GCOE Discussion Paper Series
Global COE Program

Human Behavior and Socioeconomic Dynamics
Discussion Paper No. 299

The Joneses in Japan: Income Comparisons and Financial
Satisfaction

Andrew E. Clark, Claudia Senik and Katsunori Yamada

March 2013

GCOE Secretariat
Graduate School of Economics

OSAKA UNIVERSITY

1-7 Machikaneyama, Toyonaka, Osaka, 560-0043, Japan

The Joneses in Japan: Income Comparisons and Financial Satisfaction*
Andrew E. Clark† (Paris School of Economics - CNRS)Claudia Senik‡ (Paris School of Economics and University Paris-Sorbonne)
Katsunori Yamada§ (Institute of Social and Economic Research, Osaka University)

March 2013

Abstract
This paper uses Japanese data which includes measures of self-declared satisfaction,reference-group income, and the direction and intensity of income comparisons.
Relative to Europeans, the Japanese compare more to friends and less to colleagues, andcompare their incomes more. The relationship between satisfaction and others' income
is negative, and more negative for those who report greater income comparison intensity.
A self-reported measure of others' income does better than cell-mean income in
explaining satisfaction, and would arguably make a useful addition to many existing
surveys.

Keywords: Income Comparisons, Reference-Group Income, Reference Groups,
Satisfaction.
JEL codes: D31, D63, I3, J31.
*

Financial support from CEPREMAP, the Global COE program of Osaka University
and the Grants-in-Aid for Scientific Research, the Japan Society for Promotion of
Science, is greatly appreciated.
† PSE, 48 Boulevard Jourdan, 75014 Paris, France. Tel.: +33-1-43-13-63-29. E-mail:Andrew.Clark@ens.fr.

‡ PSE, 48 Boulevard Jourdan, 75014 Paris, France. Tel.: +33-1-43-13-63-12. E-mail:senik@pse.ens.fr.
§ ISER, Osaka University, Mihogaoka 6-1, Ibaraki 567-0047, Japan. Tel. +81-6-68798566. E-mail: kyamada@iser.osaka-u.ac.jp.

The Joneses in Japan: Income Comparisons and Financial Satisfaction
Andrew E. Clark, Claudia Senik and Katsunori Yamada

1. Introduction
Work on subjective well-being and income comparisons in economics has increased
exponentially since the first labour-market based contributions of Cappelli and Sherer(1988), Clark and Oswald (1996) and Hamermesh (1977). While the broad idea that
relative standing matters is now arguably accepted by many, it is still pretty much open
season on the key questions of "How much" and "To whom".
We here contribute to this research area by using a novel Japanese dataset in which boththe intensity and direction of income comparisons are measured. In terms of the latter,
Japanese respondents compare mostly to their friends, followed by their colleagues.
Regarding comparison intensity, we suggest that the Japanese are more comparison
conscious than are Europeans.
We could establish the relationship between these two relatively unusual measures andindividual satisfaction, as in Clark and Senik (2010). We instead here show that these
two simple measures substantially mediate the effect of self-declared reference-group
income. Those who say that they compare more indeed suffer more as others' income
rises. Also, our self-reported measure of what "others like you earn" is far more salient
for those who compare to colleagues than for those who compare to family or friends,say.
Last, we compare our self-reported measure of what others earn to researcherconstructed cell-mean measures of reference-group income, both from within the sameinternet data and matched in from external sources. While some of the researcherconstructed variables attract the right-signed coefficients in satisfaction regressions,overall the fit from the cell-mean data is far worse than that from regressions using thevalues from a simple question on others' earnings. This suggests that such a question
may be a useful addition to survey questionnaires.

-1-

The remainder of the paper is organized as follows. Section 2 describes the Japanesedataset which we use here, and Section 3 covers in particular the well-being and income
comparison questions (where the latter are still very much a novelty in social science).
Section 4 then presents our main results regarding satisfaction and income comparisonsin Japan. Last, Section 5 concludes.

2. Data
The internet survey
Our data set is taken from an original web-based survey conducted in February 2010.1
This survey was carried out by a Japanese consumer monitoring company, Nikkei
Research Inc. under the direction of one of the authors. As part of the Nihon Keizai
Shimbun Group (NIKKEI), this company is considered to be trustworthy and neutral,
which makes it a suitable choice for data collection for academic research. To ensure
the reliability of its research data, the subjects who register for consumer monitoring are
subject to monthly screenings so that individual information remains up to date anddouble registrations are avoided.
The incentives for respondent participation in this particular project were provided bycash vouchers.2 The invitation email stated that the incentive would be paid on a lotterybasis: 800 winners among those who completed the survey would receive 500 JPY perperson. Subjects were ensured anonymity. Those who wished to participate were
instructed to follow the link in the email which directed them to our stand-alone survey
website. The survey was open for one week (February 18th-25th 2010), and 14,370
subjects completed the survey. This approach reduces the bias inherent in one-day

1

The recent use of the Internet to carry out social surveys is becoming increasingly widespread. Recent
work using web-based surveys includes Viscusi et al. (2008), Ida and Goto (2009), Olsen (2009) and
Bech et al. (2011).
2

We used cash vouchers rather than point vouchers that can be redeemed against specific goods. The
latter is considered to lead to potential bias, as particular respondent types (those interested in the goodfor which the points are destined) are more likely to respond to the survey. If these characteristics are notorthogonal to the right-hand side variables under consideration (here, comparison effects), the estimatedcoefficients will be biased. Our use of cash incentives avoids this problem.

