Happiness by Design Read online

  My main point here, though, is that if we ranked activities by their pleasure and then by their purpose, we would get different rankings. That is, we would make different inferences about what makes people happy. Only by looking at pleasure and purpose together can we really see just how happy we are made by what we do.

  Let us concentrate on working and watching TV for the moment. About 20 percent of the sample did both on the day they were surveyed. So we can look at the relative pleasure and purpose they got from each of these activities. This then allows us to say something speculative about the pleasure machines and purpose engines in the sample. We begin by subtracting each person’s purpose rating from their pleasure rating for each activity. If the number is positive, then they get more pleasure than purpose from the activity, if the number is negative they get more purpose than pleasure, and zero would mean an equal amount of each.

  The results are summarized in the graph below. We would generally expect most people to get more purpose from work and more pleasure from TV. These are the people represented by the dots in the top left quadrant of the graph and these are colloquially labeled “balanced folk.” About 60 percent of the sample are located here. Those who get more pleasure than purpose for both work and TV are in the top right quadrant of the graph and so they are labeled “pleasure machines.” They make up about 10 percent of the sample. Those who get more purpose than pleasure for both activities are in the bottom left quadrant and so they are labeled “purpose engines.” They make up about 30 percent of the sample. Nobody got more pleasure than purpose from working and more purpose than pleasure from watching TV. So it would seem from this analysis that most people in our study get some kind of balance of pleasure and purpose from the two activities that many of us spend quite a lot of time engaged in.

  One general consideration that shows up clearly in this study is the effect of spending time with people you like. In these and other data, being with people is good for feeling good, even at work.4 Being with others is particularly pleasurable during the most pleasurable activities, eating and watching TV. Being with others is especially purposeful when commuting and doing housework.

  In terms of background characteristics, men experience greater pleasure over the day but women experience greater happiness overall when purpose is added. Those who care for sick or elderly family members compared to those who do not, those who earn €60,000 to €80,000 compared to all other income groups, and those who are married as opposed to single are all less happy from a pleasure standpoint but they experience greater happiness overall when purpose is added to pleasure.

  American episodes

  The American Time Use Survey (ATUS) is another, larger attempt to measure the happiness associated with different activities. This study has been running for over a decade and allows analysts to estimate the amount of time that people spend engaged in work but also in activities outside of the labor market—that is, unpaid activities like housework, volunteering, and child care—that do not show up in traditional estimates of national productivity but that really should.

  In 2010, the thirteen thousand people in the ATUS were asked about the pleasure and purpose they felt during specific activities from the day before. The average age of those interviewed was forty-seven, with the youngest being fifteen and the oldest eighty-five. Sixty percent of the participants were female. All those interviewed were asked to keep a diary of what they did over the course of a randomly chosen day and then an interviewer called them the next day to ask some questions about the activities in their diary.

  One of the questions was: “From 0 to 6, where a 0 means you were not happy at all and a 6 means you were very happy, how happy did you feel during this time?” Another was: “From 0 to 6, how meaningful did you consider to be what you were doing? A 0 means it was not meaningful at all to you and a 6 means it was very meaningful to you.” The first question is of course representative of my “pleasure” category of feelings and the second concerns “purpose.” With this distinction in mind, Laura Kudrna and I have been analyzing the ATUS.

  Each day, the overall sample spent an average of about eight and a half hours sleeping, three hours working (again, only about 60 percent worked on that day), two and a half hours watching television, one hour doing housework, one hour eating, an hour with kids, a half hour commuting, ten minutes volunteering, and ten minutes doing homework. The remaining six hours or so were made up of using the computer, reading, sports and recreation, practicing religion, shopping, caring for pets, talking on the phone, socializing, and other miscellaneous activities.

  The amount of time spent on various activities differs across groups. Men spend about an hour longer working than women, and they also spend about an hour more watching TV; and women spend about an hour longer doing housework than men. These gender differences are consistent with the typical household divisions of labor found in time use surveys.5 Married people work for about forty-five minutes more than those who are single, widowed, or divorced; and people who are not married spend about a half hour more sleeping. There are also differences in time use by age. The average amount of time people spend working is roughly the same, at around four hours a day during working age, then dropping to around an hour in the sixties and seventies. The amount of time devoted to housework increases with age, but it is difficult to say whether this is an effect that reflects generational differences in housework or age-related changes in the time it takes to do chores.6 TV watching also increases with age, from around two hours a day for those in their twenties to nearly four hours a day for those in their fifties and sixties.

