performance pay and fringe benefits

International Journal of ManpowerPerformance pay and fringe benefits: Work incentives or compensating wagedifferentials?Catalina Amuedo-Dorantes Traci Mach

Article information:To cite this document:Catalina Amuedo-Dorantes Traci Mach, (2003),"Performance pay and fringe benefits", International Journalof Manpower, Vol. 24 Iss 6 pp. 673 - 698Permanent link to this document:http://dx.doi.org/10.1108/01437720310496157

Downloaded on: 22 January 2016, At: 09:55 (PT)References: this document contains references to 28 other documents.To copy this document: [email protected] fulltext of this document has been downloaded 5553 times since 2006*

Users who downloaded this article also downloaded:Benjamin Artz, (2010),"Fringe benefits and job satisfaction", International Journal of Manpower, Vol. 31 Iss6 pp. 626-644 http://dx.doi.org/10.1108/01437721011073346Janell L. Blazovich, (2013),"Team identity and performance-based compensation effects on performance",Team Performance Management: An International Journal, Vol. 19 Iss 3/4 pp. 153-184 http://dx.doi.org/10.1108/TPM-11-2012-0035Patrick L. O'Halloran, (2012),"Performance pay and employee turnover", Journal of Economic Studies, Vol.39 Iss 6 pp. 653-674 http://dx.doi.org/10.1108/01443581211274601

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 D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

*Related content and download information correct at time of download.

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

Performance pay and fringebenefits

Work incentives or compensating wagedifferentials?

Catalina Amuedo-DorantesDepartment of Economics, San Diego State University, San Diego,

California, USA, andTraci Mach

Division of Research and Statistics, Board of Governors of the FederalReserve System, Washington, DC, USA

Keywords Performance related pay, Benefits, Incentive schemes

Abstract Uses longitudinal data from the NLSY79 to examine the effect of a broad variety ofperformance-based pay schemes and fringe benefits on male and female wages between 1988 and1998. Specifically, analyzes whether the offer of various performance-based pay schemes andfringe benefits functions as an alternative work incentive, eliciting greater effort and raising wagesor, instead, it is accompanied by lower wages, as predicted by compensating wage theory. Theresults indicate that, while most performance-based pay schemes are associated with higher wagesto differing extents across gender, tips are commonly accompanied by lower wages among men.Similarly, while the offer of a retirement plan appears to as a work incentive raising male andfemale wages, workers are willing to trade wages for jobs offering life and medical insurance.

Introduction and backgroundWith the growth of ever more complex compensation packages over the lastthree decades, the design and evaluation of performance-based compensationcontracts have captured the attention of economists[1]. Theoreticaldevelopments based on agency theory have demonstrated the advantages ofadopting a performance-based pay system in order to attract superioremployees and induce greater effort from the existing workforce (e.g. Gibbons,1998). Because increased productivity should be compensated with higherearnings, a natural way to gauge the effectiveness of implementedperformance-based pay programs is through earned wages (Booth andFrank, 1999). As such, numerous studies have provided empirical evidence ofthe impact of performance-based pay schemes on workers earnings. Theseempirical analyses have either focused on specific types of performance-based

The Emerald Research Register for this journal is available at The current issue and full text archive of this journal is available at

http://www .emeraldinsight .com/researchregister http:// www.emeraldinsigh t.com/0143-772 0.htm

The authors are thankful to Cynthia Bansak, Nancy Burnett, Nels Eikenhout, Susan Pozo,Ricardo Serrano-Padial and participants at the Western Economic Association meetings forhelpful comments and suggestions. The opinions expressed are those of the authors and do notnecessarily reflect the views of the board of governors or other members of its staff.

IJM24,6

672

Received July 2002Revised March 2003Accepted May 2003

International Journal of ManpowerVol. 24 No. 6, 2003pp. 672-698q MCB UP Limited0143-7720DOI 10.1108/01437720310496157

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

compensation, such as piece rates, bonuses, promotion-based incentives orprofit-sharing plans[2], on specific groups of individuals or occupations, suchas men and CEOs[3], or on establishment and firm level data, with the latterfrequently limited to specific firms or sectors in the economy[4]. In general, theempirical research has found a positive relationship between performance-based pay and earnings.

Recognizing the complex nature of compensation packages, this studyadds to the existing literature with an analysis of the impact that abroader variety of pay schemes piece rates, commissions, tips, bonuses,stock options and others, and fringe benefits offered by employers,including health, life and dental insurance, retirement plans, maternityleave, or childcare provision have had on male and female wagesacross a variety of industries and occupations during most of the pastdecade. We rely on self-reported employee level data from the NLSY79,which ran from 1988 to 1998. The analysis differs from previous studiesin three ways. First, given the percentage of employees receiving multipletypes of performance-based pay incentives, we control for and analyze alltypes of performance-based pay schemes, rather than focusing on a fewtypes[5]. Controlling for all types of performance-based compensationreceived by the worker is of particular interest because failure to do socould result in an upward bias of the estimated effect of the specificperformance-based pay scheme being examined if the worker values otherreceived and omitted performance- based incentives.

Second, unlike previous research, we also include a rich set of fringe benefitsoffered to the employee possibly increasing her utility and affecting her wages.If employees are willing to accept lower wages in exchange for a job offeringcertain fringe benefits, as argued by the compensating wage theory (e.g. Ebertsand Stone, 1985; Rosen, 1986; Olson, 2002), the omission of informationregarding their employers offer of these fringe benefits may induce downwardbias on the estimated impact of performance-based pay schemes. On the otherhand, estimates could be upwardly biased if there is higher utility associatedwith being offered certain fringe benefits, leading to increased work effort,productivity, and wages, as argued by Shapiro and Stiglitz (1984).Furthermore, the coefficients on fringe benefits will also enable us to sort outwhich of the aforementioned theories prevails empirically with respect to thewage effect of being offered a variety of fringe benefits. Specifically, negativecoefficients on fringe benefits would support their role as compensating wagedifferentials, inducing the worker to accept a lower wage in exchange for a joboffering a particularly valued fringe benefit. Alternatively, positive coefficientson fringe benefits would favor the view of fringe benefits as work incentives tothe extent that they induce greater work effort on the part of workers in order tokeep a job they value given its offered fringe benefits.

Performance payand fringe

benefits

673

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

Finally, we carry out the analysis first grouping across gender and thencomparing our results to those from wage regressions by gender[6]. Allregressions correct for sample selection bias incurred when focusing onworking individuals[7]. The analysis by gender allows for differences in thewage distributions of men and women as well as for differences in theirpreferences, which is desirable in this context for at least two reasons. First, itis well documented that mens and womens wage distributions differ(Gunderson, 1989)[8]. Differences in the wage distributions may mask the trueimpact of these incentives if men and women are grouped in the analysis.Second, men and women may place different value on different aspects ofcompensation packages. For example, if men and women differ in theirpreferences (Hersch, 1996; Hinz et al., 1997; Jianakoplos and Bernasek, 1998),different types of work incentives, such as the employer provision of childcare,may have a different effect on wages across gender.

