Would You Be Happier If You Were Richer?
A Focusing Illusion
byDaniel Kahneman, Princeton University
Alan B. Krueger, Princeton University and NBERDavid Schkade, University of California, San Diego
Norbert Schwarz, University of Michigan
Arthur A. Stone, Stony Brook University

CEPS Working Paper No. 125
May 2006

Research support provided by the Princeton University Center for Economic Policy Studies is gratefully
acknowledged.

Most people believe that they would be happier if they were richer, but survey evidence
on subjective well-being is largely inconsistent with that belief. Subjective well-being is mostcommonly measured by questions that ask people, “All things considered, how satisfied are youwith your life as a whole these days?” or “Taken all together, would you say that you are very
happy, pretty happy, or not too happy?” Such questions elicit a global evaluation of one’s life.
An alternative method asks people to report their feelings in real time, which yields a measure ofexperienced happiness. Surveys in many countries conducted over decades indicate that, on
average, reported global judgments of life satisfaction or happiness have not changed much overthe last four decades, in spite of large increases in real income per capita. While reported life
satisfaction and household income are positively correlated in a cross-section of people at agiven time, increases in income have been found to have mainly a transitory effect on
individuals’ reported life satisfaction. (1-3) Moreover, the correlation between income andsubjective well-being is weaker when a measure of experienced happiness is used instead of a
global measure. This article reviews recent evidence that helps interpret these observations.
When people consider the impact of any single factor on their well-being -- not only
income -- they are prone to exaggerate its importance; we refer to this tendency as the focusing
illusion. Income has even less effect on people's moment-to-moment hedonic experiences thanon the judgment they make when asked to report their satisfaction with their life or overallhappiness. These findings suggest that the standard survey questions by which subjective wellbeing is measured (mainly by asking respondents for a global judgment about their satisfactionor happiness with their life as a whole) may induce a form of focusing illusion, by drawing
people's attention to their relative standing in the distribution of material well-being. More
importantly, the focusing illusion may be a source of error in significant decisions that people
make. (4)Page 2

Evidence for the focusing illusion comes from diverse lines of research. For example,
Strack and colleagues (5) reported an experiment in which students were asked: (i) “How happy
are you with your life in general?” and (ii) “How many dates did you have last month?” Thecorrelation between the answers to these questions was -.012 (not statistically different from 0)
when they were asked in the specified order, but the correlation rose to 0.66 when the order was
reversed with another sample of students. The dating question evidently caused that aspect oflife to become salient and its importance to be exaggerated when the respondents encountered
the more general question about their happiness. Similar focusing effects were observed whenattention was first called to respondents’ marriage (6) or health (7). One conclusion from thisresearch is that people do not know how happy or satisfied they are with their life in the way
they know their height or telephone number. The answers to global life satisfaction questions areconstructed only when asked (8), and are therefore more susceptible to the focusing of attention
on different aspects of life.
To test the focusing illusion regarding income we asked a sample of working women to
estimate the percentage of the time that they were in a bad mood in the preceding day.
Respondents were also asked to estimate the percentage of time people with pairs of various life
circumstances (Table 1), such as high- and low-income, typically spend in a bad mood.
Respondents’ predictions were compared to the actual reports of mood provided by participantsin the survey with the relevant circumstances. The focusing illusion predicts a systematic
overestimation of the effect of life circumstances on mood.
Table 1 presents the mean percentage of time that members in each group reported
spending in a bad mood in the preceding work day. It also shows the corresponding mean
predictions offered by the entire group (including individuals whose reports were included in theactual mood column). The predictions were biased in two respects. First, the prevalence of bad
Page 3mood was generally overestimated. Second, consistent with the focusing illusion, the predictedprevalence of a bad mood for people with undesirable circumstances was grossly exaggerated.
For example, the average respondent predicted that people with income below $20,000 per year
would spend 58 percent of their time in a bad mood, compared with 26 percent for those withincome above $100,000 per year; the actual percentages were 32 percent and 20 percent,respectively.
The focusing illusion explains why the results of well-being research are often counterintuitive. The false intuitions likely arise from a failure to recognize that people do notcontinuously think about their circumstances, whether positive or negative. Schkade andKahneman (9) noted that, “Nothing in life is quite as important as you think it is while you arethinking about it.” Individuals who have recently experienced a significant life change -- e.g.,
becoming disabled, winning a lottery, or getting married -- surely think of their new
circumstances many times each day, but the allocation of attention eventually changes, so thatthey spend most of their time attending to and drawing pleasure or displeasure from experiencessuch as having breakfast or watching television. (10) However, they are likely to be reminded of
their status when prompted to answer a global judgment question such as, "How satisfied are youwith your life these days?"
The correlation between household income and reported life satisfaction or happinesswith life as whole (assigned an integer value) in national samples typically range from 0.15 to
0.30. (11) Table 2 illustrates the relationship between global happiness and income for 2004 withdata from the General Social Survey. Those with incomes over $90,000 are nearly twice as
likely to report being “very happy” as are those with incomes below $20,000, although there ishardly any difference between the highest income group and those in the $50,000-89,999
bracket.
Page 4

