fringe benefits and job satisfaction
DESCRIPTION
Fringe Benefits and Job SatisfactionTRANSCRIPT
International Journal of ManpowerFringe benefits and job satisfactionBenjamin Artz
Article information:To cite this document:Benjamin Artz, (2010),"Fringe benefits and job satisfaction", International Journal of Manpower, Vol. 31 Iss6 pp. 626 - 644Permanent link to this document:http://dx.doi.org/10.1108/01437721011073346
Downloaded on: 22 January 2016, At: 09:56 (PT)References: this document contains references to 32 other documents.To copy this document: [email protected] fulltext of this document has been downloaded 9343 times since 2010*
Users who downloaded this article also downloaded:Mark A. Tietjen, Robert M. Myers, (1998),"Motivation and job satisfaction", Management Decision, Vol. 36Iss 4 pp. 226-231 http://dx.doi.org/10.1108/00251749810211027Carolyn Stringer, Jeni Didham, Paul Theivananthampillai, (2011),"Motivation, pay satisfaction, and jobsatisfaction of front-line employees", Qualitative Research in Accounting & Management, Vol. 8 Iss 2pp. 161-179 http://dx.doi.org/10.1108/11766091111137564Daulatram B. Lund, (2003),"Organizational culture and job satisfaction", Journal of Business &Industrial Marketing, Vol. 18 Iss 3 pp. 219-236 http://dx.doi.org/10.1108/0885862031047313
Access to this document was granted through an Emerald subscription provided by emerald-srm:586319 []
For AuthorsIf you would like to write for this, or any other Emerald publication, then please use our Emerald forAuthors service information about how to choose which publication to write for and submission guidelinesare available for all. Please visit www.emeraldinsight.com/authors for more information.
About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The companymanages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well asproviding an extensive range of online products and additional customer resources and services.
Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committeeon Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archivepreservation.
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
*Related content and download information correct at time of download.
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
Fringe benefits and jobsatisfaction
Benjamin ArtzDepartment of Economics, American University of Sharjah, Sharjah,
United Arab Emirates
Abstract
Purpose – The paper seeks to empirically identify the theoretically ambiguous relationship betweenemployer fringe benefit provision and worker job satisfaction.
Design/methodology/approach – Using the five most recent waves of the National LongitudinalSurvey of Youth, both pooled cross-section and fixed effects estimates explain the relationshipbetween fringe benefits and job satisfaction. The potential endogenous relationship is also tested usinga recursive bivariate probit procedure.
Findings – Fringe benefits are significant and positive determinants of job satisfaction. The potentialendogeneity between fringe benefits and job satisfaction is not shown in this dataset while controllingfor fixed effects does not remove the significant impact of fringe benefits.
Research limitations/implications – A limitation is the inability to control for total compensationwithin the estimations and control for wage changes as a result of fringe benefit provision.
Practical implications – Higher levels of worker job satisfaction, potentially resulting from fringebenefit provisions, have been linked to important productivity measures such as lower quit rates andabsenteeism.
Originality/value – The paper is the first to study the relationship between fringe benefits and jobsatisfaction in detail while additionally testing for the endogeneity of the relationship and controllingfor fixed effects.
Keywords Job satisfaction, Benefits, Compensation, Employee attitudes
Paper type Research paper
1. IntroductionEstablishing the determinants of job satisfaction remains at the forefront of empiricaltesting in using measures of on-the-job utility. At first consideration, desirable jobattributes such as fringe benefits should increase job satisfaction. However, the pastevidence is mixed at best and contradictory at worst. While a valuable form ofcompensation, employer provided benefits may lower earnings or reduce job mobility.This is particularly evident in the USA where many benefits are employer provided andnot transferable between jobs. Thus, the theoretical impact of fringe benefits on jobsatisfaction is not immediately clear.
Fringe benefits can impact job satisfaction in several ways. First, fringe benefits standas an important component of worker compensation. The National Compensation Surveyconducted by the Bureau of Labor Statistics estimated that benefits made up 30 per centof total compensation for all US civilian workers in 2006[1] Some benefits such asSocial Security and Medicare, the country’s publicly provided elderly pension and
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0143-7720.htm
The author would like to thanks John Heywood and the participants of the Labor Seminar Seriesat the University of Wisconsin – Milwaukee for comments and guidance as well as twoanonymous referees for their insight and suggestions.
IJM31,6
626
International Journal of ManpowerVol. 31 No. 6, 2010pp. 626-644q Emerald Group Publishing Limited0143-7720DOI 10.1108/01437721011073346
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
health insurance, are legally required and make up roughly 27 per cent of all benefitcompensation. The remaining 73 per cent of benefit compensation is comprised mostly ofpaid leave, insurance plans and retirement and savings plans. These benefits are often notsubject to taxation and are, therefore, cheaper to gain through an employer than throughthe market (Alpert, 1987). Consequently, cheaper benefits should increase worker jobsatisfaction.
Second, fringe benefits can act as valuable substitutes for wages. Employers maychoose to offer fringe benefits since workers can have strong preferences for fringebenefits thus decreasing the prevalence of turnover as effectively as an equivalentlyvaluable increase in wages (Dale-Olsen, 2006). In addition, Baughman et al. (2003)examined employer survey data and found that employers decreased wages onceseveral benefits had been offered to employees after a few years. Woodbury (1983) foundthat workers also view benefits and wages as substitutes, willing to give up wages inexchange for more benefits. This substitution can increase job satisfaction if theworker’s marginal income tax rate decreases after giving up wages for fringe benefits.The less taxed fringe benefits can be substituted for wages and increase job satisfactionby saving the worker from increased tax burden.
Third, the substitution between wages and benefits can have a negative impact on jobsatisfaction if workers find they must sacrifice wages and accept provision of a fringebenefit they do not necessarily desire. For instance, workers’ spouses may already haveprovision of a particular fringe benefit, so a second provision of that fringe benefit maybe viewed as wasteful and can therefore decrease job satisfaction, especially if wages arelower as a result. On the other hand, workers may find a particular fringe benefit asessential. Workers may have a feeling of job-lock to a particular employer or job if theyare uncertain about the provision of the necessary fringe benefit at a different place ofwork. For example, pre-existing health conditions are often not covered underemployer-provided health insurance, providing a need for employees to remain at jobsthat they may not be satisfied with (Adams, 2004). The combination of uncertainty andjob-lock can decrease job satisfaction.
Since the expected impact of fringe benefits on job satisfaction is unclear, it is notsurprising that past research is inconclusive. When included in typical estimates, theimpact of fringe benefits on job satisfaction is rarely significant. In addition, the evidencemainly depends on cross-sectional comparisons, raising questions about potentialbiases. First, the impact of a particular fringe benefit on job satisfaction can bemisleading if the worker has unmeasured individual specific determinants of jobsatisfaction. Indeed, we cannot assume that workers are randomly sorted into jobs butrather that they sort themselves into the jobs that suit their preferences. In addition, jobsatisfaction and fringe benefits may be simultaneously determined such that fringebenefits are endogenous in determining job satisfaction.
Thus, the relationship between fringe benefits and job satisfaction has not beenappropriately tested. Very little past research has isolated and examined fringe benefitsas a primary determinant of job satisfaction, few studies have included as many fringebenefits as are available in the US National Longitudinal Survey of Youth (NLSY) andnone have studied the relationship between fringe benefits and job satisfaction in detail,controlling for fixed effects and testing for endogeneity[2].
