metadata: authors: 0: author: Rawski, Tom
count: China
docna: 0: docna: How fast has Chinese industry grown?
docty: Policy Research Working Paper
subtopic: Mining & Extractive Industry (Non-Energy),Energy Policies & Economics,Inflation,Energy Demand,Energy and Environment,Energy and Mining
teratopic: Environment
abstracts: cdata!: Data for recent years indicate an
            acceleration of Chinese industrial growth, from the annual
            rates of about 10 percent recorded in the quarter century
            before economic reform to figures approaching 15 percent in
            the mid- and late 1980s. Evaluating the statistics
            underlying these reports requires an appraisal of how
            economic reform has affected the ability of China's
            statistical system to measure economic performance.
            Erroneous information about the rate and pattern of
            industrial growth could distort measures of productivity
            change considered to be central indicators of the
            effectiveness of Chinese industrial reform. The author
            describes the statistical materials and procedures used to
            provide information on the growth of industrial output. He
            investigates sources of bias in the official statistics to
            indicate, whenever possible, how these biases affected
            reported output totals, and to appraise the impact of
            adjustments to reported output growth on measures of
            industrial productivity. The specific consequences of
            decentralized decisionmaking, growing price flexibility,
            inflation, dual pricing systems, the emergence of
            enterprises with few or no ties to the system of state
            planning, and other emerging features of the industrial
            system may be unique to China but the broader issues raised
            are relevant in many countries. The author finds
            considerable evidence of an upward bias in measures of
            China's real industrial output in the past decade. The
            issue is not whether such bias exists but whether its
            presence substantially alters our perception of the rate and
            pattern of Chinese industrial growth. To clarify this issue
            requires investigating the extent of possible upward bias.
            This in turn calls for an analysis of possible links between
            upward bias - which is itself difficult to observe - and
            other economic patterns that may be more readily measurable.
geo_reg_key: 517198,119225,517191
repnme: repnme: How fast has Chinese industry grown?
display_title: How fast has Chinese industry grown
listing_relative_url: /research/1993/09/698916/fast-chinese-industry-grown
topicv3: Energy and Extractives m1326595 507,Inflation m1326709 0870F4727ACED1CF8525815C00471347,Power and Electricity Sector m1327094 515,Mining Sector m1327113 554,Iron m1503514 2931
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Environment
origu: Policy Research Department
no_of_pages: 52
model_extractions: # WPS 1194

This paper- aproduct of theTransition and Macro-Adjustmnent Division, Policy Research Deparmnenitis parn of the division's research initiative, Indusurial Reforms and Productivity in Clinese Enterprises. The study was funded by the Bank's Research Support BudgeL under research project "Reforms and Productivity in Chinese Enterprises" (RPO 675-M8). Copies of this paper are available free from the World Bank, 1818 H Street NW, Washington. DC 20433. Please contact Emily Khine, room NI 1-065. extension _37471_ (September 1993,44 pages).

Data for recent years indicate an acceleration of Chinese industtirl growth, from the annual rates of about 10 percent recorded in the quarter century before economic reform to figures approaching 15 percent in the mid- and late 1980s.

Evaluating the statistics underlying these reports requires an appraisal of how economic reform has affected the ability of China's stztistical system to measure economic performiance. Erroneous informnation about the rate and pattern of industrial growth could distort measures of productivity change considered to be central indicators of the effectiveness of Chinese industrial reformn.

Rawski describes the statistical materials and procedures used to provide information on the growth of industrial output. He investigates sources of bias in the official statistics to indicate, whenever possible, how these biases affected reported output totals, and to appraise the impact of adjustments to reported output growth on measures of industrial productivity.

The specific consequences of decentralized decision~making, growing price flexibility, inflation, dual pricing systems, the emergence of enterprises with few or no ties to the system of state planning, and other emerging features of the industrial system may be unique to China but the broader issues raised are relevant in many countiies.

Rawski finds considerabl **e** vidence of an upward bias In measures of China's real industrial output in the past decade. The issue is not whether such bias exists but whether its presnce substantially alters our perception of the rate and pattern of Chinese industrial growth.

To clajify this issue requires investigating the extent of possible upward bias. This in tumn calls for an analysis of possible links between upward bias - which is itself difficul **t** o observe - and other economic patterns that may be more readily measurable.

**Pmoducsd by dw Pobicy R.earsch Disminazia** **_Cmtar_**
# How Fast **Has Chinese Industry** Grown?

Tom Rawakl University of Pittsburgh
# **CONTES**

||ACKNWLEDGEMENT<br>.......................................|i|
|---|---|---|
|I.|INTRODUCTION<br>..........................................|1|
|II.|CONCEPTS AND CATEGORIES FOR CHNESE INDUSTRIAL STATISTICS .<br>.........|1|
|III.|CHINESE INDUSTRIAL PEILORMANCE SUMM-ARY OF RECENT OFFICIAL DATA.....|3|
|IV.|SYMPTOMS OF UPWAR BIAS IN CHINESE INDUSTRIAL STATISTICS ...<br>........|6|
||A. MISMATCH BETWEEN OUTPUT AND VALUE DATA ......<br>..................|6|
||B. Do RURAL INDUSTRIES ADHERE TO STANDARD AccOUNTING REGULATIONS ..|.<br>7|
||C.HAS THE RATE OF DOUBLE COUNTING INCREASED? ................|10|
||D. Do LOCAL AUTHORITIES FALSIFY INDUSTRIAL OUTPUT DATA? ...<br>......|12|
||E. Do INDUSTRIAL OUTPUT DATA ACCURATELY REFLECT RECENT INFLATION<br>EXPERIENCE ........|12|
||F. ARE REPORTED GAiNS IN ENERGY PRODUCTIVITY UNREALISTICALLY LARGE?|15|
|V.|CONCL.USIONS<br>**.............**|20|
||REFERENCES<br>..|43|
# TABLES

|TABLE : ALL INDUSTRY.<br>............................................<br>21|
|---|
|TABLE 2:BREAKDoWN STRUCrURE OF GVIO<sup>AT 1989 PRICEs.....</sup><br>.......... 23|
|TABLE3: BRANCH STRUCrURE oFGVIO<sup>AT 1989 PRIcES.....</sup><br>..............<br>24|
|TABLE 4: NET_OurPuT_ATCURRErrPRICES<sup>.......</sup><br>......................<br>26|
|TABLE S: CHMCALINDUSTRY<br>........................................<br>27|
|TABLu 6: ALTERNATIVE<br>DATA TO MEASURE INrLATION.....<br>...............<br>28|
|TABLE 7: PRICE INDmxs EXTRACTED<br>FROM INDUSTRTAL<br>OUTPTr VALuz DATA. 29|
|TABLE 8: ENERcY PRODUCTnvTY<br>IN CHNESE INDUSTRY, OFFICIAL DATA,<br>19781987 .......................................<br>30|
|TABLE 9: OFFICL.L ENERGY DATA FOR CHNESE<sup>INDUSTRY BY BRANCH,</sup><br>1980-'98S..................................<br>31|
|TABLE10: GVIODATAFOR1SBRANCHES<sup>...............................</sup><br>32|
|TABLE 11: REvISED CALCULATION:<sup>ANNUAL PERCENT INCREASE</sup><br>IN<br>ENERGY PRODUCTIVrrY BASED ON PHYSICAL ENROY<sup>CONSUMPTION</sup><br>AND<br>PUBLISHD GVIO DATA ............................<br>34|
|TABLE12:ENERGY DATA FOR STATE SECTOR<sup>INDEPENDENT</sup><br>UNrrS,<br>40BRANCHES, 1980AD1985..<br>35|
|TABLE 13: ROUGH CONVERSION<br>OF SOE ENERGY DATA TO 15 BRANCH<sup>FoRmAT . 37</sup>|
|TABLE14:TRIAL CALCULATION<br>OF ENEROY CONSumpONAND<br>PRODUCTIVrY FOR COLLECTIVE<br>INDUSTRY<br>.<br>.<br>38|
|TABLE 15: PERCENT CHANGE IN INDUSTRIAL<br>ENERGY PRoDucTIVrrY FOR 15<br>BRANCHES, 1980-1985 ...<br>..........<br>..................<br>40|
|TABLE16:DATA ON "ENERGYSAvwNGS"<br>(1980-1985).<br>...<br>..41|
# ACKNOWLEDGEMENT

The research projects on "Enterprise Behavior and Economic Reforms: A Comparative Study in Central and Eastern Europe", and "Industrial Reforms and Productivity in Chinese Enterprises are **research** initiatives of the Transition and Macro Adjustment Division (PRDTM) of the World Bank's Policy Research Department and managed by I.J. Singh, Lead Economist.

These projects are being undertaken **in** collaboration with the following institutions: The London Business School (LBS); Reforme et Ouvertures des Systemes Economiques (post) Socialistes (ROSES) at the University of Paris; Centro de Estudos Aplicados da Universidade Catolica Portuguesa (UCP) in Lisbon; The Czech Management Center (CMC) at Cellkovice, Czech Republic; The Research Institute of Industrial Economics of the Janus Pannonius University, Pecs (RIE) in Budapest, Hungary; and **the** Department of Economics at the University of LddI, in Poland.

The research projects are supported with funds generously provided by: The World **Bank** Research Committee; The lapanese Grant Facility; The Portuguese Ministry of Industry and Energy; The Ministry of Research and Space; The Ministry of<sup>T</sup> 'dustry and Foreign Trade, **and** General Office of Planning in France; and the United States Agency for International Development.

The Research Paper Series disseminates preliminary findings of work in progress and **promotes** the exchange of ideas among researchers and others interested in the area. The papers contain the views, conclusions, and interpretations of the attho:(s) and should not be attributed to the World Bank, its Board of Directors, its management or any of its member countries, or the sponsoring institutions or their affliated ag ncies. Due to the informality of this series and to make the publication available with the least possible delay, the papers have not been fully edited, and the World **Bank accepts no responsibility** for errors.

The authors welcome any comments and suggestions. Request for permission to quote their contents should be addressed directly to the author(s). For additional copies, please contact the Transition and Macro Adjustment Division, room N-1 1065, World Bank, 1818 H Street, N.W., Wasbington, D.C. 20043, telephone (202) 473-1442, fax (202) 676-0083 or 676-0439.

The series is also possible thanks to the contributions of Donna Schaller, Vesna Petrovic, Cecilia Guido-Spano and the leadership of Alan Gelb.

**-1i-**
# I. INMODUCnON

Data for recent years indicate an acceleration of Chinese<sup>iwdustrial growth from the annual</sup> rates of approximately ten percent recorded during the quarter-century<sup>prior to the introductiun</sup> of economic reform policies to figures approaching 15 percent<sup>annual growth during the mid-</sup> and late 1980s. Evaluation of the statistical materials<sup>underlying these reports requires an</sup> appraisal of how economic reform has affected the capacity<sup>of China's statistical system to</sup> measure economic performance. Since industrial output dominates<sup>China's national income</sup> totals, possible inaccuracies in statistics of industrial growth<sup>have the potential to affect overall</sup> measures of the size and structure of China's economy u well<sup>as perceptions about the size,</sup> structure and growth rate of the industial sector itself. Of particular<sup>concern is the possibility</sup> that erroneous information about the rate and pattern of<sup>industrial growth will distort measures</sup> of productivity change, that we regard as central indicators<sup>of the effectiveness of industrial</sup> reform efforts in China's economy.

The objective of this paper is to describe the statistical<sup>materials and procedures that stand</sup> behind published information on the growth of industrial output,<sup>to investigate sources of bias</sup> in the official statistics, to indicate, whenever possible, the<sup>quantitative impact of these biases</sup> on repcrted output totals, and to appraise the impact<sup>of adjustments to reported output growth</sup> on measures of industral productivity..

The problems explored in this paper arise primarily<sup>from thea interaction between the</sup> growing complexity of industrial organization and market<sup>structure and a statistical network</sup> designed to collect information ior the pre-reform system<sup>of industrial olanning and</sup> administration. Although the specific consequences of decentalized<sup>decision-making, growing</sup> price flexibility, inflation, dual pricing systems, emergence<sup>of enterprises with few or no ties</sup> to the system of state planning, and other emergent features<sup>of the industrial system may be</sup> unique to China, the broader issues raised by these developments<sup>would seem applicable to other</sup> socialist economies at various stages of maiket-oriented reform<sup>programs.</sup>

# **II.** CONCErr **A CATEORE FOR CNSE INDUSRIAL STsTIMMCS**

Manipulation and interpretation of data portaining to<sup>Chinese industry (which includes</sup> mining, manufacturing and utilities) requires an appreciation<sup>of important concepts and data</sup> categories used by Chinese statisticians. State enterprises (puanmin<sup>suoyouzhif are those in</sup> which the legal ownership of post-tax profits resides<sup>in the hands of some level of the</sup> government. Nearly all of China's largest enterprises<sup>belong to this category, which accounted</sup> for 83.2 percent cif indL -ial output in 1978 and 59.7 percent<sup>in 1987 [Industry 1949-84, p. 98</sup> ;TJNJ 1988, p. 311]. L.ollecti.-e enterprises (iiti suoyouzhi<sup>are those in which this residuai</sup> ownership right resides with the ente-"ise itself. Residual<sup>profit of private or individual (gc)</sup> enterprise accrues to thcz owners.

