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Productivity and cost competitiveness of Canadian food and beverage manufacturing industries Feeley, David John 1992

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PRODUCTIVITY AND COST COMPETITIVENESS OF CANADIANFOOD AND BEVERAGE MANUFACTURING INDUSTRIESbyDAVID JOHN FEELEYB.Sc.(Agr.), The University of British Columbia, 1986A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF SCIENCEinTHE FACULTY OF GRADUATE STUDY(Department of Agricultural Economics)We accept this thesis as conforming___to the required standardTHE UNIVERSITY OF BRITISH COLUMBIAOctober, 1992© David John FeeleyIn presenting this thesis in partial fulfilment of the requirements for an advanceddegree at the University of British Columbia, I agree that the Library shall make itfreely available for reference and study. I further agree that permission for extensivecopying of this thesis for scholarly purposes may be granted by the head of mydepartment or by his or her representatives. It is understood that copying orpublication of this thesis for financial gain shall not be allowed without my writtenpermission.Department of Agricultural EconomicsThe University of British ColumbiaVancouver, CanadaDate October 15, 1992DE-6 (2/88)iiAbstractThis thesis reports an analysis of the competitive positionof the Canadian food and beverage industry with respect to theU.S. industry for the year 1986. The main contribution is inproviding measures of Canada/U.S. variable factor productivityfor 38 food processing and beverage industries. It is animprovement over previous work for two reasons. First, theanalysis is conducted at a more disaggregated level thanprevious studies, that is, below the Canadian SIC level.Secondly, in using 1986 data for analysis it is the most up todate productivity study of the industry available.The study uses the index number approach to productivitymeasurement. For each industry, relative Tornqvist priceindexes for commodity outputs and materials, labour, and energyinputs were constructed. These indexes, along with data forindustry shipments and expenditures on materials, labour, andenergy, were then used to develop input and output relativeTornqvist quantity indexes, and hence, measures of relativephysical productivity. Sources of Canadian data were StatisticsCanada publications containing data for 1986 while data for U.S.industries were obtained from the 1987 Census of Manufacturesand 1986 Annual Survey of Manufactures.The results indicate that in 1986 the Canadian industry wasnot well placed with respect to its U.S. counterpart. Onaverage, relative variable factor productivity for each Canadianindustry was estimated to be 7.6 percent lower. Relativelyiiilower Canadian physical productivity was exacerbated byrelatively higher input prices, so that average output costcompetitiveness was 15.5 percent lower in Canada. Average inputcost competitiveness was found to be 4.8 percent lower inCanada. Correlation analysis found no strong evidence of a linkbetween these two measures of cost competitiveness.ivTable of ContentsAbstract iiTable of Contents ivList of Tables viList of Figures viiAcknowledgements viii1. Introduction a.1.1 Problem Statement 11.2 Outline of the Thesis 21.3 An Introduction to Productivity Measurement 31.4 Methods of Productivity Measurement 72. Literature Review: Canada/U.S. Comparisons . . .. 103. Methodology 183.1. Basic Mathematics of ProductivityMeasurement 183.2 Index Number Theory 213.3 The Empirical Model 324. Database and Variable Construction 394.1 Productivity Measurement for the InternationalCross—Sectional Comparison 394.2 Data Sources 434.3 Variable Construction 444.3.1 Disaggregating Canadian ShipmentsData 454.3.2 Constructing the Canadian MaterialsInput Data forDissagregated Industries 464.3.3 Constructing Relative Output PriceIndexes 504.3.4 Calculation of Relative MaterialsInput Price Indexes 514.3.5 Calculating Relative Input PriceIndexes for Labourand Labour Cost Shares 524.3.6 Calculating the Energy Input Dataand Energy Input Price Index . . 574.4 Database 594.4.1 MTLS Database 594.4.2 OUTPUT Database 624.4.3 INDDTA Database 655. Results . .. 67V6. Discussion of the Results. 757. Conclusions. 82References .. 84Appendix A Canada/U.S. Industry Concordance . . .. 87Appendix B An Example of Disaggregating CanadianMaterials Input Data: Slaughterers andMeat Processors (SIC 1011) 89Appendix C Packaging Cost Calculations 94Appendix D Calculation of a Relative Price Index forEnergy 96Appendix E MTLS Database 98Appendix F OUTPUT Database XAppendix G INDDTA Database Xl-I-1-31-31-3)))P)1)P)))))HbbHHHHHHHHHHftCDCD(D(DCDCDCDCD(D(DC_i)HXj0OOO)MHH‘JftH0OD0CDQ1Q’i0o’01flHQ‘-3,)H.CDrftO(-tp)H.HPHct-tYHP)HH-H-rt-H-ct000CDDJH CDHHF)ftH-ctH-’ci-.)ftCDctCtcc-i-.CDH1<WH(tCD<CDH”H-(DOCl)CDOC()O.nt0‘1ijCflCDHHH’,)0D)P)’.Ot5LQOHTjOWOD0dHCDW1-h’)(i.‘ctLjO‘-C‘1‘1c-i-,Hl))QP)•H-HCD•l))•j1ct-OQriCt))HOOCflH0•.CDH,H,•coct-C)<Cl)‘CD0•ct’dH.C’).00’(ri,‘H-frrtHoP)OH(DfrO<H-’WHCflCD1Zc-t-°CDQ.CD(I)ç0‘.Q•WODHCDP)H00ODPictP)XHOd-oftCD•c-t7jOictH-Cl).H0)<P)U)’•H-’<-‘‘c-i-.:Ci)<CDCD-‘‘CD’Hj’HJ1‘1OCDl))0.CDCD.HU)‘<OJH-OWCD’C)Cfl’IDt.0.X‘ftH-HP1CD•CD’•H••rj’1H’0I-U)•••••i’H-•0’c-I-C)c•••••CD••(I)•Cl)Ct)•..•..c—t-.“‘.OOGD—l--—IOOHHU14HOD4()OGD4j1:-IH-HtQU)irtCD0 HH17jHCl)tQo:iC IICDoU)CD U) 0 It fri 0 C 0 HH-H-H1< 0 H H, CD I-I CD 0 CD U)viiiAcknowledgementsI thank my thesis committee, comprised of Tim Haziedine,Rick Barichello and Tae Own, for helpful comments andsuggestions and Kathy Shynkaryk, Gwynne Sykes and RethaGertsmar for word processing assistance. Any remaining errorsare the sole responsibility of the author.11. Introduction1.1 Problem StatementThe productive efficiency of the Canadian food processingindustry will be decisive in determining its ability tocompete with foreign firms in both domestic and foreignmarkets. Recent bilateral reductions in trade barriers underthe Canada—U.S trade agreement will increasingly force theCanadian food processing sector to compete with its U.S.counterpart in the regime of a single North American market.Furthermore, prospective reductions in trade barriers ensuingfrom the current negotiations under the General Agreement onTariffs and Trade (GATT) may increase the exposure of the foodprocessing industries in both Canada and the U.S. tocompetition from the rest of the world.The problem addressed by this thesis is:In terms of productivity, how well positioned is theCanadian food processing industry to cope in a reformedinternational trading environment?The objective of the thesis is to answer this question byestimating relative Canada/U.S. variable factor productivitymeasures for 38 food processing industry sectors for the year1986.This objective is accomplished by calculating andanalysing unit production costs in the Canadian foodprocessing sector, comparing Canadian 4-digit SIC industrieswith their U.S. counterparts. This is performed in three2stages. First, each country’s Census of Manufactures was usedto calculate unit values of commodities produced by eachindustry and unit values of inputs purchased in Canada and theU.S. Secondly, relative productivity measures and measures ofrelative input and output cost competitiveness are estimatedfor each of the 38 industry sectors. No attempt is made toexplain productivity differentials as this study deals onlywith measurement.The main contribution of the thesis is in providingestimates of Canada/U.S variable factor productivity for 38food processing and beverage industries. It is an improvementover previous work for two reasons. First, the analysis isconducted at a more disaggregated level than previous studies,that is, below the Canadian SIC level. Secondly, in using1986 data for analysis it is the most up to date productivitystudy of the industry available, thereby supplying a measureof the competitive position of the Canadian industry shortlybefore the implementation of the Canada-U.S. trade agreement.1.2 Outline of the ThesisThe study is laid out as follows. The remainder of thisintroductory section gives an overview of the theory andpractice of productivity measurement. Section 2 then surveysthe existing empirical literature. Section 3 considers indetail the methodology of productivity measurement and indexnumber theory. Section 4 first discusses the application of3this methodology to the international cross—sectionalcomparison, then explains the database and variableconstruction. The results are reported in Section 5 anddiscussed in Section 6. Finally, conclusions andrecommendations complete the thesis.1.3 An Introduction to Productivity MeasurementIn this section we first define the concept ofproductivity and discuss factors influencing it. Then weintroduce two approaches to productivity measurement; theeconometric approach and the index number approach. Since theeconometric approach is not used in this study, it is coveredonly briefly. Finally, these two approaches to productivitymeasurement are compared and contrasted.Productivity research concentrates on the supply orproduction side of the market to measure and analyse technicaland organizational performance of a given production unitthat is, a firm, a sector, or country. Productivity growth isan indicator of how much more output can be obtained over timeby a production unit from a given set of resources. Thistypically involves the use of time series data. Differences inproductivity levels indicate differing capacities ofproduction units at a point in time. Often this form ofanalysis utilizes cross—section data.While the most elementary definition of productivity isin terms of the rate of output per unit of input, beyond the4single—output single—input case the definition and measurementof productivity becomes more complicated. The multiple-outputmultiple—input case can be analysed through a generalizationof the average productivity concept by comparing an aggregateoutput index to an aggregate input index. These comprehensiveaggregates of inputs and outputs provide the basis forproductivity research concerned with total factorproductivity, when the productivity of all factors ofproduction is being analysed, and variable factorproductivity, when the productivity due to a subset ofproductive factors is calculated.However productivity is defined, its measurement must bebased on a valid representation of the production technology.Production theory provides a means for analysing the factorsthat explain output level changes and differences. Ingeneral, three factors determine the rate of output: thequantities and types of resources utilized in the productionprocess, the efficiency with which these resources areutilized, and the state of technology or type of productionprocess utilized.The influence on measured productivity of each of thesethree factors can be illustrated with a simple single-outputsingle-input example (Capalbo and Antle, 1988). Consider Fig1, where F1(X) and F2(X) are production functions relating thetechnically efficient combinations of input X and output Q fortwo different production processes. Assume that production5function process F1 was used in period 1 and F2 in period 2,with observed outputs Q1 and Q2, respectively1 . We see thatthe average product of factor X, measured by the slope ofrespective rays from the origin, is steeper in period 2 thanin period 1. Therefore, given that productivity is defined inthis case as Q/X, total factor productivity is greater inperiod 2 than in period 1.Three distinct factors have contributed to thisproductivity change. First, there is a difference in thescale of production. This explains the difference betweenand Q2’. Second, a higher total productivity is exhibited byproduction function F2 than for F1, explaining the differencebetween Q21 and Q2. Third, technical inefficiency is indicatedby Q1 lying below F1. Efficient production would have resultedin output Q1 1This example illustrates that the differences in all ofthe scale of production, productive efficiency, and the stateof technology may explain part of the observed differences intotal factor productivity across entities at a point in timeor within an entity over time.1Price inefficiency due to non-optimal choices of input and output bundles,for given factor or output prices, is eliminated in this single input and outputcase. The assumption that profits are maximized, subject to input and outputprices, is maintained throughout the index number/cost function methodology usedin this study.6Fig 1 Sources of Productivity DifferencesO=F(X)FIG 1Source: Capalbo and Antle (1988)F(X)F’(X)a71.4 Methods of Productivity MeasurementTwo basic approaches are available for productivitymeasurement: the econometric approach and the index numberapproach.The econometric approach relies on estimation of eitherthe production technology or the cost function. The relativeefficiency of sectors can be determined through estimating theproduction function subject to a given input bundle. Thesector with the greater output will be the more efficient.Analagously, duality relations provide a means by which toinfer production function shifts from estimates of the dualcost function. With the cost function estimated subject to aparticular set of input prices and output levels, the lowestcost sector will be the most efficient.The accounting or index number method of productivitymeasurement assumes only that the production technology can beapproximated by a second—order function. Since all of theinformation required for the econometric approach is rarelyavailable, this alternate procedure utilizing accountingmethods can extract measures of relative efficiency withoutknowing the complete production technology. The second orderapproximation is appealing mainly because a quadratic functionas the second order approximation allows for a direct linkageto the economic measures of productivity and efficiency, butalso because data limitations are likely to make higher-orderapproximations infeasible.8While the index number and econometric approaches arelinked through production theory, each has its strengths andlimitations. In deriving the index numbers and their relationto production theory, several strong assumptions are madeabout both the technology and the industry being considered.These assumptions include long run competitive equilibrium andconstant returns to scale2Because these assumptions are inappropriate in manycases, the interpretation of the resulting index numbers canbe questioned. Another disadvantage of the index numberapproach is that statistical methods cannot be used toevaluate their reliability. The calculations are not based onstatistical theory. However, index number calculations can beused when econometric methods are infeasible. The problemsassociated with small samples, such as degrees of freedom andstatistical reliability, are not encountered. Very detaileddata with multiple input and output categories can be usedregardless of the number of observations.Some of the assumptions required for index numbers may berelaxed for the econometric approach, but only at the cost ofimposing other assumptions. Assumptions concerning returns toscale are not required for the estimation of an econometric21t is generally accepted that exploitable economies of scale exist amongCanadian food and beverage industries (Dhatiwal, 1990). A labour and capitalscale elasticity of 1.27 was estimated by Baldwin and Gorecki (1986) using theproduction function approach with pooled 1970 and 1979 data applied to 15 4-digitindustries in the Canadian food and beverage sector. Robidoux and Lester (1988),using the cost function approach with 1979 data, found increasing returns toscale in 12 of 18 industries in the food processing sector.9production function such as the translog. In addition,confidence intervals can be constructed about the estimates asthe estimated model has known statistical properties.However, because outputs must be aggregated into a singleindex, an assumption of input-output separability is requiredfor estimation of the translog production function. Also,input data must be aggregated into a small number ofcategories in order to maintain degrees of freedom and toavoid multicollinearity problems. This input aggregationrequires input separability assumptions. The additionalassumptions of competitive pricing and efficient inpututilization are required in order to estimate the cost model.Finally, assumptions relating to statistical properties of thedata must be made.The preceding discussion of productivity and itsmeasurement provides, a groundwork for the next section, wherethe application of both methods of productivity measurementare applied to Canada—U.S. productivity comparisons, as wellas the subsequent section dealing with the study methodology.Ctc2.d—-.—.CtaCt0FlH-HHZ’0CDHH-H)‘.D‘DCDCl)HC)H)0)C0‘1C)C)Cl)CDCD0-FlCl)Cl)pt-—.—1<C)jCl)CDCtClCl)Cl)1JH-CDQ’$1CiCtIFlH-H-dCl)CtH-Cl)Cl)HCt0CDCDCiCDCl)CDHClCD<Cl)CDH-CDCfl;ç’CDCtH-Cl)CiCDHCl’CDCt<CCidCtH-dCtCDCtFlCDH-CDCl)HCl)FlCDHHH-0HQNIIC)-QH-C)<CDFlCnCtClCtCD CDCl)C)H-H-<CDCDCDClCl)CDH-FlHCl)Ci<C)ci)Cl)CDCl))CDCDCDH)H-HH-CDCDcjCt-xFl-drjHCtCDCl0CtCDCtNCl)Cl)HCDCtFlCDCDCDCltiCtHCiFlCD‘rJClH-FlCDCl)CtH)HCl)__ClH-CD0•HC)C)Cl)H)C!)‘<CDCl’ClH-C)CiH-i-’H)000CDCl)0CtHCl)H)CDCl)FlCtCtCDCl)Cl)H-CiCi‘dCtC)dCD0HFlCDCD0CDCl)trtCt Cl) FlH-Fl CDClHCDCl)XCt-3CDHCl<:CDCDCl)CtCD0H CDH-CD<0CD HCDCDH-Cl,0FlH)CDt’tIH-CtCthCl)FlH-Cl)Z’FlCD<CDCDbH-Cl)H CDCtCl) Cl0CtC)00 CiCl)CtClFlH-H-C)CD Cl)CtCl)oCD CtoCDH)1<Cl)Cl) Fl CDFl oCl)Cl)HC)Cl)CD CD(I)CtCtCl)0Cl)H-tICtCl)CDH-CDCtCDCDCD0<CDtICDtICl)FlH-0HHCDCl)Cl)H-CictH-CDCDCl)CDCtCDCiH-CtCl)Cl) rtCDCDCtC)CDH-CDCl00C)FlCHCl)H-H-CiCDHCDCD13’CtCDCDHCDCl)Cl’C)Cl)Cl)Cl)H-HCtCtFlCDFlCl’H-Cl)Cl)H- C)Ci0CDFlHH-CDCDC)CDHHCDCi)HCDCDCDH)C)CtC),H0Cl)tICl)H-0CtCDtIFlH0ClCDH-Ct00CD0tIH-CiCtHCl)C)jHCtCl)CtCl)CDHFlCl)ClCtCDCl’FlH)CtCCDH-C)oC)FlH-CiCtHCDr1CDrtCl)ClCiHtI00CtH-tIH-<tIbrtCl)HCDCD‘<•HF-t.J H Ct CD Fl Cl) Ct Ci CD CD H- CD C-) Cl) Cl) Cl Cl)H‘—S0c U) C) 0 Cl) Fl H Cl) 0 CDC)CD.Q0CDFlC)0CtCl)H-CtII0tI’‘-3Cl)tI’Cl)CDH-HFlHH-CDCl)CtF-’H-Cl)‘-aCloCDH)QCt-CDCiCDCDHCtCDFlF-H-Cl)Cl)CDCDCDHClH-CtoCDCtHtIC)0CtCDClCtCD0Fl‘ICDCiCD<Cl)H-CDCtdFlCDFlFlCl)H-Cl)H-Q0Cl)13’CD•CDFlCD0Cl)oHCD3’CiCD-H-Cl)Cl) CtCDCtClCl’0CiC)ClH-CDFlCDH-CDH-0<CDCl)CDCDtI’FlH)CiH-H-CDCD0dCi0FlCDCt00Ct,FlFlCD<Cl)H-0HCDCtHCl)FlH-H)Ct<0<Ct:3’CDCl)Cl)CDH-CDCl)tIFlCDCttICtCl)ClCDI11U.S. made—imports to Canada is considered exogenous, and withconditions of oligopolistic interdependence fairly widespreadand a weak competition law, Canadian producers price up to thetariff.In spite of imposing strong a priori restrictions, thisapproach is appealing because relative productivity levels canbe calculated using readily available information on Canadianimport tariffs along with Census of Manufactures data on thenominal values of outputs and inputs to ascertain real inputand real output in each industry. That is, no actual pricedata are required.The data intensive approach to productivity research doesnot assume that firms follow a particular set pattern in theirpricing strategies. It requires that data on actual prices becollected and real output indexes constructed.Though this approach relieves the researcher fromdepending on a particular theoretical model, it does , ofcourse, present data related problems. Input and outputs ofan industry must be carefully matched between the twocountries. Because this approach requires considerableresources in the matching procedure, this method has beenrestricted to studies of a relatively few industries. West(1971) and Frank (1977) conducted Canada/U.S.comparisons ofabout 30 industries while Haziedine, Guiton, and Wall (1988)compiled a larger sample of 84 manufacturing industries, for1982.12The relative productivity estimates from three of thesestudies are presented in Table 1. Ratios of Canadian/U.S.labour productivity in terms of real value added for Frank,Gorecki and Baldwin, and Hazledine, Guiton and Wall are shownin the first three columns. From these figures we can seethat:1) Average Canadian productivity is lower relative tothe U.S., with a greater differential for foodprocessing than for total manufacturing.2) The estimates of Baldwin and Gorecki and Hazledine,Guiton, and Wall are similar when averaged acrossthe sixteen food processing industries common toboth studies. The estimates obtained by Frank, froma smaller and older sample, are on averagesignificantly greater than those of the other twostudies.3) A wide range of relative productivity performanceis presented by these studies with littleagreement among them on the productivityperformance of individual industries.Similiar conclusions were drawn by Rao and Lempriere(1990) in their comparisons of labour productivity betweenCanada and several other important industrial economies.Canadian productivity was found to be lower than the U.S. inboth food processing and total manufacturing (Table 2). WhileDC DC CD 1 H CD C) C CF C DC C DC C-’ CC 05 05HHIIH-CDbHC)bct1Ct——11HCDI))X0-.OC))0CDC))11H-HmH800CtHCt°iti‘-QCD00CDClçtC))HU)CCl)H-CClC)H--CHCtC))C))-H)H-t()CDH-bJCl)H-p.,CltH)C0SC))C)Cl)HCt0C))CDiCDC))C)CDH-C))C)CtCnEnHC)HClHCttCtH-H-2.