Economic assessment of climate change impacts and the role ... · Reduced-form climate change damage functions (CCDF) Using the different RCPs to obtain different (namely 3) temperature

Economic assessment of climate change

impacts and the role of autonomous

adaptation mechanisms

ISPRA, October 6th, 2017

Francesco Bosello

CMCC, FEEM, University of Milan, Department of

Environmental Science and Policy

Ramiro Parrado – CMCC, FEEM

The issue in a nutshell

1

Source: IPCC AR5 (2014)

«Point estimates» of climate change impacts on world GDP


2 Source: IPCC AR5 (2014)

Examples of reduced-form climate change damage

functions (CCDF)

)("" ,, titi TflossGDP


3

Climatic

drivers

Environmental

impacts

• Δ Temp.

• Δ Preci.

• Δ SLR

• ………

Social

Economic

impacts

• Δ flood. land

• Δ desert. land

• Δ crop yield

• Δ mort./morb.

•……………..

• Δ Agr. Prod.

• Δ Health care

expenditure

• Δ Labour

prod.

• ……………..

Climate

Models “Impact”

Models

Translation

phase

CGE

model

Economic

Assessment

This methodology has been extensively used since the beginning of

2000, see e.g.: Deke et al. (2001); Darwin and Tol (2001); Bigano et

al (2008); Aaheim et al., (2010); Bosello et al. (2006, 2007, 2014);

Eboli et al, (2010); Roson and Van der Mensbruegghe (2010); Ciscar

et al, (2011, 2013), ADB (2015) OECD (2016).

Main strenght: ability to capture the role of market adjustments or of

market driven adaptation triggered by climate «shocks» due to the

multi-sector/multi-country nature of CGE models, their explicit

representation of domestic-international market exchanges, and

endogenous price formation.

An alternative approach


4

But economic assesments of

climate change impacts conducted

with CGE models tend to

«produce» low damage estimates


5


6

Many reasons for that (Patt et al 2011, Pindick, 2013, Stern 2013):

Unability to capture «non market» losses referred to non

marketable items (e.g. ecosystem services, changes in

mortality/morbidity), institutional «failures» (lack of

adaptive capacity), social conflicts…

The main loss indicator is GDP a «flow» and not a

«stock» measure.

Instantaneous and frictionless recovery after a shock

too optimistic in assuming substitutability across/mobility

of factor of productions.

Try to assess the economic relevance of climate change using a recursive-dynamic CGE model incorporating latest evidence on different impacts categories

Quantify the role of “market driven adaptation” in determining the final impact. Firstly “full market-driven adaptation” is assumed, then limits or frictions in market adjustments is introduced.

Construct reduced-form climate change damage functions starting from the CGE results and compare with those used by well established “hard linked IA models”.

7

Objectives

Recursive dynamic computable general equilibrium (CGE) model

Based on the GTAP 8 database (Narayanan et al. 2012). Calibration

year 2007

Simulation period: 2007-2050 in one-year time steps

25 countries/regions (this study)

19 sectors (this study)

(as standard in CGE) Inter sectoral and international trade flows

explicitly modelled optimizing agents’ endogenous response

to (endogenous) price signals represents «market-driven

adaptation»

8

The model: ICES

9

Summary of scenarios

Economic reference: SSP2 (“middle of the road”) (O’Neill et al. 2012)

Climate change impacts reconstructed for RCPs: 2.6,

6.0 and 8.5 (Van Vuuren et al. 2011)

+ “Full” adaptation (“default” adjustment mechs.)

As above, but with “Limited” adaptation: - Trade (LA-TR): reducing the model’s flexibility to

accommodate international trade flows.

- Labor mobility (LA-LM): limiting workers mobility within

sectors in each region.

- Primary factor substitution (LA-PFS): decreasing the

flexibility to combine production factors (labor, natural

resources, land and capital-energy).