-1-
# _2_ **_Now Fae_** _Mm_ **_Ch*F.e hu*oy row?_**

The concept of 'independent accounting units, (dulihesuan.giye) refers to industrial enterprises that function as separate accounting iltities. Statistics for industrial output or input (fixed assets, worldng capital, labor) often refer exclusively to independent accounting units, which contributed _85.8_ percent of national industrial output (including 96.1 percent in the state and 86.4 percent in the collective sector) to the 1988 gross value total [Jefferson, Rawski, and Zheng, Table 1; these data exclude village-level industry]. Industrial activity may occur within non-industrial units, as when transport companies repair their own equipment or when universities or other non-industrial entitia operaie factories whose accounts are subsumed within their owri. The output value of these 'non-independent accounting units' (feiduliheau giy is incorporated into output totals that include all industrial production (rather than only tha' of independent accounting units).

The coverage of industrial production was expanded in 1984 to include industrial enterprises managed at and below the village level (formerly descr.bed as nanaged by the production brigades of rural communes). These enterprises were previously claisified as part of agricultural rather than industrial production [Field 1988, pp. 584-585]. Recent: vubl cations have begun to retroactively incorporate this category into the industrial totals for previous years, leading to apparent inconsistency with previously published statistics (e.g. newly published labor figures for collective industry inclusive of "village-managed' enterprises are miuch larger than identically-labell **e** d mployment totals published in earlier sources not because of any change izi underlying statistics, but merely because the "village-managed" enterprises were formerly included in the farm -ector).

Industrial production statistics are valued in terms of 'current' or "constant' prices. The current price value of industrial output indicates the value of each year's output according to the market prices of that year. For th. vast majority of products that are sold in the year of productioil, output value at current prices is identical with sales revenue. From this perspective, the existence of multiple prices for individual products poses no conceptual or practical difficulty for Chinese accountants and statisticians.

Following Soviet example, China's wconomic statistics have long been cs'culated according to "constant" as well as current prices. Constant prices of 1952 were used for the period _1952-57;_ 1957 prices were in force from 1957-71; national statistics for the years 1971-81 are based on 1970 prices; and a 1980 price base has been in force since 1981. Calculations based on 'constant' or fixed prices are made by multiplying quantities of output by the relevant "constant p.ices," the latter being supplied to enterprise accountants by planning and administrau've agencies of the Chinese govemment.

It is important to note that, as economic reform leads enterprise managers to focus more closely on financial results based exclusively on current prices, the calculat<on of output value at "constant" prices becomes increasingly peripheral to enterprise objectives'. In the absence of

1. **One official** of **Chia's State Stisca Bureau commeAed ht thi hnge enhace te veracity** of **rpotd** **_data._**
## _Flow Fast_ **_HOa_** _Chinese Indwry Gro*"? 3_

price indexes for industrial products, output value calculated at "constantu prices 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 different sets of fixed prices. If a calculation crosses more than one such gap, e.g. when comparing the levels of industrial output in 1952 and 1987, a series of chain-linked calculations is used (see Field, JEC 1986, p. 509] and the resulting time series is described as being based on "comparable* (kmi) rather than "constant' (bbian) prices.

# **III CHN S INDusiAL** PEmFQFMANCE-SUMMARz OF RECENr OmaAL DATA

Official statistics of China's industrial performance during 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 comprehensive industrial aggregate (designated 'Industry+') that includes enterprises managed at and below the village level. Output totals for village-level industry are shown separately; subtraction of 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 indicate a continuation of 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 constant prices (labelled GVIO), the ate of output growth clusters around the 10 percent annual level observed over the long term in China. If village industry is excluded, the average annual growth rate of OVIO for 1978-87 is 10.4 percent. Even though village industry reported annual growth averaging 24.1 percent in real terms during 1978-R7, the village component is so small that adding its inclusion in the total produces only 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 considerably exaggerate the growth of real output in the village segment of industry.

The figures reported in Table 1 indicate a distinct acceleration of industrial growth during the mid-1980s, with reported real output growth approa.hing the 15 percent mark in 1983/84

1. One official of China's **Sate Statitca** Bumau **oomniud tht Shim** chnp **enhanc Uth** vemcity of **repored** daa.
# **_4_** _How_ **_Fan Has ChMe Indrj&y ro*wi?_**

and 1986/87 and surpassing 15 percent<sup>in 1984/85 even without the inclusion of village-level</sup> industries.

Data showing the level and growth of industrial<sup>output at both current and constant prices</sup> can also provide information about changes<sup>in the pdice level for industrial goods. This is</sup> particularly important because Chinese<sup>sources give no systematic information on price trends</sup> fer industrial goods until 1984/85; branch<sup>indexes for prices of industrial goods exist only ftwm</sup> 1985/86 [Chirna Price 2 (1989): 59]. Implicit<sup>price indexets fer industrial output appear in Panel</sup> A of Table 1. These data reflect the gradual<sup>emergence of inflationary pressures beginning in</sup> the mid 1980s following yeaws of<sup>near-stability in industrial prices. Whether these data</sup> acciiat'ly reflect trends in prices paid<sup>for industrial goods and/or received by industrial</sup> produce." will be discussed below.

Table 2 indicates the brealkdown of output into several ownership ca.egories:<sup>state-owned,</sup> collective, private, and other. These<sup>figures show that output from the c )llective sector,</sup> particularly its sub-categories of township<sup>and vilage enterprises (jointly described by the tem</sup> xiangzhen Qa , has grown much faster<sup>than producton in state firms, leading to a rapid decline</sup> in the formerly dominant share of state firms in total<sup>output value.</sup> The output totals in Table 2 are divided into<sup>two major sub-categories, state and coUective.</sup> Additional detail is given for two segments<sup>of collective industry, firms managw at the</sup> township (xi) and viLage _(M)_ levels within the coUective<sup>sector. Since coUectiv</sup><sup>**e**nterprises</sup> also operate in urban areas, these segments<sup>do not exhaus</sup><sup>**t**he entire output of China's collective</sup> industries.

Table 2 also displays output data for<sup>a separate category, xian3gzbhCnqy,</sup> which is often translIzted as *township and village enterprises'<sup>(abbreviated lVE), even though the term's</sup> literal meaning is 'township and market-town<sup>enterprises.' These data are of interest for two</sup> reasons: first, reported output has grown with<sup>extreme rapidity in recent years, so that the total</sup> amounts in 1987 to nearly one-third of national<sup>gross output. Furthermore, the scope of the</sup> TVE data remairs uncertain for the period<sup>beginning in 1984. Prior to 1984, the TVE output</sup> data are almost precisely equal to the sum<sup>of output value at fixed prices for township and</sup> village enterprises. Beginning in .984.<sup>however, we find a large and growing gap between</sup> output of township and village enterprises and<sup>the much higher TVE total. In addition, the price</sup> basis of the TVE data reproduced in Table<sup>2 is not specified. We know that the data for</sup> 1978-83 represent the sum of output from<sup>township and village enterprise at constant prices.</sup> The enormnous growth of the TVE category starting in 1983/84<sup>suggests that the. figures shown</sup> in Column E of Table 2 may represent outpu.<sup>valued at current rather than constant prices.</sup> Table 3 presents information on the branch<sup>structure of gross industrial output value at 1980</sup> prices. These data, which exclude the minor<sup>category of non-independent</sup> accounting units and also exclude village enterprise, indicate<sup>very little change in the importance of major branches</sup> of Chinese industry during the past decade.<sup>This is confirmed by the rank correlation coefficient</sup> linking the size structure of industrial branches<sup>for combined state and collective industry (Panel</sup>
**_How FA_** _M Chha_ **_induy Orow?_** _5_

C of Table 2) in 1978 and 1987.2 The stabi!tv of br-rch stricture<sup>in both the state and</sup> collective segments of industry is a significant factor in analyzing<sup>trends in reported energy</sup> productivity. A stable branch structure eliminates the ossibility<sup>of raising energy productivity</sup> by raising the share of industil output produced in branches with 'ow energy-intensity.

The figures in Tables 1-3 arc based on the 'gross value of<sup>industrial output," which</sup> represents the combined total of enterprise output val6s inclusive of<sup>materal costs. Table 4</sup> contains information on the growth of net industrial output, which is<sup>calcu1bted by subtracting</sup> the vaiue of material inpuu (minerals, semi-fabricates. energy etc.) from gross output. The net value figures are usually rendered only in current prices; when<sup>nret output is presented in</sup> constant price terms, the figures are apparently obtained by multiplying<sup>net output in current</sup> prices by the ratio of gross output totals Li constant and current<sup>prices, which is equivalen</sup><sup>**t**o</sup> "single deflation rather than tU conceptually preferable "double<sup>deflation" used id</sup> contemporary industrial econormies, in which separate price indexes are<sup>used to remove the</sup> impact of price change from gross output and from the intermediate<sup>goods purchased hy</sup> industrial enterprises.

The general picture emerging from shese data<sup>-</sup> rapid growth, acceleration<sup>after 1983, with</sup> differentially rapid cxpansion of the collective sector<sup>-</sup> parallels<sup>the results reported in Tble 1.</sup> The ratio of net to gross output is nearly identical in the state and collective<sup>sectors. Following</sup> decades of near-constancv in this ratio rsee Industry 1949-84, p. 41J, we now see a gradual<sup>but</sup> steady decline in the net output ratio for both state and collective industry.<sup>There are several</sup> possible reasons for this change:

- changing product mix within individual brmnches of industry (note<sup>that stability of branch</sup> structure precludes change in this area as a source of decline in net<sup>outpmt ratios).</sup>

- changing technology and efficiency in some branches relative<sup>to others.</sup>

- differential inflation of raw matcrials prices relative to prices of<sup>finished products.</sup>

- changes in the rate of double counting arising fr..a response to<sup>new marketing opportunities,</sup> enlarged ialization and inter-enterprise division of labor, expansion<sup>of subcontracting,</sup> and growth of joint production and transprovincial cooperation

Of particular relevance here is the possibility that reform-induced<sup>increases in</sup> inter-enterprise specialization may have raised the, owth rate of gross output<sup>value above the</sup> growth rate of real industrial product. This outcome is not certain: we lack<sup>systematic data on</sup> the ratio of interentcrprise purchases to total out(ut (both<sup>level and time-path of this ratio) for</sup>

> 2. **Braches** 13 **nd** 14, **nd also branch 11 ad** 12 **au combined** for **te** oalwlaton **becaus they amw not** diMpiobshd **_in_ th 1978 fiSue;** with 13 **bmancr, he rmak ording** of 7 **(including**<sup>**the six**</sup><sup>**_lu_**</sup> brarchu) **.identia in** 1978 **and 1957. The am** of **squa.** of **differen0e, nak orde nga**<sup>**hrd th tmainhng**6</sup><sup>**branchs**136.</sup>
### _6 Now_ **_Fwt J.a.x_** _Chwi-e_ **_lndvWy Growns?_**

various types of erterprises. In addition, some<sup>units, isicluding the large and widely publicized</sup> Capital Iron and Steel Corporation, have taken advantage<sup>of reform policies to increase rather</sup> than reduce the degree of vertical integration, which<sup>has the opposite effect of causing gross</sup> value to lag behind the growth of real output.

# **_IV._ SYMPTOMS** OF **_UJPWAp1_** BLAS **_iN_ CmNS INDUSTRIAL** STATImCS

Careful inspection of Chinese statistical publications<sup>raises the possibility that recent output</sup> totals based on wconstant prices* may exaggerate<sup>real outpit growth in the industriai sector.</sup> Indications of upward bias in the constant-price<sup>industrial output totals for the past decade appear</sup> from the following types of materials:

- apparunt mismatch between growth of physical<sup>output and output value in certain branches of</sup> industry

- indicaLions that township and village enterprise<sup>may confuse current and constant vices</sup>

- possible increases in the rate of double counting,<sup>which would have the effect of artificially</sup> increasing the reported growth of gross<sup>output</sup>

- indications that local govemments may falsify<sup>industrial output statistics to gain administrative</sup> benefits attached to achievement of lai ? output<sup>totals.</sup>

- evidence that industrial output data do not adequately<sup>reflect price increases that have become</sup> pervasive in recent years.

- indications that reported gains in energy productivity<sup>are unrealistically large, especially in the</sup> fast-growing machinery branch.

## A. **Mlsmatch between Output and Value Data**

In some cases, the reported growth of real output value<sup>appears to outrun the expansion of</sup> physical output for major products. The most<sup>notable example of this occurs in the chemical</sup> industry, for which relevant data appear in Table<sup>5. These data show that the arithmetic average,</sup> of annual physical output growth for nine<sup>major commodities lags behind the reported growth</sup> of output value at constant prices for<sup>every year beginning with 1979/80. The positive</sup> difference between reported growth of real<sup>output value and production volume for major</sup> commodities ranges from 2.56 percentage points<sup>in 1986/87 to 12.66 percentage points in</sup> 1984/85.

