Montgomery c

8/9/2019 Montgomery c

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Corporate Restructuring and the Consolidation of US IndustryAuthor(s): Julia Porter Liebeskind, Tim C. Opler, Donald E. HatfieldSource: The Journal of Industrial Economics, Vol. 44, No. 1 (Mar., 1996), pp. 53-68Published by: Blackwell PublishingStable URL: http://www.jstor.org/stable/2950560 .

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2/17

THE JOURNAL OF

INDUSTRIAL ECONOMICS 0022-1821

VOLUME XLIV March 1996

No.

1

CORPORATE

RESTRUCTURING

AND

THE

CONSOLIDATION OF US INDUSTRY*

JULIA

PORTER

LIEBESKIND,

Tim

C.

OPLER,

DONALD E. HATFIELD

This study examines the impact of corporate

restructuring measured

at the

industry

level on

industry

concentration in

695 4-digit US industries

in

the

basic, manufacturing and services

sectors

between

1981

and 1989.

The

results show

a

modest increase

in

median industrial concentration

in

sample

industries between

1981

and 1989.

We find no evidence that selloffs

of

assets

at the

industry

level

through

horizontal

mergers,

acquisitions,

and

inter-firm

asset sales increased US industrial concentration during the 1980s.

I. INTRODUCTION

DURING the 1980s, US industrial asset

ownership changed

at

a rate

not seen since

the turn of the century. Jensen [1993] reports that

35,000 mergers and

acquisitions with a total market value of $2.6 trillion took

place

between 1976

and 1990.

Many

of these transactions resulted

in

extensive

business divestitures

and plant closings in target firms (Bhagat, Shleifer, and Vishny [1990]). At the

same

time,

numerous

independent

firms also

reconfigured

their

operations by

selling lines

of

business and

closing plants (Bowman

and

Singh [1990];

Comment

and

Jarrell

[1994]).

This boom

in

corporate restructuring activity has provoked an intense debate

about its

consequences

for the

US

economy.

Critics

attribute

the

restructuring

boom to

the Reagan Administration's

relaxed enforcement of the

Cellar-

Kefauver Act and

argue that corporate restructuring has undermined

US

industrial efficiency by increasing industrial concentration

(Adams

and

Brock

[1988]; Shepherd [1990]). Consistent with this argument, the dollar value of

horizontal

mergers

increased from

$25 billion

in

1970-78

to $261 billion

in

1979-87 (Blair,

Lane and Schary [1991]).

In

addition,

Bhagat, Shleifer, and

Vishny [1990]

find

that over two-thirds of the lines of

business sold

off

following

hostile

takeovers during the

1980s

were bought by other

firms

in

the

same

industry. They

conclude

that

a

primary

motivation for these selloffs

was market

consolidation. Others

argue

that

restructuring

has

improved

US industrial

efficiency.

For

example,

Jensen

[1988, 1993]

and

Shleifer and

Vishny [1992]

argue

that

mergers,

selloffs

and

plant

closures

during

the 1980s served

to

discipline managers

in

inefficient

firms,

to eliminate excess

capacity

at both

a

*

We thank Jennifer

Bethel,

Harold

Demsetz, Scott Lee,

Marvin

Liebernan, William Long, John

Lott, David Ravenscraft, Geoff Waring,

Fred Weston and two anonymous referees for

useful

comments. We also

thank

seminarparticipants t the Universityof SouthernCalifornia,Texas

A&M

University, and Southern

Methodist

University. Kishore Gawande, Marion Jones and Carl Voigt

providedvaluable assistance in data

acquisitionand interpretation.

()

Blackwell

Publishers

Ltd.

1996,

108

Cowley Road,

Oxford

OX4

1JF,

UK and

238

Main Street, Cambridge,

MA

02142, USA.

53


3/17

54

JULIA

PORTER

LIEBESKIND

ETAL.

firm

and

an industry

evel, and

to increase

firms'

focus on

the industries

n

which

they

held

a

competitive

advantage.

Consistent

with

this

argument,

Lichtenberg

and Siegel [1987] find thattotal factorproductivity ncreasesaftermergersand

selloffs,

while

Lichtenberg

[1992]

and

Comment

and Jarrell

[1994]

find

that

firms

increased

their

corporate

ocus,

their

productivity,

and their

value

during

the 1980s

by divesting

lines

of

business.

Despite

this vigorous

debate,

there

is

little

evidence documenting

the

overall

pattern

of changes

in US industrial

oncentration

during

the 1980s

or

indicating

whether

corporate

restructuring

was related

to any changes.

To address

these

issues,

this

study

examines

the

relationship

between

selloffs

of lines

of

business,

measured

at

the

industry

level,

and

changes

in industrial

concentration

n

a

sampleof 695 4-digit SIC-codeindustries n all sectorsof the US economy,and

in a variety

of

industry subsamples.

We

also

investigate

the effects

of

establishment

closures,

additions,

and expansion

on

industry

concentration

during

the same period.

This

study

has

two

main

results.

First,we

find

a

modest

increase

in

median

industry

concentration

between

1981 and

1989

in

the full sample

of

695

4-digit

US

industries

and a

larger

ncrease

in

median

concentration

n the subsample

of

390

4-digit

manufacturing

ndustries.

Second,

we

find that

selloffs

of

lines

of

business

measured

at

the industry

evel

are

significantly

and

negatively

associated

with change in industryconcentrationduringthe 1980s in both manufacturing

and

non-manufacturing

ndustries.

This

evidence

is

inconsistent

with

the

argument

hat

mergers

and

selloffs during

he 1980s

led to

increases

n

industrial

concentration

across

broad

samples

of

US

industries.

The plan

of

this

paper

s as follows.

Sections

IIand

III

describe

he measures

of

corporate

restructuring

used

in

this

study,

other

variables,

data,

and

methods.

