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OCR for page 69
Wage-Adjustment
Approaches to
Overcoming Discrimination
INTRODUCTI ON
We have presented evidence indicating that men and women tend to
be employed at different jobs and that jobs held mainly by women tend
to pay less than jobs held mainly by men, even when account is taken
of differences in the complexity and difficulty of jobs and the qualifi-
cations and experience of incumbents. Insofar as such pay differences
result from the concentration of men and women in different fines, the
issue is not one of pa' equity but one of equality of access to firms.
When women are concentrated disproportionately in the low-paying
jobs within a firm, however, the question anses: can differences In the
average pay of men and women be accounted for entirely by differences
in their access to or preference for high-paying and low-pay~ng jobs, or
are the pay rates influenced by the sex composition of jobs? In the latter
case the remedy would be to adjust the pay rates of jobs so as to remo`,e
what would be considered the discriminatory component. Such a pro-
cedure requires, however, the development of a means for identifying
whether and what portion of pay differences in jobs within a finn are
.. . .
alscnm~natory.
One approach to unraveling the components of pay differentials is to
measure the worth of jobs directly, using any of a number of job eval-
uation procedures. The concept of comparable worth is that jobs of
equal worth should be paid equally. The demand and supply of particular
skills and similar factors are regarded as legitimate bases of pay differ
69
OCR for page 70
70
WOMEN, WORK, AND WAGES
ences among jobs only insofar as such factors are explicitly included in
the formulas for specifying job worth.' In this approach, instances of
possible discrimination in pay are identified by using the job worth
hierarchy resulting from application of the job evaluation plan as a
standard against which to assess actual pay rates.
Acceptance of a comparable worth approach-the attempt to measure
the worth of jobs directly on the basis of their content~oes not require
an absolute standard by which the value or worth of all jobs can be
measured. In the judgment of the committee, no such standard exists
nor, in our society, is likely to exist. The relative worth of jobs reflects
value judgments as to what features of jobs ought to be compensated,
and such judgments typically vary from industry to industry' even from
firm to firm. Paying jobs according to their worth requires only that
whatever characteristics of jobs are regarded as worthy of compensation
by an employer should be equally so regarded irrespective of the sex,
race, or ethnicity of job incumbents.
The use of job evaluation procedures without modification may not
always be appropriate, however, because some job evaluation plans are
designed in such a way that they reproduce whatever biases exist in the
pay practices current when the plans were introduced. Moreover, not
all employers who use job evaluation plans base pay rates solely on the
job worth hierarchy implied by the job evaluation plan in use; in such
cases inferences regarding possible discrimination must rest not on spe-
c'fic instances of underpayment of jobs relative to their "worth" but on
a pattern of underpayment for jobs held mainly by women or minorities.
To cope with these complications, we explore two modifications to the
conventional job evaluation approach: a multiple regression approach
that includes "percent female" among the variables used to predict pay
rates, and the use of pay rates of white men in jobs held mainly by white
men as a standard of equitable pay. These approaches have potential
value in developing bias-free job evaluation plans and in identifying
instances of discrimination in pay.
In this chapter we first review the conventional job evaluation ap-
proach and the two modifications, commenting on their strengths and
weaknesses. We then demonstrate the use of these procedures to correct
discnminatory pay rates. Throughout we suggest a number of areas in
which additional research is necessary before definitive conclusions can
be reached or unqualified recommendations offered regarding the de-
sirability of adopting any of the procedures renewed.
~ For example, Ocular Wills may to in And because of the se~css of a tcch-
Dology; if so, a job factor indicating the accused of ~DoIOgy for each job could be
"deaf lo the job c~luadon pled used ('cc Remit, 1978~.
OCR for page 71
Wage-Adjustment Approaches to Overcoming Discrimination 71
CONVENTIONAL JOB EVALUATION APPROACHES
TO ASSESSING PAY RATES
METHODS OF JOB EVALUATION
At the present time in the United States many large private oompa-
nies, the federal government, and many state governments make use
of some form of formal job evaluation as an aid to establishing pay rates
for jobs. Although job evaluation systems differ in details of design and
implementation, almost all conform to a common methodology and
underlying logic: all the jobs in the unit being analyzed (firms, division,
or other)2 are described; the descnptions are then rated or evaluated
according to one or more "compensable factors" (features defined as
legitimate bases for pay differentials); the ratings are added in some
way to create a total score, sometimes called a job worth score; and the
scores are use~sometimes alone and sometimes with other informa-
tio~to assign the jobs to pay classes.3
Particularly in large firms with large internal labor markets, it is not
always evident how to set pay rates for different jobs. Even when a firm
is committed tO paying the going rate in the local labor market for each
job, such information is not always available, and, as we note in Chapter
3, many jobs are filled entirely from within a firm, so that there is no
going rate to apply. Moreover, a large firm may be the only or the
largest employer in town and hence be in the position of defining the
going rate for man, jobs. In these contexts, job evaluation systems prove
useful as a was of setting pay rates.
One type of job evaluation plan, known generically as the point
method or factor point method, is used in many organizations and is
therefore used to illustrate this discussion. In this type of job evaluation
plan a set of compensable factors is chosen. For each factor a scale is
devised representing increasing levels of "worth," and each octet is
assigned a given number of points. Each job is rated on each factor
separately, then assigned the corresponding number of points for the
rated level on each factor. The points are totaled to yield the job worth
score.
2 "Other" may be an entire industry; a job c~alustion plan for production jobs in the
tool industry is such an example. While for con~cnicocc our delusion usually refers to
"firms," it should be understood as applicable to all compensation Items, however they
may be organized.
3 TIC properties of cresting job evaluation plans arc described ~ more detail us the
oo~ttcc's intenm report to the Equal Employment Oddity ~ on (Tin,
1979~.