It is, of course, entirely possible for real<sup>output to outgrow physical production of major</sup> commodities in a large and complex industry<sup>that turns out a wide range of products as well as</sup>
**_How Fau Has ChintE Indistry Gro"?_** _7_

a variety of items within broad categories such as 'plastics." Furthermore, the calculations reported in Table 5 give identical weight to each of the nine products. On the other hand, the size of some of the annual differentials is 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 questions about 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 presumably accountants and statisticians as well) pay growing attention to current cash flows. Despite the complexity arising from sales of similar products at multiple prices, output valued at current prices is closely related to enterpnise sales revenue, and therefore appears to pose little conceptual or practical difficulty even for the inexperienced and unsophisticated accountants available to small rural enterprises.

To calculate gross output at fixed prices requires information about the fixed (1980) price o each item produced. Industrial ministries publish large compendia containing relevant price lists. Administrative units at all levels a,e responsible for passing on appropriate price information to enterprises under their jurisdiction. While this system has functioned smoothly for many years among large-scale enterprises in the staLe sector, the recent explosive growth of collective enterprise, especially in rural areas, raises the possibility that enterprises, their administrative superiors in township or county industrial bureaus, local statistical personnel, or all three group may have failed to implement the system of calculation in constant prices that is of crucial importance for industrial output statistics even though it is of little or no interest to enterprise personnel and perhaps to local government officials 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 subordinate in the bureaucratic structure. Thus national agencies receive material prepared by provincial agencies, which in turn rely on data compiled by municipal or county authorities, who base their reports on data from local enterprises. This means that statisticians at higher administrative levels cannot easily evaluate the quality of the raw data underlying the reports that arrive on their desks, particularly when, as in the case of rural industry, these reports come from literally thousands of widely dispersed units.

Under these conditions, it is entirely possible that data supposedly based on fixed 1990 prices could contain a substantial component based on (much higher) current prices. With inflation, substitution of current for constant prices imparts an upward bias to the resulting data. The view
# _8_ **_How_** _Fas:_ **_Has Chiae IndurJg_** _Grow,?_

that failure to implement accounting conventions artificially inflates reported<sup>output growth,</sup> especia.Uy in the TVE sector, is widely shared within the Chinese economics community.<sup>An</sup> experienced accountant now working with a TVE machinery producer<sup>insists that even in the</sup> capital, failure to adhere to statistical regulations is not uncommon in the<sup>TVE sector; in rual</sup> areas, neglect of these systems is said to be widespread (personal communication,<sup>May 1989].</sup> Officials of the State Statistical Bureau [SSB] agree that output data<sup>from TVE enterprises are</sup> problematic, that current prices are often used to calculate output values<sup>identified as based on</sup> fixed prices, and that the output totals tend toward bias in the upward<sup>direction (personal</sup> communication, May 1989; May 1990]. A position paper issued by<sup>the SSB in response to</sup> claims that its figures exaggerate the rate of industrial growth in recent years<sup>points specifically</sup> to rural enterprise as the chief source of what the SSB sees as a modest<sup>upward bias in its</sup> estimates of real industrial growth [SSB 1988; World Herald 1988].<sup>An extenal researcher</sup> reports that visits to Jiangsu enterprises in the xiangzenQive category<sup>do indicate extensive</sup> mixing of data in current and constant prices, with enterprise leaders<sup>finding it difficult to</sup> explain which data are based on which prices (personal communication,<sup>July 1989]. A paper</sup> prepared by personnel at China's State Statistics Bureau [SSB 1988] reports<sup>that industrial units</sup> at the township (xiang level and above are required to submit monthly<sup>reports of GVIO at</sup> constant prices. The small, dispersed and numerous village-level, jointly<sup>operated (at or below</sup> villane level) and private (gi) enterprises submit only annual figures, and<sup>these are in current</sup> rather than constant prices. Provincial and local statisticai bureaux then<sup>adjust these submissions</sup> on the basis of coefficients derived from sample surveys or surveys of<sup>key enterprises. The</sup> SSB's position paper asserts that these procedures remove most, if not all of<sup>the shuifei (literally</sup> "water content") or upward bias from the output data associated with village-level<sup>industry. The</sup> SSB also points out that figures for these units are not included<sup>in monthly reports of industrial</sup> output [See World Herald 1988 for a summary of debate on the "shuifen"issue].

Despite this explanation from the SSB, examination of available data confirms<sup>the impression</sup> that output data for TVE enterprises, especially figures said to be<sup>based on 1980 fixed prices,</sup> probably overstate the actual expansion of real output, especially<sup>during recent years of</sup> extremely rapid enterprise formation. Prior to 1985, compilations<sup>of TVE data carefully specify</sup> which data are based on 1980 prices; more recent publications conspicuously omit any mention of the price base for output data pertaining to 1985 and subsequent<sup>years r[VP, 1978-85; TVP</sup> 1987; TVP 1988; TJNJ 1988, p. 294. Note that Agriculture 1988<sup>gives TVE GVIO for 1987</sup> at 1980 prices (p. 314) using ;he same data that appear with no<sup>price attrbution in TVP 1988,</sup> p. 261.
_How_ **_Fan Hu Chia, Indtusy_** _Gro'?_ **_9_** Several specific examples can iUustrate what appears to be considerable inconsistency in these data: Data for Beijing industrial enterprises for (million yuan): 1986 1987 Index 1986-100

1. Gross output, 1980 prices (GVIO)

- a. Including village and sub-village units 34858.07 39512.33113.3

- b. Excluding village and sub-village units 32177.14 35723.28111.04

- c. Difference: GVIO for vWillage enterprise 2680.93 3789.05141.3

- 2. Village & sub-village output, current 2480.06 3382.27136.4 prices (CVIO)

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 definitely incorrect.

Shanghai industrial output figures for 1987 (million yuan) raise further questions:

||A<br>1980<br>prices|B|Ratio<br>B/A|
|---|---|---|---|
|1. Township enterprises|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," identified as based on 1980 prices, are much smaller than the figures marked "b," which appear initially without price attribution, but are also used to compile a total described as 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 mention of a price base].

Scattered data for several provinces imply improbable increases in labor productivity. GVIO for Tianjin's village enterprises reportedly increased by 81 percent between 1985 and 1987 even though employment rose 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, township enterprises reported real output growth of 15 percent during 1986/87 while employment fell by one percent (Heilongjiang 1988, p. 291].

The impression of widespread substitution of current for constant price output figures is confirmed by Robert M. Field, who finds that 'a large and growing number of provinces have not distinguished output [of village-level industry] in current and constant prices. . . . in 1985 the output of village and below-village industry 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 misleading results if changes in industrial organization alter the frequency with which materials, components, and services are exchanged among enterprises. Assuming no change in real output, a trend in the direction of vertical integration (e.g. merger of iron mines with steel plants) will cause measured output to decline (the sale of iron ore to the steel mill disappears from reported GVIO). A trend toward interenterprise division of 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 measures of industrial output growth during the 1980s. First, industrial reform has created new opportunities for inter-enterprise specialization and 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 (smaUl and complete) manufacturing establishments in order to limit their dependence on unreliable external suppliers. Economic reform has increased the availability and reliability of external suppliers for a wide variety of commodities and services. There are many reports of new sub-contracting an-angements, inter-provincial joint ventures and other institutional changes that point in the direction of an increase in the overall ratio of inter-enterprise transactions to real output within the industrial sector. [Note, however, the apparent counterexample of the Capital Iron and Steel Corporation, which has used new opportunities for independent decision-making to reduce its
_How_ **_Fast Ha Chsuu_** _Indwitry Grow? 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 specialization at 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 specialization simply 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-fabricates independent of any shift in product mix or branch structure of industry. Such a change would build an upward bias into the output totals reported in Table 1. Such a change would also systematically reduce 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 disintegration or 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 interenterprise purchase of energy, materials and semi-fabricates to gross output value in various subdivisions of the industrial sector. For example, the industry-wide average ratio of interenterprise purchases to gross output at current prices (CVIO) [call this ratio IEP/CVIO0, can be expressed as a weighted average of distinct IEP/CVIO ratios for large and small industry. Thus:

# [IEP/CVIO] = a[IEPl/CVI01] + (1-a)UEP2/CVI02]

where 1 and 2 indicate large and small-scale industry and a is the share of the former in national industrial output.

# I hypothesize that:

# (1) the ratio (IEP/CVIO] is considerably larger for large than for small firms

(2) the weight attached to large firms, a, has declined irn recent 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 should be possible to obtain some rough quantitative idea of possible bias in the output figures arising from changes in industrial organization.?

3. **Wdiliam** Byrd observes **that** the **foregoing discusion** overloolk the pouible **impat** of changes **_in_ the price** of **materils and intemediate** goods relative to **the price** of **final** producs; such changer might be **systeuailcaUy different** for **large and s1A1 finr.**
## _12_ **_How FM Ha Cbae ldutiy ww?_**

# D. Do **Local Authoritles Falsify Industril Output Data?**

Well-informed statistical personnel report the existence of incentives for exaggeration of industrial output growth by local govenments in some regions of China. In Jiangsu, for example, municipalities that surpass threshold levels of industrial output (e.g. 1 billion yuan) are granted special privileges in the form of exemption from certain types of regulation (e.g. direct access to provincial funds vs. application through county offices). Falsification, if extant, presumably **taces** the form of inflating gross rather than net output [note that the former can be easily inflated by anranging exchange of materials or semi-fabricates anong producers of similar commodities]. If so, falling ratios of net to gross output will be typical of entities with inflated gross output totals. Unfortunately, there are many other factors influencing this ratio, so that falsification might easily escape detection, especially if the amounts are small relative to local and national totals.

At the same time, other enterprises or localities may conceal some portion of their actual production in the hope of avoiding taxes.

# E. Industrial Output Data Accurately Reflect Recent Inflation Experience?

After decades of considerable price stability, China has experienced growing inflationary pressures during the 1980s. Since Chinese price index compilation has previously focused almost exclusively on consumer prices, the impact of recent inflation on industrial prices is not easily discerned. The only systematic effort to monitor trends in industrial prices appears to come from the State Price Bureau, which now surveys price conditions in several thousand industrial enterprises and uses the resulting data to compile indexes of ex-factory prices for industrial products as well as purchase prices for major raw materials, fuels, and power [personal communication, May 1989]. Summary figures for 1984/85 and more comprehensive results, including price indexes for 15 industrial branches and purchase price indexes for eight classes of materials appear in the Bureau's journal rChia Pnricc 2 (1989): pp. 59-60].

These figures confirm that industry has experienced the inflationary trend reported for urban consumer goods, Annual increases for ex-factory prices averaged 8.7 percent in 1984/85, 3.8 percent in 1985/86, 7.9 percent in 1986/87 and well over 10 percent during the first eight months of 1988 [China Price 2 (1989): 59]. Price increases for materials, fuel, and power were substantially larger in each year [ibid., 60]. The influence of commercial intermediaries (including government agencies), in the inflationary process is visible if we compare trends in ex-factory prices of mining products and raw materals" (these categories appear not to overlap) with trends in purchase prices for wall raw materials" (percent increases over the previous year):
||Ex-Factory<br>Mining<br>Products|**_HowFanHu Ouaw hmaaty_**<br>**_1r_**<br>Prices<br>Purchase Prices<br>Raw<br>All Raw Materials<br>Materials|
|---|---|---|
|1985|108.8|110.9<br>118.0|
|1986|100.6|107.5<br>109.5|
|1987|114.1|106.9<br>111.0|
|Aug.1988|108.8|117.8<br>123.9|

Source: China Price 2 (1989): 59-60.

Profitable intermediation, whether by state agencies or by legitimate or illegal private enterprise (sometimes involving persons with official connections) is an important componen of the "official speculation' (guandao) widely reported in the Chinese press. Beijing's large Yanshan Petrochemical Company reportedly "sold almost all their products to the State at official low prices" only to discover that 'most of their products' users paid much higher market prices" for the same materials [China Daily 6-3-1989, p. 1].

Although inflation of industrial prices seems to have acclerated in recent years, substantial price increases certainly occurred prior to 1984/85. Data in Table 6 show a rising trend for coal prices paid by electric power plants beginning as early as 1978/79. Data for the construction industry show a consistent pattern of rising building costs from the stat of annual time seIes data in 1978 [TJNJ 1988, p. 590]. Since these figures exclude land costs, it would appear that rising costs of construction mateials, which prompted complaints in the Chinese press during the late 1970s, also date back to this period. Interview data collected by foreign reserchers give a strong impression of rising machinery prices during the late 1970s and early 1980s [personal communication].

Information on prices paid by power plants for coal illustrates the possible inconsistency between information about inflation and the price changes implied by industrial output statistics. The electric power industry is dominated by large, stateowned enterprises. It seems reasonable to assume that thermal power plants obtain the bulk of their coal requirements through planned allocations at low official prices, and that they enjoy considerable protection from the "official profiteers' attacked in the Chinese press. This would imply that, relative to otber consumers of coal, power plants are somewhat insulatid from inflationary pressures, and that trends in their coal costs should _unmad_ the average rise in coal prices for the entire economy.

