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Economy-wide Estimates of the Implications of Climate Change: Sea Level Rise


The economy-wide implications of sea level rise in 2050 are estimated using a static computable general equilibrium model. This allows for a better estimate of the welfare effects of sea level rise than the common direct cost estimates; and for an estimate of the impact of sea level rise on greenhouse gas emissions. Overall, general equilibrium effects increase the welfare costs of sea level rise, but not necessarily in every sector or region. In the absence of coastal protection, economies that rely most on agriculture are hit hardest. Although energy is substituted for land, overall energy consumption falls with the shrinking economy, hurting energy exporters. With full coastal protection, GDP increases, particularly in regions with substantial dike building, but utility falls, least in regions that protect their coasts and export energy. Energy prices rise and energy consumption falls. The costs of full protection exceed the costs of losing land. The results also show direct costs – the usual method for estimating welfare changes due to sea level rise – are a bad approximation of the general equilibrium welfare effects; previous estimates of the economic impact of sea level rise are therefore biased.

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We had useful discussions about the topics of this paper with Andrea Bigano, Carlo Carraro, Sam Fankhauser, Marzio Galeotti, Andrea Galvan, Claudia Kemfert, Hans Kremers, Katrin Rehdanz and Kerstin Ronneberger. Useful comments on an earlier draft of this paper were provided by J.A. Smulders and two anonymous referees, but remaining errors are only ours. Marco Lazzarin gave essential support during early stages of the research, in particular on model calibration, adaptation and simulation runs. The Volkswagen Foundation through the ECOBICE project, the EU DG Research Environment and Climate Programme through the DINAS-Coast (EVK2-2000-22024) and ENSEMBLES projects, the US National Science Foundation through the Center for Integrated Study of the Human Dimensions of Global Change (SBR-9521914), the Michael Otto Foundation for Environmental Protection, and the Ecological and Environmental Economics programme at ICTP-Trieste provided welcome financial support.

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Correspondence to Roberto Roson.

Appendix 1

Appendix 1

A Concise Description of GTAP-EF Model Structure

The GTAP model is a standard CGE static model, distributed with the GTAP database of the world economy (

The model structure is fully described in Hertel (1996), where the interested reader can also find various simulation examples. Over the years, the model structure has slightly changed, often because of finer industrial disaggregation levels achieved in subsequent versions of the database.

Burniaux and Truong (2002) developed a special variant of the model, called GTAP-E, best suited for the analysis of energy markets and environmental policies. Basically, the main changes in the basic structure are:

  • energy factors are taken out from the set of intermediate inputs, allowing for more substitution possibilities, and are inserted in a nested level of substitution with capital;

  • database and model are extended to account for CO2 emissions, related to energy consumption.

The model described in this paper (GTAP-EF) is a further refinement of GTAP-E, in which more industries are considered. In addition, some model equations have been changed in specific simulation experiments. This appendix provides a concise description of the model structure.

As in all CGE models, GTAP-EF makes use of the Walrasian perfect competition paradigm to simulate adjustment processes, although the inclusion of some elements of imperfect competition is also possible.

Industries are modelled through a representative firm, minimizing costs while taking prices are given. In turn, output prices are given by average production costs. The production functions are specified via a series of nested CES functions, with nesting as displayed in the tree diagram of Figure A1.


Notice that domestic and foreign inputs are not perfect substitutes, according to the so-called “Armington assumption”, which accounts for – amongst others – product heterogeneity.

In general, inputs grouped together are more easily substitutable among themselves than with other elements outside the nest. For example, imports can more easily be substituted in terms of foreign production source, rather than between domestic production and one specific foreign country of origin. Analogously, composite energy inputs are more substitutable with capital than with other factors.

A representative consumer in each region receives income, defined as the service value of national primary factors (natural resources, land, labour, capital). Capital and labour are perfectly mobile domestically but immobile internationally. Land and natural resources, on the other hand, are industry-specific.

This income is used to finance the expenditure of three classes of expenditure: aggregate household consumption, public consumption and savings (Figure A2). The expenditure shares are generally fixed, which amounts to saying that the top-level utility function has a Cobb-Douglas specification. Also notice that savings generate utility, and this can be interpreted as a reduced form of intertemporal utility.


Public consumption is split in a series of alternative consumption items, again according to a Cobb-Douglas specification. However, almost all expenditure is actually concentrated in one specific industry: Non-market Services.

Private consumption is analogously split in a series of alternative composite Armington aggregates. However, the functional specification used at this level is the Constant Difference in Elasticities form: a non-homothetic function, which is used to account for possible differences in income elasticities for the various consumption goods.

In the GTAP model and its variants, two industries are treated in a special way and are not related to any country, viz. international transport and international investment production.

International transport is a world industry, which produces the transportation services associated with the movement of goods between origin and destination regions, thereby determining the cost margin between f.o.b. and c.i.f. prices. Transport services are produced by means of factors submitted by all countries, in variable proportions.

In a similar way, a hypothetical world bank collects savings from all regions and allocates investments so as to achieve equality of expected future rates of return. Expected returns are linked to current returns and are defined through the following equation:

$$ r_{\rm s}^{\rm e}=r_{\rm s}^{\rm c}\left(\frac{ke_{\rm s}}{kb_{\rm s}}\right)^{-\rho} $$

where: r is the rate of return in region s (superscript e stands for expected, c for current), kb is the capital stock level at the beginning of the year, ke is the capital stock at the end of the year, after depreciation and new investment have taken place. ρ is an elasticity parameter, possibly varying by region, determining the sensitivity of regional investments to rate of returns differentials. When the model is calibrated, all variables on the right-hand side are known. Therefore, to be consistent with the assumption of equalization of expected returns, this elasticity parameter ρ is estimated accordingly. In this way, investment funds are modelled as imperfectly mobile in international markets.

Future returns are determined, through a kind of adaptive expectations, from current returns, where it is also recognized that higher future stocks will lower future returns. Regional investments determine the stocks of capital at the end of each period, so that the arbitrage condition on expected returns is satisfied.

In this way, savings and investments are equalized at the international but not at the regional level. Because of accounting identities, any financial imbalance mirrors a trade deficit or surplus in each region.

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Bosello, F., Roson, R. & Tol, R.S.J. Economy-wide Estimates of the Implications of Climate Change: Sea Level Rise. Environ Resource Econ 37, 549–571 (2007).

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  • computable general equilibrium
  • impacts of climate change
  • sea level rise

JEL classification

  • C68
  • D58
  • Q25