<0Cl)ClC)CCtCC))‘-QC)C<iCD.IIH-iQQ.H-tt50C))0H)jCtH)H-H-C))H-HCtH-CtC))gI._-0<H-‘diC))tS‘<t<C))C/)U)-CD•2TJCtHHp.,Cl)CtClCDCDCDpU)CD0’000H)H)H-2 CC00H‘-oCl:CtCDH‘TjCtCtCDC/)0CClCDt-C))CtCDC))C-0CD,.CCtH-CCD01C)0(H-CtcClCtC)oC))H-C)<C/)CH-0H-CDirtoCtCDCtCCtC)H-0U)H-0CCt0CtC)U)<‘1H)C)0H-I)CtCDJH-CCDHC)))0CD•CtU)CDCDCDCl0<Cl)l)CDC))Cl)H<‘0(0HH-U)•C)C)C,E/)CtCtH-CtCDH-CDC’C)C)’c’‘<0C)H-H01U) Ct<°ii‘tJH-00CDCq-‘ 0C))Ct0CD‘CD0H)H1rJHEl)H-C))CDC)Ct<CtC00U)Ctc’0(0PdIH-CDC):3-CtH)H-HCDClT)’0)0CD0ClCDCtCDCDCt0U)H-HCHCl‘<H-Cl)H-ClC))CDH)HC’CDHC’Cl)CDH-U)C))CDH)Ct0CDCl0HCtCH)bCl1CDCDCDCt0C)<00‘<C.’COCD<.C)ClH-0C-Ct•Pd0CCDjCCCDU)H-H) C))CDU)H-C)U)H-ClH)CD ClC)’01b<Cl)CDU)CDj0Ct0Ct0CDCtClCtCtClCl•0CtCDH-C frtCDH-CC))CDC)‘CH-:3C))C)C)bU):3C)C))CtC))HH)‘CHCt-Ct0CDCDCtH-HCtC))0ClH-C<C)’CDC))0<H)H)0d00t3IICDIICtH-CtCt0ClH-iCC))•C)CtH-bC))CtCD0C))CC))2ZICtH0i‘<H<I-H)Ht-U)9’,‘C)C_,(‘C(((15and Gorecki sampled about 100 4-digit SIC industries observedin 1970 and 1979 using the U.S. as the point of reference forefficiency. They found that among industries which are bothrelatively highly concentrated and highly tariff protected,the relative Canada/U.S. average plant scale tends to belower. Canadian plants were found to suffer from technicalinefficiency. Import penetration and foreign ownership werefound to increase relative efficiency while barriers to trade,such as tariffs, decrease it, though the latter result is notrobust.Hazledine, Guiton, and Wall, using the direct comparisonmethod, do find an effect for the Canadian tariff on relativeCanada/U.S. productivity for 1982, but only in the case ofindustries that share markets with imports. However, theseare not the classic Eastman-Stykolt high concentration import-barring group.Using the theory—intensive approach, Harris and Cox(1984) make use of the Eastman-Stykolt hypothesis in theirstudy of the effect of elimination of the 1976 set of Canadianand foreign tariffs on manufacturing productivity and theallocation of resources. Their results suggest that lowertariffs would reduce domestic prices and force arationalization of Canadian industry that would exploitpotential scale economies.Multilateral tariff elimination was predicted to resultin impressive labour productivity and total factor16productivity increases of 32.6 percent and 9.5 percent,respectively, for the Canadian economy and 36.4 percent and8.2 percent, respectively, for the food and beverage sector.With Canadian import tariffs reduced unilaterally only in thefood and beverage sector, the increases in labour productivityand total factor productivity were projected to be 13.5percent and 4.6 percent, respectively.However, Hazledine (1991) suggests these free trade gainestimates are too large. Though lauding the work of Harrisand Cox as a “significant step forward in the formal modellingof the market processes that generate productivity change”with its focus on imperfect competition , Haziedine takesissue with the lack of empirical evidence for the Eastman—Stykolt hypothesis and micro-theoretical foundations for theform of oligopolistic behaviour, as well as noting thatadvances in the econometrics of cost functions have reducedscale elasticity estimates from those used by Harris and Cox.We conclude this section by summarizing findings whichare common among the studies reviewed. Irrespective of theresearch methodology employed, “data—intensive” or “theory—intensive”, Canadian productivity estimates for foodprocessors were, on average, lower than estimates of U.S.productivity.But these studies are dated and, with dynamic changesexpected in the operating environment of these industries dueto both the Canada-U.S. trade agreement and current GATT17negotiations, a more updated productivity analysis iswarranted. The next section deals with the methodology ofaccomplishing this task.183. MethodologyThis section develops the methodology for the study. Thefirst two subsections review the basic mathematics ofproductivity measurement and index number theory,respectively. The final subsection presents the empiricalmodel used to estimate the relative productivity measures.3.1. Basic Mathematics of Productivity MeasurementThis subsection deals with the fundamental algebra ofproductivity research, following Hazledine (1991).Consider a commodity produced in quantity y1 by an entityi using a single output in quantity x1. We define theproductivity of i as Z1, the ratio of output to input(1) Z1=Z!The relative productivity of i relative to another entityj can now be calculated(2) Z1XZ (1xjThe subscripts i and j could refer to either differententities at the same time or to one entity over a set periodof time.19Consider a commodity produced using more than one inputwith a production function specifying a unique quantity ofoutput for any one input bundle. For illustration, assume theproduction function is Cobb-Douglas (log-linear) with only twoinputs. Then:(3) y1=axI a1,c,13>Owhere a1,a , and B are parameters.Technological change is reflected by changes in theseparameters. Should only the intercept parameter a1 change,the ratio a1 /a will measure the rate of technical progressbetween periods i and j. In this case there is no inclinationto make one input relatively more productive than another andthe change is “neutral”.Only if both constant returns to scale prevails and asingle input is utilized will productivity growth Z1/ZJgiven by equation (2), be the same as technical progress.Non—constant returns to scale with one input (e.g. a = 0)yieldsaZ1 axf’_______z. -‘ l \P-’, axxli20Productivity growth will equal technical progress only ifinput levels are unchanged between i and j. Under any othercircumstances, productivity growth will be composed of bothscale effects and technical progress.Now consider a commodity produced with more than oneproductive input where we are interested only in theproductivity of input 1. If we define this input as labour,then labour productivity becomesI5 — —a1xfxZ——--——— —a1x1 x21x1iand labour productivity growth is(6) Ziixi1)(aZ y1x1)The proportional rate of change of labour productivitycan be calculated as••(X2(7) Z=a÷(+f3—l)x1+13I‘\x1Equation (7) shows that the proportional rate of changeof labour productivity is the sum of three elements: atechnical progress term, a term corresponding to the influenceof economies of scale, and a term which measures the effect on21labour productivity of altering the quantity of the otherinput at each employee’s disposal.In order to measure the contribution of all inputs, werequire an aggregator to assign a unique value to eachdifferent input bundle. Given perfect competition in inputmarkets and constant returns to scale (a + 13 = 1), theelasticities of output with respect to each input will be thesame as the observed shares of each input in total costs. Forthe two—input Cobb—Douglas case these are the exponents a and13. We can define the aggregator as(8) (&+=i)where a and 13 are their observed cost shares of inputs 1 and2. With perfect competition and constant returns to scale,the change in technical progress a1/a will be the same as thechange in total factor productivity, measured analogously toequation (2) but with and instead of x1 and x.3.2 Index Number TheoryThe index number approach involves collecting detailedaccounts of inputs and outputs, aggregating them into inputand output indexes, and using these indexes to calculate aproductivity index. A troublesome problem encountered by22applied economists in constructing data series is the questionof which functional form of index to use. In this section weconsider this issue and relate certain functional forms forindex numbers to functional forms for the underlyingaggregator function.3 We also introduce the concepts of exactand superlative index numbers and Tornqvist approximations toDivisia indexes. Finally, we introduce a general methodologyfor analysing the sources of intertemporal and interspatialdifferences in outputs and costs. This method is based onapplications of Diewert’s (1976) quadratic lemma, and involvesthe analysis of quadratic approximations to the function whichis generating the data.Define a quantity index between two economic entities sand r(9) Q(psprxsxr)as a function of prices in entities s and r, S > O and r >and the corresponding quantity vectors x5 > and r >where°N is an N—dimensional vector of zeroes4. Now define aprice index between entities s and r3Aggregator function is a neutral term which could denote one of either aproduction function or a cost function.4rhese two economic entities could be either one entity analyzed at twodifferent points in time or two separate entities. That is, the analysispresented here is applicable either intertemporally or interspatiatl.y.H-(fli—30CDP’——CDC)H-(fltDClI-’Cl0C))C)’tftCDciftC))ftXHYCDCDi-lH-CDhCDCDCDciCD0‘<<H-C))tH-CD0ft‘CC))CDCDddftCDCDC))HCflHhHh0(J)ClCDC))H-H-0_00()_HH-CDCDCD‘ftft0ClftCDHftCDCDClCDHH-H)(fl1<0iiCDftClftHHClCDCDXCDCDCD0H)C))H-H-0(fl C),HH-ftCD0-Cl-‘H-ft1ClP.CDtoH-H)CDC50CDxCDtft.p‘z3ClftCDdciCDH-1hC))H<CDfrH-0Z0t”)-.-ClC))0cirt-CDCDftCDH-xjC))XH-ftC))H-i)CD0H1<CDinClH-CD‘<C))CDCDCDHIIft><Clci—CDIH<I)<CDciCDC)’(1)XiClCD-ft‘DC))HH0ftftClH)CDI•ij H-0CDC)’U)ftU)ft0Cl) (C)toIHft00jCDCD011IICD1CDH-(I)CDU)H)H-U)ciH—CldftH-H00CDIIH-i.QtHXH-CDCl(‘3H-<CD0(C)CD(‘30CDU)CD•-24With quantities and prices interchanged in the formulaeabove, we can define the Laspeyres, Paasche, and idealquantity indexes. In particular, the ideal quantity index isdefined as(15) QId4PrXSi\X pX)We can see that the ideal price and quantity indexessatisfy the “adding up” property of equation (11) as- Pr.,’1(16) IdQId—______p.xIf a quantity index Q(pS,pC,xS,x) and a functional formfor the aggregator function satisfy1(17) 1 Q(Ps,Pr,xs,xr)then we say that Q is “exact” for f. Examples of indexes whichare exact for well known aggregator functions include thegeometric index, exact for a Cobb—Douglas aggregator function,the Laspeyres and Paasche indexes, both exact for the Leontiefaggregator function, and the Tornqvist index, which is exactfor a linear homogeneous translog function. Diewert (1976)has termed an index “superlative” if it is exact for anaggregator function that can provide a second—orderCDCDH-U)H)H-(I)CidU)P)H-Cl)—xi—CiCiCisCDd‘10ftCDI—iC)CD0P.ClhH-_CDCDC)CD(ClCDC)C)C)CD0CDftCDtift><ftC)CDH-CDft><‘-Q0EnH-CD0HH-H-CDCliH)Cl‘-3CDCDXU)CD(1)Cl)0ftU)CiH-CiJCDEl)tH-CDEl)-CDftftCiU)<CD‘1H-CDClH-H-Cl)ftCl)CDCDClCDU)ftCl)0Cl)Cl)Cl)(1)<HClCiftCDftbH-•Cl)CDU)HftSIH-HHCt0ClCDft0H-H-‘<Ci0dt5‘1CD:i<H‘-3CDCD<C)C)H-0Cit‘0d0CDClCDC)0•0ii9Cl)9•CDflH-1CD-HftCD(I)C)U)H-Cl)()0(1)Cl)CD-H-Ci-0‘C)ftftHU)crCDftftHCl)CtH-H212ftCi-H-CD<0C)CDCl)C)-H-ft)ft-iCl‘10CDH-0H-CDU)CiCiCl)Cl)IH-ft0H-HH-Cl)HCDCD-QU)ft ‘1InC)ClHCD:ft1MU)H-i-CDiCCl)0C)CDftHClt-ft0ft.—.0tYCl)Hft‘1CDftClftU)0CDH-0CDCDCl)H-Ct)HZftCl.’tCl)HH-00Cl‘-Cl<ClClCDHU)CDCDCDCl’0CDCDCD0ftXH)H-H-XftU)‘-QCl-CiH-0Cl)ClH-H-H-+‘1+U)H-CDc..’CDCiCD‘t5CiH)C)CDCiCl’piCD(I)XCDC)CDft0CDt-H-HH0CD0CDCDCDHC)H-SIHCiCDCl)Ci-CDftCDCDCl)CDHCl)‘ClHft-ftftH-0Cly‘.<H-0CDftCl)CD’-SICD0Cl)HCl)Cl)H-C)El)ftH)HCl)CDlCDi0CiHClU)HCDCi-H-HCDCiC)‘ClH-CDftXH-‘ClHCDft‘-CXft•H-HH)H-‘ClH-ClC)H-H-CDH-0ftHCl)CiCDCDCl)H-CD0C)Cl)El)Cl)CDSftU)XlcnlCD‘126Implicit Tornqvist price or quantity indexes can bedetermined using equation (11) with observable prices andquantities in each entity and the indexes defined in equations(18) and (19). Since the translog is not self—dual, theimplicit Torriqvist index will generally differ from thecorresponding “explicit” index. The exception is when thehomogeneous translog is restricted to the Cobb—Douglasfunctional form, then it is self—dual. However, thesedifferences are small provided that the variation in pricesand quantities between entities is not too large.The Tornqvist indexing procedure can be viewed as adiscrete approximation to the continuous Divisia index,providing an index of total factor productivity. The Divisiaindexes of aggregate output Q and aggregate input X aredefined in terms of proportional growthPQ::5(20)—_______w.x.(21) IThe Divisia index is a continuous index that cannot be27calculated from data which are observed at discreteintervals5. Equations (20) and (21) can be approximated bythe Tornqvist quantity index given in equation (18) as(22) =(23) =X5)We now introduce a general methodology developed by Dennyand Fuss (1983) for analysing the sources of intertemporal orinterspatial differences in outputs and costs. If we assumeefficient production, intertemporal productivity differencescan be attributed to technological change while interspatialdifferences are due to differences in the (efficient)production function in each region.We begin by introducing an important tool. Let Z be anN-dimensional vector. Then define the quadratic function f(Z)as5The problem with the Divisia approach to the measurement of changes inproductivity is that economic data do not come continuous-time form x(r),w(r), y(r); rather they come in discrete form x , w,y Thus, the continuoustime formula must be approximated using discrete-time data (Diewert,1976).CD0CD<t-CDCDP3-—H-r%)Cl)HHCl)CDCDCDH-aCDftP301CDp,HHCDpiCDCDCDU)<t:-1dU)P3CDHCtCD<1ftP3CDftftH00x‘H-CD0ftftftNNII(1)0CDP30—0H-0<,CDH-P3÷0H-CDft<CDiiC)CD-CDC\)If-P3H-ftCDCt--P3ft0P3ftNaNCD1H-CD$iQ0CiCDH-CDCDP3CiCDftH-CD(I)ftC)•‘ICiCDP3P3P30C3<P3CDP3it’JJi-ft+‘ftCDCDH-H-ftY’CD—C)CD+0CD-CDftft<1H-kMH-CDP3P30H-CDCDU)CDNN-H--0P3r1P3+-CDCDCD0CDCD<ftfrftP3IIHCD0CD0P3[-1-.•..—C)CDHH-NCDftCD0P)CDH-‘1I-,.CDCD+00NP39P3oH-CDZH-ftHHN$1HftCiNHCiCDpP3HCD•ftftoC)IIft0CDLi.H-0CDCD0ftftP3II0 H-CD‘-3CDNP3ft0-•CDCl)H-HftC’)00ftH-IIU)CD0Cl29where R3’ is the third order remainder term. An approximationto QS can be obtained by replacing X1 with Xs in equation(27). Similarly, expanding the production function about Xrwill yield an approximation to Qr The difference between thetwo approximations isQs — = l(fr ÷ f) (x — Xf)+_- (f — f1) (X — xf) (x — Xr)(28) ‘ i+— R35)When f(X) is either linear or quadratic, equation (28)simplifies to(29) QS — = l(fT + fS)(XS — xf)Equation (29) states that if the two functions arequadratic, the difference in output levels is a function offirst derivatives and the input levels. This corresponds tothe quadratic lemma, equation (25). Index numbers can be usedto evaluate equation (29) if the f are replaced with anexpression containing only prices and quantities. If Q and Xare expressed in logarithms, then in competitive equilibrium30frSr and fsSs where Sr and S1 are factor cost shares ofand X.S, respectively. Then equation (29) can be expressedas(30) lnQ8 — lnQr = (Sf + Sf) (lnXf — lnXf)This is the form of the Tornqvist approximation to the Divisiaindex.Suppose the production function can be written as(31) lnQ = f(lnX1 ,lnX,T,D)where T is a variable reflecting technological change and D isan efficiency difference indicator. Assume that the functionf is a quadratic function for which only the zero and firstorder parameters vary by regions. Then equation (31) can bewritten as(32) A1nQ—-(ff + iff) (lrixf — lnXf) + p +where(33) psI = - (f’ + f) (vs D1)is the interspatial effect and31(34) tSr = - (f + f2z) (75 — T’)is the intertemporal effect, and(35)(36)8lnD8f(37) T alnTBy assuming constant returns to scale and competitivemarkets f1r = S and f1S = S, and equation (32) can be writtenas(38) lnQ =--(Sf + Sf) (lnXf— lnxf) + Psr +Solving equation (38) for Tsr when DS = Dr yields theintertemporal Tornqvist index of productivity growth for aparticular spatial entity. Solving equation (38) for Psrwhen TS = Tr yields the interspatial Tornqvist productivitydifference index for a particular point in time.323.3 The Empirical ModelAs discussed above, the accounting method assumes thatthe production technology can be approximated by a second—order function. For the production function, a second—orderapproximation in the logarithms of outputs and inputs is used,while logarithms of input prices, output levels, and cost areused for the cost function. This use of a quadratic functionas the second—order approximation provides a direct link tothe economic measures of productivity and efficiency. If aproduction function can be approximated by a quadraticfunction then the application of Diewert’s quadratic lemmaimplies that the difference in the logarithm of output betweentwo sectors can be expressed exactly as a weighted sum of thedifferences in the logarithms of the inputs and a term whichcan be interpreted as the difference in the productivitybetween the two sectors. The productivity differential termis the Tornqvist approximation to the Divisia index and is ameasure of the output level in sector i relative to that insector j after taking into account differences in input levelsused by the two sectors.Alternatively, if the cost function can be approximatedby a quadratic function in the logarithms of output and inputprices, the application of the quadratic lemma yields ananalogous result. The cost differential can be decomposedinto an output effect, an input price effect, and a spatialeffect. In this case, the spatial effect is the Tornqvist33approximation to the Divisia index of cost efficiency.The various economic approaches to index numbers andproductivity measurement centre about the assumption ofoptimizing behavior on the part of producers. Define anentity k cost function(39) ,k—r,sas the minimum cost of producing the quantity yk of output infor m = 1, 2,..., M, given both identical technology betweenthe two entities and that entities face input price wk forinput Xk for n = 1, 2,..., N. The assumption of costminimizing behavior leads to the following equation:(40)Equation (40) is too general for statistical estimation to bepossible. Therefore, it is necessary to constrain the entityk cost functions ck to relate to each other in a relativelysimple manner. Thus, we now assume the following:(41)where at is the entity k relative efficiency factor and C isan entity—nonspecific cost function, that is, C does notdepend on the entity being considered. If this assumption istrue, then a natural measure of productivity change going fromentity s to entity r is ar/as.34Equation (41) can be written equivalently as(42)±inCwhere C is the entity-nonspecific cost function. Thepreferred form for the natural logarithm of C is the translogfunctional formlnC(y,. . .w)=b0+Ebiny+ e1nw+ - d1ln yiny](43) i=1j=1÷ -- f 1nw]cwjz+ glny1nwi=lj=1 m=ln=1where C = variable costw1, wk are input pricesk, .k are outputsb0, bmi e, d13, f, g, are estimating parametersWe can regard ln Ck of equation (42) as a quadraticfunction in the variables ln a, in 1k, ln 2k , in yMk, lnw1k, in w2k , in wNk, allowing the application of thequadratic lemma. Because we assumed that the cost functionsfor entities r and s had the translog functional form defined35by equations (42) and (43), the following equation is valid:lnC’-inCt= (yZ, W’) ÷y (yS, w9]1n()(yZ, Wr) +w (yS, ws)]ln(i)+ i[ölncT (yrwr) + 81nCS (ySWS)]1fl(2 ama 8lna(44)By assuming cost minimizing behavior and applyingShephard’s lemma, we can rewrite equation (44) asiflCr_1flCt=[Ym1 (yr,wI) ÷r81ncr (Yrwr)]ln(YmJ+ + in —-C’ C5+[-‘+ (-i)]ln(2(45)The assumption of competitive profit maximizing behaviorallows further simplification of equation (45), with the firstorder necessary conditions being36(46) ‘-“--PmYmEquation (46) represents the usual price equals marginal costrelationships required for the assumption of competitive pricetaking behavior. Making use of the relation(47) Ck= wx , n=l,...,Nalong with equations (42) and (46), equation (45) can berewritten as= -P’rn + PmYrn ln YmC5) 2m=i cr Cs(48) +(wx + ) J(r—mi ----The cost differential is decomposed into the three effects37given by the right hand side of equation (48). These threeterms correspond to an output effect, an input effect, and acost efficiency effect, respectively. Output and inputquantities can be observed as well as respective costs foreach entity, r and s. The only unknown in equation (48) isthe productivity differential from entity s to entity r,ar /as. Solving equation (48) for ar/as, we haveN1T Yin 2(49) 11—;a1 m=1 Ymaswhere is the implicit Tornqvist input quantity indexdefined as— wI.xr(50)2’N WIWS.XSn=1 Wwhere Sr, S are input factor cost shares.The additional assumption that the underlying technologyexhibits constant returns to scale allows furthersimplification of equation (49). We assume that if alloutputs increase by a proportional factor, then costs mustgrow by this same factor. In this case the cost function ckmust be linearly homogeneous in outputs and revenues mustequal costs for each entity38(51)Using equation (51) we can replace Cmr and C in equation (49)by Rmr and p5, respectively, and we find that equation (49)reduces toMI-I Yin 2 R’ R(52) 11ar — m=1 Yas QTEquation (52) is interpreted as follows. The numeratoris a relative output quantity index computed as the product ofrelative physical commodity quantities weighted by averagecommodity shipment shares. The implicit input quantity indexfound in the numerator is calculated as relative totalvariable costs divided by the product of relative factor inputcosts weighted by average factor input cost shares.Calculation of a productivity differential ar/as for eachindustry j required Canadian and U.S. data for commodityoutput quantities and shipment shares, total variable cost,variable input factor prices, and input factor cost shares.The following section describes the methods used to constructthese variables.394. Database and Variable ConstructionThis section begins with a description of the applicationof productivity measurement to the international cross—sectional comparison. The following subsection then describesthe sources of Canadian and U.S. data used for the study.Next we deal with the various aggregations and disaggregationsrequired to achieve comparable Canadian and U.S. data for thecalculation of relative productivity measures. The finalsubsection outlines the characteristics of the database.4.1 Productivity Measurement for the InternationalCross—Sectional ComparisonIn a study of relative industrial productivity betweentwo countries, the importance of accurate industry matching iscritical. To secure a suitably large sample size it isnecessary to obtain data for as many well—defined industriesas possible, under the assumption that similar industriesutilize similar inputs in producing similar outputs. Thegreater the level of industry data aggregation, the morediverse will be the output mix of this broadly definedindustry, and so the greater the probability that similarindustries will not, in fact, show similar mixes.Disaggregation will, therefore, allow a more accurate industryto industry productivity comparison and, by this fact, providea more direct comparison of industries which would becompetitors if trading occurred.40To this end, detailed comparisons of industry output wereundertaken for Canadian and U.S. food processors. Thesecomparisons were based on the SIC codes of each country andthe description of the products of the given industries. Asa result of this matching process, 38 industry pairs withsimilar products were isolated for this study, with a matchingof 104 processed food and beverage commodity output prices and62 material input prices, plus packaging materials and energyprices. These 104 commodities represent 68 percent and 86percent, respectively, of the total value of output of theindustries that produce them in the U.S. and Canada.6Achieving a sample of this size was accomplished bydisaggregating Canadian industry level data to match the U.S.industry definitions to reconcile for differences in SICclassifications between the two countries. Specifically, U.S.4-digit SICs tend to be more disaggregated than the Canadianequivalents. If instead of disaggregating the Canadian datathe U.S. data were aggregated to the Canadian level, theresulting smaller sample size would provide less accuratemeasurement of relative productivity, as outlined above. Thisdisaggregation procedure made use of information extractedfrom the U.S. data on relative proportions in the disaggegatedindustries, while ensuring that the Canadian estimates summedto the known aggregate total.difference in coverage between the two countries is due to the higher Level of product diversityfound in the U.S. industry. The Canadian industry is more speciaLized, as many coamodities produced in the U.S.are not produced by the Canadian industry.41For each industry, a relative output price index for aselection of commodity outputs was calculated. These relativeindustry output price indexes were based on products whichcould be closely matched between the two countries based onSIC codes and product descriptions. For some industries alarge number of products could be matched, while for otherindustries the number was far fewer. Since not all productsof an industry could be matched, the relative output priceindex calculated for each industry, being based on a selectionof matched commodities, was assumed to be an accurate estimateof the true relative price index which would result if therewas perfect matching between the two countries of all productsin a given industry.A similar matching procedure was conducted to estimate arelative materials input price index for each industry, withthe index being based on material inputs which could beclosely matched between the two countries. Analogous tocalculating relative industry output price indexes, not allthe material inputs could be matched and, therefore, thecalculated materials input price indexes were assumed to beprecise estimates of the true materials price index resultingfrom complete materials input matching between the twocountries.The concordance developed for the study between theCanadian and U.S. classification systems is presented inAppendix A. Direct concordance was possible between the two42systems for 16 