how good are india%27s industrial statistics

8/8/2019 How Good Are India%27s Industrial Statistics

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H o w G o o d A r e I n d i a ' s Industrial Statistics?An ExploratoryNoteR Nagaraj

There is a growing perception of a steady deterioration of the quality of India's industrial statistics. Isthis perception justified? To find out, this study examines the quality of the Index of Industrial Production,and some aspects of the Annual Survey of Industries, and the National Accounts Statistics. The study alsoexamines if (a) the popularly used financial indicators really reflect the underlying investment trends, and(b) the expected association between electricity consumption and industrial output holds. Though exploratory,the findings reported seem to support the growing perception.

ACCURATE and up to date industrialstatistics are essential for policy, be itpublic or corporate, n anera of economic'planning' or'reforms'. There is agrowingperception that the quality of India'sindustrial statistics has deteriorated overthe years. This exploratory note seeks tofind out if such aperception has anybasis,with respect to some of the widely usedindustrial statistics.Section I. examines the quality of theIndex of IndustrialProduction (IIP)- themost widely used leadingoutputindicator.Development finance institutions'disbursements of long-term credit, andmobilisation of capital n theprimary tockmarket rewidelyused to forecastcorporateinvestment activity. How useful these areto predictdomestic fixed capitalformationis examined in Section II. In a modernindustrial economy, there is expected tobe a close technical relationship betweenelectricity consumption and manu-facturingoutput.Does such a relationshiphold in the Indiancontext, we find out inSection III. With the rapid growth of theunorganised manufacturing, there is awidespread belief that the value added inthis sector is significantly underestimated.Section IV provides some indication ofthis tendency. Section V discusses someevidence of growing problems with theAnnual Survey of Industries (ASI).Section VI concludes by summarising themain findings of the study.The questions asked are, how reliableare these leading (and lagging) indicatorsof manufacturingoutput andinvestment?Do theyaccuratelyandconsistently reflectthe underlying trends, given that theproduction and the organisational struc-turesarebecoming increasingly complex?

Index of Industrial ProductionIndex of industrial production (IIP)-available monthly, with the least time lag- is one of the most widely used leadingindicators of industrial production.National Accounts Statistics (NAS)

contains annual value added and capital

I;'rmationestimates, with over one-yearlag, separately for the registered and un-registered manufacturing. Disaggregatedvalue added estimates for two-digitindustry groups are available with overtwo-year time lag. The NAS is the onlysource of estimates for the unregisteredmanufacturing value added and invest-ment. The ASI Summary Results of theFactory Sector that provide the dis-aggragateddata - at three-digit level andby states - are available with a lag of atleast three years.1Manufacturing sector constitutes overfour-fifths of the IIP's weightage. theremaining being mining and electricitysectors. The index is available for 18 two-digit industry groups; and for five use-based, three input-based and two sector-based categories [RBI 1986]. Source ofthe primarydata for estimating the indexis voluntary reporting of monthly outputby firms with equipment investment ofover Rs 20 lakh in 1980. However, sinceinsome industriessmall-scale sectordomi-nates, they arealso reportedly ncluded inthe index.Last year, after agap of over a decade,a revised IIP was introduced with1993-94 as the base year. Reportedly,tle number of items included in the1993-94 series is substantially larger,andil is intended to include even more itemsfrom the small sector as and when databecome available.2 Does therevised indexreallyrepresentanimprovement'? n otherwords, is it better at reflecting the under-lying productiontrends?We contend thatil probably s not,for hefollowing reasons.Periodic revision of any index numbersis desirable to account for the changes inthe composition of the basket of goodsthat they represent. During the 13 yearssince the lastrevision, the industrialoutputhasgrown annuallyat over 8 percent, andwith considerable changes in its com-position. Therefore, the IIP's revision iswelcome, to the extent the new indexbetter captures the changes in the outputcomposition. Infact, this has beenaroutinematter with the official agencies as the

