The Biden administration has made equity a priority when issuing regulations, encouraging agencies to ensure that their regulations appropriately benefit and do not inappropriately burden disadvantaged groups. But scholarly examinations of agencies’ practices to date on understanding the distributional consequences of their regulations and on promoting equity have revealed significant gaps. In particular, agencies pay very little attention to the incidence of the costs of their regulations. The U.S. Environmental Protection Agency, for example, rarely considers the incidence of regulatory costs among disadvantaged groups, despite being an agency that conducts relatively complete benefit–cost analyses and explicitly analyzes environmental justice implications of its regulations. But this cost-blindness is a mistake; it presents a missed opportunity to use the current equity-focused momentum to make real improvements for disadvantaged groups that could have long-lasting effects. This essay calls for agencies to give more attention to the incidence of regulatory costs in order to identify needs and opportunities for grants and investments to disadvantaged groups. This approach could provide much-needed direction for a program like the Biden administration’s Justice40 initiative.

We explore the structural properties of the inner model L(Vδ+1) under the assumption that δ is a singular limit of Berkeley cardinals each of which is itself limit of extendible cardinals, lifting some of the main results of the theory of the axiom I0 to the level of Berkeley cardinals, the strongest known large cardinal axioms. Berkeley cardinals have been recently introduced in [1] and contradict the Axiom of Choice.1 In fact, our background theory will be ZF.

The current fiscal climate is focusing attention on the need for more efficient government. However, we have remarkably little rigorous information on which are the most cost-effective strategies for achieving common goals like delivering high quality education in deprived neighbourhoods or reducing carbon emissions. This paper argues that randomised impact evaluations can provide an effective way to generate the information needed to make government more effective. Advances in the theory and practice of running randomised evaluations mean that a wider range of questions can be answered than ever before. Elsewhere in the world, fundamental questions are being answered about how humans behave, which in turn are being used to design new policies which themselves are rigorously tested. By learning from these results, and by conducting more randomised evaluations on issues important to UK policy (both at home and abroad) it will be possible to design more effective policies and do more with less.