Public Disclosure Authorized
Public Disclosure Authorized
Public Disclosure Authorized
Public Disclosure Authorized
PolicyAs"esch
WC*IKING
-PAPERS
Transition
andMsero-Adjuatment
Department
PolicyResearch
TheWorldBank
Septeniber1993
WPS1194
How Fast Has Chinese
Industry Grown?
Tom Rawski
An upward biasin measuresof China's real industrialoutput in
the past decademay substantiallyalter our perceptionof therate
andpatternof Chineseindustrialgrowth.The extentof suchbias
shouldbe investigatedandanalyzedfor possiblelinkswithother
economicpatterns that may be morereadily measurable.
mff And
mwig%Dank
and nc=gethe exchanucoid
PolicyRescjh WotkingPaper.dimninatethefinp of wotkin pm
alothmineadin
dopinaiTues.
llepapen, diLibutedbytheReRarbAdviamyStaff,canyditenameof de audio,aa
a Cathe
amhox'own.Theyibould
fndings,imapxuati,nd canclusios
ny diirvic andshouldbetuadandcitedaccardingly.lhe
notbe auinbutedtodteWodd Bank.its Bsrd ofDijto. its magaenat, or anyof itamanber comta.
WPS1194
Thispaper- aproductoftheTransition
andMacro-Adjustmnent
Division,PolicyResearchDeparmnenitisparnofthedivision'sresearchinitiative,Indusurial
ReformsandProductivity
inClineseEnterprises.
The
study was fundedby the Bank's ResearchSupportBudgeLunder researchproject "Reformsand
Productivity
in ChineseEnterprises"
(RPO675-M8).
CopiesofthispaperareavailablefreefromtheWorld
Bank,1818HStreetNW,Washington.
DC20433.PleasecontactEmilyKhine,roomNI 1-065.extension
37471(September1993,44pages).
Dataforrecentyearsindicatean acceleration
of
Chineseindusttirlgrowth,fromthe annualrates
of about10percentrecordedin thequarter
centurybeforeeconomicreformto figures
approaching15percentin the mid-andlate
1980s.
Evaluatingthestatisticsunderlyingthese
reportsrequiresan appraisalof howeconomic
reformhas affectedtheabilityof China'sstztistical systemto measureeconomicperformiance.
Erroneousinformnation
aboutthe rateandpattern
of industrialgrowthcoulddistortmeasuresof
productivity
changeconsideredto be central
indicatorsof the effectiveness
of Chinese
industrialreformn.
Rawskidescribesthestatisticalmaterialsand
proceduresusedto provideinformationonthe
growthof industrialoutput.Heinvestigates
sourcesof biasin the officialstatisticsto indicate,wheneverpossible,howthesebiases
affectedreportedoutputtotals,andto appraise
theimpactof adjustmentsto reportedoutput
growthon measuresof industrialproductivity.
Thespecificconsequences
of decentralized
decision~making,
growingpriceflexibility,
inflation,dualpricingsystems,the emergenceof
enterpriseswithfewor no tiesto thesystemof
stateplanning,andotheremergingfeaturesof
theindustrialsystemmaybe uniqueto Chinabut
thebroaderissuesraisedare relevantin many
countiies.
Rawskifindsconsiderableevidenceof an
upwardbiasInmeasuresof China'sreal industrialoutputin thepastdecade.Theissueis not
whethersuchbiasexistsbutwhetherits presnce
substantially
altersourperceptionof the rateand
patternof Chineseindustrialgrowth.
To clajifythis issuerequiresinvestigating
the extentof possibleupwardbias.Thisin tumn
callsforan analysisof possiblelinksbetween
upwardbias- whichis itselfdifficultto observe- andothereconomicpatternsthatmay
be morereadilymeasurable.
Pmoducsd
by dwPobicyR.earschDisminazia Cmtar
How Fast Has Chinese Industry Grown?
Tom Rawakl
University of Pittsburgh
CONTES
ACKNWLEDGEMENT
.......................................
i
I.
INTRODUCTION
..........................................
II.
CONCEPTSAND CATEGORIESFOR CHNESE INDUSTRIALSTATISTICS .
.........
1
III.
CHINESE INDUSTRIALPEILORMANCESUMM-ARYOF RECENT OFFICIAL DATA .....
3
IV.
SYMPTOMSOF UPWAR BIAS IN CHINESEINDUSTRIALSTATISTICS...
........
6
..................
6
A. MISMATCH BETWEENOUTPUT AND VALUE DATA ......
1
B. Do RURAL INDUSTRIESADHERE TO STANDARDAccOUNTING REGULATIONS...
C. HAS THE RATE OF DOUBLE COUNTINGINCREASED? ................
D.
V.
Do LOCAL AUTHORITIESFALSIFY INDUSTRIALOUTPUT DATA? ...
7
10
......
12
E. Do INDUSTRIALOUTPUT DATA ACCURATELYREFLECT RECENT INFLATION
EXPERIENCE........
12
F. ARE REPORTEDGAiNS IN ENERGY PRODUCTIVITYUNREALISTICALLYLARGE?
15
CONCL.USIONS
20
REFERENCES
.............
..
43
TABLES
TABLE : ALL INDUSTRY.
21
............................................
TABLE 3: BRANCHSTRUCrUREoF GVIO AT 1989 PRIcES .....
TABLE 4: NET OurPuT AT CURRErr PRICES .......
TABLES: CHMCAL INDUSTRY
23
..........
TABLE2: BREAKDoWNSTRUCrUREOF GVIO AT 1989 PRICEs .....
..............
24
26
......................
27
........................................
DATATO MEASUREINrLATION .....
TABLu 6: ALTERNATIVE
28
...............
OUTPTr VALuz DATA
FROMINDUSTRTAL
TABLE 7: PRICEINDmxs EXTRACTED
.
29
IN CHNESEINDUSTRY,OFFICIALDATA,
TABLE 8: ENERcY PRODUCTnvTY
19781987 .......................................
30
TABLE 9: OFFICL.LENERGYDATAFOR CHNESEINDUSTRYBYBRANCH,
1980-'98S..................................
31
TABLE 10: GVIO DATA FOR 1S BRANCHES ...............................
32
IN
TABLE11: REvISEDCALCULATION:ANNUALPERCENTINCREASE
AND
ENERGYPRODUCTIVrrYBASEDON PHYSICALENROY CONSUMPTION
34
PUBLISHD GVIO DATA ............................
UNrrS,
TABLE12: ENERGYDATAFOR STATESECTORINDEPENDENT
40 BRANCHES,1980 AD 1985..
35
OF SOE ENERGYDATATO 15 BRANCHFoRmAT . 37
TABLE13: ROUGHCONVERSION
OF ENEROYCONSumpON AND
TABLE14: TRIALCALCULATION
.
.
INDUSTRY
PRODUCTIVrYFOR COLLECTIVE
38
ENERGYPRoDucTIVrrY FOR 15
TABLE15: PERCENTCHANGEIN INDUSTRIAL
..................
..........
BRANCHES,1980-1985 ...
40
(1980-1985).
TABLE 16: DATAON "ENERGYSAvwNGS"
...
..
41
ACKNOWLEDGEMENT
The research projectson "EnterpriseBehaviorand EconomicReforms: A ComparativeStudy in Central
and Eastern Europe", and "Industrial Reforms and Productivity in Chinese Enterprises are research
initiatives of the Transition and Macro AdjustmentDivision (PRDTM) of the World Bank's Policy
Research Departmentand managedby I.J. Singh, Lead Economist.
These projectsare beingundertaken in collaborationwith the followinginstitutions: The London
Business School (LBS); Reforme et Ouvertures des SystemesEconomiques(post) Socialistes(ROSES)
at the Universityof Paris; Centro de Estudos Aplicadosda UniversidadeCatolica Portuguesa (UCP) in
Lisbon; The Czech ManagementCenter (CMC) at Cellkovice, Czech Republic; The Research Institute
of Industrial Economicsof the JanusPannonius University,Pecs (RIE) in Budapest, Hungary; and the
Departmentof Economicsat the Universityof LddI, in Poland.
The research projects are supported with funds generously provided by: The World Bank
ResearchCommittee;The lapanese Grant Facility; The PortugueseMinistryof Industry and Energy; The
Ministry of Research and Space; The Ministry of T'dustry and Foreign Trade, and General Office of
Planningin France; and the UnitedStates Agency for InternationalDevelopment.
The ResearchPaper Series disseminatespreliminaryfindings of work in progress and promotes
the exchangeof ideas amongresearchersand others interestedin the area. The papers contain the views,
conclusions,and interpretationsof the attho:(s) and shouldnot be attributed to the World Bank, its Board
of Directors, its managementor any of its member countries, or the sponsoring institutions or their
affliated ag ncies. Due to the informalityof this series and to make the publication available with the
least possible delay, the papers have not been fully edited, and the World Bankacceptsno responsibility
for errors.
The authors welcome any comments and suggestions. Request for permission to quote their
contentsshouldbe addresseddirectlyto the author(s). For additionalcopies,please contactthe Transition
and Macro AdjustmentDivision, room N-11065, World Bank, 1818H Street, N.W., Wasbington,D.C.
20043, telephone(202) 473-1442, fax (202) 676-0083or 676-0439.
The series is also possiblethanks to the contributionsof Donna Schaller, Vesna Petrovic, Cecilia
Guido-Spanoand the leadershipof Alan Gelb.
-1i-
I. INMODUCnON
Data for recent years indicate an accelerationof Chinese iwdustrialgrowth from the annual
rates of approximatelyten percent recorded during the quarter-centuryprior to the introductiun
of economic reform policies to figures approaching 15 percent annual growth during the midand late 1980s. Evaluation of the statistical materials underlying these reports requires an
appraisal of how economic reform has affected the capacity of China's statistical system to
measure economic performance. Since industrial output dominates China's national income
totals, possibleinaccuraciesin statisticsof industrial growth have the potential to affect overall
measures of the size and structure of China's economy u well as perceptions about the size,
structure and growth rate of the industial sector itself. Of particular concern is the possibility
that erroneous informationabout the rate and pattern of industrial growth will distort measures
of productivity change, that we regard as central indicators of the effectiveness of industrial
reform efforts in China's economy.
The objectiveof this paper is to describe the statisticalmaterials and procedures that stand
behind published informationon the growth of industrial output, to investigate sources of bias
in the official statistics, to indicate, whenever possible, the quantitative impact of these biases
on repcrted output totals, and to appraise the impact of adjustmentsto reported output growth
on measures of industral productivity..
The problems explored in this paper arise primarily from theainteraction between the
growing complexity of industrial organizationand market structure and a statistical network
designed to collect information ior the pre-reform system of industrial olanning and
administration. Althoughthe specific consequencesof decentalized decision-making,growing
price flexibility, inflation, dual pricing systems, emergence of enterprises with few or no ties
to the system of state planning, and other emergent features of the industrial system may be
unique to China, the broaderissues raised by thesedevelopmentswould seem applicable to other
socialisteconomiesat various stages of maiket-orientedreform programs.
II. CONCErr A
CATEORE FORCNSE
INDUSRIALSTsTIMMCS
Manipulation and interpretation of data portaining to Chinese industry (which includes
mining, manufacturingand utilities) requires an appreciation of important concepts and data
categories used by Chinese statisticians. State enterprises (puanmin suoyouzhif are those in
which the legal ownership of post-tax profits resides in the hands of some level of the
government. Nearly all of China's largest enterprises belong to this category, which accounted
for 83.2 percent cifindL -ial output in 1978and 59.7 percent in 1987 [Industry 1949-84, p. 98
;TJNJ 1988, p. 311]. L.ollecti.-eenterprises (iiti suoyouzhi are those in which this residuai
ownershipright resides with the ente-"ise itself. Residual profit of private or individual (gc)
enterprise accrues to thcz owners.
-1-
2 Now Fae Mm Ch*F.e hu*oy
row?
The concept of 'independentaccountingunits, (dulihesuan.giye)refers to industrial
enterprisesthat functionas separateaccounting iltities. Statisticsfor industrialoutputor input
(fixedassets, worldngcapital,labor) oftenrefer exclusivelyto independentaccountingunits,
whichcontributed85.8 percentof nationalindustrialoutput(including96.1 percentin the state
and 86.4 percentin the collectivesector)to the 1988gross valuetotal [Jefferson,Rawski,and
Zheng,Table1; thesedata excludevillage-levelindustry].Industrialactivitymayoccurwithin
non-industrialunits, as when transportcompaniesrepair their own equipmentor when
universitiesor othernon-industrial
entitia operaiefactorieswhoseaccountsare subsumedwithin
theirowri. The outputvalue of these 'non-independent
accountingunits' (feiduliheau giy
is incorporatedinto outputtotalsthat includeall industrialproduction(ratherthan only tha' of
independentaccountingunits).
Thecoverageof industrialproductionwasexpandedin 1984to includeindustrialenterprises
managedat and below the village level (formerlydescr.bedas nanagedby the production
brigadesof ruralcommunes).Theseenterpriseswerepreviouslyclaisifiedas partof agricultural
ratherthanindustrialproduction[Field1988,pp. 584-585].Recent:vublcationshavebegunto
retroactivelyincorporatethis categoryinto the industrialtotals for previousyears, leadingto
apparentinconsistencywith previouslypublishedstatistics(e.g. newlypublishedlabor figures
for collective industry inclusive of "village-managed'enterprises are miuchlarger than
identically-labelled
employmenttotalspublishedin earliersourcesnot becauseof any changeizi
underlyingstatistics,but merelybecausethe "village-managed"enterpriseswere formerly
includedin the farm -ector).