OCR for page 72
72
WOMEN. WORK. AND WAGES
Many of the factor point job evaluation systems in use today were
developed by using a firm's existing pay structure to statistically deter-
mine which attributes of jobs best predict their pay rates. In this ap-
proach a set of factors that is thought likely to be related to existing pay
differences among jobs is identifie~factors representing differences
in skill, effort, responsibility. and working conditions. Each job is scored
on each of the factors. These factors are then used to predict existing
pay rates (usually via the statistical technique of multiple regression
analysis), and those factors contributing substantially to the prediction
are included in the job evaluation plan q with weights proportional to
their contribution. The factors and factor weights can then be used to
assign pay rates for new jobs and to adjust the pay rates of existing jobs
that are overpaid or underpaid relative to the predictions of the formula.
This method provides an empirically derived underlying structure with
which the pay rates of all jobs in a firm can be brought into conformity.
This is sometimes called a "policy-captur~ngq' approac~the implicit
policy underlying the existing pay system is made explicit. Job evaluation
plans developed in this way necessarily produce hierarchies of job worth
that are closely related to existing pay hierarchies: that is what they are
designed to do.
Another way to develop a factor point job evaluation system is to
define a priori a set of factors and factor weights that expresses what
the employer believes are legitimate bases of pay differentials.4 In both
methods of developing factor point systems job worth is defined by the
factors that measure it, and jobs are assumed to deserve equal pay if
they have equal total scores on the job worth scale.
In both of these methods, completely different kinds of jobs may have
equal total job worth scores and hence be regarded as deserving equal
pay. In a set of jobs with equal total scores' one job. for example, may
entail great responsibility, while another job may require great skill.
The major purpose of job evaluation systems, however designed, is to
make the content of different kinds of jobs commensurable for the
purpose of determining pay rates. While this is difficult to do, and we
discuss a number of the difficulties below, we do not believe it is im-
possible in principle. In our discussion of job evaluation we accept the
criteria of worth implicit in each pla~"worth~' being determined by
those features of jobs that are identified and measure~and focus on
"'Employer" as used here refers to Shocker sets policy for a firm, regardless of how
policy decisions are made. Decisions regarding c01npcasation and job evaluation plans
may wee be the outgrowth of umon-management negotiations or the work of committees
that include members drawn from all k~rcis within a firm.
OCR for page 73
Wage-Adjustment Approaches to Overcoming Discrimination 73
ways to improve the measurement of jobs according to these cnter~a.
Although we considered the potential use of other criten~for example,
productivity-we felt it would be most useful to concentrate on the
enters that are currently used.5
Because formal job evaluation plans purport to measure the worth
of jobs in the precise sense of measuring the factors that are regarded
by employers as legitimate bases of pay differentials among job~it has
been suggested that such plans can be used to arrive at objectively fair
pay rates for jobs and thus to resolve charges of pay discrimination
based on sex, race, or ethnicity. Specifically, actual pay rates could be
compared with the pay rates that would prevail if jobs were paid ac-
cording to their job worth scores, and the difference taken as a measure
of possible discrimination. Furthermore, if the difference between actual
and predicted pay rates were shown to be correlated tenth the sex, race,
or ethnic composition of occupational categories, then a strong suspicion
would be created that pay practices are discriminatory, and appropriate
action could be taken. That is. if the jobs with actual wage rates lower
than indicated by the job worth scores tended to be held dispropor-
tionately by women or minorities. and if the jobs with actual wage rates
higher than indicated by the job worth scores tended to be held by men
or by nonminor~ties then the existence of discriminatory pay practices
would be implied.
In the judgment of the committee, four aspects of formal job eval-
uation procedures are important in assessing their practical application
in developing pay plans and in resolving complaints of pay discnmina
.. . . . . . . ~ . . . . . . .
tlon, particularly In a labor force Highly segregated by sex, race, and
cthnicity. (The first three of these features are reviewed in greater detail
in the committee's interim report; see Treiman, 1979.) First, the ranking
' jibe committee also concluded that with rare conceptions the difficulties of mcasu~g
productivity arc very great. To be useful in job evaluation the relative average productivity
(the contribution to output) of each job would have to be measured. For example, to
assess the productivity of hospital workers the relative oontabution of DUrSCS, motors,
orderlies, xactancs, and maintenance workers to hospital output would bevc to be
detennined. At the present time, however, there is no agreement on bow to m~surc
hospital output, and little attempt has been made to assist the relative contnbutions of
canons hospital workers (Scott, 1979~. While an employer may mat to Jude produc-
d~qty measures in job evaluation plans when they become available, the factors Erectly
identified in job evaluation plans remeet employers' conceptions of what Would be rc-
muncrated. For example, some plans Nymphs slcill more this rcspon~bility; some do
the opposite. Presumably these diffcrcaces reflect, at least in part, employers' judgments
about what cohanecs the perfoln.ance of their firms. Further research on the mcasuremcst
of the productivity of jobs and research OR the ~'poradon of productivity measure
job evaluation plans arc advisable.
OCR for page 74
74
WOMEN. WORK. AND WAGES
of jobs tends to be highly dependent on which factors are used in the
evaluation and how heavily each factor is weighted. And as we have
already noted, the principal method for deriving factor weights in most
currently used job evaluation plans pegs them to current pay rates,
therby reflecting existing pay differences between men and women (and
between minority and nonminority) workers. Second like other meth-
ods of establishing pay rates, job evaluation involves judgments, making
it possible for well-known processes of stereotyping to result in an un-
dervaluation of jobs held mainly by women. Third, many employers use
more than one job evaluation plan in their fimns (e.g., one for shop jobs
and one for office jobs), a policy that makes it difficult to compare the
worth of jobs or to determine the likelihood of discrimination in pav-
among different sectors of a firm. Fourth' the interpretation of the
differences between actual and predicted pay rates as evidence of dis-
cnmination requires strong assumptions regarding the adequacy of the
prediction model and the measurement of the variables included in the
modeWassumptions that may be difficult to satisfy in practice. Each of
these features is discussed below.
