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The relationship between pay and job satisfaction: A meta-analysis
of the literature
Timothy A. Judge
⁎, Ronald F. Piccolo
, Nathan P. Podsakoff
, John C. Shaw
, Bruce L. Rich
Warrington College of Business, University of Florida, USA
Crummer Graduate School of Business, Rollins College, USA
Eller College of Management, University of Arizona, USA
Davis College of Business, Jacksonville University, USA
College of Business Administration, California State University San Marcos, USA
article info abstract
Received 11 March 2010
Available online 13 April 2010
Whereas the motivational aspects of pay are well-documented, the notion that high pay leads
to high levels of satisfaction is not without debate. The current study used meta-analysis to
estimate the population correlation between pay level and measures of pay and job
satisfaction. Cumulating across 115 correlations from 92 independent samples, results
suggested that pay level was correlated .15 with job satisfaction and .23 with pay
satisfaction. Various moderators of the relationship were investigated. Despite the popular
theorizing, results suggest that pay level is only marginally related to satisfaction. Theoretical
and practical implications of the results are discussed.
© 2010 Elsevier Inc. All rights reserved.
Most individuals choose to spend the majority of their adult lives in paid employment. The reasons individuals so devote
themselves to work are varied, and for many, self-concept factors are cited (i.e., one's job is a source of one's identity; Hulin, 2002).
When individuals are asked why they work, however, money is one of the most commonly-cited reasons (Jurgensen, 1978). Locke,
Feren, McCaleb, Shaw, and Denny (1980) went so far as to argue, “No other incentive or motivational technique comes even close
to money with respect to its instrumental value”(p. 379). For most, the choice to work may not be seen as much of a choice at all,
since money provides sustenance, security, and privilege. To no small extent, people work to live, and the pecuniary aspect of the
work is what sustains the living.
In the area of money as a means to live, comparatively speaking, Americans are well off. Of the roughly 192 sovereign nations,
the United States is arguably the wealthiest (its Gross Domestic Product [GDP] is highest in the world). Thus, for many Americans
and the citizens of other wealthy nations, the question generally is not between working and starving (in America, of those who
work, “only”13.2% are below the poverty line [U.S. Census Bureau, 2009]), but rather of working for how much money. People do
differ widely in the pay they receive from their work; income dispersion is relatively high in the United States and has grown over
time (Lee, 1999). Thus, it becomes interesting to ask whether this extrinsic motive “pays off”in terms of happiness. How does the
pay we receive from our work contribute to our feelings about our jobs and lives?
Indeed, there is a substantial literature on the relationship between income and subjective well-being. Although U. S. Gross
National Product (GNP) has increased threefold over the past 50 years, levels of life satisfaction have remained constant since the
1940's (Diener & Oishi, 2000), a ﬁnding which has been replicated in Japan (Diener & Biswas-Diener, 2002). Moreover, after a
relatively short period of time (i.e., 1 year), lottery winners are no happier than before they won the lottery (Brickman, Coates, &
Janoff-Bulman, 1978). These ﬁndings suggest that income is unimportant to happiness. On the other hand, the richest Americans
Journal of Vocational Behavior 77 (2010) 157–167
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Contents lists available at ScienceDirect
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are happier than the average American (Diener, Horwitz, & Emmons, 1985), and the average individual is happier than the very
poor (Cummins, 2000). Moreover, across nations, the correlation between average well-being and average per capita income
ranges from r=.50 to r= .70 (Diener & Biswas-Diener, 2002). However, the relationship appears to diminish substantially when
the analysis is conﬁned to wealthy nations (Helliwell, 2003). Thus, at the macro level, results suggest contradictory conclusions
regarding the importance of income to life satisfaction.
Studies at the individual level reveal similarly indeterminate ﬁndings. Diener and Seligman (2004) concluded, “Dozens of
cross-sectional studies reveal that there is a positive correlation between individuals' incomes and their reports of well-being”
(p. 7). On the other hand, in the U. S., Diener, Sandvik, Seidlitz, and Diener (1993) reported the average correlation between
income and well-being to be quite modest (r=.13). In an international study, Suh, Diener, Oishi, and Triandis (1998) found the
same result (r= .13). On the other hand, Cummins (2000) concluded, “There are numerous empirical reports indicating that
people who are rich have a level of subjective well-being that is substantially higher than people who are poor”(p. 133). Thus,
though the data tend to indicate a small, positive correlation between income and subjective well-being, this conclusion cannot be
proffered with much conﬁdence.