In distinction to past results, a pooled cross-section of five NLSY waves suggests thatfringe benefits are important in determining job satisfaction. In addition several
Fringe benefits
627
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
sub-sample estimations suggest fringe benefits are more significant in determining thejob satisfaction of particular groups such as workers with children at home or non-unionworkers. Then, in order to test for the simultaneous determination of fringe benefits andjob satisfaction, a recursive bivariate probit model is used to test for the possiblecorrelation between the disturbances in job satisfaction and fringe benefit structuralequations. The cross-equation correlation is not significantly different from zero,implying that fringe benefits can be treated as exogenous in an estimation of jobsatisfaction and can be properly estimated within the ordered probit framework used inthe pooled cross-section. Finally, after worker sorting is controlled for in fixed effectsestimates, the results are not considerably different from those of the pooledcross-section estimates, further confirming the importance of fringe benefits indetermining worker job satisfaction.
The following section discusses previous research, the uncertain relationshipbetween fringe benefits and job satisfaction and the need for a detailed study on thetopic. Section 3 outlines the data that is used and the primary empirical methodologyused to test the relationship. Section 4 discusses the results while Section 5 outlines testsfor endogeneity and unobservable worker characteristics as possible biases of theprimary results. The final section concludes.
2. Past research and ambiguous resultsOver the past four decades, economists have given job satisfaction increasingattention. Job satisfaction is negatively related to job turnover (Freeman, 1978; McEvoyand Cascio, 1985; Akerlof et al., 1988; Weiss, 1984), absenteeism (Clegg, 1983) andpositively related to productivity (Mangione and Quinn, 1975). Therefore, it is useful tounderstand which job characteristics and provisions increase job satisfaction.
Although fringe benefits stand as an important piece of worker compensationpackages they have not been given much attention in the job satisfaction literature. Fringebenefits have merely acted as controls in most studies and not as the primary subject ofscrutiny. Indeed, more than one or two measures of fringe benefits are rarely found asindependent variables in job satisfaction studies.
Rather, pensions often act as the predominant proxy for fringe benefit provisionwithin the job satisfaction literature and consequently the estimated impact of fringebenefits on job satisfaction[3]. Some studies such as Artz (2008) and Donohue andHeywood (2004) find that pensions do not significantly impact job satisfaction incross-section estimates. Yet Bender et al. (2005), Heywood and Wei (2006) and Benderand Heywood (2006) find that pensions positively impact job satisfaction in cross-sectionestimates. Still others find the opposite result. Heywood et al. (2002) use the 1991-1994waves of the British Household Panel Study and find that pensions negatively impact jobsatisfaction while Luchak and Gellatly (2002), in a particularly interesting study,consider the impact of pension accrual on job satisfaction using a dedicated sample of429 employees in a large, unionized public utility company in Canada. They posit that asemployees’ pensions increase in value over their job tenure, workers may feel morevulnerable to job loss since firms may opportunistically layoff employees to reducepension liabilities. The authors use this hypothesis to explain their result that pensionaccrual decreases job satisfaction[4].
Although pensions are the predominant proxy for fringe benefits, some authorsdo include multiple fringe benefit measures as independent variables in their
IJM31,6
628
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
respective models. Donohue and Heywood (2004) report positively significantestimates for such variables as paid vacation and sick pay but no significance for anyof the remaining benefits: child care, pension, profit sharing, employer providedtraining/education and health insurance. Uppal (2005) uses a measure comprised of thenumber of fringe benefits employees receive and finds that this is positively related tojob satisfaction. However, Benz (2005) includes most of the fringe benefits found inNLSY waves 1994-2000 in his study of employees of non-profit organizations and findsonly two out of nine fringe benefits are positive and significantly related to jobsatisfaction and that one is negative and significant.
The ambiguous results of past estimates arise primarily from the conflictingtheoretical effects that fringe benefits can have on job satisfaction, but theory may not bethe only explanation for the differences. Some of these mixed results may stem from theuse of alternative sources of data or from the differences in institutions or labor marketsbetween countries. Particularly in the USA, benefits can have a different impact on jobsatisfaction than elsewhere because many benefits such as pensions and healthinsurance are employer provided and do not necessarily move with an employee upon achange in employer. This characteristic of the US labor market explains how fringebenefits may impact job satisfaction in a different way than in other countries wherepublicly provided fringe benefits are more commonplace.
3. Data and methodologyThe data used are five waves of the NLSY with each wave representing every other yearfrom 1996 to 2004. All five waves of this USA data contain a measure of overall jobsatisfaction and dozens of control variables including occupation and industry codes aswell as demographic and job characteristics. In total, there are 24,090 observations afterpooling the five waves of data. The sample includes all workers except those claiming tobe self-employed. This paper assumes fringe benefits are likely to have a differentimpact on the job satisfaction of self-employed workers and thus adversely affectthe desired estimations. The mean, standard deviations and definitions of all utilizedvariables are presented in Table I. The NLSY is unique in that it offers many differentkinds of fringe benefit variables for analysis as well as longitudinal data that can beused to control for fixed effects. This paper specifically includes eight differentemployer-provided or employer-offered fringe benefits as well as generated variablesrepresenting the quantity of these benefits individuals claim to have. The lattervariables present the general importance of fringe benefits in determining jobsatisfaction rather than each individual fringe benefit’s significance.
Overall, job satisfaction is measured on a scale of one to four, four representing thehighest level of job satisfaction. The typical cross-section estimate of job satisfaction fitsthis Likert scale to the cumulative normal distribution through the ordered-probitestimation. An ordered-probit estimation is commonly used in order to capture all of thevariation between subjective measures of job satisfaction that are not necessarily linearin nature. While cross-sectional data of individual years have been used in past studies,a problem may arise from the inability of the individual waves of the NLSY to exhibitenough variation among fringe benefits and job satisfaction to properly estimate theimpact of fringe benefits on job satisfaction[5]. Therefore, pooled cross-sectionestimation is used to expand the sample size. Since pooling longitudinal data generallycauses correlation within the individual worker observations across the waves of data,
Fringe benefits
629
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
clustering standard errors by individual respondent is necessary to maintain consistentestimators. After doing so, the dataset contains a larger sample size and offers moreconvincing results. Additionally, sampling weights are used to adjust the surveyobservations in order to fit the population better as well as correct for such surveyvariations as sample under-coverage.
4. ResultsThe pooled cross-section estimation results are presented in Table II. The first columnshows that a continuous variable consisting of fringe benefit quantities workers claim
Variables Definitions Mean SD
Job satisfaction ¼ 4 if very satisfied, 3 if satisfied, 2 if unsatisfiedand 1 if very unsatisfied 3.369 0.692
Flexible work hours ¼ 1 if employer allows flexible work hours or aflexible schedule 0.537 0.499
Pension or retirement ¼ 1 if employer provides a pension or retirementplan 0.608 0.488
Dental insurance ¼ 1 if employer offers dental insurance 0.700 0.458Parental leave ¼ 1 if employer allows maternity or paternity leave 0.702 0.457Child care ¼ 1 if employer provides or subsidizes child care 0.089 0.285Vacation days ¼ 1 if worker has paid vacation days 0.829 0.376Profit sharing ¼ 1 if employer offers profit sharing 0.270 0.444Health insurance ¼ 1 if employer offers off the job health insurance 0.807 0.394Female ¼ 1 if respondent is female 0.507 0.500Black ¼ 1 if respondent in Black 0.294 0.456Hispanic ¼ 1 if respondent is Hispanic 0.192 0.394High school education ¼ 1 if highest grade completed is 12 0.447 0.497College education ¼ 1 if highest grade completed is more than 12 but
less than 17 0.368 0.482Post college education ¼ 1 if highest grade completed is more than 16 0.089 0.285Age ¼ age of respondent 38.789 3.575Health impairs job ¼ 1 if respondent has any health conditions that
limit job performance 0.070 0.255Married ¼ 1 if respondent is currently married 0.626 0.484Urban residence ¼ 1 if respondent lives in an urban area 0.744 0.437Hourly wage ¼ wage calculation based on respondent’s usual
wage, time unit of pay and usual hours workedper time unit 16.343 15.080
Weekly hours worked ¼ usual hours worked per week 41.416 9.621Tenure ¼ tenure in weeks with employer as of interview
date 332.448 308.96Recent promotion ¼ 1 if recent position change was a promotion 0.154 0.361Union member ¼ 1 if respondent is a member of a labor union 0.175 0.380Public employer ¼ 1 if respondent works for the government 0.183 0.386Medium firm ¼ 1 if respondent has between 50 and 249
coworkers 0.264 0.441Big firm ¼ 1 if respondent has greater than or equal to
250 coworkers 0.303 0.459Observations ¼ number of pooled sample observations 24,090
Table I.Variable definitionsand sample means
IJM31,6
630
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
Poo
led
cros
sse
ctio
nw
aves
1996
-200
4
Fri
ng
eb
enefi
ts(0
-8)
0.06
1*
**
(0.0
06)
[0.0
24]
––
On
efr
ing
eb
enefi
t–
0.09
1*
(0.0
53)
[0.0
36]
–T
wo
frin
ge
ben
efits
–0.