10

CC Impacts Sources Available

Scenarios

Agriculture PIK - LPJmL ISIP-MIP runs RCPs 2.6, 6.0,

and 8.5

Health Tol (2002) 1°C

Sea level Rise Diva model - Vafeidis et. al (2008)

CLIMATECOST project A1B

Tourism Hamburg Tourism Model - Bigano et. al

(2007) CLIMATECOST project A1, B2

Energy demand POLES model - Criqui (2001), Criqui et.

al (2009) CLIMATECOST project A1B

Forestry PIK - LPJmL Bondeau et. al (2007),

Tiejten et al (2009) CLIMATECOST

project A1B

Fisheries Cheung et. al (2010) SESAME project A1B

Ecosystem Warren et al (2006) 1°C

Climate change impacts: Sources

Climate Change Impact on Gross World Product

11

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

20

08

20

10

20

12

20

14

20

16

20

18

20

20

20

22

20

24

20

26

20

28

20

30

20

32

20

34

20

36

20

38

20

40

20

42

20

44

20

46

20

48

20

50

% c

han

ge w

rt b

asel

ine

RCP 2.6

RCP 6.0

RCP 8.5

CC impacts on GDP in 2050 – regional breakdown

12

-5

-4

-3

-2

-1

0

1

USA

No

rth

_Eu

rop

e

No

rth

_EU

15

Med

_EU

15

Med

_EU

12

East

_EU

12

Ro

Euro

pe

Ru

ssia

Ro

FSU

Sou

thK

ore

a

Au

stra

lia

Sou

thA

fric

a

Can

ada

Jap

an

New

Zeal

and

NA

F

MD

E

SSA

SASI

A

Ind

ia

Ch

ina

EASI

A

Ro

LAC

A

Bra

zil

Mex

ico

Wo

rld

% C

han

ge w

ith

res

pe

ct t

o B

asel

ine

RCP 8.5 RCP 6.0 RPC 2.6

CC impacts on GDP in 2050 – decomposition RCP 8.5

13

-5

-4

-3

-2

-1

0

1

2

-5

-4

-3

-2

-1

0

1

2

USA

No

rth

_Eu

rop

e

No

rth

_EU

15

Med

_EU

15

Med

_EU

12

East

_EU

12

Ro

Euro

pe

Ru

ssia

Ro

FSU

Sou

thK

ore

a

Au

stra

lia

Sou

thA

fric

a

Can

ada

Jap

an

New

Zeal

and

NA

F

MD

E

SSA

SASI

A

Ind

ia

Ch

ina

EASI

A

Ro

LAC

A

Bra

zil

Mex

ico

Pe

rce

nta

ge c

han

ge w

ith

re

spe

ct t

o b

ase

line

Tourism

Sea level rise

Health

Forestry

Fisheries

Energy Demand

Ecosystems

Agriculture

All impacts

“Limiting” adaptation: CC impacts on GWP (RCP 8.5)

14

-1

-0.9

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

20

08

20

11

20

14

20

17

20

20

20

23

20

26

20

29

20

32

20

35

20

38

20

41

20

44

20

47

20

50

% c

ha

nge

wit

h r

esp

ect

to

ba

seli

ne

Full Market Adaptation

Labour Mobility

Trade

Factor substitution

All Rigidities

Reduced-form climate change damage functions (CCDF)

Using the different RCPs to obtain different (namely 3)

temperature increases and impacts and GDP effects in

the same year for each region, we then interpolate the

function (To “clean” or control for the social economic

factors we selected as reference one single year (2050))

We did this first accounting for just smooth market

impacts.

Then including a catastrophic damage component

following Nordhaus and Boyer (2000) and Nordhaus

(2007).

Finally adding limits to adaptation

15

Reduced-form CCDF, «smooth impacts»

16

-20

-15

-10

-5

0

0 1 2 3 4 5

Pe

rce

nta

ge

of

GD

P

Temperature change °C

EUROPE

USA

RoANNEX-I

LACA

MENA

WORLD

CHINA

RoASIA

SSA

INDIA

Reduced-form CCDF, «smooth + catastrophic impacts»

17

-10

-8

-6

-4

-2

0

0 1 2 3 4 5

% o

f G

DP


EUR-FA

WORLD-FA

CHN-FA

Reduced-form CCDF, «smooth + catastrophic impacts + lim. ad.»

