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Import competition, investment

finance, and cumulative

decline in the US steel industry,

19621981Robert A. Blecker

a

aAmerican University , Washington

Published online: 02 Nov 2006.

To cite this article:Robert A. Blecker (1991) Import competition, investment finance,

and cumulative decline in the US steel industry, 19621981, International Review of

Applied Economics, 5:2, 171-195, DOI: 10.1080/758533096

To link to this article: http://dx.doi.org/10.1080/758533096

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Import competition investment

finance and cumulative decline in the

US steel industry

1

962-

1

9

Robert A Blecker American University Washington

This paper ana lyses the effects of imp ort com petit ion on th e financing of invest-

ment in the US steel industry. M odel simulations show tha t impo rt penetration

reduced average annual investment spending by about one-quarter over the

period 1962-81, mostly as the result of a sque eze o n profit mar gins which con -

strained internal finance. A ssuming tha t this reduction is investment caused pro-

ductivity growth to slow down, the benefits of allowing imports for steel

consume rs are estimated to have been relatively small in the long run. Th e

analysis supports the concept of cumulative causation in competit iveness due

to constraints on investment financing.

ntroduction

You can t stan d still in this new industrial er a. If you don t expa nd a nd m ove

ahead you are going backward. T he longer you take to m ake u p your mind what

you are going to d o the fur ther ahead your compet i tor has gone - and the harder

it will be for you to m ak e up lost t ime; if you ca n. (Editorial .

The Iron Age

January 1956)

This quote from the leading U S steel industry trade journal was written pro-

phetically at a time when industry executives insisted that apart from their

labour unions) they had no fundamental problems to worry about see

Means, 1962; Broude, 1963). Only a few years later, the industry began to

face an onslaught of imports which revealed a genuine loss of competi-

tiveness, as documented by the U S Federal Trade Commission FTC, 1977),

Anderson and Kreinin 1981), Crandall l981), and Barnett and Schorsch

1983). The editorial suggests that a small initial competitive disadvantage

The author would like to thank Donald Harris, Bert Hickman, Nathan Rosenberg, and Gavin

Wright for help at various stages in this project, and David Houston, Fred Lee, and two

anonymous referees for helpful comments on earlier drafts. Robert Crandall, Mary Deily.

and Jerome Mark provided some of the data series. The American University and the

Economic Policy Institute provided financial support. The author a lone is responsible for the

views expressed here and any remaining errors.

,

O Edward Arnold

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172

Import competition investment finance and cumulative decline

could permanently set back the development o f the affected firms. A lthoug h

orth od ox neoclassical econom ists have traditiona lly dismissed such ideas, at

least until recently (see, for example, Krugman, 1981), such a notion of

fai lure breeding further decl ine appears as s imple common sense to the

business press.

Outside of neoclassical or tho dox y, the principle of cumu lat ive causat ion

has long been accepted by neo-Keynesian economists, especially Kaldor

(1970; 1972). In Kaldor s conc eption , cum ulative causatio n results fun da-

mentally fro m increasing returns t o scale, broadly defined t o include learn-

ing effects, induced innovation, and increasing specialization as well as

static scale econom ies. According t o Kaldor s laws, productivity grow th in

manufacturing depends on the rate of investment in capi tal equipment

embod ying new technology; the rate of investment in turn d epen ds primarily

o n the growth of dem and : Accumulat ion is f inanced out of business profits ;

the growth of demand in turn is largely responsible for providing both the

inducements to invest capital in industry and also the means of financing

it. (Targe tti an d

Thirlw all, 1989: 314).

This Kaldo rian perspective is incom plete, however, a s i t omits the equal ly

crucial role of the profit markup or price-cost margin. As Kalecki (1971),

Steindl (1952), an d E ichner (1976) em phas ized, the firm generates the gross

profits or cash flow required t o fina nce its accumu lation internally (as well

as to at t ra ct external fu nds) largely through i ts abi li ty to maintain an ade-

qu ate price-cost margin. T he abili ty to main tain this margin is cons trained,

in tur n, by a num ber of factors, including interna tional com petition. Recent

studies by Dornbusch (1987), Feinberg (1986; 1989), Karier (1988), Mann

(1986), and H oop er an d M ann (1989) have shown that im port penetrat ion

and currency appreciation can induce oligopolistic firms to cut profit

margins, both in theory an d in practice. An d the work of F azzari an d M ott

(1986-87), Fazz ari and Athey (1987), an d Fazzari

e t a / .

1988) has confirmed

that financing constraints (internal cash flows) are important for l imiting

investment spending.

These considerations imply a mechanism of cumulative causation for

industrial competitiveness. Industrial firms must invest in new plant and

equipment, embodying new vintages of technology, as well as engage in

research and development, sales promotion, and other activities required

to remain competi t ive and to expand their markets . This implies that the

development of an industry d epends on , amo ng other things, the abi li ty of

the firms that co mp rise it to raise the capital fun ds required to finance their

investment programmes and other competitiveness-enhancing activities.

Therefore, one of the main ways in which success breeds further success is

the abili ty of successful firms to make above-normal profits which can be

ploughed back into further investment and innovat ion. In addit ion, f i rms

must be able to expand their markets fast eno ugh t o justi fy continued high

rates of accumulat ion. Correspondingly, depressed profi ts and demand



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Robert

A lecker 173

can prevent firms from making the expenditures required to restore their

competitiveness.

Thes e factors suggest th e possibility of 'hysteresis' in inte rna tion al com -

peti tive advan tages or disadvantages.' In a n open econom y, the com-

petitive position of national firms vis a vis their foreign rivals affects their

price-cost m argins as well as the dem and for their produc ts . T he m arku p

rate and output level together determine the internal flow of funds (given

fixed costs). T he flow of internal funds , together with the growth of d em and

for nat ional products , affects the am ou nt of investment an d other expen-

ditures which firms are able and willing to make in order to improve the

efficiency and quality of their production.' If most of th e firms in an

industry cann ot m aintain the level of expenditures required to bolster their

competitiveness, then they may fall into a vicious circle of cumulative

decline.

In principle, the mechanism described here really applies to individual

firms rather than national industries; different firms located (or based) in

the same nation may be affected unevenly by the same competitive forces

depending o n their respective cost structures, mark et shares, financial posi-

tions, etc. Nevertheless, the concept o f th e na tion al industry is a useful level

of aggregation for US steel prod ucers for several reasons. First , global steel

production has generally been dominated by national rather than multina-

tional firms, a nd there was n o tendency o f US steel firms to invest overseas.

Secondly, until the 1980s. US steel production was highly concentrated

am on g a gro up of large oligopolistic firms with generally similar structura l

characteristics. The largest of these, the United States Steel Corporation,

was a declining dominant firm with no significant cost advantage in its

steelmak ing op era tion s (Sche rer, 1980: 239-40). Alth ou gh U S steel was

larger tha n its rival firms, its plan ts were similar in size a n d techno logy. O nly

with th e emergence of minimills in the late 1970s an d early 1980s did th e

industry structure become m ore heterogeneous. Th irdly, firm-level da ta are

not available for many of the variables needed for this study.

In a previous pa per (Blecker, 1989), con firm ed that price-cost marg ins

for American steel products became sensitive to imports (as well as to

demand conditions) after a structural break in 1962, when imports per-

manently surpassed 5 of th e domest ic market . In this paper , I est imate

how this squeeze on profit margins, along with reduced demand, affected

the financing of capital accum ulation in the U S steel industry in the 1960s

an d 1970s. In orde r to s tudy this effect of import penetrat ion, ad op t the

methodology of th e 'cliometric ' e cono mic historian by simulating a model

A

similar argument, posed at the macro level (for the manufacturing sector as a whole), is

found in Singh

(1977).