Data reproduced in Table 6 show that averagc coal costs in China's power industry havi risen steadily since 1978. The index of coal costs, which should represent an underestimate o the aveage rise in coal prices, shows an increase of 88.9 peracnt between 1978 and 1987. The implicit price indicator calculated from gross output at cunrent and constant prices for the coal industry, however, shows much smaller increases of 66.7 percent for the state sector and 48.9 percent for the (much smauller) collective mining sector. These data lead to the conclusion that the annual price changes implicit in statistics of gross output value at current (CVIO) and
# _14 How Fast_ **_Has_** _Chine_ **_Inditay Oroww?_**

constant (GVIO) prices probably understate changes in the sales price of coal received by the producers. Specifically, we anticipate that, Jf t indicates time, the ratio of annual output data CVIO(t)/GVIO(t) is too low.

Inconsistency among several data series raises the question of which is most likely to be in error. The conclusion that the ratio CVIO(t)/GVIO(t) is probably too small is based on the judgment that figures for average coal cost, which come dirctly from records of financial and material transactions maintained by large, well-establishri units, are less subject to distortion than ynthetic calculations of output value. If the distortion is contained in the output figures, the previous discussion suggests the constant-price figures (GVIO) as the probable locus of difficulty.4 This reasoning is not foolproof, but it appears that the most likely explanation of inconsistency between coal costs to the power industry and the 1VTO and CVIO data relating to coal production is that the series of output value at fixed w faster than the real value of industrial output in the coal industry.

Inconsistency between information about inflationary patterns and the price indexes implicit in China's industrial output statistics is not limited to the coal industry. More general difficulties become evident when one compares the implicit price indexes derived from output data for **the** state and collective segments of industry.

Despite the progress of economic reform, markets for Chinese indistrial output remain heavily regulated. Many firms are obliged to sell substantial portions of their output at low controlled prices. Even when firms are allowed to sell output at 'negotiated' or "imarket' rather than plan prices, they encounter numerous controls [Ishihara, 1989]. Government agencies set maximum prices, as when the State Price Bureau issues 'upper price limits for means of production outside the plan," including petroleum products, aluminum ingots and steel products [frice Thcy 3 (1988): 51-53). Extra-plan sales of steel and non-ferrous metal products are also restricted to designated commodity exchanges [rinc TheoX _5_ (1988): p. 57]. These measures are clearly designed to contain and restrict the rise of industrial prices. "law-boning," or personal official advice intended to limit price increases, has the same effect.

Each of these measures is directed primarily toward, and applied most forcefully to the activities of large, stateowned enterprises. Under conditions of excess demand in which govemment struggles to prevent prices from rising to market-clearing levels, it is difficult to doubt that small, widely dispersed collective enterprises encounter less restriction on product pricing than large, highly visible firms in the state sector. For this reason, there is a strong presumption that the rate of price increase for commodities produced in the collective sector will tend to outpace comparable inflation rates for similar products in the state sector.

> 4. **Itis also pouible that riing makups** by **_cooomeil intennsdiarim_ have widenod** Xw p **berwes tbe primes oseved** by ooal produm **and the price** paid by **oal user** for **_the_** powing porton of **astha oocur oute** X **pia** frmwork. However, **Jcfkon. RAwWi nd Zheng** find **no evidence** of **_A_ genral ris in markups** for 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 comparable state 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. Comparison of annual inflation rates for state and collective industrial ou.put witiin the same branch produces the same result. Between 1978 and 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 instances of 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 conclusions are 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, systematically understate the impact of inflation. If this is true, the most likely mechanism is that rorted output yalue at fixed prices forChir1. collective industries Systematically overstates the growth of real out= during the 1980s, particularly in recent years of strong inflationary pressures.

# F. **Are Reported Gains in Energy Productivity Unrealistically Large?**

Data reproduced in Table 8 indicate that China's industries achieved very substantial gains 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 manufacturing for major industrial nations showing average annual productivity growth 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 shortages within 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 comparable prices in cther nations and in the world market, and also that domestic energy prices have not risen in paralle with global market trends. Despite the inflexibility of official prices, the data in Table 6, showing that avemge coal prices paid by thermal power plants nearly S. **.. ece** commenu am **based** on **a workshea** DEFLATE2.wkl.

6. **Based on** _a_ **scpare workshee** NENOCOMP.wkl, **which is not included** in this **paper.**
# _16_ **_How_** _Fwat_ **_Mar Chine Irdmrbv Grow?_**

doubled between 1978 and 1987, imply still larger increases in the _mumsinal_ prices paid even by high-priority energy consumers in China's industrial economy, Even where energy prices have not risen steeply, reports suggesting widespread energy rationing point to the binding nature of energy constraints across much of Chinese energy. Under these conditions, managers seeling higher financial returns will impute a high opportunity cost to inessential energy consumption even if direct costs are low. It thus seems reasonable to conclude that many Chinese managers feel intense pressure to economize on energy consumption.

Changes in industrial energy productivity can be decomposed into three components: changes in the branch structure of industry that decrease the reladve weight of energy-intensive industries, reductions in energy requirements for producing specific commodities, and changes in the commodity structure of output within individual branches of industry. We have already seen that Chinese industry experienced no significant change in branch structure during the past decade (Table 3).

Review of Chinese publications, which include numerous descriptions of physical input-output coefficients related to energy consumption, sugest only modest gains from reduced unit energy requirements for specific products. Electric power consumed in producing one ton of crude oil or raw coal increased every year during 1980/85 (Energy 1986, pp. 86, 504]. Coal consumption per idlowatt of power turned out by large power plants or per ton of cement produced by major plants declined, but by less than five percent [ibid., 508, _527]._ Since the share of output coming from small plants, which are criticized for their excessive energy requirements, has risen in many branches, the potential for major growth of energy productivity from reduced unit energy requirements for specific products seems very limited.

This leaves structural change within individual branches of industry as the main locus of improved energy productivity for Chinese industry during 1980/85. Tlhis conclusion is problematic because substantial intra-branch restructunng appears limited to a few branches - machinery, chemicals, and perhaps textiles. This outcome draws attention to the possibility that a portion of the productivity gains repot.ed in Table 8 may be attrbutable to measurement error. To explore the possibility of measurement error, and also to investigate the branch pattern of cnange _ip._ sarmgy productivity, we turn to an examination of energy data for 15 branches of Chinese industry during 1980/85.

Table 9 pnsents energy consumption data for 15 branches during 1980/85. Panel B uses these figures to derive annual percentage changes in energy productivity (GVIO/E, where E represents energy consumption in terms of standard coal) for 15 branches. These data conta a number of improbable items: can we believe, for example, that energy productivity in food processing rose by 27.3 percent during 1984/85, or that energy productivity in machine-building rose by 21.1 percent in the same year?
**_How Fad Has CAsa Inr4ustry Oro,?_** _17_

We can investigate the consistency of the data for energy consumption<sup>(not shown) and</sup> energy consumption per unit of GVIO by extracting the implicit branch figures<sup>for GVIO and</sup> comparing them with GVIO data from other sources. Tis is done in Table<sup>10, which uncovers</sup> unacceptably large discre)ancies for branches 9-14 in the 15-branch clasification.<sup>Fortunately,</sup> data for the sectors that consume the largest quantities of energy, namely<sup>metallurgy, power,</sup> chemicals, building materials, and machine-building, are not involved in these inconsistencies.

Table 11 presents a recalculation of EIGVIO and of annual percentage changes<sup>in GVIO/E</sup> for 1980/85 based on published branch data for E and on information from<sup>other sources giving</sup> branch time series of GVIO. These revised data show fewer improbable entries<sup>(readers should</sup> ignore the problems in branches 13 and 14, which should be merged<sup>in a future recalculation).</sup> These results suggest that, among the major energy users, machinery, chemicals<sup>and, to a lesser</sup> extent, metallurgy, have achieved considerable success in raising<sup>energy productivity, while</sup> electricity and building materials have recorded much smaller<sup>gains.</sup> The veracity of these data, however, depend substantially on the accuracy<sup>of GVIO data</sup> for chemicals and machinery - exactly the sectors for which comparison<sup>of physical production</sup> and value data indicate the possibility of upward bias in the value totals.<sup>Since energy</sup> productivity in these sectors, alone among the major using branches, rises<sup>much faster than the</sup> reported national avenge, this dependence is considerable. Removal of the<sup>chemical and</sup> machinery branches, which contribute over half of the overall energy<sup>savings attained during</sup> 1980/85 (Table 16) reduces the cumulative growth of energy productivity<sup>during 1980/85 from</sup> 28.6 percent to 17.3 percent (Table 16, Panel 1). If we were to assume<sup>that the growth of</sup> energy productivity in machinry and chemicals was limited to this<sup>lower amount, rather than</sup> the much larger figures shown in Tables 1lB and 16, the average<sup>annual growth rate of the</sup> entire industrial sector (excluding village enterprises) during 1980/85<sup>would be reduced by two</sup> percentage points, from 10.8 to 8.8 percent annually.<sup>7</sup> Note, however, that the World Bank anticipates large reductions in unit<sup>consumption of</sup> electricity in the chemical brarich because of slow relative growth of synthetic<sup>ammonia,</sup> "dramatic reductions' in unit power requirements for synthetic<sup>ammonia, and the international</sup> trend toward reduced power intensity in chemical manufacture<sup>(1985-A3, pp. 47-49].</sup> Furthermore, Chinese specialists regard the materials contained in Energy (1986]<sup>as preliminary;</sup> this book was never released to the general public. However, it is my<sup>impression that data</sup> issued in subsequent publications (notably Energy [1989]), will support<sup>similar results.</sup> The importance of energy issues and the major differences in<sup>scale and technology</sup> separating state and collective industry makes it important to provide<sup>separate analysis of energy</sup> consumption in state and collective industry. As far as<sup>I can determine, China's statistical</sup> agencies have made no effort to do this. Industrial census data giving<sup>energy consumption for</sup>

> 7. Thi calculzion **is based** on **first** column of **Table 2B,** following **a** **_separae_** worksheg<sup>**'What**if</sup><sup>**Energy Savings ate**</sup> **Trimmed?' dated** 7-4-1989.
# _18 How_ **_Fa Ha CHasM . Indaw Gou?_**

state sector independent accounting units in 1980 and 1985 allow a trial calculation of energy consumption and energy productivity trends for collective industry durinig the 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 independent accounting units divided into 40 branches;

- (2) collapse data for 40 branches into 15 branches;

- (3) obtair. estimates of collective sector energy consumption in 15 branches for 1980 and 1985 by subtracting energy consumption by state-sector firms from the national totals underlying Table 9.

- (4) calculate changes in 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 significant inconsistency between implied and publisned data for branch GVIO (readers should ignore the discrepancy for branch 7, which is trivial in size, and in the residual branch 40). Again, we see substantial increases in energy productivity over _5_ years; again, these gains depend crucially on reported increases for a small number of branches that consume large amounts of energy and report above-average productivity gains: chemicals (branch 26); machine manufacture (branch 35).

These data can also be used to compute the 'energy savings' arising from the presence of lower unit energy consumption coefficients in 1985 than existed in 1980. As before, two sectors, machinery and chemicals, dominate the calculated savings, 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 (considerably slower) gains reported for other branches of industry, the average annual growth rate for state industry during 1980/85 would decline by one percentage point, from 8.2 to 7.2 percent.' Table 13 reports the result of calculations that collapse data for 40 state-sector branches into 15 branches and derive figures for changes in energy productivity for the 15 branches between 1980 and 1985. The transition from 40 to 15 braiiches is incomplete because it is not possible to make adjustments for 18 sub-branches (as is done in a separate worksheet, DATA87.wkl); the discrepancy, however, is not large. Energy productivity for 15 branches is calculated in 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 independent accounting units in the S. **Thuis i** bued on **Table** 2 **and a s.paz** workshea What if **Energy** Savings **ar Trimmed?'.**
**_HoaswFt fai Chi,e InduurJy_** _Groy? 19_

state sector according to the 15-branch classification in use before 1986. Although the differences between the two sets of calculations are not large (again, note that branches 13 and 14 should be merged), the latter figures are preferable. Here again we see the importance of machinery and chemicals, which are the only large branches reporting above-average growth 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-sector figures presented above. Comparison of GVIO figures derived in this manner with published data showing branch GVIO for collective-sector independent accounting units at and above the &ing level (recall that the basic energy consumption data for 1980/85 appear to exclude village-level industry), reveals massive inconsistency. We therefore focus our attention on Panel 2 of Table 14, in which branch energy consumption for collective industries is derived as a residual, and then combined with published data on collective sector branch output to obtain productivity figures.

# Scrutiny of these results yields the following observations:

1. There is a major inconsistency in data for the electric power industry, in which data for the state sector alone indicate much larger energy consumption in both 1980 and 1985 than for the entire power branch! As a result, the calculation reported in Table 14 indicates large negative energy consumption in the collective power industry for both years. Less worrisome discrepancies appear 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 coUective productivity on a branch-by-branch basis. Energy consumption per unit of real output by collective producers is markedly higher in branches 1, 6 and 9 (metallurgy, machinery, food processing) than in the state sector. Partial energy productivity seems to 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 comparison is blurred by major differences in product mix) and 11; the comparison is obscured by data problems for the remaining sectors.

