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Nominal wage contracts and the business cycle

Material Information

Title:
Nominal wage contracts and the business cycle an empirical investigation
Creator:
Dole, Carol Ann, 1961-
Publication Date:
Language:
English
Physical Description:
vi, 134 leaves : ill. ; 29 cm.

Subjects

Subjects / Keywords:
Employment ( jstor )
Indexing ( jstor )
Labor ( jstor )
Mathematical variables ( jstor )
Nominal wages ( jstor )
Real wages ( jstor )
Transport phenomena ( jstor )
Variable coefficients ( jstor )
Wage contracts ( jstor )
Wages ( jstor )
Dissertations, Academic -- Economics -- UF
Economics thesis Ph. D ( lcsh )
Money supply ( lcsh )
Wages ( lcsh )

Notes

Thesis:
Thesis (Ph. D.)--University of Florida, 1992.
Bibliography:
Includes bibliographical references (leaves 131-133).
General Note:
Typescript.
General Note:
Vita.
Statement of Responsibility:
by Carol Ann Dole.

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Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright [name of dissertation author]. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Resource Identifier:
028267272 ( ALEPH )
27477191 ( OCLC )
AJM0092 ( NOTIS )

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NOMINAL


WAGE


CONTRACTS


AND


THE


BUSINESS


flC'TC'


AN EMPIRICAL


INVESTIGATION


CAROL


ANN


DOLE


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY


UNIVERSITY


OF FLORIDA


1992















ACKNOWLEDGEMENTS


"Sometimes


you


bite


the


bear;


sometimes


the


bear


bites


you.

Mark


With


the


Rush,


support,


guidance


dissertation


and


additi


unrelenting

on to other


humor o

travail


along


the


way)


came


together.


David


Denslow


s contributions


(along


with


translation


servi


ces


helped


make


thi


project


complete.


Also deserving thanks


for their efforts and comments


are


other


committee


members:


William


Bomberger,


Douglas


Waldo and Michael Ryngaert.


Besides


those who directly


helped


with


my dissertation,


I would


be remiss


not


crediting


another


friend


and


advisor


without


whose


help


the


dissertation


might


even


have


been


started,


Anindya


Banerj


Throughout


these


last


four years,


other


faculty members,


staff


and


classmates


have


also


offered


helpful


advice


and


knowledge


making


this


program


markedly


more


bearable.


Lastly,


must


thank


family:


husband


Richard,


whose


love


and


continual


support


helped


make


possible


reach my


goals;


parents


, Eugene


and


Irma


Badger,


who


have


instilled


the


value


of knowledge


and


always


provided


the


love


to make


Emily


things


who


a little


always


easier;


offered


my sisters,


encouragement;


Sadie,


and


Kelley


finally
















TABLE


ACKNOWLEDGEMENTS.
ABSTRACT.........


OF CONTENTS


1(,1)((1)1)(()1(I)))()())))((a
S SS S S *S S *) IS **)aaa)) SS *1


CHAPTERS


1 INTRODUCTION


S S *S *****SS S .1


THE


POLITICAL


AND


ECONOMIC


CLIMATE


OF BRAZIL


Introduction.......
Wage Policies......


. ...15
. .16


NOMINAL WAGE
Introduct
Past Lite
Descripti
Tests of
Empirical
Summary a


CONTRACTS
ion.......
rature....
on of the
the Import
Results..
nd Conclus


--NATIONWIDE
* *****.**


Data
ance

ions


EVIDENCE


of Contracting
. .. .. .


.......32
. a a a .3

.........3
* S ** S S 53
* S S S* 5


4 NOMINAL


WAGE


CONTRACTS--STATEWIDE


RESULTS


Introduction.............
Review of Empirical Anal
Description of the Data.
Estimation Technique and
Empirical Results......
Summary and Conclusions.


.yse

i Re


.....0.
.. .00. a*


gre


00000005
. .6
. .6
..........6


ions


SUMMARY


AND


CONCLUSIONS.......................... 77


APPENDICES


MARGINAL RATES OF
WAGE SIZES.......


READJUSTMENT
" ... .. *


FOR
S....


DIFFERENT
.0............ 80


REGRESSION


RESULTS..............................


REAL


WAGE


RATES


AND


OUTPUT


BY INDUSTRY..........124


REFERENCES. .. .. .. ... .. a a a. 111


rl(cll())))ll((())(((~((


















Abstract


the


of Dissertation


University


Requirements


of Florida


the


Degree


Presented


the


Partial I
of Doctor


Graduate


fulfillmentt


School
of the


of Philosophy


NOMINAL


WAGE


CONTRACTS


AND


THE


BUSINESS


r'vr'rr


AN EMPIRICAL


INVESTIGATION


Carol


Ann


Dole


August


1992


Chairman:


Major


Mark


Department:


Rush


Economics


order


changes


the


money


supply


nonneutral,


frictions


must


introduced


into


the


standard


neoclassical


model.


One


the


most


common


sources


nonneutrality


the assumption of


nominal


wage contracts.


they


are


typically


modeled,


these


contracts


assume


nominal


wages


are


least


somewhat)


rigid


and


that


the


level


employment


adjusted


accord


with


the


firm'


labor


demand


schedule.


This


standard


nominal


contracting


approach


makes


changes


in the


money


supply


nonneutral.


This


transmission


property


of the


nominal


wage


contract


has


not


aone


unchallenged.


The


neoclassical


model


shows


that









marginal


value


of workers


' time


over


states


of nature


and


thus


jointly


determine


the


efficient


level


of employment.


this


framework


then,


money


shocks


will


not


change


employment.


Given


the


opposing


theories,


previous


empirical


work


has


attempted


this


test


research


the


are


role


mixed.


wage

For


contracts.

example,


Results


one


from


approach


investigates


the


degree


wage


indexation


and


relationship


finds


to employment


favor


and


neutrality;


output

the o


responses.


their


One


analysis


study


suggests


nonneutrality.


Following


these


empirical


analyses,


use


Brazilian


data


examine


whether


nominal


wage


contracts


contribute


propagating


macroeconomic


shocks.


Brazilian


firms


were


required


law


adjust


workers'


salaries


specified


intervals


to keep


pace


with


inflation


and


productivity.


Two


approaches


are


taken


using


approximately


two


decades


monthly


data


disaggregated


industry.


The


first


looks


across


periods


with


different


indexing


schemes


to study


the


seasonal


pattern


of output


as well


as the


correlation


between


industry


output


and


the


cumulated


increase


prices


from


one


index month


to the next.


The


second approach,


using two-stage


least


squares


(because


the


real


wage


switches


from


being


exogenous


endogenous),


looks


directly


the


effect


industries'


real


wage


changes


upon


output.








behavior


the


actual


real


wage


making


monetary


shocks


neutral.















CHAPTER


INTRODUCTION


order


changes


the


money


supply


nonneutral,


frictions


must


introduced


into


the


standard


neoclassical


model.


While


economists


have


suggested


a variety


different


frictions,


possibly


the


most


common


source


nonneutrality


assumption


of nominal


wage


contracts.


1 Azariadis (1975) was one of the first economists to
rigorously examine issues of wage contracts. Within his model
he derived an optimal contract with a fixed wage.
Importantly, however, his model delivered the conclusion that
it is the real wage not the nominal wage that is fixed.
Essentially Azariadis' work suggested that under the optimal
contract, the real wage is unrelated to the realization of the
marginal revenue product of labor (MRPL). Hence consumption
is independent of the MRPL (which is affected by states of
nature) so that the real wage is stabilized. From the
perspective of macroeconomics, though, Azariadis' "sticky"
real wage gives no role to nominal aggregate demand shocks in
determining output. Thus this line of research, which
initially appeared promising as a rationale for sticky nominal


wages,


no longer


seems


fruitful


along


this


dimension.


Recently


evolved that
source of the
(1987) or McC
existence of
find it closes
constant in
where a money
output. Giver


I

9


strand


posits sticky
friction, for
allum (1986).
small menu cc
e to" optimal
the face of a
tarv contract


I the


menu


"New


prices
example
These
ists to
to lear
change
ion loi


costs.


fil


Keynesian"


literature


has


in the output market as the
e see Blanchard and Kiyotaki
models demonstrate that the
changing prices, firms may
re the price of their output
in demand. Take the case
iers the demand for firms'
rms mav leave their nominal


w


I









Fischer


(1977)


and


Phelps


and


Taylor


(1977)


present


models


typical


of most,


which assume


that nominal


wages are


least


somewhat)

in accord


rigid

with


and

the


that i

firm's


the


level


labor


of employment


demand


schedule.


adjusted


This


very


common


approach


to specifying


nominal


contracts,


and


makes


changes


the


money


supply


non-neutral.


That


say,


increases


the


money


supply


raise


the


price


level;


given


the


nominal


wage's


failure


respond


the


disturbance,


firms


increase


their


labor


demand


due


the


lower


real


wage;


and


thus


output


expands


response


the


increase


the


money


supply.


This


point


illustrated


Figure


1-1.


Taylor


(1979)


modified this simple


framework to show that


real


effects


will


continue


beyond


price


and


wage


adjustments


long


the


contracts


are


staggered


and


the


terms


are


adjusted


periodically.


Further,


Taylor


(1980)


creates


model


that


allows


these


staggered


wage


contracts


generate


as a resu,
suggest th
changing 1
effects on
called "ex
fashion th
level.
controversy
cost to fi


only w
maximi
of ana
wh ich


rhen


It of
Lat th
their
i the
ternal
tough,
The
ial; I
rms f3


the


-i


a change in nominal
e cost to the firms ir
prices are second-ord
aggregate economy are
Lities" produced by all
create business cycle
importance of stick


3arro,


rom
nil


zing level.
lysis can ac
i n naf-laccarv


instance,


demand. These models
1 lost profit from not
ler while the overall
first-order. The so-
firms behaving in this
s at the macroeconomic
y output prices is


has pointed


out that the


not changing their prices is second-order
tial level of production is at the profit
Therefore, it is hard to see how this line
count for persistent stickiness in prices,
+t nonornso orer 4 a' ni-i nnn-nontrn t n1 44-4 acs nP


I





















a)

>1
0
0.
E








-.I


eBeM Ieel










persistence


unemployment


and


output


similar


to the


United


States'


post-war


experience


with


respect


nominal


disturbances.


More recently


, Card


s (1990)


empirical analysis


finds


are


that wages


positively


negotiated


correlated


at the


terms


start


of a contract


made


the


period


end


previous


period.


This


work


creates


some


support


for Taylor'


view


how


the


linkage


from


staggered


contracts


creates


persistence


the costs of


labor and therefore employment and


output.


This


view


of the


effects


from


nominal


wage


contracts


has


not,


however,


gone unchallenged.


Barro


(1977)


has


pointed out


that


even


though


labor


contract


fixes


the


nominal


wage,


firms


and


workers


may


equate


the


marginal


product


of labor


the


marginal


value


of workers


' time


over


states


nature


and


thus


jointly


determine


the efficient


level


of employment.


In this case,


the


"shadow"


equilibrium real


wage


(which equals


what

from


the

the


real w

actual


age


real


would


wage


be in

due


an auction


the


market)


presence


will

the "


differ


sticky"


nominal


wage.


In other words,


the


actual


real


wage,


which


affected


nominal


disturbances,


does


not


equilibrate


labor market because


it does


not


produce an efficient


level


employment.


Instead,


the


level


employment


determined










where


labor supply and demand meet at


the


(shadow)


equilibrium


real


wage.


This


idea


illustrated


Figure


1-2.


The


efficient


(and


equilibrium)


levels


of the


real


wage and


output


are


W/P


and


respectively.


the


actual


real


wage


falls


due


increase


the


price


level,


firms


and


workers


remain


value


at W/P


and


of workers


greater


between


than


otherwi


' time


the


points


(the


marginal


and


at W/P'


distance

product


and


loss


and


between


labor


occurs


the


pointss

(the

(the


marginal


A and


distance

distance


between


B and


In this


framework


then,


money


shocks


will


not


change


employment


since


the


shadow


auction


market,


wages


and


prices


change


proportionately


and


leave


the


real


wage,


and


hence


employment,


constant.


Therefore,


wage


contracts


may


no longer


a source


of non-neutrality.


Hall


(1980),


using


New


Classical


framework,


extends


Barro'


insight concerning the effects of


real


disturbances


pointing


out


that


labor


relationships


are


long


term .


Thus


each side

not taking


has


advanta


incentive

ige of the


to dea

fixed


fairly


nominal


with


wage


the


the


other

face


changes


the


marginal


product


of labor.


Let

nominal


look


wage,


Hall


point


easy


see


more

that


closely.


a monetary


For


shock


given

that


Increases


the


price


level


results


the


actual


real


wage








6






r E
C E
L E co

SE
So o

Q J E




0 0
(0 / U




^^^-.-.--....--.--/---- _,




* I



B-











standard


Keynesian


approach,


this


situation


elicits


increase


employment


as firms


move


along


their


labor


demand


curve.


Hall


(and


Barro),


however,


ask


two


important


questions


To what


extent would


existing


employees be willing


to work


additional


hours?


And


really


the


firms


' and


workers


' best


interests


determine


the


level


employment


referring


Qflly


the


labor


demand


curve?


The


argument


advanced


Barro


and


Hall


that


because


long-term


relationship


between


firms


workers,


both


parties


realize


that


these


random


monetary


shocks


will


(effectively)


lower


their


actual


real


wage


below


the


equilibrium


real


wage


(and


marginal


product


labor)


half


the


time


that


firms


benefit.


However,


the


other


half


the


time,


the


shocks


raise


the


actual


real


wage


above


the


equilibrium


real


wage


that


workers


"win.


But


both


cases


what


the


losing


party


"loses"


exceeds


what


the


benefitting


party


"wins"


since


employment


at an


inefficient


level.


Clearly,


ex ante,


each


side


can


improve


position


agrees


to operate


the


efficient


level


employment.


other


words,


firms


and


workers


not


respond


the


actual


real


wage;


instead,


they


agree


marginal


equate

product


the


marginal


of labor


value


(which


also


workers


equals


the


' time


equilibrium


real


wage)


Thus


Hall


(and


Barro)


answer


the


questions


they










pose


claiming


that


employees


would


not


be willing


to work


the


extra


hours


and


that


not


firms'


workers'


interests


to sign


contracts


that


obligate


employees


to work


the


extra


time.


contrast


nominal


shocks,


apparent


that


(because


long-term


relationships)


real


disturbances


can


generate changes


in the marginal product of


labor,


employment,


and


hence


output


However,


the


Keynesian


model


allows


both


real


and


nominal


disturbances


generate


the


same


output


response.


This


course,


the


major


difference


between


the


Keynesian


approach


to labor


contracts


and


the


Barro/Hall


New


Classical


approach.


On a related point,


Hall


discusses


the


fact


that


to meet


an increase


demand,


firms


can


expand


their


labor


input


variety


ways:


hire


more


labor,


ask


current


workers


smoother path
would prefer


of income leads
smoother income


to smoother consumption,
to a fluctuating path.


workers


5 Recognizing the Barro/Hall analysis may be one
New Keynesians have made the distinct departure f
sticky nominal price framework. Specifically, as Ball
and Romer (1989) point out, firms and their customers
part of a long-term relationship--no loyalty exists to
buyers from moving up their demand curves as price
firms maintain high real product prices in the face
monetary policy. This lack of long-term arrangements
can produce business cycles given sticky prices in tl
market.


6 For a given wage


e reason
From the
, Mankiw
are not
prevent
-setting
of tight
s, then,
he goods


level when there is a negative real










work


overtime,


persuade


them


work


more


intensely


combination


these


options.


Therefore,


empirical


work


addition


to considering


the


relationship


between


the


real


wage


and


employment,


I also


investigate


the


correlation


between


the


real


wage


and


output


order


provide


more


insight


into


the


effects


of nominal


shocks.


Given

empirical


the

work


opposing

that


theories,


attempt


there

test


are

the


two

role


strands


wage


contracts.


The


first


examines


the


time


series


relationship


between


real


wages


and


employment


activity.


Under


the


standard


contracting


case


, one


would


expect


to find


that


real


wages vary


countercyclically.


Yet,


early work


(Dunlop,


1938;


Tarshis,


1939)


found a


positive correlation between real


wages


and


employment.


More


recent


results


are


mixed,


with


some


continuing


find


support


negative


relation


while


others


find


relation.


For


instance,


Geary


and


Kennan


(1982),


studying


Canadian


data,


find


statistical


relationship


between


employment


and


the


real


wage.


Bils


(1985),


however,


using


disaggregated


data,


finds


procyclical


Actual


proportionately


varying with
that a 1%
corresponding


both


labor


to allow


an


data


tend


with


output.
change
\ change
id total


both


outpu
Okun'


show
t as
s Law


that


work


opposed


expresses


unemployment
output. In


output


options.


in separate


intensity
employmel


this


rates


fact


produce


empirical


changes
nt hours
claiming
is a 3%


work


regressions


use


order











real


wages.


Bils


credits


these


differences


to his


studying


the


behavior


of real


wages


individuals,


the


inclusion


overtime

earlier


worth


earnings


studies.

nominal


and


Whil4

wage


using

e these r

rigidity


later


results

models,


sampling


Lend


period


uncertainty


given


the


than


to the


pitfalls


the


simple


time


series


approach


taken


part


this


literature,


is perhaps unsurprising that no


firm conclusion


has


been


reached.


A more


direct


route


has


been


pursued


Ahmed


(1987)


Card


(1990).


Ahmed


investigates


the nonneutrality


of money by


testing


degree


whether


wage


employment


indexation.


and

The


output

basic i


are


idea


sensitive


that


the


nominal


wage contracting


important,


the


less


flexible


(that


the


less


indexed)


the


wage,


the


greater


the


impact


monetary


shock


employment


and


output.


Using


Canadian


manufacturing


industries,


which


employ


variety


indexing


schemes,


Ahmed


tests


this


implication


of contracting


models.


fails


find


relationship


between


the


degree


contracting


and


extent


to which


a monetary


shock


affects


real


variables,


and hence concludes that nominal


wage rigidity


cannot account


for business cycles.


Card,


also using Canadian


data,


asserts


that


the


unexpected


components


of the real


wage


(namely


unanticipated


price


changes),


along


with


the


I










model.


Card


in impacting

levels.


a results


employment


Card


support


levels


concludes


a role


.via

that


for


surprise


end-of-contract


nominal


inflation


real


contracts


wage

are


instrumental


determining


labor


and


output


reactions.


Thus


given


these


divergent


results,


this


strand


of literature


also


produces


no firm


conclusions.


Following Ahmed and


Card,


I use Brazilian


data


to examine


whether


nominal


wage


contracts


play


essential


role


propagating


macroeconomic


shocks.


exploit


the


fact


that


from


1965


through


1984,


Brazil


s price


level


rose


over


7000


times

their


as seen


employees'


Figure 1

nominal


L-3.


Brazilian


wages,


but


firms


were


generally


required


fixed


law


adjust


workers'


salaries


at specified


intervals


to keep


pace


with


inflation


and


productivity.


From


1965


1979,


the


adjustments were required annually;


1979


the law changed


require


indexing


semi-annual


formula


adjustments.


Because


and high Brazilian inflation,


the


real


lagged


wages


fell


until


readjustment occurred,


when


they were raised


to maintain


purchasing


power.


According


the


standard


contracting


approach,


as the


real


wages


fell


prior


to the


indexing


date,


firms


would


add


workers


and


output


would


respond


positively.


Conversely,


New


Classical


economists


suggest


that


firms


and


workers


would


not


change


the


level


of employment


the


face






















































I I I I I ~III Ii I I


S6Ol u! leAel eo!fd










a monetary


shock


and


there


should


tendency


contracts


influence


output.


Relative


Ahmed


Card,


data


has


major


advantage.


Because


inflation


Canada


was


relatively


low,


and


the


unexpected


inflation


Card


tries


measure


even


smaller,


both Ahmed


and


Card


must


search


relatively


small


effects.


10 However,


inflation


Brazil


was


from


small.


If there


are


any


effects


from


nominal


contracts,


data


may


be better


able


uncover


them.


9 Be
controls
In 1985,
and even
expectati
freeze co
to exist,


or did


tween
on ind
a new
chan
ons.
nsumer
the p:


not


1979


ustr
adm
ged
Stil
pri
rice


cover


and


1983


ial inputs
inistrati
the price
1, continl
ces again
controls


much


of the


, the government lifted price
but reimposed them in mid-1983.
imposed strict price controls
index to lower inflationary
d pressures made the government
Since high inflation continued


were more


than likely


ineffective


economy.


10 Indeed, this could be why Ahmed failed to find any
effect from monetary disturbances. Card's results, meanwhile,
may be the result of mismeasurement of the unexpected
component of inflation.


1 This
disadvantage
environments
adjustments


less
that
funct
infla
with


advantage,


however,


: One might worry
workers and firms
(as Barro suggested)


inflationary times.
in low inflation
ion as postulated
tion countries, thi
Barro's approach.


In other
countries
by Keynesi
e contracts


Of


course


may


also


conceal


that in 1
make effici
that they m
words, it mi
i, nominal
Lan analysis


ligh j
ency E
light f
[ght be
wage c
while


are altered to bE
ie, the observat


L related
inflation
enhancing
?orego in
the case
contracts
in high
a in line
ion that


.


j










The


Brazil


next


and


chapter


its wage


discusses


policies.


the


Chapter


historical


discusses


background


the analysis


of nationwide


data


while


Chapter


takes


a different


approach


using


statewide


data.


The


fifth


chapter


provides


a summary


and


conclusions.















CHAPTER


THE


POLITICAL


AND


ECONOMIC


CLIMATE


OF BRAZIL


Introduction


During


years


independence,


Brazil


s political


climate


has


varied


and


continues


to play


an important


role


economic


policies


, especially


the


latter


half


the


twentieth


century


Starting


1930,


a populist


dictatorship


President


Getulius


Vargas


held


control


until


1945


when


was


replaced


more


liberal


federal


republic


and


series


"popularly"


elected


presidents


1946,


the


electorate


represented


only


16 percent


of the


population)


During


thi


period


of democratic


rule,


economic


growth


varied


from


percent


annually


1954


low


percent


1963


the


economy


worsened,


President


Jodo


Goulart


s government designed a stabilizing


"Three


Year


Plan";


still,


annual


inflation grew exorbitantly,


climbing to a


level


of more


than


80 percent


1963.


Before


the


plan accomplished


its goals


, the military


s toleration of


the country


s economic


stagnation


came to an


end,


and


toppled Goulart


s government










March


1964


was


this


military


regime,


led


Castelo


Branco,


which


instituted


the


wage


indexation


scheme


Waae


Policies


During the governance of Getulio


Vargas


the


1930s,


government


enacted


a Labor


Code


creating


unions


dependent


the


Ministry


of Labor


their


existence


The


behavior


the


money


supply


notwithstanding,


clear


that


the


military


attempt


enforce


economic


policies,


attacked


the


union


structure


claiming


the


unions


were


responsible


uncontrolled


the


wage


wage-price


increases,


spiral


Circular


Therefore,


Number


combat


specifying


the


formula


used


wage


indexation,


was


enacted


June


1964


The


following


formula


(except


minor


adjustments3)


determined


wages


until


19684


Not


policy.


one


pay
with


surprise
Still,


instance,


raises f
illegal


ingly,


military


wages


its members protested


an officer


men;


troop


stormed


was


the


denied


were
their
town


not


covered


falling wages


hall


the


to demand


and


charged


movements.


Thi


Mussolini,


impose
into ac
leaders


the


union
enabled


wage


;counts


did


not


structure,


the


military


guidelines.


which


the


follow the


patterned


government


Labor


government
party lin


was


e


that
to


required


managed.
, they were


created


effectively


Spay
the


replace


dues
labor
d or,











1 424
24 -t I'


where


= the


nominal


wage


be set


the


25th


month


-- the


price


index


month


= the


expected


inflation


rate


over


the


next


year


= the


expected


rate


increase


productivity.


summary,


the


formula


contained


three


basic


elements:


compensating


factor


past


inflation,


another


anticipated


inflation


and


third


take


account


productivity


improvements.


This


initial


indexing


regime


applied


only


government


employees;


July


1964,


was


extended


the


public


sector


including


state-owned


corporations or ones


which


the


state held majority


control.


K(~











One


year


later,


wages


the


private


sector


came


under the


jurisdiction


the


law.


In addition


to the


wage


indexation


policy,


the


military


government


radically


changed


job


security


measures


1966


Prior


enacting


the


Guaranteed


Fund


Time- in-Service


(FGTS)


law,


firms


were


required


make


indemnity


payments


fired


laid


off


workers


7 In


general,


these


payments


constituted


penalties


great


enough


discourage


material


layoffs.


1966


however,


the


FGTS


changed


the


payment


structure.


Firms


were


now


required


pay


percent


employees


salaries


into an


escrow account


every


month.


When


laid


off


or fired,


the


employee


received


the


amount


set


aside


regardless

firms had


of the


length


motive


time


layoffs


employed


since


On the


the


one


percent


hand,

t had


already


been


paid;


additionally,


there


was


no difference


seniority


between


those


employed


more


or 1


ess


than


ten


years.


6 Realizing that


policy,


additional


constitution;


forbidden


strikes


were


The


labor would


legislation


instance,


Antistrike


improved


authorized by


least


where co
strength


1985,


mpanies


the


most
had


oppose
passed


strikes,


Law


working


a regional
strikes t


I


not


Labor


paid


Code


passed


conditions


labor


:hat


court


were


salaries


combined


Srul


this


restrictive wage


1964


the
June


most
1964


or wages
From 3
.ed legal


Sfor t
with ti


three
e A


11


revised
: part,
1 did pe
, once


L964
. wer
ionth


ntistr


the
were
trmit
they


through
e those
s. The
ike Law


effectively
in 1965 to


remained


detail


crushed


relatively


see


Alves


strike


1966,
low


activities


1970,


until


the


: strikes


and


none


middle


the


fell
in


from
1971


1980s


225
and
For


(1985).


I
*


L


T










Alternatively,


firms


were


only


required


pay


a portion


wage


readjustments


to those


employed


less


than


one


year.


the


face


wage


readjustments,


firms


may


have


been


motivated


layoff


higher-paid


workers


favor


those


unprotected by the wage


formula adjustments.


Additionally,


has


been


reported


that


some


workers


intentionally


goaded


the


firm


into


firing


them


enabling


them


to collect


their


fund


and


move


a higher


paying


job.


The

measures


military


and


economic


modernization


plans


and


included


strengthening


stabilization


capital


markets


addition


the


"wage


squeeze"


policy.


fact,


before


the


takeover,


the


market


long-term


securities


longer


existed


since


a usury


prohibited


interest


charges


over


percent.


During


the


same


period,


money


growth


fell


from


75.4


percent


1965


34.8


percent


1974.


These


policies


effectively


met


their


goal


of controlling


inflation


from


1964


through


1973;


1964,


inflation reached


87 percent


annually,


but


fell


percent


1967


and


percent


1973


as seen


in Figure


2-1.


For


details,


see


Smith


(1988).









































































































































































AZZfht a a AIama.i











The


latter


part


of this


period,


1968


to 1974,


was


known


as Brazil


s economic


"miracle.


" Real


economic growth averaged


over


10 percent


annually


during


the


upturn.


1968,


some


of the


weaknesses


the


original


formula


were


corrected.


Wages


would


now


adjusted


according


to: 10


A= -"+a-1
R13


where


IIR
RA=R? 1+-
2


and


= the


rate


wage


adjustments


= a productivity


factor


= the


actual


real


wage


the


two


years


preceding


the


adjustment


= the


real


wage


month


- the


mean


real


wage


the


two


years


preceding


the


adjustment


=- forecast


immediately


inflation


preceding


the


the


12 months


adjustment.












1
R=- 1
M 24


12

t-1


wtxtII


j+H1/2
where =2
1+nv/2


where


= the


mean


real


wage


the


two


years


preceding


the


adjustment


= the


wage


month


= the


= the


wage


correction


factor


index


correcting


month


the


adjustment


residual


or forecasted


inflation


= the

= the


actual

inflati


inflation d

on forecast


during

used


months


13-24


months


13-24.


Specifically,


deterioration


the


1968


wages


revisions


including


the


corrected

t average


the

real


partial


wage


calculations.











The


formula


was


fine-tuned


again


1974


A persistent


issue


was


finally


corrected--now


only


the


incorrectly


predicted ir

renegotiation


iflation


would


the


used.


months

addition,


preceding


the


the


rate


increase


in productivity would now be multiplied by


(not added


the


average


real


wage.


The


new


wage


could


now


calculated


using


this


formula:12


w
W -
We


S1
S-12
12


12 (P e
X 1+-^ ( 1+a
e | 2
c-l 2


+ 1+(IA/2)
1+ (ll/2)


where


= the


the


rate

new


the


wage


wage


once


adjustment


adjusted


= the


wage


each


the


preceding


12 months


= the


forecast


inflation


the


12 months


preceding


the


current


adjustment


= the


actual


inflation


rate


during


months


13-24


= the


residual


inflation


used


the


previous


year


s adjustment


= the

= the


rate

wage


increase


index


in productivity


month


In summary,


while the economy boomed,


the wage


indexation


fnrmiil n


TrT^a


rnni a A -. 1~ r~~7 Att warll n n4


~nht4.. ah


ratt: ah~


Ch~~r.


Ckn


T.-TY I


rn











adjustments; 13


second,


prevent


underestimation


inflation,


the


forecasting


procedure


was


refined;


third,


the


base


period


for calculating the base wage was


reduced


from two


years


one


year;


and


fourth,


the


wage


raise


was


discounted


multiplying


(rather


than


adding)


the


productivity


coefficient


the


average


real


wage.