industries, while the remaining 22 sub-industrycomparisons were based on estimates of Canadian sub—industrycosts for labour, materials, and energy, as well as labourprice, obtained by disaggregating the Canadian equivalents ofthe U.S. industries7Typically, a study of total factor productivity wouldinclude a quartet of inputs; labour, energy, and materials, aswell as measures of capital stock (the standard KLEM model).However, Statistics Canada does not publish industry specificdata for capital, forcing the researcher to either disregardcapital or make assumptions concerning its value and cost8.We chose the former of these two alternatives by assuming theproduction process is homothetic. The homotheticityassumption implies that factor proportions depend only onrelative input prices and not on output levels.Given the lack of capital data for the Canadian industry,assuming homotheticity is more a convenience rather than anassertion of a particular property of the productiontechnology. Though it is unlikely that this hypothesis isprecisely correct as an application to a study of this type,Robidoux and Lester (1988), in reference to their study,suggest that it is a “reasonable approximation”. Robidoux andLester propose that by assuming homotheticity one can let a7rndustries dropped from the study due to implausible calculated unit values include cigarettes, tobacco,.distilleries, tea, and malt.8Hazledine (1989) assumed that Canadian price levels for capital services were 10% higher than in theU.S.43non—capital cost function represent a total cost function, inthat the ratio of non—capital costs to total costs remainsunchanged when quantity changes if prices and other industrycharacteristics are also unchanged.The decision to adopt the homotheticity assumption isreinforced by the finding of Haziedine (1989) that the shareof capital services in total costs, as a mean value across 84Canadian manufacturing industries, was less than 4% in 1982.Hazledine suggests that “productivity calculations will not bevery sensitive to errors in the capital share data”. Giventhat the analysis presented here is conducted on a moredisaggregated basis and that the share of capital services infood processing is small relative to the all ready smallmanufacturing average calculated by Hazledine, this suggeststhat for our purposes any bias introduced into our results asa consequence of the exclusion of capital measures will besmall9.4.2 Data SourcesThe primary source of Canadian data were the StatisticsCanada reports on the 1986 Census of Manufactures. Data wereavailable for the food processing industries from thepublication Food Industries (Cat. 32-250) and for beverage andtobacco industries from Beverage and Tobacco Products91f the true cost functions are non-homothetic then the missing capital costs would likely bias theresutts.44Industries (Cat. 32-251). These publications providedinformation at the commodity level for quantities and valuesof materials and supplies purchased (c.i.f.), values andquantities of commodities shipped (f.o.b.), with somequantities absent from the Census being supplied by ProductsShipped by Manufacturers (Cat.31-2l1). Data at the Canadian4—digit SIC level was provided for manufacturing activityvalue of shipments, total activity salaries and wages andnumber of employees, and the costs of energy and materials andsupplies. While the Canadian Census has traditionally beenpublished annually, financial constraints forced StatisticsCanada to miss the 1987 Census, making the 1986 Census themost recent Canadian data available at the time of this study.U.S. 4-digit and 5-digit SIC industry level data wereobtained from the U.S. Census of Manufactures, published everyfive years with the most recent available being data for 1987.In addition, the 1986 Annual Survey of Manufactures gaveindustry data at the U.S. 4-digit SIC level only.4.3 Variable ConstructionWe begin with commodity-level data for both unit valuesand shipments along with SIC (industry) level data on industryshipment values and the costs of materials andsupplies,energy, and labour. The commodity—level data must beaggregated to the industry level as price indexes, while theindustry data must be reconciled for differences in SIC45classifications between the two countries. This involvesdisaggregating the Canadian data to match the U.S. industrydefinitions.The remainder of this section is laid out as follows.First we deal with the disaggregation of the Canadianshipments data and then discuss the construction of Canadianmaterials input data. These latter calculations will providematerials cost shares for the implicit input quantity indexforming the denominator of equation (52), the productivitydifferential. The construction of the relative output priceindex is then described. This index was not required for theproductivity calculations but in itself provides importantinformation. This is followed by the development of relativeinput price indexes for materials, labour, and energy, alongwith cost shares for the latter two inputs. These relativeprice indexes for the three variable inputs, along with thesum and respective shares of variable costs, are required forcomputing the implicit quantity index forming the denominatorof equation (52). A description of the database completes thesection.4.3.1 Disaggregating Canadian Shipments DataCanadian industry shipments data were disaggregated tomatch equivalent U.S. industries for 16 industries as outlinedin Appendix A. This procedure involved comparison of Canadianand U.S. shipments at the commodity (ICC) level to infer46shipment values for each Canadian sub—industry.4.3.2 Constructing the Canadian Materials Input Data forDisaggregated IndustriesWe have Canadian data for an aggregate industry and sub—industry (disaggegated) data for the U.S. For example, theCanadian industry Slaughterers and Meat Processors (SIC 1011)can be disaggregated into five distinct sub-industries: beef,pork, pork processing, sausages, and inedible tallow.We have data for sub-industries in the U.S., but only forthe aggregate industry in Canada. Therefore, we mustcalculate estimates of the data for the disaggregated Canadianequivalents of the U.S. industries, while ensuring that theseestimates are consistent with the known Canadian aggregateindustry data. This procedure will make use of commoditylevel data on relative Canada/U.S. materials input and outputprices, as well as data on commodity shipments in the twocountries.An important difference exists between the two countries’censuses with regard to the handling of the energy costcategory. The U.S. data include energy in the materials costcategory while the Canadian data report energy separately foreach industry. Since U.S. input/output ratios are used todisaggregate the Canadian industry cost data to match U.S.sub—industry equivalents, the term “materials” in this sectionrefers to “total materials”, that is, Canadian data for energy47and materials were summed in order to maintain uniformity withthe U.S. data. The procedure used to disaggregate industryand sub—industry energy and materials costs is covered insubsection 4.3.6.We defineX1 real output of sub-industry ivalue of output of sub—industry iZik = cost of input k, industry i, with k = M (materials)P1 = Canada/U.S. relative price of output of industry i= Canada/U.S. relative price of input k in industryi, with units chosen so that all U.S. nominalprices=l= input/output ratios for input k, with a = Canadaand 13 = U.S.We define the U.S price as numeraire so that the U.S“real” and “nominal” value of output are identical(53) xj1=So, the U.S. materials input/output coefficients are(54) k=M1From commodity shipments data we have inferred estimatesof Canadian sub—industry values of shipments, yC1• Now48calculate Canadian real output by dividing shipments by thesub-industry relative output price indexyC(55)piWe assume that the Canadian sub—industry had the samematerials input/output coefficient as calculated for the U.S.sub-industry in equation (54) above. The estimated Canadianinput cost levels, given the Canada/U.S. price differential,would be(56)= P ikXilIkThat is, each is the nominal materials input cost if theCanadian and U.S. sub-industry input/output coefficients wereidentical.The ZjkC are summed across the sub—industries and comparedwith the known Canadian aggregate total of materials input kfor the industry, ZCk, from the Canadian Census of ManufacturesdatazJ(57) YkZikWe can interpret equation (55) as the materials productivitydifferential, the ratio of actual industry materials cost tothat which would be incurred if the Canadian and U.S.49industries had identical input/output coefficients.The Canadian (real) materials input/output coefficientscan then be estimated(58) alk =In effect, this scales the U.S. input/output coefficient toreflect the difference in materials productivity between thetwo countries.Then, the final estimates of Canadian sub—industry materialsinput cost levels are(59) Zfk = kKiP1kAs discussed above, these estimated material input levelsrepresent total materials, being the sum of materials andenergy costs.We know ZCk, the Canadian industry aggregate total ofinput k. This allows a test(60)= Zfkto ensure that, for each k, materials input quantitiesestimated for the disaggregated Canadian industries sum to theknown aggregate industry total.An example calculation is included in Appendix B, wherethis procedure is used to disaggregate Canadian materialsinputs for the Slaughtering and Meat Processing Industry (SIC501011) into sub—industries beef, pork, processed pork,sausages, and inedible tallow.4.3.3 Constructing Relative Output Price IndexesRelative output price indexes were calculated for eachindustry as mixed weight Tornqvist indexes making use of datafor relative output commodity prices and commodity shipments.For industry j, let and S be the shipment shares ofcommodity i for Canada and the U.S., respectively. Then letSc.0 =05 13 + 13(61) 13 mj misfwhere(62) = 1and where mj is the number of commodities produced by industryJ.The relative output price index for industry j is thendefined as(63) p = pOl) pa.’ioj 13 mjwhere P is the relative Canada/U.S. output price forcommodity i.514.3.4 Calculation of Relative Materials Input PriceIndexesRelative materials input price indexes were calculatedfor each industry in a manner analogous to the output priceindexes above. Tornqvist indexes were constructed withrelative material commodity prices weighted by averageCanada/U.S. materials cost shares(64) — n8i O6mjr)0PKjMj — 1j 1flj .LpJjwhere, for each industry j, P is the relative Canada/U.S.materials price index, P is the relative price of materialsinput commodity i, e13 is the input cost share of input i, mis the number of input commodities used by industry j, 0PKj isthe cost share of packaging, and jPK is the relative packagingprice index described below.The relative packaging price index was of the form(65) —781j02jfl634PKj — 1j 2j 3j 4jwhere P, P2, P3, and P4 are the relative prices of metal,glass, paper and board, and plastic packaging, respectively,used in industry j, and e1, e2, e3, and 04j are the respectivepackaging cost shares. The data used for these calculationsare presented in Appendix C, Tables Cl and C2.524.3.5 Calculating Relative Input Price Indexes for Labourand Labour Cost SharesThe same assumptions used to calculate Canadian materialinputs are used for disaggregating the Canadian labour data.A difference in the case of labour is that data are availableon two types of labour: production workers (wage earners) andadministrative and clerical workers (salary earners). Thesedata include quantity data, unlike for output and otherinputs, in the form of levels of employment.Our task is to calculate a relative input price index foreach industry which incorporates the importance of the twolabour types and to construct labour inputs for disaggregatedindustries. This is accomplished by first estimating costs andquantities of each type of labour for each Canadian sub-industry, then calculating average wages and salaries for eachindustry in both countries, as well as total wage and salarycost for each industry. Finally, a Canada/U.S. price indexfor labour is calculated.We begin by estimating quantities and costs of eachlabour type for each Canadian sub-industry j. The followingnotation is used:E = number of employeesW = total wages or salariesw = average wage or salary ( W/E)subscripts p and a for production and administrativeworkers53subscripts c for Canada and u for the U.S.The labour input/output coefficients for production andadministrative workers in US, industry j isEu.‘66’ =—‘ I tpju(7 =‘ IxjuThe estimated Canadian sub—industry employment levels are(68)=(69)= I3ajXfThe are summed across sub—industries and comparedwith the known aggregate Canadian industry employment levels,and EaCEa”(70) YaZajj =1E(71) nj =154Then, the estimated Canadian labour input/outputcoefficients are(72)=(73)= YaI3ajand the estimated employment levels for Canadian sub—industries are(74) =(75)= cXjSince we know Ec and EaC the Canadian industryemployment levels, we can check to ensure that each of thecalculated sub—industry levels of employment sum to this knownaggregate industry total(76)=Ej(77) EaC55An analogous procedure is followed to calculate the costsof wages and salaries for each Canadian sub—industry. TheU.S. wages and salaries input/output coefficients areTTu‘77’ =‘ I pi v.ui-ru‘78’ ? a‘ ajxJThen, the estimated Canadian sub—industry wages andsalaries are(79)=80Zwaj —The andwaj are summed across sub—industries andcompared with the known aggregate Canadian industry wages andsalaries costs(81)wpjj =1WaG,(82) nEj =156and the estimated Canadian wages and salaries input/outputcoefficients are(83)=(84)=After finding total industry wages and salaries costs(85) wj = +(86) = +and average industry wages and salaries for both countries(87) = -Wa(88) waEajw .(89) w=—i57(90) =the relative Canada/U.S. labour price index isC C(91) p•U u uWpj Wajwhere(92) 0 = 0.5w wj2C U(93) 0 .=0.5-- 4--wic Wi4.3.6 Calculating the Energy Input Data and EnergyInput Price IndexThis section describes the procedures used indisaggregating estimated Canadian sub-industry total materialscosts into separate costs for materials and energy. Inaddition, it shows how the U.S. industry energy costs wereestimated. Details of the calculation of the relative energyprice index are contained in Appendix D.For the disaggregated Canadian industries, we haveestimated Canadian sub-industry total materials costs,58comprised of materials and energy costs, as outlined insubsection 4.3.2. Energy costs were assumed to be identicallyproportional to materials cost between the industry level andthe sub-industry level, allowing Canadian sub-industry energycosts to be estimated as(94) Ef’ = zi(z)where, with c for Canada,ZEjC = energy cost, industry jZMJC = total materials cost, industry jZMIC = materials cost, sub—industry ±Ec= energy cost, sub—industry ±Canadian sub—industry materials cost, that is, net ofenergy, could then be calculated by subtracting estimatedenergy cost from total materials cost.These estimates of Canadian sub—industry materials andenergy cost were then used to estimate U.S. industry energycost. For each U.S. industry j, with u for the U.S.,Ec(95) EL =J ,7c‘-‘Miwhere E and ZMjC are defined as above andEu= U.S. energy cost, industry jX = U.S. total materials cost, industry j59An analogous procedure was followed with variables fromthe industry level for industries in which disaggregation ofthe Canadian data was not required.4.4 DatabaseThe database is composed of three sections: MTLS, OUTPUT,and INDDTA. The MTLS and OUTPUT databases are used to deriverelative materials input and output price indexes,respectively, for each the industry or sub-industry. TheOUTPUT database also includes industry and sub-industrysampled commodity shipment values. The INDDTA database usesthe above information, with industry costs and total shipmentsdata, to calculate indexes for the productivity comparisons.4.4.1 MTLS DatabaseThe data for calculation of relative materials priceindexes for each of the 38 industries, MTLS, is displayed inAppendix E. An outline of a standard calculation for anindustry was as follows:1) The U.S. Census was used to identify the majormaterial inputs and approximate input proportions.To avoid adding undue complexity, materials inputcommodities contributing less than 5 percent tototal materials costs were not included in thedatabase. However, for some industries several of60these relatively insignificant inputs constituted,in sum, a large proportion of input costs. Inthese cases, this proportion was designated as“other materials” and assigned a relative priceequal to the average of the 104 relative outputcommodity prices.2) Input prices were calculated for each commodityfrom quantity and cost data taken from therespective census publications, the Canadian for1986 and the U.S. for 1987.3) American quantities were converted to Canadianunits (eg. lbs to kgs).4) The U.S. unit values were deflated to 1986 usingProducer Price Indexes, published by the U.S.Bureau of Labor Statistics, then converted toCanadian currency at an exchange rate of $l.3894.5) A relative 1986 Canada/U.S. input price wascalculated for each input commodity.6) A relative packaging cost was determined (cf.Appendix A).7) A Canada/U.S. average input cost share wasdetermined for each input commodity.8) Equation (64), with relative materials input pricesand average materials input cost shares, was usedto calculate a Tornqvist relative input price indexfor the industry.61In many cases, data was unavailable or an appropriatedeflating index was not to be found. In these cases, one ofthe following methods was employed to arrive at a relativecommodity input price, where the terms following inparentheses give the notation used in the database to indicatethe cases where each method was required:1) constructing an index from U.S. primary producerdata for deflation of U.S. unit values (PPP).2) Using a unit value calculated from differentindustry because of data being unavailable for unitvalue calculation in the industry being considered.3) Some form of calculation (CALC).4) In the case of tradable commodity inputs,invokingthe Eastman and Stykolt hypothesis and using tariffinformation to deduce a relative Canadian/U.S. unitvalue (TARIFF).5) constructing a mixed weight output price indexusing output data (MWOPI).6) Using some form of additional information to deducea relative Canadian/U.S price independent from thedata (e.g. P/P IMPOSED).624.4.2 OUTPUT DatabaseData for determining relative output price indexes, arepresented in Appendix F.Unit value calculations largely parallel those found inthe NTLS database. Respective quantities and values were usedto derive unit values for the output commodities produced byeach industry, using primary data for 1986 for Canada and 1987for the U.S. After conversion to Canadian units, the U.S.unit value was deflated to 1986, converted to Canadiancurrency, and a Canada/U.S. relative commodity pricedetermined. Then the set of relative output prices for theindustry, along with commodity shipment shares, were used withequation (63) to calculate a Tornqvist relative output priceindex for the industry.Though U.S. unit values could be readily deflated from1987 to 1986 by the use of indexes, 1986 commodity shipmentshad to be estimated. As data were available from the 1982U.S. census, 1986 commodity shipments could be estimated usingan exponential trend function with 1982 and 1987 shipments asendpoints10.We define and as known 1987 commodity shipmentsfor 1987 and 1982, respectively, and as the unknown 1986commodity shipments. With the time difference of five yearsfrom 1982 to 1987 we have10An exponential trend was considered more realistic than a linear trend in estimating 1986 u.s. sub-industry shipments.63(96) Y82exp(5r)then(97) = in[]and(98) Y82exp (42)Two methods were utilized in deflating U.S. unit valueswhen the relevant index was unavailable. First, in some casesan output commodity was broadly defined, that is, a compositeof outputs11. While indexes were available for eachcomponent of the output grouping, no one index covered thelot. In these cases, weighted average indexes were calculatedas the sum of the individual indexes weighted by shipmentshares.Secondly, a 1986 U.S unit value was estimated byinterpolation when an index specific to a commodity wasunavailable. As above for estimating 1986 U.S. commodityshipments, an exponential time trend was used, with 1982 and1987 unit values as end points. So,For example, constder bread as a more broadly defined output cofmnodity, comprising wheat, rye, whole andcracked wheat, and other bread.64(P(99)5and(100) P86 = P82exp (4f)where f is an exponential parameter, P86 is the estimated 1986unit value, and P87 and P82 are the known 1987 and 1982 unitvalues, respectively12Though the database reports shipments and unit values foreach country, the shipments data had to be adjusted to reflectthe differing coverage of output for each industry between thetwo countries since the coverage of commodity outputs is notcomplete and differs for each country. That is, we havequantity/shipments data on only a subset of each country’stotal production for each industry. Therefore, 1986 U.s.estimated commodity shipments were adjusted to match thecoverage of the Canadian data. For each industry, each of theestimated 1986 U.s. commodities shipment figures weremultiplied by the ratiovalue interpolation was not used for material inputs because primary agricultural prices tend toflucuate a great deal from year to year, making unrealistic the assumption of an exponential trend to unitvalues.65(Total sampled commodity value of shipments(101) Total industry shipments cda(Total sampled commodity value of shipments\Total industry shipmentsThen dividing these adjusted commodity shipment quantities byrespective actual unit values yielded adjusted physicalquantities yju.4.4.3 INDDTA DatabaseThe Inddta portion of the database, presented in AppendixG, represents the final stage of data preparation for theproductivity calculations. Following the concordance ofAppendix A, this portion of the database includes industrydata from both countries for:1. Value of shipments2. Relative input price indexes for materials(PMJ),labour (LJ)’ and energy (E)3. Materials,labour, and energy costs and, hence, bothtotal variable costs and variable input cost shares.The following two procedures were required in assemblingthese data:(1) The productivity calculations require 1986 U.s. 5-digitdata, but the 1986 survey of Manufactures provides data onlyto the 4-digit level. Therefore, 1986 U.S. 5-digit data wereestimated by assuming that all 5-digit industry variables(number of employees, payroll, cost of materials, and value ofshipments) grew from 1986 to 1987 at the same rate as their66parent 4-digit industry, with 1987 5-digit data beingavailable from the 1987 Census.Let 5Dgt87, 4Dgt87, and 4Dgt be the known 1987 5-digit,1987 4-digit, and 1986 4-digit variables, respectively. Thenthe unknown 1986 5-digit variable, 5Dgt, can be estimated as(102) 5D t — (5Dgt87) (4Dgt86)g 86— (4Dgt87)(2) Adjustment to U.S. 5-digit data was required to accountfor differences in reporting procedures between the twocountries. Canadian commodity shipments data includes datafor every plant reporting some shipments for each commodity,while U.S. 5-digit data reports data only for primary activityestablishments, thereby excluding diversified establishments.Relative to the Canadian data, therefore, the U.S. data willtend to underestimate values for shipments, number ofemployees, and the costs of materials and wages and salaries.Consistency between the two countries’ data was achieved inadjusting the U.S. data by assuming that non-primary data weredistributed similarly to primary data. Then, the variablesabove were adjusted by inflators calculated by taking theratio of 5-digit primary variables within a 4-digit class orgroup of 4-digit classes, and dividing into the correct 4-digit value.675. ResultsThis section first reports the results of calculations toestimate cost structures of the Canadian and U.S. industries,relative labour prices, and relative output and materialsinput price indexes. This is followed by the results of theestimation of relative productivity and cost competitivenessmeasures.Calculated cost structures for Canadian and U.S.industries, computed using data contained in the INDDTTAdatabase, are presented in Table 3. It is emphasized thatthese values are estimates, as Canadian sub—industry materialsand labour costs were estimated by disaggregating Canadianindustry data to match U.S. equivalents and U.S. energy costswere estimated using Canadian industry energy input/outputcoefficients.The cost structure calculations indicate that materialsconstitute by far the largest share of variable costs for boththe Canadian and U.S. industries, averaging 81 percent and85.4 percent, respectively, followed by respective averagelabour cost shares of 17 percent and 12.2 percent. Packagingcosts constitute a significant portion of materials costs,averaging 18.4 percent over the 25 industries surveyed inTable A2. Relative to materials and labour costs, energy costswere found to be unimportant, averaging only 2.0 percent and2.3 percent for the Canadian and U.S. industries,respectively.ctrtp’ ‘1H-CDCDCD-____—Cl)trJC,)C,)N)N)N)C,)C,)N)C,)(3N)N)N)N)N)N)N)N)N)“3-33..1(00)(30)U’•C,)N)-1(4r3(—.40)U’.C,C,’N)—‘0COO.JCCC03.0N)N)—’0(00—4CCCU’-0C,)-CQ(CCl)mO0UC1U00CC.3...CC00)(0(00)(‘000)0’(00(0‘(4—-0)0-,(C)_.P((4(0000C’)U)CD53.0CY)(0Cl)Cl)Hi>(nC)0(tCl)HdSC)HctCDgo.Q,op,CDH-(0H-H-(0C/)Cl)—‘Cl:i2H-p.Cl,,H-CDQrtoCl.1‘1HH-CDCD0)0)-)U’(30)0)(3((4U’0)0)0).0(3U’U’(0CC)(00)(30)(3(C)0)(0CC)(3(3CC)(30)0)(0(())(CC0.PPP’toPto0)0)3N)0)(0C))0)(0N)P0)P0)0)U’.0(0C,)N)-0(0N)(C)CON)400C,)(3N)00)U’.0(3-.0)C-3(-0)N)0(N)COO)-‘N).0N)U’C,).0(30(0-3(0U’(0_)N)0-30(0.00)(3(0CC(1H C)HCl)CDoE-,U)HOH—-CC.flCDC’-3-3-3-3-30N)N).0N).0N).0.0N)N)N)N)“N)0)00‘p’p•p--4•ptoto0)PpU’oppopco’.C)0(3(0(3C,)0)0U’(00-0U’.4(3(3U’U’(3)O(3’N)-0-(CC,)0)(3U’C,)0)-000)02t- CD-0)C)H,-Cl)“H.