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Do Performance Pay Workers Experience Less Job Turnover and Longer
Tenures?
Patrick L. O'Halloran
Economics, Finance and Real Estate Department, Monmouth University
Abstract
Performance Related Pay (PRP) is a contemporaneous reward and thus may substitute for
deferred compensation. Deferred compensation is associated with longer tenures and lower
turnover rates. Thus, PRP may be proxy for greater turnover and shorter tenures. Alternatively,
a main conclusion of the PRP literature is that PRP can serve as a sorting mechanism that tends
to attract higher productivity workers. Furthermore, higher productivity workers experience
longer tenures and less job market turnover, especially involuntary layoffs. I find that workers
receiving contemporaneous PRP in the form of piece rates, commissions, and tips are no more
likely to experience turnover than wage workers. Moreover, those receiving deferred PRP in the
form of bonuses, stock options, and profit sharing experience longer tenures and less job
turnover in comparison to wage workers. Specifically, profit sharing appears to have a
significant impact on job separations and quits supporting the theory that profit sharing enhances
employment stability.
JEL Classification: J33, J63, M52
Keywords: Performance Pay, Turnover, Profit Sharing, Bonuses, Deferred Compensation
Corresponding Author:
Patrick L. O'Halloran,
Department of Economics, Finance and Real Estate
Leon Hess Business School
Monmouth University,
400 Cedar Avenue, West Long Branch, New Jersey 07764-1898
e-mail: pohallor@monmouth.edu
ph: 1-732-571-7530
October 16-17, 2009
Cambridge University, UK
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Do Performance Pay Workers Experience Less Job Turnover and Longer
Tenures?
Abstract
Performance Related Pay (PRP) is a contemporaneous reward and thus may substitute for
deferred compensation. Deferred compensation is associated with longer tenures and lower
turnover rates. Thus, PRP may be proxy for greater turnover and shorter tenures. Alternatively,
a main conclusion of the PRP literature is that PRP can serve as a sorting mechanism that tends
to attract higher productivity workers. Furthermore, higher productivity workers experience
longer tenures and less job market turnover, especially involuntary layoffs. I find that workers
receiving contemporaneous PRP in the form of piece rates, commissions, and tips are no more
likely to experience turnover than wage workers. Moreover, those receiving deferred PRP in the
form of bonuses, stock options, and profit sharing experience longer tenures and less job
turnover in comparison to wage workers. Specifically, profit sharing appears to have a
significant impact on job separations and quits supporting the theory that profit sharing enhances
employment stability.
I. INTRODUCTION
There has been a great deal of research on the determinants of turnover and also a vast amount of
literature concerning the impact of performance related pay (PRP) on such things as incentive
provision and sorting, but relatively few studies explicitly investigate how turnover is affected by
various types of PRP. There are two potential relationships between PRP and turnover. PRP
may serve as a contemporaneous reward substituting for deferred compensation. Deferred
compensation is typically associated with longer tenures and lower turnover rates. Thus, PRP
may be proxy for greater turnover and shorter tenures. On the other hand, PRP acts as a sorting
mechanism that tends to attract higher productivity workers who experience longer tenures and
less job market turnover. Furthermore, PRP is known to result in better matches between jobs
and employees.
Thus, PRP may be a proxy for lower turnover and longer tenures.
Consequently, the impact that PRP has on labor turnover is ambiguous.
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This paper seeks to explore the overall impact PRP has on job market turnover as well as
addressing what impact specific types of PRP have on labor market turnover in the form of quits
and layoffs. Specifically, I test whether workers receiving various types of PRP experience
differing rates of job market separations in the form of either quits or layoffs than those receiving
standard input based pay. From a policy perspective, if PRP workers do experience differential
rates of job separation and tenure in comparison to those receiving straight input pay, firms may
be able to use PRP schemes as a mechanism to retain their most valued employees.
PRP can take several forms. PRP can be based on individual performance such as
salary/wage pay, piece rates, bonuses, and commissions, or on group performance such as stock
options and profit sharing. Furthermore, PRP can be based on measures of input such as
wages/salary and bonuses, or based on measures of output such as piece rates, tips, commissions
and profit sharing. Moreover, various types of PRP can be either objective or subjective in
nature. PRP based on measurable output is theoretically less prone to a supervisor’s subjective
performance evaluation than PRP based on observed performance evaluation (Heywood and
O’Halloran, 2004). In what follows, I assume that piece rates, commissions and profit sharing
are more objective types of PRP while tips, bonuses and stock options are more subjective types
of PRP.
Empirical evidence reveals that those who receive PRP, regardless of type, do experience
fewer job separations and hence longer tenures. However, I observe that those receiving pay in
the form of piece rates, commissions, tips, and bonuses are no more likely to experience job
separations than input pay workers. Conversely, those receiving compensation in the form of
stock options and profit sharing experience lower rates of job separation. Therefore, the main
driver of the lower separation rates among PRP workers appears to stem from stock options and
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profit sharing. Furthermore, considering the distinction between quits and layoffs, the data
reveal that workers receiving subjective PRP are less likely to be terminated but no less likely to
quit while workers receiving objective PRP are less likely to quit but not significantly less likely
to be terminated.
Also, workers who receive contemporaneous PRP are less likely to be
terminated but not significantly less likely to quit while workers who receive deferred PRP are
less likely to quit and less likely to be terminated. I also find cursory evidence of stronger
separation responses to PRP among women. The result on profit sharing appears especially
robust supporting the argument that profit sharing enhances employment stability (Weitzman,
1985). It also tends to support the argument by Azfar and Danninger (2001) that profit sharing
allows for increased expected returns on firm-specific human capital investments. In contrast to
Azfar and Danninger’s findings, I find that profit sharing tends to reduce the incidence of quits
but not the incidence of layoffs. As a result, differentiating between the various types of PRP
may be crucial if a firm wants to effectively use PRP as a retention device to retain their most
valued employees.
This paper will proceed as follows: Section II will provide background on the two
opposing hypotheses concerning the relationship between PRP and turnover; Section III will
describe the data and provide some initial findings; Section IV will summarize the empirical
results; and Section V will offer conclusions and further recommendations.
II. EXPLORING THE RELATIONSHIPS BETWEEN PRP AND TURNOVER
One conclusion of the PRP literature is that PRP serves as a sorting mechanism, whereby higher
productivity workers self-select into PRP jobs. A second conclusion of this literature is that PRP
tends to elicit greater effort on behalf of workers and hence increase worker productivity.
Furthermore, PRP workers are believed to receive a compensating differential for the greater
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risks often associated with various types of PRP in comparison to non-PRP workers.
Consequently, PRP workers typically receive higher earnings than time-rate workers due to
selection, productivity, and risk effects associated with PRP.
Most prior research has shown that PRP workers typically receive higher earnings
compared to non-PRP workers.
Seiler (1984) finds that piece rate workers experience an
earnings premium of 14% resulting from greater risk inherent in incentive pay and an incentiveeffort effect. Brown (1992) further confirms that piece rate workers do experience higher
earnings than those paid time rates, but not for bonuses subject to supervisor ratings.
Ewing
(1996) and Parent (1999) both use data from the National Longitudinal Survey of Youth 1979
(NLSY79) and find that PRP workers earn more than time rate workers. Furthermore, Azfar and
Danninger (2001) find that profit sharing is related to higher wage growth than those without
profit sharing. Booth and Frank (1999), using data from the British Household Panel Survey,
find higher earnings among workers receiving bonuses, profit related pay, or commissions.
