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Economic

m

i s i a i f l R E V I E W

1988 Quarter 1
Vol. 24, Ho A

Can C om petition Am ong

2

Lo cal Governm ents
Con strain Governm ent
Spending?

Economic Review is

published

quarterly by the Research D e p a rt­
m ent of the Federal Reserve Bank

by R andall W. E berts

of C leveland. C opies of the

and T im o th y J. G ronb erg

are available through our Public

Review

Inform ation D epa rtm en t,
T h e decentralized U .S . governm ental structure has been both praised for

216 /5 79 -215 7.

prom otin g efficiency and blam ed for stim ulating excessive local g o ve rn ­
m ent spen ding. B y exam ining the relationship between the num ber of
local g ove rnm e nts within local labor m arkets and their expenditures, the
authors find that the existing structure of gove rnm e nt creates two o p p o s ­
ing forc es. C om petition am on g general-purpose units constrains local

C oordinating Eco n o m is t:
Randall W . Eb erts
Editor: W illiam G . M urm a nn

gove rnm e nt spen d in g , while the overlapping labyrinth of single-purpose
gove rnm e nts stim ulates local gove rnm e nt spending.

A s sista n t Editor: Robin Ratliff
Design: M ichael G alka
Typesetting: L iz H an n a

E x it Barriers in the
Steel Industry

10
Opinions stated in

Review

Economic

are those of the authors

by Mary E. Deily

and not necessarily those of the

U n derstan ding how resources exit from a declining industry is im portant

Cleveland or of the Board of

for evaluating the perform an ce of those industries. This paper exam ines

Governors of the Federal Reserve

the nature and size of exit barriers in the steel industry and argues that

S y s te m .

Federal R eserve B an k of

these barriers have greatly prolonged the in d u s try’s contraction. The
effects of current trade protection and pension policies on the size of the
exit barriers are also discussed.

Material m ay be reprinted pro­
vided that the source is credited.
Please send copies of reprinted

W h y Do W ages V ary

19

material to the editor.

Am on g Em ployers?
b y E rica L. G roshen
This paper review s the burgeoning literature on w age differences am on g
industries and establishm ents. First, the empirical evidence on intra- and
inter-industry w age differentials is s urveyed . Then the author discusses
five alternative explanations for large, persistent, system atic w age
differentials for observationally equivalent w orkers across em plo yers. The
paper co ncludes with a short discussion of the policy im plications of
alternative explanations for em ployer w age differentials.

IS S N 0013-0281

Can C om petition Am ong Local
Governm ents C onstrain
Governm ent Spending?
by R andall W. E be rts and
T im o th y J. G ronb erg

Randall W . Eb erts is an assistant vice
president and ec onom ist at the Federal
Reserve B ank of C levelan d. T im o th y J .
G ron berg is an associate professor of
econom ics at Texas A & M University.
T h e authors wish to thank Ralph D ay
and D avid D ’Alessandris for excellent
co m p uter assistance and Erica
G rosh en and Daniel M cM illen for
helpful co m m en ts and suggestions.

Introduction

The United States contains more than 80,000
separate governmental units. If none of these
units overlapped, each government would serve
fewer than 2,000 individuals. Governmental
units do overlap, however, resulting in several
layers of jurisdictions. Residents within a metro­
politan area typically receive public services
from a municipality, a township, a county, and a
host of special districts.
In addition, at each level of government,
several similar governmental units may provide
services within the same geographical area. For
example, the Chicago metropolitan area alone
contains more than 250 municipalities, each
responsible for the same array of governmental
functions. Overlapping these governments are
835 special districts, which usually perform only
a single function, such as providing regional
transportation or enforcing environmental pro­
tection regulations.
The impact of this structure on government
behavior is varied, and the net effects are not yet
fully understood. Critics of the decentralized
structure of local governments blame the pro­
liferation of local governments for what they see
to be “runaway” spending. They argue that
duplication of efforts by similar but independent
jurisdictions within the same geographical area

is an inefficient way to provide public services
and that the resulting fragmentation could ne­
gate any benefits derived from economies of
scale.
Proponents of a decentralized public sector
counter with the argument that it fosters
increased efficiency in the production of public
goods. They maintain that competitive pres­
sures induce local governments to adopt the
most efficient provision techniques and to tailor
the levels of provision of public goods to the
preferences of societal subgroups (Oates [1972]).
The phenomenal expansion of the local pub­
lic sector adds fuel to this controversy. Since
1950, state and local government expenditures
have increased at a faster rate than either the
gross national product, federal expenditures, or
expenditures on private-sector services. State
and local governments currently claim 17 per­
cent of total personal income, in contrast to 10
percent in 1950. Currently, they spend two and
one-half times more than the federal govern­
ment spends on civilian services such as educa­
tion, roads, welfare, public health, hospitals,
police, and sanitation.
How much of this growth is due to govern­
ment structure and how much is due to other
factors, such as demand for local services, is an
empirical question. Even the effect of govern­
mental structure can work in opposite direc­

tions. For instance, a decentralized public sector
may increase local public spending due to
duplication of efforts, but at the same time,
competition among these units may constrain
spending. The net effect of our present govern­
mental structure on government spending
depends on which of these various factors is
more important.
To further complicate matters, there are two
distinct types of local governments. One type
provides a variety of services to a subgroup of
the county or metropolitan population, while
the second type typically provides a single serv­
ice to the entire local area. Possible differences in
behavior of these two government types must
be taken into account. Two previous studies,
one by Oates (1985) and a follow-up by Nelson
(1987), have estimated the relationship between
decentralization and government spending, but
without conclusive results.1
The purpose of this paper is to continue the
inquiry into the relationship between decentral­
ization and the size of the local public sector. We
test the decentralization hypothesis proposed
by Oates, in which an increase in the number of
governmental units reduces local government
spending as a percentage of personal income.
However, unlike Oates (and Nelson), we contend
that the hypothesized effects will most likely be
observed at the metropolitan and county levels
(referred to as the local level), not at the state or
national levels. We believe that most of the “disci­
pline” derived from competition for households
and firms would be observed at these levels of
disaggregation, because these levels more closely
approximate local labor markets within which
firms and labor are most mobile. Oates (1985), in
fact, argues that the “discipline” resulting from
fiscal competition should increase as the geo­
graphical size of the unit of analysis decreases.
However, neither Oates nor Nelson uses a unit of
analysis less aggregated than the state.
To test our point, we use various levels of
aggregation from the county to the state level.
We find solid statistical support for the
decentralization hypothesis at the metropolitan
and county levels. Increases in the number of

■

1

A n unpublished paper by Z a x (19 8 7), recently brought to our

attention, also takes exception to the use of state-level data by Oa tes and
N e ls o n . Us in g county-level data, he finds a negative and statistically
significant relationship between the n u m b er of gove rnm e nts and the size
of the local public sector. H is study differs from ours in at least three
w ays. Firs t, he uses ow n-source revenue as a dependent variable,
w hereas we use local expenditures on selected fun ction s. S e c o n d , we
explore these effects at various levels of agg regation , not just at the
c o u n ty level. T h ird , he finds that an increase in the n um ber of special
districts also reduces the size of the local public sector. W e find the
opposite effect at each level of disaggregation.

competing general-purpose government units
are associated with a statistically significant
decrease in the relative income share of local
public expenditures. At the same time, we find a
distinct difference in behavior between the two
types of government. An increase in the number
of single-purpose districts increases the share of
personal income going to local government
expenditures. To further support our point, we
find that these relationships are not significant at
the state level, which is consistent with the
results of Oates and Nelson.

I. Com petition Am ong
Local Governm ent
Jurisdictions

The potential benefits of competition among
local government jurisdictions are similar to the
benefits associated with competition in private
markets. In the private sector, competition
induces profit-maximizing firms to provide
goods or services preferred by consumers at the
lowest resource cost. The motivating force
behind this behavior is the choice of suppliers
available to consumers. If a firm raises its price,
consumers will switch to the supplier with the
lowest price, assuming that all firms are identical
and that consumers incur no additional cost in
searching for another supplier. Given enough
competing firms (that is, choices to the con­
sumer), no firm can set prices above the per-unit
cost of production.
The same competitive forces exist among
local government jurisdictions. By law, local
governments cannot earn profits. However,
according to Niskanen (1971), public adm in­
istrators may be motivated to maximize revenue,
and thus expenditures, in order to expand desir­
able aspects of their working environment. Pub­
lic administrators thereby “consume” profits on
the job instead of taking them home.
The capacity of governments to increase
revenues depends upon the customer base—
taxpayers w ho live within their jurisdictions. If
local governments attempt to raise taxes or to
reduce the level and quality of services, then
taxpayers will have an incentive to locate in
neighboring jurisdictions that provide a service/
tax package more in line with the taxpayers’
preferences. The loss of households and firms
reduces a government’s tax base and, in turn,
reduces its ability to raise revenue.
Thus, the basis for the constraining effect
of decentralization is founded upon the interjurisdictional competition for mobile resources,
both labor and firms. The line of argument

follows the old industrial-organization paradigm
of structure, conduct, and performance. Applied
to the public sector, the argument runs from an
increase in the number of independent public
jurisdictions (suppliers), to an increase in the
degree of competition, to a decrease in the
relative size of the public sector. However, the
efficacy of governmental fragmentation depends
on the mobility of households and firms.
The net benefit of the move determines the
extent to which mobility occurs or is likely to
occur. This benefit comes from either the sav­
ings derived from locating in a lower-cost juris­
diction or the advantages gained from residing
within a jurisdiction that provides more or
better services, everything else being equal.
The costs associated with choosing between
local governments are generally greater than the
costs incurred in searching for alternative sup­
pliers of private goods and services. To change
local governments, a household must change
residence and incur the costs of purchasing a
new home and finding a new job, and must bear
the emotional costs of moving to a new area.
However, these costs are in direct proportion
to the distance one must move in order to find a
more preferable governmental unit. For exam­
ple, if enough choices of local governments are
available within the same metropolitan area,
then the discontented taxpayer may not need to
change jobs in order to change jurisdictions.
Consequently, the mobility of households and
firms increases as the size of the geographical
area decreases. Therefore, we would expect
local governments to be more constrained by
competitive forces at the county or metropolitan
level than at the state or national level.
The two empirical studies by Oates and
Nelson have looked for the constraining effect of
competing jurisdictions only at the state level.
Oates proposes and tests the hypothesis that the
size of the public sector should vary inversely
with the extent of fiscal decentralization, other
things being equal. He uses the number of
jurisdictions within each state as a measure of
decentralization. Using state-level aggregates,
however, he finds no significant relationship
between state and local expenditures as a per­
cent of state personal income and the number
of jurisdictions.
In a reply to Oates’ paper, Nelson suggests
two modifications. The first is to distinguish
between general-purpose jurisdictions (such as
municipalities) and single-purpose jurisdictions
(such as school districts and mosquito-abatement districts). Nelson argues, and rightfully so,
that the two types of districts are not compara­
ble and consequently should not be lumped

together. The multiplicity of special districts
within a metropolitan area does not necessarily
indicate that consumers have a choice, but
rather that residents are provided several serv­
ices, each by a different district.
In addition, since many special districts pro­
vide only minor services and since nearly half of
them lack the authority to levy taxes, Nelson
argues that there may be little incentive for
individuals to choose between these districts.
The second modification is to include statemandated programs in the analysis to account in
some way for differences in functional respon­
sibilities among jurisdictions. W ith these modifi­
cations, Nelson finds the desired systematic
relationships, but the precision of the estimates
is below the usual acceptable confidence level.2

II. M arke t Structure of
Local Governm ents

As mentioned previously, one of the prerequi­
sites for competition is a sufficient menu of
choices offered to consumers. Tallying up the
number of local governments in the United
States casts little doubt on the potential for
choice. According to Aronson and Hilley (1986),
79,862 governmental units below the state level
existed in 1977. These units tend to fall into two
categories: general-purpose and single-purpose
governments.
General-purpose governments, such as
municipalities and counties, provide a variety of
services ranging from fire protection to health
care. As shown in table 1, municipalities num ­
bered more than 18,000 in 1977, or 24 percent
of all governmental units; counties totalled
3,042, or less than 4 percent. Single-purpose
units, consisting primarily of school districts
and special districts, comprise the majority of
local government jurisdictions. As noted in table
1, over 40,000 governmental units have been
established to provide only a single function.
More than half of these units are special districts,
which include sanitary districts, drainage dis­
tricts, and soil-conservation districts.

■

2

N els on does find the desired statistically significant relationship

betw een the n um ber of general-purpose g ove rnm e nts and the size of
the local public sector using state-level data. How ever, in w hat w e take
as N e ls o n ’s m ost preferred specification, equation (3) and dependent
variable G * , the coefficient on the genera l-p u rpo se -gove rnm e nt variable
has a t-value of only 0 .9 1. T h u s , although w e are in total agreem ent
with N e ls o n ’s m ethodological ch an ges, w e do not believe that a clear
vindication of the decentralization claim s utilizing the state sam ple has
been established.

The overlapping structure of local govern­
ments is far from static. Between 1957 and 1977,
the number of local governments fell by 22,514,
primarily from a conscious attempt to consoli­
date local school districts. The reduction in the
total number of units would have been much
I M

M

M

H

T A

B

L

E

1

Num ber and Type o f Lo cal
Governm ental U n its in th e United
S ta te s fo r Selected Years

Number of Units

Type of Government

in local labor markets, rather than on the aggre­
gate of the state and local public-goods sectors.
Consistent with this focus, we adopt two levels
of aggregation as the geographical unit of obser­
vation: the county and the metropolitan area. In
addition, as a point of reference to the previous
two studies, we also estimate the relationship at
the state level.
Our data set consists of observations on local
public-sector characteristics and relevant demo­
graphic features of more than 2,900 counties
and 280 SMSAs in 1977. This year was chosen
for two reasons. First, it is consistent with the
studies by Oates and Nelson. Second, some
information, such as state mandates, was avail­
able only during this period. We have analyzed
more current data on local-government expen­
ditures for 1985, while still using state mandates
from the earlier period, and find no qualitative
differences in the results.

