Formatvorlage des Untertitelmasters durch Klicken bearbeiten Institut für Energiewirtschaft und Rationelle Energieanwendung (IER) 17.11.2016 IER Analysis of the relative roles of supply-side and demand-side measures in tackling global climate change: TIAM-MACRO with Variable Elasticity of Substitution Babak Mousavi Markus Blesl 70 th semi-annual IEA-ETSAP workshop – Madrid (Ciemat)
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Analysis of the relative roles of supply-side and demand-side measures in tackling global climate change
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Analyzing of the relative roles of mitigation measures in tackling global climate change
Formatvorlage des Untertitelmasters durch
Klicken bearbeiten
Institut für Energiewirtschaft und
Rationelle Energieanwendung (IER)
17.11.2016
IER
Analysis of the relative roles of
supply-side and demand-side
measures in tackling global climate
change:
TIAM-MACRO with Variable Elasticity
of Substitution
Babak Mousavi
Markus Blesl
70th semi-annual IEA-ETSAP workshop – Madrid (Ciemat)
Analyzing of the relative roles of mitigation measures in tackling global climate change
Outline
IER Universität Stuttgart 2
Conclusions and outlook
Scenario Analysis
Normalization of production function
Variable elasticity of substitution
TIAM-MACRO
Objective
Motivation
Analyzing of the relative roles of mitigation measures in tackling global climate changeIER Universität Stuttgart 3
Motivation
Challenge of meeting long term decarbonisation targets cost-effectively, not only
requires the large scale uptake of low carbon technologies and fuels but also reductions
in energy-services (Webler and Tuler, 2010; Sorrell, 2015).
As time passes firms and individuals respond more strongly to a unit increase of price of
energy-services.
Mitigation
Hig
her
ren
ewab
les
Hig
her
nu
clea
r
Hig
her
CC
S
Fo
ssil
fu
el s
wit
chin
g
Demand-side
Eff
icie
ncy
impro
vem
ent
Ser
vic
e-dem
and
red
uct
ion
GeoengineeringAdaptation
Attempts to tackle climate change
Pri
ce indep
enden
t
Supply-side
Eff
icie
ncy
imp
rovem
ent
Pri
ce d
epen
den
t
Projected surface temperature changes for the late
21st century (2090-2099). Temperatures are relative to
the period 1980-1999 – Source: IPCC (2008)
Analyzing of the relative roles of mitigation measures in tackling global climate change
Including:
1)
2) Macroeconomic impacts of climate mitigation