4. Cumulative gains in energy productivity for the collective sector, summarized in Table 15, are far larger than comparable gains for the state sector in every significant branch except building materials (ignore the confused and minor branches 13-15). In most cases, the margin of difference is extremely large.
_20_ **_How_** _Fast_ **_Has Chbwae Inidut Growe?_** This last result seems quite improbable,<sup>and once again calls attention to the possibility of</sup> upward bias in available measures of real<sup>output growth fnr the collective sector.</sup> A final point about e'nergy data. There<sup>is a variety of material suggesting that</sup> overestimates of output growth may not be confined to<sup>TVE enterprises and the collective sector.</sup> Some examples: Energy consumption per 10,000 yjan of output<sup>in Beijing's electric power industry dropped</sup> from 4.62 to 4.07 tons of standard coal<sup>during 1986/87, indicating a rise of 13.6 percent in</sup> energy productivity, even though coal consumption<sup>per kldowatt-hour</sup> of power produced did not change [Beijing 1988, pp. 291, 372].

Nationally, the electric power industry<sup>reports a 7.5 percent drop in unit energy</sup> requirements during 1980/85 (Table 11-B)<sup>even though coal consumption per kwh for large</sup> power plants (6000 kw and above), which<sup>produce a large share of total power output, declined</sup> by only 3.6 percent during the same period (Ene gy<sup>1986, p. xxx].</sup> The chemical industry reports thai energy productivity<sup>increased by 12.6 percent in 1984/85</sup> (Table 11-B). During the same perio:'. !owever,<sup>8 of 16 unit energy coeffici:nts for major</sup> plants actually increased! The remainiig<sup>eight coefficients declined by an average of</sup><sup>_5.8_</sup> percent. Only 1 of 16 coefficients for major<sup>plants declined by more than the reported</sup> industry-wide average (Energy 1986, p. 87].

The building materials industry reported a<sup>20 percent rise in energy productivity during</sup> 1980/85, but unit energy requirements at major<sup>plants decline by a maximum of 6.3 percent</sup> [Energy 1986, p. 88] Reported energy productivity in coal production<sup>improved in every year but 1984/85 (Table</sup> l 1-B), showing a cumulative gain of nearly<sup>five percent. Yet data for major enterprises show</sup> a rising treiid for unit energy requirements;<sup>power consumption per ton of raw coal rises in</sup> every year [Energy 1986, pp. 86, 493-500]

# V. CONCLUSIONS

This survey reveals considerable evidence<sup>pointing to the existence of upward bias in</sup> measures of China's real industrial output<sup>during the past decade. The issue is not whether such</sup> bias exists, but whether or not its presence<sup>substantially alters our perception of the rate and</sup> pattern of Chinese industrial growth.

To clarify this issue requ res an investigation<sup>of the possible extent of upward bias. This in turn</sup> will require an analysis of possible links<sup>between upward bias, which itself is difficult to</sup> observe, and other economic patterns that<sup>may be more readily measurable.</sup>
_How Fait Has Ch;na_ **_Irdalwvy_** _Grown?_ **_21_**

# TABLE 1: ALL INDUSTRY

# A. Level of Industrial Gross Output, 100 million yuan

|Year|GVIO<br>Iadusuy|GVIO<br>_Viage_|GVIO<br>Industzy +|CvIO<br>Indus +|Price<br>Iadex|Annual %<br>Inflazion|
|---|---|---|---|---|---|---|
|Data in 1|970 prices||||||
|1978|4231|161|4392|4237|96.47||
|1979|4591|184|4775|4681|98.03|1.62|
|1980|4992|222|5214|_5155_|98.87|0.85|
|1981|5199|241|5440|5400|99.26|0.40|
|Data in 1|980 prices||||||
|1981|5178|246|5424|5400|99.56|N.A.|
|1982|5577|277|5854|5811|99.26|-0.29|
|1983|6164|325|6489|6461|99.57|0.30|
|1984|7030|460|7490|7617|101.70|2.14|
|1985|8295|661|8956|9717|108.50|6.69|
|1986|8979|841|9820|11194|113.99|5.06|
|1987|10307|1150|11457|13813|120.56|5.76|

|B. Index|of Output Growth, 1978- 100|||
|---|---|---|---|
|1979|108.51<br>114.28|108.72|110.48|
|1980|117.99<br>137.89|118.72|121.67|
|1981|122.88<br>149.69|123.86|127.45|
|1982|132.35<br>168.55|133.68|137.15|
|1983|146.28<br>197.76|148.18|152.49|
|1984|166.83<br>279.91|171.04|179.77|
|1985|196.85<br>402.21|204.52|229.34|
|1986|213.08<br>511.74|224.25|264.20|
|1987|244.59<br>699.77|261.63|326.01|

(continued)
_22 How Fast_ **_Has_** _Chine_ **_Inudwy_** _Grown?_

# TABLE 1: ALL INDUsTRy (continuation)

|Year|GVTO<br>Industry|GVIO<br>Village|GVIO<br>Industry +|CVIO<br>Indus +|Price<br>Index|Annual %<br>Inflation|
|---|---|---|---|---|---|---|
|C. Annu|al Output Increase|Over Previous|Year (percent)||||
|1979<br>1980|8.51<br>8.73|14.28<br>20.65|8.72<br>9.19|10.48<br>10.13|||
|1981|4.17|8.56|4.33|4.75|||
|1982|7.70|12.60|7.93|7.61|||
|1983|10.52|17.33|10.85|11.18|||
|1984|14.05|41.54|15.43|17.89|||
|1985|17.99|43.70|19.57|27.57|||
|1986|8.24|27.23|9.65|15.20|||
|1987|14.79|36.74|16.6|23.40|||

## Source: Rawsli written files GVIO-tables.
_How Fast Hai Chinw Indwray 7rown?_<sup>_23_</sup>

# TABLE 2: BREAKDOwN OF GROSS **INDUSRAL**<sup>OUTPUT AT CONSTANT PRICES</sup> DATA EXCLUDE VILLAGE-LEYEL<sup>UNITS</sup>

||B<br>Total|C<br>State|D|E<br>Collective S|F<br>ector Categori|G<br>es|H<br>Xiang<br>|
|---|---|---|---|---|---|---|---|
||||Total|Xiang-A|Xiang-B|CunlDui|zhen|
|1978|4231|3416|814|212|224|161|_385_<br>|
|1979|4591|3720|871|234|241|184|424|
|1980|4992|3928|1034|280|286|222|509|
|1981|5199|4028|1131|310|321|241|579|
|1981|5178|4054|1089|323|332|246<br>|579<br>|
|1982|5577|4340|1193|354|369|277|646|
|1983|6164|4748|1354|413|432|325|757<br>|
|1984|7030|5171|1758|539|575|460|1245<br>|
|1985|8295|5840|2301|742|799|661|1827|
|1986|8979|6201|2637|948|2413|||
|1987|10307|6902|1217|3243||||

||Check|
|---|---|
||H-(F +G)|
|1978|0|
|1979|-1|
|1980|1|
|1981|17|
|1981|1|
|1982|0|
|1983|0|
|1984|210|
|1985|367|
|1986|2413|
|1987|3243|

Sourvs: Rawsld written file.s GVIO-tablea
_24 How_ **_Foat Has ChinueIndwr^y Grow.?_** TABLE **3:** BRANCH STRUCTURE OF GVIO AT 1980 **PRICES** (PERCENT)

# A. Branch Structure for **State Enterprisea** (SOE)

|Br|1978|1979|1980|1981|<br>1982|1983|1984|1985|<br>1986|1987|
|---|---|---|---|---|---|---|---|---|---|---|
|1|11.80|11.99|11.81|11.08|10.96|10.73|10.77|10.51|10.5|8 10.52|
|2|4.82|4.79|4.87|4.86|4.82|4.59|4.45|4.66|4.61|4.59|
|3|4.26|3.99|3.61|3.42|3.36|3.25|3.15|2.99|2 83|2.65|
|4|8.01|7.81|7.49|7.16|6.83|6.69|6.68|6.52|6.43|6.37|
|_5_|11.81|11.60|11.92|12.02|12.41|12.44|12.43|11.70|12.61|12.36|
|6|21.12|21.34|20.26|18.55|19.86|21.34|23.12|24.58|25.86|25.51|
|7|2.75|2.69|2.67|2.50|2.57|2.56|2.59|2.81|3.45|2.70|
|8|1.89|1.86|1.78|1.73|1.67|1.56|1.48|1.24|1.14|1.13|
|9|12.44|12.65|13.01|14.30|14.58|13.86|13.52|13.19|12.99|12.99|
|10|13.83|14.20|16.11|18.10|16.67|16.78|_15.56_|<br>15.19|<br>14.56|14.42|
|11|1.04|0.51|0.54|0.60|0.56|_0.55_|0.56|0.56|0.52|0.53|
|12<br>|0.00|0.53|0.58|0.63|0.57|0.52|0.48|0.47|0.48|0.46|
|13|3.07|3.18|3.18|2.93|1.44|1.43|1.46|1.48|1.60|1.64|
|14|0.00|<br>0.00|<br>0.00|<br>0.00|<br>1.48|<br>1.44|<br>1.42|<br>1.48|<br>0.46|<br>0.47|
|iS|3.14|2.85|2.17|2.12|2.24|<br>2.26|<br>2.32|<br>2.62|<br>1.89|<br>3.67|
|Sum|100.00|00.00|100.00|100.00|100.00|100.00|100.00|100.00|100.00|100.00|

# B. Branch Structure for CoUective Enterprises (COE)

|Br|1978|<br>1979|<br>1980|<br>1981|<br>1982|<br>1983|<br>1984|<br>1985|<br>198b|<br>1987|
|---|---|---|---|---|---|---|---|---|---|---|
|1|1.97|<br>2.28|<br>2.34|<br>2.17|<br>2.32|<br>2.47|<br>2.54|<br>2.89|<br>3.39|<br>_3.56_|
|2|0.11|0.15|0.17|0.21|0.23|0.25|0.22|0.20|0.20|0.20|
|3|2.27|2.12|1.94|<br>1.87|1.93|1.94|1.92|1.64|1.63|1.42|
|4|0.12|0.13|0.13|0.11|0.11|0.14|0.13|0.15|0.18|0.21|
|_5_|10.94|10.74|10.76|10.93|11.45|11.94|11.26|10.94|11.17|11.30|
|6|36.07|34.84|32.63|30.38|30.68|31.55|30.95|33.27|32.83|33.07|
|7|8.37|8.63|8.32|7.91|8.57|8.46|<br>8.17|7.50|8.89|7.51|
|8|2.55|2.73|2.72|2.64|2.71|2.52|2.33|2.23|2.85|2.28|
|9|2.96|3.39|3.70|4.39|4.69|4.71|5.04|4.96|5.37|<br>5.46|
|10|7.90|8.58|10.04|11.92|12.08|12.26|16.02|16.3|15.76|15.96|
|11|11.28|9.36|10.49|<br>10.96|9.59|9.22|8.44|7.10|6.39|6.22|
|12|0.uO|2.35|2.94|3.05|2.58|2.34|2.09|2.08|2.17|2.20|
|13|5.48|5.06|5.35|_5.53_|5.26|4.61|1.02|1.01|2.45|2.61|
|14|0.00|1.02|1.02|1.06|1.08|1.08|4.18|5.13|3.62|3.94|
|15|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)**
_How FPa Hat ClaAmaal Industry Ora"? 25_ TABLE 3: BRLNCH STIrUCT1z o GVIO AT 1980 PRiCzS (PEcCNT)<sup>(coaninuatin)</sup> C. Branch Structure for SOE and COE Combinod<sup>(peamt)</sup>

||1978|1979|1980|1981|1982|1983|1984|1985|1986|1987|
|---|---|---|---|---|---|---|---|---|---|---|
|1|9.99|10.21|9.90|9.18|9.07|8.84<br>|8.69<br>|8.39<br>|8.49<br>|8.37<br>|
|2|3.9S|3.94|3.92|3.86|3.82|3.61|3.38|3.43<br>|3.33<br>|3.23<br>|
|3|3.91|3.6S|3.27|3.08|3.0S|2.96<br>|2.84<br>|2.61<br>|2.48<br>|2.27<br>|
|4|6.56|6.40|6.00|_5.6S_|5.36|5.22|5.02|4.7S<br>|4.61<br>|4.47<br>|
|_5_|11.65|11.45|11.69|11./9|12.20<br>|12.33<br>|12.14<br>|11.49<br>|12.19<br>|12.03<br>|
|6|23.87|23.81|22.76|21.08|22.22|23.63<br>|25.10<br>|27.00<br>|27.88<br>|27.35<br>|
|7|3.79|3.78|3.81|3.65.|3.87|3.88|4.00|4.11<br>|S.03<br>|4.19<br>|
|8|2.01|2.02|1.97|1.92|1.89<br>|1.77<br>|1.70<br>|1.51<br>|1.64<br>|1.48<br>|
|9|10.70|10.96|11.13|12.18|12.42|11.81<br>|11.38<br>|10.91<br>|10.77<br>|In).66<br>|
|10|12.74|13.17|14.89|16.78|1S.67|15.77<br>|_1S.68_<br>|1S.50<br>|14.91<br>|14.19<br>|
|1 1|2.92|2.13|2.55|2.82|2.53|2.49<br>|2.55<br>|2.38<br>|2.23<br>|2.29<br>|
|12|0.00|0.86|1.06|1.1S|1.01|0.93<br>|0.89<br>|0.92<br>|0.97<br>|1.00<br>|
|13|3.52|3.53|3.62|3.49|2.28|_2.1S_|1.34<br>|1.35<br>|1.85<br>|1.94<br>|
|14|0.00|0.19|0.21|0.23|1.39<br>|1.36<br>|2.12<br>|2.49<br>|1.38<br>|1.54<br>|
|_15_|4.39|3.91|3.23|3.14|3.22|3.21<br>|3.17<br>|3.16<br>|2.24<br>|3.79<br>|
||100.00|100.00|100.00|100.00|100.00|99.99|100.00|100.00|100.00|100.00|

Note: these data exclude vilba-level ;mepris; they ar oonfingd to indepmida accounting units.