1957

1967

1977

1982

3,047

3,049

3,042

3,041

Municipality

17,183

18,048

18,862

19,076

Township and town

17,198

17,105

16,822

16,734

School district

50,446

21,782

15,174

14,851

Special district

14,405

21,264

25,962

28,588

Variables

102,279

81,248

79,862

82,290

Local government performance is measured by
expenditures on the major local public services
as a percentage of personal income in either the
county or the SMSA, whichever is appropriate.
We include local expenditures on local schools,
public welfare, fire and police protection, sanita­
tion, and local parks.3
The key explanatory variable is market struc­
ture, which is measured by the number of local
governments within the appropriate unit of
observation. Local governments are divided
into the two classes described earlier: generalpurpose and single-purpose jurisdictions.4
Three different measures of the number of local
governments are used in the analysis. The first
measure is simply the total number of each class
of local governmental units found within the
appropriate unit of analysis (county or metro­
politan area). The second method normalizes
the number of units by the size of the popula­
tion served by all of these local governments.
The third method divides the number of juris-

County

Total

SOURCE: Num bers obtain ed from A ronson and Hilley (1986), Table 4-1, p. 76.

greater during this time if it were not for the
creation of more than 11,000 special districts.
Between 1977 and 1982, the proliferation of
special districts continued, while the number
of other types of governmental units remained
relatively constant.
As expected, local governmental units are
concentrated in metropolitan areas. We find that
counties in Standard Metropolitan Statistical
Areas (SMSAs) have almost twice as many gov­
ernmental units as do non-SMSA counties— an
average of 40 compared to 21. The ratio is even
higher for single-purpose units (2.3 to 1), but it
is smaller for general-purpose governments (1.6
to 1). In addition, we find that only 25 percent
of the metropolitan areas had fewer than 10
general-purpose units and 14 single-purpose dis­
tricts. O n the other hand, 50 percent of the
SMSAs contained more than 21 general-purpose
units and 29 single-purpose districts.

■3
III. The Em pirical Test

■4
The basic relationship to be tested is between
government performance and market structure.
The specification and analysis in this section
follow the lines initiated by Oates and Nelson.
The principal difference in our study is that we
focus solely on local government expenditures

Nelson did not include police protection in his estim ation. W e find ,

how ever, that the results are not sensitive to its inclusion or exclusion.

Th e n um ber of general-purpose g ove rnm e nts is the sum of the

n um ber of co un ty and m unicipal g o ve rn m e n ts, except in Pen nsylvan ia,
N e w Jersey, and the N e w En g la n d states, w here tow nships are also
included. Th e n um ber of single-purpose g ove rnm e nts is the su m of the
n um ber of to w n s h ip s, school districts, and special districts, except in the
aforem entioned states, w here tow n ship s are not included. T h e reason for
the exceptions is that the functional responsibilities closely resemble
municipalities in these states.

dictions by the total land area in the county or
SMSA. This last method accounts to some
degree for the ease of mobility among the
various governmental units.
The other explanatory variables include state
mandates, per-capita personal income, popula­
tion, and intergovernmental grants as a percent­
age of total local tax revenues. The first three
variables may be considered proxies for the
demand for local public services. As Nelson
notes, state mandates may impose binding m ini­
m um constraints on certain local government
activities. As defined by the Advisory Commis­
sion on Intergovernmental Relations (ACIR),
which collected the data, a state mandate is a
legal requirement imposed by the state that a
local government must undertake a specified
activity or provide a service that meets m ini­
m um state standards.5 The presence of such
restrictions would, therefore, be positively
associated with the relative size of the local
public sector.
The demand for local public services should
be positively related to personal income, accord­
ing to traditional consumer demand theory.
However, the relationship between
income and government spending as a percent­
age of personal income has been subjected to
considerable empirical scrutiny. Investigation
of Wagner’s “law” or, perhaps more correctly,
Wagner’s hypothesis of a positive correlation
between income and government’s relative
claims on that income, has sparked much
research and has kindled considerable contro­
versy.6 To our knowledge, the empirical studies
have all involved national samples. Our study
will provide a simple test of Wagner’s “law” at
the local level.
An increase in population, holding other
variables constant, would also be associated
with a larger local public sector. This result in
some ways follows the thinking of Wagner, w ho
saw an increase in population density and
urbanization leading to increased public expen­
ditures on personal protection and economic
regulation (Bird [1971]).
The ratio of intergovernmental grants to local
tax revenues measures the extent to which local

per capita

■5

governments rely on higher-level governments
for funds. Because of the matching provisions of
many federal and state grants, we would expect
the grants to stimulate local government
expenditures.7

Results

Fourteen separate models were estimated: one
for each level of aggregation and for each mea­
sure of decentralization. The estimates displayed
in table 2 for one of the models are typical of the
results found for the other models. We find that
an increase in decentralization of
governments, measured by any one of the
three measures, is statistically significantly re­
lated to a decrease in the size of the local public
sector. This finding supports the decentraliza­
tion hypothesis: an increase in jurisdictional
fragmentation is associated with a decrease in
local budget share.
O n the other hand, we find that an increase
in the number of
units increases
the local budget share. This suggests that the
costs of providing services through special dis­
tricts outweigh the constraining effects that
competition may impose on spending or the
savings that result from economies of scale.
Thus, our results support the argument that the
proliferation of special districts has increased
local spending.
The negative and significant coefficient on
per capita income is evidence against the rele­
vance of Wagner’s hypothesis applied to the
local government sector. At the state level, we
find a positive relationship, as does Oates. A
negative correlation between local public-expenditure share and income is not unexpected,
however. Most studies of local public-expenditure demand find income elasticities that are
significantly less than unity, which implies a
decline in aggregate budget share as average
community income rises.8
The positive coefficients on the population
and intergovernmental transfer variables are
consistent with our earlier discussion.

general-pur­

pose

single-purpose

Th e A C IR surveyed local gove rnm e nts about 7 7 functional

s u b c o m p o n e n ts in five broad areas: state personn el, other than police,
fire, and education (15 c o m p one nts); public safety (31); environm ental
protection (8); social services and m iscellaneous (10); and education (13).

■7

King (1984) offers a com p reh en sive s u m m a ry and critique of the

effects of grants on local gove rnm e nt spen ding.

■ 6 Bennett and Jo h n s o n (1980) provide a com prehensive s u m m a ry of
the debate and a co m p endium of the em pirical results. Ra m (19 8 7)

■ 8 Inm an (19 79 ) includes a s u m m a ry of studies of the dem a nd for

appears to have m ade the m ost recent contribution to the literature.

local public services.

T

A

B

L

E

2

Regression Results a t th e S M S A
Le v e l, 1 9 7 7

Variables_______________

Mean
(Standard error)

Coefficient
(T-statistic)

Number of generalpurpose units

28.8
(40.83)

-.015
(4.48)

Number of singlepurpose units

54.1
(80.55)

.005
(2.79)

Per capita income
($ 1,000s)

6.67
(.98)

-.317
(2.87)

Ratio of transfers
to local taxes

1.18
(.53)

.559
(3 .02)

Population in SMSA
(100,000s)

5.53
(10.04)

.45
(3.85)

Total state
mandates

37.0
(11.92)

.083
(H-59)

Constant

5.23
(6.17)

Dependent variable:
local expenditures
per personal
income

6.94
(1.80)

Number of
observations
R-square

289
.43

SOURCE: G overn m en t ex pen d itu re data from Census o f G overnm ents,
1977; personal in c o m e and p op u la tion data from the Bureau o f E c on om ic
Analysis; state mandates c o m p ile d b y the ACIR.

Various M easures of
De ce n traliza tion

The conclusion that increased decentralization
of general-purpose governments is associated
with a smaller local public sector is supported
by our analysis regardless of which measure of
decentralization is used. As seen in table 3, not
only are the coefficients statistically significant at
the 1 percent level for SMSAs and counties, but
the magnitudes of the elasticities are also of
similar magnitudes, with few exceptions. For
example, at the SMSA level (column 1), we find
that a 10 percent increase in the number of
general-purpose jurisdictions reduces the local
public sector’s share of personal income by 0.6
percent. In the case of SMSAs, a 10 percent
increase in general-purpose governments would
mean only an additional three units.

However, when state-level data are used, the
statistical significance of the estimates falls below
the 10 percent confidence level. The only excep­
tion is the effect of the number of generalpurpose governments, which is statistically sig­
nificant right at the 10 percent level.
Table 3 also reveals that the size of the local
public sector at the SMSA level is slightly more
responsive to a change in the number of generalpurpose governments than to a change in the
number of single-purpose governments. This
relationship holds no matter which decentraliza­
tion measure is used, but is less consistent at the
county level.

IV. Conclusion

We have found a significant relationship be­
tween governmental structure and government
size. Two basic relationships emerge from the
analysis. First, an increase in the number of
general-purpose government units within a
metropolitan area or county boundary reduces
the share of personal income going to the local
public sector. Second, an increase in single­
purpose government units has the opposite
and equally significant result of increasing the
size of the local public sector.
The difference in behavior between the two
types of governments underscores our conclu­
sion that competition among local general-pur­
pose governments constrains local government
spending. Recall that suppliers are disciplined
by the presence of other suppliers only when
they provide similar services to the same mar­
ket. General-purpose governments meet this
requirement more closely than do single-pur­
pose governments. Typically, a single-purpose
government is the sole supplier of a specific
service within a local market, whereas each
general-purpose district provides a similar array
of services.
Thus, the existing structure of government
creates two opposing forces of government
behavior. Competition among general-purpose
units, such as municipalities, constrains local
government spending. O n the other hand, the
overlapping labyrinth of single-purpose govern­
ments stimulates local government spending.
Much of the current arrangement of local
governments resulted from attempts by states
and localities to respond to changing conditions
within the various constraints imposed on
them. As a practical matter, states and munici­
palities have limited ability to respond to chang­
ing conditions. States are constrained by local
loyalties, vested interests, and the inertia of the

T

A

B

L

E

3

Relationship Betw een Various
M easures of Lo cal Governm ent
Com petition and Lo c a l Govern­
m ent Expe nd itu re s as a
Fra ctio n of Personal Incom e

Measure of
Competition

SMSA

All

Level of Aggregation
County
Non-Metro

Metro

State

A. Number of units
General-purpose
Single-purpose

- .063

.045

.043

.054

.069*

.040

.034

.046

.042

.005**

- .076

.036

.062

.068

.032**

.050

.035

.045

.033

.019**

- .065

.018

.022

.016

.055

.005

.028

.023

B. Number of units per capita
General-purpose
Single-purpose

C. Number of units per square mile
General-purpose
Single-purpose

Note: N um bers are ex p ressed as elasticities. All estimates are significant at the 1 p ercen t level unless d en oted b y an asterisk. A single
asterisk denotes significance at the 10 p ercen t level but less than 5 percent level. A d ou b le asterisk denotes significance at less than the
10 p ercen t level. T he estimates are d erived b y regressing the local govern m en t expen ditures as a p ercen t o f personal in co m e against
m easures o f g ov ern m en t co m p e titio n , p opu lation , per capita in co m e , intergovernm ental revenue, and state program mandates.
Estimates o f a typical regression equation are sh o w n in table 2.
SOURCE: Authors.

status quo. The power of localities to handle
public services is often made difficult by state
statutes that limit powers to tax and to incur
debt.
Since the late 1950s, special districts have
been established as a means of circumventing
these constraints by shifting responsibilities
away from general governments. The federal
government has further stimulated the creation
of special districts through “direct advocacy.”
Many federal agencies would rather deal directly
with officials of special districts than with offi­
cials from general governments such as counties
or municipalities (Aronson and Hilley [1986]).
In the past few years, a number of states have
begun to take a systematic look at the current
structure of local governments. Several states
have established advisory commissions to con­
sider reorganizing and streamlining the per­
ceived fragmented system of local governments
that dot their landscape. These commissions
appear to be particularly concerned about how
the large number of special districts affects the
provision of services.
Our analysis provides some information that

may be useful to these reform efforts. First, our
results suggest that reform efforts directed
toward special districts are well-guided. Clearly,
an increase in the number of single-purpose
governments, which consist mostly of special
districts, increases government spending.
Although these results are very strong, we
should caution that we have not been able to
control entirely for differences in the level of
services provided by these governments. It may
be the case that part of the observed increase in
spending associated with greater numbers of
units simply indicates that additional special
districts are providing additional services.
Second, our results warn against lumping
together general-purpose and single-purpose
governments when considering streamlining
local government structure. We show that the
two different types of governments exhibit
distinctly opposite behavior.
Third, our results suggest that a competitive
environment among specific types of local gov­
ernments can constrain government spending
and promote the efficient provision of local
public services.

R EFER EN C ES

Advisory Commission on Intergovernmental
Relations.
Washington, D.C.: U.S. Government
Printing Office, 1978.

tures.

State Mandating of Local Expendi­
Financ­

Aronson, J. Richard, and John L. Hilley.
(4th ed.).
Washington, D.C.: The Brookings Institution,

ing State and Local Governments

1986.

The
Political Economy of Federal Government
Growth: 1959-1978. College Station, TX:

Bennett, James T., and Manuel H. Johnson.

Texas A&M University, 1980.
Bird, Richard M. “Wagner’s ‘Law’ of Expanding
State Activity”
26(1971): 1-26.

Public Finance.

Inman, Robert P. “The Fiscal Performance of
Local Governments: An Interpretive Review.”
In Mahlon Straszheim and Peter Mieszkowski,
eds.,
Baltimore, MD: Johns Hopkins University
Press, 1979: 270-321.

Current Issues in Urban Economics.

Fiscal Tiers: The Economics of
Multi-Level Governments. London: Allen and

King, David N.

Unwin, 1984.
Nelson, Michael A. “Searching for Leviathan:
Comment and Extension.”
77 (March 1987): 198-204.

American Eco­

nomic Review.

Bureaucracy and Repre­
sentative Government. Chicago: Aldine-

Niskanen, W illiam A.
Atherton, 1971.

Fiscal Federalism.

Oates, Wallace E.
New York:
Harcourt BraceJovanovich, Inc., 1972.
________ . “Searching for Leviathan: An Empirical
Study.”
75 (Sep­
tember 1985): 748-57.

American Economic Review.

Ram, Rati. “Wagner’s Hypothesis in Time-Series
and Cross-Section Perspectives: Evidence
from ‘Real’ Data for 115 Countries.”
69 (May 1987):
194-204.

Economics and Statistics.

Review of

Zax, Jeffrey S. “Is There a Leviathan in Your
Neighborhood?” New York: City University of
New York, Department of Economics,
November 1987.

Exit Barriers in the
Steel Industry
by M a ry E. D eily
M a ry E . D eily is a visiting econom ist
at the Federal Reserve B ank of
Cleveland and an assistant professor
of ec ono m ics at Texas A & M
University. Th e author w ould like to
thank Paul Bauer, Randall E b e rts , Erica
G ro s h e n , Stephen Karlson, and M ark
Sniderm an for helpful c o m m en ts.