Section

IV

reports

evidence

on

the extent

of

corporate

restructuring

uring

the

1980s.

Section

V reports

evidence

on

the

relationships

between

corporate

restructuring

nd

changes

in industrial

concentration.

Section

VI

concludes.

II.

DEFINITION

AND

MEASUREMENT

OF

CORPORATE

RESTRUCTURING

We define

seven

measures

of

corporate

restructuring

n this

study.

Each

restructuring

measure

is

estimated

using

establishment-level

data aggregated

o

the

firm

and

industry

evel

in the two-stage

process

as follows:

Stage

1:

Establishments

in each

industry

are

classified

into

restructuring

categories

This procedure

s

illustrated

n Table

I.

First,

the status

of each

establishment

n

any given

industry

s classified according

to

whether

t was:

(a)

continuously

n

operation

n

that

ndustry

between

1981

and

1989, (b)

closed

down between

1981

and 1989,

or

(c)

added

to that

industry

between

1981 and

1989.

Any

establishment

hat

was

continuously

in

operation

between

1981

and

1989

was

C

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RESTRUCTURINGAND

CONSOLIDATIONOF US

INDUSTRY

55

TABLEI

DEFINITION F

INDUSTRY-LEVEL

ESTRUCTURING

ATEGoRIES5 SED TO

CLASSIFY

NDUSTRY

ESTABLISHMENTS

Change

in the

status

of

industry

ncumbentfirms:

Change

in

the status

of

Firm exits

Firm

remains Firm

enters

industry

establishments:

between

1981

as

incumbent

between 1981

and

1989

1981 and

1989

and 1989

Establishment

urvives and:

(i)

is sold to

another

irm

SELLOFFI

SELLOFFI

between 1981 and

1989 EXIT

STAY

(ii) is not

sold but is

expanded

EXPAND

between 1981 and 1989

Establishments

closed

CLOSE/EXIT

CLOSE/STAY

between 1981

and

1989:

Establishment s

added

to

the

ADD/STAY

ADD/IENTER

industrybetween

1981

and

1989:

REach

estructuring

ariables

definedn terms f

both:

(i)

Change

n

thestatus f the

establishmentetween

981and

1989 i.e.,

establishmenturvived ut

ownership

is changed;stablishment

s

expanded;stablishments

closed;

stablishment

s added).

(ii) Changeornochange)n thestatus f theparentirm egardingtsindustryncumbencyi.e.,parentirm

exists;parent

irm

emains

n

the

ndustry;arent

irm

nters).

Note hat he

variables

redefined

n

terms f

establishmenttatus

ndparenttatusn

1981.Thisallows

definition

of

establishments

hat hange

wnership

n

terms f

being

"sold

ff"

by a parent

irm

ather

han s

being"bought"

by

another

irm.

further

classified

according

to

whether

it

was sold

off

or

expanded

during

this

period.

Second,

the

status of

each

restructured

stablishment's

parent

firm

is

classified

according

to

whether it

remained

as an incumbent

between

1981

and

1989; exited the

industry

between

1981 and

1989;

or

entered he

industry

during

thisperiod. This classificationprocedure esults n sevenrestructuringategories,

illustrated

n

the boxes in

Table I.

Stage

2:

Employee-weighted

ndustry-level

estructuring

ntensity

variables

are

estimated

The

total

volume of each

type

of

restructuring

n

each

industry

s

estimated in

terms of

the

proportion

of

total

industry

employees

in

1981 that

was employed n

establishments

n each of

the

restructuring

ategories defined in

Table

I.

For

the

purposes

of this

study,

the

most

important

of

the seven

restructuring

ntensity

variables s SELLOFF/EXIT,hich capturesall horizontalmergerand inter-firm

asset sales

between 1981

and 1989. Ceteris

paribus,

horizontal

mergers

always

increase

industrialconcentration.

Selloffs

that result

in

industry exit

will

also

increase

industrial

concentration

f the

lines of

business

in

question

are sold to

other

existing incumbent

irms,as

Bhagat,Shleifer,and

Vishny's

[1990]

evidence

suggests occurred

during

the

1980s.

If

lines

of business are

sold to new

firms

C)

Blackwell Publsers

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1996


5/17

56 JULIA PORTERLIEBESKINDETAL.

instead, nter-firm sset sales will result in decreases n concentration.Selloffs of

establishments by continuing incumbent

firms (measured by the variable

SELLOFFISTAY)ill only increase industryconcentration f small incumbents

sell establishments

to

large firms (Hannah and Kay [1981]); otherwise, such

selloffs will decrease industryconcentration.

Plant closures, additions, and expansions may also have had a significant

impact on industrialconcentrationduring the 1980s (Hannahand Kay [1981]).

Closureof capacity by largefirmsdilutes

industrialconcentration, egardlessof

whether

hese firms exit or not.

Concomitantly,

losure

of

capacityby

small firms

increases concentration.Therefore, both

CLOSE/EXIT nd CLOSEISTAY ay

have a significant mpact

on

industryconcentration, hough the directionof their

effect cannot be predicted.Note, however,thatplant closures by existing firms

reduces the number of incumbent firms

remaining in the industry,which may

facilitate coordinationamong

the

remainingfirns,

even

if

such

closures do not

increase concentrationper

se. If

large incumbent firms add or

expand

more

establishments han small firns,

concentrationwill increase,and vice-versa (Lane

[1993]). Therefore,both ADD/STAYand

EXPANDISTAYay have a significant

effect

on

industryconcentration.Finally,

the

addition of new establishmentsby

entering firms (measuredby

ADDIENTER)

an be

expected

to

reduce

industry

concentrationbecause de novo

entry

is

usually

small

scale

and

always

adds

new

firms.