Industrialproductionstatisticsare valuedin termsof 'current' or "constant'prices. The
currentprice valueof industrialoutputindicatesthe valueof eachyear's outputaccordingto the
marketprices of that year. For th. vast majorityof productsthat are sold in the year of
productioil,output value at current prices is identicalwith sales revenue. From this perspective,
the existenceof multiplepricesfor individualproductsposesno conceptualor practicaldifficulty
for Chineseaccountantsand statisticians.
FollowingSovietexample,China's wconomic
statisticshavelongbeencs'culatedaccording
to "constant"as well as current prices. Constantprices of 1952were used for the period
1952-57;1957prices were in forcefrom 1957-71;nationalstatisticsfor the years 1971-81are
basedon 1970prices; and a 1980price basehas been in forcesince 1981. Calculationsbased
on 'constant' or fixedprices are made by multiplyingquantitiesof outputby the relevant
"constant p.ices," the latter being supplied to enterprise accountantsby planning and
agenciesof the Chinesegovemment.
administrau've
It is importantto note that, as economicreformleadsenterprisemanagersto focus more
closelyon financialresults basedexclusivelyon currentprices, the calculat<on
of outputvalue
at "constant"prices becomes increasinglyperipheral to enterprise objectives'. In the absenceof
1. Oneofficial of Chia's StateStisca
Bureau
commeAed
ht thi hnge enhace te veracityof rpotd data.
Flow FastHOaChineseIndwry Gro*"? 3
price indexes for industrial products, output value calculated at "constantuprices becomes the
chief indicator of industrial growth and structure. Intertemporal comparisons within a time
period spanned by a single set of fixed prices pose no difficulty. When the period of analysis
crosses from one to another fixed price base, as in como';ting growth between 1975 and 1985,
ratios of output totals in the bridging years 1957, 1971 o ,981 are used to link figures across
time periods served by differentsets of fixed prices. If a calculationcrosses more than one such
gap, e.g. when comparing the levels of industrial output in 1952 and 1987, a series of
chain-linkedcalculationsis used (see Field, JEC 1986, p. 509] and the resulting time series is
describedas being based on "comparable*(kmi) rather than "constant' (bbian) prices.
III CHN
SINDusiAL
PEmFQFMANCE-SUMMARzOF RECENr
OmaAL
DATA
Official statisticsof China's industrial performanceduring the past decade indicate a rapid
expansion of output coupled with considerable structural change. This is the picture that
emerges from the summary figures presented in rables 1-4.
Part A of Table 1 reproduces data on the growth of overall industrial output in constant
and in current prices for a comprehensiveindustrial aggregate (designated 'Industry+') that
includes enterprises managed at and below the village level. Output totals for village-level
industry are shown separately; subtractionof these figures from the global total generates an
output series (designated as "Industry") restricted to enterprises ope.ated at and above the
township(xiang) level. Indexes of output growth from a 1978 base derived from these figures
appear in Part B of Table 1; annual output changes for each category are derived in Part C.
These data indicatea continuationof the rapid and sustained growth that has characLerized
Chinese industry throughout the history of the People's Republic of China. Using the d-aa at
constantprices (labelledGVIO), the ate of output growth clusters around the 10 percent annual
level observedover the long term in China. If village industry is excluded, the average annual
growthrate of OVIO for 1978-87is 10.4 percent. Even though village industryreported annual
growth averaging24.1 percent in real terms during 1978-R7,the village componentis so small
that addingits inclusionin the total producesonly a marginal increase in average growth to 11.3
percent for 1978-87. This is important because, as will be seen below, there can be little dovbt
that the figures shown in Table 1 considerablyexaggerate the growthof real output in the village
segmentof industry.
The figures reported in Table 1 indicatea distinct acceleration of industrial growth during
the mid-1980s,with reported real output growth approa.hing the 15 percent mark in 1983/84
chnp
1. One officialof China's Sate Statitca Bumauoomniud tht Shim
enhanc Uthvemcity of reporeddaa.
4 How Fan Has ChMe Indrj&y ro*wi?
and 1986/87and surpassing15 percentin 1984/85even withoutthe inclusionof village-level
industries.
Data showingthe level and growthof industrialoutputat bothcurrentand constantprices
can also provideinformationabout changesin the pdicelevel for industrialgoods. This is
particularlyimportantbecauseChinesesourcesgive no systematicinformationon price trends
fer industrialgoodsuntil 1984/85;branchindexesfor pricesof industrialgoodsexist onlyftwm
1985/86[ChirnaPrice2 (1989):59]. Implicitpriceindexetsfer industrialoutputappearin Panel
A of Table 1. Thesedata reflectthe gradualemergenceof inflationarypressuresbeginningin
the mid 1980s following yeawsof near-stabilityin industrialprices. Whether these data
acciiat'ly reflect trends in prices paid for industrialgoods and/or received by industrial
produce."will be discussedbelow.
of outputinto severalownershipca.egories:state-owned,
Table2 indicatesthe brealkdown
collective,private, and other. These figuresshow that output from the c )llectivesector,
particularlyits sub-categoriesof townshipand vilage enterprises(jointly describedby the tem
xiangzhenQa , hasgrownmuchfasterthanproductonin statefirms,leadingto a rapiddecline
in the formerlydominantshareof statefirms in totaloutputvalue.
The outputtotalsin Table2 are dividedinto twomajorsub-categories,stateand coUective.
Additionaldetail is given for two segmentsof collectiveindustry, firms managw at the
township(xi) andviLage(M) levelswithinthecoUectivesector. SincecoUectiveenterprises
alsooperatein urbanareas, thesesegmentsdo not exhaustthe entireoutputof China'scollective
industries.
whichis often
Table2 also displaysoutputdata for a separatecategory,xian3gzbhCnqy,
the term's
though
even
lVE),
translIztedas *townshipand village enterprises' (abbreviated
literalmeaningis 'townshipand market-townenterprises.' These data are of interestfor two
reasons:first, reportedoutputhasgrownwithextremerapidityin recentyears, so that the total
amountsin 1987to nearlyone-thirdof nationalgross output. Furthermore,the scopeof the
TVE data remairs uncertainfor the periodbeginningin 1984. Prior to 1984, the TVE output
data are almostpreciselyequal to the sum of outputvalue at fixed prices for townshipand
villageenterprises. Beginningin .984. however,we find a large and growinggap between
outputof townshipand villageenterprisesand the muchhigherTVEtotal. In addition,theprice
basis of the TVE data reproducedin Table 2 is not specified. We know that the data for
1978-83representthe sum of outputfrom townshipand village enterpriseat constantprices.
growthof the TVE categorystartingin 1983/84suggeststhat the.figuresshown
Theenormnous
in ColumnE of Table 2 may representoutpu.valuedat currentrather than constantprices.
Table3 presentsinformationon thebranchstructureof grossindustrialoutputvalueat 1980
accountingunitsand
prices. Thesedata, whichexcludethe minorcategoryof non-independent
of majorbranches
importance
the
in
also excludevillageenterprise,indicatevery littlechange
of Chineseindustryduringthe pastdecade. Thisis confirmedby therankcorrelationcoefficient
linkingthe sizestructureof industrialbranchesfor combinedstateand collectiveindustry(Panel
HowFA M Chha induy Orow? 5
C of Table 2) in 1978 and 1987.2 The stabi!tv of br-rch stricture in both the state and
collectivesegmentsof industryis a significantfactorin analyzingtrends in reportedenergy
productivity.A stablebranchstructureeliminatesthe ossibilityof raisingenergyproductivity
by raisingthe shareof industil outputproducedin brancheswith'ow energy-intensity.
The figuresin Tables 1-3 arc based on the 'gross value of industrialoutput," which
representsthe combinedtotal of enterpriseoutputval6s inclusiveof materal costs. Table4
containsinformationon the growthof net industrialoutput,which is calcu1btedby subtracting
energyetc.) fromgross output. Thenet
the vaiueof materialinpuu (minerals,semi-fabricates.
value figuresare usually renderedonly in current prices; when nretoutput is presentedin
constantprice terms, the figuresare apparentlyobtainedby multiplyingnet outputin current
pricesby the ratioof gross outputtotalsLi constantand current prices, whichis equivalentto
"single deflation rather than tU conceptuallypreferable "double deflation" used id
in which separateprice indexesare used to removethe
contemporaryindustrialeconormies,
output and from the intermediategoods purchasedhy
gross
from
change
impact of price
industrialenterprises.
The generalpictureemergingfromshesedata - rapidgrowth,accelerationafter 1983,with
differentiallyrapidcxpansionof the collectivesector- parallelsthe resultsreportedin Tble 1.
The ratioof net to grossoutputis nearlyidenticalin the stateand collectivesectors. Following
in this ratio rsee Industry1949-84,p. 41J, we now see a gradualbut
decadesof near-constancv
steadydeclinein the net outputratio for both stateand collectiveindustry. There are several
possiblereasonsfor this change:
- changingproductmix withinindividualbrmnchesof industry(notethat stabilityof branch
structureprecludeschangein this area as a sourceof declinein net outpmtratios).
- changingtechnologyand efficiencyin some branches relative to others.
- differentialinflationof raw matcrialspricesrelativeto prices of finishedproducts.
- changesin the rate of doublecountingarisingfr..a responseto new marketingopportunities,
and
divisionof labor, expansionof subcontracting,
enlarged ialization and inter-enterprise
growthof joint productionand transprovincialcooperation
Of particular relevance here is the possibility that reform-inducedincreases in
inter-enterprisespecializationmay have raisedthe, owth rate of gross outputvalue abovethe
growthrate of real industrialproduct. This outcomeis not certain:we lack systematicdata on
the ratio of interentcrprisepurchasesto total out(ut (bothlevel and time-pathof this ratio) for
notdiMpiobshd
forte oalwlatonbecaustheyamw
2. Braches 13 nd 14, nd also branch 11 ad 12 au combined
brarchu) .identia in 1978
ording of 7 (includingthe six lu
in th 1978 fiSue; with 13 bmancr, he rmak
and1957. Theam of squa. of differen0e, nak ordenga hrdth tmainhng6 branchs 136.
6 Now Fwt J.a.xChwi-e lndvWy Growns?
various types of erterprises. In addition, some units, isicludingthe large and widely publicized
Capital Iron and Steel Corporation, have taken advantageof reform policies to increase rather
than reduce the degree of vertical integration, which has the opposite effect of causing gross
value to lag behind the growth of real output.
STATImCS
BLASiN CmNS INDUSTRIAL
OF UJPWAp1
IV. SYMPTOMS
Careful inspectionof Chinesestatisticalpublicationsraises the possibilitythat recent output
totals based on wconstant prices* may exaggerate real outpit growth in the industriai sector.
Indicationsof upwardbias in the constant-priceindustrialoutput totals for the past decade appear
from the following types of materials:
-
apparunt mismatch between growth of physicaloutput and output value in certain branches of
industry
- indicaLionsthat township and village enterprise may confuse current and constant vices
-
possible increases in the rate of double counting, which would have the effect of artificially
increasing the reported growth of gross output
- indicationsthat local govemmentsmay falsifyindustrialoutput statisticsto gain administrative
benefits attached to achievementof lai ? output totals.
-
evidence that industrial output data do not adequatelyreflect price increasesthat have become
pervasive in recent years.
- indicationsthat reported gains in energy productivityare unrealisticallylarge, especiallyin the
fast-growingmachinery branch.
A. Mlsmatch between Output and Value Data
In some cases, the reported growth of real output value appears to outrun the expansionof
physical output for major products. The most notable example of this occurs in the chemical
industry, for which relevant data appearin Table 5. These data show that the arithmeticaverage,
of annual physical output growth for nine major commoditieslags behind the reported growth
of output value at constant prices for every year beginning with 1979/80. The positive
difference between reported growth of real output value and production volume for major
commodities ranges from 2.56 percentage points in 1986/87 to 12.66 percentage points in
1984/85.
It is, of course, entirely possible for real output to outgrow physical production of major
commoditiesin a large and complex industry that turns out a wide range of products as well as
HowFau Has ChintE Indistry Gro"?
7
a variety of items within broad categories such as 'plastics." Furthermore, the calculations
reported in Table 5 give identicalweight to each of the nine products. On the other hand, the
size of some of the annual differentialsis troubling. Is it reasonable to anticipate that chemical
output could rise in real terms by 11 or 12 percent during years in which average output growth
of major commodities amounted to only 3.3 percent (1983/84) or even declined slightly
(1984/85)? At the -ery least, these results suggest the possibility of upward bias in the value
data for one of China's larger industrial branches. Figures for the machinery industry raise
similar, though less serious, issues.
B. Do Rural Industries Adhere to Standard Accounting Regulations?
The extraordinary growth of township, village, and 'TVE' enterprises noted in connection
with Table 1 raises questionsabout the veracity of the underlying output reports. In principle
each enterprise is expected to compile output values based on both current and constant prices
As reform causes managers to focus increasing attention on enterprise financial performance
enterprise leaders (and presumablyaccountantsand statisticiansas well) pay growing attention
to current cash flows. Despitethe complexityarising from sales of similar products at multiple
prices, outputvaluedat current prices is closelyrelated to enterpnisesales revenue, and therefore
appears to pose little conceptual or practical difficulty even for the inexperienced and
unsophisticatedaccountantsavailable to small rural enterprises.