<!-- Start of picture text --> Key to branches:<br>i metallurgy<br>2 power<br>3 coal<br>4 petroleum<br>S chemicals<br>6 machiney<br>7 building materials<br>8 forestry ad wood processng<br>9 food procesing<br>10 textile<br>11I<br>12 leuher prcesing<br>13 paper<br>14 cultnual and at products<br>15 other<br><!-- End of picture text -->

# Source: Wodrhot STRUCTURB.wkl
_26 How Fast Has_ **_Cine_** _Inrdwtyr Grown?_ TABLE 4: NET OUTrT AT CURRENT PRICES (100 MILON YUAN) INDEPENDENT ACCOUNTiNG UNITS, EXCLUDING VILAGE ENTERRLSEs

||Total|State|Colective|Xiang|
|---|---|---|---|---|
|1978|1358||||
|1979|1486||||
|1980|1648|1319|322|114|
|1981|1690|1317?|342||
|1982|1774|1373|369||
|1983|1930|1501||415|
|1984|2246|1721|_506_|183|
|198S|2767|2058|679|247|
|1986|2979|2178|763|296|
|1987|3488|2530|894|354|

Source: Rawali wntten files GVIO-tables.

Net output ratio (baed on CVIO data for independent accounting unit - not shown)

||Total|State|Colective|
|---|---|---|---|
|1978<br>1979||||
|1980|0.35|0.351|0.348|
|1981|0.344|0.341|0.337|
|1982|0.336|0.332|0.334|
|1983|0.332|0.332|0.332|
|1984|0.333|0.340|0.314|
|1985|0.329|0.336|0.313|
|1986|0.316|0.322|0.301|
|1987||||
**_How Fast Has ChIat Indua_** _Gretw?_ **_27_**

# TABLE 5: CEHsUcAL INDurrRy

<!-- Start of picture text --> Averag % Change Differmtial<br>Perew Change GVIO,P80 Growth of<br>physical output OVIO, percentage<br>Nine Products<br>1979 13.51 7.01 -6.60<br>1980 7.85 10.77 2.92<br>1981 -4.06 4.66 8.72<br>1982 7.30 11.43 4.13<br>1983 8.33 12.46 4.13<br>1984 3.30 12.04 8.74<br>1985 1.05 11.61 12.66<br>1986 5.77 12.17 6.40<br>1987 14.S2 17.C8 2.56<br><!-- End of picture text --> Source: 1988 TJNJ, pp. 34546 for commodity dat; OVIO **dat** aro from Indusry 1988, p. S4. Thea figtuem ezcluds villge-level onprises. Figures for 1978-80 woro converted **from** 1970 to 1980 prime usaug th ntio of .1981 **gro** output for chemicu_ at 1980 and 1970 prioe
_28 How Fast Has Chks Indawmty rotm?_ TAILE 6: ALTmENATrVE DATA To MEASURe finLATION IN THE COAL INDUSTRY

||A<br>Costiton<br>Sid Coal<br>Y/ton|B<br>_%_change<br>from pan<br>yur|C<br>Price<br>Indx<br>1978-100|CVIO/<br>Annua<br>Chan<br>Pat<br>SOB|OVIO<br>l Price<br>ge From<br>Year<br>**COE**|Cumulatve<br>Price Chang<br>Since1978<br>Percet<br>Power<br>Plats|
|---|---|---|---|---|---|---|
|1971|43.77|NA.|100.00||||
|1972|38.99|-10.92|89.08||||
|1973|39.86|2.23|91.07<br>||||
|1974|43.10|8.13|98.47||||
|1975|44.17|2.48|100.91||||
|1976|44.70|1.20|102.12||||
|1977|44.80|0.22|102.35||||
|1978|42.06|-6.12|96.09||||
|1979|44.93|6.82|102.65|14.32<br>|4.44<br>|6.82<br>|
|1980|46.18|2.78|_105.51_<br>|7.25<br>|1.38<br>|9.80<br>|
|1981|47.71<br>|3.31|109.00<br>|2.56<br>|5.05<br>|13.43<br>|
|1982|55.40|16.12|126.57|1.66<br>|4.99<br>|31.72<br>|
|1983|61.32|10.69|140.10<br>|1.23<br>|5.41<br>|45.79<br>|
|1984|64.01|4.39|146.24|2.71<br>|3.82<br>|52.19<br>|
|1985|69.21|8.12|1S8.12|13.68<br>|9.83<br>|64.5S<br>|
|1986|7S.21|8.67<br>|171.83<br>|5.13<br>|2.01<br>|78.82<br>|
|1987|79.46|5.65|181.54|4.94|3.97|88.92|

Source: Coal costs from Xu et Al (1989); implicit<sup>price</sup><sup>_indbexas_</sup> tAken fom workshoet DEFLATE2.wkl.
_How_ **_rar_** _Hu ChLRue I1duvY Grow? 219_

# TABLZ 7: PRICt INDIn EXTRACTD MOM INDUSAL Ouwnr VALUz DATA

|Year|PR1CE<br>SOE|INDEX<br>COE|ANNUAL<br>IN PRIC<br>SOE|% CHANGE<br>E LEVEL<br>COE|SOB<br>DIFFERENTLAL<br>PRCE CHANGE<br>percentage<br>poin|
|---|---|---|---|---|---|
|Combin|ed Data for All 1|5 Banch||||
|1978|0.96|0.97|N.A.|N.A.|N.A.|
|1979|0.98|0.97|1.84|-0.12|1.97|
|1980|0.99|0.96|1.09|-0.60|1.69|
|1981|1.00|0.96|0.38|0.04|0.35|
|1982|1.00|0.95|0.10|.1.06|1.17|
|1983|1.00|0.95|.0.05|4.36|0.41|
|1984|1.02|0.96|1.95|0.72|1.23|
|1985|1.08|1.00|6.30|4.28|2.02|
|1986|1.12|1.01|3.33|1.50|1.83|
|1987|1.20|1.05|7.07|3.71|3.36|

## Soure: Worksheet DEFLATE.wkil.
## _30 How F Has ChIldmsy Grows?_

# TAJLT 6S ZNUGY PRODUCtMITY PI CN INDUMY OmciAL DATA, 1918-7

|You|Eneg<br>UN<br>PA 10_Milioa_<br>_Yuan_of OVIO<br>(ton std. coal)|Annual Pecmu<br>_Chanp_in<br>Ewa<br>Productivity|
|---|---|---|
|1980<br>|78411|ns.|
|1981<br>|72380<br>|8.33|
|1932<br>|70374|2.85|
|1983<br>|6704S<br>|4.97|
|1984<br>|62592<br>|7.11<br>|
|1985<br>1986<br>1987|56872|10.06|
_How FuM_ **_HMm Chlmue Ir4Wi Gru?_** _31_

# TAILE 9: OmciAL ENERGY DATA FOR CHNE INDUSTRY BY BRANCH, 1980-198S

A. Energy consumption in tons of **standard** coal per 100 million yuas of GVIO at 1980 pricu

|branch|<br>1980|1981|1982|1983|1984|1985|
|---|---|---|---|---|---|---|
|1|164549|156603|150471|147084|142632|132.|
|2|99124|99492|96161|93911|93926|92062|
|3|162468|157580|155472|152577|151079|156652|
|4|83429|76069|73443|69541|65960|60040|
|_5_|148546|136517|127091|118445|110716|98176|
|6|32538|31160|29269|25823|22886|18894|
|7|217821|21552S|215280|20959S|193233|180283|
|8|36959|37293|33711|38041|33546|34263|
|9|131594|127529|128454|135213|128038|100577|
|10|32537|31258|29761|30040|28645|28135|
|11|701|666|712|662|633|717|
|12|6839|6371|6721|5813|5054|5224|
|13|173163|144298|161236|168497|165408|154314|
|14|11482|12205|12169|12370|11549|11476|
|1S|77476|73383|70686|66480|61444|58634|
|total|78411|72380|70374|67045|62592|56872|

B. Annual percentage rise in GVIO per ton of standard coal consumed

|brmnch|1981|1982|1983|1984|1985|
|---|---|---|---|---|---|
|1<br>|5.07|4.08<br>|2.30<br>|3.12<br>|7.56<br>|
|2|-0.37|3.46|2.40|-0.02|2.02|
|3<br>|3.10|1.36<br>|1.90<br>|0.99<br>|-3.56<br>|
|4|9.68<br>|3.58<br>|5.61<br>|5.43|9.86<br>|
|_5_<br>|8.81<br>|7.42<br>|7.30|6.98<br>|12.77<br>|
|6|4.42|6.46|13.34|12.83|21.13|
|7|1.07<br>|0.11|2.71|8.47|7.18|
|8|-0.90|10.63|-11.38|13.40|-2.09|
|9|3.19|-0.72|-5.00|5.60|27.30|
|10|4.09|5.03|-0.93|4.87|1.81|
|11|5.26|-6.46|7.55|4.58|-11.72<br>|
|12|7.35|-5.21|15.62|15.02|-3.2S|
|13|20.00|_-10.51_|-4.31|1.87|7.19|
|14|-5.92|0.30|-1.62|7.11|0.64|
|**_15_**<br>|**_5.58_**|3.82|6.33<br>|8.20|4.79<br>|
|total|8.33|2.85|4.97|7.11|10.06|

Source: Data **taken** or calculated from Energy 1986, p. 16.
_32 How F Hmm ChL.e_ Iadaiy _otrP_

# TAMZ 10: GVIO **DATA FOR 15** BRANCHS (100 MLION YUAN, 1980 PrICES)

## A. Derived from Statistics of Energy Consumption and Efficiency, 1980-1985

|brunch|1980|1981|1982|1983|1984|1985|
|---|---|---|---|---|---|---|
|1|473.05|456.70|<br>485.21|<br>523.71|579.39|<br>664.04|
|2|189.16|<br>194.89|<br>207.05|<br>220.21|235.61|<br>272.75|
|3|159.79|<br>157.25|<br>166.33|<br>173.34|194.73|<br>208.42|
|4|290.07|282.11|<br>287.98|<br>310.03|334.14|<br>416.39|
|5|565.08|591.43|<br>658.98|<br>741.10|830.32|<br>926.70|
|6|1!21.77|<br>1079.91|<br>1225.19|<br>1440.58|<br>1756.97|<br>2235.10|
|7|196.80|195.10|<br>222.59|<br>24S.43|287.27|<br>350.62|
|8|105.52|104.85|<br>112.13|<br>116.19|126.69|<br>133.09|
|9|112.32|121.78|<br>129.33|<br>134.08|151.91|<br>213.17|
|10|612.23|690.06|755.69|<br>794.27|865.77|<br>951.84|
|11|727.53|_855.86_|<br>870.79|<br>951.66|1090.05|<br>850.77|
|12|128.67|147.54|<br>141.35|<br>153.11|178.08|<br>199.08|
|13|51 63|58.56|55.69|57.03|62.21|76.47|
|14|26.13|69.64|73.96|81.65|92.65|108.05|
|15<br>|168.18|172.25|<br>188.72|<br>212.70|250.80|<br>309.55|
|total|4745.51|4946.81|<br>5330.66|<br>5900.37|6721.95|<br>7962.79|
|B.Publi|shedGVIOdaa|:SOE+ COE Ind|ependent<br>Units,1|980<br>pricas|||
|1|470.42|452.32|481.13|519.19|578.22|657.4|
|2|186.35|190.35|202.29|211.32|224.72|268.29|
|3|_15S.48_|152.04|<br>161.48|173.01|188.83|<br>204.69|
|4|285.22|278.63|284.43|305.29|334.37|<br>371.82|
|5|555.34|S81.23|647.04|721.12|807.57|<br>899.91|
|6|1081.82|1039.19|<br>1178.18|<br>1382.13|1670.42|<br>2114.46|
|7|181.02|180.18|205.45|227.13|266.29|322.17|
|8|93.75|94.75|100.47|103.71|112.93|<br>118.36|
|9|523.82|600.53|6S8.76|690.6'|756.97|854.11|
|10|707.42|827.08|830.69|922.22|1043.18|<br>1213.85|
|11|121.31|138.96|134.07|145.89|169.94|<br>186.21|
|12|50.14|56,60|_S3.S8_|54.21|59.11|72.06|
|13|171.82|171.87|120.66|125.65|89.49|105.68|
|14|9.84|11.13|73.65|79.43|141.1|19S.18|
|15|153.69|154.89|170.61|187.9|211.27|247.82|
|total|4752.45|4929.75|5302.49|S848.93|6654.41|7832.01|

