Spatial Aspects of the Productivity Slowdown: An Analysis of U.S. Manufacturing Data
Author(s): Emilio Casetti and John Paul Jones III
Source: Annals of the Association of American Geographers, Vol. 77, No. 1 (Mar., 1987), pp.
76-88
Published by: Taylor & Francis, Ltd. on behalf of the Association of American Geographers
Stable URL: http://www.jstor.org/stable/2569203
Accessed: 26-03-2015 15:14 UTC
Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at
http://www.jstor.org/page/info/about/policies/terms.jsp
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 [email protected].
Taylor & Francis, Ltd. and Association of American Geographers are collaborating with JSTOR to digitize, preserve and
extend access to Annals of the Association of American Geographers.
http://www.jstor.org
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions
Spatial Aspectsof the Productivity
Slowdown: An Analysisof U.S.
ManufacturingData
Emilio Casetti* and John Paul Jones lilt
*Department
of Geography,Ohio State University,
Columbus,OH 43210-1360
tDepartmentof Geography,Universityof Kentucky,Lexington,KY 40506
thespatialdifferentiation
intheratesofchangeofmanufacturing
Abstract.We investigate
productivity
growth
intheU.S. Usingan application
ofthe"expansionmethod,"we focuson therelation
between
theproductivity
slowdownandtheSnowbelt-Sunbelt
shiftthatmaterialized
at approximately
thesame
timeduring
themid-1960s.
We findthatthespatialpatterns
ofmanufacturing
productivity
acceleration
weredifferent
beforeandafterthemid-1960s,
andwe suggestthata redirection
ofcapitalflowsis the
mechanism
behindthespatialpatterns
observedandtheinterrelations
betweentheslowdownand the
shift.
Key Words: productivity
Snowbelt-Sunbelt
slowdown,
shifts,
capitalflows,expansion
trend
method,
surface
expansions.
THE recentslowdown in productivity
growth the midpointof the ten-yearcensus periodsfrom
and thedeclineof theNortheastand Midwest 1940. Note thatwhereasthe Snowbeltdivisions
are majoreconomicissues confronting
theUnited have decliningratesof netmigration,
theSunbelt
fromnegative
States.They are causes, effects,and symptoms
of regionsdisplaya strongturnaround
and world to positiverates. Also shownin Figure 1 are esthe erosion in the positionof strength
dominancethatthe U.S. economyenjoyedin the timatesof theU.S. annualratesof growthin labor
in bothdurableand nondurablemanperiodimmediately
followingWorldWar II. Both productivity
contributed
to the inflationary
significantly
pres- ufacturing.These estimates,coveringthe 1950suresandhighunemployment
levelsofrecentyears. 66, 1966-73, and 1973-77 time periods, come
The continuedprosperity
of theU.S. economyde- fromKendrick(1980, 14). Both manufacturing
pends largelyupon the extentto which the pro- sectorsshow a decline in growthrates, and the
ductivityslowdown and the decline of the old declineis roughlycontemporaneous
withtheshifts
industrialcore regions are counteractedand re- in regionalnetmigrationrates.
versed.
This temporalcoincidencepointsto a possible
The crisis in the Northeastand Midwest has relationbetweenthetwoand suggeststhattheprobeen associated with acceleratedeconomic and ductivityslowdownmay also possess significant
populationgrowthin some regionsin the South spatial dimensions.Althoughconsiderableattenand West. The combinationof thesetrends,often tionhas been devotedto understanding
Snowbeltreferredto as the Snowbelt-Sunbelt
shift,began Sunbeltshifts,littlework has been done on the
at approximately
thesame timeas theproductivity spatial dimensionsof the productivity
slowdown
slowdownin the mid-1960s. The temporalcoin- and on the relationshipsbetweenthe slowdown
cidence betweenthe Snowbelt-Sunbelt
shiftand and the shifts.These relativelyneglectedissues
in Figure are thefocusof thispaper.
theproductivity
slowdownis illustrated
1. In it,thepercentagenetmigration
ratesfortwo
The productivity
slowdownis a decline in the
Snowbeltcensusdivisions(theMiddleAtlanticand rate of growthof productivity
thatconstitutesa
and fortwo Sunbeltdivisions negativeproductivity
East North-Central)
acceleration.In this paper
(the East and West South-Central)are plottedat we aim to identifysignificantspatial patternsof
Annalsof theAssociationofAmericanGeographers,
77(1), 1987,pp. 76-88
(D Copyright
1987 by Associationof AmericanGeographers
76
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions
Productivity
Slowdown
77
15.0-
10.0
5.0-
MA
_ _ _ _
~~~~~DURABLE
ENC
DECENNIALPERCENT
NET MIGRATION:
SELECTED CENSUS DIVISIONS
3.5
NON-DURABLE
_r
3
//
2
25
0.0
1
2.0
-5.0
-10.0
ESC
---
_
__
/
AVERAGEANNUAL
PERCENT
PRODUCTIVITYGROWTH:
DURABLEAND
NON-DURABLE
MANUFACTURING
I
-15.0
1940
1950
1960
1970
1980
Figure 1. The productivity
slowdown and Snowbelt-Sunbeltshifts.Migrationdata are percentagerates of net
migrationby census periodfortheMiddle Atlantic(MA), East NorthCentral(ENC), West SouthCentral(WSC),
and South Atlantic(SA) census divisions.Productivity
data are average annual percentagegrowthratesby manufacturing
typeand are takenfromKendrick(1980).
productivity
accelerationfortwotimeperiods,one omybeganin themid-1960s.It soon caused grave
precedingand theotherfollowingboththeSnow- concernbecause itwas takento signala worsening
belt-Sunbeltshiftand theproductivity
slowdown. of the competitivepositionof the U.S. economy
We use trendsurfaceexpansionsto estimatethe vis a vis othercountriesand to reducethe possiincreasesin wages and
spatial variationof a differential
equation from bilityof noninflationary
slowdown was interwhichmeasuresof accelerationare extracted.As incomes. The productivity
ofperverseecoonly statisticallysignificantspatial variationis pretedas bothcause and symptom
employedto derivetheaccelerationmeasures,the nomic trends that needed to be addressed,
resultingspatial patternscan be presumedto re- understood,and corrected.
veal substantive
realitiesrather
thanaveragednoise.
slowdownhas
on theproductivity
The literature
Our results show that before the onset of the been growingrapidly(see, e.g., Denison 1979;
Snowbelt-Sunbeltshiftthe rate of productivity Federal Reserve Bank of Boston 1980; Kendrick
growthwas highestin the old industrialcore re- and Grossman 1980; Maital and Meltz 1980;
gions,whereasaftertheshiftit became highestin Moomaw 1980). Explanationshave focusedon the
portionsof theSunbelt.In theconcludingportion qualityof labor inputs,the amountand direction
of the paper, we articulatetwo hypothesescon- ofinvestments,
regand theimpactof government
cerningthelinkagebetweentheshiftand thespa- ulation (Christainsenand Haveman 1981; Filer
tial aspectsof productivity
dynamics.