Despite the considerable focus that the income–happiness relationship has garnered in psychology (see Diener & Seligman,
2004 and Diener, Suh, Lucas, & Smith, 1999 for reviews), in organizational psychology, little attention has been focused speciﬁcally
on the relationship between pay level and job satisfaction. Some studies have found positive, signiﬁcant relationships between pay
level and job satisfaction (r= .27, pb.01 (Beutell & Wittig-Berman, 1999); r= .27, pb.01 (Sanchez & Brock, 1996)). Other research
has revealed a weak relationship between the variables (r=.01, ns (Dunham & Hawk, 1977); r= .07, ns (Adams & Beehr, 1998)).
Still other research has suggested moderators of the relationship. Malka and Chatman (2003) found that income and job
satisfaction were positively correlated (r=.17, p=.06), and the relationship was stronger for individuals with extrinsic value
orientations. Overall, though, there is a dearth of research speciﬁcally focused on the relationship between pay level and job
satisfaction. Gerhart and Rynes (2003) concluded, “One curious feature of the pay level–pay satisfaction literature is that there are
virtually no studies that correlate pay level with general job satisfaction”(p. 63).
Theoretically, there are reasons to expect a positive or a negative relationship between pay level and job satisfaction. Most
models of pay satisfaction stipulate a positive relationship between pay level and pay satisfaction, and pay satisfaction is one of the
core components of overall job satisfaction (Smith, Kendall, & Hulin, 1969). Heneman and Judge (2000) noted, “Models of pay
satisfaction all suggest that the amount of pay itself should have a direct impact on pay satisfaction”(p. 71). For example, Hulin's
(1991) integrative model predicts that all else equal, role outcomes—such as pay—will result in higher levels of job satisfaction.
Similarly, Lawler's discrepancy model—where pay satisfaction is a function of what one receives relative to what one thinks one
should receive—hypothesizes that pay level should be satisfying to individuals (see Heneman , Fig. 8).
On the other hand, self-determination theory (Deci & Ryan, 1985) suggests that extrinsic rewards are ultimately demotivating
and dissatisfying to individuals. Because they have a negative effect on intrinsic interest in a task or job, extrinsic motivations tend
to undermine perceived autonomy (Deci & Ryan, 2000). Moreover, goals for ﬁnancial success have been argued to undermine
well-being, because these goals represent a controlled orientation that interferes with the fulﬁllment of more enduring needs such
as self-acceptance or afﬁliation (Kasser & Ryan, 1993), a view that has not gone unchallenged (Svrivasta, Locke, & Bartol, 2001).
Thus, relevant theories are at odds with respect to whether or not pay level and other forms of extrinsic rewards should be
positively related to job satisfaction.
Beyond the empirical results and theoretical support, a ﬁnal source of confusion with respect to the pay level—job satisfaction
relationship comes from reviews of the literature. Heneman (1985) concluded, “The consistency of the pay level–pay satisfaction
relationship is probably the most robust (though hardly surprising) ﬁnding regarding the causes of pay satisfaction”(p. 131).
Gerhart and Milkovich (1992) noted, “Pay level is a key attribute of compensation design and strategy because of its consequences
for…attitudinal objectives”(p. 495). Spector (1997), conversely, concluded, “Pay itself is not a very strong factor in job
satisfaction”(p. 42). Pfeffer (1998) lamented, “Literally hundreds of studies and scores of systematic reviews of incentive studies
consistently document the ineffectiveness of external rewards”(p. 216).
The purpose of the present study is to perform a meta-analysis of the relationship between pay level and job satisfaction.
