost in FARM is
calculated as the amount of wetland per land class lost times its value per land
class, plus the amount of dryland per use per land class lost times its value per
use per land class, plus the amount of dryland per use per land class lost times the
amount of fixed capital returns lost per unit area per use per land class, plus the cost
of coastal protection. The amount of wetland and dryland lost as well as the costs
of coastal protection used in FARM’s calculations come from FUND. FARM’s DC
estimates (including the cost of coastal protection from FUND) are annual.

ESTIMATES OF THE ECONOMIC EFFECTS OF SEA LEVEL RISE 121
Direct cost does not reflect the total value of consumer goods and service fore-
gone as a result of sea level rise, however, because it does not take account of the
higher prices that would be generated by the relatively large loss of land andcapital
resources. Higher prices mean that consumers will not only have fewer goods and
services available to them, but also that each dollar spent on goods and services
will buy less. The effects of changing prices is captured with equivalent variation
(EV), another standard measure of welfare change. EV is the difference, in terms of
money expenditure – in this case at pre-sea-level-rise prices – between the level of
consumer satisfaction under sea level rise and the level of satisfaction under no sea
level rise. Estimates of EV are provided by FARM’s CGE model for eight regions.
Direct cost also does not accurately capture the geographical distribution of
welfare losses that sea level rise would generate. Lower production levels and the
higher prices induced in one region will spill over into other regions through inter-
national trade. Because it simulates international trade in, as well as production of,
13 commodities, FARM’s regional estimates of EV reflect the geographical distri-
bution of damages more accurately than do its regional estimates of DC. Hence a
comparison of FARM’s DC and EV estimates provides information about the extent
to which ignoring price changes and international spillovers generates affects the
measurement of the potential damages of sea level rise.
FARM simulates sea level rise by reducing land and capital quantities by
appropriate amounts. The total amount (km2) of wetland and dryland lost are
derived from FUND.TheFARM’s GIS derives the amount of land lost by use
and class and creates exogenous shocks (in percent change format) for FARM’s
CGE model that are consistent with land’s heterogeneity. FARM’s GIS also esti-
mates the total annual returns to fixed capital lost by region. These lost capital
returns are combined with FUND’s annual costs of coastal protection under the
following assumptions: (i) capital is treated as a homogeneous factor in FARM,
(ii) expenditures on structures that provide coastal protection are primarily returns
to capital because their construction is capital intensive, and (iii) the construc-
tion and/or maintenance of these capital structures preclude the purchase of other
capital structures. Regional percent changes of the combined total of lost returns
from this homogeneous capital are equivalent to regional percent changes in lost
capital itself, and, therefore, are utilized as the exogenous shocks to capital by
FARM’s CGE model. The losses are imposed on 1990 conditions in a comparative
static analysis. FARM’s CGE model is implemented and solved using GEMPACK
(Harrison and Pearson 1996).
3. Results
We first present FUND’s estimates of the level of coastal protection and the corre-
sponding land losses caused by a 0.5-m rise in sea level under two different
assumptions regarding the values of land and capital endowments. We then present
two sets of estimates of the economic costs of sea level rise. The first set contains