From


1974


through


1980,


economic growth


fell


to somewhat


over


five


percent


annually,


and


then


rebounded


a bit


the


1980s.


Against


inflation,


backdrop


several


additional


lower growth

changes were


and


rebounding


made


the


indexing scheme.


Specifically,


1976 additional


refinements


were


made


the


productivity


coefficient;


was


redefined


using


a terms


trade


index


to account


for


not


only


foreign


trade


but


differences


rural


and


urban


economies.


However


in November


1979,


the


indexation


policy


underwent


much


more


pivotal


change:


after


November,


wages


were


adjusted


every


six


months


rather


than


every


twelve


months


The


National


Council


on Wage


Policy


provided


cost


living deflators and expected profit and productivity figures.











had


been


previously


the


case14


Specifically


the


formula


was"


= P6[W(1.l1c,


+ 0.8c3


+ 0.5c4)


+ W.(0


.3c3


+ 6.8c4


+ 16.8


where


= semiannual


rate


of readjustment


to be applied


wage


the


class


, of


industry


group


starting


month


(INPC-/INPC,-_)


Sii


the


semiannual


rate


of change


the


INPC


(the


National


Consumer


Price


Index)


= the


nominal


wage


to be adjusted


= the


= 1


value


wage


the


class


highest


which


regional


includes


nominal


the


wage


value


and


0 otherwise.


The


1979


law additionally


specified the


following terms:


the


included


productivity


growth


specifically


coefficient


the


formula;


was


longer


management


and


labor


would


now


negotiate


thi


factor,


and


could


not


passed


on in


prices


- the


government


would


provide


an official


price


index


(INPC)


the


month


before


the


readjustment


date;


Macedo


government


(1983),


s motivation


well


others,


switching


explain
six-month


that


the


indexing


3 /W


15


w











- wages


would


now


be differentiated


minimum


wage


level


The


minimum


wage


strata


criteria


were


updated


within


one


year.


For


minimum


example,


wage


those


received


workers


earning


percent


the


three


INPC


times


while


the


those


earning


between


and


times


the


minimum


wage


earned


adjustments.


For


specific


see


Appendix


later


empirical


work,


exploit


thi


movement


toward


more


frequent


indexing


provide


test


the


Keynesian


and


New


Classical


hypotheses.


From


late


1983


through


1984


wage


increases,


while


still


granted


every


six


months,


were based


on a


new


formula


that


related wage brackets


and


changes


the


cost


living


index.


1985,


however,


under


severe


abandoned


the


pressure

indexing


from


formula


the

. The


unions,

cessation


the government

of the indexing


formula


truncates


sample


period


1985;


however


more


complicated


schemes


were


used


until


1987


when


quarterly


indexing


was


instituted


The


quarterly wage
In subsequent


salari
index


could


(INPC)


unions,


increa
plans,


with


ses


regenerated


which


wages


be raised


. Wages


were


by a
only


the


were


t least


power,


administration


frozen;


60 percer


readjusted


durir


pressured


disallowed


renewal
it of thi
ia the cc


dates,
e price
contract


-- j


I


--















CHAPTER


NOMINAL


WAGE


CONTRACTS --NATIONWIDE


EVIDENCE


Introduction


order


changes


the


money


supply


nonneutral,


frictions


must


introduced


into


the


standard


neoclassical model.


While economists have suggested a


variety


different


frictions,


possibly


the


most


common


source


nonneutrality


the


assumption


nominal


wage


contracts.


Fischer


(1977)


presents a model


typical


of most,


which assumes


nominal


wages


are


least


somewhat)


rigid and


that


the


level


employment


adjusted


accord


with


the


firm'


labor


demand


schedule.


This


standard


nominal


contracting


approach


makes


changes


the money


supply nonneutral.


That


to say,


increases


the money


supply raise


the


price


level;


given the


1
exist;


Azariadis
-9. 1p


I,
t


throughout
optimal
realizati


That


affected


stabilized.


stickk"


Lis
the


(1975)


paper


determines


though,


contract


contract, I
on of the ma
consumption


states
As o
wacre


real


the


period,


real


irginal
is ir
of nat


opposed
a ive ss


that
real
not


wage


revenue


Dependent


:ure)
to
nn 1


optimal
wages 1


contracts


that


nominal.


is
produce


of
that


"sticky"


rml e


. t..


t


are
Under


unrelated
:t of labor
he MRPL (
the real


nominal
Snarrra nata


wt


can


fixed
the
the


(MRPL).
lich is


wage


wages,
dimnand


is
the
in


I










nominal


wage


failure


to respond


the


disturbance,


firms


increase


their


labor


demand


due


the


lower


real


wage;


thus


output


expands


in response


the


increase


the


money


supply.


Taylor


(1979)


modified this simple


framework to show that


real


effects


will


continue


beyond


price


and


wage


adjustments


long


the


contracts


are


staggered


and


the


terms


are


adjusted


periodically.


Further,


Taylor


(1980)


creates


model


that


allows


these


staggered


wage


contracts


to generate


persistence


unemployment


output


similar


the


United


States'


post-war


experience


with


respect


nominal


disturbances.


More recently,


Card


S (1990)


empirical analysis


finds


that


wages


negotiated


the


start


a contract


period


are


positively


correlated


terms


made


the


end


the


previous


period.


This


linkage


creates


persistence


the


costs


labor


and


therefore


employment.


This


view


these


effects


from


nominal


wage


contracts


has not,


however,


gone


unchallenged.


Barro


(1977)


has


pointed


out


that


even


though


a labor


contract


fixes


the


nominal


wage,


firms


and


workers


may


equate


the


marginal


product


of labor


the


marginal


value


of workers


' time


over


states


of nature


and


thus


jointly


determine


the efficient


level


of employment.


In this case,


the


"shadow"


equilibrium real


wage


(which


equals










from


the


actual


real


wage


due


to the


presence


the


"sticky"


nominal


wage.


In other words,


the


actual


real


wage,


which


affected


nominal


disturbances,


does


not


equilibrate


the


labor market because


it does


not


produce an


efficient


level


employment.


Instead,


the


level


employment


determined


where


labor supply


and demand meet at


the


(shadow)


equilibrium


real


wage.


this


framework


then,


money


shocks


will


change employment


since


in an


auction market,


wages


and prices


change


proportionately


and


leave


the


real


wage,


and


hence


employment,


constant.


Therefore,


wage contracts may no


longer


a source


of nonneutrality.


Hall


(1980)


extends


Barro


s insight


pointing


out


that


labor


relationships


are


long


term


that


each


side


has


incentive

advantage


deal


fairly


of changes


with

price


the

level


other

. For


not


example,


taking

random


money


shocks


will


lower


prices


half


the


time


and


raise


them


the


other


half.


Therefore


half


the


time,


labor


benefits


and


half


the


time


firms


benefit


depending


whether


the


money


shocks--and

expected. I


hence


however


price


shocks--are


, on average,


ex ante,


lower

each


higher


side can


than


improve


position


it agrees


operate at


the efficient


level


employment.


This


obviously


important


issue.


this










Brazilian


firms


were


required


to adjust


nominal


wages


paid


workers


interval


initially


once


every


year


and


then


later


every


months.


The next section reviews


some previous work exploring the


effects


from wage contracts.


It also describes


features of my


Brazilian


data


that


make


advantageous


exploring


this


issue.


The


third


section


discusses


the


data


that


use


and


the


fourth


presents the


specification


of my regressions and my


tests.


The


fifth


section


reports


results


of the


tests


and


the


last


section


highlights


the


important


results.


Past


Literature


Given

empirical


the

work


opposing

that


theories,


attempt


there

test


are

the


two

role


strands


wage


contracts.


The


first


examines


the


time


series


relationship


between


real


wages


and


employment


activity.


Under


the


standard


contracting


case,


one


would


expect


to find


that


real


wages


vary


countercyclically.


Yet,


early work


(Dunlop,


1938


and


Tarshi


1939)


found


a positive


correlation


between


real


wages


and


employment.


More


recent


results


are


mixed,


with


some c

others


continuing


find


to find


support


relation.


For


for


a negative


instance,


relation


Geary


and


i while

Kennan


(1982),


studying


Canadian


data,


find


statistical










behavior


real


wages


individuals,


the


inclusion


overtime

earlier

worth of


earnings


studies.


nominal


and


While

wage r


using

these


*igidity


later


results

models,


sampling


Lend


period


uncertainty


given


the


I than

to the


pitfalls


the


simple


time


series


approach


taken


part


this


literature,


is perhaps unsurprising that no


firm conclusion


has


been


reached.


more


direct


route


has


been


pursued


Ahmed


(1987)


and


Card


(1990).


Ahmed


investigates


the


non-neutrality


money


testing whether


employment


and


output


are


sensitive


to the


degree


wage


indexation.


The


basic


idea


that


nominal


wage contracting


important,


the


less


flexible


(that


less


indexed)


the


wage,


the


greater


the


impact


monetary


shock


employment


and


output.


Using


Canadian


manufacturing


industries,


which


employ


a variety


of indexing


schemes,


Ahmed


tests


this


implication


of contracting


model


fails


find


relationship


between


the


degree


contracting


and


the


extent


to which


a monetary


shock


affects


real


variables,


and hence concludes that nominal


wage


rigidity


cannot account


business cycles.


Card,


also


using Canadian


data,


asserts


that


the


unexpected


components


of the


real


wage


(namely


unanticipated


price


changes),


along


with


degree of


indexation,


that should generate negative employment










impacting


levels.


employment


Card


levels


concludes


Svia

that


end-of-contract


nominal


real


contracts


wage

are


instrumental


determining


labor


and


output


reactions.


Thus


given


these


divergent


results,


this


strand


of literature


also


produces


no firm


conclusions.


Following Ahmed and


Card,


use


Brazilian data


to examine


whether


nominal


wage


contracts


play


essential


role


propagating


macroeconomic


shocks.


exploit


the


fact


that


from


1965


through


1984,


Brazil


price


level


had


rose


7000


times.


Brazilian


firms


generally


fixed


their


employees


nominal


wages,


but


were


required


law


adjust


workers'


salaries


specified


intervals


to keep


pace


with


inflation


and


productivity.


From


1965


1979,


the


adjustments


were


required


annually;


1979


the


law


changed


require


semi-annual


adjustments.


Because


the


lagged


indexing


formula


and


high


Brazilian


inflation,


real


wages


fell


until


readjustment


occurred,


when


they


were


raised


maintain


purchasing


power.


According


the


standard


contracting


approach,


real


wages


fell


prior


the


indexing


date,


firms


would


add


workers


and


output


would


respond


positively


Conversely,


New


Classical


economists


suggest


that


firms


and


workers


would


not


change


level


of employment


the


face


monetary


shock


and


there


should


tendency










Relative


Ahmed


and


Card,


data


set


has


major


advantage.


Because


inflation in Canada


was


relatively low,


and


the


unexpected


inflation


Card


tries


measure


even


smaller,


both Ahmea

However,


and


Card must


inflation


search


Brazil


was


for relatively


far


small


from small.


effects.


If there are


any


effects


from nominal


contracts,


data may be better


able


uncover


them.


Description


the


Data


study


begins


1975


and


ends


1984


because


after


this,


the


specific


programs


(that


the


wage


freezes


and


then


reinstitution


of the


quarterly


indexing)


provide


too


few


and even changed the price index to
expectations. Still, continued pressures
freeze consumer prices again. Since high
to exist, the price controls were more than
or did not cover much of the economy.


5 Indeed, this could be why Ahmed
effect from monetary disturbances. Card'
may be the result of mismeasurement
component of inflation.


lower inflationary
made the government
inflation continued
likely ineffective


failed to find any
results, meanwhile,
of the unexpected


This


advantage,


however,


may


also


conceal


disadvantage: One might worry that in high
environments workers and firms make efficiency
adjustments (as Barro suggested) that they might f
less inflationary times. In other words, it might be
that in low inflation countries, nominal wage (


funct
infla
with


ion
tion


as postulated 2
countries, the


by Key
contr


Barro's approach. Of


nesian analysis whi
acts are altered to
course, the observe


le
bat
at


i related
inflation
enhancing
?orego in


the
cont
in
e in
ion


Case
racts
high
line
that










observations


for meaningful


results.


These data


cover some of


the


larger


and


more


important


industrial


sectors


of Brazil


well


as secondary


sectors.


The


basic


data


consist


monthly


output


series,


from


Anu&rio


Estatistico


Brasil,


seven


industries:


rubber,


plastics,


chemicals,


transportation,


beverages,


tobacco


and


machinery.


The


wage


adjustment


month


for workers


within


each


industry


varied


industry.


was


unable


uncover


written


record


the


precise


month


when


the


wages


were


indexed


some


the


industries.


Thus,


determine


the


indexing


month,


examined


wage


data


(from


The


Fundagao


Institute


Brasileiro


de Geografia


e Estatistica


Indidstria


Trans formal o)


these


industries


from


Brazil


s two


largest


states,


S&o


Paulo


and


Minas


Gerais,


since


output


these


states


effectively


dominates


the


rest


the


country


deflated


the nominal


wage


using the wholesale


price


index


from


Coniuntura Econ6mica.


These seven industries then demonstrated


consistent


pattern:


particular,


during


the


period


annual


indexing,


industries


had


one


month


where


the


real


wage


jumped


higher


thereafter


tended


decline


Figure


illustrates


this


using


data


from


the


plastics


industry.


The


upward


spike


quite


apparent


the


figure.


Thus,


the


month


jump


(January)


was


deemed


the


month


indexing





































so0!Seld-e6BM ieul











Tests


the


Importance


Contracting


The

indexing


shift


provides


November


a natural


1979

way t


from


annual


o examine


the


six-month


importance


nominal

contracts


environment;


contracting


are


indeed,


According

important f


the


feature


Keynesian


the


that


view


economic


changes


in the


money


supply


and


hence


the


price


level


affect


real o0

aspect,


output.

major


nominal


changes


wage


them--such


the


important


movement


more


frequent


indexing--ought


to affect


the


evolution


of output


The


intuition


illustrated


Figure


which


illustrates


some


hypothetical


data.


The


top


part


the


figure


shows


the


behavior


the


real


wage,


initially


with


twelve


months


between


indexing


and


finally


with


six


months


between


indexing


The


bottom


shows


the


effect


of this


This


the


game


that nominal


changes


This, then,
or output.


(1976)


change,


wage contracts are


them


ought


affect


changes


"rul


people


should be observable through changes


when
To


the
the


3s of the
actions.


in employment


8 The


fact


that


the


Also


real
not c


wage
rucial


assumed


a -


the


to fall


assumption


linearly


that


their presence


determines


how


contracts


rules
extent
game",


related


to Lucas


people


sight


s behavior


that


important


not


important.


the


are


--


w




































me


tI
I


Time





Finrla i-9 RlAwtnnth Rfohoavinr rf +hea oal Ila/,n an fl ..I ..+s










"saw-tooth"


behavior of the


real


wage on employment--and hence


output--making


the


conventional


assumption


that


firms


determine


the


level


employment


along


their


labor


demand


curve.


Thus,


the


real


wage


declines


due


inflation,


firms


move along their


labor demand


curves


and


raise


the


level


of employment.


The


figure


makes


obvious


the


point


that


behavior of


employment changes along with


the


indexing regime.


Figure


designed


convey


only


the


intuition


behind


these


tests.


Thus


not


essential


that


the


real


wage--and


hence


employment--display


the


precise


pattern


illustrated


the


figure.


The


key


observation


that


according


to the


Keynesian


approach


emphasizing


contracting,


the


switch


from annual


to semi-annual


indexing must affect


time


series


behavior


of employment.


Testing this hypothesis


conceptually


straightforward:


simply examine whether the evolution of


output differs between


indexing


regimes.


To this


end,


I used monthly


data


from seven


industries


the


period


from


1975


to 1985.


then


assumed


that


output


within


each


industry


evolved


as:


= C + MONTHLY


DUMMIES


+ CARNIVAL


(3-0)


where


level


the


log


output


industry


time


constant,


MONTHLY


DUMMIES


are


dummies










annual month


of Carnival.


In Brazil,


Carnival


a pre-Lenten


festival


amount


represents


during


which


work 2

whether


there


performed.

Carnival


obvious


The

falls


dummy


decrease


variable


February


the


CARNIVAL


or March


and


takes


account


of this


factor.


To account


the


non-stationarity


the


data,


I have


chosen


difference


the


variables:.


= C + MONTHLY


DUMMIES


+ ajDCARNIVAL


+ Mlt


(3-1)


where


DCARNIVAL


the

the


first

first


difference

difference


the

the


log


dummy


output


variable


and

for


Carnival.


If,

contracts


following


are


the


material


Keynesian

affecting


approach,

output,


nominal


changes


wage


the


indexing


regime


should


affect


the


behavior


of output.


Hence,


First


I first-differenced the data
differences were used rather


to i
than


make
log


it stationary.
levels with a


deterministic
the work of


trend
Nelson


for
and


two reas
Plosser


recognized that many time s
being difference stationar
Second, and more pragmatic
shows a distinct downward "
its usual rate. Such "steps
more than one or two per


improved mea
changes were
a level spec
this by using


during of the (
sufficient to


'ification.


c


series
y rat
, the
step"
" were
indus&
output
sever


Althouc


tg a dummy constant


ons: First, in keeping wi
(1982), it has long be
are better characterized
her than trend stationar
output series occasional


t
t

4


before conti
very infrequ


ry and
series
sly bia;


were
Wh
the


t
*E


]h I could hav
that equalled


nuing upward at
ient, usually no
likely due to
ile rare, these
trend if I used
e accounted for
i one until the


DY,~,










according to


this


view,


the


coefficients


specification


likely


will


not


be stable


across


the


periods


of annual


and


semiannual


indexing.


the


other


hand,


the


New


Classical


view,


which


suggests


that


output


unaffected


nominal


contracts,


across


predicts


indexing


that


regimes.


the coefficients

These hypotheses


will

will


stable


be examined


using


standard


F-tests.


even


more


precise


test


equation


(3-1)


may


also


allow


examine


the


effect


the


change


indexing


schemes


on output'


behavior.


Whereas


(3-1)


considered


the


stability


monthly


dummy


coefficients,


equation


(3-2)


considers


only


those


months


where


would


expect


contract


renegotiations


to have


the


greatest


effect


on output:


PjMONTHLY


DUMMIES


8 INDEXl,


+ 2INDEX2


+ a~DCARNIVAL


(3-2)


where


INDEX


INDEX2


represent


dummy


variables


months


that


are


the


new


base


date


months.


For


example,


suppose


initially


the


industry


base


month


was


January;


starting


November


1979,


the


industry


began


receive


readjustments


November


and


May.


output


behaved


proposed


the


conventional


framework,


initially


would


DY,~,










expect


occurred


output


twice


peak


each


annually,


December.


would


expect


Once


output


readjustments


to peak


April


and


October.


Correspondingly,


with


annual


indexing,


output


November


should


higher


than


would


once


semi-annual


whether


indexing


output


started

these


1979.


months


The


indeed


INDEX


dummies


lower;


that


pick

is,


negative


"i8' s"


would reflect contracts'


effect on the behavior


of output


Conversely,


the


New


Classical


model


predicts


that


the


coefficients


would


zero.


The


tests


just


outlined


ignore


some potentially valuable


information;


in particular,


they


do not


exploit


the


fact


that


a fixed


nominal


wage,


the


real


wage


falls


more


the


larger


the


increase


the


price


level


Therefore,


estimate


industry-level


regressions


similar


specification


(3-1)


where


I also


include


the


cumulated price


level


as a measure


the


fall


the


real


wage.


The


cumulated


price


level


change


a proxy


the


decline


the


real


wage.


Using


the


real


ignoring


the


effect


level, the previous work might
following tests. For instance,


could be
the two


the
at
pri
the
cha


that changes in
indexing regimes


indexing


Nonethele


least two reasons
ce-level-induced
previous test
nges in the price


. Fi


from


the beha
"cancels
ss, the
rst. it i


chance .
is les:
level


C


Lle
s


the


change


the


be thought weaker than
in the preceding section:
vior of the price level
" any effect from change
earlier test is valuable
.s clearly unlikely that


ition" will
restrictive


affect


occur.


how


it assumes
-thc tA~o


S.


outnut. That is


rice
the
n it
over
s in
for
this


P


t
*


Zln~


crprnn~











wage


directly


would


preferable,


but


data


nationwide,


industry-level


nominal


wages


do not


exist


These


equations


attempt


test


directly


the


hypothesis


that


fall


the


real


wage spurs employment and


--hence output--by examining the


significance of


the price


level


coefficient.


If the Keynesian


emphasis


on nominal


contracting


correct,


the


price


level


ought


to be


positively related


to employment,


while


the New


Classical


perspective


correct,


the


price


level


should


insignificant


the


regressions.


course,


these


hypotheses


implicitly


assume


that


the


changes


the


price


level


are


driven


the


money


supply,


since


both


Keynesian


and


New


Classical


economists


agree


that


real


shocks


can


change


both


the


price


level


and


employment.


the


that


highly


price


inflationary


level


context,


determined


however,


the


primarily


assumption


the


money


supply


reasonable.


The


second


test


estimates


a regression


similar


(3-1)


with


two


modifications:


CYxt


= C + MONTHLY


DUMMIES


+ CARNIVAL


+ 7CPxt


(3-3)


' The


cumulated


rice


level


change


can


vi Cews


n -


L U










where


x represents


the


month


which


the


industries


received


their wage

output and


adjustments


the


while


cumulated


CYx


price


and

index


CPx


represent


since


the


cumulated


adjustment,


respectively


At each


adjustment,


CYx


and


CPx


were


set


equal


to a base


of 100


in month


x and


then


cumulated


forward.


Thus,


CPx measures


the


fall


the


real


wage


between


the


industry


base


dates


readjustment


while


the


(hypothesized)


increase


output


between


the


readjustment


dates


captured


CYx


Two


additional


regressions


also


examine


the


real


wage


proxy


DYxt


= C + MONTHLY


DUMMIES


+ aJDCARNIVAL


+ TCPxt


(3-4)


where,


again,


DY i


the


first difference


of the


log


of output


Equation


(3-4)


assumes


that


the


level


of cumulated


price


changes


that


affects


the


growth


rate


of output.


While


thi


seems


keeping


with


the


idea


that


the


data


are


difference


stationary,


other


economists


might


suggest


that


the


first


difference


the


cumulated


price


changes


that


The


law mandated


adjustments would


already


1978


and


received


May


1979


that,


starting


occur semiannually.


their
were


annual


adjustment


to be reindexed


November 1!
industries
s between
i November


wage


that had
December


1979


and


~79










affects


(the


difference


output.


The


goal


this


work


not


resolve


the


issue


how


best


specify


variables


in a


difference stationary framework.


Hence,


I also


estimated:


DYxt


+ MONTHLY


DUMMIES


+ a DCARNIVAL


rDCPx


(3-5)


where DCPx represents


first


differences


in the cumulated price


level.


regressions


(3-3) ,


(3-4)


and


(3-5) ,


the


basic


idea


that


the


larger


the


increase


prices


since


the


last


indexation


period,


the


smaller


will


the


actual


real


wage.


Under


the


nominal-contracting


Keynesian


hypothesis,


the


smaller


the


real


wage,


the


more


firms


raise


employment


and


output.


Therefore,


the


Keynesian


approach


predicts


that


the


estimated


coefficient


the


price


variable


will


15 The major difference between specifications
be brought out by considering the impact of


decrease
in the pr
original
focuses c
of output
then will
As a res
output w
increase


real


ice le
level
in the
* will
return
tult,
ill b<
in the


wage brought about by a


one-t


i


vel followed immediately by a fall
In this case, specification
level of prices, implies that the
be higher in the period prices are


*n t
spet
e p
e p]


:o its usual
cification


growth


rate


implies


after
that


permanentlyy increased from
rice level. Specification


(4) and (5)
a temporary
.me increase
back to its
(4), which
growth rate
higher, and


this


the


the
(5),


period.


level of
temporary
which uses


can


~ C











positive.


The


New Classical


approach,


however,


suggests


that


firms will


not


take advantage


the


inflation-induced


fall


real


wages,


so that


output


will


not


respond


to CPx


or DCPx.


Thus,


the


New


Classical


view


hypothesizes


that


the


estimated


will


be insignificantly


different


from


zero.


Emoirical


Results


To test these hypotheses,


regressions were estimated over


entire


annual


sample


indexing


semi-annual


indexin


period


(1975-1984),


(1975-1978),

g (1979-1984)


and


over


over


Table


the


the


period


period


reports


F-test


results


the


stability


the


coefficients


over


these


periods.


Strikingly,


the


level,


none


of the


industries


show significant


changes


the coefficients.


Therefore,


none


the


results


reject


the


null


hypothesis


that


the


coefficients


are


same


over


the


two


indexing


schemes.


These


results


are


more


consistent


with


the


New


Classical


theory.


find no


support


for the


Keynesian


view that nominal


contracts


affect


the


behavior


output.


Table


(3-2)


reports


results


for the


second


test


and


also


confirms


lack


of contracts


effects


on output.


In only


one


industry,


Rubber,


was


the


coefficient


significantly


less


than


zero.











results


for the


entire


sample


period as well


as the


annual


and


semiannual


indexing


sub-periods.


only


two


industry


(Rubber


and


Tobacco)


and


only


one


specification


(the


one


with


CYx)


are


the


estimated


significantly positive


at the


level.


In only


two


industry


(Beverages


and


Chemical


and


only


two


specifications


(equations


and


respectively)


are the estimated


"r"s significantly positive at


the


level


Indeed,


the


majority


the


estimated


coefficients


are


negative,


which


perverse


from


the


Keynesian perspective.


Of the negative coefficients,


however,


only


a few


attain


conventional


level


significance.


Thus,


similar


to what


saw


the


previous


section,


these


tests


fail


confirm


mechanism focusing


conventional


on labor


contracts.


Keynesian


Instead,


transmi


they


ssion


are more


line


with


Barro


s New


Classical


suggestion


that


firms


and


workers


do not


allow the


flexibility


the


fixity

actual


of the

real


nominal


wage)


wage


(and hence


influence


the


(efficient)


level


of employment


and


output.


"6 The


react


regression


immediately


-


specification


chances


a..


the


(4)
real


assumes


waae


that


. It 1


na'


firms
y be.


..











Summary


and


Conclusions


With


respect


the


impact


nominal


wage


contracting,


the


are


opposing


examined


views


this


of Keynesian


ess


and


Seminal


New


Classical


work by


Fischer


approaches


outlines


the


mechanism


(nominal


wage


contracts)


which


propagates


nominal


shocks


generating


nonneutrality


money.


addition,


Taylor


develops


models


which


mimic


the


behavior


United States


business


cycles


seen since


the


1950s.


In these


Keynesian-based models,


firms


base


their


employment decisions


on the


labor


demand


curve as


the


real


wage changes


in response


to changes


the


price


level.


The New Classical


theory,


pointing


out the inefficiencies


in the conventional


argument,


shows


that


firms and workers


are


both better


off


ignoring the behavior


of the actual


real


wage.


Instead,


over


their


long-term


relationship,


both


parties


continue


equate


marginal


product


labor


marginal


value


workers'


time


which


equals


an equilibrium


real


wage.


this


framework,


monetary


shocks


longer


generate


output


responses.


Using


Brazilian


data


covering


seven


industries,


where


nominal

supplied


wages


were


results


indexed


which


law,


strongly


four


support


different


the


New


tests


Classical


view.


Over the


sample


period where


indexinac


schemes


switched.


i i











the


New


Classical


theory;


output


behavior


was


not


affected


the


movement


the


real


wage.


The


indeed

real w


results


set


age.


tend


efficient

In this


confirm


employment


case,


that


levels


contrast


firms


using

to the


and

the


workers


equilibrium


Keynesian


view,


wage


contracts


not


serve


source


transmission


mechanism


linking


monetary


shocks


employment


and


output


responses.















TABLE


RESULTS


FOR


STABILITY


TESTING


INDUSTRY P STATISTIC


RUBBER 1.536


MACHINERY 1.168


TOBACCO 1.627


PLASTICS 1.536


CHEMICALS .986


BEVERAGES .342


TRANSPORTATION .339















TABLE


RESULTS


FOR


EQUATION


(3-2)


INDUSTRY


INDEX


P-Value


a


INDEX


P-Value


RUBBER -.080 .048* -.005 .885


MACHINERY .065 .085 .054 .154


TOBACCO -.086 .275 .065 .386


PLASTICS -.030 .332 -.019 .553


CHEMICALS -.322 .261 -.024 .291


BEVERAGES .032 .419 -.053 .204*


TRANSPORTATION .068 .322 .010 .875


*Denotes


significance


the


coefficient


the


level









51







TABLE


RESULTS


FOR


EQUATION


*Denotes


significance


the


coeffi


cient


r at


the


eve


**Denotes


significance


of the


coefficient


7 at


the


level


INDUSTRY ENTIRE SAMPLE


Coefficient P-Value


RUBBER .145 .121


MACHINERY -.044 .667


TOBACCO -.893 .000**


PLASTICS -.193 .025*


CHEMICALS -.051 .600


BEVERAGES -.050 .758


TRANSPORTATION -.475 .008**

















TABLE


-3--continued


RESULTS


FOR


EQUATION


INDUSTRY 1975-1979 1980-1985


Coef. P-Value Coef. P-Value


RUBBER -.723 .000** .431 .004**


MACHINERY .003 .993 .139 .374


TOBACCO 1.938 .000** -1.047 .005**


PLASTICS .606 .087 -.198 .116


CHEMICALS -1.503 .000** .230 .082


BEVERAGES -.914 .229 .642 .011*


TRANSPORTATION -.440 .527 -.463 .076


*Denotes


significance


the


coeffic


lent


r at


the


level


**Denotes


significance


of the


coeffi


cient


the


level









53





TABLE


RESULTS


FOR


EQUATION


INDUSTRY ENTIRE SAMPLE


Coefficient P-Value


RUBBER -.025 .554


MACHINERY -.198 .673


TOBACCO -.194 .374


PLASTICS .059 .869


CHEMICALS .525 .054


BEVERAGES -.751 .238


TRANSPORTATION -1.608 .038*


*Denotes


significance


the


coeffi


cient


at the


level.