-2-

research, adopted by many other research companies for cost reasons. In one-day
research, subjects are chosen on a first-come first-served basis, leading to potential bias
from a potentially non-representative sample.
Nikkei Research, Inc. and the researchers commissioning the survey agreed on at least
10,000 survey respondents. Considering the response rates in seven similar academic
choice-experiment surveys run by the same company in 2008 and 2009, invitation
emails for this survey were sent to 60,482 subjects (out of over 160,000 registered in the
Nikkei Database).3 The subjects, aged between 20 and 65, were chosen via stratified
random sampling, so that the sample age profile mirrored Japanese census statistics. We
could not match by education, as subjects do not have to declare this information when
they register. The email specified that the survey was being carried out for research
purposes and followed the disclosure requirements for research involving human beings
provided with incentives as set forth by the ethics committee.
The survey consisted of three parts. The first collected information on satisfaction,
which is our key dependent variable in this paper, and the second posed the
hypothetical-choice questions over own and others' income which were analysed in
Yamada and Sato (2010). The final section then consisted of questions about individual
demographic characteristics, including age, sex, education, job, marital status, type of
housing, residential area, and annual pre-tax personal income in 2009.
Table 1 compares the characteristics of our analysis sample, the construction of which is
described below, to the overall statistics in the Japanese population. Columns (1) and(2) refer to men and women respectively in our analysis sample. Column (3) thenpresents descriptive statistics from the whole Nikkei Database, while the last column
shows the figures for men and women in national Census statistics.
Table 1 shows that the stratified random sampling worked, in that the age and gender
structure of our sample is similar to that in national statistics. Women account forsomething over 50 percent of both our sample and national statistics. There is howeverconsiderable under-representation of women who are divorced, separated or widowed.

3

Broadband Internet access is pervasive in Japan.

-3-This difference from national statistics comes about because the latter include everyone
aged over 15. As the average length of life for Japanese women is around 87 (with thatof men being around 78), women tend to be widowed towards the end of their lives,
which is reflected in the rate of female divorce/separation/widowhood in national
statistics. However, as our sample only includes those who are aged up to 65, the rates
of divorce/separation/widowhood for both men and women are lower than those innational statistics.
Only one percent of our male sample has their highest completed level of education as
middle school, with 18 percent completing high school, 10 percent having some college,
and the remaining 70 percent of the sample holding college or graduate degrees. The
same high levels of education are found in the female sample. There is thus an obvious
over-sampling of the better-educated here, likely reflecting a digital divide in terms ofinternet access or use. Analogously, we see from Table 1 an under-sampling of students
and the unemployed, although for these two groups the difference from Census statistics
is less severe. The cause of this gap is less clear, although there could again be a digital
divide by labour-force status. Last, in terms of residential area there is clear oversampling from the Kanto region, which includes Tokyo, and to a lesser extent from theKansai region, which contains Osaka. It could be argued that internet access is easier inurban areas.
Our sample is thus not entirely representative with respect to education and residential
area. It is not clear how this might bias any relative utility effect. Higher education may
cause individuals to become more altruistic, as argued in Johansson-Stenman et al.
(2002). At the same time, education is positively correlated with earnings, which in turn
may affect attitudes towards others. With respect to the residential area, Japanese urban
dwellers are sometimes said to have become rather indifferent to their neighbours, sothat social comparisons may be less salient for this group. On the other hand, they may
well encounter others much more often, leading to feelings of rivalry. The European
evidence in Clark and Senik (2010) showed that those with Internet access, city-4-

dwellers, and the more educated were more comparison-conscious. As such, our sample
dataset may well capture the upper bound of comparison intensity.4
Construction of the analysis sample
The average time taken to complete the survey, including the hypothetical questions on
preferences over combinations of own and others' income, was just over 9 minutes, witha median value of just over 6 minutes.5 We discard information from subjects with acompletion time of under four minutes (968), following feedback from a withincompany pilot test supplied by NIKKEI. In the context of weeding out spurious
responses, we also pay attention to the answer patterns supplied to the hypotheticalchoice questions. One easy way for subjects to finish the survey quickly is by providing
the same answers to all of these choice questions, which are arguably the most difficult
part of the survey. We therefore drop individuals who gave the same number for all fiveof the consecutive questions in the choice tasks (2,218). This reduces the original
sample to 10,988 respondents.
We also drop observations with missing values for any of the variables used in thehappiness regressions below (219), and the one observation reporting retirement before
the age of 55. Finally, we trim the top of the income distribution, by dropping the 565
individuals who reported a personal annual pre-tax income in 2009 of over twelve
million Japanese Yen.6 To see whether this trimmed group reflected sample selection,
we compare the dropped and retained groups along a number of different dimensions
including age, education, marital status, and residential area. No significant differenceswere found, suggesting some potential mis-reporting of high incomes. Our final analysis
sample covers 10,203 respondents. We thus lose about 30 percent of the initial sample.
It is worth noting, however, that all of our main results listed below are qualitatively
similar in the overall and analysis samples.

4

See Johansson-Stenman et al. (2002) for a discussion of other potential biases, including the purchase of
moral satisfaction (Kahneman and Knetsch, 1992) associated with hypothetical-choice experiments
referring to relative utility.
5

Observations with no recorded elapsed time (90) or an elapsed time of over one hour (106) are excluded
from the analysis sample.
6

This cut-off point, JPY 12 million, is three standard deviations over the mean value of personal pre-tax
annual income. At the March 2009 exchange rate, 12 million Japanese Yen is around 130,000 US dollars.