III. OTHER

VARIABLES,

DATA,

AND

METHODS

(i) Dependent

Variables

Change

in

industrial oncentration

s

measuredas

the

change

between 1981 and

1989

in

two standardmeasures

of

industry

concentration:

he

four-firm sales

concentration atio andthe Herfindahl ndexof sales concentration.We use two

measures

of sales concentrationbecause choice of

measure

can

bias results

(Kwoka [1981]).

Both

measures

are

estimated

in

terms

of the

value of final

shipments

of

incumbent

firms in

1981

and

1989.

The

four-firmconcentration

ratiois estimatedas

the

proportion

of the

total value

of

final

industryshipments

that is accounted

for

by

the

four

largest

firms

in

that

industry.

The

Herfindahl

index

is estimated

as

the

sum

of the

squared

marketsharesof

all

incumbent irms

where

market share

is

estimated as

the

ratio

of the

value

of

final

shipments

of

each

firm

to the total

value

of

final

shipments

n the

industry.

(ii)

Control

Variables

The

regressions

include

the

change

in the

estimated minimum efficient scale

(CHMES)

between 1981

and

1989 because a number of

studies

show that

industryplant

size and

industry

concentrationare

highly

correlated

Curry

and

George [1983];

Schmalensee

[1989]).

We

measureCHMESas

percentagechange

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6/17

RESTRUCTURING

AND

CONSOLIDATIONOF US

INDUSTRY

57

in median

establishment ize

(measured n

terms of

employees).' The

regressions

also control for

industry concentration

n

1981

(INDCONC81) because

prior

levels of industryconcentrationhavebeen shown to be a significantdeterminant

of

change in

concentration.

In

addition, the

regressions control for

industry

regulation

and

growth.

In

industries

such as

utilities and

banking,

horizontal

business

combinations

may

be

prohibited; his is

controlled

for

using

a

dummy

variable

(REGULATE).

Because

industry growth may influence

concentration,

change

in

industry sales is

controlled for

using

the

percentage increase

in

the

value of

total

industryshipmentsbetween

1981 and

1989

measured

n

constant

1981 dollars

(CHSALES).

(iii) Data

The seven

measuresof

industry-level

estructuring nd the

measures

of

industrial

concentration,

MES,

and

industry

sales

were estimated

using

TRINET

Inc.'s

Large Establishment

Database.

An

important

advantage

of

using TRINET

(rather han the US

Census of

Manufactures)

s that it provides

informationon

non-manufacturing

ectors of

the US economy.

TRINET

covers over 80

percent

of

all establishments n the

US and over 95

percentof

establishmentsowned

by

public firns; as

such,

it

is

considered

o

be reliablefor the

purposes

of

analyzing

industry structure

Kwoka

[1978]).2

The

TRINET

data include the

4-digit SIC

code

of

each

establishment's

primary industry,

its number of

employees,

its

current

dollar value of

sales,

its address and

telephone number, and its

parent

company

identificationnumber.3These

data can be

aggregated

to the

industry

level

using

the

4-digit

SIC

code and

to

the

firm

level using the parent

company

identification number.

Further details of the

TRINET

data are

given

in the

Appendix.

If

an establishment

s

redeployedbetween

one

industry

and

another,

TRINET

will

usually

recordthat establishment

as

being

closed in one

industry

and

newly

added to another.Therefore, he estimatesof ADDIENTER,ADDISTAY, LOSEI

EXIT, and

CLOSEISTAYeflect

not

only actual new plant

addition and

actual

plant closure, but

also

the

redeploymentof

establishments

across industries.

In

addition,

TRINETdata

cover

only

establishments

ocated

in

the US

(i.e.

all US-

based facilities of US

and

foreign-owned irms,

but

not

overseas establishments

of

US

firms).

This

permits

us

to

analyze

the

effects

of

restructuring

on

the

concentrationof the

value of

shipments

from

US

establishments,

but not the

effects of

restructuring

on the

concentration of the

value

of

shipments

of

' We also used two othermeasuresof minimumefficient scale in the regressions,with no effect on

results: (i) scale variance,

measured as the inter-quartile

ange of

establishmentemployment

over

median

establishment

mployment,and (ii) the first

quartileof establishment

mployment.

2

See Appendix for details of

Kwoka's

findings and furither etails of the

Large

Establishment

Database.

3TRINET usually lists

multiproduct

establishments as separate

establishments,

with separate

identification

numbers.Employmentand

sales figures are then

attributed o each

industry. n 1989,

about 2.5

percent

of

all establishments

n

TRINET

were

listed

in

more than

one

industry.

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58

JULIA

PORTER

LIEBESKIND

ETAL.

establishmentsowned by

US firms. Also, not all

marketsare national in scope,

even though

they are treated

as such using the TRINET data.4

TRINET's

coverageof small establishmentshas improvedover time, andin general,datafor

larger establishments

are

more likely to be accurate than

for smaller

establishments. Consequently, we follow

Lieberman and Hatfield [1993] by

restricting our sample to establishments

with 100 or more employees

and to

industrieswith 5 or more establishments

of this size.5This truncating

procedure

reduced

the numberof 4-digit

SIC industries n

the

sample from

745 to 695.6

(iv)

Method

and

Samples

The relationship

between industry-level

restructuringand change

in industry

concentration

s

analyzed using

OLS

regressions

and two measures of absolute

change

in

industrial oncentration

between

1981

and

1989

on seven measuresof

industry-level

restructuring ntensity and four

control variables. Following

Krasker,Kuh, and Welsch [1983]

we conductedregressions with

and without

outliers.Our resultswere substantivelyunchanged

by

the

presence

of outliers;we

therefore reportvariable

estimates and regression

results that include outlying

values. We conduct regressions

on

the

full sample

of 695

4-digit

SIC industries

from the basic, manufacturing,

and service sectors,

and on the subsamples of

manufacturing ndnon-manufacturingndustries,producerand consumergoods

industries,

and industries with low, relatively

high, and high levels

of

concentration

n

1981.