Coefficients


are


scaled















TABLE


--continued


RESULTS


FOR


EQUATION


INDUSTRY 1975-1979 1980-1985


Coef. P-Value Coef. P-Value


RUBBER .011 .997 -.486 .471


MACHINERY 1.313 .622 .256 .718


TOBACCO .020 .888 -.147 .687


PLASTICS -.590 .726 .141 .794


CHEMICALS -1.759 .335 1.025 .011*


BEVERAGES 3.851 .331 -.935 .344


TRANSPORTATION -.014 .997 -2.772 .038*


*Denotes


significance


the


coeffi


cient


at the


level


Coefficients


are


scaled
















TABLE


RESULTS


FOR


EQUATION


I I


INDUSTRY


ENTIRE


SAMPLE


RUBBER


Coefficient


I


.000


P-Value


.814


MACHINERY -.133 .328


TOBACCO -.328 .154


PLASTICS -.001 .370


CHEMICALS .032 .691


BEVERAGES -.187 .247


TRANSPORTATION


-.422


.064


Coefficients


are


scaled
















TABLE


3-5--continued


RESULTS


FOR


EQUATION


(3-5)


INDUSTRY


1975


Coef


-1978


1979-1985


a _


P-Value


Coef


P-Value


RUBBER -.353 .620 -.027 .897


MACHINERY .735 .468 .127 .519


TOBACCO .284 .553 -.243 .469


PLASTICS -.224 .759 -.049 .741


CHEMICALS -.301 .683 .163 .154


BEVERAGES 1.198 .108 -.204 .435


TRANSPORTATION .490 .727 -.550 .145


Coefficients


are


sca


I















CHAPTER


NOMINAL


WAGE


CONTRACTS


- STATEWIDE


RESULTS


Introduction


the


transmit


Keynesian


monetary


framework,


shocks


nominal


real


wage


contracts


variables.


This


nonneutrality


occurs


because


over


the


period


of a fixed


wage


contract,


increasing


price


level


erodes


the


real


wage


thereby


inducing


firms


increase


their


labor


input,


and


likewise


output.


Fischer


(1977)


presents


a model


typical


the Keynesian


framework,


which assumes nominal


wages are rigid


to some


degree


that


the


level


of employment


adjusted


accord


with


the


firm'


labor


demand


schedule.


Firms


can


raise


their


labor


input


a variety


ways


including


hiring


more workers,


eliciting greater work intensity,


using overtime


hours


combination


these


choices.


Again,


this


standard


nominal


contracting


approach


makes


changes


the


money


supply


nonneutral.


That


say,


increases


money


supply


raise


the


price


level;


since


the


nominal


wage


remains


unchanged,


firms


move


down


along


their


labor


demand


Phelps


and


Taylor


(1977)


present


model


similar


1


-V










curves


and


thus


output


responds


positively


to the


increase


the


money


supply.


In order


to represent


the


persistence


seen


empirically,


however,


Fischer


s model must be altered.


Taylor


(1979)


shows


that


real


effects


exhibit


persistence


beyond


price


wage


adjustments


long


the


contracts


are


staggered


and


the


terms


are


adjusted


periodically


Moreover,


. Taylor


(1980)


obtains


results


which


mimic


the


persistence


in unemployment


and


output


similar


to the


United


States


' post-war


experience


(with


respect


staggered


wage


nominal


contracts.


disturbances)


Providing


using


more


model


recent


with


support,


Card'


(1990)


empirical


analysis


finds


that


wages


negotiated


at the


start of


a contract


period


are


positively


correlated


terms


made


the


end


the


previous


period.


Thi


linkage


creates


persistence


the


costs


labor


and


therefore


employment.


contrast


the


Keynesian


model,


the


New


Classical


view


asserts


that


monetary


shocks


are


neutral


Neutrality


occurs as


a result


of firms


and


labor


ignoring the movement


the


actual


real


wage


and


instead


basing


their


employment


deci


sons


on an equilibrium


or "shadow"


real


wage.


Analyzing


efficient


behavior,


Barro


(1977)


has


pointed


out


that


even


though a


Labor


contract


fixes


the nominal


rage, f


'irms and










thus


jointly


determine


the


efficient


level


employment.


Hall


(1980),


extending


Barro's


work,


notes


that


relationship


nature;


between


therefore,


labor


either


and

party


management


willing


long-term

"lose" a


result


of unanticipated


price


level


changes.


For


example,


negative monetary shock unexpectedly


increases the actual


real


wage

level


and


labor


shocks


"wins.


are


just


However,


likely


workers

to work


realize

against


that

them


price


the


next


period.


essence,


neither


party


reacts


monetary


shocks


since,


average,


efficient


level


employment


obtains


where


marginal


product


labor


equals


the


equilibrium


workers'


real


time.


wage


In this


which


case,


equals


the


the


"shadow"


marginal


value


equilibrium


real


wage will


differ


from


the


actual


real


wage due


to the


presence


of the

wage,


"sticky"

affected


nominal


wage.


nominal


In other words,


disturbances,


does


the actual


not


real


equilibrate


the


labor


market


because


does


not


produce


efficient


level


employment.


Instead,


both


labor


supply


and


demand


are


taken


into


account


and


jointly


determine


the


level


employment


the


(shadow)


equilibrium


real


wage.


this


framework


then,


wages


and


prices


change


proportionately


leaving


the


real


wage


unchanged.


If follows


then


that


auction market money shocks cannot change employment since


the










real


wage


remains


constant.


Therefore,


wage


contracts


may


longer


a source


of nonneutrality.


Looking at Hall


s point more closely,


for a


given nominal


wage,


is easy


see


that


when


a monetary


shock


increases


the

than


price

the


level


resulting


equilibrium


real


the


wage


actual

firms m


real


love


wage


along


being

their


lower

labor


demand


curve and hire more workers


(in a Keynesian


framework).


Hall


(and


Barro),


however,


ask


two


important


questions:


Would


existing


employees be


willing to work additional hours?


And


really


the


firms'


and


workers'


best


interest


determine


the


level


employment


without


considering


labor


supply


curve?


The


New


Classical


argument


claims


that


because


long-term


relationship


between


firms


and


workers,


both


parties


realize


that


these


random


monetary


shocks


will


(effectively)


raise


their


actual


real


wage


below


the


equilibrium


real


wage


(and marginal


product of


labor)


half the


time


so that


workers


benefit.


However,


the


other


half


of the


time,


the


shocks


lower


the


actual


real


wage


below


the


equilibrium real


wage


so that


firms


"win"


In either case,


ante,


the economic


optimally

of nominal


respond


keeping I

shocks.


to the actual


"pie"


would be


employment

In other


real


at an

word


wage;


larger


if both


efficient

s. firms


instead,


parties


level


and


they


in the


workers


agree


acted

Face

don't


to equate


f










labor


(which


also


equals


the


equilibrium


real


wage).


answer


the


questions


posed,


not


only


would


employees


unwilling


workers


work


' interests


extra


to sign


hours,


but


contracts


not


that


obligate


firms'


employees


to work


the


extra


time.


apparent,


though,


that


(because


long-term


relationships)


marginal


real


product


disturbances


labor,


can


generate


employment,


and


change

hence


in the


output.


Allowing


both


real


and


nominal


disturbances


to generate


the


same


output


response


course,


the


major


difference


between


the


Keynesian


and


New


Classical


approaches


labor


contracts.


4 As
addresses
discussed
is simply
consumption
smoother
would pre:


Hall points o
two worker/f
in the text,
that worker
on to one th
path of income
fer smoother


ut, the idea of long-term relationships
irm issues--efficiency, which has been
and income smoothing. The latter point
s probably prefer a smoother path of
at fluctuates. To the extent that a
leads to smoother consumption, workers
income to a fluctuating path.


5 Recognizing the Barro/Hall analysis may be one reason
New Keynesians have made the distinct departure from the
sticky nominal price framework. Specifically, as Ball, Mankiw
and Romer (1989) point out, firms and their customers are not
part of a long-term relationship--no loyalty exists to prevent
buyers from moving up their demand curves as price-setting
forms maintain high real product prices in the face of tight
monetary policy. This lack of long-term arrangements, then,
can produce business cycles given sticky prices in the goods
market.


6 For a given waqe


level when there's a negative real










On a related


point,


Hall


discusses


the


fact


that


meet


an increase


demand,


firms


can


expand


their


labor


input


variety


ways:


hire


more


labor,


ask


current


workers


work


overtime,


persuade


them


work


more


intensely


combination


these


options.


Therefore,


empirical


work


addition


to considering


the


relationship


between


the


real


wage


between


insight


and


the


into


employment,


real


the


wage


effects


also


output


nominal


investigate


order


shocks.


the


correlation


provide


The


more


next section


this


essay


examines


past


empirical


work.


Next,


the


data


are


described


and


followed


a discussion


of the


estimation


technique and regression results.


The


last section summarizes


the


essay


and


results.


Review


Empirical


Analyses


test


role


wage


contracts


under


the


opposing


theories,


empirical


analysis


centers


two


primary


approaches.


The


first


examines


the


time


series


relationship


between real


wages and employment activity.


A countercyclical


Actual


proportionately


varying with


that


percent
I use b
order t


data


tend


with


output.


percent


outpu
Okun'


change


corresponding


oth


labor


o allow


and


---


chang
total


both


show
t as
s Law


that


work


opposed


expresses


unemployment


e in output.
output in s4


intensity c
> employment
this fact cl


rates


separate


options.


produce


changess
hours
.aiming
es a 3


empirical work
regressions in










real


wage,


which


the


Keynesian


approach


suggests,


would


occur


as the


price


level


rises


and


labor


demand


(along with


output)


increases.


Early work


(Dunlop,


1938;


Tarshis,


1939),


though,


found


a procyclical


real


wage.


More


recently,


mixed


results


have


been


obtained.


For


instance,


Geary


and


Kennan


(1982),


studying


Canadian


data,


find


statistical


relationship


between


employment


and


the


real


wage.


(1985),


however,


using


disaggregated


data,


finds


positive


relationship


between real


wages


and


output.


In addition


using panel


data,


accounts


these


differences


to the


inclusion


overtime

earlier


earnings


studies


and


It is


using


not


later


sampling


surprising that


these


period

results


than

lend


uncertainty


the


worth


nominal


wage


rigidity


models,


given


the


simplistic


time


series


approaches


and


ensuing


weaknesses


used


part


of thi


literature


Ahmed


(1987)


and


Card


(1990)


approach


the


debate


using


different strategy


. Ahmed


investigates whether employment and


output


are


sensitive


the


degree


wage


indexation.


Essentially,


nominal


wage


contracting


supported,


monetary


shock


will


have


a greater


impact


on employment


and


output


the


less


indexed


, the


less


flexible)


the


wage.


Using


Canadian


manufacturing


industries,


which


employ


variety


of indexing


schemes,


Ahmed


tests


implication










extent


which


a monetary


shock


affects


real


variables.


the


other


hand,


Card


claims


that


the


unexpected


components


real


wage


(namely


unanticipated


price


changes)


along


with


the


degree


indexation,


that


should


generate


countercyclical


real


wage.


Therefore,


Card


(also


using


Canadian


data)


constructs


measures


unexpected


inflation


and


real


wage


changes


for


use


labor


demand


model.


These


results


support a


role


surprise


inflation


impacting


employment


levels


via


end-of-contract


real


wage


levels;


hence


Card


concludes


that


labor


and


output


are


materially


affected


nominal


wage


contracts.


Thus


given


these


conflicting


results,


this


strand


literature


fails


produce


definitive


conclusions.


Following Ahmed and


Card,


I use Brazilian data


to examine


whether


macroeconomic


shocks


can


linked


output's


behavior via nominal


wage contracts.


Brazil


s wage


indexation


policy allows us to empirically


examine the opposing theories.


Brazilian


firms


generally


fixed


their


employees'


nominal


wages,


but


were


required by


law to adjust workers


salaries


specified


productivity.


intervals


From


keep


1965


pace


1979,


with


the


inflation


adjustments


and


were


required annually.


Because


of the


lagged


indexing


formula and


high


Brazilian


inflation,


real


wages


fell


until


readjustment










respond


positively.


Conversely,


the


New


Classical


approach


suggests


that


firms


and


workers


would


not


change


the


level


employment


the


face


of a monetary


shock and


so there


should


no tendency


contracts


to influence


output.


comparison


Ahmed


and


Card,


data


set


has


a major


advantage.


Because


inflation in


Canada was relatively low,


the


unexpected


inflation


Card


tries


measure


even


smaller,


both Ahmed and


Card must


search


relatively


small


effects.


Inflation


Brazil


though


was


significantly more pronounced.


Thus,


there are any


effects


from nominal


contracts,


data


may


be better


able


to disclose


them.


While


the


previous


chapter


examined


results


based


proxies


for the


real


wage,


this


chapter takes


advantage


of the


fact


that


real


wage


data


do exist


at a statewide


level.


This


allows


verify


the


robustness


the


national


results


9 Indeed, this could be why Ahmed
effect from monetary disturbances. Card'
may be the result of mismeasurement
component of inflation.


failed to find any
results, meanwhile,
of the unexpected


l0 This
disadvantage
environments
adjustments


less
that
funct
infla
with


advantage,


however,


: One might worry
workers and firms
(as Barro suggested)


inflationary times.
in low inflation
ion as postulated
tion countries, th<
Barro's approach.


In othe
country
by Keyne
e contract


Of


may


r
es


also


CO


that in
make effic
that they
words, it m
I, nominal


inceal
high
iency
might
light b
wage


a related
inflation
enhancing
forego in
e the case
contracts


sian analysis while in high
ts are altered to be in line
'urse, the observation that


o










using


data


from S&o


Paulo


only.


In addition,


we must


account


for the


fact


that


the


real


wage becomes endogenous


for part


the


sample


period.


Description


the


Data


Estimation


using


the


disaggregated


data


starts


1965


with


the


implementation


of the


indexing


policy


and


continues


through


1976.


The


basic


data


consist


monthly


output


series,


from


Anudrio


Estatistico


Brasil,


seven


industries:


rubber,


plastics,


chemicals,


transportation,


beverages,


tobacco


and


machinery.


The


wage


adjustment


month


for workers within


these


industries


varied by


industry.


was


unable


uncover


a written


record


the


precise


month


when


wages


were


indexed


some


the


industries.


Thus,


determine


the


indexing


month,


I examined


wage


data


(from


The


Fundagao


Institute


Brasileiro


Geografia


Estatistica


Inddstria de Transformacio)


for these industries


from Brazil


two


largest


states,


Sao


Paulo


and


Minas


Gerais,


since


output


in these


states effectively


dominates


the rest of


the country.


deflated


the


nominal


wage


using


the


wholesale


price


index


from


Coniuntura


Econ6mica.


These


seven


industries


then


demonstrated


a consistent


pattern.


In particular,


during


the


period


of annual


indexing,


industries


had


one month


where










Thus,


the


month


the


jump


was


deemed


the


month


indexing


occurred.


The


Fundaq&o


Institute


Brasileiro


de Geografia


Estatistica


Industria


Trans formacao


provides


wage


data


the


seven


industries.


Using


the


wholesale


price


index


from


Conn untura


Econ6mica,


I deflated


the nominal


wage.


As will


discussed


more


thoroughly


later,


government


spending


and


the


money


supply


will


used


instruments


the


regression


analysis.


Conjuntura Econ6mica and Industria de Transformac o


are


sources


for


both


series


and


provide


employment


and


value


of production


figures


at the


statewide


level


as well.


Estimation


Technique


and


Rearessions


number


specifications


allowing


for


different


functional


EMPt.j


forms were estimated


+ aT + ajRWAGEt,j


for the seven


+ MONTHLY


industry groups:


DUMMIES


+ AjCARNIVAL


(4-1)


where


EMP,~,


reflects


the


number


employees


time


industry


time


trend,


RWAGEt,


represents


the


real


wage


for


each


group,


MONTHLY


DUMMIES


are


dummies


for


January


through


November


and


CARNIVAL


a dummy


the


annual


month


Carnival.


Brazil,


Carnival


pre-Lenten


festival


during


which


there


obvious


decrease


the


amount


=: C










Obviously,


equation


(4-1)


addresses


the


Keynesian


suggestion


that


firms


choose


to hire


more


labor


the


real


wage


changes.


another


possibility


exists:


example,


when


there


employees,


more


ask


work


current


firms


ones


work


choose


harder


hire


both.


new


For


example during the


1970s


the


United States,


Hall


finds


that


when


output


contracted,


decreased


work


effort


(output


per


worker


and


hours


per


worker)


accounted


half


of output


decline


while


a decrease


actual


employment


accounted


the


other


half


surmises


that


the


same


would


occur


during


booms.


Thus


firms


opt


to work


employees


more


intensely


increase


their hours,


we might


only


see


a change


output and


the


real


wage.


Equation


(4-2)


allows


for


this


behavior:


VALUEt,


= C + aT + ajRWAGEt,J


+ MONTHLY


DUMMIES


+ XACARNIVAL


(4-2)


where


VALUEt,.


the


value


production


real


terms


each


industry.


In addition to estimating the equations


levels,


also


estimated


them


differences:


DEMPt,,


= C


+ ajDRWAGEtj


+ PJMONTHLY


DUMMIES


+ AjDCARNIVAL


(4-3)










Corresponding


equation


(4-2),


regression


differences


also


estimated:


DVALUEt j


= C + ajDRWAGEt,


+ MONTHLY


DUMMIES


+ AjDCARNIVAL


where


DVALUEtj,


and


DRWAGEt ,


are


first differences


of the value


output


and


the


real


wage


time


for


industry


respectively.


To calculate


the


real


wage,


I deflated


the


nominal


wage


using


the


wholesale


price


index.


issue,


however,


ari


ses


because


the


real


wage


endogenous during


some months.


Thus,


estimating


these


equations


requires


two-stage


least


squares


where


the


observations


on nominal


wages


are


exogenous


months


except


when


they


are


renegotiated


That


during


the


industry


base


month,


the


wage


becomes


endogenous


light


of the


fact


that


government


mandates


only


a minimum


wage


adjustment.


Workers


may


(and


quite


frequently


negotiate


additional


increase.


we fail


to account


fact


(that


the


wage


becomes


endogenous


when


readjusted),


the


estimated


coefficient


on the


real


wage


would


suffer


from


simultaneous


equation


bias.


Thus,


those


months


when


the


real


wage


was


endogenous--and


only


for those


months--I


formed


an instrument


using


the


price


level,


government


spending,











money


supply


and


prices


as instrumental


variables.


The


second


stage


takes


now


"exogenous"


real


wage


series


(the


endogenous


observation


having


been


estimated


unbiasedly)


and


performs


regressions


through


accordance


with


the


Keyne


sian


model,


expect


countercyclical


real


wage.


other


words,


response


changes

demand


the


curves


real

and h


wage,


ire


firms


additional


should move

labor. C


along


their


onversely,


labor


the


New


Classical


approach


suggests


the


absence


relationship


between


the


real


wage


labor


demand.


Firms


and


workers


ignore


the behavior


of the actual


real


wage basing their joint


deci


sions


on a "shadow"


real


wage.


We would


expect


not


differ


significantly


from


zero


thi


case.


Empirical


Results


Results


from


four


regression


overwhelmingly


support


the


New


Classical


model.


Tables


through


provide


estimates


, the


coefficient


the


real


wage.


majority


the


estimates


are


significantly


positive--a


perverse results


suggesting that as


the


real


wage


fall


, firms


hire


ess


labor


and


employment


well


as output)


fall


fact,


regressions


(4-1)


and


-2),


eleven


the


coefficients


are


positively


significant


For










coefficients


are


insignificantly


different


from


zero.


The


lack


any


negative


I, a"


lends


support


the


theory


that


nominal


wage contracts are unimportant in transmitting changes


the


money


supply


to output.


Summary


and


Conclusion


In a neoclassical


model,


effects


of monetary


shocks


are


transmitted


throughout


the


economy


introducing


frictions.


In this


essay,


the


frictions


analyzed


are


nominal


wage


contracts.


From


conventional


or Keynesian


approach,


these


contracts


prohibit


the


nominal


wage


from


changing while


allowing


price


the


level.


real w

Firms,


rage


to be determined


basing their


employment


movements

on the real


the


wage,


respond


monetary


shocks


for


instance,


increasing


employment


when


the


price


level


rises.


Ultimately,


these


frictions


propagate


nominal


shocks,


and


real


variables


are


affected.


Conversely,


New Classical models point out


that


firms and


workers,


both


part


long-term


relationship,


behave


efficiently


jointly


determining


employment


based


equilibrium real


wage.


This wage


equates


the marginal


product


of labor


as well


as the marginal


value


of worker'


time.


Both


parties


ignore


the


movement


the


actual


real


wage










Brazil


unique


wage


indexation


system


allows


these


opposing


theories


examined


and


compared.


Using


statewide


data,


results


provide


little


support


the


Keynesian


view


of a countercyclical


relationship


between


the


real


wage


and


employment


or output.

















TABLE


RESULTS


FOR


EQUATION


INDUSTRY COEFFICIENT P-VALUE


MACHINERY .518 .008**


TOBACCO 1.315 .000**


PLASTICS .711 .000**


CHEMICALS -.432 .716


BEVERAGES .611 .000**


TRANSPORTATION .601 .000**


RUBBER


.750


.000**


I I


**Denotes


significance


the


coeffi


cient


a at


the


level


















TABLE


RESULTS


FOR


EQUATION


I a


INDUSTRY


COEFFICIENT


_______________________________ I
I


MACHINERY


.309


P-VALUE


.554


TOBACCO .091 .695


PLASTICS 1.253 .000**


CHEMICALS -3.691 .575


BEVERAGES 2.433 .000**


TRANSPORTATION .807 .000**


RUBBER


.258


a


.376


**Denotes


significance


of the


coeffi


cient


a at


the


level.








75







TABLE


RESULTS


FOR


EQUATION


INDUSTRY COEFFICIENT P-VALUE


MACHINERY .289 .000**

TOBACCO .089 .001**

PLASTICS .116 .001**

CHEMICALS .089 .038*

BEVERAGES .295 .000**

TRANSPORTATION .179 .000**


RUBBER -.198 .484


* Denotes

**Denotes


significance

significance


the

the


coeffi

coeff


cient

icient


a at

a at


the

the


level.

level


















TABLE


RESULTS


FOR


EQUATION


(4-4)


INDUSTRY COEFFICIENT P-VALUE


MACHINERY .699 .009**


TOBACCO .046 .632


PLASTICS .382 .000**


CHEMICALS .762 .000**


BEVERAGES .562 .003**


TRANSPORTATION .788 .000**


RUBBER


.042


I I


**Denotes


significance


of the


coefficient


a at


the


level.








77





CHAPTER


SUMMARY


AND


CONCLUSIONS


Nominal


wage


contracts,


introduced


into


neocl


ass


ical


model,


can


generate


nonneutrality


money


typical


Keynesian model


delivering these results,


like Fischer


(1977),


assumes


that


nominal


wages


are


basically


rigid


and


that


firms


unilaterally


determine


employment


based


the


actual


real


wage.


Specifically,


the contract keeps


nominal


wages constant


while


real


wage


change


the


face


changes


the


price


level


as a result


of monetary


shocks.


For


example


a positive


monetary


shock


encourages


firms


hire


more


labor


at a lower


real


wage.


More


elaborate


conventional


model


, such


. Taylor


(1979,


1980)


can


generate


persistence


these


nominal


disturbances


producing


results


similar to


the


business


cycl


witnessed

The


post-war


United


nonneutrality


States


money,


data.


however,


contradicted


the


New


Classical


approach


business


cycles.


Model


developed


Barro


(1977)


and


Hall


(1980)


suggest


that


firms


and


workers


jointly


determine


employment


based













employment


determined


instead


bilaterally


based


equilibrium or


"shadow"


real


wage


and produces an


efficient or


Pareto

as well


optimal


the


outcome.


real


In this


wage,


auction


unaffected


market,


employment,


monetary


shocks


since


wages


and


prices


change


proportionately


Specifically,


the equilibrium real


wage equals


the marginal


product of


labor


and


the


marginal


value


of worker


s time;


since


money


shocks


do not


change


the


marginal


product


of labor,


employment


also


remains


unaffected.


In addition,


Hall


points


out


that


workers


and


firms


have


a long-term


relationship


and


are


therefore


motivated


to treat


each


other


fairly


when


prices


unexpectedly


move


the


other


party


s favor.


These


Brazilian


opposing


data,


theory


where


are


wage


analyzed


indexation


empirically


scheme


using


provides


unique


time


series.


Seven


industries


are


investigated


over


period


two


decades.


This


dissertation


takes


several


approaches:


one,


a nationwide study,


compares


results


from one


indexation


scheme


another;


second,


proxy


the


real


wage


generated;


and


lastly,


statewide


data


provide


a real


wage


series


which


analyzed


using


a two-step


procedure.


last


two cases,


the


relationship


between


the real


wage and


employment


or output


tested.










Tests


which


specifically


relate


the


real


wage


output


(and


employment)


also


show there


very


little


comovement


between


the


variables.









80







APPENDIX


Class


Marginal


Wage


be readjusted
units of w_


rate


of Readjustment


units


of V,


3w,
105w
15w',


3w,

15w.,


1.1
1.0
0.8


w > 20w,


MARGINAL


RATES


READJUSTMENT


FOR


DIFFERENT


WAGE


SIZES


ESTABLISHED
Source: Law
original ma


6708


of 10/


BY WAGE
Number


.rginal
30/79)


POLICY


6886,


rates
which


of
had


. (Macedo,


12/]
the
only


L0/79


new


1983).
SThi


wage


three


law


policy
asses.


changed


(Law


the


Number


rJ


W
W


W









81







APPENDIX B


RESULTS


FOR EQUATION


(3-1)


P-Values


in parentheses.


