Roberto RosonUniversità Ca’ Foscari Venezia

Dominique van der MensbruggheThe Food and Agriculture Organizationof the United Nations (FAO)

The ENvironmental Impact and SustainabilityApplied General Equilibrium Model (ENVISAGE)— An Integrated Assessment Model of the Global Economy

Potsdam Institute for Climate Impact Research (PIK)Potsdam, 18-19 September 2013

Outline

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

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—20072050/2100 with variable time steps

Implemented in GAMS with Excel interface

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.

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).

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

A Taxonomy of Impacts

• Impacts affecting primary resources or productivity

• Impacts affecting the structure of demand or production

• Impacts affecting international income transfers

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

Considered Impacts

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

% Change for 1°C Variation

sea.kp sea.tp agr.tp wat.tp onj.lp hhe.lp end.hc RHA -0.004 -0.004 5.843 -1.200 -0.13 0.066 -11.197 CHN -0.034 -0.034 10.787 -1.800 -0.83 0.077 -9.167 RHY -0.052 -0.052 2.712 -0.500 -0.10 0.034 -5.953 LMX -0.168 -0.168 -1.469 -3.000 -0.43 -0.196 -5.477 IND -0.034 -0.034 2.830 -1.600 -0.75 -0.132 -9.167 USA -0.020 -0.020 0.346 2.000 -0.06 -0.039 -8.571 BRA -0.015 -0.015 0.602 -2.500 -0.32 -0.107 -4.110 EUR -0.013 -0.013 1.667 -1.800 -0.02 0.061 -5.280 RUS -0.005 -0.005 4.794 1.000 -0.11 0.073 -12.489 JPN -0.052 -0.052 2.712 -0.500 -0.06 0.034 -5.953

Net Income Transfers for 1°C

RHA High Income A1 -4813 CHN China -43978 RHY Rest of H.I. 140782 JPN Japan 211173 LMX Rest of World -261421 IND India -29529 USA -92456 BRA Brazil -18707 EUR Europe 98968 RUS Russia -18

Emissions and climate in the baseline

2005 2010 2015 2020 2025 2030 2035 2040 2045 20500

2

4

6

8

10

12

14

16

18

20

High income countries East Asia & PacificSouth Asia Europe & Central AsiaMiddle East & North Africa Sub-Saharan AfricaLatin America & Caribbean

2005 2010 2015 2020 2025 2030 2035 2040 2045 20500

100

200

300

400

500

600

0

1

2

3

4

5

6

Concentration (ppm, left-axis)Radiative forcing (w/m2, right-axis)Temperature (° C, right axis)

CO2 emissions, gt carbon Climate impacts

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

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

-8.0

-6.0

-4.0

-2.0

0.0

2.0

4.0

High income countries East Asia & Pacific South AsiaEurope & Central Asia Middle East & North Africa Sub-Saharan AfricaLatin America & Caribbean World total

Decomposition of climate change impacts, percent deviation in 2050 GDP relative to baseline

xlc xea mex idn ssa tur xsa mna bra xha usa wld ind jpn hic eur arg xec chn rus can-15

-10

-5

0

5

10

TourismEnergy demandHealthLabor productivitySea-level riseWaterAgriculture

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).

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