To calculategross output at fixed prices requires information about the fixed (1980) price o
eachitem produced. Industrialministriespublish large compendiacontainingrelevant price lists.
Administrativeunits at all levels a,e responsiblefor passing on appropriate price informationto
enterprisesunder their jurisdiction. While this system has functioned smoothly for many years
among large-scale enterprises in the staLesector, the recent explosive growth of collective
enterprise, especially in rural areas, raises the possibility that enterprises, their administrative
superiorsin townshipor county industrialbureaus, local statisticalpersonnel, or all three group
may have failed to implement the system of calculation in constant prices that is of crucial
importancefor industrial output statistics even though it is of little or no interest to enterprise
personnel and perhaps to local governmentofficials as well.
China's statistical rystem operates according to a vertical hierarchy in which each
administrative level compiles and processes statistical reports received from its immediate
subordinatein the bureaucratic structure. Thus nationalagencies receive material prepared by
provincialagencies, whichin turn rely on datacompiled by municipalor county authorities, who
base their reports on data from local enterprises. This means that statisticians at higher
administrativelevels cannoteasily evaluatethe qualityof the raw data underlyingthe reports that
arrive on their desks, particularlywhen, as in the case of rural industry, thesereports come from
literally thousandsof widely dispersed units.
Under these conditions,it is entirelypossiblethat data supposedlybased on fixed 1990 prices
could contain a substantialcomponentbased on (much higher) current prices. With inflation,
substitutionof current for constantprices imparts an upwardbias to the resulting data. The view
8 HowFas:Has Chiae IndurJgGrow,?
that failure to implementaccountingconventionsartificiallyinflatesreportedoutputgrowth,
in the TVE sector, is widelysharedwithinthe Chineseeconomicscommunity. An
especia.Uy
experiencedaccountantnow workingwitha TVE machineryproducerinsists that even in the
capital,failureto adhereto statisticalregulationsis not uncommonin the TVE sector;in rual
May 1989].
areas, neglectof these systemsis said to be widespread(personalcommunication,
are
enterprises
TVE
from
data
output
that
agree
[SSB]
Officialsof the StateStatisticalBureau
problematic,that currentpricesare oftenused to calculateoutputvaluesidentifiedas basedon
fixed prices, and that the output totals tend toward bias in the upward direction(personal
communication,May 1989;May 1990]. A positionpaper issuedby the SSBin responseto
claimsthat its figuresexaggeratethe rate of industrialgrowthin recentyears pointsspecifically
to rural enterpriseas the chief source of what the SSBsees as a modestupwardbias in its
estimatesof real industrialgrowth [SSB 1988;WorldHerald 1988]. An extenal researcher
reportsthat visits to Jiangsuenterprisesin the xiangzenQive categorydo indicateextensive
mixingof data in current and constantprices, with enterpriseleaders findingit difficultto
July 1989]. A paper
explainwhichdata are basedon whichprices (personalcommunication,
preparedby personnelat China's StateStatisticsBureau[SSB1988]reportsthat industrialunits
at the township(xiang level and above are requiredto submit monthlyreports of GVIOat
constantprices. Thesmall,dispersedand numerousvillage-level,jointlyoperated(at or below
villanelevel)and private(gi) enterprisessubmitonlyannualfigures,and theseare in current
ratherthanconstantprices. Provincialandlocalstatisticaibureauxthenadjustthesesubmissions
on the basis of coefficientsderivedfrom samplesurveysor surveysof key enterprises. The
SSB'spositionpaperassertsthat theseproceduresremovemost,if notall of the shuifei(literally
"watercontent")or upwardbias fromthe outputdataassociatedwithvillage-levelindustry. The
SSBalso pointsout that figuresfor theseunitsare not includedin monthlyreportsof industrial
output[SeeWorldHerald 1988for a summaryof debateon the "shuifen"issue].
Despitethisexplanationfromthe SSB,examinationof availabledataconfirmsthe impression
that outputdata for TVE enterprises,especiallyfiguressaid to be basedon 1980fixedprices,
probablyoverstate the actual expansionof real output, especiallyduring recent years of
extremelyrapidenterpriseformation.Priorto 1985,compilationsofTVE datacarefullyspecify
omitany mention
whichdataare basedon 1980prices; morerecentpublicationsconspicuously
of the price basefor outputdata pertainingto 1985and subsequentyears r[VP, 1978-85;TVP
1987;TVP 1988;TJNJ 1988,p. 294. Note that Agriculture1988gives TVE GVIOfor 1987
at 1980prices (p. 314)using ;hesamedata that appearwith no price attrbution in TVP 1988,
p. 261.
How Fan Hu Chia, Indtusy Gro'?
9
Severalspecific examplescan iUustratewhat appears to be considerableinconsistencyin these
data:
Data for Beijing industrial enterprises for (million yuan):
1986 1987 Index
1986-100
1. Gross output, 1980 prices (GVIO)
a. Includingvillage and sub-village
units
b. Excluding village and sub-village
units
c. Difference: GVIO for vWillage
enterprise
2. Village & sub-villageoutput, current
prices (CVIO)
34858.07
39512.33113.3
32177.14
35723.28111.04
2680.93
3789.05141.3
2480.06
3382.27136.4
3. Ratio for village output: CVIO/GVIO 0.925
0.893
Source: Beijing 1988, pp. 255 (la-b), 364 (2).
These figures imply that village level industrial output is higher in constant than in current
prices. But a decline in average prices for industrial output betwean 1980 and 1986 is most
improbable. These data also indicate that industrial prices continued to decline during 1986/87,
which is definitelyincorrect.
Shanghaiindustrial output figures for 1987 (million yuan) raise further questions:
A
1980
prices
B
Ratio
B/A
1. Townshipenterprises
5428
8122
1.496
2. Village enterprises
4361
5029
1.153
Sources: Shanghai 1988, p. 127 (A); TVP 1988, p. 26 (B)
10 How Fat Has Chine. lndwy Grow?
The data marked 'A," identifiedas based on 1980prices, are much smaller than the figures
marked "b," whichappear initially withoutprice attribution, but are also used to compile a total
describedas based on 1980 prices in a separate source (Agriculture 1988, p. 314 - this is a table
of 1987 gross output for township and village industry by province "at 1980 prices"; although
the line for Shanghai is blank, the national totals and data for other provinces are virtually
identical with figures in TVP 1988, p. 26, which makes no mentionof a price base].
Scattereddata for several provincesimply improbableincreasesin labor productivity. GVIO
for Tianjin's village enterprises reportedly increased by 81 percent between 1985 and 1987even
though employmentrose by only eight percent [Tianjin 1988, p. 111]. In Liaoning, reported
GVIO from township enterprises rose by 21 percent during 1986/87 despite a two percent
decline in employment[Liaoning 1988, p. 508]. In Heiongjiang, townshipenterprises reported
real output growth of 15 percent during 1986/87 while employment fell by one percent
(Heilongjiang 1988, p. 291].
The impression of widespread substitutionof current for constant price output figures is
confirmed by Robert M. Field, who finds that 'a large and growing number of provinces have
not distinguishedoutput [of village-levelindustry] in current and constant prices. . . . in 1985
the output of village and below-villageindustry in current and constant prices were identi:al for
all provinces [Field 1988, pp. 586-87, with emphasis added].
C. Has the Rate of Double Counting Increased?
Measuring industrial output growth using information about changes in the gross value of
industrial output can produce misleadingresults if changes in industrial organization alter the
frequencywith which materials, components, and services are exchanged among enterprises.
Assumingno change in real output, a trend in the direction of vertical integration (e.g. merger
of iron mines with steel plants) will cause measuredoutput to decline (the sale of iron ore to the
steel mill disappearsfrom reported GVIO). A trend toward interenterprisedivisionof labor, on
the contrary, will cause measured output to increase.
There are two reasons why one might expect the use of GVIO data to artificially inflate
measuresof industrialoutput growth during the 1980s. First, industrialreform has created new
opportunitiesfor inter-enterprisespecializationand division of labor. Chinese economists and
planners have long criticized the excessive vertical integration typical of Chinese industrial
operations. Despite ample evidence that integration raises production costs, managers have
persisted in building daerguan (large and complete) or i
(smaUland complete)
manufacturingestablishmentsin order to limit their dependenceon unreliableexternal suppliers.
Economicreform has increased the availabilityand reliability of external suppliers for a wide
variety of commodities and services. There are many reports of new sub-contracting
an-angements,inter-provincialjoint ventures and other institutional changes that point in the
direction of an increase in the overall ratio of inter-enterprisetransactionsto real output within
the industrial sector. [Note, however, the apparentcounterexampleof the Capital Iron and Steel
Corporation, which has used new opportunitiesfor independent decision-makingto reduce its
How Fast Ha Chsuu IndwitryGrow?
11
reliance on external suppliers through such measures as building its ov n power plant and
acquiring a fleet of ocean freighters.]
Even if there has been no trend toward inter-firm specializationat existing enterprises, the
growing weight of rural and collective enterprises in the industrial output total has almost
certainly brought a decline in average scale of industrial operations. This probably implies an
increase in specializationsimply because small enterprises lack the capacity to achieve the high
degree of vertical integration typical of China's larger industrial units.
We thus have two reasons for anticipating an increase in the ratio of inter-enterprise
exchange of materials and semi-fabricatesindependent of any shift in product mix or branch
structureof industry. Such a changewould build an upward bias into the output totals reported
in Table 1. Such a change would also systematicallyreduce the ratio of net to gross output
value, which is exactly what we see in Table 4. Since several other factors also influence the
ratio of net to gross output, the downtrend in the ratic of net to gross output observed in Table
4, although suggestive, is not sufficient to demonstrate either the presence of vertical
disintegrationor its possible impact on measures of real output growth.
A more promising approach would be to look at levels and changes in the ratio of
interenterprisepurchase of energy, materialsand semi-fabricatesto gross output value in various
subdivisions of the industrial sector. For example, the industry-wide average ratio of
interenterprisepurchases to gross output at current prices (CVIO) [call this ratio IEP/CVIO0,
can be expressedas a weightedaverage of distinct IEP/CVIOratios for large and small industry.
Thus:
[IEP/CVIO] = a[IEPl/CVI01] + (1-a)UEP2/CVI02]
where 1 and 2 indicate large and small-scaleindustry and a is the share of the former in national
industrialoutput.
I hypothesizethat:
(1) the ratio (IEP/CVIO] is considerablylarger for large than for small firms
(2) the weight attached to large firms, a, has declined irnrecent years
(3) economic reform tends to raise the ratio (IEP/CVIO] for both large and smaii firms
It should be possible to use panel data from a enterprise surveys to investigate both the
level and time path of [IEPl/CVIOlj and IEP2/CVI02]. Together with data on the parameter,it
shouldbe possible to obtain some rough quantitativeidea of possiblebias in the output figures
arising from changes in industrial organization.?
Byrd observesthatthe foregoingdiscusion overloolk the pouible impat of changesin the priceof materils
3. Wdiliam
andintemediategoods relativeto the price of finalproducs; such changer might be systeuailcaUydifferentfor large
ands1A1 finr.
12 HowFM Ha Cbae ldutiy
ww?
D. Do LocalAuthoritlesFalsifyIndustril OutputData?
Well-informedstatisticalpersonnelreport the existenceof incentivesfor exaggerationof
industrialoutput growth by local govenments in some regions of China. In Jiangsu, for
example,municipalities
thatsurpassthresholdlevelsof industrialoutput(e.g. 1billionyuan)are
grantedspecialprivilegesin the form of exemptionfromcertain typesof regulation(e.g. direct
access to provincialfunds vs. applicationthroughcounty offices). Falsification,if extant,
presumablytacesthe form of inflatinggross ratherthannet output[notethat the formercan be
anong producersof similar
easilyinflatedby anrangingexchangeof materialsor semi-fabricates
commodities].If so, fallingratiosof net to grossoutputwillbe typicalof entitieswithinflated
gross outputtotals. Unfortunately,there are manyother factorsinfluencingthis ratio, so that
falsificationmighteasilyescapedetection,especiallyif the amountsare small relativeto local
and nationaltotals.
At the sametime, other enterprisesor localitiesmayconcealsomeportionof theiractual
productionin the hope of avoidingtaxes.
E. Industrial Output Data AccuratelyReflect Recent Inflation Experience?
After decadesof considerableprice stability,China has experiencedgrowinginflationary
pressuresduring the 1980s. Since Chineseprice index compilationhas previouslyfocused
almostexclusivelyon consumerprices,the impactof recentinflationon industrialpricesis not
easilydiscerned. The only systematiceffort to monitortrends in industrialprices appearsto
come from the State Price Bureau, whichnow surveysprice conditionsin severalthousand
industrialenterprisesand uses the resultingdata to compileindexesof ex-factoryprices for
industrialproducts as well as purchaseprices for major raw materials,fuels, and power
[personalcommunication,May 1989]. Summaryfiguresfor 1984/85and morecomprehensive
results,includingprice indexesfor 15 industrialbranchesand purchasepriceindexesfor eight
classesof materialsappearin the Bureau'sjournal rChia Pnricc2 (1989):pp. 59-60].