154
**
*(0
.058
)[0
.062
]–
Th
ree
frin
ge
ben
efits
–0.
142
**
*(0
.054
)[0
.057
]–
Fou
rfr
ing
eb
enefi
ts–
0.17
5*
**
(0.0
52)
[0.0
70]
–F
ive
frin
ge
ben
efits
–0.
249
**
*(0
.050
)[0
.099
]–
Six
frin
ge
ben
efits
–0.
299
**
*(0
.052
)[0
.119
]–
Sev
enfr
ing
eb
enefi
ts–
0.47
2*
**
(0.0
56)
[0.1
86]
–E
igh
tfr
ing
eb
enefi
ts–
0.62
3*
**
(0.0
80)
[0.2
39]
–F
lex
ible
wor
kh
ours
––
0.22
4*
**
(0.0
22)
[0.0
89]
Pen
sion
orre
tire
men
tp
lan
––
0.06
8*
**
(0.0
25)
[0.0
27]
Den
tal
insu
ran
ce–
–0.
052
(0.0
33)
[0.0
21]
Par
enta
lle
ave
––
0.11
7*
**
(0.0
28)
[0.0
46]
Em
plo
yer
pro
vid
edch
ild
care
––
0.10
5*
*(0
.042
)[0
.042
]E
mp
loy
erof
fere
dv
acat
ion
day
s–
–2
0.03
5(0
.034
)[2
0.01
4]P
rofi
tsh
arin
g–
–0.
061
**
(0.0
26)
[0.0
24]
Em
plo
yer
pro
vid
edh
ealt
hin
sura
nce
––
20.
078
*(0
.041
)[2
0.03
1]F
emal
e0.
076
**
*(0
.029
)0.
076
**
*(0
.028
)0.
065
**
(0.0
29)
Bla
ck2
0.06
8*
*(0
.029
)2
0.07
6*
**
(0.0
29)
20.
073
**
(0.0
29)
His
pan
ic0.
110
**
*(0
.032
)0.
108
**
*(0
.032
)0.
111
**
*(0
.032
)H
igh
sch
ool
edu
cati
on2
0.08
4*
(0.0
43)
20.
079
*(0
.043
)2
0.08
4*
*(0
.043
)C
olle
ge
edu
cati
on2
0.13
6*
**
(0.0
47)
20.
131
**
*(0
.046
)2
0.14
2*
**
(0.0
47)
Pos
tco
lleg
eed
uca
tion
20.
015
(0.0
65)
20.
011
(0.0
65)
20.
025
(0.0
65)
Ag
e0.
011
(0.0
45)
0.00
9(0
.045
)0.
005
(0.0
45)
Ag
esq
uar
ed2
0.01
4(0
.058
)2
0.01
1(0
.058
)2
0.00
7(0
.058
)M
arri
ed0.
066
**
*(0
.024
)0.
068
**
*(0
.024
)0.
069
**
*(0
.024
)H
ealt
him
pai
rsjo
b2
0.16
3*
**
(0.0
41)
20.
166
**
*(0
.041
)2
0.16
9*
**
(0.0
42)
Urb
anre
sid
ence
20.
070
**
*(0
.025
)2
0.07
1*
**
(0.0
25)
20.
070
**
*(0
.025
)N
orth
east
reg
ion
20.
131
**
*(0
.043
)2
0.12
8*
**
(0.0
43)
20.
123
**
*(0
.043
)M
idw
est
reg
ion
20.
061
(0.0
39)
20.
062
(0.0
39)
20.
063
(0.0
39)
Sou
thre
gio
n2
0.00
5(0
.037
)2
0.00
2(0
.037
)0.
007
(0.0
37)
Log
hou
rly
wag
es0.
137
**
*(0
.027
)0.
140
**
*(0
.027
)0.
149
**
*(0
.027
)
(continued
)
Table II.Pooled cross-section
results (1996-2004NLSY waves)
Fringe benefits
631
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
Poo
led
cros
sse
ctio
nw
aves
1996
-200
4
Log
wee
kly
hou
rsw
ork
ed2
0.04
7(0
.040
)2
0.03
7(0
.040
)0.
015
(0.0
41)
Ten
ure
inw
eek
sd
ivid
edb
y1,
000
20.
642
**
*(0
.114
)2
0.62
2*
**
(0.1
14)
20.
575
**
*(0
.115
)(T
enu
rein
wee
ks
div
ided
by
1,00
0)sq
uar
ed0.
428
**
*(0
.111
)0.
416
**
*(0
.111
)0.
383
**
*(0
.111
)R
ecen
tp
rom
otio
n0.
226
**
*(0
.026
)0.
224
**
*(0
.026
)0.
226
**
*(0
.026
)U
nio
nm
emb
er2
0.03
(0.0
34)
20.
019
(0.0
35)
20.
006
(0.0
35)
Pu
bli
cem
plo
yer
0.24
2*
**
(0.0
42)
0.25
6*
**
(0.0
43)
0.27
0*
**
(0.0
43)
Med
ium
firm
20.
156
**
*(0
.029
)2
0.14
9*
**
(0.0
29)
20.
135
**
*(0
.029
)B
igfi
rm2
0.25
2*
**
(0.0
30)
20.
256
**
*(0
.030
)2
0.24
7*
**
(0.0
30)
Occ
up
atio
nco
ntr
ols
Yes
Yes
Yes
Ind
ust
ryco
ntr
ols
Yes
Yes
Yes
Cu
tp
oin
t1
21.
891
**
(0.8
90)
21.
897
**
(0.8
90)
21.
760
**
(0.8
91)
Cu
tp
oin
t2
21.
237
(0.8
91)
21.
242
(0.8
91)
21.
101
(0.8
92)
Cu
tp
oin
t3
0.30
1(0
.891
)0.
297
(0.8
91)
0.44
4(0
.892
)N
o.of
obse
rvat
ion
s24
,090
24,0
9024
,090
Notes:
Rep
rese
nt
stat
isti
cal
sig
nifi
can
ceat
the
* 10,
** 5
,*
** 1
per
cen
tle
vel
sre
spec
tiv
ely
;sta
nd
ard
erro
rsar
ecl
ust
ered
by
ind
ivid
ual
iden
tifi
cati
onan
dar
ein
par
enth
eses
;m
arg
inal
effe
cts
are
inb
rack
ets;
ten
ure
isd
ivid
edb
y1,
000
inor
der
tod
isp
lay
its
coef
fici
ent
ina
mor
eco
mp
lete
fash
ion
Table II.