IV

INDUSTRY-LEVEL

ESTRUCTURINGACTIVITY

AND

CHANGE

IN US

INDUSTRY

CONCENTRATION,

981-89

The median and mean values

of

the

seven

measures of industry-level

restructuring

ntensity

used

in the

study

are shown

in

Table II. Panel

A

shows

values

for all 695 industries

in the

sample;

Panel

B

shows values

for the

subsample

of

390

manufacturing

ndustries.

The median

level

of

employment

change

due to selloffs

by

exiting

firms

(SELLOFFEXIT)

n both

samples

is

quite

high: 17 percent

n the

full sample,

and 18

percent

n

manufacturing

ndustries.

n

contrast,

the

median

level of

employmentchange

due

to selloffs

by

finns that

remained ncumbents

hrough

1989

(SELLOFFISTAY)

s near zero.

Mean

values

for

both

these variables

are

higher, indicating

skewness

in

the distributionof

selloff

activity

across industries.

4The

problemsof using SIC-defined ndustries o define marketsarewell known. For a discussion,

see Scherer [1980].

5

We also conducted analyses using

minimum establishment

izes

of 50 and 200 employees;

this

had little effect on the

estimate of CHMESor on the regressionresults.

6In

1987

a numberof new SICs

were

created

and severalold SICs were consolidated.To adjust

or

these changes, we consolidatedseveral SICs

in

the dataset,reducing he

total numberof 4-digit SICs

by about 3 percent.

In

addition, we excluded 4-digit industries above

7999

from the

sample

to

eliminate

industriesdominatedby non-profitorganizations.

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RESTRUCTURINGAND

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INDUSTRY 59

TABLEI

INDUSTRY-LEvEL

ESTRUCTURNG crlvrrY

1981-1989a

Variable Median Meanb Std.Dev.

A. For 695 4-digit industries

17.03

22.95 41.01

SELLOFF/EXIT

SELLOFF/STAY

0.00

0.95

2.54

CLOSE/EXIT

41.34 42.03 19.27

CLOSE/STAY

10.84

14.11

14.13

ADD/ENTER

29.38 68.85

154.40

ADD/STAY

7.21 13.08 17.15

EXPAND/STAY

-0.21 -0.73

13.17

Net Additionc -

11.90

25.05 158.07

B. For 390

manufacturing ndustries

SELLOFF/EXIT

18.22

21.14

18.45

SELLOFF/STAY

0.00 1.15

2.46

CLOSE/EXIT

37.70

37.72 15.71

CLOSE/STAY 11.59

13.40

10.20

ADD/ENTER

27.15 21.07

30.87

ADD/STAY

8.06 12.74 14.44

EXPAND/STAY

-

0.84 - 1.76

11.83

Net Addifionc

-

18.26

-

13.00 41.23

aFor definition of measures see Table I

and

the text. All

variables are measured

in

terms

of

percentage

of total

industryemployees in 1981, and each measurethereforehas a potentialvalue of between0 and 100.

bUnweighted

cThis

variable s provided for illustrative

purposes only and is estimated

as:

[(total employeers of plants added or

expanded

between 1981 and

1989)

-

(total employees

of

plants

closed

between 1981 and

1989)1/Total

ndustryemployment

n

1981.

The median level of

employment change

due

to

establishmentclosures

by

exiting finns

(CLOSEIEXI)

is

very

high:

41

percent

in

the

full

sample,

and 38

percent

n

manufacturingndustries.

n

contrast,

he

median level of

employment

change

due

to establishment

losure

by

incumbent irms

(CLOSE/STAY)

s

about

11

percent in

both samples.

(Recall that the measures of

plant closure

and

addition includeredeploymentof establishmentsacross industries,as discussed

in

Section III.) The employment

change due to

plant additionby new entrants

(ADDIENTER)s

also

high:29

percent

n

the median

industry,

and

27

percent

n

the median

manufacturingndustry.

The median rate of

employment

change

due

to

plant additions

by

incumbents

(ADDISTAY)

s

much lower: 7

percent

in

the

median

industry,

and 8

percent

in

the

median

manufacturing ndustry.

Mean

values

are

much

higher

for

both these variables

in

the

full

sample7

The

7

The mean value of

ADD/ENTER n the full sample

(69 percent)appears o be extraordinarily igh.

However, it can be validated by comparing our

estimate of ADD/ENTERfor

the subsample of

manufacturingndustries o

estimatesobtainedby

Dunne, Roberts,and Samuelson

[1988].

They

find

an

unweighted

rate

of

new

plant addition

of

25.3 percent for the five

year period

1977-82 and

for

plants with 250 or more

employees in the manufacturing ector. This rate

is equivalent to an

unweightedrate of 37.9 percent for the eight year

period we analyze.

In

comparison,

our

weighted

estimate

of

ADD/ENTER or

manufacturing

ndustries is

21.07

percent,

even

though

our

sample

includes smaller plants, which

can be expected to

increase reported evels of entry. (See

Dunne,

Roberts,

and

Samuelson[1988] for a discussion of this

issue.)

This

suggests that

our

estimates

are

conservative.

(j

BlackwedlPublshes Ltd. 1996


9/17

60 JULIA PORTERLIEBESKINDETAL.

employment change due to plant expansion

(EXPANDISTAY)

s negative (but

very small)

in

both the full sample and the manufacturing

ubsample.

For illustrative purposes, Table II also provides estimates of the total net

change im industryemployment

due to

restructuring ctivity

between 1981 and

1989. For the

full

sample, the median industry experienced

a net reduction in

employment

of

about

12

percent

due to

plant closures,

additions,and expansions;

in

manufacturing,

he net reduction

was about

18

percent.

