Who compares to whom? The anatomy of income comparisons in Europe
Andrew E. Clark* (Paris School of Economics and IZA)
Claudia Senik** (Paris School of Economics, University Paris-Sorbonne, IZA and IUF)
March 2009
Abstract. This paper provides unprecedented direct evidence on the intensity and
direction of income comparisons. Income comparisons are considered to be important
by a considerable majority of Europeans. They are associated with both lower levels of
self-reported satisfaction and a greater demand for income redistribution. Colleagues are
the most frequently-cited reference group, and the most innocuous one; comparisons to
friends are both less widespread and much more toxic for satisfaction. This set of
findings is consistent with information effects, as professional reference groups may
represent a source of information about one’s future prospects rather than a simple
benchmark for comparisons.
Keywords: Income Comparisons, Happiness, Redistribution, European Social Survey
JEL codes: D31, D63, I3, J31, Z13
*
Andrew Clark, PSE, 48 Boulevard Jourdan, 75014 Paris, France. Tel.: +33-1-43-13-63-29. E-mail:
Andrew.Clark@ens.fr. **Claudia Senik, PSE, 48 Boulevard Jourdan, 75014 Paris, France. Tel.: +33-1-4313-63-12. E-mail: senik@pse.ens.fr. The Norwegian Social Science Data Services (NSD) is the data
archive and distributor of the ESS data. We are grateful to CEPREMAP for financial support.
Who compares to whom? The anatomy of income comparisons in Europe
1. Introduction
There is by now a very substantial literature on social interactions and relative utility.
The key question in these literatures is: To whom do individuals compare, and with
whom do they interact? Outside of the laboratory, where the reference group can be
directly controlled (see Falk and Ichino, 2006, McBride, 2007 and Clark et al., 2009b),
researchers have to make non-testable assumptions about the relevance of different
reference groups for comparison purposes.
Almost all empirical papers have got round this problem by simply imposing a certain
reference group (e.g. Cappelli and Sherer, 1988, Clark and Oswald, 1996, MacBride,
2001, Bygren, 2004, Ferrer-i-Carbonnel, 2005, Luttmer, 2005, and Helliwell and
Huang, 2009). Only rarely are different reference groups tested (as in Knight and Song,
2006). Even scarcer is direct survey evidence on the groups to which individuals
compare. Knight and Song (2006) appeal to a survey of Chinese households and
showed that two-thirds of respondents report that their main comparison group consists
of individuals in their own village. In a very recent paper, Senik (2009) exploited a
survey of 25 post-Transition countries (LITS), where people were explicitly asked to
compare their current living standard with that of various groups of people that they
used to know before the transition started (i.e. before 1989). She finds that the most
important welfare impact comes from the deterioration of one’s living standard and
from under-performing relative to one’s former schoolmates or colleagues, rather than
from more general comparisons such as the individual’s self-ranking on the social
ladder.
In this paper we exploit new survey information from 22 European countries, which
contains direct measures of the intensity and the direction of income comparisons. This
information from Wave 3 of the European Social Survey (ESS) allows us to evaluate
the extent to which individuals compare their income against that of relevant others; it
also allows us to identify who these relevant others actually are.
-1-
With respect to how much income comparisons matter, empirical work almost always
calculates an average effect for the whole sample, read off as the estimated coefficient
on comparison income (y*) in a subjective well-being regression. Only rarely is
heterogeneity in the relationship between well-being and income addressed (one
exception is the latent class analysis in Clark et al., 2005). Here we can identify groups
who compare their income more and groups who compare their income less. We can
also observe whether the direction of comparisons (the relevant benchmarks) varies
across those groups.
The paper has three main aims in analysing this novel data: (i) Describe the extent of
income comparisons across Europe (do we compare our incomes?); (ii) Describe the
object of income comparisons across Europe (to whom do we compare?); and (iii) See
how income comparisons affect subjective well-being and the demand for redistribution
(does it matter?).
One implication of a well-being function that includes others’ income (y*) in the form
U=U(y, y-y*,…) is that greater comparisons (i.e. a higher value of U2) will increase or
decrease well-being depending on whether the individual’s income is greater or less
than y*. On the other hand, inequality aversion, as described in Fehr and Schmidt
(1999), supposes that individuals don’t like earning less than y* (disadvantageous
inequality), but nor do they necessarily like earning more (advantageous inequality):
they are averse to all kinds of outcome inequality. In this case, a greater weight on
comparisons will reduce well-being independently of the individual’s own position
relative to others.
The ESS dataset allows us to evaluate these kinds of predictions in a large-sample, nonexperimental way. However, we can also do somewhat more than that. While theory
provides us with some ideas about the degree of income comparisons, it does not say
much about whether the results are dependent on the object of such comparisons:
comparing to one reference group may be far more noxious in satisfaction terms than
comparing to another reference group. We are almost never able to draw this kind of
distinction empirically within the same dataset. Here we have the possibility of doing
so, and evaluating whether income comparisons matter more (for well-being) depending
on the object of the comparisons (i.e. to whom?).