(continued)
_HOw_ **_Fuc Mu CAba. 1Ay Oeu_** _t_ **_is_** TABLE 10: aoIO DATA FOR 15 BLgCNz (100 MWoN YUAN, 1930 PRC=) (On*imAsoa)

|branch<br>C. GVIO<br>|1980<br>discrepancy: d<br>|1981<br>erived- publishd<br>|1982<br>1983<br>u X of derived figurn<br> <br>|1984<br>|1935|
|---|---|---|---|---|---|
|1|0.56|0.96|0.84<br>0.86|0.20|1.00|
|2|1.48|2.33|2.30<br>4.04|4.62|1.64|
|3|2.69|3.32|2.92<br>2.99|3.03|1.79|
|4|1.67|1.23|1.23<br>1.53|-0.07|10.70|
|_5_|1.72|1.72|1.81<br>2.70|2.74|2.89|
|6|3.56|3.77|3.84<br>4.06|4.93|5.40|
|7|7.55|7.65|7.70<br>7.45|7.30|8.11|
|8|11.16|9.63|10.40<br>10.74|10.86|11.07|
|9|-370.84|-393.14|-409.15<br>-41S.11|-398.31|-300.67|
|10|-IS.SS|-19.86|-9.93<br>-16.11|-20.49|-27.53|
|11|83.33|83.76|84.60<br>84.67|84.41|78.11|
|12|61.03|61.64|62.09<br>64.59|66.81|63.80|
|13|-232.80|-193.49|_-116.6S_<br>-120.31|-43.85|-38.20|
|14|62.34|84.01|0.42<br>2.66|-52.30|-80.64|
|_1S_|8.62|10.08|9.60<br>11.66|15.76|19.94|
|tota|_-0.15_|0.34|0.53<br>0.87|1.00|1.64|
|A7. Revi|sed calcula*io:|os sad. coal per|Yi yua CIVIO,P80|||
|1|_16.55_|15.81|_1S.17_<br>14.84|14.29|13.40|
|2|10.06|10.19|9.84<br>9.79|9.85|9.36|
|3|16.70|16.30|16.01<br>15.73|1S.58|_15.95_|
|4|8.48|7.70|7.44<br>7.06|6.59|6.72|
|5|15.12|13.89|12.94<br>12.17|11.38|10.11|
|6|3.37|3.24|3.04<br>2.69|2.41|2.00|
|7|23.56|2..4|23.32<br>22.65|20.85|19.62|
|8|4.16|4.13|3.76<br>4.26|3.76|3.85|
|9|2.79|2.59|2.52<br>2.62|2.57|2.51|
|10|2.82|2.61|2.71<br>2.S9|2.38|2.21|
|11|0.42|0.41|0.46<br>0.43|0.41|0.33|
|12|1.75|1.66|1.77<br>1.64|1.52|1.44|
|13|S.20|4.92|7.44<br>7.65|11.50|11.17|
|14|3.05|7.63|1.22<br>1.27|0.76|0.64|
|_15_|8.48|8.16|7.82<br>7.53|7.29|7.32|
|Toal|7.83|7,26|7.07<br>6.76|6.32|5.78|
_34 Now_ **_Past_** _Mu_ **_C%kwe Indi&y Gro?_**

# TABLE 11: RriD CALCULATON: ANNUAL EczNT **_iNcRrAC_** IN ENEGY PRODUCTVTY BASED ON PCAL ENERGY CONSUmpON AND PUBnL GVIO DATA

|branch|1981|1982|1983|1984|1985|Cumuluivi<br>Total<br>1980/1985|
|---|---|---|---|---|---|---|
|1|4.65|4.20<br>|2.28<br>|3.81<br>|6.70<br>|23.53<br>|
|2|-1.23|3.50|0.57|.0.63<br>|5.22<br>|7.50<br>|
|3|2.44|1.77<br>|1.82<br>|0.95<br>|.32<br>|4.67<br>|
|4|10.16|3.58|5.29<br>|7.14<br>|-1.97<br>|26.19<br>|
|5|8.81|7.32|6.33|6.93|12.60<br>|49.S1<br>|
|6|4.19<br>|6.39<br>|13.08<br>|11.81<br>|20.53<br>|68.93<br>|
|7|0.96|0.06|2.99|8.65|6.25|20.09<br>|
|8|0.81|9.68|-11.72|13.25|-2.32<br>|7.98<br>|
|9|8.08|2.50|.3.89<br>|2.16<br>|2.36<br>|11.34<br>|
|10|7.97|-3.67|4.64|8.83|7.76|27.63<br>|
|11|2.49|-11.30<br>|7.09<br>|6.36<br>|23.94<br>|28.34<br>|
|12|5.67|-6.33|8.00<br>|7.83<br>|5.50<br>|21.60<br>|
|13|S.83<br>|-33.94<br>|-2.69<br>|-33.48<br>|2.98<br>|-53.40<br>|
|14|-60.06|524.68|-3.84|67.57|19.36|379.90<br>|
|1S|3.89|4.37|3.90|3.17|-0.41|15.76|
|total|7.80|2.66|4.60|6.97|9.35|35.41|
_How Fast Hai_ **_Chinea_** _Indawsy Growu? 35_

# TABLE 12: ENERGY DATA FOR STATE SECTOR INDEPENDENT **UNiTS,** 40 BRANCES, 1980 **AND** 1985

# A. Raw Data from Indusuial Cesus

||Energy Consunption|Tone of *t|d. coal per|
|---|---|---|---|
||10,000 tons std. coal|10,000 yua|n of_GVIO_|
|Branch|<br>1980<br>1985|<br>1980|<br>1985|
|1|2283<br>2543|18.24|16.22|
|2|1084<br>1147|8.27|7.15|
|3|46<br>62|5.61|5.68|
|4|106<br>116|**5.3**|4.18|
|5|69<br>76|6.61|6.11|
|6|124<br>132|7.65|8.39|
|7|0.0001<br>0.0001|3.2|3.87|
|a|156<br>183|4.06|4.98|
|9|44<br>65|4.04|3.91|
|10|740<br>1120|2.21|2.31|
|11|311<br>447|5.64|4.53|
|12|36<br>68|0.41|0.43|
|13|1<br>5|0.68|0.2|
|14|952<br>1234|1.72|1.63|
|iS|10<br>13|0.44|0.42|
|16|42<br>48|1.87|1.78|
|17|91<br>132|_4.S_|5.46|
|i8|9<br>10|1.89|1.5|
|19|594<br>746|9.21|8.15|
|20|27<br>36|0.79|0.67|
|21|11<br>13|_0.86_|0.58|
|22|6<br>9|1.27|0.87|
|23|7431<br>9127|38.89|34.44|
|24|1560<br>1613|9.43|7.76|
|25|300<br>330|23.08|20.37|
|26|5829<br>6211|18.08|13.78|
|27|237<br>322|3.97|2.68|
|28|321<br>481|9.71|5.4|
|29|160<br>195|2.19|1.84|
|30|39<br>59|1.58|1.37|
|31|2631<br>3594|21.44|19.34|
|32|5687<br>6397|19.01|16.36|
|33|620<br>754|5.2|4.64|
|34|135<br>_IS4_|2.69|2.19|
|_3S_|1170<br>1343|3.17|2.1|
|3|370<br>43S|_A.51_|1.66|
|37|194<br>224|1.8S|1.23|
|38|80<br>99|1.32|0.5|
|39|38<br>43|1.28|0.89|
|40|4<br>7|1.17|1.31|
|**sum**|33S48.00<br>39593.00|8.91|**6.99**|

Source: Indistia ceamns materias, 3: 346-355 <!-- Start of picture text --> (¢e)<br><!-- End of picture text -->
_36 How Fwzi Has Chin se Indsany Grown?_

# TABLE 12: ENERGY DATA FOR STATE SEcTOR INDEPENDENT UNITS, 40 BRANCHES, 1980 AND 1985 (contiustion)

B. Analysis and Consistency Check: Energy Data for 40 branches of State Industry

||% rise<br>in energy<br>productivity|Deriv|ed GVIO|Published OVIO|%diff.|
|---|---|---|---|---|---|
||<br>1980/15|Yi|Yuan|(Yi Yuan)|1985|
|Branch||1980|198S|1980<br>1985||
|1|12.45|125.16|156.78|1S6.19|-0.38|
|2|_15.66_|131.08|160.42|161.14<br>|0.4S|
|3|-1.23|8.20|10.92|10.86|-O.S1|
|4|26.79|20.00|7.75|27.79|0.14|
|5|8.18|10.44|12.44|11.99|-3.61|
|6|-8.82|16.21|15.73|15.75|0.11|
|7|-17.31|0.00|0.00|0.02|77300.00|
|8|-18.47|38.4|36.75|36.95|_0.55_|
|9|3.32|10.89|16.62|16.58|-0.26|
|10|-4.33|334.84|484.85|483.00|-0.38|
|11|24.50|55.14|98.68|96.83|-1.87|
|12|-4.65|87.80|158.14|156.90|-0.78|
|13|240.00|1.47|2S.00|23.82|-4.72|
|14|5,52|553.49|757.06|754.70|-0.31|
|1S|4.76|22.73|30.95|31.71|2.45|
|16|5.06|22.46|26.97|26.74|-0.54|
|17|-17.58|20.22|24.18|24.73|2.29|
|18|26.00|4.76|6.67|6.55|-1.75|
|19|13.01|64.50|91.53|90.30|-1.35|
|20|17.91|34.18|53.73|54.25|0.97|
|2 1|26.47|12.79|19.12|19.31|1.01|
|22|45.98|4.72|10.34|10.09|-2.46|
|23|12.92|191.08|265.01|263.85|-0.44|
|<br>24|21.52|165.43|207.86|207.50|-0.17|
|<br>25|<br>10.59|<br>13.00|15.81|15.85|0.24|
|26|31.20|322.40|450.73|449.98|-0.17|
|<br>27|48.13|59.70|120.15|119.55|-0.S0|
|28|79.81|33.06|89.07|90.12|1.17|
|<br>29|19.02|73.06|105.98|106.12|0.13|
|<br>30|15.3^|24.68|43.07|43.63|1.31|
|31|10.86|122.71|185.83|185.62|-0.11|
|32|1620|29916|391.01|391.90|0.23|
|<br>33|.<br>12.07|.<br>119.23|<br>162.50|<br>163.94|0.89|
|<br>34|<br>22.83|<br>50.19|<br>70.32|69.52|-1.14|
|<br>35|<br>50.95|<br>369.09|639.52|636.38|-0.49|
|36|5120|147.41|262.05|261.30|-0.29|
|<br>37|.<br>50.41|<br>104.86|<br>182.11|181.43|-0.38|
|38|16400|60.61|198.00|196.43|-0.79|
|<br>39|.<br>43.82|<br>29.69|<br>48.31|48.42|.22|
|40|-14.60|3.42|_5.11_|9.03|76.73|
|sum|27.47|3768.28|5667.07|5656.77|-0.18|
_How_ **_Fast HIt_** _Chinse Industy Grown? 37_

# TABLE 13: RouGH CONVERSON OF SOE ENERGY .1ATA TO _1S_ BRANCH FORMAT

||Energ|y Cona.|Derived|GV1O,P80|Ton aid c|oal per|% Rui|
|---|---|---|---|---|---|---|---|
|Bmnch|lOOOt|stid<br>coal|Yi|yuan|10000<br>yua|n GVIO<br>|GVIO/E<br>|
||1980|1985|1980|1985|1980|1985|1980,85|
|1. Using|DEFIVED GV|IO DATA||||||
|1|6459|7329|446.59|592.18|14.46|12.38|16.86|
|2|7431|9127|191.08|265.01|38.89|34.44|12.92|
|3|2583|2873|138.16|172.59|18.70|16.65|12.31|
|4|2644|2760|296.51|368.28|8.92|7.49|18.99|
|_5_|6265|6787|479.84|719.92|13.06|9.43|38.49|
|6|1987|2298|761.84|1400.32|2.61|1.64|58.93|
|7|2824|3802|149.36|214.00|18.91|17.77|6.42|
|8|256|325|63.41|67.59|4.04|4.81|-16.04|
|9|1087|1635|477.79|741.66|<br>2.28|2.20|3.20|
|10|1273|1715|586.55|846.13|<br>2.17|2.03|7.08|
|11|10|13|22.73|<br>20.95|0.44|0.42|4.76|
|12|42|48|22.46|<br>26.97|1.87|1.78|<br>5.06|
|13|594|746|64.50|<br>91.53|9.21|8.15|13.01|
|14|44|58|51.69|<br>83.19|0.85|0.70|22.09|
|15|49|77|15.78|<br>46.73|3.11|1.65|88.46|
|Sum|33548|39593|3768.28|5667.07|8.90|6.99|27.43|
|2. Using P|1WULISHE<br>G|D<br>VIO data||||||
|1|6459|7329|447.90|.594.50|14.42|12.33|<br>16.97|
|2|7431|9127|14.71|263.85|40.23|34.59|16.30|
|3|2583|2873|136.79|169.03|18.88|17.00|11.10|
|4|2644|2760|283.99|368.64|9.31|7.49|24.35|
|_5_|6265|6787|451.95|661.83|13.86|10.25|<br>35.18|
|6|1987|2298|768.28|1390.66|2.59|1.65|56.51|
|7|2824|3802|101.09|159.09|27.94|23.90|16.89|
|8|256|325|67.S6|<br>69.88|3.79|4.65|-18.53|
|9|1087|1635|493.22|746.11|2.20|2.19|0.57|
|10|1273|1715|610.92|859.30|2.08|2.00|4.41|
|11|10|13|20.47|31.71|0.49|0.41|19.16|
|12|42|48|21.88|26.74|1.92|1.80|6.94|
|13|594|746|120.38|83.69|4.93|8.91|-44.64|
|<br>14|<br>44|<br>_58_|0.00|83.65||0.69||
|_15_|49|77|82.28|148.08|0.60|0.52|14.53|
|Sum|33548|39593|3791.42|5656.76|8.85|7.00|26.42|