Given the sorting function that these types of PRP schemes play, it seems reasonable to
assume that jobs incorporating PRP will attract higher ability/higher productivity workers.
Indeed, much of the cited research in this paper points to the pivotal role PRP plays in attracting
higher ability/higher productivity workers. Specifically, Lazear (1995) finds that individually
based PRP attracts workers of higher ability and hence serves as a sorting mechanism, leading to
higher productivity. Ewing (1996) examines the effect that PRP has on earnings. He finds that,
after controlling for many personal, institutional, firm-specific, and demographic factors
available within the NLSY79, that those working in PRP jobs earn a substantial wage premium
which he suggests as evidence that more productive workers self-select into jobs with PRP.
Furthermore, Blinder (1990) and Ehrenberg (1990) theorize that PRP can influence employee
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behavior and provide incentives for individuals to increase their productivity. Paarsch and
Shearer (2000) find evidence of incentive and productivity effects among piece rates. Moreover,
other researchers have found support for the assumption that PRP also provides better incentives
alleviating the agency problems inherent where there is asymmetric information between the
employers and employees. Lazear (1986) finds that moving from hourly pay to piece rate pay in
one particular company results in a 41% increase in productivity for which over half of the gain
is attributed to incentive effects and the remainder attributed to sorting effects. Consequently,
evidence suggests that the increase in earnings experienced when moving from a straight input
payment system to a PRP system can be jointly associated with both sorting and incentive
provisions.
According to prior research, what types of jobs typically entail PRP? Lazear (1995)
points out that several conditions must be met if PRP is to serve as an effective sorting
mechanism. Specifically, Lazear hypothesizes that PRP in the form of piece rates will be more
successful when: (a) the cost of measuring output is low (in terms of both time and money); (b)
when the value of alternative activities (such as shirking) is high; (c) when the alternative wage
is high; (d) when workers are relatively young and haven’t accumulated a great deal of firm
specific human capital; and (e) when workers are more heterogeneous. Further, Brown (1992),
and MacLeod and Parent (1999) find output based pay to be more prevalent in the absence of
substantial team production and when monitoring output is relatively costless. Jirjahn and
Stephan (2004), also find that output based pay is common where worker performance is easily
measured and tasks tend to be relatively easy. Brown (1990) finds that PRP is more commonly
found in larger establishments due to the economies of scale involved in measuring performance.
Baker (1992) points out that when individual output is a good metric for performance and
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asymmetric information exists, one would expect to see many employees receiving pay based on
individual output such as piece rates, bonuses, and commissions. Conversely, when there is
symmetric information or when no measures of performance exist, input based pay will
dominate.
If there is asymmetric information and no good measures of performance are
available, Baker expects incentive contracts based on firm performance to dominate, such as
profit sharing or stock options.
Assuming that PRP attracts higher ability workers and provides better incentives than
input pay, one would expect that PRP workers would be less likely to experience job market
turnover, especially involuntary layoffs. This will be true if PRP tends to attract or sort workers
who can earn more within firms that offer PRP than they could alternatively earn working in
firms that base pay solely on input. Many studies find performance gains and selection effects
from PRP (Asch, 1990; Fernie and Metcalf, 1999; Parent, 1999; Lazear, 2000; Shearer, 2005;
and Freeman and Kleiner, 2005). Furthermore, many prior studies have found that workers
receiving higher pay and higher wage growth experience lower rates of job separation (Pencavel,
1972; Jovanovic, 1979; Viscusi, 1980; Bartel and Borjas, 1981; and Topel and Ward, 1992).
Accordingly, PRP may be associated with lower turnover rates and higher levels of tenure.
On the other hand, an alternative hypothesis views PRP as a contemporaneous reward for
output and hence a substitute for deferred compensation. Deferred compensation, according to
agency theory, results in “wage-tilt” or a steep age-earnings profile where a worker is “underpaid” (i.e., paid less than their value of marginal product) early in their tenure with a firm and
“over-paid” (i.e., paid more than their value of marginal product) in later years with the employer
as a reward for desirable behavior (Salop and Salop, 1976; Lazear, 1979, 1981). This is usually
intended to provide an incentive to limit the amount of worker shirking, malfeasance and
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turnover and hence increase worker productivity. Lazear (1979, 1981) focuses on the role
upward sloping age-earnings profiles play in aligning agent’s goals. This approach involves
basing future pay increases on current output and effort. Lazear (1995) points out that although
roughly equivalent to a piece rate scheme, upward sloping age earnings profiles differ in two
ways. First, the evaluation period is typically much longer than under the piece rate scheme.
Second, the worker must remain at the firm long enough to reap the reward for good
performance. Accordingly, deferred compensation may be associated with longer tenures and
thus, PRP may be a proxy for greater turnover and shorter tenure. Consequently, PRP may be
associated with greater turnover and shorter tenure instead of lower turnover and longer tenure as
hypothesized above. Thus, the effect PRP may have on labor market turnover and tenure is
theoretically ambiguous.
There is some evidence for deferred compensation from agency theory.
Although
Hutchens (1997) finds support for Lazear’s deferred compensation hypothesis using the NLSY,
Ippolito (1991) finds that wage tilt has no significant impact on tenure. Frank and Hutchens
(1993) observe evidence of “wage-tilt” among airlines pilots which they attribute to deferred
compensation, since one wouldn’t expect a pilot’s productivity to rise with experience. Also,
several researches have compared wage profiles between the self-employed and employed as
evidence of deferred compensation. According to agency theory, the steepness of the ageearnings profile, or the degree of “wage tilt”, reflects the desire of employers to provide
incentives to employees to avoid unwanted activities. Since the self-employed are not subject to
agency problems, one would expect the self-employed to have flat age-earnings profiles. Lazear
and More (1984) and Brown and Sessions (2006) both find relatively flat experience-earnings
profiles among the self-employed and steeper profiles among the employed.
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Brown and Sessions observes self-employed workers having the flattest profile, PRP employees
having steeper profiles than the self-employed and non-PRP employees having the steepest
profile. They conclude that these results provide evidence of the agency theory of deferred
compensation. Therefore, the presence of deferred compensation as an incentive device implies
that deferred compensation may partially substitute for PRP. Consequently, there appears to be
sufficient evidence that PRP may substitute for deferred compensation.
Therefore, any
conclusion regarding the relationship between PRP and turnover remains ambiguous.
Evidence of PRP workers experiencing shorter tenure and having higher turnover levels
is sporadic and typically associated with particular types of PRP. Prior research has revealed that
firms typically adopt certain PRP practices such as piece rates if they expect higher quit rates.
Goldin (1986) argues that workers who expect lower tenures will be less motivated by upward
sloping age earnings profiles. Kelly, et. al. (1998) show that workers with shorter expected
tenure will be more likely to seek jobs that reward contemporaneous remuneration. Furthermore,
Goldin (1986) and Geddes and Heywood (2003) find that women are more likely to be paid
piece rates because of their lower expected tenure but are less likely to receive PRP in the form
of commissions or bonuses. These findings further highlight the importance of differentiating
between different types of PRP schemes.