2

Note that this implies the possibility of

a

trade-off, if a nation s firms can gain greater world

market share by reducing their profit margins.

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174 Im port competition, investment finance, a n d cum ulative decline

of industry behaviour under counterfactual assumptions about the degree

of impo rt penetration. The m ain results which are obtained from this exer-

cise are estimates of the cum ulative loss of investment du e to the increase

in im ports fro m 1962 t o 1981. Specifically, it is foun d tha t im port penetra-

tion curtailed investment in the steel industry by about one-quarter com-

pared with the baseline forecast of the mode l.

In the model presented in this paper, d o not endogenize the feedback

erfects that additional investment w ould have had in raising t he industry s

productivity. Nor do atte m pt to estimate how wages (and other input

prices) would have behaved differently in the counte rfac tual sce narios. Unit

labour (as well as materials) costs are taken as exogenously given in the

estimation of the model. However, some crude estimates of the impact of

endogenous technical progress are ma de by runnin g sim ulations in which a

higher rate of investment is accompanied by more rapid growth of labour

productivity, and com paring these simulations with static ones assuming

exogenously fixed productivity gr ow th. The reasons fo r this procedu re are

discussed below.

In focusing on the role of im por ts in the decline of the U S steel industry,

d o not mean t o deny that a considerable part of the industry s problems

in the 1960s an d 1970s must be attributed to dom estic structural changes

which slowed the growth of steel dem and , as argued by B arnett an d Schorsch

(1983), Law rence (1983), an d G rossm an (1 986), am ong others. Nevertheless,

in view of the continued debate over trade policy for steel, it is still worth

investigating the mechanisms by which import competition can affect the

development of the industry an d the consequences of doing nothing in

response. W hat kind o f governm ent intervention, if a ny, was or is warra nted

for the U S steel industry is a sepa rate que stion which is beyond th e scope

of this paper.

The rest of the paper is organized as follows. Section I1 describes the

model of the industry and discusses the theoretical rationale for the indi-

vidual eq uatio ns. S ection 111 discusses the results o f th e m odel s imulations

for the effects of imports on investment financing, assuming fixed labour

productivity. Section IV then co mpa res the results of a simula tion in which

labour productivity is assumed to increase more rapidly when investment is

higher. Section V concludes by considering som e of the implications of the

analysis for both theory and policy. Diagnostic statistic on the fit of the

model are presented in an Appendix.

I Estimated equations of the model

The model described in this section draws upon and extends the pre-

vious econometric work of Mancke (1968), Rippe (1970), Jondrow (1978).

Cran dall(1981), a nd Blecker (1989). Th e core of th e model is the price equa-

tion, which captures the effect of import competition on the price-cost

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obertA lecker

175

margin. In addition, equat ions for total dem and an d import demand show

how the growth of the internal m arket a nd th e import sh are are determined

by relative prices an d other variables. Dem and c ond itions are then tran slated

into domestic outp ut levels an d util ization rates. T he price-cost m argin an d

the level of output explain the flow of internal funds, given tax rates and

overhead costs. The flow of internal funds and the util ization rate in turn

are the main variables used to explain investment expenditures, as accel-

erator effects turn out to be insignificant. The model also keeps track of

several important feedbacks, including the dividend payout rate and the

grow th of capacity, while using dum m y variables to contro l fo r certain uni-

que historical episodes (the Korean War, the 1959 strike).

Estimated equations and identities for the complete model are given in

Tab le 1. Th e model is estimated using a nn ua l industry-level t ime series for

reasons of data availabili ty. The sample period starts in the first year for

which the necessary lags of all th e variables ar e available, which is 1949 fo r

most of the equat ions (see the notes t o Tab le 1 for exceptions) . Th e sample

period en ds in 1981, just be fore the recession of 1982 which dram atically

transfo rme d the industry s s tructure. In the crisis of 1982-83, the large,

integrated producers accelerated their ab and onm ent o f capaci ty an d diver-

sification out of steel, while the small, competitive mini-mills took over a

rapidly r is ing share of the shrinking domest ic s teel market (Barnet t and

Crandall , 1986). The proportion of nonsteel investment spending by steel

firms rose sharply in the early 1980s as they moved to diversify m ore rapidly.

Nonsteel capital expenditures averaged about one-third of the total in

1979-81, an d then jumped to ab ou t one-half in 1982-84, according to

American Iron and Steel Institute (AISI) data.

The equations were estimated by 2SLS. except as noted in the table.

All variables for which no e qua tion is given in Ta ble 1 we re treated a s

exogenous; lagged endogenous variables were treated as predetermined

(except in equation 1.8). Limited information estimation procedures were

preferred du e to the sm all sample s ize (33 observations), an d so th at a ny

possible errors in the specification of o ne equa tion would not bias the esti-

mation o f the other eq uation s. Since the m ain objective is prediction, rather

than hypothesis testing, a few variables which improved the fit of the

baseline forecast are retained in spite of t-statistics which are low by tradi-

tional standards.

In discussing the individual equa tions, i t is useful to star t with the invest-

ment functio n which is so crucial to th e results. A s discussed abov e, th e neo-

Keynesian tradition contains two approaches to investment: one which

emphasizes the growth of demand ( the accelerator) and one which

emphasizes profitability (price-cost margins). In the case of the US steel

3

Separate steel and nonsteel investment series are not available before 1979



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176

Import com petition investment finance and cumulative decline

able

Estimated equations of the model

l . l)aNVEST,

= -

1.25

+

,367 INTFUND,_, + ,361 INTFUND,_;,

+

1.17 CAPUTIL,

(- 2. 09 ) (3.17 ) (3.641 (2.731

+0.7 1 C A P U T I L ,

,

+ 0.73 DKOREA, + 0.73 DSTRIKE,

_

,

(1.4 2) 13.74) (4.1 3)

Rho

= ,635

(4.18)

(Adjusted R2

=

,778; Durbin-Watson = 1.5831.

1 1 . 2 ) ~og INTFUND,

=

6.71 + 1.17 log MARGIN, + 0.55 log OUTPUT,

(2.651 (2. 51) (1.681

0.6 4 log TAXRATE, 1 14 log OVERHEAD, Rho = ,488

( - 1 581

1

- 2.47) (2.69)

Adjusted

~ =

573; Durb~n-Watson

=

1.841

1 3) MARGIN,

=

PRICE, - UNICO S TII PIN VESTI (Identity)

1.4IC

og

PRICE, =

166

+

.51 1 log UNITCOST, + 402 log UNITCOST,_ ,

1-0.87)

5.81)

(4.11)

+ ,161 log DIVPNT, + . I 84 log OVERHEAD,

4 06) (3.21)

+

,394 (01962,

x 10s

CAPUTIL,) ,058 (01962, x log IMPSHARE,)

(3 .29) ( -0 .71)

(Adjusted R2

=

.995; Durbln-Watson

=

1.834).

I1 5)d og DIVPNT,

=

- 943 + .61 1 log D I VPN T, _ , + 168 log I N TFU N D , - ,

-

1.71) 16.21)

2

18)

+

,091 log UNITCOST,

11.88)

Adjusted R Z

=

,766; Durbin s h

=

0.581

(1.6) CAPUTIL, = OUTPUT,ICAPACITY,. (Identity)

(1 7Ie

OUTPUT, =

1.38

+

1.12

DOMCONS,

-

IMPORTS,)

(0.38) (24 8)

Adjusted R~

=

.951; Durbin-Watson

=

1.375)

(1.8) CAPACITY,

=

8.61

+

,893 CAPACITY,-, + 1.52 INVEST,-, + 019 OUTPUT,_,

(4.2 7) (42 1) (4.3 4) (1.381

Rho

=

,434

(2 371

(Adjusted R2

=

,996; Durbin s h = 0.989).