Heneman and Judge (2000) called for more research on the relationship between pay level and job and pay satisfaction. One way
to further investigate this relationship is through meta-analysis. Qualitative or narrative reviews have many limitations
(potentially misleading conclusions, over- or under-weighting of particular studies, failure to take into account study artifacts and
measurement error; Hunter & Schmidt, 1990). As Judge, Piccolo, and Ilies (2004) noted, “Although there is nothing wrong with
qualitative reviews per se, they are subject to various errors, including the fact that subjective accounting of study results often
leads to inaccurate conclusions”(p. 44). Thus, it is worthwhile to consider the actual size of the relationship of pay level to job and
pay satisfaction once sampling and measurement error have been taken into account. Given the conﬂicting theoretical arguments
and empirical data, we do not offer formal hypotheses. However, we do address the following research questions:
Q-1: At the individual level, is pay level related to: (a) pay satisfaction or (b) overall job satisfaction?
Q-2: At the organization/sample level, are average levels of pay level related to: (a) pay satisfaction or (b) overall job
Because at the sample level various factors may affect the relationship between pay level and job and pay satisfaction, we also
investigate several moderators of the relationship. It has been speculated that the relationship between pay level and job
satisfaction is lower in the U. S. given that it is the wealthiest nation (Diener & Biswas-Diener, 2002). Thus, we compare the
relationships of pay level with job and pay satisfaction for U. S. vs. international samples. We also investigate whether the
158 T.A. Judge et al. / Journal of Vocational Behavior 77 (2010) 157–167
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relationships vary according to publication source (“top-tier”journal article vs. other published source or unpublished
manuscript). Some have argued that measures of job satisfaction differ in the degree to which they adequately capture extrinsic
aspects of the job. Brief (1998) argued that the Minnesota Satisfaction Questionnaire (MSQ) better assesses extrinsic attributes
than other measures. Thus, we compare the pay level–job satisfaction relationships according to the measure of job and pay
satisfaction used in the studies. Common source variance is often labeled as a biasing factor in organizational behavior research
(see Podsakoff, MacKenzie, Lee, & Podsakoff, 2003, for a review), yet some argue that common method or source effects are less
severe with relatively objective variables such as pay or beneﬁts (Crampton & Wagner, 1994). Therefore, we compare the
relationships of pay level with job and pay satisfaction when both variables were reported by the same source when pay and
satisfaction were independently reported.
Another possible moderator of the pay level–satisfaction relationship is the measure of pay. In a “pure”sense, pay or income is a
ratio variable in that the measure is separated by equal intervals and it has a deﬁned zero. However, in many cases, pay level is
measured as an interval or ordinal variable where pay is reported in intervals or increments. On the one hand, because such
measures lose information, all else equal, ordinal or interval scale measures can be expected to have inferior psychometric
properties compared to ratio measures, and therefore lower validity (see Pedhazur & Schmelkin, 1991). On the other hand,
because asking individuals to report precise ﬁgures for sensitive information such as pay may promote socially desirable
responding (Wentland & Smith, 1993), interval or ordinal measures may have higher validity. Thus, we compare validities
according to the measure of pay level.
Q-3: Do the following factors moderate the relationship between pay level and job satisfaction or pay level and pay satisfaction:
(a) U. S. vs. international samples; (b) publication source (published vs. unpublished, and quality of publication outlet); (c)
measure of job or pay satisfaction; (d) common vs. independent sources of data; and (e) measure of pay?
We searched the PsycINFO database (1887–2007) for studies (articles and book chapters) that included the keyword
“satisfaction,”and keywords such as “pay”,“compensation”,“salary”,“money”, and “earnings.”To identify articles that may have
been missed in the original search, we conducted additional searches using the following keywords: “pay satisfaction”,“work
satisfaction”,“pay and job satisfaction”, and “money and happiness.”Finally, we conducted electronic searches of four top-tier
management journals (Academy of Management,Journal of Applied Psychology,Organizational Behavior and Human Decision
Processes,and Personnel Psychology) from 1990 to 2007, looking for the words “satisfaction”,“pay”,or“income”in the title. This last
search identiﬁed 105 new journal articles for consideration. The three separate searches of the literature on pay and satisfaction
resulted in the identiﬁcation of 1156 abstracts including both journal articles and book chapters.