Note that the mean

value

for this

variable

in

the

full sample

is 25

percent,

indicating that

some

(mainly non-manufacturing)

ndustries

grew very rapidly

between 1981 and

1989.

Table

III

shows the changes

in

the two measures

of industryconcentration sed

in the study between 1981 and 1989.8 For all industries,median concentration

increasedslightly: the median change

in

four-firm atio

representsan increase of

3.4 percent between 1981 and 1989, while the median change

in

Herfindahl

indexrepresentsan increaseof 6.4 percent.Therefore,concentration ncreased

n

more than half

of

all

US industries

during

he 1980s.

In

manufacturingndustries

concentrationncreased

more: the

medianchange

in

four-firm atio represents

an

increaseof 14.0 percent,while

the

median change

in

Herfindahl ndex represents

an increase

of

20.3

percent.

V

THE

DETERMINANTS

OF

CHANGE

IN

US INDUSTRYCONCENTRATION,

981-89

We use OLS

regressions

to

explain

the

change

in

industry-level

concentration

with seven measures of

industry-levelrestructuring

and a number

of

control

variables. Lacking

a structural

model

appropriate

or

describing change

in

the

many

different

ndustries

n

our

sample,

we wish to

interpret

our

regressions

as

under-identified educed forms

of

some largerbut unknown structural ystem

(Schmalensee [1989]).

TableIV reportsregressionsusing the full sampleof 694 4-digit industriesand

the

subsample

of

390

4-digit manufacturing

ndustries.

The

most

important

esult

of these

regressions

s

that

selloffs of

establishmentsby exiting

firms

(SELLOFFI

EXI)

are shown to be significantlyand negatively associated with changes

in

concentration

n

three of the

four

regressions.

Selloffs of

establishments

by

surviving

ncumbent irms

(SELLOFFISTAY)

re

also

significantly

and

negatively

associated

with

changes

in

industry

concentration

n

the

full

sample, suggesting

that large

incumbentfirms sold off assets

to

smaller

firms

during

the

1980s.

The

regressions

show that other

types

of

corporate

restructuring

are also

significantdeterminants f changesin industryconcentration.First, he closureof

establishments

by exiting

firms

(CLOSEIEXI)

is

significantly

and

positively

associated

with

changes

in

industry

concentration

in

the

subsample

of

manufacturing

ndustries. This

suggests

that establishments

were closed

by

8The Herfindahl

ndex of industry

concentrations scaled between

0

and

1, where an industrywith

an index of 1 has all its employees

in one firm.

Herfindahl

ndices are

frequently

rescaled from

0 to

10,000

as

in the

Department

of

Justice's

Merger

Guidelines.

?

Blackwell PublishersLtd. 1996


10/17

RESTRUCTURING

AND

CONSOLIDATIONOF US INDUSTRY 61

TABLEIII

INDUSTRY CONCENTRATION

AND

CHANGE IN INDUSTRY CONCENTRATION

1981 TO 1989

Variable Median Meana Std. Dev.

A.

All

industries:

(n= 695)

Four Firm concentration atio:

1981

0.4508 0.4874 0.2324

1989

0.4515 0.4837 0.2071

Change

in Four Firm

concentration atio between 0.0157 -0.0037 0.1664

1981 and 1989b

Hirschmann-Herfindahlndex of concentration:

1981

0.0781 0.1201 0.1238

1989 0.0792 0.1146 0.1085

Change

in

Hirschmann-Herfindahlndex of 0.0050 -0.0055 0.1174

concentrationbetween 1981 and 1989b

B.

Manufacturingndustries:

(n

=

390)

Four Firmconcentration atio:

1981

0.3862 0.4170 0.1919

1989 0.4412 0.4769 0.1967

Change

in

Four

Firm

concentration atio between

0.0541

0.0599

0.1205

1981 and 18989b

Hirschmann-Herfindahlndex

of

concentration:

1981 0.0607 0.0823 0.0694

1989 0.0772 0.1060 0.0915

Change

in

Hirschmann-Herfindahlndex of 0.0123 0.0237 0.0700

concentrationbetween 1981

and

1989b

'Each ndustrys equallyweighted.

bChange

between 981and 1989 s the

dependent

ariable

sed n the

regressionseported

n

Table

V

and

V

smaller,rather

han

larger,manufacturingirns, consistentwith the argument hat

restructuring hrough plant

closures

during

the

1980s

served

to consolidate

manufacturing apacity (Jensen [1993]).

As

expected,

the addition of

establish-

ments

by entering

firms

(ADDIENTER)

s

significantlyandnegatively associated

with

changes

in

industry

concentration

n

all four

regressions.

In

contrast,

in

addition

of

capacity by

incumbent

inns

(ADDISTAY)

s

significantlyassociated

with

increases

in

concentration

n

three

out

of four

regressions, suggesting

that

large incumbent

firms

expanded

their

marketshareduringthe 1980s by adding

new

capacity.

Neither

closures

of

capacity by

incumbent firms

(CLOSEISTAY)

nor

expansions

of

capacity

(EXPANDISTAY)

ave

any consistently significant

association

with

changes

in

industry

concentration.

With

regard

o

the

control

variables,

concentration

n

1981

(INDCONC81) s

significantly

and

negatively

associated

with

industry

concentration

n

all four

?

Blackwell

Pubhshers

Ltd. 1996


11/17

62

JULIA

PORTERLIEBESKIND

ETAL.

TABLE

IV

EFFECTS

OF

CORPORAT

RESTRUCTU

ON

INDUSTRY

CONCENTR

1981-1989.

(Ordinary

least

Squares

Regressions,

t-statistics

in

parentheses.