We find that piece rates and commissions each raises male wages by a factorof 4 percent to 5 percent, while tips are accompanied by significantly lowerwages. The differential effect of tips on wages reflects the lower wages (up to11 percent lower) men are willing to accept in exchange for tips. In this respect,tips act as a compensating wage differential rather than as a work incentive.Among women, piece rates, bonuses, and other performance-based payschemes raise female wages between 1 percent and 4 percent each. Theseestimates are smaller than those obtained in previous studies using theNLSY79[9]. As previously noted, this difference may be partially due to thedifferent scope of these studies. In particular, we focus on the entire range ofperformance-based pay schemes received by the worker to avoid upwardbiases in the estimated effect of a particular type of performance pay beingexamined in the event the respondent derives any utility from othersimultaneously received and, yet, omitted performance-based compensationschemes.

Additionally, as predicted by compensating wage theory, we find that wagesare traded in exchange for jobs offering insurance for both men and women.However, we also observe that the offer of other fringe benefits, such asretirement benefits, is associated with higher, rather than lower, male andfemale wages. In these instances, the offer of retirement benefits seems tofunction as an alternative work incentive, possibly eliciting greater jobattachment, work effort, and even more investment in firm-specific humancapital, all of which would result in higher wages[10].

Finally, we find that the wage effects of both performance-based payschemes and fringe benefits differs by gender, illustrating the different valuethat men and women place on various aspects of their compensation packages.In particular, male wages are more responsive to both commissions and tipsthan female wages, while female wages appear more responsive to bonusesthan male wages. To the extent that commissions and tips are based largely on

IJM24,6

674

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

the interaction with customers, as opposed bonuses which are moreemployer-controlled and may therefore be more consistently determined, theobserved gender differences may be a reflection of male and female differencesin risk preferences or willingness to bear greater pay uncertainty (Hersch, 1996;Jianakoplos and Bernasek, 1998; Geddes and Heywood, forthcoming).Understanding the different gender responses to various compensationpackages may prove useful in retaining workers in the predominantlysingle-sex occupations currently experiencing high turnover rates, such asregistered nursing, childcare provision, and teaching.

Data and descriptive evidence on performance-based pay and fringebenefitsThe dataWe use data from the National Longitudinal Survey of Youth (NLSY79). Since1979, a vast amount of information on the labor market participation of arepresentative sample of 12,686 individuals has been collected[11]. Aside frompersonal and work related characteristics of each job held by the respondent,the NLSY79 asked respondents on five separate occasions (1988, 1989, 1990,1996, and 1998) if the earnings of their current job were based all or in part onjob performance[12]. Respondents who responded positively weresubsequently asked about the type of performance-based pay scheme theyreceived: piece rate, commissions, bonuses (based on job performance), stockoptions, tips, or some any other type[13]. In addition, the survey collectedinformation on whether the respondent was offered any of the following fringebenefits for each job held: health, life, and dental insurance, maternity leave,retirement plans, profit sharing, training, and childcare provision[14]. It isworth noting that the information collected by the NLSY79 refers to whether ornot the employer offers a particular set of fringe benefits, independently ofwhether or not the respondent ultimately takes the fringe benefits beingoffered. To the extent that performance-based pay schemes and fringe benefitsare typically implemented and offered by the employer to a broad group ofworkers at the firm or establishment level, the dummy variables indicative ofwhether the respondent receives a particular performance-based pay schemeor/and is offered a particular fringe benefit can be thought of as job levelvariables.

Our dependent variable is the log of real hourly wages. The NLSY79provides the hourly rate of pay, excluding any additional compensation in theform of commissions, bonuses, stock options, or tips. We deflate hourly wagesusing the CPI index and restrict our sample to individuals reporting hourlyearnings between $1.00 and $100.00[15]. Table AI in the Appendix contains adetailed description of the variables used in the analysis, along with theirmeans and standard deviations.


benefits

675

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

Gender differences in the receipt of performance-based pay and fringe benefitsIn order to familiarize ourselves with the data, Figures 1-7 depict the differentmale and female participation rates in a variety of performance-based incentivepay schemes over the decade 1988-1998. As evidenced by the figures, there aregender differences in the type of performance-based pay scheme received.Figure 1 indicates that a higher percentage of men than women received atleast one type of performance-based incentive. A similar pattern is observed

Figure 1.Percentage ofrespondents receiving aparticular type ofperformance-based payscheme over time: atleast one type incentivepay received

Figure 2.Percentage ofrespondents receiving aparticular type ofperformance-based payscheme over time: piecerates received

Figure 3.Percentage ofrespondents receiving aparticular type ofperformance-based payscheme over time:commissions received

IJM24,6

676

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

when we distinguish by type of performance-based pay scheme in Figures 2-7,with the exception of tips. Overall, bonuses and commissions were the mostfrequent types of performance-based pay schemes for both men and womenover the decade. Additionally, the prevalence of piece rates, commission, tipsand other types of performance-based incentives has decreased as respondents

Figure 4.Percentage of

respondents receiving aparticular type of

performance-based payscheme over time:bonuses received



performance-based payscheme over time: stock

options received



performance-based payscheme over time: tips

received


benefits

677

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

aged, while that of stock options rose for both men and women. Finally, whilemost performance-based compensation contracts moved in tandem for men andwomen over the period under consideration, bonuses began moving slightly inopposite directions for men and women in the second half of the 1990s,becoming increasingly prevalent among men while diminishing somewhatamong women.

Similarly, Figures 8-15 depict the percentage of men and women beingoffered different types of fringe benefits over the period 1988-1998. Healthinsurance, life insurance, retirement plans, dental insurance, and maternityleave for women were the most frequently offered types of fringe benefits overthe course of the decade. Of all the fringe benefits being offered, the offer ofretirement plans, dental insurance, and maternity leave for men displayed thelargest growth in percentage terms. Overall, most fringe benefits were offeredto similar percentages of men and women, with the notable exception ofmaternity leave.

Figure 7.Percentage ofrespondents receiving aparticular type ofperformance-based payscheme over time: otherincentives received

Figure 8.Percentage ofrespondents offered aparticular type of jobbenefit over time: healthinsurance benefits

IJM24,6

678

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

As discussed earlier, controlling for the receipt of multiple performance-basedpay schemes may be particularly important in evaluating the effect of aparticular type of performance-based incentive. If a large percentage ofindividuals in the sample receive multiple types of performance-based pay,omission of their complete set of incentives may significantly bias the effect ofa particular type of performance-based pay scheme being examined. In order toassess whether this is the case, each cell of Table I reflects the percentage ofindividuals receiving a particular type of performance-based pay indicated bythe row, conditional on receiving the incentive indicated by the column. Forinstance, column 4 shows that of all men who received bonuses, 3 percent also


respondents offered aparticular type of job

benefit over time:retirement plan



benefit over time: childcare


benefits

679

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

received piece rates, 13 percent received commissions, 10 percent received stockoptions, and so forth. Overall, the figures reveal that many individuals receivedmultiple types of performance-based pay schemes simultaneously. Similarly,Table II shows the percentage of males and females who were offered sometype of job benefit indicated by the row, conditional on having been offered thefringe benefit indicated by the column. As with performance-based payschemes in Table I, most employees who were offered a fringe benefit weretypically offered more than one. Due to this overlap, exclusively examining afew types of performance-based pay schemes or fringe benefits may introducesystematic biases into their coefficient estimates.

