OVERDUE FINES ARE 25¢ PER DAY PER ITEM Return to book drop to remove this checkout from your record. 3 t 1 19:54,; . .c v) *3? \" . j 4"“ 1 © Copyright by _ KENT MICHAEL LANCASTER 1979 ADVERTISING INTENSITY AND MARKET CONCENTRATION WITHIN SELECTED PRODUCT CATEGORIES BY Kent Michael Lancaster A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY College of Communication Arts and Sciences 1979 ABSTRACT ADVERTISING INTENSITY AND MARKET CONCENTRATION WITHIN SELECTED PRODUCT CATEGORIES BY Kent Michael Lancaster Despite the lack of any clear evidence or theory that advertis- ing is either a source or a consequence of market concentration, that uncertainty is not reflected in recent and separate policy proposals and decisions that assume advertising both restricts and stimulates compe- tition. The question therefore deserves further consideration. A review of this literature disclosed: (1) the existence of five contradictory theories regarding the relationships between adver- tising and market concentration as well as between advertising and other aspects of market structure, market conduct and market performance, (2) the lack of any clear evidence as to which theory correctly speci- fies the nature of the relationships between advertising and market con- centration, (3) some clear evidence that increasing returns to adver- tising messages do not exist for single brands, (4) contradictory indirect evidence of scale economies due to industry or firm advertising intensity, and (5) conflicting evidence as to the existence of pecuniary scale economies due to media rate structures, especially network tele- vision advertising rates, which may favor large, multi-product, multi- industry advertisers at the expense of their smaller rivals. Kent Michael Lancaster Several specific shortcomings of previous theories and methods were identified including: (1) use of the advertising-sales ratio, (2) insufficient attention to the relative distribution of advertising expenditures among the firms within an economically relevant market, (3) aggregation of advertising expenditures in a single index which disguises the likely differential impact on consumer behavior of separ- ate advertising media categories and (4) use of small industry samples at high, three and four-digit, IRS and SIC levels of aggregation. This study attempted to overcome these limitations by: (1) pro- viding a theoretical basis for the use of absolute advertising expendi— tures instead-of advertising-sales ratios as the correct measure of advertising intensity, (2) empirically comparing the relationship to sales and to market share of three different measures of advertising, (3) testing directly for technical or pecuniary scale economies in firm and in brand total advertising expenditures and separate advertising media category expenditures, (4) providing a theoretical basis for ex? amining the share of advertising among the brands in an industry and testing these relationships both within and across industries, (5) ex— amining and comparing brand, firm and industry level advertising media expenditures and total advertising expenditures available from syndi- cated trade sources from 1970 through 1975 and (6) examining sales and market share data available from a leading trade journal from 1970 through 1975 for a large number of firms and brands within 19 narrowly defined and economically relevant consumer non-durable product cate- gories. Kent Michael Lancaster Nine specific hypotheses were tested using linear and log linear multiple regression techniques and the following major findings are supported: (1) There are, on average, strong diseconomies of scale in total (2) (3) (4) (5) advertising expenditures at both the firm and the brand levels of aggregation. In the ready-to-eat cereal category, there appears to be slight economies of scale in total advertising expenditures at the firm level of aggregation, but not at the brand level of aggregation. There appear to be economies in total advertising expenditures for more than one brand. That is, diseconomies in advertising are much greater at the brand level of aggregation than they are at the firm level of aggregation. There are strongly diminishing returns to individual advertising media expenditures such as network television, spot television, magazines, network radio, newspaper Sunday supplements and outdoor. There appear to be significant economies to advertising more than one brand using network television or using spot televi- sion. That is, diseconomies in network television advertising or in spot television advertising are often much greater at the brand level of aggregation than they are at the firm level of aggregation. (6) (7) (8) (9) Kent Michael Lancaster The relationship between brand total advertising share and brand market share is positive and significant in each product category. The relationship between brand network television advertising share and brand market share is positive and significant in each product category. In four of 11 product categories for which brand level data are available, network television advertising shares clearly explained significantly more of the variation in brand market share than the share of any other advertising media category. These product categories include Toilet Soaps, Deodorants, Shampoos and Rinses, and Cereals. The potential exists for regression results based on brand market shares and advertising-sales ratios to lead researchers to infer increasing returns or to infer economies of scale in advertising expenditures, when, in fact, there are strongly diminishing returns or diseconomies of scale in advertising. To Marilyn, For raising Lana and Michelle. iii ACKNOWLEDGMENTS It is my pleasure to acknowledge the considerable help of many peOple in the evolution of this research. I am especially indebted to Gordon E. Miracle for first recognizing the value of the original re- search proposal several years ago, for encouraging its development and for generously criticizing the many drafts that followed. I am also indebted to Kenneth D. Boyer for making an economist out of me in just two short years and for tactfully criticizing and guiding the research in several very important and fruitful directions. Martin P. Block not only provided many helpful comments and criticisms along the way, but helped organize the large and cumbersome data base into a highly useful and efficient form. Thomas A. Muth provided several useful suggestions and cordial criticisms on various parts of the manuscript. Richard E. Kagel deserves thanks for taking time away from his own research pur- suits to help analyze advertising-sales ratios in relation to other measures of advertising. Kim B. Rotzoll endured several captive hours discussing and criticizing some important assumptions and the reasoning based on those assumptions. Finally, I am greatly indebted to my wife, Marilyn, for typing several drafts of the manuscript and especially for cheerfully assuming my share of the domestic duties for too many years. iv None of them, of course, are responsible for any deficiencies in the final manuscript. TABLE OF CONTENTS Page LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . vii LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . viii CHAPTER I: INTRODUCTION . . . . . . . . . . . . . . . . . . . . . 1 CHAPTER II: REVIEW OF THE LITERATURE . . . . . .». . . . . . . . 7 CHAPTER III: RESEARCH HYPOTHESES . . . . . . . . . . . . . . . . 59 CHAPTER IV: METHODOLOGY . . . . . . . . . . . . . . . . . . . . . 67 CHAPTER V: EMPIRICAL RESULTS . . . . . . . . . . . . . . . . . . 79 CHAPTER VI: LIMITATIONS . . . . . . . . . . . . . . . . . . . . . 116 CHAPTER VII: SUMMARY, CONCLUSIONS AND IMPLICATIONS . . . . . . . 121 APPENDIX A: A SURVEY OF CONCENTRATION-ADVERTISING INTENSITY STUDIES . . . . . . . . . . . . . . . . 134 APPENDIX B: ADVERTISING EXPENDITURE DATA ’ CODEBOOK O O O O O O O I O O O O O O O O O O 0 O O 14 1 APPENDIX C: SALES, MARKET SHARES AND ADVERTISING EXPENDITURES FOR FIRMS AND BRANDS IN 19 CONSUMER NON-DURABLE GOODS CATEGORI ES 0 O C C C O O C O C O O I C O O C l 4 3 BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 vi Table II. III. IV. VI. VII. ’ VIII. IX. XI. XII. LIST OF TABLES Title Page PREDICTIONS OF INDUSTRY CONCENTRATION ON THE BASIS OF THE DISTRIBUTION OF ADVERTISING AMONG THE FIRMS IN THE INDUSTRY . . . . . . . . . . . . . . . . . 45 U.S. ADVERTISING EXPENDITURES IN 1965 AND IN 1975 . . . . . S3 INDUSTRY SAMPLE BREAKDOWN . . . . . . . . .-. . . . . . . . 68 BUDWEISER-BEER INDUSTRY ADVERTISING SHARES: AN EWLE O O O O I O O O O O O I O C I O I O O O O O O 73 CORRELATION COEFFICIENTS BETWEEN ADVERTISING-SALES RATIOS AND ADVERTISING EXPENDITURES . . . . . . . . . . 80 REGRESSIONS OF FIRM OR BRAND SALES (LOG) ON FIRM OR BRAND ADVERTISING EXPENDITURES (LOG) FOR 19 PRODUCT CATEGORIES, 1970-1975 . . . . . . . . . . . . . 86 REGRESSIONS OF BRAND MARKET SHARES ON BRAND ADVERTISING SHARES (SIX MEDIA) FOR 11 PRODUCT CATEGORIES, 197w1975 O O O O I O O O O C O O O I O O O O O O O O O 99 RESULTS OF TESTS FOR EQUALITY OR REGRESSION COEFFICIENTS WITHIN PRODUCT CATEGORIES . . . . . . . . . . . . . . . 104 REGRESSIONS OF BRAND MARKET SHARES ON BRAND ADVERTISING SHARES (TWO MEDIA) FOR 11 PRODUCT CATEGORIES, 19 70-1975 0 o o o o o o o o o o o o o o o o o o o o o o 107 RESULTS OF TESTS FOR EQUALITY OF REGRESSION COEFFICIENTS WITHIN PRODUCT CATEGORIES . . . . . . . . . . . . . . . 108 RESULTS OF TESTS COMPARING THE RELATIVE EFFICIENCY OF THE TWO-MEDIA SHARE MODEL WITH THE SIX-MEDIA SW MODE 0 I I O C O O O O O O O O C O C O O O O O O 110 REGRESSIONS OF BRAND MARKET SHARES ON BRAND ADVERTISING- SALES RATIOS (SIX MEDIA) FOR TEN PRODUCT CATEGORIES, 1970-1975 . . . . . . . . . . . . . . . . . . . . . . . 112 vii LIST OF FIGURES Title Page Figure I. Effects of Advertising on Competitionr-Advertising Decreases Competition by Changing Consumer Tastes . . . . . . . . . . 11 II. Effects of Advertising on Competition-Advertising Increases Competition by Providing Consumers with Information . . . . 14 III. Effects of Competition on Advertising-Advertising Intensity Depends on Market Structure and on Non-Price Collusion . . 16 IV. Several Possible Relationships Between Advertising and Competition . . . . . . . . . . . . . . . . . . . . . . 49 viii CHAPTER I INTRODUCTION Economists have been debating the merits and the demerits of advertising since the turn of this century. And the debate has intensi- fied within the past 25 years. On the positive side economists have argued that advertising: informs consumers of available goods, compara- tive prices, relative product quality and where products can be ob- tained; provides an incentive for heavy advertisers to maintain high product quality; permits the realization of production scale economies; allows innovators to tap large markets rapidly; subsidizes a variety of mass communications media; mitigates business cycles and stabilizes the economy; displays high aesthetic quality and urges product images that ’ are as valuable to consumers as physical product attributes.1 But the catalog of suspected social costs of advertising looms much larger by comparison. Here economists have argued that advertis- ing: wastes resources; creates false wants; urges consumers to buy products of little individual or social value; gives rise to industries characterized by only a few large sellers; deters the entry of new firms; expenditures of the few large firms within an industry cancel each other out; raises prices to consumers; allows heavy advertisers to 1See for example, Fred M. Scherer, Industrial Market Structure and Economic Performance (Chicago: Rand McNally, 1970), Chapter 14. 2 reap monOpoly profits and accentuates business cycles.2 This study addresses itself to the relationships between adver- tising and the level of competition within an industry. Particularly, it empirically examines the question of whether advertising within con- sumer non-durable product categories leads to market concentration (the share of an economically relevant market held by a few top firms in the market). There are some who argue that market concentration, a proxy for monopoly power, does not directly affect economic performance.3 From this perspective the question of advertising's role in th9131§§_9fi1- market concentration is 992;, But the traditional view has been that industrial concentration poses a serious threat to consumer welfare. Since advertising may be a contributing factor in the rise of industrial concentration it too may threaten consumer welfare. Accordingly, ap- proximately 25 empirical studies concerning the relationships between advertising and market concentration have been published in as many , years. Yet still others have argued that the issue has been blown far out of proportion to its merit and that more substantial issues, such as inflation, unemployment, energy and the environment, should occupy economists' limited time.4 2Ibid. 3See for example, Harold Demsetz, The Market Concentration Doctrine (washington, D.C.: American Enterprise Institute, 1973), and John S. McGee, In Defense of Industrial Concentration (New York: Praeger, 1971). 4See David G. Tuerck's "Forward," in Stanley Ornstein, Industrial Market Structure and Advertising Intensity (Washington, D.C.: American Enterprise Institute for Public Policy Research, 1977). 3 Nevertheless, the issue has become something more than a mere academic exercise. The contradictory views of economists now permeate a number of past and present public policy proposals and public policy decisions despite the lack of agreement on a unified theory of adver- tising's economic impact, the lack of a sufficiently adequate and com- plete data base and the lack of consistent substantive conclusions upon which to base such policy proposals and policy decisions. For example, in 1967 and in 1968 the Federal Trade Commission successfully attacked product extension mergers in FTC v. Procter and Gamble Co.5 and in General Foods Cgrporation v. FTC6 in part because the acquired firms would be able to lower their advertising costs substan- tially since media rate structures, especially network television rate structures, appeared to favor large, multi-product, multi-industry ad- vertisers at the expense of their smaller actual and potential rivals. And a 1968 White House task force on antitrust policy proposed a Con- centrated Industries Act that suggested that restrictions on advertising . expenditures might be usedéi) In 1972 the Federal Trade Commission charged that heavy adver- tising in the concentrated ready-to-eat cereal market by the Kellogg Company, General Mills, Inc., General Foods Corporation and the Quaker 5386 U.S. 568 (1967). 6 (1968). 7U.S. White House Task Force on Antitrust Policy. The Report of 386 F. 2d 936 (3d. Cir. 1967), cert. denied, 391 U.S. 919 the White House Task Force on Antitrust Policy, July 5, 1968. (In U.S. Congress. Congressional record. (Daily ed.) v. 115 (1969) no. 87, p. 85642-85659). 4 Oats Company results in high entry barriers and allows the major cereal makers to maintain a shared monOpoly.8 In 1976 an FTC administrative law judge ruled that Borden's pro- motional efforts for ReaLemon resulted in the brand's dominance in the reconstituted lemon juice market in violation of the FTC Act.9 The H. J. Heinz Company has charged Campbell Soup Company with predatory advertising leading to monopoly.10 On the other hand, a positive view of advertising's economic effects has also been exhibited by the Federal Trade Commission. In 1976 the FTC proposed a trade regulation rule that would revoke bans on prescription eye-glass advertising, that are imposed by many states, because such bans restrict the flow of price information to consumers, increase search costs and increase eye-glass prices.11 And in 1978 the Commission proposed a similar trade regulation rule that would ban the advertising restrictions of the American Medical Association because such restrictions cause substantial injury to the public by depriving consumers of the free flow of information concerning the availability of health care services.12 The theories, research and conclusions of some economists have even found their way into the reasoning and decisions of state supreme 8Docket No. 8883, Federal Trade Commission, April 1972; pp. 7-9. 9Borden, Inc., Case, Docket No. 8978, Federal Trade Commission, August 1976, p. 67. 10H. J. Heinz Company v. Campbell Soup Company, Civil Action No. 76-1306 (W. D. Pa. 1967), p. 10 of plaintiff's complaint. 11"Advertising of Ophthalmic Goods and Services," Federal Re is- ter, Vol. 41, January 16, 1976, p. 2399; 12See, "FTC judge: Doctors Should Be Free To Advertise," Adver- tising Age (December 4, 1978) p. 4. 5 courts and District Courts in connection with First Amendment cases that attempt to remove state and/or professional association restrictions on the advertising of prescription drugs, eyeglasses, lawyer fees and abortion services.13 The available evidence supports a number of conflicting points of view on the relationships between advertising and market concentra- tion. For example, some researchers have found a significant positive 14 relationship between advertising and market concentration, while others have found a slightly negative relationship}5 Other researchers have found an upward trend in market concentration among industries with high television advertising intensities,l6 while others have found no 13See for example, Bigelow v. Virginia, 421 U.S. 809 (1975), Patterson Drug Co. v. Kingery, 305 F. Supp. 821 (W D Va. 1969), Terminal-Hudson Electronics v. Department of Consumer Affairs, 407 F. Supp. 1075, Virginia State Board of Pharmacy et al. v. Virginia Citi- zens Consumer Council, Inc. et al., 44 U.S.L.W. 4686, (also see Brief of Appellants, Brief of Appellees and Brief for Association of National Advertisers, Inc. Amicus Curia for S. Ct. Dkt., No. 74-895), John R. Bates and Van O'Steen v. State Bar of Arizona (97 Sup. Ct. 2691) and Linmark Associates, Inc. v. Township of Willingboro (97 Sup. Ct. 1641). 14See for example, H. M. Mann, J. A. Henning and James W. Meehan, Jr., "Advertising and Competition: An Empirical Investigation," Journal of Industrial Economics 16 (November 1967): 34—5. PISSee for example, Lester G. Telser, "Advertising and Competi- tion," Journal of Political Economy 72 (December 1964): 532-562. 16See for example, John M. Blair, Economic Concentration, Structure, Behavior and Public Policy (New York: Harcourt Brace Jovanovich, Inc., 1972), pp. 308-334. Also see, Michael E. Porter, "Interbrand Choice, Media Mix and Market Performance," American Economic Review 66: 2 (May 1976): 398-406. 6 economies of scale or no increasing returns favoring large network television advertisers and have therefore argued that high levels of market concentration in these industries is due to factors other than network television advertising.17 This study will present and test empirically a new paradigm which highlights underlying relationships between advertising and market concentration in an attempt to explain such seemingly conflicting con- clusions. New data on brand level and firm level advertising expendi- tures in six separate advertising media categories and new data on brand level and firm level sales will be analyzed within 19 narrowly defined and economically relevant consumer, nondurable product cate- gories. 17See for example, David M. Blank, "Television Advertising: The Great Discount Illusion or Tonypandy Revisited," Journal of Business 41 (January 1968): 10-38. Also see, David M. Blank, "Tonypandy Once Again," Journal of Business 42 (January 1969): 104-112, James M. Fergu- son, "Anticompetitive Effects of the FTC's Attack on Product Extension Mergers," St. John's Law Review 44 (Spring 1970): 392-415, and John L. Peterman, "The Clorox Case and Television Rate Structure," Journal of Law and Economics 11 (October 1968): 376-389 and 404-412. CHAPTER II REVIEW OF THE LITERATURE Five Contradictory Theories_ Advertising has been positioned within the structure-conduct- performance model in five different and sometimes contradictory ways. One theory suggests that advertising leads to anticompetitive levels of sales and of profits for the few top firms in an industry by changing consumer tastes as follows.18 63 Companies undertake promotional efforts, such as personal sell- ing, sales promotion, publicity, public relations and advertis- ing when they can efficiently influence consumers, either objectively or subjectively, as to the superior ability of their products to satisfy consumer needs and wants. (a) The Optimum promotional mix for the firm will depend on its relative cost efficiency given the nature of the product, the nature of the relevant consumer behavior associated with the product, the method of distribution, relative price, the 18See for example, Nicholas Kaldor, "The Economic Aspects of Advertising," Review of Economic Studies 18 (1949-1950): 1-27, Joe S. Bain, Barriers to New Competition (Cambridge, Mass.: Harvard University Press, 1956), and Michael E. Porter, "Interbrand Choice, Media Mix and Market Performance," American Economic Review 66 (May 1976): 398-406. 8 nature of competition, the presence of uncontrollable en- vironmental factors, and so on. (b) If advertising can be efficiently employed, the optimum ad- vertising media mix will depend on the marginal productivity of each form of advertising. That is, the media mix chosen should be the most cost efficient given the nature, number, location, media usage habits, information needs and pur- chase habits of the consumer. 2. Information causes consumers to perceive objective or subjective differences among products and helps them to choose among al- ternatives. (a) Buyers actively or passively seek additional information when they perceive the cost of doing so will be outweighed by the benefits they perceive to be gained from an informed purchase decision. (b) The sources of information available to the consumer include previous experience with various brands, advice from friends, advice from relatives, advice from salesmen, neutral technical literature such as Consumers Bulletin and Consumers Report and advertising messages in any of the various mass media. (c) Advertising facilitates consumer choice when the perceived cost of viewing advertising messages is outweighted by the perceived benefits to be gained from an informed purchase decision. 3. Consumer choices lead to brand loyalty when products perform as expected. 4. 9 Durable brand loyalties to existing brands raises the cost of entry because newcomers have to spend relatively more on ad- vertising than their established rivals to overcome these brand loyalties. Increasing returns to advertising messages with respect to facilitating consumer choice and reinforcing brand loyalties increases minimum efficient scale and can lead to increased market concentration if minimum efficient scale grows faster than industry demand. Increasing returns to advertising messages also increase entry barriers since firms operating at less than minimum efficient scale face an absolute cost disadvantage. Imperfections in the supply of advertising media time and space may also increase minimum efficient scale, hence increase market concentration, and create and maintain additional entry barriers, in varying degrees for each media type and product category, to the extent that each provides for: (a) Advertising media volume discounts that create pecuniary scale economies favoring large, multi-product, multi- industry advertisers, and (b) Indivisibilities in the supply of advertising time and space which require a high absolute advertising outlay threshold for a single advertising message and especially for minimum market coverage. Advertising's anticompetitive influences are reinforced by im- perfections in the capital markets which favor large established advertisers at the expense of their newer and smaller rivals. 10 9. Price elasticity of demand is decreased since there are fewer actual and potential rivals. 10. Reduced price elasticity leads to higher prices with little incentive to cut prices since market concentration can lead to collusion to reduce price competition to the joint profit maxi- mizing level. 11. Reduced price competition in the presence of entry barriers permits companies to more closely approach higher prices and lower outputs which consistently maximize profits. 12. Excessively high profits can be paid to owners or invested in additional advertising to perpetuate market concentration and entry barriers. This causal linkage will be referred to as the "change-of-taste" theory of advertising impact and it is depicted in Figure I below. The change-of-taste theory reasons that advertising results in restricted output, high prices, inefficient allocation of resources, long run ex- cessive profits for monopolists and oligopolists, distortions in the distribution of wealth and reduced consumer welfare. But an opposite view reasons that advertising, by providing con- sumers with product information, will result in increased competition as follows.19 l98ee for example, George J. Stigler, "The Economics of Infor- mation," Journal of Political Economy 69 (June 1961): 213-225, Phillip Nelson, "Information and Consumer Behavior," Journal of Political Econ- gmy_78 (March/April 1970): 311-329, and Phillip Nelson, "The Economic Consequences of Advertising," Journal of Business 48 (April 1975): 213- 241. 11 V ADVERTISING EXPENDITURES L 1 BRAND LOYALTY SCALE ECONOMIES DUE TO ADVERTISING 1 L ' 1 SMALL FIRM COST DISADVANTAGE MES INCREASED 1 1 ENTRY BARRIERS INCREASED CONCENTRATION INCREASED 1 1 FEWER POTENTIAL RIVALS FEWER ACTUAL RIVALS 1 1 PRICE ELASTICITY OF DEMAND DECREASED 1 HIGHER PRICES, LITTLE INCENTIVE TO CUT PRICE 1 MONOPOLY RETURNS Figure I. Effects of Advertising on Competition-Advertising Decreases Competition by Changing Consumer Tastes 12 1. Brand advertising provides information about products, including the availability of brands, relative prices and relative product quality. 2. Since price elasticity of demand is a positive function of known, alternatives, information provided by brand advertising in- creases consumer knowledge about available alternatives and in- creases price elasticity of demand. 3. Increased consumer knowledge reduces consumer search costs both individually and in the aggregate. 