PRP often encompass very diverse methods of remuneration and can provide dissimilar
incentives. Consequently, the impact that PRP has on the probability of turnover and tenure
length may potentially differ by PRP type. In what follows, I will briefly summarize the
literature concerning the relationship between the various types of PRP and turnover. Most prior
evidence has found that piece rates and commissions are associated with shorter expected tenure
and hence higher turnover rates (Lazear, 1986; Goldin, 1986; Geddes and Heywood, 2003).
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Also, bonuses are typically associated with longer tenure and lower rates of turnover
(Hashimoto, 1979; Blakemore, Low, and Ormiston, 1987; Guthrie, 2000). Hashimoto (1979)
finds evidence that flexible bonus payments enhance investments in on-the-job training, which is
known to reduce turnover rates. Balkemore, Low, and Ormiston (1987) observe lower turnover
among those paid a two-part compensation scheme composed of fixed pay plus flexible bonuses
among those drawn from the Panel Study of Income Dynamics (PSID) for 1970 – 1981. Guthrie
(2000), drawing on organizational economics literature, finds that firms using skill-based pay
systems such as bonuses, improves employee retention among a sample of New Zealand firms.
Employee Stock Ownership Plans (ESOP) has been shown to reduce turnover (Klein and
Hall, 1988; Saneyoshi, 2001). Saneyoshi observes a negative correlation between employee
stock ownership and turnover, finding that those who have been awarded stocks are 71% more
likely to stay with the firm than those without stock ownership. Also, there is extensive prior
evidence showing that profit sharing is negatively related to turnover. Azfar and Danninger
(2001) find that those receiving PRP in the form of profit-sharing do experience lower rates of
turnover and higher productivity using the 1988 through 1994 waves of the NLSY79. They find
that employees participating in profit-sharing plans were less likely to experience job separations
- both quits and layoffs - than those not participating in a profit-sharing plan. Furthermore, they
find that those who participated in profit-sharing plans received more training for longer
durations and experienced higher wage growth, which they associate with faster rates of skill
accumulation. Using data from the United Kingdom, Green and Heywood (2007) observe that
profit sharing reduces the incidence of separations and increases the incidence of training.
Chelius and Smith (1990) find suggestive evidence that profit sharing reduces the incidence of
layoffs in the face of decreased product demand. Indeed, human capital theory predicts lower
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rates of turnover among firms with high levels of firm-specific training.
Royalty (1996)
confirms the link between training and turnover using data from the NLSY. She finds that
predicted turnover is negatively related to training. Furthermore, Scoppa (2003) theorizes that
firms will employ PRP when the costs associated with turnover are higher, and fixed pay when
the costs associated with turnover are lower.
Dale-Olsen (2006) empirically confirms this
relationship using matched employer-employee data from Norway.
These studies tend to
support the theory that PRP attracts higher productivity workers and reduces turnover. Although
I was unable to find any prior empirical or theoretical evidence concerning the likely effect of
tips on turnover, I would expect tips to be associated with lower tenures and higher turnover
because tips tend to be associated with low paying service sector jobs.
What may give rise to this pattern? Why is there such differing evidence concerning the
impact of PRP on job separations and tenure? It is this author’s hypothesis that some types of
PRP are a contemporaneous reward, such as piece rates, commissions, tips, and bonuses. Other
types of PRP may serve as deferred compensation, such as stock options and profit sharing.
Deferring benefits creates an incentive for employees to remain at a particular employer,
especially if the deferred compensation is not portable between employers. The promise of
future benefits of this sort creates an incentive for workers to stay, resulting in lower levels of job
separations and quits, but not substantially lower levels of layoffs. Contemporaneous forms of
PRP may act as marginal earnings that vary with the success of the firm (i.e., commissions are
higher when sales are higher). Consequently, firms experiencing decreases in demand for their
products will also find lower compensation costs in the form of lower PRP and hence be less
likely to lay off employees during a downturn, unlike a straight wage system. Therefore, one
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would expect to observe lower rates of job separations and quits among those receiving deferred
PRP and lower rates of layoffs among those receiving contemporaneous PRP.
Another partition can be made between PRP that tends to be objective in nature, in which
the worker receives a predefined level of compensation for output such as piece rates or
commissions.
Other types of PRP tend to be subjective in nature, where the worker’s
performance is subjectively evaluated by a supervisor such as yearly performance bonuses.
Given that subjective evaluations are often confidential private information, if a worker quits,
their subjective evaluation is not an easily transferred signal for a new employer, and hence one
would expect there to be no significant difference in quit rates among those receiving subjective
PRP and straight wages. Furthermore, if pay is based on objective performance levels, those
who find that they are poor performers and would be better off receiving a straight wage may be
more likely to quit. Also, those whose pay is based on subjective evaluations may be prone to
view a negative evaluation as a misjudgment by one’s superior as opposed to true sub-par
performance, and hence be no more likely to quit but eventually be more likely to be laid off.
Therefore, one would expect to observe lower rates of job separations and quits among those
receiving objective PRP and lower rates of layoffs among those receiving subjective PRP.
Therefore, simply designating workers as PRP workers and ignoring the type of PRP may
be misleading. In what follows, I will explore the empirical relationship between differing types
of PRP and job turnover in the form of both quits and layoffs.
III. DATA AND THE DETERMINANTS OF LABOR MARKET TURNOVER
The data used for analysis is the NLSY79. This data set follows a nationally representative
sample of 12,686 men and women who where between the ages of 14-22 years old as of their
initial interview in 1979.
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These individuals were interviewed annually up to 1994 and
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subsequently interviewed every two years. As with most longitudinal data sets, there has been a
great deal of attrition since the survey’s initiation.
The NLSY79 collects data on each
respondent’s labor force experiences, labor market attachment, and investments in education and
training as well as information on PRP and turnover.
The sample employed in this analysis
consists of the 1988 – 1990 and 1996 – 2000 waves of the NLSY79, in which detailed PRP
related data was gathered.
The NLSY79 includes data on PRP as well as extensive data
concerning respondents’ demographics and work history. Work history information provides
data on up to five jobs help by respondents between waves. From this information, I focus on
the main CPS job for each respondent and simply ignore secondary jobs. From these waves, I
eliminated those from the supplemental over-samples, leaving a representative cross-section of
the population. Consequently, I do not employ weights when reporting means or performing
estimations. The sample is further reduced in size due to respondent attrition and missing data.
Eliminating those who report being self-employed, in the active military, as well as those
observations that entail missing data leaves me with an unbalanced panel of 17,114 observations
across 4,925 individuals.
The NLSY asks respondents the following questions: “The earnings on some jobs are
based all or in part on how a person performs the job. On this card are some examples of
earnings that are based on job performance. Please tell me if any of the earnings on your job
are/were based on any of these types of compensation.”, for the 1988 – 1990 waves and, “On this
card are some examples of earnings that are based on job performance. Please tell me if any of
the earnings on your job are/were based on any of these types of compensation.”, for the 1996 –
2000 waves. The various types of PRP listed are piece rates, commissions, bonuses, stock
options, tips, and “other”. Furthermore, respondents are asked if they are involved in any type of
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profit sharing or employee stock sharing plans as well as pension plans. Although respondents
were asked about participation in various payment schemes, no information was collected
concerning the extent that earnings were based on these schemes. Some respondent’s earnings
may be entirely based on performance while other’s earnings may be only marginally affected by
their performance. Furthermore, what constitutes “other” forms of PRP is ambiguous but not
insignificant given that 2.4% of the selected sample report receiving “other” forms of PRP
besides those already mentioned. Since it is impossible to interpret what these “other” types of
PRP entail, I include those reporting receiving “other” forms of PRP as receiving PRP when
constructing the PRP variable and include them as a separate type of PRP in the regressions.
