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The WITCH 2016 Model - Documentation and Implementation of the Shared Socioeconomic Pathways

Author

Listed:
  • Emmerling, Johannes
  • Drouet, Laurent Drouet
  • Reis, Lara Aleluia
  • Bevione, Michela
  • Berger, Loic
  • Bosetti, Valentina
  • Carrara, Samuel
  • De Cian, Enrica
  • De Maere D'Aertrycke, Gauthier
  • Longden, Tom
  • Malpede, Maurizio
  • Marangoni, Giacomo
  • Sferra, Fabio
  • Tavoni, Massimo
  • Witajewski-Baltvilks, Jan
  • Havlik, Petr

Abstract

This paper describes the WITCH - World Induced Technical Change Hybrid - model in its structure, calibration, and the implementation of the SSP/RCP scenario implementation. The WITCH model is a regionally disaggregated hard-linked model based on a Ramsey type optimal growth model and a detailed bottom-up energy sector model. A particular focus of the model is the modeling or technical change and RnD investments and the analysis of cooperative and non-cooperative climate policies. Moreover, the WITCH 2016 version now includes land-use change modeling based on the GLOBIOM model, and air pollutants, as well as detailed modeling of the transport sector and the possibility for stochastic modeling. This version has been also used to implement the Shared Socioeconomic Pathways (SSPs) set of scenarios and RCP based climate policies to provide a new set of climate scenarios. In this paper, we describe in detail the mathematical formulation of the WITCH model, the solution method and calibration, as well as the implementation of the five SSP scenarios. This report therefore provides detailed information for interested users of the model, and for understanding the implementation of the different “worlds" of the SSP.

Suggested Citation

  • Emmerling, Johannes & Drouet, Laurent Drouet & Reis, Lara Aleluia & Bevione, Michela & Berger, Loic & Bosetti, Valentina & Carrara, Samuel & De Cian, Enrica & De Maere D'Aertrycke, Gauthier & Longden,, 2016. "The WITCH 2016 Model - Documentation and Implementation of the Shared Socioeconomic Pathways," MITP: Mitigation, Innovation and Transformation Pathways 240748, Fondazione Eni Enrico Mattei (FEEM).
  • Handle: RePEc:ags:feemmi:240748
    DOI: 10.22004/ag.econ.240748
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    File URL: https://ageconsearch.umn.edu/record/240748/files/NDL2016-042R.pdf
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    Cited by:

    1. Antoine GODIN & Emanuele CAMPIGLIO & Eric KEMP-BENEDICT, 2017. "Networks of stranded assets: A case for a balance sheet approach," Working Paper d51a41b5-00ba-40b4-abe6-5, Agence française de développement.
    2. Johannes Emmerling, 2018. "Sharing Of Climate Risks Across World Regions," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 1-19, August.
    3. De Cian, Enrica & Dasgupta, Shouro & Hof, Andries F. & van Sluisveld, Mariësse A.E. & Köhler, Jonathan & Pfluger, Benjamin & van Vuuren, Detlef P., 2020. "Actors, decision-making, and institutions in quantitative system modelling," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    4. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2018. "Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model," Ecological Economics, Elsevier, vol. 150(C), pages 315-339.
    5. Pietzcker, Robert C. & Ueckerdt, Falko & Carrara, Samuel & de Boer, Harmen Sytze & Després, Jacques & Fujimori, Shinichiro & Johnson, Nils & Kitous, Alban & Scholz, Yvonne & Sullivan, Patrick & Ludere, 2017. "System integration of wind and solar power in integrated assessment models: A cross-model evaluation of new approaches," Energy Economics, Elsevier, vol. 64(C), pages 583-599.
    6. Luderer, Gunnar & Pietzcker, Robert C. & Carrara, Samuel & de Boer, Harmen Sytze & Fujimori, Shinichiro & Johnson, Nils & Mima, Silvana & Arent, Douglas, 2017. "Assessment of wind and solar power in global low-carbon energy scenarios: An introduction," Energy Economics, Elsevier, vol. 64(C), pages 542-551.
    7. Lara Aleluia Reis & Laurent Drouet & Rita Van Dingenen & Johannes Emmerling, 2018. "Future Global Air Quality Indices under Different Socioeconomic and Climate Assumptions," Sustainability, MDPI, Open Access Journal, vol. 10(10), pages 1-27, October.
    8. Adriano Vinca & Marianna Rottoli & Giacomo Marangoni & Massimo Tavoni, 2017. "The Role of Carbon Capture and Storage Electricity in Attaining 1.5 and 2°C," Working Papers 2017.54, Fondazione Eni Enrico Mattei.
    9. Yi-Ming Wei & Rong Han & Qiao-Mei Liang & Bi-Ying Yu & Yun-Fei Yao & Mei-Mei Xue & Kun Zhang & Li-Jing Liu & Juan Peng & Pu Yang & Zhi-Fu Mi & Yun-Fei Du & Ce Wang & Jun-Jie Chang & Qian-Ru Yang & Zil, 2018. "An integrated assessment of INDCs under Shared Socioeconomic Pathways: an implementation of C3IAM," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 92(2), pages 585-618, June.
    10. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.
    11. Enrica De Cian & Johannes Buhl & Samuel Carrara & Michela Bevione & Silvia Monetti & Holger Berg, 2016. "Knowledge Creation between Integrated Assessment Models and Initiative-Based Learning - An Interdisciplinary Approach," Working Papers 2016.66, Fondazione Eni Enrico Mattei.
    12. Heleen L. van Soest & Lara Aleluia Reis & Laurent Drouet & Detlef P. van Vuuren & Michel G. J. den Elzen & Massimo Tavoni & Keigo Akimoto & Katherine V. Calvin & Panagiotis Fragkos & Alban Kitous & Gu, 2017. "Low-emission pathways in 11 major economies: comparison of cost-optimal pathways and Paris climate proposals," Climatic Change, Springer, vol. 142(3), pages 491-504, June.
    13. Carrara, Samuel & Marangoni, Giacomo, 2017. "Including system integration of variable renewable energies in a constant elasticity of substitution framework: The case of the WITCH model," Energy Economics, Elsevier, vol. 64(C), pages 612-626.
    14. Carrara, Samuel, 2020. "Reactor ageing and phase-out policies: global and regional prospects for nuclear power generation," Energy Policy, Elsevier, vol. 147(C).
    15. I. Mouratiadou & M. Bevione & D. L. Bijl & L. Drouet & M. Hejazi & S. Mima & M. Pehl & G. Luderer, 2018. "Water demand for electricity in deep decarbonisation scenarios: a multi-model assessment," Climatic Change, Springer, vol. 147(1), pages 91-106, March.
    16. Miremadi, I. & Saboohi, Y. & Arasti, M., 2019. "The influence of public R&D and knowledge spillovers on the development of renewable energy sources: The case of the Nordic countries," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 450-463.
    17. Olivera Kostoska & Ljupco Kocarev, 2019. "A Novel ICT Framework for Sustainable Development Goals," Sustainability, MDPI, Open Access Journal, vol. 11(7), pages 1-31, April.
    18. Hongjie Sun & Shuwen Niu & Xiqiang Wang, 2019. "Future Regional Contributions for Climate Change Mitigation: Insights from Energy Investment Gap and Policy Cost," Sustainability, MDPI, Open Access Journal, vol. 11(12), pages 1-17, June.
    19. Hof, Andries F. & Carrara, Samuel & De Cian, Enrica & Pfluger, Benjamin & van Sluisveld, Mariësse A.E. & de Boer, Harmen Sytze & van Vuuren, Detlef P., 2020. "From global to national scenarios: Bridging different models to explore power generation decarbonisation based on insights from socio-technical transition case studies," Technological Forecasting and Social Change, Elsevier, vol. 151(C).

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    Keywords

    Research and Development/Tech Change/Emerging Technologies;

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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