index has been revisedfive times since1950. roughlyonce a decade.However,the otherproblemremains.The inadequateand poorqualityof theprimary production data used forestimating heindex is perhaps ar moresignificant.Unfortunately, he revisiondoes little to correctit. Reportedly,18official agenciessupply heprimary atafor estimatingthe index, though mostimportant f them all is the Departmentof Industrial olicyandPromotionearlierDGTD)thatprovidesdata on the manu-facturingsector.Development Commissioner, SmallScale Industries(DCSSI) is reportedlyresponsibleorsupplyingdataor 18 temsof thissector.However, hisagency eemsto be unable o do so. To quotethepressrelease issuedto notify the new IP, "Intheabsenceofregularmonthly roductiondata rom heunorganisedector, he tembasket has been identified on the basis ofdata from the registered sector only.Further,he sourceagency DCSSI) ouldnot line up the productiondatafor theitemsof the revised eries" p5, emphasisadded).3Evidently,the index does notcaptureheunregisteredmanufacturingtall - contraryo the officialclaimand tsendorsement by many commentators[Pradhan nd Saluja 1998b].On the face of it, there arereasonstobelievethat hequalityof theprimaryatahas deteriorated ver the decades. In aregime of industrial licensing, firmsconceivablyhadan interestnvoluntarilyreporting heir output;and the officialagency perhapshad some administrativepowers to ensure compliance.In otherwords,sincethedatagenerationprocesswasaby-productf theregulatoryegime,the ndexwasperhapsmore epresentativeof the underlyingproduction rends.However,since the mid-1980s- andespecially since 1991 - with a steadydecline and deregulationof outputandinvestment controls, firms have littleincentive to reporttheir output to theofficial agency.4Moreover. heofficialshave little leverage o enforceanyrule n

350 Economic and Political Weekly February6, 1999Economic and Political Weekly, Vol. 34, No. 6 (Feb. 6-12, 1999), pp. 350-355


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this regard. So, it is likely that non-reportinghasgone up,and the index couldhave become increasingly unrepre-sentative.To test this proposition, we computesimple correlation coefficient of annualgrowthrates of the IIPandtheNAS series.This assumes that the NAS series - thatis, in turn, based on the ASI data (exceptfor the most recent two years) - is a moreaccurate representationof the underlyingproduction trends. First, the correlationcoefficients are estimated between thegrowthratesof the IIPand(i) theregisteredand (ii) the total manufacturing.5Thesearedone for two sets of overlapping timeseries data: (i) 1970-71 to 1984-85, and(ii) 1980-81 to 1995-96, corresponding toIIP with base year 1970-71, and IIP withbase year 1980-81, respectively.Table 1 shows that for Period-I, the HPgrowth rate is statistically significantlycorrelated with both the registered andtotal manufacturing growth rates.However, for Period-II, the correlationcoefficient between the IIP and theregisteredmanufacturings notstatisticallysignificant. Further, f we restrictthe timeseries in Period-II up to 1990-91, thenthere is no statistically significantcorrelation between the IIP and eitherregistered or total manufacturing. If wetake shorter time-periods, then theassociationbecomes perverse,asillustratedin Table 2, wherein Period-II is dividedinto threesub-periods. Therefore, thereissome basis to believe that increasingly theIIP has become unrepresentative of theunderlying output trends. as reflected inthe ASI data.How does the association between theIIP and the ASI look at the disaggregatedlevel'?To findout. we do a similarexercise,by estimating correlation coefficients ofthe growth rates at two-digit industrygroups. The answer is no, as most of thecorrelationcoefficients arenotstatisticallysignificant and, there is no systematicpattern to those that are statisticallysignificant (Tables 3 (a) and (b)). There-fore. it is reasonable to infer that neitherin the period of licensing (1971-85), norin the regime of deregulation (1981-95)was the IIPan accuratepredictorof valueadded at two-digit industry level.To summarise the findings of thissection:(1) For the period 1971-72 to 1985-86(Period-I), growth rates of IIP for manu-facturing is highly correlated with thoseof (the registered and total) manufac-turingvalue added.However, this associa-tion turned statistically insignificantduring 1980-81 to 1995-96 (Period-II).The associations weaken further and