These figuresconfirm that industryhas experiencedthe inflationarytrend reportedfor
urbanconsumergoods, Annualincreasesfor ex-factorypricesaveraged8.7 percentin 1984/85,
3.8 percentin 1985/86,7.9 percentin 1986/87and well over 10 percentduring the first eight
monthsof 1988[ChinaPrice2 (1989):59]. Priceincreasesfor materials,fuel, and powerwere
substantiallylarger in each year [ibid., 60]. The influenceof commercialintermediaries
(includinggovernmentagencies),in the inflationaryprocessis visibleif we comparetrendsin
ex-factoryprices of miningproducts and raw materals" (these categoriesappear not to
overlap)with trends in purchaseprices for wallraw materials"(percentincreasesover the
previousyear):
HowFan Hu Ouaw hmaaty
Ex-Factory
Mining
Products
1985
1986
1987
Aug.1988
108.8
100.6
114.1
108.8
1r
Prices
PurchasePrices
All Raw Materials
Raw
Materials
110.9
107.5
106.9
117.8
118.0
109.5
111.0
123.9
Source:ChinaPrice 2 (1989):59-60.
Profitableintermediation,whetherby state agenciesor by legitimateor illegal private
enterprise(sometimesinvolvingpersonswith officialconnections)is an importantcomponen
of the "officialspeculation'(guandao)widelyreportedin the Chinesepress. Beijing'slarge
YanshanPetrochemicalCompanyreportedly "sold almost all their products to the State at
officiallowprices"onlyto discoverthat 'most of theirproducts'userspaid muchhighermarket
prices"for the samematerials[ChinaDaily 6-3-1989,p. 1].
Althoughinflationof industrialpricesseemsto haveacclerated in recentyears, substantial
priceincreasescertainlyoccurredprior to 1984/85. Datain Table6 showa risingtrendfor coal
pricespaid by electricpowerplants beginningas early as 1978/79. Data for the construction
industryshowa consistentpatternof rising buildingcosts from the stat of annualtime seIes
data in 1978[TJNJ1988,p. 590]. Sincethesefiguresexcludeland costs, it wouldappearthat
risingcosts of constructionmateials, whichpromptedcomplaintsin the Chinesepressduring
the late 1970s,also date back to this period. Interviewdata collectedby foreignreserchers
give a strong impressionof rising machineryprices during the late 1970sand early 1980s
[personalcommunication].
Informationon prices paid by powerplants for coal illustratesthe possibleinconsistency
betweeninformationaboutinflationand the pricechangesimpliedby industrialoutputstatistics.
Theelectricpowerindustryis dominatedby large, stateownedenterprises. It seemsreasonable
to assumethat thermalpowerplantsobtainthe bulk of their coal requirementsthroughplanned
allocationsat low officialprices,and that they enjoyconsiderableprotectionfrom the "official
profiteers' attackedin the Chinesepress. This wouldimplythat, relativeto otber consumers
of coal,powerplantsare somewhatinsulatidfrominflationarypressures,and that trendsin their
coal costsshouldunmad the averagerise in coal prices for the entireeconomy.
Datareproducedin Table6 show that averagccoal costs in China's powerindustryhavi
risensteadilysince 1978. The indexof coal costs, whichshouldrepresentan underestimateo
the aveage rise in coalprices,showsan increaseof 88.9 peracntbetween1978and 1987. The
implicitprice indicatorcalculatedfrom gross outputat cunrentand constantprices for the coal
industry,however,showsmuchsmallerincreasesof 66.7 percentfor the state sectorand 48.9
collectiveminingsector. Thesedata lead to the conclusionthat
percentfor the (muchsmauller)
the annualprice changesimplicitin statisticsof gross output value at current (CVIO)and
14 How Fast Has Chine Inditay Oroww?
constant(GVIO)prices probablyunderstatechangesin the salesprice of coal receivedby the
producers. Specifically,we anticipatethat, Jf t indicatestime, the ratio of annualoutputdata
CVIO(t)/GVIO(t)
is too low.
Inconsistencyamongseveraldata seriesraisesthe questionof whichis most likelyto be
is probablytoo smallis basedon the
in error. The conclusionthat the ratio CVIO(t)/GVIO(t)
judgmentthat figuresfor averagecoal cost, whichcomedirctly fromrecordsof financialand
materialtransactionsmaintainedby large, well-establishriunits, are less subjectto distortion
than yntheticcalculationsof outputvalue. If the distortionis containedin the outputfigures,
the previousdiscussionsuggeststhe constant-pricefigures (GVIO)as the probablelocus of
4 This reasoningis not foolproof,but it appearsthat the most likelyexplanationof
difficulty.
inconsistencybetweencoal costs to the powerindustryand the 1VTOand CVIOdata relating
to coal productionis that the seriesof outputvalue at fixed
w faster than the real
valueof industrialoutputin the coal industry.
Inconsistency
betweeninformationaboutinflationarypatternsand thepriceindexesimplicit
in China'sindustrialoutputstatisticsis notlimitedto the coalindustry. More generaldifficulties
becomeevidentwhenone comparesthe implicitpriceindexesderivedfrom outputdata for the
stateand collectivesegmentsof industry.
Despitethe progressof economicreform, marketsfor Chineseindistrial outputremain
heavilyregulated. Manyfirms are obligedto sell substantialportionsof their outputat low
controlledprices. Evenwhenfirmsare allowedto selloutputat 'negotiated' or "imarket'rather
thanplanprices, theyencounternumerouscontrols [Ishihara,1989]. Governmentagenciesset
maximumprices, as when the State Price Bureauissues 'upper price limits for meansof
productionoutsidethe plan," includingpetroleumproducts,aluminumingotsand steelproducts
[friceThcy 3 (1988):51-53). Extra-plansalesof steeland non-ferrousmetalproductsare
also restrictedto designatedcommodityexchanges[rinc TheoX 5 (1988):p. 57]. These
measuresare clearlydesignedto containand restrictthe rise of industrialprices. "law-boning,"
or personalofficialadviceintendedto limit price increases,has the sameeffect.
Each of these measuresis directedprimarilytoward, and appliedmost forcefullyto the
activitiesof large, stateowned enterprises. Under conditionsof excess demand in which
govemmentstrugglesto preventprices from rising to market-clearinglevels, it is difficultto
doubtthat small, widelydispersedcollectiveenterprisesencounterless restrictionon product
pricingthan large, highlyvisiblefirms in the state sector. For this reason, there is a strong
producedin the collectivesectorwill
presumptionthat the rate of priceincreasefor commodities
tend to outpacecomparableinflationrates for similarproductsin the statesector.
4. Itis also pouible thatriing makupsby cooomeil intennsdiarimhavewidenodXw p berwes tbe primes oseved
by ooalprodum and theprice paid by oal user for the powing porton of astha oocur oute X pia
frmwork. However, Jcfkon. RAwWi nd Zheng find no evidenceof A genral ris in markupsfor industrial
intemediat goods.
How Fail Hai Chuis Indu4wry
Grow,? IS
Unfortunately,the price indexes derived from statistics of industrial output value point in
the opposite direution. Table 7 shows that implicit price increases reported for the collective
sector fall short of comparablestate sector data in every year since 1978. Typically, reported
inflation is the coUective sector is half or less of ieported intlation in the state sector.
Comparisonof annual inflation rates for state and collective industrial ou.put witiin the same
branch produces the same result. Between 1978and 1987, nearly three fourths of the instances
where comparable data exist (91 of 126 cases; 9 cases are excluded because of data
incomparability),the implicit inflation is higher in the state sector. In recent years, this result
is even clearer: during 1984/87, we find 35 instancesof higher implicit branch price increase;
in the state sector compared with only 8 instances of higher price increases in the collective
sector (two items are discarded as incomparable)S
These conclusionsare not acceptable, particularly since data from the coal sector suggest
that price indicators extracted from the reported growth of industrial output in constant and
current prices already understate industrial inflation for the state sector. The figures shown in
Table 7 suggest that output statistics for the entire collective sector, which now accounts for
nearly one-third of industral production, systematicallyunderstate the impact of inflation. If
this is true, the most likely mechanismis that rorted output yalue at fixed prices forChir1.
collective industries Systematicallyoverstates the growth of real out= during the 1980s,
particularly in recent years of strong inflationarypressures.
F. Are ReportedGains in Energy ProductivityUnrealisticallyLarge?
Data reproduced in Table 8 indicatethat China's industries achieved very substantialgains
in energy productivity during the early 1980s. These figures, which exclude village industries
(see below) indicate annual gains averging 6.7 percent in real output per ton of standard coal
equivalent. This compares well with figures for energy productivity in mining and
manufacturingfor major industrial nations showing average annual productivitygrowth of 2.6,
3.4 and 7.0 percent for West Germany, the United States and Japan respectively during the
period 1973-86.' If correct, these figures indicate a highly effective response to energy
shortageswithin Chinese industry, which accounts for more than two-thirds of China's energy
consumption.
Many observers have noted that China's energy prices are much lower, in relative terms,
than comparableprices in cther nations and in the world market, and also that domesticenergy
prices have not risen in paralle with global market trends. Despite the inflexibilityof official
prices, the data in Table 6, showingthat avemge coal prices paid by thermal power plants nearly
S.
..ececommenu am basedon a worksheaDEFLATE2.wkl.
6. Based
on a scpare workshee
NENOCOMP.wkl,whichis notincludedin this paper.
16 HowFwatMarChine IrdmrbvGrow?
prices paidevenby
doubledbetween1978and 1987,implystilllargerincreasesin the mumsinal
high-priorityenergyconsumersin China'sindustrialeconomy,
Evenwhere energy prices have not risen steeply,reports suggestingwidespreadenergy
rationingpoint to the bindingnature of energy constraintsacross much of Chineseenergy.
Undertheseconditions,managersseelinghigherfinancialreturnswillimputea highopportunity
cost to inessentialenergyconsumptioneven if directcostsare low. It thus seemsreasonableto
conclude that many Chinese managers feel intense pressure to economizeon energy
consumption.
Changesin industrialenergy productivitycan be decomposedinto three components:
changesin the branchstructureof industrythat decreasethe reladveweightof energy-intensive
industries,reductionsin energyrequirementsfor producingspecificcommodities,and changes
in the commoditystructureof outputwithinindividualbranchesof industry. We havealready
seenthat Chineseindustryexperiencedno significantchangein branchstructureduringthe past
decade(Table3).
Review of Chinese publications,which include numerous descriptionsof physical
input-output
coefficientsrelatedto energyconsumption,sugest only modestgainsfromreduced
unitenergyrequirementsfor specificproducts. Electricpowerconsumedin producingone ton
of crudeoil or rawcoal increasedeveryyearduring 1980/85(Energy1986,pp. 86, 504]. Coal
consumptionper idlowattof power turnedout by large power plants or per ton of cement
producedby majorplants declined,but by less than five percent [ibid., 508, 527]. Sincethe
share of outputcoming from small plants, which are criticized for their excessiveenergy
requirements,hasrisenin manybranches,thepotentialfor majorgrowthof energyproductivity
fromreducedunit energyrequirementsfor specificproductsseemsvery limited.
This leavesstructuralchangewithinindividualbranchesof industryas the mainlocus of
improvedenergy productivityfor Chinese industry during 1980/85. Tlhisconclusionis
problematicbecausesubstantialintra-branchrestructunngappearslimitedto a few branchesmachinery,chemicals,andperhapstextiles. Thisoutcomedrawsattentionto the possibilitythat
a portionof the productivitygainsrepot.edin Table8 maybe attrbutableto measurementerror.
To explorethe possibilityof measurementerror, and also to investigatethe branchpatternof
cnangeip.sarmgy productivity,we turn to an examinationof energy data for 15 branchesof
Chineseindustryduring 1980/85.
Table9 pnsents energyconsumptiondata for 15branchesduring 1980/85. PanelB uses
these figuresto derive annualpercentagechangesin energy productivity(GVIO/E,whereE
representsenergyconsumptionin termsof standardcoal) for 15 branches. Thesedata conta
a numberof improbableitems:can we believe,for example,that energyproductivityin food
processingrose by27.3 percentduring 1984/85,or thatenergyproductivityin machine-building
rose by 21.1 percentin the sameyear?
How Fad Has CAsa
Inr4ustryOro,?
17
We can investigate the consistency of the data for energy consumption (not shown) and
energy consumptionper unit of GVIO by extracting the implicit branch figures for GVIO and
comparingthem with GVIO data from other sources. Tis is done in Table 10, which uncovers
unacceptablylarge discre)ancies for branches9-14 in the 15-branchclasification. Fortunately,
data for the sectors that consume the largest quantities of energy, namely metallurgy, power,
chemicals, building materials, and machine-building,are not involved in these inconsistencies.
Table 11 presents a recalculationof EIGVIOand of annual percentage changes in GVIO/E
for 1980/85based on publishedbranch data for E and on informationfrom other sources giving
branch time series of GVIO. These revised data show fewer improbableentries (readers should
ignore the problems in branches 13 and 14, which shouldbe merged in a future recalculation).
These results suggestthat, among the major energy users, machinery, chemicalsand, to a lesser
extent, metallurgy, have achieved considerable success in raising energy productivity, while
electricityand building materials have recorded much smaller gains.
The veracity of these data, however, depend substantiallyon the accuracy of GVIO data
for chemicalsand machinery- exactly the sectors for which comparison of physical production
and value data indicate the possibility of upward bias in the value totals. Since energy
productivityin these sectors, alone among the major using branches, rises much faster than the
reported national avenge, this dependence is considerable. Removal of the chemical and
machinerybranches, which contribute over half of the overall energy savings attained during
1980/85(Table 16) reduces the cumulativegrowth of energy productivity during 1980/85from
28.6 percent to 17.3 percent (Table 16, Panel 1). If we were to assume that the growth of
energy productivityin machinry and chemicalswas limited to this lower amount, rather than
the much larger figures shown in Tables 1lB and 16, the average annual growth rate of the
entire industrialsector (excludingvillage enterprises)during 1980/85would be reduced by two
percentage points, from 10.8 to 8.8 percent annually.7
Note, however, that the World Bank anticipates large reductions in unit consumption of
electricity in the chemical brarich because of slow relative growth of synthetic ammonia,
"dramaticreductions' in unit power requirementsfor syntheticammonia, and the international
trend toward reduced power intensity in chemical manufacture (1985-A3, pp. 47-49].
