WAYNE VROMAN
Urban Institute
JOHN M. ABOWD
Cornell University
Disaggregated Wage Developments
UNEMPLOYMENT has declinedsubstantiallyin the United States in recent
years, from 9.6 percent of the civilianlaborforce in 1983to 5.7 percent
in the firstquarterof 1988,while wage and price inflationhave remained
low. Annual increases in the private nonfarmaverage hourly earnings
index, for example, rangedfrom2.0 percentto 3.8 percentandaveraged
3.0 percentbetween 1983and 1987.Duringthe firstthreemonthsof 1988
averagehourlyearningsincreasedat an annualrate of 2.5 percent.
This reportexamines nominalwage growth duringthe 1980s. It first
documentsthe slowdown in wage inflationand then examines possible
sources of that slowdown.
Recent Wage Inflation
Table 1 shows data on average rates of unemploymentand of wage
andpriceinflationsince 1965.Wageinflationratesforthe privatenonfarm
sector are shownfor three series: the hourlyearningsindex, the employmentcost index, andeffective wage changesfor majorunionagreements
(agreementsaffecting 1,000 or more workers). Price inflationis shown
for the consumerprice index andthe GNP deflator.In each series, wage
and price inflationaveragedless than 4 percent a year during1983-87.
Wagegrowthduringthat period was at least 5 percentagepoints below
its average during1980-81. Not since the early 1960shas wage growth
The authors acknowledge financial support from the National Science Foundation and
the Ford Foundation. Ron Ehrenberg provided helpful comments on an earlier draft.
313
314
Brookings
Papers on Economic
Activity,
1:1988
Table 1. Average Wage Inflation, Price Inflation, and Unemployment Rates, 1965-87
Percent per year
Price inflation
Wage inflation
Employment
cost
indexb
Major
union
agr eementsc
Consumer
price
indexd
Implicit
GNP
deflatore
Unemployment
rate
Men
aged
Civilian
24-54
Period
Hourly
earnings
indexa
1965-69
1970-74
1975-79
5.4
7.2
7.7
n.a.
n.a.
7.6U
n.a.
8.2
8.4
3.8
6.7
8.2
4.2
6.8
7.6
3.8
5.4
7.0
2.0
3.0
4.4
1980
1981
1982
1983
1984
9.3
8.1
6.1
3.8
3.2
9.0
8.8
6.3
5.0
4.1
9.9
9.5
6.8
4.0
3.7
12.5
8.9
3.8
3.8
3.9
9.9
8.7
5.2
3.6
3.4
7.1
7.6
9.7
9.6
7.5
5.2
5.5
8.0
8.2
5.9
1985
1986
1987
3.2
2.0
2.6
4.1
3.1
3.3
3.3
2.3
3.1
3.8
1.1
4.4
3.1
2.2
3.3
7.2
7.0
6.2
5.6
5.6
5.0
Source: Hourly earnings index, consumer prices, and unemployment rate are from U.S. Department of Labor,
Bureau of Labor Statistics, Eniploynietit anid Earnings, various issues. Employment cost index and major union
agreements are from Bureau of Labor Statistics, Current Wage Developments, vol. 40 (March 1988). GNP deflator
is from National Income and Product Accounts.
n.a. Not available.
a. December to December percent change for private nonagricultural workers.
b. December to December percent change of wages and salaries of private industry workers.
c. Average annual wage adjustment effective in the year for all industries. Major agreements are those covering
1,000 or more workers.
d. December to December percent change.
e. Fourth quarter to fourth quarter percent change.
f. 1976-79.
been so slow. The trend is particularlystrikingbecause of the drop in
unemployment,from9.6 percentto 6.2 percent, between 1983and 1987.
Aggregate Wage Growth
To estimate the size of the unexpected component in the recent
slowdown in wage growth, we fit a series of augmentedPhillipscurves,
in which aggregatewage growth is modeled as a function of the unemploymentrateandthe expected rateof priceinflation.Expectedinflation
is measured with a three-year distributed lag on the actual rate of
inflation.The regressionsexplainannualizedquarterlypercentagechanges
in the average hourly earnings index (HEI) for the private nonfarm
economy. We use changes in quarterlyaveragesof unadjustedmonthly
Wayne Vroomanand John M. Abowvd
315
HEI data to have availablea full rangeof comparabledata for the nine
industrialdivisions thatunderliethe aggregateindex. Because we do not
use seasonally adjusted data, we include additive quarterlydummy
variablesin each regressionto controlfor seasonality.
Two specificationissues are important:the unemploymentvariable
and the variable to test for effects of internationaltrade on wages.
Because the demographicmix of unemploymenthas changed since the
1960s and 1970s, the choice of the cyclical control variable strongly
influencesthe performanceof the regressions.Associated with the high
overallunemploymentof the 1980shas been a largecomponentof longterm unemploymentand of unusuallyhigh adult male unemployment.
In every yearbetween 1981and 1987the numberof workersunemployed
27 weeks or longer exceeded 1 million, and the share of those workers
in total unemploymentwas at least 14 percent. Between 1948and 1979
long-termunemploymentsharesof 14percentor higheroccurredinjust
seven other years: 1958, 1959, 1961, 1962, 1975, 1976, and 1977. The
exceptionally high adult male unemploymentrate may be due to the
increased pace of U.S. industrialrestructuringand increased foreign
trade competitionas well as to the persistentlyhigh overall unemployment of the decade. In 1987, when the overall unemploymentrate was
6.2 percent, the unemploymentratefor men aged 25-54 was 5.0 percent,
or0.81of the overallrate.In 1976,anearlieryearwhentheunemployment
ratefor menaged25-54 was 5.0 percent,the overallratewas 7.7 percent.
Figure 1 illustratesthis relative change in adult male unemploymentof
the 1980s.The relativeunemploymentratefor men aged 25-54 averaged
0.79 between 1980and 1987,but 0.59 in the 1970s.
The change in the structureof relative unemploymentrates makes
the choice of which unemploymentrate series to use in the regressions
particularlyimportant.' We use both the overallunemploymentrateand
the rate for men aged 25 to 54. Equationsbased on the unemployment
ratefor adultmen predictlower wage growthfor the 1980s.
Given the long-run trend toward increased openness of the U.S.
1. The importance of changes in the demographic structure of unemployment and its
implications for labor market inflation were first emphasized by George L. Perry,
"Changing Labor Markets and Inflation, " BPEA, 3:1970, pp. 411-41. For a recent analysis
of demographic changes in the unemployment of the 1980s, see Lawrence H. Summers,
"Why Is the Unemployment Rate So Very High near Full Employment?" BPEA, 2:1986,
pp. 339-83.
316
Brookings Papers on Economic Activity, 1:1988
Figure 1. Ratio of Unemployment Rates for Men Aged 25-54 to the Civilian
Unemployment Rate, 1953:1-1987:4
Ratio
0.9
-
0.8
0.7
0.6-
0.5-
0.4
I
-
1955
1960
1965
I
I
1970
I
I
I
1975
I
1980
I
I
1
F
1985
Source: Eniplovy,etit and Earnings,variousissues.
economy and the persistence of large U.S. merchandisetrade deficits
since 1984, we test for the effect of foreign trade on domestic wage
growth, using both price variables and trade flow variables.2 Price
variablesinclude changes in importprices and changes in nominaland
real exchangerates.3Tradeflow variablesincludeimportsas a share of
GDP or of sales, as well as export sharesand net export shares. We find
that importprice inflationexhibits consistently small but significantly
2. John M. Abowd codirected a recent large-scale project at the National Bureau of
Economic Research that assessed the effects on the labor market of international trade
and immigration. In a later section of this paper we use international trade data and
equation specifications drawn partly from that project in a microeconomic analysis of
union wage settlements in manufacturing. See John Abowd and Richard Freeman, "The
Internationalization of the U.S. Labor Market" (National Bureau of Economic Research,
March 1987).
