>< - ~«mren‘al. . THESIS "lllllllllllllllllll Willi if 31293 00854 0282 LIBRARY 4 {3.232533 State ’m; entity ‘ m This is to certify that the dissertation entitled PURCHASING'S IMPACT: AN INPUT-OUTPUT ANALYSIS OF INTERINDUSTRY ACTIVITY CREATED BY CHANGES IN STEEL PURCHASES presented by Robert F. Reck has been accepted towards fulfillment of the requirements for Ph.D. Management degree in Major professor/ Q/ / 7527/4 / JOhn.H. Hoagland Date August 10, 1984 MSU i: an Affirmative Action/Equal Opportunity Institution 0-12771 , MSU RETURNING MATERIALS: Place in book drop to LIBRARIES remove this checkout from .—:—. your record. FINES will be charged if book is returned after the date stamped below. LIVER-v PURCHASING'S IMPACT: AN INPUT-OUTPUT ANALYSIS OF INTERINDUSTRY ACTIVITY CREATED BY CHANGES IN STEEL PURCHASES By Robert F. Reck A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Management @Copyright by ROBERT FRED RECK l984 ABSTRACT PURCHASING'S IMPACT: AN INPUT-OUTPUT ANALYSIS OF INTERINDUSTRY ACTIVITY CREATED BY CHANGES IN STEEL PURCHASES By Robert F. Reck This dissertation examines several characteristics of interindustry purchasing activity that result from major shifts in steel purchases by steel-consuming industries. Although the contribution of these fluctuations to business instability in the United States is generally recognized, the extent of their impact is not. The research focuses on measuring and analyzing the magnitude and dispersion of interindustry purchasing‘activity that is generated by actual or anticipated changes in steel purchases, in order to deter- mine its impact upon the U.S. business system. Fluctuations in steel purchases by steel-consuming industries can be caused by a strike or threat of strike endangering steel output. In anticipation of a steel strike, steel purchasers are normally forced to accumulate strike- hedge inventories, in order to protect production schedules. This is generally accomplished by expanding steel purchasing activity before the strike deadline. The change in steel Robert F. Reck purchases introduced to this study are similar to that observed prior to steel contract terminations. The 1972 Input-Output Matrices of the U.S. business system are used in the development of this study's data. These matrices are designed to study the diverse interde- pendencies of producing and consuming units in our economy. Modifications are introduced to these matrices in order that they may closely approximate material purchase/sales trans- actions at purchase prices. The study's results indicate that a $2.4 billion surge in one month's steel purchases can generate $2.6 billion of interindustry purchasing activity, affecting 389 industries in the U.S. business system. Stated more simply, each dollar change in steel purchases can result in a $l.07 change in other purchasing activity within the business system. Thus, the 13511 impact of fluctuations in steel purchases by steel- consuming industries upon our business system can be greater than the initiating change. It is important to emphasize that the estimates of interindustry activity presented in this study are probably understated. This results from input-output conventions, scope limitations, and model modifications. The study's results lead to the following conclusions: (l) major fluctuations in steel purchases have a significant impact on the general level of business activity; (2) the effects of major fluctuations in steel purchases are signi- ficantly dispersed throughout the business system; and Robert F. Reck (3) the impact of major fluctuations in steel purchases is of sufficient magnitude and dispersion to play an active role in general business instability. DEDICATION To Maryalice, for those late nights, forgotten weekends, and lost vacations. ACKNOWLEDGMENTS Although it will never be possible to thank all of the peeple who aided in the successful completion of this dissertation, I would like to mention several in particular. I am deeply indebted to my dissertation chairman, Dr. John H. Hoagland whose patience, guidance, and construc- tive criticism were instrumental in bringing this study to a close. Additionally, I would like to thank Dr. Hoagland for locating and obtaining financial assistance. I also wish to express my sincere thanks to the other members of my dissertation committee, Dr. Robert M. Monczka and Dr. Phillip Carter for their guidance, constructive criticism and encouragement. Additionally, I would like to thank Dr. Monczka for his assistance in obtaining financial aid. A sincere note of gratitude goes to the National Association of Purchasing Management for their support of this study through a Doctoral Research Grant. I would like to thank my colleagues at Arizona State University and especially Dr. Harold Fearon, Chairman of the Management Department, for their unselfish help in providing me with the time to finish this research. iv A very special note of recognition is appropriate for Dr. Ross Reck, Mr. Steve Leh, and Dr. Brian Long for their continued help and encouragement during this research project. I would like to thank my parents, Traugott and Elsie Reck for their encouragement and support during my doctoral studies. Finally, I would like to thank Maryalice for her unselfish assistance and understanding which helped bring this dissertation to a close. TABLE OF CONTENTS LIST OF TABLES . LIST OF FIGURES CHAPTER I. INTRODUCTION Importance of Study Hypotheses . . . . Scope of Study . . . General Limitations of Study . Organization of Study II. LITERATURE REVIEW Purchasing Decisions Business Factors . Supplier Performance Labor Strikes War . . Availability of Merchandise Price Movements . . . Sales Orders . . Acceleration Principle . Risk of Obsolescence . Production-to-Order Production-to-Stock Steel and the Business System Summary . . . . . III. STEEL Steelmaking . . . The Steel Industry . Inputs and Outputs of the Steel Industry : Inputs Outputs . . The United Steelworkers of America . Strikes and Collective Bargaining Summary . . . . . . . . . vi Page ix —l dooommummndom m manna N at 28 CHAPTER IV. RESEARCH METHODOLOGY The Magnitude and Dispersion of Interindustry Purchasing Activity 1972 Input- -Output Study . . The Use of Commodities by Industries The Make of Commodities by Industries Modification of l972 Input-Output Size of Fluctuation in Steel Purchases Mathematical Derivation of Interindustry Purchases . . Reflective Measure of Purchasing Activity Manufacturers' New Orders Series Simulated New Orders Series Evaluation of Data Summary V. ANALYSIS OF RESULTS Correlation Analysis Purchasing Waves . . . . . . . Steel -> Transportation -> Petroleum gefining-—>. Crude Petroleum and Natural as . Magnitude and Dispersion of Interindustry Activity . . . . . . . . Total Business System Industrial Sectors Individual Industries Summary VI. SUMMARY AND CONCLUSIONS Conclusions Conclusion I Conclusion II Conclusion III APPENDIX A. NORKSHEET: STEEL MILL INDUSTRY PURCHASES FOR 1972 . . . . . . . . . . . . . . . . . B. THE PERCENTAGE BREAKDOWN OF TOTAL MATERIAL INPUTS INTO THE STEEL INDUSTRY . . C. INDUSTRY CLASSIFICATION OF THE 1972 INPUT- OUTPUT MATRIX . . . . . . . vii Page 90 92 94 APPENDIX D. INTERINDUSTRY PURCHASING ACTIVITY CREATED BY A 100 PERCENT SURGE IN STEEL PURCHASES . E. STEEL MILL -> TRANSPORTATION -> PETROLEUM REFINPNG-—> CRUDE PETROLEUM AND NATURAL GAS CHAIN . F. TOTAL NEW INDUSTRIAL ORDERS ACCUMULATED AT EACH PURCHASING STAGE BIBLIOGRAPHY viii Page 98 113 115 117 TABLE LIST OF TABLES Description of the Steel Industry . The Intra- industry Inputs of the Steel Industry . . . . . A Delineation of Aggregate Commodity/ Industry Groups for this Study . Correlation Analysis of 1972 Simulated New Orders and the l958- l959 Manufacturers' New Orders Series . . . . . . . . . . . Comparison of the Percentage Increase in l972 Simulated New Orders with the Percentage Increase in Manufacturers' New Orders for February, l959 Interindustry Activity Created by a Change in Steel Mill Orders . . . Top Dollar Changes in Volume of Interindustry Activity Created by a Surge in Steel Purchases, by Industry . Top Percentage Changes in Volume of Inter- industry Activity Created by a Surge in Steel Purchases, by Industries . . ix Page 34 4O 59 68 7O 79 81 84 FIGURE 1 2 3 LIST OF FIGURES Steel Production Processes A Description of the Steel Industry A Percentage Breakdown of Total Material Inputs Into the Steel Industry . Percentage of Steel Shipments, by Product Group . . . . . Percentage of Steel Shipments to Market Group . . . . . . . . . . . . . A Model of The Use of Commodities by Industries Matrix . . A Model of The Make of Commodities by Industries Matrix . Producers' Price Versus Purchasers? Price A Steel Supply Chain . Total New Industrial Orders Accumulated at Each Purchasing Stage Page 29 32 37 43 45 52 54 57 73 77 CHAPTER I INTRODUCTION The purpose of this dissertation is to examine several characteristics of interindustry purchasing activity that result from major shifts in the steel purchases by steel- consuming industries. Although the contribution of these fluctuations to business instability in the United States is generally recognized, the extent of their impact is not. For example, a comprehensive study of the steel industry concluded that, "Substantial fluctuations in steel must be. . . a major factor in the transmission of cyclical shocks throughout the business system."1 Accordingly, this research will focus on measuring and analyzing the magnitude and dis- persion of interindustry purchasing activity that is stimu- lated by actual or anticipated changes in steel purchases; then, the effects of purchasing shifts on general levels of business activity will be evaluated. Importance of Study In the past, certain business authorities attempted to minimize the impact on general business activity of major fluctuations in the steel purchases of steel-consuming 1Philip A. Klein. and Richard L. Gordon, The Steel Industry and U.S. Business Cycles, (University Park: The Pennsylvania State University, l97l), p. 94. industries. For example, Henry w. Broude stated, "There appears to be considerable doubt as to the usefulness of steel series as indicators or forecasters of levels of busi- "2 ness activity. Similarly, other authorities have at- tempted to depreciate the importance of such fluctuations, particularly those caused by steel strikes. Former Secre- tary of Labor, John P. Mitchell, for example, stated that. "The long run economic effects of past steel strikes have "3 left no permanent scars on our economy. He further con- cluded: The consequences of the steel bargain have their effects primarily on the parties, and the strikes which from time to time may accompany the negotiation do not warrant the public consterna- tion and outcry that have occurred in the past. In contrast, other business authorities conclude that major fluctuations in steel purchases are of considerable importance to the general level of business activity. For example, Philip A. Klein and Richard L. Gordon stated, steel can generate economic instability that might be a contributing factor in initiating economic declines."5 2Henry N. Broude, Steel Decisions and the National Economy, (New Haven: Yale University Press, 1963), p. 27. 