policies.
IER Universität Stuttgart 4
TIAM MACRO
Implementation of variable (time-dependent)
elasticity of substitution
Normalization of the production function
Extensions:
Methodology
Analysis of the relative roles of the decarbonisation
measures in tackling global climate change:
Research question
Objective
3) The responsiveness of energy-services to their prices
becomes stronger over time.
Coupling the energy system model (TIAM) with
a macroeconomic model (MACRO):
TIAM-MACRO model with normalized
production function and variable elasticity of
substitution:
CO2 reduction
CO2 reduction Policy
Higher price of
energy services
Lower energy
service demand
Lower energy
consumption
Analyzing of the relative roles of mitigation measures in tackling global climate change
Objective Function: Maximization of Negishi Weighted sum of
regional Consumptions (C):
𝑀𝑎𝑥 𝑈 =
𝑡=1
𝑇
𝑟
𝑛𝑤𝑡𝑟 . 𝑑𝑓𝑎𝑐𝑡𝑟,𝑡 . ln (𝐶𝑟,𝑡)
𝐶𝑟,𝑡 = 𝑌𝑟,𝑡 − 𝐼𝑁𝑉𝑟,𝑡 − 𝐸𝐶𝑟,𝑡 − 𝑁𝑇𝑋𝑟,𝑡
𝐴𝐺𝐷𝑃𝑟,𝑡 = 𝐶𝑟,𝑡 + 𝐼𝑁𝑉𝑟,𝑡 + 𝑁𝑇𝑋𝑟,𝑡
Production (𝑌𝑟,𝑡) = Constant elasticity of substitution function of
labour (𝐿𝑟,𝑡), capital (𝐾𝑟,𝑡) and service demands (𝐷𝐸𝑀𝑟,𝑡,𝑑𝑚) :
𝑌𝑟,𝑡 = 𝑎𝑘𝑙𝑟. 𝐾𝑟,𝑡𝑘𝑝𝑣𝑠𝑟.𝜌𝑟. 𝐿𝑟,𝑡
1−𝑘𝑝𝑣𝑠𝑟 .𝜌𝑟 + 𝑑𝑚 𝑏𝑟,𝑑𝑚. 𝐷𝐸𝑀𝑟,𝑡,𝑑𝑚𝜌𝑟
1 𝜌𝑟
𝜌𝑟= 1 − 1/𝐸𝑠𝑢𝑏𝑟
IER Universität Stuttgart 5
Macroeconomic model (MACRO stand alone)
Quadratic supply-cost function
𝐸𝐶𝑟,𝑡=
𝑞𝑎𝑟,𝑡 +
𝑑𝑚
𝑞𝑏𝑟,𝑡,𝑑𝑚 . (𝐷𝐸𝑇𝑟,𝑡,𝑑𝑚)2
Energy model (TIAM)
𝐷𝐸𝑇𝑟,𝑡,𝑑𝑚 = 𝐴𝐸𝐸𝐼 𝑟,𝑡,𝑑𝑚 × 𝐷𝐸𝑀𝑟,𝑡,𝑑𝑚
𝑃𝐺𝐷𝑃𝑟,𝑡
𝐴𝐸𝑆𝐶𝑟,𝑡
𝐷𝐸𝑇𝑟,𝑡
𝑃𝑟,𝑡
𝐺𝐷𝑃 𝐿𝑜𝑠𝑠 𝑟,𝑡 =(𝑃𝐺𝐷𝑃𝑟,𝑡 − 𝐴𝐺𝐷𝑃𝑟,𝑡)
𝑃𝐺𝐷𝑃𝑟,𝑡× 100
For region (r), time period (t) and service-demand type (dm):
TIAM-MACRO
𝑷𝑮𝑫𝑷: Projected GDP 𝑵𝑻𝑿: Trade in the numeraire good 𝑨𝑬𝑺𝑪: Energy system cost of TIAM
𝑷 : Marginal price 𝑫𝑬𝑻: Energy service demand of TIAM
𝑬𝑪: Energy system cost [MACRO] 𝑫𝑬𝑴: Energy service demand [MACRO] 𝑨𝑬𝑬𝑰: Autonomous energy efficiency improvement
𝒅𝒇𝒂𝒄𝒕: Discount factor 𝒂𝒌𝒍, 𝒃: Production function constants 𝝆: Substituion constant (time independent)
𝒒𝒂: constant term of the QSF 𝒒𝒃: Coefficient of demands in QSF
𝑰𝑵𝑽: Investment 𝒗𝒔: Capital value share 𝑨𝑮𝑫𝑷: Actual GDP
Source: (Kypreos and Lehtila, 2013)
Analyzing of the relative roles of mitigation measures in tackling global climate change
Objective Function: Maximization of Negishi Weighted sum of
regional Consumptions (C):
𝑀𝑎𝑥 𝑈 =
𝑡=1
𝑇
𝑟
𝑛𝑤𝑡𝑟 . 𝑑𝑓𝑎𝑐𝑡𝑟,𝑡 . ln (𝐶𝑟,𝑡)
𝐶𝑟,𝑡 = 𝑌𝑟,𝑡 − 𝐼𝑁𝑉𝑟,𝑡 − 𝐸𝐶𝑟,𝑡 − 𝑁𝑇𝑋𝑟,𝑡
𝐴𝐺𝐷𝑃𝑟,𝑡 = 𝐶𝑟,𝑡 + 𝐼𝑁𝑉𝑟,𝑡 + 𝑁𝑇𝑋𝑟,𝑡
Production (𝑌𝑟,𝑡) = Constant elasticity of substitution function