Variable


MACHINERY
Estimated
Coefficient


TOBACCO
Estimated
Coefficient


PLASTICS
Estimated
Coefficient


CHEMICALS
Estimated
Coefficient


C

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

NOV

CAR

DUMMAC


-.084
(.000**)
-.015
(.607)
.278
(.000**)
.229
(.000**)
.018
(.535)
.157
(.000**)
.085
(.002**)
.084
(.003**)
.132
(.000**)
.078
(.005**)
.096
(.001**)
.023
(.408)
-.158
(.000**)
-.226
(.001**)


.051
(.170)
-.006
(.910)
.042
(.531)
.193
(.001*
-.138
(.011*
-.031
(.560)
-.235
(.000*
-.137
(.012*
-.059
(.259)
-.082
(.119)
.004
(.940)
-.098
(.063)
-.148
(.013*


-.091
(.000**
.083
(.000**
.153
(.000**
.205
(.000**
.021
(.342)
.146
(.000**
.083
(.000**
.126
(.000**
.128
(.000**
.067
(.002**
.126
(.000**
.064
(.004**
-.085
(.000**


-.059
(.000*
.031
(.074)
.058
(.006*
.156
(.000*
.040
(.016*
.109
(.000*
.100
(.000*
.121
(.000*
.089
(.000*
.034
(.042*
.067
(.000*
-.016
(.321)
-.037
(.043*


DUMTOB


.799
(.000**)













MACHINERY


Standard
Error
R-Squared
DW
SSR


.061
.632


TOBACCO


.117
.525
1.956
1.381


2.634
.383


PLASTICS


.048
.602
2.203
.244


CHEMICALS


.036
.744
1.897
.135


Dummied Observations:


Machinery-1977:1
Tobacco-1982:7
Plastics-1980:1
Chemicals-1982:1















Variable


BEVERAGES
Estimated
Coefficient


TRANSPORTATION
Estimated
Coefficient


RUBBER
Estimated
Coefficient


C

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

NOV

CAR

DUMDNK


.044
(.025*)
-.102
(.001**)
-.110
(.002**)
.051
(.088)
-.241
(.000**)
.039
(.159)
-.083
(.003**)
-.048
(.085)
.015
(.582)
-.018
(.510)
.060
(.038*)
-.041
(.145)
-.030
(.317)
-.408
(.000**)


-.09
(.00
.08
(.07
.16
(.00
.19
(.00
-.04
(.37
.21
(.00
.09
(.03
.06
(.19
.16
(.00
.03
(.51
.17
(.00
.06
(.16
-.081
(.08


.004
(.829
-.080
(.002
.083
(.008
.042
(.112
-.004
(.872
.017
(.492
.009
(.713
.035
(.157
.001
(.957
-.039
(.119
.034
(.162
-.046
(.060
-.046
(.088


DUMTRN


.464
(.000**)


DUMRUB1


DUMRUB2


-.264
(.000**)
-.273
(.000**)


Standard
Error
R-Squared
DW 2
SSR


.059
.746
.671
.321


.102
.481
2.361
1.066


.054
.518
2.397
.284













RESULTS


FOR EQUATION


(3-1)


1975-1978


Variable


MACHINERY
Estimated
Coefficient


TOBACCO
Estimated
Coefficient


PLASTICS
Estimated
Coefficient


CHEMICALS
Estimated
Coefficient


-.009
(.727
-.084
(.071
.210
(.000
.144
(.002
-.037
(.352
.051
(.177
.027
(.459
.007
(.856
.063
(.095
.004
(.914
.047
(.204
-.075


JUN


JUL


AUG


SEP

OCT

NOV


CAR


DUMMAC


Standard
Error
R-Squared
DW
SSR


(.048*)
-.130
(.007**)
-.232
(.001**)


.052
.771


2.684
.080


.070


(.013*)
-.022
(.586)
-.106
(.046*)
.158
(.001**)
-.202
(.000**)
.002
(.968)
-.096
(.016*)
-.118
(.004**)
-.030
(.435)
-.113
(.005**)
.014
(.703)
-.141
(.001**)
-.125
(.011*)


.053


.799
2.468
.084


-.065
(.008**)
.091
(.015*)
.031
(.489)
.182
(.000**)
-.003
(.932)
.127
(.000**)
.056
(.097)
.121
(.001**)
.126
(.001**)
.033
(.325)
.123
(.001**)
.045
(.180)
-.002
(.959)


.047
.672
2.427
.074


-.028
(.119)
-.013


(.635)
.069
(.044*)
.128
(.000**)
-.001
(.977)
.066
(.011*)
.074
(.005**)
.089
(.001**)
.070


(.007
.016
(.504
.040
(.108
-.031


(.217)
-.082
(.010**)


.034
.695
2.440
.037


Dummied Observations:


Machinery-1977:1


JAN

FEB


MAR


APR


MAY

















Variable


BEVERAGES
Estimated
Coefficient


TRANSPORTATION
Estimated
Coefficient


RUBBER
Estimated
Coefficient


(.009**
-.112
(.001**
-.152
(.001**
.065
(.062)
-.266
(.000**
.036
(.253)
-.083
(.013*)
-.046
(.151)
.031
(.332)
-.046
(.146)
.045
(.159)
-.065
(.031*)
.003


JUL

AUG

SEP


OCT


NOV


CAR


.938)


-.077
(.035*
.045
(.413)
.156
(.027*
.197
(.002*
-.042
(.445)
.160
(.003*
.096
(.064)
.067


.185
.123
.019
.013
.792
.152


(.005**)
.037
(.466)
-.027


.661)


DUMRUB1


-.011
(.472
.002
(.932
.009


(.109)
-.010
(.663)
.015
(.493)
-.012
(.592)
.008
(.761)
-.246
(.000**)


Standard
Error
R-Squared
DW
SSR


.041
.881
1.863
.041


.070
.566
2.638
.153


.031
.705
2.730
.027


Dummied Observation:


Rubber-1975:7


.057


JAN

FEB


MAR


APR

MAY


JUN












RESULTS


FOR EQUATION


(3-1)


1979-1984


Variable


MACHINERY
Estimated
Coefficient


TOBACCO
Estimated
Coefficient


PLASTICS
Estimated
Coefficient


CHEMICALS
Estimated
Coefficient


.000**)
.033
.377)
.325
.000**)
.284
.000**)
.057


MAR


APR


MAY


.126
.227
.000
.124
.001


JUN


JUL


AUG


SEP


.135
(.001**)
.178
(.000**)
.128
(.001**)
.128
(.001**)
.088
(.020*)
-.171
(.000**)


OCT


NOV


CAR


DUMTOB


.039
.476
.005
.947
.119
.209
.215


(.010*)
-.103
(.181)
-.045
(.559)
-.329
(.000**)
-.155
(.058)
-.079
(.304)
-.062
(.421)
-.003
(.968)
-.070
(.361)
-.159
(.053)
.829
(.000**)


-.108
(.008
.079
(.006
.220
(.000
.219
(.000
.036
(.179
.159
(.000
.102
(.000
.130
(.000
.129


.000**
.090
.001**
.128
.000**
.076


(.006**)
-.1240
(.000**)


-.080
(.000**)
.060


.011*
.057
.033*
.174
.000*


.067
.003
.138
.000
.117
.000
.142
.000


.103
(.000**)
.045
(.041*)
.085
(.000**)
-.007
(.759)
-.015
(.510)


DUMPLS


-.187
(.000**)


DUMCHM


Standard
Error
R-Squared
DW
SSR


-.330
(.000**)


.064
.647
2.652
.242


.132
.594
.036


1.010


.046
.674
1.873
.123


.037
.802
1.662
.080


-.134


JAN


FEB

















Variable


BEVERAGES
Estimated
Coefficient


TRANSPORTATION
Estimated
Coefficient


RUBBER
Estimated
Coefficient


JAN

FEB


MAR


APR


MAY


JUN


JUL


AUG


SEP


OCT


NOV


CAR


DUMDNK


.035
(.267)
-.094
(.036*)
-.084
(.100)
.048
(.286)
-.225
(.000**)
.045
(.289)
-.079
(.063)
-.046
(.278)
.011
(.785)
-.001
(.990)
.072
(.106)
-.021
(.633)
-.046
(.284)
-.406
(.000**)


-.112
(.028*)
.108
(.129)
.173
(.048*)
.199
(.010*)
-.039
(.579)
.255
(.001**
.097
(.172)
.054
(.448)
.196
(.007**
.041
(.557)
.191
(.009**
.082
(.248)
-.118
(.118)


.013
(.567
-.124
(.001
.117
(.006
.053
(.145
-.015
(.655
.003
(.921
-.011
(.741
.034
(.317
-.022
(.512
-.060
(.095
.046
(.177
-.068
(.048
-.073


(.044*)


DUMTRN


.437
(.002**)


DUMRUB2


-.262
(.000**)


Standard
Error
R-Squared
DW
SSR


.069
.713
2.780


.122
.495
.355
.858


.262


.058
.604
2.157
.197











RESULTS


FOR EQUATION


(3-3)


1975-1984


P-Values


in parentheses.


Variable


MACHINERY
Estimated
Coefficient


TOBACCO
Estimated
Coefficient


PLASTICS
Estimated
Coefficient


CHEMICALS
Estimated
Coefficient


4.757


JAN

FEB


MAR


APR


MAY


JUN

JUL

AUG


(.000**
-.125
(.001**
.124
(.008**
.027
(.503)
.050
(.009**
.046
(.200)
.004
(.921)
.002
(.952)
.051
(.161)
-.003
(.929)
.015
(.655)
.012
(.719)
-.082
(.024*)
-.049


SEP


OCT


NOV

DEC


CAR

CP4


(.204)
-.044
(.667)


8.885
(.000i
.100
(.222)
.079
(.443)
.234
(.010.
-.055
(.543)
-.168
(.106)
-.081
(.311)
-.010
(.899)
.038
(.630)
.019


.816)
.111
.167)
.102
.269)
.093


(.245)
-.055
(.530)


.453
.000**)


(.040*)
-.044
(.183)
.047
(.152)
.003


(.925
.047
(.177
.047
(.170
-.013
(.705
.050
(.118
.024
(.437
-.117
(.001
-.055
(.138


4.789
(.000**)
-.061
(.080)
-.020
(.639)
.066
(.082)
.043


(.016j
.051
(.133)
.044
(.198)
.065
(.058)
.033
(.327)
-.022
(.508)
.015
(.642)
.014
(.659)
-.056
(.096)
-.004
(.905)
-.051
(.600)


-.893


(.000**)


CP10


-.193


(.025*)


Standard
Error


.079


.176


.076


.074

















Variable


BEVERAGES
Estimated
Coefficient


TRANSPORTATION
Estimated
Coefficient


RUBBER
Estimated
Coefficient


4.939
(.000**)
-.100


JAN

FEB

MAR


APR


MAY

JUN


JUL


AUG

SEP

OCT


(.063)
-.068
(.295)
.082
(.151)
-.121
(.054)
.087
(.106)
-.035
(.507)
.000
(.993)
.063
(.240)
.029
(.583)
-.101
(.154)
.006
(.904)
.047
(.378)
-.020
(.713)
-.050
(.758)


NOV


CAR


CP10


.809
.000w
.021
.739)
.039
.619)
.038
.579)
.012
.704)
.025


(.693)
.024
(.697)
-.012
(.851)
.093
(.132)
-.042
(.502)
.092
(.119)
-.019
(.746)
-.076
(.219)
-.008
(.898)


.972


(.0004
.040
(.382)
-.022
(.715)
.017
(.695)
-.012
(.786)
.010
(.810)
-.041
(.240)
.023
(.594)
-.003
(.948)
-.070
(.078)
.028
(.476)
-.050
(.212)
.000
(.994)
-.011
(.807)


-.475
(.008**)


.145
(.121)


Standard
Error
R-Squared


.111
.324


.136
.275


.088
.384











RESULTS


FOR EQUATION


(3-3)


1975-1978


Variable


MACHINERY
Estimated
Coefficient


TOBACCO
Estimated
Coefficient


PLASTICS
Estimated
Coefficient


CHEMICALS
Estimated
Coefficient


-.173
(.000**)
.166
(.002**)
.065
(.150)
4.593
(.002**)
.041
(.258)
.018
(.611)
-.002
(.945)
.054
(.142)
-.005
(.885)
.038
(.291)
-.084
(.024*)
-.009
(.797)
-.079
(.073)
.003
(.993)


SEP


OCT


NOV


DEC


CAR


.00
(.97
-.12
(.00
.08
(.01
-.23
(.00


4.321
(.000**)
-.073
(.012*)
-.100


(.001
-.014
(.608
-.093
(.002
.035
(.211
-.117
(.000
.032
(.251
-.082
(.019


1.816
(.260)
-.061
(.436)
.101
(.128)
-.086
(.154)
.044
(.439)
-.024
(.674)
.040
(.485)
.043
(.445)
-.048
(.398)
.042
(.458)
-.035
(.539)
-.077
(.175)
.008
(.906)


.002
.963)
.046


.082
(.044*)
.083
(.041*)
.101
(.014*)
.084
(.039*)
.027
(.486)
.051
(.201)
-.022
(.586)
.002
(.962)
-.014
(.767)
-1.503
(.000**)


1.938


(.000**)


.606


(.087)


Standard
Error
R-Squared
DW


.049
.710
1.599


.037
.852
1.666


.078
.577
.398


.054
.714
.772


JAN

FEB


MAR


APR


MAY


JUN

JUL

AUG
















Variable


BEVERAGES
Estimated
Coefficient


TRANSPORTATION
Estimated
Coefficient


RUBBER
Estimated
Coefficient


.000
(.997)
-.051
(.427)
.151
(.014*
-.181
(.004*
.123
(.029*
-.004
(.942)
.038
(.477)
.114
(.038*
.038
(.509)
8.813


JUN

JUL


AUG


SEP


OCT


NOV


.016
.014
.760
.075
.097


DEC


CAR


-.018
(.727)
-.914
(.229)


CP10


-.070
(.443)
.900
(.451)
.119
(.257)
6.632
(.044*)
.095
(.266)
.029
(.732)
.002
(.985)


.058
(.499
-.053
(.532
.086
(.314
-.030
(.719
-.069
(.413
-.023
(.822


-.002
(.941)
.006
(.849)
.044
(.117)
.039
(.164)
.051
(.057)
7.937
(.000*
.037
(.140)
.045
(.052)
-.002
(.912)
.022
(.325)
-.006
(.788)
.003
(.899)
.032
(.243)


-.440
(.527)


-.723
(.000**)


Standard
Error
R-Squared
DW


.058
.636
.624


.116
.261
.435


.031
.582
.974


JAN


FEB


MAR


APR


MAY












RESULTS


FOR EQUATION


(3-3)


1979-1984


Variable


MACHINERY
Estimated
Coefficient


TOBACCO
Estimated
Coefficient


PLASTICS
Estimated
Coefficient


CHEMICALS
Estimated
Coefficient


C

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

NOV

DEC

CAR

CP4


3.827
(.000*
-.116
(.041*
.096
(.155)
-.001
(.980)
.045
(.160)
.137
(.067)
-.021
(.710)
-.010
(.858)
.035
(.526)
-.016
(.766)
-.022
(.966)
.140
(.063)
-.143
(.011*
-.041
(.455)
.139
(.374)


CP5

CP1

Standard
Error .093
R-Squared


9.634
(.000*
.147
(.231)
.144
(.324)
.268
(.039*
-.009
(.946)
-.206
(.310)
-.120
(.318)
.012
(.921)
.031
(.796)
.056
(.642)
.127
(.297)
-.206
(.310)
.106
(.376)
-.040
(.750)


5.501
(.000
-.007
(.870
.103
(.064
.055
(.249
-.048
(.276
.029
(.599
.009
(.848
.038
(.405
.035
(.432
-.003
(.948
.038
(.401
.017
(.758
-.135
(.003'
-.090
(.058


3.391
(.000
-.107
(.025
-.048
(.393
.037
(.448
.055
(.043
.160
(.012
.020
(.659
.044
(.346
.007
(.876
-.052
(.265
.003
(.955
.158
(.013
-.094
(.044
.002
(.973
.230
(.082


-1.047
(.005**)


.198
.116)


.202
.533


.076
.630


.078
.634















BEVERAGES
Estimated
Vari&ad~ficient


TRANSPORTATION
Estimated
Coefficient


RUBBER
Estimated
Coefficient


1.663
(.164)
-.177
(.019*)
-.103


FEB

MAR

APR

MAY


(.231
.008
(.913
-.033
(.737
.041
(.560
-.092
(.199
-.062
(.391
.002
(.975


JUN


JUL


AUG


SEP -.014
(.840
OCT -.015
(.886
NOV -.029
(.711
DEC -.002
(.981
CAR -.027
(.713


6.755


.000**)
.069


.458)
.026
.816)
.015


(.875)
-.027
(.601)
.007
(.957)
.020
(.813)
-.022
(.811)
.116
(.206)
-.035
(.699)
.122
(.175)
-.016
(.895)
-.082
(.369)
-.021
(.822)


2.570
(.000**)
.061
(.468)
.069
(.524)
-.003
(.964)
-.041
(.509)
-.019
(.748)
-.010
(.852)
.074


(.336)
-.038
(.523)
-.122
(.043d
.022
(.713)
-.085


(.15
-.00
(.94
-.03
(.58


CP10


.642
.011*)


-.463
(.076)


.431
(.004**)


Standard
Error
R-Squared
DW


119


.154
.482


765


.101
.203.499
.644


1.096


JAN











RESULTS


FOR EQUATION


(3-4)


1975-1984


P-Values


in parentheses.


Variable


MACHINERY
Estimated
Coefficient


TOBACCO
Estimated
Coefficient


PLASTICS
Estimated
Coefficient


CHEMICALS
Estimated
Coefficient


DUMMAC


-.062
(.277)
-.223
(.001**)


.068
(.101)


-.100
(.025*)


-.118
(.000**)


DUMTOB


.806
(.000**)


DUMPLS


-.098
(.032**)


DUMCHM


JAN


FEB


MAR


APR


MAY


JUN


JUL


-.014
(.636)
.238
(.000.
.150
(.000"
.003
(.918)
.154
(.000*
.084
(.003*
.084
(.003*
.134
(.000*
.081
(.005*
.100
(.001*
.022
(.434)
-.093
(.000*
-.198
(.673)


AUG


SEP


OCT


NOV


DCAR

CP4


-.006
(.918)
-.001
(.987)
.120
(.031*)
-.161
(.004*"
-.042
(.420)
-.238
(.000**
-.139
(.011*)
-.060
(.256)
-.081
(.123)
.006
(.908)
-.099
(.061)
-.081
(.018*)


.083
.001
.127
.000
.163
.000
.008
.728
.147
.000
.084
.000
.126
.000
.127
.000
.066
.005
.125
.000
.064


(.005**)
-.040
(.004**)


- .316
(.000**)
.027
(.116)
.040
(.029*)
.125
(.000**)
.030
(.070)
.115
(.000**)
.103
(.000**)
.120
(.000**)
.086
(.000**)
.026
(.114)
.055
(.002**)
-.014
(.397)
-.021
(.041*)
.525
(.054)


-.194
(.347)




Full Text

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NOMINAL WAGE CONTRACTS AND THE BUSINESS CYCLE:
AN EMPIRICAL INVESTIGATION
by
CAROL ANN DOLE
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
1992

ACKNOWLEDGEMENTS
"Sometimes you bite the bear; sometimes the bear bites
you." With the support, guidance and unrelenting humor of
Mark Rush, this dissertation (in addition to other travails
along the way) came together. David Denslow's contributions
(along with translation services) helped make this project
complete. Also deserving thanks for their efforts and comments
are my other committee members: William Bomberger, Douglas
Waldo and Michael Ryngaert. Besides those who directly helped
with my dissertation, I would be remiss not crediting another
friend and advisor without whose help the dissertation might
not even have been started, Anindya Banerjee.
Throughout these last four years, other faculty members,
staff and classmates have also offered helpful advice and
knowledge making this program markedly more bearable.
Lastly, I must thank my family: my husband Richard,
whose love and continual support helped make it possible to
reach my goals; my parents, Eugene and Irma Badger, who have
instilled the value of knowledge and always provided the love
to make things a little easier; my sisters, Sadie, Kelley and
Emily who always offered encouragement; and finally my
daughter, Taylor, who always gave a smile and a hug whenever
needed.
ii

TABLE OF CONTENTS
ACKNOWLEDGEMENTS ii
ABSTRACT iv
CHAPTERS
1 INTRODUCTION 1
2 THE POLITICAL AND ECONOMIC CLIMATE OF BRAZIL
Introduction 15
Wage Policies 16
3 NOMINAL WAGE CONTRACTS—NATIONWIDE EVIDENCE
Introduction 27
Past Literature 30
Description of the Data 33
Tests of the Importance of Contracting 34
Empirical Results 45
Summary and Conclusions 47
4 NOMINAL WAGE CONTRACTS—STATEWIDE RESULTS
Introduction 57
Review of Empirical Analyses 62
Description of the Data 66
Estimation Technique and Regressions 67
Empirical Results 70
Summary and Conclusions 71
5 SUMMARY AND CONCLUSIONS 77
APPENDICES
A MARGINAL RATES OF READJUSTMENT FOR DIFFERENT
WAGE SIZES 80
B REGRESSION RESULTS 81
C REAL WAGE RATES AND OUTPUT BY INDUSTRY 124
REFERENCES 131
BIOGRAPHICAL SKETCH 134
iii

Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
NOMINAL WAGE CONTRACTS AND THE BUSINESS CYCLE:
AN EMPIRICAL INVESTIGATION
By
Carol Ann Dole
August 1992
Chairman: Dr. Mark Rush
Major Department: Economics
In order for changes in the money supply to be
nonneutral, frictions must be introduced into the standard
neoclassical model. One of the most common sources of
nonneutrality is the assumption of nominal wage contracts. As
they are typically modeled, these contracts assume nominal
wages are (at least somewhat) rigid and that the level of
employment is adjusted in accord with the firm's labor demand
schedule. This standard nominal contracting approach makes
changes in the money supply nonneutral.
This transmission property of the nominal wage contract
has not gone unchallenged. The neoclassical model shows that
even though a labor contract fixes the nominal wage, firms and
workers may equate the marginal product of labor to the
iv

marginal value of workers' time over all states of nature and
thus jointly determine the efficient level of employment. In
this framework then, money shocks will not change employment.
Given the opposing theories, previous empirical work has
attempted to test the role of wage contracts. Results from
this research are mixed. For example, one approach
investigates the degree of wage indexation and its
relationship to employment and output responses. One study
finds in favor of neutrality; the other analysis suggests
nonneutrality.
Following these empirical analyses, I use Brazilian data
to examine whether nominal wage contracts contribute to
propagating macroeconomic shocks. Brazilian firms were
required by law to adjust workers' salaries at specified
intervals to keep pace with inflation and productivity. Two
approaches are taken using approximately two decades of
monthly data disaggregated by industry. The first looks
across periods with different indexing schemes to study the
seasonal pattern of output as well as the correlation between
industry output and the cumulated increase in prices from one
index month to the next. The second approach, using two-stage
least squares (because the real wage switches from being
exogenous to endogenous), looks directly at the effect of
industries' real wage changes upon output.
Results from both approaches lend strong support to the
New Classical model where firms and workers ignore the
v

behavior of the actual real wage making monetary shocks
neutral.
vi

CHAPTER 1
INTRODUCTION
In order for changes in the money supply to be
nonneutral, frictions must be introduced into the standard
neoclassical model. While economists have suggested a variety
of different frictions, possibly the most common source of
nonneutrality is the assumption of nominal wage contracts.1, 2
1 Azariadis (1975) was one of the first economists to
rigorously examine issues of wage contracts. Within his model
he derived an optimal contract with a fixed wage.
Importantly, however, his model delivered the conclusion that
it is the real wage not the nominal wage that is fixed.
Essentially Azariadis' work suggested that under the optimal
contract, the real wage is unrelated to the realization of the
marginal revenue product of labor (MRPL). Hence consumption
is independent of the MRPL (which is affected by states of
nature) so that the real wage is stabilized. From the
perspective of macroeconomics, though, Azariadis' "sticky"
real wage gives no role to nominal aggregate demand shocks in
determining output. Thus this line of research, which
initially appeared promising as a rationale for sticky nominal
wages, no longer seems fruitful along this dimension.
2 Recently a strand of "New Keynesian" literature has
evolved that posits sticky prices in the output market as the
source of the friction, for example see Blanchard and Kiyotaki
(1987) or McCallum (1986). These models demonstrate that the
existence of small menu costs to changing prices, firms may
find it "close to" optimal to leave the price of their output
constant in the face of a change in demand. Take the case
where a monetary contraction lowers the demand for firms'
output. Given the menu costs, firms may leave their nominal
price constant because they find that in spite of their
reduced sales, they still sell enough goods at the higher real
price to offset enough of the lost revenue from failing to
change their prices. This thereby generates output responses
1

Fischer (1977) and Phelps and Taylor (1977) present models
typical of most, which assume that nominal wages are (at least
somewhat) rigid and that the level of employment is adjusted
in accord with the firm's labor demand schedule. This is a
very common approach to specifying nominal contracts, and it
makes changes in the money supply non-neutral. That is to
say, increases in the money supply raise the price level;
given the nominal wage's failure to respond to the
disturbance, firms increase their labor demand due to the
lower real wage; and thus output expands in response to the
increase in the money supply. This point is illustrated in
Figure 1-1.
Taylor (1979) modified this simple framework to show that
real effects will continue beyond price and wage adjustments
so long as the contracts are staggered and the terms are
adjusted periodically. Further, J. Taylor (1980) creates a
model that allows these staggered wage contracts to generate
as a result of a change in nominal demand. These models
suggest that the cost to the firms in lost profit from not
changing their prices are second-order while the overall
effects on the aggregate economy are first-order. The so-
called "externalities” produced by all firms behaving in this
fashion though, create business cycles at the macroeconomic
level. The importance of sticky output prices is
controversial; Barro, for instance, has pointed out that the
cost to firms from not changing their prices is second-order
only when the initial level of production is at the profit
maximizing level. Therefore, it is hard to see how this line
of analysis can account for persistent stickiness in prices,
which is necessary to generate persisting non-neutralities of
money. Moreover, empirical work has not been uniformly
supportive of the New Keynesian approach; see Koelln, Rush and
Waldo (1992) for example. Therefore I concentrate on the more
conventional sticky wage approach in my dissertation.
2

Figure 1-1. Employment Determined by Labor Demand Curve and Real Wage

4
persistence in unemployment and output similar to the United
States' post-war experience with respect to nominal
disturbances. More recently, Card's (1990) empirical analysis
finds that wages negotiated at the start of a contract period
are positively correlated to terms made at the end of the
previous period. This work creates some support for Taylor's
view of how the linkage from staggered contracts creates
persistence in the costs of labor and therefore employment and
output.
This view of the effects from nominal wage contracts has
not, however, gone unchallenged. Barro (1977) has pointed out
that even though a labor contract fixes the nominal wage,
firms and workers may equate the marginal product of labor to
the marginal value of workers' time over all states of nature
and thus jointly determine the efficient level of employment.3
In this case, the "shadow” equilibrium real wage (which equals
what the real wage would be in an auction market) will differ
from the actual real wage due to the presence of the "sticky"
nominal wage. In other words, the actual real wage, which is
affected by nominal disturbances, does not equilibrate the
labor market because it does not produce an efficient level of
employment. Instead, the level of employment is determined
3 This argument assumes both parties have equal
bargaining power. If either side has monopoly power, a Pareto
optimal outcome might not occur. Regardless of whether the
equilibrium is Pareto optimal, the level of employment is
invariant to changes in the money supply so that money remains
neutral.

5
where labor supply and demand meet at the (shadow) equilibrium
real wage. This idea is illustrated in Figure 1-2. The
efficient (and equilibrium) levels of the real wage and output
are W/P and L, respectively. As the actual real wage falls
due to an increase in the price level, firms and workers
remain at W/P and L; otherwise, at W/P' and L', the marginal
value of workers' time (the distance between points A and C)
is greater than the marginal product of labor (the distance
between points A and B) and a loss occurs (the distance
between B and C). In this framework then, money shocks will
not change employment since in the shadow auction market,
wages and prices change proportionately and leave the real
wage, and hence employment, constant. Therefore, wage
contracts may no longer be a source of non-neutrality.
Hall (1980), using a New Classical framework, extends
Barro's insight concerning the effects of real disturbances by
pointing out that labor relationships are long term. Thus
each side has an incentive to deal fairly with the other by
not taking advantage of the fixed nominal wage in the face of
changes in the marginal product of labor.
Let's look at Hall's point more closely. For a given
nominal wage, it is easy to see that a monetary shock that
increases the price level results in the actual real wage
being lower than the equilibrium real wage. According to the


7
standard Keynesian approach, this situation elicits an
increase in employment as firms move along their labor demand
curve. Hall (and Barro), however, ask two important
questions: To what extent would existing employees be willing
to work additional hours? And is it really in the firms' and
workers' best interests to determine the level of employment
by referring only to the labor demand curve? The argument
advanced by Barro and Hall is that because of long-term
relationship between firms and workers, both parties realize
that these random monetary shocks will (effectively) lower
their actual real wage below the equilibrium real wage (and
marginal product of labor) half the time so that firms
benefit. However, the other half of the time, the shocks
raise the actual real wage above the equilibrium real wage so
that workers "win." But in both cases what the losing party
"loses" exceeds what the benefitting party "wins" since
employment is at an inefficient level. Clearly, ex ante, each
side can improve its position if it agrees to operate at the
efficient level of employment. In other words, firms and
workers do not respond to the actual real wage; instead, they
agree to equate the marginal value of workers' time to the
marginal product of labor (which also equals the equilibrium
real wage).4 Thus Hall (and Barro) answer the questions they
4 As Hall points out, the idea of long-term relationships
addresses two worker/firm issues—efficiency, which has been
discussed in the text, and income smoothing. The latter point
is simply that workers probably prefer a smoother path of
consumption to one that fluctuates. To the extent that a

8
pose by claiming that employees would not be willing to work
the extra hours and that it is not in firms' or workers'
interests to sign contracts that obligate employees to work
the extra time.5
In contrast to nominal shocks, it is apparent that
(because of long-term relationships) real disturbances can
generate changes in the marginal product of labor, employment,
and hence output.6 However, the Keynesian model allows both
real and nominal disturbances to generate the same output
response. This is, of course, the major difference between
the Keynesian approach to labor contracts and the Barro/Hall
New Classical approach.
On a related point, Hall discusses the fact that to meet
an increase in demand, firms can expand their labor input in
a variety of ways: hire more labor, ask current workers to
smoother path of income leads to smoother consumption, workers
would prefer smoother income to a fluctuating path.
5 Recognizing the Barro/Hall analysis may be one reason
New Keynesians have made the distinct departure from the
sticky nominal price framework. Specifically, as Ball, Mankiw
and Romer (1989) point out, firms and their customers are not
part of a long-term relationship—no loyalty exists to prevent
buyers from moving up their demand curves as price-setting
firms maintain high real product prices in the face of tight
monetary policy. This lack of long-term arrangements, then,
can produce business cycles given sticky prices in the goods
market.
6 For a given wage level when there is a negative real
shock, workers expect to be kept on the payroll while they
decrease their hours or intensity or perhaps be temporarily
laid off. So while the actual real wage is higher than the
equilibrium real wage (since the negative shock has reduced
the MPL) workers are willing to accept a reduction of labor
demanded.

9
work overtime, persuade them to work more intensely or a
combination of these options.7 Therefore, in my empirical
work in addition to considering the relationship between the
real wage and employment, I also investigate the correlation
between the real wage and output in order to provide more
insight into the effects of nominal shocks.8
Given the opposing theories, there are two strands of
empirical work that attempt to test the role of wage
contracts. The first examines the time series relationship
between real wages and employment activity. Under the
standard contracting case, one would expect to find that real
wages vary countercyclically. Yet, early work (Dunlop, 1938;
Tarshis, 1939) found a positive correlation between real wages
and employment. More recent results are mixed, with some
continuing to find support for a negative relation while
others find no relation. For instance, Geary and Kennan
(1982), studying Canadian data, find no statistical
relationship between employment and the real wage. Bils
(1985), however, using disaggregated data, finds procyclical
7 Actual data tend to show that work intensity changes
proportionately with output as opposed to employment hours
varying with output. Okun's Law expresses this fact claiming
that a 1% change in unemployment rates produces a 3%
corresponding change in output. In my empirical work I use
both labor and total output in separate regressions in order
to allow for both options.
8 I could find data on employment only in terms of the
number of workers, not hours. If, as Hall points out, firms
may not change the number of employed workers but instead
adjust intensity or hours, we may only see the effects of a
change in the real wage on output and not employment.

