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Weisskopf1983
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  • 1. Hearts and Minds: A Social Model of U.S. Productivity Growth Author(s): Thomas E. Weisskopf, Samuel Bowles, David M. Gordon, Martin Neil Baily, Albert Rees Source: Brookings Papers on Economic Activity, Vol. 1983, No. 2 (1983), pp. 381-450 Published by: The Brookings Institution Stable URL: http://www.jstor.org/stable/2534294 Accessed: 26/10/2010 17:10 Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at http://www.jstor.org/action/showPublisher?publisherCode=brookings. Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. The Brookings Institution is collaborating with JSTOR to digitize, preserve and extend access to Brookings Papers on Economic Activity. http://www.jstor.org
  • 2. THOMAS E. WEISSKOPF University of Michigan SAMUEL BOWLES University of Massachusetts at Amherst DAVID M. GORDON New Schoolfor Social Research Hearts and Minds: A Social Model of U.S. Productivfty Growth Aftertenyearsof continuingimmersioninthewholeproductivityanalysisand debate, whatcomes throughloudand clearis thatthereare some thingsthat arecommonto all circumstancesof highlevelsofperformance.... Theseare mattersof theheartandmindandnotof hardwareandcapital.-Hallett' MOSTECONOMISTSagree that the slowdown in aggregate productivity growthintheUnitedStatessincethemid-1960shasplayedapivotalrole in the poor performanceof the U.S. economy. And yet, "despite numerousstudiesoftheslowdown,"BPEAeditorsWilliamC. Brainard Theauthors'nameshavebeenrandomlyordered.Theresearchwasoriginallylaunched bya smallresearchgrantprovidedbytheProgressiveAlliance.WethankRezaBaharand ClareBattistafortheirexcellentresearchassistanceandareespeciallygratefultoMichele I. NaplesandJulietB. Schorfortheirhelpin modelingandconstructingsomevariables uponwhichwe draw.We receivedvaluablecommentsfromparticipantsin the summer 1982conferenceoftheUnionforRadicalPoliticalEconomics,andfromtheWages,Prices, andProductivityWorkingGroupattheEconomicsInstituteoftheCenterforDemocratic Alternatives.AndrewGlynalsoprovidedveryusefulcommentsonanearlydraft. 1. JeffreyJ. Hallett,"Productivity-FromtheBottomUp," inRobertFriedmanand William Schweke, eds., Expanding the OpportunitytoProduce:Revitalizing theAmerican Economy through New Enterprise Development (Washington, D.C.: The Corporation for EnterpriseDevelopment,1981),p. 406. 381
  • 3. 382 Brookings Paper-s oniEconomic Activity, 2:1983 and George L. Perryconclude, "its causes have remainedlargely a mystery. '2 We think that this mystery stems more from the limitations of conventionaleconomicanalysisthanfromtheimpenetrabilityof slower productivitygrowth.Prevailingeconomicanalysistypicallyneglectsthe humandimensionsof productionandthe institutionalcontexts within whicheconomicactorsoperate.Wedevelopinthispaperanalternative account of the productivityslowdown that addresses these various lacunae. We argue in particularthat declining work intensity and lagging business innovation since the 1960s-factors that have been almost entirelyelidedin recentanalyses-provide crucialmissingclues to the productivitymystery.To developthisargumentwe presentandecono- metricallytest a "social" modelof aggregateproductivitygrowth. It integratestechnicalandsocialdimensionsofproductionandbuildsupon ananalysisofthesocialsettingthathasconditionedproductivitygrowth in the UnitedStates in the postwarperiod.3It can accountempirically foralmostalltheproductivityslowdown.Ouranalysisis provisional;it raisesmanyissuesforfurtherresearch,butwe believethatitprovidesa promisingfoundationfor resolvingthe puzzle of slower productivity growthinthe U.S. economy. We presentan alternativeaccountof the productivityslowdownin five parts.Some simple"stylizedfacts" relatedto workintensityand business innovationare first summarized.We then outline the basic elementsof a socialmodelof aggregateproductivitygrowth.A detailed econometrictestofthatmodelisnextpresented,providingacomparison ofitsexplanatorypowerwiththatofmoreconventionalapproaches.We thenevaluateseveralpossibleadditionaloralternativehypothesesabout the productivityslowdown, showingthatthe basicresultsof the paper are robust even when confrontedwith competingor supplementary interpretations.Thepaperconcludeswithabriefdiscussionofthepolicy implicationsthatmightbedrawnfromourexplanationoftheproductivity puzzle. 2. WilliamC. BrainardandGeorgeL. Perry,BPEA,1:1981,p. vii. 3. This paperdrawsheavilyon the historicaland structuralanalysisdevelopedin SamuelBowles,DavidM.Gordon,andThomasE. Weisskopf,Beyondthe WasteLand: A Democratic Alternative to Economic Decline (Anchor-Doubleday, 1983), especially chaps.4-5.
  • 4. T. Weisskopf, S. Bowles, and D. Gordon 383 DecliningWork Intensityand LaggingBusinessInnovation Mosteconomistshaveconcentratedontwoprincipalexplanationsof the slowdownin the rateof productivitygrowth-the oil-priceshock andslowerratesof capitalformation.Butthese two explanationshave two importantflaws:first,neitherfactortookeffect until1973-74,well afterthebeginningof the productivityslowdownin the mid-1960s;and second, even after 1973, these two factors appearto account for a relativelysmallportionof theretardationinproductivitygrowth. Journalists,businessobservers,andhistoriansfrequentlyarguethat two otherseriousproblemsbeganto afflictthe U.S. economyafterthe mid-1960s:friction began to mount at the workplace, leading to an erosion of worker cooperationand worker effort; and corporations turnedincreasinglytowardshorter-terminvestmentpolicies, resulting inmoresluggishbusinessattemptsto improveproductiveefficiency.4 Thesetrends,ifmanifest,wouldobviouslyhelpexplaintheslowdown inproductivitygrowthsincethemid-1960s.Buteconomistshavetended to overlook these developmentseitherbecause they do not typically studyworkintensityandbusinessinnovationinmacroeconomicanaly- ses of aggregateproductivitygrowthorbecausethey suspectthatsuch qualitativefactorscannoteasilybe integratedintorigorousquantitative investigation.' 4. See, among many such recent commentaries,The Business Week Team, The Reindustrialization of America (McGraw-Hill, 1982); James O'Toole, Making America Work: Productivity and Responsibility (Continuum, 1981); and Ira C. Magaziner and Robert B. Reich, Minding America's Business: The Decline and Rise of the American Economy(Harcourt,Brace,Jovanovich,1982). 5. ThesequalitativefactorsaretheintangiblesaboutwhichC.JacksonGraysonwrites in"EmphasizingCapitalInvestmentIsaMistake,"WallStreetJolurnal,October11,1982: Concentrationon capitalinvestmenthas led to the relativeneglectof "otherfactors' importantforgrowth-management,quality,technology,knowledge,employeeinvolve- ment,trainingandlabor-managementcooperation. Why?Forone thing,these otherfactorsaremostlyintangibles.Econometricmodels neednumbers,andintangiblesaredifficulttomeasureandquantify.Also, . . . [it]is much morecomfortableto workwiththingsyou can see, touchandkick. Forbothreasons, theseintangiblesaremostoftenomittedfrommodels,policiesandmanagerialdecisions, eventhoughcollectivelytheyhavealargerimpact.As theseotherfactorshaveincreased in importance,theiromissionpartlyexplainswhy oureconomicpoliciesandforecasts havebecomeincreasinglyinaccurate,andwhy ourproductivityslowdownhas been so "puzzling"to many.
  • 5. 384 Brookings Papers on Economic Activity, 2:1983 It is impossible,indeed,to measuredirectlyor exactly eitherwork intensityor innovativeactivity;one can neitherattachergometersto workers in the shop and office nor track the frequency of creative breakthroughsin corporateboardroomsandresearchlaboratories.But we thinkthereis sufficientlycompellingindirectevidence of declining work intensityand laggingbusiness innovationin the U.S. economy since the mid-1960sto warrantcarefuland systematicintegrationof these factorsintoanalysesof the productivityslowdownin the United States.6 WORKPLACE FRICTION From World War II through the early 1960s labor-management relationsappearto havebecomeincreasinglypeacefulandcooperative. By 1947,90percentofunioncontractsalreadypledgednostrikesduring the term of contract. Strikeactivity itself declined substantially;the proportionof worktimeidledbecauseof strikesfell, forexample,from anaverageof 0.54percentinthefirstpostwarbusinesscycle, 1946-48, to0.22percentinthenextfourcycles, 1948-66.Althoughtheearlydata are somewhatfragmentary,it appearsthatthe proportionof workers satisfiedwiththeirjobsalsoincreasedsignificantlyfromtheearly1950s throughthemid-1960s.7 6. In all discussionthatfollows, we date businesscycles by choosingas peaksthe yearsinwhichtheratioofactualtopotentialGNP,ascalculatedbytheBureauofEconomic Analysisandrevisedby the Councilof EconomicAdvisers,reachedits business-cycle peak.Whencomparingbusiness-cycleaverages,we datethecycles inthetextandtables as extendingfrom one peak to the next even thoughmost of the cycle averagesare calculatedfortheyearsextendingfromtheyearafterthepeaktothefollowingpeak. 7. Theunionno-strikecontractfigureisfromFredH.Joiner,"DevelopmentsinUnion Agreements,"inColstonE. Warneandothers,eds., YearbookofAmericanLabor,vol. 2, Laborin PostwarAmerica(RemsenPress, 1949),p. 35. Strikefrequencyin this and subsequentparagraphsis fromU.S. Departmentof Labor,Employmentand Training Reportof the President,1981(GovernmentPrintingOffice, 1981),table G-8. Data on trendsinworkdissatisfactionsummarizeresultsofaquestionaskedconsistentlysincethe mid-1950sbytheOpinionResearchCorporation:"Howdoyoulikeyourjob-the kindof workyoudo?"Wesummedthepercentagesresponding"verymuch"or"agooddeal." Althoughthedataareconfidential,theyaresummarizedinMichaelR.Cooperandothers, "Early WarningSignals:GrowingDiscontentamongManagers,"Business, January- February1980.For dataonjob satisfactionreportedin subsequentparagraphs,dates reportedinthetextcorrespondtotheparticularperiodsofaggregationreportedinthislast article.
  • 6. T. Weisskopf, S. Bowles, and D. Gordon 385 Realandobviousbenefitsto productionworkersduringthe postwar boomled to thisharmony.Realspendablehourlyearningsincreasedat anaverageannualrateof2.1percentfrom1948to 1966;andtheincidence ofindustrialaccidents-one obviousbarometerofworkingconditions- declinedby almostone-thirdfromits averageduringthe firstcycle of the postwarboom, 1946-48, to its averageduringthe last cycle, 1959- 66.8 After 1965this rosy glow beganto fade. Duringthe next business cycle from1966to 1973,forexample,theaverageannualgrowthof real spendablehourlyearningsfellto 1.0percent,andtheaveragefrequency of industrialaccidentsincreasedby 24 percentover its averagefor the previouscycle. At the same time, tight labor marketsincreasedworkers' relative bargainingpowerandmoderatedtherisksofdismissal.Duringthe 1966- 73 cycle, for example,the averageratioof quitsto layoffsin manufac- turingalmostdoubledits averagein the previouscycle, reflectingthe greater sense of labor independencethat the late-1960s boom had engendered.9 Takingadvantageof thisheightenedrelativeindependence,workers appeartohavebecomeincreasinglyrestiveattheworkplaceandintheir relationshipswith employers.The incidenceof part-timeabsenteeism increasedby 32 percentfrom1959-66to 1966-73. The averageannual percentageof worktime lost to strikesincreasedby 115percentfrom 1959-66 to 1966-71 before the Nixon wage-pricecontrols moderated the surgein 1972-73.From1961-67to 1967-73,further,the percentof strikesbecauseofworkingconditionsincreasedbymorethanone-third, andthepercentof strikestakingplaceduringthetermof contract,more familiarlyknownaswildcatstrikes,increasedby one-fourth.'0 8. Becauseof seriousproblemswiththetraditionalBureauof LaborStatisticsseries on real spendableweekly earnings,we developedour own alternativeseries on "real spendablehourlyearnings."See ThomasE. Weisskopf,"A New SpendableEarnings Series,"TechnicalNote2(EconomicsInstituteoftheCenterforDemocraticAlternatives, October1983).We similarlyresolvedproblemsin comparingaccidentratesfrombefore andafternewreportingpracticeswereinstitutedin 1970.SeeMicheleI. NaplesandDavid M.Gordon,"TheIndustrialAccidentRate:CreatingaConsistentTimeSeries,"Technical Note 1(EconomicsInstituteoftheCenterforDemocraticAlternatives,December1981). 9. Quitsandlayoffs here andin subsequentparagraphsarefromEmploymentand TrainingReport of the President, 1981, table C-14. 10. Dataon absenteeism,strikesto improveworkingconditions,andwildcatstrikes arefromMicheleI. Naples,"TheStructureofIndustrialRelations,LaborMilitance,and
  • 7. 386 Br-ookingsPaper-s oniEconomic Activ'ity, 2.1983 This spreadingworker restiveness does not appearto have been limitedtoblue-collarworkersorworkersinunions.Amongallproduction personnel,bothblue-collarandwhite-collaremployees,job satisfaction declined between 1965-69 and 1970-74. Accordingto detailed data availablefromthe Universityof Michigan'sQualityof WorkLife Sur- veys beginningin 1969,this decliningjob satisfactionwas surprisingly widespread;itaffectedwhite-collar,professional,technical,andmanage- rialworkersas wellas thoseinblue-collaroccupations."I After1973,of course,labormarketsloosenedand-by conventional expectations-workers' sense of independencewas boundto decline. (The averageratio of quits to layoffs indeed declined, althoughonly slightly, from 1966-73 to 1973-79.) But the restiveness apparently persisted,despiterisingunemployment,andin manycases appearsto havecontinuedspreading.Absenteeismratesdidnotdeclinein 1973-79 fromthe averageof the previouscycle, while both the percentageof strikesover workingconditionsandthe percentageof wildcat strikes increased. Perhapsbecause workerswere still discontentedbut increasingly fearfulabouteitherjob quits or proteststhroughstrikeactivity, they appearto havebecomeincreasinglyalienatedonthejob after1973.The theRateof Growthof Productivity:TheCaseof U.S. MiningandManufacturing,1953- 1977"(Ph.D. dissertation,Universityof Massachusettsat Amherst, 1982),tables 24 and4. Datesinthetextfor1961-66aredeterminedby 1961startingpointsonallthreedata series. Weconcentrateinthetextonaggregateindicatorsof trendsinworkintensitybecause thefocusinthispaperisontheslowdowninaggregateproductivitygrowth.Werecognize, nonetheless,thatsuchaggregativeindicatorsaresubjectto a widevarietyof distortions andthatdisaggregatedindustrystudiesarenecessaryto providemoresubstantialsupport forourhypothesesaboutlaggingworkintensity.Thetwo mostrigorousindustrystudies of whichwe areaware,one on coal andone on automobiles,providestrongsupportnot onlyforourinferencesaboutthe timingandmagnitudeof trendsin workintensityafter the mid-1960sbutalso for ourhypothesesaboutthe linksbetweenthese developments andthe industry-specificslowdownsin productivitygrowth.On the coal industrysee M.Connerton,R. B. Freeman,andJ. L. Medoff,"ProductivityandIndustrialRelations: The Case of U.S. BituminousCoal" (HarvardUniversity,Departmentof Economics, December1979).On the automobileindustrysee J. R. Norsworthand C. A. Zabala, "WorkerAttitudesandtheCostof Production,"paperpreparedfortheNationalBureau of EconomicResearchWorkshopon InvestmentandProductivity,July 1983.Onmanu- facturingasawholesee MicheleI. Naples,"TheStructureofIndustrialRelations,Labor Militance,andtheRateof Growthof Productivity." 11. See thesequenceof surveys,Qualityof WorkLife(InstituteforSocialResearch, Universityof Michigan),for1969,1973,and1977.
  • 8. T. Weisskopf, S. Bowles, and D. Gordon 387 percentof nonsupervisoryworkerssatisfiedwiththeirjobs, according to thelongestcontinuoussurveyavailable,fellfrom68percentin 1970- 74 to 59 percentin 1977-79,triplethe rateof declinefrom 1965-69 to 1970-74.Andthe pervasivenessofjob dissatisfactionbecameincreas- inglyapparent.GrahamStainesconcludedfromthedetaileddataavail- able in the Michigansurveysfrom 1973to 1977:"The sky hadfinally fallen.Workersinvirtuallyalloccupationalanddemographiccategories evidenced appreciable . . . [and] unmistakable manifestations of rising discontent." 12 How canallthisevidencebe summarized?Wethinkthatmuchof it canbe illuminatedthrougha simplepropositionthatwe develop more formallyin subsequentsections: the higheris the cost to workersof losing theirjobs, the more cooperative they are likely to be at the workplace.Theloweris thecost oflosingtheirjobs,incontrast,theless responsivethey will be to employereffortsto boost productivityand extractgreaterlaboreffort.Wepresentinfigure1a summarymeasure ofthe "cost ofjob loss," definedastheaverageannualpercentageof an employee'slivingstandardthatarepresentativeworkercouldexpectto lose if dismissed (see the text below for furtherdiscussion of this variable).Superimposedontheannualseriesaretheperiodaveragesfor 1948-66, 1966-73, and 1973-79.Disregardingfor the momentcyclical movements,the cost ofjob loss rose untilthe early 1960sandthenfell precipitouslyuntilthe early 1970s;despitemuchhigherunemployment ratesafter1973,the cost ofjob loss didnot returnto anythingclose to itslevels duringthepostwarboom. Based on this schematicandnecessarilyindirectevidence, we hy- pothesizethatworkersbecameless fearfulof losingtheirjobs afterthe mid-1960s,thattheybecameincreasinglyrestlessattheworkplace,and thattheirlaboreffortmightwell have declinedas a result.Economists mayhave been slow to recognizethese trends,butbusinessobservers noticed them early. The Wall Street Journal reported in 1970, for example: Observersof the labor-managementscene . .. almostunanimouslyassertthat thepresentsituationistheworstwithinmemory.. . . Moraleinmanyoperations 12. GrahamL. Staines,"IsWorkerDissatisfactionRising?"Challenge,vol.22(May- June1979),p. 39.See alsoGrahamL. StainesandRobertP. Quinn,"AmericanWorkers EvaluatetheQualityof TheirJobs,"MonthlvLaborReiiew, vol. 102(January1979),pp. 3-12.
  • 9. 388 Br-ookingsPapers oniEconomic Activity, 2:1983 Figure 1. The Cost of Job Loss, 1948-79a Percent 40 30 20 1950 1955 1960 1965 1970 1975 1980 Sources: Text equation 6 and the data cited in the appendix. a. The variable is defined as the average annual percentage of an employee's living standard that a representative employee could expect to lose if that employee were dismissed from the job; the variable, expressed as a fraction, has a potential range from zero to 1.0. The horizontal lines in the figure represent averages of annual data for 1948- 66, 1966-73, and 1973-79, respectively. is saggingbadly,intentionalworkslowdownsarecroppingupmorefrequently andabsenteeismis soaring.. . . [Manycorporations]contendtheproblem... is so widespreadit's theirmajorheadacheatthemoment.'3 MANAGEMENT TORPOR It has become almost commonplace among business observers, as Business Week puts it, that U.S. corporations have recently suffered "from a refusal to see beyond the next quarterly earnings statement." 114 Many suggest that corporations have been pursuing productivity-en- hancing innovations less vigorously, shifting toward more speculative financialinvestments and shrinkingfromthe longer-term entrepreneurial risks that provide a dynamic impulse in a growing economy. 13. QuotedinJeremyBrecher,Strike!(StraightArrowBooks, 1972),pp.266-67. 14. The Business Week Team, TheReindustrialization ofAmerica, p. 48.
  • 10. T. Weisskopf, S. Bowles, and D. Gordoni 389 Thesealarmsmaybe overblown,buttheremaynonethelessbe some usefulkernelsamongthejournalisticchaff.Wethinkit quitelikely, on the basis of availableand largelyindirectquantitativeevidence, that U.S. corporationsgrew less andless inclinedto introduceproductive innovationsafterthemid-1960s. First,applicationsforpatentsgrewmoreslowlyas the boomturned to stagflation.We can comparethe averageannualratesof growthin patentapplicationsfiledfor inventionsin successive five-yearperiods fromthemid-I950s:1956-60to 1961-65,2.5percent;1961-65to 1966- 70, 1.8percent;1966-70to 1971-75, 1.4percent;and1971-75to 1976- 80, - 0.1 percent.15 Second,by mostavailableinterpretations,thegrowthof privateand publicexpenditureson researchanddevelopmentdeceleratedafterthe late 1960s.Accordingto both KendrickandGriliches,for example, it seems likely that the growthof R&Dexpendituresslowed duringthe 1966-73business cycle andthen slowedfurtheror perhapseven stag- nated after 1973.16 Third,onecanobserveatrendafterthe 1960stowardgreaterrelative use of corporatefundsforincreasesinfinancialassets-rather thanfor realinvestmentand,therefore,forsupportorapplicationof productive innovations.Increasesinfinancialassets,asapercentageofallcorporate uses offunds,rosefromanannualaverageof 19.8percentin 1959-66to 25.4percentin 1966-73andto 25.8percentin 1973-79.'7 Asweargueinthefollowingsections,innovativepressureonbusiness is best captured,otherthingsbeingequal,by changesin thefrequency of business failures.Althoughthese failuresare obviously countercy- clical, withthe deathsof firmsrisingwhenutilizationfallsinshort-term contractions,we thinkthey arealso likelyto rise over the longerterm 15. Growthrates calculatedfrom data in U.S. Bureauof the Census, Statistical Abstract of the United States, 1981 (GPO, 1981),table 945. The five-year periods reported inthetextareconstrainedbythedatareportedinthesource. 16. See, forexample,JohnW. Kendrick,"Surveyof the FactorsContributingto the Declinein U.S. ProductivityGrowth,"in FederalReserveBankof Boston, TheDecline ofProductivityGrowth,ConferenceSeries22(FRBB,1980),pp. 1-21;andZviGriliches, "R&DandtheProductivitySlowdown,"AmericanEconomicReview,vol. 70(May1980, Papersand Proceedings,1979),pp. 343-48. See also KimB. ClarkandZvi Griliches, "ProductivityGrowthand R&Dat the Business Level: Resultsfromthe PIMSData Base," WorkingPaper916(NationalBureauof EconomicResearch,June1982). 17. Basedon dataon sourcesandusesof corporatefundsinEconomicReportof the President,1981(GPO,1981),tableB-87.