<00(30)0-’(00)_CU’00C,).0-.CN)N)U’(3.0C,)(0.0U’(30)400(3U’(3.0-40)0(000-’o(0H-CDct-CDU)CD(30)0)0)(30)0)(3(0(3(30)U’0)(00)(0(3CC)0)CC)0)(0(0C))(3CC)0)0)(3CC)CC)0)(0(0C)!?iPSPP-’<(0CD.0(3—,(0(0(3(3U’(00CC)N)-3CO0)U’0)_C0)N)C,)U’U’(0(30)0N)CC).00)(30).0N)C,)N)(30)CC03.Cl)H-CDoH-C)ctCCCDLQH-—0H)IHCDII00N)00)(0N)0)N).00)N)N)1N)(0N)0)0)0)N).0(00)N)(3-‘N)C,)(3N)0)0)N)U’(0CD0-C-‘69Table 4 Calculated Canada/U.S. Relative Labour Prices, 1986Relative Labour Price ($Cdfl/$Cdn)1 Beef 0.9722 Pork 0.9723 Pork processing 0.9704 Sausages 0.9705 Inedible tallow 0.9646 PouLtry 0.7757 Canned vegetables 08658 Canned mushrooms 0.8659 Juice 0.86510 Jams & jellies 0.86511 Frozen vegetables 0.76512 Milk 0.91213 Butter 0.86714 Cheese 0.87315 Milk powder 0.84416 Ice cream 084717 Flour 0.68118 Cake mix 0.81519 Breakfast cereals 0.82820 Feed 0.81021 Dog & cat food 0.79922 vegetable oil 1.01123 Biscuits 0.77024 Bread 0.79725 Sugar 0.85526 Chewing gum 0.82227 Confectionery 0.78628 Coffee 0.75429 Pasta 0.93230 Chip & popcorn 0.88 131 Peanut butter 0.85832 Starch 0.86033 Peanuts 0.86234 Shortening & margarine 0.86035 Soft drinks 0.88436 Beer 0.78437 Wine 0.81538 Smoking tobacco 0.968Averaoe 0.864The average values calculated for relative materialsinput and output price indexes are presented in Table 5.These indexes were calculated using equation (64) and equation(63), respectively. The results indicate that the Canadianindustry, on average, fetches a higher relative price for(JiC)I-3,H-H)CDD)H1H-‘-QH0t-’ CDHP)ftftHCD 1ift 0C)CD ft i.-CDp<.<$1 HH )tiH-CDftH-CD II H-CD,--p) H CD(•) 01HHH-H-C)(-I-CDbH)bCD0CD p)ft0CD09)H)ftH) CD CDftH-CDCDoCD‘too0dCDdCD0ft H-H)ft0HH-0o00H)H)-ftH-0CD H--Iiift 9)HI-’ H-‘dH-H)iiHH)ft CD1 00CD0ftaCDHH--0ft H-CDH-HCDC)0wH-0oH-CDd9)09)I-<-ftCDH-H‘—3H)‘1‘-‘--3CDHt-i‘-3t1CDO09)9)9)30CDt300CDCD‘1ftCDCD‘1H)CDft9’CDCD9)0HHIft,CD1bt3tiCDCDHftCDHHCDH-$200hC0‘1H-ftII•9)H1CD9)CDCDCD0CDH-CDftH•CD‘109)‘dCD,CDHftH9’CD0H-9’H<0C)CDCl)•HCDCDCDCDCD9)‘1CDft9’0HH-H 9)H-ftftHCD‘rJi-QCDCDCDCDCD9)0I-bfttftH)dCD9).9)HCDftft.H-CD<CDCDH-Hft° CDH-H-0CDH‘-<-oCDCDCDCl)CDCD9’H)9’HH9)CD09Cl)II H-09’ft‘--CD-CD00I-C‘CD9’CD‘-C9’CDt-ftHCDH9)H)CD1CD$1HftCD9’CDI-b•0ftH-CDHdHCDpCDbH‘1H0‘10ZCDH-H-H-CD‘dICDC)CDCDdH-1CDCDCl)Cl)CDI-C11I-CQH-•H-H-H-H-CD9)9)0000CDCD0I-C9)CD$2CDCD‘1-ClH)CD‘-3H)09)0CibI-CftH CDCiH9)ft—01ftCDCD ‘-—.9)H-+H--CZI-C9)CD0I-HH$2Hft9)HCi9)H-H-CDft0ftftH-CDCDI-C<9)H)CiH-CDtTftCDHI-CCl)CDCl)CDft-ftCD+-‘1ft‘-CoCD0ClClI-CH-H-CiH-‘.QCDH0pH-H•-.CDCDCDftI-C C)-CDftH-0ClCiCDCiCl)pCDCDCDCDH-ft I-CCDH-H-‘-CC))CD‘I-CCDHCD ‘-C0H)H)9)‘-Cft0ftCDH-HCDCDCD9’LQftdH-CD‘-C<ftCD:$H-CD9)CD‘10i<CDCDdftCDC))CD‘-CH-I-CftH-C))9)CDH-0HHI-CCD71However, if this is the case, one would expect acorrespondingly higher output price.6) The frozen vegetables data are strongly influencedby lower prices in Canada of potatoes, used in theproduction of frozen french fries.7) Among the industries having higher relative outputprices are, again, a group of trade protectedindustries (poultry, milk, butter, cheese, icecream, flour, beer, wine).8) Substantially lower relative output prices are seenfor bread, sugar, peanuts, canned mushrooms, juice,cake mix, and breakfast cereals. The case forsugar is discussed above while the lower domesticprice for bread may be due to producing lesselaborate bread.The productivity comparisons were calculated usingequation (52). Data required for computing the numerator, therelative output quantity index, were contained in the OUTPUTdatabase. For each industry, these calculations requiredcommodity data for relative shipment quantities and averageshipment shares. U.S. commodity quantities for 1986 werederived by dividing estimated 1986 shipments by 1986 U.S. unitvalues.72Calculation of the denominator of equation (52), theimplicit input quantity index, required the relative inputprice indexes developed for the three variable inputs;materials, (PMj), labour (LJ)’ and energy (EJ) correspondingto equation (64), equation (91), and Appendix D, respectively.The results of the productivity comparison are reportedin Table 6. The results indicate that, on average, theCanadian food manufacturing industries have 7.6 percent lowerphysical productivity than their U.S. counterparts. Theestimates are widely dispersed, from about 56 percent to about123 percent of the U.S. industry benchmarks. Of the 38industries, 9 were found to have relatively higher Canadianproductivity. Notable among the lower ranked are some wellknown trade protected industries (wine, poultry, and milk).73Table 5 Calculated Values for Canada/U.S Relative Outputand Materials Input Price Indexes. 1986Relative Output Price Relative MaterialsIndex Input Price Index1 Beef 0.994 1.0162 Pork 0.959 1.0093 Pork processing 1.007 0.9834 Sausages 0.928 0.9635 Inedible tallow 1.046 1.0206 Poultry 1.259 1.1717 Canned vegetables 1.322 1.0698 Canned mushrooms 0.871 0.8589 Juice 0.854 1.09210 Jams & jellies 1.265 1.55711 Frozen vegetables 0.911 0.71912 Milk 1.434 1.20313 Butter 1.133 1.26014 Cheese 1.301 1.26415 Milk powder 1.087 1.28416 Ice cream 1.263 1.04417 Flour 1.436 1.63118 Cake mix 0.755 1.07719 Breakfast cereals 0.634 0.93120 Feed 0.934 1.08621 Dog & cat food 1.005 1.12222 Vegetable Oil 1.052 1.16623 Biscuits 1.103 1.15324 Bread 0.855 1.55225 Sugar 0.B03 0.42526 Chewing gum 1.046 0.92827 Confectionery 0.936 0.97428 Coffee 1.104 1.44529 Pasts 0.959 1.41030 Chip & popcorn 1.206 1.00931 Peanut butter 0.709 1.10732 Starch 1.245 1.21333 Peanuts 0.851 1.10634 Shortening & margarine 0.953 1.10635 Soft drinks 1.010 1.05436 Beer 1.167 1.11737 Wine 1.624 1.35138 Smoking tobacco 1.067 0.929Averaoe 1.044 1.11074Tatile 6 Estimates of Canada/U.S Relative Physical Productivity, 1966Relative Output Relative Input Relative PhysicalQuantity Index Quantity Index Productivity(X) (I) (X/l)1 Beef 0.095 0.095 0,9962 Pork 0.164 0.167 0.9793 Pork processing 0.134 0.139 0.9644 Sausages 0.071 0.075 0.949S Inedible tallow 0.119 0.130 0.9166 Poultry 0.085 0,102 0.8217 Canned vegetables 0.121 0.139 0.8738 Canned mushrooms 0.122 0.129 0.9459 Juice 0.179 0.188 0.95010 Jams & jellies 0.043 0.046 0.74111 Frozen vegetables 0.166 0.201 0.80612 Milk 0.077 0.099 0.78113 Butter 0.270 0.263 1.02614 Cheese 0.083 0.084 0.99415 Milk powder 0.115 0.120 0.95516 Ice cream 0.097 0.095 1.02917 Flour 0.109 0.113 0.95518 Cake mix 0.100 0.087 1.15119 Breakfast cereals 0.065 0.061 1.06820 Feed 0.175 0.172 1.01421 Dog & cat food 0.044 0.044 1.01022 Vegetable oil 0.064 0.059 1.08623 Biscuits 0.055 0.088 0.62424 Bread 0.086 0.082 1.05025 Sugar 0.134 0.146 0.91926 Chewing gum 0.144 0.221 0.65027 Confectionery 0.053 0.060 0.69528 Coffee 0.074 0.060 1.22529 Pasta 0.096 0.124 0.77330 Chip & popcorn 0.061 0.108 0.56231 Peanut butter 0.145 0.151 0.96432 Starch 0.076 0.076 0.99333 Peanuts 0.051 0.054 0.93834 Shortening & margarine 0.037 0.038 0.96535 Soft drinks 0.062 0.069 0.89736 Beer 0.099 0.109 0.90537 Wine 0.037 0.046 0.80138 Smoking tobacco 0.076 0.081 0.940Averaoe 0.100 0.109 0.924‘dHC)C)HCDH-H-‘III-ftQ00QH,ftU)C)U)i0HCDCDU)U)t’JH‘-3‘1CDU)U)IftH—ftU)U)IIZH-CDP)))H-CDk<U)U)ftC)-H,C)CDC)II0LQftH-oFl0ft‘-3ftP)ftIiCDC)Cl-‘-3‘1‘CDCD•H-ftU)oFlFlCD0tYFlH-H,0FlP)HFlCDCl-0U)CD0FlU)‘<CDCDP)CDH-H,P)0CDftHCD0CDH-HH0ftU)CDCD‘dftb0U)H,CDCDC))0H0FlHctftftC)0C))CDC)HFlLQtSFlC))HH-ftHH-FlU)ftIIFlHH-C))tU)ftC)ftU)k<H-U)U)CDHU)(DU)ftftCDCDH0H-H-•-H,CDU)-H•ClCDftH-U)Cl0H,CD0H,H-C)HH-CDFlHCDQ‘<0C))CDC))<CDft0cFlftU)HCDU)H-U)H-H,CDH-CDFlCD 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H-CDftftH-JH)CCDCD<C))H-CD(PCDEn-f-H-CDr.HSH)C))H-H En(PoCDEnHCDCDftC)’><<ftH-CDClH-En1<<ft-CDHftCUftftC))frCT)hCCDCDH-C))CDoClftLLCD‘-C)‘1C))•Hb’‘1ClC))HH-C))CDCDC)ClC)’0EnCDH--ftC))H1CD0ft-C’)ftftH-HH-ftC))CDClC)CDCDC))<0EnftHCCDCDftHHH-H-H-0HCl,oClHClH-ftEnft0En‘-CH-CDCDH-ftoC))C))‘1C)‘CDftCDftHoH-HC))H)ftC))CDCDftEnH-<C)’H-IIH-CCDCCUp,Cl-CftftH HH-C))0C)HHCloEn‘<iftCDEnH-CDdC)’titT0ftiEnC)00ftH‘CDH)EnCDIH-ClH-C)0C)ft‘-300•CUH)HC)U)CDCDHHftMCUC)’C))CD(PClft‘1C))-CThH-CDp,H--EnC)C))EnoCDH-CliC),HClH-ClftCUH-CD-0En‘CDHHCDHftC))C))CDCUCDC))CDClHEnH-En‘-C‘-CCDftCDCDC)HHCD EnC))CDt-ftCDCDftH-H-HC))CDftft‘1H-CDftCDHC)<C))<C)0ft0C))CD0CDEnH‘1CUClftCD,-C)CD‘-CCDC))HjEnC))C)ClCUH-H-C)H-HHH-CDHi-H)H0crjHCUC’CDCiH0CDCD—.C)CD‘C))•‘1-U)<C)ClClH-Cl-CDCiH-H-C))•ftC)C)C))HCl)0CDCDiiEn•CDC))HEnC))‘-30C))Ci ‘-CH CDC) 0wi EnCDft H-oft Ci(1)ft•CD En.LF-C 0 C) CD Cl Ci ‘-C CDC)ftbH)HU)H0C))H00C)CD100C))IISiCDftH‘1H-t-SiHCD-C)HHoC))CDC))01ft-CD<:C))b•C))CDH-C)-I-D)C).U)SILQ00C))CDCDSIxdCDCD—.0CD<U)C)ftCDC))H0CD<HH-CDCDSift‘-‘s-C))HzCDCD8SISI H-U)CDCDftHHSIC))IIC)H-0H<ftCDI:’jC))H-H-U)X<<C)(T—ftCDCDHCDC)HSi<HSIH-HH‘tiLQCDSiSiftH-ftCDU--CDCDU)ft‘dH-C)H-0U)CDftSiU)0HH 01—U)‘1•C)0‘<0100iHr1I‘tiSiCDftClCDC)C))II:jF-H-C)C))H-hCDO’H-ftH<U)—H)—çt—U)ftSIfthH-CDoCDH)0HH)C))H-CDftzJftCDSICDU)SiiC))SiU)C)ftHftCD0ft1U)C))CDIISI:iC))CDp,SiH-jCDftftSI::•rJ)CD1D•H-0HCDH)CD8ftCD:Cl0U)C)C)C))0CD U)ftH)H CDftH-SI0SIftH-ClU)H)SiCDC)CDH‘d1CDCDU)ftC))SiH- C)SiC))H-HH-C))H-HLQftIIft0ft0H)‘tiCDCl‘1SISi0-C)_SIftC)ftSiC))H-CDC)<U)ftCDH-ftH-11ft-<C))H-H-QC)’ftCD0Zft-<U)H)Cl0C)CD::0C))H-U)H‘tiSiCDCDI—aiftCDHH-CDCD CD(_)—H) 0 ‘1HCDCt)HoC))CiH-H-CDC))SI(_)SiSIC))ftCDU.‘-0-C), ii H- C), H CD C) 0 U) ft C)) ft CD H- C)) H U)H<IIIICDCDHHC))C))ftftH-H<<CDCDC_)()C))C))C)’C))ClSIC))C))C1)(I) 0H-Si ftSiSiftftSiSiC))C))ftftH-H-ftft‘-<1<H-HSISICDCD‘<x78Table 7 Estimated Measures of Competitiveness1 2 3 4 5 6Relative Relative RelativeOutput Input TotalQuantity Quantity VariableIndex Index Costs(X) (I) (C) dx I/X C/i1 Beef 0.095 0.095 0.097 1.019 1.004 1.0142 Pork 0.164 0.167 0.168 1.026 1.021 1.0053 Pork processing 0.134 0.139 0.137 1.022 1.038 0.9854 Sausages 0.071 0.075 0.072 1.020 1.053 0.9685 inedible tallow 0.119 0.130 0.131 1.103 1.092 1.0106 Poultry 0.085 0.102 0.112 1.328 1.218 1.0907 Canned vegetables 0.121 0.139 0.142 1.177 1.145 1.0278 Canned mushrooms 0.122 0.129 0.112 0.927 1.058 0.8769 Juice 0.179 0.188 0.199 1.124 1.053 1.06710 Jams & jellies 0.043 0.046 0.065 1.207 1.349 0.89511 Frozen vegetables 0.166 0.201 0.153 0.920 1.241 0.74212 Milk 0.077 0.099 0.115 1.483 1.281 1.15813 Butter 0.270 0.263 0.325 1.206 0.975 1.23714 Cheese 0.083 0.084 0.103 1.231 1.006 1.22415 Milk powder 0.115 0.120 0.147 1.275 1.047 1.21716 Ice cream 0.097 0.095 0.095 0.979 0.972 1.00817 Flour 0.109 0.113 0.173 1.593 1.047 1.52218 Cake mix 0.100 0.087 1.151 0.694 0.869 1.02919 Breakfast cereals 0.065 0.061 1.068 0.846 0.937 0.90320 Feed 0.175 0.172 1.014 1.010 0.986 1.02421 Dog & cat food 0.044 0.044 1.010 1.053 0.99 1.06422 Vegetable ml 0.064 0.059 1.086 1.064 0.921 1.15523 Biscuits 0.055 0.088 0.824 1.597 1.603 0.99624 Bread 0.086 0.082 1.050 1.127 0.953 1.18325 Sugar 0.134 0.148 0.919 0.530 1.089 0.48726 Chewing gum 0.144 0.221 0.650 1.369 1.539 0.88927 Confectionery 0.053 0.060 0.895 1.035 1.118 0.92628 Coffee 0.074 0.060 1.225 1.107 0.816 1.35729 Pasta 0.096 0.124 0.773 1.606 1.294 1.24130 Chip & popcorn 0.061 0.108 0.562 1.716 1.779 0.96431 Peanut butler 0.145 0.151 0.964 1.121 1.037 1.08132 Starch 0.076 0.076 0.993 1.149 1.007 1.14133 Peanuts 0.051 0.054 0.938 1.136 1.068 1.06634 Shortening & margarine 0.037 0.038 0.965 1.119 1,037 1.08035 Soft drinks 0.062 0.069 0.897 1.132 1.114 1.01636 Beer 0.099 0.109 0.905 1.111 1.105 1.00537 Wine 0.037 0.046 0.801 1.529 1.249 1.22438 Smoking tobacco 0.076 0.081 0.940 1.010 1.063 0.950Averaae 0.100 0.108 0.930 1.155 1.110 1.048Next, a correlation matrix was calculated to determine ifany linear relationships existed between the variables (Table8). High correlation between two variables is not proof ofcausality. It could be that two variables are stronglyo0CtC)H)U)tiCDU)00C)U)ç1C)Cto-QHU)CDCDU)<HhiçthiU)U)tiCDU)H-siU)hiCl—9)U)H-H-•HCDC)U)U)U)C)k<CD0HHCtH)CDU)CtCH) oCthiCDCDCtCDhiHhiCDH9)ti’•-<CDhiH--H-hiCDU)U)CtI-U):Ho0C)CDU)CD 9)H-H-Ct5H-hiHsiCDCtClCDCtU)H-CDqU)CtC)U)tiU)Ct-Ct H-oU)Ct-HhiCtCDH-CDU)C)C)CDCt0HH-hibH)U)hiClCDH-CDCDhihiHClCtU)H-Ct Hti)0CtH-0HHC)HhiU)CD‘-dCDCDCtH-C)CDCt0CtCDU)U)tICDU)H0hi9)H-H-CtCDtSNCtt5U)ClCDCDClU)H-tiCDU)C)H-hiU)z-U)H-0U)U)U)0CtCDCDHhiClClU)ClH-H-hitiC)0CtU)0ItTCtH-Ht3 ClCDCDH-H)CtU)H)<CDH-CDtiC)0U)HCtH-CDCD00C)—U)CDU)00CD xHCDH-0Hti0U)dCDH)H-CihitiCtCtCDtiClC)‘-CCD0‘-CCtCDU)tiU)Ct09)CtCDClH)H-‘-C0‘•tCtCthi-hiC)rH-H)CttiC)U)H-Cl4U)0CtU)hihioCD-HZiH<C)ZH0<C)C)IIIIIICDHHC)oCDCDCD0HHHhiCDCDU)U)U)hiIIHHCtCtCtCDU)U)H-H-H-HHCtCt<<<U)tiH-H-CDCDCDCt<:<<H-CDCDCDC)C)C)0hiU)U)U)tiU)H-0tiCDtiU)U)U)CtClClClU)odU)U)U)CtH)CthiCtcccH‘dC)•Xhi0C)U)U)U)oU)0••H-ClCtU)0U)CtH-iC)C)tiCtU)dCt0C)tYhihiH-0CiH-CDCtCtU)U)H-CDCDCtCtCD.QHti<H-CtgiCDCtCtH-U)U)CD—H-CttitiC)ClX<H-CtCt0CD<H-H-U)H-HtiCDCtCtCt:iCDti‘<‘<U)CDU)U)H-H-U)U)ti ClClHCDCDCDx><cci CD hi CD9) H) H, CD C) Ct CD Cl U) Ct H- hi Cl U) hi H- U) H CD (I) H H CD C) 0 hi hi CD H U) Ct H 0 H- U) U) CD U) U) hi CD0 Ct CD CD hi U) Ct 0 hi 0 H) H z Ii 0 U) Cl Ct CD Cl CD 0 H U) Ct 0 hi 0 H) H C) Ct CD hi CD0 CD CD hi H CD Ct U) Ct H Ct CD H Ct U) Ct H Ct H Cl CD x U) CD U) hi U)C)C)-000hi0HhiC)ClCD0Hti9)CDH-H-CttiU)H-Ctd0U)H-I-<H-CtCDCDCtCtH °U)CDhiCtCDU)0H-ClHCl‘‘ C)H z‘dU)9)<:0Ct‘tJU)hiClHCtH,-,H-U)zCD‘iiHCD0C)Cl•hiCthiU)U)y0CtCtCDCDH-H-Clb--0 H) Ct CD hi 0 U) U) 9) U) U) 0 C) H- U) Ct H 0 CD Ct CD CD Ct 0 U) hi H- U) H CD U)H Ct H- U) 0 Ct U) hi hi H- U) H Ct U) Ct 0 Ct Ct C) 0 U) Ct C) 0 CD Ct H Ct H CD CD U) U)ft Di 0 CD H H H- C) 0 ft CD C) ft H 0 H CD Di U) ft 0 H CD ‘1 H 0 C) Dl H tt H-C) CD U)t—l:y-b•’CtCDCDICDDiCD0H‘1CDDl1CiDiH--HftH-CDftH-CDH-1<1HDlP-<CDInU)g-DiHftI—•DlCD<:CDCD—CDU) ftci-fr,H-C)ftH-.•CDC)CDCDCDU)H0•C)H)0(-hi0oCD‘-‘Hi-30CD (fl‘0iH-CDU)-U)C)0dftH)0H)H-H-HHHftC)CDDiCDU)H-CD:iCDt5•CDIjt-.0CD—0C)CD0H-CDC)C)0CDftHCD—3t’iCDCDDiH--o0H)-pftU)0IH-H)U)CDftU)HftDift0‘1CDci-H-CDHCDDlH)ftCD-U)H)C_)C)Dl0<CD:HDl0CDftHH-0HDlCDft0U)CDH)H-U)-H)0Di0l:j_HHCDcI101C)H-H-CDCDU)U)0U)U)CDft0CDft_<)CDU)HHCDft0C)Dl0ftftC)CDH-ft‘1:iDiU)h)iHCDCDdr’jHH•riD)0 -CDCDH-HU)ci-ftCDCD1‘1P.’CDH-‘.<ftH-C)‘tDiCD0CDftH-U)CD U)ftIIH-.H-InIo•CDU)CDftCDH) H-CDDl‘10DlU)Hft-ci-ftDlci-P1H0I-Ift0CDCD$1‘—E’DlCDpiU) U)C)Ho‘-<CDC) H- Di ftH-CDdU)CD i‘tiH)hH-Q0ftl:3 DiDiHCDC) CDH)ci00Di ftDl0ftC)CD:J•CDCD,-.H -H-ft-U)CD,--00-ftQU)H)ftCDC)0•0 CDCDft<H-H-ft H-CD< CDC) CDCD U)0U)H)(I) II H- 0 U) CD CD H) 0 11 CD ft CD 0 U) ci ‘1 CD Di U) 0 Di H CD C) 0 C) H U) H 0 ci- 0 Dl0 U) H H- H H- ci ci Di ci ft CD‘ODDl CD Dl ft H CD C) 0 II CD H Dl ci- H- 0 H- Cl)81Table 8 Correlation Matrix of Canada/U.S Relative Competitiveness Variables, 1986X 1.0000.946 1.000C 0.909 0.912 1.000ROC -0.239 -0.077 0.158 1.000RIC -0.157 -0.247 0.143 0.624 1.000INVPROD -0.125 0.172 -0.075 0.630 -0.207 1.000X I C ROC RIC NVPRODC = Relative Canada/U.S variable costX Relative Canada/U.S output quantity indexI = Relative Canada/U.S input quantity indexROC Relative output cost competitivenessRIC = Relative input cost competitvenessINVPROD = Inverse of productivityH-0HQ.(U(:I-H-HU)C)H)QftU)0-ft0U)Ct)1H-‘1U)d0HU)0 C)U)HH-CD‘ftC)I_QU)(UInft0U)(UIHU)(U‘1HH-(U‘<U)tn H-(UHInHftoU)ft00(UI-H) 0HCi‘10i(UPHHftCiU) ftCDH-(UU)(UHtt3Ci-H1H—0ft(1U)U)Ci‘—‘C)H)Cift0ftH)H-Ci(UU)XC)H-(1ftftftCii<t3ti(UH-H-tiH(UU)L.QU)H-H-C) 0C)Ci‘t‘1(U(UftHC)H-U)InH-ft<0(UC)i‘1U)(U()0(U0cn0 o•dU)I-(U(UH-(UHHU)ftU)U)(UHftftH 0(U01H-10CD(UInU)In U)‘dU)(UH) 0U)U)(U(UH-H)(UH)ftCi0ft0CiCi(U U)t:3-H-ft0Ci(UU)U)ft4(_)U)I-•Ci0aU)U)ti(U(UU)(U(Uti(U<C)Ci0H- CDft(U Ii)C)H(UftC)(U0‘1(U0U)U)0(UiQftH)ti(UHC)H-H-U)—(U(UHU)t-l.<H-HU)H-0H-CiC)ftU)p CiU)U)(1ftH-‘1H- C) (U U)tU)-U)U)(UH-0H-HftU) ftU)ti(Uft0 Ci0H- ft(U0)H-0 Ci“ftC)r(Uft(UfttiHt3C)U)ft1•U) <U)(UU)U) LQ0(Uft-(U(Ut-H(UHHU) CiftHH-ft(UC)H<H-H-U)ftC)H-JC)ftU)t-H(U U)ft(UU)C)ftH-HHHH- ftH)U)0)cftft-0Cr2(U C)C)U)0iCiU)CiH-C)(UU)ft H-U)H-H- ftft0oH)H-C)H-C)i00QCi(1iCiCiU)U)ftU)ftftt-fttit-H-tiCiCDk<C)IU)ftft•(U0d1U)H-H-In‘1p(UCiC)0U)0CiftClH--ftCl (Uftft2U)(UU)HH-HCl(UH-Cl-+HH-C)U)U)-,ftb‘-U)U)U)(Uh(H-0H0(1U)ClH)Ci0(UU)C)xU)(U0HU)H)CiU)CDftCl0t5H(U(i(U<:ftft(UftU) dU)ft 0U)(UftU)ClU)C)U)Cl(Uft-H-C)(Uftft‘)C)o•ft00)CiSC)0H-0ClU)CiClpC)HftftU)ft-zH-H)ft0k<0-Cl(Uft 0t 0(UC)H-0CiClH-(UCiH-H-U)(U Cl fttj0H-U)CiU)U)ftU)Cl Cl (UU)tJ_U)H-CDU)H 0C)ftU)0H-HU)H-‘1ft0H--tYCl0LJCDH-tiCD-0U)ft•H)In-I-E3 (U 0 U (U C) ft H (U 0 H) ft (U ft (U U) H- U) U) U) ft 0 Cl (U ft (U H (U 0 (U H H ft (UC) 0 (Ut-3ft:jH‘1ft(UH-(U< (U (U U) U)Fl 0<ClU)CiH-C)C)ftU)H-HH- ftCl(U U)C)U)ftCiH-FlH(U ftCi U) H—.1 C) 0 C) H Ci U) H- 0 U)OD (‘083Canadian manufacturing? Second, given that this studyconfirms, for the most part, the findings of other studieswith respect to the relative productivity of the Canadianindustry, some attempt should now be made to explain thesedifferences in productivity performance. Finally, if bothdata and project financing requirements could be satisfied,case studies could be performed on individual industries toallow a better understanding of the reasons behind theproductivity shortfall of Canadian food manufacturingindustries.1)1)C)C)C)C)H-CDCDP)0)0)0)0)0)CDCD0)0)HHCDCDCD0))CDCD<<H--EnEnEnHHHt-CIH--CIC)GQ0)IQC)-HOirDr--JiC)tTbiCflH-CDc-i-c-i-oCDO-hQ0)10)0(.)HJCDLCDCDOts)En0000)C)-QCDo0)c-iIOEnH—0‘O(D{0HEnfr0)<-—CD-O0)-C)<QEnCDH-C)ct-•0)-H-!frrtrjOH-WCDO1-bCDEnCDOiiHIC)—)CDftc-i--ICD’iiCD1jjiH-jC)HrJ—i0)(/)OHCDqEn•tti0Q00)ctEnZID)ftHC)0)C)H•-Hl.0)tilEnrtCDI-CDp,(flOp)•CD-I-H-OHHftp)HQHCDdiH-H-C)•H-CH-CDH-OQftHftpH-ftp)HCDWC)ftCD<CDCDOHiH-,.‘C(r<CD(fliCDCDt’JEnOEnHHHH00CDO-‘OH-Il‘..DEnH•0)ftct’CDpMftP)H.0)ftftqMEn<H-QCD<tiiP)H-CD:ip’ii•4oHti0ZC)HjH-l1<H--0)H1ft?H-WH---(nOftH-H‘D0)-(f)1P)Cl-0(n<.H-—JCDpCD0)tCDCDCD-<ClftCD•o•CDCl•p)<C)jClC))Lp)H--.HcftcH-•IQQHHO-CDEnC)HH-OOEnH-ftfrHp)-1t!)paiEnQc-i-H-0CDHC)CDEnQEn<-dOCi<PftCDHIEnC)OCDCDO-i‘-‘1H-C.0En1EnH-CDctflC)HOQCClEnp)HH-ftftH-tiClEnHEnp)ftOI0•0CD0)ftC)ftP)Qft-‘rjH-O’HCI)HClC)CDftF-CDp)OOEnH000ftIH---ClP)HP)CD-H-ZEn<OEnEnCDH-JC)QCDI1<CjCDCDCDOCDH-ClWHCDH-iftH-Eni-CCli<•H-CDEn-H-’t3-CDHCDH.0H-EnCDftftCDOHfto0)CDCDICD0)CD()OClH-H°ftEnH-HH-1U1C)LftC)ftcEnxCD1<H0H-H))C)p)•H-.qH-o<EnCloC)ftoo0oClOH)OH-i-SQH.H--CDft0H-a H-C)0H-ICH1_c:,Clft0p,0)CDCDClOC1.CDi-IIfr<HOH.CDOH-CD(riH-<H0)EnIftCDCDtxjJCD1(n20)P)ftCD-HC)CDftHCDHEnH-CCDHEnH-0P)ClftItilpj0Ct3Q0)H-iCCDC)•.ftH)En•I°C)°CD0)CDH-0)H<P)‘-<EnftU1H0H0)ftlt1ft‘doIIHCl0)P)(nOHCDH(I]•OH0CDDftCDH-CDOftH----IHEn0)ftC)C—.I-CDgC)‘-oICaH-Cl<C)CCDlCD•ftH-ft4P)0)GCD’iCEnH-CDH-P)ZEnftftlCD10O(fift—QH-(.)H0-3IH-0)-fttC)tIP)(nJ-:J-IOCl-.0“CDICDftIC).‘-<ftEnClH•CDCDII-b(I)‘rJ00H-HH0NNNCDCDCDH-H-—HHHCDCDCDH-CDCDCDOH-0‘ii(fl0t’i0ctWP)bQQQQ(flWO-tHChCo<iH-H-o-‘0-OCDH-tip-’-op’-QCnH---r1-ctCDct0I1ddXiP)XHCDOLQCDIH)Efl’QCDD)D).D)0-P)P)H—<rt$D)CDH(DCD--J(DQ)CDCD.çioH-1H-OctCDH-Q(I)O-Cl)-HP)CU)CDC00bfrCl)0H-:•(DCl)HCtHQU)HCl)‘-QCDCD(DCD.tflQ-.H-NQ0Cl)I-’-QH-,<(RI1CflCDIIHOw0H-CflCD0C))p)HHCDH-tHH-H-0•TJH-ctU)(flctHH-CDPJ<oZ-H-pjWctH.CD0CDCD0C),-,Clt3)H)‘dH)‘z5°OOl4EflClJ-tn0jctHCDOCDH-ClQH)pH-H-—CD‘cCl)CDH-(tH)jp)HoEn-DCtwoClH-o)00EnW0CX)U)CDHH-cD-CD• Cl0CDCDCD3‘0IjHCD0CtH-)Qrtct<OH-CDPJClO0ct(I)Ct(Cloct-CDClot0CDHLT1H.HctjCl)CDCtH-lU)pCD‘-—cttH<H0HHHCl)C)EnHOHCtH-0000CDCl)H-‘-ti0H-1Cl)Cl)p)O<0ClClH)H-OCDOD)rtHD’CDCD(fl<HCtCD3Ct.,.C)CDCDctClOH.CDrtci-nwp)Hq,0)H-•CDClCl)H-1--0)0CDO<ClJCtCtH-H-(Dt(flQH-U)HUip0Hii.<CDcCl)iCDCDCl-’Cl’<O0)H)tCl)CD.D)oClClct0°HH-0F-ClH-0ClCl)EnH-(flCD°H-1-tClClCD0CDCDctCDU)0H)j!0‘-rjCDCl)CDZCD<CDH-ctCD0Cl)CD,HCoo0CDt-I-t•H-CDClctCD‘‘HHH-txj,0H-EnCt0(Cl0ClCDH°CDCCDCDCDop,Clt’I‘1‘CDH-HCD0H-CDHrtH;rJ)OZ04ctCDCl)ictH-OH)U)HCtç1HCl-O))QOH-C!)CD-H)HCl0.tiH00‘-<o‘-tgCDCD0)HHn•CDtctU)0’Q0)H0H-CD00U)oOctC1ClH-OCHH-CtEn0H-•0ctH-t1IH)H)U)Cl0OH-•H0CDH-0CDOOClEI)0fl-O00CDCi‘-<Hi’-ICDH-5CCEn00OH-H)0ctct0IH-OH-U)CDCtCl)CDHU)CDCDClH-ctCoCDCH-H-CiClctHCD•’-cSctCDctU)IICtCtWOCtCl)H-HHH‘-0Cl)ctH-1Enct<0CD‘0H-H-Cl)Cl<0)ctI-H-0Ci1H-H-H-0Cl)H-H-H-Cl)—1CtCtCtCtHM3O0000P)H-Cl)Cl)1OClOCt03—10‘-<‘-<(DCt•CDCDCDCDH)H)H)-HHQ(nEnCl‘-<ClCDCD••CD•ftftCl)(I)(n(1)ft•.ftft H(1)HH-OQi-CI)CDCDF-riftUftP)OtxjQd(flO3rj51(l)HCDCiCiCDft<0cio)biflXP)j-X—(D(flhW0.çpft(flW-j-WHj-•‘.<(IDftftH-•CDO0?oHftft51ftHCDH0HCD0)Ob<H)0a•iI-tbH0ft00CDCQ(tH-CD<iCD0CDCDC_)(D0D)Cl)-CDCDhCD‘&? ftHCfl51H0HP)iODH0‘DH5100ftCn(‘.CDCl)CDI—ft<P)H(‘iCDC!)53pl)WCCDftftc-i-C)I.0H)51H-CD051lH51D)Of\)C))CflIIftH-HbHHO0ftH-CDH-CD0fto-j-ftiQHH-C)CDCDCDçHft51CDHQHU)(.)U)C))‘1‘0CDCDOC.Jftl—1,._-HHac’di-JH•H(toiCD51h5HOO‘1(no•IctCDC))51CDH-HHCflHCDC))H0Dc-toH-ii00C))0CD(n—)‘<CCDHAppendix A1.2.3.plants4.Canada/U.S. Industry Concordance1011 Slaughterers & Meat ProcessorsBeefPorkProcessed porkSausages877.8.9.10.1031 Canned & Preserved Fruit &Vegetable IndustryCanned vegetablesCanned mushroomsCanned fruit juiceJams & jellies1049 Other Dairy Products IndustryButterCheeseMilk powderIce creamCanned vegetables, except mushroomsCanned mushroomsCanned fruit juicesJams, jellies, & preservesCanadian Industry U.S. Industry20111 Beef, not canned or sausage20112 Veal, not canned or sausage20113 Lamb & mutton, not canned or sausage20114 Pork, not canned or sausage20116 Pork, prcssd or cured, made in meat plants20136 Pork, prcssd or cured, not made in meat20117 Sausages & smir prdcts, made in meat plants20136 Other prcssd meats, not made in meat plants20137 Sausages & smlr prdcts, not made in meat20138 Canned meats, not made in meat plants20771 Grease & inedible tallow2015 Poultry slaughtering & processingplants5. Inedible tallow6. 