10
real wages. Bils credits these differences to his studying
the behavior of real wages of individuals, the inclusion of
overtime earnings and using a later sampling period than
earlier studies. While these results lend uncertainty to the
worth of nominal wage rigidity models, given the pitfalls of
the simple time series approach taken by part of this
literature, it is perhaps unsurprising that no firm conclusion
has been reached.
A more direct route has been pursued by Ahmed (1987) and
Card (1990). Ahmed investigates the nonneutrality of money by
testing whether employment and output are sensitive to the
degree of wage indexation. The basic idea is that if nominal
wage contracting is important, the less flexible (that is, the
less indexed) is the wage, the greater the impact of a
monetary shock on employment and output. Using Canadian
manufacturing industries, which employ a variety of indexing
schemes, Ahmed tests this implication of contracting models.
He fails to find a relationship between the degree of
contracting and the extent to which a monetary shock affects
real variables, and hence concludes that nominal wage rigidity
cannot account for business cycles. Card, also using Canadian
data, asserts that it is the unexpected components of the real
wage (namely unanticipated price changes), along with the
degree of indexation, that should generate negative employment
responses. Therefore, he constructs measures of unexpected
inflation and real wage changes for use in a labor demand

11
model. Card's results support a role for surprise inflation
in impacting employment levels via end-of-contract real wage
levels. Card concludes that nominal contracts are
instrumental in determining labor and output reactions. Thus
given these divergent results, this strand of literature also
produces no firm conclusions.
Following Ahmed and Card, I use Brazilian data to examine
whether nominal wage contracts play an essential role in
propagating macroeconomic shocks. I exploit the fact that
from 1965 through 1984, Brazil's price level rose over 7000
times as seen in Figure 1-3. Brazilian firms generally fixed
their employees' nominal wages, but were required by law to
adjust workers' salaries at specified intervals to keep pace
with inflation and productivity. From 1965 to 1979, the
adjustments were required annually; in 1979 the law changed to
require semi-annual adjustments. Because of the lagged
indexing formula and high Brazilian inflation, real wages fell
until readjustment occurred, when they were raised to maintain
purchasing power. According to the standard contracting
approach, as the real wages fell prior to the indexing date,
firms would add workers and output would respond positively.
Conversely, New Classical economists suggest that firms and
workers would not change the level of employment in the face

Figure 1-3 Price Level in Brazil

13
of a monetary shock and so there should be no tendency for
contracts to influence output.9
Relative to Ahmed and Card, my data set has a major
advantage. Because inflation in Canada was relatively low,
and the unexpected inflation Card tries to measure even
smaller, both Ahmed and Card must search for relatively small
effects.10 However, inflation in Brazil was far from small.
If there are any effects from nominal contracts, my data may
be better able to uncover them.11
9Between 1979 and 1983, the government lifted price
controls on industrial inputs, but reimposed them in mid-1983.
In 1985, a new administration imposed strict price controls
and even changed the price index to lower inflationary
expectations. Still, continued pressures made the government
freeze consumer prices again. Since high inflation continued
to exist, the price controls were more than likely ineffective
or did not cover much of the economy.
10 Indeed, this could be why Ahmed failed to find any
effect from monetary disturbances. Card's results, meanwhile,
may be the result of mismeasurement of the unexpected
component of inflation.
11 This advantage, however, may also conceal a related
disadvantage: One might worry that in high inflation
environments workers and firms make efficiency enhancing
adjustments (as Barro suggested) that they might forego in
less inflationary times. In other words, it might be the case
that in low inflation countries, nominal wage contracts
function as postulated by Keynesian analysis while in high
inflation countries, the contracts are altered to be in line
with Barro's approach. Of course, the observation that
individuals placed in high inflation countries may alter their
behavior when compared to residents in low inflation countries
is hardly unique to my study. And, given the prominence with
which high inflation countries have served as "laboratories"
for testing monetary phenomena, most economists apparently
think this potential drawback to be generally minor.

14
The next chapter discusses the historical background of
Brazil and its wage policies. Chapter 3 discusses the analysis
of nationwide data while Chapter 4 takes a different approach
using statewide data. The fifth chapter provides a summary
and conclusions.

CHAPTER 2
THE POLITICAL AND ECONOMIC CLIMATE OF BRAZIL
Introduction
During its 169 years of independence, Brazil's political
climate has varied and continues to play an important role in
its economic policies, especially in the latter half of the
twentieth century. Starting in 1930, a populist dictatorship
led by President Getulius Vargas held control until 1945 when
it was replaced by a more liberal federal republic and a
series of "popularly" elected presidents (in 1946, the
electorate represented only 16 percent of the population).
During this period of democratic rule, economic growth
varied from 10 percent annually in 1954 to a low of 1.5
percent in 1963. As the economy worsened, President Joáo
Goulart's government designed a stabilizing "Three Year Plan";
still, annual inflation grew exorbitantly, climbing to a level
of more than 80 percent in 1963. Before the plan accomplished
its goals, the military's toleration of the country's economic
stagnation came to an end, and it toppled Goulart's government
15

16
in March 1964. It was this military regime, led by Castelo
Branco, which instituted the wage indexation scheme.1
Wage Policies
During the governance of Getulio Vargas in the 1930s, the
government enacted a Labor Code creating unions dependent on
the Ministry of Labor for their existence.2 The behavior of
the money supply notwithstanding, it is clear that in the
military's attempt to enforce its economic policies, it
attacked the union structure by claiming the unions were
responsible for the wage-price spiral. Therefore, to combat
uncontrolled wage increases, Circular Number 10, specifying
the formula used for wage indexation, was enacted in June
1964. The following formula (except for minor adjustments3)
determined wages until 19684:
1 Not surprisingly, military wages were not covered by
the policy. Still, its members protested their falling wages.
In one instance, an officer stormed the town hall to demand
pay raises for his men; he was denied the raise and charged
with illegal troop movements.
2 This union structure, patterned on that created by
Mussolini, enabled the military government to effectively
impose the wage guidelines. Labor was required to pay dues
into accounts which the government managed. If the labor
leaders did not follow the party line, they were replaced or,
sometimes, the union was disbanded.
In 1965, the expected inflation and productivity
components were temporarily omitted from the guidelines.
4 For details, see Fishlow (1974).

17
‘ 1 24¿J 'It[ ( 2 J
+ CC
where
Wt+1 = the nominal wage to be set in the 25th month
It = the price index in month t
IP = the expected inflation rate over the next
year
a = the expected rate of increase in productivity.
In summary, the formula contained three basic elements: a
compensating factor for past inflation, another for
anticipated inflation and a third to take account of
productivity improvements.5 This initial indexing regime
applied only to government employees; in July 1964, it was
extended to the public sector including state-owned
corporations or ones in which the state held majority control.
5 In addition to regular wages, companies were required
to pay a "thirteenth monthly wage" (about 10% of the regular
wage) each December; in August 1965, a new law mandated that
this special wage was to be spread out over two installments -
one between January and November and the next in December.

18
One year later, all wages in the private sector came under the
jurisdiction of the law. 6
In addition to the wage indexation policy, the military
government radically changed job security measures in 1966.
Prior to enacting the Guaranteed Fund for Time-in-Service
(FGTS) law, firms were required to make indemnity payments to
fired or laid off workers.7 In general, these payments
constituted penalties great enough to discourage material
layoffs. In 1966 however, the FGTS changed the payment
structure. Firms were now required to pay 8 percent of
employees' salaries into an escrow account every month. When
laid off or fired, the employee received the amount set aside
regardless of the length of time employed. On the one hand,
firms had no motive for layoffs since the 8 percent had
already been paid; additionally, there was no difference in
seniority between those employed more or less than ten years.
6 Realizing that labor would oppose this restrictive wage
policy, additional legislation passed in 1964 revised the
constitution; for instance, strikes, for the most part, were
forbidden. The Antistrike Law passed in June 1964 did permit
strikes for improved working conditions or wages, once they
were authorized by a regional labor court. From 1964 through
at least 1985, most strikes that were ruled legal were those
where companies had not paid salaries for three months. The
strength of the Labor Code combined with the Antistrike Law
effectively crushed strike activities: strikes fell from 225
in 1965 to 15 in 1966, 12 in 1970, and none in 1971 and
remained relatively low until the middle of the 1980s. For
details, see Alves (1985).
7 This measure applied to those employed with the firm
for 1 to 10 years. For those with 10 years of service, firms
were required to prove the employee committed a grave offense
in order to terminate employment. This tended to encourage
firms to fire workers before they reached 10 years of service.

19
Alternatively, firms were only required to pay a portion of
wage readjustments to those employed less than one year. So,
in the face of wage readjustments, firms may have been
motivated to layoff higher-paid workers in favor of those
unprotected by the wage formula adjustments. Additionally, it
has been reported that some workers intentionally goaded the
firm into firing them enabling them to collect their fund and
move to a higher paying job.8,9
The military's economic plans included stabilization
measures and modernization and strengthening of capital
markets in addition to the "wage squeeze" policy. In fact,
before the takeover, the market for long-term securities no
longer existed since a usury law prohibited interest charges
over 12 percent. During the same period, money growth fell
from 75.4 percent in 1965 to 34.8 percent in 1974. These
policies effectively met their goal of controlling inflation
from 1964 through 1973; in 1964, inflation reached 87 percent
annually, but fell to 24 percent in 1967 and 15 percent by
1973 as seen in Figure 2-1.
8 For details, see Smith (1988).
9 On the whole, it appears that firms and workers were
able to control their employment decisions. However, in case
firms did fire workers as the readjustment period approached,
leads were run in the regressions. There were no signs that
this behavior, if it existed, affected the behavior of output.

250
200
150
100
50
0
Figure 2-1 Brazilian Inflation

21
The latter part of this period, 1968 to 1974, was known
as Brazil's economic "miracle.” Real economic growth averaged
over 10 percent annually during the upturn.
By 1968, some of the weaknesses of the original formula
were corrected. Wages would now be adjusted according to:10
A=
+a-l
where
and
A = the rate of wage adjustments
a = a productivity factor
Ra = the actual real wage in the two years
preceding the adjustment
R13 = the real wage in month 13
Rm = the mean real wage in the two years
preceding the adjustment
nR = forecast inflation for the 12 months
immediately preceding the adjustment.
Additionally, R„ was determined as follows:
10
For details, see Carvalho (1984).

22
E w^t+ E ^tP
t*l t-13
where
n. l+HA/2
i+n*/2
where
R„ = the mean real wage in the two years preceding
the adjustment
Wt = the wage in month t
Xt = the wage correction index in month t
P = the factor for correcting the adjustment for
residual or forecasted inflation
nA = the actual inflation during months 13-24
nR = the inflation forecast used for months
13-24.
Specifically, the 1968 revisions corrected the partial
deterioration of wages by including the average real wage in
calculations.11
11 The original formula allowed underestimated inflation
to go uncorrected in subsequent wage negotiations. The 1968
formula at least took into account residual inflation in the
12 months immediately preceding the adjustment.
Unfortunately, this identical correction was ignored in the
following renegotiation!

23
The formula was fine-tuned again in 1974. A persistent
issue was finally corrected—now only the incorrectly
predicted inflation in the 12 months preceding the
renegotiation would be used. In addition, a, the rate of
increase in productivity would now be multiplied by (not added
to) the average real wage. The new wage could now be
calculated using this formula:12
where
A = the rate of the wage adjustment
W = the new wage once adjusted
Wt = the wage in each of the preceding 12 months
IP = the forecast inflation in the 12 months
preceding the current adjustment
nA = the actual inflation rate during months 13-24
IP = the residual inflation used in the previous
year's adjustment
a = the rate of increase in productivity
Xt = the wage index in month t.
In summary, while the economy boomed, the wage indexation
formula was revised in four ways: the government moved to
provide standardized indices for determining salary
12
For details, see Carvalho (1984).

24
adjustments;13 second, to prevent underestimation of
inflation, the forecasting procedure was refined; third, the
base period for calculating the base wage was reduced from two
years to one year; and fourth, the wage raise was discounted
by multiplying (rather than adding) the productivity
coefficient by the average real wage.
From 1974 through 1980, economic growth fell to somewhat
over five percent annually, and then rebounded a bit in the
1980s. Against a backdrop of lower growth and rebounding
inflation, several additional changes were made to the
indexing scheme. Specifically, in 1976 additional refinements
were made to the productivity coefficient; it was redefined
using a terms of trade index to account for not only foreign
trade but for differences in rural and urban economies.
However in November 1979, the indexation policy underwent
a much more pivotal change: after November, wages were
adjusted every six months rather than every twelve months as
13 The National Council on Wage Policy provided cost of
living deflators and expected profit and productivity figures.
Labor courts were required to use these to settle wage
disputes. Since workers basically were not allowed to strike,
workers had little to say in salary adjustments. It should be
noted that these "guidelines" were not maximum adjustments;
firms and workers could agree to higher terms, but firms could
not use this cost to apply for product price increases.

25
had been previously the case14. Specifically the formula
was15:
AiJt = PetWfl.lCi + c2 + 0.8c3 + 0.5cA)
+ Wm(0.3c2 + 2.3c3 + 6.8c4 + 16.8c5) ]/ W
where
Aijt = semiannual rate of readjustment to be applied to
the wage in the class i, of industry group j,
starting in month t.
P6 = (INPCt-2/INPCt.8) - 1 is the semiannual rate of change
in the INPC (the National Consumer Price Index)
W = the nominal wage to be adjusted
Wm = the value of the highest regional nominal wage
c¿ = 1 for wage class i which includes the value of w
(i= 1,...,5 and 0 otherwise.
The 1979 law additionally specified the following terms:
- the productivity growth coefficient was no longer
included specifically in the formula; management and
labor would now negotiate this factor, and it could not
be passed on in prices;
- the government would provide an official price index
(INPC) the month before the readjustment date;
14 Macedo (1983) , as well as others, explain that the
government's motivation for switching to six-month indexing
was based on the idea that annual readjustments caused a lower
yearly average real wage if inflation doubled. Instead, by
reducing the time between adjustments (say, in half), the
average real wage would be maintained if inflation doubled.
15 For details, see Macedo, (1983).

26
- wages would now be differentiated by minimum wage
levels. The minimum wage strata criteria were updated
within one year.
For example, those workers earning three times the
minimum wage received 110 percent of the INPC while those
earning between 15 and 20 times the minimum wage earned 50%
adjustments. For specifics, see Appendix 1.
In my later empirical work, I exploit this movement
toward more frequent indexing to provide a test of the
Keynesian and New Classical hypotheses. From late 1983
through 1984 wage increases, while still granted every six
months, were based on a new formula that related wage brackets
and changes in the cost of living index. By 1985, however,
under severe pressure from the unions, the government
abandoned the indexing formula. The cessation of the indexing
formula truncates my sample period in 1985; however more
complicated schemes were used until 1987 when quarterly
indexing was instituted.16
16 The unions, with regenerated power, pressured for
quarterly wage increases which the administration disallowed.
In subsequent plans, wages were frozen; at renewal dates,
salaries could be raised by at least 60 percent of the price
index (INPC). Wages were only readjusted during the contract
period if the INPC rose by 2 0 percent when wages were adjusted
accordingly. This wage "trigger" was abandoned in 1987. The
movement to more frequent indexing changes, along with the
general dissatisfaction with wage levels lends support to the
hypothesis that results are not observationally equivalent to
Akerloff and Yellen's (1985) efficiency wage theory.

CHAPTER 3
NOMINAL WAGE CONTRACTS—NATIONWIDE EVIDENCE
Introduction
In order for changes in the money supply to be
nonneutral, frictions must be introduced into the standard
neoclassical model. While economists have suggested a variety
of different frictions, possibly the most common source of
nonneutrality is the assumption of nominal wage contracts.1
Fischer (1977) presents a model typical of most, which assumes
nominal wages are (at least somewhat) rigid and that the level
of employment is adjusted in accord with the firm's labor
demand schedule.2 This standard nominal contracting approach
makes changes in the money supply nonneutral. That is to say,
increases in the money supply raise the price level; given the
1 Azariadis (1975) determines that optimal contracts can
exist; in his paper though, it is real wages that are fixed
throughout the contract period, not nominal. Under the
optimal contract, the real wage is unrelated to the
realization of the marginal revenue product of labor (MRPL).
That is, consumption is independent of the MRPL (which is
affected by states of nature) so that the real wage is
stabilized. As opposed to "sticky" nominal wages, the
"sticky" real wage gives no role to aggregate demand in
determining output's response to monetary shocks.
2 Phelps and Taylor (1977) present a model similar to
Fischer's.
27

28
nominal wage’s failure to respond to the disturbance, firms
increase their labor demand due to the lower real wage; and
thus output expands in response to the increase in the money
supply.
Taylor (1979) modified this simple framework to show that
real effects will continue beyond price and wage adjustments
so long as the contracts are staggered and the terms are
adjusted periodically. Further, J. Taylor (1980) creates a
model that allows these staggered wage contracts to generate
persistence in unemployment and output similar to the United
States' post-war experience with respect to nominal
disturbances. More recently, Card's (1990) empirical analysis
finds that wages negotiated at the start of a contract period
are positively correlated to terms made at the end of the
previous period. This linkage creates persistence in the
costs of labor and therefore employment.
This view of these effects from nominal wage contracts
has not, however, gone unchallenged. Barro (1977) has pointed
out that even though a labor contract fixes the nominal wage,
firms and workers may equate the marginal product of labor to
the marginal value of workers' time over all states of nature
and thus jointly determine the efficient level of employment.3
In this case, the "shadow" equilibrium real wage (which equals
what the real wage would be in an auction market) will differ
3 This argument assumes both parties have equal
bargaining power. If either side has monopoly power, a Pareto
optimal outcome might not occur.

29
from the actual real wage due to the presence of the "sticky"
nominal wage. In other words, the actual real wage, which is
affected by nominal disturbances, does not equilibrate the
labor market because it does not produce an efficient level of
employment. Instead, the level of employment is determined
where labor supply and demand meet at the (shadow) equilibrium
real wage. In this framework then, money shocks will not
change employment since in an auction market, wages and prices
change proportionately and leave the real wage, and hence
employment, constant. Therefore, wage contracts may no longer
be a source of nonneutrality.
Hall (1980) extends Barro's insight by pointing out that
labor relationships are long term so that each side has an
incentive to deal fairly with the other by not taking
advantage of changes in the price level. For example, random
money shocks will lower prices half the time and raise them
the other half. Therefore half the time, labor benefits and
half the time firms benefit depending whether the money
shocks—and hence price shocks—are lower or higher than
expected. However, on average, ex ante, each side can improve
its position if it agrees to operate at the efficient level of
employment.
This is obviously an important issue. In this
dissertation I provide some evidence on the real effects from
nominal wage contracting by using Brazilian data. As I
describe in more detail below, I exploit the fact that by law

30
Brazilian firms were required to adjust nominal wages paid to
workers at set intervals: initially once every year and then
later every six months.
The next section reviews some previous work exploring the
effects from wage contracts. It also describes features of my
Brazilian data that make it advantageous for exploring this
issue. The third section discusses the data that I use and
the fourth presents the specification of my regressions and my
tests. The fifth section reports results of the tests and the
last section highlights the important results.
Past Literature
Given the opposing theories, there are two strands of
empirical work that attempt to test the role of wage
contracts. The first examines the time series relationship
between real wages and employment activity. Under the
standard contracting case, one would expect to find that real
wages vary countercyclically. Yet, early work (Dunlop, 1938
and Tarshis, 1939) found a positive correlation between real
wages and employment. More recent results are mixed, with
some continuing to find support for a negative relation while
others find no relation. For instance, Geary and Kennan
(1982), studying Canadian data, find no statistical
relationship between employment and the real wage. Bils
(1985), however, using disaggregated date, finds procyclical
real wages. He credits these differences to his studying the

31
behavior of real wages of individuals, the inclusion of
overtime earnings and using a later sampling period than
earlier studies. While these results lend uncertainty to the
worth of nominal wage rigidity models, given the pitfalls of
the simple time series approach taken by part of this
literature, it is perhaps unsurprising that no firm conclusion
has been reached.
A more direct route has been pursued by Ahmed (1987) and
Card (1990). Ahmed investigates the non-neutrality of money
by testing whether employment and output are sensitive to the
degree of wage indexation. The basic idea is that if nominal
wage contracting is important, the less flexible (that is, the
less indexed) is the wage, the greater the impact of a
monetary shock on employment and output. Using Canadian
manufacturing industries, which employ a variety of indexing
schemes, Ahmed tests this implication of contracting models.
He fails to find a relationship between the degree of
contracting and the extent to which a monetary shock affects
real variables, and hence concludes that nominal wage rigidity
cannot account for business cycles. Card, also using Canadian
data, asserts that it is the unexpected components of the real
wage (namely unanticipated price changes), along with the
degree of indexation, that should generate negative employment
responses. Therefore, he constructs measures of unexpected
inflation and real wage changes for use in a labor demand
model. Card's results support a role for surprise inflation

32
in impacting employment levels via end-of-contract real wage
levels. Card concludes that nominal contracts are
instrumental in determining labor and output reactions. Thus
given these divergent results, this strand of literature also
produces no firm conclusions.
Following Ahmed and Card, I use Brazilian data to examine
whether nominal wage contracts play an essential role in
propagating macroeconomic shocks. I exploit the fact that
from 1965 through 1984, Brazil's price level had rose 7000
times. Brazilian firms generally fixed their employees'
nominal wages, but were required by law to adjust workers'
salaries at specified intervals to keep pace with inflation
and productivity. From 1965 to 1979, the adjustments were
required annually; in 1979 the law changed to require
semi-annual adjustments. Because of the lagged indexing
formula and high Brazilian inflation, real wages fell until
readjustment occurred, when they were raised to maintain
purchasing power. According to the standard contracting
approach, as the real wages fell prior to the indexing date,
firms would add workers and output would respond positively.
Conversely, New Classical economists suggest that firms and
workers would not change the level of employment in the face
of a monetary shock and so there should be no tendency for
contracts to influence output.4
4 Between 1979 and 1983, the government lifted price
controls on industrial inputs, but reimposed them in mid-1983.
In 1985, a new administration imposed strict price controls

33
Relative to Ahmed and Card, my data set has a major
advantage. Because inflation in Canada was relatively low, and
the unexpected inflation Card tries to measure even smaller,
both Ahmed and Card must search for relatively small effects.5
However, inflation in Brazil was far from small. If there are
any effects from nominal contracts, my data may be better able
to uncover them.6
Description of the Data
My study begins in 1975 and ends in 1984 because after
this, the specific programs (that is, the wage freezes and
then reinstitution of the quarterly indexing) provide too few
and even changed the price index to lower inflationary
expectations. Still, continued pressures made the government
freeze consumer prices again. Since high inflation continued
to exist, the price controls were more than likely ineffective
or did not cover much of the economy.
5 Indeed, this could be why Ahmed failed to find any
effect from monetary disturbances. Card's results, meanwhile,
may be the result of mismeasurement of the unexpected
component of inflation.
6 This advantage, however, may also conceal a related
disadvantage: One might worry that in high inflation
environments workers and firms make efficiency enhancing
adjustments (as Barro suggested) that they might forego in
less inflationary times. In other words, it might be the case
that in low inflation countries, nominal wage contracts
function as postulated by Keynesian analysis while in high
inflation countries, the contracts are altered to be in line
with Barro's approach. Of course, the observation that
individuals placed in high inflation countries may alter their
behavior when compared to residents in low inflation countries
is hardly unique to my study. And, given the prominence with
which high inflation countries have served as "laboratories"
for testing monetary phenomena, most economists apparently
think this potential drawback to be generally minor.

34
observations for meaningful results. These data cover some of
the larger and more important industrial sectors of Brazil as
well as secondary sectors.
The basic data consist of monthly output series, from
Anuário Estatistico do Brasil, for seven industries: rubber,
plastics, chemicals, transportation, beverages, tobacco and
machinery. The wage adjustment month for workers within each
industry varied by industry. I was unable to uncover a
written record of the precise month when the wages were
indexed for some of the industries. Thus, to determine the
indexing month, I examined wage data (from The Fundagáo
Instituto Brasileiro de Geografia e Estatística Industria de
Transformacáo) for these industries from Brazil's two largest
states, Sao Paulo and Minas Gerais, since output in these
states effectively dominates the rest of the country. I
deflated the nominal wage using the wholesale price index from
Conjuntura Económica. These seven industries then demonstrated
a consistent pattern: In particular, during the period of
annual indexing, all industries had one month where the real
wage jumped higher and thereafter tended to decline. Figure
3-1 illustrates this using data from the plastics industry.
The upward spike is quite apparent in the figure. Thus, the
month of the jump (January) was deemed the month indexing
occurred.

6.5
Figure 3-1 Real Wage - Plastics

36
Tests of the Importance of Contracting
The shift in November 1979 from annual to six-month
indexing provides a natural way to examine the importance of
nominal contracting. According to the Keynesian view,
contracts are an important feature of the economic
environment; indeed, it is their presence that determines how
changes in the money supply and hence the price level affect
real output. If nominal wage contracts are an important
aspect, major changes in them—such as the movement to more
frequent indexing—ought to affect the evolution of output.7
The intuition is illustrated in Figure 3-2, which
illustrates some hypothetical data. The top part of the
figure shows the behavior of the real wage, initially with
twelve months between indexing and finally with six months
between indexing.8 The bottom shows the effect of this
7 This is related to Lucas'(1976) insight that when the
rules of the game change, people's behavior changes. To the
extent that nominal wage contracts are important "rules of the
game", changes in them ought to affect people's actions.
This, then, should be observable through changes in employment
or output.
8 The fact that the real wage is assumed to fall linearly
is not important. Also not crucial is the assumption that the
real wage falls to the same level immediately before indexing
in both the annual and semi-annual indexing schemes. This
assumption does, however, seem realistic since the change to
more frequent indexing was caused by the expectation of more
rapid inflation. Hence, for a given nominal wage, the real
wage would fall faster in the later part of the figure.

Output Real Wage
37
Figure 3-2 Sawtooth Behavior of the Real Wage and Output

38
"saw-tooth" behavior of the real wage on employment—and hence
output—making the conventional assumption that firms
determine the level of employment along their labor demand
curve.9 Thus, as the real wage declines due to inflation,
firms move along their labor demand curves and raise the level
of employment. The figure makes obvious the point that the
behavior of employment changes along with the indexing regime.
Figure 3-2 is designed to convey only the intuition
behind these tests. Thus it is not essential that the real
wage—and hence employment—display the precise pattern
illustrated in the figure. The key observation is that
according to the Keynesian approach emphasizing contracting,
the switch from annual to semi-annual indexing must affect the
time series behavior of employment.
Testing this hypothesis is conceptually straightforward:
simply examine whether the evolution of output differs between
indexing regimes. To this end, I used monthly data from seven
industries for the period from 1975 to 1985. I then assumed
that output within each industry evolved as:
Ytjj = C + /^MONTHLY DUMMIES + (^CARNIVAL + /¿t (3-0)
where Y is the level of the log of output in industry j at
time t, C is a constant, MONTHLY DUMMIES are dummies for
January through November and CARNIVAL is a dummy for the
9 Again, the linearity of the changes in employment is
not important.

39
annual month of Carnival. In Brazil, Carnival is a pre-Lenten
festival during which there is an obvious decrease in the
amount of work performed. The dummy variable CARNIVAL
represents whether Carnival falls in February or March and
takes account of this factor.
To account for the non-stationarity of the data, I have
chosen to difference the variables:10
DYt j = C + MONTHLY DUMMIES + djDCARNIVAL + Mt (3-1)
where DY is the first difference of the log of output and
DCARNIVAL is the first difference of the dummy variable for
Carnival.
If, following the Keynesian approach, nominal wage
contracts are material in affecting output, changes in the
indexing regime should affect the behavior of output. Hence,
10 I first-differenced the data to make it stationary.
First differences were used rather than log levels with a
deterministic trend for two reasons: First, in keeping with
the work of Nelson and Plosser (1982), it has long been
recognized that many time series are better characterized as
being difference stationary rather than trend stationary.
Second, and more pragmatic, the output series occasionally
shows a distinct downward "step" before continuing upward at
its usual rate. Such "steps" were very infreguent, usually no
more than one or two per industry and were likely due to
improved measuring of the output series. While rare, these
changes were sufficient to severely bias the trend if I used
a level specification. Although I could have accounted for
this by using a dummy constant that equalled one until the
"step" and zero thereafter, given the work of Nelson and
Plosser, I preferred to "solve" the problem by differencing.
Of course, observations for the month in which steps occurred
were large. Thus I estimated some regressions that included
dummy variables to take account of these months; however, as
I report below, this had a negligible impact on the results.

40
according to this view, the coefficients in specification (3-
1) likely will not be stable across the periods of annual and
semiannual indexing. On the other hand, the New Classical
view, which suggests that output is unaffected by nominal
contracts, predicts that the coefficients will be stable
across indexing regimes. These hypotheses will be examined
using standard F-tests.
An even more precise test of equation (3-1) may also
allow me to examine the effect of the change in indexing
schemes on output's behavior. Whereas (3-1) considered the
stability of all monthly dummy coefficients, equation (3-2)
considers only those months where I would expect contract
renegotiations to have the greatest effect on output:
DYt j = C + /SjMONTHLY DUMMIES + ^INDEXlj +02INDEX2j
+ atjDCARNIVAL + /it (3-2)
where INDEX1 and INDEX2 represent dummy variables for the
months that are the new base date months. For example,
suppose initially the industry's base month was January;
starting in November 1979, the industry began to receive
readjustments in November and May.11 If output behaved as
proposed in the conventional framework, initially we would
11 Depending on the initial base date month, the new
indexing months coincided with enactment of the legislation
for some industries while other industries' new dates remained
on schedule with their annual adjustments. For details, see
Macedo (1983).