Also, no information was collected about the magnitude of employee profit sharing or pension
accumulation. Given these restrictions, it is impossible to discern the extent to which pay is
based on performance.
The lack of detailed payment scheme information potentially
complicates analysis and limits one’s ability to disentangle the association between job mobility
and PRP. This problem becomes even worse if some jobs entail a combination of different types
of PRP.
These restrictions aside, one can use the incidence of PRP to determine if those receiving
PRP are more likely to experience turnover. Defining PRP as those who receive pay in the form
of piece rates, commissions, bonuses, stock options, tips, profit sharing and “other” forms of
PRP, I find that workers receiving PRP are less likely to be laid off or quit their job than those
who do not receive any PRP. Among those who receive PRP, only 6.6% report job separations
over the period considered, while 10.5% of those who do not receive any PRP report job
separations (See Table 1. Descriptive Statistics).
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I further lump different PRP schemes into four distinct categories. I group piece rates,
commissions, tips, and bonuses into contemporaneous PRP and stock options and profit sharing
into deferred PRP. Furthermore, I consider PRP to be objective in nature if it is a PRP scheme
that leaves little room for a supervisor’s subjective performance evaluation, and subjective in
nature if it is a PRP scheme that is at the discretion of a supervisor’s subjective performance
evaluation. Consequently, I consider piece rates, commissions, and profit sharing as objective
PRP schemes because they typically involve predefined measures of output such as pieces
assembled, cars sold, or profit generated. Also, I consider bonuses, tips, and stock options as
subjective PRP schemes because they involve some type of performance appraisal by one’s
supervisor. Given the arbitrary nature of these categorizations, especially with regard to whether
various types of PRP should be considered objective or subjective, I will perform further
sensitivity tests on these categorizations. Also, given the limitations in the data, it is impossible
to determine exactly how the PRP scheme is structured and whether it is based entirely on
objective performance measures such as output, or entirely subjective performance appraisals by
one’s supervisor, or both. Further complicating matters, respondents can and do simultaneously
receive multiple types of PRP, such that a worker may be simultaneously receiving both
contemporaneous and deferred performance based pay or objective and subjective performance
based pay at the same time. Another difficulty involves the likelihood that PRP may have
differential effects on turnover by gender. Female labor supply may be more sensitive to
earnings and the terms of employment than male labor supply. Consequently, I also split the
sample by gender to see if there are differential responses to PRP with regard to job turnover
between genders.
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The NLSY79 also asks respondents why their job terminated.1 The questions asked was
“Which of the reasons on this card best describes why you happened to leave this job.” The
reasons listed include lay offs, plant closing, end of temporary/seasonal job, firing, program
ending, quitting for family reasons, quitting to find or take another job, and quitting for other
reasons.
Also, additional information was collected about the respondent’s tenure with a
particular employer. Combining these data with the data on PRP reveals that PRP workers are
less likely to experience layoffs than those workers who do not receive any performance based
pay. As shown in Table 1, PRP workers are almost half as likely to experience job separations as
those workers who do not receive any PRP.
Many individual and firm level characteristics are available in the NLSY and are
summarized by the payment scheme in Table 1. I include several measures of human capital and
ability. These must be included in order to control for the impact education and ability have on
the propensity to quit or be fired. Also, as previously mentioned, PRP tends to attract workers of
higher ability and hence those with greater levels of education. The level of education is
measured as the highest grade completed as of May 1st of each survey year. I also include each
individual’s Armed Forces Qualification Test score as a proxy variable in a regression context
for ability. Since PRP is thought to attract higher productivity workers, one would expect higher
levels of education and measured ability among PRP workers than among non-PRP workers. As
shown in Table 1, educational levels and ability are higher among PRP workers, except for those
receiving piece rates and tips.
As previously discussed, higher wages tend to be associated with lower levels of turnover
and greater use of PRP. This is likely the result of PRP attracting higher productivity workers
into jobs that entail PRP. Therefore, including real wage and the log of the real wage in all
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appropriate estimations is critical. The real wage is constructed by taking the individual’s
nominal hourly rate of pay and dividing by each region’s Consumer Price Index - All Urban
Consumers using 1982-84 as the base period and then taking the logarithm. The hourly rate of
pay information was collected retrospectively from the respondent at the time of interview and
reports their pay at their current or most recent job and identifies the hourly earnings for the job
identified as the CPS job. Furthermore, I include an indicator denoting whether the respondent
received any training, since the last interview because training and turnover are strongly
negatively correlated (Royalty, 1996).
I also include gender and family status indicators. It is well known that females typically
experience higher rates of turnover and lower tenures than males for reasons such as childbirth
and rearing (Goldin, 1986, 1990). Therefore it is essential to control for the impacts that gender
and family status have on labor market separations and tenure. Besides an indicator for gender, I
create an indicator for those unmarried without children, unmarried with children under 6 years
of age, unmarried with children 6 years of age or older, married without children, married with
children under 6 years of age, and married with children 6 years of age or over.
Given the finding that larger establishments are more likely to make use of PRP schemes
(Brown, 1990), I include indicators of firm size. I create indicators for a small employer
employing less than 10 workers, a medium employer employing between 10 and 49 employees, a
large employer employing between 50 and 200 employees, and a very large employer employing
more than 200 workers.
Furthermore, I include variables to control for global job satisfaction. Respondents were
asked “How (do/did) you feel about (the job you have now/your most recent job)? (Do/Did) you
like it very much, like it fairly well, dislike it somewhat, or dislike it very much?” From this
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question I create four indicator variables for each level of satisfaction. A respondent’s degree of
job satisfaction should significantly influence rates of job separations. Within the sample, those
who report liking their job very much have a separation rate of 7% while those who report
disliking their job very much have a separation rate of 28%, with the vast increase among quits
as opposed to layoffs. I also include a variable to control for the presence of internal labor
markets and fringe benefits. This internal labor market indicator is constructed from a question
asking respondents whether a position change within an employer was a promotion. If they
reported it was, the variable takes a value of one, otherwise it is zero. One would expect to
observe lower levels of job separation among those working in establishments with internal labor
markets. Also, one would expect to observe lower rates of job separations for those workers
receiving more fringe benefits. Consequently, I create several indicators for the presence of
fringe benefits. I create an indicator for the presence of insurance (medical, dental, and life),
maternity leave, firm sponsored training and education, and whether the employer provides any
child care. Although select waves collect information on the presence of paid vacation and sick
leave, these questions were not consistently asked of respondents for the waves of data
considered and hence omitted from the analysis.
Since the nature of production critically determines whether various types of PRP are
feasible, I include occupational/industrial indicators at the one digit level as a surrogate for the
nature of production. I also include an indicator for union affiliation and a count variable for the
unemployment rate of the labor market of the worker’s current residence. According to the NLS,
the unemployment rate is constructed using state and area labor force data from the May
publication of Employment and Earnings for the month of March of each survey year. If a
respondent resides in a metropolitan area, then the unemployment rate is the unemployment rate
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for that metropolitan area. Otherwise, the unemployment rate is the computed balance of state
unemployment rate for the state in which the respondent resides.