1980; Baily 198la). The mainpointsof theseexplanationscan be summarizedas follows:
The ProductivitySlowdown
Productivity
growthis a traitof modem economies. This is notto say thatepisodesof declining
productivity
cannotbe foundin themodernworld.
In contemporary
developed countries,however,
theruleratherthan
productivity
growthconstitutes
theexception.Increasingproductivity
growthgenerally identifieshealthy economic sectors, regions, or countries.
The productivity
slowdownin the U.S. econ-
of laborinputshas been
(1) A higherproportion
contributed
by women and youngerpeople since
slowdown.Increased
theonsetof theproductivity
laborparticipation
by womenresultedfromstructuralchangesin Americansociety;thelargerproportionof youngerpeople in the labor forcehas
been due to theagingofthe"baby boom" cohort.
Some authors suggest that female and young
workerscontributeless productivelabor inputs
(Perry1971; Perloffand Wachter1980).
(2) The rate of capital formationhas declined
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions
78
Casettiand Jones
(Kopcke 1980; Baily 1981b; Boucher 1981; Fraumeniand Jorgenson1981). Freshcapitalhas been
divertedfromdirectlyproductiveinvestments
into
expendituresrelated to governmentregulations
(Crandall1980, 1981; Myersand Nakamura1980;
Christainsenand Haveman 1981; Link 1982c).
Researchand developmentexpenditures
have also
declined(Mansfield1965; Terleckyj1974, 1982;
NSF 1977; Griliches 1980a, 1980b; Clark and
Griliches1981; Link 1982a, 1982b).
(3) The pressuresfromunions, consumerists,
environmentalists,
and assorted social welfare
proponentsproduced "excessive" government
regulationand a businessclimateunfavorableto
productivity
growth(Freemanand Medoff1979;
Abramowitz1981; Gollop and Roberts1982).
accelerationin the industrialcore regions,where
most of the manufacturing
is concentrated,was
translatedinto a favorableproductivity
performance at the nationalscale. Subsequently,productivitygains associatedwitha smallerbutgrowing
Sunbelteconomymay not have been enough to
compensatefortheproductivity
slowdownin other
partsof thecountry.If thisis thecase, thenspatial
in productivity
differentials
accelerationassociated withthe Snowbelt-Sunbelt
shiftsmay have
contributed
to thenationaldeclinein productivity
growth.
The Snowbelt-SunbeltShift
The shiftof populationandjobs fromSnowbelt
The spatialdimensionsoftheproductivity
slow- to Sunbeltconstitutesa complex clusterof notdown have attracted
littleattention.
In an analysis too-sharply
definedspatialchangesthatare partly
at theCensus Division level, Hultenand Schwab an accelerationand partlya reversalof previous
(1984) concludedthatthe slowdownin manufac- trends(Sternlieband Hughes 1975; Vining and
turinglabor productivity
was almostubiquitous, Strauss1977). The shiftbegan in the mid-1960s,
withonlyminorregionalvariations.On theother whenpopulationand economicactivitystartedto
hand, the recentinvestigations
of the spatial va- moveoutof establishedindustrial
regionsand large
lidityof the Verdoornlaw describedbelow sug- metropolitanagglomerations.At the same time
in theproductivity
slowdown otherplaces - notablyin theWest, in theSouth,
gestspatialpatterning
and pointtowardpossible linkagesbetweenthis some mid-sizedurbancenters,and some nonmetand Snowbelt-Sunbelt
shifts.
ropolitanareas - began to grow (Beale 1977;
patterning
Accordingto the Verdoornlaw, productivity Berryand Dahman 1977; Chinitz1978; Rees 1979;
grows fasterin economic sectorsthatare in the Sternlieband Hughes 1975, 1978). The dispersal
process of expanding.Cross-sectionalstate-level of populationand economic activitiesout of old
coresis typicalofthedeglomerative
trends
analyses (Casetti 1982b; Casettiand Jones1983; industrial
and documentedfora
Casetti 1984a, 1984b) indicatedthathigherpro- thathave been investigated
ductivity
growthtendstobe associatedwithhigher numberof countries(Richardson1980; Viningand
outputgrowthand thatthe productivity
response Pallone 1982).
to outputgrowthtended to be higherin some
In many respectsthe Snowbelt-Sunbeltshift
an unexpected
reversaloflong-run
Snowbeltregionsbeforethemid-1960sand higher constitutes
trends
in some Sunbeltareas in subsequentyears. This thatshaped the spatial structure
of the American
suggeststhatdifferent
spatialpatternsof produc- socioeconomicsystem(Viningand Strauss1977).
tivitydynamicsprevailedbeforeand aftertheon- Such a shiftcannotbe explainedin termsof cuset of the productivityslowdown and of the mulativecausation and growthpole theories,as
slow- thesetheoriesimplythatthemoredevelopedareas
Snowbelt-Sunbeltshift.As a productivity
down denotesa weakeningof thecompetitivepo- will grow comparativelymore and will induce
aroundthem.The failure
sitionof an economy,it is reasonableto expect growthin theterritories
changes in the spatial dynamicsof productivity of conventionalregionaldevelopmentconceptsto
as thoseunderway
re- anticipatetrendsas significant
wheneverthecompetitivepositionof different
altered.The economic de- in the U.S. has led to a varietyof attemptsto
gions is significantly
theoriesof regionalgrowth(Richardcline of the old industrialcores in the U.S. and reformulate
therapidexpansionof some regionsin the South son 1980; Casetti 1981; Peet 1984).
of regionalgrowthand
The majordeterminants
stronglysuggestsympathetic
changes in produccan
declineaccordingto thesenew reformulations
tivitydynamics.
as follows.The old industrial
A relationbetweenspatial patternsin produc- be summarized
cores
activitiesthatare estivitydynamicsand nationaltrendsis also plau- dependupon manufacturing
sible. Prior to the mid-1960s, the productivity pecially vulnerable to competitionfrom other
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions
Productivity
Slowdown
countriesbecause of higherlabor costs and more
obsoletecapitalin sucholdermanufacturing
areas.