Introduction

The U.S. steel industry seems perennially
afflicted with overcapacity. Even after numerous
plant closings, and despite recent high capacityutilization rates, analysts suggest that another 15
to 20 percent of current capacity should close.
W hy has overcapacity been a chronic ailment
of steel firms during the 1970s and 1980s? W hy
haven’t firms closed plants more quickly, since
continued operation of these plants depresses
profits for the entire industry?
The persistent survival of excess capacity is
not inexplicable. In theory, a market system
reallocates resources from activities yielding
lower-than-normal returns to activities with
higher returns. In practice, however, firms can
be locked into a low-profit activity if large losses
are incurred when capital is transferred to new
activities. These potential losses form an exit
barrier, delaying plant closings, depressing prof­
its, and prolonging adjustment for the entire
industry.1

The primary purpose of this paper is to
examine the nature and size of exit barriers in
the steel industry. First, the necessity for contrac­
tion in this industry is summarized. Then basic
exit theory is reviewed, and several types of exit
barriers that seem most pertinent to the steel
industry are described. The potential size of
these barriers in the steel industry is assessed.
Finally, the possible effects of current trade protection and pension-insurance policies on
the size of exit barriers in the steel industry are
discussed.
This paper argues that high exit barriers have
significantly slowed the industry’s contraction
by delaying plant closings. These barriers
explain why capacity has fallen slowly even
though industry profits have been subnormal
since the late 1950s. They also help to explain
why the industry failed to modernize some
plants, even though these increasingly ineffi­
cient plants continued to operate into the 1980s.

I. The N ecessity for
Contraction

■ 1 Th e term “ exit barrier" is perhaps un fortun ate, as it carries the
conn otations of inefficiency attached to the phrase “ entry barrier.” S uch
is not the case: exit barriers are the va riou s cost conditions that m ake
lengthy exit a rational response by firm s.

The U.S. steel industry has performed poorly
during the last 25 years. Profits for the industry
have been low compared to the average man­
ufacturing return in virtually every year since

1958.2 And despite the industry’s recent buoy­
ant performance— part of which appears to be
due to trade protection— long-run trends in steel
demand and steel supply point to continued low
profits in the future.
Structural changes in steel demand have
greatly reduced the growth of the market. These
changes, which include increased use of steel
substitutes such as aluminum and plastic, and
reductions in the amount of steel used in con­
sumer durables, particularly cars, have reduced
the U.S. economy’s need for steel. The average
annual growth rate of U.S. apparent steel con­
sumption has fallen from from 4.1 percent dur­
ing 1960-1969, to 1.9 percent during 1970-1979,
to 0.2 percent during 1980-1986.
Not all steel firms have fared the same, how­
ever. The industry basically consists of two parts:
integrated mills and minimills. The integrated
mills, which produce steel from iron ore, are the
traditional steel industry, while the minimills,
which produce steel products by recycling steel
scrap, are relative newcomers. It is the integrated
portion of the industry that has performed so
poorly; minimills have flourished, increasing
their market share from about 3 percent in I960
to 18 percent in 1985.
As their name suggests, minimills produce
steel on a m uch smaller scale than integrated
plants, reducing the size of the required capital
commitment considerably 3 The mills also ben­
efit from employing workers at lower wages.
Though their costs are extremely sensitive to
the price of scrap minimills have become very
competitive in the product lines in which they
specialize, drastically reducing the integrated
mills’ sales in these markets.4
In addition, integrated firms in the U.S. faced
tough new competition from imports for a share
of the market, as fundamental changes in input
costs during the 1950s and 1960s altered the
comparative advantage in steelmaking. Two
studies, by Crandall (1981) and by Kawahito
(1972), examine the changes in the relative cost

of materials in the U.S. compared to other
countries, particularly Japan. Formerly, abundant
supplies of coal and iron ore assured U.S. pro­
ducers of a materials cost advantage that, along
with greater U.S. productivity, more than com ­
pensated for higher U.S. wage rates. However,
the discovery of rich iron-ore sources in several
parts of the world and the decreased cost of
ocean shipping began to reduce the traditional
U.S. advantage.
Also, as Barnett and Schorsch (1983) point
out, countries like Japan experienced phe­
nomenal growth in steel consumption after
World War II. Their steel industries were able to
build entirely new, large-scale plants, since their
rapidly expanding markets could easily absorb
the output of the additional capacity. These new
plants incorporated the latest technology into an
optimal plant layout, resulting in high productiv­
ity growth. Increased productivity growth,
combined with lower wage rates, reduced the
unit cost of labor further below U.S. levels. This
advantage, added to the favorable changes in
materials costs, made foreign steel very com­
petitive with U.S. integrated production.5
The result has been a decline in the market
share of integrated steel firms in the U.S. from
more than 90 percent in I960 to less than 65
percent in the 1980s. Given the slow growth of
the market, these figures translated into a need
to cut integrated steel capacity by closing plants.
And, in fact, the industry has closed plants.
From its height in the early 1970s of approx­
imately 155 million tons, annual raw steel capac­
ity has fallen to about 112 million tons.
But the contraction of the industry has taken
a long time, even though capital has been earn­
ing subnormal profits for many years.6 Rather
than moving into other activities, firms appear
to be clinging tenaciously to capacity by nursing
along aging plants, as if the growth in demand
for steel might miraculously increase to pre-1970
levels. But as the discussion in the next section
shows, this response may wrell be optimal for
firms facing high exit barriers.

■ 2 See Crandall (1981), p. 29 , for the rate of return on equity after
taxes in steel versus all U .S . m anufacturing for the years 19 5 4 -19 78 .
See U .S . D epa rtm en t of C o m m e rc e , Bureau of the C e n s u s ,

Financial Reports for Manufacturing Corporations,

Quarterly

va riou s issues, for

subsequent years.

■5

In fact, Crandall (1981) co ncludes that a totally new integrated plant

w ould be a p oo r investm ent in the U n ited S tates, given his estim ates of
the possible reductions in labor and energy savin gs attainable.

■3

M inim ills typically consist of an electric steel furnace, a co ntinu­

ou s billet caster, and som e kind of finishing mill, usually for bars. See

■ 6 Th e first m ajor plant closings, those of You n g s tow n Sheet & Tube

Miller (1984) for a goo d description of this technology.

and the United States Steel C orp oratio n at Y o u n g s to w n , did not occur

■4

addition, because capacity is usually m easured as the ability to produce

until the late 19 7 0 s , and the next episode did not occu r until 19 8 2. In
M inim ills have a cost advantage over all integrated m ills, w hether

dom estic or foreign, in the products they can p roduce. See Barnett and

raw steel, estimates of capacity reductions m ay be som ew ha t overstated.

Crandall (1986) for a detailed com p arison of minimill to integrated mill

T h e introduction of continu ou s casters has increased the yield from raw

production costs.

steel by 10 to 15 percent.

II. A M odel of the P la n t
Closing Decision

The neoclassical prediction for a competitive
industry facing an inward-shifting demand curve
is that high-cost plants will exit, leaving the
lowest-cost plants to produce in the long run.
However, as long as variable costs are covered, a
firm will continue to operate an exiting plant
that has fixed costs, since doing so minimizes
the firm’s losses.7 During this period the firm
will not make any major reinvestments; instead,
it will disinvest from the capital in place.
Because most production processes do
involve fixed costs, the decision to close a plant
usually will involve a period of operation and
disinvestment before shutdown. The optimal
closing point will not occur until the net reve­
nue, which is the return to continued operation
of the capital in place, equals the return that
could be earned on the salvage value. Thus, the
speed with which a firm closes a plant depends
on how quickly net revenues decline and on the
amount of capital that can be salvaged once the
plant is shut down.
Clearly, one important factor that will affect
the timing of plant closings is the general level of
economic activity. W hen sales decline during
recessions, they increase the probability of plant
closings by reducing net revenues. This is
especially true for a cyclical industry like steel.
Other factors are also important, however.
Since the firm will not replace the aging capital
with new equipment, one determinant of a
plant’s net revenues is the amount of mainte­
nance the capital in place requires in order to
operate (in other words, its durability). The firm
will continue to bear maintenance expenditures
as long as the capital generates enough revenue
to cover both the additional expense and other
variable costs. Obviously, the larger the mainte­
nance expenditures, the more they reduce net
revenues, and the less likely they will be worth
making.8
A low salvage value may also delay a plant’s
closing. The salvage value is the net amount of
money the firm will realize when the plant
closes. A large positive value means that much of
the capital can be extracted without loss from
the plant, thus shortening the time to shut­
down. A negative value extends the time before
exit, causing the plant to be operated even

though total variable costs are not covered. In
this situation, the firm would actually borrow to
pay the uncovered variable costs in order to
avoid the greater loss of closing.9
In general, the salvage value is determined by
a plant’s resale value minus costs incurred dur­
ing closing. The resale value of the capital
depends on its specificity to the production
process and on output growth in the industry.
The closing costs include the resources neces­
sary to gather the information to make the
closing decision and the time spent planning
and executing it. The firm may also face em­
ployee-related closing expenses, such as sever­
ance pay, early retirement pay, and pensions,
depending on previous contractual agreements
or on local plant-closing legislation. Increases in
these costs, by raising closing costs, will delay
shutdowns.10
Thus, in a contracting industry with durable
and specific capital and high closing costs, firms
will delay closing plants. The plants exit even­
tually, but only after a long period of disinvest­
ment. The result of selective and drawn-out
disinvestment is a gradual increase in the average
age of the industry’s capital stock and a slowing
of productivity growth.
Two things are vital to remember, however.
First, in an industry with high exit barriers, a
slow decline is the optimal rate of closure,
despite years of poor earnings by the industry
Resources are always being utilized in their
highest return activity during a contraction.
Second, although an industry may appear to be
failing because of lack of reinvestment, the
antiquated plants are the result of exit barriers’
prolonging exit and are not the cause of the
industry’s decline. While some plants will be
modernized, those that are exiting will receive
little investment.
In sum, an important consequence of allow­
ing the market to reallocate resources from an
industry with high exit barriers is that capacity
will contract slowly, with old capacity lingering
on and plants closing in bunches during dow n­
turns that lower revenues.

■9

The cost of going bankrupt, instead of continuing to pay uncovered

variable co sts, w ould be an up w ard b ou nd on the am ou nt the firm
w ould be willing to borrow in this situation.

■7

■ 10 T h is conclusion d e p e nds on the sim plifying assum ption m ade
In this co ntext, fixed costs refer to costs that m ust be paid w hether

the plant is open or closed.

here that closing costs do not increase over tim e . A s pointed out by
Littm an and Le e (1983), if em ployee-related closing costs rise quickly with
the seniority of the w ork fo rc e , then a firm m ight accelerate closing to

■ 8 See La m fa lu s sy (1961) for a discussion of these issues.

avoid the greater future liability.

III. Th e S ize of E x it
Barriers in the Steel
Industry

Clearly, the magnitude of exit barriers in an
industry depends on three factors: how long
gross revenues are expected to cover variable
costs, how specific and durable the capital is,
and how high closing costs are.11 This section
presents some information about these factors in
the steel industry which suggests that exit bar­
riers are large.

T A B L E

1

C osts of Steel Production
in the U .S .
(Current dollars)

1976

1986

$217.00

$206.00

Total Variable Cost of Finished Stet 1
Materials, Energy, and Labor
(per net ton of finished product)

310.28

348.00

Total Cost of Finished Steel
(per net ton of finished product)

361.38a

449.00

Total Variable Cost of Raw Steel
Materials, Energy and Labor
(per net ton)

a. T he nu m b er cite d here is slightly low er than the figure re p orted b y
the C ou n cil o n Wage and Price Stability, but is calculated as they
d escribe in the text.
SOURCES: U.S. C o u n cil o n Wage and Price Stability (1977), p. 60;
W harton E con om etrics (1987), p. 4.5.

A rough idea of the likelihood that gross
revenues will cover variable costs— the costs
of all variable inputs to production— can be
obtained by comparing the average variable cost
of a ton of steel to the prices of various steel
products. This cost is conventionally measured
as the sum of labor, energy, and materials. The
U.S. Council on Wage and Price Stability cal­
culated that the average total variable cost per
net finished ton of steel in 1976 was $310.28.
W harton Econometrics estimated that this cost
equaled $348.00 in 1986. These estimates
include the cost of producing raw steel, as well
as the average industry cost of finishing it. Both
of these studies also include estimates of the

financing costs of steel production, taken here
to be the average fixed cost of production (see
table 1).
Table 2 compares estimates of average vari­
able cost and average total cost for selected steel
products to the average realized price per net
ton of those products in 1976 and in 1986. In
most cases, product prices were above the
average variable cost. O n the other hand, almost
all of these prices were well below the total cost
of finished steel. (Product prices do vary
cyclically, causing the size of this shortfall to
change over time. See table 3.) Overall, the data
indicate that product prices may fall consider­
ably below the average total cost without making
immediate shutdown a firm’s loss-minimizing
alternative.
How long does a plant that is not covering
total cost continue to operate? As stated above,
unless prices dip or variable costs rise unexpect­
edly, a plant’s closing would depend on the
durability of its capital, on its resale value, and
on the amount of closing costs.
O f these three, the high cost of closing
appears to be the most important exit barrier
currently in the steel industry. W hen closing a
plant, a firm records a charge for the costs of
dismantling the mill, for the operating loss until
closing, for losses involved with contract termi­
nations, and for a write-down of the assets. It
also records the estimated liability for current
and future payments to employees for pensions
and insurance benefits.
The payments due to the work force when an
integrated steel plant closes are substantial. For
instance, by the provisions of a typical labor
contract, qualified union members on layoff
because of a permanent closing are eligible for
severance pay, supplemental unemployment
benefits, pension payments and, in some cases,
supplemental pension payments.12 Severance
pay for union members with at least three years
of seniority equals four to eight weeks’ wages,
depending on their years of service. A firm
continues to pay life- and medical-insurance
premiums for six to 12 months for workers with
at least two years of continuous service. Workers
may also be entitled to supplemental unemploy­
ment payments for up to two years.
One of the largest parts of the employeerelated closing costs is the estimated liability for
future pension payments. O f course, the portion
of closing costs represented by the pension
liability is not
by closing, since the firm

caused

■ 11 See C a ve s and Porter (19 76 ) and Porter (19 76 ) for an exhaustive
12

list of various possible exit barriers. T h e types of barriers discussed here

■

are those that seem particularly pertinent to the steel industry.

contracts m ade in later years appear to be quite similar.