FACTORS AND FACTOR WEIGHTS
Although in principle a very large set of compensable factors could
be developed, in practice most job evaluation systems use a similar small
set of factors. This is due in part to the propensity of designers of job
evaluation systems to borrow factors from previously developed systems
with only minor modifications. In addition. the choice of factors no
doubt reflects the industrial origin of job evaluation plans. Their use
was initially In factories, and the job characteristics chosen for evaluation
tended to emphasize shop knowledge, responsibility for equipment,
strength requirements, work hazards, and so on. Job evaluation plans
have subsequently been designed specifically for the evaluation of office
jobs as well as executive jobs. It is probably true, however' that the job
evaluation systems currently available do not correspond very closely
to the character of the contemporary labor force, which is increasingly
concentrated in technical and service jobs that did not exist when most
plans were developed (for example, jobs involving automated infor-
mation processing, such as computer operator, data entry clerk, airline
reservations agent, etc.~. It is not clear how important this issue is, but
a question must be raised as to how well these new jobs are dealt with
by systems designed to evaluate quite different sorts of jobs. Since such
technical and service jobs are often held by women, any inadequacy in
OCR for page 75
Wage-Adjustment Approaches to Overcoming Discrimination 75
the ability of existing job evaluation plans to measure properly their
compensable features may undercut the usefulness of these plans in
resolving pay discrimination disputes. In our judgment, consideration
should be given to redesigning job evaluation systems currently in use
to take account of changes in the content of jobs in the American
economy in the 40 years since most of them were initially developed.
Despite the fact that most job evaluation plans appear to tap the same
basic features of jobs skill, effort, responsibility, and working condi-
tions the particular operational indicators of the factors may vary more
widely, a possibility with important consequences. For example, "skill"
Is sometimes measured operationally by the amount of experience re-
quired to become fully trained in a job and sometimes by the amount
of formal education required to qualify for a job. Clerical jobs, for
example, tend tO entail considerable formal education but little actual
on~the-job training, while the reverse tends to be true of crah jobs. The
choice of which operational indicator of skill is used in a job evaluation
system could have substantial impact on the job worth scores of these
two categories of jobs. Furthermore' since clerical jobs tend to be held
mainly by women and craft jobs to be held mainly by men, the choice
of indicators could effectively determine the outcome of any analysis of
whether pay differences between these job categories involve discrim-
ination on the basis of sex. Proper use of job evaluation techniques to
resolve disputes involving pay discnmination depends on clear under-
standing of precisely what factors are used in the evaluation formula.
We relative weight accorded the different compensable factors used
in a job evaluation plan can have substantial impact on the resulting
hierarchy of job worth. That is, different weightings of factors can sub-
stantially alter the ordering of jobs. If the content of the jobs held by
men and women or by minorities and nonminonties differs substantially,
then different weightings of the factors can result in different outcomes
as to the average worth of jobs held by men and women or by minorities
and nonminonties, and hence in different judgments regarding the pres-
ence or extent of pay discrimination on the basis of sex or minority
status. (For a more detailed discussion of this point see Truman,
1979:5~54 )
We noted above that a frequently used method of determining the
relative weight to be accorded each factor in developing a job evaluation
plan is to predict existing market wage rates from a set of potential job
evaluation factors. This method, although it has advantages, has two
major drawbacks.
One of these drawbacks is technical. The resulting weights may vary
OCR for page 76
76
WoMEN, WORK, AND WAGES
substantially, depending on the set of jobs chosen for the prediction and
the data base used in determining the average wages of those jobs.6 In
the typical application a subset of all jobs in a firm is used to determine
factor weights: these are often called "key" or "benchmark" jobs. If,
for example, only the highest-paid blue-collar jobs and the lowest-paid
white-collar jobs in a firm are used as benchmark jobs and blue-collar
and white-colIar jobs typically have different characteristics, then the
weights for the white-collar job characteristics derived by this procedure
would be unusually low and those for the blue-collar job characteristics
unusually high, compared with their actual compensation in the firm.
Hence the choice of benchmark jobs can affect the weights derived.
Second, even if the benchmark jobs are themselves representative of
all jobs in a firm, a wide range of wage rates typically exists for each
job, and the choice of wage used to represent the job (minimum, mid-
point, mean, etc.) can affect the weights resulting from the procedure.
These technical difficulties mean that the derived weights may not ad-
equately reflect compensation. This aspect of the implementation of job
evaluation-procedures is an extremely important one, and care must be
taken that even a well-designed system is not poorly implemented at
this stage.
The second major drawback of using existing wages to derive factor
weights is that the weights wall then necessarily resect in turn any biases
that exist in market wages. To the extent that existing wages incorporate
the effects of discnnunatory practices (and we argue in Chapter 3 that
those effects can be substantial in some cases), the weights derived from
those wages as well as the resulting job worth scores also incorporate
those effects. It is hardly optimal to use job evaluation scores as a
standard against which to assess the legitimacy of existing pay differences
among jobs if the job evaluation scores themselves are designed to
replicate as closely as possible existing pay differences.
On the other hand, using existing wages to derive factor weights has
the advantage, from the point of view of the employer and many em
' In a typical prediction operose, a set of jobs has a~rcrage ~gc rates Y and preliminary,
arbitranly specified scores on job worth factors J' (i = 1, . . ., n). An equation of the
following type is estimated,
~ ~ a + ~ b' JJ 9
d-1
where Y represents the estimated wage rates of the jobs, "d b, represent the estimated
weights for the factors J.. l~c constant term, a, Ed the weights, b', arc derived, Mug
multiple regression technigocs, such that the "ready," Y - ),, arc as small as possible
(~ifi~y, ply _ ~2 ~ minimized for the ~Ic). Tbc weights c" theD be used to
rescalc Tic furors for use m denying pb worth scores.
OCR for page 77
Wage-Adjustment Approaches to Overcoming Discrimination 77
ployees, of by and large preserving customary wage relationships among
jobs and of formalizing an evaluation of the relative worth of different
attributes of jobs that already exists implicitly. The rationalization of
a system already largely in place is likely to be far less disruptive than
imposition of a substantially different hierarchy and criteria of job worth.