  • 11. 390 Br-ookingsPapers on Economic Activity, 2:1983 whenbusinessinnovationis mostintense.Firmsthatdo notkeeppace with or can least affordto keep up with modernizationwill be more vulnerableto bothcollapseandbankruptcywhen the rateof business innovationis high. Business failures do not cause intensificationof innovativepressure,accordingto this argument,butthey are sympto- maticofunderlyingincreasesintheforcesthatspurinnovativeactivity; inotherwords,thedirectionof causalityis frominnovativepressureto businessfailuresandnotthereverse. This suppositionis reinforcedby the patternof businessfailuresin the postwarperiod. Contraryto manyexpectations,business failures havenotrisenmonotonicallywithdecliningutilizationratesduringthe 1970s-although they have obviously soaredsince 1979as a resultof higherrealinterestrates.They were muchlowerin the 1970s,indeed, thanduringtheyearsof sustainedprosperity.Wepresentadecyclicized index of the frequencyof business failuresin figure2. We have both taken the residualsof a regressionof the failurerate on an index of capacity utilizationand taken a three-yearmoving average of that residualtohighlighttheseculartrends.Thefigureseemsconsistentwith muchof the business literature:forces creatingbusiness failuresrose steadily throughthe mid-1960sand then declined steadily until the dramaticshiftinmonetarypolicyinOctober1979launchedinterestrates into orbit.18 Thismeasureof innovativepressureonbusinessis indirect,as is the evidence on laggingwork intensity. It is nonetheless suggestive and moreor less consistentwiththe qualitativeandcasualobservationsof the businesscommunity.Wefindit plausibleto hypothesizethatU.S. corporationshave been less likely to pursueproductiveinnovations sincethemid-1960sthantheyhadbeenbefore.Suchaflagginginclination towardproductiveinnovationis likely to have contributedto the pro- ductivity slowdown. As thejournalistWilliamGreiderpuckishlyob- servedinarecentarticle,"WhentheHarvardBusinessReviewdiscovers that there is somethingwrong in the executive suite, something is wrong."19 18. See theappendixtothispaperfordefinitionsandsources.Wediscussbelowsome of the problemswithusingthe business-failurerateforthese purposes;see the section below, "A CompositeSocialModelof AggregateProductivityGrowth,"andnote51. 19. WilliamGreider,"TakingCareof Business,"Rolling Stone, December9, 1982, p. 11.
  • 12. T. Weisskopf, S. Bowles, and D. Gor-don 391 Figure2. AdjustedMeasureof BusinessFailures, 1949-81a Cyclicallyadjusteddeviationsaroundthe mean (failuresper 10,000enterprises) 40 20 - 20- -40 - -60 - -80 I I I I I I 1950 1955 1960 1965 1970 1975 1980 Sources: Authors' estimates based on data from sources cited in the appendix. a. The original measure of the business failure rate is expressed as the frequency per 10,000 listed enterprises. We then regressed this measure on an index of capacity with annual observations from 1949 to 1979 (the period over which our subsequent econometric work was carried out). We next took a three-year (and end-of-period) moving average of the residuals from the regression, both to control for the short-term business cycle and to smooth the cyclical fluctuations in the underlying measure. The values for 1949, 1950, 1980, and 1981 were based on predicted rather than actual observed residuals from the regression equation. Determinantsof AggregateProductivityGrowth Conventionalanalysesofproductivitygrowthhavereliedonwhatwe callatechnicalmodelofproduction:givenexistingtechnicalknowledge, laborandnonlaborinputsareroutinelyandpredictablytranslatedinto output.The prevailingconclusionderivedfromthis model is that the recentandpersistentslowdowninaggregateproductivitygrowthresults from the fact, in MartinNeil Baily's words, "either that the rate of technologicalchangeisnowmuchslowerthanitwas,orthattheeffective
  • 13. 392 Brookings Papers on Economic Activity, 2:1983 flows of capitaland laborservices have grownmore slowly thanthe measuredquantitiesof theseinputs,orperhapsboth."20 We do not doubtthat such "technical" factors affect the level of aggregateproductivity.Butwe do questionwhethersucha mechanical modelofinput-outputrelationsinproductioncouldpossiblycapturethe more complex social determinantsof aggregateproductivityand its growth. We have thereforesought a more complete social model of productivitythattreatseconomicactorsas socialbeings,aspeoplewith aspirationsandinhibitions,withneedsandresentments,witheconomi- callyimportantandpotentiallymeasurablereactionstotheirinstitutional settingandits history.Webeginwitha separateanalysisof thefactors affectingworkintensityandbusinessinnovationandthencombinethat analysiswithhypothesesderivedfromthemorefamiliartechnicalmodel. WORK INTENSITY: THE MARX EFFECT Marxiananalysisof the laborprocess has builtupona self-evident proposition:theintensityofhumanlaborinproductioncanvarygreatly.21 20. MartinNeil Baily,"ProductivityandtheServicesof CapitalandLabor,"BPEA, 1:1981,pp.1-2. Wehavenotprovidedasurveyofthemainstreamliteratureonproductivity, givenitsextensivecoverageinearlierissuesofBPEA,butwehavefoundespeciallyuseful Edward F. Denison, Accounting for Slower Economic Growth: The United States in the 1970s(BrookingsInstitution,1979);J.R.Norsworth,MichaelJ.Harper,andKentKunze, "TheSlowdowninProductivityGrowth:AnalysisofSomeContributingFactors"BPEA, 2:1979,pp. 387-421;Kendrick,"Surveyof theFactors,"pp. 1-21;andBaily,"Produc- tivityandtheServicesof CapitalandLabor,"pp. 1-50. 21. Forsomeof themostimportantanalyticcontributionsintherecentliterature,see StephenA. Marglin,"WhatDo Bosses Do?TheOriginsandFunctionsof Hierarchyin CapitalistProduction,"ReviewofRadicalPoliticalEconomics,vol.6(Summer1974),pp. 60-112; HerbertGintis,"The Natureof LaborExchangeandthe Theoryof Capitalist Production," Review of Radical Political Economics, vol. 8 (Summer 1976), pp. 36-54; JamesDevine andMichaelReich, "The Microeconomicsof ConflictandHierarchyin Capitalist Production," Review ofRadical Political Economics, vol. 12(Winter 1981), pp. 27-45; and Samuel Bowles, "The ProductionProcess in a CompetitiveEconomy: Walrasian,Neo-Hobbesian, and MarxianModels" (Universityof Massachusettsat Amherst,Departmentof Economics,May1983). Someinterestingparallelsexist betweenthisneo-Marxianliteratureandsomerecent neoclassicaldiscussionsof hierarchyandinvoluntaryunemployment.See, forexample, GuillermoCalvo, "Quasi-WalrasianTheoriesof Unemployment,"AmericanEconomic Review, vol. 69 (May 1979, Papers and Proceedings, 1978), pp. 102-07; and Edward P. Lazear,"Agency, EarningsProfiles,Productivity,andHoursRestrictions,"American EconomicReview,vol. 71(September1981),pp.606-20.
  • 14. T. Weisskopf, S. Bowles, and D. Gordon 393 Werefertothispotentialvariationinworkintensityasthe"Marxeffect" andrelyon someof Marx'sinsightsintothe structureanddynamicsof productionincapitalisteconomiesinthefollowinganalysisofthiseffect. Employerswilltry,otherthingsequal,tominimizethecost inwages, supervision,andotherexpendituresof a unitof workdone. Theirtasks arecomplicated,inlargepart,becauseemployeeswillbelikelyto value positivelyatleastsomenonworkactivitiesduringworktime-which by definitionwillnotcontributetotheoutputofthefirm-and willtherefore seek to workless intensivelythantheiremployersprefer.Thispresup- position does not implythatworkis absolutelyunbearableor that all employersapplydraconianmeasurestoexploittheirworkers.Itpresup- poses, muchmoresimply,thatemployeesandemployerspursueobjec- tives affectingemployeeworkactivitythatarenotperfectlycongruent andarehencepotentiallyinconflict. We can thereforeanalyzethe employers'minimizationproblemby focusing on workintensity,denotedas L* and definedas the ratioof total effective laborinputsappliedin productionto the total hoursof production-workerlaborpower hiredby the firm. Because effective laborinputsarepotentiallyvariable,givenpurchasedlaborhours,work intensityis clearlyvariableaswell, suggestingthecrucialimportanceof examiningthedeterminantsof itslevel andvariation.22 A criticaldeterminantof workintensityis the effectiveness of em- ployer controlover employees. This depends, in turn, on three main factors:the expectedcost ofjob loss, theprobabilityof beingdetected if an employeeis performingat a level of intensitybelow management expectations.andtheprobabilityof jobloss if thatpoorperformanceis 22. The analysisin the followingdiscussiondrawsprimarilyuponSamuelBowles, "CompetitiveWageDeterminationandInvoluntaryUnemployment:A ConflictModel" (Universityof Massachusettsat Amherst,Departmentof Economics, 1981);DavidM. Gordon,"Capital-LaborConflictandtheProductivitySlowdown,"AmericanEconomic Review, vol. 71 (May 1981, Papers and Proceedings, 1980), pp. 30-35; andJuliet B. Schor andSamuelBowles, "Conflictin the EmploymentRelationandthe Costof JobLoss," WorkingPaper6 (EconomicsInstituteof the Centerfor DemocraticAlternatives,July 1983).See alsoGerryOster,"LabourRelationsandDemandRelations:A CaseStudyof the'UnemploymentEffect,' " CambridgeJournalofEconomics,vol.4(December1980), pp. 337-48;GeoffHodgson,"TheoreticalandPoliticalImplicationsof VariableProduc- tivity," CambridgeJournalof Economics,vol. 6 (September1982),pp. 213-26; and MicheleI. Naples, "ProductionIs HumanActivity:A Social-RelationsApproachto the ProductivitySlowdown," WorkingPaper4 (Economics Instituteof the Center for DemocraticAlternatives,1982).
  • 15. 394 Brookings Papers on Economic Activity, 2:1983 detected.Theproductof these threefactorsis the expectedcost to the employeeofworkingatless intensitythanisexpectedbymanagement.23 Thefirstofthethreeisthemostobvious.Sinceemployersincapitalist economiesmaynotphysicallycoercetheirworkersor deprivethemof their liberty, one powerfulinstrumentof employer influence is dis- missal-the threatof whichwilldependonthecost to workersof losing theirjobs. Thehigherthecost ofjob loss, the morefearfulworkerswill be offailureto conformto employers'intentions. Theprobabilityofdetectiondependsontheintensityofsupervision- thatis, surveillanceanddirectionof productionworkersonthejob. The probabilityof dismissalvariesinverselywiththeextentofformalpower of the employeebasedon unionsandothercollectiveemployeeassoci- ationsandthedifficultytheemployerwillhaveinreplacingtheworker.24 Themultiplicativerelationamongthesethreefactorsimpliescomple- mentarity,as seemsreasonable:intensesupervisionwilldolittlegoodif thereis no cost to loss ofjob oriftheprobabilityof dismissalis low, for example,andcostlyjob-lossconditionswillhavelittleeffectifemployers areincapableof detectinganddismissingthosedeservingpunishment. These hypotheses suggestthe followingexpressionfor the factors affectingworkintensity: (1) E = J S *D(U, R), EJ, Es, ED, EJS, EJD, ESD>0, Du < 0, DR> 0, where E = indexof theeffectivenessof employercontroloverworkers J = expectedincomeloss resultingfromjob loss S = ratioof supervisory-workerhourstoproduction-workerhours D = indexoftheprobabilityofdismissalifdetectedworkingbelow managementexpectations 23. See Bowles, "TheProductionProcessina CompetitiveEconomy,"fora formal argumentaboutthemultiplicativenatureofthisrelationship. Ourformulationhereattemptsto model"objective"or "material"factorsaffecting workintensity,andthereforeavoidstreatingworkerattitudesas purely"exogenous." WethinkthatthisapproachispreferabletothatofanalystssuchasNorsworthandZabala, in"WorkerAttitudesandtheCostofProduction,"whoimplicitlytreat"workerattitudes" as a fullyexogenousfactoranddo notseekto understandwhatdeterminesvariationsin thatdeterminantof costs andproductivity. 24. Thelogicunderlyingthesecondoftheseconditionsis similartothatofthesearch- theoreticanalysisof theconditionsaffectingemployers'decisionto hirea newemployee orto continuesearching.
  • 16. T. Weisskopf, S. Bowles, and D. Gordon 395 U = level of collective worker membershipin unions or other employeeassociations R = indexof conditionsaffectingtheease withwhichmanagement believesit canreplacea dismissedworker. Workermotivationislikelytoconstitutethesecondmajordeterminant of work intensity. If there are substantialimprovementsin workers' earningsorworkingconditionsthatresultfromincreasesintheirintensity of work,forexample,workersmaybe moreinclinedto cooperatewith efforts to boost productivity.Conversely, if they must accept lower wages to foster investmentor sufferspeedupand hazardousworking conditionsto permitproductivityincreases,they maybe morelikelyto intensifytheir resistanceto employers'efforts to extract more labor activity. It seemslikely,then,that (2) M = M (W!, B, M*), MW!,MB, MM*> 0, where M = indexof workers'motivation W! = motivation-enhancingfactorsinworkers'earnings B = indexof qualityof workingconditions M* = vector of any exogenous factors that positively influence workers'job satisfaction. We can combineequations1and2 to forma compositeexpression forthe determinationof workintensity.Despitethe obviouslimitation thatvariationsinthelevelofworkintensitycannotbemeasureddirectly, itthenbecomespossibletospecifytheformofthefunctionalexpressions impliedby 1and2and,asshownbelow,tomeasure-albeit imperfectly- theirseveralcomponents.Thisfurtherstep makesit possible to draw inferencesaboutunmeasurablevariationsinworkintensityfromvaria- tions infactorsthatarelikelyto cause workintensityto vary;thuswe canincorporateanalysesofthefactorsdeterminingtheintensityofwork intoa moregeneralmodelof thedeterminantsof productivity. INNOVATIVE PRESSURE ON BUSINESS: THE SCHUMPETER EFFECT Mainstreamanalysesof the aggregateproductionfunctionimplicitly assumea standardneoclassicalmodelof competition:with conditions
  • 17. 396 Brookings Papers on Economic Activity, 2:1983 of perfect competitionpresumed,the forces of competition remain constant and continuousfor the individualfirm. As the production- possibilityfrontiermoves outward,firmsare forced to remainon the frontier because of the unrelentingforce of continuingcompetitive pressure.Wecallthistheassumptionofautomatictechnicaladaptation. Marx and Schumpetersuggested a quite differentconception of competition.Marxoriginallyarguedthatcompetition,whileunrelenting, was morelike warfarethana harmonyof mutualexchanges;farfrom actingas passiveprice-takers,firmsengagecontinuouslyin attackand counterattack,inforayandretreat.25Schumpetersubstantiallyextended these insights.He suggestedthatinnovativebreakthroughscreatetran- sitorymonopolypowerandgeneratequasirentsto be collectedby the innovator,so that subsequentlycompetitorsare compelledto imitate those innovations.In later work on business cycles and long waves, Schumpeterarguedthatthereareperiodicwavesofcorporateinnovation and entrepreneurialenergy. These waves of innovationalso unleash, accordingto Schumpeter,"gales of creative destruction."The firms leastableto ridethewaves of innovationfallbehindorfail.26 These insights suggest that variationsin innovative pressures on business substantiallyaffectthe level andgrowthof aggregateproduc- tivity. Automatictechnicaladaptationto exogenouslygeneratedtech- nicalprogressimplies,otherthingsbeingequal,a relativelysteadyrate of adaptationto exogenously generated expansion of productivity- enhancingknowledge.If, however,therearevariationsinthe pressure on firmsto adopt new methodsfor improvingproductiveefficiency, exogenouslygeneratedtechnicalknowledge,even if growingat a con- stant rate, will not lead to a steady rate of increase in aggregate productivity.Whencompetitivepressuresarehigh,otherthingsbeing equal,productivitygrowthwill also increase.Whencompetitivepres- suresslacken,productivitygrowthis alsolikelyto moderate.27 25. Forusefuldiscussionsof Marx'sconceptionof competitionsee AnwarShaikh, "PoliticalEconomyand Capitalism:Notes on Dobb's Theoryof Crisis," Cambridge Journalof Economics,vol. 2 (June1978),pp. 233-51; andWilliSemmler,Competition andMonopoly(ColumbiaUniversityPress,forthcoming). 26. See Joseph A. Schumpeter, The Theory of Economic Development (Harvard UniversityPress,1934);BusinessCycles,vol. 1(McGraw-Hill,1939);and"TheAnalysis of Economic Change," Review of Economics and Statistics, vol. 17(May 1935), pp. 2-10. 27. Weshouldnoteas anaddendumthatouranalysisof innovativepressures(andof businessfailures)maybe distinguishedfromtwo strandsof prevailingdiscussionin the
  • 18. T. Weisskopf, S. Bowles, and D. Gordon 397 This hypothesis can be translatedinto a form that permits direct incorporationinto a model of aggregateproductivitygrowth. Many neoclassicalgrowthmodelssuggestthattechnicaladvancecontributes to aggregateproductivitygrowthexponentiallyover time, reflectedin the exponentialadjustmentfactor, eX'.Relying on what we call the Schumpetereffect, we substitutea behavioralrelationfor the constant parameterX. We begin with the propositionthat the actualrate of implemented technicalprogressisafunctionofboththeexogenousgrowthofpotential technical progress and the currentlevels of innovative pressure on business: (3) A = A* + VLC, L> 0, where A = actualrateof technicalprogress A* = rateofgrowthofexogenouslygeneratedtechnicalknowledge 11 = coefficientof afirm'sadjustmenttovariationsincompetitive pressure C = indexof the (variable)level of competitivepressureonfirms to improveproductiveefficiency,witha meanof C equalto zero. This formulationsuggests that the neoclassical model is simply a specialcase: ifcompetitivepressurewereconstant(andequalto C), the businessandeconomicsliterature.Oneemphasizeschangesinbusinessattitudesorrisk preferencesasasourceofvariationsininnovativepressure.Thisisespeciallycharacteristic of recentjournalisticdiscussionsof managementfailuresinthe UnitedStates.A second, followingthe Schumpeterianlead, placesemphasison purelytechnicaldeterminantsof wavesof innovativepressure,focusingonburstsofinventionandsubsequentdiffusionof "epoch-making"ideas. For a justifiablycriticalreview of this approach,see Edwin Mansfield,"LongWavesandTechnologicalInnovation,"AmericanEconomicReview, vol. 73(May1983,PapersandProceedings,1982),pp. 141-45.Weargueincontrastthat longswingsininnovativepressurereflectandareconditionedbytheconstructionof new social structuresof accumulationandthe long periodsof expansionthey support.We concentrate,in otherwords, on structuralforces affectinginnovativepressuresrather thanonchangesinattitudesortrendsintechnicalinventiveness.Forfurtherelaboration, see DavidM. Gordon,RichardEdwards,andMichaelReich,SegmentedWork,Divided Workers: The Historical Transformation of Labor in the United States (Cambridge UniversityPress, 1982),chap. 2; and David M. Gordon,ThomasE. Weisskopf,and SamuelBowles, "LongSwingsandthe NonreproductiveCycle," AmericanEconomic Review, vol. 73 (May 1983, Papers and Proceedings, 1982), pp. 152-57.
