An Introduction to the Behavioural Economics of Happiness and Health

Transcription

1 An Introduction to the Behavioural Economics of Happiness and Health Andrew Oswald University of Warwick I would like to acknowledge that much of this work is joint with coauthors Chris Boyce, Andrew Clark, Nick Powdthavee, David G. Blanchflower, Eugenio Proto, and Steve Wu.

2 Why should we care about happiness and health?

3 Reason 1

4 Reason 1 We need to know if society is going in a sensible direction.

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6 Yet in 1934

7 Yet in the welfare of a nation [can] scarcely be inferred from a measure of national income...

8 Hug a tree today

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10 Prof. Simon Kuznets The originator of the concept of GDP

11 ...the welfare of a nation [can] scarcely be inferred from a measure of national income... S Kuznets

12 So even Simon Kuznets knew that we require a different yardstick.

13 Reason 2

14 Reason 2 Human beings have feelings.

15 Reason 2 Human beings have feelings.

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20 Humans have feelings, and feelings matter.

21 How do I know researchers care about feelings of wellbeing?

22 Say we do an electronic search.

23 Since 2008, approximately 110,000 articles have been published in economics journals.

24 The most-cited major article in modern economics:

25 The most-cited major article in modern economics: Relative income, happiness, and utility: An explanation for the Easterlin paradox and other puzzles Clark, Andrew E.; Frijters, Paul; Shields, Michael A. JOURNAL OF ECONOMIC LITERATURE MAR 2008

26 In these lectures I want to propose a number of ideas.

27 #1 Happiness data offer us interesting potential as proxy-utility data. u = u(y, z,..)

28 Regression equations Mental well-being = f(age, gender, education level, income, marital status, friendship networks, region, year )

29 We now know: There is a lot of regularity in these regression-equation patterns, across countries and well-being measures. Fairly robust to panel estimators and different methods. Progress can be made on causality.

30 One potentially important implication:

31 If this form of function can be estimated (and K, L, M are life events): Happiness = a + bk + cl + dm +ey where Y is income,

32 If this form of function can be estimated (and K, L, M are life events): Happiness = a + bk + cl + dm +ey where Y is income, then we may be able to use such equations to calculate the implied dollar value of the happiness from life events K, L, M.

33 Monetary equivalences A life satisfaction equation: Life satisfaction = B1*income + B2*Event + error Marriage - $100,000 (Blanchflower and Oswald, 2004), Neuroticism - $314,000 (Boyce et al., in press), Widowhood ($175,000-$496,000), Health limiting daily activities ($473,000) (Powdthavee, van den Berg, 2011)

34 #2 The next 20 years are likely to see economists work more and more with physiological and hard-science data.

35 #3 Biomarker data will (slowly) be used more and more in economics.

36 #4 Empirically, there are strong relative effects on utility:

37 #4 Empirically, there are strong relative effects on utility: u = u(y, y*) eg. if y* is others incomes.

38 #5 A crucial role in social-science behaviour is played by the second derivative, v, of the function utility = v(relative status)+..

39 In humans (I shall argue) Concavity of v(.) leads to imitation and herd behaviour Convexity of v(.) leads to deviance.

40 #6 The Stiglitz Commission s ideas will eventually take hold.

41 Stiglitz Report 2009: Measures of.. objective and subjective wellbeing provide key information about people s quality of life. Statistical offices [worldwide] should incorporate questions to capture people s life evaluations, hedonic experiences in their own survey. P.16. Executive Summary of Commission Report.

42 So...

43 Could we perhaps learn

44 ..how to make whole countries happier?

45 Though this would be my favourite way

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47 England win world cup 2018!!

48 Useful introductions Relative Income, Happiness and Utility: An Explanation for the Easterlin Paradox and Other Puzzles (Andrew Clark, Paul Frijters and Mike Shields), Journal of Economic Literature, The Happiness Equation (Nick Powdthavee), Icon Books, 2010.