Th e contract described here becam e effective in 1980. Term s of

owes retiring workers their pensions if the plant
stays open. Nor are all of these charges out-ofpocket expenses. But they do represent pay­
ments that the firm must fund from some new
source, since the cash flow from the plant will
cease. This places an increased burden on a
firm’s remaining mills.13
T

A

B

L

E

2

Price and C ost Es tim a te s fo r
Selected Steel Pro d u c ts, 19 76
and 1986
(Current dollars)

1976

Hot-Rolled Sheets
Cold-Rolled Sheets
Hot-Dipped, Galvanized
Sheets and Strip
Hot-Rolled Bars
Structurals

Average
Variable
Cost

Average
Realized
Price

Average
Total
Cost

$282.30
328.94

$229.43
288.43

$333.40
380.04

356.92
286.96
272.97

368.59
311.14
358.94

408.02
338.06
324.07

Average
Variable
Cost

Average
Realized
Price

Average
Total
Cost

$305.00
376.00

$273.04
418.21

$406.00
477.00

419.00
313.00
291.00

537.93
360.03
321.57

520.00
414.00
392.00

1986

Hot-Rolled Sheets
Cold-Rolled Sheets
Hot-Dipped, Galvanized
Sheets and Strip
Hot-Rolled Bars
Structurals

Note: T he co st data from table 1 w ere adjusted for variation in finishing
costs am on g p ro d u cts using data from W h arton E con om etrics (1987),
p. 4.7. Estimates are industry averages; costs are b o u n d to b e higher in
exiting plants.
SOURCE: Bureau o f the Census, C u rren t In d u stria l R ep orts: Steel M ill
P rod u cts, various issues.

In addition, because of the terms of pension
agreements in this industry, the pension pay­
ments are actually higher if workers retire from a
closing plant rather than from an operating mill.
Under normal circumstances, union members
are eligible for pensions after 30 years of service,
or at age 65 (with 10 years of service), or at age
60 (with 15 years of service). But for workers

laid off by plant closings, the eligibility require­
ments are eased. For instance, workers over 55,
whose age plus years of service equal at least 70,
become eligible. Also, some workers receive
supplemental pension payments of $400 per
m onth until they reach age 62, if they are laid off
by a shutdown.
By the terms of this typical labor contract, it
is clear that the size of the payments depends
crucially on the age of workers and on their
years of service. A firm might be able to reduce
the work force somewhat by attrition before
closing a plant, but under a seniority system, the
remaining workers would tend to be older, with
more years of service, which would drive up
closing costs.14
These claims raise the cost of closing steel
facilities enormously In 1979, the United States
Steel Corporation shut down a variety of mills
and parts of mills, laying off more than 11,000
workers. According to the company’s annual
reports, the total cost of the closings was
approximately $650 million, of which about
$415 million represented labor-related expenses,
implying a cost per worker of more than
$37,000. Bethlehem Steel reported similar fig­
ures in its annual report, recording a $700
million liability in 1982 when about 18,000
workers were laid off during a restructuring that
dealt principally with steel facilities.
More recent estimates show that these costs
may be higher. One study indicates that the total
cost per employee of closing a mill is $75,000, of
which $54,000 represents employee-related
closing costs (Wharton Econometrics [1987]).
Using these figures, the Bethlehem Steel restruc­
turing would currently cost $1.35 billion.
Firms cannot depend on high resale values to
cover the large closing costs. The capital is quite
specific to the industry and is of little value for
any purpose other than steelmaking. Nor are
other steel firms particularly interested in buy­
ing these plants; most integrated firms are
reducing their capacity, and minimills are build­
ing new plants. Furthermore, the equipment in a
closed plant is usually in need of major invest­
ment, since the former owner has disinvested
from it before closing.15

■

14

It is difficult to evaluate h ow these em ployee-related costs

change over tim e. T h e severance paym ent form u la does not appear
highly sensitive to the seniority profile of the plant: the m axim um sever­
ance pa ym ent is earned by w orkers with 10 years of experience. Th e
supplem ental pension pa ym ent is m ore com p licated. Th e liability w ould
increase if the n um ber of qualifying w orkers rose over tim e (w orkers

■

13

Th e problem is similar to that of Social S ecurity w hen future

qualify if their co m b ined age and years of service is over a certain

generations are smaller. W hile in 1 9 7 7 there were 2 .3 w orkers for each

m inim um ), and w ould fall if the num ber of qualifying w orkers fell over

retiree, currently there are tw o retirees for eve ry steelworker.

tim e (w orkers receive the pa ym ent only until age 62).

T

A

B

L

E

3

A verage Realized Prices of
Selected Steel Prod ucts
(Dollars per net ton)

Year

Hot-Rolled
Sheets

Cold-Rolled
Sheets

1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986

$229.43
254.15
281.10
314.87
317.30
350.12
338.79
325.53
326.01
310.35
273.04

$288.43
320.51
354.31
388.78
395.42
436.77
433.87
437.93
453.18
437.97
418.21

Hot-Dipped
Galvanized
Sheets & Strip
$368.59
392.72
430.35
468.76
487.64
532.31
525.84
525.87
560.16
536.75
537.93

Hot-Rolled
Bars

Structural

$311.14
337.23
364.26
403-38
415.90
445.83
414.94
387.38
393.49
366.89
360.03

$284.46
293.41
326.98
372.02
408.03
428.82
421.90
362.64
358.52
332.57
321.57

SOURCE: Bureau o f the Census, C u rren t In d u stria l R ep orts: Steel M ill P rod ucts, various issues.

During the industry’s contraction, there have
been few examples of closing plants sold for
continued operation as integrated steel mills.
(One notable exception is the plant in Weirton,
West Virginia. The employees purchased this
mill from National Steel and have continued
integrated production.) W hen sales do take
place, the purchasers are generally interested in
the rolling and finishing facilities, and keep steel
furnaces closed. For instance, California Steel
now imports semifinished steel for finishing at a
(formerly integrated) plant in Fontana, which it
purchased from Kaiser Steel.16
There are few opportunities to sell individual
pieces of equipment. One company reportedly
auctioned off some equipment when it went
bankrupt, and some used equipment has been
sold abroad, but no steelmaking operations have
been sold for movement. Inventories of raw
materials and parts can be distributed to other
plants, but beyond that, the equipment is likely
to sit until the price of steel scrap rises enough
to pay the junk dealer for dismantling it.

■ 15

Fro m 1960 to 1981, the average annual investm ent per ton of

capacity in m ajor pieces of steelm aking equipm ent w as $ 3 4 .0 8 in plants
w ho se closing w as an no un ced before 19 8 4 , com p ared with $ 1 2 8 .2 7 for
plants rem aining open (Deily [1988]). See Deily also for evidence that steel
firm s channeled investm ent away from plants that were least able to
com p ete with im ports and minimills, particularly during the period
1971-1981.

■ 16 See W ha rton Econ om etrics (19 8 7), p. 1 .8 , and J . Ern est Beazley,
“ Big Steel’s P u sh to E xte n d Im port Q u o ta s D ra w s D eb a te ,”

Journal,

D ece m b er 3 0 ,1 9 8 7 .

Wall Street

The last exit barrier, the durability of steel
industry capital, also works to delay plant clos­
ings by allowing the continued operation of
aging equipment without major reinvestment.
Furnaces and mills are depreciated over 15 to 20
years, but may operate for longer. For example,
table 4 indicates that the
ages of various
pieces of capital were more than 10 years in
1979, and that a significant percentage of the
equipment had been operated for more than
20 years.
O f course, operation of the equipment still
involves noncapitalized maintenance and repair
expenditures. In addition, the blast furnaces,
which provide the flow of hot metal to the steel
furnaces in an integrated plant, require periodic
relining. Blast furnaces basically operate on a
continual basis for two to eight years, depending
on their rate of utilization. But eventually the
refractory material that prevents the hot metal
from destroying the furnace must be replaced.
Figures cited for a somewhat short-term repair
process, called gunning, range from $14 million
to $18 million. Actual replacement of refractories
may cost anywhere from $20 million to $100
million, depending on the extent of the replace­
ment and furnace rebuilding, though on average
the cost will probably fall into the $20 million to
$50 million range.
Frequently, firms will postpone a reline and
leave the blast furnace idle, provided they have
another operating furnace. But there are some
limits to their ability to escape both operating
losses and closing costs by idling entire plants.
For instance, after being laid off for two years
because of idled equipment, workers eligible for

average

pensions may claim them. Also, laid-off workers
are eligible for supplemental unemployment
benefits for up to two years.
In sum, integrated steel firms appear to face
sizable exit barriers. High closing costs, consist­
ing principally of payments to employees, cur­
rently appear to be the largest barrier. Durable
capital and low resale values also work to delay
plant closings.

Average Age
of Capacity
(years)

Capacity Over 20
Years O ld
(percent)

17.3
11.0
14.3
19.0
17.5

46.9
2.3
25.3
31.5
33.3

Coke Ovens
Basic Oxygen Furnaces
Electric Furnaces
Hot Strip Mills
Aggregate*3
a. As o f January 1,1979.

b. Includes data o n o p e n hearth furnaces, plate m ills, w ire r o d mills,
c o ld strip m ills, and galvanizing lines.
SOURCES: A m erican Iron and Steel Institute (1980), p. 21. Based o n data
from The W orld Steel In d u stry D a ta H a n d b o o k , vol. 1, and the
A m erican Iron and Steel Institute.

IV. Im plications fo r
Public Policy

The data presented here suggest that the decline
of the steel industry has been painful and pro­
longed because of large closing costs and high
exit barriers created by the technology of the
production process. Although these barriers
have delayed closings, resulting in lower profits
and antiquated capital stocks in some plants, the
necessary reduction of U.S. integrated steel
capacity has been taking place, albeit slowly.
Is there any need for policies aimed at raising
or lowering exit barriers? Although different
firms, workers, stockholders, and communities
could gain or lose, it is not at all clear that the
economy as a whole benefits from either hasten­
ing or delaying plant closings. However, public
policy in at least two areas of recent concern
may have a strong impact on the steel industry’s
exit barriers.
First, the pension-insurance program affects
exit barriers in the steel industry by altering the
cost of closing plants. The Pension Benefit Guar­
anty Corporation (PBGC), a federally chartered

agency that insures all workers with definedbenefit pensions, has already assumed some of
the industry’s plant closing costs and may ulti­
mately assume more. As stated previously, pen­
sion liabilities are a major part of the cost of
closing. A firm that desires to close plants, but
that cannot afford to do so, may find that
declaring bankruptcy is the cheapest way to
reduce capacity, because the PBGC becomes
responsible for the firm’s pension liabilities.17
Thus, at least potentially, the PBGC could end
up paying the pension liability portion of some
firms’ closing costs, thereby speeding up plant
closings by lowering this particular exit barrier.18
The situation has become more uncertain, how­
ever, because of the recent and still-unresolved
differences between the PBGC and LTV Steel
over responsibility for the latter’s pension lia­
bilities. Since this uncertainty makes it more
difficult for firms to evaluate plant-closing deci­
sions, it is important for policymakers to clarify
w ho will ultimately pay these liabilities.
Policies to protect the industry from imports,
on the other hand, may raise the exit barriers
that steel firms face. The industry is currently
protected by five-year Voluntary Restraint Agree­
ments that the Reagan administration has negoti­
ated with a number of steel-exporting countries.
In the short run, the effect of the quotas may be
to delay plant closings if the protection causes
the industry to upwardly revise the expected
revenues of its plants.
The long-run effects of the legislation are less
clear. Firms are unlikely to reverse their long-run
disinvestment from marginal plants unless they
are convinced that the profitability of these
plants has increased permanently. Such an
assurance would require at least that the govern­
ment make a long-term commitment to trade
protection for the industry. But such a com m it­
ment would be expensive for domestic indus­
tries that use steel, and would by no means rule
out further capacity reductions, since the minimill sector will continue to grow.

■

1 7 See B uynak (19 8 7) for a description of the limits on the am o u n t of

the firm ’s assets that the P B G C can claim to cover unfunded pension
liabilities.

■ 18 Indeed, since the m axim u m paym ent the P B G C m akes to
w orkers m ay be well below w orkers’ contracted p en sion s, and since
supplem ental paym ents for early retirement are not covered, the total
cost of closing plants w ould be lower, thou g h at the direct expen se of
the em ployees.

What public policy should not be doing is
forcing reinvestment in the steel industry The
most misguided aspect of the trade protection
currently in place is its requirement that the
industry reinvest its net cash flow from steel
businesses back into steel plants (Steel Import
Stabilization Act of 1984,19 U.S.C. 2253). The
result of this directive may be to force invest­
ment in plants that will never yield an adequate
return, a circumstance that will increase plant
owners’ losses when the plants are eventually
closed.
Lack of reinvestment is not the underlying
problem of the steel industry. Although invest­
ment in the plants that will survive is essential to
their competitiveness, it is clear that additional
capacity will eventually close. But shutdowns
will be delayed as long as steel firms find that
exit barriers make continued operation of mar­
ginal plants less costly than closing.

REFER EN C ES

Up
from the Ashes: the Rise of the Steel Minimill
in the United States. Washington, D.C.: The

Barnett, Donald F., and Robert W. Crandall.

Brookings Institution, 1986.

Steel:

Barnett, Donald F., and Louis Schorsch.
Cambridge,
MA: Ballinger Publishing Co., 1983.

Upheaval in a Basic Industry.

Beazley, J. Ernest. ‘Agency in Crisis: Bankruptcy
Filings in Steel Overwhelm U.S. Pension
Insurer.”
May 21,1987,

Wall StreetJournal.

pi.

Buynak, Thomas M. “Is the U.S. Pension-Insurance System Going Broke?”
Federal Reserve Bank of Cleveland.
January 15,1987.

Economic Com­

mentary.

Caves, Richard E., and Michael E. Porter. “Bar­
riers to Exit.” In R.T. Masson and P. David
Qualls, eds.,
Cambridge, MA:
Ballinger Publishing Co., 1976.

Essays on Industrial Organiza­
tion in Honor of Joe S. Bain.

The U.S. Steel Industry in
Recurrent Crisis: Policy Options in a Com­
petitive World. Washington, D.C.: The Brook­

Crandall, Robert W

ings Institution, 1981.
Deily, Mary E. “Investment Activity and the
Exit Decision.”
(1988— forthcoming).