-2-
The broad distinction that we will draw here is between non-Hirschman and Hirschman
(1973) types of comparisons. The first of these concerns the “standard” envy effect: we
are left less well-off when those in our reference group do better. The second nuances
this conclusion by noting that what happens to my reference group today may provide
me with information about what will happen to me tomorrow. Here others’ good fortune
likely continues to make me feel envious, but also has an element of good news about
myself in the future. The net effect may then be negative, zero or positive, depending on
the relative size of these status and signal phenomena. Of course, for such informational
effects to take place, people in the reference group need to share some of the
characteristics that will likely influence my own future trajectory.
Senik (2004 and 2008) provides evidence of Hirschman-type informational effects in
high mobility/uncertainty countries (Russia, the New Europe and the United States),
showing that individual life satisfaction is positively correlated with the income of
others with the same occupation. Clark et al. (2009a) appeal to linked employeremployee data to suggest that the net satisfaction effect of the income of other workers
in the same firm is actually positive. These papers both consider professional reference
groups. However, neither of them were able to evaluate the effect of these comparisons
to colleagues relative to comparisons to friends or family members. We can carry out
such calculations using the data available in the ESS.
Equally, Senik (2009) evaluates the different well-being effects of various kinds of
comparisons: to past living standards; former colleagues; former high-schoolmates;
parents; and social rank. However, she has no information about how widespread these
different types of comparisons are.
The ESS data allows us to put all of these elements together, and consider the effect of
income comparisons on individual well-being, depending on both their strength and the
type of comparison under consideration. We believe that this is the first example of this
type of analysis, especially in the context of a large-scale cross-country dataset.
The paper is organised as follows. Section 2 describes the intensity of income
comparisons across European countries, and Section 3 considers the incidence of the
different reference groups (are income comparisons carried out relative to colleagues,
-3-
family members, friends or others?). Sections 4 and 5 then dissect the effect of the
intensity and direction of income comparisons on well-being and the demand for
redistribution respectively. Finally, Section 6 concludes.
2. What do people say about income comparisons?
A set of novel and useful questions appeared in Wave 3 of the European Social Survey
(the ESS: freely available from http://www.europeansocialsurvey.org). The ESS is a
multi-country survey which has covered 30 different countries at various points over its
first three rounds. Wave 3 of the ESS contains a special module on well-being, in which
the key income comparison questions appeared. This wave, collected in 2006/2007,
covers 23 different countries (although the comparison question was not asked in
Cyprus). We restrict the sample to those of working age (16-65). On average, we have
just under 1500 observations per country, for a total sample size of 34 379.
A number of the questions in this well-being module deal with the broad questions of
income comparisons to others. First, all respondents who are in employment are asked
“How important is it for you to compare your income with other people’s incomes?”.
They answer using a showcard, where 0 corresponds to “Not at all important”, and 6 is
labelled “Very important”; none of the intervening values are labelled. The weighted
distribution of answers to this income-comparison question across 22 European
countries is shown in Table 1 below.
Table1. “How important is it to you to compare your income with other people’s incomes?”
Observations
Weighted %
Not at all important
1
2
3
4
5
Very important
5293
3783
3082
3768
3006
2095
1208
23.8
17.01
13.86
16.95
13.52
9.42
5.43
Total
Note: Weighted statistics.
22234
100
-4-
Table 1 shows that just under a quarter of Europeans say that it is not at all important to
compare their incomes to others. In general there is something of a left-skew in the
distribution of comparison intensity, but there are still substantial numbers of
individuals towards the top end of the distribution.
To illustrate the country distribution of the degree of income comparisons, we assign
the cardinal numbers zero to six to the individual replies detailed above, and calculate
the average intensity of income comparisons by country. As Table 1 indicates, countries
with higher average scores therefore compare their incomes more.
Figure 1 depicts these country averages, ordered from the least to the most comparisonsensitive. Although it is difficult to establish very precise country patterns, most Eastern
European countries are found on the right-hand side of this figure, whereas Switzerland,
Germany and Austria appear towards the left-hand side. In Figure 1, we also plot the
level of Real GDP per capita, taken from the latest available Penn Table (Heston et al.,
2006). Visual evidence does suggest the existence of a negative correlation between
average income per head and the average intensity of comparisons across countries,
suggesting that most comparisons are upward comparisons, and are made by the
relatively poor. This impression can be formalised by calculating the correlation
coefficient between the two series: this is -0.63, and significant at better than the one per
cent level. As will be shown in the next paragraph, the same observation can be made
within countries: people with lower incomes seem to compare more.
-5-
Figure 1. “How important is it to you to compare your income with other people’s incomes?”.
3.1
2.9
Mean importance of income
comparisons, left axis
Real GDP per capita, right
axis
2.7
40000
35000
30000
2.5
25000
2.3
20000
2.1
1.9
15000
10000
1.5
5000
Ne
t
he
rla
nd
Fi s
nl
an
Au d
Sw stri
itz a
er
lan
Be d
lg
i
Un Ge um
r
ite
m
d
Ki any
ng
do
De m
nm
ar
Ir e k
la
Po nd
rtu
g
No al
rw
a
Bu y
lg
ar
ia
Fr
an
c
Sw e
ed
en
Ru
ss
Sl ia
ov
en
ia
Po
lan
d
Sl
ov
ak Spa
Re in
pu
bl
ic
1.7
Notes: Average weighted income comparison by country (on a 0-6 scale). Real Gross
Domestic Product per Capita in 2004, in current dollar prices, source: Heston, Summers and
Aten, Penn World Table, 2006.