Other individual specific information is incorporated, including age and experience
(measured as the sum of actual weeks worked since last interview over the respondents work
history), since it is well known that older more experienced workers are much less likely to
experience job separations.2 I also include the average hours per week worked, urban status,
number of jobs held, and indicators for each year of the panel.
IV. EMPIRICAL RESULTS
Summary statistics, combining all six years of data in which performance based pay questions
were included in the NLSY79, are shown in table 1. Absent controls, PRP workers experience
lower levels of job separation, in the form of quits and layoffs, than workers strictly receiving
input based pay. Further differentiating between the various PRP schemes reveals that layoffs
and quit rates are much lower for those who receive PRP in the form of stock options, profit
sharing, bonuses, commission, or with multiple PRP schemes. Piece rate workers initially
appear to be no different in terms of separation rates than workers receiving input based pay,
while tip workers have higher rates of labor market separation than workers receiving input
based pay. Confirming prior research (Bonars and Moore, 1995), PRP workers receive higher
wages than time rate workers and have slightly higher levels of education. Contrary to Bonars
and Moore, I find that PRP workers have longer tenures than time rate workers, but this
difference may be due to the exclusion of profit sharing and stock options from their definition of
PRP. In comparison to time rate workers, piece rate, commission and tip workers have shorter
tenures, while all other PRP workers have longer tenures. This pattern is consistent with prior
findings of Bonars and Moore. Also, confirming earlier work, PRP tends to be more prevalent in
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larger establishments.
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Furthermore, PRP workers tend to be more satisfied, receive more
promotions, and are more likely to receive fringe benefits than non-PRP workers.
In order to obtain a better picture of the impact PRP has on the proclivity of job
separations, layoffs and quits, I estimate probit models by payment scheme.3 The result of the
probit estimation, including all of the variables listed in Table 1, is shown in Table 2.4
Controlling for theoretically relevant determinants reveals that PRP lowers the probability of job
separations and layoffs but not quits. Workers receiving performance based pay are less likely to
experience job separations and less likely to be fired than those workers not receiving PRP.
Further separating PRP schemes by type, stock options and profit sharing appear to significantly
reduce the propensity of job separations while piece rates, commissions, tips and bonuses emerge
insignificantly different from zero. Moreover, profit sharing reduces the probability of quitting
while bonuses reduce the probability of layoffs.
Table 3 separates PRP into four distinct categories. In what follows, I assume that
contemporaneous PRP includes piece rates, commissions, tips and bonuses, while deferred PRP
includes stock options and profit sharing.
Given this dichotomy, I further assume
contemporaneous PRP is associated with lower probability of layoffs and deferred PRP is
associated with lower probabilities of both job separation and quits. The lower separation and
quit rates among those receiving deferred PRP can be attributed to the effect of “Lazear type”
delayed compensation, creating an incentive for workers to stay with their current employer.
The lower rates of layoffs among those receiving contemporaneous PRP in the form of stock
options and profit sharing is likely due to workers earnings varying with firm success, such that
decreases in sales would be associated with decreases in the labor compensation. This argument,
first elaborated upon by Wertzman (1985) with regard to profit sharing, has received prior
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empirical support (see Chelius and Smith, 1990; Guthrie, 2000; Azfar and Danninger, 2001;
Green and Heywood, 2007). Additionally, those receiving contemporaneous PRP such as piece
rates, commissions, tips and bonuses tend to attract those types of workers who perform better
under these types of compensation schemes. Since they are better performers, they are less
likely to be laid off than those receiving a straight wage or paid by group performance subject to
the “1/n” free-rider problem.
I further separate PRP into objective PRP, whereby pay is typically based on measurable
output such as piece rates, commissions, and profit sharing and subjective PRP, whereby pay is
typically based on subjective evaluations such as tips, bonuses and stock options.5
Those
receiving objective PRP are less likely to experience job separations or quit their job, but not less
likely to experience a layoff. Those receiving subjective PRP are less likely to experience job
separations or be laid off, but not less likely to quit. This is likely because subjective evaluations
are more easily private information and hence a negative evaluation won’t influence the
probability of obtaining a new job elsewhere. Consequently, the worker will be no more likely
to quit than otherwise, and managers may be less hesitant to lay a worker off for perceived poor
performance.
In order to control for potentially unmeasured occupational differences, I further limit the
estimations to those occupations where the different PRP schemes are more prevalent. Namely, I
limit piece rates to craft and operative occupations; commissions to sales occupations; tips to
service occupations; bonuses, stock options, and profit sharing to professional and managerial
occupations; and multiple PRP schemes to professional and managerial occupations. Doing so
obviously reduces the sample size but limits the differences among workers and jobs. These
estimations, shown in Table 4, reveal that profit sharing is associated with lower probabilities of
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job separations and quits, but no difference in layoffs in comparison to those not receiving profit
sharing among managerial and professional workers. Also, commissions tend to lower the
propensity to quit among sales workers, while piece rates tend to increase layoffs among craft
and operative occupations. As an alternative method of controlling for potentially unmeasured
occupational differences among workers and job, I further refine the occupational and industrial
indicators to the three digit level. This reveals roughly similar results as those reported above.6
It is well know that turnover rates were historically higher among females than males
(Farber, 1999). Indeed, Heywood and Geddes (2003) observe that women are more likely to
receive piece rates and less likely to receive other types of PRP such as commissions and
bonuses due to women’s weaker labor force attachment and expected tenure. Consequently,
females may have very different turnover responses to PRP than males. Therefore, I further
subdivide the sample by gender and re-estimate the probits on job separations, quits and layoffs.
Although a much more thorough analysis of gender differences in labor market behavior
associated with PRP is beyond the scope of this paper, some preliminary observations can be
made.
Running separate estimations among females and males reveals that much of the
observed lower propensity for job separations associated with PRP is attributable to females. As
shown in Table 5, male PRP workers are not less likely to experience job separations than their
non-PRP counterparts, but females are 1.2% less likely to experience job separations than their
non-PRP counterparts. Consequently, females appear to have a stronger behavioral response to
PRP with respect to job separations than males. Furthermore, males receiving piece rates are
more likely to experience layoffs but less likely to quit, whereas females are not less likely to
either quit or be laid off. Additionally, profit sharing decreases the probability of job separations
and quits among females but not males. The differences in the probability of separations, quits
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and layoffs between genders seem to imply that there are systematic differences between genders
in worker turnover in response to PRP schemes. Interacting PRP plan type with gender reveals
significant differences between genders, further supporting the differing nature of turnover
response to PRP schemes.7 Given these results and the prior evidence provided by Geddes and
Heywood (2003) that differing types of PRP may have disparate impacts on labor market
behavior between genders, further analysis of this topic should take into account potential
differences in response to PRP by females and males.
An advantage proffered by the use of panel data is the ability to control for individual
effects. Consequently, in order to control for individual effects, I also estimate fixed-effects
probit models. Tables 6 and 7 were estimated using LIMDEP’s fixed-effects probit procedure.8
Given a fixed effects approach, sample sizes are much smaller than those reported in Table 2
because workers with no change in their PRP status will fall out of the sample. Table 6 again
reveals a similar pattern to that displayed in Table 2.
