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The previous three sections argued that happiness can be measured through self-reports, individuals’ happiness scores can be meaningfully compared, and that life satisfaction is a reasonable proxy for happiness. Three things follow from this.

First, the impact that different outcomes have on happiness can be determined (at least, in theory) by using self-reported subjective being scores; ‘subjective well-being’ (SWB), recall, is an umbrella term which includes both happiness and life satisfaction.

Second, we can compare what looks best on SWB scores to the current suggestions made by Singer and MacAskill about how to increase happiness. Singer and MacAskill seem to have used health metrics (Quality Adjust Life-Years (QALYs) and Disability Adjusted Life-Year (DALYs) and income as their measures of

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happiness.¹³² Let’s call this alternative method the ‘QALY+’ approach, which I will return to shortly.

Third, if well-being consists in happiness, then we can get close—although, for reasons I will raise later, not all the way—to MacAskill’s ambition to measure impact in terms of Well-being Adjusted Life Years (WALYs) instead of QALYs: we can use SWB scores.¹³³

However, there are still two practical objections one could raise to using SWB scores instead of the QALY+ method to assess what increases happiness: first, there is not yet enough evidence on SWB to guide our decision-making; second, moving to SWB measures would not make a practical difference and is, therefore, unnecessary.

The only way to fully address those concerns is to show that we can crunch some numbers and that, when we do, it makes a difference. I postpone such analysis until chapter 7, where I provide a cost-effectiveness analysis, using SWB scores, showing a charitable priority that is different from the ones currently recommended by effective altruists. Before we get to that, I want to discuss, in the next two chapters, various methodological issues that point us towards the choice of priorities that I evaluate in chapter 7. My limited objective here is to provide reasoning that goes some of the way to countering the latter two objections.

In this section, I make two points. First, I note an advantage of using SWB scores over the QALY+ method to determine what increases happiness. Second, I state some of the latest SWB research and argue that mental health stands out as a

132 See footnote 7.

133 See footnote 8

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potential priority, which is not evident if we rely on QALYs and income as outcome measures.

5.1 The problem of subjective weights

A general challenge, if one wants to assess cost-effectiveness, is to establish how much different outcomes contribute in terms of whatever common currency effectiveness is measured in. As WALYs aren’t available, MacAskill suggests measuring the benefit of different interventions in terms of QALYs. For the moment, let’s assume that the QALY is an accurate measure of happiness in the domain of health. QALYs are measured on a 0 to 1 scale with 0 equivalent to death and 1 to a year of full health. Different conditions are assigned different QALY weights: for instance, a year with AIDS without retroviral treatment is worth 0.5 QALYs—half as good as a year in full health.¹³⁴ If QALYs are accurate in terms of happiness, then having untreated AIDS would remove half of your net happiness for a year. QALYs would then be a good metric where we compared health outcomes.

The problem arises when we want to trade-off the impact that other outcomes, such as increased wealth, have on happiness. For definiteness, we could ask: how many years of doubled income are equivalent, in terms of happiness, to increasing someone’s health from a QALY-weighting of 0 to 1 for 1 year?

If we measure happiness, an objective answer to this question can be derived: we can determine the impact that health and poverty each have on happiness. Unless we measure happiness, we’re forced to make an educated guess about their relative

134 MacAskill (2015) at p. 47.

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impact. This is the problem of subjective weights: a factual question—how much do different outcomes increase happiness? —is being judged subjectively.

On what I’ve called the QALY+ method, we start with a health metric and then subjectively weight the relative importance of different outcomes relative to units of health metric. The obvious worry is that we’ll provide flawed subjective weights.

5.2 SWB studies—some important results

Information about how much different things impact happiness can either be found (ideally) from randomised-controlled trials, or from large population surveys where statistical methods can be used to estimate the associations between various factors.