4. Reduced search costs increase entry by allowing previously un- known brands to gain rapid market acceptance and thereby in- crease consumer alternatives and product variety. Whether market concentration would increase or decrease as a result of product information provided by advertising is indeterminant however. Nelson, the chief proponent of the advertising-as-information 20 On one hand, point of view, allowed for two opposite possibilities. where consumers are guided by advertising in contrast to information based on past or present sales, a new entrant can capture a share of the market through advertising, which suggests to Nelson a possible inverse relationship between advertising and concentration. Alternatively, Nelson argues that the gains from advertising are greater for the most efficient firms who grow large and thus have the greatest incentive to advertise. Consequently, large firms will prosper at the expense of their smaller rivals--advertising will increase concentration. Since 20Phillip Nelson, "The Economic Consequences of Advertising," Journal of Business 48 (April 1975): 232. 13 both forces are offsetting, Nelson concludes that the relationship be- tween advertising and market concentration is indeterminant a priori. Nelson's view will be referred to as the "information" theory of advertising impact and it is illustrated in Figure II below. A third view also suggests that advertising intensity is pri- marily a function of market structure and not the reverse.21 This view assumes that the firm's profit maximizing advertising-to-sales ratio is given by the firm's advertising elasticity of demand divided by the absolute value of the firm's price elasticity of demand. Thus, from this perspective four outcomes are possible. 1. Higher concentration accompanied by less elastic demands, which approach the industry elasticity of demand as concentration increases, can lead to greater advertising. 2. Higher concentration accompanied by less elastic demands and tacit or explicit collusion to restrict non-price competition can lead to lower advertising. 3. Higher concentration accompanied by less elastic demands and higher rates of return caused by factors other than advertising can lead to greater advertising. 4. Advertising may be greater in more concentrated markets since non-price competition is preferred in oligopolistic markets even in the absence of scale economies. 21See for example Douglas F. Greer, "Advertising and Market Concentration," Southern Economic Journal 39 (July 1971): 19-32, John Cable, "Market Structure, Advertising Policy, and Intermarket Differ- ences in Advertising Intensity," Market Structure and Corporate Behavior, ed. Keith Cowling (London: Gray-Mills Publishing, Ltd., 1972), pp. 105-124, and C. J. Sutton, "Advertising, Concentration, and Competition," Economic Journal 84 (March 1974): 56-69. 14 QUALITY VARIATION AMONG BRANDS 1 CONSUMERS UNAWARE OF ALTERNATIVES 1 DEMAND CURVES INELASTIC BRANDS POSSESS MONOPOLY POWER L AwVERTISING INCREASES KNOWN ALTERNATIVES 1 ENTRY INCREASED 1 DEMAND CURVES BECOME MORE ELASTIC 1 BRAND MONOPOLY POWER OVER PRICE REDUCED Figure 11. Effects of Advertising on Competition--Advertising Increases Competition by Providing Consumers with Information 11 l llllfii .. .. I.I'.....}. II 15 This reasoning will be referred to as the "structure-collusion" theory of advertising as a consequence of other factors and is depicted in Figure III below. A fourth recently proposed and tested view attempted to explain a positive relationship between advertising and market concentration in the absence of support for the traditional arguments of advertising 22 scale economies and brand loyalty. On one hand it is argued that: 1. Advertising, by providing information, may lead to shifts in demand and to changes in the elasticity of demand. Increased demand may allow firms to exploit economies of large scale production and distribution leading to reductions in cost per unit which exceed increased advertising costs per unit. If minimum efficient scale with respect to manufacturing and distribution increases faster over time than market size, in- creased market concentration will result. Such newly enlarged firms will maintain high levels of adver- tising intensity. 0n the other hand, it may be that an observed positive relation- ship between advertising and market concentration is simply a spurious one because: 1. Large firms may have larger advertising intensity simply because they serve larger, more diversified markets, have higher buyer turnover and have a higher rate of new product introductions than smaller firms, or Large firms grow large because they offer higher quality per 22See Stanley I. Ornstein, Industrial Concentration and Adver- tisingilntensity. 16 NON-ADVERTISING FACTORS 1 1:— HIGHER CONCENTRATION 1 g FEWER ACTUAL RIVALS LESS PRICE ELASTIC DEMANDS HIGHER RATES OF RETURN 1 COLLUSION T0 RESTRICT ADVERTISING? LOWER ADVERTISING HIGHER ADVERTISING Figure III. Effects of Competition on Advertising--Advertising Intensity Depends on Market Structure and on Non-Price Collusion 17 unit of price leading to a high incidence of repeat sales. Holding price constant, this makes advertising more productive for high quality producers who also happen to be large pro- ducers. For simplicity, this essentially non-causal reasoning will be referred to as the "spurious association" theory of the relationship between advertising and market concentration. A fifth and final view suggests that advertising intensity and market concentration interact and are jointly determined by other fac- tors such as: (l) the margin between price and marginal cost, (2) by competitors' response to a firm's advertising strategy. (3) the adver- tising elasticity of demand facing industry members, (4) the deprecia- tion rate of advertising capital, (5) the interest rate, (6) the proximity of the product to sensitive psychological drives, (7) product complexity, (8) product testability, (9) the number and the turnover rate of buyers, (10) the dynamic character of the market, (11) the rate of new product introductions, (12) the degree of satisfaction with present goods, and (13) various consumer characteristics. The pro- ponents of this view argue that it is therefore inappropriate to test for two-way causality with single stage least squares regression equa- tions in that such tests are biased.23 However, any bias may or may not be small. 23See Douglas P. Greer, "Advertising and Market Concentration," p. 32, Allyn Strickland and Leonard Weiss, "Advertising, Concentration, and Price-Cost Margins," Journal of Political Economy 84 (October 1976): 1109-1121, and Richard Schmalensee, 0n the Economics of Advertising (Amsterdam: North-Holland, 1972), pp. 222-226. 18 For clarity, this non-causal reasoning will be referred to as the "interaction" theory of the relationship between advertising and market concentration. Empirical Evidence Several scholars have carefully summarized and criticized the many studies which attempt to empirically test the various hypothesized relationships between advertising and market concentration suggested by each of the above frameworks.24 Therefore, it is not necessary to cover all of that ground again here. For completeness, Appendix A contains a detailed list of each study dealing with advertising and market concen- tration which has been published since 1964. The appendix, compiled 25 It chrono- chiefly by Ornstein (1977), has been expanded and updated. logically names the author(s) of each study, it describes the sample and the period of years that each sample covers, it identifies, opera- tionally, the nature of the dependent and the independent variables, it describes the predicted functional form of the relationship between the two variables and it reports the statistical significance of the esti- mated relationships. Ornstein's analysis of this advertising/market concentration literature led him to make the following unsettling summary of the com- bined value of previous research. 24See for example, Stanley 1. Ornstein, Industrial Concentration and Advertising Intensity, and James M. Ferguson, Advertising_and Com- petition; Theory, Measurement, Fact (Cambridge, Mass.: Ballinger Pub- lishing Company, 1975), Chapter 5. 25Stanley Ornstein, Industrial Concentration and Advertising Intensity, pp. 68-73. 19 The meaning of the investigations summarized here is uncertain and, as a result, makes them a poor guide toward public policy on advertising as a source of monopoly power. The theories are contradictory, suggesting positive, negative, and no relation- ship. The empirical evidence is conflicting and does not clarify the contradictory theories. A survey of . . . previous studies . . . shows that the studies obtain significant or in- significant results with approximately equal frequency. There seems to be little clear support for the notion that advertising is either a source or a consequence of monopoly power. General agreement is possible, however, on the lack of any clear evidence or theory. Those who have argued that advertising leads to market concen- tration have often assumed increasing returns to advertising expendi- tures. However, the literature provides no clear or strong evidence that increasing returns to advertising exist. Quite the contrary. The available evidence suggests diminishing returns to brand advertising at every level. But there are few direct tests of increasing returns to advertising. Most researchers simply check to see if a positive rela- tionship exists between advertising intensity and brand sales, market concentration or firm profits, and then argue, in the presence of a positive association, that there exist possible increasing returns to advertising. On the other hand, the lack of an association between ad- vertising intensity and measures of market structure or measures of market performance can often be explained for several reasons other than the level of advertising intensity among firms in an industry. Before examining the evidence on returns to advertising more carefully, it is important to clarify what is meant by the concepts "returns to advertising" and "economies of scale in advertising," and to distinguish these terms from two other related but distinct con- cepts: "returns to scale" and "economies of scale." 26Ibid., pp. 37-38. 20 "Returns to scale" refers to the relationship between the quan- tity of physical outputs and the quantity of physical inputs when all inputs are increased in the same proportion. Thus, if doubling the quantity of all physical inputs more than doubles the quantity of physical output, there are increasing returns to scale. If doubling the quantity of all physical inputs exactly doubles the quantity of physical output, there are constant returns to scale. Finally, if doubling the quantity of all physical inputs less than doubles the quantity of physical outputs, then decreasing returns to scale exist.27 ' on the other hand, refers to the relation- "Economies of scale,’ ship between average unit cost and the scale of output such that aver- age unit production costs decrease as the scale of operation increases over some range of output. There are two chief sources of scale econo- mies: technical and pecuniary. Increasing returns to scale, defined above, are the only technical source for scale economies. Thus, with fixed input prices combined with increasing returns to scale, doubling an outlay on inputs at fixed prices will double the quantity of inputs but will more than double output. Consequently, the average outlay on inputs per unit of output will be less for the larger output.28 Economies of scale may also be derived from non-technical or pecuniary sources, such as quantity discounts, which lower the average cost of inputs as input outlays are increased. 27For a detailed discussion of returns to scale see Kelvin Lancaster, Introduction to Modern Microeconomics (Chicago: Rand McNally, 1974), pp. 92-98. 28For a detailed treatment of economies of scale see Kelvin Lancaster, Introduction to Medern Microeconomies, pp. 108-111. 21 It is technically incorrect to refer to increasing returns to one factor input, such as advertising, as economies of scale. Neverthe- less, the term "increasing returns to advertising" is often used inter- changeably with the term "economies of scale in advertising" to mean "decreasing average advertising cost per dollar of sales with increases in total advertising expenditures, holding the quantities of other in- puts constant."29 Such interchanging and, perhaps, incorrect use of terminology is a constant source of confusion in the literature. The confusion is compounded further by "a blurred distinction between (1) the marginal productivity of different physical quantities of adver- tising, e.g., the sales produced by a half-page versus a full-page ad- vertisement; and (2) the marginal productivity of different amounts of money spent for advertising, e.g., the sales produced by the first $1,000 spent for advertising versus the second $1,000."30 It is not the intent here to attempt to correct inappropriate use of terms that may exist in the literature. Rather, the term "in- creasing returns to advertising" will be used here to mean increasing returns either in terms of sales or in terms of intermediate consumer response, derived from a threshold advertising effect, the word of mouth flow of information due to advertising, increasing the number of advertising messages, increasing the time length or page size of adver- tising messages, increasing the effectiveness of advertising message content, increasing the size and expertise of the advertising message production process, etc. 29James M. Ferguson, Advertising and Competition; Theory, Measurement, Fact, p. 9. 30Julian L. Simon, Issues in the Economics of Advertising (Urbana: University of Illinois Press, 1970), p. 3. 22 On the other hand, "economies of scale in advertising" will be used here to refer to decreasing average advertising cost per dollar or unit of sale with increases in total sales. These economies can be derived, holding constant input prices, from any of the technical sources of increasing returns to advertising mentioned above, or from pecuniary sources, derived from decreasing input prices, such as adver- tising media volume discounts. There are several possible sources of increasing returns to advertising messages and several possible sources of economies of scale in advertising. For example, increasing returns to advertising messages may result fromi. l. A threshold effect wherein buyers remain unaware of an adver- tised brand until they have received a minimum level of im- pressions, 2. The word-of-mouth flow of information about brands, which is stimulated by advertising, may cause the proportion of buyers to increase at an increasing rate especially for those products with large numbers of potential users, 3. Increasing the frequency of advertising messages per potential prospect, 4. Increasing the time length or page size of advertising messages, 5. Increasing the effectiveness of advertising message content, 6. Increasing the size of the advertising message production process or increasing the acquisition of advertising production know-how, and 23 7. Store distribution induced by advertising.31 Technical economies of scale in advertising may result from any of the potential sources of increasing returns to advertising messages listed above. In addition, pecuniary economies of scale in advertising may also result from: 1. Media rates increasing less than proportionately with audience size, 2. Indivisibilities in the supply of advertising time and space which require a high absolute advertising outlay threshold for a single advertising message and especially for minimum market coverage. 3. Joint advertising of several products, and 4. Joint use of a family brand for several products.32 Simon (1970) investigated returns to brand advertising messages by examining those available studies which test the relationship direct- ly. Available evidence on proprietary drugs, cigarettes, liquor and milk revealed the proliferation of brands, suggesting diminishing re- turns to brand advertising. Non-sales consumer response data resulting from changing advertisement size or commercial lengths also suggest diminishing returns throughout. Direct mail reSponse evidence indicates monotonically diminishing returns to additional advertising investment. Therefore, Simon concluded that "There is not one single piece of strong evidence to support the belief that increasing returns exist in advertising. . . . Threshold effects and increasing returns to 31Ibid., Chapter 1, and Ferguson, Advertising and Competition: Theory Measurement, Fact, Chapter 4. 32Ibid. 24 repetition and size constitute a monstrous myth. . . ."33 However, Simon acknowledged that important economies may still exist for the firm using common brand names for many products, taking advantage of media volume discounts, achieving extensive retail distribution and building advertising expertise. Several indirect tests of returns to advertising have also been conducted which use the industry advertising-sales ratio as an inde- pendent variable and either optimum firm size or firm rates of return as dependent variables. Both Ferguson (1974) and Simon (1970) summarize the results of these separate indirect tests of returns to advertis- ing.34 The test results are contradictory and the discussions of their shortcomings are difficult. Nevertheless, it would be safe to charac- terize the indirect evidence on returns to advertising as inconclusive. Simon suggests that the ambiguity is due to the measure of advertising intensity employed in these studies. Simon is highly critical of the use of the advertising-sales ratio and he concluded that the index was "not competent to serve as the basis for any general investigation of the economics of advertising," and, taken by itself, . would almost surely lead a researcher to the wrong conclusion."35 Even in the absence of increasing returns to advertising mes- sages, several researchers have argued that economies of large scale investment in network television advertising schedules by large 33Simon, Issues in the Economics of Advertising, pp. 21-22. 34The interested reader should consult Simon, Issues in the Economics of Advertising, Appendix B, and Ferguson, Advertising and Competition; Theory, Measurement, Fact, Chapter 4. 35 Simon, Ibid., p. 310. 25 multi-product, multi-industry advertisers have an anticompetitive ef- fect. A substantial literature on this subject has accumulated over the years ever since the U.S. Senate conducted hearings in 1966 on the anti- competitive effects of network television advertising.36 National advertisers can purchase television advertising time for commercial announcements either from the individual stations, known as national spot sales, or from the networks, known as network sales. When purchases are made on the national spot basis the adver- tiser can place his announcements on any station desired, whereas net- work purchases require that the announcements be placed on a network affiliated station. The number of possible network stations, however, can vary, depending on the particular transaction. The rates are generally based on what, through various media measurement services like Nielson and Arbitron, the size of the audience is, as indicated by ratings and estimates of the demographic qualities of the audience. Network television advertising rates are complex and vary ac- cording to the audience size, which is usually reflected in the: (1) length of the announcement (e.g., 10, 20, 30, 40 or 60 seconds), (2) time period during the day in which the announcement is run (e.g., prime time, fringe times--ear1y and late, day time, etc.), (3) day of the week in which the announcement is run, (4) program during or adjacent to which the announcement is run (e.g., sports, news, "All in the Family," 36U.S. Senate Committee on the Judiciary, "Hearings on Possible Anticompetitive Effects of the Sale of Network TV Advertising," 89th Congress, 2nd Session, Senate Subcommittee on Antitrust and Monopoly, 1966, parts 1 and 2. 26 etc.), (5) season during which the announcement is run, (6) quantity of announcements purchased, and (7) the number of affiliates purchased. Although each of the three networks have rate cards, their rates are ultimately arrived at through negotiation. This process entails chiselling, wheeling and dealing and so on on the part of the network, to obtain the highest price possible, while the advertiser attempts to secure the lowest price possible. Negotiation can range from a single buy to the entire rate structure including demographic and geographic splits. The more flexible the schedule, the more negotiation will likely take place. Negotiations for prime time advertising favors the networks and is usually sold out to the highest bidder. Fringe times, on the other hand, are much more susceptible to negotiation. Networks may even call advertisers to get rid of unsold time at extremely low rates in some cases.37 The ultimate price an advertiser pays for a particular package is difficult to determine. Because rates are negotiated, no basis for comparison exists. And even when the facts are known, it is difficult to compare because the packages of scattered minutes of advertising differ significantly in quality. Furthermore, the value of a package will vary from one advertiser to another. The true test of comparative cost is per prospect. But, even though network television advertising rates are nego- tiated, Peterman (1968) argued that "such price adjustments would modify the details of the structure but would not be likely to affect the 37Margot Teleki, "The Negotiating Game: Rate Cut or Straight," Media Scope, October 1969, p. 42. 27 general relationships between different parts of the rate structure."38 One of the most all-encompassing articles dealing with possible discrimination in the pricing of network television advertising was written by Blake and Blum (1965). They charged that the "discriminatory and tying effects of network rate structures are masked by their own intricacy and by the complexity of the television industry."39 Blake and Blum claimed that the anticompetitive effects of rate discounts affected competition within the network television industry, affected the media categories most directly competitive with network television, including spot advertising and independent broadcasting, affected independent program producers and indirectly provided artifi- cial incentives for product and market extension mergers.40 v/ The large volume discounts were said to contribute to a concen- tration of budgets in one network to reduce the average cost per unit purchased. Further, the structure tended to penalize switching from one network to another by increasing the average cost per unit. Blake and Blum contended that this was possible because of the highly progressive network discount structure. Further, these discounts allegedly took over at a point where additional expenditures in other media such as spot-TV, independent stations, radio, newspapers, magazines and outdoor advertising might have been just as effective. 38John L. Peterman, "The Structure of National Time Rates in the Television Broadcasting Industry," p. 87. 39H. M. Blake and Jack A. Blum, "Network Television Rate Prac- tices; A Case Study in the Failure of Social Control of Price Discrimi- nation," The Yale Law Journal 74: 8 (July 1965): 396. 4oIbid., p. 419. 28 Blake and Blum pointed to the post World War II wave of mergers as an indirect effect of network rate policies. They cited two classic cases as examples, including Procter and Gamble's attempted acquisition of Clorox and General Foods' attempted acquisition of 8.0.8. In both cases the acquired and acquiring firms were distributors of consumer goods whose marketing strategies required large ad- vertising outlays. And in each a substantial incentive for merger was the volume discount rate structure of advertising media generally and, in particular, volume discounts in the sale of net- work television time. These two cases illustrate the class rela- tion of the discount rate structure of advertising media in general, and more particularly, the discounts available to users of network television, to merger patterns in consumer goods industries. However, Blake and Blum admitted that these discounts were not the sole reason for merger, but rather, an artificial incentive for product and market extension mergers. An unsigned student note in the Columbia Law Review (1965) es- sentially covered the same ground as the Blake and Blum article and was included in the record of the Hart Senate Subcommittee hearings on the anticompetitive affects of network television advertising (1966).42 The note argued that: When . . . the discounts, though more sophisticated and complex than ordinary quantity discounts, are found to reward high volume purchasers with preferential treatment, they must be considered essentially quantitative in nature. When such discounts, moreover, are found to injure competition among both the networks and the advertisers, as well as erecting barriers to new entrants at each level, the networks should not be pgrmitted to conceal the true nature of their discount practices. 3 "lIbid., pp. 425-427. 42"Antitrust Implications of Network Television Quantity Adver- tising Discounts," (Student Note), Columbia Law Review 65 (November 1965): 1213-1255. (The article is also reprinted in U.S. Senate Com- mittee on the Judiciary, "Hearings on Possible Anticompetitive Effects of the Sale of Network TV Advertising," 89th Congress, 2nd Session, Senate Subcommittee on Antitrust and Monopoly, 1966, pp. 459-502.) 431b1d., p. 1254, and Hearings, p. 501. 29 Technical Study Number 8 of the National Commission of Food Marketing (1972) describes, at some length, the inherent advantages of large-scale advertising in food manufacturing and distribution. These include volume discounts resulting in more advertising impact, better access to the more valuable prime time periods, foreclosure of smaller manufacturers "from this very productive sales producing media," and above average profits."4 Summarizing the results of his study of concentration in 33 con- sumer goods industries between 1947 and 1963, Blair (1972) reports that: While dissimilar in nearly every other respect, these diverse areas have in common one characteristic: the ability of their leading producers to exploit their differentiated products in a manner and on a scale simply not available to their smaller competitors. . . . During this period of manufacturing as a whole, increases in in- dustry concentration were roughly matched by decreases. But among these TV-advertised fields increases outweigh decreases by more than 3 to l. . . . There can thus be little doubt about the continu- ation of the upward trend in concentration among industries with high TV-advertising intensities.4S Further, Blair looked at industries in which companies were the only users of network television advertising and found that all such industries had "very substantial" increases in concentration.46 In a study of concentration in 166 producer and consumer goods industries between 1947 and 1970, Mueller and Hamm (1974) concluded that: Empirical studies suggest that for many industries product differ- entiation represents the major barrier to entry. Such barriers 44U.S. Federal Trade Commission, The Structure of Food Manufac- turing, Technical Study Number 8, National Commission on Food Marketing, U.S. Government Printing Office, washington, D.C., 1972, pp. 68-71. "SBlair, Economic Concentration, Structure, Behavior and Public Policy, pp. 323-330. 