Rules for inclusion in the meta-analysis
In reviewing the abstracts, we eliminated studies that clearly did not include primary data (such as qualitative studies or
reviews) and studies that did not appear to measure the relationship between satisfaction and pay level. For the remaining 458
articles, we examined each study to determine whether it contained the information needed to calculate validities. Studies that did
not measure pay level were excluded, as were studies that were clearly unrelated to employee attitudes in the workplace. For
example, we eliminated articles that attempted to validate existing satisfaction scales, and studies that measured customer or
patient satisfaction. In addition, several studies were excluded because authors reported proportions of means without standard
deviations or other measures of association that could not be converted to correlations. In total, 86 studies (119 correlations from
92 independent samples) met the criteria for inclusion in the database and subsequent analyses.
Using the methods of Hunter and Schmidt (1990), we conducted a meta-analysis to estimate the correlations between
satisfaction and pay level. We corrected each primary correlation for attenuation due to unreliability in the criterion variable, and
then computed the sample-weighted mean of these corrected correlations. To estimate parameters describing the variability of
and conﬁdence in these meta-analytic estimates, the variance of the observed individual estimates was corrected for the effects of
both sampling and measurement error. When authors of the original studies reported the internal consistency reliability for
satisfaction measures, we used this value to correct the observed correlation for attenuation. Of note, reliability estimates for
measures of income, pay, or salary were not provided in any of the studies, so we assumed the reliabilities were equal to 1.00.
For the 92 primary correlations between satisfaction and pay level, the reliability of satisfaction was available for 60
correlations (65%). When reliabilities for criterion measures were not reported in the original studies, we averaged the reported
reliability estimates for similar measures (i.e. job or pay satisfaction), and used these mean reliability values to correct the primary
In addition to reporting point estimates for corrected correlations, we also report 80% credibility intervals and 90% conﬁdence
intervals around the estimated population correlations. We believe it is important to report both conﬁdence and credibility
159T.A. Judge et al. / Journal of Vocational Behavior 77 (2010) 157–167
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intervals because each provides different information about the nature of the true estimates. Conﬁdence intervals provide an
estimate of the variability around the estimated mean corrected correlation that is due to sampling error. For example, a 90%
conﬁdence interval around a positive point estimate that excludes zero indicates that if the estimation procedures were repeated a
large number of times, the point estimate would be larger than zero in 95% of the cases (the other 5% would be zero or negative).
Credibility intervals provide an estimate of the variability of individual correlations across studies. For example, an 80% credibility
interval excluding zero indicates that 90% of the individual correlations in the meta-analysis excluded zero (for positive
correlations, less than 10% are zero or negative and 10% lie at or beyond the upper bound of the interval). Thus, conﬁdence
intervals estimate variability in the mean correlation, while credibility intervals estimate variability in the individual correlations
across the studies.
We divided the studies into categories according to the moderator variables and conducted separate meta-analyses in order to
estimate the true correlations delimited by moderator variables. Meta-analytical evidence for the presence of moderators requires
that (1) true estimates are different in the categories formed by the potential moderator variable, and (2) the mean corrected
standard deviation within categories is smaller than the corrected standard deviation computed for combined categories. To test
for the presence of moderator effects, as recommended by Sagie and Koslowsky (1993), we report the Q-statistic (Hunter &
Schmidt, 1990, p. 151), which tests for homogeneity in the true correlations across studies. A signiﬁcant Q-statistic (which is
approximately distributed as a chi-square [χ
]), indicates the likelihood that moderators explain variability in the correlations
across studies. If a signiﬁcant Q-statistic across moderator categories becomes non-signiﬁcant within a moderator category, it
suggests that the moderator explains a signiﬁcant amount of the variability in the correlations across the moderator categories.
Results of the overall meta-analysis are presented in Table 1, which indicate that pay level is positively correlated with both
overall job satisfaction (ρ= .15, pb.05) and with pay satisfaction (ρ =.24, pb.05). For both job (.02, .28) and pay satisfaction (.07,
.39), the average correlations with pay level are distinguishable from zero in that the 90% conﬁdence intervals excludes zero. Thus
we can be conﬁdent that the mean correlations between pay level and job and pay satisfaction are distinguishable from zero. The
population correlation between pay level and satisfaction is signiﬁcantly higher than the correlation between pay level and job
satisfaction (Z=−4.01, pb.05), suggesting that pay level is more strongly associated with satisfaction with pay than the job
The overall validities reported in Table 1 are interpretable across moderator categories. As such, we were interested in whether
or not estimated correlations among the variables were inﬂuenced by characteristics of the research design. We therefore
separated studies into their respective moderator categories, and estimated the true score correlations within each category.