1012 Poultry Products Industry20332203332033A2033811. 1032 Frozen Fruit & VegetableIndustry12. 1041 Fluid milk Industry20372 Frozen vegetables2026 Fluid milk13.1415.16.20212022-20263202352023620238Creamery butterCheese, natural & processedCottage cheeseDry milk powderCanned mik products2024 Ice creamIce cream mix17. 1051 Cereal Grain Flour Industry1052 Prepared Flour Mixes & PreparedCereal Foods IndustryCake mix20411 Wheat flour, except flour mixes18. 2045 Prepared cake mixes & doughs19. Breakfast cereals1053 Feed Industry31.FeedDog & cat food206220632067206520662099D209520982096Cane sugar refiningBeet sugarChewing gumConfectionery productsChocolate & cocoa productsTea in consumer packagesRoasted CoffeeMacaroni & spaghettiPotatoe chips & similar products32.33.34.35.36.37.38.Manufactured starchNuts & seedsEdible fats & oilsBottled & canned soft drinksMalt beveragesWines, brandy, & brandy spiritsChewing & smoking tobacco882043 Cereal breakfast foods2048 Prepared feeds2047 Dog & cat food2075 Soybean oil mills2052 Cookies & crackers2051 Bread, cake, & related products20.2122. 1061 Vegetable Oil Mills (ExceptCorn Oil)23. 1071 Biscuit Industry24. 1072 Bread & Other BakeryProducts Industry25. 1081 Cane & Beet Sugar Industry26. 1082 Chewing Gum Industry27. 1083 Sugar & Chocolate ConfectioneryIndustry1091 Tea & Coffee Industry28.29. 1092 Dry Pasta Products Industry30. 1093 Potatoe Chip, Pretzel, &Popcorn Industry1098 Other Food ProductsIndustries n.e.c.Peanut butter 2099F Peanut butterStarch 20462Peanuts 2068Shortening & margerine 20791111 Soft drinks 20861131 Beer 20821141 Wine 20841221 Smoking tobacco 21310 CD CDCDCD-•HCl)XInCDH-Ct(j)CDCD0H-Cttxi02:CDCDtiCDCDHCDInInCDCDCDCtInCDCDCD‘.P0H0CtCt000CDH-CtCtCDCDSiSiU)-CtHCDH-CDInII0HCDCDiiCtS-bCDHiDtu1H-CD0CtcDO’\H CDTIIISICDITCt0CDC)0C)C)pU)0c’CDU,CDH-P3C)Cl)0 II i)Ct—CDCl) HH-OHH 0 HHHSi CtC,)CD.9H ftCDH-CDH CD C,) ft ft CDN>C)II 0II-$10H-H10 U]Ho1w-H-U]10Oj0III\) U]ft C)OD00tJU)Hft0W 00HHCD0< CD HHC,)W CO ‘.0CD0 0CDZG’C)0CDCiiCD(-IHHCD+CD(I)CD0)ctCDC)000CDH• 0))CDUiHCDCDCDHCDc-C.CDIICDCD0H--JCDCD0Cl0II0H-N>(iiCD•HUiN>CCCDUiU)N>CDN>I>0IIC-IICDCC00) UiCDIIç--0C)HCDN>0HU)H-HH-—)I-CDHQ_H10HHH-dU)HHHC.’.)cohoCDHUi0)0to—II0)0CD0--H--0CD00çt0)‘1HLQwC)00-0)o—toUiCD0CCj—H)C)—toH)0H-U)II0C)Ct0)0)CiiCDtoU)0)toIn0CD Cl CDCDD)CDCs CD tiD)HH CD0Cs-HC))NN(_CDCI)NN0H0IICD$))CDCDC0CD CDrtct00CD(DCI)o0k-0••00H•0p00GDpoUi-I))-ViWNHIIH-JP0oHViPII0CDHCDcnoHCD>-0L\)-0wHt\.)H-000MCDGDCD 0Il) rs--00__HCDGD00GD•0•00w0CDU]00CD00U)GDt-bU)‘._n—.1IIGD0II(_)II0IIU)D)-Ht>s)GDGDCDHU)I))IIU)0GDU]H-0GD 0:iUiCDU) GDU]H U) CtHp)Cl) fti-3H)‘1H-H-Ci)CDftNH(I)F-’-C)CD—CDft oft-0NNftftt3)0CDHI’CD0to-wft(31p)ww‘1ft0)CDCD+ftH))H-totoftl))toCDHtoCDtoH-+0) toC)-jSi0a)CDCD—.1Hftft-IICD+0I-<to—I0ftSt)Hooft‘1II+p)a)H •ft0)0)CDII—3 0H-0CD :1) ‘1 CD ft CDD .n_CDItC,CDCDCDCD(DxCD (‘3000)o-U(fl-Urt7====(noii•)(--v-CD—CDCC)0)0CC)U-a(‘3CD(‘3CC),.t-,(‘3—3CDCD—.CC,—C)CD000-<D0CC)—D3CC).-t‘2.H-U-CC)30—,CD:3CD3CDCDD_- (‘3CD—C) 0CD-3-.-EnCD-0<lCD:3 CDUC)CDCD00:37(CD‘-0CD0.C-,CDCDHCD-•---C);C3CDI—’C)CD0p):3(‘rtC-,2.-CDCD0CD:-••C-,,:3C)—(CJL,J0.CDC))-OC)-EnCD•d(’cCD•0_Cl)-(I)C’) CD -3 CD C’) 0 -h-o CC) 0 ‘.3-CD CD : (095Table A2 Calculation of a Packaging Cost IndexPackaging coat share of totel packaging cost (%) Share ofpackaging cost inPaper & Packaging cost indexCanadian SIC Metal Glass Plastic total cost (%)Board1011 15 0 50 35 3 1.171012 5 0 70 25 5 1.171031 60 25 15 0 30 1.321032 15 0 75 10 15 1.21041 0 0 60 40 7 1.141049 15 15 40 30 6 1.191051 0 0 90 10 3 1.181052 0 0 80 20 20 1.171053 40 0 40 20 5 1.231061 0 0 50 50 1 1.131071 0 0 80 20 25 1.171072 0 0 45 55 12 1.131081 0 0 65 35 5 1.151082 0 0 60 40 3 1.141083 15 0 60 25 18 1.181091 10 30 40 20 10 1.211092 10 10 50 30 18 1.181093 0 0 30 70 30 1.111098 20 15 40 25 13 1.211111 65 15 5 20 42 1.331121 0 70 15 15 45 1.241131 35 15 40 10 70 1.251141 0 70 15 15 45 1.241211 0 0 100 0 2 1.191221 20 0 70 10 27 1.21CD 0 C)) C)) C)) (1) CD CD ‘1 H C) CD H H C)) In 0 H H 0 (I)xj0hC))HC)CDHH-ZCDC))CD‘0C))0H-CDHC))H-<ftH03HCD‘.QC)ftInH-H-HMC)CDHCDftCD0H-ftC))InQ-HCDCDH-C))H-C)’1C)HHft‘H-0HCDft-ClCDXInfto‘1siC))CD0CDU)H-fr’HftC)C)0CDftC))CDC)HHInftHCDiC)ftInIn‘.0CDH-ft0H-C))009C)H0HC)Ho-0InC))C))InC)ftftH‘.<HH0HH0CD•‘.0ClftH-H03C))00300)C))C))HMftW‘.0HEJCiHIH-C)0C)0ftt’iHCiC)H-0OCD1iCiHH)0ftC))H0<-H‘.0H)0)0H-LQ0oft0H-C))CD-HC)000HCCD(C)HC)CDpC))H-‘.0ft0)‘.0-J0)0)i-t,ClH-0H-CD(y4•0HH-C))HftHHIn0CDHH00In‘.0CDClH)0’C))jH-H :iftCDCicpi.<0ClCiCDF-CD<HftHftCi)ftH-HH-H-C))0C)ftCDCDC)()000HFlInC)FlCD••CDCDC)ftH-ftx()L)I)H-CD‘1H‘-)w—H-CD0C)In0D_CiftHC)H-‘.0H5Hft()H-CiaC))<0Flti0t’iHClCiC)Ii0CiCiHHCD03CD‘.QInCC)Cl‘.o‘.0Fl0ftH-0)In—‘CiFltTCD•<In-<‘.CD•ClHC)F-a• oHCDoC)•-H D.H--UCtctCtC)CDCD HI)HLOCD•HHaH0ctLOH-o:-cnfrcHCD•C)Cl)CDCDCD x—iiCDC)—HCtl-Q)•HI-<00CD—Hti(nH-o CD0CtH-CD0’ 010II-w C)-‘-cm C)i HH()-cmLOU.—••—.Cl)cjmCl)H In-CtCD ZCDPd CD H x ttj‘-3 I:-’ Cl) rt t3d p) Cl) CDtD OD99CO!!ORIT! CII. CbS. USASIC ICC II!!SJJ!,flGIIC: Ft,C1,!IZJ 1 1011 111114 III!: HOtS CILCASSHHILCt itT: F1,C1,FRZI 2 1011 011 114 1111: ?11i,SIIPLI!,!AILCLII UF1,EIHLCL,S11TSS 3 1011 011 111 1 CLII E?1HLGL,ST1T!StRIlL! TALLO! 4 1011 391 31 tRIlL! TILLO!2 POll: P1,C!, 01 PaZ! 5 1011 113 P011:11151 & liZ!LIII 1011 123 LIII3 1011 IILLISS & SItS: 7 1011 013 211 1011 IELLI!S & lASS:PCI ,RLYSLTR,CVIIR 013 22 PCLLR,ILTSLTR,CH!DSAKS: 5tH & PICIIC SASS 1011 013 212 litS: 551) 4 PICJIC SASS013 291 3Rico!: SI0E,SRtD,U!SLCS 9 1011 013 232 2 RiCO!: SIII,S5H,USSLG)RICO!: S1H,SS[),SLCR 10 1011 013 232 1 RICO!: SIH,SSLI,SLCI4 SLUiCES 11 1011 015 31 SASSACESSOLOCIA & 0TH SISCS 12 1011 015 322 ROLOCIA 40111 SASCSSumS 4 lITERS: 13 1011 015 324 1 11111154 lITERS:H) HIT SASS LI! HIT 115!SkLLS1 H! HA! lAS! 14 1011 015 323 1 SiLARI: LI! SlAT lAS!CIII!! SliT 15 1011 017 CAllER HATS 111)1St! TALLOV 1 1011 391 13 Ifl)IILI TALLOSCIICIIIS: F1,CE,PRZI 17 012 1 CIICTIJS: PL,CI,PLZJ(012 122)TUHITS 18 1012 0122 TURIRTS(01223)(01225)100CDH CON UNITSCOPPODITY USA COP IPPUTS ICC UKITSPE000CT CODEIE!!,EIGIPG: ?k,CB,!EZP 20111 12 CATTLE & CALVES (852) 001 11,12 70HZPkocEssED LEEF (10%) ouIH!,PLC[ EDT: ?E,C!,IEZP 20111 14,16,18 PAC[AGIPG (52)CEll EEEP,HAIEECE,STETES 20111 31EDIPLE 1ALLO 20118 412 POll: II,CE, OR PilE 20114 12,17,51 HOGS (852) 0031 ‘000 70HZPEOCESSED poir (102) PNOPILAiD 20115 13,17 PACLAGIEG (52)3 PORt ULIIES & HiPS: 20116 12,22 FRESH & PEOZEE Poll (451) 011 11 ‘000 70HZPCILD,DETSLTD,GLJEED 20136 12,22 PROCESSED POll (452) uoPIPACEAGIEG (102)BAPS: SP[D & PICEIC HiPS 20116 3120136 31EACOP: SIDE,SP[D,URSLCD 20116 3520136 35EACOP: SIDE,SP[D,SLCD 20116 4120136 414 SAUSAGES 20117 11 P1158 & FROZEN DEEP (252) OIl 11 ‘000 70HZ2013111 FRESH & FROZE! ou (402) 011 3 ‘000 708HZBOLOGNA & 0TH SASCS 20117 35 CASIIGS (152)2013) 35 SPCS & CURIIG ETRLS (10%)EIiEiS & FUTHS: 20117 21 PAC2ACINC (102)118 PEAT EASE 20137 21SALAPI: RED PEAT EASE 20117 1720137 17CAIHD HEAT 20118 0020138 005 IJEIIBLE TALLOP 20771 11 CAtTLE & CALVES (45%) 001 11,12 ‘000 708HZBOGS (452) 003 1 ‘000 708HZPACEAGIJG (lot)6 CEICEENS: PR,CE,FRZJ 2016 CRICIHS (502) 006 113,114,’OOO 70HZ115,1167011175 2016 TOiLETS (152) 006 12 ‘000 7088!DRESSED POULTRY (201) PHOPIPACtAGIIG (151)101CON COST USACONIODIT! Q ($iL) Pt P800 CODE USA UNIT USA gEP,JNCING: PI,C,!IZN 809.968 2289.255 2826.35 021013,23 NILL LII 32159.2III!,ILC[ EDT: Pl,CB,F8ZIGilD INEF,EAHEGE,STITIS881111 TALLON2 polL: Pi,CB, 08 !8%K 1044.828 1827.046 1748.66 021313 8111 LBS 18188.?LIII3 POlL 1111115 & 8185: 461.397 967.609 2097.13 201141 NILL LOS 892.3PCIL) ,DETSLTD,CUIIOiAS: SKID & PICNIC OAKSIICOR: SI,SNID,UNSLCNACOK: SIDI,SKL8,SLCD4 SAUSAGES 329.304 926.133 2812.40 201111 KILL LIS 3549.4461.397 967.609 2097.13 201141 KILL LBS 3835.31010111 & 0TH SASGSmillS & PLITEES:II) NEAT 1181SALAKI: lED NEAT DAlECANNED NEAT5 11181111 TALLON 809.968 2289.255 2826.35 021013,23 KILL 1.85 32159.21044.828 1827.046 1748.66 021313 KILL LII 18188.76 CHCUIS: P1,CE,PIZN 628.192 718.796 1143.14 025111,21 KILL LBS 17278.3TOiLETS 122.862 184,639 1502.82 025311 KILL LOS 3648.6KILL US 2355.4102PaCOIVU USA COST USA Q 1911 ISDU 1986 1981coionv uno (Sus !ILL) (c88 huTs) ($usi) cofllP,JIGIIG: FI,C1,flZI 0.453514 20628.5 16856.780 1388.49 PPP 92.8 107.8HOPIIIU,ILCI II!: P1,C!flZ1G1H !!,!AI1GLISTIT!SEltiLl TLLLOU2 PolL: !1,CI, Dl P128 0.453514 9219.2 8248.844 1117.64 ?PP 94.3 91.9LA!)3 P011 RELLIIS A JARS: 0.453514 619.2 404.611 1618.40 2011—4 102.3 105.2PCIL)HTSL,CULEDH8S: S[) & PICNIC 8AS11CO: SIDE,SH),UISLCDIACON: SI)1,SNL),SLCO4 SAUSACIS 0.453514 3302.6 1609.705 2051.61 2011-111 82.9 89.40.453514 3121.4 1739.365 1794.56 2011—4 102.3 105.2IDLOGNA & 0TH SASGS 2011-7 102.9 111.3TALI!!S111111$ & 18711$:11) 8817 1158SALANI: H) 8117 lAS!CLUE) 81175 IJIflILI TALLOV 0,453514 20628.5 14856.710 1388.45 PPP 92.8 107.80.453514 9219.2 1248.144 1117.64 PIP 94.3 97.96 ClicillS: P1,C1,!HI 0.453514 4524.5 7835,964 577.40 PIP 128.3 106.70.453514 1310.6 1656.694 192.05 PPP 119.2 88.10.453514 1542.5 1068.209 1444.01 HOPI103Pu Pu RITuALS1986 1986 Fe/Pu PIICICORRGDITT ($us) (ScDI) 118111llP,HGIIG: Pl,CJ,!lZ1 1195.29 1660.13 1.01 Pc/Pu IRPOSK81.00IUP,ILC[ III: F1,C1F1ZF 1.171.017Cli) liII,IAHlGlSllTESE)IIL! TALLOV2 P011: P1,CR, 01 PhI 1076.54 1495.14 1.00 Pc/Pu IRPOilD1.01LI!) 1.171.0093 P011 IILLIKS & BARS: 1632.13 2267.68 0.92PC[L),I!TSL!D,C8IID 1.011.17ILlS: SRI) & PICRIC lABS 0.985IAGOI: SIDE,S!1D,UISLC)11001: SI)1,SR[)SLCD4 SAUSAGES 1902.51 2643.35 1.061745.09 242.63 0.86I0LOGJA & 0TH 51505 0.951.001111115 & PUTfl$: 1.1711) LII! uSE 0.966Skill!: III BEAT USECliii) HAT5 IIHIILL !ALLOV 1195.29 1660.13 1.01 Pc/Pu IHOSI)1016.54 1495.74 1.00 Pc/Pu IRPOSE)1.171.0216 01101111: F1,CR,!LZJ 694.29 64.65 1.19TIllITS 1071.65 1488.95 1.011.261.171.16!104CORSODITY CII. CU. USASIC ICC SilllUll, Cli 0! SAX: CuRIO 19 1031 095 2 11113, Cli & SAX: CAREHCIHOTS: CAllED 20 1031 095 4 CAIL0TS: cAn1CORI: CAllED 21 1031 095 5 COil, UI HI & CiR:CflDPEAS: CAllED 22 1031 095 P115, cli: CmiilUSHOORS: CAllED 23 1031 095 9! SUSE100RS: CAIRn9 APPLE JUiCE, SOT COIC: CIll 24 1031 076 1 APPLE JUICE,SGL STIGTE:C1RDGild 381CR, SO! Cold: CIII 25 1031 014 4 Gild JUIC1,SIGL STIGTE:CIIRTORITO laid: CAllED 2 1031 095 981 TORATOR laId: CLUED10 1111185: F1UIT 0111111 27 1031 078 412 JELLIRS: GRAPE & 018!!1098JARS: Chill 28 1031 078 411 JARS: 1115111 A OTIKIS1090RARRALAU: CAllED 29 1031 018 413 1111111111091H UAIS,GU 01 Ill: 30 1032 092 21 lIARS, GiI,idLI, &nzi nilci CU! PillIIAIS,LIRA: P111 31 1032 092 22 IIAU,LIRL: Pill1183581 SnOUTS nis 32 1032 092 4 HUSSEL SP1OU’TS: nilCAHOTS: Fill 33 1032 092 5 CALIOTS: FillalIli PEAS: FIll 34 1032 092 1 duEl PEAS: FillPOTATOIS,F1ICI P1110: P111 35 1032 092 I POTATOIS,FHC1 PIll!: PillC01I,IICL C—OR—C: Pill 3 1032 092 COil,IICL C-el-C: P111105CDI CDV UNITSCONIODIII USA CDI INPUTS ICC UNITSPLODUCT CODE7 HANS, Gil OR VAX: CANNED 20332 05 lEANS (35%) 091 41 ‘000 TONI!con (20%) 091 6 ‘000 TONI!CARROTS: CANNED 20332 15 PEAS (10%) 091 43 ‘000 TONI!PACKAGING (35%)CON: CANNED 20332 94,95PEAS CANNED 20332 318 USEROO!S: CANED 20333 21 PRESE NUSEROONS (65%) 091 7 ‘000 TOIl!.PACKACIIG (35%)9 APPLE JUICE, lOT COIC: CUD 2033A 11 ORANGES (252)APPLES (30%) 071 ii ‘000 TONI!ORANGE JUICE, NOT CONC: CUD 2033k 25 TONATOES (10%) 091 33 ‘000 TON!PACKAGING (35%)TO!ATh JUICE: CANNED 20335 1510 JELLIES: FRUIT OR Hilt 20338 21,25 STRAVEERRIES (202) 071 12 ‘000 TONI!RASPEERRIES (20%) 071 26 ‘000 TOIl!hIS: CANNED 20338 11,15 GRAPES (202)CLASS PACKAGING (302)NARNALAD!: CANNED 20338 41 OTEER NATERIALS (101)11 IIAIS,GRN 01 VAX: 20372 13 HANS, GNU OR VAX (81) 091 41 ‘000 TONI!Pill Gil!! PEAS (9%) 091 43 ‘000 TONI!POTATOES (602) 091 14 ‘000 TONI!IIAIS,LINA: P121 20372 21 SWEET CORN (8%) 091 6 ‘000 TOIl!PACKAGING (15%)HUSSEL SP1OUTS: P11K 20372 31CULOTS: PRZN 20372 33GIVEN PEAS: 1111 20372 41POTATOES,FRNCH PUED: P111 20372 48C01I,IICL C—ON—C: P111 20312 53,55106CDI COST USAC08808177 Q ($IILL) Pc PlOD CODE 115k UlIT USA Q7 HAtS, Cli 01 VAX: CAflED 39.061 8.711 223.01 16121 ‘000 S 708 427.2187.376 20.712 110.54 16131 ‘000 S 708 1686.3CAEVOTS: CAllED 68.45 26.884 392.15 16111 ‘000 S 101 250.7Coil: CLUHPEAS: CAllED8 8115110085: CAllED 11.117 16.185 1432.53 18211 IILL LBS 83.39 APPLE JUICE, 107 COEC: CIlD169.683 27.94 164.66 17411 ‘000 STON 977.9OLAIC! JUICE, 101 COIC: CUD 495.722 58.881 118.78 16141 ‘000 $708 1414.2TOlATO JUICE: CAllED10 JELLIES: 11017 0! DEll! 3.211 4.201 1284.32 11111 ‘000 5101 100.39.523 13.603 1428.44 17022 ‘000 S 708 402.5JAIS: CAllED8Ai!ALADE: Cull11 IEAIS,CL1 01 VAX: 39.061 8.711 223.01 16121 ‘000 5708 119,4FiLE 68.45 26.884 392.15 16111 ‘000 S TOE 152.2512.026 59.027 103.19 13411 ‘000 S 708 5218HAIS,LIRA: PILl 187.376 20.712 110.54 16131 ‘000 S 701 686.61185381 SP10111S: PillCIHOTS: PillCliii PEAS: liltPOTITO!S,P1ICE PlIED: PillCGH,IICL C—UI—C: Pill107hCOITH USA COS! USA Q 1987 liflI 1986 1987COflOElI! 11110 ($Us 8ILL) (CU Unts) ($vsA) COil7 1111$, CU 0! 111: CAllED 0.90702! 67.8 387.483 174.98 PPP 93.6 93.60.907029 117.4 1529.524 76.16 USDA 113.9 105,7CAUOTS: CAllED 0.907029 60.4 227.392 265.62 PPP 92.1 92.5CDLI: CAllEDPlis: cml8 105110085: CAnED 0,453514 59.7 31.118 1580.29 PPP 96.9 101.29 APPLE JUICE, 807 COIC: CUD CALC0.907029 111.6 886.984 125.82 PPP 112.6 800111CR JUICE, 101 COIC: GIlD 0.907029 454.4 6724.898 67.57 F?? 111.6 115.6108110 JUICI: ChilD10 JELLIES: P1011 011111! 0.907029 61.3 90.975 613.81 F?? 51.6 58.50.907029 156.1 365.07! 421.58 F!? 178 193JAIS: CAllED CALCIALLLLAH: CAllEDH 11AUG11 01811: 0.907029 26.3 108.29! 242.85 F?? 93.6 93.6PIZI 0.907029 36.7 138.050 265.85 F?? 96.8 94.40.907029 539.5 4132.880 113.9! F?? 113 100.40,907029 46 622.766 13.86 F?! 113.9 105.1IIUSSEL SF10075: PHICALEOTS: PillCUll PEAS: Fill?0!AIOES,PUCE P11KD: PU)C0iIIICL C-Ol-C: Fill108Pu Pu RLYHI&LS1986 1584 Pc/Pu PIICIcooirr (Sos) ($cu) muaLLIS, GIN 01 111: CAllED 174.98 243.11 0.9282.71 114.92 0,94dUCTS: CANNED 264.47 367.44 1.071.32Goil: CilUNPals: CANNED8 NL008S: CAHID 1513.15 2102.31 0.81.320.840S APPLE JUICE, NOT COIC: CIII 1.40177.09 244.05 0.47OUNCE JUICE, NOT CONC: CUD 45.23 90.43 1.311.32TONATO JUICE: ClUED 1.0310 JELLIES: FLU!? 018111! 663.44 921.79 1.35394.35 547.91 2.41lIES: CAll 1.41I .32RALEALAH: CAININ 1.071.55511 IIAISGIl 01 Vii: 242.85 337.41 0.46liii 272.40 378.74 1.04128.30 178.25 0.58HhiS,LIRi: Flit 75.5 110.59 1.001.20ELISSIL SPLONTS: Flit 0.119ChlLOTS: PHICLCU PEAS: FillPOTITOIS,FUCI FLIED: FillC0lI,IICL C-ON-C: Flit109COPO)1TT CDI, CDI. USASIC ICCHOCCOLI: P10tH 37 1032 092 3 HOCCOLI: Pill12 FLUID !ILI: HOLE & PLCSSD 38 1041 051 231 FLUID !ILt HL & ?1CSSD051 232FLUID liLt: PLOCESSED, 51111 39 1041 051 233 FLUID lILt: StIllEDlOCH! 40 1041 051 96 lOCH!13 CHIlI! DUTTEL 41 1049 051 31 ChIll! 101711051 3314 CullS!: CHIlI! & OTHiS 42 1049 051 411 CHISE: JIlL !IC?T CT1TG!051419CUES!: P1OCESS 43 1049 051 45 P1OCESS CUES!CIlISE: C0T’TAGI 44 1049 051 44 COllAGE CutS!15 SItE lIlt ?IH 45 1049 051 52 5111 1111 PIlLfliT £01111 46 1049 051 55 11! HiTlYPITI !IL[,VBL I SKI: CIII 41 1049 051 612 E!L?O1AIII IILI: CAII!D051 62214 lCD Clii! III 48 1049 051 95! ICE Clii! IIIlILt Slit! III 4 1049 051 953 lILt SILL! IIIIC! Clii! 50 1049 051 711 IC! CULlS17 nEAT FLOUt 51 1051 062 15 HEAT PLOU1(042 155)(062 156)Ififi £1011 Al SIIOLIJA 52 1051 062 156 8110! P1001 & 51801111110COW COW UBITSC0W0DIfl USA CDI IR?U73 ICC UWITSPtODUGT CODEHOCCOLI: P10111 20372 2512 FLUID BILE: IIOLE & PRCSSD 20261 12 IBOLE ii,r (90%) 051 12 ‘000 EL20262 12,23 PACIACING (10%)FLUID 8IL: PROCESSED, S[D 20261 1520262 25YOGURT 20265 0020240 3113 C1E1E1! BUTTER 20210 13,15 VEOLE !IL (70%) 051 23 ‘000 ELCHAR (20%) 051 21 ‘000 1 8!PACIACING (10%)14 CEBESE: CEEDDIL & OTB.ELS 20223 00 IBOLE MLI (65%) 051 23 ‘000 ELCR.EA (5t) 051 21 ‘000 7 1!CREESE: PROCESS 20224 21 NATURAL CERESE (25%) 051 41 ‘000 TONERPACKAGING (51)CHISE: COTTAGE 20263 13,16,1815 SUN N1L PIOR 20235 11,43 WEOL! NILL (50%) 051 23 ‘000 ELClEAN (10%) 051 21 ‘000 7 IFWEE! POWDER 20235 45 WEE! (5:) 051 55 ‘000 lOIRECOlD & EVAP BILl (5%) 051 61 ‘000 ELITPRTD !IL[,!HL & Sri: CR10 20236 12 SWIITINEIS (51)OlE!! MATERIALS (35%)PACLACIIG (10:)16 ICE ClEAN NIX 20238 11 HOLE BILL (15%) 051 231 ‘000 ELClEAN (15%) 051 21 ‘000 1 IFBILL SEAL! NIl 20238 13 COlD & ETA? BILL (10%) 051 61 ‘000 ELMIXES (10%) 051 951 ‘000 ELId ClEAN 20240 14,15 ClOd & PLTLIIGS (151)SWEETENERS (20%)PACIAGIEG (15%)11 WHAT FLOUR 20411 05,11,13, WEEk? (95%) 061 18 ‘000 1011!15,17,21,23,26, PACIACIEG (5%)28,29WHUN FLOUR AID SIBOLIRA 20411 51111CDI COST USACOR8ODITT ($ILt) Pt PlOD CODE USA UNIT USA QBIOCCOLI: FROZEN12 PLOt) MILL: IROLI & PRCSSD 42.50 24111 BILL CNT 763.2FLUID BILE: PROCESSED, SEBBEYOGURT13 CUABKkT BUTTER 54.50 24111 BILL C 19.925.9 143.36 5535.1414 CIEESE: CHEDDAR OTHERS 54.50 24111 BILL CI! 403.125.9 143.36 5535.14 202613 BILL CI! 3.3CHEESE: PROCESS 80.64 331.2 4107.14 202210 BILL LBS 1481.5GUISE: COTTAGE15 SKIB BILE PIDR 54.50 24111 BILL CIT 107.725.9 143.36 5535.14 202613 BILL CII 1.6III! PONDER 7.319 5,101 691.29 202302 BILL US 710.81354,857 214.366 158.22 BILL LBS 1194.7ITPR!D BILK,IEL & 5KB: CII)16 ICE CREAB BIX 54.50 24111 BILL CII 16.625.9 143.36 5535.14 202613 BILL CVI 5.7BILK SNAKE Ku 1354.857 214.366 158.22 BILL LBS 1194.732.548 4.47 137.34 BILL CAL NO.4ICE CLIAK11 lEEk! FLOUR 2363.602 613.506 259.56 11111 BILL ISRLS 744.9BULUB FLOUR AID SEBOLIJA112‘UCOPfl USA COST USA Q 1987 11881 1986 1981C0OflTT uio ($s MILL) (Cu ulITs) (Susi) conIROCCOLI: PROZEI12 ILUI8 RILI: VIOL! & PVCSSO 441.7415 8565.3 337141.74! 25.41 PPP(!LD) 91.4 91.9!LUI8 !ILL: PlOCISSED, SIRIDTOG!!!13 CIII!!!! VUTTII 441.1475 246.2 8790.171 28.01 P?P(!i?lI) 91 0.2841.2 4232.15 8RS 100 9814 GillS!: CIEDDI! I OTEE1S 441.7475 4863.9 178068.447 27.31 P??(RIFII) 91 90.20.018140 285.9 59.864 4775.83 88S 100 98ClEFS!: P!DCESS 0.453514 1909.7 671.882 2842.31 2022—1 96.6 95.5Gins!: COFTAG!15 StIR KILt P101 441.7475 1251.7 47576.214 26.31 PPP(Nl!lD) 91 90.20.018140 114.3 29.025 3937.99 PS 100 98VII! ?0VDfl 0.453514 104.2 322.35! 323.24 2023-139 91.9 169.24.458049 614.3 5326.032 115.34 2023—3 93.8 94.2FY11!) KILt,VEL & 11!: CII! CALC16 IC! Clii! RI! 441.1475 191.8 1333.010 26.16 ?PP(KIit8) 91 90.20.011140 413.6 103.401 3999.95 PS 100 98KILt SILL! III 4.451049 614.3 5326.032 115.34 2023—3 93.8 4.237.85011 197.8 3043.149 65.00 2099—3 100.1 106IC! CHAR TA!!??CILC17 lillY PLOU1 26.37164 2363.9 19644.087 119.32 ?P? 70.1 74.5Rh! PLO!! 118 SPOLIIA113Pu ILTI1ILLS1984 1986 Pc/h HICIC00RIfl ($vs) ($cn) innII0CCOII: IIOZII12 PLUII flIt: VIOLI & PLCSSD 25.27 35.11 1.211.14flUII fILL: P1OC!SS1D, SLIM 1.204TO CU LT13 ChIli! IIt!U 21.24 39.26 1.394318.52 6000.15 0.921.111.24014 CHIlI: CHIll I OTEHS 21.54 38.29 1.424113.30 710.96 0.82CIHS8: PIOCKIS 2875.05 3994.60 1.031,19CHIlI: COTTACE15 IKIf fILL ?TIR 26.54 36,88 1.414018.36 5583.11 0.91III! P0111 175.57 243.93 2.83114.85 151.57 0.ITPL!l fILL IlL I SLI: CIII 0.451.071.111.21714 Id dill! fill 26.31 36.46 1.414081.58 5610.95 0.98fILL SILL! fIX 114.15 159.57 0.9161.38 85.28 1.61IC! Ciii! 1.000.451.191.04417 VIII? FLOU1 112.21 155.19 1.441.111,435Ill! 11011 All SI!OLIIA114COOi ITT Cli CIISIC ICCUS AJAilV1OLI lillY 01 Cli! PLOU1 53 1051 062 155 IIOLI flEA! !LOtJI18 PUPAl!) CA!! 81111 54 1052 O 31 PLIPAl!) CII! 811811 11EII?IST CHhlLS iTS 55 1052 0 11 IL!AIHST CHEILS: iTS1OLLEJ OATS, 11?LPDJ 54 1051 066 122 1OLLEI OATS20 FOUL!).! COJPLITI Pill 57 1053 15 15 POULTRY COIPLI!! Fillbill! COIPLIT! PU)STIlE COIPLITE Pill58 1053 15 1125 1053 15 13JAIl! CORPLETE PEED$111! COIPLITI PHIIll! COIPLET! PEE) 40 1053 j5 113 ill! COEPLITI FEED21 loG A CAT Pill ClUED 44 1153 15 31 JOG I CAT Fill: ChillJOG A CAT PiED: JOT CUD 47 1053 ISD 32 lOG I CAT F!!): DL!10151 CORPLITE 111) 41 1053 j5 12 10151 & JILt C!PLTI PIE)1111! CATTlE PIE) SPL!JYS 42 1053 151 12 JAIL! Fill: SPLEITS I CICSSTIlE Ti!) SPLUTS 43 1053 151 2 Sill! Pill: SPLEJYS & dclSUP CATTLE FEE) SPL!JTS 44 1053 158 13 I!!! CATTLE: SPL!IYS A dclPOULYL! Pill SPURT 45 1053 151 3 POILTRY: SPLEITS & CICS115CDI CON UNITSCONNODIT! USA CDI INPUTS ICC UNITSPRODUCT CODEHOLD HEAT OR GREM FLOUR 20411 3118 PREPARED CAll MIlES 2045 HEAT FLOUR (35:) 062 15 ‘000 TOIIKSUGAR , CANE & EKE! (15%)PATS & OILS (ioz) 39 ‘000 7011KOTEER MATERIALS (25:)PACAGING (15:)19 ER!AKPAST CEREALS: R1S 20430 11,12, WHEAT (20:) 062 15 ‘000 TOHE15,17,21 OATS (lot) 061 14 ‘000 7011KROLLED OATS, DIPEPRO 20430 57 DRIED FRUIT & NUTS (as:)SUGAR (CANE & DEE!) (20:)PAKAGING: PLIXIELE (5:)PAPERBOILD (20:)OTHER MATERIALS (10:)20 POULTRY COMPLETE PEED 20481 11,15, WHEAT (10:) 061 18 ‘000 10HE16,18 EARLE! (15:) 061 11 ‘000 70111SUPPLEMENTS (10:)DAIRY COMPLETE FEED 20482 00 FISH MEAL (10!) 156 61 ‘000 TOHECORN (is:) oi 13 ‘000 7011KSWINE COMPLETE FEED 20484 00 PATS & OILS (5:) 391 1 ‘000 TOREOILCA[E & HAL (20t)DEEP COMPLETE FEED 20486 00 MILLFEED & SCRHGS (5:) ‘000 TONESMICROIKGREDIUTS (10:)NOiSE COMPLETE PEED 20486 16 PACEAGINGDAIRY CATTLE FEED SPLMITS 20483 01SWINE PEED SPLINTS 20485 03DEEP CATTLE PEED SPLINTS 20487 05POULTRY PEED SPLINT21 DOG & CAT FEED: CANNED 20473 21,23 HEAT (5:) 061 18 ‘000 7011K20474 41,43 WHEAT FLOUR (5:) 062 15 ‘000 TOREDOG & CAT FEED: 10! CUD WHEAT SCREENINGS (5:) 152 92 ‘000 7011!116CDI COST USACOHHODITY Q ($HILL) Pc PROD CODE USA 0117 USAHOLE 1181! OR CREH FLOIJE18 PREPARED CUE HillS 58.37 25.41 435.33 204110 ‘000 CI! 199722.193 2.405 1096.67 207003 HILL LES 181.419 11111115! CHIlLS: ETS 35.955 9.807 272.76 11111 HILL ESELS 17.8303.722 37.417 123.19 11931 HILL ISELS 30.4ROLLED OATS, URPLPRD20 POULTRY COEPLETE 1118 829.636 116.516 140.44 11101 ‘000 S 708 1412.41405.127 165.036 117.45 11904 HILL ESIL 0.8DAIRY COEPLET! P110 49.247 24.3 493.43 207721 ‘000 5701 288.11788.583 245.998 137.54 11503 ‘000 S TOE 16232.5$8111 COHPLETZ PEED 74.607 29.837 399.92 207004 ‘000 STOl 646.3HE! COHPLKTE FEED 215.142 19.211 89.29 204122,66 ‘000 S 708 4723.510151 COEPLITE PHDDAIRY CATTLE FEED SPLHE!S$1111 PHD SPLEITSDEEP CATTLE PEED SPLHNTSPOULTRY PIED SPLEIT21 DOG & CAT 1118: CAllED 3229.193 739.828 229.11 11101 ‘000 5101 402.51040.415 446.619 429.27 204110 ‘000 C!! 2878.5DOG & CL! 1110: lOT CUD 215.142 19.211 89.29 206122 ‘000 5708 248.1117COPhI USA COST USA Q 1q87 11011 1986 1981C0ODITY RATIO (Sos IILL) (coi ouTs) ($usi) cooaHOLE EllA! 01 CR0! FLOUR18 PIIPAHO CAL! EllIS 0.045359 195.3 905.915 215.58 2041—1 91.4 89.7CALC0.453514 47.4 82.268 576.17 2079—11507 86.3 9,519 IUALFAST CEREALS: 175 26.31144 68.3 469.412 145.50 2041 91,4 19.114.94389 46.7 454.295 102.80 PIP 81.2 104.7ROLLED OATS, BIPIPRJ TARIFFSCALC20 POULTRY COEPLETE PEED 0.907029 83.8 1281.088 65.41 11? 70.1 74.521.09715 1.6 16.878 94.80 111(1810) 72.4 17.6TARIFFSIAIRT COEPLET! PIED 0.907029 91.6 261.315 373.50 2077—366 89.8 102.70.907029 1102 14723.356 74.85 PIP 113.9 105.7STIlE COEPLIT! 1110 0.907029 172.1 516.213 293.58 2079—11507 86.3 99.5TARIFFS1111 COEPLETI FEED 0.901029 308.6 4284.354 72.03 2041—213 67 60.2flUFFS10151 COEPLITE PIEDlilt! CATTLE FRED SPLUTSSIll! PEED SPLUTS111! CATTLE PIED SPLEITSPOULTRY PEED SILENT21 lOG R CAT PEEb CLUED 0.901029 31.5 365.079 102,72 1?? 10.1 14.50,045359 20.9 130.567 160.07 2041—1 91,4 89.7lOG & CAT 1110: 101 CUD 0.901029 22.2 225.034 98.65 2041-213 67 60.2118Pu Pu !ATUIALS1986 1986 Pc/Pu FlICKcooPIn ($us) ($cn) inn11011 ThAT 0! CIII PLOU1ii PUPARU CAL! 81115 219,47 305.21 1.430.40499.73 694.33 1.581.071.111.07419 II!A[PAST CflIALS: iTS 148.26 205.99 1.3279.72 110.77 1.11ROLL!) OATS, UIPIILD 1.000.401.171.0720 POULTIT CO8PLXT! PIE) 61.55 85.52 1.4488.45 122.89 0.941.00lAIR! COIPLETI P118 326.58 453.75 1.0980.65 112.06 1.2381111 COIPLIT! 