122 ROY F. DARWIN AND RICHARD S. J. TOL
Table IV. Level of coastal protection, dryland losses, and wetland losses in response to
a sea level rise of 0.5 m by source of endowment values and regiona.
Region FUND’s land values FARM’s land and capital values
CoastlinebDryland Wetland Coastline Dryland Wetland
(%) (km2)(km
2) (percent) (km2)(km
2)
USA 82 1,800 6,023 72 2,808 5,984
CAN 0 485 0 0 484 0
EC 92 163 2,019 80 386 1,967
JPN 97 38 290 98 27 290
ANZ 0 1,568 128 0 1,568 128
OEA 91 1.572 2,940 93 1,276 3,765
SEA 95 1,079 7,343 92 1,783 7,343
LA 83 4,755 25,040 49 14,535 24,156
OE 20 867 19 0 1,089 19
fSUM 0 7,569 0 0 7,569 0
OAO 90 5,144 24,130 82 16,073 24,130
AFR 86 9,442 15,396 56 29,475 15,345
aEstimated with FUND using results from equations (2), (4), and (5).
bCoastline threatened by sea level rise.
FUND’s estimates of annuitised DC based on the assumptions used for the coastal
protection estimates. The second set contains of DC and EV based on FARM’s
endowment values. A short discussion of the results ends this section.
3.1. LEVELS OF COASTAL PROTECTION
FUND’s estimates of the percent of threatened coastline protected as well as the
dryland and wetland lost to a 0.5 rise in sea level are presented in Table IV. Two
sets of estimates are presented. The first set is based on FUND’s land values while
the second set is based on FARM’s land and fixed capital values. Both sets rely on
FUND’s protection costs. As the level of protection depends on the ratio of protec-
tion costs and the value of the threatened endowments (see Equation (2)) and as
protection costs are the same in both the FUND-based and FARM-based estimates,
the regional pattern of protection levels follows directly from the regional pattern
of land values displayed in Table III.
For example, FUND-based levels of coastal protection are zero in three regions
– Canada, Australia/New Zealand, and the former Soviet Union (plus Mongolia).
FARM-based protection levels are zero in the same three regions plus other Europe.
The latter is due to FARM’s relatively low initial values of dryland plus fixed capital
in other Europe (Table III). FARM’s values of dryland plus fixed capital are lower
than FUND’sdryland values in the six other regions where FUND-based protection
levels are higher than FARM-based levels. Differences in coastline protection for

ESTIMATES OF THE ECONOMIC EFFECTS OF SEA LEVEL RISE 123
these six regions range from 3 to 69 percent. In the two regions where FARM-based
protection levels are higher than the FUND-based levels, FARM’s values of dryland
plus fixed capital are larger than FUND’s dryland values. Differences in coastline
protection in these regions are 1 and 2 percent. Overall, the amount of threatened
coastline protected in the FARM-based scenario is 17 percent lower on average than
that in the FUND-based scenario. As a result, the amount of total land lost in the
FARM-based scenario is 36 percent higher than that in the FUND-based scenario.
A comparison of land lost in Table IV with land threatened in Table II indi-
cates that coastal protection reduces the total amount of land lost to sea level rise.
Reductions in losses are limited, however, to dryland. Wetland losses are greater if
coastal protection is employed, especially in the US, EC, Other East Asia, and Latin
America. Equation (2) indicates that coastal protection decrease as wetland values
increase. We evaluate the magnitude of this phenomenon by estimating coastal
protection levels using FARM’s values for dryland and fixed capital but FUND’s
values for wetlands. Protection levels decline slightly relative to the case where
all values are from FARM (not shown). The regions most affected by the higher
wetland values were the United States and Latin America where protection of
the threatened coastline dropped to 71 percent and 48 percent respectively. Higher
wetland values did not affect the first two significant figures of coastal protection
in the other regions. The change is small because the amount of wetland lost to
coastal protection is relatively small (Table II).
3.2. ECONOMIC COST
Table V presents annuitised DC for a 0.5-m rise in sea level (with and without
coastal protection) based on both FUND and FARM’s endowment values. As
expected, annuitised costs with optimal protection are lower than net present costs
without optimal protection, about 65 percent for FARM’s endowment values and
about 75 percent for FUND’s endowment values. FARM-based DC is lower than
FUND-based DC in all regions except Japan and Other East Asia, where FARM-
based protection levels are higher than FUND-based protection levels. Without
coastal protection, FUND-based DC is 77 percent higher than FARM-based DC.
With coastal protection, FUND-based DC is 36 percent higher.
Table VI presents annual DC and lost EV based on FARM’s endowment values.
Direct cost is composed of the cost of protection, fixed capital lost, and land lost.
Annual protection costs are calculated withFUND and, given the linearity assump-
tions in this analysis, they would equal actual annual protection cost around 2050
when sea level rise is projected to rise 0.25 m. Values of fixed capital and land are
from FARM. FARM’s per-km2values of these endowments (Table III), however,
pertain to economic conditions in 1990. Because these values are expected to be
higher in 2050, total DC based on an area inundated by a 0.25-m sea level rise
would underestimate the 2050 damages. To compensate somewhat we assume that
the area inundated conforms to a 0.5-m rise in sea level in 2100. These costs are