There are reasons to believe that the modest cross-section correlation between income
and judgments of life satisfaction or overall happiness overstates the effect of income on
subjective well-being. First, increases in income have mostly a transitory effect on individuals’
reported life satisfaction (2,12). Second, large increases in income for a given country over time
are not associated with increases in average subjective well-being. Easterlin (1), for example,
found that the fivefold increase in real income in Japan between 1958 and 1987 did not coincidewith an increase in the average self-reported happiness level there. Third, although average life
satisfaction in countries tends to rise with GDP per capita at low levels of income, there is little
or no further increase in life satisfaction once GDP per capita exceeds $10,000. (3)Fourth, when subjective well-being is measured from moment to moment -- either by
querying people in real time using Ecological Momentary Assessment (EMA) (13) or by asking
them to recall their feelings for each episode of the previous day using the Day Reconstruction
Method (DRM) (14) -- income is more weakly correlated with experienced feelings such as
momentary happiness averaged over the course of the day (henceforth called duration-weighted
or experienced happiness) than it is with a global judgment of life satisfaction or overallhappiness, or a global report of yesterday’s mood.
For example, the correlation between life satisfaction and household income was 0.32 indata we collected from 745 women in Columbus, Ohio in May 2005. Two other measures ofsubjective well-being were constructed for the same sample: the duration-weighted averagehappiness rating for all episodes of the previous day and respondents’ own global estimate of thepercent of time they spent in a good or bad mood in the previous day. The correlations ofincome with the global report of good mood and with the duration-weighted average of moredetailed reports of happiness were 0.20 and 0.06, respectively; see Table 3. Both correlations are

Page 5significantly lower than the correlation between income and life satisfaction, and significantly
different from each other. (15) Correlations with other life circumstances exhibit the same
pattern: a weaker correlation with duration-weighted average happiness across episodes of the
day than with global life satisfaction. (16)An analysis of EMA data also points to a weak and sometimes perverse relationshipbetween experienced affect and income. Specifically, we examined EMA data from the Cornell
Worksite Blood Pressure study of 374 workers, who were queried about their intensity of six
feelings on a 0-3 scale every 25m or so during an entire workday. (17,18) The correlation
between personal income and the average happiness rating during the day was just 0.01 (p=0.84),
while family income was significantly positively correlated with ratings of Anger/Hostile(r=.14), Anxious/Tense (r=.14) and Excited (r=.18). Thus, higher income was associated withmore intense negative experienced emotions and greater arousal, but not greater experienced
happiness.
Why does income have such a weak effect on subjective well-being? There are several
explanations, all of which may contribute to varying degrees. First, Duesenberry (19), Easterlin(2), Frank (20) and others have argued that relative income rather than the level of income
affects well-being – earning more or less than others looms larger than how much one earns.
Indeed, much evidence indicates that rank in the income distribution influences life satisfaction.
(21-23) As society grows richer, the average rank does not change, so the relative income
hypothesis could explain the stability of average subjective well-being despite national income
growth. The importance placed on relative income may also account for the stronger correlation
between income and global life satisfaction than between income and experienced affect, as life
satisfaction questions probably provoke a reflection on relative status that is not present inPage 6

