Economy-Energy-Environment (E3)Model:
Energy Technology and Climate Change
Youngho Chang
Division of Economics and [email protected]
Nanyang Technological University
29 June 2013
Workshop at Meijo University
Agenda
• Introduction
– Climate Change: Latest Developments
• The Economics of Climate Change
– Model Structure
• Economy
• Energy
• Environment
– Data and Simulation Results
• Emission Trajectories
• Temperature Change
• Global Output Trajectories
• Concluding Remarks
2
Unequivocal Warming of the Climate System
•
Source: Intergovernmental Panel on Climate Change (2007)
3
Economic Approaches
• Bottom-up approach
– Mostly engineering-based
– Sector-specific energy demand functions
– No feedback between economic growth and energy
demand
• Not explicitly consider the shadow price of carbon
• Top-down approach
– Economic model
– Adopts a feedback relationship of carbon emissions
and their damage upon an economy
– Lack of details in representing end-uses of energy
• Insufficient reflection of the impact of more efficient end-use
technologies
4
Economy, Energy, and Environment:
An Analytical Framework
• Economy, energy, and environment are
interconnected
• How are they connected?
– Economy-energy
• Through the production function
– Energy is a third input for production along with existing
two production factors, capital and labor
– Energy-environment
• Through a carbon dynamics
– Life cycle of carbon
– When energy is used, it emits carbon dioxide among
others, and causes eventual accumulation of carbon in the
atmosphere
– Environment-economy
• Through possible damage from the accumulated carbon
in the atmosphere and/or carbon-abating activity
5
Two-sector Energy Model
• Maximizes the discounted sum of utility from per capita
consumption subject to
– Capital stock
– Resource stock
– Carbon stock
• The objective function

max W   u [ c ( t )] e dt
c(t )
–
–
–
–
–
 t
0
u(c): the utility from per capita consumption
c(t): The per capita consumption
 : The pure rate of social time preference
Population grows exogenously
Multiplying population, L(t), By the utility from per capita
consumption yields the total utility
6
Production
• A production technology, F(K, R, L)
– Exhibits constant returns to scale
– Linearly homogenous in the three inputs
– Produces capital goods and consumption goods
•
F = Fi(Ki, Ri, Li),
i = end-uses/sectors
– Ki: the capital stock in each sector
– Ri: the resource in each sector
– Li: the labor inputs in each sector
• Three resources and a backstop technology
– Oil (P),
– Coal (A)
– Natural gas (G)
– Backstop technology (B).
– Ri = Pi + Ai + Gi + Bi, i = end-uses
7
Energy (Resource)
• An energy-technology framework
– Represents endogenous substitutions among energy resources
– Reflects heterogeneous demand between sectors and
simultaneous extraction of energy resources across sectors
– Provides energy profiles for production process
– Sets into a carbon dynamics
• Structure
– Extraction cost (resource production cost)
– Conversion cost
• Cost to meet the criteria of each end-use
– Stock constraint
• Set availability of the resource
• Provide transition from one resource to another
• Scarcity rent: implicit price
8
Resource Cost Function
• The resource cost, ij,
– Defined as the sum of extraction cost and conversion costs
•
Ij = ej + zij. and ib = zib
• When we take into account heterogeneous demand, conversion
cost, and extraction cost, we have a resource cost matrix, ij (2x4)
– i : the sectors (end-uses)
• The capital goods producing sector
• The consumption goods producing sector
– j : the resources
• Oil
• Coal
• Natural gas
• Solar energy (backstop technology)
9
Environment
• Carbon Dynamics
– An aggregate representation of general circulation models
(GCMs)
– An optimal growth-damage framework
– Captures feedbacks from emission controls through the carbon
dynamics to the economy
– Damages are quantified as some fractions of the global output
• Structure
– Emissions
– Atmospheric concentration of carbons a.k.a. carbon stock
– Radiative forcings
– Temperature changes
– An output scaling factor
10
Workings of Carbon Dynamics
• When energy resource is used in an economy, it produces
– Outputs (goods and services)
– Carbon emissions with other gases
• A fraction of the emissions increases
– Atmospheric concentration of GHGs
– Radiative forcings
– Equilibrium temperature
• Eventually imposes a certain level of damage to the economy
due to the higher temperature
• A feedback relationship between climate and economic variables in
a macroeconomic structure
– An economic model
• Impact of temperature rise on the economy as a whole
– An energy model
– A carbon cycle/temperature model
• Flows of carbon dioxide emissions by economic activities and
temperature change
11
Damage from Climate Change
• Possible damage from climate change is very
elusive
– A major source of climate change
• Temperature changes due to higher concentrations of
greenhouse gases in the atmosphere
– The impact of climate change
• Can be express as a function of the change in global mean
surface temperature from pre-industrial times, T(t).
D ( t )  Q ( t ) T ( t )
2
1
– D(t) : the loss of global output
– 1 : a parameter representing the scale of damage (0.00144)
– 2 : an exponent reflecting non-linearity in the damage function
(2)
12
Total Costs Function
• The costs of reducing carbon dioxide emissions
TC ( t )  Q ( t ) b  ( t )
b
2
1
–
–
–
–
TC(t) : the total costs of reducing carbon dioxide emissions
 : the fractional reduction in greenhouse gas emissions
b1 : the scale factor (0.0686)
b2 : represent non-linearity of the cost function (2.887)
• The initial reduction in the carbon dioxide emissions is
relatively inexpensive
• An example
– If the fractional reduction in greenhouse gas emissions in the
year of 1995 is 12 % (0.12), then the total cost of reducing
emissions is 0.015 % of the global output
13
Output Scaling Factor
• A final form of output scaling factor
 (t ) 
b
2
]

2
]
[1  b  ( t )
1
[1   T ( t )
1
– b1 and b2 : parameters of emission reduction cost function
– 1 and 2 : Parameters of damage function
• F = i Fi(Ki, Ri, Li), i = end-uses/sectors
• Example
– If we assume a 3-degree increase in average temperature and
12% reduction in emissions,
• The value of is 0.987191.
