The Capability Approach (CA) as developed by Amartya Sen and Martha Nussbaum, has in part been a response to the problem of adaptive preferences. Their argument says that people might adapt to certain unfavorable circumstances and any self-evaluation in terms of satisfaction or happiness will in this case necessarily be distorted. To evaluate people's well-being in terms of functionings and capabilities guarantees a more objective picture of people's life. Next to this strong criticism on subjective measurements of well-being, we observe an increasing interest in Subjective Well-Being (SWB) or Happiness studies that are included in the broader field of Hedonic Psychology. In this paper, we thus revise the original critique of adaptive preferences and compare it with a more detailed analysis of adaptation as it is presented in hedonic psychology. It becomes clear that adaptation can be a positive as well as a negative phenomenon and that the adaptive preference critique had a particular narrow view on adaptation. However, this does not mean SWB-research is not any longer susceptible to this critique. An alternative way to assess people's subjective well-being, but which could be considered to be more in line with the CA, is proposed by Daniel Kahneman's Objective Happiness. These are all relatively new considerations, especially in economics. Therefore much more research needs to be done on the positive and negative aspects of adaptation to understand its consequences on well-being - especially when evaluated within the capability-space.functionings, capabilities, adaptation, subjective well-being, objective happiness,

Empathy is a longstanding issue in economics, especially for welfare economics, but one which has faded from the scene in recent years. However, with the rise of neuroeconomics, there is now a renewed interest in this subject. Some economists have even gone so far as to suggest that neuroscientific experiments reveal heterogeneous empathy levels across individuals. If this were the case, this would be in line with economists' usual assumption of stable and given preferences and would greatly facilitate the study of prosocial behaviour with which empathy is often associated. After reviewing some neuroscientific psychological and neuroeconomic evidence on empathy, we will, however, criticize the notion of a given empathy distribution in the population by referring to recent experiments on a public goods game that suggest that, on the contrary, the degree of empathy that individuals exhibit is very much dependent on context and social interaction.

An acceleration index is proposed as a novel indicator to track the dynamics of the COVID-19 in real-time. Using French data on cases and tests for the period following the first lock-down - from May 13, 2020, onwards - our acceleration index shows that the ongoing pandemic resurgence can be dated to begin around July 7. It uncovers that the pandemic acceleration has been stronger than national average for the [59-68] and [69-78] age groups since early September, the latter being associated with the strongest acceleration index, as of October 25. In contrast, acceleration among the [19-28] age group is the lowest and is about half that of the [69-78], as of October 25. In addition, we propose an algorithm to allocate tests among French departments, based on both the acceleration index and the feedback effect of testing. Our acceleration-based allocation differs from the actual distribution over French territories, which is population-based. We argue that both our acceleration index and our allocation algorithm are useful tools to guide public health policies as France enters a second lock-down period with indeterminate duration.

An acceleration index is proposed as a novel indicator to track the dynamics of COVID-19 in real-time. Using data on cases and tests in France for the period between the first and second lock-downs—May 13 to October 25, 2020—our acceleration index shows that the pandemic resurgence can be dated to begin around July 7. It uncovers that the pandemic acceleration was stronger than national average for the [59–68] and especially the 69 and older age groups since early September, the latter being associated with the strongest acceleration index, as of October 25. In contrast, acceleration among the [19–28] age group was the lowest and is about half that of the [69–78]. In addition, we propose an algorithm to allocate tests among French “départements” (roughly counties), based on both the acceleration index and the feedback effect of testing. Our acceleration-based allocation differs from the actual distribution over French territories, which is population-based. We argue that both our acceleration index and our allocation algorithm are useful tools to guide public health policies as France might possibly enter a third lock-down period with indeterminate duration.

This note provides an early assessment of the reinforced measures to curb the COVID-19 pandemic in France, which include a curfew of selected areas and culminate in a second COVID-19-related lock-down that started on October 30, 2020 and is still ongoing. We analyse the change in virus propagation across age groups and across départements using an acceleration index introduced in Baunez et al. (2020). We find that while the pandemic is still in the acceleration regime, acceleration decreased notably with curfew measures and this more rapidly so for the more vulnerable population group, that is, for people older than 60. Acceleration continued to decline under lock-down, but more so for the active population under 60 than for those above 60. For the youngest population aged 0 to 19, curfew measures did not reduce acceleration but lock-down does. This suggests that if health policies aim at protecting the elderly population generally more at risk to suffer severe consequences from COVID-19, curfew measures may be effective enough. However, looking at the departmental map of France, we find that curfews have not necessarily been imposed in départements where acceleration was the largest.JEL Classification NumbersI18; H12

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The radical uncertainty around the current COVID19 pandemics requires that governments around the world should be able to track in real time not only how the virus spreads but, most importantly, what policies are effective in keeping the spread of the disease under check. To improve the quality of health decision-making, we argue that it is necessary to monitor and compare acceleration/deceleration of confirmed cases over health policy responses, across countries. To do so, we provide a simple mathematical tool to estimate the convexity/concavity of trends in epidemiological surveillance data. Had it been applied at the onset of the crisis, it would have offered more opportunities to measure the impact of the policies undertaken in different Asian countries, and to allow European and North-American governments to draw quicker lessons from these Asian experiences when making policy decisions. Our tool can be especially useful as the epidemic is currently extending to lower-income African and South American countries, some of which have weaker health systems.

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