1111 254.43 353.19 1.131.00UI? COIPLI’!! 1118 80.17 111.3 0.801.0010151 COIPLI11 P11) 1.231.080IA!!! CAT!!.! PH) SPLIITSlull Ill) SILKITSIII! CAT!L1 Ph!) SF18175POULTRY 1!!) SPLIIT21 lOG A CAT 111): CAll!) 96.65 134.29 1.11163.11 226.62 1.19lOG A CAT 1118: 10! CIII 109.80 152.55 0.59119C0l!OflTT Cli. CI!. USASIC ICC22 Clill OIL: SOTIIAI 61 1061 33 l4 CiVIl OIL: SOYlIAlSQuEAl OILCAII & 1811 6 1053 153 3 SOYI!AJ OILCAIE & IEAL106123 IISCVI!S: FLAIl & PAICY 10 1071 064 22 COO[I!S24 11118 71 1072 064 11 11118: V1!,1Y1,HL & C1C1EHAT , 07115PHIl tOLLS I IllS 72 1012 014 12 tOLLS: 11118 7TH25 SIGn: CIII & IEIT,CHLTI,11! 73 1011 101 31 C1ILTE CIII & 1117 SVGAISUCH: ICIIG,PCIC?,CAIE & 888! 74 1081 101 352 COIFECTIOJE1S’ P8818 SUCHSUGAR: S0F7,CLILTP,CAIE & III! 15 1081 101 341 SOFT 01 11011 SUCHSVGA!: 117117, CIII & II!! 76 1081 101 331 117117 SUCH: CARE & 18!!LIQIER SICLOSI: CIII & II!! 71 1011 101 333 SICZOSE26 CuING CVI 18 1082 104 1 CliniC Cli120CDI CDI 01111COIODI7T USA CDI INPUIS ICC UNITSPRODUCT CODECORI (101) 061 13 ‘000 10111COiN GLUTEN (51) 062 98 ‘000 701!!0115888 citz (20%)hAT HAL (101) 156 61,81 ‘000 10(1!GIBE! IATERIALS (5%)PACLAGINC (35:)22 CRUDE OIL: SOTSRAK 20151 13 SOYUANS (go:) 212 1 ‘000 TON!!20751 15 PACIAGIIG (101)SOYBEAN OILCA[E & hEAL 20152 1123 BISCUITS: PLAIN & FANCY 20521 23,33,35, 181k! FLOUR (20%) 062 15 ‘000 7011!98,20522 13,15, SVEETRURS (151)19,21 PATS & OILS (10:) 393 ‘000 lOU!CEOCOLAT! (101) 000 TONE!OTHER EATERIALS (15:)PACIACIEG (30%)24 11118 20511 11,13, 18811 FLOUR (60%) 062 15 ‘000 1011115,17,28SWEETENERS (51)PLAIN ROLLS & BUNS 20512 33 PATS & OILS (10%) 393 ‘000 10!!!YEASTS (5%) ‘000 TOll!0TH! EATERIALS (5%)FACUCING (1st)25 SUGAR: CANE & 1EET,GLNLID,HT 20620 09,12,14, 11!! SUGAR (101)15, 20630 07,13,1kv CAN! SUGAR (80:) ‘000 7011!15 OTHER !ATEUALS (51)SUGAR: IGIKG,PCIGD,CANE & BEET 20620 31,35 PACIAGIIC (5:)20630 33SUGAR: SOFT,CHLTD,CANE & 1117 20620 41,45SUGAR: INVERT, CANE & BEET 20620 5620630 55LIQUID SUCROSE: CANE & BEET 20620 5320630 5126 CURING GUI 20670-11 GINNING GUI BASE (20:) 217 13 ‘000 10118SUGAR SOLIDS (201)121CD! COST USACOBIODITT Q (S1LL) Pt P101 COD! USA U!17 USA Q2119.26 371.239 133.57 11503 ‘OQO S TO! 1467.448.634 12.982 266.93 204607 ‘000 S 70! 305.4193.646 56,789 293.26 207121 ‘000 S TO! 634.422 C1U!! OIL: SOTIRi! 831.027 222.83 268.14 11611 ‘000 S TO! 35402.1SOTIIAI OILCAfl & !IAL23 IISCUITS: PUll & !AKCT 617.957 282.409 451.00 204117—114 IILL LBS 2855.7CA LC6.923 6.635 958.40 207011—014 !ILL LBS 720.48.112 21.689 2673.69 206601 !ILL LBS 142,724 11111 503.353 233.139 463.17 204111,2,4,!ILL LBS 14150.86,7CALC ‘000 S 10! 1535.3PHI! 1OLLS & BUIS 7.509 8.861 1180.05 !ILL LBS 990.415,581 16.754 1075.28 !ILL LBS 32925 SUCH: CA!! & !I!!,CIILTD,IW!1003.084 226.251 225.56 ‘000 S TO! 4361,7SUCH: ICIRC,PC[CD,CAI! & IBITSUCH: SO?1,GBILTD,CA!E & BEETSVGA!: IITIIT, CAll & III!LIQUID SUC1OSE: CA!! & SEE!26 CEITIIC CU! 1.506 3.684 2446,22 206701206011 ‘000 S TO! 99.6122CORTU USA COST USA Q 1987 IHEX 1986 1987CORIODITY uio ($us RILL) (coj unis) (Susi) co0.907029 107.3 1330.975 80.62 P?P 113.9 105.70.907029 61.1 277.007 220.57 2046—701 143.1 147TulIPS0.907029 143.2 575.420 248.86 2077—211 86 1O.222 CifliR OIL: SOYUAN 0.907029 6159 32110.748 191.80 HP 83.7 97.2SOTIIAR OILCAKI & HAL23 IISCUI1S: FLAIR & PARC! 0.453514 251.6 1295.102 194.27 2041—1 91.4 89.7CALC0.453514 172.3 326.712 527.38 2079—11507 86.3 99.50.453514 118.8 64.717 1835.70 2099—8 104.7 106.524 ILIAD 0.453514 1168.4 6417.596 182.06 2041—1 91.4 89.70.901029 341.1 1392.562 259.14 CALCFLAIl 1OLLS & RUES 0.453514 226.4 449.161 504.05 2079—11507 86.3 99.50.453514 118 149.206 790.85 TALIUS25 SUGAR: CAll & HI!,GRRL!D,117 CALC0.901029 1755.4 3956.190 443.71 2061—1 102.2 107.4SiGht: ICIIC,?C[CB,CARI & III?SUCH: SOPT,CLILID,CAIK & 1887SUGAR: INPUT, CAN! & RUTLIQUIR Sucioss: CARE & 181724 ChuG GUI 11.2 ASSUH DUTY0.907029 35.8 CALC123Pu Pu ILTHIALS19U 1986 Pc/Pu PuCKcoom (Sus) ($cu) Inn(6.87 120.70 1.11214.72 298.33 0.891 .00201.53 280.00 1.051 .071.231.12422 CLUfl OIL: SOTIKIK 165.11 229.48 1.171.13SOTIKAK OILCAII & IIAL 1.16523 IISCUITS: PLAIK & TAlC! 191.95 215.03 1.660.65457.41 635.53 1.511804.67 2507.41 1.071.071.171.15124 11118 185.51 257.75 1.800.65PUll LOLLS & 1185 437.18 607.42 1.941.511.071.131.55125 SUCh: CIII & I!ET,C1ILTI,V8! 0.40422.23 586.66 0.381.07Such: ICIIG,PCKCI,CAII & III! 1.150.429Such: SOFT,CRILT8,CAIE & 1117SUCIL: IITK, CIII & IKLIQUII SOCLOSI: CIII & BIT26 CIIIIIC CU 1.000.40124COPO)ITY C?I. Cli. USASIC ICC 1A1!21 CIOCOLA!! COHICTIOIUT 79 1083 104 2 CIOCOLAT! COP!CTIOIIITCIOCOLAT!, COLTIIGS 80 1083 111 32 CIOCOLATE COITIICSS8GA1 COJYZCTIOHI! 81 1083 104 7 SVGA! C0(!!CYIOI!LT28 CD!!!! : 1OLST!$ 82 1091 112 2 COP!!!: CU$,!1A8,UflS29 TIA: ILIHID, PACKID 83 1091 113 2 HA PCU II 711 lAGS30 PASTA PDODUCTS: DVI 14 1092 045 1 KACAIGII & bOIL! PlODSlOli31 POTATO! CII?S,!LA[!S,IIILLS, 15 1093 146 4 ClIPS & STICKS& SILL PLODSpoPcon (zcirT Cull!!) 86 1093 146 8 07111 ClIPS & STICKS32 PIAIIJI 10?!!! 87 1098 146 12 PlAID! 10771133 CHIlL Gill! STuCK 11 1098 062 2 STAId: CDLI & 0781101111 STAid! 89 109! 062 2 STAid: 07118125CDE CDR URITSC08ODI1T USA CD8 IIPU7S ICC U8ITSPRODUCT CODEPLA!OURIIGS (10%)SOHITOL (5%) 412 37 ‘000 70118811710$! SYRUP (5%) 101 41 ‘000 7088807881 !.ATRRIALS (10%)PACLACIEG (30%)21 CEOCOLA7K CONF!CTIOIERT 20642 00 COCOA BARS (15%) Ui 1 ‘000 7011820662 00 CEOCOLATE COATIICS (5%) 111 32 ‘000 10118CROCOLAT!, COA7IIGS 20661 12,22, COCOA tUTTlE (15%) 111 2 ‘000 7011832,52 $118781815 (15%)SUGAR COEPICTIOBRY 20643 00 RUTS (5%) 082 2RILI PIORUCTS (15%)PAP!1 COITAIIUS (ioz)PLASTIC COITIIIERS (5%)07111 PACLAGIIC (10%)OIliER RATERIALS (5%)28 COFFEE : IOASTED 20951 11,15,21 CREEl COFFEE (80%) 112 1 ‘000 70188PAC[AGIKG (isZ)07111 RATERIALS (5%)29 TEA: ELEIDED, PACLED 20998 82 LIV TEA (85%) 113 1 ‘000 lOIREPACLACTIG (15t)30 PASTA PRODUCTS: ERT 20980 21,31 SILIA & DUlU FLOUR (55%) 062 156 ‘000 7018807881 IATERIALS (20%)PACIAGIIG (25%)31 POTATO! CEIPS,FLA[ZS,FEILLS, 20961 00 P0717015 (25%) 091 14 ‘000 10118& SELl FlOES COil (5%) 061 13 ‘000 10118PATS & OILS (15%) 393 ‘000 7088!ro?con (txci CAIDIKD) 20963 00 01111 EATHIALS (20%)PACIAGING (35%)32 PEAIUT tUfTER 2099? 44,46 SEELLED PEARUTS (80%) 082 2 ‘000 7081807111 EATHIALS (ioz)PICIAGIRG (10%)33 CEREAL GLAIN STILCI 20462 41 CON (50%) 061 13 ‘000 10118lEEK! (25%) 061 18 ‘000 7011!OIlER STALCE 20462 43 07811 EATILIALS (25%)126CMI COST USACOMMODITY Q ($MILL) Pc PROD COD[ lISA UNIT USATill!!2.177 3.196 1143.688.802 5.83 662.35 204612 MILL LMS 1721 CROCOLAT! COHKCTIOIERT 19.548 58.619 2998.12 17915 ‘000 S TON 244.46.999 15.614 2230.89 206602 ‘000 S TOM 143.7CEOCOLATE, COATINGS 5.184 37.093 1155.29 206691 MILL LES 90.5CALC MILL 183 2701.7SUGAR COJPECTIOIELT Till!! 206583CALC CALC28 COPPEE : ROASTED 76.769 424.038 5523,56 17921 ‘000 CM? 2144329 Tli: ILENDED, PAC!D 14.25 41,437 2901.86 17931 MILL LBS 135.730 PASTA PRODUCTS: DRY 110.749 49.991 451.39 204115 ‘000 CMT 1531031 POTATO! CEIPS,!LAL1S,!ZILLS, 282.991 52.016 183.81 13411 ‘000 S TOM 2313,9A SILl P1015 260.00 190041 ‘000 S TON 293.233.099 28.629 864.95 207006 MILL LBS 819.9POPCORN (EXCEPT CAntED)32 PEANUT MUTTER 13923 MILL LBS 477.833 dEAL GRAIN STARCE 2779.26 371.239 133.57 11001 MILL 15815 196.73229.193 739.828 229.11 11111 MILL 15815 744.90Th SURGE127PuCOlUK USA COST USA 1987 libtI 1q86 1987CO8IODITT LATIO (Sus SILL) (CDI unrs) (Susi) co19.2TUlIPS0.453514 9.9 34.921 283.50 2044—1 97.2 92.421 CJOCOLATS COIIZCTIORIIT 0.907029 438.4 221.478 1978.55 lAS 1925—9 94.3 89.80.907029 240.9 130.340 1848.24 2066—1 106.4 106.1CIOCOLAT!, COATEICS 0.453514 201 41.043 4891.29 104.7 106.50.453514 502.1 1225.261 409.79 CAICSUCH COIIICTIOIHT TUlIPS97.5 99.528 COFFEF : ROASTED 0.045359 2641.8 972.438 2716.12 100 103,629 YEA: ILEHED, PICIED 0.453514 103 41.542 1673.66 115 1925—15 97.2 86.230 PASTA PRODUCTS: DI! 0.045359 186.2 694.450 268.13 93.1 94.431 POTATOK CEIPS,ILIUS,ILILLS, 0.907029 338.7 2098.776 161.38 11? 113 100.4& SELL PlODS 0.907029 51.1 265.941 192.15 USDA 113.9 105.10.453514 200.2 371.837 538.41 2019—11507 86.3 99.5P0?COU (zxcirr CAntED)32 11110! 807TH 0.453514 294.8 216.489 1360.41 TALIPIS33 CHILL CLIII STALCE 24.4137 1435.9 19609,735 73.22 USDA 113.9 105.724.37144 2343,9 19644.087 119.32 2041 91.4 89.7OTlil STALCI128Pu Pu IATEZIALS1986 1986 Pc/Pu PIECECOElOlITY ($us) ($cDI) Jinx1.3,1.13297.58 413.46 1.601.071.140.52727 CEOCOLA!! COIPEC!IOJELY 2077.69 2886.75 1.041153.47 2575.21 0.87CIOCOLIIl, COATIIGS 4814.52 6689.30 1.070.65SUCAI C01P!CTIOIELT 1.103166 4398.84 0.161.191.070.51328 COP?!! : tOASTED 2621.74 3642.64 1.521.221.07 1.44229 TEA: ILEHED, PACtEl 1117.23 2622.12 1.111.221.12630 PASTA PLOIUCTS: DL! 258.55 359.78 1.691.071.111.41031 POTATO! CEI?S,?LAEES,!IILLS, 181.63 252.36 0.73I SILL PLODS 201.05 287.68 0.50 Pc IEPOSED666.98 648.82 1.33PO?C0fl (ixcip! CAHIll) 1.071.11 1.00832 P11811! IUTTH 1.101.071.211.10133 CHIlL CLIII STALCE 18.90 109.63 1.22121.58 168.92 1.36OTHL STALCI 1.07129COJROUTT Cli. Cli. USASIC ICC IA134 P118015: SELLI OR OTIHISE 90 1098 082 2 P11181501181 JUTS 91 1098 082 9 01111 JUTS35 SSOITIIIJG 92 1098 122 SIOLTKJ1IC1011lilcuIn: IJCL. 108 CAL 93 1098 121 RLCA1III10436 tALl: 811181 & 07111 96 1121 062 32 8117 1 RAIl !T?HC!S1131 062 3337 CHIlI SOPT Hilts: RIG & 101 CAL, 95 1111 111 111 1 80?! 111118: CHITI,IITLB177111 171 112 1CHIlI SO!? HIltS HG & LO1 CAL, 96 1111 111 111 2 SO!! lUlLS: CLEITI,CI18CDI 171 112 2CUIU SOP! lUlLS RIG & LOl CAL, 97 1111 171 111 3 SO!! HIlL P11815P1881 171 112 3CHIT) SO!? 111115: RIG & 108 CAL, 98 1111 111 111 4 SOP? lulL POSTRISP05781 171 112 431 CIII (in) vIistr: iruu 1121 173 522in: KATURII 100 1121 173 32 lviCII: JATUIH 101 1121 173 22 cii1011.1: 8170118 102 1121 173 42 901113 111, UGH, STOUT, & P0lTH:IITLD 103 1131 112 11 liii: IOTTLII130CON CON UNITSCOEIODIT! USA CON INPUTS ICC UNITSPNODUCT CODE34 PEANUTS: SELLD Ok OTHUISE 20680 13 JUTS IN SHELL (45!) 081JUTNIATS (30!)07811 RUTS 20680 15,17,35, 07811 NATIIIALS (15!)37,55,57 PACKAGING (10:)35 SEOBTEJINC 20191 13 EDIBLE TALLON (10:) 391 31 ‘000 70888ClOD! oi’s (40!) ‘000 TORN!LEFIJED OILS (20!) ‘000 TONE!NALGALINE: IICL. LOJ CAL 20792 00 0781k NATUIALS (15!)PACKAGING (15:)36 NiL!: BALLET & OTEEk 20830 00 BilLET (100!) 061 11 ‘000 TONER37 CR1170 SO!! 011115: LEG & LOR CAL,20863 10,20,30 5111711115(20!)ITTLED COICENTLATES (30!) 104 921 1,2CARS (35:)CR1170 SOFT 011115:1KG & LON CAL,20864 10 GLASS BOTTLES (10!)CUD PLASTIC PACLAGING (5:)CIIJTD SOFT DuNKS: LEG & LON CAL,20865 02P 11 NICilITO SOP! DlINtS LEG & LON CAL,20865 01P05Th!38 CR81 (RYE) 1815K!: NATURED 20853 11,13,16,16RUN: NATUIID 20853 35GIN: NATURED 20853 22TODLA: NATUND 20853 3139 ALl, LACER, STOUT, & POLT11:!TTLR 20822 22,24,27, BALLET NiL! (30:) 062 32,33 ‘000 TOIl!28,32,34,37,38, COil (5!) 062 52 ‘000 10188131CII COSTCOBBODITY Q (SkILL)36 BALT: BAILEY i OTHE 1994.169 262.191 131.44 011913 BILL ESELS 123.3CHITI SOFT BUI[S: LEG & 101 CAL,CII BBILL LBS 6902208721,3,5 BILL CSBS 3715.1chiT) SOFT Dulls: HG & 101 CAL,CHIT) SOFT HillS: HG & 101 CAL,?OSTBI38 CIII (tTE) HISU: BATUHOEUB: BATULEDCII: BATULEDYODEl: BITULED39 ALl, LAGIL, STOUT, & POBTH:ITTLB 313.522 137.401 438.25 11913 ‘000 CIT 40612.7325.1000 51.428 176.65 11522 BILL ISULS 13.5USALEO) CODE USA OuT USAPt34 P111175: SELL) 0! OTEHISK 100122065830TH! JUTS35 S10!TUIIG 12.911 5.536 428.78 201104215.1 121.1 562.9966.08 62.2 941.28BA1CALIJE: lid. LOl CALBILL 15815 844.8BILL ISELS 632.6BILL LBS 663.9BILL LBS 6064.000BILL LBS 268531 CIII!) SOFT 111115: HG & LOU CAL,ETTLID132PuCOIPH USA COST USA 1987 IRDEl 1986 19870081001!! tino ($us 8ILL) (coi OuTS) (Susi) cooi34 LEARIITS: SILLR Dl 0111V151 458.9 TUliPS502.6 TALI!FS07111 RUTS35 S!OLTRIIIC 0.453514 112 301.088 311.98 USDA 46.9 54.30.453514 1084.4 2750.113 394.31 57 58.10.453514 635.6 1211.681 521.91 55.3 52.9RA1GA1IRE: 1ICL. LOU CAL36 RALT: RAIL!! & 01111 21.09715 314.4 2601.279 120.86 PPP 18.9 8937 CLRITD SOP! HIlLS: HG I LOU CAL,O.453514 946 3130.159 302.22 CALClITtER 3159.2 filliPSCHIlD SOFT HIlLS: HG & LOU CAL,CII,011170 SOFT HIlLS: HG & LOU CAL,CHI11 SOFT HIlLS: HG & LOU CAL,P0518!38 GIRl (iT!) 11111!: RATULERLU!: 8110118CII: RATHERTODIA: 811011139 AL!, UGH, STOUT, & POLTII:IT!L8 0.045359 553.4 1842.161 300.41 PIP 96 18.624.61370 50.3 332.285 151.38 USDA 113.9 105.7133Pu Pu ILTHHLS1986 1986 Pt/Pg PRICICORIOTIT! ($us) ($cii) huT1.21234 FIAJUTS: SILL) 01 OTIITIS! 1.101.1007111 1075 1.071.211.10635 STOITUIJG 321.2 446.40 0.96382.19 531.99 1.06545.65 758.13 1.24iticAlin: I1CL. LOT CAL 1.071.211.36 lILT: 1111!! & 07111 101.15 148.81 0.880.88331 CIII!) SOFT )L1i[S HG & LOT CAL, 0.65ITTLII 1.00CIII!) SOP! hIlLs: RIG A LOT CAL, 1.32Gill1.05 6Clii!) SOFT HINTS: HG A LOT CAL,PHIIClii!) SOP! huTs: HG & LOT CAL,1057113$ CIII (lvi) lusT!: 117111)iui: RATURI)CII: 11701!)Tout: RATULFI39 ALl, LIGH, STOUT, & POiTli:iTTLh 325.50 452.25 0.91163.12 226.64 0.78134CORIO)ITT C)!. CE!. USASIC ICC 1A1LAL!, LAG!!, STOUT, & POLTU:CflD 104 1131 172 12 1111: CLJJKALL, LAG!!, STOUT, & POlTfl:HCU 105 1131 112 13 EIAUGET ILU40 1111$: !7LE,STL,G!P,ITTU & ILL 10 1141 112 211 1 IIHS: CLAP!172 211 2tILES: fiTH,SPUL!G,GLP 107 1141 172 221 tinS: EPPILTESCELTH!! COOLUS 108 1141 172 51 COOLELSCI)!! 10 1141 172 4 CIII!41 7OIACCO: !LH-CULLD, VIOL! LEAF 110 1211 182 11 !OEACCO: LULl U!SThD LIAFTOLACCO: FLUE-CUIED, LA!1!A 111 1211 182 21 TOIACCO: STEEKED42 CICAIITTJS: 1!CULAL, FLT1 112 1221 III 312 CICLUTTES: FL!!, (: 85 81CIGAL!tflS: LIICSIZI, FL!! 113 1221 113 322 CIGAUflU: IL!!,): 100 II!43 5801110 TOEICCO 114 1221 183 1 SEOLIIC TOLACCO135CDE CON UNITSCOflODIT! USA COB IIPUTS ICC UBITSPRODUCT CODE41ALE, LACER, STOUT, & FORTEL:CHD 20821 01,02,03 BOTTLE CAPS (5%)CABS (lot)----AL!, LAGER, STOUT, & PORTER:DLGUT 20823 64,65 CLASS BOTTLES (151)PAPERBOARO PC[GIG (201)OTRER NATERIALS (151)60 WIlES: BTIO,STL,CRP,ETTLD & !L[ 20840 12,14,16 GRIPES (25!) 071 14 ‘000 TOHEPURCHASED DIRE (101) 172 2 ‘000 ELWills: ITRD,SPIILIG,CRP 20840 31 SUGAR (5!)GRAPE JUICE (101) 074 2 ‘000 ELNIH COOLERS 20840 45 GLASS BOTTLES (35%)PAPERBOARD PACtACIEG (5%)CIDER 2096 11 BETAL CABS (5%)OTIER !ATEIIALS (51)41 TOBACCO: FLUE-CURED, WROtE LEAF 21411 00 TECCO: PLUE-CRD (100%) 181 1 ‘000 TONNETORACCO: PLUE—CUHO, LABIBA 21412 11,15,2742 CIGARETTES: IIGULAR, !LTR 21110 13,16 PRCSSD LEAP (701) 182 1 ‘000 TOll!OTHER BATERIALS (15!)CIGARETTES: UICSIZE, YLTR 21110 18 PAC[AGIIG (25%)63 SBO[IRC TOIACCO 21310 08 STBBD & UISTflD u (80%)PACIAGING (20%)136CII COST USACOO1TT Q ($!ILL) Pc P0D COOK USA 0117 USA QILK, LACK!, STOUT, & POITEI:CflO 188088 lot 8018 KIPESSIYK 11 CAJIDAALL, LACH, STOUT, & POKTK8:HGET40 flitS: 8TLD,STL,GIP,ITTLO & KU 44.81479 25.578 570.75 17211 ‘000 S 708 2612.2307.191 15.451 50.20 208401 IILL I CAL 226.1KINKS: 8T11,SPIILNG,GEP CALC48.278 2.619 54.25lIlt COOLUSCII!!41 708ACC0: PLUL—CUND, IBOLK 11k! 96.40288 355.627 3688.97 214111,23, !ILL LIS 81213211TOLACCO: PLUK-CUND, LAKIKA42 CIGAIKTTIS: RICULAR, P17k 1,321059 7.583 5714.14CICILETTES: IIIGSIZE, FL?!43 SHOLINC TOKACCO 214111,23 8111 LKS 113.313211137‘aCOPhI USA COST USA Q 1987 11111 18 1987CO!IODITY RATIO (sos SILL) (CD! ouTs) ($usi) CODEAL!, LACER, STOUT, & P0RTH:C1NbIL!, LACER, STOUT, & !0kTER:BRGET40 11115: ETRh,STL,GEP,ITTLD & 1L 0.907029 493.9 2365.342 208.45 PPP 95 101.431.15011 299.7 1551.911 35.02 2084—2 93.5 100.11111$: !Tll,SflILIG,GRP CALCCALCUI! COOLERSCIhIR41 TOBACCO: !LUI—CURD, IBOLE LEA! 0.453514 1395.8 368.254 3790.32TOBACCO: !LDE—CUEED, LA!I!A42 CIGARETTES: REGULAR, !LTRCIGARETTES: hUSH!, FL?!43 $101110 TOBACCO 0,453514 160.6 51.383 3125.53138Pu Pu ATHIALS1E4 1q86 Pc/Pu PRICECOREODITY (Sos) ($cRJ) tERREALE, LACER, STOUT, & PORTEL:CEfl 1.53AL!, LIU, 5100!, & PO!fl:DtG!T 1.251.071.11740 fliEs: EflESTL,C1P,!T!LD A ILE 15.3O 271.35 2.1032.11 45.45 1.10RIlES: RTEJ,SPULEC,CE? 0.401.’1TIll COOLERS1.25CI ELI1.07 1.3441 TOIACCO: PLUE-CU1E), IROLE LEAPTORACCO: ILU!-CULED, LARIEA42 CICAIIfl!S: REGULAR, FLIL1.07CICAHITIS: IIIGSIZ!, PLIR43 SEO[IK TORACCO0.139Appendix F OUTPUT Database140C00DITT CDI. CDI. TEAl OPV SIC ICC DL1AIEEI,UGIIG: P1,CE,P1ZI I 1011 011 114 ‘000 TOHE 1986IU!,ILC[ Rb!: 7k,CD,F1ZI 2 1011 011 113 ‘000 !OIfl 1986GRID !EEP,EAHIC1,STITES 3 1011 011 111 1 ‘000 TUllE 19861)1111 TALLOI 4 1011 391 31 ‘000 TUllE 19862 POlL: PR,CH, Ok PHI 5 1011 113 ‘000 TOIl! 1986LAID 6 1011 123 ‘000 TOHE 19863 POll IELLIES & HA!S: 7 1011 013 211 ‘000 TOll! 1986PCLLD,DR!SLTD,CULED 013 22IA!S: SAID & PICIIC DA!S 8 1011 013 212 ‘000 TONI! 1986013 291 3IACOR: SIDE,SID,U8SLCD 9 1011 013 232 2 ‘000 TOIl! 1986IACOI: SIDE,SID,SLCD 10 1011 013 232 1 ‘000 TOIl! 19864 SAUSAGES ii 1011 015 31 ‘000 TOll! 1986IOLOCIL & 0TH SASGS 12 1011 015 322 ‘000 TONI! 1986fillERS & PUTERS: 13 1011 015 324 1 ‘000 70118 1986RE) IEAT EASESALAII: RED !AT EASE 14 1011 015 323 1 ‘000 TOIl! 1986CAINE) HAT 15 1011 017 ‘000 TOIl! 19865 IJIDIDLE TALLON 16 1011 391 13 ‘000 7011! 1986141C0i$OOITT 11111 1985 1986 Cli. CDL 1986 CliIUHU IIUX 11881 Q1T. YALUI UkIT TALUE($cii IILL) (ScDx)8UF,HGIIG: !L,CI,Y1ZR S45.a 1584.144 2901.901IIP,ILCI Ii!: F1,CK,flZI 303.572 1068.937 3521.20GilD 118?!A81G1,S7[TKS 53.464 164.326 3073,58RUILE 111101 32,794 17.489 533.302 YOu: YL,CE, 01 P181 1031.227 2399.288 2326.63LIII 50.146 32.744 645,253 P01 811111$ & EARS: 2.447 13.186 5388.64PC[LD 8118118, CUREDLIES: S!D & PICIIC RIES 79.042 332.326 4204.421ACOI: $181 $!U,UISLCD 4.623 15.839 3426.13DICOR: SI)F,SEtD,SLCD 73.030 290.975 3984.324 SIUSIGKS 30.052 100.385 3340.38DOLOCIL 80111 $LSGS 28.579 16,192 3036.92111181$ 8 PUllS: 51.891 173.459 3342.76118 HAT RISK$11111: LED EEL! ELSE 22.666 96.469 4256.11CAHID lii! 40.654 146.865 3612.565 11181111 111108 358.047 126.351 352.89142COflODITY 1986 C!!. Oc CI! UCK! USATALUE OUTPUT(Sd 1ILL) PECK II!!HH,UGIIG: !IIC!,YEZ8 1584.144 0.559 1111: HOLE CARCASSl!B!,ILCE UT: F1,C,FEZ! 1068.937 0.377 IUP: PLI,SUIP1I!,PAflCU) HU,LAHRGR,ST[TKS 164.326 0.058 CU! !F,HICR,ST[TKSDIlL! TALLO! 17.489 0.006 DIlL! TALLOR2834.896 1.000 1.0132 P011: !L,CH, 01 TEL! 2399.288 0.987 POlK: P185K 1 FEZ!LU! 32.744 0.0132432.032 1.000 0.9593 POEt ULLIES & 1185: 13.186 0.020 POlL !ELLIIS & 1185:PC[L! !LTSLTD,CUUD ?CILD,UTSLTKICURKD118$: S8L1 & PICEIC ElKS 332.326 0.509 118$: SHI & PICRIC lIEStaco!: SI8!,SK10,U!SLC! 15.839 0.024 taco!: SI88,S!H,U!SLCElice!: S1ll,SEti,SLCD 290.975 0.446 lice!: S1!E,SKH,SLCD652.326 1.000 0.9974 SAUSAGES 100.385 0.166 SAUSAGESROLOGH & 0TH SASGS 86.792 0.144 IOLOG!A 1 0TH SiS1111115 & FUTIkS: 173.459 0.287 HIIHS I P07115ii) HA? tASKSiL1II ED HIT lAS! 96.469 0.160 SILIKI: U! EEL? 115!GIlD) HAT 146.865 0.243 CAll!) 8817603.97 1.000 0.9455 IH)IILI TILLO! 126.351 1.000 1.046 IIIILILE TALLO!143CONftODITT USA USA 1987 USA COITII 1987 USAPEODUCT CODE VESTS Q!AETITT 11710 UA87ITTGEE UEITSI1H,EIGIEG: 1L,C8,YEZI 20111 12 ft LBS 8632.3 0.453514 3914,875IEEP,ILC lET: !1,CN,P11B 20111 14,16,18 ft LBS 7035.1 0.453514 3190.521GBH !ZU,RAftIICI,S1[TES 20111 31 ft LBS 3056.1 0.453514 1385.98620138 11lIttLE TALLOV 20111 41 ft LBS 1481.8 0.453514 672.01812 POlL: P1,C8, 01 1lZ1 20114 12,17,51 ft LBS 10083 0.453514 4572.789Lii) 20115 13,17 ft LBS 553.8 0.453514 251.15643 POll BELLIES & liftS: 20116 12,22 ft LBS 314.7 0.453514 142.7210PCLL$,D1SLTE,CU1K8 20136 12,22liftS: S!tB & PICEIC lABS 20116 31 ft LBS 1750.5 0.453514 793.877520136 31licol: SIH,SKI,U1SLCD 20116 35 ft LBS 256.5 0.453514 116.326520136 35JACOJ: SIDE,SBLB,SLCD 20116 41 ft LBS 1559.2 0.453514 707.120120136 414 SLESAGES 20111 11 ft LBS 1010.3 0.453514 458.185920137 11JOLOGEA & 0111 SASGS 20117 35 ft LBS 1911.5 0.453514 U6.893420137 35111111$ & PUllS: 20117 21 ft US 1512.1 0.453514 686.0317B!) BEAT $158 20137 21SiLifti: ill BEAT BASE 20111 17 ft LBS 596.2 0.453514 270.385420131 17CAlEB) BEAT 2011$ 00 ft LBS 1120.9 0.453514 508.344620138 00S JEBIIILE TALLOV 20771 11 ft LBS 3719.2 0.453514 1686.712144C0$IODITT 1987 1987 USA 8STT8 1986 0 USA WGET TOTAL 1987USA TALU! 8811 TALUE USA 38?R815 OUTPUT CHIT SBIPS($us 8ILL) ($us) ($us SILL) pic JIOX8UF,HCIIG: !L,CU,P1Z8 7717.1 1971.22 8191.20 0.386 7717.1!E!!,ELCr LIT: P1,C8IPLZJ 10724.8 3361.46 10016.00 0.472 10724.8CLII IH!,1A811G1,SflTIS 3065.1 2211.49 2838.10 0.134 3015.1HI1LE TALLO 199.2 296.42 179.70 0.008 199.221225.6 1.000 0.976 21701.22 POll: !L,C1, 01 LIII 1210.4 1795.49 8146.50 0.984 8210.4LIII 115.8 461.07 132.00 0.016 115.88278.5 1.000 0.960 8326.23 POll ULLIES & RAMS: 288.8 2023.53 280.40 0.058 288.8P CI L B BET S LTD GUilD8185: S8ID & PICflG 8185 2690 3388.43 2548.00 0.523 2190IACOL: S1Dt,S8[I,OLSLCD 218.7 1880.05 201.60 0.041 218.7IACOI: S1B8,S8ID,SLCB 1858.6 2628.41 1841.00 0.378 1858.64871 1.000 1.017 5051.14 SIUSICIS 1217.5 2766.34 1219.20 0.162 1267.5IOLOCIA & 0781 SASCS 2460.5 2838.30 2443.80 0.311 2460.58858115 & FUTEIS: 1673.4 2439.25 1149.80 0.210 1673.4III HAT SASI51L181: LU HIT lAS! 1209.4 4472.87 1129.20 0.144 1209.4Chill 881! 1312.1 2581,12 1351.30 0.173 1312.11848.3 1.000 0.912 7922.9S IIEDIBLE TALLOV 521 301.88 549.50 1.000 1.046 521145IHPflGI*G: T!,C8,P1ZI1E8P,ILCX II!: P!,CE,!UICU8 UU,11881G1,STLTKSIII8LE TALLOVPUG! IDtIUSII JP 1981 1987 1986 Ptirns flO8IIDlX rini ($ci) h/PtPLOPUC! GO?!87.4 95.7 2501.28 1.162011—117 82.9 89.4 4330.84 0.8181.9 89.8 2802.34 1.10tIS!i 46.9 54.3 355.72 1.500.4720.4240.0960.0071.000 0.9942 Pot!: ?1,CM, OL PILl 2011-4 102.3 105.2 2425.89 0.96 0.985LIII 2011—5 94.1 92.1 654.52 0,99 0.0151.000 0.9593 P011 !!LLI!S & RA8S: 2011—6 110.9 110.2 2829.35 1.90 0.039PC[L8,8LTSL!8,CUIIDlAss: 5810 & PICUC BASS 0.516tACO!: S1H,S8[!,USLCI 0.033tACO!: SII1,SSUJSLCD 0.4121.000 1.0074 SAUSAGIS 2011—711 110.6 120.7 3521.94 0.95 0.164IOLOGIA & 0111 SAIGS 2011—735 9,5 106.4 3481.79 0,82 0.228YflillS & PUTELS: 2011—721 102.9 112.6 3097.13 1.08 0.249H) 1117 8151SALISI: 111 1117 8158 2011—717 93.4 99.5 5833.61 0,73 0.152CAHI) SlAT 2013—8 99.2 101.9 3491.19 1.03 0.2081.000 0.9285 1118111! 71110! 78.5 99.9 337.23 1.05 1.000 1.046CORSODIT! Oi:(Oc+Og)/2 SIOPI2011—6312013 —63 52011—641103.4 102.6 4744.60 0.8997.8 90.6 2819.73 1.22123.6 124.2 3634.27 1.10146COENODITY CDI. CDI. CDI. TEll 0?SIC ICC flITS DATACIICKilS: PI,CEPP1ZI 17 1012 012 1 ‘000 1011! 1986(012 122)7111175 18 1012 0122 ‘000 7011! 1986(01223)(01225)7 tEAlS, Gil 01 VII: CAllED 19 1031 095 2 ‘000 7011! 1986ClUOTS: CAllED 20 1031 095 4 ‘000 TOll! 1986Coil: CAllED 21 1031 095 5 ‘000 7011! 1986PEAS: CAllED 22 1031 095 6 ‘000 1011K 19868 RUSHOO!S: CAllED 23 1031 095 92 ‘000 1011K 19869 APPLE JUICE, JOT COIC: CIII 26 1031 074 1 ‘000 IIC’TGLITH 1986OUNCE JUICE, 107 COIC: CIII 25 1031 074 4 ‘000 JICIOLITLE 1986TOEATO JUICE: CAllED 26 1031 095 981 ‘000 70111 198610 JELLIES: P101! 