To formalise the analysis of the intensity of income comparisons, we run a regression of
the variable in Table 1 on a standard set of individual socio-demographic variables, as
well as country dummies. Income is measured at the household level, and is banded into
eleven categories. Income information is missing in three countries (Estonia, Hungary,
and Ukraine). As the dependent variable is ordinal, rather than cardinal, we should
ideally carry out ordered probit or logit analyses. It turns out that the results from
cardinal analysis using OLS are extremely similar (as in Ferrer-i-Carbonell and Frijters,
2004), and for ease of interpretation we choose to present these in Table 2.
-6-
Table 2. The Importance of Income Comparisons. OLS estimates
Important to compare income with other people's income
Coefficient
Standard errors
Household income (omitted: Less than 150 Euros)
150 to 300 Euros
300 to 500 Euros
500 to 1000 Euros
1000 to 1500 Euros
1500 to 2000 Euros
2000 to 2500 Euros
2500 to 3000 Euros
3000 to 5000 Euros
5000 to 7500 Euros
7500 Euros or more
-0.101
-0.178**
-0.274***
-0.238**
-0.288***
-0.314***
-0.332***
-0.338***
-0.323***
-0.338***
[0.148]
[0.081]
[0.094]
[0.089]
[0.092]
[0.082]
[0.089]
[0.089]
[0.099]
[0.110]
Occupation (omitted: Elementary professions)
Armed Forces
Legislators, senior officials and managers
Professionals
Technicians and associate professionals
Clerks
Service workers and shop and market sales workers
Skilled agricultural and fishery workers
Craft and related trades workers
Plant and machine operators and assemblers
Self-Employed (as opposed to employees)
-0.617**
-0.088
-0.019
-0.008
-0.045
-0.143
0.557***
0.016
-0.027
-0.557***
[0.230]
[0.121]
[0.092]
[0.085]
[0.104]
[0.110]
[0.181]
[0.104]
[0.101]
[0.044]
Sector (omitted: Industry)
Agriculture
Services
-0.297***
-0.017
[0.100]
[0.035]
Male
-0.010
[0.037]
Age (omitted: 16-25)
25-50
Over 50
0.035
-0.163*
[0.087]
[0.093]
Education (omitted: Primary education)
Did not complete primary education
Lower secondary or second stage of basic
Upper secondary
Post-secondary, non-tertiary
First stage of tertiary
Second stage of tertiary
-0.003
-0.161*
-0.205**
-0.109
0.070
0.146
[0.193]
[0.091]
[0.090]
[0.098]
[0.097]
[0.147]
Marital status (omitted: Never in couple)
Married
Separated
Widowed
Ever given birth to child
-0.111**
-0.206***
-0.214*
0.014
[0.047]
[0.050]
[0.112]
[0.042]
-7-
Citizen
0.028
[0.069]
Country dummies (omitted: Austria)
Belgium
Bulgaria
Switzerland
Germany
Denmark
Spain
Finland
France
Great Britain
Ireland
Netherlands
Norway
Poland
Portugal
Russia
Sweden
Slovenia
Slovakia
-0.022
0.177
0.026
0.067**
0.190***
0.594***
-0.073**
0.222***
0.109***
0.133***
-0.161***
0.225***
0.480***
0.128**
0.306***
0.332***
0.496***
0.818***
[0.032]
[0.106]
[0.039]
[0.028]
[0.039]
[0.017]
[0.032]
[0.035]
[0.027]
[0.041]
[0.024]
[0.042]
[0.066]
[0.051]
[0.076]
[0.035]
[0.030]
[0.055]
Constant
2.664
[0.152]
Observations
15543
R-squared
0.037
Log likelihood
-31131
Notes: *, ** and *** denote significance at the 10%, 5% and 1% levels respectively.
Standard errors in parentheses are clustered by country.
The results show that it is those living in households with lower levels of income who
actually compare their incomes more. Those in the sixth to the tenth deciles of
household income provide income comparison responses that are on average about onethird of a point lower on the one to six income-comparison scale.
The self-employed (who constitute 11% of the sample) compare their incomes
significantly less than do employees. In terms of industry, comparisons are less
important in Agriculture than in Industry or Services. Those over 50 years old compare
less, and the single compare more. There is no significant gender difference in the
intensity of income comparisons. The country dummies are very significant. They show
that, compared to Austria, respondents in the UK and Ireland, Southern Europe (Spain
and Portugal) and most countries of Eastern Europe (Poland, Russia, Slovenia, and
Slovakia) attach more weight to comparisons. This ranking of the estimated coefficients
-8-
on the country dummies is similar to that illustrated in Figure 1. In a separate regression
where countries were grouped into more aggregated geographical zones, we find that
Scandinavians (Denmark, Finland, Norway, and Sweden) compare less on average than
do those living in central Continental Europe (Austria, Belgium, Switzerland, Germany,
France and the Netherlands).