Moreover. when as is sometimes done area wage rates rather than
a fimn s own wage rates are used. employers can be reasonably certain
that their internal pas structure is consonant with external market re-
wards and that their pay scale will enable them to recruit and retain the
necessary workers.
THE ROLE OF JUDGMENT
It is important to recognize that job evaluation ultimately rests on
judgments. Jobs are described in terms of their tasks, duties, and re-
sponsibilities. and these descriptions are rated or ranked with respect
to some set of factors. The factor ratings are seldom based on objective
information; rather. they represent judgments about such amorphous
features of jobs as the responsibility entailed or the experience required.
The nature of job evaluation makes it possible for bias to enter at two
points: in the writing of the job descriptions and in the evaluation of
the descriptions with respect to a set of factors.
One can question to what extent traditional stereotypes regarding the
complexity and responsibility of different types of work are reflected in
job descriptions. Unfortunately. there is no evidence on this issue: to
our knowledge there have been no studies of the accuracy or validity
of job descriptions. Such studies would be extremely useful. Moreover,
methods of systematic job analysis, such as structured job analysis and
task analysis, ought to be explored for their applicability to job evalu-
atio~in particular the job component method of job evaluation
(McCormick and llgen 1980:Ch. 18~. which uses structured job analysis.
One can also question to what extent sex stereotypes may affect the
evaluation process. That is' are jobs held by women evaluated differently
from jobs held by men, even when their content is virtually identical?
The e~dence in answer to this question is very sparse. Almost no evi-
dence is available that pertains directly to sex stereotyping in the c~al-
uation of jobs; there is, however, very strong e~dence that female
workers are evaluated as less worthy than male workers with identical
charactenstics. This evidence denves from a genre of studies in e%per-
~mcntal social psychology in which subjects are presented with a set of
vignettes describing the performance or qualifications of individuals and
asked to rate them on one or several dimensions. Various aspects of
OCR for page 78
78
WOMEN' WORK, AND WAGES
the vignettes are systematically vaned, and the effect of the variation
on the ratings is studied. For our purposes, the vanable of interest is
the sex of the individual described in the vignette.
These studies are reviewed in detail in our interim report (Treiman,
1979:43~5~. Here we report our conclusion (p. 4S):
In a variety of contexts the mere fact of identifying a performance as done by
a woman results In a lower evaluation and a lower likelihood of reward hinng,
promotion, etc. than when the identical performance is attributed to a man.
The only exception is when the performer is certified as competent on ~nde-
pendent grounds; in such cases there is no significant tendency to evaluate
women more poorly than men.
While most of the studies ated . . . refer to the evaluation of people rather
than jobs, the evidence for sex stcreo~ping ire jo~related contexts is certainly
strong enough to suggest the likelihood that sex stereotyping will pervade the
evaluation of jobs strongly identified with one se% or the other. That is, it is
likely that predominantly female jobs will be undervalued relative to predom-
inantly male jobs in the same way that women arc undervalued relative to men.
Given the paucity of the essence, much additional work needs to be
done to cianfy to what extent and under what circumstances sex ster-
cotyping is likely to be operating in the evaluation of jobs. For example,
experimental studies of the same type as those cited above, in which
job descriptions rather than job incumbents are evaluated, would be
very useful. If the same description received a higher rating when iden-
tified with a "male" title than with a "female" title (e.g., waiter versus
waitress, orderly versus nurse's aide), the process of sex stereotyping
the job evaluation process could be inferred. Moreover, ways should
be explored to niinim~ze the impact of stereotyped perceptions of jobs.
One possibility would be to carry out job evaluations on the basis of
job descriptions only, omitting job titles from the description.
MULTIPLE JOB EVALUATION PLANS IN A SINGLE FIRM
Another source of difficulty in using job evaluation plans to assess
complaints of pay discrimination is the tendency of firms to use different
job evaluation plans for diffcrcut categories of workers. When more
than one plan is used to evaluate the jobs in a firm, there is no way of
directly comparing all jobs ~ that firm (unless a formula exists for
translating the scores from one plan into the scores of the others, which
Is rarely the case). Since the job categories Covered by different plans
(typically shop, office, and czecutive jobs) tend to be highly segregated
by sex, race, and ethnicity (i.e., women arc overrepresented in office
OCR for page 79
Wage-Adjustment Approaches to Overcoming Discrimination 79
jobs and underrepresented in both shop and executive jobs; minorities
are underrepresented in executive jobs), the use of job evaluation ratings
to assess the existence of pay discrimination would appear to require
the ability to make comparisons among as well as within the different
plans.
The development of different job evaluation plans for different types
of jobs appears to have two explanations: first, plans were onginally
developed for blue-collar jobs and only later for white-collar office and
professional and executive jobs; second, different types of jobs are
widely believed tO have vent different job characteristics. For example,
manual dexterity, a factor thought to be unponant for most blue collar
jobs and some office jobs, is nonnally not thought to be important for
professional and executive jobs. However, it is quite possible that, as
the economy has changed, so has the nature of jobs. As both clerical
and factory jobs are becoming more automated, they perhaps are coming
to require skills that are more similar than they were previously. It has
been suggested that job evaluation plans for technical jobs, which cur-
rently form a kind of bridge between plans for shop jobs and office jobs,
could be used to evaluate all jobs. Moreover, some large fines and some
state governments do in fact use a single plan for all workers, and the
U.S. Department of Labor, in its Dictionary of Occupational Titles,
descnbes all occupations in the economy using one set of factors.