124 ROY F. DARWIN AND RICHARD S. J. TOL
Table V. Annuitised direct cost (million dollars per year) for a 0.5 m rise in sea level rise by source
of endowment values, level of coastal protection, and regiona.
FUND’s land values FARM’s land and capital values
No protectionbProtectioncWetlandsdNo protectionbProtectioncWetlandsd
USA 2,772 1,317 653 1,697 1,162 1
CAN14140220
EC 6,954 1,638 163 2,826 1,448 1
JPN 4,483 433 35 6,181 435 1
ANZ 34 34 13 31 31 0
OEA 9,289 2,329 19 11,400 2,348 0
SEA 5,061 693 68 3,062 678 2
LA 5,210 2,316 336 1,667 1,683 0
OE 290 324 1 93 93 0
fSUM 251 251 0 80 80 0
OAO 27,809 4,597 119 8,932 4,210 0
AFR 3,700 1,408 88 1,184 1,100 0
Total 42,923 10,533 2,958 24,990 8,941 5
aEstimated with FUND using equations (2)–(5).
bValue of dryland lost to sea level rise.
cValue of dryland lost to sea level rise, coastal protection, and wetland lost to coastal protection.
dValue of wetland lost to sea level rise, excluding wetland lost to coastal protection.
relatively small, especially in developed regions, when compared to total regional
economic activity (e.g., total expenditures) in 1990. Direct cost for the first five
regions listed in Table VI ranges from almost nothing to 0.009 percent of total
expenditures in 1990. Direct cost for Other East Asia, South East Asia, and the
rest-of-world is, respectively, 0.105, 0.077, and 0.049 percent of total expenditures
in 1990.
Equivalent variation is estimated by FARM. World EV lost is $4,956 million,
approximately 13 percent higher than world DC, which is equal to $4,395 million.
The additional losses are not equally distributed across the regions. In developed
regions, differences between EV losses and DC range from $11 million to $290
million (from 43 percent to 8,213 percent). In developing and rest-of-world
regions, differences between EV losses and DC range from −$227 million to $28
million (from −10 percent to +4 percent).
3.3. DISCUSSION
TableIII indicates that there is considerable uncertainty in the value of endowments
threatened by sea level rise. Results in Tables IV and V indicate that these differ-
ences can have significant effects on the level of coastal protection, the amount of
land inundated, and overall costs that a given region might have to bear. This uncer-

ESTIMATES OF THE ECONOMIC EFFECTS OF SEA LEVEL RISE 125
Table VI. Annual direct cost and equivalent variation lost (million dollars per year)
for a 0.5 m rise in sea level with coastal protection by region.
Region Direct costs Equivalent
ProtectionaFixed CapitalbLandcTotal Variationd
USA 343 50 17 410 585
CAN 0 0 0 0 11
EC 446 90 13 549 839
JPN 144 11 5 160 421
ANZ 0 1 1 3 18
OEA 763 8 9 781 809
SEA 220 3 4 226 233
ROW 2,017 117 133 2,267 2,040
LA 417 27 32 475 –
OE 0 2 2 3 –
fSUM 0 4 4 8 –
OAO 1,309 51 58 1,419 –
AFR 291 33 37 361 –
Total 3,933 280 182 4,395 4,956
aEstimated with FUND using equation (2) and FARM’s values for land and fixed
capital.
bCombines land quantities estimated by FUND with FARM’s per-hectare fixed
capital values.
cCombines land quantities estimated by FUND with FARM’s land values.
dEstimated with FARM.
tainty may also pertain to those regions for which both FUND and FARM assume
that the value of threatened endowments is small. A more accurate assessment, for
example, might find that the value of Canadian endowments threatened by sea level
rise would be high enough to trigger a positive level of coastal protection.
Results in Table VI indicate that the DC approach provides inaccurate global
and regional estimates of the economic impacts of sea level rise. Globally, DC is
lower than EV because the former does not account for the higher prices that would
be generated by the loss of endowments that sea level rise would induce around the
world. Regionally, DC differs from EV not only because of rising prices but also
because of spillovers generated by international trade. In general, trade between
regions tends to redistribute losses from regions with relatively high damages to
regions with relatively low damages. This principle may also apply to FARM’s
ROW region, that is, EV losses would probably be smaller than DC in other Asia
(plus Oceania) but larger than DC in other Europe and the former Soviet Union
(plus Mongolia). It also means that regions without coastlines are likely to sustain
some economic hardships from sea level rise.