3E. Robert Livernash (ed.), Collective Bargaining in the Basic Steel Industry; A Study of the Public Interest and the Role of Government Twashington: U.S. Government Printing Office, l96l), p. v. 41bid. 5Klein and Gordon, The Steel Industry and U.S. Business Cycles, p. 48. John H. Hoagland stated more definitively that the major fluctuations in steel purchases that are caused by strikes have determined the timing, magnitude, and duration of many business cycles.6 He reasoned: When analyzing the importance of steel strikes or similar events, researchers also need to consider not only the gigantic fluctua- tions which occur in steel inventories but the corollary fluctuations which occur in many other activities . . . there are inventory changes in many products and services that go into the manufacture of steel, changes in pro- ducts made of steel, plus changes in many raw materials and products derived from steel and coke production. Also, there is the impact that these fluctuations have on many business indices and the attitudes of many people, as well as the acceleration and deceleration caused by all these changes. This study seeks to end some of this controversy by examining the magnitude and dispersion of changes in inter- industry purchasing that are created by major shifts in steel purchases. The study thereby seeks to determine the extent of steel's role in generating business fluctuations. Hypotheses To guide this investigation, two hypotheses regarding the character of interindustry purchases were established. The basis for these hypotheses will be discussed in more detail in Chapter II. 6John H. Hoagland, “Strikes, Politics and Business Cycles," paper presented at the annual meeting of the Ameri- can Statistical Association, Chicago, Illinois, December, l964. p. l. 71bid.. p. 4. Hypothesis 1: The effects of major fluctuations in steel purchases are of a magnitude to significantly impact the general level of business activity. Hypothesis II: The effects of major fluctuations in steel purchases are significantly dis- persed throughout the business system. Whereas the first hypothesis concerns the amount of interindustry purchasing activity that results directly or indirectly from fluctuations in steel purchases, the second focuses upon the extent to which such imbalances are trans- mitted across the business system. Collectively, these hypotheses focus on the question of whether major shifts in steel purchases can generate a significant and broad-based level of general business activity. Scope of Study The magnitude of fluctuations in each industry's pur- chases is influenced by numerous business factors, which include inventories, investments, consumer spending, etc. Any combination of these factors may be relevant to a firm's purchasing decision in agiven situation. To study the effects of all combinations for each industry throughout the business system is virtually impossible because of the multi- tude of widely varying circumstances facing each. There- fore, it becomes necessary to restrict the scape of this study in order to keep it within manageable limits. Accordingly, the following restrictions are imposed on this study: 1. Lead times are assumed to remain unchanged in order to minimize the false levels of demand that may be created as lead times change. Thus, their effects on the magnitude and dispersion of interindustry purchases are ignored. 2. Prices are assumed to remain unchanged in order to minimize the false levels of demand that may be created by price changes. Thus, their effects on the magnitude and dispersion of interindustry purchases are ig- nored. 3“ All inventories are assumed to remain unchanged in order to minimize the effects of the acceleration principle. This principle suggests that inventory levels change in the same direction, but at a faster rate, than sales, thus influencing the magnitude and dispersion of interindustry purchases. 4. The levels of imports and exports of all goods are assumed to remain unchanged in order to focus the measurement of the magnitude and dispersion of inter- industry purchases on the U.S. business system. These restrictions on the scope of the study are of major importance. They may result in significant under- statement of the magnitude and dispersion of changes in interindustry purchasing activity created by major shifts in steel purchases by steel-consuming industries. The necessity of these restrictions will be discussed in more detail in Chapter II. General Limitations of Study Due to the research methodology selected, certain limitations exist with respect to the generalization of this study's results. First, purchases are examined in terms of purchasing industries, with no consideration given to the problems incurred in the purchase of specific products. The term "purchased commodity," as used in this study, represents an aggregate “mix" of the varied needs of numerous purchasers in each industry. Therefore, the generalization in this study may not fully represent the situation with respect to a specific purchaser. Second, the examination of purchases is made in terms of supplying industries, with no consideration given to commercial aspects of individual suppliers, such as: price changes, lead times, and quality levels. In this study, supplying industries represent an "average" of the diverse characteristics of individual suppliers selling each commod- ity. Therefore, the generalization in this study may not fully represent the situation with respect to a given supplier. Organization of the Study Chapter 11 presents the "Literature Review," which describes the elements of purchasing decisions and outlines business factors and events that may cause fluctuations in industrial purchasing behavior. Additionally, the chapter examines studies that analyzed the relationships between steel purchase activity and general business conditions. Chapter III, entitled "Steel," describes the steel- making process, the steel industry, and the United Steel- workers' Union. This chapter seeks to identify some of the material factors that suggest steel's role in the business system. Chapter IV, entitled "Research Methodology," describes the development of the study's data and their analysis. The chapter also details some of the more general data con- versions. Chapter V, entitled "Analysis of Results," presents an analysis of data calculated for this study to determine their validity as reflective measures of interindustrial purchasing activity initiated by fluctuations in steel purchases. Additionally, this chapter illustrates, with a select group of industries, the transmission of fluctuations in purchasing activity across the business system. Finally, estimates of the magnitude and dispersion of interindustry purchases that result from fluctuations in the steel pur- chasing activity of steel consumers are examined. Chapter VI, "Summary and Conclusions," summarizes the findings of this study and presents conclusions that are related to the hypotheses. CHAPTER II LITERATURE REVIEW In order to provide a theoretical base for this study, an examination of previous literature is presented. This investigation stresses salient concepts in the evolution of theories concerning fluctuations in industrial pur- chases, particularly those caused by steel strikes or threats of strike. To facilitate this review, the chapter is divided into three sections: (1) the elements of pur- chasing decisions, (2) key business factors and events that may cause these decisions to fluctuate, and (3) the rela- tionship between steel purchasing activity and general business conditions. Purchasing Decisions The U.S. economy comprises numerous specialized indus- tries that continually interact to transform raw materials, parts, and components into finished goods and services. As these materials, parts, and components flow from industry to industry, the activities of mines, plants, transportation companies and utilities are integrated into a single busi- ness system. The sheer volume of interindustry trade sug- gests a high degree of interdependency among specialized business units. Consequently, the activities of each 8 industry can be directly or indirectly influenced by the actions of numerous other industries. If businesses are to survive in such an environment, they must continuously ad- just to the changing needs of other industries upon which they are dependent.1 These ongoing adjustments provide a dynamic character to the business system. The flow of interindustry trade is generally coordi- nated through purchase/sales relationships. Typically, such relationships are established by decisions to purchase goods and/or services. Consequently, changes in purchasing decisions can disrupt the balance of purchase/sales rela- tionships and, thus, cause businesses to adjust. If the initial imbalance is of sufficient magnitude, the adjust- ment process can impact purchasing decisions throughout the business system. This sequential relationship leads one national business authority to conclude, "When purchasing decisions. . . fluctuate in an important industry, or company. . . the impact on the nation's economy can be very great."2 Hence, comprehension of the purchasing decision should lead to an improved understanding of general business instability. 1Leverett S. Lyon, Hand-to-Mouth_Buyin9. (Baltimore: The Lord Baltimore Press, 1929). p. 15. 2John H. Hoagland, "Purchasing and Inventory Forecast- ing," paper presented to the Business and Economic Statisti- cal Section of the American Statistical Association, Stanford University, August, l960, p. 12. 10 Purchasing decisions are partially based on expecta- 3 In formulating tions of future business conditions. expectations, purchasing executives typically identify and assess future business factors and events that may impact their companies' production schedules and/or profit margins; these factors include labor strikes, material shortages, and rising material prices. Once identified, the potential consequences of these factors and events are generally integrated with the purchasers' confidence in their assessments. As their confidence level rises, the executivesl purchases also increase in magnitude and expand to a wider variety of materials.4 The resulting observation is that future business factors and events may impact current purchasing decisions, disrupting purchase/sales relationships and, thus, initiating an adjustment process. Business Factors and Events- As discussed above, purchasers' expectations of future business conditions are partially based on factors and events that can significantly alter production schedules and/or profit margins. The purpose of this section is to review the relevant literature concerning some of these 3Ruth P. Mack, "Business Expectations and the Buying of Materials," in Expectations, Uncertainty, and Business Behavior, ed. Mary Jean Bowman (New York: Social Science Research Council, 1958), p. ll3. 4mm, p. 115. ll factors and events in order to identify their salient characteristics. To facilitate this review, the business factors and events are divided into three categories: (l) supplier performance, (2) price movements, and (3) sales orders. Supplier Performance Supplier performance refers to the speed and dependa- bility with which suppliers deliver quality materials to their customers. Changes in actual or anticipated supplier performance can alter purchasers' expectations of the future availability of materials necessary to satisfy their pro- duction schedules. In an attempt to protect these schedules, purchasers typically change their buying behavior. Professor John Hoagland observed, "Purchase. . . decisions are par- tially based upon actual or anticipated vendor performance."5 He reasoned that if purchasing executives perceive that supplier performance is deteriorating, they will lengthen forward purchase commitments to ensure material flow into their production systems. This behavior was also observed by Ruth Mack in her study of retail and durable goods industries: 5Hoagland, Purchasing and Inventory Forecasting, p. l2. 12 . the response to the expectations that delivery periods will lengthen is very likely to be not only an increase in advance orders but also an increase in purchases for immediate delivery6 and, consequently, of material stock on hand. This action of increasing new orders, however, can further deteriorate supplier performance, validating the previous expectation and stimulating purchasers to lengthen forward purchase commitments even further. Victor Zarnowitz ob- served this phenomenon in his analysis of orders, production and inventory investment: . . as suppliers approach capacity opera- tions they begin to quote longer lead times to their customers. To the extent that the latter (purchasers) respond by placing more orders in an attempt to increase their stocks on order, their actions, designed to alleviate the prob- lems for the individual firm, are apt to aggra- vate the total problem. As the additional orders only succeed in swelling the suppliers' backlogs, they actually result in an intensified excess demand situation of which the increase in back- logs, deljvery lags, and prices are primary symptoms. In a similar but more dramatic manner, when supply channels are threatened by such events as strikes and wars, purchasers freqdently increase orders in an attempt to accumulate inventories. In this way, they protect their production schedules and profit margins. Professor Hoagland concluded: 6Ruth P. Mack, Information, Expectations;_and Invento_y Fluctuations, (New York: National Bureau of Economic Research, l967), p. 179. 