Me committee is divided on the question of whether the jobs usually
found within a single firm can be adequately evaluated by a single job
evaluation plan or whether several plans would be required to measure
job characteristics adequately. Two issues are involved. First, should a
given score on a given factor be worth the same amount for all jobs in
a firm? Many on the committee would say ye~that is the meaning of
comparable worth. If, for example, degree of responsibility differen-
tiates supervisory from line jobs on the plant floor, it should do so in
the office as well. Quite possibly, of course, an entire group of jobs
could have the same rating on a particular factor. For example, a factor
for undesirable working conditions might be scaled in such a way that
all office jobs but only some plant jobs are scored in the lowest category,
so in effect the factor would be relevant only in differentiating among
plant jobs; this would not vitiate the applicability of a single job eval-
uation plan to an entire finn. The second, more difficult problem is
whether indicators can be devised to measure accurately a given factor
for all jobs in a firm. Is it possible, for example, to specify the meanung
of responsibility in such a way as to differentiate between managerial
jobs of greater and lesser responsibility and also to differentiate between
OCR for page 80
80
WOMEN, WORK, AND WAGES
shop jobs of greater and lesser responsibility? Lee answer to this ques-
tion is uncertain. Not enough is yet known about the measurement of
job characteristics to be able to assess the validity of job evaluation
plans for different categories of jobs. More research on the nature of
job characteristics and on the properties of job evaluation plans used
throughout a firm is needed before the usefulness of such plans can be
established.
MODELING AND MEASUREMENT
Two bases for specifying factors and factor weights in job evaluation
formulas are reviewed above: (1) an a priori approach, in which the
choice of compensable factors and their relative weights are decided as
a matter of policy, without regard for existing pay practices, and (2) a
policy-captunng approach, in which existing pay rates are predicted
from a set of compensable factors Ma multiple regression procedures
and weights are denved from the regression model. In the latter case,
the adequacy of the predicted scores as the basis for assigning jobs to
pay grades or for assessing whether jobs are "underpaid" or "overpaid"
depends on the adequacy of the statistical mode! used to predict existing
pay rates. There are a number of potential difficulties involved in regres-
sion procedures of this kind. First, if variables that in fact affect pay
rates are omitted from the model, two distortions result: the predictions
wall be less accurate than otherwise and may be biased, and the relative
weights of the vanables included in the mode] will be distorted. Second,
if variables in the mode] are measured imperfectly, they wall appear to
have less importance than they truly have. Third, if the functional form
of the mode] is not correct, the predictions wall be less accurate as well
as distorted. There are now wel]-developed procedures for estimating
regression models with nonlineanties and interactions of venous kinds
and for testing the relative adequacy of alternative functional fonns, but
these do not seem to have been widely used in fob evaluation systems.
Techniques used in job evaluation have not kept pace with devel-
opments in econometncs, psychometncs, and sociological measurement.
Serious attention should be given to the selection and measurement of
compensable factors, the functional form of regression models, and
assumptions about error structures, each of which can seriously affect
the factor weights and the pay rates predicted by these models. Regres-
sion-based models of the type discussed here require considerable sen-
siti~rity and ingenuity on the part of the analyst; mechanical applications
of the technique can easily produce seriously misleading results.
OCR for page 81
Wage-Adjustmen' Approaches to Overcoming Discrimination B]
SUMMARY
A number of features of existing job evaluation systems make them
less than optimal for use in the resolution of pay discrimination disputes.
First, formal job evaluation systems order jobs by reference to a set of
compensable factor~that is, factors thought to be legitimate bases of
pay differentials. As we have shown, the factors and their relative
weights are ohen chosen in such a way as to closely replicate costing
wage hierarchies. For that reason, they can hardly serve as an mde-
pcndent standard against which to assess the possibility of bias in c~ust~g
pay rates. Second, it is possible that the process of describing and eval-
usting jobs reflects pervasive cultural stereotypes regarding the relative
worth of work traditionally done by men and work traditionaDy done
by women. These features of job evaluation systems make it probable
that their use as a standard of job worth understates the extent of
differences in pay based on sex and perhaps on race or ethnicity. Third,
most firms currently use more than one job evaluation plan, a pumice
that restricts comparisons between jobs to those wit n sectors of a
fi~n~e.g., shop jobs, office jobs, or executive jobs. Finally, there are
potentially serious technical shortcomings in the way regression pro-
cedures are used to create job evaluation formulas.
Nonetheless, it would be unwise to reject the use of job evaluation
plans altogether. Despite their limitations, they do pronde a systematic
method of comparing jobs to determine whether they arc fairly com-
pensated. Because job evaluation plans as ardently implemented are
likely to understate the extent of differences In pay based on the sex,
race, or ethnic composition of occupational categories, estimates of
discrimination derived from the application of current job evaluation
plans are probably low. Still, using job evaluation scores to determine
pay rates wall generally go some way toward reducing discriminatory
differences in pay when they exist.
It may be possible to improve fob evaluation glans. The oommiKee
urges fob evaluation practitioners and users to scrutinize exists plans
for fairness in light of the considerations reviewed here and in its Interim
report (Treiman, 1979~. In addition, we urge further research into the
many unresolved technical issues regarding job cvaluabon pnoc~ples
and practices. The techniques used in job evaluation plans have been
for the most part designed and Implemented by practitioners hobo have
not been well grounded in advances in measurement in the social sci-
ences. These procedures have not to date been subject to the kind of
rigorous analytic scrutiny necessary to put them on a technicaDy sound
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82
WOMEN. WORK, AND WAGES
footing. Considering their potential usefulness in resolving wage dis-
crimination disputes and the growing interest in that use, further re-
search on techniques of job evaluation would be very valuable.
STATISTICAL APPROACHES TO ASSESSING PAY
RATES
The comparable worth approach attempts to use job evaluation pro-
cedures to determine "fair" rates of pay for jobs, but as we note above,
that approach involves the difficulties inherent in using the job evalu-
ation plans that are currently available. One of the main difficulties is
that the factor weights used in job evaluation systems frequently are
denved from a regression procedure designed to make job worth scores
replicate existing wage hierarchies as closely as possible. When this is
the case, the job worth scores themselves may reflect any existing bias.
The committee therefore explored two modifications of the statistical
approach conventionally used in developing job evaluation plans. Tl2ese
procedues may be used both to modify existing job evaluation plans to
reduce bias and to develop new bias-free job evaluation plans. They
may also procure helpful in identifying specific instances of pay discnm-
ination. The first is a multiple regression approach that, although anal-
ogous to the standard job evaluation procedure of using existing wages
to derive factor weights, includes "percent female" among the predictor
~ranables. The second is the use of wage rates of jobs held mainly by
white men as a standard of "fair" wages. These are not, of course, the
only statistical approaches available; indeed, we encourage the devel-
opment and testing of alternative statistical approaches.
