Vetting Implicit Normativity in Climate Economics

Descripción del proyecto

Mejorar la objetividad y fiabilidad de los modelos de evaluación integrada del cambio climático

Los modelos de evaluación integrada (MEI) ayudan a responder a importantes preguntas sobre el cambio climático, mediante el estudio de cómo interactúan el desarrollo humano y las decisiones sociales con el mundo natural y cuáles son sus efectos. Su objetivo es proporcionar información pertinente para las políticas sobre el cambio ambiental del planeta y los problemas de desarrollo sostenible. A menudo, requieren hacer suposiciones normativas o sobre los valores que los individuos y las comunidades deben perseguir. Estas suposiciones son inherentemente subjetivas e inciertas. El equipo del proyecto VINCE, que cuenta con el apoyo de las Acciones Marie Skłodowska-Curie, creará un nuevo método de investigación sobre los MEI que permita formular una hoja de ruta para identificar los mejores planteamientos de las suposiciones normativas. Todo ello con el objetivo de mejorar el diseño, la evaluación y el uso de los MEI a fin de mejorar la fiabilidad y la objetividad de estos modelos.

Objetivo

The project addresses the inherent presence of value judgments in current integrated assessment models (IAMs) of climate change impacts. Though widely used to inform public policy, many aspects of IAM design and use require making assumptions of an implicitly normative nature: assumptions that are ultimately about the values that individuals and communities ought to pursue. This raises a host of philosophical and methodological questions for which an interdisciplinary approach is needed: which actors and in which contexts – scientists at the model design stage, policy makers at the decision stage, etc.– should be in charge of making the normative choices that IAMs require? What practices and protocols are best suited to facilitate the recognition of normative assumptions in IAMs, the oversight by experts and stakeholders, and (if possible) the resolution of the uncertainty that surrounds them? To answer these questions, the project will first propose a taxonomy of implicitly normative assumptions in IAMs. Then, for each type identified, it will aim to determine which of several approaches is best suited to deal with that type of normativity. The resulting account will be a new model of IAM research that indicates how one ought to proceed in concrete contexts of IAM design, assessment and use. To achieve these objectives, Dr. Nappo will receive crucial training at Politecnico di Milano. Under the co-supervision of a philosopher of science and of a climate economist, he will integrate his demonstrated competences in the epistemology of scientific modelling and climate change ethics with new skills, which include first-hand experience with IAM modelling practices and grasp of their mathematical underpinnings. This training will allow Dr. Nappo to not only advance the literature on IAM normativity significantly beyond its current limits, but to also contribute to making IAM research more reliable and objective through an effective dissemination and exploitation plan.