7Victor Zarnowitz, Orders, Production and Investment-- A Cyclical and Structural AnaTysis, (New York: National Bureau of Economic Research, l97ST, p. 389. 13 If sources of supply are to be shut off, purchasers, to keep production from being shut down, must either accumulate purchase invené tories ahead of timg, seek alternative sources of supply, or both. Such purchasing behavior also aggravates the ability of suppliers to perform. In order to accumulate inventories, purchasers must significantly increase the size of purchase orders above current usage levels--commonly referred to as "overbuying." Overbuying expands the suppliers' backlogs, creating longer delivery times and, in turn, further alters purchasers' perceptions of future supplier performance. Once the threat to supply channels diminishes or is removed, imbalances exist between the level of purchase orders and inventories and the needs of the firm. These imbalances usually require adjustment. Professor Hoagland continued: . . . after shortage situations have passed, it is usually necessary for inventories to be re-adjusted by re-buigding, re-balancing, or liquidating excesses. Rebuilding deficiencies requires purchasers to continue their expanded material orders, again extending the aggravated supplier situation. However, liquidating excesses requires purchasers to reduce material orders below current usage levels, which is generally referred to as "underbuying." Supplier performance is a major business factor used 8Hoagland, Purchasing and Inventory Forecasting, p. l2. 91bid. 14 by purchasing executives to gauge future business conditions. Yet more basic and important to the issue of supplier per- formance is purchasers' perception of the future availabil- ity of requisite materials to satisfy production schedules and maintain profit margins. Previous studies have identi- fied three key events that contribute to this perception: (l) labor strikes, (2) wars, and (3) availability of merchandise. Labor Strikes. Professor Hoagland appears to be the first to link labor strikes and threats of strikes to pur- chasers' expectations of the suppliers' ability to perform. He stated: It should be pointed out that major strikes and threats of strikes have become a big factor in actual or anticipated vendor performangs and, thus, have a great impact on our economy. The threatened blocking of acquisition channels by labor strikes intensifies purchasers' expectations of supply problems. In response, purchasing executives take action to protect future production schedules. Rodney Boyes examined this behavior in a study of steel purchases and concluded: The threat of a steel strike, therefore, induces purchasers to increase purchasing activities in order to accumulate an extra amount of steel inventories, called a strike hedge. The hedge, in turn, provides protection if the supply of steel is cut off, thereby permitting manufacturing operations to continue.11 lOIbid. 1lRodney L. Boyes, "Fluctuations in Steel Purchases and Inventories, 1953-1963," (East Lansing: Michigan State University, 1964), unpublished dissertation, p. 162. 15 Professor Hoagland added: In order to protect against post-settlement uncertainties of supplies, purchasing executives eggage in preisgttleggntvgrdering of materials pos se e e y These conclusions are later supported by Emil Albert's study of the aluminum ingot industry.13 War. Wars and the threat of wars are another major factor in gauging future supplier performance.14 If anti- cipated hostilities threaten normal acquisition channels, purchasing executives typically take precautionary actions to ensure material availability. Professor Hoagland stated, "Overbuying develops when there is a threat to supply caused by . . . war."15 Emil Albert's study of fluctuationsin aluminum ingot inventories and shipments supports this con- clusion. He observed that one of the conditions that caused fluctuations in the purchase of aluminum was, "threats of interruptions in supply of ingot resulting from wars and threats of war."16 12John H. Hoagland, "Forecasting Purchasing and Business Trends," paper presented before the Forty-Ninth Annual Inter- national Convention of the National Association of Purchasing Agents, Dallas, Texas, May, 1964, p. 4. 13Emi1 Albert, "Aluminum Ingot Market, 1959-1968," (East Lansing:' Michigan State University, 1971), unpublished dissertation, p. 108. I4Ibid., p. 147. 15John H. Hoagland, "Keys to Business Forecasting," presented at the Twelfth Annual International Conference of the American Production and Inventory Control Society, November, 1969, p. 8. 16Albert, Aluminum Ingot Market, p. 147. 16 Availability of Merchandise. The availability of merchandise is a factor that contributes to the seasonal ‘7 It purchasing decisions of retailers and wholesalers. refers to the difficulties that merchants face in obtaining merchandise of the required quality on short notice. If retailers and wholesalers perceive deterioration in the selection and availability of merchandise, they may lengthen their forward purchase commitments in order to ensure a supply of the desired goods and, thus, protect customer ser- vice levels. Ruth P. Mack observed: When factories are moderately busy, the choice seasonal merchandise can no longer be obtained at the last minute, so that a larger than usual proportion of orders for these goods :25 iifiéidal’fi‘iiiZSSKSSEEéoahifli.it“ ”‘3“ Once their desired merchandise position is established, overbuying is followed by underbuying, since the need for forward purchase commitments is eliminated. In short, all three variables--labor strikes, wars, and availability of merchandise--affect purchasing execu- tives' perception of supplier performance. This perception generally influences their expectations for future business conditions and, consequently, their actions to maintain production schedules and profit margins. 17Ruth P. Mack, Consumption and Business Fluctuations, (New York: National Bureau of Economic Research, 1956), p. 7. 18Itn'ci. 17 Price Movements Changes in material purchase prices also influence purchasing decisions. In anticipation of a price change, purchasing executives typically attempt to protect or improve their profit margins. The choice of action is usually dependent upon the velocity and direction of mate- rial price changes and the costs associated with carrying additional inventories. To illustrate, if material prices are expected to moderately increase, purchasers may attempt to expand forward purchase commitments or accumulate material inventories at the current price. These actions are justi- fied as long as the price advantage is greater than the associated costs. Ruth Mack stated: . the increase that is justified by an expectation of a stipulated rise in prices is a negative function of the cost of carrying the additional stock and a positive function of the expected change in price over the relevant perigd of anticipation, discounted for uncertainty. Once material prices become firm, overbuying is followed by underbuying, since the advantage of an extended material commitment is eliminated. Mack continued: If . . . prices were expected to cease rising, there would be no buying since (materials) ownership should be reduced to the pre-rise... . level because there would 20 now be no offset to the . . . carrying cost. 19Mack, Information, Expectations, and Inventory Fluctuations, p. 178. 201nm. 18 On the other hand, when falling prices or extremely high prices are anticipated for the short term, purchasers reduce forward purchase commitments and begin the practice of underbuying, which is also referred to as "hand-to-mouth" buying. Leverett Lyon observed this behavior in his study: The causes to which hand-to-mouth buying. has been attributed include. . . extremely high prices, falling prices and the threat of falling prices.21 Thus, how purchasers respond to price changes is a function of their magnitude, direction, and associated costs. However, common to any response is the goal of maintaining or improving the firm's profit margin. Sales Orders Finally, the third key factor that can influence pur- chasing decisions is the flow of sales orders. The level of actual or anticipated sales orders typically is used to determine production schedules, which, in turn, identify material requirements that, subsequently, affect purchasing decisions. This decision sequence includes at least two additional considerations: (1) the acceleration principle, and (2) the risk of overbuying. Acceleration Principle. The acceleration principle says that changes in the rate of sales cause magnified changes in business investment.22 The principle applies to all types 2ILyon, Hand-to-Mouth Buying, p. 432. 22Edwin Mansfield, Principles of Macroeconomics, (New York: N. N. Norton & Company, 1983), p. 296. 19 of business investment, i.e., plant, equipment, and changes in inventory levels. The acceleration principle suggests that as sales are increasing at an increasing rate, business executives generally attempt to expand their ownership of plant, equipment, and inventories in order to increase their production capability. If, however, sales begin to increase at a decreasing rate, or fall, business executives typically attempt to decrease their level of business investment by not replacing old equipment or by reducing inventory levels. Thus, the rate of change in sales orders can affect the level of purchasing activity. Risk of Overbuyjng. Ruth Mack observed, ". . . current orders and their recent changes, in effect, provide a fore- cast of future orders on which . . . purchased materials will be used."23 Since sales and materials forecasts are normally less than 100 percent certain, purchasing decisions usually include an element of risk: the risk of purchasing materials that will not be needed within a-reasonable period of time. This is commonly referred to as the risk of over- buying. Purchasers attempt to minimize this risk, suggesting that the extent to which it exists can influence the outcome of a given purchasing decision.24 For example, if the risk of overbuying is high, purchasers generally select a cautious 23Mack, Business Expectations, p. 114. 24Ibid., p. 113. 20 course; however, if the risk is low, they may choose a more casual course. The degree to which the risk of over- buying contributes to purchasing decisions is partially dependent upon the manufacturing characteristics of the industry (i.e., production-to-order or production-to-stock). Production-to-Order. Production-to-order refers to industries in which the production schedule is developed from sales orders received. The presence of order backlogs tends to reduce the risk associated with foreward commitments since future material requirements are relatively certain. Mack stated: This . . . risk is virtually eliminated if materials are bought for use in connection with zgclsgggnpspdgggz.£gr which firm sales orders Thus, in the case of production-to-order, the risk of over- buying is low, while the level of purchasers' confidence in future material requirements is quite high. Production-to-Stock. Productioneto-stock refers to industries for which sales forecasts are a main factor in production scheduling. These sales forecasts are typically an extrapolation of past sales experience and current sales orders received. Sales forecasts make a less-than-dependable guide, since forecasting errors will undoubtedly occur. Victor Zarnowitz observed: 25Mack, Informatiopp Expectations, and Inventory Fluctuations, p. 189. . 21 In production-to-stock, errors of sales forecasting will inevitably occur and they imply the existence of a passive or unintended com- ponent of investment in materials (which, in turn, may give rise t36corrective elements in mater1al purchas1ng). This tends to increase the risk associated with forward purchase commitments, since future material needs are rela- tively uncertain. Thus, in the case of production-to-stock, the risk of overbuying is high, and the purchasers' confi- dence is low. In short, purchasers' response to the flow of sales orders may depend upon the effects of the acceleration principle and the degree of risk of overbuying. However, having materials to meet future demand is basic to the pur- chasing executive's function. Therefore, sales orders are a necessary component of purchasers' expectations. Since the purchasing functionisaikey in determining the interdependencies created by specialization in our economy, changes in purchasing behavior may have a significant impact upon the entire business system. This section identified three important factors that can initiate and perpetuate changes in purchasing decisions: (1) supplier performance, (2) price movements, and (3) sales orders. Steel and the Business System The role of steel in determining U.S. business trends is aggressively debated. Although the controversy is 26Zarnowitz, Orders; Production, and Investment, p. 353. 