Statistics.

Review of Economics and

TheJapanese Steel Industry,
with an Analysis of the U.S. Steel Import
Problem. New York: Praeger, 1972.
Lamfalussy, Alexandre. Investment and Growth
in Mature Economies: The Case of Belgium.
Kawahito, Kiyoshi.

New York: St. Martin’s Press, 1961.
Lawrence, Robert Z., and Robert E. Litan.

Saving Free Trade: A Pragmatic Approach.
Washington, D.C.: The Brookings Institution,

1986

.

Littman, Daniel A., and Myung-Hoon Lee.
“Plant Closings and Worker Dislocation.”
Federal Reserve Bank
of Cleveland. (Fall 1983): 2-18.

Economic Review.

Miller, Jack R. “Steel Minimills.”
250(1984:5): 32-39.

can.

Scientific Ameri­

Porter, Michael E. “Please Note Location of
Nearest Exit: Exit Barriers and Planning.”
19 (1976:2):

California Management Review.

21-33.

The Theory o f Price,

Stigler, George J.
Third
Edition. New York: Macmillan Co., 1966.

United States Council on Wage and Price Sta­
bility.

Report to the President on Prices and
Costs in the United States Steel Industry.

Washington, D.C.: U.S. Government Printing
Office, October 1977.
United States Department of Commerce,
Bureau of the Census.
Series MA-33B.
Washington, D.C.: U.S. Government Printing
Office, various issues.

Current Industrial
Reports: Steel Mill Products.

Pension Agree­
ment Between United States Steel Corporation
and United Steelworkers of America. Effec­

United States Steel Corporation.

tive July 31,1980. Document supplied by the
United Steelworkers.

Restructuring and
Revival: The World Steel Industry, 1987-2000.

W harton Econometrics.

Volume III, Part II. Bala Cynwyd, Pennsylva­
nia: Wharton Econometrics, 1987.

W hy Do W ages Vary
A m ong Em ployers?
by E rica L. G roshen
Erica L . G rosh en is an econom ist at
the Federal Reserve B ank of
C leveland. Th e author would like to
thank Jo h n T. D u n lo p , Richard B.
F re e m a n , and Law re nce H . S u m m e rs
for their co m m en ts and suppo rt on
earlier versions. T h e paper also
benefited from suggestions by M a ry
Deily, Randall W . E b e rts , and Law re nce
F. Katz.

Introduction

In neoclassical economics, wage rates— like
the price of any traded com m odity— are deter­
mined by both supply and demand. Despite the
simultaneous nature of the wage-setting process,
recent empirical investigations of the determi­
nants of wages have focused primarily on factors
affecting labor supply. Demand factors have
been relatively neglected.
During the 1940s and 1950s, participation in
the administration of wage and price controls
led a distinguished group of economists to
examine employer wage policies. Reynolds,
Segal, Dunlop, Myers, Lester, and Lewis studied
interindustry, intra-industry, union, establish­
ment size, and regional differentials.1 In
essence, they focused on variables controlled by
employers (that is,
and mediumrun labor supply. Dunlop (1957) summarizes
many of these effects in his work on wage
contours.
Research on the influence of supply-side fac­
tors was stimulated by the development of
human capital theory (Becker [1964] and Mincer
[1974]), and by the availability of household

labor demand)

surveys, which gather more information on
workers than on their employers. Since the
1960s, labor economists have primarily studied
variables controlled by employees (that is, longrun
factors) such as age, education,
and experience.
In the Current Population Survey, a house­
hold survey, regressions of wages on workers’
characteristics typically produce results similar
to those shown in table 1. In this example, the
explanatory power of human capital variables is
enhanced by exclusion of agricultural workers
and of the youngest and oldest workers from the
sample. Even within this limited population, the
narrowly defined human capital variables
explain only a quarter of the variation in the log
of wages.2 Addition of occupation raises explan­
atory power by 16 percent, while race, sex, and
union variables add another 6 percent. Industry
(broadly defined) raises explanatory power to 51
percent of the variation of wages.
What accounts for the 49 percent of wage
variation that the equation doesn’t explain? Are
there other empirical regularities or theories that

labor supply

■

2 Th e explanatory pow er of hum an capital variables reported
1 is actually relatively high co m p are d to that fou n d in m any

in

table

■

1 Segal

econom ists.

(1986) and Kerr (1983) su m m arize the w ork of these

sam ples because of exclusion of yo un ger and older w orkers and of
agricultural w orkers.

explain the residual variation? And, are we cer­
tain that industry, unionism, race, and sex reflect
differing ability on the part of workers?
This study reviews empirical evidence in
support of demand-related wage differentials,
which suggests that different employers pay
T

A

B

L

E

In none of these cases is the presence of
employer differentials inconsistent with profit
maximization on the part of employers. How­
ever, the last two theories predict the existence
of queues for high-wage employers while, in the
other three models, employer differentials are
associated with market clearance.

1

Typical C ross-Sectional W age
Regression Results in the

I. Em pirical Evidence
on Two Types of
Interem ployer W age
Effe c ts

C urrent Population Survey

Regressors_______________________________________________R ^
Years of Education, Age, Age Squared

.26

Years of Education, Age, Age Squared,
Occupation (2-digit)

.42

Years of Education, Age, Age Squared,
Occupation, Race, Sex, Union

.48

Years of Education, Age, Age Squared,
Occupation,
Race, Sex, Union,
Industry (2-digit)

.51

Note: D ep en d en t variable was log (h ou rly earnings). Mean: 2.0 5, standard
deviation: 0.5 5. N um ber o f observations: 150,579.
S ource: Current Population Survey O ne-Q uarter Earnings Sample, 1986.
Sample includes all p e o p le em p lo y e d in nonagricultural industries for
wages and salaries, aged 18-54.

different wages to workers of equal ability. This
result is at odds with the predictions of the
simple competitive model of wage determina­
tion. Where does the model fail: in assumptions
of worker or job uniformity, or of full informa­
tion in the labor market? These questions are
particularly relevant because employer wage dif­
ferences may be at the root of the observed
unequal earnings between men and women, or
among racial or ethnic groups. If these wage
differentials arise from efficient, profit-maximiz­
ing behavior by firms in a second-best world,
which policies for reducing inequality are likely
to be most effective and efficiency-enhancing?
The answers to these questions rest in identi­
fying the source(s) of employer differentials.
This paper discusses five sources of employer
wage differentials: 1) employers systematically
sort workers by unmeasured ability; 2) wages
vary because of unnoted compensating differen­
tials; 3) costly information generates or perpetu­
ates random variations in wages; 4) the efficient
wage for some employers is above the market
rate; and 5) workers inside firms exercise a claim
on rents.

The focus of this paper is on employer wage
differentials: wage differences accruing, on aver­
age, to all employees at an establishment. For
example, in a regression, these are estimated as
the coefficients on establishment dummies, con­
trolling for occupation. These differentials cap­
ture all differences in labor demand among
employers.3
Empirical studies of how wages vary among
employers can be divided into two groups:
between-industry studies and within-industry
studies. Wage variation
has
been the subject of much scrutiny and specula­
tion. Far less attention has been paid to wage
variation by employers
even
though wage variation among industries implies
variation among employers within industry for
two reasons.
The first reason is that industry is not
uniquely defined. By some criteria, the dif­
ferences among industries are continuous,
rather than categorical. Since no industrial
classification system captures all relevant dif­
ferences among product markets, sources of
wage variation among industries should be
detectable within industry as well. If explana-

among industries
within industry,

■

3

Industrial relations distinguishes between two co m p o n e n ts of w age

determ ination in an enterprise: (1) form ation of co m p ensation policy (the
periodic adjustm ent of w age and benefit schedules and rules) and (2) the
adm inistration of policy (day-to-day decisions about hiring, piece rates,
o vertim e, layoffs, discipline, pro m otio ns, etc.). T h is research does not
distinguish the im pact of w age schedules from that of personnel
adm inistration; it reports total (or net) observed effects. T h u s , the
differentials investigated could be the product of differences of policy,
adm inistration, or both . F o r exam p le , D u n lo p (1982a) notes: “ ... quite
apart from periodic ch an ges in the schedule of w ag es , salaries or
benefits, the adm inistration of these elem ents of the schedule and other
rules of the w orkplace, from day-to-day, will significantly affect average
costs and earnings.”
In the discussion that follo w s, the term “ w ages” will be used in terchange­
ably with "h o u rly earnings” , even th ou g h this blurs an im portant
distinction. W ag es are the product of policy and apply only to
nonincentive w orkers. Ea rn in g s are the product of adm inistration of
policy and apply to all w orkers, including incentive w orkers.

tions of wage variation based on characteristics
of industries are correct, we should see support­
ing evidence among establishments within
industry. Furthermore, tests within industry for
these effects may avoid problems of omitted
variables (or of confounding influences).
Second, we expect wage variation among
employers within industries because even welldefined industries are not homogeneous. Some
wage-relevant factors vary greatly within indus­
try even though they do not vary m uch among
industries. Size of establishment is a good exam­
ple. Because of this, explanations of wage levels
based on industry aggregate data understate the
economy-wide importance of factors that vary
primarily within industry.
In short, the forces that generate betweenindustry wage variation should also operate
within industry. Since looking only among
industries to understand employer variation may
be misleading because of omitted variable or
1 T

A

B

L

E

aggregation biases, a full understanding of the
association between employer and wages
requires study of both inter- and intra-industry
wage variation by employer.4

A . Betw een-lnuustry
Differentials

Table 2 summarizes a selection of the literature
on wage differentials among industries. The
studies document the existence, persistence and
some of the characteristics of industry wage
differentials. They also propose and test models
for industry differential formation. The two
Dickens and Katz studies provide the most
recent and exhaustive investigations of the char­
acteristics of industry wage differentials. They
conclude that wage differences among indus­
tries account for 7 to 30 percent of wage
variation among individuals.

2

Sam ple of Em pirical Studies
of Industry W age Effe c ts

Authors and Year
1. Slichter (1950)

Data
Survey of laborers in Cleveland; National
Industrial Conference survey of wages of
skilled and unskilled workers

Relevant Conclusions
Industry differentials are consistent
across skill levels, increase with propor­
tion male, vary positively with value
added, decrease with labor intensity,
vary positively with post-tax corporate
income, and are fairly stable over time.

2. Garbarino (1950)

BLS productivity and labor cost data for
entire industries

Productivity and concentration are
positively correlated with pay changes
across industries.

3. Reynolds and Taft
(1956)

Published data for four industries (three
unionized) in the U.S., and various European
countries and Canada

Wages vary considerably between plants
(within industry, region, and occupa­
tion), depending on the competitive
position and wage policies of employers.
Unionism decreases these variations, but
substantial industry, geographical, and
occupation differentials persist.

4. Weiss (1966)

I960 U.S. Census merged with information
on industry concentration, average establish­
ment size, and unionization

Earnings increase with concentration,
but inclusion of personal characteristics
and weeks worked diminishes and often
eliminates the effect.

5. Rosen (1969)

I960 U.S. Census-industry aggregates
standardized for occupation

In a two-stage least-squares model, size
of establishment influences demand
price for labor, but not supply price.

6. Wachter (1970)

“Employment and Earnings” aggregate
industry statistics

Coefficient of variation of industry aver­
age wages (unadjusted for occupational
composition) increases with unemploy­
ment and cost of living. High-wage indus­
tries increase wages first and allow them
to fall last.

Sam ple of Em pirical Studies
of Industry W age Effe c ts

Authors and Year
7. Waehtel and Betsey
(1972)

Survey of Consumer Finances (1967),
Institute for Social Research sample of full­
time, full-year service and production
workers

Residuals of human capital wage regres­
sions (with age, sex, race, job tenure,
education, and marital status) are highly
correlated with industry-occupation,
union status, city size, and region dum ­
mies. Conclude that these structural
(demand-side) variables, especially indus­
try-occupation, are important determi­
nants of wages because of rigidities in
the labor market.

8. Dalton and Ford
(1977)

1970 U.S. Census sample

Industry earnings increase with con­
centration up to a ratio of 0.5, after
which they are stable. Sex and race
differentials are large and significant for
high concentration industries, while
industry growth rate affects wages only
in the more competitive industries.
Regional differentials were significant
but had changed since I960.

9. Pugel (1980)

IRS profits by 3-digit industry, merged with
industry average demographic and market
data

Workers receive 7 percent to 14 percent
of total excess profits: some of which buys
higher skills, the rest of which is rent.

10. Krueger and Sum­
mers (1986a,b)

CPS, May 1974, 1979 and 1984; Quality of
Employment Survey 1977

Industry wage differentials do not disap­
pear when controlling for measured or
unmeasured differences in human cap­
ital or for compensating differentials.
Consistent with efficiency-wage models,
lower turnover and better performance
are apparently characteristic of highwage industries.

11. Dickens and Katz
(1986, 1987)

Current Population Surveys
respondents for 1983

■

4

all nonunion

A further exam ple of the co m p lexity of the subject is that this

discussion assum e s that m ost establishm ents operate within a single
industry and their w ages reflect the patterns of the in dustry alone. This is
a sim plification that abstracts from v e ry real e xam ple s. F o r instance, drug
shelf stockers in superm arkets are paid the low w ages co m m o n to drug
stores rather than higher superm arket rates. In these cases, even the
establishm ent is too high a level of aggregation.

Divided workers into 12 occupational
categories, calculated industry wage
differentials in raw data, fixed effects
equations (with human capital) and from
residuals of human capital equations.
Found that industry differentials are
large, persistent, and correlated across
occupations and countries. They are also
correlated with industry characteristics:
percent male, average education, quit
rates, and measures of product market
power and profitability. Conclude that
simple competitive models are not con­
sistent with observed patterns.

While evidence on the source(s) of the differ­
entials remains inconclusive, a strong link
between industry differentials and industrial
concentration (or profit rates) is found in all
studies that search for it (Slichter, Garbarino,
Reynolds and Taft, Dalton and Ford, Pugel, and
Dickens and Katz), except Weiss. Krueger and
Summers find links between differentials and
the predictions of efficiency wage models (lower
turnover and higher effort).