Additionally, Table III displays some preliminary evidence on the potentialwage effects of different types of performance-based pay schemes for men andwomen. For both men and women, mean wages were lower in jobs offeringpiece rates and tips than the sample average wage. The opposite was true of

Figure 11.Percentage ofrespondents offered aparticular type of jobbenefit over time: lifeinsurance benefits

Figure 12.Percentage ofrespondents offered aparticular type of jobbenefit over time:maternity benefits

IJM24,6

680

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)



benefit over time:training



benefit over time: dentalinsurance



benefit over time: profitsharing


benefits

681

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

jobs offering commissions, bonuses, stock options, or other types ofperformance-based compensation. The higher average wages associated withthe receipt of commissions, bonuses, stock options, and otherperformance-based pay schemes may be interpreted as a sign of theeffectiveness of these performance-based compensation schemes in elicitinghigh performance. Alternatively, this finding may be linked to more ableworkers self-selecting into performance-based jobs or to specific characteristicsof the jobs held by these workers, e.g. good management or work environment,suggesting the need to control for individual and job specific heterogeneitythrough fixed-effects estimation (Lazear, 1986).

Columns 2-6 of Table III further break down average wages by the types offringe benefits offered to the employee. In general, examining the first row ofcells in columns 1-6, we observe that the average wage in jobs offering at leastone type of job benefit was higher than the sample average wage. The increasewas particularly important in the case of less frequently offered fringe benefits,such as child care, training, and profit sharing, all of which were typicallyassociated with greater average hourly wages than the remaining fringebenefits. The aforementioned evidence suggests, once more, that offering fringebenefits may promote greater work effort, which, in turn, may be compensatedwith higher wages. Alternatively, as pointed out for performance-based payschemes, the positive association between real wages and the offer of specificfringe benefits may be due to the self-selection of more able workers into jobsoffering better fringe benefit packages or to specific characteristics of the jobsheld by these workers. The latter reinforcing, once more, the importance ofaccounting for unobserved individual and job heterogeneity potentiallyresponsible for the higher wages being observed.

Piecerate (%) Commission (%) Bonus (%)

Stockoptions (%) Tips (%) Other (%)

MenPiece rate 100.0 4.3 2.9 3.7 6.4 3.0Commission 8.1 100.0 13.4 13.3 16.6 6.8Bonuses 12.7 31.0 100.0 66.5 23.2 12.5Stock options 2.4 4.4 9.6 100.0 2.2 2.0Tips 3.9 5.3 3.2 2.1 100.0 2.2Other 2.5 3.0 2.4 2.7 3.0 100.0

WomenPiece rate 100.0 2.6 1.9 4.2 3.9 2.1Commission 3.8 100.0 10.7 8.3 12.2 5.4Bonuses 7.8 29.8 100.0 66.7 6.6 9.7Stock options 1.8 2.4 6.8 100.0 0.5 1.5Tips 5.5 11.6 2.3 1.8 100.0 3.9Other 1.8 3.1 1.9 3.0 2.3 100.0

Table I.Percentage of men andwomen receivingvarious work incentivesby type of workincentive in columns

IJM24,6

682

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

Hea

lth

insu

ran

ce(%

)L

ife

insu

ran

ce(%

)M

ater

nit

yle

ave

(%)

Den

tal

insu

ran

ce(%

)R

etir

emen

tb

enefi

ts(%

)P

rofi

tsh

arin

g(%

)T

rain

ing

(%)

Ch

ild

care

(%)

Men

Hea

lth

insu

ran

ce10

0.0

98.0

94.6

98.4

97.3

94.3

95.5

97.3

Lif

ein

sura

nce

83.3

100.

085

.088

.789

.686

.787

.594

.2M

ater

nit

yle

ave

65.2

69.5

100.

072

.472

.270

.972

.984

.6D

enta

lin

sura

nce

71.5

76.0

76.2

100.

080

.175

.278

.790

.2R

etir

emen

tb

enefi

ts74

.280

.680

.184

.110

0.0

84.5

83.9

91.8

Pro

fit

shar

ing

35.0

38.2

38.3

38.5

41.4

100.

042

.253

.2T

rain

ing

56.5

61.5

63.2

64.4

65.8

67.7

100.

087

.1C

hil

dca

re7.

08.

29.

49.

18.

910

.510

.910

0.0

Wom

enH

ealt

hin

sura

nce

100.

097

.990

.797

.996

.194

.292

.689

.4L

ife

insu

ran

ce84

.910

0.0

80.7

88.7

89.9

87.5

85.5

83.6

Mat

ern

ity

leav

e91

.593

.210

0.0

93.8

93.9

93.8

92.0

92.1

Den

tal

insu

ran

ce75

.078

.571

.810

0.0

80.2

77.5

77.8

80.7

Ret

irem

ent

ben

efits

76.6

82.4

75.1

83.2

100.

085

.882

.282

.8P

rofi

tsh

arin

g34

.136

.734

.136

.839

.410

0.0

37.9

41.3

Tra

inin

g62

.567

.062

.368

.870

.571

.210

0.0

82.9

Ch

ild

care

9.1

9.9

9.4

10.8

10.8

11.6

12.6

100.

0

Table II.Percentage of men andwomen offered varioustypes of fringe benefits

pay by type of jobbenefit in columns


benefits

683

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

In sum, the descriptive evidence in Tables I-III signals the need to control formultiple work incentives, individual, and job characteristics in order toappropriately sort out the effects of the traditional performance-based payschemes and fringe benefits on wages. Furthermore, the differential incidenceof each type of performance-based incentive by gender revealed by Figures 1-7,as well as mens and womens different degrees of labor force attachment,underline the need to run the analyses separately for men and women.

Empirical methodologyPerformance-based pay schemes are implemented by the firm in order toinduce greater effort from their existing workforce (e.g. Gibbons, 1998). As theirname indicates, these pay schemes promote workers productivity bycompensating workers according to their work performance. To the extent

Sample Insurance Retirement Profit Sharing Training Child care

MenSample 12.983 13.595 14.669 14.557 15.278 15.555

(8.474) (8.093) (8.268) (9.068) (8.571) (8.545)Piece rate 12.695 13.053 13.876 13.412 14.434 10.666

(9.040) (9.628) (10.637) (9.735) (10.021) (3.355)Commission 14.923 15.432 16.781 16.273 16.67 17.238

(9.962) (9.775) (10.693) (11.363) (10.324) (10.206)Bonus 15.692 16.251 17.573 16.993 18.008 19.62

(10.491) (10.514) (10.849) (10.943) (10.883) (12.603)Stock Options 20.777 21.028 21.446 19.112 22.729 22.142

(13.817) (13.875) (13.954) (12.065) (13.615) (14.404)Tips 9.745 10.372 11.793 10.887 11.638 13.105

(5.773) (5.663) (6.363) (6.697) (6.971) (9.908)Other 15.452 15.843 16.86 17.014 17.653 19.328

(11.019) (10.354) (10.439) (11.370) (10.932) (12.836)

WomenSample 10.528 11.088 11.92 11.485 12.109 11.841

(6.698) (6.136) (6.203) (6.374) (6.276) (6.414)Piece rate 9.137 8.416 9.453 9.78 10.643 13.082