  Then we looked at the average pleasure and purpose ratings for each of the main activities described above. Each activity obviously has its own combination of pleasure and purpose. The graph below summarizes the average pleasure and purpose ratings in the ATUS data, where you’ll see that the results are pretty similar to those for the German DRM data. So watching TV, eating, and commuting again have relatively more pleasure than purpose, and time with kids, volunteering, working, and doing homework are more purposeful than pleasurable. Doing housework is about equal in pleasure and purpose whereas in the German DRM data it was more purposeful than pleasurable. Again, if we ranked activities by their pleasure and then by their purpose, we would make different inferences about what makes people happy, and so we need to consider both.

  We also find in these data that people generally experience more pleasure and purpose from their activities when they do them with others. The ATUS results show that interacting with someone else is worth about an additional 0.4 points on the pleasure scale and about 0.6 points on the purpose scale. The table below shows how much more we enjoy most activities when we do them with other people. There are a few fascinating exceptions, however; where we appear to be made unhappier when we do an activity with someone else. Commuting seems to be less pleasurable when done with someone else—perhaps being in control of the radio and not having a backseat driver increases the joy of the ride. Homework is much less purposeful when engaged in with someone else, which makes sense if solitude allows people to get more done. We have to be alert to the “chicken and egg” problem as we look through this table, though; that is, people may choose to be alone when they are in a particular mood.

  Activity

  Difference when interacting with someone else

  Pleasure

  Purpose

  Volunteering

  0.67

  1.49

  Eating

  0.06

  0.00

  Doing housework

  0.02

  0.53

 
Working

  -0.05

  0.06

  Commuting

  -0.13

  0.50

  Watching TV

  0.22

  0.12

  Homework

  0.02

  –1.55

  We next looked at which types of people bring us more pleasure and purpose as we go about our daily activities. The purpose of time with kids increases when done with relatives. Volunteering is both more purposeful and more pleasurable when done with pretty much anybody else. Eating is more pleasurable when done with relatives and commuting is more purposeful when engaged in with coworkers. Housework is more purposeful when done with household children. Work is more pleasurable with family and friends. Watching TV is more pleasurable and purposeful with other people’s kids. Homework is made much less purposeful when engaged in with siblings. Apologies for the quite long list of facts here, but I hope you will agree with me when I say that these results all make intuitive sense and therefore add to the confidence we can have in these data.

  These data also allow us to consider some interesting differences in the ratings of different groups of people. The following graph illustrates that there are very small differences in pleasure or purpose by age—but that the purpose ratings of those aged fifteen to twenty-three are significantly lower than the purpose ratings of other age groups—and also significantly lower than their own pleasure ratings. If we looked only at pleasure, we would conclude that there are no age effects in these data, but consideration of purpose tells a different story.

  When we look at differences by people across activities, some interesting patterns emerge. Men experience more pleasure from time with children than women but women experience more purpose. Perhaps because men spend less time with children overall, being with children is more pleasurable, whereas for women, it’s more purposeful. As income rises, people experience less purpose from housework. If housework is seen as an added time pressure, this is consistent with research I’ll discuss later that shows the richer people get, the more pressure they feel on their time.7

  It is great that we now have data on the pleasure and purpose from different activities, and the distinction matters. By adding purpose into the mix we can show that work brings happiness in ways that would be ignored if we considered only pleasure. We can also show that we are generally happier when we are interacting with other people, and again the distinction between pleasure and purpose provides some nuance here (commuting with other people adds purpose but not pleasure, for example).

  Other evidence on happiness

  Evaluations

  When it comes to measuring happiness, it is a lot cheaper and easier to ask high-level evaluative questions than it is to ask about specific feelings and activities. While I have voiced my concerns about these questions, happiness snapshots are better than no record at all of our happiness and we have more information on them than for any other measure. As a result, some of the evidence I cite in later chapters will refer to life satisfaction and so it is worth briefly considering some of the evidence.

  Imagine yourself as a participant in one of the surveys. On a scale from 0 (not at all) to 10 (completely), overall how satisfied are you with your life nowadays?

