Marc Fleurbaey

The definition and measurement of social welfare have been a vexed issue for the past century. This book makes a constructive, easily applicable proposal and suggests how to evaluate the economic situation of a society in a way that gives priority to the worse-off and that respects each individual's preferences over his or her own consumption, work, leisure and so on. This approach resonates with the current concern to go 'beyond the GDP' in the measurement of social progress. Compared to technical studies in welfare economics, this book emphasizes constructive results rather than paradoxes and impossibilities, and shows how one can start from basic principles of efficiency and fairness and end up with concrete evaluations of policies. Compared to more philosophical treatments of social justice, this book is more precise about the definition of social welfare and reaches conclusions about concrete policies and institutions only after a rigorous derivation from clearly stated principles.

This paper examines the exercise of individual or group rights within the game form approach. It focuses in particular on what it means for a strategy or action to be feasible and admissible. Admissibility is best discussed in relation to two basic distinctions among rights, passive and active rights on the one hand and negative and positive rights on the other. It is argued that while there are quite a few cases in which the outcomes of mutual rights exercising are to the fore, there are many situations where the uninhibited exercise of individual or group rights and not particular outcomes are what society is primarily interested in.

Integrated assessment models (IAMs) of climate and the economy provide estimates of the social cost of carbon and inform climate policy. With the Nested Inequalities Climate Economy model (NICE) (Dennig et al. PNAS 112:15,827–15,832, 2015), which is based on Nordhaus’s Regional Integrated Model of Climate and the Economy (RICE), but also includes inequalities within regions, we investigate the comparative importance of several factors—namely, time preference, inequality aversion, intraregional inequalities in the distribution of both damage and mitigation cost and the damage function. We do so by computing optimal carbon price trajectories that arise from the wide variety of combinations that are possible given the prevailing range of disagreement over each factor. This provides answers to a number of questions, including Thomas Schelling’s conjecture that properly accounting for inequalities could lead the inequality aversion parameter to have an effect opposite to what is suggested by the Ramsey equation.

Integrated assessment models of climate and the economy provide estimates of the social cost of carbon and inform climate policy. We create a variant of the Regional Integrated model of Climate and the Economy (RICE)—a regionally disaggregated version of the Dynamic Integrated model of Climate and the Economy (DICE)—in which we introduce a more fine-grained representation of economic inequalities within the model’s regions. This allows us to model the common observation that climate change impacts are not evenly distributed within regions and that poorer people are more vulnerable than the rest of the population. Our results suggest that this is important to the social cost of carbon—as significant, potentially, for the optimal carbon price as the debate between Stern and Nordhaus on discounting.

We consider a special set of risky prospects in which the outcomes are either life or death. There are various alternatives to the utilitarian objective of minimizing the expected loss of lives in such prospects. We start off with the two-person case with independent risks and construct taxonomies of ex ante and ex post evaluations for such prospects. We examine the relationship between the ex ante and the ex post in this restrictive framework: There are more possibilities to respect ex ante and ex post objectives simultaneously than in the general framework, i.e. without the restriction to binary utilities. We extend our results to n persons and to dependent risks. We study optimal strategies for allocating risk reductions given different objectives. We place our results against the backdrop of various pro-poorly off value functions for the evaluation of risky prospects.