(6.709) (4.836) (5.720) (6.312) (6.354) (10.635)Commission 12.211 12.579 13.474 13.342 13.569 15.771

(9.238) (9.069) (8.865) (9.935) (10.107) (10.291)Bonus 12.441 12.573 13.544 13.623 13.529 13.576

(7.755) (7.489) (7.884) (8.343) (7.733) (8.051)Stock Options 15.465 15.534 15.841 14.904 15.734 14.629

(10.876) (10.875) (11.369) (11.623) (9.915) (9.472)Tips 8.082 8.186 7.407 8.373 7.958 6.012

(5.636) (6.049) (3.218) (4.332) (3.808) (3.494)Other 11.745 12.331 13.016 12.941 13.048 13.943

(7.417) (7.101) (6.945) (6.418) (7.296) (11.676)

Note: Standard deviation shown in parentheses

Table III.Average wages byincentive type andfringe benefits

IJM24,6

684

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

that fringe benefits may elicit improved work performance and productivity onthe part of the worker, they may also function as an alternative type of workincentive. Nonetheless, while still promoting work effort, because fringebenefits are not typically offered based on the workers performance at the firm,they are only expected to induce the minimum level of effort required to keep adesirable job (Shapiro and Stiglitz, 1984) or to persuade workers to accept orstay at a particular job.

Conversely, workers may be willing to accept lower wages in exchange for ajob offering highly valued performance-based compensation contracts orfringe benefits, as predicted by compensating wage theory. In the case ofperformance-based contracts, workers may be willing to accept a pay schemethat involves a higher volatility in earnings, such as a piece rate, in exchangefor a higher rate of pay (Sciler, 1984; Parent, 1999).

In order to decipher whether performance-based pay schemes and fringebenefits function as work incentives or, rather, as compensating wagedifferentials, we examine their effect on wages earned by men and women overthe past decade[16]. Following Heckman (1976) and Wooldridge (1995), we firstcorrect for the sample selection biases resulting from focusing on a sample ofworking individuals in each given year by including the inverse Mills ratio inour structural wage regression as follows[17]:

ln wijt Xijtb PBPjtd FBjtg 0 lijtx hijt; with : hijt aij 1ijt; 1where wijt represents the hourly wage for the ith individual in job j in year t, Xijtis a vector of personal and job related characteristics such as age, race, andexperience and tenure, industry, occupation, and union status, PBPjt is a vectorof job level dummies indicative of whether job j offers a particular set ofperformance-based pay schemes, FBjt is a vector of job level dichotomousvariables indicative of whether job j offers a particular set of fringe benefits[18],lijt is the inverse Mills ratio, aij represents individual and job-specific fixedeffect[19], and 1ijt is an independently and identically distributed error term.

As previously mentioned, one issue that arises when examining the impactof performance-based pay schemes and fringe benefits on wages is thepotential nonrandom assignment of workers into jobs offering certain types ofincentive pay or fringe benefits. For instance, if highly motivated workers injobs offering a cooperative work atmosphere are more likely to be offeredperformance-based pay schemes or/and fringe benefits, failure to control forthese individual-job fixed effects would result in upward biased estimates ofthe relative return to employment in jobs offering these types of workincentives. Panel data techniques may be used to deal with this problem[20]. Inparticular, individual-job-specific fixed effects are likely to capture fairly wellmost unobserved differences between workers in jobs offering a particular typeof performance-based incentive and/or fringe benefit and workers in jobs thatdo not given the relatively short duration of our panel. Assuming that theindividual-job-specific fixed effect is the only remaining component of the error


benefits

685

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

term correlated with the different performance-based pay schemes and fringebenefits, purging the model of this term should provide us with unbiasedcoefficient estimates. Therefore, we estimate equation (1) using fixed effects toaccount for any unobserved individual job characteristics correlated withworkers self-selection into particular types of jobs. As a result, d and g shouldonly capture wage fluctuations due to the higher (or lower) utility associatedwith being paid according to a particular performance-based pay scheme aswell as with receiving a given set of fringe benefits, and not due to unobservedindividual or job characteristics.

Finally, we correct the variance-covariance matrix to account for theheteroscedasticity, the additional source of variation in the compounddisturbance, and the correlation across observations introduced by the inverseMills ratio when statistically significant following Greene (1981) and Murphyand Topel (1985).

Wage effects of performance-based pay schemes and fringe benefitsby genderEstimation results for the combined sample of men and women, as well asseparately by gender, are shown in Table IV. The first column in Table IVshows the estimated results when men and women are combined, as has beendone in much of the previous literature on the impact of performance-basedincentive pay until very recently[21]. The estimates indicate that piece ratesand bonuses function as work incentives, increasing wages by 5 percent and 2percent, respectively. As previously argued, it is also possible that the higherwage rate associated with piece rates functions as a compensating wagedifferential for the higher pay variability to which piece rate workers aresubjected to (Sciler, 1984; Parent, 1999). Tips, however, are accompanied by upto 6 percent lower wages, reflecting workers willingness to accept a lowerwage as long as they are able to add to it at a fairly predictable rate, as is oftenthe case with tips. A similar result is found for insurance[22]. In particular, thenegative coefficient on insurance reflects the lower wage that workers arewilling to accept in exchange for a job offering insurance coverage, as predictedby compensating wage theory. However, retirement boosts workers wages byabout 3 percent, signaling its potential as an alternative work incentive,whether it works indirectly increasing workers commitment to their employersand their investment in productivity enhancing firm-specific humancapital[23], or directly through workers increased work effort.

By estimating the wage regressions separately by gender, we are able toobserve how the effect of performance-based incentives on male wages appearsto be generally understated in the combined model. While the bias is minimalfor piece rates, which continue to raise male wages by approximately 5 percent,it is larger when referred to the wage effect of commissions and tips. Inparticular, commissions now seem to boost male wages by approximately 4percent while tips are accompanied by up to 11 percent lower wages; that is, a

IJM24,6

686

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

difference of over 1.5 and 5 percentage points with respect to the combinedmodel in each case. The observed trade-off between wages and tips is alsoobserved for some fringe benefits. In particular, men are willing to accept5 percent lower wages in exchange for a job offering insurance. However, theoffer of a retirement plan functions as a work incentive, raising male wages byapproximately 4 percent. In that respect, the employers offer of a retirementplan appears to be as economically important as commissions in eliciting work

Dependent variables All Men Women

Piece rate 0.0472*** 0.0504** 0.0408***(0.0183) (0.0240) (0.0136)

Commission 0.0257 0.0412* 20.0077(0.0183) (0.0235) (0.0113)

Bonus 0.0151* 0.0157 0.0160**(0.0086) (0.0120) (0.0071)

Stock options 0.0280 0.0299 0.022(0.0201) (0.0258) (0.0206)

Tips 20.0583** 20.1108*** 0.0099(0.0267) (0.0377) (0.0119)

Other incentives 0.0116 20.0047 0.0382***(0.0169) (0.0231) (0.0150)

Insurance 20.0316*** 20.0498*** 20.0092*(0.0123) (0.0176) (0.0064)

Retirement 0.0258*** 0.0400*** 0.0117**(0.0094) (0.0141) (0.0059)

Profit sharing 20.0002 20.0108 0.0127(0.0083) (0.0119) (0.0117)