Figure 4.7. is taken from Clark et al. It is the state-of-the-art and uses a national panel data set (i.e. the same people were surveyed each year), allowing individuals to be used as their own controls and the changes observed over time. ¹³⁵

135 Clark et al. (2018) at p. 220.

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Figure 4.7. Life satisfaction effect different life-events have on oneself and others¹³⁶

If we use the life satisfaction scores, the most surprising lesson, relative to what we might expect from our folk psychology of SWB, is the comparative unimportance of income and the importance of mental health. From the table, we can see that not only does being diagnosed with depression or anxiety have about 6 times the effect on life satisfaction as a doubling of income, the aggregate effect of doubled income is roughly nil when the impact on others is accounted for; the right-hand-column figure indicates the effect that doubling one person’s income has on others and suggests their loss is approximately the same size as the individual’s gain. This result isn’t particularly surprising: it’s consistent with a wider literature (some of it mentioned in section 3) on social comparisons and how the effect of income on SWB is a substantially relative. I won’t discuss the rest of the table as that is not necessary for our purposes. The above is developed world data, but it nevertheless indicates that mental health is a possible priority if we want to increase happiness.

Neither Singer nor MacAskill mentions mental health in their books on effective altruism.¹³⁷ Given the metrics they drew on, this result is not perhaps surprising.

Not only does the above suggest mental health has a surprisingly large impact relative to income, different evidence that I now set out indicates mental health is relatively more important on SWB measures than it is on QALYs. Hence, QALYs turn out not to be an accurate measure of happiness in the domain of health.

136 Ibid

137 At the present time. Singer informs me that StrongMinds will be mentioned in the second edition of his book The Life You Can Save Singer (2019) due out in late 2019 (and this is due, in some part, to my agitation on the subject).

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Clark et al. provide the following explanation of how QALY weights are determined:

In the QALY system, the impact of a given illness in reducing the quality of life is measured using the replies of patients to a questionnaire known as the EQ5D. Patients with each illness give a score of 1, 2, or 3 to each of five questions (on Mobility, Self-care, Usual Activities, Physical Pain, and Mental Pain). To get an overall aggregate score for each illness a weight has to be attached to each of the scores. For this purpose members of the public are shown 45 cards on each of which an illness is described in terms of the five EQ 5D dimensions. For each illness members of the public are then asked,

“Suppose you had this illness for ten years. How many years of healthy life would you consider as of equivalent value to you?” The replies to this question provide 45N valuations, where there are N respondents. The evaluations can then be regressed on the different EQ5D dimensions. These

“Time Trade-Off” valuations measure the proportional Quality of Life Lost (measured by equivalent changes in life expectancy) that results from each EQ5D dimension.¹³⁸

Dolan and Metcalfe compare how individuals value the five dimensions of health in time trade-offs to the effect those dimensions have on SWB among people experiencing those states of ill-health.¹³⁹ This is displayed in figure 4.8. As we can see, the relative weights are quite different. To highlight a particular discrepancy, Dolan and Metcalfe report that subjects agreed hypothetically to give up as many years of their remaining life, about 15%, to be cured of ‘some difficulty walking’, as they would to be cured of ‘moderate anxiety or depression’. However, from SWB

138 Clark et al. (2018) at p. 85.

139 Dolan and Metcalfe (2012)

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measures, it is shown that ‘moderate anxiety or depression’ is associated with 10 times a greater loss to life satisfaction, and 18 times a greater loss to daily affect than

‘some difficulty walking’ is. On a moment’s reflection, it is obvious anxiety and depression must be much worse for happiness than some difficulty walking, but this is not what we see in the QALY weights.

What explains this? The QALY method, as described above, is different from the SWB approach in two ways. First, the latter asks subject about their SWB, whereas the former, with the question “How many years of healthy life would you consider as of equivalent value to you?” leaves it open to respondents to answer in terms of whatever they value—what they value might not consist solely in (a component of) SWB.¹⁴⁰ Individuals presumably value SWB to some extent, but not all will only value that. The extent to which individuals do value goods besides SWB is an as-yet unresolved empirical matter and hence it is unclear how much of the disparity in results this difference in methodology accounts for.¹⁴¹

140 Arguably, the question leaves it open to answer not solely about prudential value (i.e. my own well-being) – I might say I want to live longer so I could do more good.