41
expect output to peak each December. Once readjustments
occurred twice annually, we would expect output to peak in
April and October. Correspondingly, with annual indexing,
output in November should be higher than it would be once
semi-annual indexing started in 1979. The INDEX dummies pick
up whether output in these months is indeed lower; that is,
negative "0's" would reflect contracts' effect on the behavior
of output. Conversely, the New Classical model predicts that
the coefficients would be zero.
The tests just outlined ignore some potentially valuable
information; in particular, they do not exploit the fact that
for a fixed nominal wage, the real wage falls more the larger
the increase in the price level.12 Therefore, I estimate
industry-level regressions similar in specification to (3-1)
where I also include the cumulated price level as a measure of
the fall in the real wage. The cumulated price level change
is a proxy for the decline in the real wage. Using the real
12 By ignoring the effect from the change in the price
level, the previous work might be thought weaker than the
following tests. For instance, in the preceding section it
could be that changes in the behavior of the price level over
the two indexing regimes "cancels" any effect from changes in
the indexing. Nonetheless, the earlier test is valuable for
at least two reasons. First, it is clearly unlikely that this
price-level-induced "cancellation" will occur. And second,
the previous test is less restrictive in how it assumes
changes in the price level affect output. That is, the tests
in this section are forced to use specific functional forms.
While I use three different functional forms, one cannot be
sure that they are correct. Thus, the stability test in the
previous section provides additional, independent evidence
that is not necessarily linked to the precise functional form
adopted.

42
wage directly would be preferable, but data on nationwide,
industry-level nominal wages do not exist.13 These equations
attempt to test directly the hypothesis that a fall in the
real wage spurs employment and—hence output—by examining the
significance of the price level coefficient. If the Keynesian
emphasis on nominal contracting is correct, the price level
ought to be positively related to employment, while if the New
Classical perspective is correct, the price level should be
insignificant in the regressions.
Of course, these hypotheses implicitly assume that the
changes in the price level are driven by the money supply,
since both Keynesian and New Classical economists agree that
real shocks can change both the price level and employment.
In the highly inflationary context, however, the assumption
that the price level is determined primarily by the money
supply is reasonable.
The second test estimates a regression similar to (3-1)
with two modifications:
CYxt = C + ^MONTHLY DUMMIES + adCARNIVAL + rCPxt + Mt (3-3)
13 The cumulated price level change can be viewed as a
proxy for the decline in the real wage. Using the real wage
directly would be preferable, but data on nationwide,
industry-level nominal wages do not exist. Data on state-
specific . industry-level nominal wages do exist however, and
the next chapter uses these data to perform additional tests
of the importance of nominal wage contracts.

43
where x represents the month in which the industries received
their wage adjustments while CYx and CPx represent cumulated
output and the cumulated price index since the adjustment,
respectively. At each adjustment, CYx and CPx were set equal
to a base of 100 in month x and then cumulated forward. Thus,
CPx measures the fall in the real wage between the industry's
base dates for readjustment while the (hypothesized) increase
in output between the readjustment dates is captured by
CYx.14
Two additional regressions also examine the real wage
proxy:
DYxt = C + /JjMONTHLY DUMMIES + ajDCARNIVAL
+ rCPxt + jtxt (3-4)
where, again, DY is the first difference of the log of output.
Equation (3-4) assumes that it is the level of cumulated
price changes that affects the growth rate of output. While
this seems in keeping with the idea that the data are
difference stationary, other economists might suggest that it
is the first difference in the cumulated price changes that
14 The law mandated that, starting in November 1979, wage
adjustments would occur semiannually. All industries that had
already received their annual adjustments between December
1978 and May 1979 were to be reindexed in November 1979 and
remain on a November-May-November indexing pattern. Those
industries which had been indexed from June through October
1979 were to receive adjustments in December 1979 through
April 1980. For example, industries with July 1979 as a base
month would be reindexed in January 1980 and continue with six
month indexing periods.

44
affects (the log difference of) output.15 The goal of this
work is not to resolve the issue of how best to specify
variables in a difference stationary framework. Hence, I also
estimated:
DYxt = C + ^MONTHLY DUMMIES + ajDCARNIVAL +
tDCPXj + Mt (3-5)
where DCPx represents first differences in the cumulated price
level.
In regressions (3-3), (3-4) and (3-5), the basic idea is
that the larger the increase in prices since the last
indexation period, the smaller will be the actual real wage.
Under the nominal-contracting Keynesian hypothesis, the
smaller is the real wage, the more firms raise employment and
output. Therefore, the Keynesian approach predicts that the
estimated coefficient on the price variable "r" will be
15 The major difference between specifications (4) and (5)
can be brought out by considering the impact of a temporary
decrease in the real wage brought about by a one-time increase
in the price level followed immediately by a fall back to its
original level. In this case, specification (4), which
focuses on the level of prices, implies that the growth rate
of output will be higher in the period prices are higher, and
then will return to its usual growth rate after this period.
As a result, specification (4) implies that the level of
output will be permanently increased from the temporary
increase in the price level. Specification (5), which uses
the first difference of the cumulated price level, indicates
that the growth rate of output increases in the period the
price level rises and then decreases the following period as
the price level falls. Hence, in this specification, a
temporary change in the price level causes no permanent change
in the level of output.

45
positive. The New Classical approach, however, suggests that
firms will not take advantage of the inflation-induced fall in
real wages, so that output will not respond to CPx or DCPx.
Thus, the New Classical view hypothesizes that the estimated
"t" will be insignificantly different from zero.
Empirical Results
To test these hypotheses, regressions were estimated over
the entire sample period (1975-1984), over the period of
annual indexing (1975-1978), and over the period of
semi-annual indexing (1979-1984). Table (3-1) reports F-test
results for the stability of the coefficients over these
periods. Strikingly, at the 5% level, none of the industries
show significant changes in the coefficients. Therefore, none
of the results reject the null hypothesis that the
coefficients are the same over the two indexing schemes.
These results are more consistent with the New Classical
theory. I find no support for the Keynesian view that nominal
contracts affect the behavior of output.
Table (3-2) reports results for the second test and also
confirms the lack of contracts' effects on output. In only
one industry, Rubber, was the coefficient "0" significantly
less than zero.
The "t" coefficient estimates and their p-values for
specifications (3-3), (3-4) and (3-5) are reported in Table 3-
3, Table 3-4 and Table 3-5 respectively. The tables report

46
results for the entire sample period as well as the annual and
semiannual indexing sub-periods. In only two industries
(Rubber and Tobacco) and only one specification (the one with
CYx) are the estimated "t's" significantly positive at the 1%
level. In only two industries (Beverages and Chemicals) and
only two specifications (equations (3-3) and (3-4)
respectively) are the estimated "r,,s significantly positive at
the 5% level.16 Indeed, the majority of the estimated
coefficients are negative, which is perverse from the
Keynesian perspective. Of the negative coefficients, however,
only a few attain conventional levels of significance. Thus,
similar to what we saw in the previous section, these tests
fail to confirm the conventional Keynesian transmission
mechanism focusing on labor contracts. Instead, they are more
in line with Barro's New Classical suggestion that firms and
workers do not allow the fixity of the nominal wage (and hence
the flexibility of the actual real wage) to influence the
(efficient) level of employment and output.
16 The regression in specification (4) assumes that firms
react immediately to changes in the real wage. It may be,
however, that firms delay their reactions a bit. Hence, I also
reestimated the equation allowing two lags as well as
contemporaneous values of DCPx to affect DY. This made very
little difference in my results; no contemporaneous
coefficients were significant while only one lag was
significantly positive.

47
Summary and Conclusions
With respect to the impact of nominal wage contracting,
the opposing views of Keynesian and New Classical approaches
are examined in this essay. Seminal work by Fischer outlines
the mechanism (nominal wage contracts) which propagates
nominal shocks generating nonneutrality of money. In
addition, Taylor develops models which mimic the behavior of
United States' business cycles seen since the 1950s. In these
Keynesian-based models, firms base their employment decisions
on the labor demand curve as the real wage changes in response
to changes in the price level.
The New Classical theory, pointing out the inefficiencies
in the conventional argument, shows that firms and workers are
both better off ignoring the behavior of the actual real wage.
Instead, over their long-term relationship, both parties
continue to equate the marginal product of labor to the
marginal value of workers' time which equals an equilibrium
real wage. In this framework, monetary shocks no longer
generate output responses.
Using Brazilian data covering seven industries, where
nominal wages were indexed by law, four different tests
supplied results which strongly support the New Classical
view. Over the sample period where indexing schemes switched,
output's behavior did not significantly differ. Including a
proxy for the real wage also yielded strong evidence in favor

48
of the New Classical theory; output's behavior was not
affected by the movement of the real wage.
The results tend to confirm that firms and workers do
indeed set efficient employment levels using the equilibrium
real wage. In this case, in contrast to the Keynesian view,
wage contracts do not serve as a source of transmission
mechanism linking monetary shocks to employment and output
responses.

49
TABLE 3-1
RESULTS FOR STABILITY TESTING
INDUSTRY
F STATISTIC
RUBBER
1.536
MACHINERY
1.168
TOBACCO
1.627
PLASTICS
1.536
CHEMICALS
.986
BEVERAGES
. 342
TRANSPORTATION
.339

50
TABLE 3-2
RESULTS FOR EQUATION (3-2)
INDUSTRY
INDEX1
P-Value
INDEX2
P-Value
RUBBER
-.080
.048*
-.005
.885
MACHINERY
.065
.085
.054
.154
TOBACCO
-.086
.275
.065
. 386
PLASTICS
-.030
.332
-.019
.553
CHEMICALS
-.322
.261
-.024
.291
BEVERAGES
.032
.419
-.053
.204*
TRANSPORTATION
.068
.322
. 010
.875
♦Denotes significance of the coefficient 6 at the 5% level.

51
TABLE 3-3
RESULTS FOR EQUATION (3-3)
INDUSTRY
ENTIRE SAMPLE
Coefficient
P-Value
RUBBER
. 145
. 121
MACHINERY
-.044
.667
TOBACCO
-.893
.000**
PLASTICS
-.193
.025*
CHEMICALS
-.051
.600
BEVERAGES
-.050
.758
TRANSPORTATION
-.475
.008**
♦Denotes significance of the coefficient r at the 5% level.
♦♦Denotes significance of the coefficient r at the 1% level

52
TABLE 3-3—continued
RESULTS FOR EQUATION (3-3)
INDUSTRY
1975-1979
1980-1985
Coef.
P-Value
Coef.
P-Value
RUBBER
-.723
.000**
.431
.004**
MACHINERY
.003
.993
. 139
.374
TOBACCO
1.938
.000**
-1.047
.005**
PLASTICS
. 606
.087
-.198
. 116
CHEMICALS
-1.503
.000**
.230
.082
BEVERAGES
-.914
.229
.642
.011*
TRANSPORTATION
-.440
.527
-.463
.076
♦Denotes significance of the coefficient r at the 5% level.
♦♦Denotes significance of the coefficient r at the 1% level

53
TABLE 3-4
RESULTS FOR EQUATION (3-4)
INDUSTRY
ENTIRE SAMPLE
Coefficient
P-Value
RUBBER
-.025
.554
MACHINERY
-.198
.673
TOBACCO
-.194
.374
PLASTICS
.059
.869
CHEMICALS
.525
.054
BEVERAGES
-.751
.238
TRANSPORTATION
-1.608
.038*
♦Denotes significance of the coefficient r at the 5% level
Coefficients are scaled by 103.

54
TABLE 3-4—continued
RESULTS FOR EQUATION (3-4)
INDUSTRY
1975-1979
1980-1985
Coef.
P-Value
Coef.
P-Value
RUBBER
• Oil
.997
-.486
.471
MACHINERY
1.313
.622
.256
.718
TOBACCO
.020
.888
-.147
.687
PLASTICS
-.590
.726
.141
.794
CHEMICALS
-1.759
.335
1.025
.011*
BEVERAGES
3.851
.331
-.935
.344
TRANSPORTATION
-.014
.997
-2.772
.038*
♦Denotes significance of the coefficient t at the 5% level
Coefficients are scaled by 103.

55
TABLE 3-5
RESULTS FOR EQUATION (3-5)
INDUSTRY
ENTIRE SAMPLE
Coefficient
P-Value
RUBBER
.000
.814
MACHINERY
-.133
.328
TOBACCO
-.328
. 154
PLASTICS
-.001
.370
CHEMICALS
.032
.691
BEVERAGES
-.187
.247
TRANSPORTATION
-.422
.064
Coefficients are scaled by 102

56
TABLE 3-5—continued
RESULTS FOR EQUATION (3-5)
INDUSTRY
1975-1978
1979-1985
Coef.
P-Value
Coef.
P-Value
RUBBER
-.353
.620
-.027
.897
MACHINERY
.735
.468
. 127
.519
TOBACCO
.284
.553
-.243
.469
PLASTICS
-.224
.759
-.049
.741
CHEMICALS
-.301
.683
.163
. 154
BEVERAGES
1.198
.108
-.204
.435
TRANSPORTATION
.490
.727
-.550
.145
Coefficients are scaled by 102

CHAPTER 4
NOMINAL WAGE CONTRACTS - STATEWIDE RESULTS
Introduction
In the Keynesian framework, nominal wage contracts
transmit monetary shocks to real variables. This
nonneutrality occurs because over the period of a fixed wage
contract, an increasing price level erodes the real wage
thereby inducing firms to increase their labor input, and
likewise output. Fischer (1977) presents a model typical of
the Keynesian framework, which assumes nominal wages are rigid
to some degree and that the level of employment is adjusted in
accord with the firm's labor demand schedule.1 Firms can
raise their labor input in a variety of ways including hiring
more workers, eliciting greater work intensity, using overtime
hours or a combination of these choices.2 Again, this
standard nominal contracting approach makes changes in the
money supply nonneutral. That is to say, increases in the
money supply raise the price level; since the nominal wage
remains unchanged, firms move down along their labor demand
1 Phelps and Taylor (1977) present a model similar to
Fischer's.
2 Hall (1980) elaborates on these options in a New
Classical framework.
57

58
curves and thus output responds positively to the increase in
the money supply.
In order to represent the persistence seen empirically,
however, Fischer's model must be altered. Taylor (1979) shows
that real effects exhibit persistence beyond price and wage
adjustments so long as the contracts are staggered and the
terms are adjusted periodically. Moreover, J. Taylor (1980)
obtains results which mimic the persistence in unemployment
and output similar to the United States' post-war experience
(with respect to nominal disturbances) using a model with
staggered wage contracts. Providing more recent support,
Card's (1990) empirical analysis finds that wages negotiated
at the start of a contract period are positively correlated to
terms made at the end of the previous period. This linkage
creates persistence in the costs of labor and therefore
employment.
In contrast to the Keynesian model, the New Classical
view asserts that monetary shocks are neutral. Neutrality
occurs as a result of firms and labor ignoring the movement of
the actual real wage and instead basing their employment
decisions on an equilibrium or "shadow" real wage. Analyzing
this efficient behavior, Barro (1977) has pointed out that
even though a labor contract fixes the nominal wage, firms and
workers may equate the marginal product of labor to the
marginal value of workers' time over all states of nature and

59
thus jointly determine the efficient level of employment.3
Hall (1980), in extending Barro's work, notes that the
relationship between labor and management is long-term in
nature; therefore, either party is willing to "lose" as a
result of unanticipated price level changes. For example, a
negative monetary shock unexpectedly increases the actual real
wage and labor "wins." However, workers realize that price
level shocks are just as likely to work against them in the
next period. In essence, neither party reacts to monetary
shocks since, on average, an efficient level of employment
obtains where the marginal product of labor equals the
equilibrium real wage which equals the marginal value of
workers' time. In this case, the "shadow" equilibrium real
wage will differ from the actual real wage due to the presence
of the "sticky" nominal wage. In other words, the actual real
wage, affected by nominal disturbances, does not equilibrate
the labor market because it does not produce an efficient
level of employment. Instead, both labor supply and demand
are taken into account and jointly determine the level of
employment at the (shadow) equilibrium real wage. In this
framework then, wages and prices change proportionately
leaving the real wage unchanged. If follows then that in an
auction market money shocks cannot change employment since the
3 This argument assumes both parties have equal
bargaining power. If either side has monopoly power, a Pareto
optimal outcome might not occur.

60
real wage remains constant. Therefore, wage contracts may no
longer be a source of nonneutrality.
Looking at Hall's point more closely, for a given nominal
wage, it is easy to see that when a monetary shock increases
the price level resulting in the actual real wage being lower
than the equilibrium real wage firms move along their labor
demand curve and hire more workers (in a Keynesian framework).
Hall (and Barro), however, ask two important questions: Would
existing employees be willing to work additional hours? And is
it really in the firms' and workers' best interest to
determine the level of employment without considering the
labor supply curve? The New Classical argument claims that
because of long-term relationship between firms and workers,
both parties realize that these random monetary shocks will
(effectively) raise their actual real wage below the
equilibrium real wage (and marginal product of labor) half the
time so that workers benefit. However, the other half of the
time, the shocks lower the actual real wage below the
equilibrium real wage so that firms "win”. In either case, ex
ante, the economic "pie" would be larger if both parties acted
optimally keeping employment at an efficient level in the face
of nominal shocks. In other words, firms and workers don't
respond to the actual real wage; instead, they agree to equate
the marginal value of workers' time to the marginal product of

61
labor (which also equals the equilibrium real wage).4 To
answer the questions posed, not only would employees be
unwilling to work the extra hours, but it is not in firms' or
workers' interests to sign contracts that obligate employees
to work the extra time.5
It is apparent, though, that (because of long-term
relationships) real disturbances can generate changes in the
marginal product of labor, employment, and hence output.6
Allowing both real and nominal disturbances to generate the
same output response is, of course, the major difference
between the Keynesian and New Classical approaches to labor
contracts.
4 As Hall points out, the idea of long-term relationships
addresses two worker/firm issues—efficiency, which has been
discussed in the text, and income smoothing. The latter point
is simply that workers probably prefer a smoother path of
consumption to one that fluctuates. To the extent that a
smoother path of income leads to smoother consumption, workers
would prefer smoother income to a fluctuating path.
5 Recognizing the Barro/Hall analysis may be one reason
New Keynesians have made the distinct departure from the
sticky nominal price framework. Specifically, as Ball, Mankiw
and Romer (1989) point out, firms and their customers are not
part of a long-term relationship—no loyalty exists to prevent
buyers from moving up their demand curves as price-setting
forms maintain high real product prices in the face of tight
monetary policy. This lack of long-term arrangements, then,
can produce business cycles given sticky prices in the goods
market.
6 For a given wage level when there' s a negative real
shock, workers expect to be kept on the payroll while they
decrease their hours or intensity or perhaps be temporarily
laid off. So while the actual real wage is higher than the
equilibrium real wage (since the negative shock has reduced
the MPL) workers are willing to accept a reduction of labor
demanded.

62
On a related point, Hall discusses the fact that to meet
an increase in demand, firms can expand their labor input in
a variety of ways: hire more labor, ask current workers to
work overtime, persuade them to work more intensely or a
combination of these options.7 Therefore, in my empirical
work in addition to considering the relationship between the
real wage and employment, I also investigate the correlation
between the real wage and output in order to provide more
insight into the effects of nominal shocks.8 The next section
of this essay examines past empirical work. Next, the data
are described and followed by a discussion of the estimation
technique and regression results. The last section summarizes
the essay and results.
Review of Empirical Analyses
To test the role of wage contracts under the opposing
theories, empirical analysis centers on two primary
approaches. The first examines the time series relationship
between real wages and employment activity. A countercyclical
7 Actual data tend to show that work intensity changes
proportionately with output as opposed to employment hours
varying with output. Okun's Law expresses this fact claiming
that a 1 percent change in unemployment rates produces a 3
percent corresponding change in output. In my empirical work
I use both labor and total output in separate regressions in
order to allow for both options.
8 I could find data on employment only in terms of the
number of workers, not hours. If, as Hall points out, firms
may not change the number of employed workers but instead
adjust intensity or hours, we may only see the effects of a
change in the real wage on output and not employment.

63
real wage, which the Keynesian approach suggests, would occur
as the price level rises and labor demand (along with output)
increases. Early work (Dunlop, 1938; Tarshis, 1939), though,
found a procyclical real wage. More recently, mixed results
have been obtained. For instance, Geary and Kennan (1982),
studying Canadian data, find no statistical relationship
between employment and the real wage. Bils (1985), however,
using disaggregated data, finds a positive relationship
between real wages and output. In addition to his using panel
data, Bils accounts for these differences to the inclusion of
overtime earnings and using a later sampling period than
earlier studies. It is not surprising that these results lend
uncertainty to the worth of nominal wage rigidity models,
given the simplistic time series approaches and ensuing
weaknesses used in part of this literature.
Ahmed (1987) and Card (1990) approach the debate using a
different strategy. Ahmed investigates whether employment and
output are sensitive to the degree of wage indexation.
Essentially, if nominal wage contracting is supported, a
monetary shock will have a greater impact on employment and
output the less indexed (i.e., the less flexible) the wage.
Using Canadian manufacturing industries, which employ a
variety of indexing schemes, Ahmed tests this implication of
contracting models. Ahmed concludes that nominal wage
rigidity cannot account for business cycles since he fails to
find a relationship between the degree of contracting and the

64
extent to which a monetary shock affects real variables. On
the other hand, Card claims that it is the unexpected
components of the real wage (namely unanticipated price
changes) along with the degree of indexation, that should
generate a countercyclical real wage. Therefore, Card (also
using Canadian data) constructs measures of unexpected
inflation and real wage changes for use in a labor demand
model. These results support a role for surprise inflation in
impacting employment levels via end-of-contract real wage
levels; hence Card concludes that labor and output are
materially affected by nominal wage contracts. Thus given
these conflicting results, this strand of literature fails to
produce definitive conclusions.
Following Ahmed and Card, I use Brazilian data to examine
whether macroeconomic shocks can be linked to output's
behavior via nominal wage contracts. Brazil's wage indexation
policy allows us to empirically examine the opposing theories.
Brazilian firms generally fixed their employees' nominal
wages, but were required by law to adjust workers' salaries at
specified intervals to keep pace with inflation and
productivity. From 1965 to 1979, the adjustments were
required annually. Because of the lagged indexing formula and
high Brazilian inflation, real wages fell until readjustment
occurred, when they were raised to maintain purchasing power.
According to Fischer's model, as the real wages fell prior to
the indexing date, firms would add workers and output would

65
respond positively. Conversely, the New Classical approach
suggests that firms and workers would not change the level of
employment in the face of a monetary shock and so there should
be no tendency for contracts to influence output.
In comparison to Ahmed and Card, my data set has a major
advantage. Because inflation in Canada was relatively low, and
the unexpected inflation Card tries to measure even smaller,
both Ahmed and Card must search for relatively small effects.9
Inflation in Brazil though was significantly more pronounced.
Thus, if there are any effects from nominal contracts, my data
may be better able to disclose them.10
While the previous chapter examined results based on
proxies for the real wage, this chapter takes advantage of the
fact that real wage data do exist at a statewide level. This
allows me to verify the robustness of the national results
9 Indeed, this could be why Ahmed failed to find any
effect from monetary disturbances. Card's results, meanwhile,
may be the result of mismeasurement of the unexpected
component of inflation.
10 This advantage, however, may also conceal a related
disadvantage: One might worry that in high inflation
environments workers and firms make efficiency enhancing
adjustments (as Barro suggested) that they might forego in
less inflationary times. In other words, it might be the case
that in low inflation countries, nominal wage contracts
function as postulated by Keynesian analysis while in high
inflation countries, the contracts are altered to be in line
with Barro's approach. Of course, the observation that
individuals placed in high inflation countries may alter their
behavior when compared to residents in low inflation countries
is hardly unique to my study. And, given the prominence with
which high inflation countries have served as "laboratories"
for testing monetary phenomena, most economists apparently
think this potential drawback to be generally minor.

66
using data from Sao Paulo only. In addition, we must account
for the fact that the real wage becomes endogenous for part of
the sample period.
Description of the Data
Estimation using the disaggregated data starts in 1965
with the implementation of the indexing policy and continues
through 1976.11 The basic data consist of monthly output
series, from Anuário Estatistico do Brasil, for seven
industries: rubber, plastics, chemicals, transportation,
beverages, tobacco and machinery. The wage adjustment month
for workers within these industries varied by industry. I was
unable to uncover a written record of the precise month when
the wages were indexed for some of the industries. Thus, to
determine the indexing month, I examined wage data (from The
Fundagáo Instituto Brasileiro de Geografia e Estatistica
Industria de Transformacáo) for these industries from Brazil's
two largest states, Sao Paulo and Minas Gerais, since output
in these states effectively dominates the rest of the country.
I deflated the nominal wage using the wholesale price index
from Conjuntura Económica. These seven industries then
demonstrated a consistent pattern. In particular, during the
period of annual indexing, all industries had one month where
the real wage jumped higher and thereafter tended to decline.
11 It appears that statewide data collection for wage,
employment and output end in 1976.

67
Thus, the month of the jump was deemed the month indexing
occurred. The Fundagáo Instituto Brasileiro de Geografia e
Estatistica Industria de Transformacáo provides wage data on
the seven industries. Using the wholesale price index from
Conjuntura Económica. I deflated the nominal wage. As will be
discussed more thoroughly later, government spending and the
money supply will be used as instruments in the regression
analysis. Conjuntura Económica and Industria de Transformacáo
are sources for both series and provide employment and value
of production figures at the statewide level as well.
Estimation Technique and Regressions
A number of specifications allowing for different
functional forms were estimated for the seven industry groups:
EMPt j = C + aT + ajRWAGEt j + /^MONTHLY DUMMIES
+ AjCARNIVAL + Mt (4-1)
where EMPt j reflects the number of employees at time t for
industry j, T is a time trend, RWAGEt j represents the real
wage for each group, MONTHLY DUMMIES are dummies for January
through November and CARNIVAL is a dummy for the annual month
of Carnival. In Brazil, Carnival is a pre-Lenten festival
during which there is an obvious decrease in the amount of
work performed. The error term, ¿xt, is assumed normally
distributed.

68
Obviously, equation (4-1) addresses the Keynesian
suggestion that firms choose to hire more labor as the real
wage changes. But another possibility exists: for example,
when there is more work to do, firms choose to hire new
employees, ask current ones to work harder or both. For
example during the 1970s in the United States, Hall finds that
when output contracted, decreased work effort (output per
worker and hours per worker) accounted for half of output's
decline while a decrease in actual employment accounted for
the other half. He surmises that the same would occur during
booms. Thus if firms opt to work employees more intensely or
increase their hours, we might only see a change in output and
the real wage. Equation (4-2) allows for this behavior:
VALUE,, j = C + aT + ajRWAGEfc j + ^MONTHLY DUMMIES
+ XjCARNIVAL + Mt (4-2)
where VALUEt j is the value of production in real terms for
each industry.
In addition to estimating the equations in levels, I also
estimated them in differences:
DEMPt J = C + ttjDRWAGEt j + ^MONTHLY DUMMIES
+ AjDCARNIVAL + fit (4-3)
where DEMPtfj and DRWAGEt j are first differences of employment
and the real wage at time t for industry j, respectively.

69
Corresponding to equation (4-2), a regression in
differences is also estimated:
DVALUEt j = C + atjDRWAGEt j + /JjMONTHLY DUMMIES
+ XjDCARNIVAL + Mt (4-4)
where DVALUEt j and DRWAGEtj are first differences of the value
of output and the real wage at time t for industry j,
respectively.
To calculate the real wage, I deflated the nominal wage
using the wholesale price index. An issue, however, arises
because the real wage is endogenous during some months. Thus,
estimating these equations requires two-stage least squares
where the observations on nominal wages are exogenous for all
months except when they are renegotiated.12 That is, during
the industry's base month, the wage becomes endogenous in
light of the fact that the government mandates only a minimum
wage adjustment. Workers may (and quite frequently do)
negotiate for additional increase. If we fail to account for
this fact (that the wage becomes endogenous when readjusted),
the estimated coefficient on the real wage would suffer from
simultaneous equation bias. Thus, for those months when the
real wage was endogenous—and only for those months—I formed
an instrument using the price level, government spending, the
12 This estimation technique is described by U. Kohli
(1989) .

70
money supply and oil prices as instrumental variables.13 The
second stage takes this now "exogenous" real wage series (the
endogenous observation having been estimated unbiasedly) and
performs regressions (4-1) through (4-4).
In accordance with the Keynesian model, we expect a
countercyclical real wage. In other words, in response to
changes in the real wage, firms should move along their labor
demand curves and hire additional labor. Conversely, the New
Classical approach suggests the absence of a relationship
between the real wage and labor demand. Firms and workers
ignore the behavior of the actual real wage basing their joint
decisions on a "shadow" real wage. We would expect "a" not to
differ significantly from zero in this case.
Empirical Results
Results from all four regression overwhelmingly support
the New Classical model. Tables (4-1) through (4-4) provide
estimates of "a", the coefficient on the real wage. A
majority of the estimates are significantly positive—a
perverse results suggesting that as the real wage falls, firms
hire less labor and employment (as well as output) falls. In
fact, in regressions (4-1) and (4-2), eleven of the 14
coefficients are positively significant. For the
specifications in differences, the majority of the
13 Sources for the price level, money supply figures and
government spending were Conjuntura Económica. International
Financial Statistics provided additional data for spending.

