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The EN vironmental I mpact and S ustainability

The EN vironmental I mpact and S ustainability A pplied G eneral E quilibrium Model (ENVISAGE)— An Integrated Assessment Model of the Global Economy.

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The EN vironmental I mpact and S ustainability

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  1. The ENvironmentalImpact and Sustainability Applied General Equilibrium Model (ENVISAGE)— An Integrated Assessment Model of the Global Economy Roberto RosonUniversità Ca’ FoscariVeneziaDominique van der MensbruggheThe Food and Agriculture Organizationof the United Nations (FAO) Potsdam InstituteforClimate Impact Research (PIK) Potsdam, 18-19 September 2013

  2. Outline • What is ENVISAGE • Modeling impacts • Climate change and its impacts • Future steps

  3. Key design characteristicsof the ENVISAGE Model • Integrated Assessment Model (IAM) • multi-sector multi-region dynamic global CGE model • greenhouse gas emissions • integrated climate module • climate change feedbacks • GTAP8-based flexible aggregation (129 countries and/or regions, 57 economic sectors) • Dynamic recursive—20072050/2100 with variable time steps • Implemented in GAMS with Excel interface

  4. Specificity • Technology: Calibrated nested CES functions with vintage capital—3 types (crops, livestock, other) • Energy : coal, oil, gas, nuclear, hydro, renewables, new technologies (biofuels, CCS, etc.) • Land-use: 18 AEZ types based on FAO/IIASA GAEZ (forthcoming) • Emissions: Includes the main Kyoto gases—CO2, CH4, N2O, F-gases (includes agriculture, but not forestry) • Regimes: Carbon taxes, caps, caps and trade, country, regional, global, exemptions, etc. • Climate: GHG concentration, radiative forcing and global mean temperature • Impacts: Agricultural productivity, water availability, health- and heat-related labor productivity, sea level rise, and changes to energy demand and tourist arrivals.

  5. Key dynamic assumptions • UN population forecast—labor force growth equated to growth of working age population (15-65). • Rural to urban migration in developing countries. • Savings rate driven by growth and youth and elderly dependency rates. • Economy-wide labor-augmenting productivity with exogenous wedges across sectors (e.g. Manu > Serv) • Exogenous land productivity in agriculture • Autonomous energy efficiency improvement (AEEI) increases by 1% per annum (in all regions and sectors).

  6. Key parameters • Production substitution elasticities are endogenous and depend on composition of capital vintages • Demand driven by CDE utility function • All other elasticities/key parameters are fixed at base year values (potential exception of Armington) • Aggregate land supply driven by a logistic curve with maximum calibrated to FAO data • Working with different land mobility assumptions

  7. A Taxonomy of Impacts • Impacts affecting primary resources or productivity • Impacts affecting the structure of demand or production • Impacts affecting international income transfers

  8. From Micro to Macro • Available studies exists for specific impacts, but… • They use different approaches, terminology, aggregation scales, etc. • There is a need to “bridge” different models, and to identify relevant variables and parameters in models like ENVISAGE

  9. Considered Impacts • Sea level rise • Agriculture productivity • Water availability • On the job productivity • Tourism • Human Health • Energy Demand

  10. % Change for 1°C Variation

  11. Net Income Transfers for 1°C

  12. Emissions and climate in the baseline CO2 emissions, gt carbon Climate impacts

  13. Climate change impact on real GDP, percent deviation relative to baseline

  14. Decomposition of climate change impacts, percent deviation in 2050 GDP relative to baseline Note: Region labels are rest of Latin America and Caribbean (xlc), rest of East Asia (xea), Mexico (mex), Indonesia (idn), Sub-Saharan Africa (ssa), Turkey (tur), rest of South Asia (xsa), Middle-East and North Africa (mna), Brazil (bra), rest of high-income Annex 1 (xha), United States (usa), world (wld), India (ind), Japan (jpn), High-income (hic), European Union (eur), Argentina (arg), rest of Europe and Central Asia (xec), China (chn), Russian Federation (rus) and Canada (can).

  15. Future steps • Model extensions—incorporation of AEZ land data and revised land-use module, new energy technologies, mitigation technologies in agriculture, and new household demand module to ensure better behaved Engel curves • Refinement of impact estimates—including use of AgMIP model ensembles (GCM and Crop) to estimate families of parametric impact curves for crops • Phase 2 of AgMIP model comparison exercise

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