Furthermore, Chinesespecialistsregard the materialscontained in Energy (1986]as preliminary;
this book was never released to the general public. However, it is my impression that data
issued in subsequentpublications (notably Energy [1989]), will support similar results.
The importance of energy issues and the major differences in scale and technology
separatingstate and collectiveindustry makesit importantto provide separate analysisof energy
consumption in state and collective industry. As far as I can determine, China's statistical
agencieshave made no effort to do this. Industrialcensus data giving energy consumptionfor
7. Thi calculzion is basedon firstcolumn of Table 2B, followinga separaeworksheg 'What if EnergySavingsate
Trimmed?'dated7-4-1989.
18 HowFa Ha CHasM
. Indaw Gou?
state sector independent accountingunits in 1980 and 1985 allow a trial calculation of energy
consumption and energy productivity trends for collective industry durinigthe period 1980/85.
NOTE: this can perhaps be extended to 1986 (using data in TJNJ 1988, pp. 424-436).
This is done in several steps:
(1) exanine energy data for state sector independentaccountingunits dividedinto 40 branches;
(2) collapse data for 40 branches into 15 branches;
(3) obtair. estimatesof collective sector energy consumptionin 15 branches for 1980 and 1985
by subtractingenergy consumptionby state-sectorfirms from the national totals underlying
Table 9.
(4) calculate changesin energy productivity for the collective sector using derived or published
figures of branch OVIO.
Energy data for 40 branches of industry in 1980 and 1985 are reproduced in Table 12,
where I find no significantinconsistencybetween implied and publisned data for branch GVIO
(readers should ignore the discrepancyfor branch 7, which is trivial in size, and in the residual
branch 40). Again, we see substantialincreasesin energy productivityover 5 years; again, these
gains depend crucially on reported increases for a small number of branches that consumelarge
amountsof energy and report above-averageproductivitygains: chemicals(branch 26); machine
manufacture(branch 35).
These data can also be used to computethe 'energy savings' arising from the presence of
lower unit energy consumption coefficients in 1985 than existed in 1980. As before, two
sectors, machineryand chemicals, dominate the calculatedsavings, accounting for 45 percent
of the total amount (Table 16). If we were to assume that the path of energy productivity in
these two branches palleled the (considerablyslower) gains reported for other branches of
industry, the average annual growth rate for state industry during 1980/85would decline by one
percentagepoint, from 8.2 to 7.2 percent.'
Table 13 reports the result of calculationsthat collapse data for 40 state-sectorbranchesinto
15 branches and derive figures for changes in energy productivity for the 15 branches between
1980and 1985. The transition from 40 to 15 braiichesis incompletebecause it is not possible
to make adjustmentsfor 18 sub-branches (as is done in a separate worksheet, DATA87.wkl);
the discrepancy,however, is not large. Energy productivityfor 15 branches is calculatedin two
ways: first, using GVIO data that is derived from the 40-branch figures shown in Table 12; and
second, using data from other sources that give GVIO for independentaccounting units in the
S. Thuisi bued on Table2 anda s.paz
workshea What if EnergySavingsar Trimmed?'.
HoaswFt
fai
Chi,e
InduurJyGroy?
19
state sector according to the 15-branch classification in use before 1986. Although the
differencesbetween the two sets of calculationsare not large (again, note that branches 13 and
14 should be merged), the latter figures are preferable. Here again we see the importance of
machineryand chemicals, which are the only large branches reporting above-averagegrowth of
energy productivity.
Table 14 presents trial estimates of energy consumption and productivity change for 15
branches of collective industry during 1980/85. In Panel 1 of Table 14, branch clergy
consumption and branch GVIO are derived as residuals from the national totals and the
state-sectorfigures presented above. Comparisonof GVIO figures derived in this manner with
published data showing branch GVIO for collective-sectorindependentaccounting units at and
above the &ing level (recall that the basic energy consumption data for 1980/85 appear to
excludevillage-levelindustry), reveals massiveinconsistency. We therefore focus our attention
on Panel 2 of Table 14, in which branch energy consumptionfor collective industries is derived
as a residual, and then combinedwith publisheddata on collective sector branch output to obtain
productivityfigures.
Scrutinyof these results yields the following observations:
1. There is a major inconsistencyin data for the electric power industry, in which data for
the state sector alone indicate much larger energy consumptionin both 1980 and 1985than
for the entire power branch! As a result, the calculation reported in Table 14 indicates
large negative energy consumptionin the collective power industry for both years. Less
worrisome discrepanciesappear in branches 4 (in which the collective sector minute) and
14 (probably reflecting need to merge with branch 13).
2. Output value per unit of energy consumed (partial energy productivity) appears much
higher in the collective than in the state sector.
3. If valid, the foregoing observation appears to be the result of differences in output
structure rather than superior coUectiveproductivityon a branch-by-branchbasis. Energy
consumptionper unit of real outputby collectiveproducers is markedlyhigher in branches
1, 6 and 9 (metallurgy, machinery, food processing) than in the state sector. Partial
energy productivity seemsto favor collective firms in branches 7, 8, 10, and 12 (building
materials, forestry, textiles, leather), of which only 7 and 10 are major branches. In 7,
the quality of small-plant output is far inferior to the state-sector norm [World Bank
1985-A3, p. 17]. Partial energy productivity is similar for state and collective firms in
branches 5 (chemicals- here the comparisonis blurred by major differences in product
mix) and 11; the comparisonis obscured by data problems for the remaining sectors.
4. Cumulativegains in energy productivityfor the collective sector, summarizedin Table 15,
are far larger than comparablegains for the state sector in every significantbranch except
building materials (ignore the confused and minor branches 13-15). In most cases, the
margin of difference is extremely large.
Inidut Growe?
20 How FastHas Chbwae
This last result seemsquite improbable,and once againcalls attentionto the possibilityof
upwardbias in availablemeasuresof real outputgrowthfnr the collectivesector.
A final point about e'nergy data. There is a variety of material suggestingthat
of outputgrowthmaynot be confinedto TVEenterprisesand thecollectivesector.
overestimates
Someexamples:
Energyconsumptionper 10,000yjan of outputin Beijing's electricpower industrydropped
from 4.62 to 4.07 tons of standardcoal during 1986/87,indicatinga rise of 13.6 percent in
of powerproduceddid not
per kldowatt-hour
energyproductivity,eventhoughcoal consumption
change[Beijing1988,pp. 291, 372].
Nationally,the electric power industry reports a 7.5 percent drop in unit energy
requirementsduring 1980/85(Table 11-B)even thoughcoal consumptionper kwh for large
powerplants(6000kw and above),whichproducea large shareof total poweroutput,declined
by only 3.6 percentduring the sameperiod(Ene gy 1986,p. xxx].
Thechemicalindustryreportsthaienergyproductivityincreasedby 12.6percentin 1984/85
(Table 11-B). Duringthe sameperio:'. !owever, 8 of 16 unit energycoeffici:ntsfor major
plants actuallyincreased! The remainiig eight coefficientsdeclined by an average of 5.8
percent. Only 1 of 16 coefficientsfor major plants declined by more than the reported
industry-wideaverage(Energy1986,p. 87].
The buildingmaterialsindustryreporteda 20 percent rise in energyproductivityduring
1980/85,but unit energy requirementsat majorplants declineby a maximumof 6.3 percent
[Energy 1986, p. 88]
Reportedenergyproductivityin coalproductionimprovedin everyyearbut 1984/85(Table
l 1-B),showinga cumulativegain of nearlyfivepercent. Yet data for majorenterprisesshow
a rising treiid for unit energy requirements;power consumptionper ton of raw coal rises in
everyyear [Energy1986, pp. 86, 493-500]
V. CONCLUSIONS
This survey reveals considerableevidencepointingto the existenceof upwardbias in
measuresof China'sreal industrialoutputduringthepast decade. Theissueis notwhethersuch
bias exists, but whetheror not its presencesubstantiallyalters our perceptionof the rate and
patternof Chineseindustrialgrowth.
To clarifythis issuerequres an investigationof the possibleextentof upwardbias. Thisin turn
will require an analysis of possiblelinks betweenupward bias, which itself is difficultto
observe,and other economicpatternsthat may be more readilymeasurable.
How Fait Has Ch;na
Irdalwvy Grown?
21
TABLE1: ALLINDUSTRY
A. Level of IndustrialGross Output, 100 millionyuan
Year
GVIO
Iadusuy
GVIO
Viage
GVIO
Industzy+
CvIO
Indus+
Price
Iadex
Annual %
Inflazion
Data in 1970prices
1978
1979
1980
1981
4231
4591
4992
5199
161
184
222
241
4392
4775
5214
5440
4237
4681
5155
5400
96.47
98.03
98.87
99.26
1.62
0.85
0.40
246
277
325
460
661
841
1150
5424
5854
6489
7490
8956
9820
11457
5400
5811
6461
7617
9717
11194
13813
99.56
99.26
99.57
101.70
108.50
113.99
120.56
N.A.
-0.29
0.30
2.14
6.69
5.06
5.76
108.72
118.72
123.86
133.68
148.18
171.04
204.52
224.25
261.63
110.48
121.67
127.45
137.15
152.49
179.77
229.34
264.20
326.01
Data in 1980prices
1981
1982
1983
1984
1985
1986
1987
5178
5577
6164
7030
8295
8979
10307
B. Indexof Output Growth, 1978- 100
1979
1980
1981
1982
1983
1984
1985
1986
1987
108.51
117.99
122.88
132.35
146.28
166.83
196.85
213.08
244.59
114.28
137.89
149.69
168.55
197.76
279.91
402.21
511.74
699.77
(continued)
22 How Fast Has Chine Inudwy Grown?
TABLE1: ALLINDUsTRy(continuation)
Year
GVTO
Industry
GVIO
Village
GVIO
Industry +
CVIO
Indus +
C. Annual Output Increase Over Previous Year (percent)
1979
1980
1981
1982
1983
1984
1985
1986
1987
8.51
8.73
4.17
7.70
10.52
14.05
17.99
8.24
14.79
14.28
20.65
8.56
12.60
17.33
41.54
43.70
27.23
36.74
Source: Rawsli written files GVIO-tables.
8.72
9.19
4.33
7.93
10.85
15.43
19.57
9.65
16.6
10.48
10.13
4.75
7.61
11.18
17.89
27.57
15.20
23.40
Price
Index
Annual %
Inflation
How Fast Hai Chinw Indwray 7rown? 23
TABLE2: BREAKDOwNOF GROSSINDUSRAL OUTPUTAT CONSTANTPRICES
DATA EXCLUDEVILLAGE-LEYELUNITS
B
Total
C
State
D
Total
1978
1979
1980
1981
1981
1982
1983
1984
1985
1986
1987
4231
4591
4992
5199
5178
5577
6164
7030
8295
8979
10307
1978
1979
1980
1981
1981
1982
1983
1984
1985
1986
1987
H-(F +G)