– The projected global output is 1.28% less than what it would be
otherwise
14
Workings of Output Scaling Factor
Damage
Yes
No
Yes
<< 1
<1
No
<1
1
Cost
15
Extraction Costs and Resource Stocks
by Grade ($/mmBTU) (Billion mmBTU)
Resource
Grade I
Grade II
Gas
0.92
(6,683.98)
0.60
(11,242.67)
0.65
(225,622.35)
3.47
(4,916.13)
Oil
Coal
2.37
(121,354.20)
Grade III
5.08
(82,068.59)
16
Cost of Converting Energy Resources into
End Uses ($/Delivered mmBTU)
Resources
Capital Sector
Consumption
Sector
13.50
Oil
2.64
Coal
9.10
19.71
Gas
2.13
7.29
Solar
87.91
96.55
17
Simulation Scenarios
• Simulation periods
– 1965-2355 (400 years)
• Simulation scenarios
– Baseline
– Technology-related
• Costs of converting solar energy into electricity
• Decrease at 5%; 10%; 30%; 50% per decade
– Policy-related
• Carbon emissions level is stabilized at 10 billion
tons of carbon per year
18
Simulation Results and Interpretations
• Energy use patterns by sector
– The faster cost decreases, the earlier the time of switching
in resource use
• Carbon emissions trajectory
– The faster cost decreases, the lower the peak of carbon
emissions
• Global mean surface temperature change
– Under the case of cost of using solar energy decreases at
50% per decade, the maximum temperature change could
be lower than 2 degree Celsius
• Global output by technological progress
– The highest technological progress case (the 50% cost
reduction) presents the highest global output trajectory.
• Impact of different scenarios on discounted consumption
– The 50% case gives the largest objective value
19
Energy Use Pattern by Sector
Year
1965
1975
1985
1995
2005
2015
2025
2035
2045
2055
2065
2075
2085
2095
2105
2115
2125
2135
2145
2155
2165
2175
2185
2195
2205
2215
2225
2235
2245
2255
2265
2275
2285
2295
2305
2315
2325
2335
2345
Baseline
Cap S
oil
oil
oil
oil
oil
oil
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
Con S
gas
gas
gas
gas/oil
oil
oil/coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
5%
Cap S
oil
oil
oil
oil
oil
oil
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
solar
solar
solar
solar
solar
solar
solar
solar
solar
Con S
gas
gas
gas
gas/oil
oil
oil/coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
10%
Cap S
oil
oil
oil
oil
oil
oil
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
Con S
gas
gas
gas
gas/oil
oil
oil/coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
30%
Cap S
oil
oil
oil
oil
oil
oil
coal
coal
coal
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
Con S
gas
gas
gas
gas/oil
oil
oil/coal
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
50%
Cap S
oil
oil
oil
oil
oil
oil
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
Con S
gas
gas
gas
gas/oil
oil
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
solar
Emission at 10
Cap S
Con S
oil
gas
oil
gas
oil
gas
oil
gas/oil
oil
oil
oil
oil/coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
coal
20
23
45
23
25
23
05
22
85
22
65
22
45
22
25
22
05
21
85
21
65
21
45
21
25
21
05
20
85
20
65
20
45
20
25
20
05
19
85
19
65
Billion ton of Carbon
Carbon Emissions
Emissions (CO2 equivalent)
45
40
35
30
25
20
Baseline
5%
10%
30%
50%
15
10
5
0
YEAR
21
Global Mean Surface Temperature Change
Global Mean Temperature Change
7
6
Baseline
5%
10%
30%
50%
Stabilization
4
3
2
1
23
45
23
25
23
05
22
85
22
65
22
45
22
25
22
05
21
85
21
65
21
45
21
25
21
05
20
85
20
65
20
45
20
25
20
05
19
85
0
19
65
C Degrees
5
YEAR
22
Global Output Trajectories
Global Output
300
250
200
Trillion US$
Baseline
5%
150
10%
30%
50%
100
50
0
YEAR
23
Impacts of Scenarios on Discounted
Consumption
Impact of Program on Discounted Value of Consumption
1.2
1
0.8
Percent
0.6
0.4
0.2
0
5%
10%
30%
50%
E at 10
-0.2
SCENARIOS
24
Concluding Remarks
• Global negotiation meetings on replacing the Kyoto
Protocol in 2013 is on the way and a chance of
producing a new global agreement by 2010 is not large
• Switching to non-carbon emitting fuels would be a
solution for mitigating atmospheric accumulation of
carbon
– However, costs needed for realizing such technologies are not
verified
• Policies like stabilizing carbon emission at a certain level
are not effective in mitigating temperature rise and
costly.
• The difference between a climate-change and a noclimate-change scenario would be thinner than the pencil
needed to draw the curves.
– Thomas Schelling (1983)
25
Thank you for your attention!
Should you have any questions or
comments, please contact me at
[email protected]
26