18

-10

-8

-6

-4

-2

0

0 1 2 3 4 5

% o

f G

DP


EUR-FA

EUR-LA

WORLD-FA

WORLD-LA

CHN-FA

CHN-LA

Conclusions (1)

In 2050 total costs roughly amount to 0.64% of GWP in RCP 8.5 (2.5°C increase).

Aggregate figures hide important regional asymmetries: higher vulnerability of developing countries to climate change impacts. (South Asia and India lose more than 4% of their GDP, Eastern Asia and Sub Saharan Africa roughly 2% of their GDP in 2050 in RCP 8.5).

Introducing rigidities in market adjustments increases climate change costs (by roughly 30%), but does not change substantively the picture. Key is the modelling of catastrophic outcomes

In the shorter term, trade is a more important source of impact smoothing, in the longer term it is the lower degree of substitutability across primary factors.

19

Conclusions (2)

When the comparison is “even” CGE models do not provide

lower estimates of climate change damages compared to “hard

linked” IA models

More research is needed, at least:

Investigate the role of the social economic context (the

structure of the economy) in impact determination

Better define the range of uncertainties on key parameters

More observations to calibrate the reduced-form damage

functions (very limited knowledge “beyond 3°C”)

20

The need for a precutionary approach

With a doubling of CO2 concentration there is the 5% probability of

experiencing increases of temperature > 5 °C

The need for a precautionary approach

22

10-30% global GDP loss (Weitzman, 2014)

?

Both RCP 8.5 and 6 (more

than doubling CO2 conc.)

will lead us there

Support from econometrics

Source: Burke et al (2015) 23% median global GDP

loss in RCP 8.5

Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it

Thanks!

This research is based on the outcome of the European Union’s Seventh Framework Programme (FP7/2007-2013) under the grant agreement n°266992 (Global IQ)


25

Climate change impacts assessed and modelling strategy

Sea-Level Rise

Energy Demand

Tourism

Fishery

Health

Ecosystems

Δ in land and physical capital stock

Δ residential demand of oil, gas, electricity

Δ in households’ demand for recreational services (part of market services) and in expenditure

Δ labour productivity as well as private and public expenditures

Δ natural resource stock used by the fishing industry

Δ services from physical capital stock

Agriculture (Δ crop yields) Δ land productivity

Forestry Δ in productivity of natural resource stock used by the wood processing sector


26

Macro economic drivers of SSP2

World population SSPs (Million) World GDP SSPs ($ Billion)

Regional population trends SSP2

(% ch wrt 2007-2050)

Regional GDP trends SSP2

(% ch. wrt 2007-2050)

Source: https://secure.iiasa.ac.at/web-apps/ene/SspDb/dsd?Action=htmlpage&page=welcome

https://secure.iiasa.ac.at/web-apps/ene/SspDb/dsd?Action=htmlpage&page=welcome




27

Temperature increase in the different RCPs

Source: Rogelj et al (2012)


Climate Change Direct Impacts (selected)

28


29

«Limiting Adaptation»

• “Trade more difficult” (Armington elasticities reduced to 75%): LA-TR

• “Primary factor substitution more difficult” (substitution elasticity reduced to 75%): LA-PFS

• “Moving labour more difficult” -- Limited labor mobility allowing for wage differences: LA-LM

• All rigidities (TR, LM, PFS): LA-AR

We set the limited adaptation values for elasticities based on:

Armington elasticities: ratio of mean elasticity to the lower end of the 68% confidence interval: μ/(µ- 1σ).

Factor substitution: ratio of short term to medium term elasticities.