B . W ith in-ln du stry
D ifferentials

Table 3 summarizes a selection of the empirical
literature that provides evidence of the existence
of large wage differentials among firms and
among plants.5 The first studies are case studies,
where many of the issues explored singly below
are investigated for a single labor market. The
first two studies are particularly valuable because
they use data with unusually rich information on
both worker and firm characteristics. Both stud­
ies find significant differentials among firms.
Reynolds concludes that firms select the general
wage level on which they operate until forced to
change. Rees and Schultz estimate the individual
and establishment effect on wages for four
groups of occupations and find systematic dif­
ferences among firms that are not consistent
across all occupations.
Mackay, et al., Nolan and Brown, and Brown,
et al. are fairly recent case studies of English and
Australian labor markets. They find that wage
variation by plant is a large and fundamental
component of wage dispersion, and that
employer wage differences are persistent over
time and are linked to plant performance.
Like the English and Australian studies,
Groshen (1988a) focuses on the entire employer
differential within industry rather than on the
portion associated with a particular charac­
teristic. She finds that a random switch in
employer, within detailed occupational category
and industry, is associated with an expected
wage change of 12 percent. She also finds that
employer size, gender composition, and indus­
try sector are associated with wage level. How­
ever, it is unlikely that measures of human
capital such as experience, tenure, or education
explain the observed establishment differentials.
Groshen (1988b) finds that these interemployer
wage differences are virtually stationary over six
years and present within a single metropolitan
statistical area. Hodson matches U.S. household
survey data with employer information and finds
employer characteristics to be strongly signifi­
cant predictors of wages.
Investigations of employer size and gender
composition wage differentials, such as those
listed in table 3, are a dimension of the work on
employer differentials because they select one
aspect of establishment differentials for examina-

■

5

F o r a survey of the literature and the em pirical problem s

associated with m easuring a related issue, the relationship between
com pensation and firm perform ance, see Ehrenb erg and M ilkovich
(1987).

tion. The explanations for these phenomena
must also come from the theories explored
below. The worker-quality differential studies,
by Evans and Conant, are of interest because
they argue against sorting by ability or human
capital.
Finally, the last two intra-establishment stud­
ies suggest that although interoccupational dif­
ferentials are compressed within establishments,
they do have the same patterns. Thus, establish­
ment effects are fairly, but not exactly, uniform
across occupations.
In summary, these studies provide strong
evidence that within-occupation interemployer
differentials exist, and that they are associated
with measurable attributes of employers, such as
firm or plant size.

II. Sources of W age
Differentials Am ong
Em ployers

This section summarizes five models that
explain why an employer might pay a wage
premium to all of its employees rather than to
particular individuals. These theories are based
on the rigorous models of particular economic
relationships that have been developed since the
1960s. Virtually all of the ideas in the following
discussion can be found in the work of earlier
economists, but were later formalized by, and
are here referenced to, other authors.

A . The Role of
Em ployers in the Basic
M odel of W age
Determ ination

The point of departure for the models of em­
ployer wage effects listed below is basic Mar­
shallian supply and demand. I begin by noting
that in a perfectly competitive labor market with
costless contracting and information, and with
identical workers and jobs, no differentials
based on differences in labor demand
would arise.
Market labor supply is a function of leisure
preferences, population supply, and training
costs. Market labor demand is the horizontal
sum of all employers’ demand curves, that is, the
marginal revenue product of hours worked.
Under perfect competition in capital and labor
markets, equivalent workers at equivalent jobs
earn the same wage. An employer whose wages
stray from the market rate will be forced out of
business by loss of employees (wages set too

□

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Sam ple of Em pirical Studies
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W age Effe c ts

Authors and Year
Data
CASE STUDIES AND MORE GENERAL STUDIES OF INTEREMPLOYER
Case study of an urban blue-collar labor
1. Reynolds (1951)
market based on worker interviews and data
published by other sources

DIFFERENTIALS
Plant wage-level depends on industry,
unusual efficiency of plant or manage­
ment, secure monopoly or oligopoly
control of product market, and history
of relative wages. Most wage move­
ments occur uniformly within clusters
of firms. Plants operate within a range
of feasible wage rates, but movement
within the band is difficult.

2. Rees and Schultz
(1970)

Personnel records from 75 Chicago establish­
ments on 13 occupations, white- and bluecollar, skilled and unskilled; interviews with
management personnel and workers

Industry differentials vary in size and
sign across occupations, and are smaller
for skilled workers. No positive relation­
ship between establishment size and
wages, within occupation, industry,
location, and controlling for work char­
acteristics. Location differentials are
uniform across occupation.

3. Mackay, et al. (1971)

Mean earnings and quit rates by occupation
from personnel records for blue-collar work­
ers in 66 engineering plants in Birmingham
and Glasgow from 1959 to 1966.

W ithin occupation, inter-plant coeffi­
cients of variation ranged from 16
percent to 23 percent and rank order
correlations (from 1959 to 1966) were
about 0.9, except for laborers. Wages
were negatively correlated with quits,
but unrelated to changes in plant size.
Investigations of causes led to rejection
of sorting by human capital, of random
variations, and of working conditions.
Concluded that efficiency wages for
quit rates and profit-sharing were most
likely sources.

4. Hodson (1983)

Wisconsin 1975 survey of high-school gradu­ Corporate structure variables (size,
ates from 1957, matched with employer
international links, capital intensity)
information
strongly affect wages. Product market
variables (profits, productivity) have
little impact.

5. Nolan and Brown
(1983)

10-year survey of wage structure for seven
occupations in 25 factories in West Midlands,
England

Employer effects on wage changes dom ­
inate occupation effects. Nevertheless,
rankings by employer are relatively
stable across occupation over 10 years;
rank correlations of 0.8 to 0.9.

6. Brown, et al. (1984)

Survey of 44 occupations in 198 plants in
Adelaide, Australia

Overawards to Australian workers tend
to be tied to establishment rather than
to occupation. Industrial concentration
is highly correlated with size of
overawards.

BLS Industry Wage Surveys of production
workers’ wages in six manufacturing
industries

W ithin detailed job classification,
wage variation between establishments
accounts for 30-60 percent of wage
variation, generating a standard
deviation of 11 percent. Half of the
differentials were associated with
characteristics of the establishments
(size, union affiliation, etc.).

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Sam ple of Em pirical Studies
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W age Effe c ts

Authors and Year
8. Groshen (1988b)

Data
BLS Area Wage Surveys of nonsupervisory
workers’ wages (blue-collar and white-collar)
in one SMSA for six years

W ithin detailed job classification,
wage variation between establishments
accounts for 20-70 percent of wage
variation, generating a standard devia­
tion of 12 percent. Differentials were
unchanged over six years and not
associated with growth or shrinkage.

WORKER QUALITY DIFFERENTIALS, WITHIN OCCUPATION, BETWEEN ESTABLISHMENTS
Across establishments, the strongest
Private area wage and salary survey of
1. Evans (I960)
observed relationship was between
clerical workers in Boston
wages and length of service. Test
scores and education are inconsistent
predictors of wages.
2. Conant(1963)

Placement test scores and beginning salaries
for typists in Madison, W I

Test scores accounted for only 10 per­
cent of the variation in starting wages
offered by different employers to entry
level typists.

ESTABLISHMENT AND FIRM SIZE DIFFERENTIALS
BLS Establishment Surveys— Wages and Hour Hourly earnings are higher in large
1. Perlman (1940)
firms, within industry, occupation,
Statistics for six industries
product group, and region. Hourly
earnings are not affected by establish­
ment size, holding region constant.
2. Lester (1967)

BLS Industry Wage Survey and Census of
Manufactures

Except for textiles, apparel and aircraft,
earnings increase with establishment
size. Differentials increase when fringe
benefits are included.

3. Masters (1969)

BLS Census of Manufactures

Plant size variable is a stronger (larger
and more significant) determinant of
average wage differences among indus­
tries than concentration.

4. Buckley (1979)

BLS Area Wage Surveys for 29 areas

Controlling for industry mix, wages
rise with area cost of living, but not
with establishment size.

5. Miller (1981)

BLS Census of Manufactures

Controlling for industry, wages
increase with size of establishment.

6. Personick and Barsky BLS National Survey of Professional,
(1982)
Technical, and Clerical Pay 1980

Pay levels tend to increase with em­
ployer size, but above-average levels are
associated only with large firms. Wage
premia attributable to a firm’s size are
larger for entry-level than for experi­
enced professional workers. Corporate
size has better explanatory power for
professionals while establishment size
does better for clerical workers.

7. Mellow (1982)

Both plant size and firm size are
positively associated with wages, con­
trolling for personal characteristics and
concentration. The effect is propor­
tionately larger when fringe benefits
are included. Industry-plant size inter­
action variables were insignificant.

Current Population Survey 1979

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A Sam ple of Em pirical Studies of
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W age Effe c ts

Authors and Year
8. D unn (1980, 1984)

Data
Independent surveys of employee wages,
working conditions, and employer size
within one industry

9. Brown and Medoff
(1987)

Variety of public sources

Firm and plant size are associated with
higher wages, controlling for occupa­
tion, industry, and working conditions.
Differentials are smaller for highergrade occupations.

MALE/FEMALE COMPOSITION OF OCCUPATIONS WITHIN FIRMS
1. Blau (1977)
BLS Area Wage Surveys

INTRA-ESTABLISHMENT OCCUPATIONAL DIFFERENTIALS
1. Ward (1980)
BLS Area Wage Surveys

2. Van Giezen (1982)

BLS Area and Industry Wage Surveys

low) or the loss of capital (wages set too high).
The position that employers are price-takers
is the theoretical basis for the current focus on
labor supply as the only relevant determinant of
wages. The employer in a competitive labor
market faces a horizontal labor supply curve, as
shown in figure 1. In the figure, Employer 1 has
labor demand curve D ,, which differs from the
labor demand curve of Employer 2 (labeled D 2).
However, because they face a flat labor supply
curve (Ls), the differences between the two
employers affect only their employment levels
(E[ versus E2), not their relative wages. Thus,
the simple competitive model generates an
empirically testable prediction: variations in
labor demand should affect only quantity
demanded, not wage level. This is true so long as
demand differences do not affect worker utility.
The empirical work summarized above sug­
gests that this simple model does not hold.
Wages do vary among employers. In order to

Large firms pay higher wages and shift
premia than small firms, except in the
highest-paid occupations. Compensat­
ing differentials do not appear to be the
cause; infers the presence of
bargaining.

W ithin occupation, establishments
tend to be segregated by sex; pay rates
are negatively associated with percent­
age of establishment female. Occupa­
tional segregation by sex is associated
with industry.
National occupational wage spreads do
not exactly mirror individual firms;
pay differentials are smaller within
establishments.
Area occupational differentials are
larger than intra-firm differentials.
Intra-firm differentials vary by industry
and region, and decrease with estab­
lishment size, although differences are
small.

extend the simple model to allow for apparent
demand-side effects, any explanation of wage
variation by employer must answer two crucial
questions: (1) why would one employer choose
to pay more than another, and (2) why don’t
high-wage employers go out of business?
The answer to the first question is usually
that a firm paying higher wages employs more
productive workers. The advantage of the pro­
ductivity explanation is that it also answers the
second question. The disadvantage is that pro­
ductivity differentials are usually due to individ­
uals’ abilities, not to employers’ characteristics,
implying the need for more explanation. If prod­
uctivity differentials are not invoked, costly
information or imperfect competition in the pro­
duct market must be present and, again, operate
similarly on all individuals in an establishment.

□
F

I

G

U

R

E

1

The La b o r Supply Curve Facing
an Individual Firm is Assum ed to
be Infinitely Ela stic

1 . Sorting by A b ility:
Innate Differences,
Hum an C ap ital, and
M atching

The first two explanations relax the assumption
of uniformity among workers or jobs in the
market. Since the labor market is perfectly com­
petitive, workers earn the marginal product of
their work and employers pay equivalent wages
per efficiency-unit of work. However, hourly
wages may mismeasure either the workers’ units
of work (because this varies among workers) or
their compensation (because it omits nonpecuniary returns to employment). In order to
generate
differentials rather than
just
differentials, the theories must
also explain why the marginal product of work­
ers varies among employers.
Sorting models assume that some workers are
more productive than others, and employers
consistently hire their workers from a single
quality stratum, regardless of occupation. The
source of quality difference may be innate
advantages (for example, genetic or moti­
vational), or acquired differences (for example,
education or work experience). Each establish­
ment hires only the best, or only the worst,
workers of each job category.
, it is not obvious why an establish­
ment would need or choose to segregate by
ability. If all workers were paid their marginal
products, the number of workers paid to pro­
duce a certain product should be irrelevant.
For example, employers should be indifferent
between two equally productive workers at one
wage and a single doubly-productive worker at
twice the wage. Any establishment could have a
distribution of productivity levels (all rewarded
accordingly) within each occupation. In this sort
of world, no apparent establishment differentials
would arise.
In order for innate or acquired productivity
differences to generate apparent establishment
differentials, employers must choose workers of
fairly uniform productivity within occupations,
and apply this policy similarly to all occupa­
tions. That is, this theory must be combined
with an explanation for segregation by firm.
Two questions arise: why and how?
The most convincing reason may be that
employers’ technologies are differentially sen­
sitive to a worker’s ability. In this case, employ­
ees of high ability w ho are not being rewarded
for their higher ability by employers with abilityinsensitive technology have an incentive to seek
out employers w ho will pay according to ability.
This leads to a positive correlation between the

establishment
individual

Source: Author.

B . Five M odels of
Em ployer D ifferentials

Table 4 summarizes five microeconomic sources
of wage variation. Each source is developed
from the competitive model by the introduction
of transaction costs and/or of heterogeneity
among agents. The table also lists the basic
assumptions beyond those of the competitive
model, and the additional assumptions neces­
sary for the models to predict the existence of
apparent
wage differentials, rather
than differentials among individuals or among
occupations.
Each of the models examined predicts
the existence of wage dispersion, and can be
extended to predict employer-based dispersion,
though the extensions usually involve extra
twists of varying plausibility. Although none of
the five models relaxes the assumption of profit
maximization on the part of employers, they are
arranged in order of their divergence from com­
petitive theory in other aspects. In particular, the
last two models, efficiency wages and bargain­
ing, require assumptions of imperfections or
lack of competition in the product or labor
markets because they imply the existence of job
rationing or queues for high-wage employers.

employer

A priori

ability-sensitivity of the employer’s technology
and the average quality of their applicant pool.
Thus, employers with ability-sensitive technolo­
gies hire disproportionately more high-ability
workers and, therefore, pay higher wages.6

For example, establishments requiring tech­
nical typing are likely to be highly sensitive to
the skills of typists. So, we expect such employ­
ers to reward an excellent technical typist more
than would employers w ho needed only text

M icroeconom ic Sources of
Em ployer W age D iffe re ntia ls

Wage
Equation1

Model

Costly
Factor(s)

Source(s) of
Heterogeneity

Additional Assumptions Necessary
for Existence of
______Employer Wage Effects______

SORTING BY ABILITY
w = MP

Human Capital,
Innate Differences,
Job Matching

Training

Innate or
acquired worker
quality,
quality of job
match

Establishments differ systematically
by average quality of workers, or
match, consistently across all or
most occupations.

w = MP

Improvement
of undesirable
terms of
employment

Management
strategies
or technologies

Undesirable terms of employment
are uniform across all or most
occupations within establishment.

w = MP + e

Employer and/or Random draws
worker search, from the pool,
job mobility
intertemporal
wage variation

Employers vary in the average value
of their draws, employers hire
for all occupations during
growth surges.