-5-3. Happiness, income comparisons and reference income
The happiness and comparison questions
The first question in this category asked respondents about their satisfaction withincome. The answers were on a five-point scale, with 1 corresponding to "leastsatisfied" and 5 "most satisfied". The second question covered social comparisons andwas phrased as "How much are you concerned, anxious or envious about other people's
incomes?" Respondents chose from five response options, where 1 corresponded to"Not at all" and 5 to "Very". Respondents were then asked about their reference groupto whose income they compare. They chose one category from (i) family, (ii)neighbours, (iii) friends, (iv) work colleagues, (v) do not care about comparisons, and(vi) others. These last two questions therefore provide information on both "Whocompares to whom?" and "How much?" These two questions were analysed in theEuropean context by Clark and Senik (2010), where they were denoted the direction andintensity components of income comparisons.
We first consider the direction of income comparisons. Table 2 shows the distributionof the income reference groups that were indicated by respondents. The reference groupchosen the most often is friends (42%), followed by work colleagues (20%); around aquarter of the sample say that they do not make such income comparisons. It is ofinterest to compare these rankings to those from Wave 3 of the European Social Survey
in Clark and Senik (2010). In both Europe and Japan, friends and work colleagues are
the two most important reference groups. However, their relative importance iscompletely inverted. While in Japan, twice as many respondents indicate friends as thereference group, as compared to work colleagues, the European results in Clark andSenik (2010) have work colleagues (36%) being twice as important as friends (15%). In
both countries, the other named income reference groups are of only marginalimportance. Individuals can also indicate that they do not compare their income toothers, in the sense that they do not have an income comparison group. In Japan thisfigure (25%) is notably lower than that in Europe (36%). To this extent, the Japanese-6-may be considered to be more comparison-conscious (at least in the realm of income)than are Europeans.
Table 3 shows the cross-tabulation of the direction and intensity of social comparisons.
Those who do not think that comparisons are at all important tend not to declarecomparison groups, which is only natural. Respondents who say that they compare tofamily, neighbours or work colleagues tend to say that comparisons are more important
than do those whose income reference group is friends. The chi-squared statistic for thistable (with 20 degrees of freedom) is over 3000 and is significant at all conventional
levels (the critical value at the 0.1% level being 45.3): the direction and intensity ofsocial comparisons are indeed correlated.
The last column of Table 3 shows the overall distribution of the intensity of income
comparisons in Japan. While 30 percent of Japanese respondents give an answer of one
or two on the one to five scale, over 40 percent give an answer of 4 or 5, indicating thatthey find it important to compare their incomes. It is not easy to compare these figures
to their European counterparts in Clark and Senik (2010), as comparison intensity in theEuropean Social Survey is measured on a 0 to 6 scale rather. We can however compare
the percentage saying that income comparisons are "not at all important" (the lowest
value on the scale). This is only six percent in Japan, but 25 per cent in Europe (despite
the scale there being wider). This reinforces our conclusion above that the Japanese may
be more comparison-conscious than are Europeans.
Own income
In the survey respondents report their own annual pretax income using a list of 11
categories, where category 1 refers to an annual figure of below 2 million Yen andcategory 11 corresponds to an annual income of over 50 million Yen. Income iscalculated as the mid-point of each of the nine intermediate categories, with ad hoc
values of 1.5 and 55 million Yen being assigned to the two extreme categories. Over thewhole internet sample, this produces average annual pretax income figures of 5.69 and2.93 million Yen for men and women respectively. In the analysis sample allindividuals with income of over 12 million Yen are dropped. Average own pretax
annual income for men is then 4.9 million Yen (around 53 000 US Dollars) in Table 1.

-7-

The figure for women is notably lower at 2.7 million Yen. All of the income variables
are entered in log form in the regression analysis.
We also have available three different measures of the income to which individuals may
compare their own income. One of these is a self-reported measure of the income that“people like you” earn; the other two are constructed as cell means, one from with in the
database and the other from an external data source.
Self-reported reference income
The first measure of comparison income is provided by the respondents themselves. The
Japanese internet survey asks respondents directly about reference incomes: “About how
much do you suppose was the average personal income (before taxes) in 2009, forpeople of the same age, sex, and education as you?” The answers are given on the same
11-point scale used for own income above. As such we can compare the coefficient onreference income in a happiness regression directly to that on own pre-tax income, asboth are measured in the same units. Equally, it is arguably of use to have information
on what individuals believe others earn, as it is this figure which is likely important for
their feelings of deprivation or satisfaction. The disadvantage of this question is that it
captures the reference income only of one particular group defined in a Leyden-groupfashion as a cell mean. We do not know if this group is always the most salient for thekind of income comparisons that individuals carry out. We argue that this measure ofself-reported reference income will still capture some part of the effect of income
comparisons, as it is likely correlated with the real income to which the individualcompares.
The figures in Table 1 show that both men and women believe that they earn less than
do comparable others. Men think that others with the same productive characteristics
earn on average around 20% more than they do, while the comparable figure for womenis a remarkable 64%.
Cell means – internal
Our second measure of reference group income is given by the cell mean from within
the internet survey. In order to ensure the greatest compatibility with the other two-8-measures here, this will be calculated using cells defined by age, education, gender andlabour-force status (as described below). The average cell-mean internal income is thesame as average own income within the survey, by construction (see Table 1).
Cell means – external sources
Our last measure of reference group income comes from an external source. This
corresponds to the income of individuals in a number of different labour-force statuses:(i) employed in the private sector, (ii) in professional jobs, (iii) civil servants, (iv)
temporary workers, (v) other public sector (but not civil servants), (vi) unemployed andreceiving benefits, and (vii) self-employed. Income information for these groups areprovided by the Basic Survey on Wage Structure (BSWS) released by the Japanese
Ministry of Health, Labour and Welfare.7
For those in situations (i) and (iii), we construct cell average income levels by sex, andage and education categories. For individuals in (ii) we appeal to information on theincome of doctors and chartered accountants. The cell averages for this group are by age
and gender, but not by education (as that varies only little in this professional group).
For group (v), we have no direct information. These positions are public sector but
inferior to those in group (iii). We thus assume that the income of those in group (v) is
proportional to that in group (iii). For those in temporary jobs, we have information on
the average number of working days per month, working hours per day, and wage perhour by age and gender. We infer annual income levels from this information. For theunemployed, we have income information from unemployment insurance. We assume
for simplicity that the unemployed have no other sources of income. Last, we use
information on the before-tax income by age of the self-employed.
Figure 1 shows that average cell income from the BSWS is around 15-20% higher thanthat reported within the dataset. This discrepancy reflects the fact that housewives areincluded as one of the labour-force categories within the dataset, whereas we have nosuch information in the external dataset. As housewives report lower than averageannual income, the internet survey figure is below that in the BSWS.