RCP 8.5 impacts on regional GDP with limited adaptation

30

-6

-5

-4

-3

-2

-1

0

1

2

USA

No

rth

_Eu

rop

e

No

rth

_EU

15

Med

_EU

15

Med

_EU

12

East

_EU

12

Ro

Euro

pe

Ru

ssia

Ro

FSU

Sou

thK

ore

a

Au

stra

lia

Sou

thA

fric

a

Can

ada

Jap

an

New

Zeal

and

NA

F

MD

E

SSA

SASI

A

Ind

ia

Ch

ina

EASI

A

Ro

LAC

A

Bra

zil

Mex

ico

Wo

rld

% c

han

ge w

rt B

asel

ine

All Rigidities Trade Factor substitution Labour mobility CC - Full Market Adaptation


RCP2.6: climate-change impact on macro-regional GDP

31

-5

-4

-3

-2

-1

0

1%

ch

ange

wrt

to

Bas

elin

eUSA

North_Europe

North_EU15

Med_EU15

Med_EU12

East_EU12

RoEurope

Russia

RoFSU

SouthKorea

Australia

SouthAfrica

Canada

Japan

NewZealand

NAF

MDE

SSA

SASIA

India

China

EASIA

RoLACA

Brazil

Mexico

World



32

-5

-4

-3

-2

-1

0

1%

ch

ange

wrt

to

Bas

elin

eUSA

North_Europe

North_EU15

Med_EU15

Med_EU12

East_EU12

RoEurope

Russia

RoFSU

SouthKorea

Australia

SouthAfrica

Canada

Japan

NewZealand

NAF

MDE

SSA

SASIA

India

China

EASIA

RoLACA

Brazil

Mexico

World



33

-5

-4

-3

-2

-1

0

1%

ch

ange

wrt

to

Bas

elin

eUSA

North_Europe

North_EU15

Med_EU15

Med_EU12

East_EU12

RoEurope

Russia

RoFSU

SouthKorea

Australia

SouthAfrica

Canada

Japan

NewZealand

NAF

MDE

SSA

SASIA

India

China

EASIA

RoLACA

Brazil

Mexico

World


Climate change impacts on GWP for RCP 8.5 vs a Full

adaptation baseline

34

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

1

20

08

20

10

20

12

20

14

20

16

20

18

20

20

20

22

20

24

20

26

20

28

20

30

20

32

20

34

20

36

20

38

20

40

20

42

20

44

20

46

20

48

20

50

% c

han

ge w

ith

re

spe

ct t

o b

ase

line

Full Market Adaptation

Labour Mobility

Trade

Factor substitution

All Rigidities


RCP 8.5 impacts on regional GDP with Limited adaptation vs a

Full adaptation baseline

35

-22

-20

-18

-16

-14

-12

-10

-8

-6

-4

-2

0

2

USA

No

rth

_Eu

rop

e

No

rth

_EU

15

Med

_EU

15

Med

_EU

12

East

_EU

12

Ro

Euro

pe

Ru

ssia

Ro

FSU

Sou

thK

ore

a

Au

stra

lia

Sou

thA

fric

a

Can

ada

Jap

an

New

Zeal

and

NA

F

MD

E

SSA

SASI

A

Ind

ia

Ch

ina

EASI

A

Ro

LAC

A

Bra

zil

Mex

ico

Wo

rld

% c

han

ge w

rt B

ase

line

All Rigidities Trade Factor substitution Labour mobility CC - Full Market Adaptation


Temperature increases in different RCPs

36

0

1

2

3

4

5

2000 2025 2050 2075 2100

Tem

pe

ratu

re c

han

ge s

ince

pre

-in

du

stri

al

RCP8.5

RCP6.0

RCP4.5

RCP3-PD

Sources: IIASA GGI Scenario database (Version 2.0.1)

Rogelj et al. (2012)


Thanks!

This research is based on the outcome of the European Union’s Seventh Framework Programme (FP7/2007-2013) under the grant agreement n°266992 (Global IQ)

Documents

Economic assessment of climate change impacts and the role ... · Reduced-form climate change damage functions (CCDF) Using the different RCPs to obtain different (namely 3) temperature