  • 19. 398 Brookings Papers on Economic Activity, 2:1983 actualrateof growthof technicalknowledgewouldbe equalto X*.But if competitivepressurewere not constant, then C would vary, and X wouldthusdivergefromX*. These propositionsfurther suggest that variations in innovative pressurehavea cumulativeeffect, augmentingorerodinga firm'sincli- nationstoinnovateoveraperiodofyearsdefinedprimarilybythefirm's planninghorizons and the average amortizationperiod of technical innovations.Short-termcyclical variationsin innovativepressureare less likelyto affectafirm'sbehaviorthansustainedtrendstowardmore orless intensecompetitionoversubstantiallylongerperiods.Assuming that we can find a reasonableproxy measurefor C and that we can properlycumulateits effects over time, the Schumpetereffect should bejust as susceptibleto analyticinvestigationas theMarxeffect. TECHNICAL FACTORS AFFECTING PRODUCTIVITY Our attention to the Marx and Schumpetereffects is in no way intendedtodiminishtheimportanceofrelationshighlightedbythemore familiartechnicalmodel of productivity.We expect that the level of capacityutilization,the capitalintensityof production,andvariations intherelativepricesof externalinputsallaffectaggregateproductivity. Wenoteherethemaindirectionsof effect. Capacity Utilization. There are several importantreasons for ex- pectingcovariationbetweenaggregatelaborproductivityandcapacity utilization.First,theremightbe hoardingof nonproductionworkersin business-cycledownturns,whichwouldleadto reducedlaborproduc- tivity (perpurchasedtotal laborhours)duringrecession. Second, and similarly,therewouldbe underutilizationof ownedfixed-capitalstock duringa downturn,whichwouldleadto decreasedactualuse of capital inputsin production.Third,the efficiency of the productionprocess itself-including theefficiencyofutilizedcapitalinputsandofthelabor- managementapparatus-might be reducedif capacity utilizationfell belowsometargetedorwarrantedlevelforwhichproductiveoperations hadbeen designed.Fourth,it is conceivablethattheremightbe some hoardingofproductionworkersduringthecycle, withexplicitorimplicit contractspreventingtheimmediatelayoffsthatlowercapacityutilization mightotherwise cause. A fifthfactor mighthave the opposite effect: duringperiodsof low capacityutilization,firmsmightretiretheirleast
  • 20. T. Weisskopf, S. Bowles, and D. Gordon 399 efficientcapitalequipmentandthusincreasetheaverageproductiveness of capitalgoods stillinuse. Inthesubsequentanalysiswecontrolforthefirsttwofactorsdirectly. Hoardingof nonproductionworkersduringthe businesscycle is taken intoaccountbyexpressingproductivityasoutputperproduction-worker hour. Variableutilizationof the fixed capital stock over the cycle is testedbyadjustingmeasuresoftheownedfixed-capitalstockforvariable levels ofutilization. The net effect of the last threefactors is impossibleto anticipatea priori.Weweightherelativeimportanceofoffsettingpossibleeffectsof lowercapacityutilizationby testingdirectlyforthe directionof covar- iation,otherthingsequal,betweenaggregateproductivityandthelevel of capacityutilization.Wecontrolforthepossibilityof sluggishadjust- mentof staffinglevelstothebusinesscyclebypostulatingthataggregate productivitywill also varydirectlywiththe rateof changeof capacity utilization;themorerapidlyutilizationlevelsareincreasing,forexample, the greateris the likelihoodthatfirmswill makeincreasinglyefficient use of theresourcesandtheemployeesthatmighthavebeenpartlyidle duringperiodsof contraction.These controlsareobviouslyroughand imperfect,but they shouldat least allow testing of hypotheses about otherpossibledeterminantsof aggregateproductivityby provisionally controllingforthepossibleinfluenceofvariationsincapacityutilization. Capital Intensity. Aggregate labor productivity clearly varies with thecapitalintensityofproduction.Butaggregatecapitalintensitycannot be measuredby the aggregateratioof the (valueof the) owned capital stock to labor hours for at least two importantreasons. First, some portionof theownedcapitalstockmaynotenterintoproduction;itlies unutilizedas a result of fluctuationsin aggregateeffective demand. Second,theremaybe significantvariationsin the averageefficiencyof effective capital services, resultingprimarilyfrom the possibility of obsolescenceinthecapitalstocknotcapturedby theusualadjustments fordepreciation. These considerationsclearlysuggestthe need for two independent kindsofadjustmentstotheaggregatecapital-laborratio-one forvariable levels of utilizationand anotherfor factors that may lead to variable ratesofobsolescence.Wepursuebothkindsof adjustmentsinsucceed- ingsectionsof the paper,althoughtheformeris mucheasierto specify thanthelatter.
  • 21. 400 Brookings Papers on Economic Activity, 2:1983 External Input Prices. Several economists, particularlyMichael Bruno and Jeffrey Sachs, have recently focused on the effects of input price shocks on productivity growth in the United States and other advanced economies. Bruno states their conclusion quite simply: For a raw-materialintensiveactivitythe conventionaltwo-factorview of the productionprocessis onlyvalidwhenthe relativepriceof the rawmaterial(in outputunits)orits unitinputstaysconstant.Whenits relativepricerisesandit is a complementaryfactor of production,productivityper unit of the other factors,labourandcapital,mustfall.28 We agree with the microeconomic presuppositions of this argument; increases in external input-prices of crude and intermediate materials are likely to reduce the productivity of labor and capital inputs. We are concerned, however, about the way in which this insight is applied and about the specification of relative input prices in the recent literature. We make an effort in subsequent sections to improve upon the empirical specification of this effect.29 A CompositeSocialModel of AggregateProductivity It is now possible to combine both social and technical dimensions into a composite model of aggregate labor productivity. We follow convention and express productivity as a multiplicative function of the several inputs and social factors that are likely to affect it.30 The basic model becomes 28. MichaelBruno,"WorldShocks,MacroeconomicResponse,andtheProductivity Puzzle,"WorkingPaper942R(NationalBureauof EconomicResearch,July1982),p. 2. See also MichaelBruno, "Raw Materials,Profits,and the ProductivitySlowdown," WorkingPaper660(NationalBureauof EconomicResearch,April1981);andBrunoand JeffreySachs,"InputPriceShocksandtheSlowdowninEconomicGrowth:TheCaseof U.K. Manufacturing,"WorkingPaper851 (NationalBureauof EconomicResearch, February1982). 29. We note for purposesof claritythat Brunoactuallyidentifiestwo alternative possibleeffects of relativeexternalpriceincreaseson productivitygrowth.One is the substitutioneffect, illustratedby the quotationin the text. The otherfocuses on the measurementbiasresultingfromthestandardprocedureofdoubledeflationofgrossoutput datainthenationalaccounts.As Brunonotes,itis difficultto separatethetwo. 30. Thecrucialassumptioninthisformulationthatcannotbeavoidedisthatofconstant returnsto scale,andwecommentontherelevanceofandevidenceforthisassumptionas theeconometrictestsproceed.See note54below.Foradetailedcritiqueofthetraditional inferencesaboutaggregateproductionfunctions,seeAnwarShaikh,"LawsofProduction and Laws of Algebra:The HumbugProductionFunction,"Reviewof Economicsand Statistics,vol. 56(February1974),pp. 115-20.
  • 22. T. Weisskopf, S. Bowles, and D. Gordon 401 (4) Q = AGa (1 + G')O2 K*P L*y PJ e(x* + Lc)t with OX1(X2 , 7,t , > 0, 8 < 0, where Q = totaloutputperunitof purchasedproductionlaborinputs A = positiveconstant G = level of aggregatecapacityutilization G' = indexof rateof changeof thatutilization K* = utilized,nonobsolescentcapitalinputsperhourofpurchased productionlaborinputs L* = amountof effectivelaborinputsperhourof purchasedlabor inputs = indexof therelativepriceof externalinputs C = indexof thelevel of innovativepressureonfirmsto improve productiveefficiency. Comparativehypothesesaboutthe sourcesof theproductivityslow- downrequirethatwe movefromthisexpressionfordeterminantsof the levelofaggregatelaborproductivitytoafocusonchangesinproductivity overtime.Wedenotex as thelogarithmicrateof changeofX perunitof time, substitutefromexpressions1and2 into4, andintroduceYiandY2 as coefficientsof adjustmentmediatingthe two determinantsof work intensity. The following generalexpressionfor changes in aggregate laborproductivityovertimeis thusobtained: (5) q X*+ Otlg + ot2Ag + 3k*+ yle[J S D(U, R)] + Y2m(W!, B, M*) + 8px + ILC, with X, al, X2, , Y1 _Y29F > 09 8 < 0- We next providea specificationandeconometricestimationof our generalsocialmodelofproductivitygrowth,as summarizedbyequation 5. We also compareits explanatorypowerwiththatof modelsderived fromthe moreconventionaltechnicalexplanationsof the productivity slowdown. MODEL SPECIFICATION We estimatethe modelwithannualdatafor the postwaryearsfrom 1948to 1979becausetheseendpointswerebusinesscycle peaksandwe
  • 23. 402 Brookings Papers on Economic Activity, 2:1983 sought to estimate over the full rangeof completedbusiness cycles duringthe postwarperiodfor whichall necessarydatawere available. (Completeannual-but not quarterly-data seriesareavailableforour desiredvariablesonlybetween1948and1979.)Wefocusonthenonfarm privatebusiness sector in the United States, excludingboth the farm andgovernmentsectorsonthegroundsthattheirdynamicsandproduc- tionprocesses are not adequatelycapturedby the modeldevelopedin theprevioussection.Wereviewourspecificationofeachofthevariables inourgeneralsocialmodelintheorderinwhichtheyappearinequation 5. (See the appendixforfulldocumentationof thedatasources.)When we introducevariables,we normallydefinethemfirstin termsof their levels, referringbacktotheoriginalexpressionforthelevelofaggregate productivityinequation4, andthentransformthemintoratesofchange forestimationof equation5. Hourly Output. We specify the dependentvariableas the rate of changeof realoutputperhourof production-workeremployment.To obtainthis measureof hourlyoutput,we use basic indexes of nonfarm businessoutputandtotalhoursby the Bureauof LaborStatistics,and adjusttotalhoursinthedenominatorby theratioof production-worker employmentto totalemployment." Wedefinetheproductivitymeasureinrelationto production-worker hours,ratherthantotalworkerhours,inorderto focus on the differing activitiesof directlyproductivelabor,ontheonehand,andsurveillance orsupervisorylabor,on theother.(Weuse standardBLSdatato define productionworkersas "production"employeesinthegoods-producing sectorsandas "nonsupervisory"employeesinthe restof the nonfarm privatebusiness sector. Workersin thiscombinedcategorycomprised 31. Some economistsare skepticalof "value-added"measuresof productivityand preferto limitthemselvesto "physical"measuresof outputinthenumerator.Thelatter are availablein the United States only throughthe FederalReserve Boardseries on manufacturingoutput. Althoughwe recognize that value measures introducesome potential"noise" intothe measureof totaloutput,we feel comfortablewiththe value- addedmeasuresfor the purposesof this paperfor two reasons. First, thereare some obvious advantagesto being able to develop analysesfor the entirenonfarmprivate businesssector, butphysicalmeasuresof outputareavailableonly for manufacturing. Second,andmuchmoreimportant,itdoes notappearthatthephysicalandvalue-added series tell a substantiallydifferentstory for the manufacturingsector for the postwar economy.Foroneusefulcomparisonofthetwoseriesformanufacturing,seeTomMichl, "The Lowdownon the Slowdown"(New School for Social Research,Departmentof Economics,1982).
  • 24. T. Weisskopf, S. Bowles, and D. Gordon 403 81.3 percent of total private employmentin 1980.)This choice of a denominatorfor the outputvariablerecognizesthatthe specificnature of the contributionof supervisorylaborto productionis qualitatively differentfromthatof productionworkers;its contributionlies substan- tiallyin extractingworkfromdirectlyproductiveworkersratherthan directlytransformingraw materialsand intermediategoods into final outputs. We show below that our empiricalresults are robust with respectto thisandalternativespecificationsof thedependentvariable. CapacityUtilization. TheBureauof EconomicAnalysisdataon the ratioof actualto potentialGNP, as adjustedperiodicallyby theCouncil of Economic Advisers, are used to measureeconomy-wide capacity utilization.Thisratiotrackstheyear-to-yearmovementsofthebusiness cycleandisusedtomeasuretheimpactofthosefluctuationsonaggregate laborproductivity.32 CapitalIntensity. The fixed-capitalstock in the nonfarmbusiness sectoristakenfromtherecentlypublishedBureauofEconomicAnalysis data.Conformingto ourdefinitionof hourlyoutputandof productive- laborinputs,wedividethecapitalstockbyestimatedproduction-worker hours to derive an estimate of the capital-laborratio. Because only utilizedcapitalinputsaugmenthourlyproductivity,weadjustthecapital stock by the rateof capacityutilization(as definedabove), withKuas the utilizedcapital-laborratio. This proceduremeansthat the rate of changeofcapacityutilizationentersthemodeltwice-once directlyand once as a componentof themeasureof therateof changeintheutilized capital-laborratio;italsomeanswe haveto interpretthecoefficientson both variablescarefully.Thisformulationis nonethelesspreferredfor the purposesof initialestimationbecause it moredirectlyassesses the contributionoffluctuationsinthecapitalservicesactuallyappliedinthe productionprocessthana measureof theunadjustedcapital-laborratio ora measureof the ratioof theownedcapitalstockto potentialGNP.33 Again, we examine the sensitivity of the results to this particular formulationin subsequentestimations. 32. Wealsoconsideredandexploredtwoalternativemeasuresof capacityutilization andcyclicalvariation-the FederalReserveBoard'sseriesoncapacityutilizationandthe aggregateunemploymentrate.Thedisadvantageof theformeris thatit is onlyavailable formanufacturing,andnotforthetotalnonfarmprivatebusinesssector;thedisadvantage ofthelatteris thatitreflectseffectsofbothlaborsupplyanddemand. 33. Wesharesomeoftheskepticismof Cambridge,England,abouttheplausibilityof aggregatemeasuresofthevalueofheterogeneouscapitalgoods,butwe suspectthatthese
  • 25. 404 Brookings Papers on Economic Activity, 2:1983 Theissueof therelativeobsolescenceof capitalis morecomplicated, andthereareno clearguidelinesinthe availableliterature.34Following the interestingsuggestionsof MartinNeil Baily, we have formulated severalprovisionalspecificationsofthehypothesisthatthecontribution of capitalservices dependson variationsin thedegreeof obsolescence ofthecapitalstock,butwediscusstheseadditionaltestsinthesucceeding sectionbecauseof theirspeculative(andlargelyinconclusive)nature. WorkIntensity.WespecifytheMarxeffectthroughdirectestimation of allcomponentsof L*includedinequation5forwhichit was possible to obtainannualempiricaldata. Theeffectivenessof employercontrolis afunctionofthreevariables, J, S, andD. Relyingon separateworkby JulietB. SchorandSamuel Bowles, we measureJ, the cost ofjob loss, by a compositemeasureof theexpectedincomeloss resultingfromjob termination:35 (6) J = Ud [(W - WR)(W + WS)], where Ud = averageunemploymentdurationforjob losers, expressedas afractionof a year W = averageproduction-workerweeklyafter-taxearnings criticismsaremorerelevantforthedebatesaboutthemarginalproductivityofcapitalthan forthe econometricinvestigationof alternativehypothesesconcerningthe productivity slowdown.As long as the biases in aggregatevalue measuresof the capitalstock are relativelyconsistentover time, for example,thenchangesin the rateof growthof the measuredcapitalstock, andthereforein ourmeasureof capitalintensity,are likelyto provideplausibleindicationsof changesin the physicalratiosof capitalgoods to labor hoursand, consequently,of changesin the contributionof capitalgoods to the produc- tivenessof laborhoursovertime. We also consideredformulatingourvariablefor capitalintensityas the ratioof the ownedcapitalstocktopotentialoutput,withaneyeontrendsinpotential(butnotactually utilized)capitalintensity.Thisseemsto usa theoreticallyinferiorspecificationsinceitis distortedby lagsin the adjustmentof investment(andthereforechangesin the valueof thecapitalstock)to changesinthetrendgrowthof bothoutputandproductivity;it does notdirectlymeasurethevalueofthecapitalstock,whichenhanceslaborproductivity,but focuses insteadon the capitalthatmightaugmentit. Wetestedthis specificationin our estimationofequation8,inanycase,andthecapitalintensityvariablebecamestatistically insignificant. 34. SeethediscussioninBaily,"ProductivityandtheServicesofCapitalandLabor"; andBarryP. Bosworth,"CapitalFormationandEconomicPolicy,"BPEA,2:1982,pp. 286-90. 35. See JulietB. SchorandSamuelBowles, "Conflictin the EmploymentRelation andCostofJobLoss."
  • 26. T. Weisskopf, S. Bowles, and D. Gordon 405 WR = averageweeklyincome-replacingbenefitsreceivedby those withoutwork,includinga weightedallocationof unemploy- ment compensation, public assistance, food stamps, and medicalcarebenefits,to reflectrelativeworkereligibilityfor thosedifferentstreamsof benefits Ws = averageweekly nonincome-replacingbenefits, particularly includingeducationandmedicalbenefits. Definedin thisway, J measuresthe fractionof a year'soverallincome (includingbothwagesandgovernmentexpenditures)thata workercan expecttoforgoas aresultofjob loss. The intensityof supervision,S, is measuredas the ratioof nonpro- duction-workerhourstoproduction-workerhoursinthenonfarmprivate businesssector.36 We measure D, the probabilityof dismissal should a worker be detectedperformingata level of intensitybelow managementexpecta- tions, by specifyingthe two componentsidentifiedin equation 1. We define U as the percentageof the nonagriculturallaborforce that is unionized.WedefineR astheratiooftrendproduction-workeremploy- menttoitscurrentlevels;thegreateristheratiooftrendtoactuallevels, themoreslackthereis inthecurrentproduction-workerlaborforceand thereforethe easier it is to replace a productionworkerwho is not cooperativeon thejob. 36. Manywhohaveheardus presentourworkhavequestionedtherelevanceof this measureof theintensityof supervisiononthegroundsthatitincludestoo manytechnical workerstowarrantitsuseasaproxyforsupervisorylabor.Werelyonthedatadistinction instandardBureauofLaborStatisticscompilationsbetweenproductionandnonproduction employeesin the goods sectorsandnonsupervisoryand supervisoryemployeesin the service sectors. It is true that some of the employees designatedby officialdata as nonproductionor supervisorypersonnel are not managers,clerical supervisors, or foremen,butbyfarthelargestproportiondoindeedfallintothosethreecategories. In 1980,forexample,therewere 13.9millionnonproductionandsupervisoryworkers on privatenonfarmpayrollsas definedby the BLSdefinitionswe applyin ourstatistical work.Inthatsameyear,accordingtothemoredetailedthree-digitoccupationalcategories oftheU.S. BureauoftheCensus,therewereapproximately11.5millionmanagers,clerical supervisors,andblue-collarsupervisorsintheprivatesector.(Thisapproximationassumes thatthe sameproportionsof workersworkedin those categoriesin boththe publicand privatesectors.)Evenin 1980,therefore,at the endof a longperiodof rapidgrowthin technicalemploymentit remainedtruethatat least 83 percentof workersin this data categorywereexplicitlyclassifiedas managersandsupervisors.
  • 27. 406 Brookings Papers on Economic Activity, 2:1983 In the absenceof compellingtheoreticalguidelines,a multiplicative formforD is arbitrarilyadopted: (7) D = R /(Lp!Lp,)!U, whereU is definedas aboveandLpmeasuresthetimetrendof produc- tion-workerhours,Lp,, for 1948-79.37 Inthispaperwe focus on two of the threevariablescontainedin the functionalexpressionforchangesinworkers'motivation,m,inequation 5.Wemeasurew!bytherateofchangeinworkers'realspendablehourly earnings,hypothesizingthatworkers'motivationis higher,as is their workintensity,the morerapidlytheirtake-homepay increases.38We express an imperfectproxyforB, the index of the qualityof working conditions,as the inverseof Z, the industrialaccidentrate;thusB = Z-1. We postulatean inverse relationbetween the accident rate and workers'motivation.Accordingtothisformulation,risingaccidentrates arelikely to erode the qualityof workingconditions,reduceworkers' motivation,andthereforediminishworkintensity.39 Wehadhopedto findanannualmeasureof workers'job satisfaction to serve as a proxyfor M*, whichalso affectsworkermotivation.We couldnotfindasuitableannualseriesfortheentireperiodofobservation andthuswereunableto includea measureof M*inourequation.40 37. Weplanto exploretheeffectsof a varietyof possiblespecificationsinthefuture; forthemoment,sincethevariableJcarriesthegreateststatisticalweightintheeconometric applicationsreportedbelow, we retainthis simplemultiplicativedefinitionandsave for othereffortsamorecarefulanalysisofthemostappropriateformofinteractionamongthe twoconstituentvariablesofD. Wetakethesquarerootof theexpressioninequation7to avoidartificialamplificationofthevarianceofthecompositevariable. 38. Thishypothesisseemsparticularlyrelevantforunionizedproductionworkersin the UnitedStatesin thepostwarperiodbecauseit correspondsto the logicof collective bargainingoverthedistributionof thedividendsfromproductivitygrowth-to whathas usuallybeencalled,indeed,productivitybargaining. 39. One could alternativelyhypothesizethat the accident rate primarilyreflects speedupon thejob andthata risingaccidentratewouldthereforebe accompaniedby an increaseinworkintensity,notadecrease.TheactualestimatedresultsfortheeffectsofZ shouldhelpto discriminatebetweenthese two possibilities:a negativeandstatistically significanteffectofZonhourlyoutputwouldsuggestthatthenegativeimpactofaspeedup onworkermotivationswampsanydirectpositiveeffectonworkintensity,whileapositive effectonproductivitywouldindicatetheopposite. 40. Wenotewithinterest,however,thatthe seriesonjob satisfactionavailableon a consistentthoughintermittentbasissincethemid-1950sreportstrendsthatareparallelto trendsin productivitygrowthandsupportourhypothesesaboutspreadingdisaffection sincethe 1960s.Seethefirstmajorsectionofthispaperandnote7above.