(1 9) IMPSHARE, = IMPORTS,IDOMCONS,

(Identity1

(1.1019 log

IMPORTS, =

16.4

+

453 log IMPORTS,_

,

+ 1.42 log PRICE,

(- 4. 69 ) 16 26) (4.53 )

- 1.33 log IMPP91CE,

+

1.81 log DOMCONS, + ,735 DSTRIKE,

- 4.671 (5.2 5) (3.16)

(Adjusted R2 = ,966; Durbin h

=

1 238).

(1.11

)9

log

DOMCONS,

=

14 4

-

502 log

PRICE,

+

,453 log

PPINFMET,

23 . 1 ) (-4.00) (2.97)

+

,777 log

YMFR,

,00025 r

17.62)

-

1.081

(Adjusted

R 2

= .891; Durb~n-Watson

=

2.1 18)

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Robert A. Blecker

177

Notes

All stochastic equations were estimated over 194 9-19 81 by 2SLS unless otherwise

noted.

Numbers in parentheses are t-statistics.

'Log' means the natural logarithm.

See text for definitions of variables.

a

Estimated over 19 51 81 by Fair's ( 1970) method. INVEST and INTFUND are measured

in bill ions of 197 2 dollars. The sum of the coefficients on INTFUND is ,729. with a

r-statistic of 5.23. The sum of the coefficients on CAPUTIL is 1.89, with a r-statistic of

2 .73 .

Estimated over 19 50-8 1 by Fair's (1 97 0) method . INTFUND is measured in millions of

19 72 dollars; OUTPUT is based on 1977

=

1 O.

The sum of the coefficients on current and lagged

UNITCOST

is ,913 , wit h a t-statistic of

39 .5 for the null hypothesis that the sum equals zero. The null hypothesis that the su m equals

unity can be rejected at the 5 level (r-statistic of 3 .7 5 ).

Estimated by OLS INTFUND is measured in millions of 19 72 dollars.

OUTPUT

is based on 1977

=

100;

OOMCONS

and

IMPORTS

are measured in billions of

net tons.

Estimated over 195 1-81 by limited information two-step procedure la) in Hatanaka (19761.

CAPACITY

and

OUTPUT

are based on 197 7 output

=

100;

INVEST

is measured in billions

of 1972 dollars.

IMPORTS and DOMCONS are measured in thousand net tons.

industry, accelerator effects turn out to have been statistically insignificant,

although demand played a role through the effects of capacity utilization

rates. O n the other h and , profitability (as measured by lagged flows of inter-

nal funds) was highly significant in explaining steel investment. These con-

clusions may be drawn from the fol lowing regression e q ~ a t i o n : ~

INVEST, 1.95 004 ASHIP, 010 ASHIP,-, 001 ASHIP,-,

( - 1.38) -0.34) -0.74) -0.16)

002 ASHIP,-3 + .349 INTFUND,-

+ .229 INTFUND,-2

-0.28) 2.19) 1.39)

+

1.58 CAPUTIL,

+

1.49 CAPUTIL,- , 0.68 DKOREA,

1.04) 1.06) 3.25)

+

0.84

DSTRIKE,- , ,

ho

.727

)

4.23) 4.54)

(Adjusted R

=

,748; Durbin-Watson 1.568).

In equation I), the depend ent variable IN V ES T is new plant and equip-

ment expenditures in blast furnaces and steel works measured in constant

1972 dollars (US Department of Commerce, 1985). The accelerator effect

is represented by the distributed lag of AS HI P, w hich is the annu al increase

in net product shipments (from AISI). Profitability is represented by INT-

FU ND , which is internal funds (co rpo rate net income plus depreciation plus

the change in reserves minus dividends), calculated from AISl financial

4 The sample period is 1951 81. The equation was estimated by in strum enta l variables using

Fair's (1970) method. Numbers in parentheses are ;-statistics.

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178 Import competition, investment finance, and cumulative decline

data, and expressed in constant 1972

dollar^.^

CAPUTIL is the Federal

Reserve Board (FRB) index of capacity utilization in iron and steel.

DKOREA is a dummy variable set equal to 1 in 1952 to control for the

Korean War investment boom.

DSTRIKE

is a dummy variable for the 1959

strike, which is included with a one-year lag to capture the postponement

of investment expenditures until after the strike ended.

Since all the coefficients on the various lags of ASHIP are negative and

insignifi~ant,~quation (1) was rerun with these variables omitted. The

resulting specification is shown as equation (1.1) in Table 1. Note that,

when the accelerator terms are omitted, the coefficients on internal funds

INTFUND)are higher and more significant, while those on the utilization

rate are lower but also more significant.

Internal funds are determined by the simple accounting identity:

F

[ P-c)x-

] I -

,

2)

where ?r is internal funds, P is the price, C is average variable cost (unit

labour plus unit materials costs),

X

is output, F is fixed costs, and 7 is the

corporate tax rate. Since replacement investment generally raises produc-

tivity and thereby increases capacity, we are concerned with gross invest-

ment. Therefore, depreciation allowances are treated as part of the cash flow

or internal funds available to finance gross investment, rather than as part

of fixed costs.

The real amount of gross profit in terms of output is:

where P C) /Pi s the price-cost margin (PCM). Alternatively, real internal

funds can be measured in terms of their command over capital goods:

where Pi is a price index for investment expenditures. Rearranging (2b) and

taking natural logarithms yields:

log

? r / ~ ; )

log [ P

c)/P;]

log

1 7

log

X

log (1

)

3)

Th e AlSl financial da ta were deflated using the implicit price deflato r for new plant and equip-

ment expenditures in blast f urna ces and steel works

P I N V E S T )

based on 1972 100. Th e

financial data were corrected fo r the varying percentage of f irm s reporting each year by

dividing by the reporting firms' share of product shipments.

6 The sum of the coefficients on ASHIP is -.018 with a -statistic of -0.49 , which is also

insignificant. Th e insignificance of the accelerator ter ms in equ ation 1) probably reflects the

flat trend of shipments in the US steel industry, which grew at a n average annua l rate of under

I % during the sample period. Th e mean ann ual ch ange in shipments is not s ignificantly dif-

ferent from zero at the

5%

level. Assuming that steel firms did not expect any long-term

grow th of dem and , they would view increases in dema nd m erely a s cyclical fluc tuation s.

~ ~ p a r e n t l ~teel firms didrespond to cyclical effects, judging from the positive coefficients

on the utilization rate.

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Robert A. Blecker

179

where

= F / P - O X .

Although equation (3) is an accounting identity,

consistent measures of all the variables in equation (3) are not available. I

therefore treat equation

(3)

a s stochastic equ ation (1.2) in Ta ble 1.

MARGIN

is the constant-dollar profit margin, defined by identity (1.3) in the table.

OUTPUT is the FRB index for the iron and steel industry (1977 = 100).

T A X R A T E is the ave rage effective tax rate for all man ufactu ring corp o-

r a t i o n ~ . ~

VERHEAD,

which is used as a proxy for f, is the ratio of the

Bureau of Labor Statistics (BLS) index of nonproduction worker hours to

the index for production worker hours in steel (1977 = 100).

Identity (1.3) defines the gross profit margin in constant 1972 dollars.

