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A. Bigano °, F. Bosello* , R. Roson’, R.S.J. Tol”

Economy Wide Impacts of Climate Change: A Joint Analysis for Sea

Level Rise and Tourism

°Fondazione Eni Enrico Mattei*Università di Milano e Fondazione Eni Enrico Mattei ’Università di Venezia e Fondazione Eni Enrico Mattei ”Free University of Amsterdam, Hamburg University, Carnegie Mellon University, ESRI Dublin

Chronic Risk of Global Climate Change to Urban Coasts and EconomiesStevens Institute of Technology, NJ, 15-16 November 2007

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Introduction: future temperature + SLR

IPCC FAR (2007)

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Introduction: impacts

IPCC FAR (2007)

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Objectives

Evaluate economically climate change impacts with a general equilibrium perspective (first and higher

order welfare costs substitution mechanisms + market interdependencies changes induced by

changes in relative prices)

Initially one category of impact at a time

Then jointly (this study tourism + SLR)

Use and development of a CGE model/approach

Calibrate a climate change damage function accounting for “autonomous economic adaptation”

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Objectives

This approach is innovative

The predominant approach in climate change impact assessment is that of “direct costing” Partial

equilibrium:

Damage = (“price”) x (“quantity”)

This method is usually applied in “SLR studies” see e.g. Nichols et al. (2007) for discussion -> but also in other domains (e.g.

health, agriculture etc.) and to calibrate cc damage functions in global studies (see e.g. Nordhaus (1995, 1999), Manne and

Richels (1995, 2004), Tol (1995 – 2002))

This disregards rebounds and feedback: social economic systems adapt and “shocks” propagate

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Consumers(households, government)

Producers(firms, government)

Maximise welfarefrom consumption

Minimise costof production

supply

demand supply

demand

Input marketsK, L, Land, NR

Income

Income

Output marketsGoods and

services

Constrained by income

Constrained by technology

Demand and supply functions “mimic”

observed economic systems: parameters

are calibrated on “real” data. All markets are

Interdependent.

Sketching a CGE model

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The CGE Model

GTAP-EF(Extended Version of GTAP-E Burniaux and Truong 2002)

16 Regions:USA: United StatesCAN: CanadaWEU: Western Europe JPK: Japan and KoreaANZ: Australia New ZealandEEU: Eastern EuropeFSU: Former Soviet UnionMDE: China and IndiaCAM: Rest of the WorldSAM: South AmericaSAS: South AsiaSEA: South East AsiaCHI: ChinaNAF: North Africa SSA: Sub-Saharan AfricaSIS: Small Island States

17 Sectors:RiceWheatCereal CropsVegetable FruitsAnimalsForestryFishingCoalOilGasOil ProductsElectricityWaterEnergy Intensive industriesOther industriesMarket ServicesNon-Market Services

Calibrated in 1997

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The CGE Model: consumption “tree”

utility

private consumption public consumption savings

item1 item m item1 item m

domestic foreign

region 1 region n

domestic foreign

region 1 region n

Using Income (from endowment ownrship) in

fixed (C-D) shares for:Households max.

Armington

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The CGE Model: production “tree”

output

other inputsv.a.+energy

natural resources

land labour capital+energy domestic foreign

region 1 region ncapital

energy

non-electric electric

dom for

r1 rn

coal

dom for

r1 rn

non-coal

gas oil petrolemum products

dom for

r1 rn

dom for

r1 rn

dom for

r1 rn

CES

Leontieff

Armington

Armington

Min. production cost

CES

CES

CES

CES

Armington

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The CGE Model

Investment

……..

“World Bank”

• Households save a constant share of their income.

……..

• Redistribution mechanism based on the equalization of regional return to capital.

B

A

C F

E

D

REG. 1

REG. 2

REG. 1

REG. 2

REG. nREG. n 1) Investment is Endogenous.

2) A,B,C flows ≠ D,E,F flows.3) A region can run a foreign debt or credit.

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“Benchmarking” the model in the future

Starting point: core model calibrated in 1997.

Necessary to get a future reference case “without climate change” (“Pseudo-calibration” )

This refers to obtaining a picture of the future world economy. In practice, long-run estimates of primary inputs (land, labour, capital

and natural resources) stocks and productivity used to:

Shock the model 1997 calibration equilibrium to obtain future benchmark equilibria ( 2050).

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Data sources for the benchmark

- Population: World Bank.