46Ibid., pp. 323. 30 exist because of advantages existing firms have over potential entrants or because of real or pecuniary economies of scale in achieving product differentiation. It appears that the product differentiation barrier to entry has risen in recent years as has the size of economies of scale in achieving such differentiation. This increase appears to be causally related to the emergence of network television as a preferred method of advertising for many products. Porter (1976) examined the impact of network television, spot television, magazines and local newspaper advertising expenditures, all divided by sales, on profit after tax as a percent of stockholders equity in 39 consumer goods industries. Despite the small number of industries, as many as five other core variables besides advertising expenditures were included in the regression equations, including eight- firm concentration ratios, minimum efficient scale as a percent of in- dustry sales, industry growth, a dummy variable for local or regional industries, and absolute capital requirements for production at minimum efficient scale. After examining the regression coefficients, which were greater than one and significant at the .01 level for the ratio of network television advertising to sales, Porter concluded that "These results suggest that the elevation of market power due to advertising is primarily due to the size of advertising outlays on network television and magazines, especially the former. . . . Other forms of advertising appear to have little significance for long-run market power, though they may well be central to maintaining market shares."48 On the other hand, Blank (1968 and 1969) argued that there is no evidence of network rate discrimination that favored large advertisers 47Willard F. Mueller and Larry C. Hamm, "Trends in Industrial Market Concentration," 1947 to 1970," Review of Economics and Statis- tics 56 (November 1974): 511-520. 48Michael E. Porter, "Interbrand Choice, Media Mix and Market Performance," p. 403. 31 over smaller ones. He conceded that the practice of allowing volume discounts was important in the fifties, but had been eliminated as an important pricing policy by the early sixties. Blank addressed everything written on the subject in two separ- ate articles in 1968 and 1969, including Blake and Blum, Turner, the 1965 student note in the Columbia Law Review, Leonard, the Procter and Gamble/Clorox case, the General Foods/8.0.8. case, Technical Study Number 8 of the National Commission on Food Marketing, plus the Hart and Dingell Hearings. Blank attempted to point out the inadequacies of some of the arguments in each of these studies because they relied on published rate cards instead of empirical evidence and because of the development of participations as a dominant form of packaging announce- ments as opposed to sponsorship. It should be noted that none of the original analysis from which the charges against the networks derived was based on data re- lating to prices advertisers actually paid for television network time. All are based on prices in published network time rate cards. However, anyone who knew anything about network pricing practices was aware of the fact that during the years in question, network rate cards had little to do with the actual prices that networks employed, both because they did not include a charge for programs and because an entirely different pricing procedure, totally unrelated to rate cards at all, was becoming an increas- ingly important, indeed dominant form of selling.4 Blank demonstrated that for all CBS evening advertising in 1965 and in 1966 large advertisers paid more per commercial minute than small advertisers. Then he explained the relationship of this price to audi- ence size and demographic characteristics. He pointed out that "in brief, the problem is that networks simply do not sell homogeneous prod- ucts whose prices to different purchasers can be directly compared."50 49David Blank, "Television Advertising: The Great Discount Illusion," p. 16. 50 Ibid., p. 27. 32 He used cost-per-thousand homes reached as a crude measure of comparison and found no relationship between size of the advertiser and cost-per- thousand homes reached. And again, for the overall transition period between conventional sponsorship purchases of large advertisers compared with the participation purchases of smaller advertisers, Blank found no significant relationship between the size of the advertiser and the cost-per-thousand homes reached. Peterman (1968) also found no support for the hypothesis that networks favored large advertisers over smaller ones in their rate structure during 1965 and most of 1966. The networks granted several different types of discounts and, it seems, for a variety of reasons. In discussion of networks how- ever, it is quite common to lump together all of the discounts and, noting their overall size, to consider them to be obviously un- juStified. I feel that such discussions are quite misleading as are the conclusions frequently drawn from them: that the discounts should be abolished or closely regulated. No doubt improvements can be made, but it is hard to see how this can be done unless there is more understanding about the present system and of the effects which its operation has on the buyers of time. Riesz (1973) attempted to infer the existence of discounts and price concessions and their relationship to the size of the advertising budget by determining the extent to which various firms concentrated their network television advertising expenditures among the three net- works. Riesz hypothesized that: If the availability and magnitude of discounts and price concessions are strongly related to the total network budget size, then firms with small, medium, or large budgets should differ in the distribu- tion of their expenditures among the three networks. The general contention that large firms obtain better buys than smaller ones 51John L. Peterman, "The Clorox Case and Television Rate Struc- tures," p. 124. 33 under the time-change and participation-minute systems provides the rationale for this hypothesis. Riesz examined the largest proportion of a firm's budget allo- cated to single network for 54 consumer goods industries against their total network budget for the period 1961-1965. He predicted that small firms would tend to concentrate their budgets in a single network to obtain the largest possible discount. Firms with medium sized budgets were predicted to tend to disperse their budgets among the networks as a safety measure to preclude the risk of poor programming. For the very large budget advertisers, Riesz predicted no network concentration because the firm could qualify for the maximum discount on all three networks and therefore would purchase advertising time on all three networks. Riesz found a high degree of single network concentration for the smaller budget advertiser under $500,000, who would not qualify for network discounts. Medium sized firms with budgets between $500,000 and $2.8 million had a range of concentration between 60 and 85 percent. This is the category in which the discounts were expected to be particu- larly operative. For the largest budget firms only 26 percent concen- trated their expenditures on a single network. Thus Riesz concluded that there was no evidence of network price structures between 1961 and 1965 which favored large advertisers. Limitations of Previous Research The review of literature has disclosed: (l) the existence of five often contradictory theories regarding the relationships between 52?. C. Riesz, "Size Versus Price, or Another Vote for Tony- pandy," Journal of Business 46 (July 1973): 397. 34 advertising and market concentration as well as between advertising and other aspects of market structure, market conduct and market perform- ance, (2) the lack of any clear evidence as to which theory correctly specifies the nature of the relationships between advertising and market concentration, (3) some clear evidence that increasing returns to adver- tising messages do not exist for single brands, (4) contradictory in- direct evidence of the existence of ecbnomies of scale due to industry and firm advertising intensity, and (5) conflicting evidence as to the existence of scale economies due to media rate structures, especially network television advertising rates, which may favor large, multi- product, multi-industry advertisers at the expense of their smaller rivals. It will be argued below that the conflicting theories and am- biguous evidence are due to six specific limitations inherent in previous theories and research. The six limitations will be briefly listed below and a fuller discussion of each of them will follow. An attempt will be made to overcome each of these problem areas in the research that follows. 1. Previous studies which used the conveniently available adver- tising-sales ratio to facilitate inter-industry analysis of advertising effects failed to state advertising expenditures in a way which reflects their impact on consumer behavior, i.e., to take account of gross advertising message exposures (reach x frequency) and advertising message precision, effectiveness or quality (production costs). Therefore, if any increasing returns to advertising messages exist, advertising-sales ratio data are incompetent to detect them. 35 Furthermore, earlier research which used the advertising-sales ratio failed to state advertising outlays in a way which re- flects their potential for possible scale economies and absolute outlay entry barriers. Therefore, if scale economies and entry barriers due to advertising expenditures exist, advertising- sales data will not be sufficient to detect them. Previous research failed to specify, in light of the above limitations, the several possible relationships which may exist between advertising expenditures and market concentration within and across industries. Consequently, economists have been at- tempting to determine empirically which theory is correct, with contradictory results, when, in fact, each separate theory may be appropriate under certain narrowly defined circumstances. Earlier investigations failed to account for the entire adver- tising media mix, depending instead on examination of network television advertising outlays alone, or on total firm or on total industry advertising expenditures. Therefore, no direct evidence exists as to the differential impact of the various forms of advertising on aspects market structure, market conduct and market performance. Previous research leaves the direction of causality in doubt, which makes single equation estimates biased.53 Earlier investigations have "been plagued by potentially large measurement error and the use of small samples highly sensitive to the inclusion or exclusion of one or two industries."54 53Ibid., p. 38. SAIbid. 36 However, despite the many shortcomings of previous research, some economists have begun to recognize these limitations, and the lit- erature already contains suggested means of overcoming them, as de- scribed below. Specifying Advertising Intensity To Reflect Entry Barriers and Increasing Returns Almost all studies done with respect to the impact of advertis- ing on competition have employed the ratio of advertising-to-sales as an independent or dependent variable to specify advertising intensity. Use of the advertising-sales ratio, which is readily available from a number of government and industry sources and which facilitates inter- industry analysis of advertising intensity, has led to conflicting findings--even using the same data. The problem, in part, lies in fail- ure to specify the correct relation of the ratio to potential consumer response, scale economies, increasing returns, quantity discounts, and absolute advertising outlays. Comanor and Wilson (1967) were probably the first to suggest some of the shortcomings of the advertising-to-sales ratio. . . . it is useful to examine the absolute volume of advertising expenditures by existing firms as well as the advertising-sales ratio. The latter variable probably provided a good indication of the absolute cost disadvantage of the new entrant at small scales of entry, but is likely to be a less accurate index of the economies of scale and absolute capital requirements effects of advertising.55 However, in their empirical work, Comanor and Wilson were forced to use average advertising expenditures per firm instead of actual 55William S. Comanor and Thomas S. Wilson, "Advertising, Market Structure, and Performance," Review of Economics and Statistics 49 (November 1967): 428. 37 absolute advertising expenditures, which has a spurious positive rela- tionship with market concentration because the average advertising ex- penditure per firm tends to increase as concentration increases.56 Further major theoretical shortcomings with the use of the ad- vertising-to-sales ratio as a measure of advertising's economic impact have been highlighted by Ferguson (1974). . . . economies of scale due to media rate structure are a function of the level of advertising expenditures, not of the ratio of ad- vertising to sales. Also, increasing returns to creating consumer awareness are a function of the quantity of advertising messages received by consumers, not the ratio of advertising to sales. Only if the ratio of advertising expenditures to sales is highly corre- lated with the levels of advertising expenditures and advertising messages will the ratio be an appropriate variable to use in a test of the effect of advertising on monopoly. Whether the advertising-sales ratio is an adequate proxy of advertising expenditures, hence a measure of economies of scale due to advertising and a measure of entry barriers due to advertising, is an open empirical question that has never been tested directly in the literature. The discussion below strongly suggests that the advertis- ing-sales ratio is not necessarily a good proxy of advertising expendi- tures. Ornstein (1977) elaborates: Although previous studies have not used total advertising as the dependent variable . . . this use may be more appropriate than the use of the advertising-to-sales ratio. Much of the theory simply states that there will be more or less advertising, not that there will be higher or lower advertising intensity. Furthermore, the conventional theory on advertising as a barrier to entry implies that the absolute level of advertising expenditures is a more ap- propriate measure of capital requirements or economies of scale than advertising intensity. The larger the amount spent on 56See, Stanley Ornstein, Industrial Concentration and Advertis- ing Intensity, p. 43. 57James M. Ferguson, Advertising and Competition; Theory, Measurement, Fact, pp. 57-58. 38 advertising, the greater will be the potential economies and the higher the capital requirements (if they exist).58 Finally, Simon (1970) has provided considerable discussion and some evidence that the advertising-sales ratio can lead researchers to faulty conclusions. For example: advertising-ratio data alone are not competent to serve as the basis for any general investigation of the economics of advertising. The behavior of advertising expenditures in the depression of the 19303 is an example of how advertising ratio data can be misleading. If one looks at the proportion of net sales spent for advertising by department (and specialty) stores from, say, 1929 to 1944, the highest ratio occurred in 1932. . . . This suggests that advertising "intensity" rose in the depths of the depression. But if one looks at the absolute amount spent for advertising by department stores, one sees that it dropped sharply from a high in 1929 to a low in 1933, and was almost as low in 1932 as in 1933. . . . This shows that the use of the ratio data alone would almost surely lead a researcher to the wrong conclusion. Amplifying the reasoning above leads to the following conclu- sions about advertising expenditures: 1. Entry barriers and increased market concentration due to ad- vertising are a function of brand loyalty, economies of scale, increasing returns to advertising messages and absolute adver- tising outlays. (See Figure I and the corresponding discussion above.) 2. Economies of scale resulting from media rate structures are a function of absolute advertising expenditures by a firm or a brand in a particular advertising media vehicle. 3. The amount of consumer awareness and brand loyalty is a function of the quantity and effectiveness of advertising messages. 58Stanley 1. Ornstein, Industrial Concentration and Advertising Intensity, p. 43. 59Julian Simon, Issues in the Economics of Advertising, p. 310. 39 4. The quantity (reach x frequency or gross exposures) of advertis- ing messages is a function of absolute advertising expenditures. 5. The effectiveness of advertising messages, on average, is a function of advertising production expenditures for the analysis of consumer and market research, for creative energies, for copy testing and so on.60 6. Advertising production expenditures are a function of absolute advertising expenditures.61 7. From 3 through 6 it follows that the amount of consumer aware- ness and brand loyalty is a function of absolute advertising expenditures. 8. Therefore, from 1, 2 and 7 it follows that entry barriers and that increased concentration due to advertising are a function of absolute advertising expenditures. In summary then, there appears to be no theoretical rationale for the use of the advertising-sales ratio as a proxy of advertising expenditures. The measure changes in response to changes in advertising expenditures and to changes in sales. Furthermore, holding advertising expenditures constant, the advertising-sales ratio is inversely related 60This is a debatable premise in that it does not account for the highly publicized examples of creative insight that bring about spectacular results far out of proportion to the effort and expense that went into producing them. But it seems reasonable to assume that such examples are the exception and not the rule. There are probably an equal (or greater) number of examples where the reliance on quick and dirty creative intuition led to market disaster. 61For example, advertising agencies often receive a 15 percent commission on their clients' advertising media expenditures as compen- sation for creating and placing advertising messages. Thus, the larger is the total advertising expenditure, the greater will be the amount an agency receives from its commission and the more extensive will be the services which the agency provides for its clients. 40 to changes in sales. 0n the other hand, there appears to be strong theoretical support for the use of advertising expenditures unadjusted by sales since the larger is a firm's or a brand's advertising expendi- tures, the greater is the potential for barrier producing brand loyalty, scale economies, increasing returns to advertising messages, quantity discounts which favor large, multi-product, multi-industry advertisers and increased market concentration. Fortunately, the proposition that the advertising-sales ratio is ng£_a good proxy of advertising expenditures can be subject to a direct empirical test. The Relationships Between Advertising Outlays And Market Concentration Within Product Categories It has also been suggested that a distinction should be made between the level of advertising intensity of large firms and the level of advertising intensity of other firms within an industry. Yang (1966) made a clear distinction between the absolute and the relative intensity of advertising stating: The absolute advertising intensity hypothesis (implies) the assumption that the absolute volume of advertising expenditures (or the absolute level of advertising intensity) for a given industry influences its concentration ratio. Yang also stated: The relative advertising_intensity hypothesis . . . states that the extent to which advertising affects industrial concentration 62Charles Yneu Yang, "Industrial Concentration and Advertising," Hearings before Subcommittee on Antitrust and Monopoly of the Committee on the Judiciary, U.S. Senate, Part 5: Concentration and Divisional Reporting, Appendix S. Washington, D.C.: U.S. Government Printing Office, 1966, p. 2153. 41 depends to a large extent on the change in the advertising intensity of the dominant firms relative to the remaining firms in the in- dustry. 3 Analysis of evidence led Yang to conclude that the absolute level of advertising intensity, as measured by the advertising-sales ratio, was not significantly related to concentration.64 0n the other hand, he found a significant positive relationship between the change in advertising share of the leading companies in his industry sample and the corresponding change in their market shares.65 Yang's statistical analysis has been criticized.66 Neverthe- less, his reasoning has considerable face validity worthy of further investigation. Subsequently, Friedland (1974) provided a more complex structure to illustrate clearly the several dimensions in the relative advertising intensity hypothesis (based on the advertising-to-sales ratio). It assumes that industry concentration is determined by the relative intensities of large and small firms' advertising-that when large firms advertise more relative to sales than small firms, then the large firms become still larger relative to small firms, and con- centration rises. Conversely, it assumes that when small firms 631bid., p. 2154. 64Ibid., p. 2162. 651151.1. 66See for example, James M. Ferguson, Advertising_and Competi- tion;_Theory, Measurement, Fact, p. 93. Although Yang finds a signifi- cant positive relationship between changes in concentration and changes in advertising share of the leading firms, Ferguson concludes that: ". . . these results are derived from an incorrectly specified regres- sion in which both the average and the change in advertising intensity variable are included, but only the change in (and not the average) of the advertising share is included. Multicollinearity between the two advertising-intensity variables practically ensures the non-significance of their coefficients. He should have correlated the change in concen- tration on the change in each of the two advertising variables (exclud- ing the level variables)." 42 advertise more relative to sales than large firms, then the small firms grow more rapidly than the large firms, and concentration falls. Thus, when large firms' advertising is intensive but small firms' advertising is light, it predicts high concentration. When large firms do not advertise intensely but small firms do, it pre- dicts low concentration. Column 4 (below) reflects these predic- tions. Column 3 is derived from Columns 1, 2 and 4. In Line A, all firms have high advertising-sales ratios, so the industry's advertising- sales ratio is also high. Line D presents the analogous case for low ratios. In Line B, the largest firms advertise intensely while the smaller firms spend a small fraction of their sales dollars on advertising. Since Column 4 indicates that concentration is above average in this industry, one weights the large firms' ratio more heavily. This suggests that industry-advertising in- tensity is medium-high. Similarly in Line C, small firms advertise more intensely than large firms and concentration is below average. One therefore weights the smaller firms' advertising more heavily; again one expects medium-high advertising intensity for the whole industry.67 PREDICTIONS OF INDUSTRY CONCENTRATION ON THE BASIS OF THE DISTRIBUTION OF ADVERTISING AMONG THE FIRMS IN THE INDUSTRY 1 2 3 4 Advertising Advertising Average Expected Level of largest of all industry ad- of four-firm four firms smaller firms vertising concentration A High High High Medium B High Low Medium-high High C Low High Medium-high Low D Low Low Low Medium When average industry advertising is medium high, concentration is expected to be either high or low, depending on the intra-industry advertising intensities. 0n the other hand, when concentration is medium, average industry advertising can likewise be either high or low depending on the respective advertising intensities. This underscores the significance of the relative advertising intensity hypothesis and 67T. S. Friedland, "Possible Resolution of the Advertising-- Concentration Debate," Quarterly Review of Economics and Business 14 (Spring 1974): 125. 43 explains why many studies regressing market concentration on average industry advertising intensities (Column 4 by Column 3 in Friedland's paradigm above) have not found a positive and significant statistical relationship,68 while studies segmenting industries into homogeneous groups on the basis of large firm advertising intensity (Column 4, Rows A and B by Column 1, Rows A and B in Friedland's paradigm above) have found a significantly positive statistical relationship.69 Friedland's simple paradigm has two shortcomings however. It confuses actual levels of market concentration with changes in market concentration and actual levels of advertising intensity with changes in advertising intensity. And it is based on the advertising-to-sales ratio. Nevertheless, each of these shortcomings can be easily overcome and the model can be usefully extended beyond market concentration to provide a powerful link between each of the five separate theories out- lined above. Friedland's discussion of his paradigm intermixes levels of ad- vertising intensity and levels of market concentration with changes in advertising intensity and changes in market concentration. This problem is easily overcome by simply assuming, as Friedland apparently did im- plicitly, that each of the four Columns in his model refer to the level of advertising intensity or to the level of market concentration at a point in time and, further, that movement from one of the four Rows to another Row reflects the predicted change in outcome. For example, 68See for example, Lester G. Telser, "Another Look at Advertis- ing and Concentration," Journal of Industrial Economics 18 (Nevember 1969): 85-94. 