PRP workers are less likely to experience
job separations and layoffs, but not less likely to quit. Also, those receiving profit sharing are
less likely to experience job separations and quits, but not less likely to experience a layoff. The
fixed-effects estimates also reveal that piece rate workers have higher rates of layoffs,
confirming Lazear’s theory concerning the relationship between piece rates and turnover. Bonus
workers experience lower levels of layoffs which would be expected since it would seem odds to
provide a bonus to a worker that an employer will terminate. Tip workers are less likely to
experience job separations or quits. Workers receiving commissions also appear to be more
likely to quit their job. Running fixed-effects estimations on the occupational subsamples,
limited to occupations where differing types of PRP are more prevalent, further reduces sample
sizes due to time invariant observations dropping from estimations.
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reduction in sample sizes associated with the fixed-effects estimations, the presence of profit
sharing continues to reduce the probability of a worker experiencing job separations or quits. As
displayed in Table 7, profit sharing reduces the probability of job separations and quits among
professional and managerial occupations, even after controlling for individual-effects.
V. CONCLUSION AND FURTHER EXTENSIONS
The evidence presented suggests that the impact of PRP on labor market turnover critically
depends on what type of PRP one considers and whether one focuses on layoffs or quits. Also,
there appears to be gender differences in the effect of PRP on turnover. Overall, workers
receiving PRP have lower rates of job separation than non-PRP workers. Furthermore, workers
receiving PRP are no less likely to quit and much less likely to be fired than those not receiving
PRP. Confirming prior findings, these results seem to be mainly driven by the impact of stock
options and profit sharing. Those workers whose pay is partly dependent on profit sharing are
less likely to experience job separations or quits, but not less likely to experience a layoff. Also,
there is evidence that workers who receive bonuses are less likely to be laid off than whose who
do not receive bonuses. Mapping PRP types onto contemporaneous PRP and deferred PRP
reveals lower rates of job separations and quits for those who receive deferred PRP and lower
rates of layoffs for those who receive contemporaneous PRP.
Separating PRP types into
objective PRP and subjective PRP reveal that those who receive objective PRP experience lower
rates of job separations and layoffs, while those receiving subjective PRP experience lower rates
of layoffs in comparison to non-PRP workers. Therefore, among the NLSY79 cohort, PRP acts
as a sorting mechanism, attracting workers who are less likely to experience job separations and
layoffs but not less likely to quit. Consequently, employers may be able to enhance employee
retention by using alternative payment schemes rather than paying compensation strictly based
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on a worker’s input of time. Of the different types of PRP, profit sharing appears to consistently
have a desirable impact on employee retention.9
One issue that requires further exploration is difference impacts piece rates and the
broader measure of contemporaneous PRP appear to have on the propensity to quit. Another
question requiring further explanation is the behavioral difference in response to PRP between
genders. PRP appears to have a larger impact on the turnover behavior of women. Ideally, as
data becomes available enabling researches to detail the extent a worker’s pay is associated with
various types of PRP, researchers may be able to quantify the relationship between PRP and
turnover more precisely. Given that 39% of workers within the NLSY79 cohort report receiving
some type of PRP during the years 1988 – 1990 and 1996 – 2000, a better understanding of the
relationship between PRP and turnover would be a significant advance in the literature
concerning PRP and turnover.
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DATA APPENDIX
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Table 2: Determinants of job separations, quits, and layoffs - probit analysis – marginal effects
shown (Continued)
(1)
Job
Separation
PRP*
Piece Rates*
-0.008
(2.16)**
-
Commissions*
-
Tips*
-
Bonuses*
-
Stock
Options*
Other PRP*
-
Profit
Sharing*
Multiple
PRP*
Like Job
Very Much*
Dislike Job
Somewhat*
Dislike Job
Very Much*
Any formal
OJT*
Promotion*
-
Female*
Non-white*
AFQT Score
Education
(Years)
Union
Affiliation*
Small
employer*
Medium
employer*
-
-0.005
(1.42)
0.063
(8.09)***
0.126
(9.37)***
-0.018
(3.91)***
-0.030
(6.69)***
0.048
(10.36)***
0.010
(2.17)**
-0.000
(1.10)
-0.002
(2.38)**
0.003
(0.43)
-0.001
(0.24)
0.005
(0.97)
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(2)
Job
Separation
by PRP
Type
0.003
(0.24)
0.001
(0.13)
-0.013
(1.46)
-0.000
(0.05)
-0.029
(1.96)**
0.000
(0.02)
-0.010
(1.97)**
-0.002
(0.25)
-0.005
(1.38)
0.063
(8.11)***
0.126
(9.39)***
-0.018
(3.94)***
-0.030
(6.67)***
0.048
(10.34)***
0.010
(2.13)**
-0.000
(1.09)
-0.002
(2.36)**
0.002
(0.34)
-0.002
(0.35)
0.005
(0.87)
(3)
Quits
-0.003
(0.87)
-0.003
(0.90)
0.047
(7.45)***
0.107
(9.58)***
-0.014
(3.96)***
-0.017
(4.78)***
0.034
(9.41)***
0.005
(1.27)
-0.000
(0.56)
-0.001
(1.69)*
0.004
(0.83)
0.002
(0.48)
0.004
(1.02)
33
(4)
Quits by
PRP
Type
-0.007
(0.77)
0.001
(0.08)
-0.007
(1.09)
0.006
(1.11)
-0.015
(1.30)
0.013
(1.30)
-0.007
(1.73)*
-0.001
(0.13)
-0.003
(0.91)
0.047
(7.50)***
0.106
(9.59)***
-0.014
(4.03)***
-0.017
(4.86)***
0.034
(9.46)***
0.004
(1.20)
-0.000
(0.59)
-0.001
(1.69)*
0.003
(0.74)
0.001
(0.28)
0.004
(0.87)
(5)
Layoffs
-0.004
(2.23)**
-0.002
(1.05)
0.011