3. Who Compares to Whom?
The general intensity of income comparisons, described above, is difficult to interpret
precisely without knowing to whom people actually compare. If comparison
benchmarks are endogenous, as suggested in the literature, is likely that the reference
group will depend on the respondent’s age, position in their life cycle, labour market
status, and so on. The third wave of the ESS survey includes the following question:
“Whose income would you be most likely to compare your own with? Please choose
one of the groups on this card: Work colleagues/ Family members/ Friends/ Others/
Don’t compare/ Not applicable/ Don’t know.” The distribution of answers to this
question is shown in Table 3.
Table 3. “Whose income would you be most likely to compare your own with?”
Observations
Work colleagues
6 159
Family members
929
Friends
2 382
Others
1 192
Don't compare
5 185
Note: Weighted statistics.
Weighted %
38.93
6.03
14.94
7.39
32.72
Of those who identify a comparison group, most people say that they compare to their
work colleagues or (to a far lesser extent) their friends. However, 33% of respondents
say that they do not compare, which is consistent with the results in Table 1, where 24%
of respondents answered that comparisons are not at all important, and 17% chose 1 on
the 7-step scale for the importance of income comparisons. This is also consistent with
the partial correlation between comparison benchmarks and the general importance of
comparisons: those who chose “Don’t compare” in Table 3 also declare that they attach
-9-
significantly less importance to comparisons: controlling for the same right-hand side
variables as in Table 2, the partial correlation coefficient between the two is
significantly negative (not shown). Partial correlations also suggest that the greater the
intensity of income comparisons, the higher is the probability that the respondent
designate colleagues as the comparison group.
Regarding the determinants of social comparisons, it appears that, as suggested by the
literature, reference groups are correlated with the respondent’s socio-economic
situation. Table 4 presents the results of multinomial logit regressions for the probability
of reference-group choice. The coefficients represent the probability of choosing the
group in question relative to the omitted group (“work colleagues”).
Table 4. “Whose income would you be most likely to compare your own with?” Multinomial logit
regression. Omitted category: “Work colleagues”.
Family members
Friends
Others
Coefficient Std. Err
Coefficient Std. Err
Coefficient Std. Err
Household income (omitted: Less than 150 Euros)
150 to 300 Euros
0.11
0.29
0.06
0.12
0.19
-0.36
300 to 500 Euros
0.20
0.23
0.10
0.00
0.27
0.26
500 to 1000 Euros
0.20
0.14
-0.14
0.29
0.40
0.26
1000 to 1500 Euros
0.43
0.24
0.26
0.17
-0.19
0.32
1500 to 2000 Euros
0.14
0.28
0.18
0.15
-0.25
0.31
2000 to 2500 Euros
0.28
0.23
0.09
0.16
-0.58
0.34
2500 to 3000 Euros
0.39
0.25
0.13
0.17
-0.34
0.33
3000 to 5000 Euros
0.37
0.25
-0.03
0.19
-0.42
0.33
5000 to 7500 Euros
0.27
0.33
0.03
0.20
-0.58
0.32
7500 Euros or more
-0.08
0.44
0.06
0.23
-0.51
0.33
Occupation (omitted: Elementary professions)
Armed Forces
-1.70
1.07
0.30
0.40
0.08
0.58
Legislators, senior officials and managers
0.23
0.04
0.13
0.12
-0.79
0.41
Professionals
0.18
0.11
0.03
0.18
-0.92
-0.30
Technicians and associate professionals
0.16
0.10
-0.05
0.17
-0.83
-0.23
Clerks
0.13
-0.14
0.14
0.21
-0.66
-0.39
Service workers and shop and market sales
0.14
-0.01
0.12
0.20
0.14
-0.41
workers
Skilled agricultural and fishery workers
-0.26
0.33
0.18
0.30
0.41
0.36
Craft and related trades workers
0.17
0.11
-0.12
0.15
-0.47
-0.24
Plant and machine operators and assemblers
0.20
0.08
0.14
-0.56
-0.21
-0.34
Self-Employed (as opposed to employees)
0.54
0.14
0.93
0.12
0.86
- 10 -
0.13
Sector (omitted: Industry)
Agriculture
Services
Male
Age (omitted: 16-25)
25-50
Over 50
Education (omitted: Primary education)
Not completed primary education
Lower secondary or second stage of basic
Upper secondary
Post-secondary, non-tertiary
First stage of tertiary
Second stage of tertiary
Marital status (omitted: Never in couple)
Married
Separated
Widowed
Ever given birth to child
Citizen
Country (omitted: Austria)
Belgium
Bulgaria
Switzerland
Germany
Denmark
Spain
Finland
France
Great Britain
Ireland
Netherlands
Norway
Poland
Portugal
Russia
Sweden
Slovenia
Slovakia
0.36
0.08
0.30
0.13
-0.17
0.15
0.15
0.07
0.15
0.03
0.22
0.08
-0.48
0.09
0.07
0.07
0.10
0.09
-0.57
-0.66
0.15
0.15
-0.78
-1.25
0.10
0.15
0.15
