Flexible Global Climate Change PolicyESD.71 Application Portfolio: December 2009Nidhi R. SantenPh.D. Student, 2ndYearEngineering Systems [email protected]© 2009 Nidhi R. SantenPresentation Outline Problem Overview (1) Application System (1) Sources of Uncertainty (3) Fixed and Flexible Designs (1) Decision Tree Analysis (2) Lattice Analysis (2) Conclusions (2) Questions?© 2009 Nidhi R. SantenProblem Overview Current climate change policy decisions are based on deterministic views of the future events, dominated by considerations of a single optimal carbon emissions path. Many aspects of the future remain highly uncertain, creating the need for flexible climate policies. Implementing an R&D-inducing carbon tax policy today provides a form of “insurance” against future carbon-emissions related climate damages, representing a important form of flexibility. The following project examines the opportunities that flexible global climate change policy can have on the overall net present welfare of the global economy.© 2009 Nidhi R. SantenApplication System Key Components of System Aggregated Global Economy, includes Production = f(Capital, Labor, Fossil-Fuel Energy Sector) Physical Environment Population’s Utility Function (Preferences for Consumption v. Investment) Dynamic Integrated model for Climate and the Economy (DICE-99) is used as the evaluation model for system performance Timeframe is 2015 through 2335© 2009 Nidhi R. SantenSources of Uncertainty (1 of 3)Total Factor Productivity Growth Rate: TPF is the contribution to economic output not accounted for by inputs such as labor and capital; level of technology in the economy© 2009 Nidhi R. SantenHistogram: Total Factor Productivity 010203040506016.00%16.06%16.11%16.17%16.23%16.29%16.34%16.40%16.46%16.51%16.57%16.63%16.69%16.74%16.80%16.86%16.91%16.97%17.03%17.09%17.14%FrequencyPercent Per DecadeData: MIT Joint ProgramSources of Uncertainty (2 of 3)Emissions Intensity Growth Rate:Emissions intensity is the trend in CO2-equivalent emissions per unit of output without a carbon-reducing policy in place© 2009 Nidhi R. SantenHistogram: Growth Rate of Sigm a05101520253035404550‐0. 09‐1. 08‐2. 08‐3. 07‐4. 07‐5. 07‐6. 06‐7. 06‐8. 06‐9. 05‐10.05‐11.04‐12.04‐13.04‐14.03‐15.03‐16.02‐17.02‐18.02‐19.01‐20.01Percent Per DecadeFrequencData: MIT Joint ProgramSources of Uncertainty (3 of 3)Climate FeedbackA cloud-related parameter that represents the sensitivity of the climate to GHGs© 2009 Nidhi R. SantenHistogram: Climate Feedback01002003004005006001.65 4.10 6.54 8.98 11.42Climate FeedbackFrequencData: MIT Joint ProgramFixed and Flexible Designs Fixed Design In both studies: Business-as-usual case with no carbon-tax policy Flexible Designs Investigation 1 (2 Period): High or low carbon tax policy implemented in Period 1 with an option to change tax level in Period 2. Investigation 2 (6 Period): Option to implement a medium carbon tax at any period.© 2009 Nidhi R. SantenDecision Analysis (1 of 2)© 2009 Nidhi R. SantenDesign Emissions Reduction (µt) ($ Tax)Fixed “No” Policy (“Business‐as‐Usual”) No Control ($0 per ton) Both Decision PointsFlexible Policies (Carbon Taxes) 2015: High ($30) / 2065: High ($80)2015: High ($30) / 2065: Low ($30)2015: Low ($10) / 2065: High ($80)2015: Low ($10) / 2065: Low ($30)Policy Design Alternatives and UncertaintiesDecision Analysis ComponentsStages: 2 (2015-2055 and 2065-2335)Decision in Period 1: Tax High, Tax Low, or No TaxUncertainties Considered: Emission Intensity Growth Rate and Climate FeedbackPayoff Value: NPV WelfareUncertain Parameter High Medium LowEmission Intensity Growth Rate (σt)P(σ=‐30.055) = 0.185 P(σ=‐‐15.885) = 0.63 P(σ=‐1.082) = 0.185Climate Feedback Parameter (λt)P(λ=4.682) = 0.185 P(λ=2.908) = 0.63 P(λ=1.134) = 0.185Decision Analysis (2 of 2)© 2009 Nidhi R. SantenDecision Tree Analysis VARG Curve00.10.20.30.40.50.60.70.80.91966.6 966.8 967 967.2 967. 4 967.6 967.8 968 968.2 968. 4NPVProbabilitTax Hi gh Tax Low No Tax (No Flexibility-Fixed) Decision Tree Analysis VARG CurveDecision Tree Solution Optimal Strategy: Tax Low in Period 1; Tax High in Period 2Risk Assumption Preferred Period 1 DesignP10 Tax LowP15 Tax HighP50 No Tax (Inflexible Case)P75 No Tax (Inflexible Case)P90 No Tax (Inflexible Case)Lattice Analysis (1 of 2) Policy Design Alternatives BAU No-Tax Case Option to Begin Implementing a $45 per ton Carbon Tax in any Period (Modeled as a “Call Option”) Uncertainty Considered: TPF Growth Rate “How long should we wait to implement a carbon tax?”© 2009 Nidhi R. SantenLattice Analysis (2 of 2)Dynamic Programming Decision Analysis Optimal Strategy:Always Decide to Implement $45 per ton Carbon Tax© 2009 Nidhi R. SantenPeriod t = 0 t = 1 t = 2 t = 3 t = 4 t = 5 t = 6Exercise CALL OPTION?NO YES YES YES YES YESYES YES YES YES YESYES YES YES YESYES YES YESYES YESYESRisk Assumption Preferred Period 1 DesignP10 Flexible CaseP25 Flexible CaseP50 Flexible CaseP75 Flexible CaseP95 Flexible CaseConclusions Investigation 1 (Decision Tree Analysis): The value of flexibility was $0.019316 trillion for the optimal strategy. Investigation 2 (Lattice Analysis): the value of the call option to implement a carbon-tax when deemed appropriate was $0.51 trillion. Flexible policy strategies are chosen over inflexible policy strategies in both investigations.© 2009 Nidhi R. SantenConclusions© 2009 Nidhi R. SantenConclusions© 2009 Nidhi R. SantenThank [email protected] Richard de NeufvilleTA Michel-Alexandre Cardin © 2009 Nidhi R.
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