126 ROY F. DARWIN AND RICHARD S. J. TOL
Region-specific impacts on EV depend on the relative importance of land,
labour, and capital as sources of income, the composition of exports and imports,
and trade policies. This implies that the DC-EV comparison is subject to a few
limitations. One limitation pertains to the uncertainty surrounding the value of
endowments. Different regional estimates of DC, either in total or among endow-
ments, would have led to different estimates of EV. Another limitation is that
FARM imposes impacts of sea level rise projected for 2050 on 1990 conditions.
Differences in regional growth rates, however, mean that the 2050 pattern of trade
spillovers is likely to vary from the one depicted here.
4. Summary and Conclusions
Direct-cost estimates are commonly used to measure the economic damages of
sea level rise. Such estimates suffer from three limitations: (i) values of threatened
endowments are not well-known, (ii) loss of endowments does not affect consumer
prices, and (iii) international trade is overlooked. We have shown that, because of
these limitations, DC estimates may significantly misrepresent the economic losses
that might be generated by sea level rise, globally and even more so regionally.
For many parts of the world there is considerable uncertainty about the value
of land and capital endowments threatened by sea level rise. This is turn generates
uncertainty about the level of coastal protection, the amount of land inundated,
and overall DC that a given region might have to bear. In the example presented
in this paper, differences in endowment values lead to a 17 percent difference in
coastal protection, a 36 percent difference in the amount of land protected, and
a 36 percent difference in DC when coastal protection was implemented. When
coastal protection was not implemented, the difference in DC is 77 percent. One
way to reduce this uncertainty is to obtain more accurate data on the value of land
and capital in general. Ideally, values for both dryland and wetland would include
market and non-market components. A related activity would be to obtain data on
the value of water and labour (both market and household) endowments threatened
by sea level rise.
As a worldwide phenomenon, climate-induced sea level rise is likely to cause
significant losses in land and capital endowments in many regions simultaneously.
The size and scope of these losses will induce a general increase in consumer prices
that will generate economic costs above those considered by DC. In our example
global EV-based damages are 13 percent higher than DC-based damages. At the
same time, the response of international traders to differential changes in regional
prices will tend to redistribute losses from regions with relatively high damages
to regions with relatively low damages. This means that sea level rise is likely to
reduce economic welfare even in land-locked regions. The only way to overcome
these limitations is to substitute partial equilibrium analyses of isolated regions
with general equilibrium analyses of the world as a whole.

ESTIMATES OF THE ECONOMIC EFFECTS OF SEA LEVEL RISE 127
Finally, because the experiments conducted for this analysis do not accurately
depict reality in all respects, we recognize that our estimates of the potential
economic damages of sea level rise may be seriously flawed. This possibility,
however, should not detract one from the insights that the analysis in the paper
provides. The objective of this research was to determine the extent to which
limited knowledge of the value of endowments and inadequate modeling capa-
bilities may affect economic assessments of sea level rise. Our results indicate that
significant gains in accuracy are likely to be obtained with greater knowledge and
improved modeling capabilities.
Acknowledgments
This paper originates in the authors’ participation in the climate change impacts
workshop of the Energy Modeling Forum. We appreciate comments by two
anonymous reviewers. Any errors, of course, are ours. The views expressed herein
do not necessarily reflect those of the U.S. Department of Agriculture.
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