turn perverse for sub-periods since1980-81.(2) At two-digit industry groups, duringboththesub-periods, here snostatisticallyvalid association between thegrowthratesof the IIP and (the registered and total)manufacturing value added.From these, one can reasonably inferthat the IIP never accurately predictedmanufacturinggrowth ratesata disaggre-gated level. Though forthemanufacturingsector as a whole the IIPcould have beenwell used as a lead indicatorfor the 1970s,it cannot be used to predictmanufacturingvalue added in a period of deregulation(in the 1980s and beyond).Clearly, the IIP hasdeterioratedover thelast two decades. This is mainly becausetheprimarydatathat s used forcomputingtheindex has become poorer nqualityandprobably scarcer in quantity. The recentofficial press note in fact admits it: "Forthe registered sector... the quality ofproduction data supplied by the majorsource agencies suffer from substantialnon-responseon thepartof manufacturingunits andconsequentialestimationresortedto bythesource agencies.... Theindustrialgrowth based on the revised IIP do nottherefore, seeni to reflect the perceivedground realities" (p 5, emphasis added).Therefore, no amount of updating andrefining the IIP's weighting diagram cancompensate for lack of reliable primarydata that are used for computing it.Evidently, theofficial agency is well awareof the problem. To quote the press releaseonce again,"Inordertoimprovethequalityof production data, the Department ofStatistics is having regular nteractionwiththesourceagencies toimprovetheirsystemof data collection and estimation pro-cedures. It is expected that the quality ofdata will improve in the near future".Howwill 'regular interactions' ensure betterdata collection? They probably will not,unless the firms face a credible incentive(and a threat) to supply the data.6

IIFinancial Data and Trendsin Fixed Investment

Development finance institutions'(DFIs) sanctions and disbursements oflong-termcredithave been widely used as

lead indicators of privatecorporate nvest-ment. This is based on Samuel Paul andRangarajan' (1973) short-term orecastingmodel thathas been regularlyupdatedforover two decades now.7 Does the flow oflong-termcreditreally predictfixed capitalformation in the private corporatesector?To test the proposition, we computedsimple correlationcoefficient between theannualgrowthrates of fixed capitalforma-tion inprivatecorporatesector (NAS data)and disbursementof long-termcredit(bothin nominal terms) for the period 1965-66to 1995-96. Since fixed capital formationis likely to spill over into more than oneyear,we havealso estimated the correlationcoefficient with one year lag. Table 4shows that for none of the time-periodsis there astatisticallysignificantcorrelation

TABLE 2: COMPARISONOFTHE ASI AND IIPGROWTHRATES OVER THREESUB-PERIODS

Average Total Registered IIPof Years Manufacturing Manufacturing1981-85 6.2 7.7 5.71986-91 7.5 7.5 8.91992-96 6.6 7.1 6.41981-96 8.8 7.5 7.2Source. NAS, various issues: Econom,ic andPolitical Weekly,Vol 29. No 29, July19-25, 1997.

TABLE(a): SIMPLEORRELATIONOEFFICIENTSBETWEENTHEANNUAL GROWTH RATES OF THE IIP

AND THE NAS VALUE ADDED SERIES. AT 152-DIGIT INDUSTRYGROUPS

AverageGrowth Registered TotalRate for Years Manufacturing Manufacturing1971-72/1974-75 0.168 0.480*1975-76/1979-80 0.349 0.433*1980-81/1984-85 -0.437 -0.2301970-71/1984-85 0.176 0.100Source: Same as in Table 2.

TABLE 3 (b): SIMPLE CORRELATIONCOEFFICIENTSBETWEENTHEANNUAL GROWTHRATES OFTHE IIP

AND THE NAS VALUE ADDED SERIES, FOR 152-DIGIT INDUSTRYGROUPS

AverageGrowth Registered TotalRate forYears Manufacturing Manufacturing1980-81/1984-85 0.128 -) 0.170*1985-86/1990-91 (-)0.223 0.694*1991-92/1994-95 0.450* (-)0.2781980-81/1994-95 (-)0.241 0.430Source: Same as in Table 2.

TABLE 1: SIMPLECORRELATIONCOEFFICIENTS ETWEENANNUAL GROWTHRATES OF IIP AND NASMANUFACTURINGVALUE ADDED.

CorrelationCoefficient between PeriodI PeriodII Period IIIIPand NAS (1970-71/1984-85) (1981-82/1995-96) (1981-82/1990-91)(1) (2) (3)Registeredmanufacturing 0.741* 0.440 (-) 0.403Total manufacturing 0.701* 0.706* (-) 0.007? Statisticallysignificantat 5 percent confidence interval,in a two-tailed test.Sour-ce:NASandEconomicSurvey,variousissues.

Economic and Political Weekly February6, 1999 351


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between the DFIs disbursement andcorporatefixed investment.However,during he periodof industrialicensing(1995-80) the correlation s valid withone-year ag.But this ceases to be so inthe period of deregulation(1981-96),suggesting hatwhile long-term endingcould havebeenused as a leadindicatorin a periodof investment icensing, itcannotbe used in the liberalised egime.Theabsenceof the associationn recentyearss widelybelieved o bedue toDFIs'growingpractice f 'evergreening':oansdisbursedodefaultershatareoften usedto repayold debts. As the dataon dis-bursements et of ever greeningarenotpubliclyavailable, hewidelyheld beliefcannotbe tested.