IJM31,6
632
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
to have is significantly and positively related to job satisfaction. Also, fringe benefitquantity dummies located in the second column of Table II tell a convincing story.The estimated impact of fringe benefits on job satisfaction generally grows both in sizeand significance as the number of fringe benefits increases. Although these twocolumns do not indicate which particular fringe benefits are important to worker jobsatisfaction, they do show that fringe benefits are important as a whole and need to beincluded in job satisfaction estimations and not overlooked as an insignificantdetermining factor of job satisfaction.
The third column considers individual fringe benefits and shows that five out of eighthave a significantly positive impact on job satisfaction with only one, health insurance,showing a significantly negative coefficient. As mentioned, health insurance maydecrease job satisfaction if the worker’s spouse already has it, effectively lowering theworker’s wages for a duplicate and unnecessary fringe benefit. Also, health insurance maycreate job lock if an employee cannot leave an unsatisfactory job and health insurance isnot available at other, more appealing jobs.
While direction and significance of the estimation coefficients are important, theirmagnitudes are equally crucial in determining the complete impact of fringe benefitprovision on job satisfaction. Marginal effects are reported in brackets within Table II foreach fringe benefit variable, representing how much an additional benefit might changethe proportion of workers that report the highest level of job satisfaction. For instance,if workers change from having no fringe benefits to six fringe benefits, the percentage ofworkers reporting the highest level of job satisfaction can be expected to increase bynearly 12 per cent. Similarly if an employer begins offering a pension or retirementplan, workers reporting very high job satisfaction may increase by nearly 3 per cent.The magnitudes reinforce the notion that fringe benefits are indeed important indetermining employee job satisfaction.
Each benefit, such as health insurance, illustrates a distinct explanation for itsindividual impact on job satisfaction and offers broad conclusions regarding the type ofworker that may value a particular fringe benefit. In order to examine the prevalence of therole of fringe benefits, the pooled dataset is split four ways and cross-sections areestimated for each demographic sub-sample of the dataset. The results are shown inTable III. First, the sample is split by gender and pooled cross-sections of each sub-sampleare estimated. Both males and females seem to value similar fringe benefits includingflexible work hours, parental leave and employer provided child care. However, onlyfemales significantly value pensions while only males value profit sharing[6].
Next, the impact of fringe benefits on job satisfaction for union members is comparedto non-union members. As a result of collective bargaining, union members generallyhave more fringe benefits than non-union members. Specifically, though, non-unionworkers seem to value fringe benefits more than union workers. Both groups valueflexible work hours and profit sharing, yet only non-union workers additionally valuepensions, parental leave and employer provided childcare. It is evident that fringebenefits are not as important in determining the job satisfaction of union workers as theyare for non-union workers. Union workers may take fringe benefit provision for granteddue in part to their bargaining power, effectively reducing the relationship betweenfringe benefits and job satisfaction[7].
The sample is then split by marital status indicated at the time of the respondent’sinterview. Flexible work hours, pensions and parental leave are positively
Fringe benefits
633
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
Fem
ales
Mal
esU
nio
nm
emb
ers
Non
-un
ion
mem
ber
sM
arri
edS
ing
leC
hil
dre
nat
hom
eN
och
ild
ren
ath
ome
Fle
xib
lew
ork
hou
rs0.
208
**
*(0
.031
)0.
232
**
*(0
.032
)0.
126
**
(0.0
57)
0.24
8*
**
(0.0
24)
0.25
7*
**
(0.0
28)
0.15
8*
**
(0.0
34)
0.23
5*
**
(0.0
27)
0.20
6*
**
(0.0
37)
Pen
sion
orre
tire
men
tp
lan
0.11
3*
**
(0.0
35)
0.02
6(0
.037
)0.
071
(0.0
59)
0.06
7*
*(0
.028
)0.
074
**
(0.0
32)
0.06
8*
(0.0
40)
0.07
3*
*(0
.031
)0.
059
(0.0
45)
Den
tal
insu
ran
ce0.
047
(0.0
49)
0.05
6(0
.046
)0.
088
(0.0
83)
0.03
6(0
.036
)0.
071
*(0
.042
)0.
027
(0.0
53)
0.06
8*
(0.0
40)
0.03
1(0
.057
)P
aren
tal
leav
e0.
133
**
*(0
.047
)0.
114
**
*(0
.036
)0.
070
(0.0
71)
0.12
7*
**
(0.0
30)
0.12
4*
**
(0.0
34)
0.10
0*
*(0
.048
)0.
136
**
*(0
.034
)0.
081
*(0
.048
)E
mp
loy
erp
rov
ided
chil
dca
re0.
090
*(0
.052
)0.
111
*(0
.067
)2
0.05
7(0
.129
)0.
139
**
*(0
.042
)0.
070
(0.0
53)
0.17
6*
**
(0.0
62)
0.14
7*
**
(0.0
51)
0.00
4(0
.070
)
Em
plo
yer
offe
red
vac
atio
nd
ays
20.
035
(0.0
46)
20.
015
(0.0
51)
20.
169
*(0
.091
)0.
006
(0.0
36)
20.
070
(0.0
44)
0.02
0(0
.052
)2
0.06
6(0
.041
)0.
021
(0.0
57)
Pro
fit
shar
ing
0.03
3(0
.037
)0.
082
**
(0.0
38)
0.17
1*
*(0
.070
)0.
047
*(0
.028
)0.
068
**
(0.0
33)
0.04
1(0
.042
)0.
065
**
(0.0
32)
0.05
8(0
.046
)E
mp
loy
erp
rov
ided
hea
lth
insu
ran
ce2
0.08
7(0
.061
)2
0.05
5(0
.057
)2
0.05
2(0
.135
)2
0.09
9*
*(0
.043
)2
0.10
9*
*(0
.053
)2
0.02
9(0
.062
)2
0.07
8(0
.051
)2
0.09
5(0
.067
)
Nor
mal
con
trol
sY
esY
esY
esY
esY
esY
esY
esY
esO
ccu
pat
ion
con
trol
sY
esY
esY
esY
esY
esY
esY
esY
esIn
du
stry
con
trol
sY
esY
esY
esY
esY
esY
esY
esY
esC
ut
poi
nt
12
1.67
4(1
.283
)2
1.40
9(1
.240
)2
3.16
8(2
.186
)2
1.45
9(0
.981
)2
1.91
1*
(1.0
93)
21.
784
(1.5
59)
21.
398
(1.0
80)
22.
910
*(1
.649
)C
ut
poi
nt
22
1.05
2(1
.282
)2
0.70
4(1
.243
)2
2.57
2(2
.187
)2
0.78
3(0
.981
)2
1.19
7(1
.094
)2
1.19
4(1
.558
)2
0.73
7(1
.080
)2
2.24
8(1
.652
)C
ut
poi
nt
30.
404
(1.2
82)
0.94
2(1
.244
)2
0.95
6(2
.187
)0.
755
(0.9
81)
0.38
8(1
.094
)0.
292
(1.5
59)
0.82
3(1
.080
)2
0.71
7(1
.653
)N
o.of
obse
rvat
ion
s12
,214
11,8
764,
212
19,8
7815
,084
9,00
616
,717
7,37
3
Notes:
Rep
rese
nt
stat
isti
cal
sig
nifi
can
ceat
the
* 10,
** 5,
**
* 1p
erce
nt
lev
els
resp
ecti
vel
y;
stan
dar
der
rors
are
clu
ster
edb
yin
div
idu
alid
enti
fica
tion
and
are
inp
aren
thes
es
Table III.Pooled cross-sectionresults of selectedsub-samples
IJM31,6
634
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
and significantly related to job satisfaction for both groups, yet interesting differencesremain. First, employer provided child care is only important for single workers.After all, married workers may not need employer provided child care if their spousehas time to look after the children. Second, employer provided health insuranceis significantly and negatively related to job satisfaction only for married workers.This may be a result of the wasteful duplication of fringe benefit provision amongspouses and the reduction of wages that results.