0! IHfl 27 1031 078 412 ‘000 TOIl! 19861098JAIS: CAllED 28 1031 078 411 ‘000 TOll! 19851098EUEALID!: CAllED 29 1031 078 413 ‘000 TOIl! 1986109811 ttLIS,Cil Di VAX: 30 1032 092 21 ‘000 70118 1986Fill147C0!0DITY TIDE! 1985 1986 CDI. CDL 1986 CDIHEll 18811 III!! QIT. TALUE 8111 VALUE(DI EILL) ($cTI)6 CIICLEIS: Pl,CE,1ZI 46.933 1164.646 2343.67TUILETS 96.267 265.917 2762.917 fiLlS, CLI 01 VA!: CAllED 24.154 26.928 1114.85CULOTS: CAllED 3.313 3.182 960.46COlE: CAllED 61.931 14.431 1201.84PEAS: CAllED 32.143 37.779 1175.348 EUSHOOES: ChilD 9.915 22.794 2298.949 APPLE JUICE, JOT COJC: CUD 2160.517 155.4 71.93O1AIGI JUICE, 107 COIC: CIII 1411.987 122.146 86.51TOIATO JUICE: CALlED 60.406 54.27 898.4210 JELLiES: FLUIT 01 HILT 3.099 6.721 2168.76JAIS: CLuED 611094 127.7 130.3 24.119 62.161 2655.12lARALLH: CAllED 4.537 10.691 2356.4011 lFhlS,C1J 0! lAX: 12.613 16.492 1307.54P1ZI148C0!08ITT 1986 CU. Oc CU V!T USATALU! OUTPUT IAE($cDJ EILL) PlC! 11016 CUCtEIS: P1,C!,UZJ 1164.646 0.814 ClICHES: F1,CE,PEZI7111115 265.917 0.186 TVIIITS1430.623 1.000 1.2597 lIdS, CU 01 SAX: CAllED 26.928 0.189 HiSS, Cli & SAX: CARRElCJ.IIOTS: CAllED 3.182 0.022 CAHOTS: CAllEDCoil: CAllED 74.431 0.523 COil, ilL [ii I ClK:CUDPEAS: ClUED 37.779 0.265 PEAS, Gil: CAllED142.32 1.000 1.3138 !US8l00S: CAllED 22.794 1.000 0.871 IUSHOOES: CARIES9 APPLE JUICE, ROT C0RC CUD 166.001 0.485 APPLE JUICE,SC1 STIGTK:C1OLAIGI JUICI, SOT COSCI CIII 122.146 0.351 O1IC JUICE,SICL ST1GTD:CIT0SLTO JUICE: CAllED 54.27 0.158 TOSATOK JUICE: ClUED342.417 1.000 0.85410 JELLIIS: hUll 01 HilT 6.721 0.077 JELLIES: CIAPE I 07111iii!: CAllED 69.747 0.800 iLls: STiSIET I 071115ILUALLEE: ClUED 10.691 0.123 EALEALIDE87.159 1.000 1.29211 IEIISC11 01 VAX: 16.492 0.050 SEAlS, G1I,EGLR, &nzi Phd c: PHI149COEEODITT USA USA 1987 USA COITEl 1987 USA!EODDC! C08! 01175 Q0A171!T 16710 QH17117CII UUTS6 CUCEEIS: PL,CB,PEZJ 2016 ! LES 13561 0.453514 6150.113TOilETS 2016 8 US 2161 0.453514 982.16641 BILlS, Cli 01 ELI: CAllED 20332 05 ‘000 CS! 49721.9 0.011925 593.0101dEC15: CLUED 20332 15 ‘000 CS! 4652.5 0.011925 55.48152coil: CLUED 20332 94,95 ‘000 C!! 69031.4 0.011966 826.0103PEAS: CLUED 20332 37 ‘000 CS! 26807.9 0.012123 325.0149I !USHOOIS: CLUED 20333 21 ‘000 CS! 4305.1 0.011925 51.347089 APPLE JUICE, lOT COIC: CUD 2033A 11 8 CAL 151.4 37.85011 5730.507OILIGI JUICE, NOT CONC: CIfl 2033k 25 8 CAL 314.5 37.85011 14174.86TONATO JUICE: CAllED 20335 15 8 CAL 97.1 0.003915 382.941710 JILLIES: P1017 01 BEllY 20338 21,25 8 LBS 264.9 0.453514 120.1360JAN!: dANIEl 20338 11,15 8 LBS 454.9 0.453514 206.3038OLUALAII: CAllED 20338 41 8 LBS 18.9 0.453514 8.57142811 11AUG11 01 JLX 20312 13 I LBS 261.9 0.453514 118.7755‘UI150C00JITT 1987 1987 USA 1STJT8 1986 On USA UGH! TOTAL 1987USA TALUZ 8111 TALUK USA S1P1TS OUTPUT C!TT SHIPS(Sus JILL) (Sus) (Sus JILL) ic issi6 CUCUSS: !1,CH,!LZ! 7017.5 1141.04 7139.70 0.826 7451.6TUILITS 1344 1361.57 1506.80 0.174 1511.98646.5 1.000 1.260 9023.51 18115, CLI 08 VII: CAJJH 358.2 604.04 355.40 0.311 358.2CARLOTS: CAHID 35 630.84 35.20 0.031 35COil: CAllED 538.7 652.12 524.30 0.459 538.7P113: ChilD 238.5 733.81 221.30 0.199 238.51142.2 1.000 1.331 1110.48 RUSJLOOJS: CAllED 114.3 2226.03 117.00 1.000 0.871 114.39 APPLI JUICE, JOT COJC: GIlD 355 61.95 347.10 0.210 355081801 JUICE, 80! COIC: 0188 1196 84.37 1012.50 0.614 1196TOJITO JUICE: CAllED 296.5 774.27 290.10 0.176 296.51649.1 1.000 0.154 1847.510 JLLI!S: PLUIT 01 1881! 180 1498.30 186.10 0.364 180JAJS: ClUED 312.3 1513.79 310.40 0.607 312.3RAL!ILADE: CAllED 15.1 1761.67 15.10 0.030 15.1511.8 1.000 1.240 507.411 BUSCh OR UAX 111.1 935.38 114.10 0.049 111.1FBI151PUCE 11081C0E0flTT 8518 1? 1986 1987 1986 ? Oi:(Oc+0)/2 8!OPIIIPPEUS P10811081 11881 ($CDJ) Pc/PuPUODUC7 COOl4 ClIduIS: P1,CE,7128 2018-133 124.4 108.8 1841.81 1.21 0.820TULIETS 2018—3 127.9 105.4 2301.35 1.20 0.1801.000 1.259hIS, CLI Dl 8A1 CAllED 2033—207 106.1 113.1 717.31 1.42 0.250CAnals: CAllED 94.5 105 788.84 1.22 0.027Coil: CAllED 2033—294 88.3 89.4 894.91 1.34 0.491P115: ChIll 2033—294 94.9 91.1 980.31 1.20 0.2321.000 1.3228 8USELOOES: CAllED 78.8 92.3 2440.48 0.87 1.000 0.8119 APPLE JUICE, JOT COlC CIII 2033-411 115.9 118.4 84.25 0.85 0.348OUICE JUICE, 101 COIC: CIII 2037—119 90.4 104 101.90 0.85 0.485101110 JUICE ClUED 2033—515 123.7 128.8 1033.17 0.87 0.1471.000 0.85410 JELLIES: YLUIT 011811! 2033-821 104 104.2 2038.42 1.04 0.220ins: Chill ICITI ATIG 112.5 122.5 1931.54 1.31 0.704IILEALAU: CAllED UlIT VALUE lIT 2421.64 0.97 0.0761.000 1.26511 IUIS,G1I 01 III: 110.1 111 1289.08 1.01 0.050‘LII152CO!!OOITY CII. CDI. Cli. TEA! OFSIC ICC HITS IATAIEAIS,LIA: P111 31 1032 092 22 ‘000 TOHE 1q86I1USSEL SP1OUTS: P121 32 1032 092 4 ‘000 70118 1986CAILOTS: P111 33 1032 092 5 ‘000 70118 1986Cliii PEAS: P111 34 1032 092 7 ‘000 TOll! 1986POTATO!S,PllCB FRIED: P118 35 1032 092 81 ‘000 TOIl! 1985C0Rf,IICL C—oI—C: Fill 36 1032 092 6 ‘000 70111 1986HOCCOLI: P10188 37 1032 092 3 ‘000 TOll! 198612 FLUID lILt: HOLE & PRCSSD 38 1041 051 231 ‘000 !ECTOLITRK 1986051 232FLUID lILt: PROCESSED, StEID 39 1041 051 233 ‘000 IECTOLITRE 1986TOCHR7 40 1049 051 96 ‘000 7011! 198613 CRIAIIRT 807711 41 1049 051 31 ‘000 10111 1986051 3314 CHili: CR8181! & OTHERS 42 1049 051 411 ‘000 7011! 1116051419CHIli: PROCESS 43 1049 051 45 ‘000 7011! 1986CHili: COTTAGE 44 1049 051 44 ‘000 TOIl! 198615 5111 liLt LID! 45 1049 051 52 ‘000 TOIl! 1986H!! P011!! 46 1049 051 55 ‘000 7011! 1986153COEIODITY 11111 1585 1986 Cfl. COO. 1986 COORUHH INDEX INDEX QTT. TILDE UNIT TILDE(Scox NILL) ($coo)IIAIS,LIA: FEZ! 0.681 0.726 1505.20IIUSSEL SflODTS: YEZI 6.42* 5.214 1177.51CAHOTS: FEZ! 15.068 11.417 723.28CEEKI PEAS: FuN 33.124 42.117 1271.49POTA!GES,PHCB 71110: P12! 611058 113.1 114 278.636 214.667 772.45COU,I*CL C—ON-C: £118 22.939 29.81 1299.53RIOCCOLI: P10218 3.005 7.812 2050.9312 FLUID NIL[: 180LE & PECSSD 24126.207 2006.147 83.15FLUID NILE: PLOCESSU, StOOD 1404.716 110.663 78.78TOCOULT 74.025 154.181 2623.1813 CLIANIET EUTTOL 116.822 597.675 5116.1214 ChESt: CIEDDAL & OThERS 157.430 1032.281 5228,59CHOSE: PROCESS 76.244 447.320 5867.06CHESt: COTTAGE 32.041 85.202 2659.1615 SUN NILE POOL 107.441 302.064 2811.44OUT P08111 67.126 27.613 411.36154C088001TT 1986 CDI. Oc CDT VGKT USAVALUE OUTPUT lATE($CDJ IILL) PECK ITO!IIAIS,LIlA: FEZI 0.724 0.002 IDAIS,LITA: PHIHUSSIL SPROUTS: FBI 5.214 0.016 IEUSSEL SPROUTS: P121CARROTS: P111 11.477 0.035 CARROTS: FEllGREET PEAS: FIll 42.117 0.128 CUll PEAS: FillPO!A1OKS,PRICE flIED: P128 214.667 0.654 POTATOIS,IIIC! PlUS: FEZC01J,IICL C—0I-C: FElT 29.11 0.091 CO1I,IICL C—OI-C: FLiTIEOCCOLI: P80118 7.812 0.024 HOCCOLI: FEll328.313 1.000 0.88212 FLUID EILL: HOLD & PICSSD 2006.147 0.868 FLUID TILL: TEL I PICSSDFLUIJ TILL: PROCESSED, SITED 110.663 0.048 FLUIJ TILL: StiflEDTOGIUIT 194.181 0.084 YOGI!!2310.991 1.000 1.43313 CHATUT TUTTlE 597.675 1.000 1.133 CiLATUT IUTTFI14 ClUB: CHIDAl I OTTERS 1032.281 0.660 dUSK: ITEL Lid?! CTATGKdUST: PROCESS 441.328 0.286 PROCESS CR1851CURSE: COTTAGE 85.202 0.054 COflACK CURSE1564.811 1.000 1.30415 5118 TILL P18! 302.064 0.602 SLIT TILL PHITHY POUT! 21.613 0.055 JET THY155C0I0DIT! USA USA 1987 USA COlT!! 1987 USAP1ODUCT COD! VIITS QUAITIII LATlO QUAITIT!CDI UlITSllA1S,LIA: 1121 20372 21 LII 110.4 0.453514 50.06802ILUSSIL ShOUTS: 111! 20372 31 I LII 52.8 0.453514 23.94557CA11OTS: 7!!! 20372 33 I 1.15 272 0.453514 123.3560CIII! PEAS: 7!!! 20372 41 I 1.15 375.2 0.453514 170.1587?OTATO!S,11!CB 71118: 1!!! 20372 48 1 LIS 4735,1 0.453514 2147,437COII,1!CL C—O!-C: ILL! 20372 53,55 1 1.15 701.3 0.453514 320.7709ILOCCOLI: 710211 20372 25 I LII 330 0.453514 149.659812 ILUID EIL[: 1801! & PRCSSD 20261 12 I GALS 5620.84 37.85011 212749.420262 12,231101? IILL: P1OCISSID, 51118 20261 15 I GALS 510.4 37.85011 19318.6920262 25TOCEU1T 20265 00 I LII 1339.07 0.453514 601.291620240 3113 CHAlEt! ZUTTE1 20210 13,15 1 LII 1080.6 0.453514 490.068014 CR115!: CUDDLE & OTULS 20223 00 I LII 4801.6 0.453514 2177.596CURS!: P1OCISS 20224 21 I LII 1356.9 0.453514 615.3141CR115!: COTTACK 20263 13,16,18 1 L!S 993.1 0.453514 450.385415 StIR lILt P181 20235 11,43 N LII 1026.9 0.453514 465.7142III! 701811 20235 45 I LII 962,4 0.453514 436.4625156CORKOIITY 1987 1987 051 !STKTD 1986 0 USA VCET TOTAL 1987USA TALUK 881! TALUK USA SIPilTS OUTPUT CKDTT SNIPS(Sos KILL) (Sos) ($os KILL) FtC Ill!IEAIS,LI!A: FRZ! 52.6 1050.57 54.60 0.024 52.6HUSSEL SPLOUTS: FiLE 30.2 1261.19 31.40 0.014 30.2CAHOTS: PiLl 18 632.32 71.00 0.031 78lUI P815: FiLE 153.5 902.10 154.10 0.067 153.5POTATOKS,118C! 11188: FiLl 1465.8 682.58 1400.70 0.607 1465.8COt1,IICL C-Of—C: PILE 298.5 930.57 302.00 0.131 298.5I1OCCOLI: P10288 114.6 1166,65 171.30 0.077 114.62306.9 1.000 2364.312 PLUIN KILL: 8EOLI & P1CSSD 9169.1 43.10 9152.30 0.867 9169.1FLU!) KILL: 110085518, SL!K8 721.2 37.33 703.20 0.067 721.2YOCIULT 789.8 1300.53 703.2 0.067 789.810558.7 1.000 1.435 10680.113 0181881! IUTTEI 1544.3 3151.20 1601.10 1.000 1.133 1544.314 CEllS!: CR8811 A OTHELS 6414.5 2945.68 6248.30 0.710 6414.5CElls!: P1OCISS 1860.8 3023.85 1892.00 0.215 1160.8ClEfS!: COTTAGE 657.2 1459.19 659.60 0.075 657.28799.9 1.000 1.297 8932.515 SKI! KILL P811 819 1758.59 896.30 0.644 819JUT P08088 221.4 507.26 192.60 0.138 221.4157PUCE 11181C0$80D11T USEO IP 1986 1987 1986 Pu Oi:(Oc+Ou)f2 !EOPIOIPPHS P10811081 11011 ($CD1)PEODUC! COOLIEAIS,LIEi: Pill UU! VALUE ES! 1478.75 1.02 0.013IZUSSIL SPEOUTS: Pill 106.4 107.1 1140.85 0. 0.015CAflOTS: FiLE 121.3 124.6 855.27 0.85 0.033Cliii PUS: FEll 133.9 133.9 1253.38 1.01 0.098POTA!DES,PEJCE Y1IED: rizi 123.4 125.2 934.74 0.83 0.631C0Ll,IICL C-Of-C: Pill ICITO ATEG 10.3 108.5 1266.72 1.03 0.111HOCCOLI: P10188 103.8 105.8 1590.30 1.29 0.0511.000 0.90712 FLUID EILI: 88018 & PECSSD VGRTD AVEG 100.6 102.6 58.71 1.42 0.867FLUID 1111: PEOCESSED, StEED 2026-225 103.9 111.3 48.42 1.63 0.057TOGRU8T 2026—432 108.2 112 1745.65 1.50 0.0751.000 1.43413 CLIAEEET EUTTER 2021—1 98.1 95.1 4516.39 1.13 1.000 1.13314 GUiSE: CEEEDAL & OTHERS 2022—1 96.6 95.5 4139.87 1.26 0.685CINSI: FEOCISS 2022—211 91.5 91.2 4215.16 1.39 0.250ClHSE COTTAGE 2026—3 100.8 105.2 1942.61 1.37 0.0651.000 1.30115 SUE EILL P801 2023—143 88.9 87 2496.74 1.13 0.623HEY POllEE 2023—13 91.9 169.2 382.80 1.01 0.097158COi08ITY CII. CDI. CDI. 7811 OFSIC ICC HITS 1111ITFITE EILI,IEL & SEE: CUD 47 1049 051 612 ‘000 EECTOLITEE 1986051 2216 IC! CRIAl II 48 1049 051 951 ‘000 IICTOLITE! 1986I1L SILK! III 49 1049 051 953 ‘000 EECTOLITEE 1986IC! CElL! 50 1049 051 711 ‘000 HCTOLIflE 198617 IHAT PLOUE 51 1051 062 15 ‘000 TOIl! 1986(062 155)(042 156)IULU! FLOUE AID SE!OLIIA 52 1051 062 156 ‘000 7011! 1986HOLE VEIL! 0! GE!! P100! 53 1051 062 155 ‘000 70111 198111 PUPAl! CAl! 81185 54 1052 066 31 ‘000 70118 198619 IUAKPAST dUALS: IS 55 1052 066 11 ‘000 1011! 1981tOLLED OATS, UIPEFED 51 1051 061 122 ‘000 TOIl! 198620 P00111! COIPLETE PHD 57 1053 159 15 ‘000 TOIl! 1985lAItY COEPLCT! PU! 58 1053 159 112 ‘000 7011! 19858111! COEPLET! PEED 59 1053 159 13 ‘000 TOll! 1911HIP COIPLITI FlU 40 1053 159 113 ‘000 10118 1986159COEIODITY TIDE! 1985 1986 CDI. CDI. 1986 CDI108111 1188! TIDE! Qil. VALEt HIT VALUE(ScED 8111) ($cDI)ZYPETD 8IL,HHL & 1t8: CIII 1046.993 111.792 164.0816 ICE CIIAI III 230.865 34.116 141.77III! SHAKE III 201.279 19.543 97.09IC! CuE 2812.004 379.51 132.1411 11117 FLOU1 1595.785 674.844 422.89DULUE FLOUI 110 18801111 121.607 52.267 429.80JIOLI HEAT 01 CEll! FLOUk 54.407 21.054 386.9718 ?lIPA1i CAll EIIES 31.502 75.344 2009.0719 IIIAULS1 CEREALS: uS 107.256 339.537 3165,67ROLLED OATS, UIPIPH 40.224 39.604 984.5920 POULTRY COEPLETE FEED 611121 91.9 89.1 2504.810 630.923 244.21DAIRY COEFLET! PIED 611119 101.1 92 1529.824 339.411 201.8951118 COEPLETE FEED 2033.191 465.617 229.01IHI CORPLITI PHD 613.65 Q.477 147.77160C0!O)ITT 1986 CDL Dc CD! !GET USAVALUE OUTPUT EAHE($cos 8311) PIG! IHI!TP1 8IL[,VEL & SEE: CUD 171.792 0.343 111P011788 EILE: CLUED501.469 1.000 1.08216 IC! dEL! III 34.116 0.079 ICE CIIAE Eli8111 SEAL! ElI 19.543 0.045 EILI SHALE 831IC! CIII! 379.51 0.876 IC! dUkES433.169 1.000 1.24617 fEEl! PLOUE 674.844 0.902 VIII! PLOUIDUEU! PLOUE AND SUOLINA 52.267 0.070 EUIU! PIQUE. & SKEOLINA18011 fEEl! 08 CII! P1001 21.034 0.028 VEOLI 1111! PLOUI148.165 1.000 1.43518 PLIPHED dIE! $1181 75.344 1.000 0.755 PUPAtED CAL! 8111119 IIIACPAST CEUALS: iTS 339.531 0,896 IUALPAST dEALS: US101111 OATS, UJPIPDJ 39.604 0.104 tOLLED OATS319.141 1.000 0.64120 POULTEY COEPLET! FEED 594.202 0.343 POULT8T COEPLET! FEED81111 COEPLETE PHD 323.387 0.187 8118! CORPLE!! PEEDEVIl! COEPLETE P811 465.611 0.269 Sf11! COEFLETE PEED11EV COEPLETE VIII 90.611 0.052 811! COEPLETE 8189161C0880D1TT USA USA 1987 USA COIVR* 1987 USAPIODUC! COil UlITS QUifT1T RATIO QUAE!ITTCDI UUTS1T?lTb !ILL,EUL & 5t8: GlIB 20236 12 8 LBS 535.8 4.671201 2502.82916 IC! GRuB BIX 20238 11 8 CAL 220,6 37.85011 8349.735BILL 51118 811 20238 13 8 CAL 55.9 37.85011 2115.821ICE CREA! 20240 14,15 8 GAL 832.4 37.85011 31506.4311 VHA7 PLOUR 20411 05,11,13, ‘000 SLS 293171. 0.045351 13295.7515,17,21,23,26,28,29BURUB ?LOU AID SEBOLIIA 20411 51 ‘000 SLS 26121.8 0.045351 1212.145UOLE IHAT 01 Gill PLOUR 20411 31 ‘000 SLS 5383.4 0.045351 244.145118 ?HPflH GALE 81185 20450 5354 ‘000 SLS 9103.9 0.045351 412.87519 BUAL!AST CEREALS: iTS 20430 11,12, 8 LBS 2649 0.453514 1201.36015,17,21LOLL!) OATS, 8111118 20430 57 8 LBS 287.1 0.453514 130.476120 POULTRY CORPLITE P11) 20481 11,15, ‘000 S 10118437.2 0,901029 16723.0816,18lilt! COIPLETE PIED 20482 00 ‘000 S 701 8620.4 0.907029 7818.9561111! COIPLETE PEED 20484 00 ‘000 S 101 2144.5 0.907029 1945.124III? CORPLITI TUB 20486 00 ‘000 S 708 3056,9 0.901029 2772.698162CO!ODITY 1987 1987 USA UST!TD 1986 On USA ICE! TOTAL 1987USA TALUE UII! !ALUE USA SIPITS OUTPUT C!DTT SEIPS(Sas !ILL) (Sus) ($us IILL) PiC 110!IT?Efl 81L[,IAL & Sri: CUD 290.9 116.23 303.60 0.218 290.91392.5 1.000 1.093 1331.316 ICU CLEAR II 491.3 58.84 471.20 0.155 491.3SILt SKAtE 111 120.4 56.90 122.50 0.040 120.4IC! CLEAE 2562.4 81.33 2451.20 0.805 2562.43064.9 1.000 1.282 3174.117 WHAT PLOU1 2755.8 207.27 2745.20 0.905 2755.811108 11001 AID SE8OLIIA 258.3 213.09 243.60 0.080 258.3HOLE HEAT 01 ClUE 11011 50,4 206.43 44.70 0.015 50.43033.5 1.000 1.437 3064.518 PL8PA1E CitE EIIES 823.9 1995.52 763.80 1.000 0.155 82319 ILEIIPAST CE1EALS:’LTS 4630 3853.96 4221.10 0.973 4630LOLL!! OATS, 1111111 120.5 923.54 116.10 0.027 120.54337.2 1.000 0.628 4750.520 POULTIT COEPLETE PEED 2708.3 161.95 2769.30 0.372 2708.3lilt! COEPLIT! 111! 1221.5 156.22 1268.30 0.172 1221.55111K COEPLUTE PEED 416.3 216.02 445.70 0.060 416.3II!! C08?Lfl! 111! 431.2 155.52 446.20 0.060 431.2163PRICE INDEXCOEEONITT USED IF 1986 1987 1984 h Oi:(Oc+Ou)/2 EROFIDIPPERS FROEIIDEX 111k! ($cn) Pc/PuPRODUCT CODEETFITE EILK,V!L & SKE: CUD 2023-212 104.8 104.2 162.42 1.01 0.2801.000 1.08716 ICR ClEAN NIX UNIT VALUE ES! N4.07 1.76 0.117NILL SELL! NIX UNIT VALUE ES! 19.72 1.22 0.043IC! ClEAN 2024-1 106.1 109.7 109.29 1.21 0.8411.000 1.26317 TREAT FLOUR 2041—1 91.4 89.7 293.44 1.44 0.903DURUN FLOUR AID SENOLINA 0117 VALUE ES! 303.36 1.42 0.075YROLE HEAT OR CDII FLOUR UNIT VALUE 85! 297.67 1.30 0.0211.000 1.43618 PREPARED CAKE 11185 2045-553 101.5 105.7 2662.41 0.75 1.000 0.75519 IDIALPAST CEREALS: iTS 2043—1 116.1 122.5 5074.94 0.62 0.934ROLLED OATS, NIPEPED 2043—115 117.3 123.6 1217.74 0.81 0.0461.000 0.63420 POULTRY CONFLEII PUN 28-1 71.1 71.4 224.07 1.09 0.358DAIRY CON?LETE FEED 2048-2 77.8 76.1 221.90 0.91 0.179STIR CONFLETE PEEP 2048—4 86 83.5 306.27 0.75 0.165NE!? COEPLETE TEED 2048-6 89.3 100.1 192.76 0.17 0.056164COIROIITY CDI. CII.SIC ICCCl!. 781! 0!OuTS 11711986198619861 9198621 JOG & CAT !EEJ: ClUED 66 1053. 159 31 ‘000 70HZ 1986JOG & CAT FEED: 10! CIII 67 1053 159 32 ‘000 TOIl! 198622 CIVIL OIL 8071111 68 1061 393 194 ‘000 10111 1916507111! OILCI[K I REAL 69 1053 153 3 ‘000 TOIl! 1986106123 IISCOITS: FLAIl & luCY 70 1071 064 22 ‘000 TOIl! 1986107224 11118 71 1072 064 11 ‘000 TO!!! 1986FUll tOLLS & 801$ 72 1072 064 12 ‘000 TOIl! 1986lots! CORPLET! PIED 61 1053 159 12 ‘000 TO!!!11111 CATTLL PIED SPLR11S 62 1053 158 912 ‘000 701!!SOIl! PEED SPLIRTS 63 1053 158 92 ‘000 7011KIII! CATTLE PHI SPLEITS 64 1053 158 913 ‘000 7011!POULT!T PEED SPLI!! 65 1053 158 93 ‘000 7011K25 SVGA!: CII! & !L1T,GHLTD,H7 73 1081 101 31 ‘000 10111 SLI 1116165C00UTY 11081 1985 1986 CDI. CD!. 1986 CD!I0!Ek III!! IIDIX (1!. TALU! USI! YALU!($cD! EILL) ($co)IOU! COEPLITI PIED 59.629 14.875 249.46III!! CATTLE IKE! SPLETS 294.758 83.151 282.10SI!!! PU! SPL!ITS 258.54 91.587 354.251!!! CATTLE FEED SPLIITS 149.242 33.796 226.45POULT1T 1110 SPL8IT 91.265 34.802 381.3321 lOG & CAT PU!: CLUED 143.127 144.841 1007.75DOG & CIT FEED: JOT GIlD 214.358 220.313 1027.7822 CLU)! OIL: SOTIEA! 95.108 57.271 602.17SOTIEA! OILCLLE I HAL 605.948 162.052 267.4423 uSd178: FLAIl & PAICT 168.201 503.21 2991.7224 1181! 604.876 744.6 1231.00PHI! tOLLS & ILIIS 121.533 200.55 1650.1725 SUCfl: CUE & REET,GLJLT!,!ET 638.084 286.839 449.53166IORSI COEPLETI FEEDlAItY CATTLE FEED SPLEETSSEINE FEED SPLENTSREEF CATTLE FUD SPLINTSPOULT1T Fill SPLINT14.875 0.00983.151 0.04891.587 0.05333.796 0.02034.802 0.0201732.094 1.000 0.91010151 & NULl CEFITE PHDRAIL! FEED: SPLINTS & dCSTINK TEED: SPLINTS & CRCREEF CATTLE: SPLINTS & CEPOULTU: SPLINTS I CICS21 lOG & CAT PIED: CANNED 144.841 0.391 lOG & CAT Fill: GAllED)OG & CAT PEED: JOT CUD 220.313 0.603 lOG & CAT FEED: It!365.154 1.000 0.99322 CLUDE OIL: SOYHAN 57.271 0.261 CLUDE OIL: 5011118SQuEAl OILCALI & NEAL 162.052 0.739 SOYHiE GILCAIK & NEAL219.323 1.000 1.05324 IlIAD 744.6 0.788 11111: 8E1,LYE,IIL & CLCEUEAT,OTKLS200.55 0.212 tOLLS: IlIAD TTPL945.15 1.000 0,854CONNODITY 1986 CDI. Oc CDI EGET USATILE! OUTPUT IAN!($cDN NILL) PLC! 118123 flSCUITS: PLAIN & PAId! 503.21 1.000 1.103 COOKIESPLAIN tOLLS & EElS25 $1011: CIII & IE17,C1ILTD,EIT 286.839 0.626 CULT! CIII & 1111 $1011167C0810fl1T USA USA 1987 USAPLODUCT CODE 01175 QUA(TIflCOIVU 1987 USARA1IO QUAITITYCDI 11817521 bOG & CAT PEED: CAHED 20473 21,23 E 185 3532 0.453514 1601.81420474 41,43SOC & CA! YB18 107 GIlD 20473 26,36 8 LBS 10109.7 0.453514 4584.89720474 54,5722 CIUDE OIL: SOYBEIE 20751 13 8 LBS 9895.4 0.453514 4487.70920751 15SOTUAI OILCAU & 8811 20752 11 ‘000 S 70126450.6 0.507029 23591.4723 BISCUITS: P1118 & FANCY 20521 23,33,35,98! LBS 5340.4 0.453514 2421.9502213,15,19,2124 11118 20511 11,13, 8 LBS 11629.2 0.453514 5274.01315,17,28PLAIN tOLLS A BUNS 20512 33,35,36, 8 11537,39,40,425251.3 0.453514 2381.54125 SUGAL: CANE & BKET,GIIL7D,8!! 20620 09,12,14, ‘000 S 701 7064.1 0.907025 6401.34615, 20630 07,13,801$! CO!PL!7E PEED 20488 16 ‘000 S 701 1316.1 0.907025 1193.741BAIL! CATTLE PEED SPLINTS 20483 01 ‘000 S 708 1680.3 0.907029 1524.081$811! PEED SPLUTS 20485 03 ‘000 S 701 3360.8 0.907029 3048.344IKE! CATTLE PEED SPL!!TS 20487 05 ‘000 S 708 2642.4 0.907029 2396.734P00171! FEED SPIlL! 20481 21,22,23,24’OOO S 101 1649.1 0.907029 1495.182168CO!OBITY 1987 1987 USA ESTEID 1986 h USA ICET TOTAL 1987851 TALUE 8111 !ALUI USA SEPNITS OUTPUT CEDIT SEIPS($us EILL) (Sus) ($us EILL) PEC rx80111 COEPLETE PEED 225.1 188.57 220.80 0.030 225.1DAILY CATTLE FEED SPLUTS 398.2 261.27 423.90 0.057 398.25818K PEED SPLEITS 930.4 305.21 964.50 0.131 930.4III! CATTLE P888 SPL!1TS 476.2 198.6 500.00 0.068POULI1T PHD SPLERT 331.8 221.82 366.40 0.050 331.81385.1 1.000 0.958 6807.221 DOG & CI! PRED CAllED 1439.2 898,48 1398.90 0.319 143.2DOG & CAT PEED: 801 CR88 3090 673.95 2992.80 0.681 30904391.7 1.000 1.017 4529.222 CLUDE OIL: 5011818 1620.5 361.10 1659.40 0.254 1620.55011111 OILCA[K & EKAL 4962.9 206.86 4875.10 0.746 4962.96534.5 1.000 1.051 6583.423 IISGUITS: PLAID & PARC! 4906 2O25.4 4582.40 1,000 1.103 490624 11811 5695.8 1079.97 5427.80 0.772 5695.8FLAIR LULLS & 8015 2972 1247.93 1600.40 0.228 29721028.2 1.000 0,855 8667.825 SUCh: CARE & EEE!,CLILTD,WET 3419.4 533.67 3404.70 0.834 3419.4169PuCE IHEXC0E0D1T 8311 1! 1986 1981 1986 h Oi:(Gc+Ou)/2 EVOPIDIflHS P1081108! lEn! (Scn) Pc/PaPRODUCT CODERORSE CORPLETE PEED 2048-816 .7 100.1 253.10 0. 0.019lATH CATTLE FEED SPLRETS 2048—3 19.8 81.1 354.57 0.80 0.053SUE! FEED SPLEETS 2048—5 87.5 93.5 396.85 0i9 0.092EU? CATTLE PEED SPLEITS 2048—7 85.8 86.8 212.88 0.83 0.044POULTRY PHD SPLUT 2048—117 85.6 92.6 284,90 1.39 0.0351.000 0.93421 DOG & CAT PEED: CAllED EGETO AVEG 100.8 102.7 1225.25 0.82 0.358DOG A CAT FEED: 80! CR10 EGITI ATRG 100.9 103,3 914.63 1.12L000 1.00522 CRUDE OIL: SOYlKAN 2075—11 58.7 57 516.67 1.17 0,258SOYHAl OILCAEE & REAL 2075—2 83.4 91 263.41 1.02 0.7421.000 1.05223 USCUITS: PLAID A FAICT 2052-fl 112.3 116.5 2712.96 1.10 1.000 1.10324 IlIAD ICE!) AUG 130,2 131.3 1487.95 0.83 0.780FLAIR ROLLS & lUll 2051—23 128,8 129.1 1121.84 0.96 0,2201.000 0.85525 SUGAR: CAll & IIET,CRILTD,IET ECETO AUG 105 107.8 722.22 0.62 0,73017026 CIIIIIG G08 18 1082 104 1 ‘000 70111 198627 CIOCOLAT1 C01?ECTIOIZ1T 79 1083 104 2 ‘000 70818 1986CHOCOLATE, COATIEGS 80 1083 111 32 ‘000 70818 1q86SECAE COIYECTIOIHT 82 1083 104 7 ‘000 TOIl! 198628 COP!!! : IOAST!D 83 1091 112 2 ‘000 70111 198529 711: ILLIDKI, PACLID 84 1091 113 2 ‘000 7011! 198630 PASTA PEODUCTS: 8!! 85 1092 065 1 ‘000 TOIl! 1986109831 P071108 C!IPS,PLAIIS,!1ILLS, 86 1093 146 ‘000 70811 1986& 581.8 PlODSPOPCOLI (!XC!PY CAJOlED) 87 1093 146 8 ‘000 7011! 1986COUODITT CDI. CII. CDI. TEAl 0!SIC ICC HILTS DATASUCAL: ICIIG,PC[CD,CAEE & 1887 74 1081 101 352 ‘000 70118 SLD 1986SUCAL: S0!T,GLILTD,CAII & 1111 75 1081 101 341 ‘000 TOIl! 51.8 1986SUCH: IIVELT, CUE & lEE! 76 1081 101 331 ‘000 70188 SLO 1986LIU1D SUCLOS!: CAN! & 11!! 77 1081 101 333 ‘000 TOIl! SLD 1986171C08ODI1T IIDKI 1985 1986 CDI. CDI. 1986 CDIIUflEL 11HZ 1188! Q7T. TALUE 0817 VALUE($cDI IILL) ($cD8)SUGAL: ICIIC,PCLCD,CAII & 1111 40.142 20.67 514.92locAl: S0?1,CRILT),CAIE & 8887 53.971 21.599 529.90SUGIL: 18781!, CAll & III! 150.9 67.557 447.43LIQUTI SUCEOSE: CI!! & BEE! 135.031 54.606 404.4026 CIEHIG CU! 19.297 149.72 7758.7227 CIOCOLITE COIPECTIOIELY 73.788 478.723 6487.82CEOCOLA!!, COA’IIGS 7.006 16.956 2420,21SUCh COIFECTIGIELY 78.368 238.405 3042.1228 COflK! : 8015718 611176 128.7 166.8 51.456 387.226 9753.1729 TEA: ILEIHD, PICKED 13.169 98.045 7445.1430 risii PIOIUCTS: IL! 144.615 200.412 1386.2531 8071708 CBIPS,PLAKES,PEILLS, 71.644 475.905 6642.64& SELL PLODS?OPCOLI (EXCEPT CAIDIED) 1.416 10.866 7673.73172C0iODITT 1986 CDX. Oc CDI ICR! USATALUE OUTPUT IAK($cn 8ILL) ric ixSUCAR: ICIIG,PCCD,CAI8 & 188! 20.67 0.045 C0XF!CTIOflIS’ P8810 SVGASUCH: SOFT,GRJLTD,CAIE & IRE! 28.595 0.062 SOFT OR IlOli SUGARSUGAR: INTER!, CANE & lilT 67.557 0.147 mU! SUGAR: CAN! & U!!LIQUID SUC1OSE CUE & IRE! 54.606 0.119 SUCROSE436.271 1.000 0.59626 ClUING GUN 149.72 1.000 1.046 CERVING GUN27 CIOCOLATE COIIECTIOIKLT 478.723 0.652 CROCOLATE CONPECTIONELTCHOCOLATE, COATINGS 16.556 0.023 CIOCOLA7E coiicsSUGAR CONFEC!IONIIY 238.405 0.325 SUGAR CONFECTIONERY734.084 1.000 0.94528 COPPER : ROASTED 480 1.000 1.104 COFFEE: G1NDEEAN,NIflS29 TEA: ELUDED, PICKED 98.045 1.000 0.920 TEA: PCKI II TEA NAGS30 PASTA PRODUCTS: UT 200.472 1.000 0.959 NACHONI & NOODLE PRODS31 POTATOR CBIPS,YLAIES1FRIL S, 475.905 0.950 CUPS & STICKS& SILt PRODSPOPCORN (EXCEPT CANDIED) 10.866 0.050 OTIEL CUPS & STICKS173CONNODIT! USI USA 1987 USAPL000CT CODE VESTS QUAITIT!COITLI 1987 USALATIO QUAETITTCDI OUTS26 ClInIC GU 20670 11,14 8 LES 299.847 0.453514 135.985027 CIOCOLATE COEPECTIOIELT 20642 00 N uS 1909.2 0.453514 865.850320662 00CROCOLATE, COATIECS 20661 12,22, 8 LES 528.7 0.453514 239.773232,52SUCH COEPECTIOEEL! 20643 00 N LES 1991.6 0.453514 903.219928 COFFEE LOISTED 20951 11,15,21 N LES 1126.7 0.453514 828.435329 TEA: ELUDED, PACtED 20998 82 N LIS 124.1 0.453514 56.2811730 PASTA PLODUCTS: DL! 20980 21,31 N LES 1833.9 0.453514 831.700631 POTATON CIIPS,!LAIES,TLILLS, 20961 00 8 LES 2297.2 0.453514 1041.814& SILL PLODSP0?COLI (EXCEPT CAnTED) 20963 00 N LIS 319.1 0.453514 144.116515SUCH: TCIEC,PC[GD,CUE & IRE! 20620 31,35 ‘000 S TOE 354.4 0.907029 321.451220630 33SUCH: SOPT,CULTD,CAIE & lEE! 20620 41,45 ‘000 S TOE 222.9 0.901029 202.1768SECAL: lEVEL!, CAIE & III! 20620 56 ‘000 S 101 92.2 0.907029 83.6281120630 55LIQEID SUCEOSE: CAll & DIET 2O20 53 ‘000 S TOE 477.6 0.907029 433.197220630 51174CONODITY 1987 1987 USA ISTITU 1986 Ou USA UGHT TOTAL 1981USA !ALUE UNIT TALON USA SHNE!S OUTPUT C8DTT SHIPS(Sos Eli.’