of labour ( 𝐿𝑟,𝑡) , capital ( 𝐾𝑟,𝑡) and service demands
(𝐷𝐸𝑀𝑟,𝑡,𝑑𝑚) :
𝑌𝑟,𝑡 = 𝑎𝑘𝑙𝑟. 𝐾𝑟,𝑡𝑘𝑝𝑣𝑠𝑟.𝜌𝑟. 𝐿𝑟,𝑡
1−𝑘𝑝𝑣𝑠𝑟 .𝜌𝑟 + 𝑑𝑚 𝑏𝑟,𝑑𝑚. 𝐷𝐸𝑀𝑟,𝑡,𝑑𝑚𝜌𝑟
1 𝜌𝑟
𝜌𝑟= 1 − 1/𝐸𝑠𝑢𝑏𝑟
IER Universität Stuttgart 6
Macroeconomic model (MACRO stand alone)
Quadratic supply-cost function
𝐸𝐶𝑟,𝑡=
𝑞𝑎𝑟,𝑡 +
𝑑𝑚
𝑞𝑏𝑟,𝑡,𝑑𝑚 . (𝐷𝐸𝑇𝑟,𝑡,𝑑𝑚)2
Energy model (TIAM)
𝐷𝐸𝑇𝑟,𝑡,𝑑𝑚 = 𝐴𝐸𝐸𝐼 𝑟,𝑡,𝑑𝑚 × 𝐷𝐸𝑀𝑟,𝑡,𝑑𝑚
𝑃𝐺𝐷𝑃𝑟,𝑡
𝐴𝐸𝑆𝐶𝑟,𝑡
𝐷𝐸𝑇𝑟,𝑡
𝑃𝑟,𝑡
𝐺𝐷𝑃 𝐿𝑜𝑠𝑠 𝑟,𝑡 =(𝑃𝐺𝐷𝑃𝑟,𝑡 − 𝐴𝐺𝐷𝑃𝑟,𝑡)
𝑃𝐺𝐷𝑃𝑟,𝑡× 100
For region (r), time period (t) and service-demand type (dm):
TIAM-MACRO
𝑷𝑮𝑫𝑷: Projected GDP 𝑵𝑻𝑿: Trade in the numeraire good 𝑨𝑬𝑺𝑪: Energy system cost of TIAM
𝑷 : Marginal price 𝑫𝑬𝑻: Energy service demand of TIAM
𝑬𝑪: Energy system cost [MACRO] 𝑫𝑬𝑴: Energy service demand [MACRO] 𝑨𝑬𝑬𝑰: Autonomous energy efficiency improvement
𝒅𝒇𝒂𝒄𝒕: Discount factor 𝒂𝒌𝒍, 𝒃: Production function constants 𝝆: Substituion constant (time independent)
𝒒𝒂: constant term of the QSF 𝒒𝒃: Coefficient of demands in QSF
𝑰𝑵𝑽: Investment 𝒗𝒔: Capital value share 𝑨𝑮𝑫𝑷: Actual GDP
Source: (Kypreos and Lehtila, 2013)
Analyzing of the relative roles of mitigation measures in tackling global climate changeIER Universität Stuttgart 7
Variability of elasticity of substitution
• In the MACRO model, elasticity of substitution represents the
ease or difficulty of price-induced substitution between energy-
service demands and the value-added pair capital and labor.
• The assumption of constant elasticity of substitution, which limits the reaction of economy to energy price changes,
represents a unique function form of the production function over time.
• However, the constancy of this parameter may contain specification bias in the sense that as time passes firms and
individuals may react differently to price changes.
• To address this issue, Revankar (1966) introduced the concept of Variable Elasticity of Substitution (VES)
production function, in which the assumption of constancy is dropped.
• Several studies (e.g., Diwan, 1970; Lovell 1973; Zellner and Ryu, 1998; Karagiannis et al., 2005) analyzed the
validity of VES production function using empirical data and found it a better function compared to CES and Cobb-
Douglas.
Capital Labor Energy service demands
Analyzing of the relative roles of mitigation measures in tackling global climate change
Applying first-order optimality condition for the base year (t = 0):
• Impossible to implement variable elasticity of substitution.