Finally, the sample is split between workers who have children at home and thosethat do not. Fringe benefits are often suited for workers with families so those withdependents at home are more likely to value fringe benefits than those that do not.As anticipated, six of the eight fringe benefits positively impact job satisfaction of workerswith children at home while only two significantly impact the job satisfaction of those withno dependents at home.
5. Robustness checksThe pooled cross-section results may be biased due to unobservable individualcharacteristics that are correlated with both job satisfaction and fringe benefits,generating a potential problem of workers sorting themselves into jobs with particularcharacteristics. This possible selection bias has often been controlled for by researchersin their cross-section estimates. Bender and Heywood (2006), McCausland et al. (2005)and Bryson et al. (2005) use instruments to control for worker selection into a particularoccupation, sector or performance payment system and find that selection issignificant. Green and Heywood (2008), Cornelissen et al. (2008) and Pouliakas andTheodossiou (2009) use panel data and a fixed effects estimator to control for workersorting. These studies confirm that researchers agree non-random worker sorting intovarious workplace characteristics is evident.
Without accounting for worker sorting, the pooled cross-section results of Table IImay be unreliable. Unobservable individual preferences decide, at least in part, theworker’s job satisfaction but also what fringe benefits workers receive. In order todiscover the true impact of fringe benefits on job satisfaction, we must first hold theeffects of unmeasured individual preferences on job satisfaction fixed and only allowobservable worker and job characteristics including the provision of fringe benefits tovary. The possibility of worker sorting necessitates the use of a fixed effects estimatorand is only possible by using panel data. As workers move from job to job, theirunobservable characteristics are assumed to remain constant but their fringe benefitsare allowed to vary. Therefore, if worker job satisfaction changes, it is due to changesonly in fringe benefits and other measurable characteristics.
A straightforward translation to a fixed effects estimator is provided by adichotomous logit procedure, the conditional logit[8]. This method estimates whetheror not a worker is very satisfied using the NLSY waves as panel data and is based onthe cumulative logistic distribution rather than the cumulative normal distribution.The logistic and normal distributions are quite similar, thus the logit and probitestimation results are comparable[9].
In the conditional logit procedure, individual workers are first categorized intogroups by their NLSY identification number across all five waves so that each group,or individual worker, consists of all the observations attributable to that worker.The conditional logit procedure then removes from the estimation all of the groups
Fringe benefits
635
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
that do not exhibit a change in their job satisfaction at all across the five waves. Theseindividuals do not contribute to the likelihood function and, therefore, have no effect onthe conditional probability of very high job satisfaction. Finally, the conditional logitremoves any independent variables from the regression that do not vary at all over thefive waves of data. These variables exhibit no within-group variation across the wavesand include not only race and gender but also characteristics among workers that areunobservable and assumed to remain constant. The result is a conditional probabilityof very high job satisfaction based entirely on observed characteristics of workers andjobs and not on fixed effects. The conditional logit model is more thoroughly presentedin the Appendix.
The results of the fixed effects estimation are presented in Table IV. The fringe benefitvariable portrayed in the first column remains a positive and significant determinant ofjob satisfaction[10]. Also, five individual fringe benefits remain significant and positivewhile health insurance remains negatively related to job satisfaction, though it lost itssignificance. In addition, most of the fringe benefit dummies reflecting the quantity ofbenefits retain their positive and significant relationship with job satisfaction. Thus, theunobservable individual characteristics of workers do not greatly alter the pooledcross-section results. These results may also be biased if worker job satisfaction and fringebenefit provision are simultaneously determined or endogenous. In other words,unmeasured determinants of job satisfaction might also determine fringe benefits foremployees.
A formal test of endogeneity between fringe benefits and job satisfaction has notbeen undertaken. Although not with job satisfaction, fringe benefits such as pensions,health insurance and paid vacations have been found to be endogenous in wageregressions and thus result in simultaneity bias in ordinary least squares estimates( Jensen and Morrisey, 2001). Since wages and job satisfaction are highly related, it ispossible that endogeneity between fringe benefits and wages could raise a similarsimultaneity bias between fringe benefits and job satisfaction. Therefore, a test forendogeneity should be employed to be certain that a two-stage least squares estimationis not required to control for the correlation in the error terms that jointly determinejob satisfaction and fringe benefits.
Normally, an instrument is used in a two-stage least squares procedure to correct forendogeneity between the dependent variable and independent variable of interest.However, in this case, job satisfaction and fringe benefit variables are categorical ratherthan continuous and so it is problematic to employ the same two-stage least squaresapproach. Rather, a recursive bivariate probit approach can detect the presence ofendogeneity by testing if the cross-equation correlation between the identificationequation and the job satisfaction equation is significantly different from zero. Considerthe following structural equations explaining job satisfaction and fringe benefits:
JSk ¼ b1Xk þ b2Fk þ 1k
Fk ¼ a1Xk þ a2I k þ mk
where k indexes an individual worker, F is the worker’s fringe benefit provision, X is avector of independent variables influencing both worker job satisfaction and fringebenefit provision, I is an instrument that impacts fringe benefit provision but is notsignificantly related to job satisfaction and 1 and m are random error terms. If fringe
IJM31,6
636
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
Fix
edef
fect
ses
tim
atio
n
Fri
ng
eb
enefi
ts(0
-8)
0.12
5*
**
(0.0
16)
––
Fle
xib
lew
ork
hou
rs–
0.29
1*
**
(0.0
50)
–P
ensi
onor
reti
rem
ent
pla
n–
0.28
4*
**
(0.0
59)
–D
enta
lin
sura
nce
–0.
158
*(0
.082
)–
Par
enta
lle
ave
–0.
142
**
(0.0
66)
–E
mp
loy
erp
rov
ided
chil
dca
re–
0.26
4*
**
(0.0
86)
–E
mp
loy
erof
fere
dv
acat
ion
day
s–
0.04
8(0
.082
)–
Pro
fit
shar
ing
–0.
005
(0.0
62)
–E
mp
loy
erp
rov
ided
hea
lth
insu
ran
ce–
20.
146
(0.0
97)
–O
ne
frin
ge
ben
efit
––
0.28
0*
*(0
.123
)T
wo
frin
ge
ben
efits
––
0.20
6(0
.133
)T
hre
efr
ing
eb
enefi
ts–
–0.
165
(0.1
31)
Fou
rfr
ing
eb
enefi
ts–
–0.
393
**
*(0
.125
)F
ive
frin
ge
ben
efits
––
0.53
5*
**
(0.1
23)
Six
frin
ge
ben
efits
––
0.65
4*
**
(0.1
25)
Sev
enfr
ing
eb
enefi
ts–
–0.
928
**
*(0
.136
)E
igh
tfr
ing
eb
enefi
ts–
–1.
192
**
*(0
.175
)N
orm
alco
ntr
ols
Yes
Yes
Yes
Occ
up
atio
nco
ntr
ols
Yes
Yes
Yes
Ind
ust
ryco
ntr
ols
Yes
Yes
Yes
No.
ofob
serv
atio
ns
13,2
0213
,202
13,2
02
Notes:
Rep
rese
nt
stat
isti
cal
sig
nifi
can
ceat
the
* 10,
** 5
,*
** 1
per
cen
tle
vel
sre
spec
tiv
ely
;st
and
ard
erro
rsar
ein
par
enth
eses
Table IV.Fixed effects results
Fringe benefits
637
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
benefits are indeed endogenous to job satisfaction, then the error terms in the structuralequations should be significantly correlated.
In order to proceed with the recursive bivariate probit approach, job satisfaction is firsttransformed into a binary job satisfaction variable that equals one when respondents’ jobsatisfaction is very high and zero otherwise. A dummy variable is also generated for eachparticular fringe benefit as well as the minimum quantity of fringe benefits each workerclaims to have, from one benefit to eight. For instance, the dummy variable representingfour fringe benefits equals one for all individuals claiming to have at least four fringebenefits and zero for all those with less than four. In all, sixteen generated binary forms offringe benefit provision are used in sixteen different recursive bivariate probit estimations.