Table 2 provides the meta-analytic results for job satisfaction and pay satisfaction, broken down by six moderator criteria: measure
of pay (exact or interval), independence of data source (same or different source), measure of satisfaction (MSQ, JDI, PSQ, and
Other), sample nationality (United States or international), publication status (published or non-published), and ranking of
journal source (top-tier, other ranked, unpublished).
The Q-statistics for both job satisfaction (Q= 221.54, pb.05) and pay satisfaction (Q= 280.36, pb.05) are signiﬁcant, meaning
there is signiﬁcant variability in the correlations even after taking measurement and sampling error into account. A signiﬁcant Q-
statistic indicates the likelihood that moderators explain variability in the correlations across studies. Accordingly, we conducted
separate meta-analyses within each moderator category and used the technique proposed by Quiñones, Ford, and Teachout
(1995) to determine if observed differences within each category were signiﬁcant. A Z-score greater than + 1.96 or less than
−1.96 would indicate that observed differences were signiﬁcant at α=.05.
The correlations between pay level and job satisfaction, and between pay level and pay satisfaction appear to generalize across
moderator variable categories. The pay level–job satisfaction correlation in the United States (ρ= .15), although lower for
employees in other countries (ρ= .21) such as Great Britain, India, Australia, and Taiwan, was not signiﬁcantly different (Z=
−1.42, ns). The same was true for pay satisfaction, where the estimated correlation between pay level and pay satisfaction in the
U. S. (ρ= .23) was not signiﬁcantly different from that of international samples (ρ =.19; Z=−1.82, ns).
Correlations of pay level with job satisfaction and pay satisfaction.
kN r ρ Q80% CV lower 80% CV upper 90% CI lower 90%CI upper
Job satisfaction 61 18,460 .14 .15 ⁎221.54 ⁎.02 .28 .12 .18
Pay satisfaction 48 15,576 .22 .23 ⁎280.36 ⁎.07 .39 .18 .25
Notes: k= number of correlations. N= combined sample size. r= mean observed correlation. ρ = estimated true score correlation. CV = Credibility interval. CI
= Conﬁdence interval.
160 T.A. Judge et al. / Journal of Vocational Behavior 77 (2010) 157–167
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The pay level–job satisfaction relationship was only partially moderated by the measure of satisfaction used in the study. The
estimated population correlation between pay level and job satisfaction (ρ= .24) in studies that used the MSQ (Weiss, Dawis,
England, & Lofquist, 1964) was not signiﬁcantly higher than the correlation (ρ= .24; Z=−0.34, ns) in studies that used the JDI
(Smith et al., 1969). However, studies that used the MSQ yielded a higher correlation between pay level and job satisfaction than
studies used other measures of satisfaction (ρ= .13; Z= 5.11, pb.01). For pay satisfaction, the estimated average correlation is
unaffected by the measure of satisfaction used in the study, as differences within this moderator category were found to be non-
As indicated in Table 2, relationships between pay level and both job and pay satisfaction were unaffected by the type of pay
measure assessed (exact or interval), independence of data source, publication status, or rank of journal source. Although we
observed a small difference in the pay level and pay satisfaction relationship in published (ρ = .18) and unpublished studies
(ρ= .23), this difference was non-signiﬁcant (Z=−1.62, ns). We conducted an additional moderator analysis of pay level–
satisfaction based on the rank of publication source as deﬁned by Gomez-Meija and Balkin (1992). With one exception (pay level–
pay satisfaction in top-tier publications vs. unpublished studies), no signiﬁcant differences were found among the estimated true
correlations reported in top-tier published journals, non-top tier published journals, and unpublished studies.
