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EC 936 ECONOMIC POLICY MODELLING LECTURE 8: CGE MODELS OF CLIMATE CHANGE.

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Presentation on theme: "EC 936 ECONOMIC POLICY MODELLING LECTURE 8: CGE MODELS OF CLIMATE CHANGE."— Presentation transcript:

1 EC 936 ECONOMIC POLICY MODELLING LECTURE 8: CGE MODELS OF CLIMATE CHANGE

2 POLICY ISSUES Environmental impact of economic growth Environmental impact of liberalization policies Global warming and the cost of greenhouse gas emissions control Tradable permits for CO 2 Carbon tax policies Deforestation and reforestation Environmental standards legislation/regulation Double dividends?

3 SOCIAL ACCOUNTING APPROACH SAMEA (SAM with Environmental Accounts) Standard SAM (expressed in monetary units) linked to: EA (expressed in physical units) –Additional rows displaying environmental inputs consumed as resources –Additional columns displaying discharge of emissions and pollutants to the environment

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5 COST-BENEFIT OF SAMEA Diagnostic tool for evaluating impact of policies and growth patterns on environmental outcomes Adaptable to different environmental contexts Multiplier analysis the core mechanism of analysis Multiplier decomposition a la Pyatt-Round Fix price, fixed coefficients model; no substitution effects

6 APPLICATION OF SAMEA MODEL TO SPAIN (MORILLA et al, 2007)

7 WHY CGE MODELS? General vs partial equilibrium analysis Counterfactual modeling Decomposition of complex array of simultaneous influences (exogenous as well as policy decisions) Simulation exercises Evaluation of key parameters

8 ECONOMIC MODELS OF CLIMATE POLICIES Early 70s: first models mainly build by natural scientists focusing on GHG Late 70s: first economic models Toronto Climate Conference in 1988 Late 80s/early 90s first CGE models, analysis of CO 2 taxes CGE modeling of climate policies took off in the 90s –More powerful software to handle larger models –GTAP Energy –GAMS codes for standard models available (Rutherford) The Kyoto Protocol

9 JORGENSON & WILCOXEN, 1990 For USA only; 35 industrial sectors, 672 household types, labor, capital, energy, materials Parameters estimated for 1947-1987 data Dynamic; until 2050 Experiments: - Freeze emissions at 1990 or 2000 level - Cut emission in 2080 to 80% of 1990 level

10 WHALLEY & WIGGLE, 1990 6 regions: EU, North America, Japan, other OECD, Oil exporters, ROW 4 resources: carbon/non-carbon energy resources, sector-specific factors in energy intensive manufactures, other primary factors 5 products: carbon/non-carbon energy, composite energy, energy intensive goods, other goods Period 1990 - 2030 Experiments: –reduce carbon emissions by 50 % rel. to benchmarks by producer, consumer or internationally levied tax

11 MORE RECENT MODELS I (Peterson)

12 MORE RECENT MODELS II (Peterson)

13 CLIMATE CHANGE MODELS BASIC MAPPING OF CLIMATE CHANGE

14 GTAP-E MODELS (Roson et al) Use extended GTAP model incorporating greenhouse-gas emissions to evaluate probable path of greenhouse gases on: –Tourism (2006) –Coastal inundation/erosion (2007) –Human health (2006) Constructs base snapshots for 2010, 2030, 2050 with and without climate change effects

15 Source: Roson (2003)

16 CGE MODEL OF SEA LEVEL RISE (Bosello, Roson and Tol, 2007) Calibrates model to 2010, 2030, 2050 by setting population, capital, natural resources and productivity (endogenous→exogenous) Shocks system by reducing stock of land according to predictions of Global Vulnerability Assessment database –Without any investment in protection against rising sea levels (reduction in land) –With capital investments in dikes and flood barriers (no reduction in land, but increase in investment expenditure)

17 Source: Bosello, Roson & Tol (2007)

18 ADDING A DYNAMIC COMPONENT (Eboli, Parrado, Roson, 2010) ICES (Inter-temporal Computable Equilibrium System)— extension of GTAP-E which incorporates capital and international debt accumulation as endogenous factors to simulate growth in combination with exogenously determined growth in labour, land and natural resources. Essentially an escalator model—calibrated to a new benchmark at annual intervals to establish a baseline global growth forecast Model is then shocked with new exogenous variables, such as land loss due to sea level rise and a new series of benchmark equilibria are generated

19 Source: Eboli, Parrado, Roson (2010)


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