0.22
0.14
0.15
0.25
-0.15
-0.17
-0.23
-0.06
-0.01
0.27
0.16
0.18
0.21
0.21
0.31
-0.08
-0.29
-0.27
-0.33
-0.26
-0.04
0.33
0.10
0.08
0.11
0.10
0.16
-0.37
0.13
-0.09
0.05
0.11
0.30
0.25
0.20
0.20
0.17
0.21
0.28
0.31
-0.12
-0.20
0.09
0.18
0.34
-0.32
-0.27
0.09
0.08
0.08
0.23
0.01
-0.01
0.07
0.11
0.13
0.31
0.24
0.11
-0.12
0.09
0.20
0.09
-0.26
0.16
0.21
0.11
0.17
0.21
-0.17
-1.36
-0.35
-0.56
-0.46
0.32
0.36
-0.02
0.10
0.22
-0.36
-1.08
0.47
-0.38
-0.43
-0.73
-0.40
-0.90
-0.61
0.08
0.19
0.09
0.08
0.09
0.05
0.07
0.07
0.07
0.07
0.04
0.11
0.14
0.07
0.17
0.07
0.06
0.15
0.31
-0.39
0.12
0.08
-0.23
-0.37
0.10
-0.12
-0.72
0.11
-0.10
-0.36
-0.43
0.67
-1.41
0.16
-1.12
-0.60
-0.90
0.25
0.07
0.12
0.09
0.06
0.08
0.04
0.06
0.06
0.07
0.08
0.05
0.09
0.10
0.04
0.09
0.06
0.04
0.08
0.22
0.56
1.26
0.07
0.64
0.12
0.59
0.69
0.25
0.31
0.16
0.35
0.02
0.77
-0.33
-0.67
-0.43
-0.26
0.09
-2.20
0.06
0.19
0.07
0.06
0.06
0.03
0.06
0.07
0.05
0.07
0.04
0.07
0.13
0.07
0.17
0.06
0.06
0.14
0.38
- 11 -
Observations
10374
Pseudo R2
0.06
Log Likelihood
-10783
Notes: Multinomial logit regressions of the answer to the question “Whose income would you be most
likely to compare your own with?” The possible answers are Work colleagues (the omitted category),
Family members, Friends, Others, Don’t compare, Not applicable, and Don’t know. The regression
omits those who say that they “Don’t compare”. Standard errors in parentheses are clustered by country.
Bold coefficients are significant at the five per cent level.
Table 2 suggested that the self-employed compare less in general. Table 4 nuances this
result: it shows that they are significantly less likely to compare to their colleagues, but
more likely to compare to family members, friends and “others”. Men compare less to
family members than do women. Comparisons to colleagues (and “others”) increase
after the age of 25, whereas the opposite is true of comparisons to family members and
friends. Higher levels of education are positively correlated with comparisons to
colleagues, but reduce comparisons to friends. The married compare more to colleagues
and family members but less to friends. Respondents with children compare more to
family members. These results are consistent with the choice of comparison benchmark
being closely related to the type of regular social interactions that are experienced.
In terms of geography, those in central Continental Europe compare much more to their
colleagues than do respondents elsewhere. Spaniards and Irishmen compare
significantly more to family members, as do Scandinavians. Those in Eastern Europe
compare significantly less to their family than elsewhere. Esping-Andersen (1999) has
proposed a classification of European countries in terms of their system of social
protection. Southern European countries appear to rely much more heavily on family
solidarity than other groups of countries. The primary importance of comparisons with
family members in this group of countries is consistent with this classification.
To go one step further, we also used another question in the survey: “How often do you
meet socially with friends, relatives or work colleagues?”. The distribution of answers
to this question is shown in the Appendix. The more often people declare that they meet
socially, the more likely they are to declare that they compare to friends, and the less
likely they are to compare to colleagues or family members (and to “others”). Income
comparisons are also less important for those who meet socially more often.
- 12 -
In summary, when talking about “income comparisons”, what most people have in mind
is comparisons to colleagues, rather than to other non-professional groups. But beyond
this general finding, comparison benchmarks are also endogenous: people compare to
those that they meet the most often. We now ask whether all of the comparison groups
are identical in terms of their effects of subjective well-being.
4. The Effect of Comparisons on Well-Being
Comparisons are important, and comparison benchmarks vary according to the
individual’s situation in the labour market and society. But what is the well-being effect
of comparisons? To investigate, we analyse the relationship between life satisfaction, on
the one hand, and the intensity and direction of comparisons on the other.
Respondents answered the question “How happy are you?” by ticking one response on
an 11-step ladder, where 0 was labelled “extremely unhappy” and 10 “extremely
happy”. The overall distribution of responses is shown in Table 5 below.
Table 5. “How happy are you?”