Between-study evaluation of correlations
Estimating the population correlation provides information about the average within-study relationship between pay level and
satisfaction. To determine if pay level–satisfaction relationships differ between studies as a function of the average level of pay and
satisfaction in the sample, we conducted a separate analysis of the mean level meta-analytic data. We createda database of studies
that reported pay level and satisfaction means. For each of the 50 independent samples that reported the necessary information,
we recorded the mean pay level of the sample, as well as the job and/or pay satisfaction scale means and standard deviations. We
derived a satisfaction “scale maximum”score based on the mean satisfaction reported by the study's authors and on the scale
range used by the authors in a particular study. For example, when a single item measure of job satisfaction was used with a scale
ranging from 1 to 7 (e.g., Martins, Eddelston, & Veiga, 2002), the scale maximum recorded in our database was 7. When three items
were used in a study with a scale ranging from 1 to 5 (e.g., Dreher & Ash, 1990), the scale maximum recorded in the database
depended on how authors reported the job satisfaction score. In one such study, the satisfaction score was reported as 3.30 (Rice,
Philips, & McFarlin, 1990), or the mean of three responses on a 1 to 5 Likert-scale. In this case, the scale maximum was recorded as
5. In another study using three items and a 1 to 5 Likert-scale, the satisfaction score was reported as 10.28 (Lee & Martin, 1991), or
the average in the sample of the sum of three responses. For this study, the scale maximum is recorded as 15 (three items times 5
Job satisfaction Pay satisfaction
Moderator kr ρ kr ρ
Measure of pay level
Exact 23 .12 .13*
24 .22 .23*
Interval 28 .15 .17*
19 .22 .24*
Independence of sources
Same source 48 .14 .15*
39 .22 .23*
Different source 10 .15 .16*
8 .22 .23*
Measure of satisfaction
MSQ 10 .23 .24*
4 .22 .23*
JDI (not including JDS) 5 .22 .24*
10 .19 .20*
Other 40 .12 .13*
18 .25 .27*
PSQ 14 .16 .16*
United States 52 .14 .15*
36 .22 .23*
International 10 .18 .21*
11 .18 .19*
Published 43 .13 .14*
36 .17 .18*
Unpublished 4 .13 .14*
Rank of journal source
Top-tier published (21) 23 .12 .13*
24 .14 .14*
Other published 20 .15 .16* 12 .21 .22*
Unpublished 4 .13 .14*
Rank of journal source
Top-tier published (6) 17 .12 .13*
18 .10 .11*
Other published 26 .15 .16* 18 .23 .24*
Unpublished 4 .13 .14*
Notes: k= number of correlations. N= combined sample size. r= mean observed correlation. ρ = estimated true score correlation.
Gomez = Meija and Balkin
Zickar and Highhouse (2001). *90% conﬁdence interval excluded zero.
80% credibility interval excluded zero. Correlations reported for relationships
where k=1 are not population estimates. Credibility and conﬁdence intervals were not calculated for relationships where k=1.
161T.A. Judge et al. / Journal of Vocational Behavior 77 (2010) 157–167
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scale points). Finally, we calculated a “percent of scale maximum”score for each study by dividing the reported satisfaction score
(mean or cumulative) by the calculated scale maximum.
To standardize the reported salaries, we converted the salary ﬁgures reported in each study to 2009 U. S. dollars using an online
conversion calculator provided by the U.S. Bureau of Labor Statistics (http://www.bls.gov/data/inﬂation_calculator.htm). For
studies that did not report the year in which the pay data were collected, we recorded the pay year as 2 years prior to study
publication date. For example, when an author of a study published in 1992 did not report the year in which pay data were
collected, we entered 1990 as the baseline conversion year in our database. It was assumed by the authors that the average time
between data collection and publication, including revision and print, was approximately two years.
The mean pay level (in 2009 $U. S.) for all 61 studies included in the between-study analysis was $64,119. The average percent
of job satisfaction scale maximum was 76%. The average percent of pay satisfaction scale maximum was 65%. Fig. 1 is a scatter-plot
of the study reported mean pay level and percent of job satisfaction scale maximum. As the ﬁgure indicates, the average level of job
satisfaction remains relatively stable across studies, regardless of the change in mean pay level. In other words, the reported level
of job satisfaction is independent of pay level across studies and across pay levels. Employees earning salaries in the top half of our
data range (N$64,000) reported similar levels of job satisfaction to those employees earning salaries in the bottom-half of our data
range (≤$64,000). Fig. 2 is a scatter-plot of mean pay level and percent of pay satisfaction scale maximum. The results for pay
satisfaction are similar to those for job satisfaction.