3. Rudiger Dornbusch and Stanley Fischer, "The Open Economy: Implications for
Monetary Policy and Fiscal Policy," Working Paper 1422 (NBER, August 1984); Robert
J. Gordon, "U.S. Inflation, Labor's Share and the Natural Rate of Unemployment,"
paper presented at International Seminar on Recent Developments in Wage Determination,
Mannheim, Germany (October 5-6, 1987).
Wayne Vroman and John M. Abowd
317
positiveeffects on the growthin privatenonfarmhourlyearnings.Import
price inflationnet of petroleumand petroleumproductshas coefficients
rangingfrom 0.08 to 0.14 in aggregateequations. Expected negative
effects of changes in the trade-weightedreal or nominal U.S. dollar
exchange rate are not significant.Also insignificantare the potential
positive effects of the export share and the net export share (as a
percentageof real GDP) and an expected negative effect of the import
share. As will be reported later, import shares are significantin an
analysis of microeconomicdata from manufacturing.We attributethe
contrast in results to the greaterrange of variationof import shares in
the microeconomicdata.
Table 2 shows a set of six regressionresults and equationprojections
for 1980-87. Price inflationis measuredwith the consumerprice index,
entered as a twelve-quarterdistributedAlmon lag startingwith a onequarterlag. Importprice inflation,measuredwith a fixed-weightindex
of nonpetroleumimportpricesfromthe nationalincomeaccounts, enters
as an Almon variable with a four-quarterlag. The data period for all
regressionsbegins in 1964:2and ends in either 1979:4or 1987:4.
The first two equationsin table 2 show the importanceof the choice
of unemploymentmeasure. In augmentedPhillipscurves fittedthrough
1979:4,unemploymentandlaggedinflationare both significant,with the
inflationrate the more significantof the two. Equation2, which uses the
unemploymentrate for men aged 25-54, fits somewhat better over the
sampleperiodand makes much moreaccuratewage growthprojections
for 1980-87. The average overprediction errors over the eight-year
projectionperiodare, respectively, 1.50percentand0.49 percent.When
import price inflationis added, in equation 3, the average eight-year
projectionerror drops to 0.02 percent. The addition of import prices
causes the equationto make lower wage growthprojectionsfrom 1981
through1985.As the averageprojectionerrorsin table 2 show, the use
of the unemploymentratefor men 25-54 causes abouttwo-thirdsof the
difference between the projections made by equations 1 and 3 in the
1980s.4
4. A similardecompositionbetween the averageerrorsfrom equations 1 and 3 was
obtainedwhen importprice inflationwas addedto equation 1. In a regressionthat used
importprice inflationand the unemploymentrate for persons aged 16 and older, the
averageoverpredictionerrorsfor 1980-87and 1984-87were, respectively,0.88 percent
and 1.11percent.Thusunderbothpossibledecompositions,the use of the unemployment
rate for men aged 25-54 made a largercontributionthan importprice inflationto the
superiorperformanceof the projectionsfromequation3 comparedwithequation1.
Brookings Papers on Economic Activity, 1:1988
318
Table 2. Regressions Explaining the Growth in the Hourly Earnings Index,
1964:2-1979:4 and 1964:2-1987:4a
Eqluation
Independent
variable
Constant
(1)
4.95
(11.2)
.. .
4.93
(10.8)
...
Laggedimportpricec
0.81
(7.1)
...
-0.81
(4.2)
0.81
(9.1)
...
- 0.89
(4.0)
0.74
(8.6)
0.11
(3.0)
Predictionerror
(actualminus predicted)
1980
1981
1982
1983
1984
0.70
2.17
1.65
1.02
1.87
- 0.06
- 1.59
- 0.28
0.50
- 0.91
Civilianunemployment
rate
Unemploymentrate,
men aged 25-54
Lagged CPIb
5.65
(8.6)
- 0.59
(3.3)
...
1964.2-1979:4
(2)
(3)
1964.2-1987:4
(4)
(5)
(6)
6.87
(12.1)
- 0.89
(7.6)
...
5.26
(15.0)
4.91
(14.5)
.
...
0.87
(13.7)
...
- 0.85
(9.9)
0.79
(16.9)
...
- 0.83
(10.4)
0.75
(16.2)
0.10
(3.6)
0.50
- 0.69
0.50
0.99
- 0.29
- 0.22
- 1.56
- 0.28
0.51
- 0.90
0.26
- 1.26
0.12
0.85
- 0.70
0.38
-0.84
0.24
0.76
-0.44
1985
1986
1987
- 1.33
- 1.71
- 1.56
-0.41
-0.66
-0.48
0.60
- 0.68
- 0.80
- 0.42
- 0.82
-0.92
- 0.22
- 0.48
- 0.32
0.39
-0.73
-0.79
1980-87
1984-87
-1.50
-1.61
-0.49
- 0.62
0.02
- 0.29
-0.58
-0.76
- 0.22
- 0.43
-0.13
-0.39
0.68
0.97
1.77
0.73
0.89
2.02
Summarystatistic
R2
Standarderror
Durbin-Watson
0.65
1.02
1.65
0.75
1.14
1.33
0.80
1.01
1.68
0.83
0.94
1.85
Source: Authors' calculations based on data from the Bureau of Labor Statistics and the National Income and
Product Accounts.
a. The dependent variable measures the annualized quarterly percent change in the average hourly earnings index.
Data are not seasonally adjusted, and each regression includes quarterly seasonal dummies. Numbers in parentheses
are t-statistics.
b. Lagged one quarter. The variable enters as an Almon variable with a 12-quarter distributed lag.
c. Fixed-weight index of nonpetroleum import prices. The variable enters as an Almon variable with a four-quarter
lag.
Equations 4-6 apply the specificationsof equations 1-3 to the full
period 1964:2through1987:4.Equations5 and 6 are similarto equations
2 and 3 in both their coefficients and average projection errors. In
equation 4 the average projection errors of the 1980s are reduced,
comparedwith those of equation 1, because these later observations
help to determine the estimated coefficients. Although the average
Waynie Vroman and John M. Abowd
319
residualsin the 1980s are generally smallerin equations 4-6, the rank
orderingacrossthe threeequationsis generallypreserved-that is, those
from equation4 are the largest. All equations overpredictin 1986 and
1987.Importprice inflationof these years adds to the overpredictions.
Wage Adjustments in Broad Industrial Divisions
As a check on ouraggregatewage changeequations,we next conduct
disaggregatedanalysis on the nine broadindustrialdivisions that make
up the hourlyearningsindex. As table 3 shows, the divisions have wide
variationin the demographicmix of employment,the degreeof openness
to internationaltrade, and the extent of unionization.
In general,the industrialdivisionsin whichmenaged25-54 constitute
a large share of total employmentare also comparativelyopen to trade
and have above-averageunionization.Miningand durablemanufacturing, for example, rankhigh on all three dimensions, while retail trade,
finance, and services rank low on all three. The other four industry
divisions are more mixed, with the two biggest exceptions being wholesale trade,whichhas moreadultmaleemployeesthanmightbe expected,
and construction,which is less open to internationaltradethanmightbe
expected.
Because demographic mix, openness to internationaltrade, and
unionizationhave common patternsacross broad industrialdivisions,
an analysis of wage dynamics at this level of disaggregationis less
revealingthan might be expected. In a longer, unpublishedversion of
this paper, we report wage growth regression results for the nine
industriesusing the same specificationas in the aggregateanalysis of
table 2. While interestingin several respects, the results for the nonpetroleum import price inflation variable were not consistent across
industrialdivisions. Specifically, wage growth in wholesale and retail
trade showed more sensitivity to internationaltradethan was plausible
giventhese industries'tenuousconnectionto the internationaleconomy.
To help isolate the separate effects of demographics,international
trade, and unionwage developments,we conduct two additionalanalyses. First, we examineunionwage adjustmentsfromthe manufacturing
sector, using detailed internationaltrade data by industry to explore
bothtradeanddemographiceffects on unionwage adjustments.Second,
we examinemajorcollective bargainingagreementsin the 1980s.