7

The data can be obtained from: http://www.mhlw.go.jp/english/database/dbl/.

-9-4. Satisfaction and Income Comparisons in Japan
Our goal here is not just to catalogue the direction and intensity of income comparisonsin Japan, but also to see how these relate to income satisfaction. To do so we are goingto marry two disparate strands of the literature. The first considers how comparison
income levels affect various measures of subjective well-being. Comparison income inthis literature is most often considered here as either a Leyden-type cell mean or apredicted value from a Mincerian earnings equation (measuring "what other people likeme earn"). The cell mean can refer to the whole country (Easterlin, 1974, and Stevenson
and Wolfers 2008), a more disaggregated geographical area (Clark et al. 2009a, Ferreri-Carbonell, 2005, and Luttmer, 2005), or colleagues in the same workplace (Cappelli
and Sherer, 1988, Brown et al., 2008, and Clark et al. 2009b). The predicted value froman earnings equation, as in Clark and Oswald (1996), is similar in nature, calculating
expected mean earnings conditional on all of the control variables in the earnings
equation.
Controlling for own income, others' income is typically negatively correlated withindividual well-being (see the survey in Clark et al., 2008), although others' incomesmay sometimes serve to provide information about the individual's own likely future
income (Senik, 2004).
The second, much smaller, strand of research has considered the different referencegroups to which individuals compare and/or the intensity of comparisons.8 As well as
the work in Clark and Senik (2010) based on data from the European Social Survey,
Senik (2009) provides direct evidence from 25 post-Transition countries (LITS) thatcomparisons affect subjective well-being and evaluates the relative importance of thedifferent benchmarks. Internal comparisons to one’s own past living standard are themost important, but local comparisons (to parents, former colleagues or high-school
friends) also matter, especially upward comparisons.
8

An associated, but more specific question, concerns the direction of comparisons of immigrants, as inStark and Taylor (1991): do they compare to the home or host country? In Gelatt (2013) immigrants’affective well-being is more affected by comparisons to others in the United States than to those in thehome country.

- 10 -

Somewhat analogously, in Sági (2011) respondents in Ukraine, Poland, Hungary andGeorgia were asked to name three groups to which they compare their own standard ofliving, and how they thought the standard of living in these three groups compared tothat in the respondent's own country. The potential reference groups were neighborhood,friends, earlier standard of living, wealthy people in respondent country, average of thecountry, average of the former socialist countries, and average of the West European
countries. Respondents tended to compare upwards, in using reference groups that werein a better financial situation. The most popular reference groups were own earlier
living standards, current country average, and current neighbourhood average. In alogistic regression, comparing to the local neighbourhood reduces the individual's
satisfaction with standard of living, while comparing to former communist countries
raises satisfaction.
In research on Asia, Knight et al. (2009) used survey data from Chinese households toshow that, when asked explicitly to whom they compare themselves, 68% of survey
respondents report that their main comparison group consists of individuals in their own
village.
The paper the most closely-related to our own is Mayraz et al. (2009), who use a small
sample from the 2008 pre-test module of the Socio-Economic Panel Study (SOEP).
They ask both about the intensity of their income comparison to various referencegroups (on a 1-7 scale, from "completely unimportant" to "extremely important"), andthen how their income compares to that of these groups on a 1-5 scale (from "muchlower" to "much higher"). Half of respondents say that income comparisons arecompletely unimportant: this is most true for comparisons to neighbours, and least true
for comparisons to colleagues. Life satisfaction is shown to fall with the intensity ofcomparisons, as in Clark and Senik (2010).
We are here in the rather advantageous position of having not only information on wellbeing and comparison intensity and direction, but also a number of different measuresof individual comparison income (both self-reported and constructed as a cell mean,
either within the dataset or from an external source). As such, we are arguably able toput all the various pieces of information in the existing literature above together. We- 11 -

thus ask whether intensity and direction moderate the effect of comparison income on
satisfaction.
The first question is a fairly simple one: the more I care about comparisons, the greater
should be the effect of comparison income on my satisfaction. The second question asks
whether the correlation between comparison income and satisfaction is moderated by
the group to which I compare. As the measures of reference group income above areconstructed by age, sex and education, they may be thought (for example) to provide acloser fit to the income profile of the individual's work colleagues and friends rather
than their neighbours or family.
Satisfaction and Comparison Intensity
The relationship between the intensity of income comparisons and reference group
income is explored in Table 4. The estimation method here is OLS, although similar
results pertain if we instead use an ordered probit. The first column of this table shows
the results from a relatively standard regression of income satisfaction on own income,reference group income (here self-reported) and a number of demographic controls. Allof the income variables are entered in logarithms in the regressions. The results reveal a
positive relationship between income satisfaction and own income, but a negative
relationship with reference-group income. The size of the two estimated coefficientssuggests that the satisfaction effect of a ten percent (say) rise in income is about half aslarge again when only I receive it, as opposed to when it is received by both myself andthe members of my reference group.9
Column 2 of Table 4 adds the index of comparison intensity to the specification. This ishere treated as a cardinal variable, taking on the values of one to five. As in Clark andSenik (2010), the more the individual compares to others the less satisfied they are.10
Last, in column 3 we test whether comparison intensity tempers the effect of reference-

9

It is of interest to run this regression separately for men and women. The coefficient on own income islarger for men by a factor of three, and that on comparison income is larger by a factor of 8. The R2 formen is twice as high as that for women. As such, income matters more for men, and they are morecomparison-sensitive.
10

Although we cannot of course rule out reverse causality in this cross-section data, with lower levels of
subjective well-being leading individuals to become more status-conscious.