Similarly,nrecentyears, apitalraisedby initialpublicofferingin the primarystockmarkets alsowidelyused opredictcorporatenvestment rends n the shortto medium erm.Thismeasure oo has anintuitive ppeal.But sitempiricallyalid?Table5 shows hat heseresults re imilarto the above findings:In the regimeofindustrialicensing1962-80), otal apitalraised in the primarystock market ispositive and statistically significantlycorrelated ith orporateixed nvestment.This is true even with one-year ag. Butthe relationshipeases to exist since the1980-81.Therefore,n thepresentontext,theprimarytockmarketmobilisation aslittle elationocorporateixed nvestment.

IIIElectricity Consumption andIndustrial Output

Sincealmostallmodernmanufacturingindustries seelectricity s motivepower,and since there is a broad technicalrelationship etweenelectricityuse andvalue added,growthin electricitycon-sumption,n principle,can be used as aproxyfor industrialoutput growth.Totest hisproposition,we estimated implecorrelation oefficients betweenannualgrowth rates of industrialoutput andelectricity onsumption Table6). Noneof thesecorrelationoefficientsarestati-stically significant, though all of themhave heexpectedpositivesign.Since,inprinciple,here s atechnicalrelationshipbetween the two variables, lack ofcorrelation uggestsincorrectrecordingof inputsandoutput.

IVUnderestimation of UnregisteredManufacturing OutputOvera long period, here s a positiveand statistically significant correlationbetween hegrowth atesof theregistered

and the unregistered manufacturingvalueadded that are reported in the NAS.Therefore,one maybelieve that thegrowthrates of unregisteredsector arereasonablysatisfactory, despite some widely knownoutput underestimation (of level of valueadded) in this sector.8 However, carefulmicro studies haverepeatedlyhintedat thegrowing manufacturing activity in un-registered sector that escapes the officialestimation. While such a criticism has anintuitive appeal, it has been difficult tosubstantiate it in the aggregate. We nowprovide some evidence that seems to lendcredence to the widely held suspicion.Between 1977-78 and1993-94, whiletheunregisteredmanufacturing ector's sharein total manufacturing value added dec-lined by 4 per cent, its share in totalmanufacturingemployment hasincreasedby5.1 percent (Figure 1).9These changescan be reconciled only under the assum-ption that the growth rate of value addedper worker (labour productivity) in un-registeredmanufacturing as beengrowingslower than that in registered manu-facturing.10Since value added nunregisteredsectoris a productof (i) numberof workers and

(ii) benchmark estimates of value addedper worker, the underestimation could bebecause of either variable. A preliminaryscrutiny ruled out underestimation ofnumber of workers, as they seem to bebased on decennial census and the NSSestimates. Since the estimates of valueadded per worker are allegedly outdated,this possibly accounts for the under-estimation of value added.This seems tobeborneoutbythe exercisereportedhere,examiningtherelativemove-ments in the growth in value added perworker, and fixed capital stock perworkerduring 1981-91 in the registered and un-registered manufacturing sectors. It wasfound that for 100 units increase in fixedcapital per worker in registered manufac-turing, value added per worker increasedby 156 units. However, in unregisteredmanufacturing, hecorresponding ncreasein value added per worker was only 88units. Relatively slower growth of valueadded per worker in unregisteredmanufacturing seems to suggest under-estimation of value added in this sectordue to usage of outdated parameters.The parameters could be outdated (orunder-reported) or thefollowing reasons.

TABLE 4: SIMPLE CORRELATIONCOEFFICIENTBETWEENNOMINALANNUAL GROWTH RATES OF DFIs'DISBURSEMENTAND CORPORATEGFCF

With One-YearLagYears No of Correlation No of CorrelationObservations Coefficient Observations Coefficient1965-66/1979-80 15 0.0 14 0.662*1980-81/1995-96 16 0.0 15 0.1581965-66/1995-96 31 0.0 30 0.540*:'Statisticallysignificantat least I per cent level.Source: RBI Currency and Filnance,and NAS.TABLE 5: SIMPLE CORRELATION ETWEENANNUAL GROWTH RATES OF NOMINALCAPTIAL RAISED IN STOCK

MARKET AND GROSS FIXED CAPITALFORMATION N PRIVATE CORPORATESECTORWith One-YearLagYears No of Correlation No of CorrelationObservations Coefficient Observations Coefficient

1961-62/1979-80 19 0.446* 18 0.424*1980-81/1995-96 16 0.101 15 (-)0.2151961-62/1995-96 35 0.246 34 0.068**Significantat 5 percent level, *** significant at 10 percent level.Source: Same as in Table4.