Brookings Papers on Economic Activity, 1:1988
320
Table 3. Demographic, International Trade, and Unionization Characteristics of Major
Industrial Divisions
Expor-t
employinent share
gained,
Import employment
shar-e lost,
Industry
Employment share
of men aged
25-54,
1980
1984a
1984b
Union r-epresentation
share,
1987
Mining
Construction
Durable manufacturing
Nondurable manufacturing
Transportation and utilities
0.606
0.604
0.505
0.400
0.546
0.245
0.016
0.154
0.093
0.101
0.460
0.022
0.254
0.251
0.076
0.195
0.222
0.263
0.224
0.362
Wholesale trade
Retail trade
Finance
Services
0.481
0.243
0.286
0.253
0.060c
0.060c
0.026
0.025
0.014c
0.014c
0.027
0.023
0.091
0.074
0.032
0.076
All industries
0.372
0.065
0.078
0.146
Sources: Employment shares for men aged 25-54 taken from U.S. Bureau of the Census, Censuis of Popiulation
1980, Detailed Populationi Characteristics, U.S. Surnmnary,Sec. A: United States (Government Printing Office, 1980).
Export employment shares taken from Kan Young, Ann Lawson, and Jennifer Duncan, "Trade Ripples Across U.S.
Industries" (U.S. Department of Commerce, January 1986), tables 3A, 3B, and appendix table 4B. Union representation
data from Employmenit anid Earnings, vol. 35 (January 1988).
a. Share of industry's total employment gained from export activity.
b. Share of industry's total employment lost due to import activity.
c. Average shares for wholesale trade and retail trade combined.
Major ManufacturingSettlements
In this section we disaggregatefurtherand examine data from major
manufacturingcollective bargainingagreementsbetween January1959
andDecember 1984.Ourgoal is to quantifythe determinantsof nominal
wages at the bargainingunit level. Using the estimatedwage settlement
equation, we show that settlements from 1980 through 1984 were
predicted well by the same determinantsthat explained wages in the
precedingtwo decades.
We also examinethe extent to which wage settlementsare influenced
by changing import and export competition in the industry. Because
manufacturingindustriesdifferin theirsensitivityto importcompetition,
we simulatedour estimated equationfor each majorindustrygroup to
study the effects of a permanentincrease in the rate of importson wage
settlements.
The dependentvariableis the annualizedrate of wage growth over
the life of the collective bargainingagreement.This rate includes wage
changeseffective on the dayof settlement,scheduleddeferredincreases,
Wayne Vromanand John M. Abowd
321
and realizedcontingentcost-of-livingadjustments(COLAs). The wage
settlementsare datedfromthe beginningof the new contractso that, for
example, the wage growth dated 1984covers 1984-86 for a three-year
collective bargain.
We considerthree distincttypes of explanatoryvariablesin the wage
settlement equations-aggregate labor market conditions, aggregate
price inflationexpectationsand realizations,and industry-levelproduct
marketconditions. We discuss each below.
The labormarketcontrols are the adultmale unemploymentrate the
monthbefore settlement, the change in that rate since the last contract
settlement(annualized),and the most recent wage settlement in either
the automobileor steel industry(annualrate).The adultmaleunemploymentrateis most naturallyviewed as anindicatorof the generaltightness
of the labor market. One expects the current wage settlement to be
inversely related to the unemploymentrate. The most recent nominal
wage settlement in the automobile or steel industry is a well-known
leadingindicatorof the new wage settlementsin general.If it is providing
informationthataugmentsthe informationintheprevailingpriceinflation
expectations, it shouldbe positively relatedto wage settlements.
We use two differentmeasuresof the expected inflationrate. The first
is based on the predictedannualrateof changein the CPIas determined
by the most recent annual rate of change and two annual lags. The
expected inflationrate is calculatedfromthe regression:
(1) ln CPI(t + 12) - In CPI(t)
= 0.913 + 0.855 [ln CPI(t) - ln CPI(t - 12)]
(4.847) (19.516)
- 0.375 [ln CPI(t - 12) - ln CPI(t - 24)]
(7.329)
+ 0.307 [ln CPI(t - 24) - ln CPI(t - 36)]
(7.994)
Period:January1950-July1986;K2 = 0.58; Durbin-Watson= 0.085.
Since we require a forecast of the annual inflation rate based upon
inflationduringthe previous contract, this specificationis the natural
extensionof the distributedlag specificationswe fit to the quarterlydata
for the aggregateequations. The CPI-basedexpected inflationrate is
322
Brookings Papers on Economic Activity, 1:1988
calculatedas the predictedannualinflationrate from this regressionin
the month before the contract was settled. The CPI-based inflation
surpriseis calculatedas the realized inflationrate duringthe life of the
contract (annualrate) minus the CPI-basedexpected inflationrate the
monthbefore the contractwas settled.
Our second measureof expected inflation,the Livingstonexpected
inflationrate, is the consensus expected annualinflationrate from the
Livingstonsurveyjust priorto the contractsettlement.5The Livingston
inflationsurpriseis calculatedas the realized inflationduringthe life of
the contract (annualrate) minus the Livingstonexpected inflationrate
the month before the contract was settled. We also considered an
expected inflationrate and inflation surprise based on the Survey of
Consumer Finances, but the results did not differ substantiallyfrom
those obtainedwith the other two measuresand are not reportedhere.
The inflationsurpriseover the life of the currentcontractis relevant
only for contracts that contain a contingentCOLA clause. Because of
the effects of triggers(minimumchangesin the CPIrequiredto produce
an adjustment),such clauses typically increase realized wages more
when the inflationsurpriseis positive. For this reason we allowed the
inflationsurpriseto enter separatelyfor positive and negativesurprises.
Only the positive inflationsurprises over the life of the contract had
consistently large effects. The inflation surprise affects wage growth
more in contractsthat do not cap the COLA formulathan in contracts
that cap the cost-of-livingadjustmentat a specified amountregardless
of the level of inflation.For this reason we estimate the effects of the
inflationsurpriseseparatelyfor cappedanduncappedCOLAcontracts,
and we suppressthe currentinflationsurprisefor contractsthat do not
includea COLA.
The effects of laggedinflationsurprisesarecalled "catch-up"effects.
Wagecatch-upoccurs when the previouswage settlementwas based on
an inflationexpectationthat turnedout to be substantiallyin error.This
erroris measuredby the laggedinflationsurprise(the differencebetween
the realized inflationrate over the life of the previous contract and the
inflationrate expectation the month before that contract was settled).
5. The Livingstonsurvey, conductedby J. A. Livingstoneach June and December,
surveys6d economistsfrombanking,labor,government,anduniversitiesregardingtheir
predictionsfor variousleadingeconomicindicators.Surveyresultsare maintainedby the
PhiladelphiaFederalReserveBank, Departmentof Research.
WayneVromanand John M. Abowd
323
The effects of catch-upare symmetric,so no distinctionis requiredfor
positive and negative surprises. However, catch-up should be a less
importantphenomenonfor contractswith uncappedCOLAclauses. We
estimate separate catch-up terms for the cases in which the previous
contractcontainedno COLA,anuncappedCOLA,anda cappedCOLA.
Finally, we consider two types of productmarketcontrols. The first
is the annualrate of change in industryprices as measuredby the value
of productshipmentsdeflatorfrom the AnnualSurvey of Manufactures
(ASM). The second productmarketmeasureis a decompositionof the
ASM value of shipments into the weighted sum of the annual rate of
changein apparentdomestic consumption(D), definedas shipments(S)
plus imports(M)minusexports(X);the annualrateof changein exports;
and the absolute change in IPR, the importpenetrationratio (100 times
importsdividedby apparentdomesticconsumption).Thedecomposition
of productshipmentsis given by:
dlnS - (
X)dlnD
+ -dlnX-
-dIPR,
andall changeshave been multipliedby 100.This decompositionallows
us to measurethe effects of increasedimportand export activity in the
productmarketholdingconstanttotal apparentdomesticconsumption.6
In particular,if the absolutevalue of the effect of the importpenetration
ratio on wage settlements exceeds the absolute value of the effect of
apparentdomestic consumption,then importcompetitionhas a greater
effect on wage settlementsthanjust the effect impliedby the reduction
in domesticoutputthataccompaniesan increasein the IPR withindustry
prices and domestic consumptionheld constant.