moment-to-moment ratings of happiness. The relative income hypothesis cannot by itself
explain why a permanent increase in an individual’s income has a transitory effect on her wellbeing, as relative standing would increase. However, the increase in relative standing can beoffset by changes in the reference group: After a promotion, the new peers increasingly serve asa reference point, making the improvement relative to one’s previous peers less influential. (24)Second, Easterlin (1,2) argues that individuals adapt to material goods, and Scitovsky(25) argues that material goods yield little joy for most individuals. Thus, increases in income,which are expected to raise well-being by raising consumption opportunities, may in fact havelittle lasting effect because the consumption of material goods has little effect on well-being
above a certain level of consumption or because of hedonic adaptation. (26) Moreover, people’s
aspirations adapt to their possibilities and the income that people say they need to get along rises
with income, both in a cross-section and over time. (27)
Finally, we would propose another explanation: as income rises, people’s time use does
not appear to shift toward activities that are associated with improved affect. Subjective wellbeing is connected to how people spend their time. Table 4 presents our tabulations from theAmerican Time Use Survey on how the average individual’s waking time is divided among
various types of activities. The last two rows show the average experienced happiness andtense/stress rating associated with each activity based on the Columbus DRM survey. People
with greater income tend to devote relatively more of their time to work, compulsory non-work
activities (such as shopping and childcare) and active leisure (such as exercise), and less of theirtime to passive leisure activities (such as watching TV). On balance, the activities that highincome individuals spend relatively more of their time engaged in are associated with no greater
happiness, on average, but with slightly higher tension and stress.

Page 7

The results in Table 4 also highlight the possible role of the focusing illusion. Whensomeone reflects on how more income would change subjective well-being, they are probably
tempted to think about spending more time in leisurely pursuits such as watching a large-screen
plasma TV or playing golf, but in reality they should think of spending a lot more time working
and commuting and a lot less time engaged in passive leisure (and perhaps a bit more golf). By
itself, this shift in time use is unlikely to lead to much increase in experienced happiness,
although it could increase tension and one’s sense of accomplishment and satisfaction.
Despite the weak relationship between income and global life satisfaction or experienced
happiness, many people are highly motivated to increase their income. In some cases, thisfocusing illusion may lead to a misallocation of time, from accepting lengthy commutes (which
are among the worst moments of the day) to sacrificing time spent socializing (which are among
the best moments of the day). (28) An emphasis on the role of attention helps to explain both
why many people seek high income – because they over predict the increase in happiness due tothe focusing illusion and because changes in relative income are associated with strong
emotional responses – and why the long-term effects of these changes are relatively small -because attention eventually shifts to less novel aspects of daily life.

Page 8

Table 1. The Focusing Illusion: Exaggerating the effect of various circumstances on well-being
Percentage of Time in a Bad Mood _ActualPredicted
1
Actual Predicted Difference Difference2

VariableGroup2

HouseholdIncome< $20,000> $100,000

32.0
19.8

57.7
25.7

12.2

32.0*

Woman Over
40 Years Old

alone
married

21.4
23.1

41.1
27.9

-1.7

13.2**

Supervision
At Work

definitely close
definitely not close

36.5
19.1

64.3
22.3

17.4

42.1**

FringeNo health insurance
26.6
49.7
4.5
30.5**
Benefits
Excellent benefits
22.2
19.2
___________________________________________________________________________**

Indicates that predicted difference is significantly larger than actual difference at p < .001.