Also, old industrial
coresoftenexperiencestronger
social and politicalpressuresby groupscommitted
to protectingthe environment,
the workers,and
theless fortunate
membersof society.Despitethe
positiverole suchpressuresplay,theybringabout
higherbusinesscosts thatcompoundtheperverse
dynamicsexperiencedby theseregions(Bluestone
andHarrison1982;Casetti1984c;Peet1983, 1984).
New businessesand plants,however,thatare disproportionately
thoseeconomicactivitiesin which
the U.S. is stronglycompetitivetendto locate in
a few Sunbeltareas thatare experiencingspectacular growth.
It is generallybelievedthatcapitalflowsplayed
a veryimportant
rolein theSnowbelt-Sunbelt
shift
(Clark and Gertler 1983; Clark, Gertler, and
Whiteman1986, 210ff.). Capital leavingregions
withpoor business climatesin the old industrial
in theSuncoresformorefavorableenvironments
belt producesjob shiftsthatalterthe traditional
interregional
migration
streams.An influxof capital will, however, tend to increase the rate of
productivitygrowth(Casetti and Jones 1983).
Therefore,it seems reasonableto hypothesizethat
the faster-growing
Sunbeltregionshave recently
accelerationthan
experiencedhigherproductivity
previously,whereas the opposite holds for the
Snowbeltareas thatare stagnatingor declining.
The Model
79
and laborinputs,so thatlaborproductivity
is given
by
P = YIL.
(1)
Let Z signifythelogarithmic
transformation
of P:
Z = lnP.
(2)
Denotethefirstand secondderivativeofa variable
withrespectto timet, as follows:
Z' = dZ/dt,and
(3)
Z" = dZ'/dt.
(4)
Since Z = lnP, the logarithmicderivativeof productivitywithrespectto time,Z', is the percentage rateof changeof productivity
over time:
Z' = (l/P)(dPldt).
(5)
The timederivativeof Z' is theinstantaneous
rate
of changeof percentageproductivity
change and
acconsequentlyis an indicatorof productivity
accelerationmeaceleration.Z" is theproductivity
surethatwe use in thispaper.
The methodemployedto investigatethespatial
variationof productivity
accelerationinvolves(1)
specifyingan equation capable of yieldingproductivityaccelerationby implicitderivationwith
respectto timeand then(2) expandingtheparametersof thisequationto producespatiallydifferentiatedestimatesof productivity
acceleration.The
specificsof the methodfollow. Let
Evaluatingthe spatialvariationof productivity
Z' = f(Z)
(6)
acceleration(the rate of change of the rate of
growth)is not an easy task. The straightforward
equationrelatingpercentagerate
approachto measuringaccelerationinvolvesfirst be a differential
to thelogarithmof proobtaininggrowthrates for two consecutivetime of changeof productivity
therateof changebe- ductivity.Taking the derivativeswithrespectto
periodsand thenestimating
tweenthetwo. Because thecalculationof a growth timeof bothsides of Equation(6) we obtain
rateamplifiesany noise presentin thedata, howZ = g(Z,Z'),
(7)
ever, thisapproachamplifiesnoise in theoriginal
data threetimes:(1) in producingthe
productivity
growthrates, (2) in obtainingaccelerationmea- whichexpressesthemeasureof accelerationused
sures, and (3) in computingrates of change of in thisinvestigation,
Z", as some functionof peraccelerationover space.
centagerateof changeof productivity,
Z', and of
We assess spatialvariationin theratesof change the logarithmof productivity,
Z. If Equation (6)
of productivity
of lev- definesZ' as an intrinsically
growthfromcross-sections
-linearfunctionof Z,
els of and rates of change in productivity.
The accelerationestimatescan be arrivedat by ordinoise amplificationwiththis methodologyis not narymultipleregression.To showit,letus specify
anal- f(Z) as a polynomialin Z
greaterthan that involved in growth-rates
yses.
...
Z=
Let Y and L denote,respectively,value added
(8)
ao+aZ+a2Z2+a3Z3+
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions
80
Casettiand Jones,
so that
Z' = Z'(a I + 2a2Z + 3a3Z2 .).
(9)
If cross-sectionalvalues of Z' and Z are available, regressionestimatesof the a's in Equation
(8) can be obtained and then employed using
Equation(9) to obtaincross-sectional
estimatesof
Z'. Specifically,accelerationestimatesby area can
be obtainedfromthe estimateda's and fromthe
Z andZ' values fortheobservations.However,Z"
estimatesobtainedusing this approachwould be
based on the assumptionthatthe Z'(Z) relation
specifiedby Equation(6) is stableoverthespatial
contextconsidered.In otherwords,it assumesnot
onlythatthesamefunctional
ofZ'(Z)
specification
is valid throughout
the area underconsideration
butalso thatits parametersare spatiallyinvariant.
The assumptionthatthe same specificationof
Z'(Z) is valid throughout
the periodis not unreasonable,especiallyif thetimeintervalconsidered
is nottoo large. The specificationof a functional
relationin termsof a low-orderpolynomialis one
of thesimplestpossible,and it is legitimateto use
a simplefunctionin theabsenceof reasonsfavoringa morecomplexfunction.No suchreasonsare
apparenthere. The assumptionthatEquation (8)
should hold with the same parametersover the
studyarea is, however,undulyrestrictive.
Regionaldifferences
in economicstructure
and
level of economicmaturity,
and differences
stemmingfromhistoricaland physicalfactors,suggest
thatthe parametersof Equation (8) mightnot be
spatiallyinvariant.A reformulation
of the model
thatallows thetestingfor,and estimationof, spatial parametervariationcan be easily arrivedat
usingtheexpansionmethod(Casetti1972, 1982a).
The approachused in thispaperis a modification
of thetrendsurfaceexpansionsdiscussedin Jones
(1984).
The expansionmethodis a techniqueforgeneratingmorecomplexterminalmodelsfromsimpler initialones and involves redefiningat least
some of the parametersof the initial model as
functionsof relevantvariables.The expandedparametersare thenput back intothe initialmodel
to producea terminalmodel. For appropriateinitial models and functionalspecificationsof the
expansions,theterminalmodelis intrinsically
linear and consequentlyits parameterscan be estimatedby ordinary
multipleregression.In thetrend
surfaceexpansionsthe parametersof the initial
model are expanded into polynomialsin the coordinatesof areal centroids.