To complete our dynamicspecification,we also include the nominal
wage settlementfromthepreviouscontractandthe annualrateof change
of bargainingunit employmentover the life of the previous contractas
controlvariablesin our estimatedequation.7
Table4 comparesalternativespecificationsof the dynamicmodel for
6. This decompositionis discussed and used in RichardB. Freemanand Lawrence
Katz,"WagesandEmploymentinanOpenEconomy,"preparedfortheNBERconference
on Immigration,Trade,andLaborMarkets(September1987).
7. John M. Abowd and Thomas Lemieux, "The Effects of InternationalTrade on
Collective BargainingAgreements:Evidence from Canada," preparedfor the NBER
Conferenceon Immigration,Trade,and LaborMarkets(revisedJanuary1988).
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326
Brookings Papers on Economic Activity, 1:1988
wage settlementsestimatedfor 1959-84. Columns1-4 reportregression
coefficientsand theirassociated t-statistics, with columns 1-3 using the
CPI-basedmeasure of expected inflationand column 4 using the Livingstonexpected measure.
The first question of interest is the extent to which the period from
1980 through 1984 represents a break from the structure of wage
determinationin the previous two decades. Column 1 reports the
regression estimates of the dynamic wage settlement equation from a
specificationthat includes year effects (dummies)for each year from
1980 to 1984. These year effects show that the equation overpredicts
wage settlements in four of the five years, althoughonly the 1980and
1981overpredictionsare statisticallysignificant.The relevant standard
for interpretingthese year effects as forecast errorsis the standarderror
of the equation, which is 2.028; hence, none of the errorsin the 1980s
exceeds one-halfof the standarderrorof the equation. Althoughoverprediction 4i 1980 is large, it is about the same as overpredictionsin
1960, 1969, 1970,and 1971.The errorsin 1981-84are aboutthe same as
those of the previousdecades. The equationwiththe Livingstonmeasure
of expected inflationreaches a similarconclusion.
Figure2 breaksthe predictedwage settlements into five key components. Not shownis a sixth component,averageannualeffect of changes
in industryconditionsincludingimports,discussed below, that contributes an average of 88 basis points a year and explains about 50 basis
points of the decline in the 1980s. The figure shows that from 1980
through1984nominalwage settlementsdeclinedabout600basis points.
Of thattotal the decline in expected inflationcontributedabout200basis
points; the decline in key settlements in the automobile and steel
industriescontributedanother 200 basis points; positive inflationsurprises contributednothing;catch-up(laggedinflationsurprises)contributed about 100 basis points; and the level and change in adult male
unemploymentcontributedabout 50 basis points.
The next questionof interestis the extent to which the decomposition
of the aggregatefactors affectingthe wage settlementsis sensitive to the
choice of expected inflationrate measureor the use of the key auto and
steel settlement variable. Table 4 reports results in column 4 for the
Livingstonexpected inflationrate measure. The equationbased on the
Livingston expected inflationrate fits the data slightly better than the
equationbased on the CPI expected inflationrate (column2). The only
Wayne Vroman and John M. Abowd
327
Figure 2. Components of Predicted Wage Settlement, 1959-84
Percent
12-
10
Predicted wage
settlement
8 -
6-
42 ->
0-
A
-2 -
I
1960
1965
1970
1975
1980
Key to components
+ Key auto and steel settlements.
O Expected inflation rate.
* Positive inflation surprise in current contract.
x Total inflation surprise in previous contract.
V Adult male unemployment rate and its change since previous contract.
Source: Authors' estimates based on equation 2 (using CPI-based expected inflation) of table 4.
estimated effects that are materiallydifferent are the lagged inflation
surpriseterms. Withthe CPI-basedmeasure,the estimatedcatch-upfor
contractswith no COLA is smallerthanthe catch-upfor capped COLA
contracts.Withthe Livingstonmeasure,thereis no significantdifference
between the no-COLAand the capped-COLAcatch-upestimatedelasticities.
Columns2 and 3 of table 4 provide comparableestimates with and
withoutthe key settlementsvariable.The expected inflationrateelasticity in column3 aboutequals the sum of the key settlementand expected
inflationelasticities in column2. The positive inflationsurpriseelasticities in column 4 are greater than those in column 2, and the catch-up
effects are also slightlylarger.The effects of the level and change in the
adultmaleunemploymentratearealso largerin column3 thanin column
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Wayne Vroman and John M. Abowd
329
2. However, the equationin column 3 fits the data substantiallyworse
than that in column2. (The F-statisticfor the significanceof the change
in R2 is 234.46, which is the squareof the t-statisticon key settlements
in column2.)
The final question of interest is the extent to which changes in the
productmarkets,particularlychanges relatedto importactivity, affect
wage settlements. As noted above, the cumulative contributionof all
product marketfactors to the decline in wage settlements duringthe
early 1980swas about50 basis points. This estimatemasksconsiderable
heterogeneityamong industrygroups. As is clear from the estimated
effect of changesin importpenetrationon nominalwage settlementsfor
all of the models in table 4, the coefficient is six times greaterthan the
coefficient on the change in apparentdomestic consumption. In other
words, the effect of importpenetrationon nominalwage settlementsis
approximatelysix times greater than one would predict from the lost
domestic outputalone.
Table 5, which shows the effects on wage settlements of increasing
imports,reportsthe resultsof simulatingthe equationin table4, column
3, separatelyfor 20 two-digit StandardIndustrialClassification(SIC)
code industries.Each settlementis firstsimulatedto approximatesteady
state, using the 1984 values of expected inflation, unemployment,
changes in the nominalwage over the previous contract, and change in
employment over the previous contract. The 1984 positive inflation
surprises,laggedinflationsurprises,andchangein adultmaleunemployment are enteredas initialconditions, then zeroed to obtain the steady
state. Finally, the 10-year industry average annual growth rates for
prices, shipments,exports, and importsare used to generatethe simulation values for the change in industry prices, apparent domestic
consumption,exports, and the importpenetrationratio. We simulated
the transportationequipmentindustryfirstandused laggedvalues of the
predictedsettlements in this industryas the key settlementvariablein
the steady-statesimulation.
Once the industryis in steady state (approximately10 years into the
simulation),the rate of growthof importsis permanentlyincreased by
one standarddeviationfor each industry.The table reportsthe resulting
differencesin predictedwage settlements in that industryfor the first,
sixth, and eleventh years following this change. The simulationholds
constantthe growthrate of industryprices, shipments,and exports, so
330
Brookings Papers on Economic Activity, 1:1988
thereis no changein the rateof growthof real domesticproduction.The
entirechangeis in the rate of growthof apparentdomestic consumption
and in the import penetration ratio. The simulated wage settlement
effects, then, may be interpretedas the net effects of increasedforeign
productmarketshareholdingconstantthe rateof growthof realdomestic
shipments.
Wage increases in all industriesare slowed by the increasedgrowth
of imports.The leatherproducts,primarymetals, andapparelindustries
have the largestpredictedeffects in the firstyear of the simulation.The
largest long-term effects occurred in the tobacco products, lumber
products,and primarymetals industries.