There are few more visible hallmarks of success in society than those owing to the income of individuals. Comparatively
wealthy people are able to afford a whole host of goods and services—homes, schooling, health care, luxuries—that presumably
greatly enhance quality of life. That the jobs which provide these things are little satisfying to individuals is, at ﬁrst blush,
surprising. Both within- and between-studies, level of pay had little relation to either job or pay satisfaction. This indicates that
within an organization, those who make more money are little more satisﬁed than those who make considerably less. Moreover,
relatively well paid samples of individuals are only trivially more satisﬁed than relatively poorly paid samples. For example, in
2009 dollars, a sample of lawyers earning an average of $148,000 per year was less job satisﬁed (68% of scale maximum; Wallace,
2001) than a sample of child care workers earning $23,500 per year (79% of scale maximum; Kontos & Stremmel, 1988). Of course,
there were counter examples where higher pay was associated with higher job satisfaction, but in general the ﬁndings suggested
little relationship between level of pay and satisfaction with one's job or one's pay.
The result for pay satisfaction is particularly surprising. One might argue that pay level is weakly related to overall job
satisfaction because, of the facets of job satisfaction, pay is not as important as other facets such as work satisfaction (Judge &
Church, 2000). However, when pay level bears only a slightly stronger relationship with pay satisfaction than with overall job
satisfaction, such an argument is not plausible. Past qualitative reviews have suggested that pay level is a strong predictor of pay
satisfaction (Heneman, 1985). The results of this review—the ﬁrst quantitative review to appear in the literature—suggests that
earnings are only weakly satisfying to individuals even when they conﬁne their satisfaction to an evaluation to their pay.
One explanation for these ﬁndings can be found in adaptation level theory (Helson, 1947). Adaptation level theory posits that
judgments of experience are relative to a reference point that shifts with past experience and current background stimuli.
Although originally formulated in the area of visual studies (e.g., how perception of a color is affected by contrasts with
Fig. 1. Between-study relationship between average pay level and average level of job satisfaction.
162 T.A. Judge et al. / Journal of Vocational Behavior 77 (2010) 157–167
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background colors), adaptation level theory has been applied in many areas of psychology, including consumer behavior (e.g.,
Niedrich, Sharma, & Wedell, 2001), personality (e.g., Goldstone & Goldfarb, 1964), and social psychology (Marshall & Kidd, 1981).
Lucas, Clark, Georgellis, and Diener (2003) found that individuals adapted very quickly to social events. Individuals' life satisfaction
increased after getting married, but this apparent boost was mostly due to initial reactions, and individuals quickly returned to
their pre-marriage set-point. Thus, in the context of the present study, as soon as an individual receives an increase in pay, it may
be quickly psychologically “spent”and thereby loses its satisfying value. Indeed, rising aspirations in response to rising incomes
have been documented in the subjective well-being literature (Frey & Stutzer, 2002). It would be interesting to test this process in
future job satisfaction research.
This study has implications for employees and employers. For the employee, if the ultimate goal in a job is to ﬁnd one that is
satisfying, given a choice, individuals would be better off weighing other job attributes more heavily than pay. For example,
intrinsic job characteristics—even when objectively measured (via job complexity)—better predict job satisfaction than,
apparently, does pay (Judge & Church, 2000). Moreover, although individuals often cannot choose their leaders, leadership
behaviors such as consideration (Judge et al., 2004) display non-trivial correlations with job satisfaction. Further, when individuals
are asked what would most improve the quality of their lives, the most common response is a higher income (Campbell, 1981). Yet
if job satisfaction can be equated with the perceived quality of one's job, then our results suggest that many employees are
mistaken about what would improve the perceived quality of their work life.