Dependent

variable

=

Change

in:

Four

Firm

Concentration

Ratio:

Herfindahl

Index:

Four

Firm

Concentration

Ratio:

Herfindahl

Index:

Full

Sample

Full

Sample

Manufacturing

Manufacturing

Intercept

0.1950

0.0766

0.1024

0.0105

(9.10)***

(5.85)***

(3.14)**

(0.58)

SELLOFF/EXIT

-0.0005

-0.0003

-0.0009

-0.0004

(-3.87)***

(-3.34)***

(-2.17)**

(-1.60)

SELLOFF/STAY

-0.0041

-0.0032

-0.0039

-0.0016

(-1.96)

(-2.29)**

(-1.74)*

(-1.20)

EXPAND/STAY

0.0003

0.0003

0.0003

0.0002

(0.80)

(1.08)

(0.53)

(0.68)

CLOSE/EXIT

-0.00008

-0.0001

0.0018

0.0012

(-0.23)

(-0.48)

(3.86)***

(4.37)***

CLOSE/STAY

-0.0006

-0.0004

-0.0013

-0.0003

(-1.37)

(-1.24)

(-1.83)*

(-0.62)

ADD/ENTER

-0.0003

-0.0001

-0.0014

-0.0010

(-7.50)***

(-3.01)***

(-4.76)***

(-5.39)***

ADD/STAY

0.0010

0.0005

0.0016

0.0008

(3.06)***

(2.32)**

(3.05)***

(1.61)

CHMES

0.0008

0.0003

0.0003

-0.00006

(3.87)***

(1.95)*

(0.99)

-(0.35)

lNDCONC81

-0.3403

-0.5730

-0.1468

-0.1126

(-14.98)***

(-19.62)***

(-4.68)***

(2.12)**

REGULATEa

0.0149

0.0001

(-0.83)

(-0.02)

CHSALES

0.0001

0.0001

0.0004

0.0004

(4.17)***

(4.85)***

(3.71)***

(5.54)***

Adjusted

R2

0.344

0.396

0.216

0.165

F

Value

34.13***

42.32***

11.72***

8.68***

N

(industries)

695

695

390

390

*(**)(***)

denotes

significance

at

the

10%

(5%)

(1%)

level.

'There

are

no

regulated

manufacuring

industries.

? Blackwell

Publshers

Ltd.

1996


12/17

RESTRUCTURING

AND

CONSOLIDATIONOF

US

INDUSTRY

63

regressions,

indicating

that

increases

in

concentration

duringthe

1980s mainly

took

place

in

those

industries

hatwere

the least

concentrated n

1981.

Industry

growth (CHSALES) s significantlyand positively associated with changes in

concentration,while

change

in

median

plant

scale

(CHMES) and

regulation

(REGULATE) ave

no

significant

effect.

Table V

presents

summary

results for

regressions

in the

subsamples of

producer

and

consumer

goods

industries,

non-manufacturing

ndustries,

and

industries

with

low,

relatively

high

and high

levels of

concentration n

1981.

Consistent

with the

regression

results

in

TableIV,

TableV

shows that

SELLOFFI

EXIT

s

significantly

and

negatively

associated with

change

in

concentration n

producer

and

non-manufacturing

ndustries.

SELLOFF/EXITs

also

significantly

and negatively associated with changes in concentration n industrieswith low

concentration n

1981.

Also

consistent

with the

results of the

main

regressions,

SELLOFFISTAY

s

significantly

and

negatively associated with

changes

in

concentration

only

in

non-manufacturing

ndustries,

while

CLOSE/EXIT s

significantlyand

positively

associated

with

changes

in

concentration n both

subsamples of

manufacturing

industries, and

also

in

industries

with

low

concentration n

1981.

ADDISTAYs

shown to

be

significantly

and

positively

associated with

changes

in

concentration n

consumer

goods

industries,

while

EXPANDISTAYs

shown to be

significantly

and

positively

associated with

changesin concentration n non-manufacturingndustries,even thoughit is not a

significant

determinant f

changes

in

concentration

n

the

main

regressions.

The

most

important

esult of

these

regression

analyses, given

the

purpose of

this

study,

s

the

consistentlysignificantand

negative

associationwe

find between

selloffs

measured

at

the

industrylevel

and

changes

in

industrial

concentration

during

the

1980s.

Recall that

our

measures

of

selloffs

capture

all

horizontal

mergers and inter-firm

asset

sales

in

sample

industries

between 1981

and 1989.

Therefore,this

finding

is

inconsistent with

the

argument hat

relaxed

antitrust

enforcement

during

the

1980s

resulted

n

mergers and inter-firm

asset

sales that

increased industrialconcentration

across

broad

samples

of US

industries.

In

addition,

he

significantand

economicallyimportant

negative

association

we find

between

prior levels of

industry concentration

INDCONC91)

and

changes

in

concentration

s

consistent

with a

claim of

continued

antitrust

vigilance.

Some

caution is

warranted

n

arriving

at this

interpretation,

however,

because we

consider

only

broad

samples

of

4-digit

industries

n

this

study.

Therefore,

our

results

cannot be

interpretedas

ruling out the

possibility

that

some

horizontal

mergers

and inter-firm

sset

sales

did result

n

increases n

concentration n

some

US

industries

during

the

1980s.

The

regressionsdo

show that

additions

of

capacity

by large

incumbentfirms

between

1981 and

1989

increased

ndustry

concentration.

However,

this

finding

indicates that

the

large

finns that

increasedtheir market

share

during

the 1980s

did so

by

internal

expansion,

rather

han

by

acquiring

rival

firms.

?

Blackwell Publshers

Ltd.

1996


13/17

64

JULIA

PORTER

LIEBESKIND

ETAL.