MP = f(w)w* = MP*

Monitoring of
workers’ effort,
turnover, design
of internal wage
structure, firmspecific training

Management
strategies
or technologies,
corporate size

Employers adopt similar strategies
(or technology has a similar effect)
on the efficient wage across all or
most occupations, workers in most
occupations develop firm-specific
training.

w = MP +
f(7r,workers’
bargaining
power)

Monitoring of
workers and/or
of management

Varying rents,
Rent capture is achieved and/or
ability of workers shared by all or most occupations,
to capture
rents, and/or
managerial
altruism

COMPENSATING DIFFERENTIALS
Working Conditions,
Fringe Benefits,
Risk of Layoff

RANDOM VARIATIONS
Information, Search,
Lagged Adjustment

e~f(0,a2)

EFFICIENCY WAGES
Monitoring, Turnover,
Market Insulation,
Corporate Consistency,
Morale, Loyalty

BARGAINING
Insider/Outsider,
Rent Capture,
Gain-Sharing

■

1 Th e

s ym b o ls in this colum n are defined as:

w =w age
M P = m a r g in a l revenue product
e = r a n d o m error te rm , distributed with m ean of

0

and variance of

f ( * ) = s o m e function of *
w ,* M P * = t h e unique profit-m axim izing values of w and M P
tt=

profits

a2

□
typing. The higher pay for skills will, in turn,
attract other typists with technical skills into the
applicant pools for employers needing technical
typing. In order to create establishment differen­
tials, this explanation must be expanded by the
assumption that ability-sensitivity in establish­
ments is highly correlated across occupations.
Otherwise, wage variation would occur pri­
marily by occupation within establishment, not
by establishment across all occupations. Thus,
in the example, the need for technical typing
must be associated with ability-sensitivity in
other occupations.
The second explanation is not mutually
exclusive with the first and could provide a
rationale for the correlation in ability-sensitivity
across occupations. This model assumes that
variation in the quality of workers in an estab­
lishment imposes negative externalities on the
productivity of more able workers. Envision
establishments as assembly lines where work
stations are indivisible, or where the timing of
the output depends on the speed of the slowest
operative. Then, the productivity of the slowest
worker determines the productivity of all the
workers. As workers seek their best-paying job,
establishments become segregated by quality.7
Employers maximize profits by hiring or retain­
ing (through their recruitment and termination
policies) only those workers at least as able as
those in their existing work force.
Job matching provides another approach
within the sorting models (Jovanovic [1979]).
Here, both worker and employer are unin­
formed about the worker’s productivity in a
particular job, until both have experienced it.
The productivity of a worker-job combination is
random, with a distribution known to both
sides. Workers accept jobs that pay more than
their current jobs. Employers offer wages based
on the mean of the distribution, and later adjust
wages to reflect measured productivity. Accu­
racy of productivity measurement improves as

tenure increases. Employees with bad matches
eventually leave in hope of finding a better
match elsewhere. Then differences in the dis­
tribution of productivity across employers could
lead to sorting.8
Other explanations for sorting come from the
sociology literature on the joint productivity of
teams as a product of the uniformity of team
members. In all versions, all employers (whether
high- or low-wage) earn zero or equal profits in
equilibrium. But, high-wage/high-productivity
employers are not associated with higher or
lower profit levels than their low-wage/ lowproductivity competitors. Only consistency
matters.
The human capital model, formalized by
Becker (1964) and Mincer (1974), provides a
rationale for the variance of wages according to
acquired training. Training increases productiv­
ity, raising the demand curve for hours of trained
persons’ time over that for untrained people.
However, the costs of training, such as forgone
wages and tuition, raise the supply curve for
trained persons’ time. Thus, the price of trained
labor is higher than that of untrained labor and
reflects the difference in marginal product
between the two.
If human capital differences are manifested as
employer differentials, employers must be able
to predict productivity on the basis of acquired
training (education and seniority), and both hire
and pay workers accordingly. High-wage employ­
ers are such because they select the most highly
trained workers in each occupational category.
Low-wage employers hire (or end up with) work­
ers with the least training across the board.9
Innate differences in productivity (for exam­
ple, due to perseverance, or motivation) are less
amenable to measurement by all parties, and are
not included in the data bases generally available
to economists. As such, they can only be investi­
gated indirectly However, if these innate qualities

■ 8 Fo r instance, s u p po se that all jobs had the sam e expected

■ 6 M odels of self-selection and sectoral choice w here the sectors

productivity, but those offered by certain em ployers had a higher

va ry in returns to ability in a com petitive labor m arket were introduced in

variance. In this case, the high-variance em ployers m ight tend to have a

R o y (1951). A m ore recent treatm ent appears in La n g and D icken s (1987).

h igh-w age, m ore-productive w ork force. This w ould happen because the
w orkers with the go o d draw s w ould stay longer and the w orkers with the

■7

W hen an em ployer pays w ages that reflect actual marginal

product, w orkers will be paid the marginal product of the least-productive

w orst draw s w ould leave m ore quickly than they w ould in a firm with less
variance.

worker, rather than according to their ow n individual abilities. W orkers
with higher potential will leave for jobs with a m ore productive “ weakest

■9

link” , causing average potential productivity to decline toward that of the

particular form of acquired h um an capital: w ork experience. High-w age

O n e explanation for sorting by establishm ent applies only to a

least-productive w orker. Em ploye rs w ho pay w orkers according to their

establishm ents m ay be older and have a relatively old, experienced w ork

potential m arginal product will keep their w orkers, but lose m oney. This

fo rc e , com p ared to the younger, less-productive w orkers in low-wage

argum en t is similar to the “ Jo b s as D a m Sites” idea introduced in Akerlof

plants. If s o , differences in age of em ployer w ould be reflected in w ages,

(1981).

although w age per efficiency-unit of w ork is identical for all em ployers.

are correlated with the usual measures of
acquired human capital such as age and experi­
ence, then controls for measures of human
capital also control for innate differences.10
Conant (1963), Evans (I960), and Groshen
(1988a) all suggest that employer wage dif­
ferences are not associated with sorting by
measured human capital or by ability correlated
with human capital. Gibbons and Katz (1987)
suggest that the unmeasured ability explanation
also faces a number of empirical problems in
addition to high correlation in employer differ­
entials across occupations. One problem is the
lower quit rates in high-wage firms and indus­
tries, which suggests that the high-wage jobs
may be rationed, unless high ability has a partic­
ularly strong association with a tendency for
employment stability. Another problem is that
workers displaced from high-wage industries do
not appear to retain their wage differentials if
they switch industries. Finally, the correlation of
employer wage differentials with product market
power is difficult to explain within this model.

2 . Com pensating
D ifferentials

The second possibility is compensating differen­
tials, described by Adam Smith (1776), refined
by other economists since then, and summa­
rized in Smith (1979). The essential problem is
mismeasurement of the total return to working.
In the case of poor working conditions, mone­
tary wage overstates the returns to individuals
for their work because it ignores the extra costs
imposed by working conditions.
Working conditions vary among employers,
and it is costly to improve them. All else equal,
workers prefer jobs with safe or pleasant work­
ing conditions to those with poor conditions.
Thus, employers providing unfavorable condi­
tions will be unable to meet their labor demand
at the going wage. In response, the firms offer­
ing undesirable jobs must improve the working
conditions or raise wages, whichever costs less.
If improvement of conditions is costly, wages
will be higher in order to attract sufficient labor,
but the profitability of each hour worked is
higher because of money saved during each
hour worked under poor conditions.
If workers were identical, the wage differen­
tial between any two jobs would ensure that

workers were indifferent between the two. If
workers varied in their tastes, the differential
would depend on the tastes of the marginal
worker. The allocation of the work force among
poor and good jobs depends on the assump­
tions made about existing production technolo­
gies. Technology is usually assumed exogenous,
so we need a random distribution of differences
in costs of improving conditions. If technology
is not exogenous, all firms will choose the one
that maximizes profits, so only those combina­
tions of technologies and compensating differen­
tials that yield the maximum profits will coexist.
In all versions of this model, employer (rather
than individual) differentials arise only when
quality of working conditions is consistent
across all or most of the work force in establish­
ments.11 Many working conditions, such as
physical exertion, do not apply because they are
occupation-specific. However, high risk of layoff,
poor ventilation, minimal fringe benefits, or
inconvenient location could presumably affect
all or most workers in an establishment. Then,
the costs of improvement of these conditions
must vary enough among employers to generate
the large and persistent differentials.
Empirical studies of compensating differen­
tials have been notably unsuccessful in finding
evidence of their contribution to wage disper­
sion.12 One exception to this generalization is
Eberts and Stone (1985), w ho find evidence of
compensating differentials only after controlling
carefully for characteristics of employers, sug­
gesting that compensating differentials are second-order effects. That is, type of employer
determines overall level of compensation, but
there is some substitution between wages and
nonpecuniary compensation within groups of
otherwise similar employers.

■ 11 In addition, two fairly m echanical versions of com p ensating
differentials are possible. T h e first is based on different age-earnings
profiles with differing average tenure am on g plants. T h e second is
variation in tim ing of annual salary adjustm ent. G rosh en (1988a) presents
evidence that suggests that neither of these possibilities is likely.

■ 12

F o r exam p le , see S m ith (1979). M o s t studies have attem pted to

identify co m pensating differentials am o n g industries, w here conditions
va ry m ost am on g em ployers. N everth eless, such inquiries have been
m arked by their lack of success. Fo r w orking co nditions, see Brow n
(1980); for layoff risk, see Topel (1984). It is also unlikely that em ployer
w age differences com p ensate for differences in fringe benefits. Free m a n
(1981), Sm ith and Ehrenb erg (1981), and Atrostic (1983) find that inclusion

■

10

Jo b m arket signalling (S pe nce [19 73]) is an extrem e exam ple of

of fringe benefits exaggerates w age differences am on g em plo yers. Tha t

this type of correlation, which blurs the distinction betw een hum an

is, high-w age em ployers pay even m ore of total com pensation in the form

capital and innate differences.

of fringe benefits than do low -w age em ployers.

3 . Random Variations

Seminal articles by Stigler (1962) and Rothschild
and Stiglitz (1976) launched a family of pure
information models that use costly job search to
explain wage dispersion. Suppose search were
expensive for job-seekers. In this case the mar­
ketplace can sustain a range of wages because
the gain from further search becomes uncertain,
rather than a known quantity.13
In the typical model, establishments offer
wages according to a distribution known to all
job-seekers. Workers accept offers that exceed
the expected value of further search. Job-rejecters pay to search again. Thus, the only sustaina­
ble distributions of wages are those where the
m inim um wage paid differs from the mean offer
by less than the costs of employee search.
These models focus on the role of the indi­
vidual in wage determination. No rationale is
offered for variations among employers. A sym­
metric formulation of the problem from the
employers’ point of view posits the existence of
a known distribution of reservation wages
among a population of potential employees.
Employers interview applicants to ascertain
their reservation wages, and jobs are offered to
workers (at their individual reservation wages)
when the expected value of the wage reduction
from an additional interview by the employer
falls below the employer’s search costs. Em­
ployer search costs consist mainly of advertising
and interview expenses.
The employee-cost/employer-distribution
model provides no theoretical basis for the
existence of employer differentials. Rather, it ex­
plains only persistence of variance, leaving unan­
swered the question of why the employers who
pay over the mean do not reduce their wages.
The converse model, the employer-cost/
employee-distribution model, abstracts from the
fact that firms usually set wages for a job rather
than for an individual. Indeed, wages are usually
attached to jobs before the interviewing proc­
ess. Exceptions to this rule occur where job
responsibilities are not well-defined, such as in
very small firms and for highly skilled or very
senior employees. In general, two individuals
w ho differed only in reservation wage would

not be offered different wages at the same plant.
Lagged adjustment, a second type of random
variations model, is not inconsistent with the
information/search models, but provides a basis
for the variations (wage shocks) and an addi­
tional reason for their persistence (internal
adjustment costs). These models, coined “geo­
logical models” by Dunlop (1982a), focus on the
employer. Establishments may tend to hire in
surges rather than in steady flows. If the costs of
redesigning an internal wage structure are high
or if workers are immobile, a firm’s internal
pattern and general level of wages will reflect
the market wage pattern of its most recent
expansion.14
In the random variation models, wages
approximate the worker’s marginal product, but
costs of information introduce an error term.
The mean of the error term is zero, and its
variance is a positive function of the search and
mobility costs for one or (perhaps) both parties.
Consequently, establishment differentials result
from random variations in the average error
terms of employers. But, if establishment differ­
entials are large, long-lived, and associated sys­
tematically with characteristics of employers— as
suggested by the empirical work cited above—
they are not random variations.