69See for example, H. M. Mann, J. A. Henning and James W. Meehan, Jr., "Advertising and'Market Concentration: An Empirical Investigation." 44 assuming a market situation characterized by Row D in period t, Fried- land's model would predict that a change in the relative distribution of advertising intensity among the firms in the industry, such as that characterized by Columns 1, 2 and 3 of Row B, would bring about an in- crease in concentration so that Column 4 of Row B would characterize the outcome in period t+l. Friedland's paradigm is also based on the advertising-sales ratio as a measure of advertising intensity as is typical of research of this type to date, except for Yang, who used advertising shares as a measure of relative advertising intensity. However, Yang's specifica- tion may be the correct one. It was argued above that if the effects of advertising on compe- tition are to be accurately assessed, advertising should be measured in absolute dollars instead of with the advertising-sales ratio. This respecification would more nearly reflect scale economies due to media rate structures, increasing returns to advertising messages and the absolute large size of advertising expenditures. However, absolute ad- vertising expenditures are not comparable across industries. Advertis- ing shares of firms or brands within an economically relevant market, on the other hand, are comparable across markets because they reflect the proportion of total market advertising accounted for by a particular firm or brand. Therefore, the advertising share variable, which re- flects the intra-industry distribution of absolute advertising outlays is expected to provide a better (unbiased) estimate of the impact of advertising on competition within an industry than is the ratio of ad- vertising-to-sales. However, advertising shares do not take into 45 consideration the differences in the absolute level of advertising ex- penditures between markets. Friedland's relative advertising intensity paradigm can be use- fully modified then, by substituting advertising shares in Columns 1 and 2 of his original model (see above), instead of using advertising-sales ratios. This substitution will change the relative intensities of Rows A and D to reflect the relative equality of advertising shares among the top and all other firms in an industry. The difference in the absolute level of advertising between industries A and D is still reflected in the average industry advertising intensity of Column 3,'as originally specified by Friedland. Modified, the paradigm then becomes: TABLE I PREDICTIONS OF INDUSTRY CONCENTRATION ON THE BASIS OF THE DISTRIBUTION OF ADVERTISING AMONG THE FIRMS IN THE INDUSTRY l 2 3 4 Advertising Advertising Average Expected Level Share of Share of All Industry of Market Larger Firms Smaller Firms A/S Ratio Concentration A Medium Medium High Medium B High Low Medium-High High C Low High Medium-High Low D Medium Medium Low Medium The respecified model highlights: (1) the direct relationship which is expected between the advertising share of the top firms in an industry (Column 1) and market concentration (Column 4), (2) the ex- pected lack of relationship between the advertising-to-sales ratio (Column 3) and market concentration (Column 4), and (3) the inverse 46 relationship which should exist between the advertising share of all smaller firms in an industry (Column 2) and market concentration (Column 4). Friedland's reasoning can also be extended beyond market con- centration to illustrate how each of the five separate theories out- lined above are not necessarily incompatible. That is to say, the rela- tive advertising intensity hypothesis is useful toward understanding the narrow conditions under which each separate theory is appropriate. \/ The term "advertising" is used loosely in both the change-of- taste theory (see Figure I above) and the information theory (see Figure II above). Neither theory explicitly states whose advertising expenditures are involved. Each model tacitly assumes different kinds of advertising expenditures. The change-of-taste theory defines the expected impact of advertising outlays of the single large firm or of a group of large firms within an industry. The advertising-as-infor- mation theory addresses itself to the advertising outlays of all market participants and, further, appears to assume relative advertising equality among market participants. That is to say, because of the advertising by all market participants, consumers know of each market alternative equally. Therefore, the two models, which suggest opposite outcomes in terms of monopoly power over price, are not necessarily incompatible. The information approach addresses itself to the outcome anticipated when all market participants advertise equally in terms of message frequency and in terms of message effectiveness. But as soon as one or a few market participants violate that implicit assumption and advertise more heavily or more effectively than other market 47 participants, the change-of-taste model should predict the outcome. Thus, it is more likely that more consumers will know more about the one or the few market alternatives that are more heavily advertised or more effectively advertised. Therefore, the demand curves for these more heavily or more effectively advertised brands should become less elastic and tend to lead to more discretion over price. The question then, is not which theory is correct, but rather, what is the relative distribution of advertising impact, either in terms of message frequency or in terms of message effectiveness or both, among market alternatives? When the distribution of advertising impact is spread relatively equally among the market participants, so that the consumers know equally of all of the market alternatives, Nelson's in- formation model should explain the outcome: industry advertising in- creases the number of known alternatives, there is no small firm cost disadvantage due to advertising, advertising should facilitate entry, the presence of more actual and potential rivals should increase the price elasticity of demand and lead to lower prices and firms should earn normal returns. 0n the other hand, when the distribution of adver- tising impact is spread unevenly among the market participants, so that more consumers know more of one or of a few market alternatives, the Kaldor, Bain and Comanor and Wilson change-of-taste theory should ex- plain the outcome: increasing returns and economies of scale due to advertising favor large firms at the expense of their smaller rivals and may increase minimum efficient scale and market concentration, increase brand loyalty, put small firms at a cost disadvantage and increase entry barriers, resulting in fewer actual and potential rivals and lower 48 price elasticity of demand leading to supra-normal profits for heavy advertisers. A complete model then would combine the two separate theories, which suggest opposite outcomes, with the relative advertising intensity hypothesis as illustrated in Figure IV below. The third theory, which suggests that non-advertising factors which influence entry barriers and market concentration can lead to higher or lower advertising, depending on the existence of collusion to restrict non-price competition, can also be incorporated without affect- ing the relationships suggested by the information and change-of—taste theories. The structure-collusion theory has therefore also been added to Figure IV below. The fourth and fifth theories cannot be in- corporated usefully or explicitly into the previous discussion or into Figure IV. The spurious association theory suggests that advertising and market concentration may be related in the absence of traditional arguments for scale economies and entry barriers due to advertising be- cause advertising may help large firms exploit economies of large scale production and distribution, cope with buyer turnover and large diversi- fied markets. Furthermore, the spurious association theory suggests that large firms may have gotten large because of superior product qual- ity and it therefore pays to advertise heavily a superior product. The interaction theory argues that advertising and market concentration interact and that they are jointly determined by other factors, such as the number and turnover rate of buyers, consumer characteristics and so on. Unfortunately, it is no easier a task to test empirically any of the inter-relationships suggested by Figure IV below than it would be to 49 “fl QUALITY VARIATION AMONG BRANDS L .4 1 [ CONSUMERS UNAWARE or ALTERNATIVES 1 { Dmnmammnmixmxmuc J l 1 ‘ NON- 4 J, 1 unnumnm 1 1 , r BRANDS Possess MONOPOLY POWER , I “”035 a J _1 1_€% RELATIVE AD IMPACT axons BRANDS EQUAL? j 1 YES N0 4, so \ 1 ADS INCREASE KNOWN ALTERNATIVES! { BRAND LOYALTY l 1 Y SCALE ECONOMIES DUE TO ADVERTISING 1 .-..-._ - ._ ...-1 _. ..._..-._-..1 .. \ l— [N0 SHALL FIR“ C°ST DISADVANTAGE! [SMALL FIRM cosr DISADVANTAGE 1 NES INCREASED J 1 I i \k 1 ' I . I ENTRY INCREASED _._1 [ ENTRY 31321235 INCREASED _j I CONCENTRATION INCREASED _j \ sou: xcruu. a. POTENTIAL mus rm 201mm RIVALS [ mm 1mm. RIVALS 1 1 PRICE ELASTICITY INCREASED 1 PRICE EIASTICITY 0P DELAND DECREASED F l LOWER PRICES HIGHER PRICES. LITTLE INCBTTIVE TO CUT PRICES T 1 % ‘ COLLUSION TO RESTRICT NON-PRICE COMPETITION? 4L3» \LYES HIGHER ADVERTISING LOWER ADVERTISING 1 NORMAL RETURNS J { MONOPOLY RETURNS Figure IV. Competition Several Possible Relationships Between Advertising and 50 test the inter-relationships among elements of each of the separate theories. However, the discussion above, which is based on an under- standing of the relative distribution of advertising among the firms in an industry, does suggest the conditions which may be necessary for a particular model to explain the circumstances which characterize a particular market structure, market conduct and market performance rela- tive to advertising as well as the impact that changes in market circume stances are likely to have on market structure, market conduct and market performance. Accounting for the Advertising Media Mix There are two principal reasons why it may be inappropriate to aggregate advertising expenditures in a single index such as the adver- tising-sales ratio: (1) some advertising media categories may be more persuasive in content and therefore more conducive to consumer inertia _(brand loyalty) and decreased competition while other advertising media categories may be more informative and conducive to consumer disloyalty and increased competition, and (2) some advertising media rate struc- tures may favor large, multi-product, multi-industry advertisers at the expense of their smaller rivals while other advertising media may not favor large advertisers. Each of these possibilities will be discussed below more fully. Informative versus Persuasive Advertising_ Several economists have attempted to distinguish between inform- ative and persuasive advertising, arguing that each type affects Sl economic performance differently.7O On one hand, persuasive or goodwill advertising is thought to have anti-competitive effects to the extent that it encourages buyer inertia and brand loyalty which increases entry barriers. On the other hand, informative advertising discourages satisfaction with habitual or uninformed behavior in the marketplace and therefore stimulates competition by facilitating entry. There is some limited empirical evidence that the distinction may be valid. A recent study by Resnik and Stern (1977) published in the marketing literature showed that even with food, personal care products and the like, only 23.5 percent of commercials sampled included one or more information cues such as price, quality and performance.71 Boyer (1974) found a significant differential impact between informative versus persuasive advertising after dividing a sample of industries into two distinct groups: (1) consumer goods manufacturers, who undertake primarily persuasive advertising, and (2) retail and service trades, whose advertising is characterized as chiefly informa- tive.72 While Boyer found a strong positive correlation between adver- tising intensity and industry profitability in the consumer goods manu- facturing sector, no such relationship existed in the retail and service 70See for example, Kenneth D. Boyer, "Informative and Goodwill Advertising," The Review of Economics and Statistics 56 (November 1974): 541-548, and Fred M. Scherer, Industrial Market Structure and Economic Performance, Chapter 14. 71See Alan Resnik and Bruce L. Stern, "An Analysis of Informa- tion Content in Television Advertising," Journal of Marketing 41 (January 1977): 50-53. 72 Kenneth D. Boyer, "Informative and Goodwill Advertising," p. 543. 52 sector. Boyer thus recommends that the heterogeneous nature of adver- tising should be recognized when undertaking research and formulating policy. Another approach to drawing a distinction between informative and persuasive advertising is to consider the distribution of adver- tising expenditures among media, as Scherer (1970) did with 1965 U.S. advertising expenditures. Newspaper advertising, accounting for nearly 30 percent of total outlays, is preponderantly of an informative character, although (as any erstwhile home seller knows) even classified ads are written in persuasive fashion. However unwelcome it may be to the deluged recipient, direct mail advertising plays a largely informative role, as do many of the advertisements in business and farm periodicals. The information content of radio and tel- evision commercials is also not zero, despite a seemingly mag- netic attraction toward that value. Even outdoor billboards sometimes supply wanted information, as travelers who sought gasoline or lodging in the early sign-less days of the U.S. interstate highways can testify. If a horseback generalization must be hazarded, it would be that half of all advertising ex- penditures cover messages of a primarily informative character, while the other half serve largely to persuade. But since 1965, the relative distribution of advertising expend- itures among the various media has changed as Tablelfliillustrates below. It appears that the persuasive advertising media, which Scherer sug- gested might include radio, television and outdoor, have increased in importance relative to the more informative media, such as newspapers, magazines, business and trade publications and direct mail. And if a horseback generalization must be hazarded, to use Scherer's phrase, it would be that more than half of all advertising is now persuasive while less than half is now informative. 73Fred M. Scherer, Industrial Market Structure and Economic Performance, p. 326. 53 TABLE II U.S. ADVERTISING EXPENDITURES IN 1965 AND IN 1975 Millions of Dollars Percent Medium 1965 1975 1965 1975 1965 1975 Newspapers 4,457 8,442 29.2 29.9 Classified ads 1,200 a Local display 2,400 7,221 National display and other 857 1,221 Magazines 1,199 1,465 7.9 5.2 Farm publications 34 74 0.2 0.3 Business and trade publications 671 919 4.4 3.3 Television 2,515 5,263 16.5 18.6 Network 1,237 2,306 Local 412 1,334 Spot 866 1,623 Radio ' 917 1,980 6.0 7.0 Network 60 83 Local 589 436 Spot 268 1,461 Direct Mail 2,324 4,181 15.2 14.8 Outdoor billboards and signs 180 335 1.2 1.2 Miscellaneous 2,959 5,571 19.4 19.7 TOTAL 15,256 28,230 100.0 100.0 Sources: Printers' Ink, February 24, 1967, pp. 9-10; Jules Backman, Ad: vertising and Competition (New York: New York University Press, 1967), pp. 30 and 161-179; Neil H. Borden, The Economic Effects of Advertising_ (Chicago: Irwin, 1942), pp. 52-58; Fred M. Scherer, Industrial Market Structure and Economic Performance (Rand McNally, 1970), p. 326; and Robert J. Cohen, "Advertising volume to top $36.5 billion in 1977," 5g: vertising Age, December 27, 1976, pp. 3 and 46. 8A separate breakdown for 1975 is not available. 54 If the informative-persuasive advertising distinction is valid, as theory and evidence suggest it might be, then research into the ef- fects of advertising on competition should attempt to clearly distin- guish between the two. And if particular advertising media can be characterized as either primarily informative or primarily persuasive, aggregating advertising expenditures across advertising media (as each of the studies included in Appendix A has done) is inappropriate. For example, research might support the change-of-taste theory of advertis- ing effects in industries which rely heavily upon more "persuasive" media while research might support the information theory of advertis- ing effects in industries which rely heavily upon more "informative" media. Network Television Advertising In addition to the chiefly persuasive character of the medium, several researchers have singled out imperfections in the supply of network television advertising as being particularly conducive to entry barriers and increased market concentration in the manner outlined in the change-of-taste theory of advertising impact above. Some researchers have argued that network television volume dis- counts favor large multi-product, multi-industry advertisers at the ex? pense of their smaller rivals.74 In contrast, other researchers have presented cost-per-thousand household evidence which suggests that large advertisers do not receive a lower cost-per-thousand households reached 74See John M. Blair, Economic Concentration, Structure, Be- havior and Public Policy, pp. 308-334. 55 75 But since network advertising rates than their smaller counterparts. are largely negotiated, with rate cards serving merely as a starting point, and since the ideal measure of the relative value of advertising time to advertisers is cost-per-prospect reached and not merely cost- per-thousand, this issue may never be satisfactorily resolved because such proprietary data is not likely to become readily available. Still other researchers have argued that since there are no perfect substitutes for television advertising within some industries, indivisibilities in the supply of network television advertising time, which are similar across the three major networks, require network ad- vertisers to use a large portion of the network station lineup which precludes a gradual buildup of scale. On one hand, this requires large absolute capital outlays on the part of the network advertisers attempt- ing to effectively compete on a national scale. 0n the other hand, television advertisers in the same product category who are too small to effectively utilize the networks are at a great cost disadvantage since network rates can range from 10 to 70 percent of the sum of the rates of the individual stations in the network lineup.76 A major limitation of studies attempting to focus directly on the relationship of network television advertising expenditures to market concentration has been, among other things, a failure to take into consideration the relative importance of network television 75See David M. Blank, "Television Advertising: The Great Dis- count Illusion on Tonypandy Revisited," James M. Ferguson, "Anticom- petitive Effects of the FTC's Attack on Product Extension Mergers," and John L. Peterman, "The Clorox Case and Television Rate Structure." 76See Michael E. Porter, "Interbrand Choice, Media Mix and Market Performance," p. 403. 56 advertising given a firm's or brand's entire advertising media mix, depending instead on examination of network television advertising out- lays alone. Since it is likely that a high correlation exists between network television advertising expenditures and other advertising media expenditure, omitting other elements of a firm's or brand's advertising media mix could seriously overstate the relative importance of network television advertising.77 Causality Five theories suggest three conflicting causal linkages between advertising intensity and market concentration: (1) advertising in— tensity affects market structure, (2) market structure affects adver- tising intensity and (3) advertising intensity and market structure interact and are jointly determined by other factors. And, the empiri- cal evidence is compatible with a number of conflicting interpretations. None of the three kinds of evidence needed to support causal inferences exist, including: (1) concomitant variation, (2) time order of occur- rence of variables and (3) the elimination of other possible causes.78 Previous empirical research has found both significant and non-signifi- cant relationships between measures of advertising intensity and measures of market concentration with about equal frequency. Most of 77See for example, Blair, Economic Concentration, Structure, Behavior and Public Poligy, pp. 308-334. For a detailed discussion of other shortcomings of Blair's 1972 study, see James M. Ferguson, Ad: vertisinggand Competition; Theory, Measurement, Fact, pp. 97-98. 78For a complete discussion of the kinds of evidence needed to infer causality, see Gilbert A. Churchill, Jr., Marketing Research: Methodological Foundations (Hinsdale, Illinois: The Dryden Press, 1979), pp. 67-73. 57 the research is cross sectional and not time series. And so many other factors influence market structure and advertising intensity that it is unlikely that the separate effects of either variable can be satisfac- torily isolated with the limited data currently available. This study addresses itself to the change-of-taste, the theory of Kaldor, of Bain and of Comanor and Wilson, but it argues for measures of advertising intensity that fit the theory. Nevertheless, the emr pirical analysis of cross sectional data with single equation estimation takes the hypothesis of this study far short of the distance required to infer causality. Measurement Error and Sample Size Three primary shortcomings in the data bases used in previous research are: (1) small samples, (2) aggregated measures of advertising intensity and of industry concentration and (3) non-constant error. Except for Ornstein's (1977) study, previous research has re- lied heavily upon relatively small samples, which introduces large potential error that could be avoided with much larger samples. There- fore, the use of large samples, both within and across industries, can help further reduce the potential measurement error found in previous investigations. Another source of measurement error found in earlier studies arises from the insensitivity of measures of advertising intensity and of industry concentration at high, three and four-digit IRS and SIC levels of aggregation. It turns out that assigning firms to SIC industries and the IRS industries both involve severe statistical problems owing to errors in measurement and aggregating data whose net effect is 58 indeterminate, with the measurement errors biasing correlation downward and the aggregation errors biasing it upward. Ideally, brand level advertising expenditures and brand level sales within narrowly defined and economically relevant markets can effectively overcome these shortcomings. Finally, previous studies have relied heavily upon measures of total industry sales and of total industry advertising, which intro- duces the possibility of non-constant error terms (heteroscedasticity) into the estimation in violation of the ordinary least squares assump- tion of constant error (homoscedasticity). The problem arises due to the highly skewed distribution of the size variables across industries-- a few industries have very large size values while other industries have relatively small size values. This problem has been reduced by some researchers who have transformed the sales and the advertising variables into logarithms.80 If this body of literature is to advance beyond its present inconclusive state, it was recommended above that future analysis of the relationships between advertising intensity and market concentra- tion should be conducted both across and within economically relevant markets. But this introduces the potential size bias outlined above both within and across product categories. Therefore, it is necessary to transform the advertising and the sales data in a way that eliminates the potential for size bias in both instances. The advertising share variable introduced above accomplishes this goal. 79For an excellent discussion of the limitations of IRS and SIC data, see Stanley Ornstein, Industrial Concentration and Advertising_ Intensity, pp. 16-18. 