Extremely unhappy
1
2
3
4
5
6
7
8
9
Extremely happy
Total
Observations
115
142
280
545
642
2142
1893
4395
6836
4200
2306
Weighted %
0.49
0.6
1.19
2.32
2.73
9.12
8.06
18.7
29.09
17.88
9.81
23496
100
Note: Weighted statistics.
We first check that the life satisfaction function is “well-behaved” in terms of the usual
correlates of subjective well-being (see Clark et al., 2008b). Self-declared happiness
- 13 -
was indeed higher for richer, younger people, the married, women (although not
significantly so in Southern and Eastern Europe) and for more-skilled workers. The
ranking of regions in terms of happiness is, in descending order: Scandinavia, the
British Isles, Continental Europe, Southern Europe, and finally, Eastern Europe.
In order to make the results more directly interpretable, we sometimes appeal to an
alternative specification of the happiness estimate: we dichotomize the happiness
variable, coding those who declare that they stand at over 7 on the 11-step happiness
ladder as 1 (56% of the sample), and the rest as 0. We call this new dichotomized
variable “high happiness”.
4.1 Those who compare more are less happy
Table 6 illustrates the significantly negative impact of comparison intensity on
subjective happiness. Comparisons here are measured cardinally from 0 to 6; using a
dummy variable for comparisons being important produces the same qualitative results.
The regression estimates using the dependent variable “high happiness” and a dummy
for comparisons being “very important” (i.e. over 4 on the 7-step ladder) show that
those saying that comparisons are “very important” are 7% less likely to be very happy.
We can check this negative relationship between the intensity of comparisons and
happiness by using a number of different notions of well-being present in the survey,
namely “satisfaction with life as a whole”, “satisfaction with how life turned out so far”,
subjective general health, “feeling of depression during the past week”, “feeling always
optimistic about my future”, as well as more economic notions of satisfaction such as
“satisfaction with one’s standard of living”, “difficulty of living with present income”,
“satisfaction with job” and feeling that one “gets paid appropriately, considering efforts
and achievements” (see the Appendix for the descriptive statistics regarding these
variables). As shown in Table 6, the greater is the importance that people attach to
comparisons, the lower they rank on these different satisfaction scales.
- 14 -
Table 6. The Welfare Effect of Comparison Intensity. OLS Estimates of Various Subjective Satisfaction Variables
How happy are you
Important to compare
Observations
R-squared
-0.095***
[0.013]
15502
0.178
How satisfied
with life as a
whole
-0.122***
[0.015]
15520
0.234
Satisfied with how
life turned out so far
Health
Feeling
optimistic
-0.074***
[0.011]
15523
0.176
-0.012***
[0.004]
15534
0.156
-0.039***
[0.004]
15510
0.058
Felt depressed, how
often past week
Satisfied with
How satisfied with Paid
Living
standard of
job
appropriately comfortably
living
Important to compare
0.021***
-0.113***
-0.124***
-0.126***
-0.039***
[0.003]
[0.010]
[0.013]
[0.008]
[0.003]
Observations
15496
15530
15523
15487
15524
R-squared
0.086
0.302
0.085
0.134
0.377
Notes: Each column corresponds to a separate regression. Controls: income, occupation, self-employed,
sector, age, education level, marital status, children, citizen dummy, and country dummies. *, ** and ***
denote significance at the 10%, 5% and 1% levels respectively. Standard errors in parentheses are
clustered by country.
It is of interest to note that four of the groups who compare their income the most in
Table 2 (those with lower income, employees, those aged under 50, and singles) are
often found to report lower levels of well-being in empirical analyses. This is entirely
consistent with Table 6’s suggestion that such income comparisons render individuals
unhappy on average. It is thus possible that the degree of comparison intensity be an
omitted variable that underlies some of the common correlations in the well-being
literature.
4.2 Which comparisons hurt the most?
With reference to those who declare that they do not compare, all comparisons are
welfare-reducing, but not equally so: the results in Table 7 show that comparisons to
friends and “other” are twice as painful as comparisons to colleagues and family. The
same results hold after dropping those who do not compare: those who declare that they
compare to colleagues are significantly happier than those who choose friends (or
“others”) as their benchmark. Those who declare that they compare to their colleagues
are 4% more likely to declare that they are very happy than those who choose their
friends as a benchmark (Table 7). This actually nuances the above finding that increased
social activity reduces the importance of income comparisons. While this is true, the
- 15 -
remaining comparisons are more likely to be friends, and this is the most painful type of
comparison for well-being.
- 16 -
Table 7. Happiness and comparison benchmarks. OLS estimates of self-declared
happiness.
Whose income would you be most
likely to compare your own with?
Work colleagues
0.138***
[0.040]
0.143*
[0.081]
Observations
R-squared
log likelihood
-0.169***
[0.034]
-0.162*
[0.088]
-0.313***
[0.048]
-0.406***
[0.088]
15421
0.172
-29050
Omitted category
Don’t compare
Friends
Family members
Friends
Others
-0.104*
[0.051]
10348
0.179
-19254
Notes: Column 1: regression over the entire sample. Omitted category: “Don’t compare”.
Column 2 drops those who reply that they “don’t compare”. Omitted category: “Friends”.