Suppose, forinstance,thatwe selectthedifferentialequation
Z=
ao+aZ+a2Z2
(1 0)
as theinitialmodel. Equation(10) is a specialcase
of (8) and is theequationthatwill be used in the
empiricalanalysesdescribedlater.A quadratictrend
the
surfaceexpansionof (10) involvesredefining
parametersao, a,, and a2 of (10) into quadratic
polynomialsin the spatialx-y coordinatesof the
observations,which in this studyare state centroids:
ao = a00 + a0jX + a02Y + a03X2
+ a04Y2 + a05XY,
al
(11)
= a10 + aj1X + a12Y + aj3X2
(12)
+ a14Y2 + a15XY, and
a2
=
a20
+ a2IX
+ a22Y
+ a24Y2 + a25XY.
+ a23X2
(13)
sides of Equations(11),
Replacingtheright-hand
in
(12), and (13) forthecorresponding
parameters
Equation (10) yieldsan 18-termterminalmodel.
This model is capable of estimationby ordinary
multipleregression.Specifically,stepwiseregressionor backwardselectioncan be used to estimate
theterminalmodel thathas the largestR2 and all
from
regressioncoefficients
significantly
different
in thisestimated
zero. The appropriate
parameters
intotheexpansion
equationcan thenbe substituted
Equations(11), (12), and (13) in orderto specify
of theinitial
thespatialvariationof theparameters
model.
on polynomialregressionsand on
The literature
trendsurfaceanalysesnotesthatsuccessivepowers of temporaland/orspatial coordinatescan
produce highlycorrelatedvariables. This multicollinearitycan pose a seriousproblemif all the
termsin a polynomialareincludedin,a regression.
The techniquessuggestedforobviatingthisproblem have includedorthogonalpolynomials,ridge
regressions,and principalcomponentsanalysis.
The approachadoptedhere involvesobtaining
varimaxrotatedprincipalcomponentsof thepowersof theobservations'coordinatesand thenusing
these to expand the initialmodel. Expansionsin
termsof rotatedprincipalcomponentswere carriedout by redefining
thecoefficients
ao, a,, and
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions
Productivity
Slowdown
81
a2 of Equation(10) as linearfunctions
of variables 1981, 201ff.).For each regressionfourtestswere
executed,each based on a different
specification
PI, P2, -.- :
of theweightmatrix,W:
,
+
+
+
ao = a00
ao pI
a, = al0 + allp,
a02P2
(14)
*--
+ aI2p2 + ...,and
a2 = a20 + a2IpI + a22p2 + *-
,
(15)
(16)
wherethep's are rotatedprincipalcomponentsof
X, Y, X2, Y2,andXY whenquadratictrendsurface
ofX, Y, X2, y2,XY,
expansionsare contemplated;
X3, Y3, X2Y, and XY2 when cubic trendsurface
expansionsare desired,and so on.
Expansionsin termsof rotatedprincipalcomare
ponentsof the coordinates'transformations
vastly preferableto using the rotatedprincipal
componentsof variablesappearingin trendsurface expansions.They constitute
a convenientapproachof generalapplicability
to theinvestigation
of the spatialor temporalvariationof theparameters of an initialequation using the expansion
method.Rotatedprincipalcomponentsof the coto a trend
ordinatetransformations
corresponding
surfaceof a givenorderfora givenspatialsetting
needs to be done only once and can be used repeatedlyto carryoutexpansionsof different
initial
models. Such reusabilityof the rotatedcomponentsroutinizesthe applicationof the expansion
methodto investigating
the spatialvariationof a
model's parameters.It is also likelyto solve multicollinearity
problemsthatdo not arise fromthe
initial model itself. This approach proved adequate to solve themulticollinearity
problemin the
empiricalanalyseshere.
The stepwiseregressionand backwardselection
proceduresemployedin theestimationof terminal
the
modelsrelyupont (or F) testsfordetermining
variables that are significantlyassociated with
andshouldbe retained.These
population
parameters
significancetestsare based, however,on the assumptionthatthe errortermsassociatedwiththe
a significant
observationsare independent;
spatial
of regressionresidualsis inconsisautocorrelation
tentwithsuch independence.Spatial autocorrelation of the regressionresidualscould resultfrom
errortermsproducedby spatiallyautoregressive
of theregression
processesor by misspecification
model. A failureto incorporate
systematic
parametervariationin a regressionmodelconstitutes
potentialmisspecification.
This reasoningsuggestedthattestsforautocorrelationshould be performedfor all the regresin thisinvestigation.
The testscarried
sionsreported
out were based on the I statistic(Cliffand Ord
W(ij) = 1 if d(ij)<200
miles,
else W(ij)=0,
W(ij) = 1 if d(ij)<400
miles,
else W(ij)=0,
W(ij) = 1 if d(ij)<600
else W(ij)=0,
miles,
and
W(ij) = 1 if d(ij) < 800 miles,
else W(ij) = 0
where W(ij) is the entryof the weightmatrix
to observationsi and j, and d(inj)
corresponding
is the distancein miles betweenthe locationsof
observationsi and j. Here the observationsare
states, and the distancesare between-statecentroids.These specificationsof the weightmatrix
W allow testingfor spatial autocorrelation
at the
local scale (200 and 400 mi.) and at the regional
scale (600 and 800 mi.), and have alreadyproved
usefulfordetectingspatialautocorrelation
among
residualsin regressionsemployingstatelevel data
(Jones1983).
Analysis
The purposeof theempiricalanalysispresented
in thissectionis (1) to determinewhetherstatisticallysignificantspatial patternsof productivity
accelerationexist and (2) whethertheydifferbeforeand afterthe onset of the Snowbelt-Sunbelt
slowdown.It is useful
shiftand oftheproductivity
to pointoutthattheanalyseshere,as well as those
by Hultenand Schwab (1984), are based on agdata and do notaddressthe
gregatemanufacturing
comparativeimpactsof spatialvariationin indusiftheseinvestigations
are
trymixes.Undoubtedly,
attentionhas to be given to inpursuedfurther,
dustrymix effectsand to the spatial impactsof
in productivity
differentials
industry
dynamics.The
occurrenceof significantspatial patternsof productivityaccelerationneeds, however,to be investigatedand establishedfirst.