Training 0.0028 0.0006 0.0051(0.0076) (0.0112) (0.0053)

Childcare 0.0067 0.0182 20.0073(0.0121) (0.0183) (0.0085)

Lambda 0.1515 20.068 0.1381***(0.0973) (0.1339) (0.0408)

Number of obs. 26,203 13,817 12,386Number of groups 15,989 8,372 7,617Regression F-stat 66.33 32.20 36.79R-squared

Within 0.215 0.200 0.246Between 0.104 0.153 0.093Overall 0.112 0.164 0.108

Notes: All models include the following controls: firm size, tenure, tenure squared, occupationalexperience, industry experience, industry, occupation, union status, work shift, age, race,immigrant status, marital status, number of kids, education, AFQT score, urban status,unemployment rate and year dummies. Insurance is a dummy indicating receipt of healthinsurance, dental insurance, life insurance, or maternity leave. Robust standard errors are shownin parentheses. * Indicates significance at the 10 percent level; ** indicates significance at the 5percent level; and *** indicates significance as the 1 percent level

Table IV.Worker and job fixed

effects wage equations


benefits

687

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

effort and raising wages, with both increasing male hourly wages byapproximately 52 cents[24].

Among women, bonuses continue to raise female wages by approximately2 percent, while the effect of piece rates in boosting female wages dropsfrom 5 percent to about 4 percent when estimating the wage regressionsseparately by gender. At any rate, aside from the new statistical significance ofother non-specified performance-based pay schemes, the largest differencebetween the results in the combined model and those from the female wageregression is in the estimated wage effect of tips. While the combined modelpredicts an average wage trade-off of approximately 6 percent in exchange fortips, we now find that tips do not significantly alter female wages. That is,women are not willing to accept a lower wage rate as a trade-off for thepossibility of higher income with tips, as appears to be the case with men. Thisresult points towards gender differences in workers preferences, such asdifferences in the willingness to bear greater pay variability as is often thecase with performance-based incentives originating from the interaction withcustomers. Finally, the offer of insurance is accompanied by approximately 1percent lower wages, revealing womens willingness to trade wages inexchange for a job offering this fringe benefit. However, as in the case of men,the offer of a retirement plan raises female wages by approximately 1 percent,underscoring, once more, the potential role of this fringe benefit in elicitingwork effort resulting in higher wages.

Some of the fringe benefits are not significant in any of the specifications. Anatural question is whether these benefits do not affect wages or whether thereis something causing them to be insignificant. Evidence from the 1972 Qualityof Employment Survey suggests that a large portion of employees who areoffered insurance and retirement plans choose to participate, with over 90percent of men and 80 percent of women participating. However, participationin training programs, profit sharing plans and stock option plans issignificantly lower for both men and women. While these data are quite old,they do give some indication of the benefits that respondents may be leastlikely to take up. It could be the lack of information on participation that causestraining, profit sharing and stock options to be insignificant in the regressions.To address this more fully, better data would be needed.

Summary and conclusionsIn this paper, we use longitudinal data from the NLSY79 to examine the effectthat a broad variety of work incentives, including multiple performance-basedpay schemes and fringe benefits, have had on male and female wages between1988 and 1998. We estimate wage regressions grouping both genders andcompare our results to those from wage regressions by gender. Several findingsare worth summarizing. First, most traditional performance-based payschemes appear to be effective in eliciting higher productivity (as capturedby higher wages) to differing degrees, with the exception of tips among men.

IJM24,6

688

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

The possibility exists that the higher wages associated with some of theseperformance-based pay schemes, such as piece rates, may be functioning as acompensating wage differential for the higher earnings uncertainty that oftenaccompanies these compensation packages (Sciler, 1984; Parent, 1999). In anyevent, we find that piece rates and commissions raise male wages by 5 percentand 4 percent, respectively, while tips are accompanied by approximately 11percent lower wages, reflecting mens willingness to accept a lower wage aslong as they are able to add to their pay at a fairly predictable rate, as is oftenthe case with tips. This is not the case among women, for whom piece rates,bonuses, and other performance-based pay schemes boost wages by a factor of1 percent to 4 percent. The magnitude of these estimates is smaller than that ofprevious estimates obtained using the NLSY79, possibly due to the differentscope of the studies. In particular, we control for all types of performance-basedpay schemes received by the worker with the purpose of avoiding upwardbiases in the estimated wage effect of a specific performance-based pay schemebeing examined resulting from the omission of other simultaneously receivedperformance-based compensation contributing to the workers utility.

Second, we find that, as predicted by compensating wage theory, wages areoften traded in exchange for a job offering certain fringe benefits, includinginsurance for both men and women. These observed trade-offs might bereinforced by the opportunity of forgoing insurance coverage for a higher payrate, as with the Flex Cash option offered by some employers[25]. This is nottypically a possibility with retirement plans, which, in turn, appear to beaccompanied by higher wages for both men and women. One explanation as forwhy the offer of retirement plans appears to be associated with higher wagesmight be linked to the more limited portability of some retirement plans fromemployer to employer. In those instances, if workers value retirement plans,these may operate as a work incentive inducing greater employee workcommitment and effort so as to guarantee a long-run relationship with the firm,as pointed out by Shapiro and Stiglitz (1984). In a similar vein, Azfar andDanninger (2001) argue that retirement packages may provide workers with anincentive to invest more heavily in firm-specific human capital, increasing theirproductivity and wages.

Finally, we find that the wage effects of both performance-based payschemes and fringe benefits differs by gender, illustrating the different valuethat men and women place on various aspects of their compensation packages.In particular, male wages are more responsive to both commissions and tipsthan female wages, while female wages appear more responsive to bonusesthan male wages. These gender differences may be partially explained by thecharacteristics of these types of performance-based compensation contracts.Commissions and tips are pay schemes based on individual job performanceoften observed in sales and service-oriented jobs, therefore, highly dependenton the employee interaction with clients. To the extent that the outcome of thisinteraction with clients is not easily foreseeable by the employee, commissions


benefits

689

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

and tips have the potential of being more volatile and irregular than otherperformance-based incentives originating from the employees individualperformance. The greater responsiveness of male wages to both commissionsand tips than female wages, as well as that of female wages to bonuses, may beexplained by gender differences in risk preferences or willingness to beargreater pay variability (Hersch, 1996; Jianakoplos and Bernasek, 1998; Geddesand Heywood, forthcoming). Future research examining mens and womensresponses to various performance-based compensation contractscharacteristics such as their dependability, is needed to further ourunderstanding of the reasons behind the differential effectiveness ofperformance-based pay incentive schemes by gender.

Policy-wise, far from advocating a differential discriminatory treatment ofmen and women in the workplace, our findings provide useful information withrespect to the design of compensation packages that would best promote workerproductivity and retain qualified workers, as can be done by appropriate workincentives and compensating wage differentials, respectively. This may beparticularly important in predominantly single-sex occupations with highturnover rates, such as registered nursing, childcare providers, and teachers.

