We construct a model in which firms use workers' productivities in determining their job assignments. A worker's productivity must exceed some lower bound to satisfy the minimum qualifications for a particular job. If the worker's productivity exceeds some upper bound he is promoted. Under these conditions it is possible that the better educated and more experienced individuals would be the least productive workers on every job, even though, for each worker, education and experience increases his productivity. Whether this anomalous result occurs depends on the underlying distribution of ability in the population and the job assignment policy delineated above. One implication of our analysis is that firms that use hiring criteria that accurately predict a worker's success on the job may not be able to validate those criteria through measurements of the performance of the workers that they had hired. EEOC rules that require hiring criteria to be validated in that fashion may penalize firms with the most efficient hiring and promotion standards.

Andrew Weiss

Henry Landau

English

Research Papers in Economics

NBER WORKING PAPER SERIES
VALIDATING HIRING CRITERIA
Andrew Weiss
Hanry Landau
Working Paper No. 2167
NATIONAL BUREAU OF ECONOMIC RESEARCH
1050 Massachusetts Avenue
Cambridge, MA 02138
February 1987
The research reported here is part of the NBER's research program
in Labor Studies. Any opinions expressed are those of the authors
and not those of the National Bureau of Economic Research.NBER Working Paper #2167
February 1987
Validating Hiring Criteria
ABSTRACT
Weconstruct a model in which firms use workers' productivities in determining
their job assignments. A worker's productivIty must exceed some lower bound to
satisfy the minimum qualifications for a particular job. It the worker's productivity
exceeds some upper bound he is promoted.
Under these conditions it is possible that the better educated and more experienced
individuals would be the least productive workers on every job, even though, for each
worker, education and experience increases his productivity. Whether this anomalous
result' occurs depends on the underlying distribution of ability in the population and
the job assignment policy delineated above.
One implication of our analysis is that firms that use hiring criteria that accurately
predict a worker's success on the job may not be able to validate those criteria
through measurements of the performance of the workers that they had hired. EEOC
rules that require hiring criteria to be validated in that fashion may penalize firms
with the most efficient hiring and promotion standards.
Andrew Weiss HenryLandau
Bell Communications Research 2A-351 Bell Laboratories
435 South Street 600 Mountain Avenue
Morristown, NJ 07960-1961 Murray Hill, NJ 07974VALIDATING HIRING CRITERIA*
by
Andrew Weiss
Bell Communications Research and NBER
Henry J. Landau
AT&T Bell Laboratories
I. INTRODUCTION
it is a commonplace observation that while earnings generally increase withage,
labor market experience, and education, performance withina job often decreases with
age, experience and education. (See for example, Medoff and Abraham, Berg,
Kutscher and Walker, or Clay.)
One reason for this apparent divergence between performance andearnings is that
the distribution of workers on a job is generally truncated from above and below:
there are usually hiring criteria that applicants must satisfy to be assigned to thatjob
(or to keep it), and there are usually also promotion criteria. Since measures of
productivity within a job are necessarily restricted to workers who were assigned to
those jobs and have not yet been promoted (or demoted), there is a clear sample-
selection bias operating. For example, Medoff and Abraham (1980a) find in an
empirical study that better educated workers need to achieve a lower level of
productivity before being promoted than do less well educated workers.1 Hence, even if
*Theopinions expressed are not necessarily those of AT&T Bell Laboratories, of Bell Communications
Research, or of NBER.
1. This could be explained if some of the learning in school has a greater effect on productivity in
higher level jobs than in lower level ones.-2-
productivity were positively correlated with education we could find that the better
educated within a job (those who haven't been promoted) are, on average, less
productive than the less well educated workers.
In this paper we prove a stronger point. Suppose job assignments were determined
soieiy by productivity (so that the same level of performance were required for each