71
coefficients are insignificantly different from zero. The
A
lack of any negative " a" lends support to the theory that
nominal wage contracts are unimportant in transmitting changes
in the money supply to output.
Summary and Conclusion
In a neoclassical model, the effects of monetary shocks
are transmitted throughout the economy by introducing
frictions. In this essay, the frictions analyzed are nominal
wage contracts. From a conventional or Keynesian approach,
these contracts prohibit the nominal wage from changing while
allowing the real wage to be determined by movements in the
price level. Firms, basing their employment on the real wage,
respond to monetary shocks by, for instance, increasing
employment when the price level rises. Ultimately, these
frictions propagate nominal shocks, and real variables are
affected.
Conversely, New Classical models point out that firms and
workers, both part of a long-term relationship, behave
efficiently jointly determining employment based on an
equilibrium real wage. This wage equates the marginal product
of labor as well as the marginal value of worker's time. Both
parties ignore the movement of the actual real wage as
determined by wage contracts and the price level effectively
rendering monetary shocks neutral.

72
Brazil's unique wage indexation system allows these
opposing theories to be examined and compared. Using
statewide data, results provide little support for the
Keynesian view of a countercyclical relationship between the
real wage and employment or output.

73
TABLE 4-1
RESULTS FOR EQUATION (4-1)
INDUSTRY
COEFFICIENT
P-VALUE
MACHINERY
.518
. 008**
TOBACCO
1.315
.000**
PLASTICS
.711
.000**
CHEMICALS
-.432
.716
BEVERAGES
.611
.000**
TRANSPORTATION
.601
.000**
RUBBER
.750
.000**
**Denotes significance of the coefficient a at the 1% level.

74
TABLE 4-2
RESULTS FOR EQUATION (4-2)
INDUSTRY
COEFFICIENT
P-VALUE
MACHINERY
.309
.554
TOBACCO
.091
.695
PLASTICS
1.253
.000**
CHEMICALS
-3.691
.575
BEVERAGES
2.433
.000**
TRANS PORTATION
.807
.000**
RUBBER
.258
.376
**Denotes significance of the coefficient a at the 1% level.

75
TABLE 4-3
RESULTS FOR EQUATION (4-3)
INDUSTRY
COEFFICIENT
P-VALUE
MACHINERY
.289
.000**
TOBACCO
.089
.001**
PLASTICS
. 116
.001**
CHEMICALS
.089
.038*
BEVERAGES
.295
.000**
TRANSPORTATION
. 179
.000**
RUBBER
-.198
.484
♦Denotes significance of the coefficient a at the 5% level.
♦♦Denotes significance of the coefficient a at the 1% level.

76
TABLE 4-4
RESULTS FOR EQUATION (4-4)
INDUSTRY
COEFFICIENT
P-VALUE
MACHINERY
.699
.009**
TOBACCO
. 046
.632
PLASTICS
. 382
.000**
CHEMICALS
.762
.000**
BEVERAGES
.562
.003**
TRANSPORTATION
.788
.000**
RUBBER
4.731
.042
**Denotes significance of the coefficient a at the 1% level.

77
CHAPTER 5
SUMMARY AND CONCLUSIONS
Nominal wage contracts, introduced into a neoclassical
model, can generate nonneutrality of money. A typical
Keynesian model delivering these results, like Fischer (1977) ,
assumes that nominal wages are basically rigid and that firms
unilaterally determine employment based on the actual real
wage. Specifically, the contract keeps nominal wages constant
while real wage change in the face of changes in the price
level as a result of monetary shocks. For example, a positive
monetary shock encourages firms to hire more labor at a lower
real wage.
More elaborate conventional models, such as J. Taylor
(1979, 1980) can generate persistence of these nominal
disturbances producing results similar to the business cycles
witnessed in post-war United States data.
The nonneutrality of money, however, is contradicted by
the New Classical approach to business cycles. Models,
developed by Barro (1977) and Hall (1980) suggest that firms
and workers jointly determine employment based on an
eguilibrium real wage. For example, given a fixed nominal
wage and a positive monetary shock, real wages fall. Firms
and labor, however, ignore this actual real wage. The level

78
of employment is determined instead bilaterally based on an
equilibrium or "shadow" real wage and produces an efficient or
Pareto optimal outcome. In this auction market, employment,
as well as the real wage, is unaffected by monetary shocks
since wages and prices change proportionately. Specifically,
the equilibrium real wage equals the marginal product of labor
and the marginal value of worker's time; since money shocks
do not change the marginal product of labor, employment also
remains unaffected.
In addition, Hall points out that workers and firms have
a long-term relationship and are therefore motivated to treat
each other fairly when prices unexpectedly move in the other
party's favor.
These opposing theories are analyzed empirically using
Brazilian data, where a wage indexation scheme provides a
unique time series. Seven industries are investigated over a
period of two decades. This dissertation takes several
approaches: one, a nationwide study, compares results from one
indexation scheme to another; second, a proxy for the real
wage is generated; and lastly, statewide data provide a real
wage series which is analyzed using a two-step procedure. In
the last two cases, the relationship between the real wage and
employment or output is tested.
Results convincingly lend support to the New Classical
model. The first test shows that regardless of the indexing
scheme, there is very little effect on output's behavior.

79
Tests which specifically relate the real wage to output (and
employment) also show there is very little comovement between
the variables.

80
APPENDIX A
Class Wage to be readjusted
(i=l,...,5) (w) in units of wm
/ • • • /
Marginal rate
of Readjustment
in units of V6
1
2
3
4
5
3wm < w < 10wm
10wm < w < 15wm
15wm < w < 20wm
w > 2 0wm
w < 3wra
1.1
1.0
0.8
0.5
MARGINAL RATES OF READJUSTMENT FOR DIFFERENT WAGE SIZES
ESTABLISHED BY WAGE POLICY. (Macedo, 1983).
Source: Law Number 6886, of 12/10/79. This law changed the
original marginal rates of the new wage policy (Law Number
6708 of 10/30/79) which had only three classes.

81
APPENDIX B
RESULTS FOR EQUATION (3-1)
P-Values in parentheses.
MACHINERY
Estimated
Variable
Coefficient
C
-.084
JAN
(.000**)
-.015
FEB
(.607)
.278
MAR
(.000**)
.229
APR
(.000**)
.018
MAY
(.535)
. 157
JUN
(.000**)
. 085
JUL
(.002**)
. 084
AUG
( .003**)
. 132
SEP
(.000**)
.078
OCT
(.005**)
.096
NOV
(.001**)
. 023
CAR
(.408)
-.158
DUMMAC
(.000**)
-.226
DUMTOB
DUMPLS
DUMCHM
(.001**)
TOBACCO
PLASTICS
Estimated
Estimated
Coefficient
Coefficient
.051
-.091
(.170)
(.000**)
-.006
.083
(.910)
(.000**)
.042
.153
( .531)
(.000**)
. 193
.205
( .001**)
(.000**)
-.138
.021
(.011*)
(.342)
-.031
.146
( .560)
(.000**)
-.235
.083
(.000**)
(.000**)
-.137
. 126
(.012*)
(.000**)
-.059
. 128
(.259)
(.000**)
-.082
.067
(.119)
(.002**)
. 004
. 126
( .940)
(.000**)
-.098
.064
(.063)
( .004**)
-.148
-.085
(.013*)
(.000**)
.799
(.000**)
-.207
(.000**)
CHEMICALS
Estimated
Coefficient
-.059
(.000**)
.031
(.074)
.058
(.006**)
.156
(.000**)
.040
(.016*)
.109
(.000**)
.100
(.000**)
. 121
(.000**)
.089
(.000**)
.034
(.042*)
.067
(.000**)
-.016
(.321)
-.037
(.043*)
-.322
(.000**)

82
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Standard
Error
.061
.117
.048
.036
R-Squared
.632
.525
.602
.744
DW
2.634
1.956
2.203
1.897
SSR
.383
1.381
.244
. 135
Dummied Observations:
Machinery-1977:1
Tobacco-1982
: 7
Plastics-1980:1
Chemicals-1982:1

83
BEVERAGES
TRANSPORTATION
RUBBER
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
C
.044
-.099
.004
(.025*)
(.003**)
(.829)
JAN
-.102
.085
-.080
(.001**)
(.075)
(.002**)
FEB
-.110
. 165
.083
(.002**)
(.005**)
(.008**)
MAR
.051
. 196
.042
(.088)
(.000**)
(.112)
APR
-.241
-.042
-.004
(.000**)
( .371)
(.872)
MAY
.039
.214
.017
(.159)
(.000**)
(.492)
JUN
-.083
. 096
.009
(.003**)
(.037*)
(.713)
JUL
-.048
.060
. 035
(.085)
(.199)
(.157)
AUG
.015
. 167
.001
(.582)
(.000**)
(.957)
SEP
-.018
.030
-.039
(.510)
(.511)
(.119)
OCT
.060
. 175
.034
(.038*)
( .000**)
(.162)
NOV
-.041
.064
-.046
(.145)
(.165)
(.060)
CAR
-.030
-.088
-.046
DUMDNK
DUMTRN
DUMRUB1
DUMRUB2
(.317)
-.408
(.000**)
(.089)
.464
(.000**)
(.088)
-.264
(.000**)
-.273
( .000**)
Standard
Error
.059
. 102
.054
R-Squared
.746
.481
.518
DW
2.671
2.361
2.397
SSR
.321
1.066
.284
Dummied Observations
Beverages-1982:1
Transportation-1980:5
Rubber-1975:7,1981:9

84
RESULTS FOR EQUATION (3-1) 1975-1978
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Estimated
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
Coefficient
C
-.009
.070
-.065
-.028
(.727)
(.013*)
(.008**)
(.119)
JAN
-.084
-.022
. 091
-.013
(.071)
(.586)
(.015*)
(.635)
FEB
.210
-.106
.031
.069
(.000**)
(.046*)
(.489)
(.044*)
MAR
. 144
. 158
.182
.128
(.002**)
(.001**)
(.000**)
(.000**)
APR
-.037
-.202
-.003
-.001
(.352)
(.000**)
(.932)
(.977)
MAY
.051
.002
. 127
.066
(.177)
(.968)
(.000**)
(.011*)
JUN
.027
-.096
.056
.074
(.459)
(.016*)
(.097)
( .005**)
JUL
.007
-.118
.121
.089
(.856)
(.004**)
(.001**)
( .001**)
AUG
.063
-.030
.126
.070
(.095)
(.435)
(.001**)
( .007**)
SEP
.004
-.113
.033
.016
(.914)
(.005**)
(.325)
(.504)
OCT
.047
.014
.123
.040
(.204)
(.703)
(.001**)
(.108)
NOV
-.075
-.141
.045
-.031
(.048*)
(.001**)
(.180)
(.217)
CAR
-.130
-.125
-.002
-.082
DUMMAC
(.007**)
-.232
(.001**)
(.011*)
(.959)
(.010**)
Standard
Error
.052
.053
.047
.034
R-Squared
.771
.799
.672
.695
DW
2.684
2.468
2.427
2.440
SSR
. 080
.084
.074
.037
Dummied Observations: Machinery-1977:1

85
BEVERAGES
TRANSPORTATION
RUBBER
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
C
.057
-.077
-.011
(.009**)
(.035*)
(.472)
JAN
-.112
.045
.002
(.001**)
(.413)
(.932)
FEB
-.152
.156
.009
(.001**)
(.027*)
(.760)
MAR
.065
. 197
.015
(.062)
(.002**)
(.552)
APR
-.266
-.042
.013
(.000**)
(.445)
(.579)
MAY
.036
. 160
.039
(.253)
(.003**)
(.111)
JUN
-.083
.096
.045
(.013*)
(.064)
(.072)
JUL
-.046
.067
.032
(.151)
(. 185)
(.185)
AUG
.031
. 123
.036
(.332)
(.019*)
(.109)
SEP
-.046
.013
-.010
(.146)
(.792)
(.663)
OCT
.045
. 152
.015
(.159)
(.005**)
(.493)
NOV
-.065
.037
-.012
(.031*)
(.466)
(.592)
CAR
.003
-.027
.008
DUMRUB1
(.938)
(.661)
(.761)
-.246
(.000**)
Standard
Error
.041
.070
.031
R-Squared
.881
.566
.705
DW
1.863
2.638
2.730
SSR
.041
. 153
.027
Dummied Observation: Rubber-1975:7

86
RESULTS FOR EQUATION (3-1) 1979-1984
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Estimated
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
Coefficient
C
-.134
.039
-.108
-.080
(.000**)
(.476)
(.008**)
(.000**)
JAN
.033
.005
.079
.060
(.377)
(.947)
(.006**)
(.011*)
FEB
.325
. 119
.220
.057
(.000**)
(.209)
(.000**)
(.033*)
MAR
.284
.215
.219
.174
(.000**)
(.010*)
(.000**)
( .000**)
APR
.057
-.103
.036
.067
(.126)
(.181)
(.179)
( .003**)
MAY
.227
-.045
. 159
. 138
(.000**)
(.559)
(.000**)
( .000**)
JUN
.124
-.329
. 102
.117
(.001**)
(.000**)
(.000**)
(.000**)
JUL
.135
-.155
.130
. 142
(.001**)
(.058)
(.000**)
(.000**)
AUG
.178
-.079
. 129
. 103
(.000**)
(.304)
(.000**)
(.000**)
SEP
.128
-.062
.090
.045
(.001**)
(.421)
(.001**)
(.041*)
OCT
.128
-.003
.128
.085
(.001**)
(.968)
(.000**)
(.000**)
NOV
.088
-.070
.076
-.007
(.020*)
(.361)
(.006**)
(.759)
CAR
-.171
-.159
-.124
-.015
DUMTOB
DUMPLS
DUMCHM
Standard
(.000**)
(.053)
.829
( .000**)
(.000**)
-.187
(.000**)
(.510)
-.330
(.000**)
Error
.064
. 132
.046
.037
R-Squared
.647
.594
.674
.802
DW
2.652
2.036
1.873
1.662
SSR
.242
1.010
. 123
.080
Dummied Observations: Tobacco-1982:7
Plastics-1980:1
Chemicals-1982:1

87
BEVERAGES
TRANSPORTATION
RUBBER
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
C
.035
-.112
.013
(.267)
(.028*)
(.567)
JAN
-.094
. 108
-.124
(.036*)
(.129)
(.001**)
FEB
-.084
.173
.117
(.100)
(.048*)
(.006**)
MAR
.048
. 199
.053
(.286)
( .010*)
(.145)
APR
-.225
-.039
-.015
( .000**)
(.579)
(.655)
MAY
. 045
.255
.003
(.289)
(.001**)
(.921)
JUN
-.079
.097
-.011
(.063)
(.172)
(.741)
JUL
-.046
.054
.034
(.278)
(.448)
(.317)
AUG
.011
. 196
-.022
(.785)
(.007**)
(.512)
SEP
-.001
.041
-.060
(.990)
(.557)
( .095)
OCT
.072
. 191
.046
(.106)
(.009**)
(.177)
NOV
-.021
.082
-.068
(.633)
(.248)
(.048*)
CAR
-.046
-.118
-.073
DUMDNK
DUMTRN
DUMRUB2
(.284)
-.406
( .000**)
(.118)
.437
(.002**)
(.044*)
-.262
(.000**)
Standard
Error
.069
. 122
.058
R-Squared
.713
.495
.604
DW
2.780
2.355
2.157
SSR
.262
.858
.197
Dummied Observations: Beverages-1982:1
Transportation-1980:5
Rubber-1981:9

88
RESULTS FOR
EQUATION (3
-3) 1975-1984
P-Values
in parentheses
•
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Estimated
Estimated
Estimated
Estimated
Variable
Coefficient Coefficient
Coefficient
Coefficient
C
4.757
8.885
5.453
4.789
(.000**)
( .000**)
(.000**)
(.000**)
JAN
-.125
.100
.009
-.061
(.001**)
(.222)
(.773)
(.080)
FEB
.124
.079
.055
-.020
(.008**)
(.443)
(.211)
(.639)
MAR
.027
.234
.078
.066
(.503)
(.010**)
(.040*)
(.082)
APR
.050
-.055
-.044
.043
(.009**)
(.543)
(.183)
(.016*)
MAY
.046
-.168
.047
.051
(.200)
(.106)
(•152)
(.133)
JUN
.004
-.081
.003
.044
(.921)
(.311)
(.925)
(.198)
JUL
.002
-.010
.047
.065
(.952)
(.899)
(•177)
(.058)
AUG
.051
.038
.047
.033
(.161)
( .630)
(.170)
(.327)
SEP
-.003
.019
-.013
-.022
(.929)
( .816)
(.705)
(.508)
OCT
.015
. Ill
.050
. 015
(.655)
(.167)
(.118)
(.642)
NOV
.012
-.102
.024
.014
(.719)
(.269)
(.437)
(.659)
DEC
-.082
.093
-.117
-.056
(.024*)
(.245)
(.001**)
(.096)
CAR
-.049
-.055
-.055
-.004
CP4
CP5
CP10
(.204)
-.044
(.667)
( .530)
-.893
(.000**)
(.138)
-.193
(.025*)
(.905)
-.051
(.600)
Standard
Error
.079
. 176
. 076
.074
R-Squared
.598
.527
.666
.710
DW
1.273
.587
.803
.726

89
BEVERAGES
TRANSPORTATION
RUBBER
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
C
4.939
6.809
3.972
(.000**)
(.000**)
(.000**)
JAN
-.100
.021
.040
(.063)
(.739)
(.382)
FEB
-.068
.039
-.022
(.295)
(.619)
(.715)
MAR
.082
.038
.017
(.151)
(.579)
(.695)
APR
-.121
.012
-.012
(.054)
(.704)
( .786)
MAY
.087
.025
.010
(.106)
(.693)
(.810)
JUN
-.035
.024
-.041
(.507)
(.697)
(.240)
JUL
.000
-.012
.023
( .993)
( .851)
(.594)
AUG
.063
.093
-.003
( .240)
(•132)
(.948)
SEP
.029
-.042
-.070
(.583)
(.502)
(.078)
OCT
-.101
.092
.028
(.154)
(.119)
(.476)
NOV
.006
-.019
-.050
(.904)
(.746)
(.212)
DEC
.047
-.076
.000
(.378)
(.219)
(.994)
CAR
-.020
-.008
-.011
CP10
CP4
CP6
(.713)
-.050
(.758)
(.898)
-.475
( .008**)
(.807)
.145
(.121)
Standard
Error
. Ill
. 136
.088
R-Squared
.324
.275
.384
DW
.603
.952
.644

90
RESULTS FOR EQUATION (3-3) 1975-1978
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Estimated
Estimated
Estimated
Estimated
Variable Coefficient
Coefficient
Coefficient
Coefficient
JAN
-.173
.001
1.816
.002
(.000**)
(.971)
(.260)
(.963)
FEB
. 166
-.129
-.061
.046
(.002**)
(.002**)
(.436)
(.410)
MAR
.065
.086
.101
. 125
(.150)
(.017*)
(.128)
(.014*)
APR
4.593
-.231
-.086
11.526
(.002**)
(.000**)
(.154)
(.000**)
MAY
.041
-4.321
.044
.082
(.258)
(.000**)
(.439)
(.044*)
JUN
.018
-.073
-.024
.083
(.611)
(.012*)
(.674)
(.041*)
JUL
-.002
-.100
.040
.101
(.945)
( .001**)
( .485)
( .014*)
AUG
.054
-.014
.043
.084
(.142)
(.608)
( .445)
( .039*)
SEP
-.005
-.093
-.048
. 027
(.885)
(.002**)
(.398)
(.486)
OCT
.038
.035
.042
.051
(.291)
(.211)
(.458)
(.201)
NOV
-.084
-.117
-.035
-.022
(.024*)
(.000**)
(.539)
(.586)
DEC
-.009
.032
-.077
.002
(.797)
(.251)
(.175)
(.962)
CAR
-.079
-.082
.008
-.014
(.073)
(.019)
( .906)
(.767)
CP4
.003
-1.503
(.993)
(.000**)
CP5
1.938
(.000**)
CPI
.606
(.087)
Standard
Error
.049
.037
.078
.054
R-Squared
.710
.852
.577
.714
DW
1.599
1.666
.398
.772

91
BEVERAGES TRANSPORTATION
Estimated Estimated
Variable Coefficient Coefficient
RUBBER
Estimated
Coefficient
JAN
.000
FEB
(.997)
-.051
MAR
(.427)
.151
APR
(.014*)
-.181
MAY
(.004**)
. 123
JUN
(.029*)
-.004
JUL
(.942)
.038
AUG
(.477)
. 114
SEP
(.038*)
.038
OCT
(.509)
8.813
NOV
(.016*)
.014
DEC
(.760)
.075
CAR
(.097)
-.018
CP10
(.727)
-.914
CP4
CP6
(.229)
Standard
Error
.058
R-Squared
.636
DW
.624
-.070
-.002
(.443)
(.941)
.900
.006
(.451)
(.849)
. 119
.044
(.257)
(.117)
6.632
. 039
(.044*)
(.164)
.095
.051
( .266)
(.057)
.029
7.937
(.732)
(.000**)
.002
.037
(.985)
(.140)
.058
.045
(.499)
(.052)
-.053
-.002
(.532)
(.912)
.086
.022
(.314)
(.325)
-.030
-.006
(.719)
(.788)
-.069
.003
(.413)
(.899)
-.023
.032
(.822)
(.243)
-.440
(.527)
-.723
(.000**)
. 116
.031
.261
.582
.435
.974

92
RESULTS FOR EQUATION (3-3) 1979-1984
MACHINERY
Estimated
Variable Coefficient
TOBACCO PLASTICS CHEMICALS
Estimated Estimated Estimated
Coefficient Coefficient Coefficient
c
3.827
9.634
5.501
3.391
(.000**)
(.000**)
(.000**)
(.000**)
JAN
-.116
.147
-.007
-.107
(.041*)
(.231)
(.870)
(.025*)
FEB
.096
. 144
.103
-.048
(.155)
(.324)
(.064)
(.393)
MAR
-.001
.268
.055
.037
(.980)
( .039*)
(.249)
(.448)
APR
.045
-.009
-.048
.055
(. 160)
(.946)
(.276)
( .043*)
MAY
. 137
-.206
.029
.160
(.067)
(.310)
(.599)
(.012*)
JUN
-.021
-.120
. 009
.020
(.710)
(.318)
(.848)
(.659)
JUL
-.010
.012
. 038
.044
(.858)
(.921)
(.405)
(.346)
AUG
.035
.031
.035
.007
(.526)
(.796)
(.432)
( .876)
SEP
-.016
.056
-.003
-.052
( .766)
(.642)
(.948)
(.265)
OCT
-.022
. 127
.038
. 003
(.966)
(.297)
(.401)
(.955)
NOV
.140
-.206
.017
. 158
(.063)
(.310)
(.758)
(.013*)
DEC
-.143
. 106
-.135
-.094
(.011*)
(.376)
(.003**)
(.044*)
CAR
-.041
-.040
-.090
.002
( .455)
CP4 .139
(.374)
CP5
CPI
Standard
(.750)
-1.047
(.005**)
(.058)
-.198
(.116)
(.973)
.230
(.082)
Error
.093
.202
.076
.078
R-Squared
.533
.630
.634
DW
1.155
. 618
.964
.777

93
BEVERAGES
TRANSPORTATION
RUBBER
Estimated
Estimated
Estimated
Variabdfif icient
Coefficient
Coefficient
C 1.663
6.755
2.570
(.164)
(.000**)
(.000**)
JAN -.177
.069
.061
(.019*)
(.458)
(.468)
FEB -.103
.026
.069
(.231)
(.816)
(.524)
MAR .008
.015
-.003
(.913)
( .875)
(.964)
APR -.033
-.027
-.041
(.737)
(.601)
(.509)
MAY .041
.007
-.019
( .560)
(.957)
(.748)
JUN -.092
.020
-.010
(.199)
( .813)
(.852)
JUL -.062
-.022
.074
(.391)
(.811)
(.336)
AUG .002
. 116
-.038
(.975)
( .206)
(.523)
SEP -.014
-.035
-.122
( .840)
(.699)
( .043*)
OCT -.015
. 122
. 022
(.886)
(.175)
(.713)
NOV -.029
-.016
-.085
(.711)
(.895)
(.155)
DEC -.002
-.082
-.004
(.981)
( .369)
(.942)
CAR -.027
-.021
-.034
(.713)
(.822)
(.580)
CP10 .642
(.011*)
CP4
-.463
(.076)
CP6
.431
(.004**)
Standard
Error .119
. 154
. 101
R-Squared
.482
.203.499
DW .765
1.096
.644

94
RESULTS FOR EQUATION (3-4) 1975-1984
P-Values in parentheses.
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Estimated
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
Coefficient
C
-.062
.068
-.100
-.118
(.277)
(.101)
(.025*)
(.000**)
DUMMAC
-.223
(.001**)
DUMTOB
.806
(.000**)
DUMPLS
-.098
(.032**)
DUMCHM
-.316
(.000**)
JAN
-.014
-.006
.083
.027
(.636)
(.918)
(.001**)
(.116)
FEB
.238
-.001
. 127
.040
(.000**)
(.987)
(.000**)
(.029*)
MAR
. 150
.120
.163
. 125
( .000**)
( .031*)
(.000**)
(.000**)
APR
.003
-.161
.008
.030
(.918)
( .004**)
(.728)
(.070)
MAY
.154
-.042
. 147
.115
(.000**)
( .420)
(.000**)
(.000**)
JUN
.084
-.238
.084
.103
(.003**)
(.000**)
(.000**)
(.000**)
JUL
.084
-.139
.126
.120
(.003**)
(.011*)
(.000**)
(.000**)
AUG
.134
-.060
.127
.086
(.000**)
(.256)
(.000**)
(.000**)
SEP
.081
-.081
.066
.026
(.005**)
(•123)
(.005**)
(.114)
OCT
. 100
.006
. 125
.055
(.001**)
(.908)
(.000**)
( .002**)
NOV
.022
-.099
.064
-.014
(.434)
(.061)
(.005**)
(.397)
DCAR
-.093
-.081
-.040
-.021
(.000**)
(.018*)
(.004**)
(.041*)
CP4
-.198
.525
(.673)
(.054)
CP5
-.194
(.347)
CPI
.059
(.869)
Standard
Error
.062
. 117
.049
.036
R-Squared
.626
.525
.587
.755
DW
2.642
1.970
2.149
1.925

95
Coefficients on CPx variables are scaled by 103.
Dummied Observations: Machinery-1977:1
Tobacco-1982:7
Plastics-1980:1
Chemicals-1982:1

96
BEVERAGES
TRANSPORTATION
RUBBER
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
C
. 126
.084
.037
DUMDNK
DUMTRN
DUMRUB1
DUMRUB2
(.081)
-.407
(.000**)
(.367)
.461
(.000**)
(.530)
-.264
(.000**)
-.274
(.000**)
JAN
-.097
.095
-.086
(.001**)
(.045*)
(.002**)
FEB
-.119
. 163
.053
(.000**)
( .002**)
(.065)
MAR
.057
. 183
.021
(.077)
(.000**)
( .433)
APR
-.241
-.026
-.008
(.000**)
(.579)
(.750)
MAY
.043
.196
.017
(.123)
(.000**)
(.492)
JUN
-.074
.087
.007
(.011*)
(.060)
(.788)
JUL
-.033
.060
.027
(.273)
(.189)
(.348)
AUG
.036
. 178
-.005
( .277)
(.000**)
(.839)
SEP
.009
. 053
-.044
(.812)
(.259)
(.101)
OCT
.049
.213
.030
(.088)
(.000**)
(.227)
NOV
-.044
.056
-.047
(.118)
( .223)
(.057)
DCAR
-.001
-.053
-.869
CP10
CP4
CP6
Standard
(.952)
-.751
(.238)
(.071)
-1.608
(.038*)
(.582)
-.250
(.554)
Error
. 059
.101
.054
R-Squared
.747
.488
.519
DW
2.611
2.349
2.415

97
Coefficients on CPx variables are scaled by 103.
Dummied Observations: Beverages-1982:1
Transportation-1980:5
Rubber-1975:7, 1981:9

98
RESULTS FOR EQUATION (3-4) 1975-1978
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Estimated
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
Coefficient
C
-.170
.069
.014
.188
DUMMAC
(.604)
-.243
(.001**)
(.020*)
(.951)
(.401)
JAN
-.084
-.023
. 071
-.008
(.067)
(.580)
(.306)
( .783)
FEB
. 169
-.139
.002
.049
(.001**)
( .004**)
(.976)
(.147)
MAR
.058
.090
.170
. Ill
(.261)
( .039*)
(.007**)
( .004**)
APR
-.035
-.228
-.015
-.052
(.624)
( .000**)
(.786)
(.307)
MAY
.076
.002
. 114
.031
(.235)
(.958)
(.026*)
(.475)
JUN
.050
-.095
.045
.044
(.393)
( .017*)
(.327)
(.282)
JUL
.025
-.118
. 112
.064
(.629)
(.004**)
(.012*)
( .087)
AUG
.078
-.030
. 119
.050
(.104)
(.437)
(.005**)
(.133)
SEP
.015
-.113
.028
. 002
(.728)
(.005**)
(.454)
(.943)
OCT
.054
.014
.119
.031
(.168)
(.703)
(.002**)
( .266)
NOV
-.072
-.141
.044
-.035
(.057)
(.001**)
(.203)
(.193)
DCAR
-.083
-.077
.011
-.034
CP4
CP5
CPI
Standard
(.003**)
1.313
(.622)
(.007**)
. 020
(.888)
(.610)
-.590
( .726)
(.075)
-1.759
(.335)
Error
.051
.053
.047
.037
R-Squared
.787
.806
.675
.668
DW
2.706
2.347
2.413
2.383
Coefficients on CPx variables are scaled by 103.
Dummied Observation: Machinery-1977:1