The results using microeconomicdata contrast with the aggregate
results mentioned earlier. With microeconomic data the effect of expected inflationis only 0.54 when the key settlementsvariableis omitted,
rangingup to 0.61 if one thinks that expected inflationis measuredby
addingits own coefficient and the coefficient on key settlements when
they are entered together. By comparison, the elasticities from the
macroeconomicresults in table 2 range from 0.74 to 0.87. The larger
expected inflationcoefficientsin table 2 probablymean that these price
terms are incorporatingcatch-up as well as expectational effects on
nominalwageadjustments.Theeffects of unemploymentarealso smaller
in the microeconomicdata where both level and rate-of-changeeffects
are identified.Together, their coefficients imply that it is lagged unemploymentthataffectscurrentwage settlements.Separateproductmarket
and labor marketeffects on wage settlementsare successfully isolated
in the microeconomicdata. In both the microeconomicand macroeconomic data, the effects of internationaltradeappearto operatethrough
imports but not exports and to moderate wage inflationin the 1980s.
Aggregatedatashow thatwages are affectedby importprices. Disaggregated data show wages affectedby the importpenetrationratio.
Union Wage Settlements
Duringthe 1980swage growth has slowed more in union bargaining
situations than elsewhere in the private sector. Possible explanations
include changes in unemploymentdemographics,internationaltrade,
andothercompetitivefactors. In tradedgoods industriesin which union
workers are paid more per hour than nonunion workers, increased
Wayne Vroman and John M. Abowd
331
Table 6. Average Annual Rates of Wage Growth, Selected Periods, 1964-87a
Percent per year
Hourly earningsindex
Period
High-union
industriesc
1964-69
1970-75
1976-82
1983-87
5.1
7.6
8.1
2.5
Low-union
industriesd
5.7
6.7
7.7
3.0
Employmentcost indexb
Union
workers
n.a.
n.a.
8.6
2.8
Major
Nonunion
workers
union
agreements
n.a.
n.a.
7.4
4.0
n.a.
8.3
8.5
3.3
Source: Based on data from Currett Wage Developmetnts, various issues.
n.a. Not available.
a. December to December rates of growth.
b. Indexes for wages and salaries.
c. Weighted average of hourly earnings indexes for mining, construction, manufacturing, and transportation and
utilities based on each industry's percentage of hours in 1967.
d. Weighted average of hourly earnings indexes for wholesale, retail, finance, and services.
importcompetitioncould have adverseeffects on both employmentand
wages for union workers. This section examines overall union wages
and employment with attention to developments in the 1980s. Before
discussingthe 1980s,however, we brieflyreview earlierunion-nonunion
wage trends.
Because comprehensivetime series data distinguishingunion from
nonunion wage growth became available only with the advent of the
employment cost index in 1975, inferences for earlier periods must
compare hourly earnings growth in industries with high unionization
rates with that in industrieswith low unionizationrates. In an examination of the growth in average hourly earningsamong private nonfarm
three-digitindustriesbetween 1953and 1976, Dan Mitchellfound that
hourly earningsin highly unionized industriesgrew more rapidlythan
those in low-unionizationindustriesbetween 1953and 1958and again
between 1971 and 1976.8 During 1971-76 the wage growth differential
favored high-unionindustriesby about 1 percentagepoint a year. By
contrast, between 1964and 1968,hourlyearningsgrew more rapidlyin
industrieswith low unionizationrates.
Table6, whichshows averageannualratesof wagegrowthfor selected
periods for three wage series, confirmsMitchell's findings.The hourly
earningsindex data show that wages grew more rapidlyin low-union
industriesin the late 1960sand againduring1983-87,while the converse
held during 1970-75 and 1976-82. Over the entire 1964-87 period,
8. See DanielJ. B. Mitchell, Unions, Wages, and Inflation(Brookings,1980),chap.
2, pp. 23-61.
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Wayne Vroman and John M. Abowd
333
however, averageannualwage growthwas aboutthe same (5.7 percent)
in low- and high-unionindustries.The explicit union-nonunioncomparison using employment cost index data shows a 1 percentage point
differentialin favor of union workers during 1976-82 (8.4 percent, as
against7.4 percent), but then a 1 percentagepoint lower rate of union
wage growth during 1983-87 (3.3 percent, as against 4.3 percent). The
wage deceleration since 1983 has been 2 percentage points larger for
union workers than for nonunion workers (5.1 points, as against 3.1
points). Table 6 also shows the similarityof union wage increases in the
employmentcost index and the effective wage changes in majorunion
agreements(those affecting 1,000 or more workers). The simple correlation of the two annualwage change series from 1976to 1987is 0.990.
Workerscovered by majoragreementsconstitute more than half of
all union workers in the private nonfarmeconomy. Althoughthe ECI
has wage changedatafor all unionworkers,the majorunionagreements
data have some importantadvantagesfor present purposes. They go
back to 1968for all privateindustriesand includedetail not availablein
the ECI data:effective wage changes brokendown by source (currentyear negotiationsor first-yearincreases, deferredincreases from prior
settlements,andcost-of-livingincreases),the numberof workersreceiving each type of wage change, and the coverage of COLAclauses.
Table 7 summarizesinformationon employmentand effective wage
changes in majoragreementssince 1968. One importantfeature of the
datais the declinein the numberof workerscoveredby these agreements,
as shown in column 1-from 10.8millionworkersin 1968,to 9.7 million
in 1977, to only 6.3 million in 1987. Employment covered by major
agreementsfell from 19.3percentto 7.4 percentof privatenonfarmwage
and salary employment during these 20 years. The decline in the
employmentshareparallelsthe generaldecline in privatesector unionization. For 1973-81 and 1983-87, the years when comparisons with
CurrentPopulationSurvey (CPS)-based unionizationestimates can be
made, the two series move almost identically. The major settlements
employment shares of column 2 averaged 62.8 percent of the CPS
unionizationrate estimates, and theirtime series correlationwas 0.973.
About 85 percent of workers covered by majoragreementswork in
the highly unionized mining, construction, manufacturing,and transportationandutilitiesindustries,industrieswhose shareof privatewage
and salaryemploymentshrankfrom50.0 percentin 1968to 35.6 percent
334
Brookings Papers on Economic Activity, 1:1988
in 1987.The changingmix of employmentby industrythus also affects
the majoragreementsemploymentshare in column 2. Column3, however, shows thatthe shareof employmentcovered by majoragreements
in the highly unionized industries declined from 34.3 percent to 17.0
percentbetween 1968and 1987.Because majoragreementsemployment
has declined relativeto total employmentin all privateindustries,most
of the decline in the shareof overallemploymentshown in column2 has
been due to developments within industriesand not to changes in the
industrymix of employment.The employmentpercentagein column 2
for 1987 would have been 9.5 percent, rather than 7.4 percent, if the
highlyunionizedindustrieshad retainedtheir 1968shareof total private
nonfarmemployment.
The first three columns of table 7 suggest that the decline in major
agreementsemploymentwas morerapidin the late 1970sand 1980sthan
in earlier years. The explanationfor the decrease in the employment
base for majoragreements,and for privatesector union employmentin
general,includesregionalemploymentrelocationtowardless unionized
states in the Sun Belt; changes in the industrialrelations practices of
employers, particularlylargeemployers, towardunions;reducedunion
organizingactivity and lower success rate in representationelections;
changesin workerattitudestowardunions;deregulationin the transportationandcommunicationindustries;andincreasedimportcompetition.9
The increase in the union wage premium implied by the union and
nonunionwage growthtrendsduring1970-82probablygave employers
increasedfinancialincentives to use nonunionworkers. Table 7 shows
that even after the economy emergedfrom the 1981-82 recession, the
employmentbase for the majoragreementscontinuedto decline, from
7.9 millionworkersin 1983to 6.3 millionin 1987.
To explain the decline in employmentcovered by majoragreements
we fittime seriesandcross-sectionregressions.Bothregressionanalyses
include controls for the effects of internationaltrade. Time series
variationin the major agreementsemployment percentage within the
highly unionized industries(P), column 3 of table 7, is explained with
9. For analysesof the decline in privatesector unionization,see WilliamT. Dickens
and JonathanS. Leonard, "Accountingfor the Decline in Union Membership,19501980,"Industrial andLaborRelations Review, vol. 38 (April1985),pp. 323-34;andHenry
S. Farber,"TheDeclineof Unionizationin the UnitedStates:WhatCanBe Learnedfrom
RecentExperience?"WorkingPaper2267(NBER, May 1987).