worker's promotion) and productivity were an increasing function of experience and
education. The use of productivity as the sole criterion for promotions could still
cause a negative relationship between productivity and experience (or education)
within jobs. The reason is that although the productivity of each individual increases
with experience, the distribution of people by innate ability changes across experience
and education bands within a job. The lower innate ability of the more experienced
and better educated workers on a job could outweigh the direct effect of experience
and education on their performance, and cause a negative correlation between
experience (or education) and performance on that job.
Our argument is based on a model in which productivity is linked to job
assignment. Such a linkage is explicitly formulated in models by Calvo and Wellisz,
Rosen, and Guasch and Weiss.
In the Calvo-Wellisz model, shirking by supervisors is more harmful to the firm
than is shirking by production workers. Consequently the more able workers are
assigned to supervisory positions and are paid more (to increase their effort).
In the Rosen model, the production technology of the firm amplifies the
productivity of supervisors relative to that of production workers.The output of
supervisors affects the output of their subordinates. In equilibrium,the most-3-
productive, and most highly paid, workers are assigned jobs higher up in the corporate
hierarchy.
In the Guasch-Weiss model, promotions of the more able workers are used as
sorting mechanisms to induce applications from workers of high ability.
II. THE MODEL
Assume a continuous distribution F(i) of the underlying abilities of individuals in
the population, i E R, and we denote F'(i) by 1(i). The productivity of an
individual i is ix + cxiy where x represents either experience, age or education (for
concreteness we shall refer to x as experience); x affects productivity on all jobs
equally; y is the worker's tenure on his current job, and does not affect the worker's
productivity on other jobs; o is a non-negative constant.
Firms observe productivity. Only workers whose productivity is above r are hired
for this job. Workers whose productivity on an alternative job exceeds s are
promoted. If i and x were independent (or negatively correlated) an outside observer
would note that workers with greater experience (or education) are both more likely to
get these jobs and are more likely to be promoted.
Consequently the abilities and experience (or education) levels of workers on this
job satisfy.
r<xi<s. (1)
Since, according to (1), the job begins when x =r/i,and ends when x =s/i,we have-4-
y=x—r/i, (2)
O<y<(s—r)/i. (3)
To put this in terms of the variable x, we substitute for y from (2), obtaining
ix +aiy =x(1+a)i —r , (4)
in which, by (1) 1 is restricted to the range
r/x<i<s/x. (5)
From (5) it follows that on any job longer experience x is associatedwith groups of
lower ability. We now show that this sorting effect can outweigh thedirect effect of
experience on the productivity of each worker.
By (4) and (5), the average productivity, AP(x), of workers on a particularjob who
have total work experience, x, is
AP(x)
s:!:Ix(1+a) I —ar]f(i)di
di
rs/x XI,2J2)d2 =(1+a)
.irjx — crr (6)
f,jxf(i)di
To show that this expression can decrease with increasing x we need only produce an
example. Suppose
1(i) = ￿1
(7)
and consider an experience cohort for which r/x ￿1.Then we find-5-
8/Z. xfr/zif(z)dz rs2 r2s2
f:!:f(i)di
—x
1+
— 2r s -
2 rs3 rrss
g(11)2
6— 1
r S
3(--+-)
=
2(*+--±--)
+
3(+)+2x(-++)
3(1_1)2
—3(1+1)
+2(*++--)
—
2(*+--+--)
the first reduction obtained by removing the common factor x2(1/r —1/8) from
numerator and denomInator, and the second by writing the result, (A +BX)/(C + Dx),
in the form B/D + (A —BC/D)/(C+Dx). As the final expression decreases when x
inëreases, the average product of labor on the job is a decreasing function of total
labor experience.
Thus for each individual, productivity increases with experience. However, in the
job-experience cohort being selected, the more experienced workers are less productive.
Of course these results are sensitive to the distribution, F(i), of ability in the
population. For example, suppose that, within the relevant range of ability types,-6-
f(i) =Ki,where K is a constant of normalization. Then given our learning function
and job assignment criterion, expected productivity within the job would be
independent of experience. (This result follows trivially from substituting into (6)).
Note that this result holds regardless of the sign of B, so f'(i) can be positive or