PRICE is the average realized price of all steel products, in current dollars

per net ton, calculated from Census Bureau and AISI data. UNITCOST

is the average direct cost of prod uctio n workers labo ur plus seven raw

materials (iron o re, coking co al, noncoking coal, steel scrap, fuel oil, pur-

chased electricity, and natural gas) in current price^.^

Eq uatio n (1.4) then explains the price level, allowing chan ges in unit costs

to be passed on over tw o years. PRICE also depends on the dividend payout

rate, overhead costs, and after a structural break when imports became

firmly established in the early 1960s (D l96 2 is a du m my variable equ al to

on e in 1962-81 and zero earlier) im po rt pene tration and capacity utiliza-

tion. Previous studies (Mancke, 1968; Crandall, 1981; Blecker, 1989) have

confirmed the hypothesis of such a structural break, which is simply

assumed here.

DIVPNT

is cash dividends paid, in current dollars per net

ton of

trend

produ ct shipm ents, calculated from AISI series. Dividends

are included as a proxy fo r the managers. sense of their firms. ma rket

power (see Adelman, 1961; Means, 1962 .

IMPSH RE

is the share of

imports in apparent supply (AISI). The price equation is not linearly

hom ogeneous with respect to direct costs, as the sum of the coefficients o n

UNITCOST

is significantly below unity (see Table I, note c). Apparently,

the combined pressures of trade union strength at home and intensifying

TAX RA TE is the ratio of taxes paid af ter credits to income subject to tax, for total m anufac-

turing, from US Internal Revenue Service, Storisrics of incom e corpo rurion tux returns .

This is used as an instrument for the actual effective tax rate for the steel industry, which

would not be independent of the industry s realized profitability .

Th e method of calculating the average realized price was adapted from Crand all (1981),

a s explained in Blecker (1989). D etails on the deriv ation of all th e dat a series used in this

paper are available from the autho r o n request .

Th e calculation of m aterials costs was based on the sources and procedures used in US FT

(1977). with some modifications. Th e main source for physical input d ata was AISI. T he

BLS index of production worker hours (1977

=

100) was used fo r the labo ur inp ut, scaled

by the A lSl figure for wage employee hour s (divided by the percentage of f irms reporting)

for 1977. Th e wage rate is the AlS l measure of t otal employment cost per hour for wage

employees. Raw materials and energy prices were calculated from a variety of public and

private sources. Details are available from the aut hor on request.

l a

Th e log-linear time trend of net prod uct shipme nts over 1945-83 is used fo r the den om ina tor

o f D lV PN T to eliminate the effects of cyclical fluctuations in demand , which would be cor-

related with CAPUTIL.

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180 Im po rt competit ion, investment f inance, a n d cumu lat ive decline

competition from abroad prevented US steel firms from fully passing on

their increases in direct costs.

Th e specification of dividends in (1.5) is ada pte d fro m L intner (1956). Th e

current payout decision is based on the past level of dividends, with

adjustments made according to recent profitabili ty. I use one-year lagged

IN TF UN D to represent profitabil ity, s ince using current IN TF UN D would

result in circular reasoning in the contex t of the present mo del. Since

DI V PN Ti s measured in nominal dollars , a l so add UNIT CO ST to cont ro l

for inf lat ion, assuming th at f i rms try to make nominal dividend payments

keep pace with wages and other costs (Eichner, 1976).

Equation (1.6) is an identity for capacity util ization. CAPACITY is the

FRB index based on 1977 ou tpu t 100. Equ ation (1.7) is used to link the

F R B

outp ut index to the physical da ta for s teel product d em and : domestic

consum ption (DOM CONS), measured by 'apparent supply ' (net shipments

plus imports minus exports) , and IMPORTS. Equation (1.8) for s teel

capacity is based o n the presum ption tha t past capacity is adde d t o by one-

year lagged real investment (INV ES 7). Lagged O U T P U T is also included

as a proxy for expected changes in dem an d, which affect t he rate a t which

old capacity is retired. Includ ing this variable improved the baseline forecast

of the equation, in spite of the low /-statistic.

Equat ions (1.9) to (1.11) determine the import share, import demand,

and total d em an d, respectively. Following a suggestion of Rippe (1970: 42),

I include lagged im ports in the imp ort de ma nd equa tion (1.10) to represent

' the learning process involved in the purch ase of imports ' . I M P R I C E is

the weighted average price of imports of five major carbon steel products

(bars, cold- and hot-rolled sheet, plate, and structurals), including esti-

mated freight, insurance, an d custom s charges. Th e relatively high price-

elasticity of demand for steel imports (about 1.4 in the short run and 2.6

in the long ru n) indicates that foreign steel products were good substitutes

fo r domest ic products . Domest ic consumption (DOM CO NS) is the total

demand for steel products, measured by 'apparent supply' (domestic ship-

ments plus net imports) . Th e DS TR IK E dum my is used to con trol for the

surge of imports d uring th e 1959 str ike.

Th e BLS producer price index fo r nonferrous metals (P PI N FM E 7) is used

in ( I . 11) to represent the price o f substitute materials. YMFR is the FR B

index of man ufacturin g o ut pu t, used as a proxy for the 'income' of steel con-

sumers. Note that overall steel demand is relatively income-inelastic,

INT FUN D is a function of MA RG IN by 1.2 ). Since MA RG IN PRICE- /TOTCOST)/

PINVESTby

1.3) ,

and PR ICE is a function of D l VPNT by

1.4).

if DIVPN Twer e a func-

tion of current INTFUND, then current DIVPNT would be a function of itself.

12

This measure was adapted and extended from data in Crandall 1981). a s explained in

Blecker 1989). The weights are the shares of each product type in net shipments.

13 The PPIs for concrete products and plastic materials result in similar estimated coefficients,

but PPIN FM ET yields the best fit.

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Robert A Blecker 18 1

which reflects the s tructu ral decline in steel usage in an advanced economy.

The negative time-squared trend also indicates accelerating technical pro-

gress in findin g substitutes fo r steel.I4 And the sensitivity of to tal steel

demand to relative prices may also be conceptualized as reflecting technical

progress. Following Rosenberg's (1976) view of rising ma terials prices as an

'inducement mechanism' or 'focusing device' for technological innovation,

the rising relative price of steel in the postwar US economy can be said to

have induced a cum ulative innovative effort aimed a t reducing the steel con-

tent of national output. The fact that innovation is required, rather than a

costless shift along a given production function, probably accounts for the

relative price inelasticity of total steel demand (elasticity of about 0.5).

ffects of imports on investment financing

Th e effects of im port penetration o n capital accumulation in the US steel

industry are estimated using in-sample simulations of the model described

in the previous section. Th e year 1962 is chosen as the s tarting point for the

simulations because it is the year of th e optim al struc tural break in the price

equation (1.4), when prices became sensitive to import penetration and

capacity utilization. This was also the first year in which imports rose

above 5% of domestic consumption (except for the strike year 1959). The

simulations end in 1981 for the same reasons indicated in the previous

section.

A baseline simulation of the model was run assuming actual historical

values for all the exogenous variable s, allowing all the endo genous variables

to ad just dynamically (see the Appendix for diagnostic tests of the m odel).

Then, the model was simulated under the counterfactual assumption that

import penetration remained a t approximately 1962 levels throug h 1981.

Two counterfactual scenarios were tested: (1) the share of imports in

domestic consumption is constrained t o 5 % ; and (2) the volume of imports

is constrained to four million net tons. In both cases, equation (1.10) for

import demand is dropped from the model, either IMPSHARE or

IMPORTS is set exogenously, an d identity (1.9) is used t o calculate the oth er

import variable.