- 12 -

group income. We find that this is indeed the case. In this specification with aninteraction, both of the main effects (comparison income and intensity) attract
insignificant coefficients, but the interaction between them is negative and significant.
To illustrate the impact of this interaction, consider a rise in reference group income of
one log point. If I report the lowest comparison intensity of one, this rise is estimated toreduce my satisfaction by 0.1 points. However, if I report the maximum comparison
intensity of five, this one log point rise in others' income reduces my income satisfaction
by just over half of a point (which is a sizeable movement on a one to five satisfaction
scale). Hence, the brunt of the effect of income comparisons is indeed borne by those
who declare that this is more important for them.
The estimated coefficients on the other right-hand side variables are reassuringly similar
to those that are found in existing work (which has mostly used data from Westerncountries). Women report higher satisfaction scores than do men (Nolen-Hoeksema andRusting, 1999), while satisfaction is U-shaped in age, with a minimum at about age 46(Clark et al., 1996). Education in Japan is strongly positively correlated with income
satisfaction, even controlling for the level of income. This perhaps runs a little contrary
to existing work, which has often struggled to find a clear correlation between wellbeing and education (see Clark et al., 2012). Last, marriage is found to be positively
correlated with satisfaction in our cross-section data (although a reverse causality
reading is of course possible here: see Stutzer and Frey, 2006).
Satisfaction and Comparison Direction
Table 5 then turns to the direction of income comparisons. We here re-estimate
satisfaction with income using the specification from the first column of Table 4
separately for each of the different possible reference groups to which the individual cancompare. Reference-group income, as was the case in Table 4, is self-reported (as theindividual's guess of the average income of individuals of the same age, sex, andeducation as themselves).
The first column of Table 5 shows the estimates over the whole sample, as in Table 4,
where both own and reference group income are significant, with the latter being about
40% the size of the former. The remainder of the table splits the sample up according to- 13 -

the direction of comparisons. It can be seen that reference group income is associatedwith significantly lower income satisfaction for those who compare to colleagues or to"others", as well (but with a coefficient only half as large) as for those who compare toneighbours or friends. Reference-group income is insignificant for those who compare
to family, or who say they don't compare. As noted above, this self-report measure ofothers' income does therefore seem to provide a meaningful measure for a number ofreference groups, and especially work colleagues. Own income is positive andsignificant in all of the different regressions in Table 5.
The estimated relative importance of own income and reference-group income in these
regressions is strikingly similar to that found in the hypothetical-choice experiments
using the same dataset in Yamada and Sato (2010). For example, in the whole sample incolumn 1 of Table 5, the ratio of the effect of reference-group income to own income isabout -0.39. The analogous figure from the analysis of the hypothetical-choice questions
for the same individuals in Table 4 of Yamada and Sato (2010) is -0.46. For the othercolumns of Table 5, very similar trade-offs are also found for those who compare to
their neighbours, friends or colleagues.11
Which Measure of Comparison Income Matters Most?
The regression results discussed so far have used self-reported reference income levels.
Table 6 then considers the relationship between satisfaction and comparison income,but using a cell-mean measure of reference group income from within the same internet
survey, as described in Section 3 above.12 All of the regressions in Table 6 allow forstandard errors that are clustered at the level of the cells used to construct the averagereference income, for reasons that are set out in Moulton (1990). The specification hereis the same as that which appears in the first column of Table 4.

11

The empirical analysis of subjective measures using mixed methods is rare. One exception is Clark etal. (2010), who consider the role of income comparisons in determining the level of effort exerted byworkers, using both experimental and large-scale international survey data.

12

Oshio et al. (2011) use a cell-mean (gender x age x education) approach to analyse life satisfaction inthree Asian countries, among which Japan. Reference-group income is negatively correlated withsatisfaction in all three countries.

- 14 -

The results in Table 6 show that this new measure of comparison income attracts a wide
variety of estimated coefficients, depending sharply on the cells that are used toconstruct it. In general, age seems to be a salient component of reference income: all of
the point estimates on reference income from cells including age are negative, while allof those from cells which do not use age are positive. However, many of these negative
coefficients are insignificant, and only that from the reference group defined by region
and age is negative and significant. Hence the cell-mean measure of reference-group
income seems to behave significantly worse than the previous self-reported measure, interms of picking up any comparison-income effects.13
We can also split the sample up by direction of comparison, as in Table 5. The results(available on request) show that this internal cell mean (from the same dataset)
continues to perform poorly. In particular, across the six comparison groups theestimated coefficient on comparison income is never negative and significant, and thepoint estimate is actually positive for three groups.
One way of reading this result is that the data from the internet survey does not actuallyprovide a very good measure of the income in the different cells. We therefore turn tothe external cell-mean income information from the BSWS. Table 7 reruns all of theregressions in Table 5. While the signs of the estimated coefficients on comparison
income agree with those in Table 5 in five out of the seven regressions, only two of therelevant coefficients in Table 7 are significant, and then only at the ten percent level.
Overall, it then seems that self-reported levels of what others like me earn are far moresalient in providing comparison-income information than are a variety of both internaland external cell-mean measures.

13

De la Garza et al. (2010) test for income comparisons among Japanese union workers using a variety ofreference-income variables. They also find that self-reported reference-group information (the income ofpeople like you) provides the best fit to the data. They also propose a simple IV strategy for happiness
regressions when self-reported reference income information is not available, which is the main
contribution of their paper. They do not have information on the direction of comparisons.