801bid., pp. 43—44. CHAPTER III RESEARCH HYPOTHESES The literature review and the discussion of the shortcomings of previous research suggested three general prepositions which can be tested directly: (1) whether the advertising-sales ratio is a good proxy of advertising expenditures, (2) whether there exist technical or pecuniary scale economies due to advertising, and (3) whether network television is a more important source of scale economies than other advertising media categories. Earlier research relied almost exclusively on the conveniently available advertising-to-sales ratio as a measure of advertising in- tensity which was comparable across industries. But it was argued above that the use of the advertising-sales ratio was theoretically incorrect because it did not necessarily correlate with potential barriers to new firm entry due to advertising, with increasing returns to advertising messages, with scale economies due to media volume discounts and with high absolute advertising outlay entry barriers. Only if the advertising-sales ratio is highly correlated with advertising expenditures is it appropriate to use to test the effect of advertising on competition. The discussion above strongly suggests that the advertising-sales ratio is 325 necessarily a good proxy of advertis- ing expenditures. Therefore, there should be little or no correlation 59 60 between the corresponding advertising-sales ratios and advertising ex- penditures for product categories, firms or brands. It is important to test this proposition directly, for the first time, because if there is little or no correlation between the two measures, previous research, which relied heavily on the ratio of advertising-to-sales, was biased and probably understated the impact of advertising on competition. If the above reasoning is correct, Hypothesis I below should not be rejected. Hypothesis I Within the consumer non-durable goods sector of the economy, there is no correlation between advertising-sales ratios and advertising expenditures for product categories, for firms or for brands. Those who have argued that advertising leads to market concen- tration usually assume that there are increasing returns to advertising messages or that there are economies-of-scale due to media volume dis- counts which favor heavy advertisers and which increase minimum effi- cient scale within an industry faster than industry size increases. There is some evidence that increasing returns_to advertising messages do not exist for single brands and there is contradictory indirect evi- dence concerning the existence of economies-of-scale due to advertising intensity. There is also conflicting evidence as to the existence of scale economies due to network television rate structures. If the existence of technical or pecuniary scale economies due to advertising cannot be demonstrated, advertising cannot, by itself, directly lead to market concentration. If advertising and market concentration are 61 related in the absence of technical or pecuniary scale economies due to advertising, it must be due to factors other than advertising which in- fluence the level of industry advertising or influence the level of market concentration. Hypotheses II and III below are direct tests of the existence of technical or pecuniary scale economies due to firm or brand total advertising expenditures or due to firm or brand expenditures in par- ticular advertising media categories. Hypothesis II Within the consumer non-durable goods sector of the economy, a production function with firm or brand sales (in units or in dollars) as an output and with total firm or total brand advertising expenditures as inputs, will exhibit economies of scale in advertising. Hypothesis III Within the consumer nonrdurable goods sector of the economy, a production function with firm or brand sales (in units or in dollars) as an output and with six separate advertising media expenditures as inputs in: (1) network television, (2) spot television, (3) magazines, (4) newspaper Sunday supple- ments, (5) outdoor and (6) network radio, will exhibit econo- mies of scale in advertising. It was argued above that the correct measure of advertising to use in assessing the impact of advertising on competition is firm or brand advertising expenditures unadjusted by sales. However, 62 advertising expenditures are not comparable across industries and they introduce size bias and possible heteroscedasticity, while advertising shares are comparable across industries and contain essentially the same information. But advertising shares cannot take into account differ- ences in the absolute level of advertising across industries. Furthermore, it seems reasonable to assume that total advertis- ing expenditures as well as selected advertising media expenditures vary across product categories with respect to their relationship to market share. 0n the other hand, it is also maintained that all advertising expenditures, or at least some advertising media expenditures, con- sistently contribute to market share across product categories. There- fore, at the outset, it is important to test the hypothesis that no differences exist across product categories with respect to the rela- tionship between a brand's market share and that brand's share of: (1) all product category advertising or (2) product category advertising in particular media. This reasoning leads to Hypotheses IV and V. Hypothesis IV Across product categories within the consumer non-durable goods sector of the economy, differences exist with respect to the relationship between a brand's market share and a brand's share of all product category advertising media expenditures. H othesis V Across product categories within the consumer non-durable goods sector of the economy, differences exist with respect to the relationship between a brand's market share and-a 63 brand's share of product category expenditures in each of the following six separate advertising media: (1) network television, (2) spot television, (3) magazines, (4) newspaper Sunday supplements, (5) outdoor and (6) network radio. If differences are found across product categories with respect to the relationship of market share to total advertising share or to advertising media shares, then it would be incorrect to pool the in- dustry sample or to make general statements as to the contribution to market share of all advertising or of particular advertising media. Each industry should be examined separately. Therefore, if advertising creates and maintains entry barriers or if there are increasing returns to advertising messages or if there are scale economies due to media volume discounts, then a brand's share of product category advertising should be positively related to a brand's market share. This reasoning suggests that if advertising contributes to entry barriers and to technical or to pecuniary scale economies, Hypothesis VI below should be accepted. Hypothesis VI Within a product category in the consumer non-durable goods sector of the economy, there is a positive relationship between a brand's market share and a brand's share of all product category advertising expenditures. It was further argued that aggregation of advertising expendi- tures in a single index could be misleading because some advertising media categories may be more persuasive in content and therefore may be 64 more conducive to consumer inertia, to brand loyalty and to decreased competition, while other advertising media categories may be more in- formative and conducive to consumer disloyalty and to increased compe- tition. In addition, some advertising media rate structures, such as network television rate schedules, may favor large, multi-product, multi-industry advertisers at the expense of their smaller rivals, while other advertising media may not give heavy advertisers a rate advantage. Therefore, Hypothesis VII, which extends Hypothesis VI to include advertising media shares instead of total advertising shares, should also be supported. Hypothesis VII Within a product category in the consumer non-durable goods sector of the economy, there is a positive relationship be- tween a brand's market share and a brand's share of product category expenditures in each of the following six separate advertising media: (1) network television, (2) spot televi- sion, (3) magazines, (4) newspaper Sunday supplements, (5) outdoor and (6) network radio. Assuming that total advertising shares and some individual media shares are positively related to market share and, assuming further, that differences exist in these overall relationships across product categories, then the next step is to directly examine the relative ef- fectiveness of particular media categories within each economically relevant market. Since it has been suggested that certain advertising media, particularly network television advertising, are important con- tributors to market concentration, then within each product category we 65 should reject the hypothesis that the relationship between each adver- tising media share and market share is equal. This reasoning leads to Hypothesis VIII. Hypothesis VIII Within a product category, in the consumer non-durable goods sector of the economy, differences exist in the relationship between a brand's market share and a brand's share of exr penditures in each of the following six separate advertising media: (1) network television, (2) spot television, (3) maga- zines, (4) newspaper Sunday supplements, (5) outdoor and (6) network radio. If Hypothesis VIII is accepted, then it will be possible to directly compare the relationship of network television advertising shares to market shares with the relationship of the shares of all other media categories combined to market shares. This reasoning leads to Hypothesis IX. Hypothesis IX Within a product category in the consumer non-durable goods sector of the economy, a brand's share of network television advertising expenditures will explain more of the variation in a brand's market share than will a brand's share of ex- penditures in all other advertising media categories combined. And finally, if it turns out that advertising-sales ratios are not highly correlated with advertising expenditures as expected in Hypothesis I above, then it might be instructive to duplicate the 66 regression equations used to test Hypotheses II through IX above using advertising-sales ratios instead of advertising expenditures. The re- gression results derived from using advertising-sales ratios could then be directly compared with the regression results obtained from using advertising expenditures to determine the direction and the magnitude of any differences which might exist. The results of this undertaking might, for the first time, shed some light on how previous research, which was conducted without the luxury of advertising expenditures at narrow and economically relevant levels of aggregation, may or may not have led researchers to the wrong conclusions. No a priori hypotheses regarding the nature and the scope of these differences are possible however. CHAPTER IV METHODOLOGY Market shares and advertising expenditures, by media type, at the brand, firm and product category level were gathered for 19 consumer non-durable product categories. Table III below lists the product cate- gories by name, the years for which compatible advertising and market share data are available and the number of firms and brands for which these data apply. The brand level market share data were obtained from'approxi- mately 50 issues of Advertising Agg from 1971 through 1976. Advertising_ ‘Agg_obtained some of the product category data from its own sources, and the remaining data were acquired from Maxwell Associates of Richmond, Virginia. Advertising expenditures matching the available market shares, including product category total advertising expenditures, were obtained from: LNA Class/Brand Year-to-Date Expenditures (New York: Leading National Advertisers, Inc., January-December, 1970-1975). LNA prepares its own Publishers Information Bureau, Inc. (PIB) Magazine Advertising Analysis for general consumer magazines and for nationally distributed newspaper Sunday supplements. Expenditures are based on current one-time gross rates before discounts. The broadcast expenditure data LNA publishes are obtained from Broadcast Advertisers 67 68 TABLE III INDUSTRY SAMPLE BREAKDOWN LNA* Product Categories 2 1: 13 2 TI 12 E E 6°49- s s 2: a a a E a l. D112 Lip and eye beauty products X X X X X X 18 00 2. D113 Perfumes X X X X X X 24 00 3. D114 Makeup X X X X X X 17 00 4. D115 Manicure preparations X X X X X X 12 00 5. D121 Toothpaste, mouthwash X X X X X 15 6. D122 Toilet Soap X X X X 16 7. D123 Feminine hygiene products X X X 00 8. D124 Deodorants X X X X X 10 14 9. D125 Shaving cream X X X X X 7 7 10. D141 Hair treatment X X X X X 10 26 ll. D142 Shampoo Rinses X X X X 13 27 12. F122 Cereals X X X X 7 47 13. F310 Beer . x x x. x 19 oo 14. F320 Wine X X X X X 24 00 15. G112 Cigars X X X X X 14 29 16. 6330 Restaurants X X X 27 00 17. 6531 Pet foods X X 21 35 18. H412 Detergents, light X X X X 8 19. H413 Detergents, heavy X X X X 21 tate all subsequent analysis and discussion. *Note that the first letter of the LNA code will be converted to its corresponding numeric value (i.e., D84, F36, G=7 and H88) to facili- 69 Reports, Inc. (BAR), which monitor every broadcast minute during the year for the three major television and radio networks. Average commercial minute costs for each program are provided to BAR by each network, based on the total revenues for each program before deduction of the agency commission. These rates are combined with the monitored brand activity to pro- duce brand expenditures. BAR monitors 260 television stations in 75 top markets one full week per month. BAR also contracts with a major advertising agency to provide commercial rates for each monitored station. These rates are a composite of this agency's experience in buying on these stations. Rates are individualized for each quarter hour, every day of the week, and are up-dated monthly. BAR combines the one-week data for 75 markets, projects it to monthly figures and produces national estimated brand expenditures. LNA publishes outdoor advertising expenditures in cooperation with the Institute of Outdoor Advertising and the Outdoor Advertising Association of America. Outdoor expenditures represent national, poster and paint advertising in plant operator markets over 100,000 population. For each of the 19 product categories for which brand and firm level market shares were available, corresponding media expenditures, by year, were obtained from LNA. Advertising media expenditures for each product category, firm and brand obtained from LNA include: (1) six media total advertising expenditures, (2) total magazine advertis- ing expenditures, (3) total newspaper Sunday supplement advertising expenditures, (4) total network television advertising expenditures, (5) total spot television advertising expenditures, (6) total network 81LNA Class/Brand Year-to-Date Expenditures (New York: Leading National Advertisers, Inc., January-December, 1974), p. ii. 82Ibid. 70 radio advertising expenditures and (7) total outdoor advertising ex- penditures. Other researchers have obtained brand level local newspaper ad- vertising expenditures from: Expenditures of National Advertisers in Newspapers (New York: Bureau of Advertising of the American Newspaper Publishers Association, 1967 and 1968).83 However, publication of the data ceased after 1970. And since the market share data available for this research covers the years 1970 through 1975, and since market share data for only one product category is available at the brand level for 1970 (see Table III above) and for only six product categories at the firm level for 1970, newspaper advertising expenditures have not been included. The implications of this omission are outlined in Chapter VI, Limitations, below. Pearson product moment correlations will be sufficient to directly examine the relationship between advertising sales ratios and advertising expenditures at the product category, firm and brand levels of aggregation. A significant positive correlation coefficient would be sufficient to reject the null hypothesis (Hypothesis I above). How- ever, in the event that the null hypothesis is rejected, the degree to which the advertising-sales ratio serves as a proxy for advertising expenditures is not testable. Rather, it is a matter for subjective interpretation upon which reasonable persons could disagree. Cobb-Douglas production functions will be estimated and will be checked for scale economies in accordance with Hypotheses II and III above. The logarithm of sales will be used as the dependent variable 83See the technical appendix for Michael E. Porter, "Interbrand Choice, Media Mix and Market Performance." 71 and the constant term and the logarithm of the absolute amounts of total advertising expenditures and each separate advertising media expenditure will be used as independent variables. The following equations will be estimated for each product category at the brand and at the firm levels of aggregation: log(Si) = log(a) + bllog(Ali) + ei, (l) log(Si) a log(a) + b210g(A21) + b310g(A3i) + balog(A4i) + b51°g(ASi) + b6log(A6i) + b7log(A7i) + e1, (2) Where: Si - total firm or brand sales, 1 - brand or firm level observations, where i = l, 2, ..., n, a - constant or intercept, A11 - firm or brand total advertising expenditures, A21 - firm or brand magazine advertising expenditures, A - firm or brand newspaper Sunday supplement advertising expenditures, A41 - firm or brand network television advertising expenditures, A51 - firm or brand spot television advertising expenditures, A61 8 firm or brand network radio advertising expenditures, A7i - firm or brand outdoor advertising expenditures, bJ - simple and multiple regression coefficients, where j - l, 2, ..., 7, and - residual, error or disturbance term. The simple and multiple regression analysis will ignore the time series nature of the data at the likely expense of an unknown degree of 72 serial correlation. The unequal number of years for most product cate- gories, and missing years for some brands within product categories, presents some difficult analytical problems. Therefore, a pooled cross- sectional time series analysis will be employed. Hypotheses II and III predict economies-of—scale to firm and brand advertising expenditures with sales as an output and total adver- tising expenditures and separate advertising media expenditures as in- puts. The coefficient(s) of the independent variab1e(s) derived from estimating simple and multiple regression equations (1) and (2) above must be checked to see if they equal one or (in the case of multiple advertising media expenditures) sum to one. If the coefficients equal (or sum to) one, there are constant average advertising costs per dollar or per unit of sales with increases in total sales; if (the sum of) the coefficient(s) is/are greater than one, there are economies of scale in advertising and if the (sum of the) coefficient(s) is/are less than one, there are diseconomies of scale in advertising. A further useful property of the Cobb-Douglas production func- tion is that each coefficient can be interpreted as the elasticity of sales with respect to the corresponding total or separate advertising media expenditures. Thus, if total advertising is increased by one percent, and all other inputs are held constant, sales will increase by bi percent. The same reasoning applies to the relationship between sales and each of the separate advertising media expenditures. To test the remaining hypotheses, the brand advertising media expenditure totals were divided by the corresponding industry adver- tising media expenditure totalsto obtain each brand's share of that product category's media or total advertising expenditures. An example 73 of the procedure is illustrated in Table IV below with 1974 advertising expenditures for Budweiser beer, manufactured by Anheuser-Busch, Inc. TABLE IV BUDWEISER-BEER INDUSTRY ADVERTISING SHARES: AN EXAMPLE Advertising . Budweiser Beer Industry Budweiser- Expenditure Media 84 Media 85 Beer Indus- Category Expenditures Expenditures try Media Shares Six Media Total $ 6,755,600 ' $ 89,415,000 .0755 Magazines 478,000 3,666,300 .1303 Newspaper Sunday Supplements 00 36,000 .0000 Network Television 5,587,700 26,552,200 .1690 Spot Television 1,023,500 54,713,000 .0187 Network Radio 675,900 1,010,100 .6691 Outdoor 90,600 3,437,400 .0263 Simple and multiple linear regression analysis will be utilized to estimate the relation between brand market shares and total advertis- ing shares and between brand market shares and individual media shares. Each of these relationships will be estimated across the 11 product categories with brand level data (pooled) as well as within each of the 11 product categories. Total and individual media advertising shares will be regressed on brand level market shares as follows: Yi - a + blxli + e1, (3) Y1 ' a +’b2X2i + b3X3i + b4X41 + bSXSi + b6x6i + b7X7i + e1, (4) 84Ibid., p. 191. 85 Ibid., p. 193. Y Where: X11 21 31 41 51 61 71 81 8 a + b X + b X + e brand brand 74 4 4i 8 81 market share, level observations, where i = l, 2, ..., n, constant or intercept, brand brand brand brand brand brand brand brand total advertising share, magazine advertising share, newspaper Sunday supplement advertising share, network television advertising share, spot television advertising share, network radio advertising share, outdoor advertising share, share of all advertising media expenditures except network television advertising expenditures. simple and multiple regression coefficients, where j - 1, 2, ..., 8, and residual, error or disturbance term. To test Hypothesis IV, which suggests that differences are (5) likely to exist across all product categories with respect to the rela- tionship between a brand's market share and a brand's share of total advertising expenditures, an overall F ratio will be computed. ing for sample sizes and degrees of freedom, the overall F ratio will be based on a comparison of the error sums of square for the pooled Adjust— simple regression, total advertising share model (see Equation 3 above) with the total of the error sums of square for each of the 11 separate 75 simple regression, total advertising share models (also see Equation 3 above).86 Similarly, to test Hypothesis V, which extends Hypothesis IV to include six separate advertising media shares instead of total ad- vertising shares, an overall F ratio will again be computed. Again, adjusting for sample sizes and degrees of freedom, the overall F test will be based on a comparison of the error sums of square for the pooled multiple regression, advertising media share model (see Equation 4 above) with the total of the error sums of square for each of the 11 separate multiple regression, advertising media share models (also see Equation 4 above). If total advertising shares or individual advertising media shares vary systematically across product categories with respect to their relationship to market share, as indicated by a significant over- all F ratio, it would be misleading to use ordinary least squares on the pooled sample. An F statistic which rejects the null hypothesis would suggest additional analysis taking into consideration differences in parameters which occur when moving from one product category to another. The t ratio is appropriate to test for positive and significant total advertising share regression coefficients within each of the 11 product categories suggested by Hypothesis VI (see Equation 3 above). Likewise, the t statistic is also appropriate to test for positive and significant advertising media share regression coefficients within each 86For a fuller discussion of the test, see Jan Kmenta, Elements of Econometrics (New York: The MacMillan Company, 1971), pp. 373-374. This test allows for all regression parameters to change when moving from one product category to another. 76 of the 11 product categories suggested by Hypothesis VII (see Equation 4 above). To test Hypothesis VIII, that within a product category not all advertising media share regression coefficients are equal, an F sta- tistic will be computed, adjusted for sample sizes and degrees of free- dom, by comparing the error sums of square for the reduced total adver- tising share model (see Equation 3 above) within a product category with the error sums of square for the full six media share model (see Equa- tion 4 above) within the same product category.87 A significant F ratio would indicate that within that product category not all advertis- ing media shares affect market share equally. It is then appropriate to proceed to identify which of the six advertising media shares within a product category are the most strongly associated with market share. To test Hypothesis IX, that network television advertising shares are more strongly associated with market share than are the shares of all other advertising media expenditures combined, an F test will again be computed for each product category after respecifying the multivariate equation to include only two independent variables: the network television advertising share and the share of all other ad- vertising media expenditures combined (see Equation 5 above). This F test essentially determines whether within a product category the net- work television advertising share regression coefficient equals the regression coefficient of the share of all advertising media 87For the specific test used, see Fred N. Kerlinger and Elazer J. Pedhazur, Multiple Regression in Behavioral Research (New York: Holt, Rinehart and Winston, Inc., 1973), pp. 233-237 and Harry H. Kelejian and wallace B. Oates, Introduction to Econometrics: Principles and Applications (New York: Harper and Row, 1976), pp. 178-181. 77 expenditures combined. Adjusting for sample sizes and degrees of free- dom, this F statistic will be computed for each product category by comparing the error sums of square for the reduced total advertising share model (see Equation 3 above) for that product category with the error sums of square for the full, two-media share model (see Equation 5 above) for the same product category.88 A significant F ratio would indicate that within that product category network television adver- tising share explains significantly more of the variation in market share than the share of all other advertising media expenditures com- bined. Finally, in the unlikely event that advertising-sales ratios are highly correlated with advertising expenditures, as expected in Hypothesis I above, then it might be useful to duplicate the regression equations used to test Hypotheses 11 through IX above using advertising- sales ratios instead of advertising expenditures or the logarithm of advertising expenditures. Therefore, total and individual media ad- vertising-to-sales ratios will be regressed on brand level market shares as follows: Y1 = a + blxli + e1, (6) Y1 =- a + bzx21 + b31131 + b4X41 + b5X51 + b6X61 + b7x7i + e1, (7) Where: Y = brand market share, 1 = brand level observations, where i = l, 2, ..., n. a = constant or intercept, 88For the specific test used see, Harry H. Kelejian and wallace E. Oates, Introduction to Econometrics: Principles and Applications, pp. 178-181 and Fred N. Kerlinger and Elazer J. Pedhazur, Multiple Re- gression in Behavioral Research, pp. 233-237. 11 21 31 41 51 61 71 = brand - brand = brand = brand - brand a brand 8 brand 78 total advertising-to-sales ratio, magazine advertising-to-sales ratio, newspaper supplement advertising-to-sales ratio, network television advertising-to-sales ratio, spot television advertising-to-sales ratio, network radio advertising-to-sales ratio, outdoor advertising-to-sales ratio, - simple and multiple regression coefficients, where 1‘1. 