TABLE6: CORRELATIONOFGROWTHRATES OF ELECTRICITYCONSUMPTIONAND INDUSTRIAl.OUTPUTCorrelationCoefficient between Years No of Coefficient ofObservations Correlation(i) IIPmanufacturingandenergy sales 1981-82/1993-94 13 0.426(ii) Real GDP in regd mfg andenergysales 1981-82/1993-94 13 0.276(iii) Real GDP in total mfg andenergysales 1981-82/1993-94 13 0.284(iv) RealGDPin redmfg andreal valueof fuelused 1973-74/1993-94 20 0.243N'otes: In(i), (ii) and(iii) above, energysales refer to public utilities' sale of electricityto industryin physical quantity. In (iv), it is value of fuel consumed by registered manufacturingindustries as reported n the ASI deflatedby price index for fuel.Source: NAS, ASI, and Public ElectricitySupply:All India Statistics, various issues.

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FIGURE1: UNREGISTEREDMANUFACTURINGSECTOR'SSHARE IN TOTAL MANUFACTURING

EMPLOYMENTAND VALUE ADDED, 90 ......................................................................................................bo 90? 80

7060

1977-78 1983 1987-88 1993-94Year

5] Employment * Value addedFIGURE2: SHARE )F FACTORYSECTOR IN CENSUS

MANUFA(TURING EMPLOYMENT5048~ 46444240 198( 1990

YearFirst, labour productivity could havesignificantly gone up with diffusion ofelectricity as motive power that hasoccurred during the last two decades.Second, unregistered manufacturing haswitnessed a steady growth in fixed capitalformation,thusindicating asteady growthin potential output. Finally, since un-registeredmanufacturing,unlike theregis-tered sector, operates under competitiveconditions (due to low entry barriers), itis reasonableto arguethat investment andemployment growth in this sector wouldhave occurredmainlyunderprivate profit-ability considerations. In other words, onthe face of it, growth in wage employmentand fixed capital formation in this sectoris unlikely to have occurred unless theincrease in labourproductivity more thancompensatedthe cost of capitaland labour.Therefore, we have a reasonable basis toargue that parametersof value added perworker used for unregistered manu-facturingare likely to be underestimated,

FIGURE: NO OFFACTORIESN STEEL NDUSTRYNIC 331)4000 . ............................................................................................................................................35003000250020001500--1000-500

o - F. -, o ,-- O-. . .Cj 00 00 00 00 00 00 00 00 00 ON ON O O0' 0s 0t O O ON 0 0s Oo 0oN O 0sYear

No of Factorieswhich accounts for the growing under-estimation of value added in this sector.

VAnnual Survey of IndustriesInprinciple,all factoriesregisteredundertheFactories Act (undersection 2m(i) and

(ii)) are included in the Annual Survey ofIndustries (ASI). The universe of the ASIis the live registerof factories maintainedby the Chief Inspectorate of Factories ineach state. Therefore, the ASI's coveragecan only be as good as the factories' list.UJnderhe Collection of Statistics Act (andrelated laws), all registered factories areexpected to file an annual return. Everyyear, the CSO conducts a census of allfactoriesemploying 50 workersand above(100 workers and above without usingpower). Sample surveys - covering one-half of all registered factories employingbetween 10 and 50 workers (20 and 100workers without using power) - are con-ducted every year.1How good are these estimates? Re-viewing the methodology, Pradhan andSaluja (1998a) said, "For the organisedmanufacturing industries fairly reliabledata are available annually, but with aconsiderabletime-lag" (p 1270). This viewneeds to be re-examined for three reasons:(i) incomplete coverage of factories,(ii) under-reporting f workers n factoriescovered, especially in small factories, and(iii)under-reportingofvalue added.12Withthe size structure moving towards thesmaller sized factories within the factory