Controls: income, occupation, self-employment, sector, age, education level, marital status,
children, citizen dummy, and country dummies. Standard errors in parentheses are clustered by
country. *, ** and *** denote significance at the 10%, 5% and 1% levels respectively.
4.3. Heterogeneity
Are these effects the same for everybody, or is there some heterogeneity in the welfare
effect of comparisons? To elucidate, we interacted the answer to the comparison
questions with dummy variables indicating the socio-professional status of respondents.
As Ai and Norton (2003) have shown that the coefficients in interactions in ordered
logit or probit models are not easily interpretable, we ran a simple OLS estimate of
happiness on the interacted terms, controlling for the usual socio-demographic variables
and main effects.
Regarding the impact of the intensity of comparisons, the resulting estimates show that
comparisons are less painful for the youngest group (aged up to 25), those in higher
professions (senior managers), and service workers and machine operators (as compared
to elementary occupations). They are also less painful in the UK and Ireland. None of
the other interactions (with sex, income and employment status - self-employed versus
employee) were significant.
- 17 -
Turning to the impact of different directions of comparisons, interaction effects suggest
that comparisons to colleagues are particularly painful for the older (the coefficient on
the interaction with the 25-50 age category is -0.152 [0.086] and that with the 51-65
category is -0.164 [0.082]) and the poorer (the coefficient on the interaction with those
who earn less that the median wage is -0.194 [0.052]), but less so in higher occupations.
Income comparisons to family members are more painful for Southern Europeans and
older people (over 50 years). Income comparisons to friends are significantly more
painful in Great Britain than in Continental Europe; they are significantly less painful
for those aged over 50 (which contrasts with comparisons to colleagues), and for certain
occupation categories such as professionals and service workers. The interaction terms
were never significant for comparisons to “others”.
This set of findings rules out the idea that people endogenously choose their comparison
benchmark in order to maximize their well-being. For instance, we found that Southern
Europeans compare more to family members even though this is the most painful type
of comparison for them. People seem to compare to those they interact with often, rather
than those to whom they enjoy comparing their own outcomes.
These results concerning the welfare impact of the intensity and the direction of
comparisons also naturally raise the question whether those for whom comparisons are
very important are less happy when they compare to a certain group rather to another.
Experiments along theses lines did not reveal any interesting results: comparison
intensity reduces well-being pretty much independently of the reference group.
5. Income comparisons and the demand for redistribution
Do painful comparisons make people more favourable to compensating measures, such
as income redistribution?
Here we use the following question: Using this card, please say to what extent you
agree or disagree with each of the following statement: “The government should take
measures to reduce differences in income levels”.
- 18 -
Table 8. “The government should take measures to reduce differences in income levels”
Frequency
Strongly agree
Agree
Neither agree nor disagree
Disagree
Strongly disagree
Weighted %
6433
9709
3655
2892
602
27,62
41,69
15,69
12,42
2,59
Note: Weighted statistics. Sample: age between 16 and 66.
A preliminary simple estimate of the demand for income redistribution by the State
showed that Scandinavians are less in favour of income distribution, as compared to
those in Continental Europe, while Southern and Eastern Europeans are more in favour.
The richer categories, those in higher occupations, the self-employed, men, the younger,
the married, the more educated and those who have never had children are less in favour
of income distribution.
Table 8 shows that the more people consider income comparisons to be important, the
more they are in favour of income redistribution by the State. However, excluding those
who declare that they “don’t compare”, Table 9 also shows that it is comparisons to
family members and “others”, much more than to colleagues, that prompt the demand
for income redistribution.
- 19 -
Table 9. Comparisons and the demand for income redistribution by the State.
OLS estimates of the demand for redistribution.
Important to compare
income with other people's
income
0.027***
[0.008]
Whose income would you be
most likely to compare
your own with?
Omitted category: “others”
Work colleagues
-0.074**
[0.033]
Family members
0.019
[0.047]
Friends
-0.074
[0.046]
Observations
15411
Observations
10307
R-squared
0.150
R-squared
0.158
Log likelihood
-21689
Log likelihood
-14329
Notes: Column 1 corresponds to a regression over the entire sample; Column 2 drops those who
reply that they “don’t compare”. Omitted category: “others”. Dependent variable: Agree that
“The government should take measures to reduce differences in income levels”. Other controls:
income, occupation, self-employed, sector, age, education level, marital status, children, citizen
dummy, and country dummies. Standard errors in parentheses are clustered by country. *, **
and *** denote significance at the 10%, 5% and 1% levels respectively.
The demand for redistribution therefore seems to follow the same patterns as the
welfare effects of comparisons: the intensity of comparisons reduces subjective
happiness and increases the demand for redistribution. Comparisons to colleagues are
the least painful and also produce the weakest correlations with the demand for income
redistribution.
6. Conclusions
This paper has analysed unprecedented direct evidence on the intensity and direction of
income comparisons. Income comparisons are acknowledged as important by the
majority of Europeans. They are associated with lower levels of self-declared happiness,
and this negative impact increases with the age of the respondent but falls with their
income. Colleagues are the most frequently-cited reference group. They are also the
- 20 -
most innocuous, i.e. that which produces the smallest fall in happiness; comparisons to
friends are much more damaging for happiness.