  • 28. T. Weisskopf,S. Bowles, andD. Gordon 407 External Input Costs. We beginby measuringthe relativepriceof externalinputcosts by Pf, an index of the relativepriceof fuels. This choice reflectsthe importanceplacedon oil prices in the mainstream literature.41Wearenotcontentwiththismeasure,however. A varietyof externalinputsexists whose supplycan be subjectto shocksandwhoserelativepricemightthereforeincreaseandadversely affectthe productivityof otherfactorsof production.Forthe domestic privatenonfarmbusinesssectorinthepostwarperiod,suchshockshave occurredin the productionand pricingof many nonagriculturalraw materials,notjust oil andcoal. This has been due to bothforeignand domesticeffects. Internationally,OPECandothersuppliershavecom- binedto producesharpincreasesin the priceof importedoil anda few otherimportedcrudematerials.Domestically,popularresistanceto the physicalandenvironmentaleffects of energyproduction-embodied in the movementfor environmentalregulation,the campaignagainstnu- clearpower, andthe mineworkers'strugglesfor greatersafety in the mines-have combined to increase the relative productioncosts of domesticnonagriculturalcrudematerials.Thesetwodevelopmentshave jointly affected the relativecosts of externalinputsconsumedby the domesticprivatenonfarmbusinesseconomy.42 We capture this effect with an alternativevariable representing externalinputprices,Px, measuredastherelativecostofnonagricultural crudematerials,whichwe calculatebydividinganindexofthepricesof fuelsandothercrudematerials(excludingfoodstuffsandfeedstuffs)by theaggregateGDPpricedeflator. Theperformanceofthesetwoalternativemeasuresofrelativeexternal inputpricesis comparedthroughouttherestoftheanalysis.Evenatthis 41. For a summaryof muchof this literaturesee ErnstR. Berndt,"EnergyPrice Increasesandthe ProductivitySlowdownin UnitedStatesManufacturing,"in Federal Reserve Bank of Boston, The Decline in Productivity Growth, pp. 60-89. Technically it oughttobepossibletocapturethesubstitutioneffectofrelativeexternalinputpriceshocks bymeasuringchangesintherelativequantitiesofenergyinputs,ratherthanintheirprices, andto rely on pricemeasuresto test for the effect of measurementbiasresultingfrom doubledeflationof gross outputmeasures(see note 29 above). In practice,however, quantitymeasuresdonotprovideadditionalexplanatorypowerintheeconometricresults reportedbelow, so thatwe areconstrainedforempiricalreasonsto relyexclusivelyon relativepricemeasuresof thiseffect.See thetextbelowforadiscussionof theeffectof a quantitymeasureof energyinputs. 42. See thediscussionin Bowles, Gordon,andWeisskopf,Beyondthe WasteLand, pp.91-94and136-38.
  • 29. 408 Brookings Papers on Economic Activity, 2:1983 stageof initialspecification,the principaldifferencesareevident.The index of relative fuel prices pays attentionto only one category of externalinputsandthereforetendsto confuse a particularinstanceof recentpriceshockwiththemoregeneralpoliticaleconomicproblemsof sluggish supply responses, occupational safety, and environmental problems.Thefuelscoveredintheindexof relativefuelprices,indeed, accountforonlyaboutone-third(byvalueweights)of thetotalvalueof inputsincludedin the nonagriculturalcrude-materialpriceindex. This index, because of its focus on the priceof importedoil, also tends to givetoomuchattentiontoasingletypeofforeignshock-the successive OPECpricehikes-and too littletootherdomesticmovementsthatalso affectrelativeinputpricesof crudematerials.4 Innovative Pressure on Business. Following Schumpeter's clues aboutcreativedestruction,we focus on the rateof businessfailuresas anindirectmeasureof thepressureonbusinessfirmsto remaincompet- itive andadoptavailabletechnicalinnovations.Datafor the business- failurerateareavailableon a continuousbasisthroughoutthe postwar period.Use of thisvariabledoes notimplythatbusinessfailuresarethe onlyormostimportantcauseofproductiveinnovationbutthatvariations in the business-failureratereflectandthemselvesdirectlycovarywith awidevarietyof factorsaffectingbusinessinnovationforwhichcontin- uousannualdataarenotavailablethroughoutthepostwarperiod. Furtherapplyingthesuppositionthatvariationsininnovativepressure havecumulativeeffects, we transformthebusiness-failurerateto elimi- nateshort-termcyclicalvariationandtohighlightitsmoreseculartrends. Weresidualizethebusinessfailurerateonthelevelofcapacityutilization and then take a three-year (end-of-period)moving average of this residualizedvariable.We labelthis variableC*. This involves the hy- pothesis thatrecentvariationsin the business-failureratethatare not simplyfunctionsof fluctuationsin the level of capacityutilizationcan providea proxymeasureof recenttrendsinthe intensityof innovative pressureon firms.44Wefurthertest the robustnessof this specification 43. We placeheavyemphasisin ourbookon the roleof domesticandinternational "popularresistance"as a sourceof risingexternalinputpricesafterthemid-1960s.This involvesanargumentaboutandaninterpretationof ourvariableforexternalinputprices thatcannotbefurtherexploredthroughtheeconometricsof thispaper;see ibid., chaps. 4and6. 44. Inbackgroundworkforthispaperwe developeda modelof the failureratethat supportsthis interpretation.We showthat,whenone controlsforthe level of capacity
  • 30. T. Weisskopf, S. Bowles, and D. Gordon 409 by exploringseveralalternativevariablesbasedon thebusiness-failure rate. EMPIRICAL ESTIMATION Basedon these variabledefinitions,we arriveat a finalspecification of equation5 forthepurposesof initialeconometricestimation: (8) q =A* +Otlg + t2Ag +f3k,, + Pyle + 'y2IAw! + 'Y22Z+ bPx + pC*, where the variablesare defined as above. We hypothesize that the coefficientsX*, xtl,(X2, ,Yi lY21, andp.arepositiveandthatY22 and 8 are negative.Asinstandardeconometricestimation,weassumeastochastic componentinthedependentvariable,withu, distributedwithzeromean andC2 variance.45 Two considerationsinfluencedthe empiricalwork: first, since we could not assumea priorithatourhypothesesaboutthe effects of our unfamiliarandunconventional"social" variableswereassociatedwith changes in aggregateproductivity,it seemed crucialto test these hy- pothesesagainstthenullhypothesisof no significantstatisticalassocia- tion.46Furthermore,although we preferredto estimate equation 8 directly,ratherthanuse a modifiedversionof theaggregateproduction functionwithoutputas the dependentvariableanda measureof labor utilizationand the cost of capital,variationsin the failurerate are almostcompletely explainedby trendsincapitalintensity,anda trendtermthatclosely mirrorsthepattern reflectedin figure2-suggesting a smoothandinvertedU-shapetrajectoryin the deter- minantsof thefailurerateinthepostwarperiod. Wechosea three-yearperiodforthemovingaverageof thefailureratebecausethisis thelengthof theperiodoverwhichpastvaluesof theratearesignificantinexplainingits currentvaluesinanautoregressiveestimation. 45. Weuseordinaryleastsquaresestimationinthetestsreportedhere,asimplechoice thatdoes notappearto requireemendationas a resultof the specificationor theresults themselves.Seethetextbelowforcommentsonpotentialsimultaneousequationbiasand autocorrelation. We add here the moreinclusivemeasureof externalinputprices,p,, because we believe it bettercapturesthe politicaleconomicdeterminantsof variationsin external inputprices.Belowwe compareitsperformancewiththenarrowermeasure,pf. 46. Oneof the mostglaringpresumptionsof the accounting-methodapproachis its axiomaticapplicationofthemarginal-productivitytheoryofwagestotheadjustmentsfor "quality"in estimatinglabor.See thecriticaldiscussionof thisprocedureinthe section entitled"ExtensionsandCompetingHypotheses"below.
  • 31. 410 Brookings Papers oniEconomic Activity, 2:1983 hourson the right-handside of the equation,we test the sensitivityof ourresultsto thisparticularspecification.47 We show below the averagevaluesfor the dependentvariable,the averageannualgrowthin realoutputperproduction-workerhour,for the entireperiod, 1948-79, andfor three subperiodsin which, as the previousliteratureattests, the productivityslowdownis most clearly revealed.48These dataareconsistentwithotherestimatesin the litera- ture. Differences in estimates of the timing and magnitudeof the productivityslowdownprimarilyarein the levels of subperiodgrowth rates.If we compareourestimateswiththose of MartinNeil Baily,for example, the productivitygrowthrates estimatedhere are higherfor everysubperiod,buttherelativemagnitudesofdeclinefromoneperiod to the next areroughlycomparable;the highergrowthratesestimated herearedueto the use of production-workerhoursas the denominator inthemeasureofhourlyoutput,sincetotalworkerhoursgrewatamore rapidratethanproduction-workerhoursduringthepostwarperiod.49 Average annual rate of growth (percent) 1948-79 2.34 1948-66 2.87 1966-73 2.19 1973-79 0.85 47. Ourpreferredspecificationfocusesdirectlyontheobjectofanalysis-variationin the rateof changeof productivity-and poses a morestringenttest forthe explanatory powerof thevariousindependentvariablesintheanalysis. Onedangerof this specification,of course,is thatwe maycompoundtheproblemof potentialerrorsinvariablesbyincludinglaborhoursinthedenominatoron boththeleft- andright-handsidesof the equation.Wetest forthispossiblebiasbelowby comparing ourbasicresultswitha specificationinwhichonlyoutputappearsontheleft-handsideof theequationandlaborhoursappearsasanindependentvariable. 48. Productivitygrowthis definedastheaverageannuallogarithmicrateofgrowthof outputper production-workerhour.The averagesare calculatedas the means of the individualannualgrowthrates,sincethesearetheactualobservationsforthedependent variablein subsequenteconometricestimation.See Bowles, Gordon,and Weisskopf, Beyondthe WasteLand,chap.2, forfurtherjustificationoftheseperiodsforcomparison. 49. See Baily, "Productivityandthe Servicesof CapitalandLabor,"p. 9. Growth ratesforthecounterparttoourdependentvariabledefinedasoutputpertotal-workerhour fortheentireperiodandthethreesubperiodsreportedintable1were2.08,2.56,2.10,and 0.63percent,respectively.
  • 32. T. Weisskopf, S. Bowles, and D. Gordon 411 Table 1. A Social Model of Aggregate Productivity Growth in U.S. Nonfarm Private Business, 1948-79a Equation Independentvariable 1-1 1-2 1-3 1-4 1-5 1-6 1-7 Trend growth rate, X* 0.015 0.016 0.016 0.004 0.015 0.017 0.017 (7.98) (6.35) (7.97) (1.02) (6.92) (8.07) (8.39) Capacity utilization g 0.485 0.519 0.449 0.419 0.408 0.442 0.415 (4.80) (4.43) (4.68) (4.58) (3.47) (4.48) (4.41) Ag 0.074 0.049 0.082 0.094 0.091 0.125 0.103 (1.33) (0.78) (1.48) (1.74) (1.50) (2.29) (1.96) Utilized capital-labor ratio, 0.401 0.385 0.411 0.419 0.472 0.373 0.373 k,, (4.64) (4.26) (4.74) (4.99) (5.29) (4.17) (4.26) Effectiveness of employers' 0.035 ... ... ... ... ... ... control, e (3.74) Real spendable earnings, 0.075 0.073 0.072 0.069 0.121 0.292b Avw! (1.68) (1.57) (1.60) (1.57) (2.71) (1.37) Accident rate, z -0.083 -0.088 -0.086 -0.087 -0.100 -0.081 (-3.50) (-3.38) (-3.60) (-3.74) (-3.29) (-3.23) Relative extemal input -0.040 -0.042 -0.041 -0.037 - 0.013b -0.048 -0.055 prices, p, (-2.13) (-2.13) (-2.14) (-1.95) (-0.52) (-2.62) (-3.27) Business failure measure, 0.011 0.011 0.011 0.020b 0.012 0.010 0.008 C* (2.81) (2.72) (2.75) (2.98) (2.43) (2.50) (2.20) Cost of job loss,j . . . 0.036 0.034 0.031 0.027 0.027 0.034 (3.72) (3.60) (3.41) (2.74) (2.48) (3.58) Supervision intensity, s ... 0.001 ... ... ... ... . (0.01) Probability of dismissal, d ... 0.100 ... ... .. . ... ... (1.20) Predicted job satisfaction, ... ... ... ... ... ... 0.450 i! !(3.74) Summary statistic 1R2 0.913 0.908 0.910 0.914 0.893 0.906 0.909 Standard error of estimate 0.005 0.005 0.005 0.005 0.005 0.005 0.005 Durbin-Watson 2.095 1.891 2.092 2.200 2.184 2.214 2.096 Source: Authors' estimates based on data cited in the appendix. a. The dependent variable is the rate of change in output per production-worker hours, measured as change in logs. The independent variables are all growth rates measured as change in logs, with the exception of C*, which is a level variable, and Ag and Aw!, which are first differences of changes in logs. Given first differences, the actual observations are for 1949-79. The numbers in parentheses are t-statistics. b. The values for C* (equation 1-4), p, (equation 1-5), and Au'! (equation 1-6) are for the alternative variables described in the text. Wepresentintable 1theresultsof thedirectestimationof equation8 andseveralvariantsofit. Webegininequation1-1withthebasicmodel. All coefficientshave the expected signs. All independentvariablesare statistically significant(on one-tailed tests), with six variables at 1 percent, two at 5 percent, and one, Ag, at 10 percent. The variance explainedby the model is quite high given its focus on changes in
  • 33. 412 Br-ookingsPaper-s on Econiomic Activity, 2:1983 aggregateproductivity(ratherthan levels), and the Durbin-Watson statisticallowsusto acceptthenullhypothesisof zeroautocorrelation. The second columnpresentsresultsfor the samemodelwithe, the effectivenessofemployercontrol,decomposedintoitsthreeconstituent variables.The model remainsrobust,with virtuallyno changein the coefficientson theothersignificantindependentvariables.Thecost-of- job-loss componentof e, the variablej,is highlysignificantandclearly constitutestheunderlyingcomponentof e withthegreatestexplanatory power;its standardizedregressioncoefficientis actuallyhigherthanthe standardizedregressioncoefficientfore inequation1-1.Thecoefficient ondalsohastherightsign,butotherwiseperformspoorly.Thecoefficient for s, the rateof changeof the intensityof supervision,is statistically insignificant. Wepresentinthe columnfor 1-3the resultsof equation8 estimated withonlyj includedas a measureof variationsin e. As inequation1-2, j is positive and significant,with a coefficientnearto the value for e reportedin 1-1,andtheresultsfortheothervariablesremainconsistent. Giventheessentialequivalenceof the resultsin 1-1,1-2,and1-3,we choose to work with the simplerversion presentedin equation 1-3. Althoughwe believe that the version in 1-1, with the fully specified variablee, representsthe theoreticallycorrect representationof the microeconomiclogic of our analysisof the effectiveness of employer control,we retainthe versionin 1-3for subsequentstatisticalanalysis to avoid the possibility that some other components of e with less powerful statistical effects might complicate these comparativeand forecastingexercises.50 We turn next to our proxy measure for innovative pressure on 50. See Bowles, "CompetitiveWageDetermination,"forfurthertheoreticaljustifi- cationfortheuseofJ, ourmeasureof thecostofjobloss. Somereadersof anearlydrafthaveexpressedconcernaboutapossibleidentityinthe relationbetweenQandJ inourmodelbecausetheexpressionforJ includesthewagerate andthereis a close relationbetweentheratesof changeof productivityandthe product wage(see equation6). Thisconcernis misplaced,however,becauseWappearsin both thenumeratorandthedenominatorofJ. IftheotherdeterminantsofJ wereconstantand small,J wouldfluctuatearoundavalueof 1.00,ratherthanaroundthevalueof W.Infact, variationsinJ aredominatedby variationsin ourmeasuresof unemploymentduration, income-replacingpayments,andnonincome-replacingpayments,notbychangesineither theproductwageorinourmeasureofrealspendablehourlyearnings.Indeed,thesimple correlationcoefficientbetweentherateof changeof the productwageandJ is actually negative.
  • 34. T. Weisskopf, S. Bowles, and D. Gordon 413 business. Assumingfor the momentthatthe business-failureratecon- stitutes the appropriatebasis for such a measure, we test several alternativespecificationsof this variable.We reportin 1-4the results witha simplealternativespecification,C', anonresidualized,three-year moving average of the business-failurerate. The magnitudeof the coefficientsfor C* and C' differbecause the residualizationshifts the unitsofmeasurementonC*,butthestandardizedregressioncoefficients arealmostexactlyequalandso aretheirlevelsof statisticalsignificance. This suggests, in other words, that our results are insensitive to the choice aboutwhetheror not to adjustthe business-failureratefor its cyclicalcovariationwiththecapacityutilizationrate;we prefersuchan adjustmentto focus attentionon longer-termtrendsin innovativepres- sure.Wealsotestafive-yearmovingaverageofthebusiness-failurerate anda specificationin whichwe treatthe currentvalueof this rateas a two-yearautoregressivedistributedlagonpastvaluesofthesamerate- analternativemeasureof the notionof cumulativetrendsininnovative pressure.Bothof these specifications,notreportedhere,yieldedequiv- alentresultson boththe innovativepressurevariableandon the other independentvariablesinthemodel.5" Weconsidernextourspecificationof thevariablemeasuringrelative externalinputprices.Equation1-5revealstheresultsof substitutingpf, thevariablemeasuringrelativefuelprices,forp. Althoughitscoefficient hastherightsign,itis quitesmallandstatisticallyinsignificant.If, aswe and many other economists suspect, movements in one or another componentof externalinputpriceshavedampenedproductivitygrowth since the mid-1960s,our measure of relative nonagriculturalcrude- materialspricesappearsto capturethiseffectmoreadequatelythanthe narrowermeasureof relativefuelprices. 51. We also exploreda definitionof the variablebasedon net businessformations, takinginto accountnot only failuresbutnew enterprises.The problemwithadditional attentionto new enterpriseformation,however,is thatit is almostentirelya functionof realinterestratesandappearsto havelittleconnectionwithotherdimensionsof macro- economicactivity. The frequencyof net businessformationsgrew steadilyduringthe postwarperiod,particularlyduringthe yearsof low realinterestratesin the 1970s,and does notappearto havemovedinclose relationto otherfactorslikelyto affectaggregate productivity.Failuresandnetbusinessformations,indeed,moveinoppositedirections; the simplecorrelationbetweenthe frequencyof businessfailuresandnet formationsis - 0.47.Wethereforethinkthatthefailureratemorecloselyreflectstheunderlyingfactors thataffectrelativesuccessatmodernizationandinnovation.
  • 35. 414 Br-ookinigsPaper-s oniEconomic Activ'ity, 2:1983 The two other "social" variables,zAw!and z, also deserve further comment.Althoughproductivitygrowthandwage growthare closely linked,theintroductionof siw!, one of ourindicatorsof workermotiva- tion, shouldnotintroducesimultaneousequationbiasintoourequation becauseitrelatesthelevelof workermotivation(andthereforethelevel of work intensity and of aggregatelaborproductivity)to the rate of changeinworkers'take-homepayinequation8. Thereis no necessary statisticalrelationbetweenthefirstandsecondderivativesofavariable, so thereis no apriorireasonto treatsiv'! asanendogenousvariableand toexpectsimultaneousequationbiasasaresultof itsinclusionin8. The simplecorrelationcoefficientbetween q and svit! is only 0.37, barely morethanhalfthesimplecorrelationbetweenqanduv!,thefirstderivative of realspendablehourlyearnings. Theresultsreportedforequation1-3maystillreflectcausalityrunning fromtherateofgrowthofproductivitytotherateofgrowthofrealwages (andtherefore,if even indirectly,ZAw!).Wecantest for this possibility by residualizingAi'! on the rateof growthof the productwage (hourly compensationdeflatedby the GDP deflator)and then includingthat residualized variable, &w!* in 8. (This residualization allows us to eliminate the portion of variations in sit'! that are plausibly understood asendogenouslydeterminedalongwithq.)Wepresenttheresultsofthis procedure in equation 1-6, in which we substitutethe residualized independentvariable zw!* for Zw!. There is some decrease in the coefficientandstatisticalsignificanceofthismeasureofourmotivational hypothesis, but the variableremainssignificantat 10percentand the rest of the results remainrobust. (Thereis little changein the results largelybecausethe simplecorrelationbetweenzAw!andrateof change of theproductwageis only0.36.)52 We would obviously have preferreda measure of the quality of workingconditionsthatcovers theentirenonfarmprivatesectorrather thanjust the industrialaccidentrate, z. Lackingsuch a series, we are reasonablyconfidentthat trends in manufacturingclosely paralleled trendsinothersectors.Duringtheperiodwhenindustrialaccidentrates 52. We further estimated Phillips curve relations with uw!and Aeit!, respectively, as dependentvariables,andthelaggedunemploymentrateandproductivitygrowth,among others,as independentvariables.Whilesucha modelexplainsa largeportionof annual variationin wt,!-therateofgrowthofourmeasureof realspendableearnings-it explains only 10percentof theannualvariationinAit!(adjustedfordegreesoffreedom).