141 Adler, Dolan and Kavetsos (2017) investigate hypothetical trade-offs between levels of SWB and levels of income, physical health, family, career success, and education. They found individuals prefer SWB to all the other attributes except health. This analysis doesn’t tell us how much weight individuals put on others goods vs SWB, or which of those goods are intrinsically valuable, only that they are, in practice, sometimes prepared to trade them off.

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Figure 4.8. How life satisfaction and daily affect (0-1) are affected by the EQ5D, compared with weights used in QALYs.¹⁴²

The second difference is that QALY weights are determined by asking people to judge how bad various health states would be, rather than by asking people who are experiencing those health states about their SWB and then inferring (via regressions) how bad they, in fact, are.¹⁴³ Psychological research into affective forecasting—how individuals expect to feel about future events—finds that individuals display an impact bias, overestimating the intensity and duration of future emotional states.¹⁴⁴ There are several reasons for this bias, such as focusing illusions, paying too much attention to easily imaginable details, and immune

142 Data from Dolan and Metcalfe (2012). Table produced by Derek Foster.

143 This is the approach taken in Clark et al. (2018) at the wider SWB-literature in economics.

144 Wilson and Gilbert (2005)

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neglect, not accounting for the fact they will adapt to some conditions but not others.¹⁴⁵

What seems to have happened is that, when you ask people to compare ‘some difficult walking’ to ‘moderate anxiety or depression’ they overweight the SWB impact of the former because it is easier to visualise—walking with a cane vs. feeling sad on the inside—and they haven’t considered that they will adapt to the former but not the latter. The general problem with time trade-offs, however they are done, is that there is a difference between how important something seems when you are instructed to think about it compared to how it normally affects your experience.¹⁴⁶ As Daniel Kahneman pithily puts it, ‘Nothing in life is as important as you think it is when you are thinking about it’.¹⁴⁷ This is why, if we want to know the SWB-impact something has, it is essential to ask people about their SWB in general, and then infer what impact their circumstances have on their SWB, rather than asking them what impact they think X or Y would have on their SWB.

Hence, if one used QALYs as a proxy for happiness, a key implication is that this would lead you to underweight the unhappiness caused by mental illness. I am not aware of equivalent research comparing SWB to DALY weights, but as DALY weights are also constructed by asking individuals to judge the badness of health states, the same concerns about affecting forecasting will presumably apply.¹⁴⁸

145 Kahneman et al. (2006), Gilbert et al. (1998)

146 Hence, while QALYs are generally derived from members of the public making hypothetical judgments, they would not ‘fixed’ by getting those in poor health engage in time trade-off about their specific conditions; the concerns about affective forecasting remain.

147 Kahneman (2011) at p. 400-1.

148 Gold, Stevenson and Fryback (2002)

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The preceding analysis should go some way to addressing two objections to using happiness data to guide (moral philosophers’) happiness-related recommendations—that there isn’t enough evidence to draw on and that, if we did, it wouldn’t change our priorities. What it shows is there is some data on SWB and it shows us at least one new priority compared to the QALY+ approach, namely the potential importance of mental health.

Assuming we want to make people happier, given we now have a new methodology—

SWB scores—to assess this and, with it, new evidence, this should prompt us to revaluate our priorities and see if we can find more effective ways to increase happiness. This, in turn, leads us to ask what method we should use, in general, for determining what our priorities are. Effective altruists have suggested such a method, a three-factor ‘cause prioritisation’ framework. In the next two chapters, we assess whether this framework is fit for purpose and, having suitably modified it, we take another look at what the happiness-increasing priorities are.

6. Conclusion

This chapter started with the realisation that while social scientists have been busy trying to measure happiness through self-reports, moral philosophers have not paid much attention to the social scientists’ endeavours. I considered four possible objections to relying on self-reports to measure happiness. I argued the first objection can be met and made some progress towards address the remaining three.

I am unable to say any more on the second objection in this thesis, but I aim to provide a compelling response to the third and fourth objections in chapter 7.

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