The primarydata used in our analysesare (1)
the numberof manufacturing
productionworkers
value added for
and the aggregatemanufacturing
theyears 1954, 1963, 1967, and 1977 forthe48
coterminous
statesof theU.S. plus theDistrictof
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions
82
Casettiand Jones
Table 1. Regression Resultsa
Columbiaand (2) thegeographicalcoordinatesof
theseareal units.
1954-63
The 1954, 1963, and 1967 manufacturing
data
Z'=
.04355 + .OlOlSZ + .00167Z2
were takenfromthe 1977 Cityand CountyData
(25.58)b
(1.62)
(.08)
Book (U.S. Bureau of theCensus 1979); the 1977
R= .254
R2 = .064
data come fromthe 1980 StatisticalAbstractof
I(200)C = .694
I(400) = 2.018
theU.S. (U.S. Bureau of The Census 1980). The
I(600) = 1.263
I(800) = .234
value added was convertedintoconstant1967 dollars. From these sources, we calculatedthe per- 1967-77
Z'=
.02022 + .00336Z + .05870Z2
centageratesof changeof productivity
over time
(10.80)
(.48)
(2.29)
intervalsencompassing1954-77 and logarithms
R= .320
R2 = .100
of productivity
at the midpointof the intervals.
I(200) = - .274
I(400) = .311
The x-y geographicalcoordinatesof the state
I(600) = - .155
I(800) = .543
centroids
arefromDouglas (1932). Thesedatawere
firstreplaced by deviationsfromthe respective 1 954-63 d
Z=
.04353 + .01213Z- .0029-P32
means.These deviationswereused to generatethe
(- 2.57)
(38.91)
(2.44)
transformations
that appear in second-, third-,
+ .01424Zp32
fourth-,and fifth-degree
polynomialtrendsur(2.64)
faces. These setsof variableswerethenseparately
R= .539
R2 = .291
subjected to principalcomponentsanalysis folI(200) = - .016
I(400) = .604
lowed by varimaxrotation.Onlycomponentswith
I(600) = .538
I(800) = .374
eigenvaluesgreaterthanone wereretained.These
manipulations
produced2 componentsfromthe5- 1967-77d
Z'=
.02033 + .01561Zp31 + .07900Z2
termsecond-degreepolynomialvariables,3 com(12.07)
(2.04)
(3.29)
ponentsfromthe9-termthird-degree
polynomial,
+ .05184Z2p32
. 10572Z2p33
4 componentsfrom the 14-termfourth-degree
(2.07)
(-3.01)
polynomial,and 4 componentsfromthe 20-term
R
R2 = .308
.555
fifth-degree
polynomial.The ith varimaxrotated
I(200) = - .0602
I(400) = - .202
principalcomponentcomputedfromthevariables
1(600) = -1.123
I(800) = -.024
appearingin a polynomialtrendsurfaceof degree
a
=
Z'
instantaneous
percentagerateof growthof manufacbe denotedas Pij
j will henceforth
forthe intervals1954-63 and 1967turinglabor productivity
Separateanalyses were carriedout forthe pe- 77.
=
Z
at the
naturallogarithmof manufacturing
productivity
riodsrespectively
precedingand followingtheonof thetimeintervals1954-63 and 1967-77.
set of the Snowbelt-Sunbeltshift.The 1954-63 midpoint
b t-valuesare in parenthesesunderthe respectiveregression
and 1967-77 timeintervalswere chosen because coefficients.
C StandardizedI statisticscalculated fromthe regressionretheycover the endpointsof the 1954-77 timepesiduals usingthe four-weight
matricesspecifiedin the text.
riodforwhichpostwardata are available and bed Obtainedby backwardselectionfromexpansionsin terms
cause theystraddletheonsetoftheshift.The 1963- of third-degree
varimaxrotatedcomponents.
67 period was skipped on the groundsthat the
shiftsmaterializedapproximately
at thattime.The
the validityof thesetestsis open to
tocorrelated,
analyses involved(1) specifyinga suitableZ'(Z)
is a potentialindifunction,(2) specifyingand estimatinga suitable question.This autocorrelation
ofthemodel. The
trendsurfaceexpansionofZ'(Z), and then(3) ob- catorof spatialmisspecification
accelerationby 1967-77 regressionsshow a statisticallysignifitainingestimatesof productivity
stateforthe 1954-63 and 1967-77 timeintervals. cantquadratictermand no evidenceof spatialauThese estimates were then summarized, dis- tocorrelation.
We experimented
withvarioustrendsurfaceexplayed, and interpreted.
Aftersome experimentation
theZ'(Z) equation pansionsby expandingtheZ = a + bZ + cZ2 equawas specifiedas a second-degreepolynomial.Es- tionintotrendsurfacesof degrees1 through5. In
timates of the nonexpanded Z' = a + bZ + CZ2 the first-degree
expansionx-y coordinateswere
equationare shown in the firstand second parts used. In the expansionsof degree 2 through5,
of Table 1. None of thecoefficients
forthe 1954- varimaxrotatedprincipalcomponentsoftrendsur63 regressionare statistically
but be- face termswere employed.The terminalmodels
significant,
cause the regression'sresidualsare spatiallyau- wereestimatedforthe 1954-63 and 1967-77 data
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions
Productivity
Slowdown
83
theregres- withlargerproductivity
usingbackwardselectionand retaining
accelerations
foundin New
sion stepwiththelargestR2 in whichall variables England,the upperMidwest,and the Northwest.
are significant
at p S .05. Spatial autocorrelation Loweraccelerations
prevailin theSouthand West.
testson the residualsfromthese ten regressions Some elementsof thispatternremainin the 1967yielded no significantautocorrelation
for any of 77 map (Fig. 3), in which the states along the
thefourweightconfigurations
considered.