- 15 -

5. Conclusions
This paper has used relatively large-scale internet survey data from Japan to lift part ofthe veil regarding the process of income comparisons. In contrast to the vast majority of
empirical work in the area of subjective well-being, we are able to measure both thedirection (to whom?) and intensity (how much?) dimensions of income comparisons.
Respondents compare first to friends and then to work colleagues, whereas this order isinverted in Europe. In addition, the intensity of income comparisons is higher in Japan
than in Europe.
Beyond documenting the existence of income comparisons, we also show that theymatter for subjective well-being. Satisfaction with standard of living rises with own
income, and falls with the income of the reference group. This latter correlation ismediated by both the intensity and the direction of income comparisons. The
relationship between satisfaction and others' income is indeed more negative for those
who state that they compare their incomes more; in addition, it is stronger for those who
compare their incomes to those of their colleagues than for those who compare to family
or friends, say.
Our final contribution concerns the measure of the relevant reference-group income. It
is common in non-experimental work to calculate "others' income" as some conditionalor unconditional cell-mean, with the cells being defined by neighbourhood, workplaceor demographic type. We here show that two such cell-mean measures (one from within
the dataset, the other matched in from external sources) fit the well-being data worse
than does a simple self-reported measure of what relevant others earn.
There are two ways of reading this result. Either simple questions on others' earnings
are better able to capture the actual reference group to which our respondents compare,or it is not what others actually do earn that matters, but rather what individuals believe
they earn.
In our survey, the "relevant others" were defined by age, sex, and education. While wehave shown that this question does indeed capture some useful information, there is no- 16 -

reason why the same question could not be asked about the neighbourhood or the
workplace. In general, asking questions about self-reported comparison income would
seem a simple useful addition to current surveys, in the same way that the addition ofsubjective questions to many has helped contribute to the current outpouring of researchacross the social sciences on individual and societal well-being.

- 17 -

Appendix. Questionnaire

Satisfaction and Income-Comparison Questions:
1. How satisfied are you with the amount of your current income?
1: Extremely dissatisfied.
2: Dissatisfied
3: Neither dissatisfied nor satisfied
4: Satisfied
5: Extremely satisfied

2. How much are you concerned, anxious or envious about other people’s income?
1: Not at all
2: Not much
3: Neither yes nor no
4: Fairly much
5: Very much

3. When you compare the amount of your income with that of someone else, which of
the following best describes that person?
1: Family
2: Neighbour
3: Friend
4: Colleague
5: Don’t compare
6: Others- 18 -

Demographic Variable Questions:
1) What is your age in years?
2) What is your sex?
3) What is your highest educational qualification?
4) What is your occupation?
5) What is your marital status?
6) What best describes your current residence? (Type of dwelling, for example ahouse that you own)
7) Where do you live? (Which prefecture in Japan)
8) What was your approximate personal income (before taxes) in 2009? Pleasealso include pension income, remittances, and so on.
9) About how much do you suppose was the average personal income (before
taxes) in 2009, for people of the same age, sex, and education level as you?

- 19 -

References
Bech, M., T. Kjaer and J. Lauridsen (2011), “Does the number of choice sets matter?
Results from a web survey applying a discrete choice experiment,” Health
Economics, 20, 273–286.
Brown, G. D. A., J. Gardner, A. J. Oswald and J. Qian (2008), “Does Wage Rank Affect
Employees’ Well-being?,” Industrial Relations, 47, 355–389.
Cappelli, P. and P. D. Sherer (1988), “Satisfaction, Market Wages, & Labor Relations:
An Airline Study,” Industrial Relations, 27, 56–73.
Clark, A.E., Frijters, P., and Shields, M. (2008). “Relative Income, Happiness andUtility: An Explanation for the Easterlin Paradox and Other Puzzles”. Journal of
Economic Literature, 46, 95-144.
Clark, A. E., N. Kristensen and N. Westergard-Nielsen (2009a), “Economic Satisfaction
and Income Rank in Small Neighbourhoods,” Journal of the European Economic
Association, 7, 519–527.
Clark, A. E., N. Kristensen and N. Westergard-Nielsen (2009b), “Job Satisfaction andCo-worker Wages: Status or Signal?,” Economic Journal, 119, 430–447.
Clark, A.E., Layard, R., and Senik, C. (2012). “The causes of happiness and misery”. In
J. Helliwell, R. Layard, and J. Sachs (Eds.), World Happiness Report. New York:
Columbia Earth Institute.
Clark, A.E., Masclet, D., and Villeval, M.-C. (2010). “Effort and Comparison Income”.
Industrial and Labor Relations Review, 63, 407-426.
Clark, A. E. and A. J. Oswald (1996), “Satisfaction and comparison income,” Journalof Public Economics, 61, 359–381.
Clark, A.E., Oswald, A.J., and Warr, P.B. (1996). “Is Job Satisfaction U-shaped in
Age?” Journal of Occupational and Organizational Psychology, 69, 57-81.
Clark, A.E. and C. Senik (2010), “Who compares to whom? The anatomy of income
comparisons in Europe,” Economic Journal, 120, 573–594.
de la Garza, A., G. Mastrobuoni, A. Sannabe and K. Yamada (2010), “The Relative
Utility Hypothesis With and Without Self-reported Reference Wages,” ISER
Discussion Paper 795, Osaka University.
Easterlin, R. (1974). “Does Economic Growth Improve the Human Lot? ” In P.A. David
and W.B. Melvin (Eds.), Nations and Households in Economic Growth. Palo Alto:
Stanford University Press.
Ferrer-i-Carbonell, A. (2005). “Income and well-being: an empirical analysis of thecomparison income effect”. Journal of Public Economics, 89, 997-1019.