49 This is a great time for general questions if people would like to ask any?

50 Now let s think about how human beings report their feelings (for example, in a survey).

51 First, they have genuine feelings inside themselves (about how happy they are, say).

52 Second, they make a decision about how to report those feelings.

53 There are then two processes going on inside a person.

54 Human feelings Human reporting

55 Let s think of the example of money and people s well-being.

56 Assume

57 Assume People get true happiness, h, from income, y. Call it h(y).

58 Assume People get true happiness, h, from income, y. Call it h(y). They give a number for this, which is their reported happiness, r. Call it r(h).

59 The Reporting Function

60 The Reporting Function Write R(y) which is reported happiness as a function of income. This is what is studied in wellbeing regression equations.

61 Now think of the function-of-afunction rule in calculus.

62 R(y) = r(h(y)) By definition

63 By definition R(y) = r(h(y)) so Rʹ(y) = rʹ(h) hʹ(y) > 0 where y is income.

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65 In the cross-section, income is positively correlated with happiness Take America in 1994 for example

66 From Deaton-Kahneman in PNAS 2010

67 Now let s think of the second derivative

68 The first derivative earlier was: Rʹ(y) = rʹ(h) hʹ(y)

69 The first derivative earlier was: Rʹ(y) = rʹ(h) hʹ(y) where y is income, r is reported happiness, h is actual happiness.

70 Think of the second derivative The curvature of reported happiness is

71 Think of the second derivative The curvature of reported happiness is R (y) = r (h) hʹ(y) hʹ(y) + rʹ(h) h (y)

72 But if R (y) is found to be negative that does not prove that h (y) is negative. R is reported happiness h is true happiness

73 Hence there are lots and lots of papers in the literature that get this wrong.

74 Reiterating why: The curvature of reported happiness is R (y) = r (y) hʹ(y) hʹ(y) + rʹ(h) h (y)

75 Even if the estimated happiness function itself is concave, we cannot be certain that true happiness is concave.

76 All social scientists (and many medical scientists) need to know more about the reporting function.

77 So is there any way to make progress on this tricky issue?

78 Height as an example

79 113 Men and 106 Women The respondents were asked to record how tall they felt, using a continuous un-numbered line with the words very short written at the left-hand end to very tall at the right-hand end.

80 113 Men and 106 Women The respondents were asked to record how tall they felt, using a continuous un-numbered line with the words very short written at the left-hand end to very tall at the right-hand end. Numbers were coded 1 10 afterwards.

81 Then we looked at the correlation between feelings of being tall and actual true height.

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83 How well correlated are feelings of height and actual height?

84 How well correlated are feelings of height and actual height?

85 Feelings of height and actual height in 113 men 10 y = x R= Subjective assessment of height from very short to very tall Actual height of men (in cm)

86 Feelings of height and actual height in 106 women 10 y = x R= Subjective assessment of height from very short to very tall Actual height of women (in cm)

87 These plots are consistent with a linear reporting function.

88 Much more research on the reporting function r(.) will be required in the future.

89 Evidence from Neuroscience Positive feelings correspond to brain activity in the left-side of the pre-frontal cortex, above and in front of the ear Negative feelings correspond to brain activity in the same place in the right side of the brain

90 Happy and Sad Pictures

91 The Brain Responses to Two Pictures (MRI Scan) Source: Richard Davidson, University of Wisconsin

92 The types of statistical sources General Social Survey of the USA British Household Panel Study (BHPS) German Socioeconomic Panel Australian HILDA Panel Eurobarometer Surveys Labour Force Survey from the UK World Values Surveys NCDS 1958 cohort BRFSS

93 From the U.S. General Social Survey (sample size 40,000 Americans approx.) Taken all together, how would you say things are these days - would you say that you are very happy, pretty happy, or not too happy?

94 An alternative DRM approach A study by Daniel Kahneman and his colleagues on 1,000 working women in Texas (see Kahneman et al, 2003) These women were asked to divide the previous day into 15 episodes. They were then asked what they were doing in each episode, and who were they doing it with.