Canadian borderretainhighlevels of acceleration
The regressionsforthe earlyperiodindicate relativeto theremainderof thecountryand some
theexistenceof spatialvariationin theparameters southernstatesretainlow values. In the 1967-77
oftheinitialequationeven forexpansionsin terms period,however,highaccelerationsare also found
of a first-degree
polynomial.For thelatterperiod in Texas and Louisiana, two stateslocated in a
only the expansionsof thirddegreeor higherin- regionthatpreviouslyhad consistently
low scores,
volve spatial terms.The statisticallysignificant whereasaccelerationvalues in thelowestquartile
spatialtermsdemonstrate
the existenceof spatial materializein some New England and western
in the initialmodel's parameters.
states.
instability
Individualaccelerationsby statewere obtained
A comparativepictureof accelerationchanges
fromthe derivativeswithrespectto time of the is providedin Figure4. This map is based on an
regressionequations, using estimatedregression indexconstructed
the 1954-63
by firstconverting
coefficientsand productivitydata as shown in and 1967-77 accelerationvalues to "standardEquation (9). The accelerationestimateschange ized" accelerationsand thentakingthedifference
somewhatwithdifferent
expansions.The overall betweenthetwostandardized
foreach
accelerations
spatial patternsthattheyproduce, however,are state. Standardizedaccelerationsare in deviation
quitestableforexpansionsof sufficiently
highde- fromthe U.S. mean dividedby the standarddegree. Specifically,the same statestend to have viationfortheU.S.
overthesametime
This indexis unaffected
highestand lowestaccelerations
by theoverallnational
periodacrossall theexpansionsintotrendsurfaces decline in accelerationduringthe studyperiod.
of thirddegreeor higher.Therefore,we selected Minorchanges(from- 0. 10 to 0. 10) characterize
thethird-degree
trendsurfaceexpansionsforfur- thosestatesthatmaintainedtheirrelativeposition
therconsideration.The regressionresultscorre- between1954 and 1977 (thesestatesare shownin
spondingto these expansions are shown in the whitein Fig. 4). Figure4 revealsthatstateswith
thirdand fourthparts of Table 1. Acceleration standardizedaccelerationstabilitycan be foundin
estimatesbased on these regressionswere com- the West, South, and North-Central
Census Reputedforstates,ranked,and mappedby quartiles. gions, whereasmoderateor large declines domiThe maps forthe 1954-63 and 1967-77 periods nate in New England. Moderate increases
are shownrespectivelyin Figures2 and 3.
characterizethe midsectionof the country(IlliFigure 2 reveals a strongnorth-south
pattern, nois, Iowa, Kentucky,and Missouri),some westAccelerationby Regions and Divisions
Table 2. Productivity
1967-77
1954-63
NortheastRegion
New England
Middle Atlantic
North-Central
Region
East North-Central
West North-Central
South Region
South Atlantic
East South-Central
West South-Central
West Region
Mountain
Pacific
a
ACa
SACb
AC
SAC
.4447
.5149
.3044
.2638
.2106
.3018
-.4547
-.3649
-.3811
-.7302
.1006
-.0981
.6306
.62
.72
.42
.36
.28
.42
-.67
-.54
-.56
- 1.06
.13
-.16
.88
-.0283
-.0601
.0353
.0467
.0373
.0534
-.0070
-.0258
-.0803
.1089
-.0019
.0145
- .0458
- .23
- .45
.23
.31
.24
.35
- .07
-.21
- .60
.75
-.04
.08
- .35
Accelerationtimes 100.
acceleration(accelerationin deviationfromthe U.S. mean dividedby the standarddeviationforthe U.S.).
bStandardized
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions
Casetti and Jones
84
-2.52 -0.22 0.14
0.42
2.14
accelerationforthe 1954-1963 timeperiod.
Figure 2. Estimatesof productivity
ern states (Arizona, Nevada, and Utah), and
Oklahoma and NorthDakota. Increasesof more
than 1.00 are confinedto the Sunbelt states of
Florida, Alabama, Louisiana, Texas, New Mexico, and to Wyoming.Declines,on theotherhand,
occur to a largerextenton the northeastern
seaboardand in thesouthernstatesof Arkansas,Mississippi, Virginia,and the Carolinas. The largest
declines are confinedto northern
states:Oregon,
Idaho, South Dakota, Maine, and New Hampshire.Thus, althoughstandardized
accelerationincreases, decreases, and stabilitycan be foundin
manyareas of the country,the overall pictureis
one of increases in a handfulof southernstates
combinedwitha contiguousregionof decline or
at beststabilityin theindustrial
and northern
states
of the East.
A pictureof the change in productivity
accelerationat the census region and census division
level of resolutionis given in Table 2. The accelerationmeasures for the 1954-63 and 1967-77
timeperiods(shown in Cols. 1 and 3 of Table 2)
were obtainedby takingthe mean of theacceleration values forthe statesin each regionand division; columns 2 and 4 of the table contain
standardized
accelerations.Contrasting
theentries
in Columns 2 and 4 of Table 2 shows thatthe
Northeastregionsuffereda majordecline in productivity
acceleration,thattheSouthwas thelargestrelativegainerin acceleration,
andthattheWest
andNorth-Central
regionsexperienced
littlechange.
At the division level the clear "winner" is the
West South-Central,
while theclear "losers" are
theNew Englandand Pacificdivisions.The overall pictureemergingfromTable 2 and fromFigures 2, 3, and 4 leads us to speculateabout the
mechanismsthatproducedit.
Discussion
Prosperouseconomiesare characterized
by productivityacceleration.This is whytheproductivityslowdownbecamethefocusof publicconcern.
Approximatelycoincidentwith the productivity
growthslowdown were the shiftsof population
andjobs describedearlier.How can we relatethe
productivity
slowdownto theseshifts?
The populationandjob shiftscan be creditedto
theflowof capitalout of areas formerly
thefocus
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions
ProductivitySlowdown
ACCELERATION x 1X
85
_
-0.28 -0.07 0.01 0.03 0.44
accelerationforthe 1967-1977 timeperiod.
Figure 3. Estimatesof productivity
economiesand laterthefocusof Conclusion
of agglomeration
concernover business costs and
entrepreneurial
businessclimate.The worstbusinessclimatesmay
Our findingsindicatethatthespatialpatternsof
have occurred,however,in Snowbeltareas with
accelerationin theU.S.
productivity
manufacturing
This
acceleration.
andproductivity
highproductivity
beforevs. aftertheondifferent
significantly
were
population
the
between
linkage
a
points toward
and the Snowslowdown
productivity
the
set
of
slowand employmentshiftand the productivity
and jobs. A
in
shift
population
belt-Sunbelt
gainswere
down: Beforetheshift,theproductivity
acceleration
productivity
between
correspondence
the
As
Sunbelt.
in
the
than
Snowbelt
higherin the
sense that
in
the
was
detected
growth
and
regional
businessclimateslowlybecame morefavorablein
pein
the
earlier
growth
with
lower
regions
some
the Sunbelt, investmentsstartedto respond to
also
were
West
South-Central,
the
as
such
riod,
proto
than
more
business climate differentials
acceleration.In
by low productivity
characterized
ductivitydifferentials.