WayneVromanand John M. Abowd
335
regressionsthat also include controls for the business cycle (URM, the
unemploymient
ratefor menaged25-54), the regionalmixof employment
in these industries(EMIX, employmentin the Northeast and Midwest
as a percentageof nationalemployment),anda controlforthe accelerated
downward trend that started in 1976 (T76). The internationaltrade
variable in the time series analysis is real imports measured as a
percentage of real GDP(RMS). The regression shown below, with
t-statistics in parentheses, explains 99.1 percent of variation in the
employmentpercentageduring1968-87.
P = 6.41 + 0.564 URM + 0.598 EMIX - 0.540 776 - 0.991 RMS
(0.7)
(3.8)
R2 =
(4.7)
(6.2)
(4.9)
0.991;standarderror = 0.51; Durbin-Watson= 1.45.
All four explanatoryvariablesare statistically significant.In recessions, majoragreementsemploymentdeclines more slowly than overall
employmentin the highlyunionizedindustries,perhapsbecauseworkers
are still covered by the agreementseven if they are not all employed.
The downwardtrend in the majorsettlements employmentpercentage
is explained by regionalemploymentmix, the trend accelerationafter
1976,andgrowthin the real importshare. Because the real importshare
grew from 7.9 percent of real GDP in 1968to 14.8 percent in 1987, the
equation implies that growth in internationaltrade accounted for 41
percent of the total decline in the majoragreementsemploymentpercentage.
The cross-section analysis examines the change in the majoragreements employmentsharebetween 1978and 1987at the level of two-digit
SIC industries. For 36 private nonfarm industries in which major
agreementscovered at least 5 percent of industryemploymentin 1978,
themajoragreementsemploymentsharewas lowerin allbutone industry
(SIC 24, lumber)in 1987.To explainthe decline, we fit regressionsthat
include the level or the change in import-relatedemployment losses
between 1977 and 1984.10Also included are controls for industry employmentgrowthand a dummyvariablefor three industrieswith major
10. Kan Young, Ann Lawson, and JenniferDuncan, "Trade Ripples Across U.S.
Industries"(U.S. Departmentof Commerce,January1986).
336
Brookings Papers on Economic Activity, 1:1988
regulatorychanges (trucking,airlines, and communications).Employment growth and deregulationdo not add significantlyto explained
variationin this analysis. The simpleregressionsthat use, respectively,
the average level and the change in import-relatedemploymentlosses
are as follows:
DP = -33.86
(88.3)
K2
DP
0.30 A VIMP
(2.0)
= 0.081;standarderror = 18.31,
=
-36.42
(10. I)
K2
-
- 0.324 DIMP
(1 .7)
= 0.048;standarderror = 18.65.
In the regressionsthe variablesare measuredas follows:
DP = the percentage change between 1978 and 1987 in major
agreements employment as a percent of total industry
employment
MEL77 = employmentlosses due to importsin 1977measuredas a
percentof domestic employmentin the industryin 1977
MEL84 = employmentlosses due to importsin 1984measuredas a
percentof domestic employmentin the industryin 1984
AVIMP = average employment loss due to imports between 1977
and 1984 = (MEL77 + MEL84)/2
DIMP = difference in employment loss due to imports between
1977 and 1984 = MEL84 - MEL77.
The cross-sectionregressionsallowfor changesin importpenetration
by industryin ways not permittedin a more aggregateanalysis. Both
import variables have negative coefficients as expected, but note the
size and significance of the intercepts. The regressions suggest that
import penetration accounted for 10-20 percent of the employment
losses between 1978and 1987experiencedby workerscovered by major
agreements. Taken together the time series and cross-section results
implythat internationaltradehas contributedto the employmentlosses
in majoragreements,but that other factors combinedhave had quantitatively largereffects.
The steady decline in membershipand in the size of bargainingunits
has undoubtedlyinfluencedunion objectives in collective bargaining.
Wayne Vrornan and John M. Abowd
337
Greaterjobsecurityhas become such an importantobjectivein the 1980s
thatunionshave been willingto tradeaway wage increasesto get it. The
1980shave seen the spreadof so-calledconcession bargainswhose wage
provisions include freezes and reductions, an increased prevalence of
lump sum payments, and two-tier pay arrangements.Coincidentwith
these changesin contractualwageprovisionshave been sharpreductions
in work stoppages.
Table7 displays selected indicatorsof increasedunion willingnessto
forgo wage increases in recent years. All three componentsof effective
wage increases(columns5, 6, and7) declined sharplybetween 1981and
1983and remainedlow through1987.From 1983through1987the total
annualeffective wage change was below 4 percent, and first-yearand
COLA increases remainedbelow 1 percent a year. Columns 8 and 9
show thatunionwillingnessto accept wage freezes andwage reductions
increased sharplyduring1983-87, contributingto the smallerobserved
first-yearwage increases. In any one year in this five-yearperiod about
one-fifthof workers received no wage increase. In the decade 1973to
1982,thatproportionreachedas highas 6 percentonly twice.
Union bargainershave also been willing to give up cost-of-living
escalators in recent years. Following nearly a decade (1976 to 1984)
when COLAcoverage averagedabout60 percent, coverage declinedto
50 percent in 1985and then to roughly40 percent in 1986and 1987. Of
workers with COLA coverage, the proportion who actually receive
COLAs, the ratioof column 11to column 10, droppednoticeablyduring
1983-87,averaging0.76 between 1976and 1982but only 0.57 from 1983
through1987.The decline in the importanceof COLAs as a component
of unionwage changes has been due to threefactors identifiablein table
7: the low inflationrate of 1983-87 (column 12), the decline in COLA
coverage(column10),andthe decline in the proportionof those covered
who actuallyreceive COLAs (column 11as a fractionof column 10).
The full extent of the union wage deceleration and the component
parts of the decelerationare clearly illustratedby the data in columns
4-7 of table 7. First-yearadjustmentsand COLA increases have both
been especially smallduring1983-87.
The explanation for the deceleration of union wage gains, both
absolutelyand relativeto nonuniongains, could be internationaltrade.
At least four considerations, however, suggest that other factors are
importantas well. First, the accelerateddecline in the employmentbase
for the majoragreements, and for union employmentmore generally,
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predates by at least seven years the emergence of the large U.S.
merchandisetrade deficits in 1984. Second, domestic economic developments are capable of explaining why recent union wage increases
have been unusuallysmall. In both the time series and the cross-section
analysis of majorsettlementsemploymentshares, we findthat international trade is importantbut does not account for the majorityof the
employmentlosses. The growthof nonunionemployment,deregulation
in the transportationandcommunicationindustries,the developmentof
dualunion-nonunionindustrialrelationsstrategiesamonglargeemployers, and worseningworkerattitudestowardunions have all contributed
11 The emergenceof a substantialmerchandise
to hardtimes for unions.
trade deficit has contributedto the decline in unionized employment,
but so have all these other developments.Third,our analysis of microeconomic data from manufacturingdoes not suggest that international
tradeis the maincausefor smallerunionsettlementsin the 1980s.Fourth,
an analysis by Mitchellconcludes that internationaltradeand deregulation have not been the root cause for the large increase in concession
bargainingsince 1982.12He finds that in industriesnot directly affected
by trade or deregulation,union wage concessions have been at least as
prevalentand as largeas elsewhere.
The preceding suggests continuing moderation in union wage demands. The short-termprospect for union employment is for further
reductions,both generallyand in the majorbargainingsituations. With
a decliningemploymentbase, union negotiatorswill continue to focus
on job securityand downplaywage demands.
In summary,the slowdown in wage inflationof the 1980sis due not
only to reducedinflationaryexpectations, but to the increase in relative
unemploymentamongadultmen, the decline in unionwage settlements,
and the competitive effects of importedgoods and services. Because
these developmentsare likely to persist, they pointto continuedmodest
wage growthfor the rest of 1988and into 1989.