Tables 2 and 3 give the means and growth rates, respectively, for the

baseline and counterfactual simulations.

The endogenous variables are

listed in the same order a s they appear in Ta ble 1, except that the constant

dollar margin in (1.3) is replaced by the true PCM, defined as

(PRICE-

UN ITCO ST)/PR ICE (expressed as a percentage). Th e two counterfactual

l With the dependent variable measured in logs,

steel demand decays at the rate of

2(.00025) O.S % per year. Thi s term is included in spite of th e low -statistic because

it improves the fit of the baseline forecast. linear time trend is not used because it would

be collinear with log

YMFR



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182 Im po rt competi t ion, investment f inance, a n d cumulat ive decline

Table

Sample means, 1962- 1981

Variable

Counterfactual S imulations

Actual Baseline

Data Simulat~on

1 1

(21

Nores

In billions of

1972

dollars, deflated by

PINVEST.

Price-cost margin d efined as

I(PR1CE UNICO ST)/PR ICEI 1 0 0 .

In current dollars per net ton of p roducts shipments.

In current dollars per net ton of tren produc t sh~pments

OUTPUT and CAPACITY are ~nde xes ased on 1977 output

=

10 0. CAPUTIL is OUTPUT

as a percentage of CAPACITY

Measured In per cent

g

Assumed lexogenously f ixed .

In millions of net tons.

simulations generate very similar results,

with scenario

2)

the more

restrictive assum ption generating slightly greater effects, as on e would

expect.

Th e average

PCM

fo r the period 1962-1981 would have been abo ut 10

o r 11 higher with im po rts constrained (in scenarios

1 )

and (2), respec-

tively), compared with the baseline forecast. Underlying this difference is

a faster average annual rate of price increase:

7 . 8

compared with

7 .3

in the baseline (recall th at unit co sts are exogenously fixed). T he higher

prices are mainly due to the direct effects of the assumed restrictions on

imp ort competi t ion. T here is a lso an indirect d ynam ic effect operating via

the feedback of higher lagged prof i ts ( INTFUND,- , ) on to current divi-

dends (DIVPNT,) . In addi t ion, there is a small boost to pr ices f rom the

higher rate of capacity utilization.

Turning to the underlying determinants of capaci ty ut i l izat ion, output

averages abou t 6 higher in the coun terfactual scenarios (compared with

the baseline), while capacity averages only ab ou t

3 higher (see Table 2).

The increase in output is due to the fact that the restr ic t ions on imports

mo re tha n offset the reduct ions in total s teel dem and (DOM CO NS), which

are due in

turn

to the higher prices of steel products relative to substitute

material s. Th e counter fac tua l means and growth ra tes for DO M C ON S are

lower tha n in the baseline sim ulation, confirm ing th at th e gains for dom estic

product ion come par t ly at the expense of domest ic s teel consumption



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Robert

A

Blecker

183

able

3

Average annual grow th rates. 196 2-1 98 1 ( i n per cent)

Actual

Counterfactual S imulations

Baseline

Variable Data Simulation (1 )

12)

1) INVEST

21

INTFUND

3 PCM

PRICE

5 ) DIVPNT

6 ) CAPUTIL

7 ) OUTPUT

8 ) CAPACITY

9 ) IMPSHARE

10 ) IMPORTS

f l

DOMCONS

Nores Growth rates are calculated from OLS regressions of the natural logs on linear time

trends except as noted.

Variables are defined as in Table 2.

a

Estimated by AR1 procedure

Not significant at the

5

level (two-tailed test).

Assumed fixed.

especially when productivity growth is taken as exogenously fixed.

Internal funds are consistently well above the baseline levels in the

counterfactual scenarios. IN TF U N D averages 571.3 million higher in

scenario (1) and 653.8 million higher in scenario (2), com pared with the

baseline, o r abo ut 27% and 319'0, respectively. Th e increased internal funds

are due primarily to the increase in the profit margin and only secondarily

to higher output. The higher constant-dollar

M RGIN

accounts for an

average 20% rise in annual internal funds in scenario 1) and a 23% rise in

scenario (2); higher

OU TP UT accou nts for about a 3% rise in both scenarios

(evaluated at the sample means in logarithms).

Th e model also fore casts higher levels of investment spending as a result

of the increased internal fun ds and capacity utilization in the cou nter factu al

scenarios. Average ann ual real investment w ould have been 407.0 million

higher in scenario (1) com pared with the baseline, and 459.8 million higher

in (2), or a bo ut 22% and 25 % , respectively. The present value of the total

add itiona l investment for the 20 years 1962-1981 is 7.5 billion in scenario

(1) and 8.5 billion in scenario (2), mea sured in 1972 do llars, assuming a

5 % discount rate.

In ord er to apprec iate the econo mic significance of these increased expen-

ditures on new plant and equipment due to import restrictions, it is help-

ful to have some sense of the industry's cap ital requireme nts. O ne useful ben-

chmark is the cost of constructing new, integrated steel plants in the

early 1970s, aro un d the midpoint o f o ur sam ple period. C randall(19 81: 78)

estimates that th e capital costs for a new integrated steel mill were 41 1 per

net raw ton of capacity in 1972. Thus the total extra investment spending



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184

Import competition investment finance and cumulative decline

which would have resulted from restricting steel imports t o 5% of the market

(or four million net tons) over a 20-year period could have purchased

approximately 18 (or 21) million tons of new integrated capacity, repre-

senting only about 12% (or 13%) of the total industry capacity of 156 million

tons in 1972, as estimated by Crandall (1981: 24-25).

Crandall (1981: 11) reports that 'the minimum efficient scale of a new

integrated greenfield plant is somewhere between 6 and 7 million raw

tons'. t $411 per ton, the total cost of one efficient, new integrated mill

would therefore have been between $2.5 and $2.9 billion in 1972. If all the

extra investment forecast in the counterfactual simulations had been devoted

to constructing new integrated mills, about three such mills could have been

built. While this would have quadrupled the number of new greenfield plants

actually built in the

US

after 196 (the only one was Bethlehem Steel's Burns

Harbor, Indiana plant), it would clearly not have permitted a thorough

modernization of most US steelmaking facilities.

From a competitive viewpoint as well, building more integrated mills

might not have been a wise strategy, even if more capital funds had been

available. Barnett and Schorsch (1983) and Barnett and Crandall(1986) have

demonstrated that, by the late 1970s and 1980s. US integrated mills were

not cost competitive with their foreign counterparts, while the nonintegrated

minimills were still competitive. Barnett and Crandall (1986: 52-53; 65-67)

estimate that minimills could be built at a cost of about $300 per net ton

of capacity for bars and wire rod, or $700 for cold-rolled sheet coils, in 1985

prices. Using the implicit price deflator for steel investment, these figures

translate into approximately $140 and $325, respectively, in 1972 prices.

Therefore, over the entire 20 year period 1962-81, the industry could have

afforded about 53 million tons of additional minimill bar/rod capacity or

23 million tons of minimill sheet capacity under scenario (I), and 60 million

tons of barhod or 26 million tons of sheet with minimills under scenario

(2). Clearly, the industry could have afforded much more modernization if

it had ploughed the extra internal funds into more minimill construction,

rather than more integrated mills.