95 Happiness in Different Activities

96 Happiness while Spending Time with Different People The average reported feelings across 1,000 people correspond well with activities predicted to be good for us, as well as activities predicted to be bad for us

97 So how has the modern work on the economics of happiness proceeded?

98 Here is a modern US happiness equation (courtesy of David Blanchflower, Dartmouth College and NBER)

99 Could you turn to the NBER Blanchflower-Oswald table on international happiness?

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101 Some cheery news:

102 Some cheery news: In Western nations, most people are pretty happy with their lives.

103 Some cheery news: In Western nations, most people are pretty happy with their lives.

104 The distribution of life-satisfaction levels among British people Percentage of Population Self-rated Life Satisfaction Source: BHPS, N = 74,481

105 Exogenous shocks and happiness

106 Exogenous shocks and happiness New work looks at

107 Exogenous shocks and happiness New work looks at Genes Lottery wins 9-11 s effects Deaths of children Sporting results Movements in air pollution

108 Other work on happiness as causal John Ifcher and Homa Zarghamee, in the AER, on happiness leading to different rate of time discount. Oswald, Proto, Sgroi on happiness leading to higher productivity. These randomly assign happiness.

109 Is modern society going in a sensible direction?

110 This is an empirical question "Does Economic Growth Improve the Human Lot?" Richard Easterlin in Paul A. David and Melvin W. Reder, eds., Nations and Households in Economic Growth: Essays in Honor of Moses Abramovitz, New York: Academic Press, Inc., 1974.

111 We will focus on it, in detail, later.

112 Let s return for a moment to the microeconomics of human well-being

113 What have we learned?

114 Big effects Unemployment Divorce Marriage Bereavement Friendship networks Health No effects from children [but + for grandchildren: Nick Powdthavee]

115 There is also an intriguing life-cycle pattern

116 The pattern of a typical person s happiness through life 5.6 Average life satisfaction score Age group

117 Arthur Stone, Angus Deaton, et al (2010)

118 Overall well-being

119 Quadratic Life-Satisfaction in the US Steve Wu on BRFSS 2010 data age agesq Again the U-shape.

120 A life satisfaction U-shape in age also exists in many developing nations In World Values Survey data, there is a U- shape and it reaches its minimum at:

121 A life satisfaction U-shape in age also exists in many developing nations In World Values Survey data, there is a U- shape and it reaches its minimum at: Brazil 37 China 46 El Salvador 48 Mexico 41 Nigeria 42 Tanzania 46

122 Obviously life is a mixture of ups and downs

123 Much of the recent research follows people through time. eg. Andrew Clark s work

124 The unhappiness from bereavement

125 Human beings also bounce back from, say, disability. Work with N. Powdthavee, Journal of Public Economics, 2008

126 Life-Satisfaction Path of Those Who Entered Disability at Time T and Remained Disabled in T+1 and T+2 BHPS data Mean Life Satisfaction T-2 T-1 T T+1 T+2

127 However, there is a downside to that adaptability (eg. marriage)

128 However, there is a downside to that adaptability (eg. marriage)

129 Is there income adaptation? Maybe. The joy of having higher income may also wear off

130 Source: Di Tella et al (2008), German Socio-Economic Panel

131 And should you invest in a baby?

132 Happiness and children

133 But people do not seem to adapt to joblessness

134 The evidence suggests that when a person is made unemployed:

135 The evidence suggests that when a person is made unemployed: 20% of the fall in mental well-being is due to the decline in income 80% is due to non-pecuniary things (loss of self-esteem, status..).

136 An important question in a modern society is the impact of divorce.

137 Divorce (eventually) makes people happier

138 Divorce (eventually) makes people happier

139 I wonder if anyone would like to raise points or questions?

140 What about money and happiness?

141 A key social-science fact

142 A key social-science fact The data show that richer people are happier and healthier.

143 But some general economists have low life-satisfaction when they hear about this research.

144 The tradition of economics has been to ignore what people say about the quality of their own lives.

145 The tradition of economics has been to ignore what people say about the quality of their own lives. Many are opposed to the idea of measuring happiness.