22 widespread, current available literature that analyzes this relationship appears limited. This section reviews studies that are representative of the unfolding recogni- tion of steel's impact. As a result of the general public's concern over the possible adverse economic effects of steel strikes, John P. Mitchell, former Secretary of Labor, commissioned a special government study on the subject in 1960. Analyzing quarterly and annual data on production, final sales, and inventory changes for the durable goods component of the gross national product, this commission stated, ". . . that the long range economic effects of past steel strikes have left no permanent scars on our economy.“27 Additionally, it concluded: The consequences of the steel bargain have their effects primarily on the parties, and the strikes which from time to time may accompany the negotiations do not warrant the public con- sternggion and outcry that have occurred in the past. However, the use of quarterly and annual data suggests that these conclusions may have been influenced by an aggre— gative bias. Additionally, this study concentrated on the steel-using community, with minimal focus on the material- supplying industries. Such weaknesses in this study's methodology suggest that its conclusions are questionable. In 1963, Henry Broude attempted to determine whether the distortions that existed in the steel industry were of 27Livernash, Basic Steel Industry, p. v. 28 Ibid. 23 such fundamental significance to the economy that their correction was of paramount importance.29 During the course of his study, he attempted to establish a direct relation- ship between Gross National Product and the iron and steel output series. Using annual data, he found a close rela- 'tionship between steel production and GNP. However, Broude had little confidence in the results because of the coarse- ness of the data. He concluded: In summary, then, there appears to be considerable doubt as to the usefulness of steel series as indicators 35 forecasters of levels of bu51ness act1v1ty. Philip Klein and Richard Gordon examined in consider- able detail the relationships between cyclical instability in the steel-producing process (from iron ore to steel forgings) and in the general economy.31 The cyclical be- havior of twenty-seven steel-related monthly data series, compiled by the American Iron and Steel Institute and the U.S. Bureau of Mines, was analyzed, with the reference -business cycles established by the National Bureau of Economic Research. The emphasis of this study was deter- mining lead and lag relationships for each steel series with the duration and magnitude of business cycles. They concluded: ngroude, Steel Decisions and the National Economy, p. 27. 3011111., p. 49. 3IKlein and Gordon, The Steel Industry and U.S. Business Cycle , p. l. 24 That all parts of the steel industry participated in the periodic instability which has characterizgg economic activity in the United States. Steel can generate economic instability that might be a contributory factor in initiating economic declines. However, we are reluctant to argue that these weaknesses are large enough by themselves to precipitate a recession. Accelerator effects are pronounced in the steel industry. Small variations in product shipments are accompanied during reference cycles by considerably larger fluctuations in activity in the early stages of the steel-producing process, and fre- quently by relatively larger changes in later intermediate production activity.34 While concluding that little evidence was found to support the concept that the steel industry plays an active role in initiating business cycles, Klein and Gordon indi- cated that the current state of many of the steel-related data series was inadequate.35 For several years, John H. Hoagland has studied past business trends and events in order to discover keys to unlock information about the past. Using these keys, Hoagland built his forecasts of future business trends. In his research of monthly data from the National Association of Purchasing Management (NAPM) Business Survey and other published and unpublished information, Hoagland concluded 321bid., p. 32. 33Ibid., p. 48. 3411311., p. 86. 351bid., p. 94. 25 that, "Steel strikes have been a major cause of recent . . . . 36 bus1ness recess1ons and bus1ness expan51ons." He reasoned: The threat of steel strike endangers many vital sources of supply and disrupts normal procurement channels. To protect against possi- ble shortages of materials needed to sustain production, purchasing executives are forced to accumulate strike-hedge inventories prior to the strike deadline. This is an expensive process, but it is more expensive to shut down production because of a lack of materials. Inventory hedging prior to a steel strike takes many months and is of such magnitude that it results in a period of business expansion prior to the settlement. In order to protect against post-settlement uncertainties of supplies, purchasing executives engage in pre-settlement ordering of materials for post-settlement delivery. This causes continued stimulation of business activity for a few months after contract settlement. By the time normal systems of supply have been fully re-established, widespread inventory excesses and imbalances have developed. It then becomes necessary for inventories to be liquidated, which results in declining business activity. Moreover, since this inventory liquidation is attempted in a period of declining activity, it takes longer to liquidate inventories than it does to accumulate them. Business activity becomes depressed for many months, and the result usually is a business re- cession starting within on§ year following the steel contract settlement. 7 Under Hoagland's leadership, Rodney L. Boyes, in an unpublished dissertation, examined steel purchases and inventories in order to establish the causes and importance of major fluctuations in steel purchasing activity. Studying 36Hoagland, "Forecpsting Purchasingsand Business Trends," p. 4. 37Ibid. 26 several monthly data series, he observed that: Major increases per month in steel new orders occur from one to nine months prior to steel contract terminations and reopeners.38 During the five years 1959-1963, the new orders for steel evidenced four major fluctua- tions which demonstrated a shift in steel new orders of approximately $1 billggn or more in the monthly rate of new orders. This led to Boyes' conclusion that, "Major fluctuations in steel purchases and steel inventories have a significant impact upon the general level of business activity."-4’0 Although his study estimated only the fluctuations in steel purchases, Boyes suggested, The total impact of fluctuations in steel purchases (e.g., the effects on factor markets such as ore, coke, etc., or on steel by-products) is greater in monetary terms. I This dissertation continues the investigation by exam- ining the magnitude and dispersion of the "total impact" that major fluctuations in steel'purchases by steel consumers have upon the U.S. business system. Summary In the highly interdependent U.S. business system, the purchase/sales relationship integrates the activities of various business units. Fluctuations in purchase decisions 38Boyes, Steel Purchases and Inventories, p. 48. 391bid., p. 161. 4°1b1d. “rpm, p. 49. 27 disrupt the balance of purchase/sales transactions throughout the economy. The resulting adjustments to restore balance are a basis for the dynamic nature of the business system. The purchasing decisions are based partially on expecta- tions about future business conditions. In formulating expectations, purchasing executives typically identify and assess key business factors and events that may significantly impact production schedules and profit margins. Previous research has identified three of these key factors as sup- plier performance, price movements, and sales orders. The impact of changes in steel purchases by steel con- sumers on the purchase/sales balance throughout the business system has been disputed. Initially, the impact was not recognized. Later works departed from that initial position and began to recognize the significance of fluctuations in steel purchases. The progression continues as this disser- tation examines the magnitude and dispersion of interindustry purchases that are generated by fluctuations in actual or anticipated steel purchases and determines their impact upon the U.S. economy. CHAPTER III STEEL The purpose of this chapter is to examine the major components of the steel-producing process in order to better understand some of the factors that attest to the industry's significant role in the U.S. business system. The chapter includes: (1) a description of the steelmaking process, (2) a definition of the steel industry, (3) an analysis of the inputs and outputs of the steel industry, and (4) a discussion of the United Steelworker's Union (USW). Steelmaking The steel production process encompasses a variety of diverse industries, such as mining, transportation, utili- ties, steel mills, steel rolling and finishing, and steel scrap. Each industry contributes expertise via the purchase/ sales relationship to create a synergistic production system. The steel-making process (Figure 1)1 can generally be understood by: (1) following the two routes of producing molten steel, (2) examining the two methods of forming 1The Council on Wage and Price Stability, Rpport to the President on Prices and Costs in the United States Steel Industr , (Washington, D.C.: Government Printing Office, I977), p. 4. 28 29 FIGURE 1 STEEL PRODUCTION PROCESSES A circle at a junction indicates alternatives.) 9l938 lllW (Note: ‘ Coal Ore Fines} ggggt ‘Electricity lfstrlglt Sinter 1m 5 on _Coke Fines (Breezei E_ Plant I *~ Sinter Blast Iron Ore Pellets Coke *1 ‘ Furnace, ime tone Electricity Molten Iron 1 Scrap Scrap v i 1 l . Elec- Open Ba51c . . Electric “‘91 Hearth gag—Oxygen €25.12... Arc Furnace Furnace Furnace [ Molten IA Steel ,] 1 Ingot POUFTOO (Continuous Scrap l Casting — - ilii — i 1ng Blooms, ed Sha es s Plaie, fiOE ’f’ SEmifinisr ‘Hot Roll-i Rolled Sheet and Strip I ing Till Cold Rolled Sheet and Strip l [Acid Pickling J V Cold Roll- ing Mill Scrap, Mill Scale;7 Scrap, Mill Scale;: 30 semifinished shapes, and (3) concluding with their conversion into finished products. The two basic technologies for producing molten steel from raw materials are called the hot metal process and the cold metal process.2 The hot metal process produces molten steel from iron ore. First, coke is manufactured from coal and smelted with iron ore in a blast furnace to produce molten iron. In the Open Hearth or Basic Oxygen steel-making furnaces, the molten iron is subsequently combined with steel scrap and refined into molten steel. This process involves coking, agglomeration, iron-making and steed-making. The cold metal process refines recycled steel scrap into molten steel in an Electric Arc steel-making furnace. Since this proce- dure is scrap intensive, its cost advantage over blast fur- naces is dependent upon the price of steel scrap. Addition- ally, the cold metal process requires a smaller capital investment, since it does not need the support of coke ovens, sinter strands, or blast furnaces. Regardless of how the molten steel is produced, it must be solidified into shapes suitable for further processing. Currently, the two procedures available are the conventional 3 The conventional method method and continuous casting. involves pouring molten steel into ingot molds, allowing it to cool, and then reheating the ingots so that they may be rolled into semi-finished shapes (i.e., blooms, billets. 21bid., p. 3. 3Ibid., p. 5. 