.) (Sos) ($us NuLL) TRC iioiSUGAR: ICIIC,PCrGH,CAN! & Nfl! 208.5 448.62 214.80 0.053 208.5Such: S0YTGLRLT9,CAII & lENT 137.6 680.59 142.50 0.035 137.6SUGAR: INTIL!, CAIN A BET 47.1 563.21 44.90 0.016 47.1LIQUID SUCROSH: CIII & lEE! 243.3 561.64 254.70 0.062 243.34081.6 1.000 0.611 4055.926 ClUING GUN 785.6 5777.11 116.10 1.000 1.046 185.621 CHOCOLATE COIFECTIONERT 4082 4716.44 3163.60 0.586 4082CHOCOLATE, COATINGS 580.4 2420.62 525.2 0.082 580.4SUGAR COIFEC!IQIIIY 2296.7 2542.79 2136.10 0.332 2296.76423.6 1.000 0.921 6959,128 COPIRE : ROASTED 4302.7 5193.71 4191.20 1.000 1.104 4302.729 TEA: ILEIDED, FAdED 569.1 10111.13 568.90 1.000 0.920 569.130 PASTA PRODUCTS: DLI 902.8 1085.49 872.10 1.000 0.959 902.831 POTATOR CUPS,PLI[E5,P1.ILLS, 4265 4093.82 3872.60 0.872 4245I SELL PRODS?0?COLI (flczr! dAllIED) 559.1 3863.41 566.7 0.128 559.1175PRICR I8OEXUSK8 1! 1986 1987 1986 P81F!IIS Fk0IJDEI 11181 ($cn) Pc/PaPRO8UCT COOKSUCH: ICIIC,!CKG8,CU8 & HE!SVCAR: SOTTGIILT8,CAR! & 8!!!SUCH: IE1T, CIII & 88!!LIQU SOCKOSK: CAK! & EKE!UJIT YALUE ES!HIT TALUE IS!UflT VILUE KS!HIT TALUR KS!0.0490.0490.0820.0911.000 0.60326 CIIIIJC CUE 2067-112 111.3 120.4 7420.04 1.05 1.000 1.04627 ChOCOLATE CONPECTIOJE[Y 2065—211 114.8 114.7 6555.95 0,99 0.619CEOCOLATE, COATINGS 2066-1 106.4 106.1 3372.72 0.72 0.052StJCA1 COIFECTIONHY 2065—311 109.6 111.9 3460.34 0.88 0.3291.000 0.93628 COP!!! : ROASTED 141.5 115.6 8833.00 1.10 1.000 1.10425 Hi: ILINHO, PICtfl 2099-5 101.7 102.1 13994.19 0.92 1.000 0.92030 PASTA PLOEUCTS: 81! 2098-1 98.2 102.5 1444.91 0.96 1.000 0.95931 POTATO! CHI!S,PLAUSJLILLS, 2099—211 99.9 101 5626.01 1.18 0.911& SELl P1005rocou (EXcEPT CANDIED) 2095-985 100 102.5 5236.91 1.47 0.089C0EIOD ITT Oi:(Oc+Ou)/2 ENOPI857.12 0.57542.56790.771’0.000.560.570.53176COIIODITY Cli. CII. CDI. TILL 0!SIC ICC RuTS IATA32 PlAID! 107711 88 1098 146 12 ‘000 TOUR 198633 CIHAL CLIII 5111CR 89i 1098 062 2 ‘000 TOUR 19860718k STUCK 89b 1098 062 2 ‘000 TOUR 198634 PL6IUTS: SKLLD 01 OTRLUSE 90 1098 082 2 ‘000 7011K 191601111 lOTS 91 1098 082 9 ‘000 10118 198635 SIOLTEIIIC 92 1098 122 ‘000 10188 19861011KALGAIIIE: IICL, 108 GAL 93 1098 121 ‘000 70118 198636 KiLT: 11111! & 07111 94 1098 062 32 ‘000 10111 198637 CHIlI SOfl 811185: tIC & 108 CAL, 95 1111 171 111 1 ‘000 IICTOLIIII 1986ITTLI8 171 112 1Chill SO!! 811115: tIC & LOU CAL, 96 1111 111 111 2 ‘000 HCTOLIflI 1986CIII 171 112 2C1UTI SO!! HIltS: HG & 108 CAL, 91 1111 171 111 3 ‘000 HCIOLIIH 1986PlINY 171 112 3CHIlI SO!! 88188$: HG & 108 CAL, 98 1111 171 111 4 ‘000 IICIOLITLI 198638 CIII (irK) 11158!: 1170118 99 1121 173 522 ‘000 IlLS ALCUL 19868118: 81111811 100 1121 113 32 ‘000 LILS ALCIL 1q86177COKEOVITY TIDE! 1965 1986 CU. CIV. 1986 CDVIUEIE! 11161 11HZ QIT. VALUE III! VALUE($cDI EILL) (ScIl)32 PEAIUT IUTTE! 41.357 111.178 2688.2533 CE1EAL CLIII STILCE 70 20.4 291.4301111 5711GB 106 71 669.8134 PIAIUTS: SBLLD 0! 01111158 19.391 66.716 3440.5701111 VUTS 12.506 53.074 4243.8835 SEOLTHJIG 175.898 187.363 1065.18EALCAVIIE: IICL. LOU CAL 116.1 212.928 1209.1336 iLL?: BAlLET & 0111! 461.854 180.177 390.1237 ChIll SOFT DRIlLS: RIG & LOU CAL, 10810.921 956,695 18.49BIlLEDCHIlD SO?! lIlIES: lEG & LOU CAL, 6120.879 546.743 89.32CUDCR1171 SOFT lIlIES: LEG & LOU CAL, 961.779 10.546 73.35FREE!611178 SOFT DlIJES LEG A LOU CAL, 2941.296 109.947 37.3038 CIII (RYE) lUStY: EATURED 86393.457 497.148 5.76III: 1171111 10117.503 17.687 7.16178COftOUTY 1986 CDI. Dc CDT fOR! USATALUK OU’TPUT($coi TILL) PICK 1181416.771 1.000 1.19432 P8110! IUTTER 111.178 1.000 0.709 PIAJU! TUTTEL33 CUEIL 01111 STUCK 20.4 0.223 STUCK: CUll07811 STUCK 710.777 8111CR 0788191.4 1.000 1.26134 £111078: SILLI 01 07111188 p.116 0.550 111181801181 KUTS 53.074 0.450 01181 lUll119.79 1.000 0.88935 $101111110 187.363 0.468 SiOLTEUTORA1GA1III: ITCI. LOT CAL 212.928 0.532 TACilhil400.291 1.000 0.93336 TILT: TITLE! & GIll 180.177 1.000 1.453 TALl & TILT RTP1DC7S31 011178 SOFT 811115:180 & LOT CAL, 956.695 0.568 SOFT 81111$: CIIITD,TTTLDIT!LKDClii!) SO!! hutS: 180 & LOT CAL, 546.743 0.325 SOFT 111115: CTUTD,C1JDCII,CRlf!) SO?! buTts: lEG & LOT CAL, 70.546 0.042 SO?! 11111 £18815£1181CIIITD SOP! DullS: 180 1 LOT CAL, 109.947 0.065 SOY! DLIII POSYTIS1683.931 1.000 1.00138 CHJ (ITs) luSt!: TATUID 491.748 0.149 111518!118: TATUlU 17.687 0.111179C0OD1TY USA USA 1987 USA CONTfl 1987 USAP1000CT C01 URITS QUA1TY 1ATIO QUA8T1TCol UUTs32 FIAJUT IUTTH 2099! 44,46 US 661.9 0.453514 300.181433 CIfEAL Gull STItCH 20462 41 N US 1107 0.453514 3676.64307111 STARCH 20462 63 I US 611 0.453516 271.097534 F1AIUTS: SELLO OR OTEItISK 20680 13,33,53 I LIS 622.4 0.453514 282,261507811 JUTS 20680 15,17,35, ILlS 601.6 0.45351% 272.834437,55,5735 58011111kG 20791 13,15 1 US 6508.9 0.653514 2951.882NA1GnIJE: IICL. LOY CAL 20792 00 1 US 2247.6 0.453514 1019.31936 LILT: IARLET & OTHER 20830 00 I LI 6538.2 0.453514 2965.17031 C1IITO SOFT DRIllS: LEG & LOW CAL,20863 10,20,30 NILL CSES 1846.9 56.77517 104858.0*1! U EDCI.IJTD SOFT HIllS: LEG & LOW CAL,20864 10 IILL CSIS 2006.4 56.77537 113913.7CII,GRIJTO so,! DRIllS: LEG & LOk CAL,20865 02 I GALS 91.3 31.85011 3455.715Pill!CHJTD SOFT DRIllS: LEG & LOW CAL,20865 01 I GALS 311.1 37.85011 11775.1738 CIDI (LYE) THIS!!: NATU1ID 20853 11,13, I WI GALS 98.7 37.85011 3735.80616,18LVI: NATURED 20853 35 I B GALS 9 15.14004 136.2604180COJ0DITT 1987 1987 USA KST!D 1986 On USA UCUT TOTAL 1987USA TALU8 OUt! TALUU USA S8PHTS OUTPUT CU!T SHIPS($us UILL) ($us) (Sus SILL) PRC IRDI4439.3 1.000 1.21432 ?!LUUT !UTTKI 846.2 2818.96 836.10 1.000 0.109 846.233 CEHAL GRAIU STARCH 613.2 166.18 606.20 0.870 613.20711k STARCH 106.7 385.06 90.8 0.130 106.7497 1.00-0 1.22934 P811075: SHLLD OR OTHUISE 697.4 2470.71 691.60 0.378 697.4OTEKE JUTS 1256.4 4604.99 1136.1 0.622 1250.51827.7 1.000 0.82235 SIORTHIIIG 1886 638.91 1492.30 0.559 188JALGARIJE: IICL. LOU CAL 1167.5 1145.37 1178.80 0.441 1167.52671.1 1.000 0.973 3053.536 lILT: huh & 07511 528.8 178.34 551.40 1.000 1.453 528.831 CR1871 SOFT 811115: NC & LOU CAL, 6430.1 61.32 6316.10 0.463 6430.1CR117) SOFT 811115: NC & LOU CAL, 7178.8 63.02 6543.00 0.480 7178.8- CIII -Clii!) SOFT 811115: RIG & LOU CAL, 201 58.16 181.90 0.013 201P1181CR1170 SO!! 8lII1S RIG & LOW CAL, 648.8 55.10 587.50 0.043 648.813628.5 1.000 1.018 14458.731 CIII (Rn) VEISIT: IATURED 1132.4 303.12 1159.50 0.673 1132.2ill: 8110180 55.6 4.08 48.20 0.028 55.6181PUCE JJDEXCOEWOOITY 8888 IF 1986 1987 1986 P Oi:(Oc+Ou)/2 !VOPIDIFFELS FLO1IRDEX 18081 (SCOW) Pc/PuPRODUCT CODE1.000 1.20632 PEAWUT DOTTER OUT VALUE ES! 3789.81 0.71 1.000 0.70933 CHilL GRAIl STARCE 2046-301 87.1 84.7 238.29 1.22 0.546OTHR STALCE 2046-303 99.7 101.3 526.56 1.27 0.4541.000 1.24534 PEAJUTS: SKLLD OR 01818138 2065—853 109.5 119.3 3150.81 1.09 0.46607881 JUTS 2065—857 130.9 136.5 6135.68 0.69 0.5361.000 0.85535 SIO1TEJINC 106.9 106.6 890.21 1.20 0.513WALCALIH: IRCL. LOW CAL 105.7 104.3 1612.74 0.75 0.4871.000 0.95336 WALT: WALLET & 07881 2083-? 96 88.6 268.48 1.45 1.000 0.97037 CiflYD SOFT 8lIJES LEG & LOW CAL, 2086 114.6 117.2 83.31 1.06 0.516RIflEDCLII!) SO!! DRIllS: LEG & LOW CAL, 2086 114.6 117.2 85.62 1.04 0.402CUDCIII!) SOFT )lIJtS RIG & LOW CAL, 2087-3 102.4 106.5 77.10 0.94 0.028PHEXCIII!) SOFT DRIlLS: LEG & LOW CAL, 2087-3 102.4 106.5 73.61 0.51 0.0541.000 1.01038 CIII (IT!) 8813EV: RITULED WC!TD AVIG 105.1 107.3 414.88 0.01 0.711LII 1118111 lii! VALUE 1ST 5.52 1.30 0.072182COPOPITY CDI. CDI. CII. TEA! OFSIC ICC UlITSCII: EITU1ED 101 1121 173 22 ‘000 LTLS ALCEL 1986TD[A: RAT0LE 102 1121 113 42 ‘000 LTlS ALCEL 198639 ALE, LAGIk, STOUT, & ?GflEk:ITTLD 103 1131 172 11 ‘000 EKCTOLITEI 1986ALE, LACE!, STOUT, & POTEl:CIND 106 1131 172 12 ‘000 EECTOLITkE 1986AL!, LACH, STOUT, & ?OE.7!I:DRGRT 105 1131 172 13 ‘000 BECTOLITH 198640 11185: 8UD,S!L,G1P,817L8 & EU 106 1141 172 211 1 ‘000 UCTOLITU 1986172 211 2fliEs: II1SPflLIG,GIP 101 H41 112 221 ‘000 BECTOLITH 1986UJE COOLE!S 108 1141 172 51 ‘000 EECTOLIT1E 1986CIDU 109 1141 112 4 ‘000 HECTOLITRI 198641 TOIACCO: FLUE-GUilD, HOLE LEA! 110 1211 182 11 ‘000 G 1985TOIACCO: FLUE-CUEKO, LA!IIA 111 1211 182 21 ‘000 IC 198642 CICAIETTES: LECULU, FL?! 112 1221 183 312 EILLIOIS 1986CICA1ETTIS: IIICSIZE, FL!! 113 1221 183 322 iILLIOIS 198643 SIOILIC TOEACCO 114 1221 183 1 ‘000 IC 1986183lieu 1985 1986 Cli. CII. 1986 CII88!!!! III!! 11111 Q7Y. TALU! 8817 VALUE($cn !ILL) ($coi)Cli: !ATUUD 3792.687 27.559 7.27Volil: KATU!H 8926.123 61.455 6.8839 AL!, LACH, STOUT, & POLTP:ITTLD 17797.417 1819.574 102.24AL!, LACU, STOUT, & PO!TKE:CiiD 22e6.614 264.605 119.91AL!, LACE!, STOUT, & POLTEE:D1GBT 1958.42 139.755 71.3640 fliEs: !TLD,STL,C1P,!TTLI & 8LE 902.191 179.949 199.30tIlES: !1ID,S?ULIC,C 113.527 39.194 225.87fill COOLFES 169.761 26.258 154.68CII!! 82.117 13.714 165.5941 7OIACCO: ILUE-CUND, VIOL! LIA! 611232 110.5 103.1 2921.215 10.417 3.33TOUCCO: ILUE-CUtF0, LAlIlI 52082.36 300.921 5.7842 CICUETTES: UCULI1, FL!! 25466.797 509.367 0.02CICAIITTES: EIIGSH!, FL!! 28062.95 556.46 0.0243 SIOLIEC TOIACCO 7455.956 110.704 14.85184COKIODITY 1986 C8$. Oc CDJ VCBT USATALU! OUTPUT IA!!($coi KILL) PECK 1101CII: !AT8119 21.559 0.061 CIIT0DA: KITULED 61.455 0.092 YODIA4.449 1.000 0.04439 ALl, LAG!!, STOUT, & !O!TH:E!TLD 1819.574 0.818 1111: IOT!LEDAL!, LAG!!, STOUT, & POETU:CIKD 264.605 0.119 3111: CAI%KDALE, LACE!, STOUT, & POL!E!:DLCET 139.755 0.063 DIAUCKT IEEE2223.934 1.000 1.08640 flIES: !T18,STL,CEPIKTTLO & KLI 179.949 0.694 flIES: CLAP!flIES: !TL!,SP![LKG,G!P 39.194 0,151 fillS: IPF11Y!SCZFUI! COOLEES 26.258 0.101 COOLKESCH!L 13.714 0.053 Cmi259.115 1.000 1.60641 TOKACCO: PLUI—CEUD, IIOLK LU! 12.3 0.039 TOIACCO: 11919 81STh9 LUTOIACCO: FLUE-CU!!), LAIIIA 300.921 0.961 TOUCCO: STEKEED313.221 1.000 0.86842 CICfl!T!KS: UCULA!, FL!! 509.367 0.478 CICAUTTES: !LT!, <: 85 KCICALITTIS: KIIGSIZK, IL!! 556.46 0.522 CICALITT!S: ILfl,): 100 K1065.827 1.000 0.59543 S!OtIIC TOIACCO 110.704 1.000 1.067 SKOLlIG !OUCCO185COPODITY USA USA 1587 USA COIVII 1987 USA?IOIUC1 COlt VIlTS QVAITITT 8ATIO QUAITITTCDI UUTSCII: IATU8KI 20153 22 1 VI GALS 25.8 15.14004 390,6131You: IATUVED 20853 31 8 VI GALS 71 15.14004 1074.5435 AL!, uGH, S!OUT, & !0lT!I:!TTLD 20122 22,24,27, ‘000 IlLS 48065.9 1.19 51158.4228,32,34,37,38,41ALl, LAGH, STOUT, & ?OITH:CPD 20821 01,02,03 ‘000 iLLS 107255. 1.19 127681.8IL!, LAGI1, STOUT, & POLTKR:DLGVT 20823 64,65 ‘000 IlLS 20900.3 1.15 24966.5540 VIIES: ITLO,STL,GL!,ETTLD & ILl 20840 12,14,16 8 VI GALS 575.9 31.85011 21797.8811115: 8718,S?L[LNG,GLP 20840 31 8 Vi GALS 36.5 37.85011 1381.529UI! COOLRRS 20840 45 8 VI GALS 106 37.85011 4012.112CIII! 20556 11 1 GALS 14.2 37.85011 531.471641 TOIACCO: 1111—GUilD, 11018 LIA! 21411 00 8 183 45.8 453.5147 22585.03TOIACCO: !LUE—CUHD, LAIIIA 21412 11,15,27 8 LIS 895.7 453.5147 406213.142 CICAIITT!S: LIGULIL, !LTL 21110 13,16 IILLIOIS 355460CICALITIZS: IIIGSIZK, ItT! 21110 H IILLIOIS 25092643 58011kG TOIACCO 21310 08 8 LIS 28.5 453.5141 12925.17186COI0DITT 1987 1987 USA EST!ID 1986 Ou USA VCET TOTAL 1981USA VALUE Uffi! VALUE USA OUTPUT COTY SEIPS($us SILL) ($us) ($us 1LL) PLC IJOXGtE: RATUIID 155.2 3.97 156.50 0.091 155.2YOEfl: EATU1ED 341 3.17 359.50 0.209 3411723.7 1.000 0.064 168439 ALE, LACER, STOUT, & POLTH:!TTLD 4044.3 70.71 4028.20 0.324 4044.3ALE, LACER, STOUT, & POR!KR:CkkD 8212.2 64.32 1708.8 0.619 8212.2ALE, LAGER, STOUT, 6 PORTEL:DLCRT 122.1 28.92 714.90 0.057 722.112451.9 1.000 1.254 12978.640 flIES: ETLD,STL,GIP,ETTLD & ELI 1789.3 82.09 1781.80 0.801 1789.3fliEs: ETL8,S!ULIG,GLP 223.4 161.70 228.00 0.102 223.4filE COOLERS 384 95.71 185.10 0.083 384CIII! 26.3 48.93 29.50 0.013 26.32224.4 1.000 1.642 242341 TOEACCO: FLUE—CURED, IHOLE LEAF 103.2 4.57 102.20 0.048 103.2TOIACCO: PLUg—CURED, LAEIIA 1889.1 4.65 2033.90 0.952 1889.12136.1 1.000 0.865 1992,342 CIGARETTES: REGULAR, FL!! 8976.7 0.03 8152 0.567 8976.7CIGARETTES: [IIGSIZE, FL!! 6977.3 0.03 6229.90 0.433 6977.314381.9 1.000 0.601 1595443 SEOtIEC TOIACCO 135.5 10.48 134.20 1.000 1.067 135.5187PLICE JIDEXC0!!ODITT 0588 H 1986 1q87 1986 P 0i:(Oc+O)/2 !VOPIDIPPE1S flOII8EI 18881 ($cDI) ?c/?uP1ODUCT CODECII: !ATUIIE 2085—321 98.5 104 5.23 1.39 0.066TOILA: RATUND 2085—333 102.6 102.3 4.42 1.56 0.1511.000 0.05339 AL!, LACH, STOUT, & FO1TEL:ITTLD 2082-2 113.9 110.6 101.17 1.01 0.571AL!, LAGER, STOUT, & PORTU:CHD 2082-1 113.6 114.7 88.51 1.35 0.369ALE, LACfl, STOUT, A POlTfl:DRGET 2082—312 110.8 114.3 38.95 1.83 0.0601.000 1.16740 flIES: !TRD,STL,GRP,ETTLD & DLI 2084—1 99.3 101.9 111.14 1.79 0.748Juts: !T1D,SPULIC,CRP 2084—Sit 106.9 106.6 225.31 1.00 0.127III! COOLERS ICE!! ATRG 99.8 103.6 128.10 1.21 0.0922099-6 98.8 102.3 65.66 2.52 0.0331.000 1.62441 TOIACCO: FLUE—CURED, HOLE LEAF 2141-! 95.9 98.6 6.17 0.54 0.044TODACCO: FLUE-CURIE, LA!1IA 2141-2 90.9 90 6.53 0.89 0.9561.000 0,86642 CIGARETTES: REGULAR, FLTR 2111-116 117.3 129.7 0.03 0.63 0.522CIGALKT!ZS: [IEGSIZE, !LT1 2111—118 121.6 133.9 0.04 0.57 0.4781.000 0.59843 S!OKIIC TOIACCO 2131—111 122 127.7 13.92 1.01 1.000 1.067188Appendix G INDDTA Database189InputRelativeCn Cdn Cdn QuantityPu Real Real Real Index($Cdn/$Cdu) tr1s Cost Lbr Cost Engy Cost (torriqtist)I BEEF 0.972 3142.652 213.492 37.305 0.0952 P081 0.972 2177.446 286.522 25.641 0.1673 PRCSSD P0 0.970 770.489 143.853 8.858 0.1394 SAUSAGES 0.970 730.782 168.141 8.240 0.0755 IHO. TAL 0.964 65.977 29.332 0.786 0.1306 POULTRY 0.775 1028.256 310.961 23.004 0.1037 CNND YEGI 0.865 182.051 92.842 6.032 0.1418 CUD SBR 0.865 16.489 4.085 0.440 0.1319 JUICE 0.865 325.922 75.797 11.043 0.19010 JELLY & J 0.865 20.554 8.567 0.746 0.04711 P818 YEGE 0.765 454.188 116.468 20.358 0.20612 1LK 0.912 1689.972 422,708 44.821 0.09913 BUTTER 0.867 495.318 32.229 12.407 0.26314 CEEBS! 0.873 1061.690 157.777 26.669 0.08415 $IL PWDR 0.844 383.582 91.930 9.786 0.12016 ICE CRBA 0,847 290.345 107.099 6.027 0.09517 FLOUR 0,881 422.086 107.649 10.966 0.11418 CAL! IX 0,815 98.740 35.336 3.990 0.08819 !RLFST CE 0,828 112.249 78.496 3.923 0.06120 P110 0.810 1623.865 223.021 47.693 0.16721 EG & CT F 0.799 12.035 39.153 3.915 0.04422 HG! OIL 1.011 545.875 34.812 16.984 0.05923 BISCUIT 0.770 201.868 196,671 8.841 0.08824 BREAD 0.797 420.962 631.399 51.041 0.08325 SUGAR 0.855 636.922 73.138 20.105 0.14126 CBEVIXG C 0.822 69.174 79.320 1.817 0.22327 CORFECTIO 0.786 371.515 189.595 11.812 0.06028 COFFEE 0.754 372.179 101.997 6.015 0.06129 TEA30 PASTA 0.932 59.654 51.928 2.705 0.12431 CUP & PP 0.881 174.583 149.905 14.658 0.10832 PEANUT EU 0.858 93.211 10.239 4.770 0.15033 STARCE 0.860 41.634 13.477 2.334 0.07734 PELIUTS 0.862 79.599 17.157 4.067 0.05435 SNETNIG & 0.860 176.579 20.158 9.026 0,03836 8ALT37 SOFT 0818 0.884 1007.603 395.471 29.223 0.06938 BEER 0.784 586.660 613.973 45.135 0.11139 VINE 0.815 98.517 46.497 2.910 0.04640 SELIG TOE 0.968 28.432 17.125 0.441 0.082average190: - CABADIAN DATA-: COSTESTS PURL & COST TOTAL VALUE RUMBER VACES & REAL REALELCIECTY MTRLS MilLS SBPMRIS BIPS SALARIES CAKADN CA8ADM(S MILL) (S MILL) (5 MILL) (S MILL) (S MILL) OUTPUT MTRLS1 BEEP 165 37 3196 3233 3730 8610 208 3753 31432 PORE 101 26 2197 2222 2600 10103 278 2711 21773 PRCSSD P0 67 9 759 768 1030 5419 140 1023 7104 SAUSACES 116 8 706 714 1010 6166 163 1088 7315 INED. TAL 32 1 67 68 130 810 28 124 666 POULTRY 101 23 1201 1226 1666 11515 241 1323 10281 CNRD VEGE 47 6 195 201 480 4114 80 363 1828 CNND MSBR 5 0 14 15 23 148 4 26 169 JUICE 37 11 356 367 470 2101 66 550 32610 JELLY & J 16 1 24 25 53 227 7 42 2111 PRIR VEGE 37 20 321 347 619 5049 89 746 45412 MJL[ 160 45 2033 2078 2931 13647 386 2044 169013 BUTTER 40 12 624 637 650 947 28 574 49514 CHEESE 66 27 1342 138 1860 5910 138 1430 106215 MILl PVDR 21 10 492 502 660 2266 78 607 38416 ICE CREAM 41 6 303 309 570 3431 91 451 29017 PLOUR 40 11 689 699 861 2932 95 604 42218 CAIE MIX 11 4 106 110 180 1270 29 238 9919 EREPST CE 8 4 105 108 350 1812 65 552 11220 PLED 442 48 1764 1811 2200 7874 181 2355 162421 DC & CT P 90 4 145 149 340 1078 32 338 12922 TEGE OIL 11 17 636 653 732 1052 35 696 54623 BISCUIT 34 9 233 242 520 6268 151 472 20224 BREAD 479 51 653 104 1552 22000 503 1816 42125 SUGAR 8 20 271 291 466 1915 63 713 63126 CHVING C 6 2 64 66 226 2113 65 216 6927 CONPECTIO 101 12 362 374 760 6795 149 812 37228 COFFEE 21 6 538 544 820 2535 77 743 37229 TEA30 PASTA 33 3 84 81 153 1761 48 159 6031 CHIP & PP 24 15 116 191 507 5226 132 420 11532 PEANUT RU 9 5 103 108 111 294 9 151 9333 STARCE 7 2 51 53 91 281 12 73 4234 PEANUTS 18 4 88 92 119 597 15 140 8035 SBRTMNG & 25 9 195 204 240 518 11 252 17736 MALT31 SOFT OlIN 192 29 1062 1091 1789 12350 350 1112 100838 BEER 43 45 655 700 2184 13614 481 1872 58739 VINE 41 3 133 136 262 1407 38 161 9940 SMLMG TOE 1 0 26 27 120 486 1? 112 28a,erage 68 14 553 567 836 4402 116 7 509191RELATIVE RELATIVE C00DITTC0E0DITOUTPUT MTRLS SUIPENTS SEIPRTSPRICE PRICE CAMADA US1 BEEP 0.994 1.017 2834.896 204052 P011 0.959 1,009 2432.032 8180.93 PRCSSD P0 1.007 0.985 652.326 4485.54 SAUSAGES 0.928 0.966 603.97 7705.95 1118. TAL 1.046 1.021 126.351 6206 P0ULTR 1,259 1.168 1430.623 7850.77 GIlD VEGE 1.322 1.069 142.32 1080.6a GElD ESER 0.871 0.860 22.794 123.39 JUICE 0.854 1.093 342.417 1300.710 JELL! & J 1.265 1.171 81.159 522.311 P111 VEGE 0.911 0.119 328.313 2166,212 IILL 1.434 1.203 2310.991 10319.413 BUTTER 1.133 1.260 597.675 1137.514 CEEBSE 1.301 1.264 1564.811 8517.815 EILI PVDL 1.087 1.284 501.469 1573.716 ICE CREAE 1.263 1.044 433.169 2772.817 FLOUR 1.436 1.631 748.165 2969.218 CII! BIX 0.755 1.077 75.344 88.819 BRKFST CE 0.634 0.931 379.141 3530.820 FEED 0.934 1.086 1132.094 757321 DC & CT F 1.005 1.122 365.154 4095.722 YEGE 011 1.052 1.166 219.323 6433.123 BISCUIT 1.103 1.153 503.21 3926.924 BREAD 0.855 1.552 945.15 6306.225 SUGAR 0.603 0.425 458.271 4172.521 CEEVIEG C 1.046 0.928 149.72 756.927 COBPECTIO 0.936 0.974 805.267 5860.32$ COFFEE 1.104 1.445 480 3949.429 TEA30 PASTA 0.959 1.410 200.472 808.131 ClIP & PP 1.206 1.009 415.905 180132 PEANUT EU 0.709 1.107 111.178 813.633 STARCE 1.245 1.213 91.461 657,634 PEANUTS 0.851 1.106 66.716 252.835 SilTING & 0,953 1.106 400.291 264631 lILT37 SOFT DLII 1.01 1.054 1683.931 11900.538 BEER 1.167 1.117 2223.934 11311.239 VINE 1.624 1.351 259.115 2079.440 SELEG lOB 1.067 0.929 110.704 131.4average 1.044 1.101 677 4066192-US DATA (in $us)-USA SIC TOTAL TOTAL TOTAL TOTAL TOTALWU!BER VALUE VALUE WUBKR WAGE &ESTS. TILS SEIPINTS EMPLOYEE SALARIES(000)I BEEF 20111+112+113 887 24556 28380 60.9 10692 PORE 20114 306 9877 11903 41.5 8333 PRCSSD P020116,36 324 4268 5485 27.2 5104 SAUSAGES 20117+13B+131+138 1225 7588 10938 58.0 11165 1888. TAL20771 159 413 752 4.9 1176 POULTRY 2016 325 8021 11264 112.6 13667 CUD VEG820332 237 1151 2149 21.0 2658 CUD 8SBR20333 17 104 156 0.8 129 JUICE 2033A 84 1405 2221 1.4 14810 JELLY & J20338 41 316 718 3.4 1111 PRZW Y8GE20372 152 1543 3258 35.7 51212 NILE 2026-20263 1103 13907 19031 69,4 155413 BUTTER 2021 69 1430 1531 1.7 4014 CHEESE 2022+20263 106 9909 12335 34.3 63915 NILI PWDR2O23S+20236 68 2586 3784 9.5 26016 ICE CREA2O24+2O238 572 2610 3751 19,2 40511 FLOUR 20411 289 3021 3993 10.1 27518 CAL! NIX 2045 113 952 1714 7.4 16719 BRIFST CE2043 53 1681 6168 16.4 58520 PEED 2048 1700 7536 9674 30.0 59621 DC & CT P2047 257 2361 5418 16.2 41322 FEC! OIL 2015 107 7105 7816 1.0 16123 BISCUIT 2052 316 2203 6177 45.0 102024 BREAD 2051 2345 5566 15148 153,4 331125 SUGAR 2062+2063 66 3209 4363 13.4 36626 CIIVING G2067 13 354 1082 5.4 12627 CONFECTIO2O65+2066 928 5556 10891 63.7 126828 COFFEE 2095 143 5140 7544 11.5 30729 TEA30 PASTA 2098 255 494 1200 7.2 14031 CHIP & PP2096 340 1676 4614 30.0 55232 PEANUT 8U2099F 23 483 176 1,5 3433 STARCH 20462 24 442 142 2.9 9134 PEA8UTS 2068 90 1176 1915 8.6 16135 58178KG &2019 103 3631 4951 10.4 26336 NALT37 SOFT DR182086 1280 12483 20681 102.0 234838 8111 2082 129 6503 12678 34.0 125539 flU 2084 480 1896 3163 13.1 31840 381KG 7082131 29 328 1062 3.3 78average 387 4108 6279 28 5731931.3894 RPFUEI, 1REAL REAL TOTAL TOTAL IV iv ivEN? FUEL PUEL COST COST SHAll SHARE SHARECANADA CANADA US CANADA US FUEL NTRLS LABOUR1 EEEF 210 37 392 3441 35603 0.011 0.938 0.0512 PORK 282 26 156 2501 14880 0.010 0.895 0.0953 PRCSSD P0 141 9 66 907 6639 0.010 0.860 0.1304 SAUSAGES 165 8 115 877 12094 0.009 0.833 0.1575 INED. TAL 29 1 7 96 735 0.009 0.735 0.2576 POULTR! 194 23 272 1465 13051 0.018 0.827 0.1557 CUD VEGE 72 6 50 281 1967 0.023 0.740 0.2378 CUD NSBR 3 0 4 18 161 0.023 0.829 0,1489 JUICE 59 11 62 433 2151 0.021 0.850 0.12310 JELL! & J 7 1 18 32 621 0.026 0.780 0.19411 FRZN VEGE 101 20 124 436 2856 0.045 0.728 0.22712 NILK 425 45 580 2463 21482 0.023 0.849 0.12913 EUTTER 31 12 46 665 2043 0.021 0.945 0.03514 CHEESE 153 27 320 1506 14656 0.020 0.904 0.01615 NILE PDR 86 10 85 580 3954 0.019 0.868 0.11316 ICE CREAN 101 6 70 400 4190 0.016 0.804 0.18117 FLOUR 111 11 101 794 4579 0.018 0.881 0.10118 CAKE NIX 40 4 40 139 1554 0.027 0.195 0.17819 EREPS! CE 90 4 61 173 3149 0.021 0.663 0.31620 PEED 217 48 272 1992 11298 0.024 0.894 0.08221 DC & CT F 38 4 88 180 3854 0.022 0.815 0.16222 ?EGE OIL 35 17 265 689 10103 0.025 0.938 0.03123 BISCUIT 197 9 161 393 4417 0.029 0.620 0.35124 BREAD 612 51 592 1208 12411 0.045 0.558 0.39725 SUGAR 73 20 158 353 4967 0.044 0.816 0.14026 CHEflKG C 68 2 13 131 667 0.016 0.604 0.31921 CONFECTIO 188 12 220 523 9482 0.023 0.742 0.23528 COFFEE 94 6 85 621 7568 0.010 0.899 0.09029 TEA30 PASTA 47 3 28 135 880 0.026 0.685 0.28931 CHIP & PP 134 15 224 323 3096 0.059 0.613 0.32832 PEANUT EU 9 5 33 117 718 0.043 0.887 0.07033 STARCH 12 2 33 64 140 0.040 0.785 0.17534 PEANUTS 16 4 80 107 1858 0.041 0.830 0.12935 31118KG & 18 9 247 222 5410 0.043 0.884 0.07336 KILT37 SOFT DRIN 395 29 414 1441 20606 0.022 0.718 0.20038 JEER 698 45 425 1182 10778 0.039 0.677 0.28539 WINE 41 3 79 174 3077 0.021 0.798 0.18140 SKING 108 16 0 6 43 564 0.010 0,703 0.287average 133 14 152 683 6505 0.025 0.795 0.180194X I C:CcfCu I/I C/X i/X GilI IRE! 0.095 0.095 0.097 0.996 1.019 1.004 1.0142 PURL 0.164 0.167 0.168 0.979 1.026 1.021 1.0053 PRCSSD P0 0.134 0.139 0.131 0.964 1.022 1.038 0.9854 SAUSAGES 0.071 0.075 0.073 0.949 1.020 1.053 0.9685 lIED. TAL 0.119 0.130 0.131 0.916 1.103 1.092 1.0106 POULTR! 0.085 0.103 0.112 0.821 1.328 1.218 1.0907 GIlD URGE 0.121 0.139 0.143 0.873 1.177 1.145 1.0278 GIlD ISER 0.122 0,129 0.113 0.945 0.927 1.058 0.8169 JUICE 0.179 0.188 0.201 0.950 1.124 1.053 1.06710 JELLT & J 0.043 0.058 0.052 0.741 1.207 1.349 0,89511 PRZN URGE 0.166 0.206 0.153 0.806 0.920 1.241 0.74.212 KILL 0.077 0,099 0.115 0.781 1.483 1.281 1.15813 EUTTER 0.270 0.263 0.325 1.026 1.206 0.975 1.23714 CEEESE 0.083 0.084 0.103 0.994 1.231 1.006 1.22415 KILl PVDR 0.115 0,120 0.147 0.955 1.275 1.047 1.21716 ICE CREAK 0.097 0.095 0.095 1.029 0.979 0.972 1.00817 FLOUR 0.109 0.114 0.173 0.955 1.593 1.047 1.52218 GALE III 0.100 0.087 0.090 1.151 0.894 0.869 1.02919 IVIES! CE 0.065 0.061 0.055 1.068 0.846 0.937 0.90320 FEED 0.115 0.172 0.176 1.014 1.010 0.986 1.02421 DC & CT P 0.044 0.044 0.047 1.010 1.053 0.990 1.06422 TIC! OIL 0,064 0.059 0.068 1.086 1.064 0.921 1.15523 IISCUIT 0.055 0.088 0.088 0.624 1.597 1.603 0.99624 IREAD 0.086 0.082 0.097 1.050 1.127 0.953 1.18325 SUGAR 0.134 0.146 0.071 0.919 0.530 1.089 0.48726 CREVIKG C 0.144 0.221 0.197 0.650 1.369 1.539 0.88927 CONFECTIO 0.053 0.060 0.055 0.895 1.035 1.118 0.92628 COPE!! 0.074 0.060 0.082 1.225 1,107 0.816 1.35729 lEA30 PLSTA 0,096 0.124 0.154 0.773 1.606 1.294 1.24131 GRIP & PP 0.061 0.108 0.104 0.562 1.716 1.779 0.96432 PEANUT EU 0.145 0.151 0.163 0.964 1.121 1.037 1.08133 S!AECR 0.076 0.076 0.087 0.993 1.149 1.001 1.14134 PEANUTS 0.051 0.054 0.058 0.938 1.136 1.066 1,06635 SERTING & 0.037 0,038 0.041 0.965 1.119 1.037 1.08036 KALT37 SOFT DVII 0.062 0.069 0.070 0.897 1.132 1.114 1.01638 lEER 0.099 0.109 0.110 0.905 1.111 1.105 1.005391118 0.037 0,046 0.057 0.801 1.529 1.249 1.22440 SILIG TOE 0.076 0.081 0.071 0.940 1.010 1.063 0.950a,erage 0.100 0.109 0.113 0.924 1.155 1.110 1.048

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