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A new robustness analysis for climate policy evaluations: A CGE application for the EU 2020 targets

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  • Hermeling, Claudia
  • Löschel, Andreas
  • Mennel, Tim

Abstract

This paper introduces a new method for stochastic sensitivity analysis for computable general equilibrium (CGE) model based on Gauss Quadrature and applies it to check the robustness of a large-scale climate policy evaluation. The revised version of the Gauss-quadrature approach to sensitivity analysis reduces computations considerably vis-à-vis the commonly applied Monte-Carlo methods; this allows for a stochastic sensitivity analysis also for large scale models and multi-dimensional changes of parameters. In the application, an impact assessment of EU2020 climate policy, we focus on sectoral elasticities that are part of the basic parameters of the model and have been recently determined by econometric estimation, alongside with standard errors. The impact assessment is based on the large scale CGE model PACE. We show the applicability of the Gauss-quadrature approach and confirm the robustness of the impact assessment with the PACE model. The variance of the central model outcomes is smaller than their mean by order four to eight, depending on the aggregation level (i.e. aggregate variables such as GDP show a smaller variance than sectoral output).

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  • Hermeling, Claudia & Löschel, Andreas & Mennel, Tim, 2013. "A new robustness analysis for climate policy evaluations: A CGE application for the EU 2020 targets," Energy Policy, Elsevier, vol. 55(C), pages 27-35.
  • Handle: RePEc:eee:enepol:v:55:y:2013:i:c:p:27-35
    DOI: 10.1016/j.enpol.2012.08.007
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    References listed on IDEAS

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    1. Arndt, Channing, 1996. "An Introduction To Systematic Sensitivity Analysis Via Gaussian Quadrature," Technical Papers 28709, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    2. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, September.
    3. DeVuyst, Eric A. & Preckel, Paul V., 1997. "Sensitivity analysis revisited: A quadrature-based approach," Journal of Policy Modeling, Elsevier, vol. 19(2), pages 175-185, April.
    4. Azusa OKAGAWA & Kanemi BAN, 2008. "Estimation of substitution elasticities for CGE models," Discussion Papers in Economics and Business 08-16, Osaka University, Graduate School of Economics.
    5. Boeters, Stefan & Koornneef, Joris, 2011. "Supply of renewable energy sources and the cost of EU climate policy," Energy Economics, Elsevier, vol. 33(5), pages 1024-1034, September.
    6. Capros, Pantelis & Mantzos, Leonidas & Parousos, Leonidas & Tasios, Nikolaos & Klaassen, Ger & Van Ierland, Tom, 2011. "Analysis of the EU policy package on climate change and renewables," Energy Policy, Elsevier, vol. 39(3), pages 1476-1485, March.
    7. Böhringer, Christoph & Rutherford, Thomas F. & Tol, Richard S. J., 2009. "The EU 20/20/2020 Targets: An Overview of the EMF22 Assessment," Papers WP325, Economic and Social Research Institute (ESRI).
    8. Tol, Richard S.J., 2009. "Intra-union flexibility of non-ETS emission reduction obligations in the European Union," Energy Policy, Elsevier, vol. 37(5), pages 1745-1752, May.
    9. Hermeling, Claudia & Mennel, Tim, 2008. "Sensitivity Analysis in Economic Simulations: A Systematic Approach," ZEW Discussion Papers 08-068, ZEW - Leibniz Centre for European Economic Research.
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    1. > Economic Development Technological Change, and Growth > Technological Change: Choices and Consequences > Technology Assessment

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