(2.91)***
0.010
(1.86)*
-0.002
(0.85)
-0.010
(4.41)***
0.009
(4.01)***
0.004
(1.70)*
-0.000
(1.08)
-0.001
(1.66)*
-0.002
(0.50)
-0.002
(0.88)
0.001
(0.34)
(6) Layoffs
by PRP
Type
0.008
(1.36)
0.001
(0.20)
-0.004
(0.88)
-0.006
(1.74)*
-0.013
(1.54)
-0.010
(1.69)*
-0.002
(0.72)
-0.001
(0.26)
-0.002
(0.93)
0.011
(2.93)***
0.010
(1.90)*
-0.002
(0.82)
-0.010
(4.26)***
0.009
(3.93)***
0.004
(1.74)*
-0.000
(1.02)
-0.001
(1.66)*
-0.002
(0.54)
-0.002
(0.80)
0.001
(0.38)
9th Global Conference on Business & Economics
ISBN : 978-0-9742114-2-7
Table 2: Determinants of job separations, quits, and terminations - probit analysis – marginal
effects shown (Continued)
(1)
Job
Separation
Large
employer*
Unmarried with
Children < 6*
Unmarried with
Children >= 6*
Married w/o
Children*
Married with
Children < 6*
Married with
Children >= 6*
Avg. Hours of
Work Per Wk
Age
(Years)
Urban Status*
Unemp. Rate
Number of
Jobs Held
Log real wage
Insurance*
0.011
(2.07)**
0.018
(2.24)**
-0.016
(2.58)***
-0.016
(2.85)***
0.019
(3.78)***
-0.017
(3.29)***
0.000
(1.74)*
0.000
(0.30)
0.008
(2.16)**
0.007
(3.26)***
0.001
(1.90)*
-0.026
(6.22)***
-0.024
(4.37)***
-0.034
(7.08)***
-0.011
(2.49)**
(2)
Job
Separation
by PRP
Type
0.011
(2.03)**
0.018
(2.24)**
-0.016
(2.61)***
-0.016
(2.88)***
0.018
(3.76)***
-0.017
(3.33)***
0.000
(1.69)*
0.000
(0.26)
0.009
(2.25)**
0.007
(3.25)***
0.001
(1.90)*
-0.025
(6.10)***
-0.023
(4.28)***
-0.034
(7.01)***
-0.010
(2.27)**
(3)
Quits
(4)
Quits by
PRP Type
(5)
Layoffs
0.006
(1.39)
0.019
(2.95)***
-0.012
(2.58)***
-0.007
(1.49)
0.023
(5.73)***
-0.007
(1.67)*
0.000
(1.48)
-0.000
(0.06)
0.004
(1.16)
0.002
(1.12)
0.000
(1.39)
-0.018
(5.74)***
-0.014
(3.32)***
-0.018
(4.83)***
-0.005
(1.42)
0.005
(1.28)
0.019
(2.96)***
-0.012
(2.58)***
-0.007
(1.53)
0.023
(5.70)***
-0.007
(1.66)*
0.000
(1.38)
-0.000
(0.03)
0.004
(1.27)
0.002
(1.07)
0.000
(1.40)
-0.018
(5.70)***
-0.013
(3.21)***
-0.017
(4.72)***
-0.004
(1.28)
0.004
(1.31)
-0.002
(0.46)
-0.002
(0.57)
-0.006
(2.35)**
-0.004
(1.91)*
-0.007
(2.88)***
0.000
(1.09)
0.000
(0.63)
0.004
(1.84)*
0.004
(3.49)***
0.000
(1.21)
-0.005
(2.15)**
-0.005
(1.98)**
-0.013
(4.93)***
-0.005
(2.16)**
(6)
Layoffs by
PRP Type
0.004
(1.40)
-0.002
(0.50)
-0.002
(0.62)
-0.006
(2.35)**
-0.004
(1.89)*
-0.007
(2.94)***
0.000
(1.14)
0.000
(0.47)
0.004
(1.88)*
0.004
(3.46)***
0.000
(1.23)
-0.004
(1.99)**
-0.005
(1.97)**
-0.013
(4.99)***
-0.005
(2.02)**
Maternity
Leave*
Firm
Sponsored
Education*
Firm
-0.001
-0.000
-0.001
-0.000
-0.001
-0.000
Sponsored
(0.12)
(0.04)
(0.16)
(0.07)
(0.15)
(0.07)
Child Care*
Log Likelihood -4231.36
-4226.93
-3180.17 -3175.14 -2019.68
-2013.30
2
Pseudo R
0.169
0.170
0.151
0.152
0.140
0.143
Observations
17,114
17,114
17,114
17,114
17,114
17,114
(*) dF/dx is for discrete change of dummy variable from 0 to 1
z and P>|z| correspond to the test of the underlying coefficient being 0
Absolute value of z statistics in parentheses
* significant at 10%; ** significant at 5%; *** significant at 1%
All estimations include dummies for industry, occupation, tenure, tenure squared and year.
October 16-17, 2009
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9th Global Conference on Business & Economics
ISBN : 978-0-9742114-2-7
Table 3: Determinants of job separations, quits and terminations by PRP type - probit analysis –
marginal effects shown
Contemporaneous
PRP 1
Deferred PRP 2
Objective PRP 3
(1)
Job
Separation
-0.005
(1.13)
-0.010
(2.35)**
-
(2)
Quits
0.000
(0.07)
-0.006
(1.85)*
-
(3)
Layoffs
-0.004
(1.92)*
-0.003
(1.28)
-
(4)
Job
Separation
-
(5)
Quits
(6)
Layoffs
-
-
-
-
-
-0.007
-0.006
(1.82)*
(1.92)*
Subjective PRP 4
-0.008
-0.000
(1.74)*
(0.09)
Log Likelihood
-4230.15
3178.81
-2019.38
-4230.34
-3178.68
Pseudo R squared
0.169
0.151
0.141
0.169
0.151
Number of Obs.
17,114
17,114
17,114
17,114
17,114
All coefficients report dF/dx for discrete change of dummy variable from 0 to 1
z and P>|z| correspond to the test of the underlying coefficient being 0
Absolute value of z statistics in parentheses
* significant at 10%; ** significant at 5%; *** significant at 1%
Each estimation includes the full set of controls as indicated in Table 2.
1. Includes piece rates, commissions, tips and bonuses.
2. Includes stock options and profit sharing.
3. Includes piece rates, commissions and profit sharing.
4. Includes tips, bonuses and stock options.
October 16-17, 2009
Cambridge University, UK
35
-0.001
(0.28)
-0.007
(2.84)***
-2017.83
0.141
17,114
9th Global Conference on Business & Economics
ISBN : 978-0-9742114-2-7
Table 4: Determinants of job separations, quits and terminations by occupation - probit analysis
– marginal effects shown
PRP by Occupations
(1)
Job
Separation
by
Occupation
0.010
(0.70)
-0.006
(0.65)
0.017
(1.72)*
Commissions among
Sales Occupations
-0.020
(1.54)
-0.018
(2.03)**
-0.000
(0.18)
765
Tips among Service
Occupations
-0.014
(0.80)
-0.013
(1.02)
0.001
(0.23)
1,970
Bonuses among
Professional and
Managerial Occupations
0.003
(0.43)
0.003
(0.52)
-0.000
(0.12)
6,155
Stock Options among
Professional and
Managerial Occupations
-0.017
(1.39)
-0.007
(0.65)
~
6,155
Profit Sharing among
Professional,
Managerial, and Clerical
Occupations
-0.014
(2.57)**
-0.012
(2.81)***
-0.001
(0.25)
6,155
Piece Rates among Craft
and Operative
Occupations
(2)
Quits
by
Occupation
(3)
Layoffs by
Occupation
Obs
3,519
Multiple
-0.008
-0.005
-0.002
6,155
PRP among Professional (1.12)
(0.88)
(0.68)
and Managerial
Occupations
All coefficients report dF/dx for discrete change of dummy variable from 0 to 1
z and P>|z| correspond to the test of the underlying coefficient being 0
Absolute value of z statistics in parentheses
* significant at 10%; ** significant at 5%; *** significant at 1%
Each estimation includes the full set of controls as indicated in Table 2.
~ Stock Options predicts failure perfectly in termination specification and hence cannot be estimated.