Cultural differences are apparent: the negative welfare effect of comparisons is larger in
Continental countries and smaller in the British Isles, which is also the region in which
comparisons most frequently concern colleagues. Southern Europeans seem to be more
family-oriented: they compare more to family members and suffer more from this type
of comparisons than do inhabitants in other parts of Europe.
Income comparisons are also associated with a greater demand for income
redistribution. It is comparisons to family members and “others”, much more than
comparisons to colleagues, that prompt the demand for income redistribution.
Finally, the choice of comparison benchmarks seems to be endogenous, being closely
related to the type of regular social interactions that respondents experience. For
example, those who “socialize” more compare less to their colleagues.
The above empirical findings are redolent of an information effect à la Hirschman
(1977). Senik (2004, 2008) and Clark et al. (2009a) have produced evidence consistent
with professional reference groups acting as a source of information regarding one’s
future prospects, as well as being a simple benchmark for comparisons. This reflects
that individuals in these groups share the same productive characteristics as the
respondent, and hence the same expected earnings profile. This is obviously less true of
other non-professional groups, such as family members or friends. This could explain
why people mostly compare to their colleagues (in order to acquire information about
their professional future) and why these comparisons are not as damaging to welfare as
comparisons to family members, friends or “other” groups.
- 21 -
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- 24 -
Appendix. Weighted Descriptive Statistics
Sample: respondents aged 16-65 years old.
Observations
Percentage
Household income
Less than 150 Euros per month
150 to 300 Euros
300 to 500 Euros
500 to 1000 Euros
1000 to 1500 Euros
1500 to 2000 Euros
2000 to 2500 Euros
2500 to 3000 Euros
3000 to 5000 Euros
5000 to 7500 Euros
7500 Euros or more
952
1221
1765
2459
2375
2419
2407
2478
4387
2028
1101
4.04
5.17
7.48
10.42
10.07
10.25
10.20
10.50
18.60
8.59
4.67
Occupation
Armed forces
Legislators senior officials and managers
Professionals
Technicians and associate professionals
Clerks
Service workers and shop and market sales workers
Skilled agricultural and fishery workers
Craft and related trades workers
Plant and machine operators and assemblers
Elementary occupations
71
1869
3245
3853
2338
3427
625
2709
1704
2050
0.33
8.54
14.82
17.60
10.68
15.65
2.85
12.38
7.78
9.36
Sector (NACE)
Agriculture
Industry
Services
871
5815
14948
4.03
26.88
69.10
Marital status
Married
Separated
Widowed
Never in couple
13901
2244
579
6768
59.17
9.55
2.46
28.81
Had child
Citizen
23294
23321
68.25
96.14
Father’s employment status when resp. was 14
Employee
Self-employed
Not working
Father dead/ absent
Note: Weighted statistics.
16149
4471
791
1354
70,94
19,64
3,47
5,95
- 25 -
Weighted number of observations per country/regions
European regions :
Continental British
Austria
Belgium
Switzerland
Germany
France
Netherlands
United Kingdom
Ireland
Portugal
Spain
Norway
Denmark
Finland
Sweden
Bulgaria
Poland
Russia
Slovenia
Slovakia
Note: Weighted statistics.
1276
1272
1159
1700
1487
1391
Southern
Scandinavian
Eastern
1491
1081
847
915
1449
1082
1374
1481
878
1185
1670
959
895
Subjective Variables
Obs.
Mean
Std. Dev.
Min
Max
Happy
Comparisons are important
I compare to colleagues
I compare to family
I compare to friends
I compare to others
I compare to other people
Redistribute income
Often meet socially with friends. relatives or colleagues
Satisfied with life as a whole
Satisfied with how life turned out so far
Health
Feel optimistic about future
How often felt depressed past week
Satisfied with standard of living
Satisfied with job
Paid appropriately considering efforts and achievements
Living comfortably on present income?
Note: Weighted statistics.
23235
16045
15959
15959
15959
15959
15959
23027
23257
23274
23275
23305
23241
23202
23284
16182
16133
23276
7.38
2.30
0.39
0.06
0.15
0.07
0.33
3.79
5.12
7.04
7.06
3.90
3.71
1.45
6.73
7.16
3.08
3.06
1.89
1.83
0.49
0.24
0.36
0.26
0.47
1.06
1.50
2.23
1.93
0.85
0.90
0.67
2.25
2.09
1.14
0.86
0
0
0
0
0
0
0
1
1
0
0
1
1
1
0
0
1
1
10
6
1
1
1
1
1
5
7
10
10
5
5
4
10
10
5
4
- 26 -
“How often do you meet socially with friends, relatives or work colleagues?”
Never
Less than once a month
Once a month
Several times a month
Once a week
Several times a week
Every day
Note: Weighted statistics.
Observations
Weighted Percentage
109
831
1 188
2 998
3 052
5 028
2 618
0.68
5.41
7.60
18.96
19.35
31.42
16.58
- 27 -