0
-1
1
17
1
0
0
210
367
2413
3243
3416
3720
3928
4028
4054
4340
4748
5171
5840
6201
6902
Check
file.sGVIO-tablea
Sourvs: Rawsld written
814
871
1034
1131
1089
1193
1354
1758
2301
2637
1217
G
F
E
Collective Sector Categories
CunlDui
Xiang-B
Xiang-A
H
Xiang
zhen
161
184
222
241
246
277
325
460
661
385
424
509
579
579
646
757
1245
1827
212
234
280
310
323
354
413
539
742
948
3243
224
241
286
321
332
369
432
575
799
2413
24 How FoatHas ChinueIndwr^yGrow.?
TABLE3: BRANCHSTRUCTUREOF GVIO AT 1980 PRICES(PERCENT)
A. Branch Structure for StateEnterprisea
(SOE)
Br
1
2
3
4
5
6
7
8
9
10
11
12
13
14
iS
Sum
1978
11.80
4.82
4.26
8.01
11.81
21.12
2.75
1.89
12.44
13.83
1.04
0.00
3.07
0.00
3.14
100.00
1979
1980
1981
1982
1983
11.99
11.81
11.08
10.96
10.73
4.79
4.87
4.86
4.82
4.59
3.99
3.61
3.42
3.36
3.25
7.81
7.49
7.16
6.83
6.69
11.60
11.92
12.02
12.41
12.44
21.34
20.26
18.55
19.86
21.34
2.69
2.67
2.50
2.57
2.56
1.86
1.78
1.73
1.67
1.56
12.65
13.01
14.30
14.58
13.86
14.20
16.11
18.10
16.67
16.78
0.51
0.54
0.60
0.56
0.55
0.53
0.58
0.63
0.57
0.52
3.18
3.18
2.93
1.44
1.43
0.00
0.00
0.00
1.48
1.44
2.85
2.17
2.12
2.24
2.26
00.00 100.00 100.00 100.00 100.00
1984
1985
10.77
4.45
3.15
6.68
12.43
23.12
2.59
1.48
13.52
15.56
0.56
0.48
1.46
1.42
2.32
100.00
10.51
4.66
2.99
6.52
11.70
24.58
2.81
1.24
13.19
15.19
0.56
0.47
1.48
1.48
2.62
100.00
1984
1985
1986
1987
10.58 10.52
4.61
4.59
2 83
2.65
6.43
6.37
12.61
12.36
25.86
25.51
3.45
2.70
1.14
1.13
12.99
12.99
14.56
14.42
0.52
0.53
0.48
0.46
1.60
1.64
0.46
0.47
1.89
3.67
100.00 100.00
B. BranchStructure for CoUectiveEnterprises (COE)
Br
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
1978
1979
1980
1981
1982
1983
198b
1987
1.97
2.28
2.34
2.17
2.32
2.47
2.54
2.89
3.39
3.56
0.11
0.15
0.17
0.21
0.23
0.25
0.22
0.20
0.20
0.20
2.27
2.12
1.94
1.87
1.93
1.94
1.92
1.64
1.63
1.42
0.12
0.13
0.13
0.11
0.11
0.14
0.13
0.15
0.18
0.21
10.94
10.74
10.76
10.93
11.45
11.94
11.26
10.94
11.17
11.30
36.07
34.84
32.63
30.38
30.68
31.55
30.95
33.27
32.83
33.07
8.37
8.63
8.32
7.91
8.57
8.46
8.17
7.50
8.89
7.51
2.55
2.73
2.72
2.64
2.71
2.52
2.33
2.23
2.85
2.28
2.96
3.39
3.70
4.39
4.69
4.71
5.04
4.96
5.37
5.46
7.90
8.58
10.04
11.92
12.08
12.26
16.02
16.3
15.76
15.96
11.28
9.36
10.49 10.96
9.59
9.22
8.44
7.10
6.39
6.22
0.uO
2.35
2.94
3.05
2.58
2.34
2.09
2.08
2.17
2.20
5.48
5.06
5.35
5.53
5.26
4.61
1.02
1.01
2.45
2.61
0.00
1.02
1.02
1.06
1.08
1.08
4.18
5.13
3.62
3.94
9.97
8.61
7.43
6.88
6.74
6.50
5.71
4.59
3.11
4.07
100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00
(continued)
IndustryOra"?
HowFPaHat ClaAmaal
25
TABLE3: BRLNCHSTIrUCT1z o GVIO AT 1980 PRiCzS(PEcCNT) (coaninuatin)
C. Branch Structurefor SOE and COE Combinod(peamt)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
9.99
3.9S
3.91
6.56
11.65
23.87
3.79
2.01
10.70
12.74
2.92
0.00
3.52
0.00
4.39
10.21
3.94
3.6S
6.40
11.45
23.81
3.78
2.02
10.96
13.17
2.13
0.86
3.53
0.19
3.91
9.90
3.92
3.27
6.00
11.69
22.76
3.81
1.97
11.13
14.89
2.55
1.06
3.62
0.21
3.23
9.18
3.86
3.08
5.6S
11./9
21.08
3.65.
1.92
12.18
16.78
2.82
1.1S
3.49
0.23
3.14
9.07
3.82
3.0S
5.36
12.20
22.22
3.87
1.89
12.42
1S.67
2.53
1.01
2.28
1.39
3.22
8.84
3.61
2.96
5.22
12.33
23.63
3.88
1.77
11.81
15.77
2.49
0.93
2.1S
1.36
3.21
8.69
3.38
2.84
5.02
12.14
25.10
4.00
1.70
11.38
1S.68
2.55
0.89
1.34
2.12
3.17
8.39
3.43
2.61
4.7S
11.49
27.00
4.11
1.51
10.91
1S.50
2.38
0.92
1.35
2.49
3.16
8.49
3.33
2.48
4.61
12.19
27.88
S.03
1.64
10.77
14.91
2.23
0.97
1.85
1.38
2.24
8.37
3.23
2.27
4.47
12.03
27.35
4.19
1.48
In).66
14.19
2.29
1.00
1.94
1.54
3.79
100.00
100.00
100.00
100.00
100.00
Note: these data excludevilba-level
6 machiney
7 buildingmaterials
8 forestry ad wood processng
9 food procesing
12 leuher prcesing
13 paper
14 cultnualand at products
15 other
Source: Wodrhot STRUCTURB.wkl
100.00
100.00
100.00
;mepris;they ar oonfingdto indepmida accountingunits.
Key to branches:
i metallurgy
2 power
3 coal
4 petroleum
S chemicals
10 textile
11I
99.99
100.00
26 How FastHas Cine InrdwtyrGrown?
PRICES(100 MILON YUAN)
TABLE4: NETOUTrT ATCURRENT
INDEPENDENT
ACCOUNTiNG
UNITS,EXCLUDING
VILAGE ENTERRLSEs
Colective
State
Total
Xiang
1978
1358
1979
1980
1981
1486
1648
1690
1319
1317?
322
342
1982
1774
1373
369
1983
1984
198S
1930
2246
2767
1501
1721
2058
506
679
415
183
247
1986
2979
2178
763
296
1987
3488
2530
894
354
Source:RawaliwnttenfilesGVIO-tables.
Net output ratio
(baed on CVIO data for independentaccountingunit - not shown)
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
Total
State
Colective
0.35
0.344
0.336
0.332
0.333
0.329
0.316
0.351
0.341
0.332
0.332
0.340
0.336
0.322
0.348
0.337
0.334
0.332
0.314
0.313
0.301
114
How FastHas ChIat Indua Gretw? 27
TABLE5: CEHsUcAL
INDurrRy
Averag
Perew Change
% Change
GVIO,P80
physical output
Nine Products
1979
1980
1981
1982
1983
1984
1985
1986
1987
13.51
7.85
-4.06
7.30
8.33
3.30
1.05
5.77
14.S2
Differmtial
Growthof
OVIO, percentage
7.01
10.77
4.66
11.43
12.46
12.04
11.61
12.17
17.C8
-6.60
2.92
8.72
4.13
4.13
8.74
12.66
6.40
2.56
Source: 1988TJNJ, pp. 34546 for commoditydat; OVIOdat aro from Indusry 1988, p. S4.
Thea figtuemezcluds villge-level onprises. Figures for 1978-80woro converted from 1970
to 1980prime usaug th ntio of .1981gro output for chemicu_at 1980 and 1970 prioe
28 How Fast Has Chks
Indawmty rotm?
finLATIONIN
DATATo MEASURe
TAILE6: ALTmENATrVE
THE COAL INDUSTRY
A
B
C
Costiton
Sid Coal
% change
frompan
Price
Indx
yur
1978-100
Y/ton
CVIO/OVIO
Annual Price
Change From
Cumulatve
Price Chang
Since1978
Pat Year
Percet
SOB
COE
Power
Plats
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
43.77
38.99
39.86
43.10
44.17
44.70
44.80
42.06
44.93
46.18
47.71
55.40
61.32
64.01
69.21
7S.21
79.46
NA.
-10.92
2.23
8.13
2.48
1.20
0.22
-6.12
6.82
2.78
3.31
16.12
10.69
4.39
8.12
8.67
5.65
100.00
89.08
91.07
98.47
100.91
102.12
102.35
96.09
102.65
105.51
109.00
126.57
140.10
146.24
1S8.12
171.83
181.54
14.32
7.25
2.56
1.66
1.23
2.71
13.68
5.13
4.94
4.44
1.38
5.05
4.99
5.41
3.82
9.83
2.01
3.97
6.82
9.80
13.43
31.72
45.79
52.19
64.5S
78.82
88.92
tAkenfom workshoetDEFLATE2.wkl.
Source: Coal costs fromXu et Al(1989); implicitprice indbexas
How rar Hu ChLRueI1duvY Grow?
TABLZ
7: PRICt INDIn EXTRACTDMOM INDUSAL
Ouwnr VALUzDATA
Year
PR1CE
SOE
INDEX
COE
ANNUAL % CHANGE
IN PRICE LEVEL
SOE
COE
N.A.
1.84
1.09
0.38
0.10
.0.05
1.95
6.30
3.33
7.07
N.A.
-0.12
-0.60
0.04
.1.06
4.36
0.72
4.28
1.50
3.71
SOB
DIFFERENTLAL
PRCE CHANGE
percentage
poin
CombinedData for All 15 Banch
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
0.96
0.98
0.99
1.00
1.00
1.00
1.02
1.08
1.12
1.20
0.97
0.97
0.96
0.96
0.95
0.95
0.96
1.00
1.01
1.05
Soure: WorksheetDEFLATE.wkil.
N.A.
1.97
1.69
0.35
1.17
0.41
1.23
2.02
1.83
3.36
219
30 How F
Has ChIldmsy
Grows?
TAJLT 6SZNUGY PRODUCtMITY
PI CN
OmciAL DATA,1918-7
You
Eneg
UN
PA 10 Milioa
Yuanof OVIO
(ton std. coal)
1980
1981
1932
1983
1984
1985
1986
1987
78411
72380
70374
6704S
62592
56872
INDUMY
Annual Pecmu
Chanp in
Ewa
Productivity
ns.
8.33
2.85
4.97
7.11
10.06
How FuMHMm
ChlmueIr4Wi Gru?
TAILE9: OmciAL ENERGY
DATAFORCHNE
1980-198S
INDUSTRY
BYBRANCH,
A. Energyconsumptionin tons of standard
coal per 100 million
yuas of GVIO at 1980 pricu
branch
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1S
total
1980
1981
1982
1983
1984
1985
164549
99124
162468
83429
148546
32538
217821
36959
131594
32537
701
6839
173163
11482
77476
78411
156603
99492
157580
76069
136517
31160
21552S
37293
127529
31258
666
6371
144298
12205
73383
72380
150471
96161
155472
73443
127091
29269
215280
33711
128454
29761
712
6721
161236
12169
70686
70374
147084
93911
152577
69541
118445
25823
20959S
38041
135213
30040
662
5813
168497
12370
66480
67045
142632
93926
151079
65960
110716
22886
193233
33546
128038
28645
633
5054
165408
11549
61444
62592
132 .
92062
156652
60040
98176
18894
180283
34263
100577
28135
717
5224
154314
11476
58634
56872
B. Annualpercentage
risein GVIO per ton of standardcoalconsumed
brmnch
1981
1982
1983
1984
1985
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
total
5.07
-0.37
3.10
9.68
8.81
4.42
1.07
-0.90
3.19
4.09
5.26
7.35
20.00
-5.92
5.58
8.33
4.08
3.46
1.36
3.58
7.42
6.46
0.11
10.63
-0.72
5.03
-6.46
-5.21
-10.51
0.30
3.82
2.85
2.30
2.40
1.90
5.61
7.30
13.34
2.71
-11.38
-5.00
-0.93
7.55
15.62
-4.31
-1.62
6.33
4.97
3.12
-0.02
0.99
5.43
6.98
12.83
8.47
13.40
5.60
4.87
4.58
15.02
1.87
7.11
8.20
7.11
7.56
2.02
-3.56
9.86
12.77
21.13
7.18
-2.09
27.30
1.81
-11.72
-3.2S
7.19
0.64
4.79
10.06
Source: Data takenor calculatedfrom Energy 1986,p. 16.