11. The changingenvironmentof industrialrelations is documentedin Thomas A.
Kochan, Harry C. Katz, and Robert B. McKersie, The Transformationof American
IndustrialRelations (Basic Books, 1986). One analysis of changes in workerattitudes
towardunionsis found in Farber,"The Decline in Unionization."His analysissuggests
that nonunionworkersbecame less favorablyinclinedtowardunions between 1977and
1984.
12. See DanielJ. B. Mitchell,"WageTrendsandWageConcessions:Implicationsfor
MediumTermEconomicExpansion,"WorkingPaper 114(Institutefor IndustrialRelations, Universityof Californiaat Los Angeles, July 1986).
Comments
and Discussion
Gary Burtless: WayneVromanandJohnAbowd have writtena rather
discursivepaperon three aspects of recent wage inflation:the changing
demographicprofileof unemploymentandits effect on wage pressurein
labormarkets, the impact of internationaltrade on wage bargains,and
the declining role of unions in aggregate wage determination.In my
comments, I shall focus on the regressionresults discussed in the first
two-thirdsof the paper.
The authorsbeginby analyzingaggregatewage inflation,as measured
by the hourlyearningsindex. The econometricspecificationand results
of this analysisare shown in table 2. The Phillipscurves estimatedin the
table are based on an extremely parsimoniousspecification.The equations include only the level of the unemploymentrate and the lagged
value of price inflation.The authorsargue-and I certainlyagree-that
the unemploymentrate of men between the ages of 25 and 54 is a more
reliableindicatorof labor markettightness than the overall unemployment rate. The results in table 2 suggest that a 1 percentagepoint rise in
male unemploymentis associated with a dropin nominalwage inflation
of 0.8-0.9 percent.
The specification of the effects of price inflation will raise a few
eyebrows. In the simplest equation, Vroman and Abowd include the
distributedlagged rate of change in the consumerprice index over the
previous three years. The coefficientson this variableimplythat within
three years of a jump in prices, hourly earningsrise enough to offset
about 80 percent of the price hike. When the authorswant to juice up
thisparsimoniousspecification,they addthe four-quarterdistributedlag
of import price inflation (excluding petroleum).
Under one interpretationof this procedure,the authorsare tryingto
capture the impact of greater or lesser price competition in product
markets on the pace of domestic wage increases. If importprices fall
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relative to domestic prices, wages will be held down in the domestic
sectors that compete with importedgoods. The estimated coefficient,
which significantlyimprovesthe fit of the equation,especially in recent
years, appearsto confirmthis hypothesis.
Onemightthinkthatthis kindof product-marketpressurewouldgrow
as the share of importedgoods in the U.S. market rises. In the mid1960s, U.S. importswere less than 5 percent of GNP; today, they are
around11-12 percent. So one would anticipatethat the effect of import
price movements on U.S. wages would be greater today than in the
1960s. Perhapsthis is the reason that the regressionsin table 2 consistently overpredictaggregatewage inflationin recent years, even when
they include the termmeasuringimportprice inflation.Note, however,
that the errorin predictionis consistently smallerin the equationsthat
includeimportprice changes thanin those that exclude this term.
Although the effect of trade on the overall U.S. economy may be
growing, the effect on average wage bargainsmay be declining. My
impressionis that goods-producingindustriesthat are heavily involved
in trade account for a decliningfractionof U.S. employment.So while
the effect of tradeon these sectors may be rising, the importanceof the
wage settlementsstruckin these sectors is probablyshrinking.
It would be reasonableto expect thatimportprice movementsshould
have the greatestinfluencein sectorsthatdirectlycompetewithimported
goods-namely, the goods-producingindustries, excluding construction. But such was not the patterndiscoveredby the authorsin sectoral
regressionsthat are mentioned, thoughnot presented, in this paper. In
those sectoral regressions the authors found that wage increases in
mining and durable and nondurablemanufacturingare significantly
affected by importprices. That is, wages in those sectors are restrained
if overall import prices decline or grow slowly. But the authors also
found that wages in transportationand in retailand wholesale tradeare
just as stronglyinfluencedby importprice movements as wages in the
goods industries. Why should this be the case when workers in these
service industriesdo not directlycompete with importedservices?
Partof the problemis that relevantimportprice pressuresare poorly
measured by the regressor included in table 2 and in the sectoral
regressionsmentionedinthe text. Inprinciple,the authorsshouldinclude
a variablethatcapturesimportpricesof goods andservices thatcompete
directlywith those of the affected industry.Overall importprice movements mightdo a badjob.
Wayne Vroman and John M. Abowd
341
Vromanand Abowd addressthis issue in the most novel partof their
paper-the section dealing with collective bargainingsettlements in
manufacturing.Here their data set includes detailed informationabout
tradepressurewithinspecificindustrialproductlines. Beforedeveloping
this point, though, I should brieflydescribe the data set, which, as just
mentioned,pertainsto union settlementsin manufacturing.
It is unfortunatethatmanufacturingemploymentis a decliningportion
of all U.S. employment.And it is still more unfortunatethat collective
bargainingcovers a steadily dwindlingshare of workers, even in manufacturing.These things are not necessarily unfortunatein themselves,
eitherfor the economy or for workers-although there are still a few of
us who thinkso. They are unfortunatefromthe point of view of analysts
who take a great interest in collective bargainingarrangementswithin
manufacturing.However intriguingthese arrangementsare, their relevance to generalwage patternsis receding.
But I have come to praise this data set, not to bury it. The authors
have collected in one place a truly astonishingfile of informationabout
collective bargainingagreementsin manufacturing.The file covers a 26year span from 1959through 1984, and includes informationon more
than2,700 individualagreements.The datahave been organizedin such
a way that the analyst can derive the implications of an individual
contractforwagechangesin each yearcoveredby the contract,including
the effect, if any, of the COLA clause. Whatis more, the authorshave
tabulateddetailed informationabout the specific manufacturingindustries representedin the file, includingsuch data as the level of industry
shipments,imports,exports, domesticconsumption,andpricechanges.
Consequently,the regressions reportedin table 4 are estimated with a
huge cross-sectionaltime series data set, packed with detailedinformation that is generallybelieved relevantto wage settlements.
Veteranmacroeconometriciansmightbe astonishedat the numberof
observationsused to estimatethe equations. As a microeconometrician
myself, I am less easily impressed. Articles in leading microeconomic
journalsoften containas manyor moreobservations.Themanyavailable
observations here present some problems of interpretationto macroeconomistsaccustomedto dealingwithcompactdatasets. Givenenough
observations,one could enter "Numberof Light-yearsto the Dog Star"
as a right-hand-sidevariable and get a "significant"-'coefficient. A
coefficient that is statistically significantis not necessarily practically
significant,in the sense that it has a meaningfullylarge effect on the
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dependentvariable. On the other hand, a very low t-statistic is informative. If a variable is reasonably well identified in the data-and I
would expect all of Vromanand Abowd's are-an insignificantcoefficient does not mean "undecided," as it might in smaller data sets. It
means "This variableis unimportant."Even at the outer boundsof the
95 percentconfidenceinterval,the variablehas no meaningfuleffect on
the dependentvariable.
The specificationused by Vromanand Abowd in table 4 includes the
prime-agemale unemploymentrate, anticipatedinflationat the time of
the contractsettlement(measuredtwo differentways), the "inflationary
surprise"over the life of the contract(relevantmainlyfor wage bargains
containinga COLA clause), and several measures of demand for the
industry'sproductline. Thislast set of variablesis aclever decomposition
of demand changes into product price changes, changes in domestic
shipments,changes in exported shipments,and changes in the share of
imports in domestic consumption. The last variable-changes in the
importpenetrationratio-is clearly included to capture the effects of
importpressureson wage settlements.
What should we conclude from the results in table 4? First, the male
unemploymentratehas a remarkablysmall, althoughstatisticallysignificant, effect on wage settlements. If I read the results correctly, the
effect is only a smallfractionof thatimpliedin the aggregateregressions
reportedin table 2.