IER Universität Stuttgart 8
Normalization of production function
• The production function constants are dependent to elasticity of substitution value(s):
𝑌𝑟,𝑡 = 𝑎𝑘𝑙𝑟 . 𝐾𝑟,𝑡𝑘𝑝𝑣𝑠𝑟.𝜌𝑟 . 𝐿𝑟,𝑡
1−𝑘𝑝𝑣𝑠𝑟 .𝜌𝑟 +
𝑑𝑚
𝑏𝑟,𝑑𝑚. 𝐷𝐸𝑀𝑟,𝑡,𝑑𝑚𝜌𝑟
1 𝜌𝑟
𝑏𝑟,𝑑𝑚 = 𝑃𝑟,0,𝑑𝑚 . (𝐷𝐸𝑀𝑟,0,𝑑𝑚𝑌𝑟,0
)1−𝜌𝑟 𝑎𝑘𝑙𝑟 =𝑌𝑟,0𝜌𝑟 − 𝑑𝑚 br,dm. DEMr,0,dm
ρr
𝐾𝑟,0𝑘𝑝𝑣𝑠𝑟.𝜌𝑟
• To tackle this issue, the production function is normalized (introduced by Klump and Grandville, 2000)
𝑌′𝑟,𝑡 = 𝑎𝑘𝑙𝑟∗ . 𝐾′𝑟,𝑡𝑘𝑝𝑣𝑠𝑟.𝜌𝑟 . 𝐿𝑟,𝑡
1−𝑘𝑝𝑣𝑠𝑟 .𝜌𝑟 +
𝑑𝑚
𝑏𝑟,𝑑𝑚∗ . 𝐷𝐸𝑀′𝑟,𝑡,𝑑𝑚
𝜌𝑟
1 𝜌𝑟
Where: 𝑌′𝑟,𝑡 =𝑌𝑟,𝑡
𝑌𝑟,0𝐾′𝑟,𝑡=
𝐾𝑟,𝑡
𝐾𝑟,0𝐷𝐸𝑀′𝑟,𝑡,𝑑𝑚 =
𝐷𝐸𝑀𝑟,𝑡,𝑑𝑚
𝐷𝐸𝑀𝑟,0,𝑑𝑚
𝑏𝑟,𝑑𝑚∗ = 𝑃𝑟,0,𝑑𝑚 . (
𝐷𝐸𝑀𝑟,0,𝑑𝑚𝑌𝑟,0
) 𝑎𝑘𝑙𝑟∗ = 1 −
𝑑𝑚
𝑏𝑟,𝑑𝑚∗
• Normalization creates specific ‘families’ of functions whose members share the same baseline points.
Analyzing of the relative roles of mitigation measures in tackling global climate changeIER Universität Stuttgart 9
VES versus CES: scenario description
• In order to compare VES production function with CES production function, following two scenarios are defined:
Scenario Description
Elasticity of substitution 1000 GtCO2 budget (2020-2100)
2D (0.25) 0.25 (constant)
2D (0.2-0.3) 0.2 - 0.3 (variable)
0.1
0.15
0.2
0.25
0.3
0.35
2000 2020 2040 2060 2080 2100
Ela
stic
ity
of
sub
stit
uti
on
Analyzing of the relative roles of mitigation measures in tackling global climate changeIER Universität Stuttgart 10
VES versus CES: results World GDP-Loss
• The level of net effect of decarbonisation on GDP is related to the demand reduction possibility. Thus, higher/lower
elasticity of substitution leads to lower/higher GDP-loss.
• Due to the assumed function of variable elasticity, service demand reduction of 2D (0.25) case is lower than that of 2D
(0.2-0.3) before 2060 and higher after this year.
• In 2100, service demand reduction and GDP losses of 2D (0.2-0.3) are 23% higher and 12% lower than those of the
other case, respectively.
• changes of total global energy-service demand:
%
• Total global GDP-Loss:
0
1
2
3
4
5
6
2020 2030 2040 2050 2060 2070 2080 2090 2100
%
2D (0.2-0.3)
2D (0.25)
-30
-25
-20
-15
-10
-5
0
2020 2030 2040 2050 2060 2070 2080 2090 2100
2D (0.2-0.3)
2D (0.2)
Analyzing of the relative roles of mitigation measures in tackling global climate changeIER Universität Stuttgart 11
Scenario definition
1. To limit 2 degree temperature increase by the probability of more than 50%.
2. The initial potentials are mainly based on the high estimate of nuclear electrical generation capacity in 2013 report of International
Atomic Energy Agency (IAEA).
3. The initial potentials of carbon storages are given based on the “best estimation” of econfys (2004).
4. The initial potentials of renewables are based on the assumed possible expansion pathways of different renewables which are provided by