31
32 HowF
HmmChL.e Iadaiy otrP
TAMZ 10: GVIO DATAFOR15 BRANCHS(100 MLION YUAN,1980 PrICES)
A. Derived from Statisticsof Energy Consumption andEfficiency, 1980-1985
brunch
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
total
1980
1981
1982
1983
1984
473.05
189.16
159.79
290.07
565.08
1!21.77
196.80
105.52
112.32
612.23
727.53
128.67
51 63
26.13
168.18
4745.51
456.70
194.89
157.25
282.11
591.43
1079.91
195.10
104.85
121.78
690.06
855.86
147.54
58.56
69.64
172.25
4946.81
485.21
207.05
166.33
287.98
658.98
1225.19
222.59
112.13
129.33
755.69
870.79
141.35
55.69
73.96
188.72
5330.66
523.71
220.21
173.34
310.03
741.10
1440.58
24S.43
116.19
134.08
794.27
951.66
153.11
57.03
81.65
212.70
5900.37
579.39
235.61
194.73
334.14
830.32
1756.97
287.27
126.69
151.91
865.77
1090.05
178.08
62.21
92.65
250.80
6721.95
664.04
272.75
208.42
416.39
926.70
2235.10
350.62
133.09
213.17
951.84
850.77
199.08
76.47
108.05
309.55
7962.79
578.22
224.72
188.83
334.37
807.57
1670.42
266.29
112.93
756.97
1043.18
169.94
59.11
89.49
141.1
211.27
6654.41
657.4
268.29
204.69
371.82
899.91
2114.46
322.17
118.36
854.11
1213.85
186.21
72.06
105.68
19S.18
247.82
7832.01
1985
B.PublishedGVIO daa: SOE+ COE Independent
Units, 1980pricas
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
total
470.42
186.35
15S.48
285.22
555.34
1081.82
181.02
93.75
523.82
707.42
121.31
50.14
171.82
9.84
153.69
4752.45
452.32
190.35
152.04
278.63
S81.23
1039.19
180.18
94.75
600.53
827.08
138.96
56,60
171.87
11.13
154.89
4929.75
481.13
202.29
161.48
284.43
647.04
1178.18
205.45
100.47
6S8.76
830.69
134.07
S3.S8
120.66
73.65
170.61
5302.49
519.19
211.32
173.01
305.29
721.12
1382.13
227.13
103.71
690.6'
922.22
145.89
54.21
125.65
79.43
187.9
S848.93
(continued)
HOwFuc Mu CAba. 1Ay
Oeu t
TABLE10: aoIO DATAFOR15 BLgCNz (100 MWoN YUAN,1930 PRC=) (On*imAsoa)
branch
1980
1981
1982
1983
1984
1935
0.86
4.04
2.99
1.53
2.70
4.06
7.45
10.74
-41S.11
-16.11
84.67
64.59
-120.31
2.66
11.66
0.87
0.20
4.62
3.03
-0.07
2.74
4.93
7.30
10.86
-398.31
-20.49
84.41
66.81
-43.85
-52.30
15.76
1.00
1.00
1.64
1.79
10.70
2.89
5.40
8.11
11.07
-300.67
-27.53
78.11
63.80
-38.20
-80.64
19.94
14.84
9.79
15.73
7.06
12.17
2.69
22.65
4.26
2.62
2.S9
0.43
1.64
7.65
1.27
7.53
6.76
14.29
9.85
1S.58
6.59
11.38
2.41
20.85
3.76
2.57
2.38
0.41
1.52
11.50
0.76
7.29
6.32
13.40
9.36
15.95
6.72
10.11
2.00
19.62
3.85
2.51
2.21
0.33
1.44
11.17
0.64
7.32
5.78
C. GVIO discrepancy:derived - publishd u X of derivedfigurn
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1S
tota
0.56
1.48
2.69
1.67
1.72
3.56
7.55
11.16
-370.84
-IS.SS
83.33
61.03
-232.80
62.34
8.62
-0.15
0.96
2.33
3.32
1.23
1.72
3.77
7.65
9.63
-393.14
-19.86
83.76
61.64
-193.49
84.01
10.08
0.34
0.84
2.30
2.92
1.23
1.81
3.84
7.70
10.40
-409.15
-9.93
84.60
62.09
-116.6S
0.42
9.60
0.53
1.64
A7. Revised calcula*io: os sad. coal per Yi yua CIVIO,P80
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Toal
16.55
10.06
16.70
8.48
15.12
3.37
23.56
4.16
2.79
2.82
0.42
1.75
S.20
3.05
8.48
7.83
15.81
10.19
16.30
7.70
13.89
3.24
2..4
4.13
2.59
2.61
0.41
1.66
4.92
7.63
8.16
7,26
1S.17
9.84
16.01
7.44
12.94
3.04
23.32
3.76
2.52
2.71
0.46
1.77
7.44
1.22
7.82
7.07
is
34 Now Past Mu C%kwe Indi&y Gro?
TABLE11: RriD
ON
ANNUALEczNT iNcRrAC IN ENEGY PRODUCTVTYBASED
CALCULATON:
PCAL
ENERGY
CONSUmpONANDPUBnL
GVIO DATA
Cumuluivi
branch
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1S
total
1981
1982
1983
1984
1985
Total
1980/1985
4.65
-1.23
2.44
10.16
8.81
4.19
0.96
0.81
8.08
7.97
2.49
5.67
S.83
-60.06
3.89
4.20
3.50
1.77
3.58
7.32
6.39
0.06
9.68
2.50
-3.67
-11.30
-6.33
-33.94
524.68
4.37
2.28
0.57
1.82
5.29
6.33
13.08
2.99
-11.72
.3.89
4.64
7.09
8.00
-2.69
-3.84
3.90
3.81
.0.63
0.95
7.14
6.93
11.81
8.65
13.25
2.16
8.83
6.36
7.83
-33.48
67.57
3.17
6.70
5.22
.32
-1.97
12.60
20.53
6.25
-2.32
2.36
7.76
23.94
5.50
2.98
19.36
-0.41
23.53
7.50
4.67
26.19
49.S1
68.93
20.09
7.98
11.34
27.63
28.34
21.60
-53.40
379.90
15.76
7.80
2.66
4.60
6.97
9.35
35.41
How FastHai Chinea Indawsy Growu? 35
UNiTS, 40 BRANCES,
TABLE12: ENERGYDATAFOR STATESECTORINDEPENDENT
1980 AND1985
A. Raw Data from Indusuial Cesus
Branch
1
2
3
4
5
Energy Consunption
10,000 tons std. coal
1985
1980
2283
1084
46
106
69
Tone of *td. coal per
10,000 yuan of GVIO
1985
1980
2543
1147
62
116
76
18.24
8.27
5.61
5.3
6.61
16.22
7.15
5.68
4.18
6.11
6
124
132
7.65
8.39
7
0.0001
a
156
9
10
11
12
13
14
iS
16
17
i8
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
3S
3
37
38
39
44
740
311
36
1
952
10
42
0.0001
183
65
1120
447
68
5
1234
13
48
3.2
4.06
4.04
2.21
5.64
0.41
0.68
1.72
0.44
1.87
3.87
4.98
3.91
2.31
4.53
0.43
0.2
1.63
0.42
1.78
91
132
4.S
5.46
9
594
27
11
6
7431
1560
300
5829
237
321
160
39
2631
5687
620
135
1170
370
194
80
38
10
746
36
13
9
9127
1613
330
6211
322
481
195
59
3594
6397
754
IS4
1343
43S
224
99
43
1.89
9.21
0.79
0.86
1.27
38.89
9.43
23.08
18.08
3.97
9.71
2.19
1.58
21.44
19.01
5.2
2.69
3.17
A.51
1.8S
1.32
1.28
1.5
8.15
0.67
0.58
0.87
34.44
7.76
20.37
13.78
2.68
5.4
1.84
1.37
19.34
16.36
4.64
2.19
2.1
1.66
1.23
0.5
0.89
1.17
8.91
1.31
6.99
40
sum
4
33S48.00
7
39593.00
materias, 3: 346-355
Source: Indistia ceamns
(¢e)
36 How FwziHas Chin se Indsany Grown?
UNITS,40 BRANCHES,
DATAFORSTATESEcTORINDEPENDENT
TABLE12: ENERGY
1980 AND1985 (contiustion)
B. Analysis and ConsistencyCheck: Energy Data for 40 branchesof State Industry
% rise
in energy
productivity
1980/15
Branch
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1S
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
sum
12.45
15.66
-1.23
26.79
8.18
-8.82
-17.31
-18.47
3.32
-4.33
24.50
-4.65
240.00
5,52
4.76
5.06
-17.58
26.00
13.01
17.91
26.47
45.98
12.92
21.52
10.59
31.20
48.13
79.81
19.02
15.3^
10.86
16.20
12.07
22.83
50.95
51.20
50.41
164.00
43.82
-14.60
27.47
Derived GVIO
Yi Yuan
198S
1980
125.16
131.08
8.20
20.00
10.44
16.21
0.00
38.4
10.89
334.84
55.14
87.80
1.47
553.49
22.73
22.46
20.22
4.76
64.50
34.18
12.79
4.72
191.08
165.43
13.00
322.40
59.70
33.06
73.06
24.68
122.71
299.16
119.23
50.19
369.09
147.41
104.86
60.61
29.69
3.42
3768.28
156.78
160.42
10.92
7.75
12.44
15.73
0.00
36.75
16.62
484.85
98.68
158.14
2S.00
757.06
30.95
26.97
24.18
6.67
91.53
53.73
19.12
10.34
265.01
207.86
15.81
450.73
120.15
89.07
105.98
43.07
185.83
391.01
162.50
70.32
639.52
262.05
182.11
198.00
48.31
5.11
5667.07
PublishedOVIO
(Yi Yuan)
1985
1980
1S6.19
161.14
10.86
27.79
11.99
15.75
0.02
36.95
16.58
483.00
96.83
156.90
23.82
754.70
31.71
26.74
24.73
6.55
90.30
54.25
19.31
10.09
263.85
207.50
15.85
449.98
119.55
90.12
106.12
43.63
185.62
391.90
163.94
69.52
636.38
261.30
181.43
196.43
48.42
9.03
5656.77
% diff.
1985
-0.38
0.4S
-O.S1
0.14
-3.61
0.11
77300.00
0.55
-0.26
-0.38
-1.87
-0.78
-4.72
-0.31
2.45
-0.54
2.29
-1.75
-1.35
0.97
1.01
-2.46
-0.44
-0.17
0.24
-0.17
-0.S0
1.17
0.13
1.31
-0.11
0.23
0.89
-1.14
-0.49
-0.29
-0.38
-0.79
.22
76.73
-0.18
How Fast HIt Chinse Industy Grown? 37
.1ATATO 1S
OF SOE ENERGY
TABLE13: RouGH CONVERSON
FORMAT
BRANCH
Bmnch
EnergyCona.
coal
lOOOtstid
1985
1980
Derived
Yi
1980
GV1O,P80
yuan
1985
Ton aid coal per
10000yuan GVIO
1985
1980
% Rui
GVIO/E
1980,85
1. Using DEFIVED GVIO DATA
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Sum
6459
7431
2583
2644
6265
1987
2824
256
1087
1273
10
42
594
44
49
33548
7329
9127
2873
2760
6787
2298
3802
325
1635
1715
13
48
746
58
77
39593
592.18
446.59
265.01
191.08
172.59
138.16
368.28
296.51
719.92
479.84
1400.32
761.84
214.00
149.36
67.59
63.41
477.79 741.66
586.55 846.13
20.95
22.73
26.97
22.46
91.53
64.50
83.19
51.69
46.73
15.78
5667.07
3768.28
14.46
38.89
18.70
8.92
13.06
2.61
18.91
4.04
2.28
2.17
0.44
1.87
9.21
0.85
3.11
8.90
12.38
34.44
16.65
7.49
9.43
1.64
17.77
4.81
2.20
2.03
0.42
1.78
8.15
0.70
1.65
6.99
16.86
12.92
12.31
18.99
38.49
58.93
6.42
-16.04
3.20
7.08
4.76
5.06
13.01
22.09
88.46
27.43
447.90. 594.50
263.85
14.71
169.03
136.79
368.64
283.99
451.95 661.83
1390.66
768.28
159.09
101.09
69.88
67.S6
493.22 746.11
859.30
610.92
31.71
20.47
26.74
21.88
83.69
120.38
83.65
0.00
148.08
82.28
5656.76
3791.42
14.42
40.23
18.88
9.31
13.86
2.59
27.94
3.79
2.20
2.08
0.49
1.92
4.93
12.33
34.59
17.00
7.49
10.25
1.65
23.90
4.65
2.19
2.00
0.41
1.80
8.91
0.69
0.52
7.00
16.97
16.30
11.10
24.35
35.18
56.51
16.89
-18.53
0.57
4.41
19.16
6.94
-44.64
GVIO data
2. Using P1WULISHED
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Sum
6459
7431
2583
2644
6265
1987
2824
256
1087
1273
10
42
594
44
49
33548
7329
9127
2873
2760
6787
2298
3802
325
1635
1715
13
48
746
58
77
39593
0.60
8.85
14.53
26.42
Note: 'published GVIO for 1S branches is from DEFLATE.wkl. Derived GVIO daa comes from collpeing
40-branchGVIO figure implicit in th eergy and energy/GVIOfigur. into 15 bmnch.s followingthe algorithm
containedin workshootDATA86.wkl, omitting ub-branchadjuatmets for whichno data are available. *Yi yuan
-
100,000,000
Yuan.
38 How Fast HMsChiir
Indamuyr
Grown.?
TABLI 14: TRIALCALCULATION
OF ZNERGY
CONSUWrnON
ANDPRODUCTITYFORCOLLCTm
NON-INDEPENDENT
UNITSAND"OTHER"OwNERmu FORMS)1980 AND1955
INDUSTRY
(INCLUDING
1. Using DERIVEDGVIO figur.
Derived
OVIOYi P80
FAwvycons.
Bralch
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Sum
Branch
1
2
3
4
5
6
7
8
9
10
11
12
13
14
I5
Sum
lOOCKt
std coal
1980
1985
1325
1477
-6616
392
-260
2311
1925
2519
131
509
963
48
S6
434
66
1738
5693
-5556
13
-224
2129
1663
1441
134
391
719
41
46
300
-14
1254
3662
1980
1985
26.46
-1.92
21.62
-6.44
85.24
359.93
46.44
42.11
-365.47
25.68
704.80
106.21
-12.87
-25.56
152.40
977.23
71.86
7.74
35.83
48.11
206.78
834.78
136.61
65.50
-528.49
105.71
819.81
172.11
-15.07
24.86
262.81
2295.72
Publishe OVIO
Yi Yuan, P80
1980
1985
22.51
1.65
18.69
1.23
103.39
313.54
79.92
26.18
35.6
96.5
100.33
28.26
51.44
9.84
71.41
960.99
62.90
4.44
35.66
3.18
237.98.
725.86
163.08
52.71
108.00
354.55
154.50
4S.32
52.88
36.33
87.86
2175.25
Ton utdcoal per
10000yuan OVIO
1980
1955
% RiPe
GVIO/E
1980/85
50.07
143.60
-438.44
-94.50
-743.73
123.50
100.36
68.28
59.09
11.08
207.36
-0.65
33.11
-19.06
-79.37
24.43
51.11
20.55
-854.85
10.94
-S.40
11.18
2.31
18.44
2.00
-0.96
9.11
0.06
0.33
-28.81
2.66
6.61
2.48
2893.17
0.60
34.79
24.98
4.62
31.03
3.18
-1.07
28.00
0.06
0.43
.23.3
0.!'