Finally, it is important to point out some of the limitations of our analysisand provide suggestions for future studies. In particular, it would be of interestto examine the reasons behind the differential effect of offering variousperformance-based pay schemes and fringe benefits on male and female wagesrevealed in this paper; specifically, the role played by gender differences in riskpreferences. Additionally, the use of richer data providing information not onlyon the availability but, also, on the size (relative to the wage) and theparticipation in the various types of performance-based pay schemes beingpaid and the generosity of the different fringe benefits being offered, would behighly valuable. Finally, our results are specific to the USA over the 1988-1998decade. It would be very interesting for future research to determine whetherthe found gender differences in the value placed on a variety ofperformance-based pay schemes and fringe benefits being offered differacross countries and over time.

Notes

1. See Jensen and Murphy (1990), Brown (1990), and Booth and Frank (1999).

2. For instance, Booth and Frank (1999), McCue (1996), and Parent (1999).

3. Some examples are Abowd (1990), Jensen and Murphy (1990), and Parent (1999).

4. A vast literature can be found in this category, such as Lazear (2000) and Hubbard and Palia(1995).

5. For instance, also using the 1979 National Longitudinal Survey of Youth (NLSY79), Ewing(1996) examines the combined wage effect of piece rates, tips and stock options, as well as theindividual wage effects of bonuses and commissions, on a grouped sample of men andwomen. Separating men and women, Parent (1999) also relies on NLSY79 data to examinethe effect of piece rates and bonuses on male and female hourly wages.

IJM24,6

690

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

6. Alternatively, the model could be estimated interacting gender with each of the variables. Asthis would use up considerable degrees of freedom, the regressions are run separately by gender.

7. While others have estimated results separately by gender (e.g. Parent, 1999), there has beenno control for sample selection. While the sample selection term is significant for women, itdoes not appreciably alter the estimates of the impact of the various types of workincentives. Estimates with and without the correction are available from the authors uponrequest.

8. Wage distributions for men and women differ considerably due to differences in their laborforce attachment, human capital accumulation, and possible discrimination, among other factors.

9. In particular, Parent (1999) finds that piece rates increase male wages by approximately7 percent, while Ewing (1996) finds that commissions and bonuses raise wages for thecombined sample of men and women by 9 percent and 4 percent respectively.

10. See Azfar and Danninger (2001) for a similar argument when examining employmentrelationship hazard rates.

11. Respondents were interviewed yearly between 1979 and 1994. Beginning with the 1994interview, interviews are only scheduled to take place biennially.

12. In 1988, 1989, and 1990 this question was asked of the current or most recent job. In the 1996and 1998 interviews this was asked of all jobs held since the last interview. In order to makethe observations comparable across years, information on the current or most recent job wasused in all years.

13. A detailed description of this survey question is contained in the Appendix.

14. As with performance-based incentives, we used fringe benefit information for the current ormost recent job.

15. The latter was retrieved from www.bls.gov/cpi/home.htm using the year 1996 as the base year.

16. For a literature review on the theoretical relevance of incentive pay, see Gibbons (1998).

17. Following Wooldridge (1995), we estimate selection equations for whether the individualworks or not for each time period or year in the sample. The selection equations include age,race, years of education, AFQT scores, marital status, presence of young kids in thehousehold, total number of kids, region of residence, and the unemployment rate asregressors. In addition to the functional form, the inclusion of young kids and individualspecific and time invariant regressors (such as gender, race, immigrant status, and AFQTscores) that drop from the fixed-effects estimation of the panel wage regressions help usidentify the selections equations. The predictions from the selection equations are used toconstruct the inverse Mills ratio included in equation (1). Results from the selectionregressions for each year and gender are available in Tables AII-AIV in the Appendix.

18. As previously mentioned, the dummy variables on the receipt of a particularperformance-based pay scheme and/or the offer of a particular fringe benefit can bethought of as job level variables to the extent that performance-based pay schemes and fringebenefits are typically implemented and offered by the employer to a broad group of workers.

19. These are dummies for each individual job pair in our sample. Every time a respondentchanges jobs, a new dummy variable is created to capture unobserved individual jobcharacteristics of the new pair.

20. See Wooldridge (1995).

21. For example, see Ewing (1996), Brown (1990), and Drago (1991).

22. In order to avoid potential collinearity problems, we created a dummy variable to indicatethe receipt of health insurance, dental insurance, life insurance or maternity leave as thesevariables were highly correlated.


benefits

691

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

23. A similar argument is pursued in relation to the employment relationship hazard rate inAzfar and Danninger (2001).

24. These values are obtained by taking the percentage of the average male wage displayed inTable III.

25. Flex Cash is a cash amount that may be added to an employees pay if he/she showsmedical and/or dental plan coverage through a source other than the current employer andwaive plan enrollment with the current employer. The Flex Cash payment is treated astaxable income and is subject to payroll taxes.

References

Abowd, J.M. (1990), Does performance-based managerial compensation affect corporateperformance?, Industrial and Labor Relations Review, Vol. 43, special issue, pp. 52S-72S.

Azfar, O. and Danninger, S. (2001), Profit sharing, employment stability, and wage growth,Industrial and Labor Relations Review, Vol. 54 No. 3, pp. 619-30.

Booth, A.L. and Frank, J. (1999), Earnings, productivity, and performance-related pay, Journalof Labor Economics, Vol. 17, pp. 447-63.

Brown, C. (1990), Firms choice of method of pay, Industrial and Labor Relations Review, Vol. 43,pp. 165s-82s.

Center for Human Resource Research (1999), NLSY79 Users Guide, CHRR, Columbus, OH.

Drago, R. (1991), Incentives, pay, and performance: a study of Australian employees, AppliedEconomics, Vol. 23, pp. 1433-46.

Eberts, R. and Stone, J. (1985), Wages, fringe benefits, and working conditions: an analysis ofcompensating wage differentials, Southern Economic Journal, Vol. 52, pp. 274-80.

Ewing, B.T. (1996), Wages and performance-based pay: evidence from the NLSY, EconomicLetters, Vol. 51, pp. 241-6.

Geddes, D.A. and Heywood, J.S. (forthcoming), Gender and piece rates, commissions andbonuses, Industrial Relations.

Gibbons, R. (1998), Incentives in organizations, Journal of Economic Perspectives, Vol. 12 No. 4,pp. 115-32.

Greene, W.H. (1981), Sample selection bias as a specification error: comment, Econometrica,Vol. 49, pp. 795-8.

Gunderson, M. (1989), Male-female wage differentials and policy responses, Journal ofEconomic Literature, Vol. 27, pp. 46-72.

Heckman, J.J. (1976), The common structure of statistical models of truncation, sample selection,and limited dependent variables and a simple estimator for such models, The Annals ofEconomic and Social Measurement, Vol. 5, pp. 475-92.

Hersch, J. (1996), Smoking, seat belts and other risky consumer decisions: differences by genderand race, Managerial and Decsion Economics, September, pp. 471-81.

Hinz, R.P., MacCarthy, D.D. and Turner, J.A. (1997), Are women conservative investors: genderdifferences in participant-directed pension investments, in Gordon, M.S., Mitchell, O.S.and Twinney, M.M. (Eds), Positioning Pensions for the Twenty-first Century, University ofPennsylvania Press, Philadelphia, PA, pp. 91-103.

Hubbard, R.G. and Palia, D. (1995), Executive pay and performance: evidence from the USbanking industry, Journal of Financial Economics, Vol. 39 No. 1, pp. 105-30.