We wish to make clear at the outset that we discuss these approaches
because of their potential and not because of their proven value. Hey
are at present completely untried, and their application would entail the
solution of many theoretical and practical problems of measurement.
Were is also a serious question as to whether the quality of the data
generated by job evaluation plans In current use Is adequate to sustain
the kinds of statistical adjustments we describe. (The discussion in the
previous section details some of the problems.) Moreover, there is con-
siderable debate regarding the interpretation of the statistics generated
by these adjustments (specifically, regression cocffiacats), especially
given Imperfect measurement (see B~rnbaum, 1979~. In order to en-
courage the kind of practical research and development that should be
earned out in order to create technically sound procedures for identifying
and correcting pay discrimination, we present these approaches as ex-
amples of two that might be considered.
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Wage.Adjustmer't Approaches to Overcoming Discrimination 83
INCLUDING · PERCENT FEMALE'' IN THE ESTIMATION OF PAY
RATE S
As we discuss above, the fact that men tend on the average to be paid
more than women guarantees that any job evaluation factor that is
correlated with the sex composition of jobs will receive some weight,
and those factors that are more strongly correlated with sex composition
w'll on the whole receive greater weight. Thus, the use of job evaluation
plans perpetuates existing pay differences among jobs, which-as we
have argued in Chapter May reflect discriminatory as well as leoi~-
unate components of pay.
~. . . . . ~
_ a
One potential method of removing the bias built into factor weights
denved in the conventional way is to estimate the factor weights from
an expanded equation that includes measures of the sex (or race or
ethnic) composition of occupational categones. As we showed above
(see note 6), the conventional approach to denying factor weights for
job evaluation plans is to estimate a regression equation of the forth
y=a+~:bili (~)
over a set of occupations in a Fin., where Y is the average pay rate of
each occupation, the Ji are potential compensable features of jobs (meas-
ures of skill, effort, responsibility, working conditions, etc.), and the hi
are the estimated weights for the factors hi.' Now consider a modification
of eq. ~ of the form
Y= a' + I:b,']i + cF,
(2
' While these equations arc in linear form, as required by the regression estimating
cdurc, it is possible to represent quite complex relations, including interactions and
nonlincarities of various kinds, by appropriate transformations of the vanables. For e%-
amplc, an exponential equation of the foully
Y= e.~"`x
cut be written in a mathematically equivalent way as a linear additive equation
in(Y) = a + ]:b~Y,.
Similarly, an equation of the form
can be rewritten as
Y = Q + b,X, ~ b2X2 + b3X,X2
Y = a + b,X, ~ b2X2 + b3X3
simply by defining X3 = X,X2. See Goldberger (1968), MostcDcr "d Tubby (l977), and
Stolzenberg (1919) for a discussion of these and similar t~sfo~s.
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84
WOMEN, WORK, AND WAGES
where Y and the li are as before, F is the percentage of incumbents of
each job who are women, the b,' are the estimated weights for the factor
li (in general, these will not be the same as the corresponding coeffi-
cients, hi, estimated by eq. 1), and c is the weight for the percent female.
The coefficients, hi', associated path each of the compensable factors,
Ji, can be interpreted as indicating the contribution of each factor in
determining the average pay rate of workers in these occupations, hold-
~ng constant each other factor, plus percent female. Specifically, each
hi' indicates the number of dollars a one-point change in the factor score
is worth, on the average, for occupations that have identical scores on
the other factors and the same percent female. For example, suppose
the first factor, ],, indicates the number of months of training necessary
to become fully qualified. Estimating the equation yields a value for the
coefficient bit' that indicates how many dollars each month of training
is worth. That is, for 2 jobs equal in all other respects except that one
requires 2 months of training and the other requires 12 months of train-
ing, a difference in their average pay rates of job,' dollars would be
predicted, since they differ by 10 units on the variable I,.
These coefficients differ from the corresponding coefficients in eq. I,
the conventional job evaluation equation, in that they are adjusted for
the propensity of characteristics that distinguish between jobs held
mainly by women and jobs held mainly by men to be heavily weighted
as a consequence of the strong negative association in most firms be-
tween the percent female and the average earnings of jobs; the explicit
inclusion of percent female in the equation is what adjusts the weights.
Given the usual association between sex composition and earnings, job
evaluation scales built by weighting the factors in proportion to the
coefficients b,' from eq. 2 will ordinarily be less sex-biased than scales
built by weighting the factors in proportion to the corresponding coef-
ficients of eq. 1.
Me coefficient c indicates the effect of sex composition on pay rates
for occupations that are identical with respect to all of the other vari-
ables. Specifically, c indicates the difference in pay rates that would be
expected on the average between two occupations that differ by one
percentage point in their sex composition but are identical with respect
to all other measured variables. As such, c can be taken as a direct
measure of potential discrimination. Whenever c is significantly different
from zero, the sex composition of occupations would have to be inter-
preted as a compensable factor-but to pay jobs on the basis of the sex
of their incumbents would be regarded as discnnunatory.