31 and slabs). Continuous casting shortcuts this process by (pouring the molten steel directly into water-cooled molds of the desired semi-finished shapes. Finally, these shapes are converted into finished products by more hot and cold rolling, acid pickling, galvanizing and tin plating. Thus, the production of finished steel shapes and forms is a multi-step process to which numerous technologies must be applied. The Steel Industry At this point, it is necessary to establish a working definition of the steel industry. Thus, for this study, the steel industry represents a collection of manufacturing establishments4 engaged primarily in the smelting, refining, . and converting of iron ore and steel scrap into finished steel shapes and forms. As Figure 25 illustrates, the in- dustry includes: (1) fully-integrated establishments, con- sisting of coke ovens, blast furnaces, Steel furnaces, and rolling and finishing mills; (2) semi-integrated establish- ments, consisting of either blast furnaces, steel furnaces, and rolling and finishing mills or steel furnaces and 4The SIC system uses "establishment" to denote the unit of classification. "Establishments" are business units that produce goods and services. Generally, they are located in one geographic area and are engaged in predominantly one type of economic activity for which the industrial codes are applied. 5American Metal Market, Metal Statistics 1973 (New York: Fairchild Publications, Inc., 1973), p. 245. 32 muuzuocm __wz Pompm _ prz mom:t=m-mom=g:d- meum meum pmmpm .uym .muom .mumpp_m _ umumAMmucplxppad mcm>o- mxou .uam .muom .mpaF_tm cmumtmmpcmuwsmm u=a_a meow :ugmz \ 9x- . m.a mxoo \ .-/ ppm: mumccad umumgmmucwiwsmm use (a - - \ .a axou Jr kl mmumcgad pmmpm cmsutmz mm_epm:u:~ tacos seed mgaacfi >mhmaozH Amth mxh do onhaHmummo < N mmszd 33 rolling and finishing mills: and (3) non-integrated establishments that operate independently, such as merchant coke plants, merchant blast furnaces, ferroalloy plants, and rolling and finishing mills. In short, the industry represents a collection of manufacturing establishments and operations that integrate various stages of the multi- step production process. According to the Standard Industrial Classification (SIC) system, the steel industry consists of manufacturing establishments classified in the following industrial cate- gories: - Blast Furnaces (including coke ovens), Steel Works and Rolling Mills Electrometallurgical Products Steel Wiredrawing and Steel Nail and Spike Cold Rolled Steel Sheet, Strip and Bars ° Steel Pipe and Tubes A detailed description of each industrial category is presented in Table 1. Inputs and Outputs of The Steel Industry The steel industry in the United States is character- istic of an oligopoly, a few large producers of a homogeneous product. Although there are several steel producers, a few firms appear to control the majority of the industry's output. These firms are generally fully-integrated to oper- ate continuously from coke production through finished, .ee_-ma_ .aa .fimsm_ .eueeeo eeepseta acesete>oe .m.= ".u.e .eoeeewemezv .mnmp Pessez sowuequPmmepo Femsumsusm useuseum .ummuam use useeemesez mo mowewou 34 .mpewseuee uemesuses ease museum use mp_es Pemum mswssuuee isses s? use "use: use ween .muos meum _ museum so so»? uemesusss ease use: mswzesu use mFFez Pmmpm use s? ummemse upwseswss museEsmwpseumm mswzesueswz pmeum mopo.~m mpmm . .mmmmmuoss uwsseseoppeuee so peevmssp_epesosuuepe zu whoppe e>Pu . -wuue osseensos use ossme mswssuueeasee muueuoss Fee s? ummemse upwseewss musessmvpeeumm lems=PFepmsosuompm No_o.sm mpmm .ueu=_osw ompe use mse>o exou usesoses use mmuessue umepu usesu -smz .mesesm upmeu ogsw Foepm use sosw mswppos no; sp use ”meum ops? 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ws .z>eas use maaap use aawa Paaum mma_Eeem sa uaupaz ea sawpaau -asa sw uaaemsa apvseEwsa musaEsmwFaeumm .Faaum uasmwses upaa smsua mswuauasa use "msea Paaum ua——as was Ease maaesm Paaum use msea Faaum mswzesu uFaa ”mamasm uappas was uemesu -ssa Ease mawspm use mamasm Pmaam msmp_as uFaa sw uauemsa apmseEwsa musaEsmwpaeumm awash use mars paaum msem use .sesam .aaesm peeam eeppos esoa mopo.nm upmm uopo.nm mpmm sawuawsamas aEez xspmausH uHm unsweetuaasm uHm Eosaeusesmmesa >mhm=ozH Aumhm mxk no onhaHmumma seesssaeoav _ aam .Nnmp .msasauaemasez ea mamswu .mamsau as» ea aeasam .m.=m_ .meseea use edeeesesmeF muuau mxsaz Fmaum toss peo_msap m.m .mpm.~um use mmaesssd umepm m»a_F< u—euaEasuaapm mxsaz ~aaum mxsaz Paaum use ~.P Eodom use maaessad umeFm exam mauessad umepm . mxsaz Faaum mesa: Paaam use m.N mpo.oom use mmaessas awe—m sasH mes maaessas umepm mxsaz Paaum mxsaz Pmapm use u.mp mpo.opm.~ use maaessad umepm maaesm Paaum maaessas umepm mpaasa Pemsapez Asamapeu N asamaueu Feuae xuwuseao Aw*m:usmuaam a wmausw1a=m ea ameusaasas seppao msm>maaam Fewseuez mseaaesm Amseppao mum. so musemaaspv >spmuozH ammpm are so mhusz~,>mhm=ozHiwaaam Fewsapez mswaawsm Amseppao New, ea musemaashv >mpm=oz~ 4mmhm “IE do mhuszm >mpm=ozHu Feuah zas sms useEau Feswm peuah passe auewuaEsaasH p a» ._N w: nexumsasz . paauao mx Nx Fx Fewsumausm Peach me me _~ eeee< aese> m> m3 mmx me pmx sampeusaamsesp N> N3 mmx mmx me mspsapaesasez _.> P3 MPX NFX _._.X DCPCPZ sampeusaamsesp mswsauoewasez uses? uaauao usean xuwuaEEau Fesws mawppuaEEau Fepah ~epa» mapsumeusu do ammo: <. m wmstd mehm mmHPHoozzou do mm: mzh 53 wherezajj = input coefficient Xij = cell total Xj = column total i = row j = column Input coefficients facilitate the mathematical calcu- lation of interindustry response to changing levels of business activity. The Make of Commodities by Industries. This matrix, illustrated by a model in Figure 7, presents in each row the dollar values (yij) of the various commodities produced by that industry. The entry in the main diagonal (where the row with the given industry/commodity code intersects the column with the same code) is the value of the primary product of the industry. The other entries in the row are the dollar values of the industry's secondary products. Each column presents the amount of each commodity produced by each industry. The column sum (Yj) equals total commod- ity output, and the row sum (Xi) equals total industry output.4 4Department of Commerce, Definitions and Conventions, p. 36. 54 sEapaa sea uaauaa xeeuaEEau _euap 0P 0'- On >,>< >- seex sea «sauna m.»spmausw Peach u paapaa aumuaEEaa m.xspm=usH u u uaauao ms es s» seseeeeda Peuah mx mm» mm» —ma sawueusaamses» «x mm% mm» Pm» mswsauaemase: Px mp» up» pp» mswspz uaauao sawueusaamsesp mswsapaeeasez usesvz asumausm memsumausH Feuae mewumuaEEau xmmhm mmeHoozzou no mx 'Transportation-—~» Petroleum Refining —~» CrudeiPetroleum and Natural Gas Chain Examination of this supply chain reveals the existence of purchasing waves (See Figure 9). Typical of this phenom- ena is the fact that each industry's purchases peak at sub- sequent stages of the purchasing mechanism. The four observable peaks resulted in fluctuations of 78 index units for steel mills at stage 0; 57.6 index units for 5Klein and Gordon, The Steel Industry and U.S. Business Cycles, p. 74. :73 . .m xvuseaa< eem.pweueu so...a mswmesasaa ea memeum op o m N. m m u m N P o d- db .40N mew Fesauez use.E:ePasuea euasu illlltv mswseees Eaepasuea 1. Jeoe sawueusaamsese I111. peeum ammem 2e P fcop xeusH «z~<:u >4aazm 4mmhm < m mmzwaa 74 transportation at stage 1; 38.4 index units for petroleum refining at stage 2, and 33.3 index units for crude petro- leum and natural gas at stage 3. Additionally, the continued flow of each industry's purchasing activity subsequent to each peak further suggests the transmission of purchasing activity. Although a surge in new steel orders directly influences transportation, petrol- eum refining, and crude petroleum and natural gas, its impact cascades to each subsequent industry, creating waves of purchases. This phenomenon suggests the important role of secondary industries when analyzing the effects of major fluctuations in purchasing activity upon the general business system. The "wave" behavior transmits the strength of the initial change to numerous other industries within the busi- ness system. Consequently, it appears that the intensity of these secondary relationships can significantly influence the magnitude and dispersion of interindustry activity that results from an initial change in purchasing behavior. Magnitude and Dispersion of Interindustry Activity In this section, estimates of the magnitude and disper- sion of interindustry purchases created by a 100 percent surge ($2.4 billion) in monthly new steel orders are examined. Consideration is given to: (l) the total business system, (2) major industrial sectors, and (3) individual industries. It is important to emphasize that the estimates of 75 interindustry activity are significantly understated. This resulted from: The input-output convention of not tracing the actual flow of commodities purchased and resold by the Wholesale and Retail Trade Sectors, eliminating two important levels of purchases. The scope limitations placed upon this study in Chapter I, which minimized the influence of other economic variables. The modifications made to the 1972 Input- Output Model in Chapter IV, which confined the study to a limited number of industries. Total Business System The total business activity created by major fluctua- tions in steel purchases suggests the important role of the steel industry within the U.S. business system. The modi- fied 1972 Input-Output Model conservatively estimates that the production of an additional $2.4 billion in steel mill products would require, directly and indirectly, an addi- tional $2.6 billion in materials, parts, components, and services. Given the constraints of the study, this figure suggests that a $2.4 billion surge in one month's steel purchases by steel consumers would create, for the business system, an additional $2.6 billion in new business. This new business would be created as the initial imbalance was transmitted across our economy through the sequential development of purchase/sales relationships between one 76 specialized industry and the next. The aggregate effects of the $2.4 billion surge in one month's steel purchases on this sequential development are illustrated in Figure 10. It shows that during the first purchasing stage, the initial imbalance of $2.4 billion creates $1.4 billion in new purchases of materials, parts, components and services from suppliers; during the second purchasing stage, these suppliers purchase $648 million; during the third, $277 million; the fourth, $117 million; the fifth, $50 million, etc. This sequential impact of the initial imbalance_upon numerous levels of purchase/sales relationships exemplifies the stimulative influence that the steel industry has upon the U.S. business system. The significance of steel's role in our business system becomes evident when considering that the impact of major fluctuations in steel purchases is more than doubled by the subsequent interindustry activity. This leads to the obser- vation that such fluctuations can play a very active role in generating new business of a magnitude that will signif- icantly influence the general level of business activity. Industrial Sectors If all of the new business activity that resulted from a surge in steel purchases were confined to a very few indus- tries, the significance of steel's role in the overall business system would be questionable. However, disaggre- gating the estimates of purchasing activity discloses the 77 FIGURE 10 TOTAL NEW INDUSTRIAL ORDERS ACCUMULATED AT EACH PURCHASING STAGE* Millions of Dollars 56001' 4800" 40001 3200‘ r 1600‘ 800'“ 4 n T I 9 10 *For detail,see Appendix F. Stages of Purchasing L 1 I Y T I 1- O 1 2 3 4 5 6 7 78 enormous dispersed effects of a 100 percent increase in steel purchases. As Table 6 indicates, the dollar value of new purchasing activity precipitated by a surge in steel purchases is monetarily significant for each of the major industrial sectors. The demand for newly manufactured goods increases $1.4 billion, far greater than for any other sector. Mining and transportation sectors show major expan- sions in monetary activity of $366.8 million and $258.2 million, respectively, while utilities, wholesale and retail trade, and business services record moderate gains. Note that the $154 million in wholesale and retail trade repre- sents only trade margins. If their merchandise purchases were included, this value would be significantly larger. Finally, the communication and automotive repair sectors show modest changes. These findings indicate that a surge in steel purchases impacts a wide range of industrial sectors. Consequently, the effects of changes in steel purchasing activity is not limited to a few selected industries but is broadly-based throughout the business system. The percentage change in purchasing activity exempli- fies the degree of impact that a surge in steel purchases by steel consumers has on the major industrial sectors. In Table 6, a major 14.5 percent surge in the mining sector's activity can be seen. The transportation and utility sectors each register impressive expansions of 4.1 percent, while manufacturing and business services recorded moderate 79 TABLE 6 INTERINDUSTRY ACTIVITY CREATED BY A CHANGE IN STEEL MILL PURCHASES (Millions of 1972 Dollars) Industrial Average Monthly New Percent Sectors Orders (I-O) Activity. Change Mining $ 2,532.62 $ 366.77 14.5 Manufacturing 64,992.52 1,376.80 2.1 Transportation 6,231.59 258.17 4.1 Communications 3,006.53 23.12 .8 Utilities 4,178.97 169.40 4.1 Wholesale and retail trade* 10,832.01 154.00 .9 Business _ services 5,725.82 102.31 1.8 Automobile Repair 2,024.35 13.82 .7 Total $106,724.41 $2,564.70 2 5 *Wholesale and retail trade represents only trade margins and not the purchase of merchandise. 