146 I always liked the retort:

147 I always liked the retort: If molecules could talk, would physicists refuse to listen? A. Blinder

148 I always liked the retort: If molecules could talk, would physicists refuse to listen? A. Blinder

149 So how could we move forward?

150 So how could we move forward? Brain-science correlates as a validation

151 So how could we move forward? Brain-science correlates as a validation Physiological correlates as a validation

152

153 A brain-science approach (Urry et al Psychological Science 2004)

154 Andrew Steptoe s work

155 But, for a sceptic, there is a major difficulty.

156 Biological data only validate well-being scores in so far as they are unambiguously measures of utility or happiness.

157 A killer question Can we devise a test in the economist s spirit that shows, once and for all, a match between subjective well-being data and objective well-being data?

158 Yes.

159 I would like to give you the flavour of the argument in Oswald-Wu in Science in 2010.

160 16 0 Are objective and subjective data on quality-of-life correlated?

161 We can exploit neo-classical economic theory to assess the validity of well-being data.

162 Think not about people but about places.

163 Joint work with Steve Wu New data from the Behavioral Risk Factor Surveillance System (BRFSS) 1.3 million randomly sampled Americans 2005 to 2008 A life-satisfaction equation

164 Then we go to the compensatingdifferentials literature dating back to Adam Smith, Sherwin Rosen, Jennifer Roback, etc. The most recent is Gabriel et al 2003.

165 Gabriel painstakingly takes data on Precipitation Humidity Heating Degree Days Cooling Degree Days Wind Speed Sunshine Coast Inland Water Federal Land Visitors to National Parks Visitors to State Parks Number of hazardous waste sites

166 and Environmental Regulation Leniency Commuting Time Violent Crime Rate Air Quality-Ozone Air Quality-Carbon Monoxide Student-teacher ratio State and local taxes on property, income and sales and other State and local expenditures on higher education, public welfare, highways, and corrections Cost-of-living

167 Then there are 2 ways to measure human well-being or utility across space. Subjective and objective

168 Gabriel s work assigns a 1 to the state with the highest imputed quality-of-life, and 50 to the state with the lowest.

169 So we need to uncover a negative association in order to find a match.

170 And there is one.

171 One Million Americans Life Satisfaction and Objective Quality-of-Life in 50 States 0.04 y = x R= Life Satisfaction Fully Adjusted (ie income also) Objective Quality of Life Ranking (where 1 is high and 50 is low)

172 To conclude across US states: There is a match between lifesatisfaction scores and the quality of life calculated using (only) nonsubjective data.

173 Some ideas to end:

174 My hunch

175 My hunch The methods of the economics of happiness and mental wellbeing will slowly enter public life.

176 Other important applications

177 Other important applications The valuation of environmental amenities (e.g. Levinson Journal of Public Economics 2011)

178 Other important applications The valuation of environmental amenities (e.g. Levinson Journal of Public Economics 2011) The valuation of health states

179 Other important applications The valuation of environmental amenities (e.g. Levinson Journal of Public Economics 2011) The valuation of health states The valuation of emotional damages for the courts.

180 Conventionally: Economics is a social science concerned with the efficient allocation of scarce resources

181 We owe this definition to Lionel Robbins of the London School of Economics. For a long time, it served us well.

182 But perhaps the time has come to think differently and to define economics differently.

183 An alternative definition:

184 An alternative definition for 2011: Economics is a social science concerned with the best way to allocate plentiful resources to maximize a society s well-being and mental health.

185 Looking ahead Policy in the coming century may need to concentrate on non-materialistic goals.

186 Looking ahead Policy in the coming century may need to concentrate on non-materialistic goals. GNH not GDP.

187 And the next research area?

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189 An Introduction to the Behavioural Economics of Happiness and Health Andrew Oswald Research site: I would like to acknowledge that much of this work is joint with coauthors Chris Boyce, Andrew Clark, Nick Powdthavee, David G. Blanchflower, and Steve Wu.