The chosen instrument (I) used in the recursive bivariate probit procedure iswhether or not the respondent or the respondent’s spouse has additional sources of incomebesides their jobs. This may include interest income, dividends, annuity payments or anyother regular source of income. The instrument is positively related to fringe benefits butnot significant in determining job satisfaction. Fringe benefits may be considered a normalgood. That is, a worker with an additional source of income may be inclined to purchasemore fringe benefits from the primary employer. At the same time, the additional sourceof income may not have an impact on the worker’s job satisfaction. The strength ofthe instrument is tested by considering theF-statistic in the first stage regression of fringebenefit provision. According to Staiger and Stock (1997), an instrument is weak if theF-statistic in the first stage regression is ,10 when there is only one endogenousregressor. Regardless of which measure of fringe benefit provision is used, theF-statistic issufficiently large (.10) to ensure that the instrument is not weak.
Estimation of the recursive bivariate probit model explained above and endogeneitytesting follows from Monfardini and Radice (2008). The authors explain that, unless thereis a very large sample, the likelihood ratio test of the cross-equation correlation coefficientis the best test for endogeneity of the fringe benefit dummy variable. If the correlationcoefficient between the error terms 1 and m is significantly different from zero, then thefringe benefit dummy is indeed endogenous. This paper’s results show the opposite andare presented in Table V.
The first column shows the pooled cross-section result when job satisfaction is adichotomous dummy and a probit estimation is used only for each individual measure ofbenefits as the independent variable of interest. The second column shows the estimatedcoefficient of each fringe benefit measure on job satisfaction within the recursivebivariate probit framework. In this way job satisfaction and each fringe benefit dummyvariable are simultaneously determined within the model, effectively controlling forpotential endogeneity. The third column shows the results of the likelihood ratio test forthe cross-equation correlation equal to zero. If the likelihood ratio test reflects that thiscorrelation is not significantly different than zero, we cannot accept the hypothesisof endogeneity. Indeed, all but two of the correlations are far from a significance level of5 per cent. Only profit sharing reports a cross-equation correlation that is significantlydifferent from zero at the 5 per cent significance level while the fringe benefit dummyreflecting workers with at least seven fringe benefits has a cross-equation correlationsignificantly different from zero at the 10 per cent level. Although these two show evidenceof endogeneity, their coefficients are still positive and significant, confirming that therelationship still remains even after controlling for endogeneity.
IJM31,6
638
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
Wor
ker
has
atle
ast
Pro
bit
resu
lts
Biv
aria
tep
rob
itre
sult
sL
ikel
ihoo
dra
tio
test
ofr¼
0
On
eb
enefi
t0.
169
**
*(0
.049
)0.
274
**
(0.1
27)
0.31
Tw
ob
enefi
ts0.
150
**
*(0
.038
)0.
221
**
(0.0
90)
0.18
5T
hre
eb
enefi
ts0.
119
**
*(0
.035
)0.
139
(0.1
63)
0.68
1F
our
ben
efits
0.15
2*
**
(0.0
32)
0.12
1(0
.098
)0.
935
Fiv
eb
enefi
ts0.
168
**
*(0
.027
)0.
125
(0.1
58)
0.92
8S
ixb
enefi
ts0.
165
**
*(0
.026
)2
0.07
2(2
0.34
)0.
299
Sev
enb
enefi
ts0.
260
**
*(0
.034
)0.
516
**
*(0
.149
)0.
064
Eig
ht
ben
efits
0.35
5*
**
(0.0
66)
0.35
8(0
.311
)0.
859
Fle
xib
lew
ork
hou
rs0.
193
**
*(0
.017
)2
0.08
2(2
0.44
8)0.
55P
ensi
onor
reti
rem
ent
pla
n0.
101
**
*(0
.020
)0.
174
(0.1
44)
0.60
9D
enta
lin
sura
nce
0.07
6*
**
(0.0
21)
0.06
5(0
.130
)0.
931
Par
enta
lle
ave
0.12
6*
**
(0.0
21)
0.32
0*
*(0
.136
)0.
155
Em
plo
yer
pro
vid
edch
ild
care
0.18
2*
**
(0.0
30)
20.
01(2
0.22
1)0.
382
Em
plo
yer
offe
red
vac
atio
nd
ays
0.01
4(0
.024
)0.
131
(0.1
11)
0.28
1P
rofi
tsh
arin
g0.
111
**
*(0
.020
)0.
504
**
*(0
.163
)0.
021
Em
plo
yer
pro
vid
edh
ealt
hin
sura
nce
0.05
0*
*(0
.024
)0.
109
(0.0
89)
0.49
1O
bse
rvat
ion
s24
,090
24,0
9024
,090
Notes:
Rep
rese
nt
stat
isti
cal
sig
nifi
can
ceat
the
* 10,
** 5
,*
** 1
per
cen
tle
vel
sre
spec
tiv
ely
;li
kel
ihoo
dra
tio
test
ofr¼
0:P
rob
abil
ityr.
x2
Sta
nd
ard
erro
rsar
ein
par
enth
eses
Table V.Bivariate probit results
and comparison
Fringe benefits
639
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
An additional concern is the potential for wage endogeneity in the job satisfactionequation. The results thus far follow much of the job satisfaction literature and assumewages are exogenous in job satisfaction estimations, though recent research suggeststhat wages should not be treated as such (Pouliakas and Theodossiou, 2009;McCausland et al., 2005). As a test to see if wages are indeed endogenous, the log wagevariable is removed from the bivariate probit models. The resulting likelihood ratio testsconfirm that now six out of the 16 cross-equation correlations suggest the possibilityof endogeneity within this dataset. Yet still the majority of the tests discount thesignificance of endogeneity between job satisfaction and fringe benefits[11]. Thus, theendogenous relationship between fringe benefits and job satisfaction is not a problematicissue in this NLSY data. The estimates obtained from the pooled cross-section datashould be used to study the impact of fringe benefits on job satisfaction.
6. ConclusionFringe benefits make up a significant portion of employer compensation packages inthe USA, but their impact on worker job satisfaction has yet to be given muchattention. Fringe benefits can affect job satisfaction in opposing ways. First of all, sincefringe benefits are generally less taxed than wages, they can be purchased at less costthrough an employer than if bought on the market. Second, fringe benefits are oftendesirable pieces of compensation packages and so increase job satisfaction. However,if spousal compensation packages already provide particular fringe benefits, thoseoffered by an employer might be considered wasteful. Since past research has shownthat wages often suffer in exchange for fringe benefits, those that are wasteful maydecrease job satisfaction. Finally, workers can feel locked into a particular job oremployer if the fringe benefits they need or desire cannot be gained at a better, moresatisfying job elsewhere. This job-lock can decrease job satisfaction.
In order to estimate the relationship between fringe benefits and job satisfaction,five waves of the NLSY are used as a pooled dataset and then are split into particulardemographic sub-samples to analyze the extent of the impact of fringe benefits on jobsatisfaction. Specific fringe benefits and also the quantity of benefits are revealed asimportant determinants of job satisfaction in the entire sample and also in expecteddemographic sub-samples. As a robustness check, a fixed effects estimator is used tocontrol for potentially biasing unobservable individual characteristics captured and notcontrolled for in the pooled cross-section estimation. The results generally carry overfrom the pooled cross-section estimation to the fixed effects estimation, suggestingthat unobservable worker characteristics do not seem to compromise the significantrelationship between fringe benefits and job satisfaction.