80 changes of 2.1 percent and 1.8 percent. Finally, the wholesale and retail trade, communications, and automobile repair sectors show modest increases of .9 percent, .8 percent, and .7 percent, respectively. These results again show that fluttuations in steel purchases can have a significant impact on the activities of a wide range of major industrial sectors, including the mining, transportation, and utility sectors, with a lesser impact on manufacturing and business services. The magnitude and dispersion of new activity supports the two hypotheses proposed herein of steel's significant role within the busi- ness system. Individual Industries Continued disaggregation of the estimates of total purchasing activity created by a 100 percent surge in steel purchases by steel consumers at the individual industry level further documents steel's large and varied impact. Appendix 0 shows that the surge in monthly steel purchases stimulated activity in 389 of the 393 industries included in the study, with more than 140 of these industries expanding activities by at least $1 million. The top dollar changes in volume of interindustry activity (Table 7) shows that four industries increased volume by more than $100 million; six industries improved volume by more than $50 million; eight industries expanded volume by more than $10 million. Of these thirty-two industries, six are mining, fifteen are manufacturing, four are transportation, two are utilities, 81 TABLE 7 TOP DOLLAR CHANGES IN VOLUME OF INTERINDUSTRY ACTIVITY CREATED BY A SURGE IN STEEL PURCHASES, BY INDUSTRY (Millions of 1972 Dollars) Input-Output Model's Industry Number and Name Activity 1 371000 Steel mills 1376.80 2 050000 Iron and ferroalloy ore mining 170.56 3 690100 Wholesale trade* 150.29 4 650100 Railroad transportation 124.30 5 070000 Coal mining 95.92 6 680200 Gas production and distribution 85.52 7 680100 Electric services 78.94 8 730100 Miscellaneous business services 73.52 9 650300 Motor transportation 63.00 10 372000 Steel foundries 55.84 11 080000 Crude petroleum and natural gas 44.88 12 650400 Water transportation 33.55 13 380600 Secondary nonferrous metal products 30.84 14 730300 Miscellaneous business services 25.58 15 410100 Screw machine products 24.54 16 380100 Primary copper metal products 23.76 17 060100 Copper ore mining 22.61 18 650500 Air transportation 21.45 19 421100 Fabricated metal products 19.66 *Wholesale trade represents only trade margins and not merchandise purchases. 82 TABLE 7 (continued) Input-Output Model's Industry Number and Name Activity 20 660000 Communications, except radio & TV 18.41 21 500002 Machinery 17.02 22 470300 Special dies and tools 16.72 23 060200 Nonferrous ore, except copper 16.19 24 490500 Power transmission equipment 15.96 25 490200 Ball and roller bearings 14.17 26 750000 Automobile repair 13.83 27 380500 Primary nonferrous metals 12.80 28 380300 Primary zinc metal 12.56 29 490100 Pumps and compressors 12.07 30 530700 Carbon and graphite products 11.72 31 380400 Primary aluminum metal 10.79 32 090000 Stone and clay mining 10.56 83 and two are business services. The top percentage changes in volume of interindustry activity (Table 8) also illustrates the degree of impact and dispersion of steel's influence. It shows one industry's volume increased more than 100 percent; four industries' volume expanded more than 40 percent; nine industries' volume improved more than 10 percent; and fourteen industries' volume advanced more than 5 percent. The industries con- sisted of four mining, twenty-one manufacturing, two trans- portation, and one utility. Additionally, twenty of the manufacturing industries were durable goods producers. The evidence continues to lead to the conclusion that imbalances created by changes in steel purchases can signif- icantly influence a number of diverse industries throughout the business system. The magnitude and dispersion of busi- ness activity that results from shifts in steel purchasing behavior again suggests steel's active role in generating and perpetuating general business fluctuations. Summary The correlation coefficients calculated between the Manufacturers' New Orders Series and simulated series developed with the modified 1972 Input-Output Model appear to be significant. This suggests that the data calculated by the modified 1972 Input-Output Model are a valid, reflec- tive measure of interindustry purchasing activity created by major fluctuations in steel purchases by steel-consuming 84 TABLE 8 TOP PERCENTAGE CHANGES IN VOLUME OF INTERINDUSTRY ACTIVITY CREATED BY A SURGE IN STEEL PURCHASES, BY INDUSTRY (Millions of 1972 Dollars) Input-Output Model's Increased Percent Industry Number and Name Activity Change 1 050000 Iron and ferroalloy ore 170.56 166.1 2 380500 Primary nonferrous man. 12.80 41.4 3 380100 Primary zinc man. 12.56 41.1 4 530700 Carbon and graphite products 11.72 40.5 5 361300 Lime 8.28 40.3 6 371000 Steel Mills 1376.80 28.7 7 070000 Coal mining 95.92 21.1 8 060000 Nonferrous metal ores 38.80 20.5 9 380600 Secondary nonferrous metal 30.84 19.9 10 380200 Primary lead metal man. 6.37 15.6 11 490500 Power transmission equipment 15.96 13.1 12 420402 Metal coating and allied ser. 7.55 13.0 13 361600 Abrasive products 9.12 12.8 14 790200 Pumps and compressors 14.17 11.3 15 650100 Railroad transportation 124.30 9.9 16 550100 Electric lamps and lighting 8.80 9.8 17 410100 Screw machine products 24.54 9.7 18 100000 Chemicals and fertilizers min. 6.05 9.4 19 470402 Rolling mill machinery 2.47 9.4 85 TABLE 8 (continued) Input-Output Model's Increased Percent Industry Number and Name Activity Change 20 380100 Primary copper metal man. 23.76 8.8 21 420401 Plating and polishing 6.67 7.8 22 530200 Transformers 8.84 .2 23 270100 Industrial chemicals 86.84 6.4 24 470403 Metalworking machinery 2.11] 6.1 25 450200 Mining machinery 3.41 5.7 26 380400 Primary aluminum 10.79 5.5 27 650400 Water transportation 33.55 5.5 28 680200 Gas production and distribution 85.52 5.1 86 industries. However, this data appears to provide an understated estimate of interindustry purchasing activity. The phenomenon of purchasing waves" was illustrated for a select group of industries belonging to one of steel's supply chains. The transmission of purchasing activity across the business system suggests how an initial imbalance in purchasing activity can create a dynamic busi- ness environment. The conservative estimate of interindustry purchases created by a 100 percent surge in steel purchases appears to be significant in terms of both magnitude and dispersion. Introducing a $2.4 billion surge in monthly steel purchases to the business system resulted in a corresponding surge in interindustry purchases of $2.6 billion. Furthermore, this surge impacted 389 of 393 industries included in the study. These observations strongly suggest that major fluctuations in steel purchases by steel consumers are of significant magnitude and dispersion to impact the general level of business activity. CHAPTER VI SUMMARY AND CONCLUSIONS This study examined some of the characteristics of interindustry purchasing activity that are created by major fluctuations in steel purchases by steel-consuming industries. The research focused on measuring the interindustry purchas- ing activity initiated by these fluctuations and analyzed their impact upon the total business system, major industrial sectors,and individual industries. Conclusions The study was approached by analyzing estimates of interindustry activity created by fluctuations in monthly steel purchases by steel consumers. The analysis identified and evaluated the effects of a 100 percent surge in steel activity upon the business system. The results of this analysis, as applicable to the hypotheses, are discussed below. It is important to emphasize that the estimates of interindustry activity presented in Chapter V were considered understated. This resulted from: The input-output convention of not tracing the actual flow of commodities purchased and resold by the Wholesale and Retail Trade Sectors, eliminating two important levels of purchases. 87 88 The scope limitations placed upon this study in Chapter I, which minimized the influence of other economic variables. The modifications made to the 1972 Input- Output Model in Chapter IV, which confined the study to a limited number of industries. The conservative nature of these estimates, however, does not appear to inhibit their interpretation. Conclusion I: Major fluctuations in steel purchases have a significant impact on the general level of business activity. The magnitude of interindustry purchasing activity created by a major change in steel purchases by steel-con- suming industries was established through the use of a modi- fied 1972 Input-Output Model in Chapter V. The introduction of a $2.4 billion surge in monthly steel purchases to the business system resulted in a subsequent increase in busi- ness activity, conservatively estimated at $2.6 billion. Therefore, it can be seen that fluctuations in steel purchasing behavior substantially influence interindustry activity in monetary terms. Conclusion 11: The effects of major fluctuations in Eteel purchases are Significantly dispersed throughout the business system. 89 The dispersion of interindustry purchasing activity, as measured by the modified 1972 Input-Output Model, was presented in Appendix D. The 100 percent surge in monthly steel purchases stimulated activity in 389 of the 393 indus- tries included in the study. More than 140 of these indus- tries expanded activity by at least $1 million, with only two increasing activity by more than $100 million. The diverse characteristics of the effects of a major change in steel purchases by steel consumers was illustrated in Tables 6, 7, and 8. This evidence indicates that major fluctuations in steel purchasing behavior influence a sub- stantial number of industries in the U.S. business system. Conclusion III: The impact of major fluctuations in steel purchases is of sufficient magnitude and dispersion to play an active role in general business instability. A change in purchasing behavior by steeleconsuming industries increased one month's steel purchases by $2.4 billion and, subsequently, created $2.6 billion of inter- industry purchasing activity, affecting 389 industries in the business system. The broad impact of this enormous monetary stimulus leads to the conclusion that major changes in steel purchases can play an important role in general business fluctuations. APPENDICES APPENDIX A WORKSHEET: STEEL MILL INDUSTRY PURCHASES FOR 1972 This appendix presents a worksheet used to calculate the volume of 1972 purchases of the basic steel industry. The data were collected from published results of the 1972 Census of Manufacturers' conducted by the Bureau of the Census. 