4 . Effic ie n c y W ages

Efficiency wage arguments posit a causal rela­
tionship between the wage level and a worker’s
on-the-job productivity.15 Efficiency wage
employers maximize profits by paying workers
a premium above the market-clearing wage,
because the resulting increment in productivity
yields the highest profits. The increased produc­
tivity has been modeled as coming from three

■ 14 Fo r exam ple , establishm ents m ay grow by the addition of a
second or third shift, rather than by hiring a few new w orkers each
m o n th . W ages at the tim e of a hiring surge reflect current labor-m arket
conditions. If the m arket is tight, w ages paid to attract new em ployees will
be relatively h igh. Later, w hen m arket w ages fall, adjustm ent dow n to the
new m arket-clearing level will not be im m ediate. Redesigning the internal
w age structure im poses costs (out-of-pocket and m orale) on the
em ployer. W age schedules are rarely adjusted m ore often than annually
and are rarely adjusted dow n w ard nom inally. U p w a rd adjustm ents will be
slow if w orkers face m obility costs. T h u s , the internal pattern and general

■

13

Originally, the inform ation m odels were form ulated to explain the

existence of price or w age dispersion. S u b s e q u e n t w ork uses these ideas

level of w ages at any particular tim e reflects the m arket w age pattern of
the e m p lo yer’s m ost recent exp an s io n . (H e n c e , the term “ geological.” )

to predict the level of un em plo ym ent. F o r exam p le , see A za ria dis (1983).
Since the focu s of the current w ork is w age dispersion, the earlier

■ 15 T h e main versions of these m odels are s u m m arize d in Yellen

form ulations of Stigler will be used to characterize the results of this

(1984) and Stiglitz (1984). Effic ien cy w ages were originally form ulated as

diverse literature. Later versions of these m odels generate term inal w age

an explanation for equilibrium u n em p lo ym en t, rather than for w age

distributions from initially assum ed distributions. Stiglitz (19 79 ) and

dispersion. W ages do not fall to clear the m arket because firm s m axim ize

Venables (1983) provide exam ples of these m odels.

profits in a labor m arket w here w ag es are high and jobs are rationed.

sources: reduced monitoring (or shirking) costs,
decreased turnover, and sociological considera­
tions. The internal labor market literature adds
two more possibilities: market insulation and
corporate consistency.
In the monitoring/shirking version, workers’
effort is costly to monitor (Bulow and Summers
[1986], Shapiro and Stiglitz [1984]). An increase
in wages decreases a worker’s incentive to shirk,
because shirking increases the probability of
losing a high-wage job. In comparison to an em­
ployer paying the equilibrium wage, efficiency
wage employers pay higher wages, experience
higher worker productivity, and have lower
direct monitoring expenses.
The turnover version emphasizes employer
costs of hiring and training (Salop [1979]). Wages
above equilibrium reduce turnover because
workers have fewer superior alternatives and/or
because the general level of unemployment
rises. Thus, workers paid higher wages have
longer tenure. Two related search/recruiting ver­
sions of the model show that firms with high
costs of unfilled vacancies will offer high wages
to more quickly fill vacancies (Lang [1987] and
Montgomery [1987]).16
A third variant of the argument is based on
sociological morale, loyalty, or teamwork effects.
Group work norms are raised by wages above
the m inim um required. Akerlof (1982) terms this
the “partial gift exchange” model.
The two internal labor-market variants, as
described by Doeringer and Piore (1971), focus
on the out-of-pocket and morale costs of design­
ing a compensation package for a group of
employees, and on firm-specific human capital.
If all wages are to be set constantly at marketclearing levels, shocks to the external labor
market will necessitate periodic readjustments
of internal pay relationships. Yet, redesign of
wage schedules may be expensive for certain
types of employers, especially large ones, or for
certain groups of employees, such as incentive
workers. In addition, any change in relative
wage relationships may be perceived as inequita­
ble or as a breach of implicit contract. Such
dissatisfaction could reduce productivity
through increased shirking or turnover.
An alternative to frequent, disruptive adjust­
ments in response to market fluctuations is to

■

16

L a n g (19 8 7) extends the analysis to s ho w that an equilibrium

distribution of w ages can be sustained a m o n g otherwise-identical firm s,
but there is no reason to expect firm s’ positions in the distribution to
persist, unless firm s lock in their position by their choice of technology.
This assum e s the existence of a range of tech no logies, each with
different capital-intensity (a nd , th u s, cost of unfilled vacancy).

set wages above the market level. If, on average,
workers receive a premium, then wage shocks
that are small relative to the premium will not
force a firm to readjust its compensation pack­
age. Employers save out-of-pocket and produc­
tivity costs of the adjustment, in return for
paying higher wages.
Corporate consistency, the second internal
labor-market version, is based on the tendency
of large firms to promote workers from within
whenever possible rather than hire from outside.
Presumably, firm-specific human capital makes
promotions or transfers among plants efficient.
Nevertheless, such a policy requires that internal
wages for each occupation in each plant meet
two criteria: (1) they cannot be much lower than
local wages for the occupation (or the workers
will leave the firm), and (2) they cannot be lower
than firm-wide wages for that occupation (or
workers will refuse transfers to the plant). This
implies identical wage structures for each plant
within the firm regardless of location, as long as
product lines are similar enough for personnel
to be transferred among them. Furthermore,
each occupation will earn the maximum local
rate over all plant locations. O n average, this
yields positive establishment differentials that
increase with firm size.
Efficiency-wage models can be invoked to
explain differentials among firms in two ways.
First, the profit-maximizing point is, almost by
definition, locally flat. This implies the existence
of a plane of (almost) iso-profit wage-productivity points for identical firms. That is, variations
in wages from the optim um lead to only small
profit losses. Firms are close to indifferent
among the possible combinations, so a random
distribution of strategies results (Bulow and
Summers [1986]).
A second, more plausible, explanation stems
from economically important heterogeneity
among employers: differences in technology
(vintage effects, for example), or differences in
products (such as differentiated quality niches).
The productivity of workers at the marketclearing wage may be indistinguishable from
high-productivity work under some technolo­
gies, or may be adequate for one market but not
for another. Workers paid the market-clearing
wage form a queue for jobs at the elevated wage,
while recipients of the high wage avoid job loss
or job changes because of the scarcity of equiv­
alent opportunities.
Efficiency differentials can explain establish­
ment differentials when workers in all or most
occupations in the establishment are affected.
That is, it is crucial that the heterogeneity
among employers affect the efficient wage for all

occupations similarly. The plausibility of this
assumption depends on the version of the
model in question.
Few empirical tests of efficiency wage models
have been performed, primarily because of the
lack of appropriate data. One recent exception,
Leonard (1987), finds little evidence to support
the turnover or supervisory-intensity versions
among electronics companies in California.
Another study, Krueger and Summers (1986a)
finds some support for efficiency wage explana­
tions of interindustry wage differentials. Interest
in these models suggests that the results of other
tests may be available shortly.

5 . Insider/Outsider
Bargaining M odels

When bargaining between workers and their
employers takes place in the context of com ­
petitive markets (in labor, capital, and products),
bargained wages cannot differ from the marketclearing wage. Otherwise, the firm would close
or the workers would leave. However, if employ­
ees can exercise a claim on the rents generated
by an enterprise, they will bargain (implicitly or
explicitly) with their employers. Wage settle­
ments will reflect both the size of rents and the
relative bargaining power of the parties. Thus,
the existence of both rents to the firm and
employee bargaining power are necessary con­
ditions for wage bargaining to produce wage
variation.
Although all versions of bargaining models
must assume the existence of rents, the models
differ in the identity of the bargaining agents and
in the enforcement mechanisms for the bargain­
ing. The bargaining agent for the workers is
most clear in the case of unionism. In the
collective bargaining literature, the outcome of
negotiation is likened to the Edgeworth Box.
Bargaining is a positive-sum game until the
contract curve is reached, and a zero-sum game
along the contract curve. The outcome is deter­
mined by the relative bargaining ability and
credibility of participants’ threats. The range of
possible wages is bounded by the market-clear­
ing wage on the bottom end and by the worker’s
actual marginal product (with labor appropriat­
ing all rents and capital earning the normal rate
of return) on the high end.
In a nonunion setting, the bargaining agent
for the workers is not obvious. However, econo­
mists have long noted the existence of informal
organization by workers in nonunion settings
(Dunlop [1957]). One version is the union-threat
effect, where the threat of unionization forces

owners to provide nonunion workers benefits
similar to those they would receive if unionized
(Dickens [1986]).
In a second version, the managerial-capitalism or agency-cost version, managers act as
mediators between labor and the owners of
capital. If the rewards to management are not
highly correlated with rents to the owners, or if
managers maximize a utility function dependent
on worker satisfaction (whether due to manage­
rial altruism or to the ability of workers to
impose on-the-job problems), then management
may not act to maximize rents to owners.
Implicit bargaining may occur, with manage­
ment cast in various roles from agent for the
workers, to mediator between the two sets of
interests, to agent for the owners. The latter role
would generate a model all but institutionally
indistinguishable from a union bargaining
model. For example, Aoki (1984) presents coop­
erative bargaining models for modern nonunion
corporate enterprises with various constituen­
cies. Edwards (1979) also presents an informal
model of nonunion bargaining.
Bargaining models easily lend themselves to
the prediction of establishment differentials. The
only additional assumption necessary is one that
binds together workers of different occupations
in the establishment. Three possibilities exist.
First, workers’ bargaining power may be consis­
tent across occupations in an establishment.
Second, perhaps workers must form large
groups in order to exert bargaining power.
Third, managerial altruism may extend uni­
formly across occupations.
The persistent link between measures of
product-market power and industry wage differ­
entials provides an empirical basis for further
investigation of bargaining theories. More direct
evidence is limited by the lack of data, but
studies by Abowd (1985) on unionized firms and
by Kleiner and Boullion (1987) on both union
and nonunion firms provide some support for
bargaining hypotheses.17 As with efficiency
wage models, more direct tests of these models
are certain to be available in the near future.

■

17

A b o w d (1985) finds evidence that union contract settlem ents

dim inish the value of the firm by exactly the ch an ge in the value of the
negotiated settlem ent. Kleiner and Boullion (19 8 7) find that firm s’ w ages
are strongly positively correlated with the provision of sensitive financial
inform ation to em ployees.

III. La b o r M a rke t Policy
and Em ployer
W age Effe c ts

The empirical work cited in this paper suggests
that employer wage differentials are large. Thus,
they may account for many of the observed
inequalities in the labor market, such as those
among races or between men and women.
Exploration of five models of employer differen­
tials clarifies the point that these differentials are
not necessarily inconsistent with profit max­
imization by firms acting in a competitive labor
market. Yet each model suggests the existence of
a particular barrier that prevents formation of a
single market wage.
The link between theories of employer wage
effects and labor market policy to reduce
income inequality is labor-market segmenta­
tion.18 W hen labor markets are segmented,
workers are separated into distinct markets by
institutional barriers that prevent workers or
employers from switching between markets.
Thus, different wages persist for each sector of
the labor market. Although workers in each
sector are paid their marginal product, produc­
tivity varies between sectors according to sectorspecific supply and demand, or sector-specific
quality. Obviously, the costs of barrier removal
must be high enough to prevent profit-seeking
employers from eroding the differences
between sectors.
Employer differentials will create segmented
markets only if employers limit their recruit­
ment to one sector, so any model must explain
why employers hire all (or most) of their employ­
ees from the same market sector. Each model
discussed above introduces a barrier that could
create segmentation, with strikingly different
policy implications. Thus, it is precisely the
identification of the source of the barrier that
makes segmentation difficult to cure with policy.
For example, under the sorting model, seg­
mentation will arise if workers of different sex or
race have different access to human capital. The
model implies a need for the development of
human capital among secondary sector workers
(for example, lower cost, better education, or
job training). Alternatively, compensating differ­
entials imply no role for policy, since the market
actually remunerates all workers equally. Appar­
ent segmentation arises simply because tastes

differ systematically among groups.19 Random
variations suggests that search costs are higher
for the classes of workers in predominantly lowwage jobs. A possible solution may be expansion
of job-service agencies targeted to these groups.
Efficiency wages and bargaining imply the
existence of queues of workers for high-wage
jobs. Thus, any attempt to reduce inequality
should rest on regulation of employers’ recruit­
ment policies, on improvement of placement
services for secondary market workers, and on
elimination of any minor productivity deficien­
cies among workers in the secondary sector.20
These five theories of wage determination
also diverge from each other in their predictions
for the impact of other kinds of policy. For
example, Stiglitz (1984) and Bulow and Summers
(1986) analyze the effects of efficiency wages on
macroeconomic performance and trade policy.
Weitzman (1986) offers an analysis of the effects
of a particular form of profit-sharing on eco­
nomic stability and growth.
Understanding the source of employer differ­
entials is clearly important for understanding the
distribution of wages, and for formulating policy
to affect it. New sources of data must be devel­
oped to allow research on employer activities
such as supervision, recruitment, terminations,
and wage-setting. Without further research on
these topics, we will remain unable to sort out
whether employer wage differentials are signs of
inefficiency, of discrimination, or of other mar­
ket imperfections.

■ 19 F o r instance, co m p are d to m e n , w om en m ay prefer quieter,
cleaner, or m ore flexible jobs (Filer [1983]).

■ 20

B ulow and S u m m e rs (1986) dem onstrate h ow efficiency w ages

m ay be a source of m arket segm entation. T h e y em ph asize that
segm entation requires the existence of a small productivity differential

■

18

F o r a s u m m a ry of the literature on seg m en ta tion , see Cain (19 76 )

between w orkers of the two sectors, but that the w age difference between

and D ickens and La n g (1985). L a n g and D icken s (19 8 7) provide a detailed

the two sectors will be far greater than the productivity difference. A

investigation of the relationship betw een the literature on segm ented

similar argum ent can be m ade for differentials associated with rent-

m arkets and neoclassical econom ic theory.

s haring, assum ing profit m axim ization on the part of em ployers.

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E c o n o m ic R e view

■ Quarter I 1987
Concentration and Profitability in
Non-MSA Banking Markets
by Gary Whalen

■ Quarter III 1987
Can Services Be a Source o f Export-led
Growth? Evidence from the Fourth District
by Erica L Groshen

The Effect o f Regulation on
Ohio Electric Utilities
by Philip Israilevich
and K.J. Kowalewski

Identifying Amenity and Productivity Cities
Using Wage and Rent Differentials
by Patricia E. Beeson
and Randall W. Eberts

Views from the Ohio Manufacturing Index
by Michael F. Bryan
and Ralph L Day

FSLIC Forbearances to Stockholders and
the Value o f Savings and Loan Shares
by James B. Thomson

■ Quarter II 1987
A New Effective Exchange Rate Index
for the Dollar and Its Implications
for U.S. Merchandise Trade
by Gerald H. Anderson,
Nicholas V. Karamouzis
and Peter D. Skaperdas

■ Quarter IV 1987
Learning, Rationality, the Stability o f
Equilibrium and Macroeconomics
by John B. Carlson

How Will Tax Reform Affect Commercial
Banks?
by Thomas M. Buynak

Airline Hubs: A Study o f Determining Factors
and Effects
by Paul W. Bauer
A Comparison o f Risk-Based Capital and
Risk-Based Deposit Insurance
by Robert B. Avery
and Terrence M. Belton

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