ICES Intertemporal Computable Equilibrium System

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ICES (Intertemporal Computable Equilibrium System) is a recursive dynamic general equilibrium model developed with the purpose to assess the final welfare implication of climate change affects regional and world economies. The model has been developed at the Climate Change Modelling and Policy Research Programme of the Fondazione Eni Enrico Mattei – FEEM, a research institution in the field of sustainable development.

Contents

[edit] Overview

As in every computable general equilibrium (CGE) model, its general equilibrium structure - in which all markets are interlinked - is tailored to capture and highlight the production and consumption substitution processes at play in the social-economic system as a response to climate shocks. In doing so, the final economic equilibrium determined, takes into account explicitly the autonomous adaptation of economic systems. The idea behind ICES is to provide a climate change impact assessment tool that can go beyond the simple quantification of direct costs, thus offering an economic evaluation summarising second and higher-order effects. In addition to climate-change impact assessment, the model can be used to study mitigation and adaptation policies as well as different trade and public-policy reforms in the vein of conventional CGE.

[edit] Model description

ICES is a top-down recursive growth model with a sequence of static equilibria intertemporally connected by endogenous investment decisions and capital accumulation. On the economic context, the model accounts for intersectoral factor mobility, international trade and also international investment flows allocated by a global financing entity. Within the climate change assessment framework, its general equilibrium characteristics have been suited to assess different global warming effects on sea level rise[1], agriculture[2], energy demand[3], health[4] and tourism[5]; and also include emissions of the main greenhouse gases (GHG): carbon dioxide, methane, and nitrous oxide. By taking advantage of the database from the Global Trade Analysis Project (GTAP) the model offers a flexible regional and sectoral disaggregation, which allows the analysis of climate effects at a global and regional scale. The importance of energy use and its sourcing is crucial, predominantly for the reason that carbon dioxide emissions are closely linked to fossil fuel combustion. Because of its essential role in economic development, energy commodities along capital have a special treatment as a capital-energy composite factor using a top-down approach[6] in ICES. Within this context the use and substitution of energy can be evaluated through time with the scope of analyzing climate driven policies such as those aimed to reduce GHG emissions.

[edit] Supply and demand

On the supply side, industries are modelled through a representative cost-minimizing firm, taking input prices as given. In turn, output prices are given by average production costs. The production functions are specified via a series of nested constant elasticity of substitution (CES) functions. Peculiar to ICES is the isolation in the production tree of energy factors which are taken out from the set of intermediate inputs and are inserted as primary production factors in a nested level of substitution with capital. The demand side is characterized by a representative consumer in each region, which receives income defined as the service value of national primary factors (land, labour, capital and natural resources). Capital and labour are perfectly mobile domestically but immobile internationally. Land and natural resources, on the other hand, are industry-specific. Income generated by factors is then used to finance three classes of expenditure: aggregate household consumption, public consumption and savings. The expenditure shares are generally fixed, which amounts to saying that the top-level utility function has a Cobb-Douglas specification. Demand for production factors and consumption goods can be satisfied either by domestic or foreign producers which are not perfectly substitutable according to the “Armington” assumption which accounts for product heterogeneity.

[edit] Dynamics

The model’s dynamic is driven both by exogenous and endogenous sources. The first source stems from exogenously imposed growth paths for some key variables – population, labour stock, labour productivity, land productivity. The values for these variables are taken from available statistics and projections from other modelling exercises. The second source concerns the process of capital accumulation. Capital stock is updated over time in order to take into account endogenous investment decisions: capital goods are allocated among different regions in such a way that the current rate of return to capital grows at the same pace with the global rate of return.

[edit] Example of regional aggregation

The model initially calibrated for 2001 is disaggregated in 8 world regions and 17 production sectors and recursively solved up to year 2050, creating a baseline in which the climate change impacts are imposed to assess their economic feedbacks. Since climate change impacts have a diverse effect on regions and sectors, the selected aggregation can reveal the general equilibrium impacts among sectors within a single region but takes into account also the interaction between regions through international trade and investment mobility.

[edit] See also

[edit] References

  1. ^ Bosello F., Roson R. and Tol R.S.J., (2007), “Economy-wide Estimates of the Implications of Climate Change: Sea Level Rise”, Environmental and Resource Economics , 37, 549-571.
  2. ^ Bosello F. and Zhang J., (2005), “Assessing Climate Change Impacts: Agriculture”[1], Fondazione Eni Enrico Mattei Working Paper N.94.2005.
  3. ^ Bosello F., De Cian E. and Roson R., (2007), "Climate Change, Energy Demand and Market Power in a General Equilibrium Model of the World Economy"[2], Fondazione Eni Enrico Mattei Working Paper N.71.2007. De Cian E., Lanzi E. and Roson R., (2007), “The Impact of Temperature Change on Energy Demand: A Dynamic Panel Analysis”[3], Fondazione Eni Enrico Mattei Working Paper N.46.2007
  4. ^ Bosello F., Roson R. and Tol R.S.J. (2006), “Economy-Wide Estimates of the Implications of Climate Change: Human Health”, Ecological Economics , 58, 579-591.
  5. ^ Berritella M., Bigano A., Roson R. and Tol R.S.J. (2006), “A General Equilibrium Analysis of Climate Change Impacts on Tourism”, Tourism Management , 25, 913-924. Bigano A., Bosello F., Roson R. and Tol R.S.J. (2006), “Economy-Wide Estimates of the Implications of Climate Change: a Joint Analysis for Sea Level Rise and Tourism”[4], Fondazione Eni Enrico Mattei Working Paper N.135.2006.
  6. ^ Burniaux, Jean-Marc & Truong Truong, (2002). "GTAP-E: An Energy-Environmental Version of the GTAP Model"[5] GTAP Technical Paper 16, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, revised

[edit] Further reading

  • Bosello F. and Roson R. (2007), Climate Change and CGE Models: A Proposal to Estimate Climate Change Damage Functions, paper presented at the GTAP Tenth Anniversary Conference “Assessing the Foundations of Global Economic Analysis”, 7-9 June 2007, Purdue University, West Lafayette, USA
  • Ronneberger K., Berrittella M., Bosello F. and Tol R.S.J. (2006), “Klum@Gtap: Introducing Biophysical Aspects of Land-Use Decisions Into a General Equilibrium Model A Coupling Experiment”[6], Fondazione Eni Enrico Mattei Working Paper N.102.2006.
  • Roson R., Calzadilla A. and Pauli F. (2006), “Climate Change and Extreme Events: An Assessment of Economic Implications”[7], Fondazione Eni Enrico Mattei Working Paper N.44.2006.
  • Roson R. (2003), "Modelling the Economic Impact of Climate Change"[8], EEE Programme Working Papers Series., EEE Programme Working Papers Series.

[edit] External links