90 91 APPENDIX A WORKSHEET Steel Mill Industry Purchases for 1972 (Millions of 1972 Dollars) Beginning Inventory1 $ 2177.0 Purchases2 Materials and Supplies $15002.7 Resales 221.2 Fuel Consumed 915.6 Electrical Energy 522.3 Contract Work 360.6 17012.4 Cost of Materials Available $19189.4 Ending Inventory3 2217.8 Cost of Materials Consumed $16971.6 U.S. Bureau of the Census, Census of Manufacturers', 1972, Volume 1, Subject and SpecialTStatistics, D.C.: U.S. Government Printing Office, T976), 2 (Washington, p. 3-8. U.S. Bureau of the Census, Census of Manufacturers', 1972, Volume II, Industry Statistics, Partl2} SIC Ma or Groups 27134, (Washington, D.C.: U.S. Government Printing Office, 1976), p. 33A-13. 3 U.S. Bureau of the Census, Census of Manufacturers', 1972, Volume I, Subject and SpeciElTStatistics, p, 3-8. APPENDIX B THE PERCENTAGE BREAKDOWN OF TOTAL MATERIAL INPUTS INTO THE STEEL INDUSTRY Presented in this appendix is a calculation of the percentage breakdown of total material purchases by the basic steel industry. The dollar data were collected from published results of the 1972 Input-Output Study. This data is aggregated to the 85-industry summary level to facilitate evaluation. 92 93 APPENDIX B THE PERCENTAGE BREAKDOWN OF TOTAL MATERIAL INPUTS INTO THE STEEL INDUSTRY (Millions of 1972 Dollars) Input-Output Model's Dollar Percent of Industry Number and Name Activity Total Mining 5 Iron Ore 1710.6 9.9 7 Coal 755.8 4.4 Other Mining Industries 124.9 .7 Manufacturing 37.0 Primary Iron and Steel 5539.0 32.1 37.5 Iron and Steel Forgings 414.0 2.5 27 Chemicals 603.0 3.5 38 Primary Nonferrous Metals 576.1 3.3 49 Industrial Machinery 403.5 2.3 42 Fabricated Metal Products 390.3 2.3 41 Screw Machine Products 241.3 1.4 36 Stone and Clay Products 197.3 1.1 53 Electrical Transmission 196.0 1.1 47 Metalworking Machinery 195.2 1.1 31 Petroleum Refining 139.4 .8 All Other Manufacturing 691.9 4.0 Transportation, Communications and Utilities 65 Transportation 1863.5 10.8 68 Utilities 977.1 5.7 Other 51.9 .4 Wholesale and Retail Trade 69 Wholesale and Retail Trade 1051.9 6.1 Service 73 Business Services 552.6 3.2 75 Automobile Repair 27.7 .2 Scrap 81 Scrap 546.1 3.2 APPENDIX C INDUSTRY CLASSIFICATION OF THE 1972 INPUT-OUTPUT MATRIX This appendix presents the 85 industrial classifica- tions as determined by the Interindustry Economics Division of the Bureau of Economic Analysis, United States Department of Commerce. For the detailed (496-industry) classification, see: Philip M. Ritz, "Dollar-Value Tables for the 1972 Input-Output Study," Survey of Current Business. April, 1979, pp. 58-61. Industry groups included in this study are designated by an asterisk (*). 94 95 APPENDIX C INDUSTRY CLASSIFICATION OF THE 1972 INPUT-OUTPUT MATRIX Input-Output Model's Industry Number and Name AGRICULTURE, FORESTRY, AND FISHERIES 1. Livestock and livestock products 2. Other agricultural products 3. Forestry and fishery products 4. Agricultural, forestry, and fishery services* MINING Iron and ferroalloy ores mining* Nonferrous metal ores mining* Coal mining* Crude petroleum and natural gas* Stone and clay mining and quarrying* 10. Chemical and fertilizer mineral mining* SOCDVO‘UT CONSTRUCTION 11. New construction 12. Maintenance and repair construction MANUFACTURING l3. Ordnance and accessories* 14. Food and kindred products* 15. Tobacco manufactures* 16. Broad and narrow fabrics, yarn and thread mills* 17. Miscellaneous textile goods and floor coverings* 18. Apparel* 19. Miscellaneous fabricated textile products* 20. Lumber and wood products, except containers* 21. Wood containers* 22. Household furniture* 23. Other furniture and fixtures* 24. Paper and allied products, except containers and boxes* 25. Paperboard containers and boxes* 26. Printing and publishing* 27. Chemicals and selected chemical products* 28. Plastics and synthetic materials 29. Drugs, cleaning and toilet preparations* 30. Paints and allied products* 31. Petroleum refining and related industries* 32. Rubber and miscellaneous plastics products* 33. Leather tanning and finishing* 96 INDUSTRY CLASSIFICATION OF THE 1972 INPUT-OUTPUT MATRIX Input-Output Model's Industry Number and Name MANUFACTURING (continued) 64. Footwear and other leather products* Glass and glass products* Stone and clay products* Primary iron and steel manufacturing* Primary nonferrous metals manufacturing* Metal containers* Heating, plumbing, and fabricated structural metal products* Screw machine products and stam mpings* Other fabricated metal products Engines and turbines* Farm and garden machinery* Construction and mining machinery* Materials handling machinery and equipment* Metalworking machinery and equipment* Special industry machinery and equipment* General industrial machinery and equipment* Miscellansous machinery, except electrical* Office, computing, and accounting machines* Service industry machines* Electrical transmission and distribution equipment and industrial apparatus* Household appliances* . Electric lighting and wiring equipment* Radio, TV, and communication equipment* Electronic components and accessories* Miscellaneous electrical machinery, equipment, and supplies* Motor vehicles and equipment* Aircraft and parts* Other transportation equipment* Professional*, scientific, and controlling instruments and supplies* Optical, ophthalmic, and photographic equipment and supplies* Miscellaneous manufacturing* TRANSPORTATION, COMMUNICATION, AND UTILITIES Transportation and warehousing* Communications, except radio and TV* Radio and TV broadcasting* Electric, gas, water, and sanitary services* 97 INDUSTRY CLASSIFICATION OF THE 1972 INPUT-OUTPUT MATRIX Input-Output Model's Industry Number and Name WHOLESALE AND RETAIL TRADE 69. Wholesale and retail trade* FINANCE, INSURANCE, AND REAL ESTATE 70. Finance and insurance 71. Real estate and rental SERVICES 72. Hotels and lodging, personal and repair services (except auto) 73. Business services* 74. Eating and drinking places 75. Automobile repair and services* 76. Amusements 77. Health, educational, and social services and non- profit organizations GOVERNMENT ENTERPRISES 78. Federal Government enterprises 79. State and local government enterprises DUMMY AND SPECIAL INDUSTRIES 80. Noncomparable imports 81. Scrap, used, and secondhand goods 82. Government industry 83. Rest of the world industry 84. Household industry 85. Inventory valuation adjustment FINAL DEMAND 91. Personal consumption expenditures 92. Gross private domestic fixed investment 93. Change in business inventories 94. Exports 95. Imports 96. Federal Government purchases, national defense 97. Federal Government purchases, nondefense 98. State and local government purchases, education 99. State and local government purchases, other APPENDIX D INTERINDUSTRY PURCHASING ACTIVITY CREATED BY A 100 PERCENT SURGE IN STEEL PURCHASES This appendix presents the total interindustry impact of a 100 percent surge ($2,405.6 million) in steel purchases by individual industrial groups. The industrial totals are collected from calculations of the modified 1972 Input- Output Model of the U.S. economy. The induStry number and name are designated by the 1972 Input-Output Model's classification system. 98 99 TABLE D INTERINDUSTRY PURCHASING ACTIVITY CREATED BY A 100% SURGE IN MONTHLY STEEL PURCHASES (Millions of 1972 Dollars) Industry Number and Name Activity After 15 Cycles MINING 5 Iron and ferroalloy ores 5.0000 Iron and ferroalloy ores 170.556 6 Nonferrous metal ores 6.0100 Copper ore mining 22.608 6.0200 Nonferrous metal ores 16.192 7 Coal 7.0000 Coal 95.917 8 Crude petroleum and natural gas 8.0000 Crude petroleum and natural gas 44.880 9 Stone and clay 9.0000 Stone and clay 10.560 10 Chemical and fertilizer mineral 10.0000 Chemical and fertilizer mineral 6.053 MANUFACTURING 13 Ordnance and accessories 13.0100 Complete guided missiles 0.076 13.0200 Ammunition 0.185 13.0300 Tanks and tank components 0.039 13.0500 Small arms 0.086 13.0600 Small arms ammunition 0.010 13.0700 Other ordnance and accessories 0.055 14 Food and kindred products 14.0101 Meat packing plants 0.554 100 TABLE 0 (continued) 14 Industry Number and Name Food and kindred products —lu—l—l—l—l—l—l—I—l-—l—l—ldd—l-lu—ln—l—J—Jd—l—l—J-lu—lu—l—l—l-l—l—J—l—J—l—l—J—ld—l—l—l—l b-bbh-bbhb-b-b-h-hh-bh-hhhh-hkhhhhhhbb-fihhhbbhbhh-fibhb .0102 .0103 .0104 .0200 .0300 .0400 .0500 .0600 .0700 .0800 .0900 .1000 .1100 .1200 .1300 .1401 .1402 .1403 .1501 .1502 .1600 .1700 .1801 .1802 .1900 .2001 .2002 .2003 .2101 .2102 .2103 .2104 .2200 .2300 .2400 .2500 .2600 .2700 .2800 .2900 .3000 .3100 .3200 Sausages and prepared meats Poultry dressing plants Poultry and egg processing Creamery butter Cheese, natural and processed Condensed and evaporated milk Ice cream and frozen desserts Fluid milk Canned and cured sea foods Canned specialties Canned fruits and vegetables Dehydrated food products Pickles, sauces, and salad dress. Fresh or frozen packaged fish Frozen fruits and vegetables Flour and other grain mill prod. Cereal preparations Blended and prepared flour Dog, cat, and other pet food Prepared feeds Rice milling Wet corn milling Bread, cake, and related products Cookies and crackers Sugar Confectionery products Chocolate and cocoa products Chewing gum Malt Malt Wines, brandy, and brandy spirits Distilled liquor, except brandy liquors Bottled soft drinks Flavoring extracts and sirups Cottonseed oil mills Soybean oil mills Vegetable oil mills Animal and marine fats and oils Roasted coffee Shortening and cooking oils Manufactured ice Macaroni and spaghetti Food preparations Activity After 15 Cycles OOOOCOOOOOOOOOOOOOOOOOOOOOOOOO00000000000O O N O 0 2019 101 TABLE D (continued) Industry Number and Name Activity After 15 Cycles 15 16 17 18 19 Tobacco 15. 15. 15. 15. 0101 0102 0103 0200 manufactures Cigarettes Cigars Chewing and smoking tobacco Tobacco stemming and redrying Broad and narrow fabrics, yarn mills 16. 16. 0100 0200 Broadwoven fabric mills Narrow fabric mills 16.0300 Yarn mills 16.0400 Thread mills Miscellaneous textile goods —l—l—l-—l—l—l—l—l—J—l \INNNNVNNNN .0100 .0200 .0300 .0400 .0500 .0600 .0700 .0900 .1001 .1002 Apparel Miscellaneous fabricated textile products .0100 .0200 .0301 .0302 .0303 .0101 .0102 .0201 .0202 .0203 .0300 .0400 Floor coverings Felt goods Lace goods Padding and upholstery filling Processed textile waste Coated fabrics, not rubberized Tire cord and fabric Cordage and twine Nonwoven fabrics Textile goods Women's hosiery Hosiery Knit outerwear mills Knit underwear mills Knitting mills Knit fabric mills Apparel made from purchased mat. Curtains and draperies Housefurnishings Textile bags Canvas products Pleating and stitching COCO OOON OOOOOOOOOO 00000 #000000 .192 I000 .058 .481 .343 .528 .030 .070 .137 .004 .016 .060 .175 .558 .206 .091 .132 .136 :169 .397 .011 102 TABLE 0 (continued) 19 20 21 22 23 Industry Number and Name Activity After 15 Cycles Miscellaneous fabricated textile products 19.0304 Automotive and apparel trim. l9. 19. 