Jensen, M.C. and Murphy, K.J. (1990), Performance pay and top-management incentives,Journal of Political Economy, Vol. 98 No. 2, pp. 225-64.

IJM24,6

692

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

Jianakoplos, N.A. and Bernasek, A. (1998), Are women more risk averse?, Economic Inquiry,Vol. 36 No. 4, pp. 620-30.

Lazear, E.P. (1986), Salaries and piece rates, Journal of Business, Vol. 59 No. 3, pp. 405-31.

Lazear, E.P. (2000), Performance pay and productivity, American Economic Review, Vol. 90No. 5, pp. 1346-61.

McCue, K. (1996), Promotions and wage growth, Journal of Labor Economics, Vol. 14 No. 2,pp. 175-209.

Murphy, K.M. and Topel, R.H. (1985), Estimation and inference in two-step econometricmodels, Journal of Business & Economic Statistics, Vol. 3 No. 4, pp. 370-9.

Olson, C.A. (2002), Do workers accept lower wages in exchange for health benefits?, Journal ofLabor Economics, Vol. 20 No. 2, pp. S91-S114.

Parent, D. (1999), Methods of pay and earnings: a longitudinal analysis, Industrial and LaborRelations Review, Vol. 53 No. 1, pp. 71-86.

Rosen, S. (1986), The theory of equalizing differences, in Ashenfelter, O.C. and Layard, R. (Eds),Handbook of Labor Economics, Vol. 1, North-Holland, Amsterdam.

Sciler, E. (1984), Piece rates versus time rate: the effect of incentives on earnings, The Review ofEconomics and Statistics, Vol. 66 No. 3, pp. 363-76.

Shapiro, C. and Stiglitz, J.E. (1984), Equilibrium unemployment as a worker discipline device,American Economic Review, Vol. 74 No. 3, pp. 433-44.

Wooldridge, J.M. (1995), Selection corrections for panel data models under conditional meanindependence assumptions, Journal of Econometrics, Vol. 68, pp. 115-32.

Appendix. DataHourly wage computationThe hourly wage variable used in the analysis is taken from the Hourly Rate of Pay Job #1variable constructed by Center for Human Resource Research (CHRR). This variable provides thehourly wage rate for the main job reported by respondents. The actual responses of thoserespondents who report wages with an hourly time unit in the initial earnings question appear inthis variable. For those reporting a time unit other than per hour or other in the initialearnings question, CHRR calculates an hourly rate of pay. The calculation procedure employedby CHRR factors in each respondents usual wage, time unit of pay, and usual hours worked perday/per week (Center for Human Resource Research, 1999).

Performance-based pay schemesThe variables used in our analysis to indicate the receipt of a particular type ofperformance-based pay scheme are taken from responses to the following question:

THE EARNINGS ON SOME JOBS ARE BASED ALL OR IN PART ON HOW A PERSON PERFORMSTHE JOB. (HAND CARD D) ON THIS CARD ARE SOME EXAMPLES OF EARNINGS THAT AREBASED ON JOB PERFORMANCE. PLEASE TELL ME IF ANY OF THE EARNINGS ON YOUR JOB(ARE/WERE) BASED ON ANY OF THESE TYPES OF COMPENSATION. PLEASE DO NOTINCLUDE PROFIT SHARING OR EMPLOYEE STOCK PURCHASE PLANS.

EARNINGS OF CURRENT JOB/MOST RECENT JOB BASED ON: WHICH ONES?

1 PIECE RATE

2 COMMISSIONS

3 BONUSES (BASED ON JOB PERFORMANCE)

4 STOCK OPTIONS

5 TIPS

6 OTHER

CHOOSE ALL THAT APPLY


benefits

693

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

Variable names Description Men Women

White Race dichotomous variables 0.583 0.569Hispanic 0.148 0.142Black 0.245 0.264Native American 0.024 0.025Immigrant Immigrant dichotomous variable 0.039 0.033Age Age of respondent 30.747

(4.486)30.952(4.525)

Years schooling Number of completed years of schooling 12.921(2.479)

13.294(2.272)

AFQTa Armed Forces Qualification Test percentilescore

24.782(22.490)

22.959(19.888)

Married Marital status dichotomous variable 0.539 0.544Kids Number of children in the household 0.908

(1.167)1.220

(1.186)Young child Dichotomous variable indicating the presence

of any children less than two years old 0.396 0.471Real hourly wage Hourly rate of pay in 1996 dollars 12.981

(8.493)10.528(6.698)

Log real hourlywage

Log of hourly rate of pay in 1996 dollars 2.407(0.550)

2.204(0.545)

Piece rate Dichotomous variables indicating whetherthe respondent received a particular type ofperformance-based incentive (see dataappendix)

0.033 0.025Commission 0.062 0.037Bonus 0.144 0.103Stock options 0.021 0.010Tips 0.020 0.035Other incentives 0.027 0.020Insurance Dichotomous variables indicating whether

the respondent received a particular type ofjob benefit (see data appendix)

0.780 0.784Retirement 0.569 0.570Profit sharing 0.277 0.258Training 0.443 0.486Childcare 0.053 0.074Firm size Total number of employees at the firm 552.270

(2,794.402)486.667

(1,989.297)Tenure Tenure in weeks 208.415

(214.583)195.609

(207.302)Occupational

experienceOccupational experience in weeks 108.320

(120.248)104.678

(120.981)Industry

experienceIndustry experience in weeks 146.671

(156.968)150.937

(164.903)Industries: Dichotomous variables for working in:

Agriculture andmining

Agriculture and mining

0.046 0.012Construction Construction 0.121 0.012Manufacturing Manufacturing 0.236 0.139TCPU Transportation, communications, and other

public utilities 0.098 0.051Trade Wholesale and retail trade 0.174 0.184

(continued )

Table AI.Variable description,means, and standarddeviations (forcontinuous variables)

IJM24,6

694

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

Variable names Description Men Women

FIRE Finance, insurance, and real estate 0.042 0.087Services Services 0.230 0.459Public

administrationPublic administration

0.054 0.056Occupations Dichotomous variables for occupations in:

Farming Farming 0.038 0.007Craftsmen Craft and related services 0.200 0.021Operators Machine operators 0.256 0.094Managerial Managerial positions 0.243 0.313Sales Sales 0.076 0.100Administrative

supportAdministrative support and clerical

0.070 0.275Service Other service related occupations 0.114 0.189Union status Unionization dichotomous variable 0.193 0.156Fixed work shift Dichotomous variable indicating a fixed shift 0.687 0.698Urban Dichotomous variable indicating an urban

area 0.781 0.783Unemployment

rateLocal unemployment rate 5.766

(2.440)5.762

(2.479)Year 1988 Year dichotomous variables 0.226 0.222Year 1989 0.227 0.221Year 1990 0.196 0.192Year 1996 0.157 0.163Year 1998 0.195 0.201Lambda Inverse Mills ratio from selection equations 0.213

(0.068)0.291

(0.083)

Note: a The AFQT numbers are deviations from the mean percentile score of their birth cohort.Therefore, people below average for their birth year will have a negative score. The overallaverage is also negative, which may be related to the over-sampling of the poor white population.The AFQT scores are reported in this manner by the Center for Human Resource Research sincethe test was taken at different points in time for the youthsSource: Authors tabulations using the NLSY79 Table AI.