For employers, several aspects of the results are salient. First, it is important to be mindful of the fact that even though level of
pay may have a limited ability to satisfy, that does not mean that pay is not motivating. Although scholars differ on the motivating
effects of incentives (see Gerhart & Rynes, 2003; Pfeffer, 1998), it is clear that to many individuals, pay is motivating. Second,
employers should realize that being a pay leader is not likely, by itself, to result in a satisﬁed workforce. Given that job satisfaction
is related to employee withdrawal (Hulin, 1991), and the ﬁnancial effects of positive job attitudes are well-documented (Harter,
Schmidt, & Hayes, 2002), employers interested in having a satisﬁed workforce may need to turn elsewhere to raise job satisfaction
Interestingly, research in the subjective well-being literature suggests that income is satisfying only so far as one's income is
higher than others. So, for example, if incomes generally rise within a nation, individuals are no more satisﬁed with their lives
because, while their income has risen, so have those of others generally. From an organizational standpoint, this suggests that
being a pay leader may have little effect on job satisfaction because the people to whom individuals would naturally compare
themselves—their fellow co-workers—also are paid at above-market levels. Following this logic, high pay would satisfy the
employee only to the extent that there was high pay dispersion in the organization, which creates an interesting pay policy
dilemma for employers. To the extent one is able to distinguish pay levels, and those most highly paid are the ones the
organization wishes to keep, a policy of high pay dispersion may make sense. Indeed, Trevor, Gerhart, and Boudreau (1997) found
that rewards were particularly effective in retaining high performers. It would be interesting to see how this framework would
translate into pay/job satisfaction.
Fig. 2. Between-study relationship between average pay level and average level of pay satisfaction.
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Limitations and future research
One limitation inherent in all meta-analyses, including this one, is that we were not able to investigate several relevant
moderators of the relationship between pay level and job satisfaction. Possible moderators of the relationship include the degree
to which pay is valued by employees (Locke, 1969), frames of reference (Hulin, 1991), and expectations (Lawler, 1971).
Unfortunately, we were not able to code these moderators at the study level. Given the overall weak effects, however, beyond the
moderators studied herein, it would be worthwhile to discover for whom pay is satisfying, and under what conditions. Initial
efforts to study moderators of the relationship are underway (Malka & Chatman, 2003), and should continue.
Another interesting area for future research lies in the goals that individuals have with respect to their income. Kasser and Ryan
(1993) concluded that those who have ﬁnancial goals (i.e., the importance placed on ﬁnancial success relative to other aspirations
such as self-acceptance and afﬁliation with others) are less happy. Srivastava et al. (2001) argued that the motives behind the goal
are what matters. Speciﬁcally, Srivastava et al. found that once the reasons underlying the pursuit of money were controlled, the
importance placed on money was unrelated to subjective well-being. In the realm of job satisfaction, perhaps it is not the money
per se one makes but more the reason why one makes it that matters. Paradoxically, it may be that earning relatively large amounts
of money is more satisfying when the individual does not have earning money as an explicit goal. Alternatively, it may be that
having a goal to earn money is satisfying, if it is the right motive. Locke, McClear, and Knight (1996) suggest that ﬁnancial goals
differ in their ability to contribute to well-being or self-concept, and Srivastava et al. (2001) found that income goals which are
based on seeking power, showing off, and overcoming self-doubt are less satisfying than income goals based on security, familial
support, and leisure time. These are all issues for future research to consider in detail.
Finally, it would be interesting for future research to investigate another psychological process that may explain our results.
Lucas et al. (2003) argued that a process of hedonic leveling occurs which tends to equalize individuals' well-being. For individuals
whose lives are going well, for example, positive events are less likely to affect them because they have less to gain (and, by the
same token, more to lose from negative events). Conversely, those whose lives are going poorly have more to gain from positive
events, and thus may be more affected by these events (and less affected by negative events). Applied to this study, the hedonic
leveling process suggests that high pay levels may be more satisfying to relatively deprived individuals (where relative deprivation
is based on their past experience; Crosby, 1976). Indeed, there is some initial cross-sectional support for this proposition
(Sweeney, McFarlin, & Inderrieden, 1990). For the same reason, increases in pay may be more satisfying to those at the low end of
the pay scale. These would be interesting avenues for future research to explore.
In sum, this study provided the ﬁrst meta-analytic evidence on the relationship of pay to job and pay satisfaction. The results
suggest that, within-studies, level of pay bears a positive, but quite modest, relationship to job and pay satisfaction. Between
studies, there also is little relationship between average pay in a sample and the average level of job or pay satisfaction. Future
research could build on these results by testing theoretical mechanisms that may explain why that which so motivates us has such
little potential to satisfy.
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