An objection could be raised that variables excluded from consider-
ation in estimating job worth may cubist that arc both vatid indicators
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Wage-Adjustment Approaches to Overcoming Discrinunation 85
of worth and correlated with percent female. Insofar as such vanables
exist, sex composition would stand as a surrogate for differences in job
worth, in which case the coefficient c could not be regarded as a valid
measure of potential discnmination. For example, training in mathe-
matics could be a job-related factor correlated with sex; its exclusion
would cause c to overstate the extent of potential discrimination. In the
judgment of the committee, however, the burden should rest on the
designer of the job evaluation system to identify and explicitly incor-
porate all factors regarded as legitimate components of pay differences
between women and men, not merely to assert the possibility that in-
cluding unspecified and unmeasured factors or improving the measure-
ment of existing factors could reduce the `~disc~imination" ooeffic~ent c.8
One variable in particular that might usefully be added to pay pre-
diction equations is the average experience of job incumbents. It is well
known that men tend to have more occupational experience than
women' and occupational experience is generally regarded as a com-
pensable factor for individual workers. By not including a measure of
the average work experience of incumbents in each occupation, an
equation such as eq. 2 overstates the amount of sex-based discrimination
to the extent that the average work experience of incumbents Is nega-
tively correlated with percent female. Other worker characteristics, such
as educational qualifications, may also be important determinants of
wages. Equation 2 could be expanded to include those characteristics
of workers that are regarded as legitimate bases of pay differentials. An
equation of the form
Y = a + I:bi ~' ~ IcjXj ~ OF,
(~3)
~ Ibc approach outlined here is an example of a class of models that treat discrimination
as a residual factor. He characteristic feature of such models, which have been unduly
applied in economics and sociology, is that they attempt to explain observed diffcrenocs
between groups with respect to some attribute (e.g., income) by predicting that attribute
from a small number of other charactenstics, then relating the residual diffcrcocc between
observed and predicted values to group membership, intcrpretmg group diffcrcaces In the
evcra~c size and sign of the residual as evidence of disnmination.
From a technical point of view, howe~cr, the residuals estimated from such equations
indicate the effect of all factors not explicitly measured pus any error m mcasuremcat;
discrimination per sc may or may not account for a large fraction of the residual ~rananCc.
Interpreting the residual as indicating damnation, then, requires Other the monk
Ed clearly untenable assumption that all relevant factors have been measured, and
measured without error, or a determination that discrimination ~ lively. ~ our jUd - Cut,
the proper interpretation in light of the c~idencc reduced in Chapters 2 and 3 is to treat
the unexplained differences in average pay rates between men "d women "d between
mDontics and nonrrunontics as indicating the probability of disenmizutory protest
unless the contrary can be shown.
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WOMEN, WORK. AND WAGES
where the X, represent average characteristics of incumbents and the
other vanables are as defined above, can be interpreted in ~ manner
identical to eq. 2. The substantive problem of determining which char-
actenstics of workers should be regarded as legitimate bases of pay
differentials corresponds to the problem of determining which aspects
of job content should be regarded as legitimate bases of pay differentials.
Ultimately, both determinations are matters of values. We should point
out that job evaluation plans currently in use do not ordinarily include
worker characteristics because these plans typically attempt to measure
only the required elements of jobs. Experience that incumbents happen
to have that is not required by the job is ordinarily considered irrelevant,
while required experience is usually included as a job element, one of
the lit If job evaluation procedures are to.be used for the resolution of
claims of pay discrimination, however, their usefulness would be en-
hanced by including those worker characteristics regarded as legitimate
compensable factors.
JOBS HELD BY WHITE MEbt AS A STANDARD
We now turn to a different approach, the use of features of jobs held
mainly by white men as a standard for assessing the fairness of the pay
rates of other jobs. The key assumption of this approach is that white
men in jobs held mainly by white men are not subject to discrimination.9
With this assumption, the average pay rates of white men in jobs held
mainly by white men can be used as an indication of the relative worth
of these jobs; for this subset of jobs, then, there is an objective, market-
based criterion of job worth.
In this approach one determines what features of those jobs contribute
to differences in their level of compensation, using the familiar technique
of regressing average pay rates on job characteristics. That is, an equa-
tion analogous to eq. 1,
};,,,,, = a ~ I;biJi,
(4)
can be estimated for the subset of jobs held mainly by white men, where
Y.,,,,, Is the average pay rate for white male incumbents. The coefficients
of such an equation can then be used to assign a job worth score to
' Discnniinatory treatment of women or minorities would have the effect of driving
down the pay of white men in jobs with substantial proportions of women and minontics.
We mow empirically that pay rates of men arc negatively correlated with the percent
female among incumbents of aD occupation (see Chapter 2) and would expect a similar
Cation tenth the proportion in an occupation who are minority workers.
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Wage-Adjustmen~ Approaches to Overcoming Discruninaiion 87
every job in a firm if it can be assumed that whatever factors differ-
entiate the actual earnings of white men in jobs held mainly by white
men also, and in equal proportion, differentiate the actual earnings of
women and minorities and of white men in other jobs within a finn.
The weakness of this approach is that if jobs held mainly by white men
have characteristics substantially different from those held mainly by
m~nonties or women, the coefficients from the earnings equation for
jobs held mainly by white men wall not be good estimates for jobs held
mainly by women or minorities. This is an empirical issue that should
be resolved in each specific case.
The strength of this approach is that it entirely avoids the question
of what ought to be the bases of compensation question we regard
as being a matter of values and admitting of no technical answer and
takes the marketplace as the arbiter of pay rates for that subset of jobs
for which there is no suspicion that discriminatory processes affect the
rates. To use the results of such an analysis as the standard of equitable
compensation, one would apply the estimated coefficients to jobs held
mainly by other workers and estimate the average wage or salary level
that would be expected if such workers are compensated in the same
way as white men in jobs held mainly by white men. The average earn-
ings levels estimated in this way could then be compared tenth the actual
earnings of those workers and the difference taken as a measure of
possible discrimination. If the expected value is greater than the actual
value, one could conclude that those workers are underpaid relative to
the worth of their jobs; if the expected value is smaller than the actual
value, one could conclude that they are overpaid. It would then be
possible to adjust the pay rates of those jobs or workers who are sub-
stantially underpaid (or overpaid).
USING STATISTICAL PROCEDURES TO CORRECT
DISCRIMINATORY PAY RATES
It may be possible to use the sorts of models outlined ~ the previous
Actions to make adjustments in discriminatory pay rates, although me-
chanical application of these approaches without careful consideration
of the measurement issues noted In this chapter would be iB-adv~sed.
Many other procedures for adjusting discriminatory aspects of pay dif-
ferences could be devised; we have selected several as illustrations.