benefits

695

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

1988 1989 1990 1996 1998

Male 0.264*** 0.257*** 0.194*** 0.300*** 0.244***(0.035) (0.035) (0.039) (0.043) (0.040)

Hispanic 0.057 0.112* 0.158*** 0.107 0.012(0.058) (0.059) (0.063) (0.070) (0.065)

Black 20.018 0.035 20.055 20.020 0.018(0.047) (0.048) (0.052) (0.057) (0.052)

Native American 20.105 0.022 20.110 0.071 20.123(0.104) (0.102) (0.126) (0.144) (0.126)

Immigrant 20.004 0.135 20.032 0.005 0.175(0.099) (0.107) (0.108) (0.125) (0.119)

Age 0.013 0.015* 0.021** 0.022** 0.007(0.008) (0.008) (0.009) (0.010) (0.009)

Years schooling 0.037*** 0.023** 0.018 0.029** 0.023**(0.010) (0.010) (0.011) (0.012) (0.010)

AFQT 0.004*** 0.005*** 0.006*** 0.006*** 0.005***(0.001) (0.001) (0.001) (0.001) (0.001)

Married 0.195*** 0.140*** 0.207*** 0.166*** 0.156***(0.039) (0.040) (0.044) (0.048) (0.044)

Kids 20.062*** 20.049** 20.068*** 20.004 20.058***(0.025) (0.023) (0.025) (0.021) (0.021)

Young child 20.081 20.108** 20.073 20.088* 0.289***(0.054) (0.051) (0.054) (0.053) (0.058)

Urban 20.090** 20.088** 0.010 20.114** 22.7e-04(0.045) (0.045) (0.051) (0.056) (0.044)

Unemployment 20.023*** 20.022*** 20.033*** 20.028*** 20.003rate (0.007) (0.009) (0.010) (0.007) (0.008)

Constant 0.335 0.426* 0.404 0.113 0.317(0.248) (0.254) (0.301) (0.371) (0.352)

Number of obs. 8,165 8,254 6,984 5,772 7,060Wald chi2(14) 211.55 171.14 177.39 155.27 142.34Log likelihood 23,363.14 23,372.67 22,665.99 22,177.15 22,611.83

Notes: Whites robust standard errors shown in parentheses. * Indicates significance at the 10percent level; ** indicates significance at the 5 percent level; and *** indicates significance as the1 percent level. White is used as reference

Table AII.Sample selection probitsfor the entire sample

IJM24,6

696

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

1988 1989 1990 1996 1998

Hispanic 0.100 20.057 20.041 0.148 20.016(0.084) (0.082) (0.091) (0.112) (0.098)

Black 20.054 20.042 0.182** 20.096 20.121*(0.068) (0.068) (0.074) (0.085) (0.074

Native American 20.084 20.028 0.026 0.260 20.100(0.153) (0.153) (0.214) (0.263) (0.208)

Immigrant 0.077 0.103 0.009 20.137 0.060(0.150) (0.145) (0.159) (0.184) (0.167)

Age 0.003 20.002 0.001 0.013 20.004(0.012) (0.012) (0.013) (0.015) (0.013

Years schooling 0.021 20.005 20.013 0.039** 0.015(0.015) (0.014) (0.016) (0.018) (0.015)

AFQT 0.006*** 0.007*** 0.005*** 0.004* 0.004**(0.002) (0.002) (0.002) (0.002) (0.002)

Married 0.380*** 0.259*** 0.429*** 0.460*** 0.350*(0.066) (0.066) (0.073) (0.084) (0.074)

Kids 20.009 0.006 20.077* 0.028 0.006(0.052) (0.044) (0.044) (0.037) (0.036)

Young child 0.039 0.117 0.085 20.043 0.135(0.106) (0.096) (0.095) (0.092) (0.092)

Urban 20.173*** 20.107 0.127* 20.001 20.042(0.069) (0.068) (0.075) (0.084) (0.067)

Unemployment 20.042*** 20.023* 20.026* 20.043*** 20.025**rate (0.011) (0.013) (0.014) (0.012) (0.011)

Constant 1.116*** 1.418*** 1.340*** 0.417 1.159**(0.373) (0.374) (0.441) (0.571) (0.515)

Number of obs. 4,169 4,230 3,587 2,875 3,563Wald chi2(13) 122.63 101.26 100.04 105.24 108.13Log likelihood 21,486.81 21,498.90 21,220.68 2897.47 21,161.45


Table AIII.Sample selection probits

for men


benefits

697

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

1988 1989 1990 1996 1998

Hispanic 0.024 0.271*** 0.345*** 0.114 0.062(0.080) (0.084) (0.088) (0.092) (0.088)

Black 0.044 0.136** 0.083 0.036 0.151**(0.066) (0.068) (0.074) (0.076) (0.073)

Native American 20.093 0.065 20.188 20.020 20.106(0.145) (0.141) (0.165) (0.180) (0.160)

Immigrant 20.096 0.211 20.014 0.141 0.291*(0.139) (0.156) (0.148) (0.168) (0.170)

Age 0.021* 0.028*** 0.040*** 0.026** 0.015(0.011) (0.011) (0.013) (0.013) (0.012)

Years schooling 0.039*** 0.038*** 0.037** 0.016 0.022(0.015) (0.014) (0.016) (0.016) (0.014)

AFQT 0.003** 0.004*** 0.009*** 0.008*** 0.006***(0.002) (0.002) (0.002) (0.002) (0.002)

Married 0.018 20.026 4.7e-04 20.066 0.016(0.051) (0.052) (0.059) (0.062) (0.057)

Kids 20.112*** 20.102*** 20.100*** 20.058** 20.107***(0.031) (0.030) (0.032) (0.027) (0.027)

Young child 20.199*** 20.277*** 20.186*** 20.154** 0.307***(0.066) (0.064) (0.068) (0.066) (0.078)

Urban 20.019 20.086 20.085 20.198*** 0.040(0.061) (0.061) (0.072) (0.076) (0.059)

Unemployment 20.007 20.021* 20.036*** 20.015 0.018*rate (0.009) (0.012) (0.014) (0.100) (0.011)

Constant 0.122 0.042 20.159 0.350 20.003(0.335) (0.347) (0.415) (0.494) (0.482)

Number of obs. 3,996 4,024 3,397 2,897 3,497Wald chi2(13) 140.29 162.72 141.84 64.68 52.60Log likelihood 21,822.67 21,804.14 21,399.37 21,243.64 21,423.82


Table AIV.Sample selection probitsfor women

IJM24,6

698

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

This article has been cited by:

1. Ali Fakih. 2014. Vacation Leave, Work Hours, and Wages: New Evidence from Linked Employer-Employee Data. LABOUR 28:10.1111/labr.2014.28.issue-4, 376-398. [CrossRef]

2. K. Sommerfeld. 2013. Higher and higher? Performance pay and wage inequality in Germany. AppliedEconomics 45, 4236-4247. [CrossRef]

Dow

nloa

ded

by S

AU

DI D

IGIT

AL

LIBR

ARY

(SDL

) At 0

9:55 2

2 Jan

uary

2016

(PT)

performance pay and fringe benefits

Documents