A narrowly person-affecting (NPA) axiology is an account of the moral ranking of outcomes such that the comparison of any two outcomes depends on the magnitude and weight of individuals’ well-being gains and losses between the two. This article systematically explores NPA axiology. It argues that NPA axiology yields an outcome ranking that satisfies three fundamental axioms: Pareto, Anonymity and, plausibly, Pigou-Dalton. The axiology is neutral to non-well-being considerations (desert); and (assuming well-being measurability) leads to the Repugnant Conclusion (RC). In short, NPA axiology provides a grounding for Paretian, equity-regarding welfarism, albeit one that includes the RC.

Scholars have long debated the appropriate balance between efficiency and redistribution. But recently, a wave of critics has argued not only that efficiency is less important, but that efficiency analysis itself is fundamentally flawed. Some say that efficiency is incoherent because there is no neutral baseline from which to judge inefficiency. Others say that efficiency is biased toward those best able to pay (generally, the rich). This essay contends that efficiency is not meaningfully incoherent or biased. The most widely discussed forms of efficiency do not require any particular baseline, and even those that do require a baseline can still serve as useful approximations of more theoretically sound but computationally demanding measures. Moreover, arguments of bias do not account for the source of funds in public projects, produce unintuitive results, and draw an arbitrary cutoff between bias and non-bias that elides important distributional details. Ultimately, the tradeoff between efficiency and redistribution remains the most useful frame for policy debate.

We highlight a new paradox for the social evaluation of risk that bears on the evaluation of individual well-being rather than social welfare, but has serious implications for social evaluation. The paradox consists in a tension between rationality, respect for individual preferences, and a principle of informational parsimony that excludes individual risk attitudes from the assessment of riskless situations. No evaluation criterion can satisfy these three principles. This impossibility result has implications for the evaluation of social welfare under risk, especially when the preferences of some individuals are not known. It generalizes existing impossibility results, while relying on very weak principles of social rationality and respect for individual preferences. We explore the possibilities opened by weakening each of our three principles and discuss the advantages and drawbacks of these different routes.

This paper provides a Consent Justification for benefit–cost analysis (BCA). The Consent Justification is based on a tendency toward actual compensation. A substantial justification for using BCA as a tool is the actual Pareto test, called the Consent Justification, in combination with the net present value criterion for individual projects. The traditional justification, the potential compensation test (PCT), is unsatisfactory on several grounds. In addition, the PCT occupies the uneasy position of being the source of extended criticisms in the economic literature and especially in the legal and philosophy literature. The argument for the Consent Justification lies not only in the deficiencies of the PCT, but also, especially, in a showing through simulation that all tend to gain across a portfolio of projects which is not large but rather robust with respect to errors and assumptions.

Power law distributions have a certain appeal to researchers, not least because they often insinuate a general empirical law. Hence, searching for them in data generated by social and political processes has become popular. In the political science literature, however, power law behavior has rarely been assessed rigorously. Relying mainly on qualitative appraisals of log–log plots, merely a necessary, but no sufficient, condition of power law behavior is tested. This letter therefore seconds the note of caution expressed recently. Moreover, it showcases the use of a principled statistical framework to test power law behavior in a quantitative manner. Applying this method to a seminal case in political science, the results of the analysis invite an empirical as well as theoretical refinement of the claim that changes in public budgets follow a power law. In a more general sense, the letter wishes to contribute to a more thorough practice of stochastic process methods in political science.

My fellow contractarians and I are of a mind that it would be irrational to comply with a distribution of the cooperative dividend that worsens one’s condition. But worse than what? According to David Gauthier et al., it’s non-interaction, i.e., what would be the case were the negotiators never to have met. I argue that it’s what would be the case in the absence of their coming to an agreement. As it turns out, this distinction can be, and often is, a matter of life and death.

A new approach to goodness-of-fit for Pareto distributions is introduced. Based on Euclidean distances between sample elements, the family of statistics and tests is indexed by an exponent in (0,2) on Euclidean distance. The corresponding tests are statistically consistent and have excellent performance when applied to heavy-tailed distributions. The exponent can be tailored to the particular Pareto distribution. The goodness-of-fit statistic measures all types of differences between distributions, hence it is also applicable as a minimum distance estimator. Implementation of the test statistics is developed and applied to estimation of the tail index in three well known examples of claims data, and compared with the classical EDF statistics.

The copula of a multivariate distribution is the distribution transformed so that one-dimensional marginal distributions are uniform. We review a different transformation of a multivariate distribution which yields standard Pareto for the marginal distributions, and we call the resulting distribution the Pareto copula. Use of the Pareto copula has a certain claim to naturalness when considering asymptotic limit distributions for sums, maxima, and empirical processes. We discuss implications for aggregation of risk and offer some examples.

The classical evaluation of pure premiums for excess of loss reinsurance with reinstatements requires the knowldege of the claim size distribution of the insurance risk. In the situation of incomplete information, where only a few characteristics of the aggregate claims to an excess of loss layer can be estimated, the method of stop-loss ordered bounds yields a simple analytical distribution-free approximation to pure premiums of excess of loss reinsurance with reinstatements. It is shown that the obtained approximation is enough accurate for practical purposes and improves the analytical approximations obtained using either a gamma, translated gamma, translated inverse Gaussian or a mixture of the last two distributions.