to bothhigh
these
areas
shifted
second
period
the
It seems legitimateto hypothesizethatthecapConacceleration.
productivity
higher
and
growth
proof
higher
areas
from
away
ital movements
and
high
growth
acceleration
high
formerly
versely,
ductivity growth toward areas where the
con- areas such as theNortheastshiftedto "perverse"
growthwas sloweror stagnating
productivity
dynamicsandto lowerratesof growth.
productivity
productivity
overall
the
to
tributedsignificantly
Perhaps the coincidence between Snowbeltdynamicsin the U.S. Perhaps in the futurethe
reversewill occur. As the Sunbelt maturesand Sunbeltshiftsand spatialpatternsof productivity
takes on a largershareof Americanmanufactur- accelerationreflectstheoutflowof resourcesfrom
accelerationand into
accelerationin the Sunbelt areas of higherproductivity
ing, the productivity
accelerationbutbetmay morethancompensateforthe lowerproduc- areas withlowerproductivity
climates.
ter
business
tivityaccelerationin some of the old industrial
The debatesover thecauses of theproductivity
to an increasein prostates.This could contribute
slowdownhave pointedout thatabout40 percent
ductivitygrowthat thenationallevel.
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions
Casetti and Jones
86
CHANGE IN SCORES
-275 -1.00 -0.10 0.10 1.00 4.83
accelerationbetweenthe 1954-1963 and 1967-1977
Figure 4. Differencein statestandardscores of productivity
timeperiods. A negativevalue indicatesa lowerstandardscore forthelatterperiod,and a positivevalue indicates
a higherstandardscore forthe latterperiod. States withlittlechange in standardscores are blank.
of thedecline in growthsince 1965 cannotbe exmethods.The
aggregate-level
plainedby traditional
growth
failureof pastresearchto treatproductivity
as a spatiallycomplexphenomenonmayhave contributedto the inadequacyof theseanalyses. The
of capital flowsthatbegan duringthe
redirection
1960s is a spatial forcewithmajor systemicimas an aspacts. Ratherthantreatingproductivity
patial phenomenonunrelatedto the spatial shifts
rein populationand jobs in thiscountry,further
to the regional
search should relate productivity
dimensionsof economicand demographicdynamics.
References
Abramowitz, M. 1981. Welfarequandariesand productivityconcerns. American Economic Review
71:1-17.
Baily, M.N. 1981a. Productivityand the services of
capital and labor. BrookingsPapers on Economic
Activity1:1-65.
growthslowdownand
. 198lb. The productivity
capital accumulation.AmericanEconomic Review
71:326-31.
Beale, C.L. 1977. The recentshiftsof United States
populationto nonmetropolitan
areas, 1970-75. InternationalRegional Science Review 2:113-22.
Berry, B.J.L., and Dahman, D. 1977. Populationredistribution
in theUnitedStatesin the 1970's. Populationand DevelopmentReview 3:443-71.
Bluestone, B., and Harrison, B. 1982. The deindustrializationofAmerica:Plant closings,community
abandonment,and thedismantlingof basic industry.New York: Basic Books.
Boucher, T. 1981. Technical change, capital investin the U.S. metalworking
ment,and productivity
industries.In Aggregateand industry-level
productivity
analyses,ed. A. Dogramaciand N.R. Adam,
pp. 93-122. Boston: MartinusNijhoff.
Casetti, E. 1972. Generatingmodels by the expansion
method: Applications to geographical research.
GeographicalAnalysis4:81-91.
. 1981. A catastrophemodel of regionaldynamics. Annals of theAssociationof AmericanGeographers71:572-79.
. 1982a. Mathematicalmodellingand theexpansion method.In Statisticsfor geographersand social scientists, ed. R.B. Mandal. New Delhi:
ConceptPublishing.
. 1982b. Technological progress,capital deepening, and manufacturing
growthin the U.S.: A
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions
Productivity
Slowdown
regional analysis. Environmentand Planning A
14:1577-85.
. 1984a. Manufacturing
productivity
and snowbeltsunbeltshifts.EconomicGeography4:313-24.
. 1984b. Verdoornlaw and the componentsof
manufacturing
productivity
growth:A theoretical
model and analysis of U.S. regionaldata. In Regional and industrialdevelopment
theories,models
and empiricalevidence,ed. A.E. Andersson,W.
Isard, and T. Puu. New York: Elsevier Science
PublishersB.V. (North-Holland).
1984c. Peripheralgrowthin matureeconomies.
Economic Geography60:122-31.
Casetti, E., and Jones,J.P., III. 1983. Regionalshifts
in the manufacturing
productivity
responseto output growth:Sunbelt versus snowbelt. Urban Geography4:285-301.
Chinitz, B. 1978. The declining Northeast: Demographicand economicanalyses. New York: Praeger.
Christainsen,G.B., and Haveman, R.H. 1981. Public regulationsand the slowdown in productivity
growth.AmericanEconomicReview 71:320-25.
Clark, G.L., and Gertler, M.S. 1983. Migrationand
capital. Annals of the Association of American
Geographers73:18-34.
Clark, G.L.; Gertler,M.S.; and Whiteman,J. 1986.
Regional dynamics.Boston: Allen & Unwin.
Clark, K., and Griliches,Z. 1981. Productivity
growth
and R and D at the businesslevel: Preliminary
resultsfromthe PIMS data base. Paper presentedat
the National Bureau of Economic Research Conferenceon R and D, Patents and Productivity,
Lenox, Mass.
Cliff,A.D., and Ord, J.K. 1981. Spatial processes.
Models and applications.London: Pion.
Crandall, R.W. 1980. Regulation and productivity
growth.In Federal ReserveBank of Boston 1980,
pp. 93-111.
. 1981. Pollutioncontrolsand productivity
growth
in basic industries.In Productivity
in
measurement
regulatedindustries,ed. T.G. Cowing and R.E.
Stevenson,pp. 347-68. New York:AcademicPress.
Denison, E.F. 1979. Accountingfor slower economic
growth.The UnitedStates in the1970's. Washington, D.C.: The BrookingsInstitution.
Douglas, E.M. 1932. Boundaries, areas, geographic
centersand altitudesof the UnitedStates and several states. UnitedStates Geological Survey,Bulletin 817. Washington,D.C.: U.S. Government
PrintingOffice.