Moreover, fringe benefits may be simultaneously determined with job satisfaction.If fringe benefits are indeed endogenous, then their estimated impact on job satisfactionwill be biased. Using a recursive bivariate probit approach, this endogenous relationshipis tested using the likelihood ratio test of the cross-equation correlation of the structuralequations for job satisfaction and fringe benefit provision. Most of the correlationsare indeed not significantly different from zero, confirming that endogeneity is not aproblem in this dataset. The pooled cross-section estimates remain as accuratedepictions of the positive impact that fringe benefits have on job satisfaction.Consequentially, a complete measure of fringe benefits should be included as acontrol variable in future job satisfaction estimations. Additionally, studies focusing
IJM31,6
640
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
on particular fringe benefits may more fully explain the idiosyncratic affects that fringebenefits might have on job satisfaction.
Notes
1. The definition of civilians includes all workers in the private non-farm economy, excludinghouseholds and the public sector, excluding federal government employees.
2. While most studies fail to control for fixed effects, some do not. These include Vieira et al.(2005), Donohue and Heywood (2004), Heywood et al. (2002), Benz (2005) and Heywood andWei (2006), although some do not report coefficients on fringe benefits after controlling forfixed effects.
3. Another prominent subject in the literature is the role of profit sharing in determining jobsatisfaction. Profit sharing is included in this paper as a fringe benefit since it is not directlyrelated to an individual’s effort, but as such it is commonly considered a method ofperformance pay. Green and Heywood (2008) and Cornelissen et al. (2008) have found thatperformance pay, including profit sharing, often increases job satisfaction.
4. This result is even more impressive since all of the survey respondents in the study are unionworkers. Union workers are generally more difficult to layoff due to their relative labormarket power. So union workers feeling more risk of layoff from higher pension accruals is astriking result indeed.
5. Individual NLSY waves display some variation in the strength and significance of fringebenefits’ relationship with job satisfaction and these results are available from the author.
6. Artz (2008) includes profit sharing as a form of performance pay and shows thatperformance pay indeed has an impact on males’ job satisfaction but not females. However,the author’s primary focus was individual performance pay rather than broad forms such asprofit sharing.
7. In order to see if individual fixed effects are at play here, fixed effects estimation is used forboth sub-samples of workers. For union workers, only pensions are significantly andpositively related to job satisfaction whereas five out of the eight fringe benefits have asignificant and positive impact on job satisfaction for non-union workers. Thus, it is possiblethat union workers have individual unobservable characteristics that determine largelywhether or not they value fringe benefits.
8. An alternative to the conditional logit method is a fixed-effects ordered logit technique.Though less computational, the conditional logit estimation method carries the potential oflosing large amounts of information since the dependent variable is condensed from multiplecategories into only two. This problem was highlighted by Ferrer-i-Carbonell and Frijters(2004), but Jones and Schurer (2009) use an alternative approach of the conditional logit tomitigate some of the information loss. Their binary dependent variable uses the mean ofevery group’s job satisfaction rather than the highest level as the arbitrary threshold. In thisway, the conditional logit captures more variation in job satisfaction and does not lose asmuch information. The results of the conditional logit using the highest level of jobsatisfaction as the threshold are very similar to the conditional logit that uses the mean of jobsatisfaction as the threshold.
9. The ordered-probit model’s results generally carry over to the ordered-logit model and alsoto the dichotomous logit model. These are available from the author to interested readers.
10. The size of the fringe variable coefficient in the first column of Table IV (0.125) is noticeablylarger than the same variable’s coefficient (0.061) in the ordered probit cross-section estimate.The difference can at least partly be explained by the change in estimation methodologybetween the pooled ordered probit estimation and the fixed effects estimation that instead
Fringe benefits
641
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
uses a dichotomous dependent variable and assumes a logistic distribution rather than acumulative normal. The difference in coefficient sizes is reduced when a pooled binary logitcross-section estimate is used rather than the ordered probit. In the binary logit model, thecoefficient on the same fringe benefit variable is (0.092). The remaining difference, thoughsmaller, could still be attributed to unobservable effects or also differences in estimationsample sizes between the cross-section and fixed effects estimations.
11. As an additional measure to test the impact of wage endogeneity on the likelihood ratio tests,the fitted values of log wage are estimated including all the normal controls except for age,which serves as a convenient instrument that is not significantly related to job satisfactionor fringe benefits in this particular NLSY dataset but significantly related to wages.The likelihood ratio tests of the cross-equation correlations of the estimations with fittedvalues of log wage are almost identical to those when wages are simply removed from thebivariate probit models. This implies that although wages may be considered endogenous tojob satisfaction in this dataset, the simultaneity bias is not strong enough to significantlychange the primary result that the pooled cross-section estimation can be used to identify thesignificant relationship between fringe benefits and job satisfaction. Many thanks to ananonymous reviewer who suggested methods of testing for wage endogeneity.
References
Adams, S. (2004), “Employer-provided health insurance and job change”, ContemporaryEconomic Policy, Vol. 22 No. 3, pp. 357-69.
Akerlof, G.A., Rose, A.K. and Yellen, J.L. (1988), “Job switching and job satisfaction in the USlabor market”, Brookings Papers on Economic Activity, Vol. 2, pp. 495-582.
Alpert, W.T. (1987), “An analysis of fringe benefits using time-series data”, Applied Economics.,Vol. 19, pp. 1-16.
Artz, B. (2008), “The role of firm size and performance pay in determining employee jobsatisfaction”, Labour: Review of Labour Economics and Industrial Relations, Vol. 22 No. 2,pp. 315-43.
Baughman, R., DiNardi, D. and Holtz-Eakin, D. (2003), “Productivity and wage effects of‘family-friendly’ fringe benefits”, International Journal of Manpower, Vol. 24 No. 3,pp. 247-59.
Bender, K.A. and Heywood, J.S. (2006), “Job satisfaction of the highly educated: the role of gender,academic tenure and earnings”, Scottish Journal of Political Economy, Vol. 52 No. 2,pp. 253-79.
Bender, K.A., Donohue, S.M. and Heywood, J.S. (2005), “Job satisfaction and gender segregation”,Oxford Economic Papers, Vol. 57, pp. 479-96.
Benz, M. (2005), “Not for the profit, but for the satisfaction? Evidence on worker well-being innon-profit firms”, KYKLOS, Vol. 58 No. 2, pp. 155-76.
Bryson, A., Cappellari, L. and Lucifora, C. (2005), “Why so unhappy? The effects of unionizationon job satisfaction”, Oxford Bulletin of Economics and Statistics, Vol. 72 No. 3, pp. 357-80.
Clegg, C.W. (1983), “Psychology of employee lateness, absence and turnover: a methodologicalcritique and an empirical study”, Journal of Applied Psychology, Vol. 68, pp. 88-101.
Cornelissen, T., Heywood, J. and Jirjahn, U. (2008), “Performance pay, risk attitudes and jobsatisfaction”, German Socio-Economic Panel Study Papers, No. 136, DIW, Berlin.
Dale-Olsen, H. (2006), “Wages, fringe benefits and worker turnover”, Labour Economics, Vol. 13No. 1, pp. 87-105.
IJM31,6
642
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
Donohue, S.M. and Heywood, J.S. (2004), “Job satisfaction and gender: an expanded specificationfrom the NLSY”, International Journal of Manpower, Vol. 25 No. 2, pp. 211-34.
Ferrer-i-Carbonell, A. and Frijters, P. (2004), “How important is methodology for the estimates ofthe determinants of happiness?”, The Economic Journal, Vol. 114, pp. 641-59.
Freeman, R.B. (1978), “Job satisfaction as an economic variable”, The American EconomicReview, Vol. 68 No. 2, pp. 135-41.
Green, C. and Heywood, J. (2008), “Does performance pay increase job satisfaction?”,Economica, Vol. 75 No. 300, pp. 710-28.
