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The Economics of Happiness and Health Andrew Oswald IZA and Warwick I would like to acknowledge that much of this work is joint with coauthors Chris Boyce,

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Presentation on theme: "The Economics of Happiness and Health Andrew Oswald IZA and Warwick I would like to acknowledge that much of this work is joint with coauthors Chris Boyce,"— Presentation transcript:

1 The Economics of Happiness and Health Andrew Oswald IZA and Warwick 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.

2 This week Id like to propose a number of ideas.

3 #1 Happiness data offer us interesting potential as proxy-utility data. u = u(y, z,..)

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

5 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.

6 One potentially important implication:

7 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,

8 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.

9 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)

10 #2 The next 20 years are likely to see economists work more and more with physiological and hard-science data.

11 #3 Biomarker data will (slowly) be used more and more in economics.

12 #4 Empirically, there are strong relative effects on utility:

13 #4 Empirically, there are strong relative effects on utility: u = u(y, y*) eg. if y* is others incomes.

14 #5 A crucial role in social-science behaviour is played by the second derivative, v, of the function utility = v(relative status)+..

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

16 #6 The Stiglitz Commissions ideas will eventually take hold.

17 Stiglitz Report 2009: Measures of.. objective and subjective well- being provide key information about peoples quality of life. Statistical offices [worldwide] should incorporate questions to capture peoples life evaluations, hedonic experiences … in their own survey. P.16. Executive Summary of Commission Report.

18 So

19 Could we perhaps learn …

20 ..how to make whole countries happier?

21 Preferably not like this…

22 Germany 4 England 1

23

24 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.

25 This is a good time for general questions if people would like to ask some?

26 Now lets think about how human beings report their feelings (for example, in a survey).

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

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

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

30 Human feelings Human reporting

31 Lets think of the example of money and peoples well-being.

32 Assume

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

34 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).

35 The Reporting Function

36 Write R(y) which is reported happiness as a function of income. This is what is studied in well- being regression equations.

37 Now think of the function-of-a- function rule in calculus.

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

39 By definition R(y) = r(h(y)) so R ʹ (y) = r ʹ (h) h ʹ (y) > 0 where y is income.

40

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

42 From Deaton-Kahneman in PNAS 2010

43 Now lets think of the second derivative

44 The first derivative earlier was: R ʹ (y) = r ʹ (h) h ʹ (y)

45 The first derivative earlier was: R ʹ (y) = r ʹ (h) h ʹ (y) where y is income, r is reported happiness, h is actual happiness.

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

47 Think of the second derivative The curvature of reported happiness is R(y) = r(h) h ʹ (y) h ʹ (y) + r ʹ (h) h(y)

48 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

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

50 Reiterating why: The curvature of reported happiness is R(y) = r(y) h ʹ (y) h ʹ (y) + r ʹ (h) h(y)

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

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

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

54 Height as an example

55 113 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.

56 113 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.

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

58

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

60 Feelings of height and actual height in 113 men

61 Feelings of height and actual height in 106 women

62 These plots are consistent with a linear reporting function.

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

64 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

65 Happy and Sad Pictures

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

67 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

68 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?

69 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.

70 Happiness in Different Activities

71 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

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

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

74 Could you turn to the NBER Blanchflower-Oswald paper on international happiness?

75

76 Some cheery news:

77 In Western nations, most people are pretty happy with their lives.

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

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

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

81 The distribution of life-satisfaction levels among British people Source: BHPS, N = 74,481

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

83 Other work on happiness as causal John Ifcher and Homa Zarghamee, forthcoming 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.

84 Is modern society going in a sensible direction?

85 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.

86 We will focus on it tomorrow.

87 Lets return for a moment to the microeconomics of human well-being

88 What have we learned?

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

90 There is also an intriguing life-cycle pattern

91 The pattern of a typical persons happiness through life

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

93 Overall well-being

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

95 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:

96 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

97 Obviously life is a mixture of ups and downs

98 Much of the recent research follows people through time. eg. Andrew Clarks work

99 The unhappiness from bereavement

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

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

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

103

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

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

106 And should you invest in a baby?

107 Happiness and children

108 But people do not seem to adapt to joblessness

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

110 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..).

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

112 Divorce (eventually) makes people happier

113

114 Points or questions?

115 What about money and happiness?

116 A key social-science fact

117 The data show that richer people are happier and healthier.

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

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

120 Many are opposed to the idea of measuring happiness.

121 I always liked the retort:

122 If molecules could talk, would physicists refuse to listen? A. Blinder

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

124 So how could we move forward?

125 Brain-science correlates as a validation

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

127

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

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

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

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

132 Yes.

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

134 134 Are objective and subjective data on quality-of-life correlated?

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

136 Think not about people but about places.

137 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

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

139 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

140 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

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

142 Gabriels work assigns a 1 to the state with the highest imputed quality-of-life, and 50 to the state with the lowest.

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

144 And there is one.

145 One Million Americans Life Satisfaction and Objective Quality-of-Life in 50 States

146 To conclude across US states: There is a match between life- satisfaction scores and the quality of life calculated using (only) non- subjective data.

147 Some ideas to end:

148 My hunch

149 The methods of the economics of happiness and mental well- being will slowly enter public life.

150 Other important applications

151 The valuation of environmental amenities

152 Other important applications The valuation of environmental amenities The valuation of health states

153 Other important applications The valuation of environmental amenities The valuation of health states The valuation of emotional damages for the courts.

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

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

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

157 An alternative definition:

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

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

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

161 And the next research area?

162

163 Thank you.

164 The 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.


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