Federal Reserve Bank of Boston. i980. The decline
in productivity
growth.Proceedingsof a conference held in Juneat Edgartown,Mass. Conference
Series no. 22. Boston: Federal Reserve Bank of
Boston.
in productivity
Filer, R.K. 1980. The downturn
growth:
A new look at its natureand causes. In Maital and
Meltz 1980, pp. 109-23.
Fraumeni, B.M., and Jorgenson,D.W. 1981. Capital
formation
andU.S. productivity
growth,1948-1976.
In Productivity
analysis: A range ofperspectives,
ed. A. Dogramaci, pp. 49-70. Boston: Martinus
Nijhoff.
Freeman, R.B., and Medoff,J.L. 1979. The twofaces
of unionisms.The Public Interest57:69-93.
87
Gollop, F.M., and Roberts, M.J. 1982. Environmental regulationand productivity
growth:The case of
fossil-fueledelectric power generation. Boston
College WorkingPaper no. 114, ChestnutHill,
Mass.
slowGriliches,Z. 1980a. R and D and theproductivity
down. AmericanEconomicReview 70:343-48.
. 1980b. Returnsto researchand development
expendituresin the privatesector. In New develmeasurement
opmentsinproductivity
and analysis,
ed. J.W. Kendrickand B.N. Vaccara, pp. 419-54.
Chicago: Universityof Chicago Press.
Hulten, C.R., and Schwab, R.M. 1984. Regionalpro1951-78.
ductivitygrowthin U.S. manufacturing:
The AmericanEconomicReview74:152-62.
Jones, J.P. III. 1983. Parametervariationvia the expansion method with tests for autocorrelation.
Modelingand Simulation14:853-57.
. 1984. A spatiallyvaryingparametermodel of
AFDC participation:
Empiricalanalyses using the
expansion method.The ProfessionalGeographer
36:455-61.
Kendrick, J.W. 1980. Surveyof the factorscontributingto the decline in U.S. Productivity
Growth.
In Federal Reserve Bank of Boston 1980, pp. 121.
Kendrick, J.W., and Grossman, E.S. 1980. Productivityin the UnitedStates. Trendsand cycles. Baltimoreand London: The JohnsHopkinsUniversity
Press.
Kopcke, R.W. 1980. Capital accumulationand potential growth.In Federal Reserve Bank of Boston
1980, pp. 26-53.
Link, A.N. 1982a. A disaggregatedanalysisof industrialR and D: Productversusprocess innovation.
In The transferand utilizationof technicalknowledge, ed. D. Sahal, pp. 45-62. Lexington,Mass.:
D.C. Heath.
. 1982b. The impactof federalresearchand deIEEE Transvelopmentspendingon productivity.
actions of EngineeringManagementEM-29:16669.
. 1982c. Productivity
growth,environmental
regulations, and the compositionof R and D. Bell
JournalofEconomics 13:548-54.
Maital, S., and Meltz, N.M., eds. 1980. Laggingproductivitygrowth. Causes and remedies. Cambridge,Mass.: Ballinger.
Mansfield, E. 1965. Rates of returnfromindustrialresearchand development.AmericanEconomic Review 55:310-22.
Moomaw, R.L. 1980. The American productivity
slowdown:Much ado about what?WorkingPaper
no. 1447-3, The UrbanInstitute,
D.C.
Washington,
Myers, J.G., and Nakamura, L. 1980. Energyand
A putty-clay
pollutioneffectson productivity:
apmeaproach.In New developmentsinproductivity
surements
and analysis,ed. J.W.KendrickandB.N.
Vaccara, pp. 463-98. Chicago: Universityof Chicago Press.
National Science Foundation. 1977. RelationshipsbetweenR and D and economicgrowth/productivity.
Washington,D.C.: U.S. Government
PrintingOffice.
Peet, R. 1983. Relationsof productionand the reloca-
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions
88
Casettiand Jones
tionof UnitedStatesmanufacturing
industry
since
1960. Economic Geography59:113-43.
1984. Class struggle,therelocationof employment, and economic crisis. Science and Society
48:38-51.
Perloff,J.M., and Wachter, M.L. 1980. The productivityslowdown:A labor problem?In Federal Reserve Bank of Boston 1980, pp. 115-42.
Perry, G.L. 1971. Labor forcestructure,
potentialoutput, and productivity.
BrookingsPapers on EconomicActivity3:533-65.
Rees, J. 1979. Regional industrialshiftsin the U.S.
in
and the internalgenerationof manufacturing
growthcentersof the Southwest.In Interregional
movements
and regionalgrowth,ed. W.C. Wheaton. Washington,D.C.: The UrbanInstitute.
Richardson, H.W. 1980. Polarizationreversalin developingcountries.Papers oftheRegionalScience
Association45:67-85.
Sternlieb,G., and Hughes, J.W. 1978. The new economic geographyof America. In Revitalizingthe
northeast:Prelude to an agenda, ed. G. Sternlieb
and J.W. Hughes, pp. 75-127. New Brunswick,
N.J.: Centerfor Urban Policy Research, Rutgers
University.
Sternlieb,G., and Hughes, J.W., eds. 1975. Post industrialAmerica:Metropolitandecline and interregionaljob shifts.New Brunswick,N.J.: Center
forUrbanPolicy Research,RutgersUniversity.
Terleckyj, N.E. 1974. Effectsof R and D on theproAn exploratory
ductivity
growthof industries:
study.
Washington,DC.: NationalPlanningAssociation.
. 1982. R and D and the U.S. industrialproductivityin the 1970's. In The transfer
and utilization
oftechnicalknowledge,ed. D. Sahal, pp. 63-100.
Lexington,Mass.: D.C. Heath.
U.S. Bureau of the Census. 1979. 1977 cityand county
data book. Washington,D.C.: U.S. Government
PrintingOffice.
. 1980. Statisticalabstractof the UnitedStates:
1980. Washington,D.C.: U.S. Government
Printing Office.
Vining, D.R., and Pallone, R. 1982. Migrationbetween core and peripheralregions:A description
andtentative
explanationofthepatterns
in 22 countries.Geoforum13:339-410.
Vining,ID.R., and Strauss, A. 1977. A demonstration
thatthe currentdecentralization
of populationin
the United States is a clean break withthe past.
and PlanningA 9:751-58.
Environment
This content downloaded from 157.253.50.51 on Thu, 26 Mar 2015 15:14:57 UTC
All use subject to JSTOR Terms and Conditions