sector and into the unorganised sector.(i) and (ii) are believed to have increasedsignificantly [Nagaraj 1994].To illustrate the extent of non-recordingof factories and changes in them, wecompared the number of factories in ASIin manufacturing with number ofestablishments in manufacturing emplo-ying 10 or more workers in economiccensuses of 1980 and 1990.13 In 1980,number of factories in ASI formed lessthan one-half (48 per cent) of manu-facturing establishments in the census.Even if avarietyof manufacturingestabli-shments are exempt from the FactoriesAct, the fact that over 50 percent of themhave not registered underthe act suggestsa gross extent of under-reporting offactories (Figure2). This is consistent withevidence from many micro level studies.More significantly, the proportion offactories registered under the FactoriesAct fell by 5 per cent, to 43 per cent in1990 suggesting a rapidgrowth of under-reporting of factories.14This finding can be corroborated withother evidence as well. During 1980-90,when registered manufacturing valueadded grew annually at over 8 per cent,with a steady delicensing of investmentand output controls resulting in consi-derable new entry into manufacturingindustries, yearly trend growth in numberof factories was as low as 0.9 per cent.Under-reporting of value added isanother important problem that has beenrepeatedly pointed out by careful studies.Raj(1986) suggested serious underestima-tion of value addedin registeredmanufac-turingdue to growing taxevasion.15 Morerecently, T N Srinivasan (1994) reiteratedthe same point: "... given the incentive forevasion of excise and other taxes, thereare reasons to believe that value addeddata may be biased and the extent of thebias could be varying over time" (p 9).The above mentioned problems ofincreasingly poor coverage and probableunder-reporting of value added can be

TABLE 7: GROWTH IN STEEL INDUSTRY(Averageannual growth rate)

Years Finished Steel Hot Metal Real Gross Value Real Gross(in Physical (in Physical of Production Value AddedUnits) Units) (ASI Series)

(i) 1980-81/1994-95 5.7 5.1(ii) 1985-86/1994-95 5.7 5.6(iii) 1981-82/1994-95 5.4 4.1 5.4(iv) 1985-86/1994-95 6.7 5.9Note: Gross value of outputand gross value added include NIC 330, 331, 332.Source: ASI Sumnmlaryl esults and SAILYearBook,various issues.



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illustrated by the following example ofsteel industry. As shown in Figure 3,numberof factories in 3-digit industry33 1('manufacture of semi-finished iron andsteel products in re-rolling mills, cold-rolling mills and wire drawing mills) hassharply allen from about3,200 till 1988-89to about 1,400 thereafter. On the face ofit, it could be due to a reclassification,to accommodate a change over fromNIC 1971toNIC 1987. But aclose perusalof data did not suggest any. correspon-ding increase in other steel related 3-digitindustry groups. Therefore, we suspectthat enumerationhasbecome incomplete,unlessthere s evidenceof a large-scaleplantclosures.The sharp fall in number of factoriesin this industry is in contrast to otherevidence, mainly from the corporatesector.16 Since mid-1980s, in response todelicensing, there has been considerableexpansion of existing firms, and new entryinto the industry. Moreover, there seemsto have been a change in the productmix in favourof' flat'productsand techno-logical upgradation leading, in principle,to greatervalue addition perunit of output- for example, automobile grade flatproducts of thinner gauge and greaterwidth.

Table 6 shows estimated growth ratesof output from SAIL YearBook, and realgross value of production and grossvalue added using ASI data. Evidently,growth rates reported by different meas-ures areroughlyof same orders of magni-tude. However, given the changes in theindustry since delicensing in mid-1980s,many indications suggest an increasein value added to value of productionratio. Since this is not revealed in thegrowth ratesreportedabove, one suspectsthat value added estimates may be under-estimated.

VISummary and Conclusion

Reliable and up to date statisticalinformation s vital foreconomic decision-making,both atthe micro and at the macrolevel. This exploratorynote tried to assessthe quality of some of the widely usedindustrialstatistics. IIP is the most widelyused leading indicator of outputtrends,asit is available monthly, with least time lag,and with analytically meaningful dis-aggregation. NAS is the only source ofdata for the unregistered manufacturingvalue added and capital formation. ASIprovidesdetailed nformationonregisterednianufacturing.though with considerable