- 20 -

Fujita, F. (2008). “The Frequency of Social Comparison and Its Relation to Subjective
Well-Being”. In M. Eid and R. Larsen (Eds.), The Science of Subjective Well-Being.
New York and London: Guilford Press.
Gelatt, J. (2013). “Looking Down or Looking Up: Status and Subjective Well-Being
among Asian and Latino Immigrants in the United States”. International Migration
Review, forthcoming.
Hamermesh, D.S. (1977). “Economic Aspects of Job Satisfaction”. In O.C.Ashenfelterand W.E.Oates (Eds.), Essays in Labor Market Analysis. New York: John Wiley.
Ida, T. and R. Goto (2009), “Simultaneous Measurement of Time and Risk Preferences:
Stated Preference Discrete Choice Modeling Analysis Depending on Smoking
Behavior,” International Economic Review, 50, 1169–1182.
Johannsson-Stenman, O., Carlsson, F., and Daruvala, D. (2002). “Measuring Future
Grandparents' Preferences for Equality and Relative Standing”. Economic Journal,
112, 362-383.
Kahneman, D. and J. L. Knetsch (1992). “Valuing public goods: The purchase of
moral satisfaction”. Journal of Environmental Economics and Management, 22,
57-70.
Knight, J., Song, L. and Gunatilaka, R. (2009). “Subjective Well-being and its
Determinants in Rural China”. China Economic Review, 20, 635-649.
Luttmer, E. (2005). “Neighbors as Negatives: Relative Earnings and Well-Being”.
Quarterly Journal of Economics, 120, 963-1002.
Mayraz, G., Wagner, G. and Schupp, J. (2009). “Life Satisfaction and Relative Income:
Perceptions and Evidence”. IZA Discussion Paper 4390, Institute for the Study ofLabor (IZA)
Moulton, B. (1990). “An Illustration of a Pitfall in Estimating the Effects of Aggregate
Variables on Micro Units”. Review of Economics and Statistics, 72, 334-38.
Nolen-Hoeksema, S., and Rusting, C.L. (1999). “Gender differences in well-being”. In
D. Kahneman, E. Diener, and N. Schwartz (Eds.), Well-being: The foundations ofhedonic psychology. New York: Russell Sage Foundation.
Olsen, S. (2009), “Choosing Between Internet and Mail Survey Modes for Choice
Experiment Surveys Considering Non-Market Goods,” Environmental & Resource
Economics, 44, 591–610.
Oshio, T., Nozaki, K., and Kobayashi, M. (2011). “Relative income and happiness in
Asia: Evidence from nationwide surveys in China, Japan, and Korea”. Social
Indicators Research, 104, 351-367.
Sági, M. (2011), “Determinants of Satisfaction with Living Standards in Transition
Societies”, International Journal of Sociology, 41, 55-78.

- 21 -

Senik, C. (2004). “When Information Dominates Comparison: A Panel Data Analysis
Using Russian Subjective Data”. Journal of Public Economics, 88, 2099-2123.
Senik C. (2009), “Direct Evidence on Income Comparisons and their Welfare Effects”,
Journal of Economic Behavior and Organization, 72, 408-424.
Stark, O., and Taylor, J.E. (1991). “Migration Incentives, Migration Types: The Role ofRelative Deprivation”. Economic Journal, 101, 1163-1178.
Stevenson, B., and Wolfers, J. (2008). “Economic Growth and Subjective Well-Being:
Reassessing the Easterlin Paradox”. Brookings Papers on Economic Activity,
Spring, 1-102.
Stutzer, A., and Frey, B.S. (2006). “Does Marriage Make People Happy, Or Do Happy
People Get Married?”. Journal of Socio-Economics, 35, 326-347.
Viscusi, W. K., J. Huber and J. Bell (2008), “Estimating discount rates forenvironmental quality from utility-based choice experiments,” Journal of Risk andUncertainty, 37, 199–220.
Yamada, K. and M. Sato (2010), “Another Avenue for Anatomy of Income
Comparisons: Evidence from Hypothetical Choice Experiments,” Journal of
Economic Behavior and Organization, forthcoming.

- 22 -

Tables
Table 1.Descriptive Statistics of the Regression Sample

Female [0.1]Age category
20‐29
30‐39
40‐49
50‐59
60‐65
Education (a)Middle school
High schoolSome college
College
Marital Status
SingleMarriedDivorced/Separated/Widowed
RegionHokkaido
Tohoku
Kanto
Koshinetsu
Chubu
Kansai
Chugoku
Shikoku
KyushuStudent [0.1]
Unemployment
Income satisfaction
Annual income (Thousand Yen)
Own income in survey
Reference income in survey
Income of Cell average(age*gender*education*job)
Income of cell average from Externalsource (age*gender*education*job)(1)
Our Survey(analysis sample)
Male
Female
55.6
18.1
25.4
19.2
22.5
14.8

21.5
23.2
24.8
18.9
11.7

0.9
21.2
11.1
66.7

0.9
25.9
32.1
41.1

33.2
63.3
3.5

25.8
67.9
6.3
4.7
4.4
44.2
4.2
10.0
20.6
3.9
1.9
6.3
3.4
4.0

(2)

(3)

NIKKEI

National Data (b)

2.27

4 902
5 993

2 709
4 458

4 902

2 709

5 555

3 237

Female
51.3

19.5
24.5
21.8
22.1
12.1

18.7
24.1
21.7
22.6
12.8

18.2
41.6
11.4
28.3

20.8
43.4
24.5
10.7

32.0
61.8
6.2

23.4
57.6
19.0

56.6
13.7
36.4
30.1
13.9
5.9
N.A.

30.0
60.7
9.3
4.0
4.1
46.9
3.7
9.5
19.7
3.8
1.9
6.4
N.A.
N.A.

2.22

Male

4.3
7.4
32.9
6.7
11.9
16.3
6.0
3.1
11.4
7.6
4.9

All figures are in percent for each category except for the annual personal pretax income variables.
(a) Those who are currently students are excluded from the figure.
(b) Demographic characteristics are from the Population Estimates by the Statistics Bureau (Sep. 2009).
Education is from the Employment Status Survey (Table 3; 2007) by the Statistics Bureau. Marital Status isfrom the Population Statistics of Japan (Table 6.21; 2008) by National Institute of Population and Social
Security Research. Region is from the Population Statistics of Japan (Table 9.5; 2008). and theunemployment rate is from the Labour Force Survey (Feb. 2010) by the Statistics Bureau.