  • 36. T. Weisskopf, S. Bowles, anidD. Gor-don 415 beganto riseafterthemid-1960s,forexample,therewasbothrisingjob dissatisfactionandincreasingconcernaboutworkingconditionsamong theworkersinwhite-collaroccupations.53 Thereis one finaltest of the adequacyof Aivt!andz as measuresof factorsaffectingworkermotivation.As noted at the beginningof this paper,one consistentdataseries on employee satisfactionis available since the mid-1950s;thereare six observationson this series over the periodofouranalysis(seenote7).Despitethelimiteddegreesoffreedom, ourtwo proxyvariablesshouldcertainlyhelpexplainvariationsin the intermittentvariablemeasuringjob satisfaction.Whenwe regressM!, this measureof job satisfaction,on W!andZ, indeed, the two proxy variableshavetheexpectedsignsandexplain65percentofthevariation inM!. Wecanfurtherusethecoefficientsfromthisregressiontogenerate anannualseriesof predictedjob satisfactionbasedontheannualvalues for w! andZ. Equation1-7shows the resultsof substitutingthe rateof changeof this measureof predictedjob satisfactionfor zAw!and z in equation1-3.Thecoefficienton in! is statisticallysignificantandallthe otherresultsremainrobust.Thisfurtherstrengthenstheconclusionthat theeffects of &i'!! andz in equations1-1through1-3captureto a large degreethe effects of shiftsin factorsaffectingworkermotivation.We retainthose variablesfor subsequentanalysis,ratherthanourmeasure of predictedjob satisfaction,because the coefficientsgeneratingthat measurearebasedon only six observations. The three columnsof table 2 providetests of the sensitivityof the results to the specificationof the dependentvariable. Equation2-1 replicates1-3,exceptthattotal employeehours,ratherthanproduction- workerhours, are in the denominatorof productivity,the dependent variable(and, maintainingconsistency, in the indexof k14,the ratioof utilizedcapitalto labor).Themodelremainsrobust,withno significant changesincoefficientmagnitudeor significancebetween 1-3and2-1. The results of decomposing the dependent variable specified in equation8appearinequation2-2.Thedependentvariablein2-2isy, the changeinoutputinthenonfarmprivatebusinesssector;andthechange inproduction-workeremployment,4p,is addedto theright-handsideas an additionalindependentvariable.We also convert the measureof 53. See Qualityof WorkLife(InstituteforSocialResearch,Universityof Michigan, 1979);andthesummariesinStaines, 'IsWorkerDissatisfactionRising?"
  • 37. 416 Brookings Papers on Economic Activity, 2:1983 Table 2. Alternative Dependent Variables in the Social Model of Productivity Growth in U.S. Nonfarm Private Business, 1948-79a Independent Equation variable 2-1 2-2 2-3 0.014 0.026 0.016 (7.78) (4.97) (8.09) g 0.481 0.799 (4.84) (4.09) Ag 0.091 0.056 0.120 (1.61) (1.05) (4.31) ku, 0.417b 0.143b 0.427 (4.69) (0.92) (5.11) j 0.033 0.024 0.028 (3.52) (2.38) (4.77) AW! 0.080 0.089 0.064 (1.74) (2.06) (1.47) z -0.079 -0.068 -0.083 (-3.25) (-2.81) (-3.55) p." -0.037 -0.022 -0.040 (-1.91) (-1.10) (-2.12) C* 0.011 0.012 0.010 (2.64) (3.17) (2.67) Ip ... 0.619 (3.28) Summary statistic R2 0.917 0.983 0.899 Standard error of estimate 0.005 0.004 0.005 Durbin-Watson 2.254 2.402 2.142 Source: Authors' estimates based on data cited in the appendix. a. The dependent variable in 2-1 is the rate of change of output per total-employee hour; in 2-2, the rate of change of output; and in 2-3, the rate of change of production-worker hourly output residualized on the rate of change of capacity utilization. The variable Ipis rate of change in production-worker hours. Given first differences, actual years of observation are 1949-79. The numbers in parentheses are t-statistics. b. Adjusted to correspond with the redefinition of the dependent variable, as described in the text. capitalintensityto a directmeasureof therateof changeof theutilized capitalstock by removinglaborhoursfromthe denominator.TheR2is naturally higher in 2-2 than in 1-3.54 Otherwise the model is relatively insensitiveto this changein the formof specificationof the dependent variable:the social variables are robust, althoughj falls slightly in magnitudeof coefficientandstatisticalsignificance;thetechnicalvaria- bles are the ones, interestingly,that shift substantiallywith this re- 54. Theresultsin2-1areroughlyconsistentwiththeassumptionof constantreturns to scaleimpliedintheinitialspecificationof equations4 and5, forthecoefficienton Ipis close to theshareof productionworkers'compensationinnonfarmbusinessincome.
  • 38. T. Weisskopf, S. Bowles, and D. Gordon 417 specification,inasmuchas the coefficientson g, ku,andp, all change greatly. Because manyof the variablesincludedin the modelvaryover the businesscycle, it seems importantto test the sensitivityof ourresults thusfarby usinga dependentvariablethatis itselfcyclicallyadjusted. Wecomputedsucha variableby firstregressingq, therateof changeof productivity,on g, the rateof changeof capacityutilization,andthen takingthe residualfromthat equationas our measureof decyclicized productivitygrowth. We then regressedthis measureof residualized productivitygrowth on all variablesin equation8 with the obvious exceptionofg itself.Wereporttheseresultsinequation2-3.55Giventhe possibilities of cyclical covariationamong many of the independent variables,theresultsaresurprisinglyrobust.TheR2remainshigh.Only zAg,thechangeintherateofchangeofcapacityutilization,isdramatically affected by moving to the decyclicized dependentvariable, with its coefficientincreasinginbothmagnitudeandsignificance. COMPARATIVE PERFORMANCE We retainthe decyclicized specificationin 2-3 for the purposesof comparativetests of the model's explanatorypower and structural stability.Table3comparesourresultswiththosethatmightbeextracted fromprevailingdiscussionsof theproductivityslowdown.Equation3-1 reproducesthe model as reportedin 2-3. Equation3-2 estimates the simplestpossibletechnicalmodelthatcanbederivedfromtheavailable mainstreamliterature;itincludeszAgto controlfor sluggishfirmadjust- mentsto changesinthe level of businessactivity;k11,the changeinthe utilized capital-laborratio, reflectingthe concern of the mainstream 55. Therearea varietyof waysof performingthisresidualization;one canworkfrom eitherequation4 or5, whichhavecomparableresults.Twofeaturesof thedecyclicized modelin 2-3 areworthnotingin this regard.First,the fact thatthe effects of] remain robustevenafterthedependentvariablehasbeenresidualizedong suggeststhatitseffects arenot simplyanadditionalvariablereflectingthecycle. Second,we havetestedforthe relativeimportanceofthetwomaincomponentsofJ inequation6:unemploymentduration andrelativeincomeloss. Whenwe reestimate2-3withthe ratesof changeof those two componentssubstitutedfor j, both componentvariablesare statisticallysignificant, althoughthe standardizedregressioncoefficienton theunemployment-durationcompo- nent is the largerof the two. All otherresultsremainessentiallyunchangedwith this decomposition.
  • 39. 418 Br0ookingsPapers on Economic Activity, 2:1983 Table 3. Alternative Models of Aggregate Productivity Growth in U.S. Nonfarm Private Business, 1948-79a Independent Equation variable 3-1 3-2 3-3 3-4 0.016 0.009 0.011 0.015 (8.09) (2.12) (2.50) (7.09) Ag 0.120 0.048 0.066 0.114 (4.31) (0.91) (1.25) (3.74) kl, 0.427 0.758 0.771 0.469 (5.11) (4.57) (4.50) (5.39) j 0.028 ... ... 0.028 (4.77) (4.72) Aw!! 0.064 . . . . .. 0.075 (1.47) (1.67) z -0.083 ... ... -0.076 (-3.55) (-2.73) P, -0.040 ... ... -0.039 (-2.12) (-2.04) C* 0.010 . . . . . . 0.011 (2.67) (2.49) Pf . . -0.037 0.028 . . . (-1.06) (0.48) Dumtny,967-73 . . . . . -0.009 -0.002 (-1.82) (-1.04) Duxmmy1974-79 . . . ... -0.011 0.001 (-1.21) (0.25) Summary statistic R2 0.899 0.485 0.512 0.899 Standard error of estimate 0.005 0.010 0.010 0.005 Durbin-Watson 2.142 1.517 1.767 2.257 Source: Authors' estimates based on sources cited in the appendix. a. The dependent variable is the logarithmic rate of change in output per production-worker hour residualized on the logarithmic rate of change in capacity utilization. The variable pf denotes the rate of change in relative fuel prices. Given first differences, the actual years of observation are 1949-79. The numbers in parentheses are t-statistics. literaturewith capitalintensityandthe hypothesisof capitalshortage; andpr' the measureof relative inputprices that seems to reflectthe hypothesesofrecentdiscussionsabouttheoil-priceshockmostclosely. We considerelaborationsandextensionsof this simpleformulationof thetechnicalmodelinthefollowingsection,withparticularattentionto theeffectsof changesincharacteristicsof thelaborforce. Several conclusions flow from the comparisonof the results in equations3-1and3-2.First,thiskindof"technical"modelthatexcludes oursocialvariablesneitherexplainsas muchof the annualvariationin
  • 40. T. Weisskopf, S. Bowles, and D. Gordon 419 (decyclicized) productivitygrowth nor remains as free of potential inefficiencyfromautocorrelationas the moreinclusivemodelreported in 3-1. Second, such a technicalmodelgeneratessubstantiallyhigher estimates of the impact of variationsin utilized capital intensity on productivity;assuming,on both theoreticalandeconometricgrounds, thatthe socialmodelis amorefullyspecifiedequation,thissuggeststhat conventionalstudies have sufferedfrom underspecificationbias and havesubstantiallyoverestimatedtheimpactof slowdownsintherateof growthof the capital-laborratio. Third,p, is statisticallyinsignificant even in the morelimitedtechnicalmodelandappearsagainas a more statisticallyimprecisemeasureof effectsof externalinputprices. Thereis anotherusefulway to assess econometricallythe abilityof these alternativemodels to accountfor period-specificdeclines in the rateof productivitygrowth.As thedatainthedisplayabovereport,the rate of growthof outputper production-workerhour slowed by 0.68 percentagepoints from 1948-66 to 1966-73 and by 2.02 points from 1948-66to 1973-79.Thecorrespondingdecrementsforthedecyclicized measureof productivitygrowthwe use, the dependentvariablein 3-1 and3-2,were0.69and1.76percentagepoints,respectively.Wecantest for the ability of these two models to capturethese between-period declines by addingdummyvariablesfor the years between 1967and 1973and between 1974and 1979.If the other independentvariables accountnot only for annualvariationsin productivitygrowthbut also foraveragebetween-perioddeclines,theestimatedcoefficientsonthese respective dummy variables should be statisticallyinsignificantand close to zero. If, on the otherhand,one oranotherof the modelscould account for little of a specific between-perioddecline, the estimated coefficient on that dummyvariablewould be close to the values of - 0.0069or - 0.0176and,presumably,statisticallysignificant. Equations3-3and3-4showresultsof thistest forthetwo models.In 3-3,the resultsforthe technicalmodel,the 1967-73dummyvariableis statisticallysignificantat 5 percent and is actually greaterthan the between-perioddifferenceinproductivitygrowthrates;thisconfirmsa familiarresult in conventionalstudies of the slowdownfrom 1966to 1973-that is, capitalintensitygrewveryrapidlyduringthisperiod,and technicalfactors are unableto account for any of the first phase of slower productivitygrowth between 1966 and 1973. The estimated coefficienton the second dummyvariablein 3-3 fallsjust below a 10
  • 41. 420 Brookings Papers oniEconomic Activity, 2:1983 percentlevel of significanceandis equalto roughlythree-fifthsof the overalldeclineinproductivitygrowthfrom1948-66to 1974-79,further confirmingthe recent conclusionsof Bosworthand many others that slower capitalformationin the 1970sexplains relativelylittle of the productivityslowdowninthoseyears.56 Equation3-4 suggests, in contrast,thatthe basic social modelpre- sented in 3-1 can account statisticallyfor virtuallyall between-period productivityslowdowns; neither dummy variablereported in 3-4 is statisticallysignificant,andbotharequitesmall. What factors in that model play the greatest (estimated)role in accountingfor the slowdown itself? We can providedirect statistical estimatesof therelativeexplanatorypowerof thedifferentconstitutent variablesrepresentedin equation8. Relyingon the generalalgebraic result, in matrix notation, zA^= PAX, we can estimate the predicted changein q betweenthe variousphasesof the postwarperiodthatwe expect to result from the movements in the respective independent variablesusingcoefficientscalculatedinthebasicestimationofequation 8.Wepresentthiscomparisonintable4;therewe accountforthedecline in q fromthe 1948-66boom years to the 1966-73phase of slowdown andthenagainforthedeclineingrowthratesfrom1948-66to 1973-79. Wemakeuse of thecompleteversionof themodelreportedinequation 1-3,ratherthanthedecyclicizedversionin2-3,inorderto takeaccount ofdifferencesintherateofchangeofcapacityutilizationfromtheperiod of prosperitytothe successive periodsof slowdown. The firstandthirdcolumnspresentthe predictedpercentagepoints of decline in hourlyproductivitygrowth,while the second andfourth columns report the percentageof the total predicteddecline that is attributableto each of the variables.For explainingthe decline from 1948-66to 1973-79we use thecoefficientsreportedincolumn1-3.For thedeclinefrom1948-66to 1966-73we use coefficientsforthecompa- rable equationestimatedfrom the shorterperiodfrom 1948to 1973. Furtherto clarify the relativecontributionsof differentvariableswe providesubtotalsby the majorcategoriesof factors stipulatedin the originalpresentationof the socialmodelof productivitygrowth.57 56. See Bosworth,"CapitalFormationandEconomicPolicy." 57. Theprocedureappliedintable4 wouldnotbe validif a significantnumberof the variablesincorporatedin the calculationswere statisticallyinsignificant;since we are relyingonlyonvariablesthatproveto be statisticallysignificantincolumn1-3,ouruseof
  • 42. T. Weisskopf, S. Bowles, and D. Gordon 421 Table 4. Accounting for the Productivity Slowdown, Selected Periods, 1948-79a Attributionof declineinproductivitygrowth 1948-66 to 1966-73 1948-66 to 1973-79 Percentage Shareof Percentage Shareof points of the decline points of the decline Variable declinein q (percent) declinein q (percent) g, Ag 0.13 23 0.34 16 ku -0.12 -21 0.53 25 e, z, Aw! 0.57 98 0.60 28 P., 0.07 12 0.35 16 C* -0.07 - 12 0.32 15 Totalpredicteddecline 0.58 100.0 2.14 100.0 Actual decline 0.68 . . . 2.02 . . . Source: Authors' calculations. a. Percentage points of predicted decline in productivity growth, q, are calculated by multiplying the regression coefficients from the basic model of equation 8 by the decline in the average values for the respective independent variables for two periods being compared in the two parts of the table. The comparison of the decline from 1948-66 to 1973-79 is based on the coefficients reported in equation 1-3. The comparison between 1948-66 and 1%6-73 is based on the comparable coefficients estimated for the period from 1948 to 1973. Table4 showsonceagainthattheestimatedsocialmodelcanaccount foressentiallyalltheactualdeclineinqineachofthetwocriticalphases of the slowdown. We conclude, as muchas one can rely on statistical estimationsof this sort, thatthe social modelof aggregateproductivity growthhas "solvedthepuzzle"of theproductivityslowdown. Inthefirstphaseofdeclinethemovementsofcapacityutilizationand capitalintensity,the core variablesin traditionalanalysesof aggregate productivitygrowth,areunableto accountfor any of the slowdownin productivitygrowth,andboth variablespredicta decline of only 0.01 percentagepoints in productivitygrowthbetween 1948-66 and 1966- 73;thisis dueto thesignificantincreaseinthegrowthrateof theutilized capital-laborratioin 1966-73. Amongthe variablesintroducedin this discussion of the social dimensionsof productivity,those measuring changesinfactorsaffectingworkintensityaccountforbyfarthelargest unadjustedregressioncoefficientsisappropriate.Wecalculatetheproportionateinfluence of ourvectorof explanatoryvariablesas a percentageof totalpredicteddecline, rather thanactualdecline,to maintaininternalconsistencywithinthecalculations. The resultsreportedin equation1-3of table 1 andin table4 differslightlyfromthe resultsreportedin chap.6 andapp.C of ourbook,Beyondthe WasteLand.Theresults reportedhere supersede those in our book, since they are based on an improved specificationofthebasicmodelandsomedatarevisionsthatwewereunabletoincorporate intotheversionsreportedinourbook.
  • 43. 422 BrookinigsPapers on Economic Activity, 2:1983 share of the first period of slowdown, more than 98 percent of the predicteddecline. This lends credence statisticallyto what we have alreadysuggestedhistorically-that workintensitydeclinedrapidlyafter 1966andthatcorporationswerenotcapableof restoringworkintensity in the years before 1973.58 Thesecondphaseof declinesuggestsapatternthatis quitedifferent, one with each of the five categories of variables accountingfor a significantportionof the totalpredicteddecline;thevariablesaffecting workintensityremainthe most importantin accountingfor the slow- down.59 Onefinaltest of the statisticalpropertiesof thebasic socialmodelis in some ways the most demandingand the most important.Many mainstreamanalyses of the productivityslowdown conclude that its mysteriesresultfromexogenousstructuralchangesdistortingtheecon- omy'snormalmechanismsgeneratingsteadyexpansion.Thisconclusion impliesthatmodelsexplainingproductivitygrowthwouldbe incapable of accountingendogenouslyfor the productivityslowdown and that recourseto externalfactorswouldbe necessaryto explainchangesin theperformanceof theeconomy,particularlyafter1973. Ourhistoricalanalysisleadsus to anoppositeconclusion.Weargue thatthe structuralforces thatprovidedthebasisforpostwarprosperity alsoledtothestagnationofthelate1960sand1970s;thatis, thestructure of postwarprosperityitselfeventuallygenerateddecliningproductivity growth. Thisconclusioncanbetestedthroughanex postforecastingexercise. Ifwe arecorrectinourhypothesesaboutstructuralstability,the social model,as estimatedin eitherits basicordecyclicizedversions, should do as well in explaining productivitygrowth during the period of prosperityas it does duringthe two periodsof slowdown.Moreperti- nently,itshouldbepossibletoexplaintheproductivityslowdownsafter 1966and1973bymeansofanexpostforecastwithstructuralcoefficients estimatedfortheyearsleadingupto 1966and1973,respectively. Tables 5 and 6 and the followingparagraphspresentthe resultsof 58. See Bowles, Gordon, and Weisskopf, Beyond the Waste Land, chaps. 4-5. 59. Ibid.We providetherean additionalargumentaboutthefeedbackof policiesto restorework intensityon decliningcapacityutilizationand slower growthin capital intensity;we call it the "cold batheffect" andpresentsomeeconometricevidencefor thoseconnectionsinappendixCofthebook.