time lag. Long-termcreditby developmentfinance institutions (DFIs) and the initialpublic offerings in the primary capitalmarket are also widely used to predictfixed investment trends in the privatecorporate sector.How reliable are these data sources?Have theirquality deterioratedover time?Thisnotesought toanswerthesequestions,using simple correlation?o.~oefficientmethod to time series of ann'ualgrowthrates. The following are the.main results.(1) Annual growth rates of the IIP formanufacturing and value added in manu-facturing (registered and total) sector arehighly correlated, for the periods1971-85(Period I). But the association turnsstatistically insignificant for 1981-96(period II), and parts thereof. Correlationbetween the IIP and the ASI for cross-section of 2-digit industry groups is notstatistically significant for both the timeperiods. Since the IIP is a lead indicator,it could have been used to predict value-added trends in Period I, that is, duringthe regime of investment and outputlicensing. However, it cannot be used inthe same way in the liberalised regime(Period II). The study supports the viewthatthequality of IIP as deterioratedsincethe 1980s with gradual industrial

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deregulation,s muchof theprimary ataforestimatinghe ndexwasaby-productof the regulatory egime.(2) Widelyused nformationn (i)deve-lopmentinance nstitutions'anctions nddisbursementsftermoansand(ii)capitalraisedn theprimaryapitalmarket s notcorrelated ithfixedcapital ormationntheprivateorporateector ince1980-81.Therefore,hisfinancial nformations apoorpredictorof the real trends in thederegulated egime.(3) In principle, houghthere is a stricttechnical elationship etweenelectricityuse and manufacturingalue added,inreality his associationwas not found toexist in India,This findingquestions hequalityof the recorded nformationonelectricitynput ndvalueadded stimates.(4) During1977-78and 1993-94, whilethe employmentshare of unregisteredsector n totalmanufacturingasgoneup,thecorrespondingalueadded harewentdown.Theseinversemovementscan bereconciled nlyunderheassumptionhatthe abour roductivityrowthnunregis-teredmanufacturings lowerthan hat ntheregisteredector.Acloserexaminationseems ostrengthenhesuspicion hat'theparametersf valueaddedperworker sedin computingoutputcould have beenseriouslyunderestimated.(5)Inrecentimes, heASIseems o under-report umber f factories ndhencevalueaddedeven in a well-organisedndustrylike steel. It, therefore,raises suspicionthat hequality f theASIdata sdecliningin recentyears.Admittedly,esultsof thisexploratoryeffort have yieldedonly bits andpiecesof evidenceon the qualityof the data.Theyneverthelesseem o tellareasonablyconsistentstory:India's industrialdatasystemhasweakened vertheyears,andthereforehe nformationmaynotreliablycapture the underlying real tendencies.Manyof the widelyused indicatorsandpresumedtechnical relationshipshavelittle empirical validity. This findingsupports he popularperceptionof thedeterioratingataquality. f this nferenceiscorrect,hen here s anurgentneedforathoroughre-examination,andrevampingof the statisticalsystem.

Notes[Following heusualdisclaimer, heauthor hanksK V Ramaswamy, M H SuryanarayanaandA Vaidyanathanortheirdetailedcomments andsuggestionson earlierversions of this study.]

I Fora detailedaccount of the strengthsandlimitations of all these sources of data, seePradhanand Saluja (1998a).2 Pradhan nd Saluja(1998b) gives details of