- 23 -

Table 2. The Direction of Self‐Declared Income ComparisonsObservations
Percent

Family483
4.7

Neighbours
578
5.7

Friends
4279
41.9

Colleagues
2024
19.8

Don't compare
2592
25.4

Others247
2.4

Table 3. Cross‐Tabulation of the Direction and Intensity of Income Comparisons
FamilyNeighbours

Friends

Colleagues

Don't
compareOthers

Total

3.0
3.9
4.1
21.1
5.5
33.8
4.7
35.2
6.0
6.0
4.7

0.5
0.5
2.8
11.8
5.2
27.0
8.4
52.8
9.5
8.0
5.7

13.2
2.0
24.9
14.3
40.2
28.0
58.3
49.5
54.7
6.2
41.9

8.0
2.5
15.2
18.8
20.0
29.5
24.2
43.5
25.3
6.0
19.8

74.3
18.2
51.7
49.2
26.9
30.9
1.1
1.5
0.8
0.2
25.4

0.9
2.4
1.3
13.4
2.3
27.5
3.4
49.4
3.7
7.3
2.4

100.0
6.2
100.0
24.2
100.0
29.2
100.0
35.7
100.0
4.7
100.0

Total
100.0
100.0
Note: Figures in italics are row percentages.

100.0

100.0

100.0

100.0

100.0

Comparisons

Not at All
Not Much
Neither Yes nor No
Fairly Much
Very Much- 24 -

Table 4. OLS Estimates of Satisfaction with Income
Dependent Variable
Own income
Self‐reported reference income
Comparison Intensity
Reference Income * Intensity
FemaleAge
Age squared/100
Education (Omitted: high school)
Middle School

(1)
(2)
(3)
Satisfaction with income
0.360***
0.350***
0.351***(0.020)(0.020)(0.020)‐0.134***‐0.127***‐0.028(0.021)(0.021)(0.051)‐0.482***1.115(0.030)(0.750)‐0.104**(0.049)0.228***
0.230***
0.229***(0.022)(0.022)(0.022)‐0.057***‐0.059***‐0.058***(0.006)(0.006)(0.006)
0.062***
0.063***
0.063***(0.007)(0.007)(0.007)‐0.240***(0.089)‐0.115***(0.040)0.065**(0.027)0.126***(0.022)0.278***(0.042)‐0.234***(0.088)‐0.104***(0.040)0.069***(0.027)0.122***(0.022)0.271***(0.042)‐0.233***(0.088)‐0.104***(0.040)0.069***(0.027)0.123***(0.022)0.273***(0.042)0.175***(0.024)‐0.005(0.043)0.193***(0.024)‐0.003(0.043)0.194***(0.024)‐0.001(0.043)

Urban (Tokyo. Kanagawa. Nagoya
Osaka. and Fukuoka)
Constant

0.013(0.017)‐0.077(0.357)0.014(0.017)0.346(0.353)0.014(0.017)‐1.203(0.808)Observations
R‐squared

10203
0.101

10203
0.124

10203
0.124

Technical school
Two years college/some college
Undergraduate
Graduate school
Marital status (omitted: Single)
MarriedDivorced/Separated/Widowed- 25 -

Table 5. Evidence from self‐reported reference income. OLS Estimates of Satisfaction with Income
Comparison Benchmark

(1)
Whole

(2)
FamilyDependent Variable
Own income
Self‐reported reference income(3)
Neighbours(4)
Friends(5)
Colleagues(6)
Don't compare(7)
Others

0.461***(0.049)‐0.285***(0.057)0.331***(0.038)‐0.047(0.038)0.307***(0.116)‐0.251**(0.116)

2592
0.095

247
0.240

Satisfaction with Income
0.360***(0.020)‐0.134***(0.021)

0.242***(0.089)‐0.033(0.090)0.229***(0.079)‐0.151*(0.082)0.378***(0.031)‐0.157***(0.035)Observations
10203
483
578
4279
2024
R‐squared
0.101
0.113
0.115
0.091
0.092
Note: The regressions in each column include all of the other control variables in Table 4. Column (1) estimate on thewhole sample. Columns (2) to (7): each column presents an estimate on the sub‐sample of respondents who indicatethat they compare to a certain group.

26

Table 6 Evidence from internal cell mean reference income. OLS Estimates of Satisfaction with
IncomeCell type(1)
age
education(2)
educationjob(3)
regionDependent Variable
Own income
Cell mean reference income(4)
regionage(5)age
educationjob(6)
regioneducation
gender(7)
age
education
genderjob

0.316***(0.017)0.122*(0.069)0.321***(0.047)‐0.012(0.092)

Satisfaction with income
0.321***(0.030)‐0.178(0.156)0.315***(0.093)0.169(0.196)

0.318***(0.017)0.166*(0.089)0.329***(0.049)‐0.290***(0.087)0.323***(0.051)‐0.037(0.106)

Observations
10203
10203
10203
10203
10203
10203
10203
R‐squared
0.098
0.098
0.098
0.099
0.098
0.098
0.098
Notes: the regressions in each column include all of the other control variables in Table 4.; the standard errors are
clustered according to the cell definition at the head of each column.

27

Table 7. Evidence from cell mean reference income, based on an external source. OLS Estimates ofSatisfaction with Income
Cell type(1)
age
education(2)
educationjob(3)
regionDependent Variable
Own income(4)
regionage(5)age
educationjob(6)
regioneducation
gender(7)
age
education
genderjob

Satisfaction with income
0.329***(0.049)‐0.290***(0.087)0.323***(0.051)‐0.037(0.106)

0.316***(0.017)0.122*(0.069)0.321***(0.047)‐0.012(0.092)

Observations
10203
10203
10203
10203
R‐squared
0.098
0.098
0.098
0.099
Notes: the regressions in each column include all of the other control variables in Table 4.;
the standard errors are clustered according to the cell definition at the head of eachcolumn.

10203
0.098

10203
0.098

10203
0.098

Cell mean reference income

0.321***(0.030)‐0.178(0.156)0.315***(0.093)0.169(0.196)28

0.318***(0.017)0.166*(0.089)