  • 44. T. Weisskopf, S. Bowles, and D. Gordoni 423 Table 5. Structural Stability Tests, Selected Periods, 1948-79a Social model Technzicalmodel Independent 1948-79 1948-73 1948-66 1948-79 1948-73 1948-66 variable 3-1 5-1 5-2 3-2 5-3 5-4 0.016 0.015 0.017 0.009 0.014 0.017 (8.09) (5.62) (5.56) (2.12) (2.97) (2.96) Ag 0.120 0.114 0.038 0.048 0.022 0.009 (4.31) (2.90) (0.69) (0.91) (0.39) (0.14) k,, 0.427 0.440 0.439 0.758 0.543 0.519 (5.11) (4.24) (3.56) (4.57) (2.91) (2.17) j 0.028 0.027 0.039 . . .. . ... (4.77) (4.15) (5.63) AII,! 0.064 0.054 0.117 . . . . .. ... (1.47) (1.10) (2.07) z -0.083 -0.103 -0.033 . . . . .. ... (-3.55) (-2.73) (-0.71) pX -0.040 -0.018 -0.018 . .. ... . (-2.12) (-0.47) (-0.35) C* 0.010 0.013 0.008 . . . . .. ... (2.67) (1.98) (1.21) pf . . . . . . . . . 0.037 -0.031 -0.003 (-1.06) (-0.51) (-0.03) Summary statistic K2 0.899 0.799 0.812 0.485 0.203 0.120 Standard error of estimate 0.005 0.005 0.005 0.010 0.010 0.010 Durbin-Watson 2.142 2.188 2.367 1.517 1.802 2.027 Source: Authors' estimates based on data cited in the appendix. a. The social model and the technical model are estimated based on three suLccessiveperiods reprodLcing the model structure from 3-1 and 3-2, respectively. The dependent variable is q*, the decyclicized rate of growth of hourly output. The numbers in parentheses are t-statistics. suchanexercise. As in the analysisof comparativeexplanatorypower above, we use the decyclicized model, denotingthe decyclicized de- pendent variable as q*, and present evidence comparingboth the structuralstabilityandforecastingperformanceof the social andtech- nicalmodelsrepresentedby 3-1and3-2. Columns5-1 and 5-2 presentthe resultsof estimationof the social modelfortwo differentperiodsof estimation:firstforthelongerperiod from 1948to 1973andthenfor the moredemandingandshorterperiod from 1948to 1966.(Thefirstcolumnreproducesthe coefficientsfrom 3-1 of table 3 for ease of comparison.)Particularlyfor the periodof estimationfrom1948to 1973,buteven forthe shorterperiodfrom1948 to 1966,the resultssuggest substantialcomparabilitybetween the full
  • 45. 424 Brookings Papers on Economic Activity, 2:1983 Table 6. Ex Post Forecasts of Aggregate Productivity Growth, Selected Periods, 1967-79 a Social model Technicalmodel Independent 1974-79 1967-79 1974-79 1967-79 variable 6-1 6-2 6-3 6-4 Constant 0.0002 0.007 0.012 0.019 (0.13) (3.02) (9.61) (11.83) q* 0.841 0.857 0.314 0.371 (10.21) (8.11) (5.33) (5.25) Summary statistic R?_2 0.954 0.844 0.846 0.689 Standard error of estimate 0.004 0.006 0.003 0.004 Durbin-Watson 1.272 1.778 1.541 1.171 Source: Authors' estimates based on data cited in the appendix. a. The dependent variable is predicted q*, the out-of-sample forecast for equations from columns 5-1 and 5-2, 5-3 and 5-4, respectively. The numbers in parentheses are t-statistics. and shorterperiods of estimation. The signs and magnitudesof the coefficientsarequiteclose andtheregressionstatisticsarealso similar. Threevariables,z, p., andC*, have smallandinsignificantcoefficients fortheshortestperiod,butthesevariablesthemselvesdisplayrelatively littlevariationduringtheperiodof prosperity.60Thefactthatthismodel stillexplains81percentofthevariationinproductivitygrowth,adjusted for degreesof freedom,withouttakingintoaccountinformationabout the periodsof slowdownafter 1966and 1973suggeststhatthe model's explanatorypoweris notdependenton specificorexogenouspostpros- perity developments.61 Columns3-2,5-3,and5-4presentparalleldataforthetechnicalmodel. Thatmodelfaresless well whenestimatedforthe shorterperiods,with 60. Itis alsointerestingto notethatbothjandAw!arehighlysignificantintheestima- tionfor1949-66,lendingsupporttotheanalysisdevelopedinBeyondtheWasteLandthat rapidproductivitygrowthinthepostwarboomdependedheavilyon the stimuluseffects of a risingcostofjob loss andtheincentiveeffectsofrapidgrowthinworkers'take-home pay. 61. Itis possibleto conductmoreformalstatisticaltestsforthestructuralstabilityof theequationsbyconductingaChowtestfortheequalityofthecoefficientsoftheestimated equationsfortherespectiveperiodsofestimation.Twopair-wisetestsarepossible:1948- 66versus1966-79;and1948-73versus1973-79.Thelatteris inappropriateforthesocial modelbecausethereareinsufficientdegreesoffreedomtoestimatethefullequationduring the 1973-79period.Fortheformercase, therelevantF-statisticfallssubstantiallybelow thecriticalvalue(at5percent)forthatcomparison,allowingustoacceptthenullhypothesis of equivalentcoefficients.
  • 46. T. Weisskopf, S. Bowles, and D. Gordon 425 asignificantdropinitsadjustedcoefficientofdeterminationandanotable declineintheestimatedmagnitudeof thecoefficientfork,.62 Below we use the respective period-of-estimationcoefficients to generateaverageannualpredictedratesofproductivitygrowthfor1966- 79 and 1973-79 and comparethem with the actual average rates of changeinthedecyclicizeddependentvariableforthoseyears.Withthe Average annual rate of productivity growth (percent)63 1973-79 1966-79 Actualq* 1.036 1.669 Socialmodel,q* 0.894 2.164 Technicalmodel,q* 1.526 2.546 1948-73estimation,forexample,the socialmodelforecastsanaverage annualpredictedrateofproductivitygrowthfor1973-79of0.89percent, whichis very close to the actualrate;the technicalmodelgeneratesan averageannualpredictedrateof 1.53percent,roughly50percenthigher thanthe actualrate. Althoughthe predictionsfromourforecasts, not surprisingly,are less accuratebasedon the shorter1948-66periodof estimation,the socialmodelnonethelessoutperformsthe morelimited technicalmodelby a comparablemargin. Theaboveresultsforaverageforecastperformanceignoretheclose- ness of fit fromyear to year. Table6 providesthe basis for the latter comparisonby regressingout-of-samplepredictedvalues for q* from the appropriateequationsin table5 againstthe actualvaluesforq*for 1974-79 and 1967-79, respectively. A perfect forecast performance, obviously, would result in an estimatedregressioncoefficientof 1.00 andanR2of 1.00. 62. The coefficienton the k,,variablein the equationsfor 1949-73 and 1949-66 equations5-3and5-4fallsto a valueclose to its stablelevels intheestimationswiththe socialmodel,suggestingthatitshigherestimatedvaluesinthe 1949-79estimationsofthe technicalmodelaredueto theartificiallyhighweightplacedon decliningratesof capital formationin 1974-79intheunderspecifiedtechnicalmodel;itattributestodecliningrates ofgrowthofcapitalintensitysomeofwhatisexplainedbythesocialvariablesinourmore inclusivesocialmodel. 63. Thepredictedvaluesforq*arecalculatedwiththeperiod-of-estimationcoefficients fromequations5-2and5-4forthe 1966-79estimatesandfrom5-1and5-3forthe 1973-79 estimates.
  • 47. 426 Brookings Papers on Economic Activity, 2:1983 Equations6-1 and 6-2 reportthese forecast results for the social model,providingsubstantialsupportfor ourconclusionsof structural stability.Theforecastfor 1974-79,basedoncoefficientsfor 1948-73,is particularlysuccessful:theestimatedcoefficientis 0.841;theR2 is 0.95; andwe reject,bytheappropriatetest [t = ( - 1.00)Af)],thealternative hypothesisthata is statisticallydifferentfrom 1.00 at the 95 percent confidencelevel. Theforecastresultsfor 1967-79,basedoncoefficients estimatedfor 1948-66, areonly slightlyless impressive,witha compa- rablevaluefor andtheR2almostas large. Subjectedto the same tests, the technicalmodel exhibitsless suc- cessful forecasting characteristics:the estimated magnitudesof the regressioncoefficientsaresubstantiallylower;theadjustedcoefficients of determinationarealso lower;andtheforecastperformancedepends muchmoreon theconstanttermthaninthecase of the socialmodel. It appears, in short, that the social model provides a robust and comprehensivestatistical explanationof the slowdown in aggregate productivitygrowthinthe U.S. economyafter1966. Extensionsand CompetingHypotheses Howeversuccessful, the basic socialmodeldevelopedandtested in the two preceding sections represents a very provisional effort to encompasssome social determinantsof aggregateproductivitygrowth that have been ignoredin mainstreamanalyses. We explore in this sectionalternativehypothesesadvancedin the productivityliterature. We show that this basic model remainsrobust in the sense that its explanatorypoweris notundercutwhenconfrontedwithalternative(or competing)explanations. Wefollow a standardprocedurethroughoutthissection:afterspeci- fyingastringofadditionalvariablesidentifiedbyalternativehypotheses, we firstconsiderthe effects of addingthose variablesto the technical model,withthedecyclicizeddependentvariableas reportedin3-2,and thenlookatthe effectsof addingthemto theapparentlymorecomplete social modelas reportedin 3-1. Any of the additionalvariableswhose signis consistentwiththeoreticalexpectationsandwhose inclusionin the morecomplete social modelis warrantedon econometricgrounds will then be carriedover to a roundof estimationaftereach of these
  • 48. T. Weisskopf, S. Bowles, and D. Gordon 427 separatetests. As before,we introducevariablesinthetextaslevelsfor ease of expositionandthen translatethemintoratesof changefor the purposesof econometricestimation.M4 LABOR FORCE COMPOSITION AND QUALITY Somehaveattributedasignificantportionofthedeclineinproductivity growthratesto changesincompositionof thelaborforceanddeclining "quality"of the employedpopulation.Althoughseveraldimensionsof thispossibleeffecthavebeenexplored,mostanalystshaveconcentrated on the ostensibleimpacton qualityof the risingproportioninthe labor forceof womenandyoungerworkers.65 A problemwith most of these studies, however, is that they have axiomaticallyappliedthe marginalproductivitytheory of wages. De- mographicallyadjustedindexesof laborinputarederivedby assuming thatthe relativeproductivity,or labor"quality,"of differentage-sex laborforcegroupingsiscapturedbytherelativewages.Weareskeptical aboutboth the validity of and the necessity for the use of wages as proxies for productivity.A1Hypotheses about the effects of changing labor force composition on productivitycan and should be tested directly,notpresumed.Weconsiderherethreemainhypothesesabout howeducation,agecomposition,andsex compositionaffectlaborforce quality. As Denisonandothershavenoted,theeducationalattainmentof the laborforce has risenfairlysteadilyover the entirepostwarperiod, so 64. We requirethata variableat least increasethe adjustedcoefficientof multiple determinationinthesocialmodel,withthecorrectsign,forinclusioninthefinalroundof estimation.This criterionis properlyappliedonly when inclusionor exclusionof the variableinvolveddoes not otherwisesubstantiallyaffect the coefficientson the other independentvariables.For one usefuldiscussionof this problemof specification,see PotluriRao and Roger LeRoy Miller,AppliedEconometrics(Wadsworth,1971),pp. 35-38. 65. Fortwoof themostsystematicdiscussionsof theseeffects, see GeorgeL. Perry, "LaborForceStructure,PotentialOutput,andProductivity,"BPEA,3:1971,pp. 533- 65; andJeffreyM. PerloffandMichaelL. Wachter,"The ProductivitySlowdown:A Labor Problem?" in Federal Reserve Bank of Boston, TheDecline inProductivity Growth, pp. 115-42. 66. For a usefulrecentsummaryof problemswith interpretingdemographicwage differentialsas indicatorsof differencesinproductivity,particularlyby raceandby sex, see DonaldJ. TreimanandHeidiI. Hartmann,eds., Women,Work,and Wages:Equal Pay for Jobs of Equal Value (National Academy Press, 1981), chaps. 2-3.
  • 49. 428 Brookings Papers on Economic Activity, 2:1983 thatvariationsinitsmovementsareunlikelyto accountforvariationsin the growthof aggregateproductivity.67Butthispresumptionshouldbe tested like any other. We can measure changes in the educational "quality"of the laborforce at least approximatelyby a variablemea- suringchangesinthe medianeducationalattainmentof thelaborforce; thisvariableis denotedv. Equation7-1 in table7 reportson the additionof v to the technical model. Its coefficient is significantand positive, as expected. When addedto the socialmodelinequation7-2,however,thecoefficientfalls toone-thirditslevel in7-1andis nolongersignificantevenat 10percent. SinceitsinclusionnonethelessslightlyraisestheadjustedR2,itbecomes a candidateforinclusioninthefinalroundof estimation. It is also possible to test directlyfor the effects of the age and sex compositionofthelaborforce.Somehavearguedthatrelativelyyounger workershaveloweredtheaverageexperienceofthelaborforce,reducing thegeneralskilllevelsoftheemployedandtherebyretardingproductivity growth.We test this effect by addinga variableforlaborforce inexpe- rience,whichweexpressasLy, thepercentageofthelaborforcebetween sixteenandtwenty-fouryearsold;thismeasureof "inexperience"rose significantlyafterthe early1960s.Othershaveargueda similarhypoth- esis aboutthe shareof womeninthelaborforce, assumingthatwomen haverelativelylower skillsthanmenandthattheirrisingshareof total employmenthas similarlyretardedproductivitygrowth. We test this hypothesis by includinga variablefor the female-employmentshare, whichwe expressasLf, thepercentageoftotalnonfarmprivateemploy- mentthatis female. In equations7-3 and 7-4 we reportthe resultsof addingthese two variablesto the technical model. The proxy for inexperience, ly, is insignificant,whileIfhasthe correctsignandis statisticallysignificant. Wheneachvariableis addedtothesocialmodelin7-5and7-6,however, neitheris significantandeachreducestheadjustedR2. Tocheckforpotentialcomplementaritiesamongthesethreemeasures of laborforce characteristics,we includeall of them in the finaltwo columns of table 7. The results of their inclusionremainconsistent: when addedto the technicalmodel, both the proxyfor educationand thefemale-employmentsharehavethecorrectsignsandaresignificant. When added to the social model in 7-8, neither the variables for 67. SeeEdwardF.Denison,"ExplanationsofDecliningProductivityGrowth,"Survey of CurrentBusiness, vol. 59 (August 1979), pp. 2-3.
  • 50. T. Weisskopf, S. Bowles, and D. Gordon 429 Table 7. Productivity Growth and Labor Supply Characteristics, 1948-79a Independent variable 7-1 7-2 7-3 7-4 7-5 7-6 7-7 7-8 0.004 0.013 0.009 0.013 0.016 0.016 0.007 0.013 (0.92) (4.94) (2.09) (2.91) (7.89) (7.41) (1.32) (4.00) Ag 0.083 0.104 0.051 0.014 0.119 0.118 0.052 0.100 (1.61) (3.46) (0.94) (0.27) (4.19) (3.89) (1.00) (3.03) kl, 0.753 0.450 0.762 0.844 0.427 0.434 0.817 0.465 (4.88) (5.34) (4.51) (5.18) (5.00) (4.60) (5.29) (4.79) j ... 0.029 ... ... 0.028 0.028 ... 0.028 (4.99) (4.46) (4.59) (4.43) Aw! . . . 0.095 ... ... 0.064 0.062 ... 0.099 (1.93) (1.43) (1.37) (1.88) z ... -0.053 ... ... -0.083 ;0.082 ... -0.050 (-1.64) (-3.28) (- 3.40) (-1.48) pf or p, - 0.003 -0.033 - 0.035 -0.036 -0.40 -0.040 - 0.002 -0.034 (-0.09) (-1.72) (-0.97) (-1.07) (- 2.05) (- 2.08) (-0.44) (-1.67) C* ... 0.010 ... ... 0.010 0.010 ... 0.008 (2.92) (2.13) (2.32) (1.45) v 0.730 0.301 ... ... ... ... 0.849 0.386 (2.27) (1.28) (2.25) (1.39) lY ... -... 0.021 ... -0.001 ... 0.051 0.029 (-0.33) (-0.02) (0.76) (0.65) if ... ... .. . -0.526 ... - 0.026 -0.447 -0.023 (-2.01) (-0.18) (-1.78) (-0.16) Summary statistic T2 0.554 0.902 0.467 0.537 0.894 0.894 0.592 0.894 Standard error of estimate 0.010 0.005 0.011 0.010 0.005 0.005 0.009 0.005 Durbin-Watson 1.647 2.090 1.526 1.609 2.143 2.149 1.794 2.083 Source: Authors' estimates based on data cited in the appendix. a. The dependent variable is the decyclicized rate of change of hourly output, q*. The variable v is rate of change in the educational attainment of the labor force; I(, the rate of change in the labor force aged sixteen to twenty-four; and If, the rate of change in the female share of employment. Given first differences, actual years of observation are 1949-79. The numbers in parentheses are t-statistics. The input-price variable is entered as pf in the technical model and Px in the social model. inexperiencenorfor female-employmentshareis significantwhile the proxy for educationis now significantat 10percent. Based on these results,we carryover vforuse infinalestimation.68 ADDITIONAL FACTORS OF PRODUCTION Someanalystshavefocusedon theeffectsonproductivitygrowthof additionalfactorsof production,exploringthe impactof variationsin 68. These results confirmour concern about the possible biases in conventional accounting-methodstudiesoftheproductivityslowdown.Seenote46andthecorrespond- ingdiscussioninthetext.
  • 51. 430 Brookings Paper-s on Economic Activity, 2:1983 energyconsumption,supervisoryinputs, or both. Theory mightlead one to expect thatproductivitywouldbe positivelyrelatedto the ratio of energyconsumptionto production-workerhoursandalso positively relatedto the ratioof nonproduction(or supervisory)employmentto production-workeremployment,particularlywith our definitionof a dependentvariableas outputper production-workerhour. We have tested these two hypothesesaboutadditional"factors"of production byaddingvariablestoourbasicmodelmeasuringX, theratioofphysical energyunits(inBtuunitsconsumedby industry)to production-worker hours;and S, the intensity of supervisionas definedabove. Neither variableis statisticallysignificantin eitherspecification.Giventhatwe hadalreadytakenintoaccountthe relativepriceof externalinputs,p., it is not surprisingthataddinga measureof the energy-laborratiodid notimprovetheexplanatorypowerofourmodel.Buteven inaseparate equationfromwhichp, was excluded,x was not significant.Andgiven whatwe have alreadyobservedin column1-2,it is also not surprising thatthe additionof a measureof the intensityof supervisionas a direct factorof productiondidnotaffecttheresults. SECTORAL COMPOSITION AND MARKET GROWTH Someanalystshavepaidparticularattentionto theeffectsof product market composition and market scale. It is possible to test these additionalhypothesesalso. Onecommontheoryinboththepopularandtheanalyticliteratureis thatof "deindustrialization."69Thistheorysuggeststhatat least some of the slowdown in productivitygrowthsince the 1960shas resulted from the shift in output, away from manufacturingand other goods- producingsectorsinwhichproductivitylevels andratesof growthhave 69. See, forexample,BarryBluestoneandBennettHarrison,TheDeindustrialization of America (Basic Books, 1982);Lester C. Thurow, "The ProductivityProblem" (MassachusettsInstituteofTechnology,DepartmentofEconomics,November1980);and GregoryB. ChristainsenandRobertH. Haveman,"TheDeterminantsof the Declinein MeasuredProductivityGrowth:AnEvaluation,"inJointEconomicCommittee,Produc- tivity:TheFoundationof Growth,SpecialStudyon EconomicChange,vol. 10,96Cong. 2 sess. (GPO,1980),pp. 1-17. We notethatBluestoneandHarrison,despitetheirtitle, focus moreon changinginvestmentpolicies andwhatthey call the "hypermobilityof capital"thanthedirecteffectsof shiftsinemploymentoroutputoutof manufacturing.
  • 52. T. Weisskopf, S. Bowles, and D. Gordon 431 historicallybeenrelativelyhighandtechnicalchangeis likelyto haveits biggest impact, into service sectors in which productivitylevels and growthrateshavebeenrelativelylow. Ifthedeindustrializationhypothesisis correct,we shouldexpectthat aggregateproductivitygrowth would vary directly with the rate of changeinL,n,defined astheportionoftotalnonfarmprivateemployment inthe(one-digit)manufacturingsector.70 Equations8-1and8-2oftable8reporttheresultsofthistest. Equation 8-1 shows that the manufacturing-sharevariableis significantwhen addedto the technicalmodelbuthasthe wrongsign. Whenit is added to the more complete social model, it still has the wrong sign but is statisticallyinsignificant.We conclude that this measure of sectoral compositiondoes nothelpaccountforvariationsinproductivitygrowth andshouldnotbe carriedforwardforfurtheranalysis.71 A complementaryvarianton the sectoral compositiontheme has emergedfromrecentMarxiandiscussionsof the process of accumula- tion. Some Marxistsdefinecertainsectors as nonproductivebecause theirworkersdo notcreatevalue,intheMarxianvalue-theoreticsense, butsimplyserve the functionsof distributingcommoditiesor realizing surplusvalue. If therewerea significantshiftof employmentintothese nonproductivesectors, accordingto thishypothesis,one mightreason- ablyexpectaretardationintherateofgrowthofaggregateproductivity. Wecantestthishypothesisinthesamewayaswehavealreadyexplored the deindustrializationhypothesis.WedefineL,, as the portionof total nonfarmprivateemploymentintheone-digitsectorsoftradeandfinance, insurance,andrealestate.Addingthisvariabletotherespectivemodels, 70. Thisvariablecouldalternativelyhavebeendefinedintermsof the proportionof employmentinthegoods-producingsector,butwechosemanufacturingforamoreliberal test of the effectsof sectoralshiftsbecausethegrowthof productivityhelduplongerin manufacturing-through1973-than inanyothermajorsector. Foranadditionalreviewof theeffectsof changesinsectoralcomposition,see Martin Neil Baily, "The ProductivityGrowthSlowdownby Industry,"BPEA, 2:1982, pp. 423-54. 71. Thereasonithasthewrongsignandisso significantinthetechnicalmodelappears toreflectthefactthatthemanufacturingshareincreasedduring1966-73whileproductivity growthdeclined;becausethetechnicalmodelcannotaccountfortheproductivitydecline duringthat period, it appearsstatisticallyin 8-1 that a risingmanufacturingshare is associatedwith slower productivitygrowth, a resultthat disappearsonce our social variablesareaddedtotheanalysis.