1“Now we would like to know overall how you felt and what your mood was like yesterday.
Thinking only about yesterday, what percentage of the time were you: in a bad mood____%, alittle low or irritable____%, in a mildly pleasant mood____%, in a very good mood____%.
Bad mood reported here is the sum of the first two response categories. A parallel question wasthen asked about yesterday at work. Bad mood at work was used for the supervisioncomparison.
2

Data are from the Texas sample used in Kahneman, et al. (29). For actual column, thepreceding day was a workday. Reading down each column, sample sizes are Household Income:Actual (n=64, 59), Predicted (n=83, 83); Woman over 40 years old: Actual (n=82, 221),
Predicted (n=85, 87); Supervision at Work: Actual (n=75, 237), Predicted (n=84, 84); Fringe
Benefits: Actual (n=96, 211), Predicted (n=83, 85).

Page 9

Table 2: Distribution of Self-Reported Happiness by Family Income, General Social Survey,
2004"Taken all together, howwould you say things arethese days--would you
say that you are very
happy, pretty happy, orUnder
not too happy?"$20,000

Family Income$20,000$49,999$50,000-$89,999

Not too happy
17.2%
13.0%
7.7%
Pretty happy
60.5%
56.8%
50.3%
Very happy
22.2%
30.2%
41.9%
Notes: . Sample size is 1,173 individuals. Observations are weighted
by sample weights.

Page 10$90,000
and over
5.3%
51.8%
42.9%

Table 3: Correlations between selected life circumstances and subjective well-being measures
Life
Satisfaction

Percent of
Day inGood Mood

DurationWeighted"Happy"Household Income

.32*

.20*

.06

MarriedEducation
Employed
BMI

.21*
.16*
.14*
-.13*

.15*
.13*
.13*
-.08*

.03
.02
.01
-.06

Characteristic

Notes: n = 745, Columbus, Ohio DRM sample. * indicates p<0.05.
Percent of the day in good mood is from two questions of the form: “We would like to knowhow you feel and what mood you are in when you are at home [at work]. When you are at home,what percentage of the time are you in a bad mood____%, a little low or irritable____%, in a
mildly pleasant mood____%, in a very good mood____%. A parallel question was asked about
their time at work. The last two response categories were added together to obtain the percentageof time in a good mood, and the home and work questions were averaged to produce the goodmood variable.
Duration-weighted “happy” is the average of each person’s duration-weighted average rating of
the feeling happy over episodes of the day, where 0 refers to “not at all” and 6 refers to “verymuch,” and each individual’s responses were weighted by the duration of the episode.

Page 11

Table 4: Percent of Time Spent in Various Activities by Family Income, 2004 and Average
Affective Ratings During Activities

EatingPassive
Work &
Leisure Compulsory Commute

Other

6.6%
8.1%
10.2%

6.6%
7.2%
8.6%

34.7%
26.4%
19.9%

20.8%
21.8%
23.6%

29.1%
35.4%
36.9%

2.1%
1.1%
0.8%

Women
<$20,000$20,000-99,999$100,000+

5.3%
7.5%
9.1%

5.7%
6.7%
7.0%

33.5%
23.8%
19.6%

35.6%
34.3%
35.9%

18.5%
26.7%
27.3%

1.4%
1.0%
1.1%

Feelings (0-6)
HappyTense/Stressed

4.67
0.92

4.45
1.17

4.21
1.30

4.04
1.80

3.94
2.00

4.25
1.61

Family IncomeMen<$20,000$20,000-99,999$100,000+

ActiveLeisureNotes: Time allocation is weighted-average percentage of the day for each sampled observationfrom the American Time Use Survey (30). Weighted average of weekday (5/7) and weekend(2/7) is presented. Sample consists of 3,917 men and 4,944 women age 18-60. Last two rows
are computed from a DRM survey of 810 women in Columbus, Ohio in May 2005; if multiple
activities were performed during an episode, the activity refers to the one that was selected as“most important” at the time.

Page 12References
1.

R. Easterlin, Journal of Economic Behavior and Organization 27, 35 (1995).

2.

R. Easterlin, Building a better theory of well-being. Discussion Paper No. 742 (IZA,
Bonn, Germany, 2003).

3.

R. Layard, Happiness: Lessons from a new science (Penguin Press, London, 2005).

4.

D. Gilbert, Stumbling on happiness (Knopf, New York, 2006).

5.