V Effects of allowing for increased productivity growth

In order to demonstrate conclusively that the profits-investment link can

lead to a cumulative improvement or worsening of competitiveness, it would

be necessary to prove that additional investment in an industry would

reduce its unit costs in the long run. This would require showing not only

that more investment would increase productivity growth, but also that

increased productivity growth would not be offset by higher input prices

(especially wages). Since there is a close correlation between capital-labour

ratios and labour productivity in the steel industry, after correcting for

cyclical effects (Barnett and Schorsch, 1983: 147), we may infer that the



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Robert A Blecker 185

increased investment which would have resulted from restrictions on imports

would have enabled productivity to rise more rapidly. The likely reaction

of wages to such restrictions is much less clear, however.

It could be argued that unions would have taken advantage of import

restrictions to win greater wage increases for their members. But whether

steel workers could have obtained wage increases greater than those actually

obtained in 1961-81 is doubtful. Steel wages rose faster than average for

US manufacturing in 1957-77 anyway, in spite of rising imports (Anderson

and Kreinin, 1981). Lawrence and Lawrence (1985) found striking evidence

that, in the 1970s, employed steelworkers obtained above-average wage

increases in a declining industry facing stiff international competition by

playing an 'end game' over the quasi-rents from the operation of existing

facilities. The authors found no evidence that steel wages rose more rapidly

during the two periods of binding protection in the 1970s; the 197 1-72 volun-

tary restraint agreements; and the 1978-79 trigger prices. It is therefore far

from clear that wages would have risen more if the industry had suffered

less foreign competition and had better growth prospects. Indeed, unions

might have exercised more wage restraint if they had thought that the pro-

spects for increased investment and job opportunities were brighter. In this

case, unions might have believed that higher cash flows would actually be

reinvested in the industry.

Given the uncertain effects of protection on wages, it seems safest to

assume that protection would have had a net negative effect on unit labour

costs through increased labour product~vity. In order to obtain a rough

estimate of how the results of the present simulations are affected if the

higher investment rates would have generated more rapid productivity

growth, the counterfactual simulations described in the previous section

were rerun with labour productivity assumed to grow

at a

compounded 1

per year more than it actually grew, starting in 1962. The 1% increase in

the productivity growth rate was arrived a t in two ways. First, the additional

investment forecast by the model in scenario (I), with imports constrained

to 5% of the market, is estimated to make net capital per worker grow about

0.8

per year faster than in the model baseline.I6 Assuming a unitary

elasticity of labour productivity with respect to net capital per worker, the

1 Th e aut ho r attem pted to estimate a Kaldorian technical progress function by regressing the

annu al growth rate of labour prod uctivity on the rate of increase in estimated) capital per

production worker, af ter controlling f or changes in capacity utilization and o ther variables.

While significant positive coefficients were ob tain ed, the quan tita tiv e results were very sen-

sitive to the precise specification ch osen, a nd t hos e estim ated coefficie nts ar e not relied upon

here. The estimation of the capital stock is described in the following note.

6

The net capital stock was estimated by accumulating annual real investment spending,

assuming a 20-year service life for all steel investment and using straight-line depreciation.

Hou rs of production workers in the counterfactual scenario were estimated by multiplying

actual hours for each year times the ratio of counterfactual

OUTPUT

t o

OUTPUT

from

the baseline simulation.



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186

Imp ort com peti tion investment finance and cum ulative decline

former would also rise about 0.8% faster per year. Secondly, the BLS

index of ou tput per prod uction w orker ho ur in steel rose by ab out 0.6% per

year slower than the average fo r a ll US m a n ~ f a c tu r i n g . ' ~ fa ir ly neut ra l

assum ption is that protection fro m im por ts could at least have enabled the

industry to achieve the average productivity growth rate for all manu-

facturing (Scott, 1989). I rounded these growth differentials up to

1

t o

compensate for the possible effects of additional investment in lowering

energy and materials costs, which could not be modelled so easily due to

the heterogeneity of these inputs.

T he results of the simu lations with variable productivity are summ arized

in Table 4 for scenario (l).' he ma in diffe renc e is tha t the price increases

are much more m oderate , as lower unit costs are only partly offs et by profit

margins which are only slightly higher. As a result, total domestic con-

sumption and o utput are both higher, an d the costs of the hypothesized pro-

tection to domestic steel consum ers a re greatly reduced. As Figures 1 a n d

2 show , in the first few years after im por ts are controlled, domestic prices

and consumption in the counterfactual simulation with increased produc-

tivity ar e close to their trajectories in the counterfa ctual simula tion with c on-

stant productivity. H owever, after 10-20 years have elapse d, the simulation

with increased productivity generates forecasts closer to the model baseline

than t o the counte rfactual simu lation with constan t productivity. By 1981,

the final year in the sim ulations, the price is forecast to be

566

per net ton

with increased productivity, about 4.6% higher tha n in the baseline forec ast

( 541), ut abou t 6.4% lower than in the counterfa ctual forecast with cons-

tant productivity

( 605).

imilarly,

1981

domestic consumption falls to only

100.5

million net tons in the simulation with increased productivity from

102.8 million in the baseline, a s com pare d with 97 2 million in the c ounter-

factual simulation with constant productivity.

V

Conclusions and implications

If the US steel industry had been fully insulated from rising imports after

1962, t would hav e benefited from the ability to raise mor e internal funds

by setting higher pro fit m argins as well as by selling m ore o ut pu t. W ith the

P M

abou t 10-1 higher and ou tput a bout 6% higher, real internal funds

would have been about 27-31 To higher and real investment expenditures

would have been about 22-25% greater. These expenditures could have

enabled the industry to replace or refurbish a portion of its plant and

l Grow th rates are est imated by least squares. The index of production worker productivity

for all manufa cturing was obtained by dividing the index of m anufac turing output by the

index of average weekly hours of production workers

Handbook of labor

srarisrtcs, 1989;

both indexes based on

1977 100 .

8 Results for scenario

(2)

were quali tat ively similar and are omitted for reasons of space.



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Robert A Blecker

187

Table

Means and g row th rates for a lternative simulations: co nstant versus increased pro-

ductiv ity (Scenario 1 -Impo rts Restricted to 5 of Market)

Means

Grow th Ratesa

Variable Constant Increased Constant Increased

1 INVEST

2 INTFUND

3 ) PCM

4 ) PRICE

51 DIVPNT

6 ) CAPUTIL

7 ) OUTPUT

8 ) CAPACITY

9 ) IMPSHARE

10

IMPORTS

1 1)

DOMCONS

Notes

Variable are defined as in Table

2.

Grow th rates calculated as in Table 3.

Simulation with increased productiv ity growth assumes labour productiv ity rose by

1

per

year more than it actually did.

a In per cent per year.

Not significant at the 5 level.

Assumed (exogenously f ixed).

equipment. Although the additional expenditures would not have been

enough to mod ernize most of the industry

-

especially if the fu nd s had been

spent on greenfield integrated mills the simulations d o show tha t a profit

squeeze due to import competition significantly restricted the ability of

firms to finance their capital expenditures. T o this extent, it may be said that

import penetration contributed to a vicious circle of cumulative decline.

Th e analysis in this paper su ppo rts the view th at competitive advantages

or disadvantages, to a certain extent, can be created or lost by specific

historical events and social institutions. It is also implied tha t artificial gains

or losses of competitiveness (e.g., du e to tem porary undervaluation or over-

valuation of a nation s currency) can have pe rma nen t, potentially irrever-

sible effects. From this perspective, comparative cost advantages and

disadvantages at any given point in time are not merely manifestations of

inherent comparative adv antages based solely on exogenous factor endow -

ments. T he analysis also implies that the pu tative benefits t o dom estic steel

consum ers of allowing steel imp orts ar e exaggerated by analyses which fail

to take account of the productivity losses engendered when investment

finance is constrained by import competition.