October 16-17, 2009
Cambridge University, UK
36
9th Global Conference on Business & Economics
ISBN : 978-0-9742114-2-7
Table 5: Separations, quits, and layoffs by gender - probit analysis – marginal effects shown
(1)
(2)
(3)
(4)
(5)
(6)
Job
Job
Layoffs Layoffs
Quits
Quits
Separation Separation - Male - Female - Male - Female
- Male
- Female
PRP
-0.006
-0.012
-0.001 -0.006
-0.004 -0.004
(1.46)
(1.88)*
(0.41) (1.19)
(1.79)* (1.20)
Piece Rates
0.000
-0.001
-0.012 0.003
0.012
-0.000
(0.04)
(0.07)
(1.67)* (0.19)
(1.87)* (0.06)
Commissions -0.003
0.003
-0.004 0.003
0.002
0.001
(0.34)
(0.18)
(0.64) (0.23)
(0.45) (0.13)
Tips
-0.018
-0.014
-0.011 -0.008
-0.003 -0.004
(1.68)*
(1.01)
(1.45) (0.69)
(0.55) (0.60)
Bonuses
-0.007
0.010
-0.000 0.014
-0.006 -0.004
(1.08)
(0.80)
(0.09) (1.45)
(1.77)* (0.78)
Stock options -0.021
-0.036
-0.009 -0.021
-0.012
(1.39)
(1.37)
(0.99) (0.94)
(0.95)
Other
-0.006
0.014
0.008
0.020
-0.010 -0.003
PRP
(0.51)
(0.64)
(0.89) (1.07)
(1.77)* (0.34)
Profit sharing -0.003
-0.017
-0.000 -0.014
-0.002 -0.001
(0.57)
(2.23)**
(0.07) (2.30)** (0.61) (0.31)
Multiple PRP 0.006
-0.008
0.006
-0.008
-0.003 0.000
(0.55)
(0.52)
(0.73) (0.65)
(0.59) (0.06)
Obs
8,521
8,593
8,521
8,593
8,521
8,593
All coefficients report dF/dx for discrete change of dummy variable from 0 to 1
z and P>|z| correspond to the test of the underlying coefficient being 0
Absolute value of z statistics in parentheses
* significant at 10%; ** significant at 5%; *** significant at 1%
October 16-17, 2009
Cambridge University, UK
37
9th Global Conference on Business & Economics
ISBN : 978-0-9742114-2-7
Table 6: Fixed effects probit analysis of job separations, quits, and terminations
PRP
Piece Rates
(1)
Job
Separation
(2)
Job
Separation
by PRP
Type
(3)
Quits
(4)
Quits by
PRP Type
(5)
Layoffs
(6)
Layoffs by
PRP Type
-0.068
(-2.71)***
-
-
-0.109
(1.27)
-
-
-0.301
(2.61)***
-
-
Commissions
-
Tips
-
Bonuses
-
Stock Options
-
Other PRP
-
Profit Sharing
-
Multiple
PRP
-
-0.031
(0.15)
0.107
(0.58)
-0.311
(1.66)*
-0.099
(0.80)
-0.586
(1.83)*
-0.067
(0.33)
-0.283
(2.98)***
0.098
(0.56)
-
-0.351
(1.23)
0.430
(1.79)*
-0.357
(1.69)*
0.004
(0.03)
-0.465
(1.27)
0.210
(0.89)
-0.270
(2.32)**
0.144
(0.69)
Number of
1,484
1,484
1,080
1,080
individuals
Log
-1914.10
-1912.25
-1333.53 -1328.41
Likelihood
Absolute value of z statistics in parentheses
* significant at 10%; ** significant at 5%; *** significant at 1%
Each estimation includes the full set of controls as indicated in Table 2.
October 16-17, 2009
Cambridge University, UK
38
-
0.522
(1.93)*
-0.395
(1.42)
-0.203
(0.61)
-0.404
(1.79)*
-1.033
(1.35)
-0.818
(2.01)**
-0.163
(1.05)
-0.082
(0.28)
574
574
-783.24
-775.31
9th Global Conference on Business & Economics
ISBN : 978-0-9742114-2-7
Table 7: Determinants of job separations, quits and terminations by occupation - fixed effects
probit analysis
PRP by
Occupations
(1)
Job
Separation
by
Occupation
Number of
individuals
(2)
Quits
by
Occupation
(3)
Layoffs by
Occupation
Number of
individuals
Number of
individuals
Piece Rates among
Craft and
Operative
Occupations
0.545
(1.48)
305
0.013
(0.02)
178
0.424
(0.83)
158
Commissions
among Sales
Occupations
-0.134
(0.00)
37
-0.967
(0.00)
27
-24.46
(0.00)
10
Tips among
Service
Occupations
0.016
(0.04)
204
-0.097
(0.15)
159
-10.124
(0.00)
65
Bonuses among
Professional and
Managerial
Occupations
0.094
(0.33)
322
-0.063
(0.18)
228
-1.056
(1.20)
110
Stock Options
among
Professional and
Managerial
Occupations
-0.540
(1.63)
322
-1.003
(1.30)
228
-7.244
(0.00)
110
Profit Sharing
among
Professional and
Managerial
Occupations
-0.521
(1.92)*
322
-0.865
(2.40)**
228
-0.237
(0.39)
110
Multiple
0.003
322
-0.111
228
-1.507
110
PRP among
(0.01)
(0.22)
(1.80)*
Professional and
Managerial
Occupations
Absolute value of z statistics in parentheses
* significant at 10%; ** significant at 5%; *** significant at 1%
Notes:
Each estimation includes the full set of controls as indicated in Table 2. Several categorical variables are
dropped from these estimations because of a lack of variation within individual.
October 16-17, 2009
Cambridge University, UK
39
9th Global Conference on Business & Economics
ISBN : 978-0-9742114-2-7
ENDNOTES
Light and McGarry (1998) has noted the difficulty in distinguishing voluntary and involuntary
job separations in the NLSY. Specifically, they observe that a majority report voluntary
separations and a significant proportion (25%) reporting separations for “other” reasons.
However, they do note that replacing their measures of total separations with voluntary
separations other than discharges or layoffs does not qualitatively change their inferences
concerning the influence job mobility has on wage paths. Although potentially arbitrary, I code
those who report separations for reasons of layoffs, plant closings, end of temp or seasonal jobs,
firings, or program endings as involuntary separations (Termination) while those who report
separations as quits, regardless of reasoning, as voluntary separations (Quit).
1
Experience in the NLSY can be measured in several ways including a Mincer function. Within
the NLSY literature, multiple empirical definitions exist. Including alternative measures of
experience, such as a Mincer type function, do not change any substantive results in the analysis.
2
3
Logit estimations reveal a similar pattern as that shown using probit analysis and are available
from the author upon request.
The standard errors reported in table 2 are not corrected for correlated errors within each
cluster. Employing corrected standard errors by clustering in individuals slightly reduces
coefficients and levels of significance, but does not alter the observed pattern.
4
5
Alternative specifications were attempted as a sensitivity analysis and are available from the
author upon request. Limiting objective PRP to piece rates and commissions and subjective PRP
to bonuses reveals no significant differences between objective PRP and subjective PRP in
overall job separations and quits, but lower rates of layoffs among those receiving bonuses.
6
Results of estimations including three digit occupational and industrial controls are available
from the author upon request.
7
Interaction effects on separations, quits and layoffs revealed significant differences in
separations, quits and layoffs for an overall indicator of PRP. Also, there are significant
differences in quits among piece rates workers and significant differences in job separations and
quits among both tip and profit sharing workers. These estimations are available from the author
upon request.
8
See LIMDEP manual Version 9 (2007) Panel Data Models for Binary
Choice, p. E20-1 – E20-17.
9
For theoretical explanations and further background concerning the influence of profit sharing
on productivity and employment stability, readers can reference Kruse (1993).
October 16-17, 2009
Cambridge University, UK
40