Researching Climate and Policy with WITCH
Valentina Bosetti is sure that "algorithm is an universal language, even more than English. Algorithms ease communication among researchers. They are immediately understandable by a physicist, a climate scientist, an economist. They allow interdisciplinarity and internationalization of research groups". Bosetti is Associate Professor in the Department of Economics at Bocconi University, teaching Environmental and Climate Change Economics, and she's a researcher at the WITCH project funded by Fondazione Eni Enrico Mattei, Centro Euro-Mediterraneo sui Cambiamenti Climatici and the European Commission. WITCH stands for World Induced Technical Change Hybrid model. It's a dynamic integrated model designed to assess climate change mitigation and adaptation policies in thirteen macro regions including among others Western EU Countries, United States of America, China, India, South East Asia.
"The model" Bosetti says "is the outcome of the work of an interdisciplinary team where Italian, German, French, Portuguese, Belgian, Chinese, Japanese, and Australian researchers all interact. It evaluates the impacts of climate change, starting with the question: how much energy will be needed in the next hundred years? At what level of emissions? The model predicts what will happen in the next century according to macroeconomic, political, and demographic assumptions". Macro regions can be adjusted to the scope of the analysis. One algorithm assesses the consequences of regional disaggregation using a game theory setup. "WITCH is the only existing Italian model. Nearly every Country has one, or more than one. Policy makers must trust algorithms that help them to understand the economic consequences of climate policies. Moreover, a multiplicity of models is required to mitigate uncertainty about estimations and processes". These models are meant for use in advising on climate policies, they can be the basis of negotiations and agreements. "It is a research area where policies are necessarily built on estimations provided by algorithms. It is challenging, and rewarding".
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