2, ..., 7, and = residual, error or disturbance term. The results of this comparison might shed some light on how previous research, which relied heavily on the advertising-sales ratio, may or may not have led researchers to the wrong conclusions. However, no a priori hypotheses regarding the direction and the magnitude of these differences are feasible. CHAPTER V EMPIRICAL RESULTS Advertising-Sales Ratios Versus Advertisipngxpenditures Hypothesis 1, which predicts no correlation between advertising- sales ratios and advertising expenditures, clearly was rejected. Table V below presents the correlation coefficients, coefficients of determi- nation, significance levels and sample sizes based on pooled estimates across 16 of the 19 product categories and on estimates for each of the 16 separate product categories at the product category, firm and brand levels of aggregation. Advertising-sales ratios appear to most closely parallel adver- tising expenditures at the industry level of aggregation, while the relationship deteriorates substantially at the firm and at the brand level of aggregation. Although Hypothesis I clearly is rejected, the question that the statistics in Table V must still address concerns whether the advertis- ing sales ratios is a "good" proxy of advertising expenditures. This is an important question, since a high correlation between the two measures of advertising has been implicitly assumed to exist in prac- tically all of the research to date dealing with the economic effects of advertising. If the correlation between the two measures of adver- tising, which apparently has never been estimated directly due to lack 79 80 TABLE V CORRELATION COEFFICIENTS BETWEEN ADVERTISING-SALES RATIOS AND ADVERTISING EXPENDITURES Product Category/Aggregation Level R R Alpha N Pool* Industry .60 .36 .01 67 Firm .14 .02 .01 615 Brand .17 .03 .01 686 4112-Lip and Eye Beauty Products Industry .96 .93 .01 6 Firm -.01 .00 .45 75 4113--Perfumes Industry .87 .75 .01 6 Firm .39 .15 .01 101 4114--Makeup Industry .77 .59 .03 6 Firm .49 .24 .01 56 4115--Manicure Preparations Industry .99 .98 .01 6 Firm .04 .01 .40 36 4121--Toothpaste and Mouthwash Industry .79 .63 .05 5 Firm .62 .38 .01 30 Brand .34 .ll .01 62 4122-Toilet Soap Industry -.47 .22 .26 4 Firm .44 .20 .02 20 Brand .26 .07 .02 53 81 TABLE V--Continued Product Category/Aggregation Level R R2 Alpha N 4123--Feminine Hygiene Products 1 Industry .68 .47 .25 3 Firm .68 .47 .01 19 4124--Deodorants Industry .52 .27 .18 5 Firm .09 .01 .27 41 Brand .16 .02 .11 52 4125--Shaving Cream Industry .29 .08 .31 5 Firm .91 .84 .01 25 Brand .40 .16 .01 27 414l-Hair Treatment Industry .99 .98 .01 5 Firm .09 .01 .27 40 Brand .20 .04 .01 100 4142--Shampoo and Rinses Industry -.15 .02 .42 4 Firm .33 .ll .01 47 Brand .14 .02 .08 93 6122--Cereals Industry -.98 .97 .01 4 Firm -.40 .16 .01 31 Brand .41 .17 .01 156 7330--Restaurants Industry .99 .98 .04 3 Firm .50 .25 .01 66 82 TABLE V--Continued Product Category/Aggregation Level R R2 Alpha N 753l--Pet Foods Industry N/A N/A N/A 2 Firm .38 .14 .02 28 Brand .27 .07 .01 64 8412--Detergents, Light Industry .14 .02 .42 4 Firm .72 .52 .01 13 Brand .18 .03 .16 29 8413--Detergents, Heavy Industry .91 .84 .12 3 Firm .31 .10 .15 12 Brand .09 .01 .21 76 *Note: Four product categories were deleted from the pooled correlations. Product categories 6310 (Beer), 6320 (Wine) and 7112 (Cigars) reported sales in barrels, gallons and units respectively. Therefore, advertising sales ratios for these product categories are not comparable to those of other product categories. Product category 4125 (Shaving Cream) is reported above separately, but is not included in the pooled correlations because its advertising-sales ratios are unusually high in comparison to other product category advertising-sales ratios. For example, when product category 4125 is included, the pooled product category correlation drops .33 to .27, the pooled firm correlation in- creases .02 to .16 and the pooled brand correlation remains .17, and all are still significant at the .01 level. 83 of sufficient data, is low, previous conclusions may have been based on a poor or biased estimate of advertising. But Table V does not allow the luxury of an easy conclusion. Nevertheless, some generalizations seem apparent. The correlation is always less than one at every level of aggregation, which means that the advertising-sales ratio is certainly not a perfect proxy of advertising expenditures. Across the 16 product categories a positive and signifi- cant .60 correlation between the two measures of advertising exists at the industry level of aggregation. Only half of the 16 separate product category correlation coefficients are significant at least to the .10 level. Of these, one correlation coefficient is significantly negative at -.98 (see 6122, Cereals, in Table V above), while all other correla- tion coefficients are positive with four greater than .90 and the other three greater than .77. Since the pooled industry correlation coefficient is greater than .50, it seems safe to conclude that the advertising-sales ratio is, on average, a fair to good proxy of advertising expenditures. But that interpretation is subject to dispute. In some specific product cate- gories the ratio can be an excellent proxy of advertising expenditures, exhibiting very high, positive correlations. But, in still other product categories, it can be extremely poor, exhibiting very high, negative correlations. At the firm and at the brand levels of aggregation, however, it must be concluded that the advertising-sales ratio is, on average, a very poor proxy of advertising expenditures. For firms, the pooled cor- relation coefficient equals .14 and is significant at the .01 level and 84 for brands the pooled correlation coefficient equals .17 and is signifi- cant at the .01 level. At the firm level of aggregation ten of the 16 correlation co- efficients are positive and significant at least to the .05 level and range from .33 (see 4142, Shampoo and Rinses, in Table V above) to .91 (see 4125, Shaving Cream, in Table V above). But the correlation co- efficient equals -.40 in one product category (see 6122, Cereals, in Table V above) and is significant at the .01 level. Again, the varia- tion in the correlation between the two measures of advertising at the firm level indicates that the advertising-sales ratio, on average, is a poor proxy of advertising expenditures. But, at the firm level, the advertising-sales ratio can be a good proxy of advertising expenditures in many product categories and it can be a very poor proxy in still other product categories. Seven of the 11 product categories for which brand level data are available exhibit correlation coefficients between advertising-sales ratios and advertising expenditures that are positive and significant at least to the .10 level. These correlation coefficients range from .14 (see 4142, Shampoo and Rinses, in Table V above) to .41 (see 6122, Cereals, in Table V above). At the brand level of aggregation none of the significant correlation coefficients are negative. Interestingly, the cereal industry correlation coefficient is significantly positive at the brand level of aggregation, but is significantly negative at both the firm and the industry levels of aggregation. In summary, it appears that there is a wide range in the corre- lation between advertising-sales ratios and advertising expenditures at the industry level of aggregation, but the average correlation is 85 moderately high. At progressively narrower levels of aggregation the range in the correlation is progressively narrower, but the average correlation is low. One could speculate that if the correlations improve at pro- gressively greater levels of aggregation, then perhaps the correlations are very good at three and four-digit IRS and SIC levels of aggregation. That is the level at which the bulk of previous research on the effects of advertising on competition has occurred. Given the large variation in the relationship between advertis- ing expenditures and advertising-sales ratios, it would be useful to compare the regression results below, that will be used to test the remaining hypotheses, with regression results derived from using adver- tising-sales ratios instead of advertising expenditures and advertising shares. Such a comparison might shed light on the question of whether the use of advertising-sales ratios in previous research has led researchers to the wrong conclusions. Economies of Scale in Firm and Brand Advertising Table VI below lists 60 regression equations obtained from re- gressing firm or brand sales (in units or in dollars), in logarithmic form, on total or separate advertising media expenditures in logarithmic form. The rows of Table VI contain one simple and one multiple regres- sion equation at the firm level of aggregation for each of 19 available product categories. Table VI also contains one simple and one multiple regression equation at the brand level of aggregation for each of 11 product categories for which brand level data are available. The columns of Table VI include: (1) the years for which the data are 86 afloao.v Assam.v mates . om moo.a~ mm. «amen. moao.m m-oeaa Aomao.v Aeoso.v Aoqmo.v Assao.v Amomo.v Aoao~.v wanes om mwo.m es. --- some. maao.- awoke. nmoqo. scene. meow.o n-oasfi mmoxmz-SHHS AoNoo.v Aesom.v mania HOH «Na.om om. «make. mmuo.s m-oaaa Anamo.v Ammoo.v Aaqao.v Aaaao.v Ammoo.v haaoo.v Acmma.v mange Hod mmq.m an. ammo.- oomao. «mesa. mmao. momma. «ammo. uoo~.~ m-okaa mmaamumm-maas AquH.v Amqmc.v mauwm ma mo~.wa ma. «moms. msmm.e m-ohaa assmo.v isomo.v isomo.v Awomo.v Aamwo.v Amamm.v mania mm mom.o mm. -- «sacs. BANGO. ms~o.- cake. amoa.- meow.~ m-oama muosmoum Nwmmom ohm mom mag-Imaac z m mm >omuoua Housed unmsosq bummed smmmeA >uonmg uxauodq sumaooa Amvumow mama-ohma .mmHmoomso< azamm mo zens zo Auoav mma m4momuou4 Housed unmamsq ouuosA snowmaq >uoamq uxaumsa summooa Anyhow» omzcfiucoollH> mamomu0ua Housed unmsmsg unused :ummeA >uonma ux3umsA aumaooA Amvummw wmsafiuGOUllH> m4maem-mmae z m «M >omu0ua upusoq Hanson; ouuosg snowmag >uonm4 uxauosq sumsooq Amvumow UmacwuaoollH> mqm<fi 90 Anamo.v Accae.v mEuHm Hm mmm.mmm Hm. meo.H oe~¢. mlmnaa Ammoo.v Amoco.v Amoco.v Awmeo.v Acmmo.v Awmqo.v Ammqm.v maufim Hm mmH.Hm mm. mmqoo. acmao.l Hmoo.l Hm~0.I Denna. cameo. mm¢~.~ mlmnma Ammao.v Anamo.v mosmum oma mmN.Hm ca. mamas. momm.o mlmmma Amwmo.v fiasco.v Aooao.v Ammoo.v Ammao.v Ammoo.v Amsaa.v museum oma mw~.oa mu. cameo. “Hoo.u mmoo. mmnao. nmmwo. muwmo. mam~.~ nlumaa mamouoollmmfic Aoeqo.v Amemm.v msuam sq mmc.mm we. mcmwm. m~mo.m mlwnma Aamao.v Aeoao.v Ameao.v Aumoo.v Acnao.v Aquna.v mange we mmH.HH mm. IIIII mooco. mqao. omqmo. mooo. emcee. moo~.n mlmnma Aeeco.v Am¢c~.v mosmum mm mwm.qm mm. «meow. mqom.m mINan ahkao.v Ammao.v AHHHo.v asmmo.v aaoao.v Am~sa.v season mm mmm.w mm. III-I mmsqo. commo. waoo.l mnwo.| moomo. moo~.~ mummma momcfim use oomamnmllmqaq z m NM >omu0ua Housed nomads; vuuosq snowmen >uoemg uxsuosa summooq Amvummw vmscfiufioollH> mqmflwu cu..— HUUfiOH HQmbQA chum—HA cumwms >uoama— uiBuUfiA flumcood Any Hum? wmacfiuaoollH> mqmomu0uq wousoq unnamed ouumsq snowmen >uoemq uxzuosg sumsooa Amvumow omaafiuaoollH> mqm<fi 93 .mumaaoo ca mum moamm knowoumu Desmond nocuo HH< .ham>«uooommu mode: can msoaamw .mamuumn SH moamm moanedmu Amumwaov «an» new Amsuzv oume .Aummmv Came mofiuowoumo mosooum .huommumo mooooud you mousuwosoaxo o: moumoaosfi :IIIII: was momm0fimaswfim mo Ho>ma OH. moumofioma :u: noosmofimwswam mo Ho>mH moosmofimaawwm mo Ho>MH Ho. mouoofimsw :m: «monogamouma :H muouum wumosmum "ouoz moumoaosw :n: Annma.v Aasmm.v maufim NH mm~.sH mm. mmem. msmm.s mlunma Anamo.v Ammoo.v cho0.v Amwoo.v Acm-.v AanH.V AmmH.Hv magma NH mos.mH mm. mmao.- whoo. mmaso.| momma. mNNH. mmoa. mmmm.o nlmmma Ammso.v Asmom.v «oo«um on mNs.cNH Ho. «womm. soa.s mlmnaa Amsso.o Amoso.o Aomso.o amaso.o Amoos.o Ammso.o Assam.o «oo«um on ch.~H Hm. emmo.- ssmo. smoo. NNHO. msmsm. manso. mmww.m mlmnma h>mm= «musowumuonllmasw Auhmo.o Asmom.v «ease ma wus.sca mo. mmsmn. mosm.~ mlmnma Aoooo.o Amaoo.o AHANH.V ammmo.v asnoa.o «some ma www.mm so. lllll mwoo. IIIII Hooo.l moham. mmsom. mmmm.~ mummoa mossausoollunwfia «musmwumumnllmasm z m mm >omuoug nousoq unnamed muons; snowmeq >o0qu uxsumsq sumsooq Amvumm» vmsawucoollH> mumouuomm >u33umz usumsoo ooou mums-ohms .mmmmoomaso soooomm as mom Ammomz moms momsmm oszHamm>o< ozsmm zo momsom seems: ozsmm so monmmmmomm HH> mqm<8 100 Awomo.v AnHNH.V Amasa.v aNamo.v asoao.v aN oNHo. msH.oN mmam. lllll wmoo.l IIIII Amman. HsHN. scams. NoHc. Nst Ammoo.o Ammoo.o .so mmoo. mso.oo omam. mmmmm. momoo. Hmmm Aksmo.v Anamo.o assso.o Amooo.o Aooao.o Ammoo.o so snoo. mnm.sa Nmom. mHNo. mmNo.- III-I HmHo. shoe. moanm. mmwoo. ammo Ammao.o Amsoo.o ooH NONH. mma.sN moms. momso. mNmHo. NHHN AmoNo.v Ameo.V Anaoo.v ANNso.v Ammso.v Amoco.v ooa NNoo. moo.ms ammo. mmooN. ooao. IIIII Hsso. omHo.I mNNoN. mmoNo. NHHN Aomoo.o Ammoo.o oma mmNo. oHH.sm Nmmm. mowmm. mwmoo. NNHo Amooo.o xooHo.o Amoso.v Aooso.v Asomo.o Aesoo.o oma ONNo. mMN.ON omss. mmomo. Homo. mooo. III-I mHHma. mosns. «once. NNHo Aamoo.v AoNoo.V mm NmNo. mmm.NON sooo. shown. onsoo. NsHs aNoHo.v Amado.v Aomso.v Amono.v AmNmo.v AmNoo.V mm mNNo. moa.mm Nmmm. IIIII msao. osoo. nsmmo. oaso.| mmwso. smooc. Nsas Aomso.v AsNoo.v coa nmmo. was.maa Nmsm. mamas. mmHHo. HsHs 2 wow N Na w>ouuoom >uxauoz usumsoo ooou ouncHHSOUIIHH> Manda 101 .mumaaoo sH mouswfiw oumam uoxums memosoamouuou ozu aouw hausmUNmNswam Homwao uo: masonm muss: so mmuawwm oumnm moxuma madam mum: muaomou osu momwmm mo: oasonm mocmuommao umsu mom .mumHHoo so mouuodou mum mouswam moamm anomoumo Desmond Honuo HH< .mumaaov no: .muaa: sH composes mum aNHHNV mumwfio now mouswfim moamm m:H .soamsaosfi omfi3noum you oaam> m Enafiawa moms mos vac oHAmHum> no huowoumo uosooun How mousu Ifioamdxo o: nosufio mmumooosa :IIIII: pom ouomowmwswfim mo Ho>oa OH. moumowosw :o: nonsmowmfiswfim No Ho>oa no. mmumooosw :n: moosmommfiswfim mo Ho>oH Ho. moumomosfi :o: "momosusmumd so muouuo ousosmum "ouoz AHNNo.V Aoaoo.v mam omwm. moN.wmm Noon. mussm. meoo. Hoom nomao.v Ammao.v Aomoo.v AsONo.v AoNNo.v AmmNo.v Aoaoo.v mam mmam. mNN.mmH Nasm. onNo. mmoo.l maaNo. momoa. mmoo. mNNmn. «some. Hoom Aomac.v Amoco.v on name. msH.NHH sNoo. mmooo.H nnoo.l masw AmNNo.v Asmmo.v AsHHo.v AMNNo.v Anmso.v Ammso.v Ammoo.v oN mmNo. mam.aoa owam. mono.| soso. wmoo. msNHm. oasc. mmsms. omooo. masw Asmwo.v anoo.V aN omHo. mms.mOH Nomn. momoo. omoc. NHsm 2 wow m NM w>ouuonm >uxsuoz usumsou oooo omnafiu600IlHH> mgmdfi 102 Support was found for the hypothesis that differenées exist across product categories, even within the consumer non-durable goods sector of the economy, between a brand's market share and: (l) a brand's share of all product category advertising (Hypothesis IV), and (2) a brand's share of product category expenditures in each of the six separate advertising media (Hypothesis V). The test of the null hy- pothesis for equal parameters for all product categories resulted in an overall F value of 164.05 for the reduced model with total advertising shares as the independent variable and an overall F value of 115.63 for the model with the separate media shares as independent variables. It can therefore be misleading to use ordinary least squares on the pooled data. Instead, each product category should be examined separately. Hypothesis VI, which states that there is a positive relation- ship between a brand's market share and a brand's share of all adver- tising expenditures, is strongly supported. The coefficient for total advertising is positive and significant at least at the .05 level in 2222 of the 11 product categories. The total advertising coefficient actually exceeds 1.00 in three product categories (Toothpaste, Mouth- wash, 4121; Shaving Cream, 4125 and Heavy Detergents, 8413) and is slightly below .50 in only one instance (Hair Treatments, 4141). There were 54 opportunities to test Hypothesis VII, which states that there is a positive relationship between a brand's market share and a brand's share of expenditures in each of six separate advertising media. But the hypothesis received support at least to the .10 level in only 22 of these instances. Two media share coefficients in the same product category (see network radio and newspaper Sunday supplements in Toothpaste, Mouthwash, 4121, in Table VII above) were actually negative 103 at the .05 level, while the remaining 30 coefficients were not signifi- cantly different from zero. At least one media share coefficient in each product category failed to reject the null hypothesis. One product category had only one positive media share coefficient significantly different from zero at the .01 level (see Pet Foods, 7531, in Table VII above), and only one product category had three positive media share coefficients significantly different from zero at the .01 level (see Cereals, 6122, in Table VII above). Each of the remaining product categories had two media share coefficients significantly different from zero at least at the .10 level. Interestingly, in gagh sampled product category, the network television advertising share coefficient was positive and significant-- at the .01 level in ten of the 11 industries and at the .05 level in the remaining industry. No other media category rejected the null hy- pothesis as conclusively. In fact, the null hypothesis was positively rejected for magazine advertising shares only four times out of ten op- portunities. Spot television positively rejected the null hypothesis three times out of 11 opportunities. Network radio and outdoor each positively rejected the null hypothesis twice out of 8 and 4 opportuni- ties respectively. The research hypothesis found no positive support out of ten opportunities for newspaper Sunday supplements. Hypothesis VIII states that within each product category dif- ferences exist in the relationship between a brand's market share and a brand's share of expenditures in each of the six separate advertising media. The hypothesis was assessed by testing for the equality of re- gression coefficients within each product category. This was accom- plished by computing F statistics based on comparing the error sums of 104 square for the reduced total advertising share model within each product category with the error sums of square for the full six media share model within the same product category. The appropriate F statistics are displayed in Table VIII below. TABLE VIII RESULTS OF TESTS FOR EQUALITY OR REGRESSION COEFFICIENTS WITHIN PRODUCT CATEGORIES Product Product Category F Ratio Category F Ratio 4121 3.38b 6122 6.48a 4122 5.38a 7112 22.89a 4124 4.738 7531 1.76 4125 5.263 8412 0.73 4141 0.14a 8413 40.053 4142 5.60 Note: "a" indicates F ratio significant at the .01 level, "b" indicates F ratio significant at the .05 level. Table VIII indicates that the null hypothesis was not rejected in three product categories (Hair Treatment, 4141; Pet Foods, 7531 and Light Detergents, 8412). From this it can be concluded that in the remaining eight product categories examined, not all media shares are equally associated with market share--some media shares are more strongly associated with market share than others. Furthermore, since some of the regression coefficients are significantly different in eight of the 11 product categories examined, an interaction between some media shares is indicated--a potentially fruitful possibility for future re- search. 105 Network Television Advertising Shares Hypothesis IX states that network television advertising shares are more strongly related to market share than the share of all other advertising media combined. The hypothesis was tested both indirectly and directly. Since the relative contribution of each of the media shares were not significantly different in three of the product cate- gories (see product categories 4141, 7531 and 8412 in Table VIII above), the null hypothesis cannot be rejected here. The hypothesis can be tested for the remaining eight product categories however. Stepwise multiple regression was employed, since the first media share entered into the estimated equations will be a good indicator that the variable explains more of the variation in the market share than those media shares not yet entered into the equation. In addition, an indication of the relative importance of the media share can be veri- fied by examining its beta weight (standardized regression coefficient) in relation to all others estimated in the equation. In five of the remaining eight product categories then (see 4121, 4122, 4124, 4142 and 6122 in Table VII above), network television advertising shares were entered into the regression equation first. And the corresponding beta weights suggest that network television adver- tising shares are indeed the most important variables in the final estimated equations. In the remaining three product categories (see 4125, 7112 and 8413 in Table VII above), network television advertising shares were entered secondly into the estimated equations after network radio, outdoor and magazines respectively. And the corresponding beta weights further suggest that in these product categories network tele- vision advertising shares are also second in importance. Therefore, it 106 is concluded that although network television advertising shares are positively and significantly related to market shares in every product category sampled, in only five of these product categories can it be suggested that network television advertising shares are the most im- portant contributors to market share. The estimated regression equations useful for testing Hypothesis IX directly are listed in Table IX below and the test results for the research hypothesis are presented in Table X below. Table IX is or- ganized in the same manner that Table VII above is organized except that only two independent variables (network television advertising shares and five-media advertising shares) are included in the regression equa- tions instead of six separate advertising media shares. Table X lists the F statistics which test for the equality of regression coefficients within each product category. The F ratio was computed, after adjusting for sample sizes and degrees of freedom, by comparing the error sums of square for the reduced total advertising share model (see Column 12 of Table VII above) with the error sums of square for the full, two-media advertising share model (see Column 7 of Table IX below). Once again, in every product category, the network television advertising share regression coefficient is positive and significant at the .01 level (see Column 3 of Table IX below). On the other hand, the five-media advertising share regression coefficient is positive and significant at the .01 level in five product categories and is positive and significant at the .05 level in one product category. The five- media advertising share regression coefficient is not significantly 107 TABLE IX REGRESSIONS OF BRAND MARKET SHARES ON BRAND ADVERTISING SHARES (TWO MEDIA) FOR 11 PRODUCT CATEGORIES, 1970-1975 CODE CONSTNT NETWKTV SMEDIA 32 F SSE N 4121 .0033 .8884a .43428 .7094 72.06a .0831 62 (.0074) (.1734) (.1532) 4122 .0154c .66698 .0170 .5682 32.898 .0647 53 (.0089) (.0881) (.1159) 4124 .01968 .7826a --.1564c .6881 54.053 .0519 52 (.0074) (.0816) (.0894) 4125 .0516 1.77498 -.5817 .3385 6.14a .1099 27 (.0351) (.5403) (.5758) 4141 .0106a .36628 .1323a .5419 57.398 .0340 100 (.0025) (.0587) (.0486) 4142 .0769a .64523 .0420 .7300 121.688 .0251 93 (.0025) (.0511) (.0686) 6122 .00938 .4277a .15968 .3739 45.68a .0250 156 (.0017) (.0594) (.0520) 7112 .0105a .2207a .49563 .4673 45.188 .1096 106 (.0041) (.0552) (.0750) 7531 .0075a .37958 .0868 .5516 37.52a .0077 64 (.0023) (.0538) (.0796) 8412 .0074 .4227a .53533 .7980 51.358 .0184 29 (.0086) (.0907) (.1293) 8413 .0028 .8049a -—--- .6909 165.463 .0774 76 (.0049) (.0625) Note: Standard errors in parentheses, "a" indicates multiple re- gression coefficients and F ratios are significant at the .01 level; "b" indicates .05 level of significance, "c" indicates .10 level of significance and "----" indicates that the variable did not meet the minimum F value for stepwise inclusion. 108 TABLE X RESULTS OF TESTS FOR EQUALITY OF REGRESSION COEFFICIENTS WITHIN PRODUCT CATEGORIES Product Product Category F Ratio Category F Ratio 4121 0.85b 6122 4.89: 4122 6.33 7112 9.96b 4124 15.29: 7531 4.75 4125 5.83 8412 0.28 4141 1.42 8413 20.848 4142 12.91a Note: "a" indicates F ratio significant at the .01 level, "b" indicates F ratio significant at the .05 level. different from zero in the remaining five product categories (see Column 4 of Table IX above). In ten of the 11 product categories (the exception is 7112), network television advertising shares appear to be more important in' explaining market share than the share of all other advertising media categories combined as indicated by stepwise multiple regression and by an examination of standardized regression coefficients. However, in three of these product categories the two advertising media coefficients are not significantly different (see 4121, 4141 and 8412 in Table X above). From these results it might be concluded that in seven of the 11 product categories (4122, 4124, 4125, 4142, 6122, 7531 and 8413), net- work television advertising shares are the most important media shares associated with market share. However, with the six-media regression equations (see Table VII above) the indirect tests of Hypothesis IX dis- cussed above indicated that in two of the remaining seven product cate- gories (4125 and 8413) that stepwise multiple regression and that an 109 examination of standardized regression coefficients revealed that net- work television shares were, in fact, second in importance to network radio advertising shares and magazine advertising shares respectively. Furthermore, no significant differences were found among the six sep- arate advertising media share coefficients in product category 7531 al- though significant differences were found in the two-media model for that product category. This leaves only four product categories (Toilet Soap, 4122; Deodorants, 4124; Shampoo, Rinses, 4142 and Cereals, 6122) in which it is clearly correct to state that network television adver- tising shares explain significantly more of the variation in market share than the share of any other advertising media category. It appears then that a direct test of research Hypothesis IX, while preferable to an indirect test using stepwise inclusion and standardized regression coefficients as indices of relative media share importance, can be misleading. This suggests that separate media ad- vertising expenditures should be employed whenever available. As a further test of this proposition, the F ratio was again computed for each product category after adjusting for degrees of free- 1 dam and sample sizes by comparing the relative efficiency (sums of squared error) of the reduced two-media share regression equation em- ployed here (see Column 7 of Table IX) with the relative efficiency (sums of squared error) of the six-media share regression equation above (see Column 12 of Table VII). The results are listed in Table XI below. Table XI suggests that in seven product categories the six media regression model has significantly less unexplained variation than the two variable equation, while in the remaining four product categories it cannot be said that the two models are significantly different. 