Estimates of the elasticity of the marginal utility of income are necessary for determining distributional weights to correct for diminishing marginal utility of income, which is particularly important in light of increasing concern about accounting for distributional impacts in regulatory review. The elasticity is also necessary for computing the social discount rate using the Ramsey formula. Despite many attempts to estimate the elasticity of the marginal utility of income, considerable uncertainty exists about the magnitude of this key parameter. In this paper, we use meta-analysis of estimates of the elasticity from the US and UK to shed light on the appropriate elasticity values to use for both distributional weighting and discounting. Relying on our findings, we tentatively conclude that it is reasonable to base the social discount rate and distributional weights on an elasticity of 1.6, with lower- and upper-bound sensitivity testing at 1.2 and 2.0. This estimate results in distributional weights which appear plausible, and which we believe can contribute to a consensus on how to conduct distributional weighting. Moreover, the resulting social discount rate is within the range typically recommended when the Ramsey formula is used.

There are increasing calls for concrete suggestions on how to account for distributional impacts in policy analysis. Within the context of benefit-cost analysis, per se, one possibility is to apply “distributional weights,” to inflate costs and benefits experienced by poor or disadvantaged groups. We distinguish between “utility-weights,” intended to correct for the bias in willingness to pay caused by diminishing marginal utility of income, and “equity-weights,” intended to account for the possibility that decision makers might have disproportional concern about the welfare of the poor or other disadvantaged groups. We argue that utility-weights are appropriate and necessary to maintain the legitimacy of BCA as a measure of aggregate welfare, but that equity-weights are inappropriate because they involve moral judgments that should remain in the domain of democratically accountable decision makers, and because they conflate information about both the welfare and equity impacts of policies, making it impossible for decision-makers to apply their own moral values to the assessment of tradeoffs between welfare and equity. We offer concrete suggestions regarding the application of utility-weights and the calculation of a set of metrics to provide intuitively comprehensible and useful information about, and allow decision makers to quantitatively assess the tradeoffs between, welfare and equity caused by specific policies.

Health economic evaluations are comparative analyses of alternative courses of action in terms of their costs and consequences. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement, published in 2013, was created to ensure health economic evaluations are identifiable, interpretable, and useful for decision making. It was intended as guidance to help authors report accurately which health interventions were being compared and in what context, how the evaluation was undertaken, what the findings were, and other details that may aid readers and reviewers in interpretation and use of the study. The new CHEERS 2022 statement replaces previous CHEERS reporting guidance. It reflects the need for guidance that can be more easily applied to all types of health economic evaluation, new methods and developments in the field, as well as the increased role of stakeholder involvement including patients and the public. It is also broadly applicable to any form of intervention intended to improve the health of individuals or the population, whether simple or complex, and without regard to context (such as health care, public health, education, social care, etc.). This summary article presents the new CHEERS 2022 28-item checklist and recommendations for each item. The CHEERS 2022 statement is primarily intended for researchers reporting economic evaluations for peer-reviewed journals, as well as the peer reviewers and editors assessing them for publication. However, we anticipate familiarity with reporting requirements will be useful for analysts when planning studies. It may also be useful for health technology assessment bodies seeking guidance on reporting, as there is an increasing emphasis on transparency in decision making.

We describe punctual categoricity in several natural classes, including binary relational structures and mono-unary functional structures. We prove that every punctually categorical structure in a finite unary language is ${\text {PA}}(0')$-categorical, and we show that this upper bound is tight. We also construct an example of a punctually categorical structure whose degree of categoricity is $0''$. We also prove that, with a bit of work, the latter result can be pushed beyond $\Delta ^1_1$, thus showing that punctually categorical structures can possess arbitrarily complex automorphism orbits.

As a consequence, it follows that binary relational structures and unary structures are not universal with respect to primitive recursive interpretations; equivalently, in these classes every rich enough interpretation technique must necessarily involve unbounded existential quantification or infinite disjunction. In contrast, it is well-known that both classes are universal for Turing computability.

The role of the law librarian or legal information professional is thought by some to have been diminished significantly by technological advances which provide instant access to an enormous range of materials direct to individual users at their desks. The reality is that the wide range of instantly accessible materials makes the experience and knowledge of the information professional more important, not less; and imminently expected advances in machine learning and artificial intelligence are likely to confirm the vital importance of the legal information professional at the centre of legal services.

This article contributes to the general program of extending techniques and ideas of effective algebra to computable metric space theory. It is well-known that relative computable categoricity (to be defined) of a computable algebraic structure is equivalent to having a c.e. Scott family with finitely many parameters (e.g., [1]). The first main result of the article extends this characterisation to computable Polish metric spaces. The second main result illustrates that just a slight change of the definitions will give us a new notion of categoricity unseen in the countable case (to be stated formally). The second result also shows that the characterisation of computably categorical closed subspaces of ${\Cal R}^n $ contained in [17] cannot be improved. The third main result extends the characterisation to not necessarily separable structures of cardinality κ using κ-computability.

We study the computable structure theory of linear orders of size $\aleph _1 $ within the framework of admissible computability theory. In particular, we characterize which of these linear orders are computably categorical.

We study the computable structure theory of linear orders of size $\aleph _1 $ within the framework of admissible computability theory. In particular, we study degree spectra and the successor relation.