The first procedure is to pay each job according to its worth as de-
termined by the job evaluation plan In use. This ensures that aD jobs
In a firm are compensated on the basis of the same cntena. If a firm
Is willing to use job evaluation ratings as the sole basis for establishing
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88
WOMEN, WORK, AND WAGES
pay rates for jobs-as, for example, most steel manufacturers do for
shop jobs and as the federal government does for white-collar jobs
(Treiman, 1979 - and if the job evaluation system is free of bias, this
procedure may be satisfactory.
A major disadvantage of this procedure, however, which we have
noted several times above, is that, since the factor weights are usually
denved in such a way as to ma~cim~ze the prediction of existing pay rates
and since pay rates may be strongly correlated with the sex composition
of jobs, those factors most strongly correlated with sex composition may
receive the heaviest weights. To the extent that this is the case, any sex
bias in pay rates Will tend to be preserved. To overcome this disadvan-
tage, we suggest two modifications to the procedure.
The first modification is to use factor weights derived for white men
in jobs held mainly by white men as the standard applied to all jobs.
This technique has the advantage of adjusting all pay rates to a level
commensurate with the highest returns currently offered, which is prob-
ably psychologically preferable but has the corresponding disadvantage
of increasing the cost of the total pay package (unless, of course, the
pay rates for all jobs are reduced by some constant). This technique has
another disadvantage: factor weights chosen to differentiate among jobs
held mainly by white men may not differentiate well among other jobs.
The second modification is to adjust the weights to remove sex com-
position as a compensable factor and to use the adjusted weights to
develop a '`bias-free" job evaluation plan. Formally this involves com-
puting an expected income for each occupation by substituting the mean
percent female offer all jobs into eq. 2 (or eq. 3) and evaluating the
equation. That is, for each job, I, a fair pay rate, Y', can be estimated
by
fj = a + I:bi'Jij ~ c(F),
(5)
where l,j is the score on the ~ factor for the jth job, and F is the mean
percent female for aB jobs in a firm. This technique has the advantage of
of adjusting the coefficients b,' to estimate the contribution of each
factor to total earnings among jobs that have the same percent female.
The conventional job evaluation procedure and its modifications are
similar In that they determine earnings entirely on the basis of a weighted
sum of compensable factors. In this sense they arc all versions of a
comparable worth approach. An employer may feel, however, that such
an approach is overly deterministic. After all, a variety of idiosyncratic
factors may legitimately create pay differences among jobs and, it could
be argued, these ought not to be ignored or arbitrarily omitted. Hence,
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Wage-Adjustment Approaches to Overcoming Discrimination 89
we suggest another procedure, which preserves differences in the pay
rates of jobs insofar as the unmeasured idiosyncratic components of pay
differentials are uncorrelated with sex composition.
This second procedure makes use of the coefficient of percent female
in eq. 2 (or eq. 3) as an adjustment factor, adding to the existing pay
rate of each job a constant equal to -c(F') or, to keep the total wage
cost unchanged, - c(Fj - F), where Fj is the percent female in the jth
job, F is the mean percent female for all jobs In a firm, and c Is the
associated net regression coefficient. That is, -c dollars are added to
the pay rate of each job for each additional percent female among the
incumbents. Me result of such a procedure is to reduce the net effect
of sex composition to zero. Of course, since the legitimate compensable
factors will typically be correlated with sex composition, the resulting
zero-order correlation between sex composition and earnings ordmaniy
will not be exactly zero, although it usually will be reduced.
Me basic difference between the first procedure and its modifications
and the second is that the former adjust all pay rates to the policy line
defined by a job evaluation formula, while the latter permits pay rates
to vary around the policy line, with a sole constraint: the Sedations
from the policy line must be uncorrelated with the sex composition of
occupational categories.
With the exception of the use of unadjusted job evaluation scores as
the basis for setting pay rates, these procedures have seldom been im-
plemented, so it Is difficult to anticipate what practical difficulties may
be involved. Hence it would seem prudent to exercise considerable
caution in applying them, attending carefully both to the statistical issues
discussed above and to substantive concern~the possibility that some
workers may perceive new inequities as replacing old ones, that to avoid
such perceptions may require a substantial increase in the wage bill for
an enterprise, and that statistical adjustment procedures often generate
tension between the need to eliminate discrimination for groups in the
aggregate and the need to protect the rights of individuals. Despite these
caveats, we urge the exploration of these and similar procedures as a
means of eliminating discrimination in pay rates for aB workers.
CONCLUSION
Starting from the evidence that erasing occupational pay hierarchies
sometimes embody discnnunatory elements, this chapter proposes and
reviews several approaches to Feting and conechug discrimination in
pay rates. These approaches are of two kinds: one involves improvements
m Me design and impiementai~on of job evaluation pears ourrendy In use
OCR for page 90
go
WOMEN, WORK. AND WAGES
and the other involves statistical adjustments to pay rates to estimate and
remove the effect of the sex, race, and ethnic composition of job categories
on their pay rates. Both kinds of approaches depend on two assumptions:
Mat the basis on which jobs are paid at different rates can be made largely
explicit and measurable, and that whatever cannot be measured does not
favor any sex, race, or ethnic group. These assumptions seem to us to
represent useful foundations for the design of methods to assess the fairness
of existing pay rates within a firm. Me approaches reviewed here and the
procedures we illustrate are at present, however, not very well developed
and are almost completely untested. Hence, it is not possible to recommend
any of them unequivocally at this time.
We prefer to encourage experimentation with and exploration of the
properties of these approaches in order to determine their usefulness
in eliminating discrimination in pay rates. In particular, efforts should
be made to improve job evaluation techniques. Research on the pos-
sibility that stereotypes are operating in the evaluation of jobs as well
as research on the actual characteristics of jobs held by different groups
is extremely important in ~mprowng job evaluation systems. In addition,
further research on the discriminatory components of pay rates is
needed. It is important to note, however, that we do not recommend
requiring the installation of a job evaluation plan in a fimn not using
one in an attempt to ensure that the firm's pay system is nondiscr~mi-
natory. At present we know of no method that would guarantee a "fair"
pay system.
Representative terms from entire chapter:
pay rates