negative. Examples of distributions for which expected productivity increases with
experience are likewise easy to find.
As we already mentioned, this argument is directly applicable to the relationship
between productivity and education: we need only change the definition of x and
rewrite (6) as AP(x) =
j,1 f(i)dz
ifi.DISCUSSION
We have shown that sample selection can cause the measured relationship between
particular worker characteristics and productivity on a job to be the reverse of what it
actually is in the entire worker population. The distributions we have chosen to
illustrate this do not seem unreasonable. Moreover, there is evidence that promotional
criteria are less stringent for better educated workers, which would tend to strengthen
the bias further.
Consequently it may be impossible to validate a firm's hiring criterion by
comparing the performance of different workers that were hired under that criterion.
Indeed, validation of that sort may be measuring the distribution of unobserved ability
differences rather than the effect of observed attributes on performance.
A similar critique can be made of studies that seek to judge the effectiveness of
SAT scores or high school grades as predictors of academic success at a particular-7-
Universityby comparing ex post academic success with SAT scores or high school
grades of students that satisfied the admissions standards of the university. In that
case, promotion in the work setting would have its analog in choosing an academically
more demanding University.-8-
REFERENCES
[1] Becker, 0., Human Capital, Chicago: University of Chicago Press, 2nd edition;
1975.
[2]Belbin, R. M., "Difficulties of Older People in Industry," Occupational
Psychology, 1953, 27, 177-190.
[3] Berg, I., The Great Train Robbery: Columbia Univ. Press, 1973.
[4]Birren, J. E., The Psychology of Aging, Englewood Cliffs, N.J., Prentice Hall,
1964.
[5]Calvo, G. and S. Wellisz, "Hierarchy, Ability and Income Distribution," Journal
of Political Economy, 87, (October 1979), 991-1010.
[6] Clay, H. M., "A Study of Performance in Relation to Age at Two Printing
Works," Journal of Gerontology, 1956, 11, 417-424.
[7] Freeman, S., "Wage Trends as Performance Displays Productive Potential: A
Model and Application to Academic Early Retirement," The Bell Journal of
Economics, Vol. 8, (Autumn 1977), 419-443.
[8] Guasch, J. L. and A. Weiss, "An Equilibrium Analysis of Wage-Productivity
Gaps," Review of Economic Studies, Vol. 49, (1982), 485-497.
[9] Kutscher, R. E. and Walter, J. F., "Comparative Job Performances of Office
Workers by Age," Monthly Labor Res., 1960, 83, 39-44.
[10] Lazear, E., "Why is There Mandatory Retirement?" Journal ofPolitical
Economy, Vol. 87, (December 1979), 1261-1284.-9-
[ii] Lazear, E., "Agency, Earnings Profiles, Productivity and Hours Restrictions,"
American Economic Review, Vol. 71, (September 1981), 606-620.
[12] Medoff, J., and K. Abraham, "Experience, Performance and Earnings,"
Quarterly Journal of Economics, Vol. 95, (December 1980), 703-736.
[13] Medoff, J., and K. Abraham, "Are Those Paid More Really More Productive?"
Journal of Human Resources, Vol. 41, No. 2, (Spring 1981), 186-216.
[14] Mincer, J., Schooling Experience and Earnings, New York, NBER; 1974.
[is] Muriel, K. F. N. and Griew, S., "Age Experience and Speed of Response," In A.
T. Welford and J. E. Birren, Behavior Aging and the Nervous System,
Springfield, Illinois, Charles C. Thomas, 1965.
[16] Rosen, S., "Authority, Control and the Distribution of Earnings," Bell Journal
of Economics, Vol. 13, (Autumn 1982), 311-323.

A Study of Performance in Relation to Age at Two Printing Works,&quot;

Age Experience and Speed of Response,&quot; In

Agency, Earnings Profiles, Productivity and Hours Restrictions,&quot;

An Equilibrium Analysis of Wage-Productivity Gaps,&quot;

Are Those Paid More Really More Productive?&quot;

Authority, Control and the Distribution of Earnings,&quot;

Comparative Job Performances of Office Workers by Age,&quot; Monthly Labor Res.,

Difficulties of Older People in Industry,&quot; Occupational Psychology,

Experience, Performance and Earnings,&quot;

Hierarchy, Ability and Income Distribution,&quot;

Schooling Experience and Earnings,

The Great Train Robbery:

The Psychology of Aging,

Wage Trends as Performance Displays Productive Potential: A Model and Application to Academic Early Retirement,&quot;

Why is There Mandatory Retirement?&quot;

Validating Hiring Criteria

Validating Hiring Criteria

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