A stochastic optimization approach to determine efficient environmental protection strategies
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1 Institut für Energiewirtschaft und IER Rationelle Energieanwendung A stochastic optimization approach to determine efficient environmental protection strategies Christian Schieberle 46th Task Force on Integrated Assessment Modelling (TFIAM), 2-3 May 2017, Paris
2 Overview Approach to determine efficient environmental protection strategies Objectives Methodology Meta-regression based evidence on travel demand elasticities Case study: Passenger transport in 2030 in EU28+2 Conclusion and future work IER Universität Stuttgart 2
3 Objectives Approach to determine efficient environmental protection strategies General objective: Cost-efficient environmental protection strategies by trading-off the avoidance of impacts against cost and loss of surplus Scope of this presentation: Passenger transport as a representative example for sectors in which considerable technical progress has already been achieved; necessity to model behavioural change ( MRA) Account for decision-maker s risk attitude; i.e. deal with uncertainty of impact assessment as well as uncertainty of response to policy implementation ( stochastic CBA) IER Universität Stuttgart 3
4 Methodology Summary of main methodological aspects Cost-benefit analysis including avoided damages (assessed via IPA) and induced costs (including utility losses) Degrees of freedom (i.e. variables): policy implementation (fares, tolls, taxes, etc.) Objective: maximization of net benefit (EV, CVaR, weighted) Implementation: Uncertainty of response estimated by meta-regression Non-linear nature of response accounted for by piecewise-linear approx. Uncertainty of individual IPA steps (from emission to monetized impacts) Stochastic optimization: MIP formulated in GAMS EMP IER Universität Stuttgart 4
5 Meta-regression analysis (MRA) Systematic literature review to determine meta-regression models Data sources: TRID (TRB+OECD) BITRE Elasticity database TDM encyclopedia Focus: PT wrt. fuel price PT/IT wrt. bus fares PT/IT wrt. city transit fares (rail-bound) Toll / road pricing IT / PT wrt. train fares IT / PT wrt. coach fares IER Universität Stuttgart 5
6 IER Universität Stuttgart
7 Meta-regression analysis (MRA) Example: Country-specific short-/long-term PT cross-demand elasticity of fuel price IER Universität Stuttgart 7
8 Meta-regression analysis (MRA) Example: Country-specific short-term PT cross-demand elasticity of fuel price IER Universität Stuttgart 8
9 Case study: Passenger transport in EU28+2 Model set-up 2030 reference demand levels adjusted for income Selection and parametrization of policies (under constraints), e.g. Fuel tax Public transport fares (bus, metro, trains, ) City toll Objective function Risk-neutral case (EV) Risk-averse case (CVaR 0.2 ~ EV of 20% worst cases) Parametrized risk-attitude: (φ * EV) + ((1- φ) * CVaR Θ ), φ in [0; 1], Θ in {0.2, 0.1, 0.05, } IER Universität Stuttgart 9
10 Case study: Passenger transport in EU28+2 Different risk attitudes 7 6 Objective function: maximize z = (φ * EV) + ((1- φ) * CVaR Θ ) EV (expected value) Net benefit [10 9 ] CVaR 0.2 (conditional value-at-risk) risk premium 2 φ= φ= φ= φ= IER Universität Stuttgart 10
11 Case study: Passenger transport in EU28+2 Avoided damages in risk-neutral case (k-eur per country per income group) IER Universität Stuttgart 11
12 Conclusions wrt. results of the case study Both scenarios yield net benefit; only moderate risk premium Summary of policies: General tendency to lower fares to pull people towards public transport in urban areas Favourable to implement city toll, especially for vans Avoid to push people away from individual travel using a fuel tax as people s response is highly uncertain; might even cause rebound effects Transport inequality will even be aggravated spend money on compensation payments for higher acceptance IER Universität Stuttgart 12
13 Institut für Energiewirtschaft und IER Rationelle Energieanwendung Vielen Dank! Christian Schieberle Telefon +49 (0) Fax +49 (0) Universität Stuttgart
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