TABLE

V

THE

EFFECTS

OF

CORPORATE

REsTRucTuRING

ON

INDUSTRY

CONCENTRATION,

1981-1989

IN

SELECTED

SUBSAMPLES

OF

INDUSTRIES

(T-STATISTICS,

R2,

AND

VALUES

REPORTED

FROM

OLS

REGRESSIONS:

SEE

TABLE

IV

FOR

FULL

MODEL)

SELLOFFI

SELLOFF

EPAND

CLOSE

CLOSE

ADD

ADD

R2

F-Value

N

STAY

STAY

STAY

EXIT

STAY

ENTER

STAY

Industry

Subsamples:

Manufacturing:

Producer.

Four

firm:

-2.14**

-1.32

0.20

2.84**

-1.79**

-4.85***

1.68*

0.23

9.09***

297

Herfindahl:

-

1.90*

-0.85

0.49

2.93**

-0.50

-5.07***

0.11

0.20

8.30***

2947

Consumer:

Four

firm:

-1.72*

0.03

0.92

1.52

-0.57

0.54

3.74***

0.21

3.38***

93

Herfindahl:

-1.35

-0.81

1.82*

3.10***

-0.28

-1.35*

5.39***

0.42

7.79***

93

Non-manufacturing:

Four-firm:

-2.68***

-1.75

1.79*

1.44

1.00

-4.92***

1.32

0.36

18.16***

305

Herfindahl

-2.19**

-

1.83*

1.79*

0.57

0.30

-1.60

0.79

0.48

29.49***

305

Concentration

in

1981:a

Low:

Four-firm:

-4.08***

-0.18

0.51

2.14**

-

1.70*

-6.32***

3.00***

0.22

12.86***

411

Herfindahl

-3.48***

-0.77

0.66

3.24***

-0.72

-5.16***

1.83*

0.15

8.29***

411

Relatively

high:

Four-firm:

-0.42

-0.14

-0.08

-

1.81*

0.25

-4.52***

0.88

0.17

3.90***

138

Herfindahl:

-1.42

-0.06

-0.30

1.18

0.19

-3.83***

0.05

0.07

2.17***

139

High:

Four-firm:

-1.30

-2.49*

1.12

-1.72*

-0.83

-2.41***

1.11

0.19

4.47***

145

Herfindahl:

-2.17*

-1.57

0.91

-0.46

0.17

0.02

0.43

0.50

15.63***

145

*

(*)

(***)

denotes

significance

at

the

10%

(5%)

(1%)

level.

aIndusty

concentration

categories

are

defined

for

each

4-digit

SIC

industry

following

Department

of

Justice

guidelines

as

follows:

High

Concentration:

Herfindahi

Index

>

0.18;

Relatively

High

Concentration:

0.10

<

Herfindahi

Index

<

0.18;

Low

Concentration:

Herfindahl

Index

<

0.10.

?

Blackwell

Publishers

Ltd.

1996


14/17

RESTRUCTURING

AND CONSOLIDATION

OF

US INDUSTRY

65

VI. SUMMARY

AND CONCLUDING

REMARKS

The purpose

of this study

has been

to document the

changes

in US industrial

concentrationduring he 1980s andto investigatewhethercorporate estructuring

was

a

determinant

of any changes in concentration.Although

there has been

extensive debate

regarding he effects

of corporaterestructuring

n US industry,

we are

not

aware

of any other study

that has examined

this issue

in

detail.

This

study

has

sought

to

fill

this gap

in

our knowledge

about

the

aggregate

effects

of

corporaterestructuring

and to inform the

on-going

policy debate about

the

regulation

of corporate

control transactions

n the US. Based on

a broadsample

of 695 4-digit

US industries,and

a number of industry sub-samples,

this study

finds

no evidence that

horizontalmergersor

inter-firm sset sales

wereassociated

with increasing ndustryconcentrationduringthe 1980s.

JULIAN

PORTER

LIEBESKIND,

ACCEPTED

MAY

1995

School of

Business

Administration,

Universityof

Southern California,

Los Angeles,

California

90089-1421,

USA

TIM C. OPLER,

Department

of

Finance,

Max

M

Fisher

College

of Business,

Ohio State

University,

1775

College Road,

Columbus,

OH

43210,

USA

and

DONALD E.

HATFIELD,

Departmentof Management,

R. B.

Pamplin College of

Business,

VirginiaPolytechnic

Instituteand State University,

Blacksburg,

VA.24061-0233,

USA

APPENDIX: DETAILS OF

TRINET INC.'S

LARGE ESTABLISHMENT

DATABASE

TRINET, Inc.'s Large

Establishment

Database was originally

developed by

Economic

Information Systems, Inc.,

(EIS) for

sale to companies

involved

in

direct industrial

marketing. The database contains a variety of information on manufacturing and non-

manufacturing

establishments

with more

than 20 employees

in

the US

only.

The data

are

derived from a

variety

of

sources,

including

state and

county

industrial directories,

corporate

reports,

trade

association and Chamber

of Commerce directories,

the trade

press,

telephone

directories,

and mailing lists. Data

are cross-checked with

the Census Bureau's

County

Business

Patterns,

and

by telephone

calls.

All

of the data

are

subject

to continuous

update

and

review;

this is

essential,

because the database

is sold for

marketing purposes.

(C

Blackwell

Publishers

Ltd. 1996


15/17

66

JULIA PORTERLIEBESKIND

ETAL.

The Large

Establishment

Database was first

established

in

1968.

In the late 1970s, the

database was sold

by

EIS

to

TRINET,

Inc.

In

this

study,

we refer to this database as the

"TRINET data." New versions

of the database

were issued commercially by

TRINET each

year during the 1980s. Data

were released

for research purposes only on

tape in 1981,

1983, 1985, 1987 and 1989.