  ________ out of 10.

  Probably the best international data on life satisfaction come from two studies carried out in the UK and Germany. In each data set, for about the past twenty years, the same ten thousand or so people have been asked about their life satisfaction alongside lots of other questions about themselves and their lives. These are called longitudinal data because we have multiple observations on the same people over time. Economists like me generally prefer longitudinal data because they allow us to see how each individual’s happiness changes in response to good or bad life events. A few years ago, I led a comprehensive review of this literature with Tessa Peasgood and Mat White, gathering up papers that had looked at the variables associated with reports of life satisfaction, focusing on large longitudinal data sets like the ones from the UK and Germany.

  Our conclusions were that life satisfaction ratings are higher for those who:

  a.are wealthier (especially when compared to people who are like them)

  b.are young or old (being in your forties and fifties is a bad time for life satisfaction)

  c.are healthier

  d.have lots of social contact

  e.are married (or at least cohabiting)

  f.are a little more educated (having a degree is good but you probably shouldn’t get a PhD if you want to maximize your life satisfaction)

  g.are religious (it doesn’t matter which religion)

  h.have a job

  i.commute a short distance to work8

  Since our review, some further details have been added to some of these effects. Money appears to matter a lot when you are poor, but the impact on life satisfaction of each additional dollar shrinks—though never to zero, as it appears to do for daily mood.9 We need to be careful here, though, because income does not only directly affect life satisfaction; it also indirectly affects happiness through its impact upon other inputs that affect life satisfaction. Richer people are generally more likely to have more friends, get married, be in better health, and so on, all of which improve life satisfaction. So rather than isolating the effect of income, which economists tend to do, we need to sprinkle its effects across all the other inputs into life satisfaction. When this sprinkling takes place, the effect of income on life satisfaction is much greater than found previously in the literature because we are picking up its indirect effects as well as the direct effects that come from having a bigger bank balance.10

  It has been suggested that the U-shaped relationship between life satisfaction and age (with happiness lowest in middle age) might be because of expectations: as young people get older, they expect to be more satisfied with their lives than turns out to be the case, but once they get through their fifties, they expect to be less satisfied than they end up.11 Having children delays the onset of the downward move on the U by two decades but this is due to differences in income and education among people with and without children rather than the children per se.12 It would also appear to be the case that life satisfaction takes another dip again once you are lucky enough to reach seventy-five.13 There is some evidence that those who say they are at the top point on a life satisfaction scale, such as “10 out of 10,” are likely to be older (as well as poorer, less healthy, and less educated) than those who say they are “9 out of 10.”14 Such findings can lead us to further question just what the term “satisfaction” is getting at.

  Context seems to matter, too. As a nice example, in an analysis of data from forty-three European and Anglo-Saxon countries, personal religiosity is associated with higher life satisfaction in countries where religiosity is higher on average as well. So the happiness benefits from religion stem in large part from the benefits that come from being part of a group.15

  Our ratings of life satisfaction are also affected by “internal” attributes, like personality and genes. Sociable people (high in extroversion) tend to be the most satisfied with their lives, and anxious people (high in neuroticism) tend to be the least satisfied.16 It is important to keep in mind, though, that personality is not entirely fixed and can change over time.17 The effect of genes, in particular, has led some to believe that we each have a set point of happiness that we fluctuate around but always return to. But this is not supported by evidence, because some events, like unemployment and disability, can permanently lower satisfaction with life.18 And for some people, marriage can have long-lasting positive effects.19 In the next chapter, I’
ll consider in more detail the evidence on what we get used to and what we do not.

  The ONS four

  There are also some exciting new data that, in time, will enable us to make more confident claims about the associations between different measures. The Office for National Statistics (ONS) in the UK, which gathers a range of data about economic growth and about how well life is going in other ways, is now trying to monitor national happiness in a number of ways.

  The ONS asked Richard Layard and me, ably abetted by Rob Metcalfe, to make recommendations about which questions to ask.20 The questions were intended to be added to existing surveys that already ask lots of questions about income, work, education, health, etc., and so they needed to be questions that could be answered quite quickly. It was not possible, therefore, to add detailed questions on the flow of happiness over time but the ONS did eventually agree to include four “headline questions” about happiness. This meant that we could ask some general questions that broadly covered pleasure and purpose, though in a more evaluative way than I would have ideally preferred.

  As a result, the ONS surveys are now asking nearly two hundred thousand people per year across the UK about their happiness, using four main questions:

  1.Overall, how satisfied are you with your life nowadays?

  2.Overall, to what extent do you feel the things you do in your life are worthwhile?

  3.Overall, how happy did you feel yesterday?

  4.Overall, how anxious did you feel yesterday?