Economy-Energy-Environment (E3)Model: Energy Technology and Climate Change Youngho Chang Division of Economics and Nanyang Technological University 29 June 2013 Workshop at Meijo University

2 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

3 Unequivocal Warming of the Climate System Source: Intergovernmental Panel on Climate Change (2007)

4 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

5 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

6 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 –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

7 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 = F i (K i, R i, L i ), i = end-uses/sectors –K i : the capital stock in each sector –R i : the resource in each sector –L i : the labor inputs in each sector Three resources and a backstop technology –Oil (P), –Coal (A) –Natural gas (G) –Backstop technology (B). –R i = P i + A i + G i + B i, i = end-uses

8 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

9 Resource Cost Function The resource cost,  ij, –Defined as the sum of extraction cost and conversion costs  Ij = e j + z ij. and  ib = z ib 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)

10 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

11 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

12 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) : the loss of global output –  1 : a parameter representing the scale of damage ( ) –  2 : an exponent reflecting non-linearity in the damage function (2)

13 Total Costs Function The costs of reducing carbon dioxide emissions –TC(t) : the total costs of reducing carbon dioxide emissions –  : the fractional reduction in greenhouse gas emissions –b 1 : the scale factor (0.0686) –b 2 : 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 % of the global output

14 Output Scaling Factor A final form of output scaling factor –b 1 and b 2 : parameters of emission reduction cost function –  1 and  2 : Parameters of damage function F =  i F i (K i, R i, L i ), i = end-uses/sectors Example –If we assume a 3-degree increase in average temperature and 12% reduction in emissions, The value of is –The projected global output is 1.28% less than what it would be otherwise

15 Workings of Output Scaling Factor Damage YesNo Cost Yes<< 1< 1 No< 11

16 Extraction Costs and Resource Stocks by Grade ($/mmBTU) (Billion mmBTU) ResourceGrade IGrade IIGrade III Gas0.92 (6,683.98) Oil0.60 (11,242.67) 3.47 (4,916.13) Coal0.65 (225,622.35) 2.37 (121,354.20) 5.08 (82,068.59)

17 Cost of Converting Energy Resources into End Uses ($/Delivered mmBTU) ResourcesCapital SectorConsumption Sector Oil Coal Gas Solar

18 Simulation Scenarios Simulation periods – (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

19 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

20 Energy Use Pattern by Sector

21 Carbon Emissions

22 Global Mean Surface Temperature Change

Global Output Trajectories 23

24 Impacts of Scenarios on Discounted Consumption

25 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 no- climate-change scenario would be thinner than the pencil needed to draw the curves. –Thomas Schelling (1983)

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