It does not necessarily follow from this analysis that more protectionism

was actually warranted f or the

US

steel industry du ring the 1960s and 1970s,

or that additional investment could have permanently averted its decline.

For one thing, mere protection would have left steel firms free to plough

the add itional fund s into greater diversification out of steel, in the absence

of a m ore comprehensive industrial policy. Unless steps were taken t o en sure



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188

Imp ort co mp etitio n investment finance and cumulative decline



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Million Net Tons

120

70

1962 1964 1966 1968 1970 1972 1974 1976 1978 1980

Figure

US domestic steel consumption, alternative simulations, 1962-81

Source Author's calculations. Simulations with constant and increased productivity both assume imports constrained to

5

of consumption.

aseline Productivity Productivity

I

I

I I

I

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190 Im po rt competition investment finance and cumulative decline

that additional profits were actually invested in raising steel productivity,

the negative allocational effects on steel consumers emphasized in the tradi-

tional analyses (e.g., Crandall, 198 1; 1987) might have predominated. The

need to compel firms receiving protection (or subsidies) to reinvest in moder-

nizing their steel operations is especially important in the light of the dif-

ferences found in our forecasts for steel prices and consumption in the

counterfactual simulations with constant versus increased productivity.

Another difficulty with protecting the steel industry arises from the fact

that steel is a mature product with a slowly growing market, especially in

advanced industrialized countries such as the United States. For this rea-

son, efforts to sustain large, integrated steel works in all the industrialized

countries have only led to global excess capacity (Barnett and Schorsch,

1983: 38-47). Our estimated total steel demand function (I . l l ) shows that

steel demand is income-inelastic and has an accelerating negative time trend.

And even the insignificance of accelerator terms in the investment function

I ) can be interpreted as reflecting the poor prospects for the growth of steel

demand. Protection simply could not have preserved the relative importance

which steel had in the US economy in the postwar years, and excessive

protection could have hindered necessary structural changes at high social

costs.

There may be situations, however, in which a more activist response to

a loss of competitiveness in steel might be indicated. For example, macro-

economic imbalances and exchange rate fluctuations can potentially cause

lasting damage to domestic producers. For the period 1979- 1983, about

55

of the employment losses in the

US

steel industry have been attributed to

the overvaluation of the dollar combined with sluggish real income growth

(Grossman, 1986). In this situation, if profits and investment were also cur-

tailed, a case for some kind of remedial intervention could be made.

The connection between pricing, profitability, and investment which has

been identified in this paper also suggests a reorientation of economic theory

along the lines suggested (in a different context) by Heim and Mirowski

(1987).

In particular, this connection implies

a

shift in the focus of price

theory, away from the traditional view of prices as scarcity indexes, toward

a conception of prices as instruments in firms competitive efforts to expand

a shift advocated earlier by Robinson (1962) and Levine (1982). In this

light, the long-standing debate about whether industrial prices are flexible

or rigid has missed the point. This debate has been based on the pre-

sumption that any sign of price flexibility in response to demand conditions

indicates a tendency toward neoclassical market-clearing pricing; thus critics

of neoclassical price theory have been forced to claim that prices are rigid .

An alternative approach is to view flexible prices as signalling firms chang-

ing abilities to finance their growth along irreversible paths, rather than as

signals inducing them to allocate resources efficiently in a preordained

equilibrium state.

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Robert A Blecker

191

This alternative app roac h would place the expand ing business firm , rather

than the intertemporal-utility-maximizing household, at the centre of the

analysis of ca pital accumulation. O n the o ne side, gross realized profits a re

the main source of saving; on the other side, expected net profits are the

principal inducement t o invest. Investment decisions, m ade at th e microlevel

by competing firms, determine income levels and growth rates at the macro-

level. Th e analysis in this pape r is intended t o validate the mic rofou nda-

tions of this approac h at the industry level.

VI References

Ad elma n, M.A. 1961: Steel, administered prices and inflatio n. Quarterly

Journal of Economics

75, 16-40.

American Iron and Steel Institute.

Annual Statistical Report

Various

issues.

An derso n, R.G. an d Kreinen, M.E. 1981 La bo ur costs in the Am erican steel

and auto industries.

Wo rld Economy

4, 199-208.

Bar nett, D.F. an d Cra ndall, R.W. 1986:

U p from the ashes: the rise of the

steel minimill in the United States

Washington: Brookings.

Barnett, D.F. and Schorsch,

L

1983:

Steel: upheaval in a basic industry

Cambridge, Mass: Ballinger.

Blecker, R.A. 1989: M ar ku p pricing, import com petition , and the decline

of the American steel industry.

Journal of Post Keynesian Economics

12, 70-87.

Broude, H.W. 1963:

Steel decisions and the nationa l econom y

New Haven:

Yale University Press.

Crandal l, R.W. 1981

Th e USstee l industry in recurrent crisis

Washington:

Brookings.

987: Th e effects o f

US

trade protection f or auto s and steel.

Brookings

Papers on Economic Activity

1, 271-88.

Do rnbu sch, R. 1987: Exchange rates and prices.

American Economic

Review

77, 93-106.

Eichner, A.S. 1976:

Th e megacorp and oligopoly

Cambridge: Cambridge

University Press.

Fair, R.C. 1970: Th e estim ation of sim ultaneo us equa tion m odels with

lagged endogenous variables and first order serially correlated errors.

Econometrica

38, 507-16.

Fazzari, S.M. and Athey, M.J. 1987: Asym metric inf orm atio n, financing

constraints, and investment.

Review of Econom ics and Statistics

69,

481-87.

Fazzari, S.M. H ub ba rd, R.G. and Peters en, B.C. 1988: Financing con-

straints and corporate investment.

Brookings Papers on Economic

Activity

1, 141-95.

Fazzari, S.M. and Mott, T L 1986-87: T he investment theories of Kalecki

and Keynes: an empirical study of firm data, 1970-1982.

Journal of

Post Keynesian Economics

9, 17 1-87.

Feinberg, R.M. 1986: T he interaction of foreign exchange an d mark et power

Downloaded



ary2015


24/27

192 Import competition investment finance and cumulative decline

effects on German domestic prices. Journal of Industrial Economics

35, 61-70.

989: The effects of foreign exchange movements on US domestic

prices.

Review of Economics and Statistics

71, 505-1

1

Grossman G.M. 1986: Imports as a cause of injury: the case of the US steel

industry. Journal of International Economics 20, 201 -23.

Matanaka M. 1976: Several efficient two-step estimators for the dynamic

simultaneous equations model with autoregressive disturbances. Jour-

nal of Econometrics 4, 189-204.

Heim C.E. and Mirowski P. 1987: Interest rates and crowding-out during

Britain s industrial revolution. Journal of Economic History 47, 117-

39.

Wooper P

and

Mann C.L.

1989: Exchange rate pass-through in the 1980s:

the case

of

U

manufactures.

Brookings

Papers

on Economic Activity

1

297-337.

Jondrow J.M.

1978: Effects of trade restrictions on imports of steel. In

Dewald, W.G., editor, The impact of international trade and invest-

ment on employment

Washington: US Department of Labor.

Kaldor

N .

1970: The case for regional policies. Scottish Journal of Political

Economy 17.

972: The irrelevance of equilibrium economics. Economic Journal 82,

1237-55.

Kalecki M.

197 1 Selected essays in the dynamics of the capitalist economy.

Cambridge: Cambridge University Press.

Karier T . 1988: New evidence on the effects of unions and imports on

monopoly power. Journal of Post Keynesian Economics 10, 414-27.