  • 53. 432 Brookings Papers on Economic Activity, 2:1983 Table 8. Sectoral Composition and Market Growth, 1948-79a Independent variable 8-1 8-2 8-3 8-4 8-5 8-6 0.019 0.016 0.030 0.019 0.025 0.017 (6.25) (7.46) (5.23) (4.54) (3.46) (4.46) Ag 0.165 0.136 0.118 0.122 0.062 0.120 (4.38) (3.28) (2.72) (4.37) (1.30) (4.27) ku, 0.404 0.414 0.426 0.395 0.812 0.442 (3.44) (4.70) (2.89) (4.36) (5.35) (4.77) j . ... 0.023 ... 0.024 ... 0.027 (2.24) (3.49) (4.01) Aw! . . . 0.058 . . . 0.075 ... 0.068 (1.26) (1.66) (1.49) z . . 0.083 . .. -0.075 . .. -0.083 (-3.52) (-2.28) (-3.49) pforp - 0.072 -0.037 -0.034 -0.040 -0.037 -0.037 (-3.19) (-1.84) (-1.26) (-2.01) (-1.16) (-1.75) C* . . . 0.010 .. . 0.009 . . . 0.011 (2.63) (2.35) (2.64) -0.217 -0.027 ... ... ... (-6.51) (-0.54) In . . . . . -. 0.553 -0.109 ... ... (-4.46) (-0.93) Ytr . . . . .. . .. -0.418 -0.040 (-2.62) (-0.40) Summary statistic R2 0.797 0.896 0.843 0.898 0.577 0.895 Standard error of estimate 0.007 0.005 0.006 0.005 0.009 0.005 Durbin-Watson 1.903 2.179 1.976 2.270 1.663 2.275 Source: Authors' estimates based on data cited in the appendix. a. The dependent variable is the decyclicized rate of change of hourly output, q*. The variable Im is the rate of change in the manufacturing share of unemployment; In, the rate of change in the nonproduction sector's share of unemployment; and Ytr,the trend rate of change in real manufacturing output. Given first differences, actual years of observation are 1949-79. The numbers in parentheses are t-statistics. The input-price variable is entered as pf in the technical model and Px in the social model. we would expect its coefficientto have a negativesign if the nonpro- ductive-sectorhypothesisis valid.72 Equations8-3 and8-4 reportthe resultsof this test. As was shown forthe manufacturingvariable,this compositionmeasureis significant 72. Foradiscussionofthispossibleeffect,seeAnwarShaikh,"TowardsaCritiqueof KeynesianTheoryontheRoleoftheState"(NewSchoolforSocialResearch,Department of Economics,September1980).To referto thesesectorsas nonproductivesectorsdoes notimply,of course,thatthe efficiencyof productioninthose sectors-that is, valueof the outputperlaborhourpurchased-is irrelevantor constantthroughtime. Growthof outputperhourinthesesectorsalsodeclinedafter1966.
  • 54. T. Weisskopf, S. Bowles, and D. Gordon 433 when addedto the technicalmodelbutinsignificantwhenaddedto the morecompletesocialmodel.(Inthiscase, atleast, thevariablehas the rightsign.)Wechoose notto carryforwardthisvariable. A thirdhypothesisaboutsectoralcompositionandmarketscale has beenmorewidelydiscussedintheBritishandEuropeanliteraturethan it has in the UnitedStates. Thishypothesisis most commonlylabeled Verdoorn's law or Kaldor's law. Although originallyand typically appliedto cross-sectionalcomparisonsof productivitygrowthwithin manufacturing,the Verdoornhypothesismaybe at least provisionally andinferentiallyappliedtovariationsinproductivitygrowthovertime.73 Accordingto the implicitlogic of this hypothesis, rapidgrowthin marketscale, resultingin rapidgrowthin marketedoutput,is likelyto resultinrapidgrowthinproductivityforeither(orboth)oftwoimportant reasons. First, particularlyin earlier stages of the development of domesticmarkets,rapidgrowthin effective demandis likely to make possibleimportanteconomiesofscaleintheorganizationandproduction ofindustrialoutput.(Theliteraturefocusesprimarilyonindustrialoutput becausethatsectoris thoughtto correspondmostclosely to traditional hypothesesofAdamSmithabouttheefficiencyeffectsofafinertechnical divisionof labor.)Second, even at laterstages of development,rapid andsustainedgrowthin outputis likelyto permitandencouragelarge- scale andlong-periodinnovationsin the techniqueandorganizationof industrialproduction,at least in partas a result of decliningworker resistancetotechnologicalchange.Oncetheseincreasesinproductivity growth are realized, of course, they are likely to result in further expansionsin the scale of outputwithina particulareconomythrough furtherextensionofthescaleofthedomesticmarket,throughexpansions of exports as a result of increasinginternationalcompetitiveness,or throughboth. This anticipationof positive feedback on the scale of 73. Thereis a scatteredliteratureon "Verdoorn'slaw." For a sampling,see the seminalpiecebyNicholasKaldor,originallywrittenin 1966,"Causesof theSlowRateof EconomicGrowthin the United Kingdom,"in Kaldor,FurtherEssays on Economic Theory(HolmesandMeier,1978),pp. 100-38;JohnCornwall,"Diffusion,Convergence, and Kaldor'sLaws," EconomicJournal,vol. 86 (June 1976),pp. 307-14; A. Parikh, "DifferencesinGrowthRatesandKaldor'sLaws,"Economica,vol. 45(February1978), pp. 83-91; R. E. Rowthorn,"A Note on Verdoorn'sLaw," EconomicJournal,vol. 89 (March1979), pp. 131-33; and Robert Boyer and Pascal Petit, "Employmentand Productivity in the EEC," Cambridge Journal of Economics, vol. 5 (March 1981), pp. 47-58.
  • 55. 434 Brookings Papers on Economic Activity, 2:1983 output leads to models of "cumulativecausation" in the Verdoorn literature.Thepolicyimplicationis clear:"Thecentralgrowthproblem ina capitalisteconomy," MichaelJ. Pioreconcludes, "becomesthatof howto organizedemandso thattherequiredexpansionis assured."74 OnesimpletestoftheVerdoornhypothesisispossibleandconsistent at least with the spiritof the availableliterature:productivitygrowth over time shoulddepend, otherthingsbeingequal, on past long-term trendsinindustrialoutput.Themorerapidthecumulativeexpansionof industrialoutputin the recentpast-and thereforethe morerapidthe recent expansionof marketscale-the morerapidwill be the current increasesin laborproductivity.Wefollowthe appliedVerdoornlitera- turein defininga variableto test thishypothesis,tracingthe growthof industrialoutputover a ten-yeartimehorizon,andcapturingits cumu- lative effects througha ten-yearend-of-periodmovingaverage.75We thusdefine Ytr= [(> Y,i,)/10], wheres is 0, . . , 9, andy., is theannualrateofgrowthofrealindustrial output. Equations8-5 and8-6 reportthese results.Again,as was shownfor the manufacturingvariable, and probablyfor the same reasons, the variableis statisticallysignificantbutwiththe wrongsignwhen added tothetechnicalmodel.Itis statisticallyinsignificantifaddedtothesocial model.76 CAPITAL SERVICES We noted in our originaldiscussion of capital intensity that the productivityof the utilizedcapitalstock will dependon the degreeof 74. MichaelJ. Piore, "TheTheoryof Macro-EconomicRegulationandthe Current EconomicCrisisintheUnitedStates,"WorkingPaper285(MIT,Departmentof Econom- ics, July1981),p. 20. 75. Theformulationof theten-yearmovingaveragefollowstheexampleof Vladimir Brailovsky,"IndustrializationandOilin Mexico:A Long-TermPerspective"(Ministry of IndustrialandNaturalResources,Mexico,September1980).We aregratefulto John EatwellandTomMichlforusefulconversationsaboutthetime-seriesapplicationsof the Verdoorn'slawanalysis. 76. Thefactthatthetrend-outputvariableis not significantdoes notfullyvitiatethe trend-growthanalysis.WenotethatourownanalysisoftheSchumpetereffectissomewhat
  • 56. T. Weisskopf, S. Bowles, and D. Gordon 435 nonobsolescenceoftheavailablecapitalstock.Weintroduceheresome alternativetests forthiseffect. One is to equate obsolescence with the age of the capital stock, postulatingthatarelativelyoldercapitalstock,otherthingsbeingequal, will providerelativelyfewer productivecapitalservices. (Thiswould presumealagintheadaptationofthemarketvaluationofcapitalgoods.)77 A second, morecomplicatedtestfollowsanideaproposedbyMartin NeilBaily.78Hearguesthattherelativeefficiencyofthecurrentavailable capitalstockwilldependsubstantiallyontheextentofpastunanticipated pricechangesin the relativeprice of inputscomplementaryto capital services, and particularlyin the relative price of energy inputs. If complementaryinputpricesremainpredictable,conformingto expec- tationsat the time of the originalpurchaseof the capitalstock, thena relativelylargefractionof thecurrentavailablecapitalstockwillremain nonobsolescent.If, incontrast,therehasbeena sharpupturninrelative energycosts since the originalpurchasesof the currentcapitalstock, Bailyconcludes, "energy-inefficientvintagesof capitalwillbe utilized less intensivelyandscrappedearlierfollowingariseinenergyprices."79 Welookedattwoalternativeversionsofthishypothesis,andtheresults arereportedinthenotebelow.80 Wecanexplorethe hypothesisthroughone furthertest. Particularly as highlightedby Baily,energy-priceshocksareviewedas reducingthe analogous;ourshastheadvantage,we think,of focusingmoredirectlyonfactorsrelated toinnovationandavoidingconfusionbetweentherateofgrowthoftheeconomyitself,on theonehand,andchangesinthepaceof innovationorthetechnicaldivisionof labor. 77. Forthisversionwe directlymeasuredtherelativeageof thecapitalstock,Ka, as theaverageageof industrialequipmentexpressedas a deviationaroundits meanforthe periodofobservationfrom1948to 1979.Whenthisvariable,expressedasarateofchange, is addedto equation3-2,ithastheexpectedsignandis statisticallysignificant.Whenitis addedtothesocialmodel,itbecomesinsignificant. 78. See Baily,"ProductivityandtheServicesof CapitalandLabor." 79. Ibid.,p. 20. 80. Webeginwiththepropositionthattheutilized,nonobsolescentcapitalstockmay bedefinedasK* = gnK,whereg, asabove,istherateofcapacityutilization;nisanindex ofthenonobsolescenceofcapital,with0s ns 1,measuredinunitsthatreflecttherelative obsolescenceoftheutilizedcapitalstock;and,asbefore,Kis themeasuredrealavailable capitalstock. Wethenproposethatn be a functionof unanticipatedpricevariabilityintherelative price of external inputs, n = (1 - pj-, with a > 0, where puis a measure of unanticipated pricechangesin the relativepriceof nature-basedinputswhicharecomplementaryto capitalservices,anduTisanadjustmentcoefficient.Wefurtherproposethatthisexpression
  • 57. 436 Brookings Papers on Economic Activity, 2:1983 relative efficiency of utilized capital inputs after the initial oil-price shockshitin 1973(withpotentiallycomparableeffects afterthe second wave of increasesin 1979).Interpretedquiteliterally,thissuggeststhat thepositiveeffectsofincreasesinthecapital-laborratioweredampened after1973.Thissuppositionis testedthrougha piece-wiseregressionin which the slope of the coefficienton the utilizedcapital-laborratiois allowed to vary after 1973.81 None of these tests, whose details are reportedin notes, provides supportfor the hypothesisaboutvariationsin the nonobsolescenceof the capital stock. While we continue to think that the hypothesis is plausible on theoretical grounds, we are unable to find evidence to support it.82 forpmcanbeformulatedineitheroftwoways.Oneis t( - a tU P(',/Pxt1) wherea is theaverageageof thecurrentstockoffixedcapital;mis theperiodoverwhich priceexpectationsareformed;andthe absolutevalueof thedifferencebetweenthetwo pricetermsintheexpressionembodiesthehypothesisthatunanticipatedpricechangesin eitherdirectionwouldreducethenonobsolescenceoftheutilizedcapitalstock. The samevariablecan be formulatedwithoutthe expressionforthe absolutevalue, indicatingthatunanticipatedpriceincreaseswillincreasetheobsolescenceof theutilized capitalstockwhileunanticipatedpricedecreaseswillhavetheoppositeeffect. Neitherformulationwasstatisticallysignificant,andthelatterversionactuallyhadthe wrongsign.Wealsotesteda versionof thisvariableinwhichpf was substitutedforp, in thedefinitionofp,. Thisvariablehadevenless statisticaleffect. 81. Use of piece-wiseregressionensuresthatwe test fora changeinthe slopeof the coefficienton thecapitalintensityvariableandnotsimplyfora changeintheinterceptof the equation,as we didwiththe dummyvariablesin table3, andthatwe constrainthe coefficientson theeffectsof capitalintensityto be equalatt = 1973andto allowthemto differthereafter. Addingthis variableto both models results in a coefficientwith the wrong sign; whateverthemeaning,itis difficultto sustaintheempiricalconclusionthatunanticipated externalvariabilityin inputprices,otherthingsbeingequal,eitherdampenedthe contri- butionof risingcapitalintensityorslowedtherateof productivitygrowth. 82. Wenoteherethatwe testedoneotherhypothesisconcerningpriceeffectsandthe productivityslowdown.MichaelR. Darbyhas proposedthatthe Nixon roundof price controlsartifically(andtemporarily)dampenedpricesandthereforeartificallyoverstated thevalueofrealoutput(withrespecttotrend),therebygeneratingartificallyhighestimates of productivitygrowthin 1972and1973.Heteststhishypothesiswithavectorof dummy variableslinearlyincreasingfrom1971:2to 1973:1andthenlinearlydecreasingbackto zero in 1974:4.We cannotperfectlyreproducehis tests because we areconstrainedto workwithannualdata. Butwe soughtan approximationby defininga dummyvariable
  • 58. T. Weisskopf, S. Bowles, and D. Gordon 437 FINAL ESTIMATION These sequentialtests provideonlyone additionalvariableforinclu- sion in a final round of estimations. Based on earlier results, and particularlyon the effects of addingvariablesto the social model, it wouldappearthatonlythemeasureofeducationalattainmentdescribed abovedeservesfurtherconsideration.Thissuggeststhatwe mighttreat the results reported in column 7-2 as the most complete possible operationalversionof thegeneralsocialmodel. The particularformof this finalspecificationseems to us relatively less importantthanthe full effect of all the additionaltests reportedin thissection. Wehavetestedas manyadditionalhypothesesas we could identifyin the literature.Theresultsseem consistent.Manyvariables, whenincludedinthesimpletechnicalmodelfirstreportedin3-2,appear to be significant.Whenaddedto the moreinclusivesocial model,only oneeffect-that of educationalattainment-holds up.Atthesametime, the basicresultsof the socialmodelitselfremainrobustandconsistent throughout. Thisstrengthensthe premisewithwhichwe began:therecentlitera- ture has not only been unable to explain much of the productivity slowdownbuthasalsobeenmisledbytheunderspecificationofthebasic technicalmodel on which it has built its analyses. The social model developed here can both providewhatappearto be the missingclues inthemysteryof decliningproductivitygrowthandcorrectsomeof the misperceptionsandbiases thathave resultedfromthis underspecifica- tion. In particular,thereappearto be fourimportantinstancesof under- specificationbiasinthe estimationsreportedinthese variouscompara- tive exercises: they involve v, the variablemeasuringchangesin edu- cationalattainment;If,the proxyforchangesin the sex compositionof thatassumesthevaluesof 0.5in 1972,1.0in 1973,and0.5in 1974.Onewould,according to Darby'shypothesis,expectapositivesignforthisproxy. Whenthisvariableisaddedtothetechnicalmodel,thevariableisstatisticallysignificant buthasthewrongsign.Whenitis addedto thesocialmodel,ithasthecorrectsignbutis statisticallyinsignificant,with a t-statisticof only 0.77. We cannotfully explain the inconsistencywithDarby'sresults,givenourannualdata,butwe suspectthathisresults sufferfrombiasas a resultof exclusionof oursocialvariables.See MichaelR. Darby, "TheU.S. ProductivitySlowdown:A Caseof StatisticalMyopia,"WorkingPaper1018 (NationalBureauof EconomicResearch,November1982).
  • 59. 438 Brookings Papers on Economic Activity, 2:1983 the laborforce; the coefficientson g, the rate of change of capacity utilization;andk11,the rateof changeof theutilizedcapital-laborratio. The firsttwo examplesof underspecificationbias reinforceprevalent conceptionsabouttheproductivityeffectsofchangesinthecomposition ofthelaborforce,andthusstrengthentendenciesto blametheunskilled andwomenfor the underlyingsources of stagnation.The second two examplesreflecttheanti-Keynesianstrandsof thoughtinrecentdiscus- sionsof macroeconomics:if the coefficientson g andA?garerelatively low (as in 3-2)andthe coefficientson kuarerelativelyhigh(alsotruein 3-2), these findingsreinforcethe beliefs of currentpolicymakers,who tendto relyheavilyon effortsto increasetherateofinvestmentdirectly throughprofitsubsidiesratherthanthrougheffortstoexpandthegrowth of effectivedemand.In eithercase, judgingby the resultsof oursocial model,thepotentialharvestofpoliciesgroundedinthistechnicalmodel willbe dramaticallyoverestimated. Policy Implications Wehaveidentifiedsomesocialfactorsaffectingaggregateproductiv- ity thathelpilluminatethe declineinproductivitygrowthinthe United States. In particular,we have concentratedon the effects of declining workintensityandlaggingbusinessinnovation.Attentiontothesesocial determinantsappears to provide some crucial missing clues to the productivitypuzzle. Does thisofferanyguidelinesforpoliciesto helpreviveproductivity growth?Welimitourselvesto twogeneralobservations. The firstis thatit is possible to addressproblemsof workintensity andbusinessinnovationthroughdirectpolicyintervention.Thesecond isthattheanalysispresentedinthispaperdoesnotandcannotdistinguish amongthe varietyof possiblepolicyapproachesto these socialsources oftheproductivityslowdown.Althoughthisanalysishelpstounderscore the importanceof the problems, it is incapableof rankingvarious alternativeson thebasisof eitherefficacyorpoliticaldesirability. Considerafewleadingalternatives:conservativesproposetorestore workintensitythroughintensifiedlabormarketdiscipline(and,wemight add,assaultsonunions)andtorevivebusinessinnovationbyunleashing privateenterprisefromthecollarofgovernmentregulation.Neo-liberals
  • 60. T. Weisskopf,S. Bowles, and D. Gordon 439 proposetorestoreworkintensitythroughanewtripartitesocialcontract amongbusiness,labor,andthegovernmentandsuggestplanninginstru- mentslikethoseof theJapanesetofosterlonger-termbusinessplanning andinnovation.Progressivesandleftistsproposetoraiseworkintensity byincreasingworkermotivationthroughmoreparticipatoryanddemo- craticorganizationof the workplaceand by rapidwage growth;they suggesta combinationof full-employmentprograms,democraticplan- ning,andrisingminimumwagesto spurgreaterbusinessinnovation.If necessarytheyrecommendsupplementingtheseinstrumentswithpublic innovationandinvestment.83 Choices amongthese alternativeapproachesinvolve clearconflicts in basic policy directionsand thereforeinvolve fundamentalpolitical questionsabouteconomicpriorities.Althoughthisanalysisofthesocial determinantsof the productivityslowdownhelpsdramatizethe impor- tanceofthiskindofpoliticaleconomicdebate,itisincapableofresolving it.Onemustreturntomorebasicconsiderationsofpoliticalandeconomic possibility and desirabilityto move from analysis to policy. If the productivityslowdownis nolongerso puzzling,policiesto addressthat slowdowncan at last be debatedwith the clarityand coherence they deserve. APPENDIX Variables and Data Sources LISTEDBELOWare the variablesenteringour empiricalanalysis and, whererelevant,the methodsused to compilethe time series. Except whereotherwisenoted, the dataapplyto the nonfarmprivatebusiness sectorof the U.S. economy.Thesourcenotesdo notprovidesufficient detailoneverydataadjustmentorcalculationbasedonthecitedsources; interestedreadersshouldcontacttheauthorsforfurtherclarification.84 C = Business-failure rate, fromEconomic Report of the President, January 1981, table B-91. 83. Wediscussthedifferencesamongthesepolicyapproachesindetailinparts2 and 3of Bowles,Gordon,andWeisskopf,BeyondtheWasteLand. 84. TheonlyvariablesnotlistedhereareE,D, andR,whicharederivedfromvariables reportedherebytextequations1and7, respectively.