0305 0306 Schiffli machine embroideries Fabricated textile products COO Lumber and wood products .0100 .0200 .0300 .0400 .0501 .0502 .0600 .0701 .0702 .0800 .0901 .0902 .0903 Logging camps and logging contrac. Sawmills and planing mills l Hardwood dimension and flooring Special product sawmills' Millwork Wood kitchen cabinets Veneer and plywood Structural wood members Prefabricated wood buildings Wood preserving Wood pallets and skids Particleboard Wood products donooomoooo—am Wood containers 21.0000 Wood containers ' 1 Household furniture .0101 .0102 .0103 .0200 .0300 .0400 Wood household furniture Household furniture Wood TV and radio cabinets Upholstered household furniture Metal household furniture Mattresses and bedsprings OOOOOO Other furniture and fixtures .0100 .0200 .0300 .0400 .0500 .0600 .0700 Wood office furniture Metal office furniture Public building furniture Wood partitions and fixtures Metal partitions and fixtures Blinds, shades, and drapery Furniture and fixtures CDC—40°00 .079 .007 .080 .292 .079 .356 .087 .237 .000 .331 .003 .012 .012 .482 .070 .635 .072 .037 .019 .022 .007 .028 .025 .003 .082 .042 .449 .028 .083 103 TABLE 0 (continued) Industry Number and Name Activity After 15 Cycles 24 25 26 27 Paper and allied products .0100 .0200 .0300 .0400 .0500 .0602 .0701 .0702 .0703 .0704 .0705 .0706 Pulp mills Paper mills, except building Paperboard mills Envelopes Sanitary paper products Building paper and board mills Paper coating and glazing Bags, except textile Die-cut paper and board Pressed and molded pulp goods Stationery products Converted paper products Paperboard containers and boxes 25. Printing 0000 .0100 .0200 .0301 .0302 .0400 .0501 .0502 .0601 .0602 .0700 .0801 .0802 .0803 .0804 .0805 Paperboard containers and boxes and publishing Newspapers Periodicals Book publishing Book printing Miscellaneous publishing Commercial printing Lithographic platemaking Manifold business forms Blankbooks and looseleaf binders Greeting card publishing Engraving and plate printing Bookbinding and related work Typesetting Photoengraving Electrotyping and stereotyping Chemicals and selected chemical products .0100 .0201 .0202 .0300 .0401 .0402 Industrial inorganic and organic Nitrogenous and phosphatic fert. Fertilizers, mixing only Agricultural chemicals Gum and wood chemicals Adhesives and sealants OO-‘Od—‘OOOOOUIO OOOOOOONOO—‘OONO‘I COCO-‘01 .818 .051 .153 .507 .399 .216 .563 .511 .035 .097 .199 .550 .482 .143 .292 .944 .454 .209 .260 .227 .075 .092 .225 .424 .186 .027 .380 .466 .346 .787 I712 104 TABLE 0 (continued) Industry Number and Name Activity After 15 Cycles 27 28 29 3O 31 32 33 Chemicalsand selected chemical products 27.0403 Explosives 3.079 27.0404 Printing ink 0.356 27.0405 Carbon black 0.216 27.0406 Chemical preparations 6.381 Plastics and synthetic materials 28.0100 Plastics materials and resins 5.030 28.0200 Synthetic rubber 1.452 28.0300 Cellulosic man-made fibers 0.247 28.0400 Organic fibers, noncellulosic 1.012 Drugs, cleaning and toilet preparations 29.0100 Drugs 0.628 29.0201 Soap and other detergents 0.788 29.0202 Polishes and sanitation goods 0.395 29.0203 Surface active agents 0.440 29.0300 Toilet preparations 0.149 Paints and allied products 30.0000 Paints and allied products ‘ 3.861 Petroleum refining and related industries 31.0100 Petroleum refining 48.939 31.0200 Paving mixtures and blocks 0.121 31.0300 Asphalt felts and coatings 0.066 Rubber and miscellaneous plastics products 32.0100 Tires and inner tubes 5.048 32.0200 Rubber and plastics footwear 0.023 32.0301 Reclaimed rubber 0.034 32.0302 Fabricated rubber products 3.355 32.0400 Miscellaneous plastics products 7.721 32.0500 Rubber and plastics hose and belt. 1.983 Leather tanning and finishing 33.0001 Leather tanning and finishing 0. 072 105 TABLE 0 (continued) Industry Number and Name Activity After 15 Cycles 34 Footwear and other leather products 34.0100 Footwear cut stock 0.006 34.0201 Shoes except rubber 0.002 34.0202 House slippers 0.000 34.0301 Leather gloves and mittens 0.002 34.0302 Luggage 0.051 34.0303 Women's handbags and purses 0.004 34.0304 Personal leather goods 0.029 34.0305 Leather goods 0.162 35 Glass and glass products 35.0100 Glass and glass products 2.183 35.0200 Glass containers 0.121 36 Stone and clay products .0100 .0200 .0300 .0400 .0500 .0600 .0701 .0702 .0800 .0900 .1000 .1100 .1200 .1300 .1400 .1500 .1600 .1700 .1800 .1900 .2000 .2100 .2200 Cement, hydraulic Brick and structural clay tile Ceramic wall and floor tile Clay refractories Structural clay products Vitreous plumbing fixtures Vitreous china food utensils Fine earthenware food utensils Porcelain electrical supplies Pottery products Concrete block and brick Concrete products Ready-mixed concrete Lime Gypsum products Cut stone and stone products Abrasive products Asbestos products Gaskets, packing and sealing dev. Minerals, ground or treated Mineral wool Nonclay refractories Nonmetallic mineral products doowmomooooooooooooooooo on ‘0 w 106 TABLE 0 (continued) Industry Number and Name Activity After 15 Cycles 37 38 39 40 Primary .0101 .0102 .0103 .0104 .0105 .0200 .0300 .0401 .0402 Primary .0100 .0200 .0300 .0400 .0500 .0600 .0700 .0800 .0900 .1000 .1100 .1200 .1300 .1400 iron and steel manufacturing Blast furnaces and steel mills Electrometallurgical products Steel wire and related products 10. Cold finishing of steel shapes Steel pipe and tubes Iron and steel foundries Iron and steel forgings Metal heat treating Primary metal products nonferrous metals manufacturing Primary Primary Primary Primary Primary Metal containers 39. 39. Heating, 0100 0200 .0100 .0200 .0300 .0400 .0500 .0600 .0700 .0800 .0901 .0902 copper lead zinc aluminum nonferrous metals Secondary nonferrous metals Copper rolling and drawing Aluminum rolling and drawing Nonferrous rolling and drawing Nonferrous wire drawing and insul. Aluminum castings Brass, bronze, and copper castings Nonferrous castings Nonferrous forgings Metal cans Metal barrels, drums, and trim N w—l—J—J OOH-”SOMU'IO‘ONONOSW plumbing, and fabricated products Metal sanitary ware Plumbing fixture fittings Heating equipment, except elect. Fabricated structural metal Metal doors, sash, and trim Fabricated plate work Sheet metal work Architectural metal work Prefabricated metal buildings Miscellaneous metal work O-‘O—h-‘OOOOO .062 839 .136 .969 .722 .203 .356 .563 .760 .339 .564 .789 .800 .840 .271 .376 .481 .509 .054 .892 .334 .109 .773 .510 .836 .286 I973 .000 .575 .302 :168 107 TABLE 0 (continued) Industry Number and Name Activity After 15 Cycles 41 42 43 44 45 46 Screw machine products and stampings 41.0100 Screw machine products 41.0201 Automotive stampings 41.0202 Crowns and closures 41.0203 Metal stampings Other fabricated metal products 42.0100 Cutlery 42.0201 Hand and edge tools 42.0202 Hand saws and saw blades 42.0300 Hardware 42.0401 Plating and polishing 42.0402 Metal coating and allied servi 42.0500 Miscellaneous fabricated produ 42.0700 Steel springs, except wire 42.0800 Pipe, valves, and pipe fittings 42.1000 Metal foil and leaf 42.1100 Fabricated metal products Engines and turbines 43.0100 Steam engines 43.0200 Internal combustion engines Farm and garden machinery 44.0001 Farm machinery and equipment 44.0002 Lawn and garden equipment Construction and mining machinery 45.0100 Construction machinery and equ 45.0200 Mining machinery, except oilfi 45.0300 Oilfield machinery .539 .001 .047 .761 atom-I:- .113 .996 .393 .187 .669 .548 .220 .176 .248 .055 .661 CES cts LOO-hOCDNO‘INOOO —I 0.604 3.744 1.085 0.244 .268 .413 .014 ip. eld #0001 Materials handling machinery and equipment 46.0100 Elevators and moving stairways 46.0200 Conveyors and conveying equipment 46.0300 Hoists, cranes, and monorails 46.0400 Industrial trucks and tractors .058 .944 .766 .337 NOOO 108 TABLE 0 (continued) Industry Number and Name Activity After 15 Cycles 47 48 49 50 51 52 Metalworking machinery and equipment .0100 .0200 .0300 .0401 .0402 .0403 Special .0100 .0200 .0300 .0400 .0500 .0600 General .0100 .0200 .0300 .0400 .0500 .0600 .0700 Machine tools, metal cutting Machine tools, metal forming Special dies and tools Power driven hand tools Rolling mill machinery Metalworking machinery industry machinery and equipment Food products machinery Textile machinery Woodworking machinery Paper industries machinery Printing trades machinery Special industry machinery industrial machinery and equipment Pumps and compressors Ball and roller bearings Blowers and fans Industrial patterns Power transmission equipment Industrial furnaces and ovens General industrial machinery Miscellaneous machinery, except electrical 50. 50. 0001 0002 Office, .0101 .0102 .0200 .0300 .0400 Service 52. 52. 0100 0200 Carburetors, pistons, rings, valves Machinery, except electrical computing, and accounting machines Electronic computing equipment Calculating and accounting mach. Typewriters Scales and balances Office machines industry machines Automatic merchandising machines Commercial laundry equipment ..a—a NNOO‘O“ ddU‘l-‘C‘hN COCO-h 0000000 .273 .707 .724 .605 .470 .105 .068 .778 .029 .958 .202 .851 .685 .021 .682 .016 .212 .143 .354 .067 .028 109 TABLE 0 (continued) Industry Number and Name Activ After 15 CyC 13% 52 53 54 55 56 57 Service 52. 52. 52. Electric 0300 0400 0500 .0100 .0200 .0300 .0400 .0500 .0600 .0700 .0800 industry machines Refrigeration and heating equip. Measuring and dispensing pumps Service industry machines transmission and distribution Instruments to measure electricity Transformers Switchgear and switchboard appar. Motors and generators Industrial controls Welding apparatus, electric Carbon and graphite products Electrical industrial apparatus Household appliances Electric 55. 55. 55. .0100 .0200 .0300 .0400 .0500 .0600 .0700 0100 0200 0300 Household cooking equipment Household refrigerators and freez. Household laundry equipment Electric housewares and fans Household vacuum cleaners Sewing machines Household appliances lighting and wiring equipment Electric lamps Lighting fixtures and equipment Wiring devices Radio, TV, and communication equipment 56. 56. 56. 56. 0100 0200 0300 0400 Radio and TV receiving sets Phonograph records and tape Telephone and telegraph apparatus Radio and TV communication equip. Electronic components and accessories 57. 57. 57. 0100 0200 0300 Electron tubes Semiconductors and related devices Electronic components 00‘ ....n N-‘m OOQOOOO o-u—nc-wwooo 00°C #09 .471 .185 .540 .462 .837 .020 .487 .394 .952 .720 .875 .068 .038 .015 .362 .028 .027 .045 .800 .287 .156 .315 .013 .878 .668 .212 .973 .642 110 TABLE 0 (continued) Industry Number and Name Activity After 15 Cycles 58 Miscellaneous electrical machinery 58.0100 Storage batteries 0.231 58.0200 Primary batteries, dry and wet 0.393 58.0300 X-ray apparatus and tubes 0.042 58.0400 Engine electrical equipment 0.745 58.0500 Electrical equipment 1.238 59 Motor vehicles and equipment 59.0100 Truck and bus bodies 0.106 59.0200 Truck trailers 0.072 59.0301 Motor vehicles 2.004 59.0302 Motor vehicle parts and access. 9.922 60 Aircraft and parts 60.0100 Aircraft 0.306 60.0200 Aircraft and missile engines 1.800 60.0400 Aircraft and missile equipment 0.784 61 Other transportation equipment 61.0100 Ship building and repairing 1.311 61.0200 Boat building and repairing 0.070 61.0300 Railroad equipment 6.040 61.0500 Motorcycles, bicycles, and parts 0.504 61.0601 Travel trailers and campers 0.034 61.0602 Mobile homes 0.002 61.0700 Transportation equipment 0.477 62 Professional, scientific instruments 62.0100 Engineering and scientific inst. 1.403 62.0200 Mechanical measuring devices 2.778 62.0300 Automatic temperature controls 0.678 62.0400 Surgical and medical instruments 0.054 62.0500 Surgical appliances and supplies 1.159 62.0600 Dental equipment and supplies 0.007 62.0700 Watches, clocks, and parts 0.652 63 Optical and photographic equipment 63.0100 Optical instruments and lenses 0.065 63.0200 Ophthalmic goods 0.477 63.0300 Photographic equipment and supplies 1.478 111 TABLE 0 (continued) Industry Number and Name 64 Miscellaneous manufacturing .0101 .0102 .0104 .0105 .0200 .0301 .0302 .0400 .0501 .0502 .0503 .0504 .0600 .0701 .0702 .0800 .0900 .1000 .1100 .1200 Jewelry, precious metal Jewelers materials Silverware and plated ware Costume jewelry Musical instruments Games, toys, and children's veh. Dolls Sporting and athletic goods Pens and mechanical pencils Lead pencils and art goods Marking devices Carbon paper and inked ribbons Artificial trees and flowers Buttons Needles, pins, and fasteners Brooms and brushes Hard surface floor coverings Burial caskets and vaults Signs and advertising displays Manufacturing industries TRANSPORTATION, COMMUNICATION, AND UTILITIES 65 66 67 Transportation and warehousing .0100 .0200 .0300 .0400 .0500 .0600 .0700 Railroads and related services Passenger transportation Motor freight transportation Water transportation Air transportation Pipe lines, except natural gas Transportation services Communications, except radio and TV 66.0000 Communications, except radio & TV Radio and TV broadcasting 67.0000 Radio and TV broadcasting Activity After 15 Cycles 18 d—‘OOOOOOOOCOOOOOOOOO .304 .037 .000 .546 .450 .582 .247 .408 .715 112 TABLE 0 (continued) Industry Number and Name Activity After 15 Cycles 68 Electric, gas, water and sanitary services 68.0100 Electric services (utilities) 78.943 68.0200 Gas production and distribution 85.523 68.0300 Water supply and sanitary services 4.940 WHOLESALE AND RETAIL TRADE 69 Wholesale and retail trade 69.0100 Wholesale trade 150.291 69.0200 Retail trade 3.706 SERVICES 73 Business services 73.0100 Miscellaneous business services 73.521 73.0200 Advertising 3.210 73.0300 Miscellaneous professional services 25.583 75 Automobile repair and services 75.0000 Automobile repair and services 13.826 APPENDIX E STEEL MILL —-> TRANSPORTATION —- PETROLEUM REFINING -> CRUDE PETROLEUM AND NATURAL GAS CHAIN This appendix presents the indexes used to illustrate the development of purchasing waves in the steel mill-d» transportation -a> petroleum refining -—>-crude petroleum and natural gas chain. 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