110 TABLE XI RESULTS OF TESTS COMPARING THE RELATIVE EFFICIENCY OF THE TWO-MEDIA SHARE MODEL WITH THE SIX-MEDIA SHARE MODEL Product Product Category F Ratio Category F Ratio 4121 4.306 6122 6.828 4122 4.60a 7112 25.188 4124 1.20b 7531 0.78 4125 4.39 8412 1.02 4141 0.28b 8413 28.09a 4142 2.81 1'— Note: "a" indicates F ratio significant at the .01 level, "b" indicates F ratio significant at the .05 level. Therefore, the six media share model is the appropriate choice since it provides more information than the two media share model and is gener- ally more efficient. Advertising-Sales Ratios and Economies of Scale in Advertising The results in Tables VII and IX, which predict market shares on the basis of advertising shares, are in essential agreement with the results in Table VI, which predict the log of sales on the basis of the log of advertising expenditures. For example, the pooled equation in Table VII indicates that a company which has a four percent as opposed toa three percent share of the advertising expenditures of all brands will, on average, have a .84 percent higher share of product category sales. That seems to imply increasing advertising costs as the sales of the firm increase. And, except for the cereal industry, Table VI, which presents the results of direct tests of economies of scale in lll advertising, also indicates strongly decreasing returns to advertising at both the brand and the firm levels of aggregation. But, since it was indicated in Table V above that there is a low correlation between the advertising-sales ratio and advertising expendi- tures, further analysis using advertising-sales ratios instead of the log of advertising expenditures or advertising shares might provide ad- ditional insight. In particular, a comparison of regression results using advertising-sales ratios with comparable regression results using the log of advertising expenditures or advertising shares might help determine whether previous use of the advertising-sales ratio has led economists to erroneous conclusions. Therefore, Table XII below was created to examine how the regression results might differ using adver- tising-sales ratios instead of the log of advertising expenditures or advertising shares. Table XII is organized in the same manner as each of the previous regression tables. The coefficient for total advertising expenditures-to-sales is always negative--a finding that previous researchers would have inter- preted as suggesting increasing returns or economies of scale in ad- vertising since advertising intensity decreases as market share in- creases. But this interpretation contradicts the direct tests of economies of scale in advertising reported above. Furthermore, it suggests that the use of the advertising-sales ratio can indeed lead researchers to the wrong conclusions. For example, the pooled total advertising-sales equation in Table XII indicates that a firm with a four percent as opposed to a three percent advertising-sales ratio will, on average, have a .03 percent lower share of product category sales. 112 amaoa.o hammo.o NN aaNa. mNm.a maNN. masos.l momma. mNas amm.oso aoms.ao aaomm.o aooma.o asomo.o NN mmoo. ssm.m Nmao. mh.a0N oomo.l Ammom.l nmwam.l mNmoa. mNas Aosmo.v Aooao.v No ms.ma Nm.m NNNo. ommoo.- oaomo. sNas aomas.o aasm~.o aoaoa.o aomao.o amoao.o Nm mmNa. oaa.s NmmN. moaa.al osmm.| oNNNm.I momma. msmmo. .sNas amomo.o amoao.o mm Nmsa. os.a mNNc. mano.l maNNo. NNas AoN.wav aNma.Nv Amma.av aNNoo.v Amoma.v nomao.v mm mama. am.a sNNa. NNm.N moNo.I ONmoa.I Nmma. msmmo. NNas Aammo.v Amsao.v No oomN. mN. Nsoo. oosc.l «muse. aNas ahmo.ao Aoomm.o asama.o aosao.o No ssoN. ma.a homo. bmo.Na- mNm.a| oNom.a III-I sMNo. mmmoo. aNas z Mmm m NM m\< uoa uooouao nonmaoz oaouuoz msnmwmz >uuoam >ux3umz usumsoo oooo HHX MAQo< ozuu0dm >uxsumz usumcou moou nmaaaucoollaax mamoom aax manna ca kHONOumo mosooud umsu How muasmou amoamxum mam camamxm oasoa noaga Ao>onm > manmfi oomv swan zaamsmsss mum AmNasv ammuo wsa>m5m How moaumu moammlwsamauuo>om osu umsu aamuou ou asmaaon on omam mamas ma .mmauowmumo mosooun “onus mo mmuswam moamm umaaoo mouuonou mzu cu maamumnaoo on me: snowmuonu oa=o3 mam moan: ca coauoomu mum mmumwam mmamm umwau madam o>onm mamhamsm onu ma oomsaosa some uos mm: muomoumo musooun umzu .ANaan mumwao How mammaam>m mum mousuapsmnxo wnamauuo>om ao>oa woman swoonua< .soamnaosa omaanoum mom osam> m assasaa moms mos oao oanmaum> no hHONOumu uosooud How monouaosmaxm on nonuao moumoapsa : IIIII : moosmoamaswam mo ao>oa no. mmumuaosa :9: moosmoamacwam mo ao>oa ao. moumoaosa :m: “mononusmuma ma muouum osmosmum "muoz . aooao.o ammoo.o Nam ommm.a mNs.m amao. msto.- mowso. aoom aam.sooaaomm.o amaoa.o aosmo.o Ammmo.o aaomo.o ammoo.o Nan mmao.a ma¢.m muse. sns.m owNNN.I Nmom.l osno.l mmNaa.| mumso. mamso. aoom Amaoo.v Aomoo.v on omsN. ms.a mmao. Nono.- moamo» masw aoa.moo Ama.mao Aoam.oo amamo.o ahoaa.o amaam.o aoaao.o on mmNN. wN.a sooa. mm.ma oa.NaI NmN.NI OONa.a mmomN.I aon. mNmso. masw z mmm m NM m\< mos uooouzo unamaoz oaouuoz msnmwmz >uuonm >u¥3uoz usumsoo oooo vmsaauCOUIIHHx mamwm Euamuunom manamm wamomav moans unmoamaswamsa umosaa ca owsmso ca owsmso moaalsmma .am um can: can osnam oaumu moamm stamauum>om moauu Spam moms soaumuusoosoo Imsosa 0am unmoawacwamsa umonaa Iano owmum>< Spam-usom mmma uawamlusom oN wamomav puma soaumuusoo Isoo wsamauuo> oaumu moamm Asamuaum ummuov unmoamacwamsa unmeaa tom auawlomunh stamauuo>o< wmoa moomuu mm mawomav was oaumu mmamm stamauum> mmauu Amom nova low spam mam: coaumuusmosoo moaa osm Imnosa uawam nonwoz o some ma usmuamaswam umocaa nasco owmum>< shawlunom mnma .smaa lusow 0am sa meadow: .so oaumu moamm Iwaamauum>om umosaa ca mwsmnu one soaumuusoosoo can woa oaumu moamm moans wnamauuo>om somsuon .oau stamauum>om Immosa mooow nasmsoaumamu unusaa Imuomsw .mumnm Isamauuo> soaumuusoosou wmaa nosnmsoo mamas «>auamoo .oo«uaoaomsm .p««oaa -o« :a «mo«oo as «mo«oo o:« msoa -mouou mma om oaoooao mo moans unmoawasmamca omam Imsosa mooow moocouowwao umuaw ammo» oaumu moamm soaumuusmosoo wmaa was mesomsou uawao ou«« as uo«uaoa=mamoa C««caa -moamaup«>o< spam-Doom sooa .Asoa -««pou mma ms oasooao “moo ousmuamaswam Show mammaum> oanmaum> coauom manEmm ho: amoaumaumum amaoauossm usoosonoosa unmosmnon mmmHQDHm WHHmzmezH wszHHmm>Qm=m 4 < Naazmmm< mmmao sumo ca hum aamnm oaumu soaumuusoocoo oaumu mmamm mmma mam Imsosa mso mmoa cosmos o unmoamaswamsa maamuosoo tonne Shawlusom stamauuo>o< smma .Nsma moademm m.umouu .wsassmm .s: masonw suaaao«aua«poooao monooun mouau cusa ooumou manamm omoa>ao moauumsosa so wsaosmdmo unmoamas oaumu soaumuusoocoo caumu moamm wmma pom mooow umSSmsoo -ma« oo« uo«oaoaomamoa -o«=o spam-noon -moa«aou«>o< sooa .asoa Damao-m mma as aaaaoao o«« xmosa unmoamaswamsa ummsaa assocamuom oaumu moamm soaumuusoosoo mommmao Desmond usmuawacwamsa umocaa Isoauoeoum Euaulusom mooa .soma damnedmuonu ma xaanmav cos» umosaa usoauamwooo Nsmuoa moauu usoaoawwooo ucmuoa moan: Imsosa mooow scammouwou umosaa new woa pom oaumu moamm coaumuuomosoo smasmsoo uawao Oo«6m« oo«osoaomaooa p««oao -moa«aup«>o< sham-pace mooa .mmoa -««pou mma om aaaaoao so mmauu usmuawacwamsa Imsoaa mooow omam soaumuusoosoo ca oaumu mmamm soaumuuaoocoo umaomsou uawao thaav ass mwcmzo musmoamaswamsa smocaa stamauum>m< auaulusom moma Immunu mMa mm a was mosaQ mammaum> moauu meant waamau coaumuusoosoo Imnoca mooow musoauammooo Enaoma mom Iuo>om 30a no EHaNIHDON Hossmsoo uawao omao poo oo«oaoacmam p««oaa .e=ao«s .omao as «mo«oo mooa-asoa -p=oo oam ma oaoooao «out mosmoamaswam Show mammaum> mammaum> moaumm madamm at: amoaumaumum amcoauossm usoosoaoosa osmosmdoa .mmmmaucoo-< xaozmmm< oaumu asamuaum ummuuv unmoamaswamsa loose moaumu muam moauumsmsa (sop Euamlo>au oaumu moamm mooow Hoasmsoo uc«oaoaama«oa p««aaa o=« Spam-«ones -moa«auu«>o< aaoa «ao«p=o:o: mo «Aoaoao «as. moanmaum> . mason o>am Ismuca wsamau soaumuucmosoo mumuooos was Iuo>om 36a mam enamlusom mmauumsosa uawao wasumav_§ ems; Coo o««uaoacmam D««oaa mo«n«ooa .omam ca «mo«oo oaoa-asoa -nooo oam ooa oo« umaa. uaumu Ammxmu mmaoxm unmoawasmam tomso mo m>am=aoaav Acamuaum ummuuv :oaumuusoosoo oaumu moamm moauumnosa mooow unmoamaswamsa ummsaa Ehamlo>am stamauuo>o< moma umsnmsoo mN vasmmav can” oaumu moamm nAmnmav mo>mah unmoamaawam twsamauuo>o< was scum“ soaumuusousoo moauu Iauusa .soDm u:«uaoacmam moo moamaopm>os spam-Once mooa -«=oca mmH maa .:a«o«. Nessa oaumu moamm mm zoom... -N..m.w..m 3.....1: o o a w x u o moauumsosa mooom Show amsoauosso pom soaumuusoosou oaump moamm uoeamsou oosaw so wsaosmamo omxaz umosaa Euaulmouno stamauum>o< moma loo hasouums oN oaNmmav ma oaumu mmamm coaumuusmosoo mason Do«uaoaama«oa p««oaa -m«a«aop«>o< Spam-«opoa oooa .sooa a«ooau«: om camaoao «op«. ousmoamaswam Such mannaum> oanmaum> ooauom mamamm mo— amoaumaumum amsoauosnm usoosmnoosa usoosmdmn vmzcauGOUls< XHszmmd huamsouaa wsamau Iuo>om so comma madamm huumspsa ao How soaumausouommav coaumuusousoo mmauumsosa unmoamaswamsa “madamm Desmond Enaoms swam-unmao mooow meson huumsosa on now mooaHOQ was swa: HON was lusom isoo uawaoiusom aa«op«u ca ua«oaoaomam p«ooaa «ao«ap«> mezzo as «mo«oo mooa-asoa oam ao oo« ma xaoaoao moon oaumu oaumu moammlwsamau usmuamacwamsa loose lum>om Shaw coaumuusoosoo ucmsaaoo own moauuwsosa uawao unmoamaswam umosaa Spam-usom Iuo>m moonwaoz momalsmaa IHDON 0am wN Baonmav cm mmauuasoo moaumu soaumuu soonousm :uoumoz usmuanmnca non Icmosoo Esau :a mooow moasm wsamauuo>om was Im>aw mam Esau taco mo mousse moanamm xam mo o>aw ma oaumu moamm Immunu .xmosa Noa Eoum samuo «>auamoo mauo«uaoaomamoa p««:aa -moa«aopm>o< ao«ooaop«: onoa-oooa «maos««o:« xam >Aoaoao some. mooow mooow common was msnmuso coupon you unmoamas Inc: .manmuno Imam .mooow manmusooos mosmauoaxo coca was manmuso mosoauoaxo oaumu moamm soaumuusoocou omoa>ao mooow How usmuawaswamsa umocaa stamauuo>o< Spam-usom mmma Hoanmsoo mma as Damnaav com Ammxmu omauxm oaumu wsaoSaoxm Iomsv can wsaosaosav oopsaosa mum mom soaumpusmosoo oaumu mmamm Asamuaum umouov moxmu sons unmoawaswam umosaa auamlm>am stamauum>o< woma .moma oadfimm m.n0uu:m uAmNmav mm mosmoamaswam Euom mammaum> mannaum> ooauom manamm mo: amoaumaumum ascoauossh osmosoooosa uaovsmaon vmaaaucooll< Nanzmmm< .so- m .oaslsmm "Awoma umnfim>ozv ON mummmm oaaosoom whomxo :.osmaon amasmsoo can manuaosmaxm wsamauuo>oozv ma moaaosoom amauumsvsa mo amGHSOH :.:oaumuucmocoo was wcamauum>m< um xooa umnuocon oa moasosoom amamumsomw- .soaumwaumo>sa amuauaoem s< "soaumuucmocoo can wsamauuo>pmz ..uh .smnooz .3 .h was .wsacsmm .< .H .ost .2 .mo .moam-moam .oo .oooa .«uaooo maaooapo aspects” .m.D "scuwcasmmz .m xaosmmms «wdauuomom assoama>an was soaumuusmusou "m uumm «Moscow .m.= «humaoaosh was so mouuaaaoo m «o xaomocoz osm umsuuaus< so omuuaanopsm mucous mwsaumo: :.wsamauum>o< pom noaumuusoosou amauumsosa: .wsmw .w moaumnou amassed : .Nomlmmm "Asoma Honamumav Nu maosoom amuauaaom No amcusoh :.:oauaumasoo one wsamauum>oo< can coaumuucoosoo amauumsosa .saoumcuo .a xmacmum aouw mouamo was zusouw Dwayne mm zoom moanmaum> ucoosonmosa umcuo om: moaoaum casuuoo "muoz ham>auomnmou moubuaosoexo moma was moamaopm> mooa .asoa poo ummsaa moamm muumsona tom huumsosa moanmu unnuso soaumuusmocoo can woa pom amu0u .oaumu amuou No woa lusdsa .m.: wcamauuo>om sooaumn oaumu soaumuucoosoo .oaumu mmamm am>oa xuumnoca nanosoaumamu ummsaa nomsv nonsenanm mo Iwaamauuo> Noaa pom mamaolusom st «>aoamoo .oo«usomcmsm .D««osa 6=a«> atom-poem -o« Apuosoaa mooa .ksoa oo« omm .aom Namaoav osmomc oaumu moamm soaumuusoosoo unmoamaswam umocaa stamauuo>o< Euamlusom oaumu coaumnusmoaoo oaumu moamm moauumsosa uawao haonmav mma oo«uaoaomam -o«=o spam-Doom -moa«aop«>o< mooa -uooo oam mos o:« oo«axuao mosmuamaawam Each mammaum> mammaum> ooauom maaamm hos amoaumaumum amsoauossm unopsmooosa unmosonma vmaaau:00ll< xaazmmm< .asNImaN “Ammma aauno< mo moucmswmmsoo oaaosoom one: .comaoz maaaasm: .smalmoa “Ammma sou. mm amousow anocoom :.mua=mom umsuusm was unoEEoo < ”soauauoasoo mam .coaumuusoocou .wsamauum>m<: .moom .n .mu .soaioma ”Ammma soumzv mm amnusow anosoom :.:omoudn< Hozuoc< “ouauoauum moxumz was moamauuo>v<: .oaammm smossn .3m .oNo-aam "asaoa p6o56>ozo om «oaomao. mam manocoom mo Boa>mx :.omma Cu Nsma .coaumuusmocoo umxumz anauummoca ca mocmuoz .Esm: .u manna mom Hmaaosz .m mumaaazu .monom "Asmma Loumzv so amsusow uaaosoum 2.:oauauonsoo was .soaumuusmosoo .wsamauum>o<: .:0uu=m .h .oo .mNoINao "Ammma aaumoau£m pamsom mam .HOumwaaauuaa ammcoaz .GOummz posh .h .samumauo .a hoasmumm .sNaImoa .nn .ANNma ..oua maaaZIhmum “soosoav .oo .wsaaaoo nuamx .uoa>m:mm oumuomuou mam summon” moans: :.>uam:6usa wsamauum>m< :a mmocouowmao umxumaumusa was .moaaom wsamauum>o< .ousuunuum umxumz: .oanmo cacao .NmIMN ”AmNma wsauamv ma saumaasm umsuuaus< :.wsaxcnm ca coauaDOQEOU mam wsamauum>v<: .moumzmm .m saaxsmums .amslwss “Annma humssmnv mm amass anosoom smocmsom :.usmEEoo "soaumuucmosoo moans: can wsamauum>o<: ..uh .cmsmmz .3 .h was .msassom .4 .h .csmz .2 .ma .lema “hamoa mashv mm amou50h anocoom sangusom :.c0aumuu:musoo umxumz osm wcamauum>w<: .Hoouu .m moawsooa .oom-osm “aaaoa sasoo oa «Osgooooo a«spo«=x we assu:Oh :.%uum:osa amoausmomEumcm may :a auaaanmum mumsm uoxumz com .soauoEoum .soaumuusoucooz .soaum> .z anchx .mmalmma "Aamma aaunom manuosuum moans: onm moamauuo>om Bmz mEom "coaumuucoocoo mam wcamaupm>w<: .EEmuU .m Emaaaa3 was ..uh .wCSanm .m unanOMH .aNaInaa "Amoaa “uncuuov om amsusoh uansoom amozunom :.:oaumuusmusou ca mmwamco can msaoauum>mozv ma moasocoom amauumsosa mo amcua :.usoaaoo "soaumuusmusoo was wsamauum>o< No soaumwaumm>sa amoauaaem s<= .ooausmz mmaumsu osm ..uh .osnaoxm .m uumnomw vmnfiaufiooll< NHDzmmm< .C .munuaumsa omauapoucm cmoauma< "scuwcanmm3v muamsousa wcamauuo>o< mom soaumuusmucoo amauumsosa .saOumsuo .a omacmumn .aNaaImoaa “aona non0uoov sm.Nmmm amoauaaom No amcp20h :.msawumz umoolmoaum pom .soaumuunmosoo .wcamauum>o<: .mmao3 .3 pumsooa mom osmaxoauum .a ahaa<3 .okms .omsu mo >uamum>aca .uoama oozmaanaaca :.usoEEoo < x.soaumuusmocoo ca mmwsmso mam wcamauuo>o<. .msoumz: .xsouone .h oa>mox .Nolmm “Aomma monaoun mN muaSocoom amauumsoca mo amassed :.%uam:oU:a moamaumm>o< mummDUSH co muauosuum moans: mo mucosawsa one: .nmaum .o :maumB .Aouoa .oamaaozlsuuoz usmmuoumaaa uauuoEocoom s< "maaa uo>o maomowaao ca monocoo moans: was 4doauauonano «wdamauuo>o< .saoama monsomwlsm06> vQDGaDGOUIld Xamzmmm< APPENDIX B ADVERTISING EXPENDITURE DATA CODEBOOKa Column 1-4 Industry Code 4112 8 Lip and Eye Beauty Products .. v 4113 = Perfumes I 4114 = Make-up 4115 = Manicure Preparations Y412l = Toothpaste, Mouthwash oy4122 = Toilet Soap '4123 = Feminine Hygiene Products 4124 = Deodorants 4125 = Shaving Cream 4141 8 Hair Treatment 4142 = Shampoo, Rinses 6122 = Cereals ppwk6310 = Beer (barrels) '1 6320 = Wine (gallons) , 7112 = Cigars (units) .-1 7330 = Restaurants, Fast Food 7531 = Pet Foods 8412 = Detergents, Light 8413 = Detergents, Heavy 6-7 Firm Number 0 = Industry 1 to 99 8 Individual Firm 9-10 Brand Number 1 to 16 = Brands 17 = Industry or Firm 12-13 Year 70 to 75 = 1970 to 1975 15-18 Market Share Nearest Tenth of a Percent (X.XXX) 20-26 Total Advertising - 6 Media Total Hundreds of Dollars (add 00) aFor use in conjunction with Appendix C below. 141 142 APPENDIX B--Continued Column 27-33 Magazines Hundreds of Dollars (add 00) 34-40 Newspaper Supplements Hundreds of Dollars (add 00) 41-47 Network Television Hundreds of Dollars (add 00) 48-54 Spot Television Hundreds of Dollars (add 00) 55-61 Network Radio Hundreds of Dollars (add 00) 62-68 Outdoor Hundreds of Dollars (add 00) 69-75 Total Industry Sales Hundreds of Thousands of Dollars (add 00,000) Note: Industries #6310, #6320 and #7112 are in barrels, gallons and units respectively. 77-80 Record Identification Number 1 to 1722 APPENDIX C SALES, MARKET SHARE AND ADVERTISING EXPENDITURES FOR FIRMS AND BRANDS IN 19 CONSUMER NON-DURABLE GOODS CATEGORIESa \UJ .35 42 0...! \Ju 13.5 4., .00 33 100043 73042 149785 124905 183 3‘0 00470 05602 306090 271053 0 17 75 1000 J 17 74 1000 140 1.1.. 6.4 . .r4 4.) 04 UNU ”.0 UOJ U 0320 O 0.3 H .3.) .00-UV ‘a‘z A T111- 111 0 4 ”4 FO’N# U 000 85.0 0 £232 07 05 .J. IUJUU ..V.U-U.U 1.61.7. 04.351 7. .414 TI n+5 [303.3 393l- 3297 797 4 1.2.... UJ.U.U willed; 28.07 3 J O 0 Jane, 1‘... U 371 534.3 03.3 .3 79... J33 .W924 USU 111‘. D Q .‘ol. I777 [777. 7111 111010 .6222 1.1.71 1111. 4144 511‘. 3400'] 02:0 0300 0300 JJJ U llb3fi U000 J.U.U\.U 1233.1. lolqlfil I777 711‘. 1.2).)- I. 42). I117 1'11 3 4.. 4 rl .L3 .w. DON/.0 7.11.10; Uivu-J .235): 1235-4 12 0.1 .573 1| 1| 00.09 9 34 23 O. ‘ UJ U‘U U470 b-U’ 030...! .6153 1.91.7 [-10.5 0 a... ‘7: 907 31.2 54.1.1- 57.1.1 7111 T1342... 7777 -777 final-cl] [53.1. fix? a). 111 1111 3644 UO.JU 3431! 341459 5 575.» .0 3.4 Q 6 38.0 ..J H1! ((1. U 039:3 [~1- 3 r ..bSFJ U 0 07‘ vial." J1J5 I771 I777 111-1Uol J33 .4 .4221. 711lol 1011.1. J ‘44 [‘2‘]. vJ-U-U. dad-0.03 4.01.0 I o d a .J.J . 0 0.0 .01 .0-0 .001 r 057 V90 :9 .1731. 3 0.3 I1 [7.3.0 325 3 35 U1 21 U.U VJ W479 .3621 0092 .7 O1... 0w-.3 U J~I.‘74 {7083 37.5 3231- “5.15). .I O r310n i777. .1777 77.11. aquvfl 42./:4 1.11:1 I117A 3 .Q i 4 4 59.01.4134 337.6 12.22.5331. 5335 0.0.0 9.10.0 00 U JO). 5.30.0..UUUQ 0.6be 42.-0443084.. 4.603 07 0054005000 .3 3 3 .00-0 010 U .0 U0 0.100. 000 0010 JAJU.U.U.U 01001000 010 UKUUU Udonuxuo.bo 0.0 00 09.375.100 U-U.U.U Saw V v.3 23107-4 07.3.3343.3 3.301- J7 “25.336 Cue/N O 42 OOSIJ.¢24«IS 311031! 1.. o 07 2833.3 JJJI JJ.33.3.5.J,O 09.4.0 1671.94.54.43U1-r3 3173‘ s... 5319.01678 .4 Q 45.“ J 33211.24..- 3 Q Jul-1‘U3211R437. 777777777777 I7777777f777 #151111117111 1.135.355 06 0777 42222.2 1.27.222 111101171. 1.11.. 511145551 111 6H46Q444 9.04.4 0.0 55 .7. 07 00 0-U 37 4.3 I .O 3 4 37 +11. IJ I.‘ :4 ‘1 £4 .40 39 «=7 .93- 74.3 3 «a 7.3 04 [.0]. r7 r8 TI] r2 1...: 1.1 1.01.). 345.675.201.434 3 07.... 7 U1). 34.3.0 7.5 710 W; a JD. 33573.17). 34044400044535552555506006660637.777-77775 0000J00000000000000000J030000000OOOOJJJJ 0000055000003000005008003500053000850000 .03. . 02.48320). 2.0320228 0 2.03 .203 7.283 6321.03 2.1 7 0004076 ad.» 07005.4 070 s 000076.0070000070004 r3 3 :23 .3 3 .J 5.3 000000000000J000000000000000000000400000 00 .003 0.00 00 JJ 00.00.0000 .0000 0.0 .00 300-0 001-5 o 070 4 2.0. 371.0 T 50 40 .5. 1. 2 4 33.2 JOJOJUOZIOJOJJ7UDOJOJ000040580933031s092 H; .b 0 117.40. Joonl .35034fiv1l .0 a 1. Q5). 69 3.5 1937 7. 3 W ..- 33. $555 42 . 43 333}. 000000.03 200000003000 000.0 0181.0 097 ”00!.JF354 50 “w..- .IJ 13 1.3.4.» .33 00;. .04 7437037 1-. 4.. "0.45 “no.7. .-.... ...«s....l. 1- 77 O 43.3 .0 0.0 .03 UOU 0000 0 000 00 0.0 0000 .0.U.UU 0 0,00 .0000 .0 00 0 0 0.093 0455.05.02 959.5T691. 1.15.0 40.17 27.0 0 41 0.0 T31). 04931051- 02703938 4050 0761.8 5373351307 083.0 1.3822616 :55..- 35 o 0.3 9.07 W .0033 02.08 0.6 0 0 00 I 0.0 3 11.11 .455 099331.553 fi- 7 J3 4 s I ,2..- T 85 i 711- 0011193501i4921%1244031.315059334074§7315813936 0 “913110.37 0.1.7 U 390670.30 1.7 01. 310 39 J.» 0.1 Tddol [90.5 T 38?. 4.01.7 3551. 55507957 56.93 0580782.... 0 08 4 717 0 T11..- 45099933195 0 138343751 0 s 3297 ml 11.. 3.‘797 O 1l1l To 3030.333306100903233333207881111T1177875 .11 .111 1. 9n34100 1" fill-AI + 5.21 05 43.21.05 +3.41L05QJ 053.25 4.32 34.3233 45 4 D210 v77777777 177777777777 [777 7777 7777 4777 777‘ {7777777 7777 7777 T777 1777 7777 7777 {777 I777 T111 111 7111:1151-911011 7101111111 111-1111711111. To... 155.545 5339 99933000 1071.1 127.2333}; 4.3 .9 ..4 3.3 06 no 06.0 ‘711‘111' T111V‘1IQI1TI1IOI1 11.11- 1.171 £27.1n2a522.4122&22 4.4222222 £22212246 £22.). 42.1.2 Talc-.4.- olalcl 11.771111. 411.11 771-11-71711-1T-Iol1l1o1a11l $444444w4#44444444630443T440 949 4949.40 1“ See Appendix B above for a description of the data organization. a 143 144 APPENDIX C--Continued 3333 111 1411! .4 4.4 4 .1.ng 5839 0000 5050 5579 3937 r000 D O1 03 .7843 2.033 #4411 D326 v3 n4 .21 3 05 1 7335 ad 1040 U U 2J33Jl ‘Jrl’ 10471 9009 2302‘ 3333 T111 1.411111 4444 r...234 39,99 UUGU 3.3105 1457 1 0.7.0 0000 7000 r11.°\U 1.7.0.0 U712 .3993 1 189.: 4.1. ..an 4.4444 43.U7 1 U0 ‘1 47 .3). 1 .36..) 65.1% .4 b C 395 0431 .0715 J OQHV .I 000 13.‘ 2 D..13 12.5.4.8 J3 2154 {777 7777 117‘! .1121. (c.3344. 111111 1111 4444 6789012. .9999 000 111 3 9 .Uoooo Loo 35.3650573 11 “ca—.3791.“ I b 39.577 0 00000000 U0 UUU .U.U\U 0.20 .41-21.3 221 VO.U\U\U.U\U\U C J .U.\V.U. .- U87. 0 .05..2U7 SZQNUQII 777 48.U.23 33295.3“ ‘93.U7..: I. “11.3.: “111 J3 05.0 055 3.411.515.0331. 3 21054 3.21. 77777777 #7777777 j1111111 1.27.33.17.33 j“.¢n§40“0 3333333). r3311.) 5.1.33 111411.111 T1111 T11 1 111111111111! 714111 T 414111 runfiabfidgo UUUrU 0001 .1111 7.111 $00,000,010 3.0.3.U.3.35 0 557.9 1.4.0.3 3.4.577 O34. .U...UU.UJ.UUU JU.U.U J .U.\U U U511LI 0.37 .91-.) 157 02.0n017 ..O .4 .554 1 U1 U1 72.630 0.27 3 O O .03.? U UAV ..U.25 016 5.5.2.11 2 UUU D U05 I 7 .72 15,34 U712... 037 .9 31Q1 O 04:; 2 017 7 44.0 0.252 T 34 3 71.9.3 0.2.0.4 .107 3 I.J.U1 1.70.7 71' Inn: 91117 .Onwsda J27a1 4.774 115.2 255.3 33 6.3 U.3 43:1US r777 I7ql7 F777f777 T111 T1191 304.4 44424 4 4.4 .4 4 4 4 4 1.2.3.4 1111 T111 .UQUU ..05 05 4.157 [79.0 .UUUU JO‘UU .3678 1111 .1111 UOOU 0.355 171.48 ’7 O 3 UJOU 0000 .2198 U818 7470 7.14 .1 U690 00 U000 4377 7399 («“644 014.35 .1. DB 3 1.70.0 1.921 7356 1* .Q 1111 .. J7-1 U 7777 P777 11101 0.0.0.0 3.3.3.4 11141 1'11] . “.94“ T012 1. 2.22 1.111 0000 0.305 3791. 1377 JOJJ U00.U $700 5.147 11.4 5.0 UOJAU 0.374. .192). l. 51 1534 .1 41. 0 9.092 1 30 41.013 Yul—’1 r) «409.5 260.0 1 37000 4“”33 3432 7777 7777 141111 7777 1.333 1111 7.44.4 I45: 2222 11701 UUO‘U 5.3.05 “£337 0.3%: d 0700 0000 .424!) T040 .5933 211 U U723 9 O 99 7U 1 r473 .31QO 1.20 L T... 090/. 1.67.5 336.9 1‘ 3.57.4. J.U55 .3994. 57 45 .4 a 3.190 D 03 Q 1U.34 r777 7777 1411.11 7703 3333 711101 1111 4444 [Bad 15.67-J r111 .UOUU USOQJ 1.1.37 (7910 JJ U29 JOU.U S 1 .43 U0.5.J .4937 T1 2.33 1.1 0063 Ob 23 57 z UOU EU I J 3.553 U307 0102 19.5 0 £21111 59.4 9 0301 5Ub 3 32.57 1323.42 2477 4.4 J3 .47234 777.7 7777 T1111 5.5932 3333 1111 .1111 4444 T12J ..Q («333 T111 .U UUO .9355 3143 .I7 0.3 0000 UUU.O 8 5 77 ”40 5391 3.U00 3 .b O 3 O ..3 302 2 O7“ 9 r0 U15 38.91. T 11 3760 3035 341.145 4.3 Q7 2111 U231 .4 43.1. 1.210 77 77 T777 11.11 3999 3.3143 1111 .1111 4444 000000 050505 37915-7 307790 U0 JU.U 1.- U0.U.Uo .U 0156\U71 313 3.0 555 57 ...4 UUUO.J.3 ..U .4 ...Ual 22.3 U170). O 0 1.8312}. 1. “3.4.05 H ‘Q.I~U.O 2 41UU1Q 1711111 34325.4 .77-I777 {77777 T111111 7.7.7.788 101.111.. 333333 711.1141 11111111. 7 Q “Q .Q Q 56783U1234507890F2345670?U1Zf45578 3331.. 364.“ U “I...“ “05.3.355.3§.55_3,066 Db 0.0.0 0 11.11.1111 7111. 111.1111... 11141111 111111 0000J0000000C000T00000000000 050505050505050505565005U555 3791 579157915791 11.457957 71 4.0 3877157790771377770937907703 00000000000000000000f0000000 0 2 000007000000000000000074J000 4 74 7 79 1.1 3450000021870000000232605055 452 0128 2303 73Uo 232 O 5 3 J2 7 3... 351 2 4 4 49 .135 4000000000000000000570005000 4 K «J 4a 2 Y). S (J Y1 J 3 4.... o 000000000700364500870020uOUUUUOU 81U 0751 .42 7.5 3.14 7 9., 0 0521.902 4.808 9002 fi3d8 9600 r250 2473185743074597l01340 0107 1041210903u3033324004u 4909 7.2.1 JJQ3Z.3“§J 33241 1.1.5» .11 1. 00021323050030694307f0344000 JUU3127712903539I09970640413 2071. 20320549 08.3 2 240.9 089 .7410 .58). («..qu n» n.3u7 33.1. 4 11.3 uxv11 0.3.01 1| 1' TI 43 4.7 2 2 0.0 T212 0 909 0.273 431.2 29 07 33.22.33... 22.222 2121 T221 1111. n 543254323432543232154354I210 7777/777f777l777{7777777F777 I777I777f777r777r7777777f777 .1111 1111 r1111 T111 .1111 .1111 .1111 0000111122223333344505660000 1111111 1111 111171111 1411.11.11 3333333f3335333333343335333 117 9'11! 4 411 1311 111 111 7‘15 111T< 1 41 111 1‘1. 111 111T111 4444444444440444344444440444 145 APPENDIX C--C0ntinued va 57 1:! CU .UCJ .9] 77 714 507 9.3 Oil _3\U 7.3 34 77 77 11 3.3 11 33 11:! 1|..l “a 723"» I777 Til-11 JUOU 030 0 373.3 1 574; UUU U UOUU UzUU U U.U\U.U 3 .43..: I777 777 11". 9.3.31! 112 14333 T111 T111 #44“... 5675 I777 T111 U000 30.5.5 I 91»: 677, UUUU JUUU 0002 9000 ’8 v.3 IL [191 Du30 J41? 1.1.1.. 0 ’95 3 43.U 351.1 711...... 709] ql + 325 I777 T777 1.111. 711). fizz 3.1.3 «I11! 71.1.1! 3.9%.“ ‘.J..‘:J 34H» 301.23.45.O 108.0 0353 1111111 UUUUUUUU 3mg 030,3 0 [91.379413 1077.7 577 .7 UOOLJqu 000.4000.) .3 Q 7 5 1. JaUUUUAUxO n9 7 7 1| 2 .3 2 JJUUWUOO 2 .3 7 3.0.75an 0 J661579u 4.1. 10 («I ab ’2 09 00.1.6 4)..)- D1656 50923 U.3C7 +6714.J.3.3 73077355 u51¢¢774 C4 c8955670 9 “32 3 77777777 77777777 ~|11l1117 22233133 42222241 33513333 71:1 171 .lgl T11! «[1111, ““44 T890 8889 111... UU U.U 3.3.UU 4.61.9 0.3.3“ JJ.J4 U U03.U 31:3 371- 03.3)- ]11 H 12.3 U 53.3.3 [-3.3% T2611. 4.9.49 43 Uh» hfjlou 73,63 03.35 40 0.). AU “.0 75 Q 4. 0.1.9 SIZJ .V ‘9 O7. 3.3.0U 364.3 54.31. 1.8 ’1» 7.67...» 777.1. .373 1'1“ 020 U 3.1. .U U 4.3.JJ 11 1.0.3.4 7777 T777 T111. 4“\U\U I52 3J6“ 11.01 111 .9Qhwfi r.£3§ 3999 T...“ 1 UUUU UUOU 531 Q 4 Q 4 uOOO U U07 .5 34“.... 7.3.36 3.5.54 517) J “22 f266 d U,O7 i 002 0.37 O 3.3 .93 4 Uu.3 7.3 \‘1 3557 f5 07 077.3 ..IJFU] 7‘ J“ O 1.13... 3777 43).“ [76..U 1337.14 1111 UUUU .J UU U UJUJ 7.111 :41J 7777 7777 11107 UUJU 4+44 71101 1171' .9444 ..Uo U U 30.U.U 1— V. 6054 {71.0 132.0 1.un 4 71.11 Jddnfi 3190 473d 562% J11QI. g“.u.3 3.51 U 71101.» J (4.1—1. 7777 7777 1111 7.111 T0 “9 ..Q n» 1111 T711 ¢$44 9000 124i .. 1U..U|.U..v a U0 U 7117‘ ..VJOU U.UO U .V .42 .03 11.0 .025 210 11 002.0 5 Q 69 ~35 WU UUU 7,). 4.3 3,0204 ..U .b.c 1| 34 Z 3 .Q./.\J 719.3 U b 475 1.231.! 4 .4. 7740.). U1 73; filcl US.33 T777 T777 Yul 111 r233 14 .Q 4 H 71.11! 1111 46““ 4.33.4. UUU..U .8030 0.438 01.39 I anJ 22 J981 6696 ’32) 4173 22 UUU.U 0905 3J0. >77q 7594 1! D‘AUnw 7d.) 4 Q7 “.3 3.901! 1... .06 3737. 0.3.0 0 41.34 7777 T777 11.11 .3344 .Q Q 4 an 1111 1.111 3.44.“ I713, {890 JJOI £22). UUUU UUUU [DJ] Y+¢4 JUJU UJUU .4734 .3989 J Q .04 [-6.31 1.2.1.1 IUZS 6377 £923 5 1‘7.) (.333 UUUO 1.). 02 .3797 321.1 3). 11 3314 (.17—3 3 USS). {.327 0 0,0“ 1.973 05.35 321....U 7777 I777 1111! 3.44"» $44u 1110 11.1: 3&6“ r43§ 1111'. 6.1-2 .‘ .UnUUnU UU U0 797s 3“ .i .4 $000 UUU..U U003 U000 3432 777 7777 73111 333.3 * Q .6 4 10111 7111 $9.49 r67a [.11-1| ‘22.}. UUnUO U000 T197 4 3,.» 4 .UUUU 0000 3141. 3U2..‘ 724.3 71! ra). 05 3 DUI 57.0.3 271 31.. GUJ1 v-°“\d U34.) 7777 I777 1.1.17 3,0 07 3444 7‘07} 1111 T4 4 4 4 01.2 .42): 4.4.6.4 0000 U000 33]! qu54 JJJJ U.UUU UUUO vooc U U?