Krugman P.R. 1981 Trade, accumulation, and uneven development. Jour-

nal of Development Economics 8, 149-61.

Lawrence C.

and

Lawrence R.Z.

1985: Manufacturing wage dispersion:

an end game interpretation. Brookings Papers on Economic Activity

1, 47-106.

Lawrence R.Z. 1983: Is trade deindustrializing America? A medium-term

perspective. Brookings Papers on Economic Activity 1, 129-72.

Levine D.P. 1982: Determinants of capitalist expansion.

Economic Devel-

opment and Cultural Change 30, 299-320.

Lintner J.

1956: Distribution of incomes of corporations among dividends,

retained earnings, and taxes. American Economic Review Proceedings

46 (May), 97-1 13.

Mancke R. 1968: The determinants of steel prices in the U.S.: 1947-65.

Journal of Industrial Economics 16, 147-60.

Mann C.L.

1986: Prices, profit margins, and exchange rates. Federal

Reserve Bulletin 72, 366-79.

Means G.C. 1962: Pricing power and the public interest: a study based on

steel.

New York: Harper.

Rippe R.D.

1970: Wages, prices, and imports in the American steel

industry. Review of Economics and Statistics 52, 34-46

Robinson J 1962: Essays in the theory of economic growth. London:

Macmillan.

Downloaded



ary2015


25/27

Robe rt A. Blecker 193

Rosenberg N . 1976: Perspectives on technology. Cambridge: Cambridge

University Press.

Scherer F.M.

1980: Industrial m arket s truc ture a n d economic performance,

second edition. Boston: Houghton Mifflin.

Scott R.E. 1989: Trade policy, employment and the costs and benefits of

protection. Ind ustr ial Relation s Research Association Proceedings,

536-46.

Steindl

J.

1952: M aturity a n d stagnation in Am erican capitalism. Ox ford:

Basil Blackwell.

Targetti F. and Thirlwall A.P. 1989: The essential Ka ldor. New York:

Holmes Meier.

Theil

H.

1966: App lied economic forecasting. Am sterdam: North -Hollan d.

US

Department of Com merce Bureau of Econ omic Analysis.

1985: Survey

of Cur ren t Business (Feb ruary ).

US Federal Trade Comm ission (FTC ). 1977: The Un ited State s steel industry

a n d its international rivals. Washington: GP O.

VII Appendix

This Appendix discusses the diagnostics of baseline simulation of the model

presented in the text. Th e first two colum ns of Table 2 com pare the means

of the baseline forecasts of the endog enous variables with the actu al sample

means; growth rates are compared in Table 3. Table A-1 gives the ro ot mean

squared errors (RMSEs) for the baseline forecasts, both in levels and in

natural logarithms (the latter measured in percent), along with Theil's u

(coefficient of inequality).

For purposes

o

the present study, only the forecasts

o

the long-run

trends of the variables are of interest, and the model does quite a good job

of sim ulating those trends. In fact, the simulations track the annual changes

very well for several variables (PCM, PRICE, CAPUTIL, OUTPUT, and

DOMCONS), and moderately well for others (IMPORTS, IMPSHARE,

INT FU ND , and IN VES T). Th e baseline forecasts of the other tw o variables

(D IV PN Ta nd CA PAC ITY) essentially look like trends o r moving averages

draw n throu gh the actual series. Generally speaking, the mo re the variables

depend o n lagged endog enous variables, th e worse the m odel forecas ts their

year-to-year fluctuations. Nevertheless, the simulations foreca st the sample

means and growth rates quite closely for all the variables.

The baseline forecasts of investment spending (INVEST) and internal

funds (IN TFU ND ) both underpredict the am plitude of the cyclical swings,

and miss some of the turning points, while approximating the long-run

9

Theil's 1966) u-statistic, which is 0 for perfect forecasts and for the 'naive' forecast of

no change, was designed to evaluate how well models forecast short-term percentage

increases. The magnitudes of these statistics in Table

A-1

should not be surprising for a

20-year historical simulation.

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194 Import competition, investment finance, and cumulative decline

able A 1 Error diagnostics of baseline forecast ( ~ nample. 1962-81)

RMSE

in

RMSE

in Theil s

Variable Levels Loga rithms

11

INVEST

2 )

INTFUND

3 )

PCM

PRICE

5 )

DIVPNT

6 )

CAPUTIL

7 )

OUTPUT

8 )

CAPACITY

9 ) IMPSHARE

10 IMPORTS

1

1

DOMCONS

Nores: The root mean squared error RMSEI in levels is measured In the same units as the

variable (see Table

2

for mean levelsl.

The

RMSE

in logarithms is expressed as a percentage.

Theil s

u

IS the coefficient of inequality as de f~ ne dn Theil

1

9 6 6) . the ratlo of the percen-

tage

RMSE

for the baseline forecast to the percentage

RMSE

for the na ~ ve orecast of no

change

trends reasonably well. The forecast of the mean level of INVEST is about

0.5 above the actual mean, while the forecast of the mean of INTFUND

is only about 1.5 above the actual (see Table 2). The large RMSEs for INT-

FUND (see Table A-I) are due mainly t o the failure of the model to predict

the wild fluctuations of this variable in just three years: 1974; 1977; and

1981.

The model slightly overpredicts the means for PRICE and the PCM,

but only by about 2 in each case. The RMSEs are proportionately small

for these variables. The baseline price series grows at about the actual

average annual rate of 7.3 (see Table 3). The model more seriously over-

predicts the level of dividends paid per net ton (DIVPNT), with a greater

proportional RMSE and a Theil's u just over 1. However, since the elasticity

of PRICE with respect to DIVPNT is only 0.16 (equation 1.4), the over-

prediction of DIVPNT has only a slight effect on the forecasts of PRICE

and PCM.

The model comes within 0.4 percentage points of predicting the mean

capacity utilization rate, with a proportionally small RMSE. The close fit

for CAPUTIL results from the fact that while the model systematically

underpredicts both OUTPUT and CAPACITY, it still predicts the

OUTPUT/CAPACITY ratio quite well. Moreover, most of the year-to-year

fluctuations in CAPUTIL are due to fluctuations in OUTPUT, which the

model simulates very closely. While the annual forecast changes in CAPA-

CITY are worse than naive extrapolation, according to the high Theil's u,

the forecast of CAPACITY has the lowest logarithmic (percentage) RMSE

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Robert A. Blecker 195

of any equation. The forecast and actual series grow at the same average

annual rate (0.8%) for the entire period, and the forecast mean is less than

2% below the actual.

With regard to imports, the baseline forecasts of the means and growth

rates of IMPORTS and IMPSHARE are very close to the corresponding

statistics for the actual series. The RMSEs are proportionally large in the

forecasts for these variables because the forecasts miss some of the turning

points by one or two years, probably due to the lagged dependent variable

in (1.10). The model predicts total domestic consumption (DOMCONS)

much more closely. The mean for the baseline forecast is only 1% lower than

for the actual series, and the RMSEs are not large. Domestic consumption

grows slightly more slowly in the baseline forecast compared with the actual

trend (1.2% per year versus 1.4%), while imports grow at the same rate

(6.1'70).

2

Th e reason fo r this discrepancy is that the predicted series

P)

ags consistently b ehind th e

actual series A )while the latter rises rapidly fro m 1965 to 1977; hence the predicted change

PI A , - , ) / A , - , is negative while the actual change is positive for much of that period.

While this in flates Theil s

u ,

it does not necessarily imply large RMS Es, since the pro por -

tional difference between P, and A , is never very large.



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