8.23
3.7S
PFrent Difference
(Deived-publshed)
As perc of Derived
1980
.14.93
-155.92
-13.56
-119.10
21.30
-12.89
72.09
-37.84
-109.74
275.79
-85.69
-73.39
-499.77
-138.49
-53.14
-1.66
1985
-12.46
-42.63
-0.47
-93.39
15.09
-13.05
19.38
-19.53
-120.44
235.40
-81.15
-73.67
-450.98
247.30
-66.57
-5.25
Note:publishedCOBOVIO wefromDEPLATE.wkl.
(cmmd
How Fan HE Oshna ladwauyGroww? 39
TABLE14: TRuALCALcuLATiONOFzNzRGY CONSUWnON ANUD
PRoDucTIVIY FORCOLLECTIVE
INDUSTRY
(INCLUDING
NON-INDEPENDENT
UNITSAND"OTMERN
OwNERsH FORUS)1980 AND1985 (continuaton)
2. Using Pubbshed
GVIO Figures
Branch
Energy Cons.
10000t
atd coal
1980
1985
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Sum
1325
-5S56
13
-224
2129
1663
1441
134
391
719
41
46
300
-14
12S4
3662
1477
-6616
392
-260
2311
1925
2519
131
509
963
48
56
434
66
1738
5693
OVIO Yi P80
1980
1985
22.51
1.65
18.69
1.23
103.39
313.5'
79.93
26.18
3S.60
96.50
100.83
28.26
51.44
9.84
71.41
961.01
62.90
4.44
35.66
3.18
238.08
723.80
163.08
48.48
108.00
354.55
154.S0
45.32
21.99
111.53
99.74
2175.25
Ton std coal per
10000yu ff GVIO
1980
1985
58.85
-3372.19
0.70
-182.11
20.59
5.30
18.03
5.12
10.93
7.45
0.41
1.63
5.83
-1.42
17.56
3.81
23.48
-1490.09
10.99
-81.76
9.71
2.66
15.45
2.70
4.71
2.72
0.31
1.24
19.74
0.59
17.43
2.62
% Rise
GVIO/E
1980/85
150.62
126.31
-93.67
122.74
112.14
99.42
16.72
89.39
133.03
174.33
30.88
31.71
-70.45
-340.43
0.78
45.60
40 HowFdwha,
as.u. IndumyGam"?
TABLJ15: PzatCzNTCHANCEiN JNDUIIRIAL
ENzaGYIRoDucTTY roFO
15 BUSNcuS, 1980/85
1
2
3
4
s
6
7
a
9
10
11
ToWl
Stale
Collective+
23.53
7.S0
4.67
26.19
49.S1
68.93
20.09
7.98
11.34
27.63
28.34
16.97
16.30
11.10
24.35
35.18
56.51
16.89
-18.53
0.57
4.41
19.16
150.62
126.31
-93.67
122.74
112.14
99.42
16.72
89.39
133.03
174.33
30.88
12
21.60
6.94
13
14
15
-53.40
379.90
15.76
-44.64
n.a.*
14.53
-70.45
-340.43
0.78
Totl
35.41
26.42
45.60
31.71
Souem: Table 11, 12, and 13. Baundon calculatins usingpublishe raher than derived daft for brmachOVIO.
*Branches13 and 14 should be meged in a revinsdca1ulatio underlying outt
jumbled.
dat for thee two bncls
ame
HowFa Ns OuLw hdmty Oro
TABL 16: DATAONwENGY SAVYNGSo,
1980)J35
1. IndustryAbovethe Ville Level, 1SBraOch.
EnergyUe in 19t5
Enegy Savinp
10,000 Tos
St. Coal
bruach
1980
Relaios
10000l
Acoal
B
*Svinge
(A.B)/B
pero"
of tow
A
1
10878
8806
0.235
2072
16.01
2
3
4
2699
3418
31SS
13602
7134
7591
492
2387
3418
78
126
5S0
595
2101
58225
2511
3265
2500
9091
4223
6321
456
2144
2678
61
104
1180
124
1115
45286
0.075
0.047
0.262
0.495
0.689
0.201
0.080
0.113
0.276
0.283
0.216
40.534
3.799
0.151
0.256
188
153
655
4504
2911
1270
36
243
740
17
22
630
471
286
12939
1.46
1.18
S.06
34.51
22.50
9.81
0.28
1.83
5.72
0.13
0.17
4.47
3.64
2.21
100.00
37489
31965
0.173
5524
42.69
306
156
-1
31
3
-12
0
-33
2
-53
4.09
2.48
.0.01
0.42
0.04
.0.15
0.00
.0.44
0.03
.0.70
5
6
7
a
9
10
11
12
13
14
15
total
Excluding
MB&CHEM
2. Sta Sector idespndat Aooxm*ing
Units,40 bunches
1
2
3
4
S
6
7
I
9
10
2849
1333
61
147
79
120
0
150
67
1067
2543
1147
62
116
76
132
0
183
65
1120
0.120
0.162
-0.017
0.270
0.043
4.087
639.000
4.110
0.031
.0.047
(-4""
41
42 How Fast Has Ch*ne ?sdauy Groins?
TABLE16: DATAON"ENERGY
SAVINGS,.1980-198S(continualioa)
2. Stae SectorIdependent AccountingUnits, 40 banches
Energy Use in 1985
10,000Tonb
Energy Savings
Sd. Coal
100001
porcmi
branch
1980
Relations
A
Actu
B
*Saving
(A-B)/B
11
12
13
14
1S
16
17
i8
19
20
21
2
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
TOTAL
546
64
16
1298
14
50
111
12
832
43
17
13
10261
1957
366
8136
475
875
232
69
3980
7450
852
187
2017
656
336
259
62
11
47070
447
68
5
1234
13
48
132
10
746
36
13
9
9127
1613
330
6211
322
481
195
59
3594
6397
754
154
1343
435
224
99
43
7
39593
0.222
-0.054
2.240
0.052
0.073
0.042
-0.157
0.238
0.115
0.190
0.277
0.424
0.124
0.213
0.109
0.310
0.474
0.819
0.192
0.168
0.107
0.165
0.131
0.214
0.502
0.508
0.498
1.619
0.441
0.509
0.189
99
-4
11
64
1
2
-21
2
86
7
4
4
1134
344
36
1925
153
394
37
10
386
1053
98
33
674
221
112
160
19
4
7477
1.33
40.05
0.15
0.86
0.01
0.03
40.28
0.03
1.15
0.09
0.05
0.05
15.17
4.60
0.48
25.74
2.04
5.27
0.50
0.13
5.16
14.08
1.32
0.44
9.02
2.95
1.49
2.14
0.25
0.05
100.00
34642
30508
0.135
4134
55.3
of total
SUM Less
MB&Chem
HowFan Has Chnes Induoy Grown? 43
REFERENCES
an 1988. Beijing, 1989.
Agriculture 1988. Zhongguo n
Beijing 1988. Beiiing shehui iingii tongiinianiian I98.
ChinaDai.
Beijing, 1988.
Beijing.
China Price. Zhongguowujia (monthly).
Energy 1986. Zhongguo nengyUantongj n
n. 18.
Beijing.
Energy 1989. Zhongguo lengyUantongii nia&iian1989. Beijing, 1990
Field, Robert M. (1986). 'China: The Changing Structureof Industry," in U.S. Congress, Joint
EconomicCommittee,China's EconomyLooks Toward the YXr 2000. WashingtonD.C., vol.
1, pp. 505-547.
Field, Robert M. (1988). 'Trends in the Value of Agricultural Output, 1978-86,n Qhi
Ouanerly116, pp. 556-591.
Heilongjiang1988. Heilongiiangiingji togii nianjian 1988
IndustrialCensus Materials. Zhonghua renmin gonhegug 12853, guanbu gongye giye. Beijing, 1988.
pucha ziliao; vol.
Industry 1949-84. Zhongguo gonrgyeiingji tongji ziliao 1949-198. Beijing, 1985.
Industry 1988. I2
Zhongguo o
. 'i tongii nianiia. Beijing, 1988.
Industry 1989. 1989 Zhongguo gongye jingii tongii nianiian. Beijing, 1989.
Ishihara, Kyoichi (1989). "China's Multiple Price System," TF0
(1989): 2-9.
China Newslet
No. 80
Jefferson, Gary H., Thomas G. Rawsld, and Yuxin Zheng. 'Growth, Efficiency, and
l=.
Convergencein ChineseIndustry," forthcomingin EcgnoMicDevelg.ment d Clturl
Liaoning 1988. Lianningjing-i tongii nianjian 1988.
Price Theory. Jiage lilun yu shijian (bi-monthly)
44 How FM MM Chi"" Iary
or
0?
SSB(1988). StateStatisticalBureau. "Gongyezengzhangsuduzhongde 'shuifen' youduoda
[HowMuchUpwardBiasDoesthe Rateof IndustrialCrowthContain?]. November9, 1988.
Shanghai 1988. Shanghai ton-jl
-
18.
Tianjin 1988. Tia&jintongji nia&jign1988
TJNJ 1988. Zhon.uo toneii nianlian 1988. Beijing, 1988
TVP 1978-85. Xizhenile
xiangzhenqiyeju,1986
tongji zilian (1978-1985S.
Beijing: Nongmuyuyebu
TVP 1987. Ouanguo xiangzhengiye tongji zhaiyao 1987.
xiangzhenqiyeju,1986
Beijing: Nongmuyuyebu
TVP 1988. Quanguo xiangzhenaiyetongii
Xu et al (1989). Xu Yizuo, Huang Yongda, Zhang Ling (?), 'Brief Analysis of Cost Trends
in ElectricPower," Zhonng.guo
MbLj 1 (1989):39-45.
World Bank 1985-A3. China! 'Me Energy Setor
DevelopmentTssuesandOptions..
Annex 3 to report China! Lng:=
WorldHerald1988. "Jinnianwoguogongyezengzhangtongjijin(?)you'shuifen'"[UpwardBias
in Statisticsof China's IndustrialGrowthfor RecentYears]. Shjie jinji
o 11-14-1988.
Policy ResearchWorking Paper Series
TtlI
Contact
for paper
Author
Date
JohnBaffes
AnwarShah
September
1993
. Jones
37699
WPS1179 Howthe MarketTransition
Affected BartlomblKaminski
ExportPerformance
Inthe Central
European
Economies
September
1993
P. Kokila
33716
WPSI180 TheFinancing
andTaxationof U.S.
Dirct Investment
Abroad
HarryHukinga
September
1993
R. Vo
31047
WPS1181Reforming
HealthCare:A Casefor
Stay-WellHealthInsurance
ZeljkoBogetic
DennisHoffley
September
1993
F. Smith
36072
WPSI182 Corporate
Governance
in Central
andEasternEurope:Lessonsfrom
AdvancedMarketEconomies
CherylW. Gray
RebeccaJ. Hanson
September
1993
M. Berg
31450
WPS1183 WhoWouldVotefor Inflationin
Brazil?An Integrated
Framework
Approach
to InflationandIncome
Distribution
CheikhKane
JacquesMorisett
September
1993
T. Holbestelle
30968
WPS1184 ProvidingSocialBenefitsin Russia: SimonCommander
Redefining
the Rolesof Firmsand
RichardJackman
andGovernment
September
1993
0. delCid
35195
WPS1185 Reforming
Hungarian
Agricultural
TradePolicy:A Quantitative
Evaluation
MorrisE. Morkre
DavidG.Tarr
September
1993
N. Artis
37947
WPS1186 RecentEstimatesof CapitalFlight
StijnClaessens
DavidNaud6
September
1993
R. Vo
31047
WPS1187 HowShouldSovereign
Debtors
Restructure
TheirDebts?Fixed
InterestRates,FlexibleInterest
Rates,or Inflation-indexed
AndrewWarner
September
1993
J. Queen
33740
WPS1188 Developmentalism,
Socialism,
and MarioMarcel
FreeMarketReform:ThreeDecades Andr6sSolimano
of IncomeDistribution
in Chile
September
1993
S. Florez
39075
WPS1189CanCommunist
Economies
Transform
Incrementally?
China's
Experience
September
1993
PRDTM
37471
September
1993
T. Ishibe
37665
WPS1I'8 Productivity
of PublicSpending,
SectoralAllocatk%n
Choices,and
Economic
Growth
AlanGelb
GaryJefferson
lnderjitSingh
WPS1190 TheGovemment's
Rolein Japanese YoonJo Cho
andKoreanCreditMarkets:
A New Thomas
Hellmann
InstitutionalEconomics
Perspective
Policy Research Working Paper Series
Tili
Contact
for paper
Author
Date
GeoffreyJ. Bannister
September
1993
A. Daruwala
33713
WPS1192 Effectsof TaxRuformon Argentina'sJacquesMorisset
Revenues
Alejandrokzquierdo
September
1993
G. Cater
30603
WPS1193 TheArmenian
LaborMarketin
Transition:IssuesandOptions
MilanVodophvec
WayneVroman
September
1993
S. Florez
39075
WPS1194 HowFastHasChineseIndustry
Grown?
TomRawski
SeptemLer
1993
E. Khlne
37471
WPS1195TheEnterprise
Sectorand
MarkSehaffer
September
1993
WPS1191Rent-Sharing
in the Multi-Fibre
Arrangement:
TheCaseof Mexico
Emergenceof the PolishFiscal
E. Khine
37471
Crisis,1990-91
WPS1196 Corporate
TaxStructure
and
Production
JeffreyBernstein
AnwarShah
September
1993
C. Jones
37699
WPS1
197 Determinants
of inflationamong
BrunoBoccarn
September
1993
Shantayanan
Devarajan
C.Jones
37699
FrancZoneCountries
in Africa