Lives v livelihoods, part 1: how can we measure the value of a life?

Policies that suppress or control the COVID-19 pandemic prevent illness and save lives, but exact an economic toll. How should we balance lives and livelihoods to determine which policy is best? In the first of two posts, Matthew Adler (Duke University/LSE), Richard Bradley (LSE), Maddalena Ferranna (Princeton), Marc Fleurbaey (Princeton and Paris School of Economics), James Hammitt (Harvard) and Alex Voorhoeve (LSE) compare the benefit-cost and social welfare approaches to doing so

Assessing the Wellbeing Impacts of the COVID-19 Pandemic and Three Policy Types: Suppression, Control, and Uncontrolled Spread

The COVID-19 crisis has forced a difficult trade-off between limiting the health impacts of the virus and maintaining economic activity. Welfare economics offers tools to conceptualize this trade-off so that policy-makers and the public can see clearly what is at stake. We review four such tools: the Value of Statistical Life (VSL); the Value of Statistical Life Years (VSLYs); Quality-Adjusted Life-Years (QALYs); and social welfare analysis, and argue that the latter are superior. We also discuss how to choose policies that differentially affect people’s wellbeing. We argue in favor of evaluating policies using a Social Welfare Function (SWF), which evaluates the possible distributions of wellbeing across individuals that may result from a policy. Such a function, we argue, should regard increases in the wellbeing of the less well-off as especially valuable. We then use a model to illustrate how such a framework can help evaluate two broad policy types in response to the pandemic: eradication of the virus, and more lenient control of the spread. Our model reveals how such evaluations depend on many empirical facts but also on key value judgments about the relative importance of health and on the extent of special concern for the worse off. The purpose of this brief is not to make precise recommendations, as conditions vary widely across countries and over time, but to provide a methodology

How to Balance Lives and Livelihoods in a Pandemic.

Control measures, such as “lockdowns”, have been widely used to suppress the COVID-19 pandemic. Under some conditions, they prevent illness and save lives. But they also exact an economic toll. How should we balance the impact of such policies on individual lives and livelihoods (and other dimensions of concern) to determine which is best? A widely used method of policy evaluation, benefit–cost analysis (BCA), answers these questions by converting all the effects of a policy into monetary equivalents and then summing them up. A different method, social welfare analysis, proceeds by determining the effects of a policy on individual wellbeing and then applying an aggregation formula to them to evaluate the overall effects of a policy. In this chapter, we survey these methods and argue that social welfare analysis has important advantages. One crucial advantage is that it enables ethical considerations relating to the impact of policies on individual wellbeing and its distribution to be incorporated into policy assessments in a transparent way. We illustrate this with a simple numerical model for evaluating pandemic policies that vary in terms of the stringency of the controls that they impose on individual behaviour, showing how the evaluation depends on the ethical significance accorded to their impact on the wellbeing of different age and income groups

Consumer\u27s Guide to Regulatory Impact Analysis: Ten Tips for Being an Informed Policymaker

Regulatory impact analyses (RIAs) weigh the benefits of regulations against the burdens they impose and are invaluable tools for informing decision makers.We offer 10 tips for nonspecialist policymakers and interested stakeholders who will be reading RIAs as consumers. Core problem: Determine whether the RIA identifies the core problem (compelling public need) the regulation is intended to address. Alternatives: Look for an objective, policy-neutral evaluation of the relative merits of reasonable alternatives. Baseline: Check whether the RIA presents a reasonable “counterfactual” against which benefits and costs are measured. Increments: Evaluate whether totals and averages obscure relevant distinctions and trade-offs. Uncertainty: Recognize that all estimates involve uncertainty, and ask what effect key assumptions, data, and models have on those estimates. Transparency: Look for transparency and objectivity of analytical inputs. Benefits: Examine how projected benefits relate to stated objectives. Costs: Understand what costs are included. Distribution: Consider how benefits and costs are distributed. Symmetrical treatment: Ensure that benefits and costs are presented symmetrically

Consumer\u27s Guide to Regulatory Impact Analysis: Ten Tips for Being an Informed Policymaker

Regulatory impact analyses (RIAs) weigh the benefits of regulations against the burdens they impose and are invaluable tools for informing decision makers.We offer 10 tips for nonspecialist policymakers and interested stakeholders who will be reading RIAs as consumers. Core problem: Determine whether the RIA identifies the core problem (compelling public need) the regulation is intended to address. Alternatives: Look for an objective, policy-neutral evaluation of the relative merits of reasonable alternatives. Baseline: Check whether the RIA presents a reasonable “counterfactual” against which benefits and costs are measured. Increments: Evaluate whether totals and averages obscure relevant distinctions and trade-offs. Uncertainty: Recognize that all estimates involve uncertainty, and ask what effect key assumptions, data, and models have on those estimates. Transparency: Look for transparency and objectivity of analytical inputs. Benefits: Examine how projected benefits relate to stated objectives. Costs: Understand what costs are included. Distribution: Consider how benefits and costs are distributed. Symmetrical treatment: Ensure that benefits and costs are presented symmetrically

Ancillary human health benefits of improved air quality resulting from climate change mitigation

<p>Abstract</p> <p>Background</p> <p>Greenhouse gas (GHG) mitigation policies can provide ancillary benefits in terms of short-term improvements in air quality and associated health benefits. Several studies have analyzed the ancillary impacts of GHG policies for a variety of locations, pollutants, and policies. In this paper we review the existing evidence on ancillary health benefits relating to air pollution from various GHG strategies and provide a framework for such analysis.</p> <p>Methods</p> <p>We evaluate techniques used in different stages of such research for estimation of: (1) changes in air pollutant concentrations; (2) avoided adverse health endpoints; and (3) economic valuation of health consequences. The limitations and merits of various methods are examined. Finally, we conclude with recommendations for ancillary benefits analysis and related research gaps in the relevant disciplines.</p> <p>Results</p> <p>We found that to date most assessments have focused their analysis more heavily on one aspect of the framework (e.g., economic analysis). While a wide range of methods was applied to various policies and regions, results from multiple studies provide strong evidence that the short-term public health and economic benefits of ancillary benefits related to GHG mitigation strategies are substantial. Further, results of these analyses are likely to be underestimates because there are a number of important unquantified health and economic endpoints.</p> <p>Conclusion</p> <p>Remaining challenges include integrating the understanding of the relative toxicity of particulate matter by components or sources, developing better estimates of public health and environmental impacts on selected sub-populations, and devising new methods for evaluating heretofore unquantified and non-monetized benefits.</p