therevision hat heIIPhasrecentlyundergone.3 Brief Note on the Revision of Base Year ofIndexof IndustrialProduction rom 1980-81to 1993-94 (undated).4 In fact, the CSO officials have admittedthis. ToquoteKulashrestha nd Kolli (1995):"After iberalisation, ome of the majorunitsincluding some of the PSUs have not beenfurnishingreturns.Thismakes the estimationprocedure for non-responding units verydifficult in the absence of information onwhether he unit is in existence or closed, oronstrikeoronpartial peration.Government'seffortsto persuade heunits to furnishreturnsnow met with little success. The GOI havesubsequentlyssued a Piess iJote .. reiteratingthe requirement f submission of returnsbythe industrial undertakings to concernedtechnicalagencies. Despitethis, thecoverageof units hasbeen steadilydeclining". (p 125)5 Unless otherwisementioned,all variables nthis paperare in real terms.6 A report n The Timesof India (January16,1999) said, 'TheDepartment f Statistics hasnotreleasedthe industrialproduction iguresfor November 1998 on the groundthat thedataprovidedby thedepartment f industrialpolicy and promotion(DIPP) on manufac-turingsector 'suffers from lackof quality' ...'Despite repeatedefforts, the DIPP ... hasnot furnished he information egardingtem-wise response rate as well as the methodof estimation or non-response'Mr Asthana[Secretaryin the departmentof Statistics]said (p 17).7 Till 1982, Rangarajah'sorecastof corporateinvestmentwasreportedn theEconomic andPolitical Weekly.In the recent years, thesewere officiallyestimated,andreported n theReserve Bank of India Bulletin.8 There have been many studies on the 'blackeconomy' that in fact looked carefully atspecific unorganisedmanufacturingndustrieslikepower oomweaving, dyestuffs,etc.Mostof them estimate the extent (level) ofunderestimationwithout saying if the blackeconomyis growingfasterthan the measuredeconomic output.9 This method of looking at the relativeemploymentand valueaddedshares to detectoutputunderestimations an old one, widelyused instudying helong term rendbyArthurBurns and Simon Kuznets.10Sources of data forFigure1are,NSS employ-ment and unemployment urveys,and NAS,various issues.I I Foracarefulandfullerdescriptionof the ASI'smethodology, ee Pradhan ndSaluja(1998a).12Growingnon-responseoASI swidelybelievedto be yetanotherreason ordeteriorating ataquality.On a closer examination,we did notfindanystatisticallysignificantdeteriorationin the extent of non-responseover the period1980-81 to1994-95.13These figures refer to all-India, excludingAssam, as the censuses were not conductedin that state.14 This evidence on the growingextent of non-registrationof factories under the factoriesact seems to reinforce indingsof manyfield-work based micro studies [Nagaraj 1989;Singh 1990]. But what is more surprisingas

we discovered during our field-work inBangalore city in mid-1980s, was thatmanymediumsized factories hatwe hadpersonallyvisited were missing from the factories' list.Thoughwe do not havedocumentaryvidenceto supportourcase, we do believe there is acase forexaminingthequalityof thefactories'list maintainedbytheInspectoratefFactories.15 To quote Raj (1986:11), "The number of'registeredfirms', i e, those registeredwithincome tax authorities,has been increasingat a phenomenalrate from about the middleof the 1960s. Manyof themareknownto beused by manufacturing enterprises ascommission agentsforpurchaseof inputsandsale of products, thereby siphoning awayprofits through various forms of transferpricing. Underestimationof value added inthis manner has been therefore probablyincreasing in scale throughthis period".16 After delicensing of steel industryin 1985,there was considerable new entry into theindustryas evident fromcapitalmobilisedinthe primary stock market and term loansgrantedby developmentfinance institutionsOf the 48 listed 'mini steel' companies istedin Bombay Stock Exchange in 1997, halfentered the industryafter 1985. Fordetailedstatisticalinformation,see the annualreportof the Departmentof Steel, 1997-98.

ReferencesAhluwalia,IsherJudge 1985):IndustrialGrowthin India: Stagnation since the Mid-1960s,Oxford University Press, Delhi.Kulashreshtha,A C and Ramnesh,Kohli (1995):

'Impactof Liberalisation n DataCollection',TheJournal of Incomeand WealtlhVol 17.No 2, July.Nagaraj, R (1989): Sub-Contractingin Manu-facturing Industries: The BlangacloreEx-perience,PhDthesis(Centre orDevelopmentStudies, Thiruvananthapuram,JawaharlalNehru University, New Delhi.- (1994): 'Employment and Wages inManufacturingndustries: rends,Hypothesisand Evidence', Economic and PoliticalWeekly,Vol 29, No 4, January22.Paul, Samuel and C Rangarajan 1974): Short-Term Investment Forecasting, Macmillan,Delhi.

Pradhan,Basanta K and M R Saluja (1998a):'Industrial Statistics in India: Sources,Limitationsand Data Gaps', Economic andPolitical Weekly,Vol 33, No 21, May 23.- (1998b):'RevisedIndexof Industrial roduction:A Note', Economic ciandPolitical Weekly,Vol 33, No 28, July 11.Reserve Bank of IndiaBulletin (1986): 'IndexNumbersof IndustrialProduction Revisionof Weights',Reserve Bankof IndiaBulletin.Vol 40, No 10, October.

Singh, Manjit(1990): The Political EconomyofUnorganisedIndustry:AStudl)of the LabourProcess, Sage India, Delhi.Raj, K N (1986): New Economic Policy, V TKrishnamachariMemorial Lecture. OxfordUniversity Press, Delhi.Srinivasan,T N (1994): 'DataBase forDevelop-ment Analysis: An Overview', Journal ofDevelopmentEconomics, Vol 44.


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