Heywood, J.S. and Wei, X. (2006), “Performance pay and job satisfaction”, Journal of IndustrialRelations, Vol. 48 No. 4, pp. 523-40.
Heywood, J.S., Siebert, W.S. and Wei, X. (2002), “Worker sorting and job satisfaction: the case ofunion and government jobs”, Industrial & Labor Relations Review, Vol. 55 No. 4,pp. 595-609.
Jensen, G.A. and Morrisey, M.A. (2001), “Endogenous fringe benefits, compensating wagedifferentials and older workers”, International Journal of Health Care and Economics,Vol. 1, pp. 203-26.
Jones, A. and Schurer, S. (2009), “How does heterogeneity shape the socioeconomic gradient inhealth satisfaction”, Journal of Applied Econometrics (December 14, 2009).
Luchak, A.A. and Gellatly, I.R. (2002), “How pension accrual affects job satisfaction”, Journal ofLabor Research, Vol. 23 No. 1, pp. 145-62.
McCausland, W.D., Pouliakas, K. and Theodossiou, I. (2005), “Some are punished and some arerewarded: a study of the impact of performance pay on job satisfaction”, InternationalJournal of Manpower, Vol. 26 Nos 7/8, pp. 636-59.
McEvoy, G.M. and Cascio, W.F. (1985), “Strategies for reducing employee turnover: a metaanalysis”, Journal of Applied Psychology, Vol. 70, pp. 342-53.
Maddala, G.S. (1987), “Limited dependent variable models using panel data”, The Journal ofHuman Resources, Vol. 22 No. 3, pp. 307-38.
Mangione, T.W. and Quinn, R.P. (1975), “Job satisfaction counter-productive behavior and druguse at work”, Journal of Applied Psychology, Vol. 60, pp. 114-16.
Monfardini, C. and Radice, R. (2008), “Testing exogeneity in the bivariate probit model: a montecarlo study”, Oxford Bulletin of Economics and Statistics, Vol. 70 No. 2, pp. 271-82.
Pouliakas, K. and Theodossiou, I. (2009), “Confronting objections to performance pay: a study ofthe impact of individual and gain-sharing incentives on the job satisfaction of Britishemployees”, Scottish Journal of Political Economy, Vol. 56 No. 5, pp. 662-84.
Staiger, D. and Stock, J.H. (1997), “Instrumental variables regression with weak instruments”,Econometrica, Vol. 65 No. 3, pp. 557-86.
Uppal, S. (2005), “Workplace characteristics and job satisfaction”, International Journal ofManpower, Vol. 26 No. 4, pp. 336-49.
Vieira, J.C., Menezes, A. and Gabriel, P. (2005), “Low pay, higher pay and job quality: empiricalevidence for Portugal”, Applied Economics Letters, Vol. 12, pp. 505-11.
Weiss, A. (1984), “Determinants of quit behavior”, Journal of Labor Economics, Vol. 2 No. 3,pp. 371-87.
Woodbury, S. (1983), “Substitution between wage and nonwage benefits”, American EconomicReview, Vol. 73 No. 1, pp. 166-82.
Fringe benefits
643
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
AppendixThis appendix briefly presents the conditional logit model assuming two time periods anddiscusses its extension to more than two periods.
Consider the logit model as:
Probð yit ¼ 1Þ ¼expðb0xit þ aiÞ
1 þ expðb0xit þ aiÞ
where ai are the unobservable characteristics that help determine the state ( yit) thateach worker is in.
The conditional logit eliminates the fixed effects thereby isolating how the changes ofthe observed characteristics explain changes in the dichotomous job satisfaction variable.The elimination of fixed effects in a two-period conditional logit model is constructed below.
First, if Syit ¼ 0 or Syit ¼ 2, then the worker never changes states and so contributesnothing to the likelihood function. These observations are then discarded so only those workerschanging states remain in the model. We are then left with two possible outcomes:
Probð0; 1Þ ¼1
1 þ expðb0xi1 þ aiÞ·
expðb0xi2 þ aiÞ
1 þ expðb0xi2 þ aiÞ
(probability of state yi2 being true)
Probð1; 0Þ ¼expðb0xi1 þ aiÞ
1 þ expðb0xi1 þ aiÞ·
1
1 þ expðb0xi2 þ aiÞ
(probability of state yi1 being true)Since both states are mutually exclusive:
Prob½ð1; 0Þjð1; 0Þorð0; 1Þ� ¼Probð1; 0Þ
Probð1; 0Þ þ Probð0; 1Þ¼
exp½b0ðxi1 2 xi2Þ�
1 þ exp½b0ðxi1 2 xi2Þ�
and:
Prob½ð0; 1Þjð1; 0Þorð0; 1Þ� ¼Probð0; 1Þ
Probð1; 0Þ þ Probð0; 1Þ¼
1
1 þ exp½b0ðxi1 2 xi2Þ�
Thus, the fixed effects (ai’s) have been cancelled out and so only a standard logit model remainsto be estimated. This can of course be extended to include five periods (as is represented in thispaper) rather than two. Then we must not only consider the case when Syit ¼ 1 but also whenSyit ¼ 1, 2. . .4. Still, since all of the states are mutually exclusive, we can cancel out the ai’s andleave only a standard logit model remaining. For details see Maddala (1987).
About the authorBenjamin Artz is an Assistant Professor of Economics at the American University of Sharjah,Sharjah, UAE. Benjamin Artz can be contacted at: [email protected]
IJM31,6
644
To purchase reprints of this article please e-mail: [email protected] visit our web site for further details: www.emeraldinsight.com/reprints
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)
This article has been cited by:
1. Mai Ngoc Khuong, Nguyen Hoang To Uyen. 2016. Factors Affecting Employee Job Engagement towardsAircraft Maintenance Organizations - A Mediation Analysis of Job Satisfaction. Journal of Economics,Business and Management 4, 339-346. [CrossRef]
2. Scott Adams, Benjamin Artz. 2015. Health Insurance, Familial Responsibilities and Job Satisfaction.Journal of Family and Economic Issues 36, 143-153. [CrossRef]
3. Chad D. Cotti, M. Ryan Haley, Laurie A. Miller. 2014. Workplace Flexibilities, Job Satisfactionand Union Membership in the US Workforce. British Journal of Industrial Relations 52:10.1111/bjir.2014.52.issue-3, 403-425. [CrossRef]
4. Kerri Anne Crowne, Jeremy Cochran, Caryl E. Carpenter. 2014. Older-Worker-Friendly Policies andAffective Organizational Commitment. Organization Management Journal 11, 62-73. [CrossRef]
5. Benjamin Artz, Ilker Kaya. 2014. Job insecurity and job satisfaction in the United States: the case of publicsector union workers. Industrial Relations Journal 45:10.1111/irj.2014.45.issue-2, 103-120. [CrossRef]
6. Martina Mysíková, Jiří Večerník. 2013. Job satisfaction across Europe: differences between and withinregions. Post-Communist Economies 25, 539-556. [CrossRef]
7. Susan Linz, Anastasia Semykina. 2013. Job satisfaction, expectations, and gender: beyond the EuropeanUnion. International Journal of Manpower 34:6, 584-615. [Abstract] [Full Text] [PDF]
8. Cornelia Rolli Salathé, Achim Elfering. 2013. A Health- and Resource-Oriented Perspective on NSLBP.ISRN Pain 2013, 1-19. [CrossRef]
9. Soumen Chatterjee, Paramita SarkarImpact of Managerial Atmosphere on Turnover Intent in the PrivateEducation Institutions of West Bengal 113-120. [CrossRef]
Dow
nloa
ded
by S
AU
DI
DIG
ITA
L L
IBR
AR
Y (
SDL
) A
t 09:
56 2
2 Ja
nuar
y 20
16 (
PT)