Second, wage earners obtain a substantiallysmaller share of price
increases than is suggested in table 2, where the aggregateequations
showed thatwages eventuallyrose by 75-80 percentof the changein the
CPI. The results in table 4 suggest that on average workers might get
only one-thirdto two-thirdsof the price rise, with workerscovered by
COLA clauses getting the most and workers not covered by COLAs
gettingthe least.
Third,wages appearto be relativelyinsensitiveto demandconditions
in productmarkets.Althoughthe coefficients are often significant,as I
just noted, small coefficients can be statistically significantin large
samples without any practical significancefor the dependentvariable.
Even underthe highestestimateof wage rate sensitivity, for example, a
10 percentagepoint rise in industryproduct prices leads to only a 0.2
percenthike in negotiatedwages.
The notable exception to this generalizationappearsto be imported
Wayne Vroman and John M. Abowd
343
goods competition, althougheven here the simulationresults reported
in table 5 suggest that the cumulativeeffect of importsis small. Import
penetrationhas a significant,butnot especiallylarge,effect in restraining
wages.
Fourth,in a nod towardinstitutionaltheories of wage bargaining,the
authors include a variable reflectingthe wage gain in the most recent
auto or steel settlement. This variableis always found to have a large
and reliablyestimatedeffect on new wage bargains.Withoutquibbling
with the institutionalknowledgelying behindthis specificationchoice, I
thinkthe inclusionof the steel and auto settlementvariableis probably
a bad idea.
Presumably,the most recent steel and auto wage increase already
reflects the influenceof some or all of the factors in the specificationthe currentunemploymentrate, expected inflation,general inflationin
productprices, and so on. Hence, part of the effects of these variables
is being capturedby the coefficient on the auto and steel settlement,
leaving the readerwith no idea of the net equilibriumimpactof, say, a
changein unemploymenton new wage settlements.
Of course, even with the currentspecificationthese effects could be
derived using appropriatesimulations.But the authorsdo not provide
these, so the readeris left in the dark.
Even thoughI have emphasizedthe differencesbetween the Phillips
curves impliedby the manufacturingregressions, on the one hand, and
the aggregateequations, on the other, I think it importantto note an
interestingsimilarity.Nearly all of the recentresidualsin the regressions
have been negative. The aggregateas well as the microeconomicequations tend to overpredictnominalwage gainsin the pastfew years. Many
of the errorsare quite large,particularlyin view of the slow pace of real
wage movements-and even nominalwage movements-in the 1980s.
Finally, we shouldtake note of the absence of any productivityterm
in the equationsshown on table 4. While this is customaryin aggregate
Phillips curve equations, it may not be as reasonablewith this kind of
data set.
If there is a sectoral slowdown in productivity growth, and if the
equationsreportedin table4 remainvalidpredictorsof wagemovements,
the combinedeffect would be higherunemploymentor higherinflation,
or both. Unless workers obtain a rising share of value added, either
overall inflationor joblessness must rise to slow down the rate of real
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wage increase. The estimated coefficient on the unemploymentrate is
quitelow, so it would presumablytake a large-and permanent-rise in
unemploymentto effect the requiredwage slowdown. An increase in
general price inflation would accomplish the same result, because
nominal wages apparentlyrise only a fraction of a point for each 1
percentagepoint rise in inflation.
Perhaps the specification in table 4 is generally correct. Neither
workers nor employers pay any attention to productivitytrends when
strikingwage bargains.But it is at least possible that some employers
take account of worker productivity when making wage offers or
acceptinga union's counteroffer.This propositioncould be examinedin
the authors' data set by includingsectoral productivitymovements in
the specification.Even if the industry-levelproductivitydataare bad, it
may be easier to test the idea here thanin a normalmacroeconomicdata
set. I do think this data set offers some intriguingpossibilities. The
authors should be congratulatedfor assemblingit and showing how it
can be exploitedin a macroeconomiccontext.
General Discussion
Several panelists suggested modificationsin the authors' aggregate
wage equations.RobertGordonagreedwith Burtlessthatthe equations
are overly parsimonious,and he suggestedincludingseveral lags of the
unemploymentrate. He noted thatin his own paperin this volume, rateof-changeeffects are important;withoutlags such effects are precluded
and the coefficient on the unemploymentrate may be biased. Gordon
also suggestedallowinglaggedwages to compete with laggedprices. He
arguedthatthe priceeffects were likely to have variedduringthe period,
as the use of indexed wage contracts increased markedlyduring the
1960s and decreased in the 1980s; ideally a variable reflecting this
differencein coverage would be used in the equations. EdmundPhelps
noted that the price variable may be serving as a proxy for expected
wage change. He suggested adding productivity growth to the wage
equationsas a variableindicatingboththe capacityof firmsto pay higher
wages andworkers'realwage aspirations.Such a variable,he reasoned,
mightaccountfor the slowdownof wage growthin the 1980s.
Gordon observed that wages are only half the story. The ultimate
Wayne Vroman and John M. Abowd
345
object is to understandhow wages get translatedinto prices. The recent
theoreticalemphasison price rigidity,for example in the paperby Ball,
Mankiw,andRomerinthisvolume,has reopenedthe questionof whether
wages are importantto prices in the shortrun-an issue, Gordonnoted,
that is ignoredby Vromanand Abowd. He suggested that large swings
in labor's shareargueagainsta simplemodel in whichprices are marked
up over wages. The recent decline in labor's shareis the counterpartof
the recentoverpredictionof the wage equations.Gordonalso noted that
these movementsin labor's share mirrormovements in the ratio of the
adult male unemploymentrate to the total unemployment rate. He
speculatedthat when adult males are doing relativelywell, they bid up
wages in general,resultingin an increasein labor'sshare.Vromanlinked
the reductionin labor's shareto the decline in unionjobs in manufacturing.
Robert Hall noted the existence of simultaneitybias in the microeconomic as well as in the macroeconomicwage equations. In the face
of shocks to wages, the dependentvariablewould be expected to feed
positively into contemporaneousprice changes, causingan upwardbias
in that coefficient. Similarly,feedbackfrom wage change to unemploymentwouldbe expected to bias the coefficienton unemploymenttoward
zero. Finally, bothof these effects wouldlead to an underestimateof the
standarderrorof the equation.Because it neglects these feedbacks, Hall
reasoned, the estimated response of wages to aggregatedemandfrom
this type of equation is misleading, and the implicationthat inflation
changesdo not originatewith wages cannot be accepted.
Abowd acknowledgedthe possibility of bias for the macroeconomic
variablesbut arguedthat the variationin many of the variablesin the
paper'smicroeconomicequationsis primarilycross-sectional.He added
that the estimatedequationswere properlyspecifiedwage models with
seriallyuncorrelatederrors.He reportedthatthe resultsare similareven
if annual dummy variables are included. For example, the effects of
trade penetrationand contract-specificinflation surprises are consistentlyestimated.However, ChristopherSimsobservedthatbiases could
exist even for these variables; for example, trade penetration in a
particularindustrycould resultfromwage shocks in that industry.
Charles Schultze noted that the coefficient on expected inflationin
the microeconomicequations should vary dependingon whetherthere
is a COLA clause and on the type of COLA clause in the contract. He
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found it puzzling that the equations implied that contracts without
COLAs had respondedvery differentlythan contracts with COLAs to
the combinedeffects of pastandexpectedpricechanges.Vromanreplied
thatattemptsto estimate separateexpected inflationeffects on different
types of contractshad not indicateda significantdifference.
Gordonconjecturedthat the price coefficient in the aggregatewage
equationswas less thanunity-the value some theorieswouldpredictbecause the consumerprice index substantiallyoverestimatedhousing
costs in 1980-81.Vromanrepliedthatalthoughthe coefficientsestimated
using other price indexes were sometimes closer to unity, the recent
overpredictionsof the wage equationsremained.