99
BEVERAGES TRANSPORTATION RUBBER
Estimated Estimated Estimated
Variable Coefficient Coefficient Coefficient
C
DUMRUB1
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DCAR
CP10
CP4
CP6
Standard
Error
R-Squared
DW
-.345
(.403)
-.124
(.001**)
-.179
(.000**)
.025
(.641)
-.323
(.000**)
-.038
(.644)
-.169
(.077)
-.146
(.179)
-.083
(.490)
-.174
(.200)
.062
(.092)
-.058
(.064)
.004
( .850)
3.851
(.331)
. 041
.886
1.917
-.076
(.860)
.045
(.422)
.160
(.018*)
. 177
(.015*)
-.053
(.584)
. 160
(.068)
.095
(.227)
.067
(.345)
. 122
(.061)
.013
(.821)
.152
(.008**)
.037
(.474)
-.034
(.349)
-.014
(.997)
.071
.576
2.615
-.013
(.968)
-.246
(.000**)
.002
(.934)
-.002
( .945)
.026
(.501)
.022
(.666)
.039
(.519)
.045
(.374)
.033
(.455)
.037
(.307)
-.010
(.749)
.015
(.546)
-.012
(.596)
.025
(.107)
.011
(.997)
.030
.732
2.675
Coefficients on CPx variables are scaled by 103
Dummied Observation: Rubber-1975:7

100
RESULTS FOR EQUATION (3-4) 1979-1984
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Estimated
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
Coefficient
C
-.161
.054
-.123
-.189
(.047*)
(.421)
(.047*)
(.000**)
DUMTOB
.832
(.000**)
DUMPLS
-.187
(.001**)
DUMCHM
-.321
(.000**)
JAN
.030
.003
.079
.048
(.421)
(.965)
(.008**)
(.032*)
FEB
.275
.068
.180
.039
(.000**)
(.421)
(.000**)
(.094)
MAR
. 186
. 135
.152
. 136
(.000**)
(.093)
(.000**)
( .000**)
APR
.016
-.129
. 010
.032
(.711)
(.107)
(.768)
(.179)
MAY
.229
-.048
. 159
. 145
( .000**)
(.537)
(.000**)
( .000**)
JUN
.123
-.331
. 101
. 116
(.001**)
(.000**)
( .000**)
(.000**)
JUL
.132
-.156
. 128
.131
(.001**)
(.059)
( .000**)
(.000**)
AUG
. 174
-.079
. 126
.083
(.000**)
(.309)
( .000**)
(.000**)
SEP
.121
-.061
.085
.015
(.006**)
(.436)
(.Oil*)
(.513)
OCT
.117
.000
. 122
.042
(.016*)
(.999)
( .002**)
(.112)
NOV
.090
-.072
. 077
.000
(.018*)
(.361)
(.007**)
(.991)
DCAR
-.102
-.084
-.066
-.015
(.000**)
(.081)
( .000**)
( .224)
CP4
.256
1.025
(.718)
( .Oil*)
CP5
-.147
(.687)
CPI
. 141
(.794)
Standard
Error
.063
. 134
. 048
.035
R-Squared
.658
.590
.659
.827
DW
2.641
2.018
1.863
1.716

101
Coefficients on CPx variables are scaled by 103.
Dummied Observations: Tobacco-1982:7
Plastics-1980:1
Chemicals-1982:1

102
BEVERAGES
TRANSPORTATION
RUBBER
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
C
.140
. 184
.085
DUMDNK
DUMTRN
DUMRUB2
(.228)
-.410
(.000**)
(.218)
.436
(.001**)
(.405)
-.265
(.000**)
JAN
-.087
. 136
-.144
(.057)
(.055)
( .002**)
FEB
-.099
. 191
.068
(.038*)
(.017*)
(.132)
MAR
.055
.212
.006
(.280)
(.009**)
(.872)
APR
-.234
.018
-.033
(.000**)
(.822)
( .383)
MAY
.042
.238
-.002
(.325)
( .002**)
(.951)
JUN
-.074
.101
-.015
(.087)
(.145)
(.664)
JUL
-.032
.083
.012
(.484)
( .242)
(.799)
AUG
.034
.248
-.041
( .483)
(.001**)
(.347)
SEP
.033
. 122
-.074
(.552)
(.124)
(.077)
OCT
.059
.308
.037
(.201)
(.001**)
(.322)
NOV
-.027
.064
-.073
(.550)
(.360)
(.043*)
DCAR
-.003
-.071
-.026
CP10
CP4
CP6
Standard
(.913)
-.935
(.344)
(.094)
-2.772
(.038*)
( .231)
-.486
(.471)
Error
. 070
. 118
.060
R-Squared
.712
.531
.589
DW
2.737
2.206
2.114

103
Coefficients on CPx variables are scaled by 103.
Dummied Observations: Beverages-1982:1
Transportation-1980:5
Rubber-1981:9

104
RESULTS FOR EQUATION (3-5) 1975-1984
P-Values are in parentheses.
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Estimated
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
Coefficient
C
-.077
.066
-.086
-.060
DUMMAC
DUMTOB
DUMPLS
DUMCHM
(.000**)
-.229
(.001**)
(.083)
.801
(.000**)
(.000**)
-.204
(.000**)
(.000**)
-.322
(.000**)
JAN
-.013
-.003
.082
.031
(.657)
(.954)
(.001**)
(.079)
FEB
.240
.001
. 123
.047
(.000**)
(.986)
(.000**)
(.011*)
MAR
. 149
. 125
.165
. 137
( .000**)
(.025*)
(.000**)
(.000**)
APR
-.014
-.158
.010
.033
(.621)
(.005**)
(.653)
(.056)
MAY
.152
-.046
. 143
. 110
(.000**)
(.398)
(.000**)
(.000**)
JUN
.086
-.235
.084
. 100
(.002**)
(.000**)
(.000**)
(.000**)
JUL
.086
-.134
. 128
.120
(.002**)
(.014*)
(.000**)
( .000**)
AUG
.134
-.057
. 129
.089
(.000**)
( .276)
( .000**)
(.000**)
SEP
. 082
-.078
.069
.033
(.003**)
(.140)
( .002**)
(.049*)
OCT
.101
.014
. 130
.066
(.000**)
(.791)
(.000**)
(.000**)
NOV
. 018
-.112
.060
-.015
(.520)
(.037*)
( .009**)
(.369)
DCAR
-.097
-.082
-.041
-.022
DCP4
DCP5
(.000**)
-.133
(.328)
(.016*)
-.328
(.154)
(.004**)
(.037*)
.032
(.691)
DCP1
-.001
(.370)

105
MACHINERY TOBACCO PLASTICS CHEMICALS
Standard
Error .060 .116 .049 .037
R-Squared .647 .532 .590 .745
DW 2.549 1.900 2.147 1.884
Coefficients on DCPx variables are scaled by 102.
Dummied Observations: Machinery-1977:1
Tobacco-1982:7
Plastics-1980:1
Chemicals-1982:1

106
BEVERAGES TRANSPORTATION RUBBER
Estimated Estimated Estimated
Variable Coefficient Coefficient Coefficient
c
.053
DUMDNK
(.013*)
-.407
DUMTRN
DUMRUB1
(.000**)
DUMRUB2
JAN
-.098
FEB
(.001**)
-.123
MAR
(.000**)
.047
APR
(.108)
-.246
MAY
(.000**)
. 041
JUN
(.140)
-.079
JUL
(.006**)
-.042
AUG
(.141)
.021
SEP
(.460)
-.010
OCT
(.719)
.052
NOV
(.083)
-.040
DCAR
(.156)
-.003
DCP10
(.849)
-.187
DCP4
DCP6
(.247)
Standard
Error
.059
R-Squared
.747
DW
2.652
-.077
.002
(.024*)
(.932)
.457
(.000**)
-.264
(.000**)
-.273
(.000**)
.090
-.079
(.054)
(.003**)
. 152
. 058
(.003**)
(.035*)
. 162
. 023
( .001**)
(.364)
-.059
-.007
(.217)
(.786)
.200
.017
(.000**)
(.501)
.099
.009
(.030*)
(.718)
.066
.037
(.149)
(.161)
.172
.002
(.000**)
(.947)
. 040
-.039
(.379)
( .126)
.193
.033
(.000**)
(.175)
.048
-.046
(.300)
(.064)
-.058
-.009
(.050*)
(.587)
-.422
(.064)
. 000
(.814)
. 101
.055
.501
.505
2.308
2.351

107
Coefficients on DCPx variables are scaled by 10z.
Dummied Observations: Beverages-1982:1
Transportation-1980:5
Rubber-1981:9

108
RESULTS FOR EQUATION (3-5) 1975-1978
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Estimated
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
Coefficient
C
-.027
.066
-.060
-.020
(.450)
(.021*)
(.056)
(.426)
DUMMAC
-.235
(.001**)
JAN
-.091
-.025
.085
-.009
(.051)
(.541)
(.043*)
(.763)
FEB
.164
-.142
.022
.043
( .001**)
( .003**)
(.568)
(.221)
MAR
.054
.185
. 189
.098
(.254)
(.055)
( .000**)
(.008**)
APR
-.047
-.234
.002
-.019
(.317)
(.000**)
(.956)
(.577)
MAY
.046
. 005
. 129
. 068
(.213)
( .894)
(.001**)
(.016*)
JUN
.026
-.095
.057
. 074
(.469)
(.016*)
(.098)
(.008**)
JUL
.003
-.119
. 122
. 090
( .927)
(.003**)
( .001**)
(.002**)
AUG
.058
-.031
. 128
. 072
(.124)
( .405)
( .001**)
(.Oil*)
SEP
.000
-.114
.034
.018
(1.00)
(.005**)
(.315)
(.499)
OCT
.043
. 014
. 124
.042
(.240)
(.703)
( .001**)
(.123)
NOV
-.079
-.140
.046
-.029
(.037*)
(.001**)
(.176)
( .276)
DCAR
.082
-.076
.012
-.034
(.003**)
(.007**)
( .607)
(.079)
DCP4
.735
-.301
(.468)
(.683)
DCP5
.284
(.553)
DCP1
-.224
(.759)
Standard
Error
.050
. 053
.047
.037
R-Squared
.789
.808
.675
.659
DW
2.698
2.376
2.373
2.349
Coefficents on DCPx variables are scaled by 102.
Dummied Observation: Machinery-1977:1

109
BEVERAGES
TRANSPORTATION
RUBBER
Estimated
Estimated
Estimated
Variable Coefficient
Coefficient
Coefficient
C
.033
-.089
-.004
DUMRUB1
(.187)
(.075)
(.873)
-.249
(.000**)
JAN
-.124
.039
.006
(.000**)
(.498)
(.806)
FEB
-.173
. 150
.004
(.000**)
(.027*)
(.881)
MAR
.041
.164
.035
(.248)
(.018*)
(.239)
APR
-.292
-.041
.031
(.000**)
(.534)
(.308)
MAY
.013
. 157
.047
(.690)
(.004*)
(.100)
JUN
-.096
.095
.037
(.005**)
(.067)
(.199)
JUL
-.065
.065
.034
(.053)
( .205)
(.152)
AUG
.010
.119
.039
(.757)
(.026*)
(.086)
SEP
-.064
.011
-.008
(.055)
( .836)
(.716)
OCT
. 069
.149
.017
(.048*)
(.006**)
(.434)
NOV
-.070
.034
-.010
(.019*)
(.499)
(.633)
DCAR
.005
-.033
.025
DCP10
DCP4
DCP6
(.794)
1.198
(.108)
(.365)
.490
(.727)
(.111)
-.353
(.620)
Standard
Error
. 039
.070
.030
R-Squared
.894
.578
.734
DW
1.932
2.630
2.674
Coefficients on DCPx variables are scaled by 102
Dummied Observation: Rubber-1975:7

110
RESULTS FOR EQUATION (3-5) 1979-1984
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Estimated
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
Coefficient
C
-.143
.055
-.111
-.091
(.000**)
(.355)
(.000**)
(.000**)
DUMTOB
.823
(.000**)
DUMPLS
-.187
(.001**)
DUMCHM
-.327
(.000**)
JAN
.032
.006
.079
.057
(.393)
(.939)
(.008**)
(.012*)
FEB
.278
.069
.181
.057
(.000**)
( .408)
(.000**)
(.016*)
MAR
.189
.139
. 154
.159
(.000**)
(.084)
(.000**)
(.000**)
APR
.021
-.027
.013
.059
(.573)
(.111)
(.646)
(.008**)
MAY
.235
-.061
. 162
.148
( .000**)
(.449)
(.000**)
( .000**)
JUN
. 122
-.328
. 101
.115
( .002**)
(.000**)
( .001**)
( .000**)
JUL
.132
-.150
. 129
.138
( .001**)
(.069)
(.000**)
(.000**)
AUG
. 176
-.078
. 129
. 100
( .000**)
(.317)
(.000**)
( .000**)
SEP
. 123
-.057
.088
.039
(.002**)
(.464)
(.003**)
(.072)
OCT
.120
.009
. 125
.074
(.003**)
( .906)
( .000**)
(.001**)
NOV
.097
-.086
.079
.004
(.016*)
( .285)
(.009**)
( .851)
DCAR
-.102
-.085
-.066
-.016
(.000**)
(.077)
(.000**)
( .223)
DCP4
. 127
. 163
(.519)
(.154)
DCP5
-.243
(.469)
DCP1
.049
(.741)
Standard
Error
.064
. 133
.048
.036
R-Squared
.660
.593
. 660
.813
DW
2.675
1.991
1.863
1.702

Ill
Coefficients on DCPx variables are scaled by 102.
Dummied Observations: Tobacco-1982:7
Plastics-1980:1
Chemicals-1982:1

112
BEVERAGES TRANSPORTATION RUBBER
Estimated Estimated Estimated
Variable Coefficient Coefficient Coefficient
c
.047
DUMDNK
(.184)
-.409
DUMTRN
(.000**
DUMRUB2
JAN
-.089
FEB
(.050*)
-.107
MAR
(.023*)
.039
APR
(.390)
-.238
MAY
(.000**
.045
JUN
(.295)
-.075
JUL
(.085)
-.039
AUG
(.376)
.017
SEP
(.686)
. 010
OCT
(.828)
. 059
NOV
(.217)
-.020
DCAR
(.656)
-.007
DCP10
(.785)
-.204
DCP4
DCP6
(.435)
Standard
Error
. 070
R-Squared
.711
DW
2.756
-.075
. 016
(.179)
(.606)
.435
(.002**)
-.263
(.000**)
.114
-.126
(.108)
(.002**)
.147
.085
(.057)
(.029*)
.154
.020
(.036*)
(.584)
-.053
-.024
(.459)
(.501)
.221
. 003
(.006**)
(.933)
.103
-.011
(.145)
(.750)
.066
.032
(.349)
(.421)
.206
-.023
( .005**)
(.518)
.061
-.060
( .393)
(.105)
.226
.047
(.003**)
(.188)
.045
-.068
(.542)
(.055)
-.070
-.026
(.104)
(.230)
-.550
(.145)
-.027
(.897)
. 121
.060
.512
.585
2.259
2.101

113
Coefficients on DCPx variables are scaled by 102.
Dummied Observations: Beverages-1982:1
Transportation-1980:5
Rubber-1981:9

114
RESULTS FOR EQUATION (4-1)
P-Values are in parentheses.
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Estimated
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
Coefficient
C
7.201
2.328
5.646
14.018
RWMAC
RWTOB
RWPLS
RWCHM
(.000**)
.518
(.008**)
(.024*)
1.315
(.000**)
(.000**)
.711
(.000**)
(.099)
-.432
(.716)
TREND
.001
-.002
-.001
.006
(.858)
(.000**)
(.375)
(.596)
JAN
.023
. 038
-.038
. 023
(.282)
( .321)
(.068)
(.731)
FEB
.023
.176
-.028
.013
( .463)
(.006**)
( .355)
(.795)
MAR
.021
-.014
-.036
.014
(.338)
(.715)
(.092)
(.691)
APR
.013
.022
-.022
.027
(.569)
(.549)
(.291)
(.578)
MAY
.004
-.086
-.029
. 020
(.850)
(.031*)
(.161)
(.549)
JUN
.013
-.069
-.014
.019
(.549)
(.078)
( .480)
(.487)
JUL
.010
-.072
-.001
.015
(.647)
(.064)
(.961)
(.616)
AUG
.014
-.030
-.007
.013
(.524)
(.421)
(.748)
(.694)
SEP
.029
-.008
.007
.011
(.188)
(.838)
(.722)
(.790)
OCT
.024
-.011
.014
.009
(.276)
(.769)
(.486)
(.807)
NOV
.015
.018
.021
. 005
(.505)
(.631)
(.308)
(.884)
CAR
-.007
-.034
.009
-.003
(.815)
(.473)
(.749)
(.930)
Standard
Error
.051
. 086
.049
. 064
R-Squared
.977
.781
.956
.498
DW
0.091
1.030
.463
.235

115
BEVERAGES TRANSPORTATION RUBBER
Estimated Estimated Estimated
Variable Coefficient Coefficient Coefficient
RWDNK
(.000**)
.611
RWTRN
(.000**)
RWRUB
TREND
-.002
JAN
(.000**)
-.008
FEB
(.605)
.017
MAR
(.492)
.011
APR
(.568)
.014
MAY
(.473)
.002
JUN
(.920)
.021
JUL
(.294)
.043
AUG
(.030*)
.055
SEP
(.008**)
.079
OCT
(.001**)
.005
NOV
(.756)
.417
CAR
(.790)
.460
DNK1
(.817)
.266
DNK2
(.000**)
.263
DNK3
(.000**)
.270
(.000**)
Standard
Error
.065
R-Squared
.361
DW
.203
6.676
5.224
(.000**)
(.000**)
.601
(.000**)
.750
(.000**)
.000
-.001
(.931)
(.446)
-.017
.031
(.446)
(.136)
.015
. 052
(.644)
(.059)
. 008
. 052
(.727)
( .017*)
-.020
.057
(.393)
(.009**)
-.033
.055
(.175)
(.010)
-.016
.004
(.502)
(.831)
-.011
-.027
(.633)
(.239)
.001
-.029
(.967)
(.196)
.014
-.002
(.521)
(.940)
.013
-.001
(.559)
( .972)
.008
.009
(.720)
(.641)
.008
-.002
(.774)
(.939)
.052
.050
.962
.939
0.173
.303

116
RESULTS FOR EQUATION (4-2)
MACHINERY TOBACCO PLASTICS CHEMICALS
Estimated Estimated Estimated Estimated
Variable Coefficient Coefficient Coefficient Coefficient
c
6.421
6.393
.469
35.715
RWMAC
RWTOB
RWPLS
RWCHM
(.077)
.309
(.554)
(.000**)
.091
(.695)
( .810)
1.253
(.000**)
(.447)
-3.691
(.575)
TREND
.010
.006
-.001
.046
(.173)
(.000**)
(.686)
(.426)
JAN
-.157
. 104
-.065
. 182
(.007**)
(.008**)
(.161)
(.627)
FEB
-.107
. 044
.050
. 112
(.207)
(.504)
( .455)
(.689)
MAR
.008
.091
. 024
.098
(.889)
(.017*)
( .616)
(.609)
APR
-.041
.018
.021
. 160
(.494)
(.631)
(.644)
(.548)
MAY
.017
.048
.061
.135
(.792)
(.235)
(.189)
(.466)
JUN
.058
-.026
.024
.066
(.327)
(.514)
(.603)
(.662)
JUL
.051
.040
.065
.065
(.404)
(.769)
(.155)
(.701)
AUG
.048
-.014
.069
.053
(.424)
(.716)
(.134)
(.775)
SEP
.038
-.071
.056
.013
(.515)
(.056)
(.222)
(.954)
OCT
.056
.014
.124
.045
(.336)
(.702)
(.007**)
(.824)
NOV
-.035
-.081
.094
-.014
(.543)
(.030*)
(.039*)
(.939)
CAR
-.012
-.053
.028
-.072
(.871)
(.273)
(.636)
(.727)
Standard
Error
. 136
.087
. 108
.353
R-Squared
.954
.897
.939
.671
DW
0.464
.670
.540
.246

117
DRINKS TRANSPORTATION RUBBER
Estimated Estimated Estimated
Variable Coefficient Coefficient Coefficient
c
-6.256
3.380
6.909
RWDNK
RWTRN
RWRUB
(.034*)
2.433
(.000**)
( .008**)
.807
(.000**)
(.000**
.258
(.376)
TREND
-.004
.001
.004
(.082)
(.468)
(.042*)
JAN
-.033
-.034
-.056
(.591)
(.391)
(.156)
FEB
-.075
. 152
.020
(.430)
(.007**)
(.854)
MAR
-.074
.155
-.008
(.304)
(.000**)
( .843)
APR
-.132
.078
-.053
(.087)
(.055)
(.197)
MAY
-.210
.114
-.010
( .002**)
(.007**)
(.809)
JUN
-.160
.047
-.018
(.036*)
(.249)
(•645)
JUL
-.002
.125
.013
(.979)
( .002**)
(.767)
AUG
.132
.141
. 042
(.103)
(.000**)
(.325)
SEP
.244
. 107
-.006
(.008**)
(.006**)
(.872)
OCT
.031
. 168
.040
(.598)
(.000**)
(.304)
NOV
-.055
.072
-.017
(.361)
(.064)
(.659)
CAR
.033
-.116
-.041
(.663)
(.021*)
(.358)
Standard
Error
.139
.091
. 093
R-Squared
.877
.952
.879
DW
.643
1.003
0.794

118
RESULTS FOR EQUATION (4-3)
MACHINERY
TOBACCO
PLASTICS
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
C
-.010
-.001
-.012
(.009**)
(.912)
(.007**)
DRWMAC
.289
(.000**)
DRWTOB
. 089
(.001**)
DRWPLS
. 116
(.001**)
DRWCHM
JAN
.023
-.006
.003
(.000**)
(.498)
(.647090)
FEB
.013
.002
.024
(.033*)
(.786)
(.001**)
MAR
. 016
-.001
.014
(.006**)
(.935)
(.052)
APR
.009
.004
.018
(.104)
(.567)
( .005**)
MAY
.010
.000
.019
(.053)
( .998)
( .003**)
JUN
.017
. 000
.024
(.001**)
( .988)
( .000**)
JUL
. 014
-.005
.025
(.008**)
(.532)
(.000**)
AUG
.015
.001
.018
(.004**)
(.869)
( .006**)
SEP
.020
-.004
.022
( .000**)
(.586)
( .001**)
OCT
.009
.002
.029
(.097)
(.849)
( .000**)
NOV
. 007
.003
.013
(.213)
( .658)
(.041*)
DCAR
.002
-.001
-.005
(.668)
(.874)
( .315)
DUMMAC
.081
(.000**)
DUMTOB
-.153
(.000**)
DUMPLS
-.171
(.000**)
DUMCHM
CHEMICALS
Estimated
Coefficient
-.012
(.018*)
.089
(.038*)
.022
(.004**)
.017
(.040*)
.018
(.025*)
.017
(.015*)
.015
(.035*)
.021
(.003**)
.015
(.041*)
.013
(.065)
.015
(.031*)
.008
(.240)
.344
(.418)
.000
(.953)
-.148
(.000**)

119
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Standard
Error
.012
.019
. 016
.016
R-Squared
.583
.452
.730
.462
DW
1.976
1.922
1.947
2.285
Dummied Observations:
Machinery-1967:1
Tobacco-1973:
: 9
Plastics-1967:1
Chemicals-1969:1

120
DRINKS
TRANSPORTATION
RUBBER
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
C
.000
-.006
-.004
(.991)
(.146)
(.547)
DRWDNK
.295
(.000**)
DRWTRN
.179
(.000**)
DRWRUB
-.198
(.484)
JAN
-.004
-.577
.016
( .689)
(.376)
(.229)
FEB
.010
. 024
.014
(.338)
(.002**)
(.223)
MAR
-.008
.014
.021
(.407)
(.033*)
(.042*)
APR
-.005
.367
-.001
(.578)
(.561)
(.944)
MAY
-.003
.932
.013
(.695)
(.125)
(.185)
JUN
.009
.016
.025
(.319)
(.007**)
( .261)
JUL
.021
.007
.018
(.016*)
(.224)
(.241)
AUG
.008
.016
.006
(.371)
(.006**)
(.564)
SEP
.014
.010
.002
(.124)
(.108)
( .881)
OCT
-.037
.012
.003
(.000**)
( .037*)
( .780)
NOV
-.001
. 003
.003
(.900)
(.609)
(.747)
DCAR
.000
.002
-.009
(.965)
(.656)
(.210)
DUMDNK
-.152
(.000**)
DUMTRN1
.070
(.000**)
DUMTRN2
-.066
(.000**)
DUMTRN3
.061
( .000**)
DUMRUB1
-.160
(.000**)
Standard
Error
. 020
. 014
.023
R-Squared
. 608
.576
. 101
DW
2.172
1.562
1.634

121
Dummied Observations: Beverages-1967:1
Transportation-1971:1,1973:1,1973 : 2
Rubber-1969:1

122
RESULTS FOR EQUATION (4-4)
MACHINERY
TOBACCO
PLASTICS
CHEMICALS
Estimated
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
Coefficient
C
.039
.088
-.082
-.049
DRWMAC
DRWTOB
DRWPLS
DRWCHM
(.164)
.699
(.009**)
(.000**)
.046
(.632)
(.000**)
.382
(.000**)
(.004**)
.762
(.000**)
JAN
-.199
.028
.025
-.021
(.000**)
(.368)
(.285)
(.396)
FEB
.021
-.156
.091
. 103
(.647)
(.000**)
(.001**)
( .000**)
MAR
.071
-.021
. 179
.081
(.102)
( .566)
(.000**)
( .002**)
APR
-.090
-.155
.069
.045
(.023)
(.000**)
(.003**)
( .060*)
MAY
.015
-.048
. 143
.107
(.704)
(.124)
( .000**)
(.000**)
JUN
.017
-.156
.042
.068
(.678)
(.000**)
( .073)
(.005**)
JUL
-.047
-.045
.123
. 099
(.235)
(.141)
(.000**)
(.000**)
AUG
-.033
-.109
.102
.063
(.395)
( .000**)
( .000**)
(.008**)
SEP
-.030
-.141
.064
.056
(.455)
(.000**)
(.006*)
(.019*)
OCT
-.016
.003
.164
.064
(.687)
(.903)
(.000**)
(.007**)
NOV
-.129
-.179
.045
-.022
(.001**)
(.000**)
(.053)
(.347)
DCAR
-.009
-.042
.020
-.033
(.770)
(.067)
(.249)
(.067)
Standard
Error
.092
.071
.054
.055
R-Squared
.436
.580
.581
.418
DW
2.627
2.836
2.687
2.532

123
DRINKS
TRANSPORTATION
RUBBER
Estimated
Estimated
Estimated
Variable
Coefficient
Coefficient
Coefficient
C
.088
-.071
-.008
DRWDNK
DRWTRN
DRWRUB
(.000**)
.562
(.003**)
(.010*)
.788
(.000**)
(.888)
4.731
(.042)
JAN
-.186
.014
.098
(.000**)
(.725)
(.421)
FEB
-.237
.249
. 101
(.000**)
(.000**)
(.260)
MAR
-.065
.082
-.076
(.095)
(.059)
(.354)
APR
-.183
-.003
.018
(.000**)
(.948)
(.833)
MAY
-.102
. 108
.002
(.004**)
(.006**)
(.977)
JUN
-.089
.005
-.299
(.014*)
(.906)
(.063)
JUL
.069
. 150
-.171
(.050*)
(.000**)
( .156)
AUG
. 030
.088
.019
(.392)
(.024*)
( .793)
SEP
-.027
.038
.099
(.451)
( .332)
(.377)
OCT
-.067
. 133
.064
(.097)
( .001**)
(.395)
NOV
-.167
-.025
.003
(.000**)
( .526)
(.971)
DCAR
.043
-.107
.026
DUMRUB2
(.101)
(.000**)
(.632)
-.443
(.141)
Standard
Error
.082
.091
.180
R-Squared
.618
.476
.095
DW
2.341
2.771
2.277
Dummied Observation
Rubber-1976:6

Real Wage Value of Output
1,400,000
1,200,000
1,000,000
800,000
600,000
400,000
200,000
0
1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976
Transportation
Real Wage Value of Output
REAL WAGE RATES AND OUTPUT BY INDUSTRY

Real Wage Value of Output
125

Real Wage Value of Output
Plastics
Real Wage Value of Output
126

Chemicals
Real Wage Value of Output
127

Real Wage Value of Output
Beverages
Real Wage Value of Output
128

Real Wage
Value of Output
40.000
1966 1967 1968 1969 1970 1971 1972 1973 1974 1975
Tobacco
1976
30,000
- 20,000
10,000
Real Wage Value of Output
129

Real Wage Value of Output
Rubber
Real Wage Value of Output
130

131
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134
BIOGRAPHICAL SKETCH
Carol Ann Badger Dole was born in Palatka, Florida, in
1961. She received a Bachelor of Science degree from the
University of Florida in 1982. In 1983, she earned a Master
of Business Administration from the University of
Cincinnati. After working in the financial institution
industry, she returned to the University of Florida in 1988
and earned a Master of Arts degree in 1991.

I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
Mark Rush, Chairman
Professor of Economics
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
David Denslow
Professor of Economics
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
William Bomberger
Associate Professor of Economics
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
Douglas Waldo
Associate Professor of Economics
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
Michael Ryngaert
Assistant Professor of Finance,
Insurance and Real Estate

This dissertation was submitted to the Graduate Faculty
of the Department of Economics in the College of Business
Administration and to the Graduate School and was accepted
as partial fulfillment of the requirements for the degree of
Doctor of Philosophy.
August 1992
Dean, Graduate School

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