Note: 'published GVIO for 1S branches is from DEFLATE.wkl. Derived GVIO daa comes<sup>from collpeing</sup> 40-branch GVIO figure implicit in th eergy and energy/GVIO figur. into 15 bmnch.s following the algorithm contained in workshoot DATA86.wkl, omitting ub-branch adjuatmets for which no data are available. *Yi yuan - 100,000,000 Yuan.
_38 How_ **_Fast HMs_** _Chiir_ **_Indamuyr_** _Grown.?_

# TABLI 14: TRIAL CALCULATION OFZNERGY CONSUWrnON AND PRODUCTITY FOR COLLCTm INDUSTRY (INCLUDING NON-INDEPENDENT UNITS AND "OTHER"OwNERmu FORMS) 1980 AND 1955

# 1. Using DERIVED GVIO figur.

||_FAwvy_c|ons.|De<br>OVIO|rived<br> Yi P80|Ton utd co|al per|%RiPe|
|---|---|---|---|---|---|---|---|
|Bralch|<br>lOOCK**t**<br>s d|coal<br>|1980|1985|<br>10000 yuan|<br>OVIO<br>|GVIO/E<br>|
||1980|1985|||1980|1955|1980/85|
|1|1325|1477|26.46|71.86|50.07|20.55|143.60|
|2|_-5556_|-6616|-1.92|7.74|2893.17<br>|_-854.85_|-438.44|
|3|13|392|21.62|35.83|0.60|10.94|-94.50|
|4|-224|-260|-6.44|48.11|34.79|_-S.40_|<br>-743.73|
|_5_|2129|2311|85.24|206.78|24.98|11.18|123.50|
|6|1663|1925|359.93|834.78|4.62|2.31|100.36|
|7|1441|2519|46.44|136.61|31.03|18.44|68.28|
|8|134|131|42.11|_65.50_|3.18|2.00|59.09|
|9|391|509|-365.47|-528.49|-1.07|-0.96|11.08|
|10|719|963|25.68|105.71|28.00|9.11|207.36|
|11|41|48|704.80|819.81|0.06|0.06|-0.65|
|12|46|_S6_|<br>106.21|172.11|0.43|0.33|33.11|
|13|300|434|-12.87|-15.07|.23.3|-28.81|-19.06|
|14|-14|66|-25.56|24.86|0.!'|2.66|-79.37|
|_15_|1254|1738|152.40|262.81|8.23|6.61|24.43|
|Sum|3662|5693|977.23|2295.72|3.7S|2.48|_51.11_|
||Pu|blishe O|VIO|PFre|nt Difference|||
|Branch|Y|i Yuan,|**P80**|(Dei|ved-publshed|||
|||||**As**per|c<br>of Derived|||
||1980||1985|1980|1985|||
|1|22.51||62.90|.14.93|-12.46|||
|2|1.65||4.44|-155.92|-42.63|||
|3|18.69||35.66|-13.56|-0.47|||
|4|1.23||3.18|-119.10|-93.39|||
|5|103.39||237.98.|21.30|15.09|||
|6|313.54||725.86|-12.89|-13.05|||
|7|79.92||163.08|72.09|19.38|||
|8|26.18||52.71|-37.84|-19.53|||
|9|35.6||108.00|-109.74|-120.44|||
|10|96.5||354.55|275.79|235.40|||
|11|100.33||154.50|-85.69|-81.15|||
|12|28.26||4S.32|-73.39|-73.67|||
|13|51.44||52.88|-499.77|-450.9|8||
|14|9.84||36.33|-138.49|247.30|||
|_I5_|71.41||87.86|-53.14|-66.57|||
|Sum|960.99||2175.25|-1.66|_-5.25_|||

Note: published **COB** OVIO we from DEPLATE.wkl.

<!-- Start of picture text --> (cmmd<br><!-- End of picture text -->
_How Fan HE Oshna ladwauy Groww? 39_

# TABLE 14: TRuAL **CALcuLATiON** OF zNzRGY **CONSUWnON ANUD PRoDucTIVIY FOR COLLECTIVE** INDUSTRY (INCLUDING NON-INDEPENDENT UNITS AND "OTMERN OwNERsH FORUS) 1980 AND 1985 (continuaton)

# 2. Using Pubbshed GVIO Figures

|Branch|Energy<br>10000<br>1980|Cons.<br>t<br>atd coal<br>1985|OVIO<br>1980|Yi P80<br>1985|Ton**st**<br>10000y<br>1980|**d**coal per<br>uffGVIO<br>1985|%Rise<br>GVIO/E<br>1980/85|
|---|---|---|---|---|---|---|---|
|1|1325|1477|22.51|62.90|_58.85_|23.48|150.62|
|2|_-5S56_|-6616|1.65|4.44|-3372.19|-1490.09|126.31|
|3|13|392|18.69|35.66|0.70|10.99|-93.67|
|4|-224|-260|1.23|3.18|-182.11|-81.76|122.74|
|5|2129|2311|103.39|238.08|20.59|9.71|112.14|
|6|1663|1925|313.5'|723.80|5.30|2.66|99.42|
|7|1441|2519|79.93|163.08|18.03|15.45|16.72|
|8|134|131|26.18|48.48|5.12|2.70|89.39|
|9|391|509|3S.60|108.00|10.93|4.71|133.03|
|10|719|963|96.50|354.55|7.45|2.72|174.33|
|11|41|48|100.83|_154.S0_|0.41|0.31|30.88|
|12|46|56|28.26|45.32|1.63|1.24|31.71|
|13|300|434|51.44|21.99|5.83|19.74|-70.45|
|14|-14|66|9.84|111.53|-1.42|0.59|-340.43|
|15|12S4|1738|71.41|99.74|17.56|17.43|0.78|
|Sum|3662|5693|961.01|2175.25|3.81|2.62|45.60|
_40 How_ **_Fdw ha,_** _as.u. Indumy Gam"?_

# TABLJ 15: PzatCzNT CHANCE _iN_ JNDUIIRIAL ENzaGY IRoDucTTY roFO 15 BUSNcuS, 1980/85

||ToWl|Stale|Collective+|
|---|---|---|---|
|1|23.53|16.97|150.62|
|2|7.S0|16.30|126.31|
|3|4.67|11.10|-93.67|
|4|26.19|24.35|122.74|
|s|49.S1|35.18|112.14|
|6|68.93|56.51|99.42|
|7|20.09|16.89|16.72|
|a|7.98|-18.53|89.39|
|9|11.34|0.57|133.03|
|10|27.63|4.41|174.33|
|11|28.34|19.16|30.88|
|12|21.60|6.94|31.71|
|_13_|-53.40|-44.64|-70.45|
|14|379.90|n.a.*|-340.43|
|15|15.76|14.53|0.78|
|Totl|35.41|26.42|45.60|

Souem: Table 11, 12, and 13. Baund on calculatins **using** publishe raher than derived daft for brmach OVIO. *Branches 13 and 14 should be meged in **a** revinsd ca1ulatio underlying outt dat for thee two bncls ame jumbled.
_How Fa Ns OuLw hdmty Oro_ _41_

# TABL 16: DATA ON **_wENGY SAVYNGSo, 1980)J35_**

# 1. Industry Above the **Ville** Level, _1S_ BraOch.

||EnergyUe<br>10,000<br>St.<br>|in 19t5<br>Tos<br>Coal<br>||Enegy<br>10000l|**Savinp**<br>pero"|
|---|---|---|---|---|---|
|bruach|1980<br>Relaios<br>|Acoal<br>B|***Svinge**<br>(A.B)/B||of tow|
||**A**|||||
|1<br>|10878<br>|8806|0.235|2072|16.01|
|2<br>|2699<br>|2511<br>|0.075<br>|**188**<br>|1.46<br>|
|3<br>|3418<br>|3265|0.047|153|1.18|
|4<br>|31SS<br>|2500|0.262|655|S.06|
|5<br>|13602<br>|9091|0.495|4504|34.51|
|6<br>|7134<br>|4223<br>|0.689|2911|22.50|
|7|7591<br>|6321|0.201|1270|9.81|
|a<br>|492<br>|456|0.080|36|0.28|
|9<br>|2387<br>|2144<br>|0.113<br>|243|1.83|
|10<br>|3418<br>|2678<br>|0.276<br>|740|5.72|
|11<br>|78<br>|61|0.283|17|0.13|
|12<br>|126<br>|104<br>|0.216<br>|22<br>|0.17|
|13<br>|5S0<br>|1180|40.534|630|4.47|
|14<br>|595|124|3.799|471|3.64|
|15<br>|2101<br>|1115<br>|0.151<br>|286|2.21|
|total|58225|45286|0.256|12939|100.00|
|Excluding||||||
|MB&CHEM|37489|31965|0.173|5524|42.69|

2. Sta Sector idespndat Aooxm*ing Units, 40 bunches

|1|2849|2543|0.120|306|4.09|
|---|---|---|---|---|---|
|2|1333|1147|0.162|156|2.48|
|3<br>|61|62|-0.017|-1|.0.01|
|4|147|116|0.270|31|0.42|
|S|79|76|0.043|3|0.04|
|6|120|132|4.087|-12|.0.15|
|7|0|0|639.000|0|0.00|
|I<br>|150|183|4.110|-33|.0.44|
|9|67|**65**|0.031|2|0.03|
|10|1067|1120|.0.047|_-53_|.0.70|

(-4""
_42 How_ **_Fast Has Ch*ne ?sdauy Groins?_**

# TABLE 16: DATA ON "ENERGY SAVINGS,. 1980-198S (continualioa)

# 2. Stae Sector Idependent Accounting Units, 40 banches

||Energy Us<br>|e in 1985<br>||Energy|Savings|
|---|---|---|---|---|---|
||10,00|Tonb||||
||Sd.<br>|Coal<br>||100001|porcmi|
|branch|1980<br>Relations<br>|Actu<br>B|*Saving<br>(A-B)/B||of total|
||A|||||
|11<br>|546|447|0.222|99|1.33|
|12<br>|64<br>|68|-0.054|-4|40.05|
|13<br>|16<br>|5<br>|2.240<br>|11<br>|0.15|
|14<br>|1298<br>|1234|0.052|64|0.86|
|1S<br>|14<br>|13<br>|0.073|1|0.01|
|16<br>|50<br>|48<br>|0.042<br>|2<br>|0.03<br>|
|17<br>|111<br>|132<br>|-0.157|-21|40.28|
|i8<br>|12<br>|10<br>|0.238<br>|2|0.03|
|19<br>|832<br>|746<br>|0.115<br>|86|_1.15_|
|20<br>|43|36|0.190|7|0.09|
|21<br>|17<br>|13<br>|0.277|4|0.05|
|2<br>|13<br>|9<br>|0.424<br>|4|0.05|
|23|10261|9127|0.124|1134|15.17|
|24<br>|1957<br>|1613<br>|0.213|344|4.60|
|25|366|330|0.109|36|0.48|
|26|8136|6211|0.310|1925|25.74|
|27<br>|_475_<br>|322<br>|0.474|153|2.04|
|28|875|481|0.819|394|5.27|
|29<br>|232<br>|195|0.192|37|_0.50_|
|30<br>|69<br>|**59**<br>|0.168<br>|10|0.13|
|31<br>|3980<br>|3594<br>|0.107|386|5.16|
|32<br>|7450<br>|6397<br>|0.165|1053|14.08|
|33<br>|852|754|0.131|98|1.32|
|34<br>|187<br>|154<br>|0.214|33|0.44|
|35<br>|2017<br>|1343<br>|0.502|674|9.02|
|36<br>|_656_|435|0.508|221|2.95|
|37|336|224|0.498|112|1.49|
|38<br>|259<br>|99|1.619|160|2.14|
|39|62|43|0.441|19|0.25|
|40<br>|11<br>|7<br>|0.509|4|0.05|
|TOTAL|47070|39593|0.189|7477|100.00|
|SUM**Less**||||||
|MB&Chem|34642|30508|0.135|4134|55.3|