- Capital stock: G-Cubed model Version48E (McKibbin, 2001).

- Labour stock: G-Cubed model Version48E (McKibbin, 2001).

- Labour productivity: G-Cubed model Version48E (McKibbin, 2001).

- Crops’ productivity: IMAGE 2.2, B1 Scenario (RIVM, 2001).

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Benchmark Assumptions

Capital stock

(initial) Agriculture Energy Electricity ServicesEnergy

Intensive industries

USA 30.4 253.7 249.6 346.3 114 120.1 0 69.5 100 120.1CAN 15.6 186.3 263.7 376.4 225.5 134.1 6.1 80.1 157.6 134.1WEU -3.7 164 266.6 234.7 52.8 140.8 9.4 85.3 177.2 140.8JPK -11.6 177.5 214.5 263.7 162.5 133.6 0 79.8 163.1 133.6ANZ 18.7 184.8 263.7 227.3 225.5 133 6.1 79.4 156.3 133EEU -2.7 260.1 257 460.8 267.3 221.9 47.5 148.3 267.1 221.9FSU -2.7 275.5 257 407.5 267.3 235 50.3 157.1 282.9 235MDE 107.7 373.7 324.2 419 379.9 227.3 48.7 151.9 276.2 227.3CAM 54.9 375.4 352.4 523.8 379.9 287.8 72.8 197.1 330 287.8SAM 51 411.4 352.4 530.8 379.9 315.4 79.7 216 207 315.4SAS 72.6 500.8 254.4 818.8 339.5 346.3 75 237.1 422.9 346.3SEA 68.9 336.7 352.4 560.5 379.9 258.2 65.3 176.8 316.8 258.2CHI 29.4 463.4 254.4 660.5 339.5 251.2 63.5 172 306.7 251.2NAF 127 235.1 352.4 441.9 379.9 180.2 45.6 123.4 221.2 180.2SSA 135.8 375.9 352.4 711.4 379.9 288.2 72.9 197.4 353.7 288.2SIS 49.1 419.9 352.4 572.5 379.9 321.9 81.4 220.4 332 321.9

Land Productivity

Labour Productivity

PopulationLabour stock

Natural Resources

stock

% changes 1997-2050

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Baseline GDP

% changes 1997-2050

0

500

1000

1500

2000

2500

3000

3500

Our

A2

B1

B2

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The Modeling Exercise

SLR (No protection): Land loss is modeled as a negative “supply-side” shock on the endowment LAND (which is an exogenous variable in the model).

Tourism: Changes in tourism demand are modeled as changes in the demand for recreational services (within the market service sector), income flows determined by additional foreign expenditure are modelled.

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Climate Change Scenarios and Models

• T = + 1.2 °C. in 2050 wrt 1980 -1999• SLR= + 25 cm. in 2050

SLR -- > Data set on land loss wrt different sea-level rise scenarios (based on Delft Hydraulics GVA

(1993), Beniston (1998 ), Nicholls (1995), Bijlsma et al. (1996))

Tourism -- > HTM model (Tol et al. 2002): changes in arrival,

departures and expenditures, determined by socio-economic +

environmental drivers (changes in temperature and coastal land

availability)

Environmental Impact Models

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Sea level rise alone

Inputs to the CGE model Outputs from the CGE model

ml $as % of

GDP Land Labour CapitalUSA -0.052 121 0.0002 -0.0013 -0.016 0.015 0.684 -0.034 -0.034