Data for earlier

years were obtained by some researchers

from

EIS. (See, for example, Montgomery

and

Wemerfelt, 1988, who use EIS data

from 1976.)

A detailed

discussion of the reliability of

the Large Establishment Database

is given by

Kwoka, "Economic Information

Systems,

Inc. (EIS)

Market

Share

Data: Nature,

Reliability, and Uses," American

Bar Association Antitrust Journal, 47, pp.

1089-1098.

Kwoka considers the Large

Establishment

Database

to be

generally

reliable:

"The sheer volume of

these data make total

accuracy impossible, of course,

but by and

large,

the data are judged

to have substantial reliability."

(Kwoka, 1978, page 1093.)

Comparing the TRINET data and Census market share data for 314 manufacturing

industries

in

1972,

Kwoka found a cross-sectional

correlation of 0.922 for

the

four-firm

concentration

ratio

(CR4).

However,

he noted that deviations between

the

Census data

and

the TRINET data are not completely random,

as

follows:

(i) The

diferences

in concentration between

Census data

and TRfINETdata are larger

for

small industries

than

for large

industries.

In this

study,

we correct for

this

possible

source of bias

by

eliminating very small

industries

from our sample. (See page

5 of the text for details.)

(ii) The

differences

in concentration

between Census data

and

TRINET

data

are smaller

in

more

concentrated

industries.

This bias will not result in failure to measure industries where concentration

increased

between

1981 and 1989,

which

are

of interest

in

this study.

(iii) There

is some systematic

over-estimation of concentration

in the TRINET

data.

The

most

likely

source for this bias,

in

our

view,

is that

TRINET

includes only

establishments

employing

20 or more

persons. Consequently,

concentration will be

over-estimated

for industries

with

many

small establishments

operated

by many

small

firms.

In

addition,

this

bias

can

be

expected

to

create

larger

differences

between the

Census

data and the

TRINET data in

measuring

the

Herfindahl

index,

than

in

measuring

the four-finn ratio.

We

compared

the concentration

ratios in the Census

of Manufactures

with

those

estimated in this study for the manufacturing sector. Unfortunately, we were unable to

compare these for identical

years,

as did Kowka, because

the Census

of

Manufactures

was

conducted

in

1982 and 1987

only,

whereas we use

TRINET data

from

1981 and 1989.

In

addition,

the

classification

of

4-digit

SIC codes

in

the Census was

changed

between 1982

and

1987.

Nonetheless,

we

find a cross-sectional correlation

in

the four-firm ratio

of

0.665

(p

<

0.001)

between

TRINET

1981

and Census

of Manufactures

1982

data,

and 0.761

(p

<

0.001)

between

TRINET 1989 and Census

1987 data.

The

cross-sectional

correlations for

the Herfindahl index are

lower: 0.559

(p

<

0.001)

and 0.478

(p

<

0.001)

respectively.

This

lower

correlation is most probably

due to

systematic

biases

in the

TRINET and Census data

which differentially

affect measurement of

this ratio.

First,

establishments with less than

20

employees

are not

reported

in TRINET

but are included

in

the Census estimates

of concentration.

Second,

the

Herfindahl

ratios

in

the

Census are

estimated

for

only

the

top

50

finns,

whereas we

estimate

them for all

firms

in

a

given

industry.

In

our

sample,

73% of

manufacturing

industries

in

1981 had more than

50

firms,

and 81% had more

than 50 firms

in

1989.

Because data on

large

establishments,

and the

establishments

of

larger

finns,

is more

likely

to

be

reliable

than data on

smaller

establishments,

and

the establishments of

smaller

finns

(biases

that also apply

to the Census

data,

as discussed

by Dunne,

Roberts and

C) Blackwell Publshers

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16/17

RESTRUCTURINGAND CONSOLIDATIONOF

US INDUSTRY

67

TABLE

A.I

ESTABLISHMENTSDDED BY SIZE

CLASS BETWEEN 981 AND 1989 ACCORDiNGTO

CoUNTRY

BuSINESS

PArrERNS

Yearand Source

Size Class:

20-49

50-99 100-249 250-499 500-999

1000

<

A. All industries:

1981:

379,303 130,880

71.453 20,209 7,986

4,700

1989: 495,678

172,323 95,291

23,898 9,437 5,489

Change:

+30.7%

+31.7% +33.4%

+

18.2%

+

18.2%

+

16.8%

B.

Manufacturingndustriesonly:

1981: 56,179 28,370 23,121 8.902 3,923 2.354

1989:

59,965 30,832

24,327 8,799 3,679

1,986

Change:

+6.7% +8.7% +5.2% - 1.1 -

6.3%

-

16.5%

Samuelson

[1988]),

and because TRINET has increased the

accuracy

of

its

reporting

of

small establishments

over

time,

we restrict our

sample

in this

study to establishments with

100 or

more employees. However, this raises

the question

of

whether such a truncation

procedure differentially eliminates smaller

establishments

added between 1981 and 1989,

resulting

in

biases of concentration ratios and

MES. As

shown in

Table A.I

below,

according

to

Country

Business

Patterns,

the

highest

rates

of overall establishment addition

between 1981 and 1989 took place among establishments with 100-249 employees. Rates

of addition were

lower

in

both

larger

and

smaller establishments.

In

contrast,

in

the

manufacturing

sector,

rates

of establishment addition

were higher

among

smaller

establishments, and

the

number

of

large

establishments decreased. To

examine

possible

bias of

our results from

using

the 100

employee

cutoff

level,

we conducted

additional

regressions

that

included smaller

establishments. We found

that

our regression results

were

not highly sensitive to the elimination

of smaller establishments

in

either the full

sample of

695

industries,

or

in

the

subsample

of 390

manufacturing

industries.

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