  • 61. 440 Brookings Papers on Economic Activity, 2:1983 G = Ratioof actualto potentialoutput,basedon series provided by Bureauof Economic Analysis, as updatedin Surveyof CurrentBusiness, vol. 62 (April 1982), p. 25. J = Cost ofjob loss, calculatedas reportedin the text, supplied by JulietB. SchorandSamuelBowles. Sources reportedin theirpaper, "Conflictin the EmploymentRelationandCost of Job Loss," WorkingPaper6 (EconomicsInstituteof the CenterforDemocraticAlternatives,1983). K Realcapitalstock, definedas theweightedsumof thenet(1/4) andgross (3/4) values; mid-yearestimateswere obtainedby averagingprevious and currentend-yearvalues, based on U.S. Departmentof Commerce,Bureauof EconomicAnaly- sis, FixedReproducible Tangible Wealthin the United States, 1925-79(GovernmentPrintingOffice,March1982). Ka = Age of capital stock, based on series for gross stocks of equipmentin industry, from U.S. Bureau of the Census, Historical Statistics of the United States (GPO, 1976), Series F-517, and Bureau of the Census, Statistical Abstract of the United States. L = Basic BLS index of hours of all persons, as reported in Economic Report of the President, January 1981, table B-38. Lf = Percentageoflaborforcethatisfemale,fromU.S.Department of Labor, Employment and TrainingReport of the President, 1981(GPO,1981),tableA-2. Lm = Percentageof nonagriculturalemploymentinmanufacturing, from Employment and TrainingReport of thePresident, 1981, tableC-1. Ln = Percentageof nonagriculturalemploymentin trade and in finance, insurance, and real estate, from Employmentand TrainingReport of the President, 1981, table C-1. L= Percentageofthelaborforcebetweenagessixteenandtwenty- four, from Employment and TrainingReport of the President, 1981,tableA-5. Pf = Calculatedby the sameprocedureas thatfordeterminingPx, withBLS indexforfuelsinthenumerator. Px = Calculatedby dividingthe BLS quarterlyprice index for nonagriculturalcrudematerialsbythecorrespondingimplicit pricedeflatorforgrossdomesticproduct,basedondatafrom
  • 62. T. Weisskopf,S. Bowles, andD. Gordon 441 thenationalincomeandproductaccounts,updatedinSurvey of CurrentBusiness, vol. 62 (July 1982). Q = Indexof production-workerhourlyoutput,(Y!L) (1 + S). S = Ratio of nonproductionworkers to productionworkers in privatenonagriculturalestablishments,basedonU.S. Bureau of Labor Statistics, Employment andEarnings, United States, 1909-78 (GPO, 1979), updated in Employment and Earnings, June1982,pp. 2-3. U = Percentofnonagriculturallaborforcethatisunionized,based on Bureau of Labor Statistics, Directory of National Unions and Employee Associations, 1979, Bulletin 2079 (GPO, Sep- tember1980),incorporatingrevisionsreportedinBLS, "Cor- rected Data on Labor OrganizationMembership-1980," USDL Release81-446,September18, 1981. V = Medianyears of educationalattainmentof the civilianlabor force, from Historical Statistics of the United States, table 13,withlinearinterpolationsforearlieryears. W! = Based on new series reportedin ThomasE. Weisskopf, "A New SpendableEarningsSeries,"TechnicalNote2(Econom- ics InstituteoftheCenterforDemocraticAlternatives,1983). X = Energyconsumedby industry,measuredin Btuunits,based on Statistical Abstract of the United States (various years). Y = BasicBureauof LaborStatisticsindexof output,as reported in Economic Report of the President, January 1981, ta- bleB-38. Ytr = Based on index of industrialoutput,fromEconomic Report of the President, January 1981, table B-40. Z = BasedonsplicingofBLSdataformanufacturingonfrequency of work-timelost from industrialaccidents, periods before andafter1970.Formethodandsources,seeMicheleI. Naples andDavidM. Gordon,"The IndustrialAccidentRate:Cre- atingaConsistentTimeSeries,"TechnicalNote 1(Economics Instituteof theCenterforDemocraticAlternatives,1981).
  • 63. Comments and Discussion MartinNeil Baily: Manyof us havebeen strugglingover the pastfew years to understandthe slowdown in productivitygrowth. We have lookedforevidenceofdeclinesintherateoftechnicalchange,incapital services, orinworkeffort.Variousattemptshavebeenmadeto control fortheimpactofthebusinesscycle. Despiteourbestefforts,thereexists no consensus amongeconomists on the relativeimportanceof these alternativeexplanationsof theslowdown. Thisoriginalandprovocativepaperarguesthatthe slowdownis due tothecombinedeffectsofthebusinesscycle, areductioninworkeffort, anda diminutioninthe rateof innovation.Itdevelopsnewvariablesto proxyforthese lattertwo factorsandtests the resultseconometrically. I foundit animpressiveandvaluablepaper.I hadmanyproblemswith the results, so thatI am skepticalthatthe authorshave an explanation of the slowdowninwhichI canhaveconfidence.ButI certainlydo not dismisstheirfindings. ThereweretwofeaturesofthepaperthatIparticularlyliked.First,it didattemptto providea seriousrationaleforeachof thevariablesused to explainthe slowdown. Second, the econometricresults were very goodandwere surprisinglyrobustto theinclusionof othervariablesor to variationsinthetimeperiod. Turningto the criticisms,I beginwithgeneralcommenton method- ology.Thepaperusesanunconstrained,multivariableregression.Apart fromcyclicalmovements,however,thereareonlythreedistincttrends to be observedin postwarU.S. productivitydata.These consist of the growthratesoverthethreeperiodsdistinguishedbytheauthors.Itis all too easy tofindhalfadozenvariablesto "explain"thesethreeobserved rates of growthin a regression.Several studies in the literaturehave 442
  • 64. T. Weisskopf, S. Bowles, and D. Gordon 443 done well econometricallyusing very different sets of explanatory variables.Theauthorsdescribegrowthaccountingas tautological.That isnottrue.Itsproblemisthereverse,thatitreliesonstrongassumptions. But those assumptionsdo providea disciplineby constrainingcoeffi- cients.Regressionanalysissimplyselects thevaluesthatfitbest. Inadditiontomygeneralsuspicionoftheirmethod,Ihadtwospecific problemswith the authors' model. The first problem concerns the capacityutilizationvariable.Capacityutilizationis definedasGNPover potentialGNP. ButmovementsinGNPareveryhighlycorrelatedwith movementsinnonfarmbusinessGNP,thenumeratoroftheirproductiv- ity measure.Thismeansthatwhencapacityutilizationis multipliedby thecapital-laborratio,theresultisalmostequaltothedependentvariable times the ratio of the capital stock to potentialoutput. This makes spuriouscorrelationvery likely and probablyexplains why k, has a coefficientwell above the incomeshareof capital.Since boththe level and rate of change of capacity utilization also enter the equation separately,thepossibilitiesforspuriouscorrelationaremultiplied.The sumof thecoefficientson g, Aig,andk1,is equalto 0.96incolumn1-1of theirtable 1.Thatis suspiciouslyclose to unityandraisesconcernthat thereisalmostanidentityimplicitintheequation.Atfacevalueitimplies that an increase in capacity utilization,other things being equal, is reflectedalmostone-for-onein productivity.A cyclical adjustmentof thismagnitudeistwoorthreetimestheshort-runeffectthatIhavefound usingunemploymentas ameasureof thecycle. Not onlydoes theauthors'specificationexaggeratetheimpacteffect of slackcapacityonproductivity,butalsoit does notallowtheproduc- tivity loss to be regainedin a persistentrecession. If short-runlabor hoardingis a cause of the decline in productivityin a downturn,then onewouldexpectmuchof theexcess laborto be shedduringaperiodof persistent slack. Jeffrey Sachs found that persistent slack actually increasesproductivity,whichcouldbe trueif theremainingproduction is concentratedon high productivitycapitaland labor.' This issue is importantwhen the authorsaccountfor the slowdownin table 4. The loweraveragerateof capacityutilizationin the 1970scomparedto the 1960sprobablyaccounts for less of the slowdown than their table indicates. 1. JeffreyD. Sachs, "Real Wagesand Unemploymentin the OECDCountries," BPEA, 1:1983, pp. 255-89.
  • 65. 444 Brookings Papers on Economic Activity, 2:1983 I wantto discuss now the generalissues raisedby the paper.Have therebeendeclinesinworkeffortandintherateof innovationthatcan be reasonablyproxiedby suchvariablesas the industrialaccidentrate, the cost ofjob loss, andthe businessfailurerate?My basic reactionis thatthese proxy variablesare ratherdistantfromthe underlyingcon- cepts. Considerfirstthebusinessfailurerateas aproxyforinnovation. The paperis a littleunclearaboutthe interpretationof the business failurevariable.Bankruptcyis describedas a threatto business. This presumablywouldmeanthatmanagersinnovatewhenbankruptcyseems likely.Withthisinterpretation,bankruptcycanbetakenasanexogenous determinantof productivitygrowth.Butthenthevariableshouldnotbe cyclically corrected.Recessions shouldstimulateinnovation.The au- thors' preferredinterpretationis based on Schumpeter's idea that innovationcauses bankruptcy.Therearetwo problemswiththisview. The first is that it suggests that the failure rate is not exogenous. Productivitygrowthcausesbankruptcyratherthanvice versa. Second, I suspectthatmostbankruptciesarenotaresultofchangingtechnology. OsborneComputercertainlywent underbecause of innovationby its competitors,but the majorityof failurestake place amongsmallcon- structioncompaniesandretailingconcernsthatstartupandfoldallthe time,andthesefailuresarenotrelatedtoinnovation.(In1978,62percent ofallbankruptcieswereinthesetwoindustries.)Iamcurrentlyresearch- ing the questionof whetherinnovationhas slowed. It may well have doneso, butwe needabetterproxythanthebusinessfailurerate. I was also concernedabout the way in which the failurerate was manipulatedbeforebeingputintotheregression.Therawdata,givenin various issues of the Survey of CurrentBusiness, show by far the lowest failureratesoccurringfrom1943through1948.The ratethenrises to a peakin 1961.Thisiswellbeforetheslowdownbegan.Theirtransformed variableis shown in figure2 of the paper.It peaks in 1967andhas its lowestvaluesinthelate 1970s. TheauthorsallegethatonlyMarxianeconomistsallowforvariations inworkeffort.Thatis nottrue.Peoplehavebeenblamingproductivity problemson a lack of workeffortat least since biblicaltimes. Arthur Burnsblamedthecurrentslowdownonworkeffortina speechin 1977, and David Stern has developed this idea in detail.2The authorscite 2. ArthurM. Burns,"The Significanceof OurProductivityLag," commencement addressat the Universityof SouthCarolina,May 16, 1977;andDavidStern,Managing Human Resources: TheArt of Full Employment (Boston: Auburn House, 1982).
  • 66. T. Weisskopf,S. Bowles, andD. Gordon 445 evidenceof a breakdownin labor-managementpeace thatbeganin the late 1960s.Ariseintheindustrialaccidentrateatthetimealsoincreased alienation,they argue. Many of the anecdotes and also the data on accidentsapplyto the highlyunionizedmanufacturingsector. Butthat is aproblembecauseproductivitygrowthinmanufacturingdidnotslow downatalluntilafter1973.Thetimingdoes notlookright. The cost-of-job-lossvariableis, in principle,an appealingway to capturevariationsin the effective pressureon workers.In practice, I was uneasyabouttheway it turnedout. Thisseriesis showninfigure1 of the paperanddisplaysa very markedcycle thatmay be drivingits statisticalsignificance.This suspicion is fueled by the fact that this variable,unliketheauthors'othersocialvariables,holdsits significance in 1948-66.Whenoneabstractsfromthecycle, thetrendsdonotdowell in explainingthe slowdown.The variablereachesa maximumin 1961, thenfalls until 1969beforerisingagain.The averagevaluefrom 1973- 79, when the slowdown was most severe, is about the same as the averagevaluefrom1948-54,aperiodof rapidproductivitygrowth. Iwonderhowasimilarvariablewoulddoinothercountries.Certainly transferprogramshavegrowninEuropeaswellasintheUnitedStates. Butthe Europeanslowdownhascoincidedwitha seriousdeterioration inunemployment.In1982thesimpleaverageoftheunemploymentrates in GermanyandFrancewas 7.4 percent,two or threetimesits level in the 1960s.Andanaverageof56percentoftheunemployedhadbeenout of work for more than six months (comparedwith 17 percent in the UnitedStates).3Supposethese countrieshadhada productivityspeed- up.TheMarxistswouldprobablybe complainingaboutthebarbarityof asysteminwhichthereservearmyoftheunemployedallowedcapitalists to pressureworkersinthisway. Because therehas been a slowdown,thereis a naturaltendencyto select alltheevidencepointingtowarda declineinworkeffort.Butnot all the evidence points the same way. For example, Janice Hedges, writingin the MonthlyLaborReview, concludesthatjob commitment hasnotdeclined.4Moreover,myownworkontheslowdownbyindustry hasfoundthat,withinmanufacturing,itisthecapital-intensiveindustries 3. Organizationfor Economic Cooperationand Development, OECD Economic Outlook(Paris:July1983),pp.45-46. 4. Janice N. Hedges, "Job Commitmentin America:Is It Waxingor Waning?" Monthly Labor Review, vol. 106(July 1983), pp. 17-24.
  • 67. 446 Brookings Papers on Economic Activity, 2:1983 thathave hadthe biggestslowdowns.5This resultis consistent with a declineoccurringin capitalservices. It is inconsistentwiththe Weiss- kopf-Bowles-Gordonview thatlaborserviceshavedeclined. The authorstest a few alternativehypothesesaboutthe slowdown usingtheirequation.Giventhe problemswiththeirspecification,I am unsureof thevalidityofanyofthesetests. ButIwillcommentbrieflyon thetests oftheBailyhypothesis.Inonetesttheyuse pricevariabilityas a proxy for capital obsolescence. That is not unreasonable,but the particularvariabletheyuse impressedmeas afairlyweakone, so I was not surprisedat its poorstatisticalperformance.Thevariablethey use to test the Brunohypothesisis also quiteconsistentwithmy approach, andthattest does somewhatbetter. Theirsecondtestwasnotvalid.Totestforadeclineincapitalservices somevariablehastobeincludedintheregressionthatcarriesinformation aboutthisdecline-such asthepricevariableusedinthefirsttest orthe marketvalue of capital. Their second test does not include such a variable.A simpleproductionfunctionframeworkshowsthattheirtest could come out either way depending,arbitrarily,on the correlation betweenthedeclineincapitalservicesandthegrowthrateofthecapital- laborratio. Theauthorshavewrittentheirpaperforcefully,suggestingthatthey can solve the mysteryof the slowdown.I have respondedin kindwith some strongcriticismsof theirspecificationandvariables.But I do not wantto tip the scales too farthe otherway. The slowdownis such an interestinganddifficultpuzzlebecausethe evidenceis so hardto come by anddifferentpieces of it oftenpointindifferentdirections.Declines inthe rateof innovationandinworkeffortmaywellbepartof the story ofthe slowdown.Andtheauthorshavemadeaninterestingandoriginal attemptto test thesehypotheses. AlbertRees: Thisis aninterestingandhighlyoriginalpaper,butnotan easy one on which to comment.The modelpresentedis complexand includesmanyunfamiliarvariables. The authors'basic thesis is thatmost of the declinein productivity growthsincethemid-1960scanbeexplainedbytwofactors,adeclinein 5. MartinNeil Baily, "The ProductivityGrowthSlowdownby Industry,"BPEA, 2:1982,pp.423-54.
  • 68. T. Weisskopf, S. Bowles, and D. Gordon 447 workintensityanda declinein the propensityof businessto innovate. This leaves little groundfor roundingup manyof the usual suspects, suchas a declinein investmentin plantandequipmentor increasesin governmentregulation. I shallconfinemyremarksto thepartof themodelthatdealswiththe declinein workintensity.Let me firstsay thatI see nothinginherently implausibleaboutthishypothesis;indeeditis supportedbyagreatdeal of anecdotalevidence andsome scatteredstatisticalevidence on such mattersas ratesof absenteeism.I do have seriousdifficultieswiththe wayinwhichthehypothesisis modeled. Oneof thevariablesusedto representthedeclineinworkintensityis thechangein realspendableearnings,on the theorythatworkershave less motivationto work hardwhen theirreal earningsare not rising. Weeklyafter-taxearningsalso are partof the highlysignificantinde- pendentvariable,"cost-of-jobloss" (enteringtwice),thoughtheyenter thevariableinacomplicatedfashion. Conventionaltheory also assumes a relationbetween realearnings andproductivity,butwiththecausalitypointingintheoppositedirection. Insteadof assumingthat a decline in realearningscauses a declinein productivity,conventionaleconomistsassumethata declineinproduc- tivitycauses a declineinrealearnings.It is well knownthattime-series regressionswith no laggedvariablesarepoortools fordeterminingthe directionof causality.Observingahighcorrelationbetweenthenumber ofstorknestsinSwedenandtheSwedishbirthratedoesnotdiscriminate betweenthe theorythatstorksbringbabiesandthe theorythatbabies bringstorksand,of course,does notprovethecorrectnessof either. The authors'preferredmethod of cuttingthe causality knot is to replace the change in real spendableearningswith the second time derivativeofrealspendableearnings.Thishasbeendoneintheequations shownin theirtable 1. The rationalefor includingrealearningsas an explanationforworkintensityseemsto meto beweakenedbythisshift tothesecondderivative,andI donotknowwhatto makeoftheresults. Mystrongpriorbelief,whichis thatcausalityflowsfromproductivityto realwages, is unshaken,butthismaytestifyonlyto thestubbornnessof myadherenceto conventionaleconomics. Let me turnnext to anotherof the variablesused to representthe declineinworkintensity.Thisisthevariable"intensityofsupervision," chosento representtheeffectivenessof employercontroloveremploy-
  • 69. 448 Brookings Papers on Economic Activity, 2:1983 ees. This variableturnsout to be simplythe ratioof nonproduction- workerhourstoproduction-workerhoursinthenonfarmprivatebusiness sector.Theauthorscontendthatessentiallyallnonproductionworkers are engagedin the surveillanceor supervisionof productionworkers. This contentionis outrageous,particularlyas it appliesto miningand manufacturing.Itis correctforforemen,plantmanagers,andpersonnel departmentstaff. But all the people engaged in sales, advertising, distribution,accounting,finance,andresearcharenonproductionwork- ers.Typistsandbillingclerksemployedincentralheadquartersorsales brancheshundredsof miles fromminesor factoriesare consideredin this model to be engaged in the surveillanceof productionworkers. SurelyKarlMarx,who was an acute observerof the industrialscene, wouldhavebeenamusedby thenotion. Theratioof production-to nonproduction-workerhoursis one of the few variables in the model whose behavior is easy to understand intuitively.Itmustbehighlycyclicalandhencehighlycollinearwiththe explicitcyclicalvariableinthemodel,capacityutilization.Itistherefore no surprisethatit is insignificantwhenenteredseparately. The authorsalso use the accident rate as a variableto proxy for changesinworkingconditions.Thisvariableturnsouttobe surprisingly powerful,andI cansee no seriousproblemswiththeirinterpretationof it. Since many of my remarkshave been critical,let me conclude by sayingagainthatIfindthebasichypothesisofadeclineinworkintensity a plausible one. I wish, however, that it had been modeled more convincingly. GeneralDiscussion There was broadinterestamongthe participantsin the attemptto integratesocial factors in analyzingproductivity.At the same time, manywereunconvincedthatthevariablesusedbytheauthorscouldbe giventheinterpretationassignedto theminthepaper. RobertJ. Gordonobservedthat,becauseunemploymentdurationis a complicatedlaggedfunctionof the businesscycle, its cyclical corre- lationwith productivitymightnot be purgedby the authors'use of a dependentvariablecorrectedonly for capacityutilization.This could contributetothestatisticalsignificanceofj, thecost ofjob loss variable,
  • 70. T. Weisskopf, S. Bowles, and D. Gordon 449 which is constructedfromunemploymentduration.JeffreySachs re- called his finding (BPEA 1:1983) of a positive correlationbetween unemploymentdurationandproductivity,presumablyarisingbecause inefficientfirmsgo out of businessduringprolongedrecessions. Chris- topherSims noted thata positive correlationbetween unemployment durationandproductivitycouldreflectthebehavioroffirmsadjustingto changesin the labormarketandin theirdemandfor laborratherthan reflectingworkplacediscipline.Theinfluxof newlyunemployedat the beginningof a recessionlowersaveragedurationat the sametimethat productivityis reducedbecausefirmsdonotadjustemploymentfullyto the reducedlevel of production.As the recession deepens, firmsstart dishoardinglabor,thusboostingmeasuredproductivityatthesametime unemploymentdurationrises. Sims suggestedbreakingup the compo- nentsofj to determinewhateachcontributedseparatelyinaregression. SimsreiteratedMartinBaily'sconcernthatthecapitalintensityvariable was close to anidentitywiththe dependentvariable.Andhe observed thatthe authors'use of a "decyclicized"productivitymeasureas the dependentvariabledid not eliminatethe difficultybut only madethe equationharderto interpret.RobertGordonaddedthat the problem couldnot be dealtwithin any simpleway because it was a problemof simultaneityover decades-those with slower andfasterproductivity trends-not overyears. CharlesSchultzereasonedthatsomeofthesevariablesarenotproxies forthe socialfactorsbutmoreparalleltoproductivity,eithercoinciden- tallyorbecauseof acommoncausalfactor.Theexogenousshiftsinthe ratioof nonproductionworkersto productionworkersjust happenedto coincide with productivity shifts in the period being studied. The slowdowninrealwagegrowthandtheproductivityslowdownafter1973 couldbothbe dueto theoil-priceshock. Sachsurgedtheauthorstotesttheirthesisbyextendingtheirworkto othercountries.He notedthattheproductivityslowdownis auniversal phenomenonand that in most industrialcountries this slowdown is abruptandsignificantonly after1973.Thispointsto the oil shock and the consequent sluggishoutputgrowthas the maincandidatesfor an explanationof the productivityslowdown. He also arguedthatoutput levels andproductivitycouldbe relatedinmorecomplicatedways than those impliedby the simplecyclicaladjustmentusedby the authorsso thatmoreof theproductivityslowdownmightbe explainedinthisway.
  • 71. 450 Brookings Papers on Economic Activity, 2:1983 JamesTobinsuggestedthatthelawsandinstitutionalarrangementsthat determinethe likelihoodthata workerwouldlose hisjob differamong countriesandhave changedthroughtime;thus the importanceof this phenomenonforproductivitycouldbeexaminedmoredirectly.Samuel Bowlesrepliedthat,preciselybecausethestructureoflaborrelationsis so differentacross countries and historicalperiods, the response of workerswouldbedifferent.Thushedidnotbelievethepresentrulesfor the postwar U.S. economy could be easily extended either across countriesorbetweenhistoricalperiods. RichardCooper reasoned that, if the decline in work effort is a pervasivephenomenon,it shouldbe discernibleinindividualindustries oroccupationsinwhichproductiontechniqueshavenotchangedmuch. If decliningworkeffortcouldnot be foundin such situationsin which its effects would be easily observed, it would cast doubt on the hypothesisthatdecliningworkeffortwas responsiblefor slow produc- tivitygrowthintheaggregate.

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