F. Strack, L. Martin, & N. Schwarz, European Journal of Social Psychology 18, 429(1988).

6.

N. Schwarz, F. Strack, & H. Mai, Public Opinion Quarterly 55, 3 (1991).

7.

D. Smith, N. Schwarz, T. Roberts, & P. Ubel, Quality of Life Research (in press).

8.

N. Schwarz & F. Strack, in Well-being. The foundations of hedonic psychology, D.
Kahneman, E. Diener, & N. Schwarz, Eds. (Russell Sage Foundation, New York, NY,
1999), pp. 61-84.

9.

D. Schkade & D. Kahneman, Psychological Science 9, 340 (1998).

10.

D. Kahneman & R. H. Thaler, Journal of Economic Perspectives 20, 221 (2006).

11.

E. Diener & R. Biswas-Diener, Social Indicators Research 57, 119 (2002).

12.

B. Frey & A. Stutzer, Happiness and economics: How the economy and institutions affectwell-being. (Princeton University Press, Princeton, NJ, 2002).

13.

A. Stone & S. Shiffman, Annals of Behavioral Medicine 16, 199 (1994).

14.

D. Kahneman, A. Krueger, D. Schkade, N. Schwarz, & A. Stone, Science 306, 1176
(2004).

15.

In general, we find that the retrospective report of mood on the previous day, which is a
global evaluation, shares variance both with the global measures of life satisfaction andwith disaggregated measures of emotional experience at particular times.

16.

The higher correlation of these circumstances with satisfaction than with durationweighted happiness is probably not a result of greater noise in the duration-weighted
happiness measure than in life satisfaction. We conducted a reliability study of the DRM
that asked the same questions of 229 women two weeks apart, and found about the sametwo-week serial correlation in duration-weighted happiness as in life satisfaction for the
respondents.

Page 13

17.

P. Schnall, J. Schwartz, P. Landsbergis, K. Warren, & T. Pickering, Psychosomatic
Medicine 60, 697 (1998).

18.

The adjectives were Anger/Hostile, Anxious/Tense, Overwhelmed, Excited, Happy and
Tired. All 6 adjectives were asked at 9 of the sites with 296 people, and another site with
78 people asked only the first three (negative) adjectives.

19.

J. Duesenberry, Income, saving, and the Theory of Consumer Behavior (Harvard
University Press, Cambridge, MA, 1949).

20.

R. Frank, Luxury fever (Princeton University Press, Princeton, NJ, 1999).

21.

A. Clark & A. Oswald, Journal of Public Economics 61, 359 (1996).

22.

A. Ferrer-i-Carbonell, Journal of Public Economics 89, 997 (2005).

23.

E. Luttmer, Journal of Economics 120, 963 (2005).

24.

W. Runciman, Relative deprivation and social justice (University of California Press,
Berkeley, CA, 1966).

25.

T. Scitovsky, The joyless economy (Oxford University Press, Oxford, 1976).

26.

S. Frederick & G. Lowenstein, in Well-being: The foundations of hedonic psychology, D.
Kahneman, E. Diener, & N. Schwarz, Eds. (Russell-Sage, New York, 1999), pp. 302329.

27.

B. Van Praag & P. Frijter, in Well-being: The foundations of hedonic psychology, D.
Kahneman, E. Diener, & N. Schwarz, Eds. (Russell-Sage, New York, 1999), pp. 413433.

28.

See Stutzer and Frey (2004) for evidence on the misallocation of commuting time andKahneman et al (2004) on the hedonic experience of commuting and socializing.

29.

D. Kahneman, E. Diener, & N. Schwarz, Well-being: The foundations of hedonic
psychology (Russell Sage Foundation, New York, 1999).

30.

Time-use survey - First results announced by BLS, United States Department of Labor,
USDL 04-1797.

31.

The authors thank Marie Connolly, Molly Fifer and Amy Krilla for research assistance,
and the Hewlett Foundation, the National Institute of Aging and the Woodrow Wilson
School and Center for Economic Policy Studies of Princeton University for financial support.

Page 14