CAN -0.002 72 0.0017 -0.0004 0.029 0.032 0.822 -0.013 -0.009

WEU -0.029 298 0.0005 -0.0019 -0.005 0.016 0.608 -0.035 -0.036

JPK -0.141 146 0.0004 -0.0018 0.006 0.011 1.132 -0.034 -0.035

ANZ -0.010 237 0.0075 -0.0008 0.081 0.010 0.967 -0.022 -0.028

EEU -0.041 45 0.0016 -0.0047 -0.001 -0.037 0.629 -0.074 -0.079

FSU 0.000 0 0.0000 -0.0007 -0.005 0.010 0.613 -0.038 -0.040

MDE -0.007 75 0.0011 -0.0045 0.000 -0.001 0.998 -0.035 -0.044

CAM -0.120 182 0.0049 -0.0098 0.052 -0.023 0.806 -0.053 -0.059

SAM -0.041 647 0.0043 -0.0007 0.102 0.020 0.742 0.005 0.007

SAS -0.396 6000 0.1180 -0.0649 0.078 -0.212 1.420 -0.285 -0.292

SEA -0.839 14913 0.1475 -0.1092 -0.032 -0.357 2.372 -0.468 -0.504

CHI -0.091 579 0.0063 -0.0303 -0.060 -0.236 0.521 -0.235 -0.260

NAF -0.039 1120 0.0548 -0.0036 0.012 0.039 0.795 -0.002 0.016

SSA -0.130 8869 0.2359 -0.0094 0.100 -0.029 1.034 -0.055 -0.062

SIS -0.167 188 0.0220 -0.0189 -0.020 -0.086 0.885 -0.162 -0.169

Terms of Trade

Invest. flows

Factor PricesLand loss

Direct costs: value of land lost

GDP

Reference Year 2050: % changes wrt baselineland loss ranking

direct cost

ranking

gdp loss ranking

USA 8 15 12CAN 15 10 16WEU 12 13 10JPK 4 14 11ANZ 13 6 13EEU 9 11 7FSU 16 16 14MDE 14 12 8CAM 6 8 5SAM 10 9 15SAS 2 3 2SEA 1 2 1CHI 7 7 3NAF 11 4 9SSA 5 1 6SIS 3 5 4

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The difference between direct and general equilibrium cost

0.1475

0.0063

0.0548

0.2359

0.0220

0.0649

0.1092

0.0303

0.0036 0.00940.0189

0.1180

0

2000

4000

6000

8000

10000

12000

14000

16000

SAS SEA CHI NAF SSA SIS

Mill

ion

s $

0.00

0.05

0.10

0.15

0.20

0.25

2050

GD

P %

DC abs GEC abs DC %GDP GEC % GDP

0.00

02 0.00

17

0.00

05

0.00

04

0.00

75

0.00

16

0.00

00 0.00

11

0.00

49

0.00

43

0

100

200

300

400

500

600

700

800

USA CAN WEU JPK ANZ EEU FSU MDE CAM SAM

Mill

ion

s $

0.000

0.002

0.004

0.006

0.008

0.010

0.012

2050

GD

P %

DC abs GEC abs DC %GDP GEC % GDP

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Tourism Alone

Imposed Endogeno

us USA -0.874 -1.259 1.457 -0.365 -0.0015 -0.511 -0.626CAN 0.459 0.755 -1.381 0.211 -0.0004 0.420 -0.116WEU 0.883 1.357 -2.287 0.378 0.0556 0.331 0.238JPK 5.639 8.096 -14.760 2.779 -0.1768 3.768 3.810ANZ -1.530 -2.096 3.475 -0.696 0.0493 -0.063 -0.654EEU -3.172 -4.683 3.255 -1.169 -0.1068 -0.803 -0.999FSU -0.024 -0.073 0.052 -0.011 -0.0311 -0.135 -0.390MDE -5.974 -8.600 8.295 -2.074 0.0030 -2.279 -1.960CAM -5.519 -7.980 7.518 -2.387 -0.1139 -1.030 -1.805SAM -1.521 -2.015 1.583 -0.558 -0.0027 -0.100 -1.161SAS -1.532 -1.794 1.102 -0.453 0.0251 0.596 -0.507SEA -5.452 -7.057 6.854 -1.629 -0.0324 -0.825 -0.620CHI -6.777 -8.020 2.731 -1.129 -0.0442 -1.127 -0.854NAF -3.204 -4.179 1.314 -0.646 -0.1614 -0.795 -0.640SSA -3.068 -4.122 2.993 -1.053 -0.0079 -0.359 -0.951SIS -12.251 -18.984 17.001 -5.990 -0.5330 -7.522 -7.852

Market services demand

Other goods/services dem.

Income transfers

GDP Terms of

TradeInvest. Flows

Reference Year 2050: % changes wrt baseline

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Tourism and sea level jointly

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

USACAN

WEU

JPK

ANZEEU

FSUM

DECAM

SAMSAS

SEACHI

NAFSSA

ROW

-90

-70

-50

-30

-10

10

30

SLR&TOU SLR TOU %D SLR&TOU-SUM

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Conclusions

Using a CGE approach to evaluate climate change impacts is important: huge difference respect to a

partial equilibrium assessment

Interactions among impacts are alslo non-negligible

A lot to do: - improve the quality of input data

- expand the set of impacts considered (on health, energy demand, physical capital, agriculture etc.)

- consider a dynamic setting

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Thank You!