- Q 2.3 $939 1303 4419 6&13 5439 6429 7&01 31.2945 415% £777 1777. 711.7 I788 5 “a.“ 71001. T1011. +444 J “.36. [222 23.2). U000 .UUUU [54.09. V 4.3a“ W000 JJUO u006 0000 JUUO I020 66‘ Q30 21! I026 0101' ®?o 21 6.1242 3254 T777 1777 T111 5.699 3 Q 4 4 7111 1:111..- 7943 £223 [242 V000. U000 7000 .UUOO U.U..UU £5Q3 I777 1777 7171!. 9UUU «I‘ll- Qua,“ 771.1 T111! 3 0%..0 r234567u. 133353344 [22212.2 UUOUOUUO U UUUOU.U.U 3311.37.33 . J$4544 4“ JUOUJUOQ uJOUOJUO VUOUOU7O VUOOJOCO uUOUUOUO 30.‘272U9 [7767 .58): [8131206 fil 1552 ..Q 4 3.4.4.47 £7 7 471618.02 48131106 7 1.352‘“ 322 ”335.0 Q 7.171114. .17-'05 *321 17777777 r7777777. U0011c¢|1l¢| 1111111... run» 4 Q 4 4 4 11111111 117101111, “QUQQQQQ 701...]; J456k I390 JQQQ W.“ 4 a 6835 £7.27. .2 £2 .27.). UUUCJUOUUUOU 0000 000.0 UUUU I197I9117515 53$234454Q54 TUOUUOUOJOQU JOUU JUOU JUJU 1.000 UxUanl 00.00 1- 22 9 33 27 L000?UOQJ003 .D 3 3 1 UdUUUUéUU07G 8 b 9 65157030+272 1.1.35 568 519.0 U331 .42 58.3.3 6 Q I 5.315%] 4.01 1&1. {Z35 SQSql 1.77 w831 7.3.19 («.319 3.3 r. .‘ 32107043J¢93 1.11! a! O .9. 3 754356051252 17777777 1777 I7777777r777 1.111. [717 711:1 .422 3555 0.077 11.1 714:" 1:11. 3 ““4 Q Q a“ 4 44 T171. I111 1.11: rI..I1u1.. 77.117 111-, «$44HJJQJQJJ 1.3.. 3.3.3.3. 1.2.1.2 0000 uOZAL 6934 Tue-I11- U000 uUUO 3 0 3p: 62 rU 0 J0 o1. ‘1 .33 .05 U0 UU UU 71! T0 I7 [7 T1 J0 .33 71 1.1 .04 1600 louu U 146 APPENDIX C--Continued . JJJU . J‘UAU‘U J JJJ JOUU UUU’V 3 49.0 b.1491 021 .1. 04’ 0.0.”). 623.31 (45.3847 09.1 2 3.232 652.). . . «1.01:0 . 1 5.2.21 -3210 I777 7777 7111 T111 J 4.0 Q 1. +240 3 1.30.3 10.623311 631.8 7181 371727 . 3.2.3.15 Z Wrasfil 11 (J1 HgJ 44% oyd 1224 1993 T72J 334 809 1254 [pro law) 7351 .0.) 1.2 5.3..U U 7.111 T111 3432705452545210 {777177777777777 1111 T111 .9111. ‘JS 35 Q 1111 3555 5555 012 .585 2222 UUU.U U164). 053.3 1110.1 JUUJ 000.0 JIUUAJ JJOU fwod 15 119 3 I)_71 507 +53: 3 9771 <1 07 1,054 T111 1323 I777 F777 1111 5 3,07 3:455 T111 111 1111 1111 oweruu¢444JQ¢J 111 4414 #8902 5369 2222. J.Uoo. v 01.3. 5.05”? IIIIA U U30 U 000 figsa 9569‘ 7 O7, .007 12 ..J1Uook. 3432 I777. I777 1.111 3223‘ Htass 3511. 111 111 4¢4jwuuW¢u+ £22,}. ‘6 O7 vuzu “ 5910 222 2*). 11 . 3.39,0 2811. [73.3 3173 (“90. I... .31 I772 353.U 5.249 071 qu7 5%06 JUJ9 11 3797 £345 19.1.7 [97 ,0 '11 1 000,3 ..v 03 no. U003 (11 J31» 3078. .3999. UUUOA 3000. 7742; 0583 . 2 u26 J1U3 . 1113 3214L I771 1777. .1111 UQU1A 1111. [-2272 1111'. r0123us O iufiboaduu 1. 333333 1) 00000000 3J0.3.U\U “0 37237422 00766077 U U00 U0 3J~U U 0238000 5&7“ 10.41 111 J0528091 ‘82“567AU 07322212 31327724 37733557 (5330335 3061u727 (‘3.31Qd118 {0287367 56320138 [111111 U15U0000 86 1 1O 9 lung 1 J5 471.093 .331 “194 Q 1879.3.2u1 U ’1“ ,0 “.61 [—13.53 11 I100791J $05d63o9 60170206 02154 .074 5.3519707 £22211.‘1 00130131 43336653 j.(q1d1114\1 I2432154 r7777777 77777777 11111111, {1111111, 22.222222 711914.111 wéJQuJQJ ZJU {890 U001 3333 UU.UO 30 .40 9422 O 077 00 UO J7 00 3240 .5901 .2950 "792“ 191 #079 0250 995“ .5111 6700 56 10 VJ “2.1-3 U580, .0701 4186 UQ11 11 3367 J211 ‘11 31.34 7777 7777 1111 3344 1111 (.422 1.111 4444 0.083. 123d. 1111 .3333 0000 3090 9722 0,077 .UQJU J70‘U Mn 0 1 0365 0609 I325 [—931 12 3832 2.035 32.05 1.019 3557 W 000 I. JBJo U713. .781 b [11 I. D “3 0.354 [-211 r“ .982U 1 J851 Za‘bfi. 11 3254 I777 I777 1.111 a. “55 1.222 [1..." 1111. “Q44, 5.678 1111 3333 0000 b‘U‘US 77 49 bbbb J .U‘Uo U000 08270 (4.30 123 9012 1222 3333 .0000 0040 7422 0077 0000 U U00 2078 0997 0278 1.3 0663 21 Q 127 111 W00” 0078 07 29 1 2.008 0121 0506 280 112 13.16 19244.3 [15% 7777 T777 T111 6677 .1111 2222 1.111 4.494 J“.36 £22.). 3333 6000 .3000 r7u2 6607 UJUQ .307 . I “add? 4 1d 7. T991 1Q13 7937 0796 .126 3 3917 5563 3214 7777 7777 1111 T779 1‘11 111 44.44 W222 3.35229965320 182626802903 4992 Guido 376 4 2311 0295 3.4"»). 14533312 1 $81039693132 959957511945 51.431.02.137 OxUJ r32 an» 35.33 2590 211989353443 :11 H9001340J00u 3 03,3 31 11 J $2015500JJB9 0128050 70 1.30151 9 .J0 9.0.030 ’1 2 311112 389350956931 393335923329 97393313OQQU 32231154,.05044 b7853ub77075 J111T1 331113425320 [32.13.21 4 Q Q 97.] 22222 T54321543243 777777777777 [1111121475233 1 1,1111 4‘11 111 F1111111T11ai 222. 2222222 1101 14 1 411111 T444$Q44 444 1890123436783012 222333333333336Q 3333333333333333 UUDOUOUOJVUOVUOO DQOSUOQODDOSVQJS 31.429.7“229729 [1‘29 6770067706760770 JUOQUUUJJJOJUUOO fOOOUOUOJOOOuUOOY 5 6 T Ub.3.0 0555 J076 31222 432 9.081 1404U3 3.6.9.0 T1315 302.7 “ U‘UUU J00: JQ37 13 23‘) 3.329 1“ 4 564.9 111 111 7777 $044 OIGU’ 343 J 3sU8‘ 4292 1U 09 0 229.5 223.3 7083 0323, 25.44. 3111 17522 111111 27.2 1"" nude 344 U 30 69 If). “Q 2 £9 43 dd 33 22 w11 VI. ‘1 77 1.1 1.2 11 1.2 11 4 Q 147 APPENDIX C--Continued 4 0 alafitv .U 0 .U.5 29 73 .J l. .37 \7J F590 .0 .4 4:) JJzJUJ 0000 0040 T02; 0077 0000 USUU 307.3 J 3). 3 .01; U 4 O T 040.1 333 J 31 0.7 09.43 6H7?) J 000 i “~41 41.3 1v - 7.2 J...) v T‘. .6)-\‘ 11! 44 T1111 7.3.22 111‘ 7600 T01). 72343678 I456 355535553666666006677777. JJJ}. 3333 3333 11.1.1.1. 331.3333 00000000F000J000ru000000 a 050 00 05 0000 500003050405 ££97w£23702£v742£2237229 {70007760077oob7i77oo77b 000000000000000000000000 00000000r700f00000007000 T0 0 .19 PU 1 334000315631536671003856 0 1Obb9734391286r0166092 1. 21 5.0 0d 0025 4 692 7 30032.30 :666W622143332429616 221.. 1 .4: 0000 o7 9: 0593 1017 60335327 £61J34961v6317326357 098b0243069005032053 4231675f9£1v5470190 45310124117 1138676 1 0 0.0 U 0003 U7 UOJOOQ 0000.00 00 O .Q 1 0 7 5 6 3n 2 1 T 00070031T000£00040000300 .0 755 T 2 a 7 I U719 5 5028 7 53 7b1o 1 1.4,). 5 D ‘511 1: 33 47 07 .43 .1520 T77ZZZJ2 0433 U 1d 01 05.) $30.. [1 015200 O 3.54.U r 200593¢87b019300175186 1+03JJ~363494~OSZZ110 7679412241101109807 1| 1| 1.. .4590 J32.“ .7. 107 r?» O0 4.3.73 0.1.12 11607392213300112403i 3.43415 03 ‘15“ J 41 3 33 03 4543 1777 1777 f777 .7777 T77 77777 J ”H .4“ .4111. r12). L ‘23 31.111.111 T2221...) J3 5333 53335 4 Q 0 4.3.35 f111lr1l11: T111 r111T1111-111 1.222 2222 £22 2. 22).). 4222 2.222 111111111 1111! 111111110111 4440040014040+044044Q444 F890123U~ 3675 I777. I333 0000 0050 7444- 0006 0000 UU‘UJ r202 49 .06 303.0 JO 424 IQUU 14 59 D7 W000 {000 09 :3 3 06). 1 60,0 .0 “3b 010 01 Q. 15 J91. ..V U1;- a). 51‘) . .1777 1.10.1 3.36 O 1111 22“ 11111.- 0 0 .4 W 01.). .585 5 J33 0 0.00 040.3 0). ‘3. O77 0 J000 0000 J78: 3979 57.5.3 fil D 3 b,°32 690 41 5079 T27, .11-11: .0009 J000 .3 00117 .1120 586.,» «7:6.» 1114‘ 5.1.57 4333 (23“.) [777 T11... 5777 r111 1.22)- 11111 .404“ 105.0 655 d .0.J.J3 JO‘UO .00 .40 1422 5,077 00.00 JOJU .0 400 02 55 18 rxca rJ 1.1! 39 .11. ruu9 0073 29 1a TS77 (450‘? 592.7 7 1 .12 3013 3422 1.15 .fi I777 T114). 7777 119.1 1.222 1.1141 3Q44 F890 T839 .33.: $000 3005 57 U?! 0 O 0.3 .VXV...U.J ‘34 3.078 yu1zr“s.bw 999 390.. 9 3000 3 00° J33: 07.47 5.333 0059 I 025 1.03) 1.1. J97..U 36). U J 3.1075 fl73 2 T333 T777 I77L T1111 ‘JOU1 4 12.7.2 479‘). T111 4 .4“ .Q 0747 3:35 U.U U“ 3 8 44 $043 I335 n£807 [ 437 343 616“ -3 ad 3630 4575 £236 T11 {000 :b 42 1 I090 I777 T11] T11. ,— 41.24 4222 1.1111 w “4 4 u}. 47 53.3.3 0000f000J000 300 .0 O O 5 0.563 1835 3623 land “7 1t 4 810 019 3546 .670 $007 0000 U060 ‘U 37514 4770 0065 .3304 3.362 1| 5 Uglhv T125 7221 0325 I777 r777 T1111 £3.23 ‘2. 62 ‘fl‘Zslu TI‘IQ. H004 J333Juu4tu44 0060000000600060 299393.505250525 07 .07 3313.3. 0000 UUOb 2 .3 013 30106 3.0.5.0 5.) O}- Q3110 f304 329.521 1 Q ...9 Q .0885 0.7.23 03 09 01°“ 0:04 club 00217 «131.7 "Ob/O U750“. T .005 T 0392 5627 TIC-I +525 7777 7777 1111 .0334 4444 222 1'1" J64! r890. 0001 a 4.4“ V060. .0525 0707 D34. 3. U000 2 3 UU0OJUUBI050 F2333673i012f056. T111. l111.V)-).~4 42.42. $40444duuu4034u9 0060 00.00 b0b0 0.0.60 USZSWSZSUSZSUSiS 0747 07 67.07 07 U747 93353J3§5J33fi335. 0000J000000JJ000 0000000000000000 J995F137T247¢267 .317531297341020? ‘062363515221030 0830 [.479 I9 07 303.» {8196573W2433138 b780b9095700r0b9 3930 3013 4 035 .3 00 4 6194001035230570 1.21.0 52.42 f2..4 J33} U00000023007 102 «b by 3 78 .3). 25 dd30000000000050 05b 9 0 511 8 I.bll 1 3560405056259314 000000993095T2dd 73235769r469381OK 3.053 6063 I 05 0 0:71 D 55553052 J J2 D 5054 00900139J8933095 0170900434477210 4111 1.11 11 032533;?) 3325 0325 77717777777177? I771T112£42+3045 T11 0 0,01 T111.F111fil111 1.222 422.2 .. 2.2 4 1222 (22212222122 1.22). T7110 114 111 111. 40037444q04$ 044 1590 6.1.23 704.0 00.00. 0525. J7 47. 303.3. 0000 uHUUAJ 0.347 06 36 0.477 Iraq-12L V. .370 004. F53 477 433 0000 7 UQUU 4.317 0 Ed 0 3.909 1392. n “3 37 0.3 03).) 17.77. jSS‘AO 11.0 4111 1.222 4.422 1|...“ 1* 0 0 Q r5 «w 59 10 D a I. 3 U0 0.3 3.5 m% 148 APPENDIX C--Continued 33.367.69.012 J“.3.0l.d9\u 33.3.33334443Q4 JJJuS Q + QQQQQQQ 6.4“4 “4.9“.“ C U daudo‘v .000 0000 000.0 .3 U.3.)L.303)~SS 7230.3 1.30.3 70.1.9707 Q77 .4707 4707 .33 33.33.3353 3.3.33 3.3.3.3 .UJUJ.U.VU U0 UUOQQJUUJ .93 U0 J.U.U.U0.U UOQUJQUQ 3.5 970 5.3 J1io156336d4125262 .33 O3 U320 1: 7.323.496 3.3 OZJ.J27 3291.175 . 1.1.. 4 “a 133.). .391 12 1111 321 106181330003000920 32513132 8 .03 .123 34.934 3 2 4.1. .3). 674.550 9 .08 43 b 433).... .l 22 JD JO .UUJU‘U U VOUU V 00.0 C J J30 .3070 UJUOU U .U 00 .3. L 4 «U ..H 9 .I .3d/576’d‘00772318z .u » 173%.37 3132.3}. 09 31. u 093 0.0 03.91.90 4 Q .59331 .U “91. 1.1.. .3123 09.36% 5.1.1 23 5.3 31021.75 39 U 48“ $33.0 .3914770037341 33.; ~ «al- $.1- 54 32.3“ 32.33 4.3.93 4.3 43 77 17~17777777777777 é}. al1111£2f33§34113 2). 1.2335333333333313 22 L £2.4«42.422.4a42222 4 22.222222224224222 1.11 T171711111111‘11I 44JQ¢QQ4 QQJ +4Q494¢ 123 4 3.3.3.3 3&44 00.00 U.32.3 U7 “7 33.33 V...U.U\U .VOUJ ..UJ U.U JOJJ 1| 11.1703 311.31- 66 4 4 ~.0.3 O 033 3 7.27. 93.413 7777 555 0 333.1; "4.422 2.4.1.2 1111 4+44 3678 .3 35.3 QQQQ 0000 1230.3 7.07 J 3.33 0.0.03 .J 90 ,0 :0 al— 337.3 30.00 1 v. 3873 1.3.7] T805 775 «I 1. 4.34.3 22)) 25 43 7777 0111 3.! 3 ”H 42.)...)- 2222 (11111! “#44 T012 arorogv i .4 4 4 000 V 1.5.05 47.07 3.333 .UUU .U J6¢lu 71.4! $5.1 .zz 1 [—3.47 , 3.1.4.3 373.3 .3497 3348.43 5.43.1. 3.45 3.4.1 42). 39.38 2.9.91 3.4.3.6 03b2 033d 4 631; U661 1333 579.3 J .95., 1.3“3 1333 4““4 2.2.. 422.). 111.1 w444 UQ.U\U. UUOU 9 v 00') 250 £851! U30 1. j 3 J 1. T. 1. 000 ‘o4rT 2432 7777 34%“ $441 4222 7.7.22 111 6444 189JTZ3B 67690121056F890 06677777 77718866688588? 1h443444w4u44nuuw44uquuw UOQOTOUOUOOJOUOQJUOOUOQO JUSJUSOOBOOSOUSOSUUSUSJS 33353353453333J535333362 ++344344J443$43434439J35 JUOOJOUJuUUOUOJJJuOJJOQJ JO1OUJUOJOOULO1JUOOOJ037 3 3 39 2 2 38 1. 1. .35 362JJU75§61007160237ZS72 .100 1.3 337 7.37 6370..»64 511. 3335.3 I74 87 4 135.3 033 51 3 120 555938 4.4“ .1238 1 599000303380191OUJ09U954 w13 5 1d u55 71038 1.07 .3 .b3 .4 8.1303 0 Q7 4 .133 4.3 3.0.31.“ 052 3 a 43 4236 T. 65 3030 7d9uu7730003000035$ 0131-037 0 757 51.1 431001! .4 .3 OS .Yglaob1 32 3 “1.110010 371413473] .084 03 94 7 41709.30 3437 u 409 Q 33 331.7 14.7u3éd1u7512384 10390 12:26090080615323 uU33 .ufdéa3 x¥4AJJLZ~ 5537 1.1.1 3961+7356673903¢721uuo+6 J7Zduiojq9o1646044291607 10Q93Q50~11OIQO9JBGHT589 33.6.302026Q77 U452 .4 5.3.3477 1.2623343117133le 1UHU23 324 1187 7J0672035J2233596031uudu uu09oou7~027wul1 ZBQZZJJ 0002241 333422 U0 T‘Iqo 1.1 342.342.33.123 “.4 3“.432.3u9232.3.9 777777777777177777771777 77777777T7771777T7771777 711771117111~l11qliu1|111111.1... 3001T12223JJ~%4536661760 («3.3330133 43.111). .3313 131...: .134“ 7‘14.4141.-s«4-.14fi414o‘wga‘.‘q4 4.41‘ac 4151.1. wJ4444494+44+4444440JJMw 123456789012 399939995000 3+QQVQ¢64555 U000 0000 U000 355535053505 1237;8021862 4434+3553355 IBOUJOUOUOJU iu¢64100J008 390076 0 512345 0 I57 Eu 1 .111 ud1o 2583912 3685.3743018 670577440956 43£79J370Q3 7:31 10.]- T111 J0u737701999 5.0 4.3. A Q .99 370.3 00433Q1RT746 5.322 5051 1.3.3.3 .477 uw 0997 12410 64.341 I 1|", 101210396480 3082~ 88 25 397 33 0723036820800 5.3.55 39.36 US d906J383fi6 3.323 $321 2 364 1 993150390069 617763653773 u 5311861393 8 4002106565 £935£1288310 3 0.3.] filalal 1.1: 000435001500 0004 24JJZ33 J0 U). 211 To «I11: 5:... JZ1J£15+J15Q 177717771777 177717771777 300111221233, WQJQfiaqwquuu 22)» 4.2.2.1.. 422). 1.11.rl1| 11! 1'1", 44Q14444444 F. “567390 000000.01. 355353.35. JCUUOOUO 3.35 05.353 F28 0):]. £3 {“335443 rNUJUU 0J0 F73H.U\U.U»Uo “9 7a 22 r31101410 013.91336 [2272177 .34 2.09.32“ 1.2..» 4.32 .309 U636 .O 0.52.30 ‘11-. 0657705,.0 O 49.393“7 18.3.05 ..w .0 nu .Il 4101.1...- UOOGSOOU 25 211 1 «4406.371145 50679726 ’7. 318.35 16 0.3412 1| .1 13.93.141.86 1.4.5.36 J 0.6 00204160 09 ’8 $5.30.,“ £12211: OS al.111223— 33fiU US$110 4 “.3 0,5.153 T117411 J41SQ321 17777771 rI777~le71i 1.1111111 I334w464 “H“QQQJQ 12222222 11111111. 644w4u$4 IZJ¢ 111011 35.3.3 00.00 'US 33 072/). 3544 JJOU UOQU $61.5 £167 .3 O .I.4:3.u~ 3.0 39 “.347. 641.5 3343 341.). T777 F777 1111 33.35. $.44“ 1.222 71:11: 4444 «H.078 1.110 3.353 GQOO 305.3 6027 3.3 3H» rU.U,U\.U .0000 6056 d 42 J 12 30 12 3.3 J0 35 [8 ¢3 U0 u 150 17 :5 .90 .11.. Ho UQII 4) T7. 00 149 APPENDIX C--Continued 53] 34 47SQ 9450 .33 13 9.0 7 Q «#69 “ 32 77 77 nlldl. M49 .42 44 an.3b 5.4).). 33.33 UJ .Ud Y923 07.7). 354.4 JJUJ JanuJ do 07 1 35.37 3.887 TILUJ1 31.495 T 12 DVUJ 91 4 4.3 7 0.0 4 3.3 .n .47 3.3393 Tiled.» 031“ 3 * 4.3 e (fit—.13 «30 .J 35 3.3 343). I777 I777 1111 5833 4&1“ 42./2.6 1111 $¢4+ 07 “iv , J 000 r23u 15.333 5555 UOJO 35 35 57d6 3463 JUUJ 3.078 333 355.3 U000 3.353 [728 3‘ 4.3 U 003 I 011 Hdéé ‘35.: “a [99.0 4.303. 5775 4003 0008 4650 [966 $000 .I d 0.0 3Q19 137.3 I .43 [3.3.0 1621 31.70 3.1.3 0 1U67 1' .3qlos 39 .UCJ 11a 51 “4321 I777 T111 7111 Qua“ £2.42 T111 W414 T013. 3 .Q ,4 4 3.3.33 U300 Y”V3.3.3 0723 UUUU IUJ1O 372 D 0&2.3 1297 T 27 1 I75“ 0546 via} u933 jawst...‘ V1.10 24 J>.3J 1.. V.» 37.3 7.1 1.8.1- J 13.0 l- 01.51 .12). 0 7.343 375x.) 3 J 33.41 1777 1.2.4}— 1111 194““ 2222 1111 #44 d 3443. [410 3".) I” T r4436 Fax! J Q .Q 4 4 3 Q “.3 3.3.3.3 3.3.3.3 0000 3000 J 33.3 303.3 0.47.5] 027 3 343$.3.34 J U30 ..J J U u 0 \U 1 318,0 33 I 01., 0999 09\‘J 3.347 0.38 T417 100 .3115 335 377). 101 11.. 3.3 .V .9 U 01» U 35 4 S 3.3 52 U6 .v U03 3.003 3 6.3.30 7 41.44 6 7 J 3 LJdan.’ 0.937 57.9). d O n 33.013 0 10 O D .039 48 O..3 1 U2 T 1.!1 UZU.3.3CMUC—3 43. .-4 .334 1111 111 3431 3.3.4.3 [777 I777 1111 £111 42. 53‘ 1.333 434.4944.» 1:). 1.2.1.). ‘2 flan-111111 Tu+4444$ 123Q.3.07d 3.33.3135.3.3_ 3.35.3 3.3.3 3. .UU‘UU 3.3.301 U0 00 7355 j 4 J5 VJ HYU ..U 000 U \U .U U 005301300 Jivoo U? {Q [.4 5619512731321d08 9042,6869 u48$£562£2393873 30.111.94.53 £221T1 2 .4658. 05.739.11.11 0.331 3.5.0.4 497.3 3.972 39.03 JQQQ I UU‘UO U908 2 2 1 743.43 +4.30 Wu. 0.3 62.02 4 315.3 3 29 433.3 dd 04 .4321 O). O 0 '07:11. 3599 5.31.7.3 O Q “.0 17.57 003.3 T1 1 5.UxU.33 Down “.3 0 O 1.7de 11 1 1.1343213 I777 1777 11111112 .3 3 Q 3 3 4 44 in“ Q34“4 7.227. 42.1.2 11111111 Q Q .4 4 4 J “.4 r4012. 3 0.0.5 3.3.3.3. 0000 3550. c726. 3445. UQJU U000 5934. iqwz .2331. IO). .3“ .3 4 “ Q. 10 336 09 u. D 30.00 D . 1 V .3371. ’19)) 1.9.3.0. 0313 I 4.102 47 «V1 T 02;; 0.3 4 .4. a“ 5. 11 U03.U «- Q 7 1 $1425 [777. I. 47.1 3 4“.) V “ 4,04 1.227. 1111' Q44.» 35.35. U000 35.35 4728 3 4 43. 0 U0) JOQU 3307.. . l.’9d 6098 3:31-13 1.3 b.3 I 4.3.1.7 6307 4 {0.4.4 ”30.3.3 H44 63161. r777. l 111 3 3.3.3 U44“ .222 wunn DC 07. fier3ca U000; U555. 0272 234i U\UJ‘U U00 U. 1.3 87. 0.1. 1).. 42 1 V72“ 826 593....- 72 1 do U0 r.¢99 3 H3... I777. T111 3.0 00 java 3 62.1.2 T111 64 V 4 17777777 UJ.U\U«UO\U\U 3.3.35.U.333 6772 0.477. 3.4 ”w $33.3 In ‘0 J UAUU .U\U\U U UU‘UUJOOU 3 1355.00.07 319312337 3.0231 08 5.3553)- 5.3 .I 1 UHvoo3nw27 [2 O7 43 U2 10J1 U2 31.5.3 6 1 12 UUOOéxUUU 9 - 300....» .41 4.3 J 0.363529 3.493123.» 3.52 08 51 a 17255 4 .95 J 222.3 g3534300 .I 1 .3)..3.3..3,.3 I33£5432 17777777 117.).1111 07 77 338.5 qugu$uQ4 1.2222 ‘22 11111111 3+4~J444 1890.12345678 Y012T 456 .1390 158.5 668.6, 0000 000 U 3.3.3.3 30.35 0 0.1.7 1.52.5 3.3.3 1 $.34)... JOJOJJUu U1“ .9 T-O‘UJ 1.343.43 .‘1 I777 I777 1111 Yul-.47. .0999 r3139 344u34““ 4222-1222 1111 1111 “$14.44“; 89.3.1 “631 2.013 1 rd751701. I 7 O“ 3 I. 1 3 3 5&203000 60903 3895/ [4123 333 50001000 I 1 3 18301093 in... 3 7% 30.0 1 .33 .913 .3 03793759 33816477 T3903 53 53243 1 .433 IB13UQ$Q 341.151.1211 5305c, 0300 00.0 .006 1100 110 1110'. 101-1| J‘UOJJUJ U 32790 .002 3.3183664 11 111 403 68.3.0 09.1.5. Jacuu1 3 1 .72)?! 3.3.3 T703 774 0.370 114 rnluka 153 UQU U71 “121 32.42 343. SQJ rI777 777 F777 777 7111 111 3.0.00 111 333 3.3.3.3 622. 2.42 11 111' 4144 4“.Q «’99 17.3313 35535555 .3555 35.35 355 355 3 5.355 233507630123456fd 100.0 v0.0.0 UU 36.0 0 0.0 0600 fUJ‘U U000 UU.U.UU.U 360.0 1.3.00 32.5.0 V23 008 0911uug11J91T-J 1 1111 111 111 JOJJJJOUVOQOJu OJJOUUJ U .J\v 000 .u 51 11 37315402‘256J2 5321001515037 0.3 1393331510133 q 5 U9 3.0.,0 0.33 17.4 21 39093563194333 39 U.3.0.1.JQU7.J3J).— . 378733793711 .3 .U 0.0.3 080 O 4927 U9 ‘1 1 1 1 11 V0 U0 UUUJ UOJO U0 37000090000730 JO 1 .2 T3 .531 3390 39.35.914.231 0.327 72.3.3 0.5.03 JJ 5.41.35718 36.3.0flv1r0 1.13.1. 3403—.- 3). 08 31 53511111. 1.11 T2 39 0.3 133d 4.56.: O U .10110 U4411‘J 3.177 . 4.31111 1111 41.3.45213 4),-1.3 v3 47771777177777 7777 I777 [77777 11111al11111111 112222231334QQ 3.3.3.3 3.3.3.3 3.3.3.333 1.22.4 42w.22227.22 11111111111111 444463144461“ ~ 150 APPENDIX C--Continued ..- ‘7J \U‘l ..O O U) .123 uv.’ 0'“ 0.0 :33 .IUx.’ 7&1 72.33 Till-I‘ll 30.00 00J.0 0.020 7000 VUJJ 7033 I770 31:3 3 4.3 14 4). 31058 3603 Til 30in 5.U1.I:J 1|1l 0.0010 3 02.0 3417.3 4 .731. 9 06.0 44.33 “.30 4 3.3.1.3 77.1! . 3, TONI—3. 4 U3 ..I-‘lu 77 77 7". “J 33 742 11 + n! 7.00..) 1.71.. 3 323 T777 r777 11.107! 3.3.3.0 3.3.3.2 2 4.4 4 5‘11 4444 3 07a 1‘11 6.0.0 0 J .000 4.060 9711 11‘“. JUPJJ 0.3.30 043 651.. \U1l 024 J 992 {a ,0 .3 1 7428 4 J23 70J70. £577.. 711! 3‘ T210 J7 d c )4 4.4 4 3.34 7777 7.11:1 1018 671.11 555; 4.2. 42 1111 4444 000.0 3272 03.310 0.12 O 4732 3:352 0.1. 4 U 5.3 0.0 09 0.0 T111. 0000 31“]. 3.0.0 0 7.05:3 313U9 Tl. Lu/a1| C 05304 I700 wfiqJ/uql I777 1110' 0344 35.35 222.2 v-111 ’0I2f456F090 234 7222.42.42 4.423 3 33 .0 06.0 0.0.0.0 #70 0 0 0 0.0.0 0000000000000000 0 4 3.0 U..3.0..0 02.3.0 U23 0 J.U.71I 791:1 70091. VI 091. 1|.I. 1 1| 11 filil 0|. ..lql. 1| 0300000000001000 200030J00000J000 Q84. 5 711 037.4 30.11. 6.43). 2,256 36.37 I. 21. .0021 6037 .395 O 33 3.016 [846 3.3 3 .0 0 0.33 724 5993 T009 3583 4949 0.3.3.4 0 0.3 0.4.34 07.33 4378 3 ..07 4.979 37 4.! TU 04 0 0.3 0.00 0 49.47 ‘21! 1| T 1. 000.00 00030.0 030.00 (Z370 0900 000 J 00.U7 0.31 S «I Ila... 4 2 4133.3 ’09 0.39.0.3 41.92 468 7 0327 72.3.3 3.0 0.3 3093 0 .4133 07.0 3 0.3 00 71.0.3 4 3.2 3.457 3263 4 42 7 qlql 7101 71:1! T.373/26.3U’33 .0 4.043 775.3 3.3111 UZVQIT- T.J.D7 .4 1:4 1.1.7.1- 7~|1|¢| 32154154 32123 4215 7777177777771777 1.17). 2.41.1 111.2 4.421. T111T1222223 3336 33.3.3 3.333 33.3.3 33.33 222.2 42222222 222 4 1.111....1111-1771'1411 44447440404444443444 00.000000 032326.33. 70.00.0333 11711.3.D.3 .U UsU-U U‘U.°..3 .3 02 .00 .00 0007905 .4 ‘75 1:55 Sanl 77700036 31033 3.00 025 213 042 622 237 7.7.] 54!.3878Q38 .00 034.478 775770.023 30152070 1:1 4.37 3233 UUO 0.9.6 00 8.47 7.3.)— 1.33:. 5020.0 0.01 3.993 .49.» 9.3.37 1:7 .J 1431. 5.35 110l- 3 0407.033 4 49.04 01...! 74.3 0.47136 3575). 0 00. T71 .330 0 07 7.0.933 0.0 U j] 000 11.1 332 32343 [7777777 T111177? 111:! 35555111 7.22 4.24.4 Q 11111111 3150444.”; 344.546.0007 . F330 0445 0606 0.000 30 0.3 4.33]... 3.3.3.3 300.0 I I. 253 U002 3 33.3).- 470 .3371! [.377 373.“ ..l.| 33007 T7 07 I203 .3 “75 b [-9.1 via/.ua..‘1| J0.Hl . T1101. .4.“an 154.11 109.00 T2345078T012fuiofd90WZJQ 3.3.3.3 3555 3 65.0 066.0 0 067 777 006000066000000000060600 00000000000000000000J000 3 0.6.3 65 0,0 335 0 0585 5 0 06 35.0 0 4.3 333453 33.45533 4 335.3 34.33 3.3.3.3 3555 35.3.3 3 3.353555 3.355 vOUJUOJJquJ00007000J000 000000000000000006500000 39400547U530259570960995 313637095764Y037 403058 331013472 2 4018.08 704.30 2959 0 .34 z. .4 37 07 2212 ‘11 £00.“? 11 3077300924542047WOOBJ016 00503 339010075 2 8 590 03934 274796643 4 3 2.33 0370 2 2 4.31.“ 2.01...» 9 .024 710233 33.3.3 2 .01: T00000000000000000800000 fl 3 6 TI 204936030005 68004470620 (07544.41 1 .083 7.02181! 37.31. T22 84.362 3.4 6.337 31 4 2 1 2221 13 321 ’3 115033J029030’12T0134521 0077 02016072500 9323903 0003 79535173084 784J939 0.4.39.0 764.320 0943 25 0160 31634 13593 1 212 ...2 1 J0940522134339020229l790 214043222222709011171120 £2 1 41.5 .4 32123.43)...» 3 4.3;. 3315 0.41:3 1777 T777 7777 T777 1777 I777 I777f777 777777717771777 T171T‘77 71:1... 7111] 71.71 1.1110 T122 22.2 . 33.334334 5.3560667 1‘31T111T1111111 141 1‘ 170' 444430404444304u 4463444 1777711771117111 «0717 141... 34444444444644443444 444 W078 012 456 777.880 066 6 066 66 6 0 O 06 00000000 000 35063350 85) 34.33 334.3 334.3 335535555355 UQOOUOOUUJJU 00.00.0000 00.00 .4 0.05 2252 T522 6.38 7721. T076 381 5 562 343 Q 403 22 11 07 60 0000 i556 :99 6479 .130 T683 361 3763 Q. 42 T13}. 000000000000. 0840J7000710 2.3 n» 1:03 62 0 104 23 1.- 61.. 210529520000 003 7121» J70.’ 037 2 4230 030 6 4347 355 1253 088643462115 189 232 421.543 41.4321 I777 I777 I777 I777f777f777 111711.111 7171 177333683993 71.114.171.1711 QQQQU4BQ Qua 11.011! 111 111 4444 444 444 I890f23930 0003(9995) 0.0.0 0:» 6.0.0 0 0 UOOUJOJOJJ 35.0.3 35005.0 34333 4.3333 3.3.3 .3. 3.3 3 3 3.3 05.0.0 00.00 J V 07 03 HUO.U 0.0.00 J.0 0. .0 (J 35.05.0953 7 36.67.3731: )4 3310792404 I .5 T 37 9.3 03 1| 1:1 d41n23u07 ‘C. 3 4 4.2 429.0 ..7 3403 077....F7 3 4 Z: 0596 «.0 [433 34.1.4 22 471. 0 30.00 0 .0 37 Q 0.: 33.5 4 4 740 6 399 35.01 T7 39 39 0.3.67 32 .3 007 01. 0.6 37 00.40 0 1.7.3 71! 7- 011-7117 71! 379.6 0.] 41. 49 0 3.04, .039 42 [7 bro :5 033 39 3 349 4.343 37 9250 u 3.35 a 4 rial 5783569.: 38 000 0 237777 341.7 42.34 3215r3 .I.Iqtqr¢:waql.lri.l 7711777212 7. fiO'Q'iIIIlQ'CII -1 1 7117.71.11 .lal uQuBQQQWB 1717111710 343.440.9610 151 APPENDIX C--Continued 657 01d .7 012.5345 0. . .10 00.0000. E 3950 3300 07777777. U0mu0g J 0.38, 000 U 0585 3.33 3333.3 . 3.3.33. 3.3.3.3 . 0.0.00.0 00 0 0.0. 59. 1 .u 33 11 7.3. 7.3 ’03. 71 4/0 11.1 09 .44.). «4.3 20. ..3.% 7o 01 77. ..Ib.‘ 11 4..“ 11 “J JUJOJOUJ. 5213 1.781 70.3.£.D3“ 31 .H r1071. T734 12.02 w “57. .3173; 39 V J 0 372° 18.: 11.2.3.5 u.‘1l 4 ‘2 4.3 udodbudu .O U 0 61~J 1‘ 40046722. l 071 635.5. 5 369 H.873. 31 0 0 O7 074 6 £3 + $3930. 3.3.3.0 715.0 7.3 04 £1.40 .73 .1 39 O3. 0 Q 0 0 3111 fd77 a 0.49 3 ,4 Q 4 fl). 41 .j 4.¢d./. TIS .“3 I7777777. I333344+ T1111 T111 QUQQ T111 .4004 1‘1‘. 1111 W“ 4 4 11111. 3441 1.690123“ 36733012 VJU11111T1111222 r7777777f777l777 0190000000000 0000 3.06.36.30.30 0.33 3063 v.3 33333 4 5333 J 533 3.33.3.3.3.3.3 3.3.3.3 33.3.3 JJQOJOUJJduouvU TUOOOZJOJJOOQOUJ J 6 “0806026U400347J H ,4 03421333651098 I 171.198.41.101 #72). .3139 0.39 O .34). 1 ‘11 1.1. J07826321773 3092 6,526.307869 J33 2024.31693 4 Z1 093 03.0 570).. 2 I. 32 4.33“ .‘2x33 .00 O 01.090.000.0000 U 0 00.0931 1 $3.30 0 .4 1011 1.30.34‘721. #313 0.00.0 321 0103112304 1.1 I7 3.99927 [c.1112 3.1.6120 0.01. 2 .4 15.44.40 T59936111304JJOZ 37.151.413.477; 0 401 7973.371 3 C3719.34 6001.3.197 13 30 7 D 3 “47.0.30 3030 f 11 1 T247571do9403221 ‘2Q3777534¢»3242 c1595Q32qu32134 I7777777l777i777 3 J.).32°l°6;3 91111111 11111111122). 1.233 711111111 11111“ 111 Human» ““3434“ 9.649“ 11111111111111.1111! 4946+44¢46$4$¢QJ 345678901234 42.42.2223 33.33. 7777i777f777 0000 0000 0000 050.0 3.3.05 .630 O 34.3330333 453 3 3.3 3 33.3.3, 3.3.3 3 fixv00 00 00 ..J 000 TQJUUOOJJOOU 33 OJJZZJJOSB 7.043 19 7.50.3 .90 a 5.» 04.9..) 1 1115‘ 3.3“.001831325 301 .387 7173 079 .69.) 072 o 314 3.5.0.3.):3 J 1 1.. 2 0.0 00 00 00 000 0 3055900301307 1753 J 9 5304 5 1211-. 35.34 33.73130 0 0 O71 0 41.07 19.5 3172 0.0.“ 0 a 017 32 031799303 4 1 1 11.31 q TQ351355IOJZ -62 I. 1 11.3 921541543215 777777771777 1111112 4.1—2 1.3 3334483434u4 1111011111111 “40045 “QWQQQ 1111111 111 QQQ¢4Q643+QQ 3678 2332. I777 000.0 33.36 .3343 35.3.3 0.000 0 000 13.9." 67.00 0.3.31 3 $33 11.9 33.30 [7).- ..u 4.3 .066 .622 000,0 7000 009‘, 3320 .1861 109 U 4 D r760 .J551 4325 1777 3334 QQQJ 1.111 9 “4.4 1111 $40.4 T01 4 343 0 F890 1.1.3.“ 3.078 301). 3456:1633 JJQJ » a”. 4 4 .» “53555 35555666 066 o 6 07 f777l777i7777777f777777717774777 JOUOJOOUUJOOTOOOUOOOUJOOUOOOGUOU 3a5553300585u6506585066565006585 3343334553343345333333333u553334 35353335335535553355353515555353 JudduOdUUdQOJUUQUJJOTJOQJJUOFJOU JOJJuOOJJUOOQOOOUOOOUOOOuOOOWOOJ J1123342T294I1090625$710036O7a14 i§21u 23275; 8 1866910 67 0673 18.0 1. 7 09335 7 48313 90 455 155 4 3 .v 237 .72 32 537 r 14.1 04006085 08310000099080061103QOC .93 d 35 1 I 2 74 8 029 7101 .323 I 3.0 3 1 4 5). 3 T05 I333 240 4 27 2 z 13 9 552 5361 1 3 2.).1 UUUJJOUUUOOO«OOBJOQOUOOUUOOOJUUJ 3 6 uOGSUOOSWZéOJQQQ~807J300392000u0 2 8 95 76.7 7 0 307“ u 1 1 36 3413 2 4 8115 8 3 11 1 (33 3.}. 1 1 3317192254540141341135101Q903614 T3533 4631550 9549b5661419341778 [051? 3013533 73£9¢di1 00857785 53; o 25 24 4 2355032 J141Udu1 21 1| 1| 1| T1! 243 438o3470111£102243£2f1u43599J471 332433213431T5213¢32fi5545£115432 I777F777I777I77717777777I7777777 4 4 453 O 90 F777 I111 1111 324“» 43451111 4J4¢J444T44u45556666000610667777 1111T1111111 1.1. . 11 111 11111111 IBQQJBBQEkauuuuafiuuuiwuduuua4344 111.1111. 111.1111 T111iI1l1-1 11111 11:11 4+4J44+ ¢¢QJ¢Q4JuQ44444IH4QQQ+4 0000 0 0.38 3.333 3.3.3.3 J00) 000.0 .3309 .310 2 d U 3 0302.0 03 Usé 01.414 (4.037 111 6000 1190 3,033 ‘11 .002—3 0111 1.343 I777 Ti). 4 r777 Tic-I111 ““04 Tel-11, $444 WUGOGU UO 303.3.U.°.3 0 43345333 3.3 3.3 3.3 3p3 IUJJUJJJ 000.0.00100 H .6 .Ud3r327. .3 1.3 17 2 0.0 3 Q 73 Q .3223 4000 [3 .015 32993 3475“ 0000 00,00 u1u88007 8 89 4 S 77 5 1 1 1.520.523.1143 [,0 623 11 30.372 2 0073.0 .0 1.. 11 0.9 “11.03‘3 71111 1.1 32.1—30.3 7777777~I 22333233 17777835 T1. 111111 ““00““43 1111...!111 “304.3444 T2343678901£5+ {777/7777683fl8 177777777777 7 (a 30 +4.3 3.3 Id 00 .3). A1 0.0 32 ‘1 64 ‘1' I7 33 Id 1 11 a.“ 152 APPENDIX C--Continued haao 3859 JUJJ 5 UV.) ~57 3.37 O idud J059 21.. 24 an» 2 5.4.31. 7.09U 0.468 53.39 7146 11 2604 732.3 03J6 c394 32§3 35 Jubd clcl SJ 27‘ 73.37 33.3.3 .4 4.07 .l .3 U 07 10.0va 5.3174 n U3+ nqlzu? 3:371 76 7—3~UJ A GU OH 11' $137+ .7777 f177 101. 1.903 17122 igfiu 111 344* I777. vzsa 999 777 Jada UUXU.3 (4.527 6.37 0 J00 U T700 .06 JV .3). 1-1! J2.0)5 397 0 .3943 39.43 71 J61“ F130 3671 00“ O 0320 441] 3.33 O 378..“ “.60“ 1.21.1. 1079 Sana 51.3“ 3743 16 3.5., MI I. 9.37 1 9.0 D 023.0 5.437“ [717.] 0.077 U293 O bd1uql 77 .41-.3 H rI-I7~I T777 1.111! UUqlsl L22). 4n» Q 11!} T4QQ [J97. 3676 3999 1777 .0de UQJ.3 J37=I 0.376 U090 0.59.3 €11.35 3 .537 1.3. b5 3 583 in T600 Z7 57 7Q 5.33 3137 .357 U 22) 1| 39.41.. O.£.§.l 7.5.34 7 Q 3). 4.460 11 1 02 O17 d.U U1! 10 ‘11- 3.4.34 7777 7777 Til-O" #1122 2222 4 “Q“ 1111 H4u4 .301. A [3235 I000 JUGS 3 67.7 0570 JIUJU 0.31.0 33.47 .3185 I .i ..n HQ 2033 1.926 ’2 US 3771' D 9.34 U240 J 2 ‘ Q7170 Duals I 71.1- 31.33 1", j Ox’J U7 36 3.327 ,6 O 3.9 .33-lb 53“.. 7.46 3 1.11 3234 T777 T777 #0117 2 2.1)) 42;.)- 97.44"! 711.1 QQfii 1.U0\U , J‘UUV T350 U 03 7C 1.1 5411 3018 3463 7270 11!!" J176 w 9un 3.377 .057 3 +201 5 fi $1.6 O J [.437 H U.-L.U .1590 JQJ‘I 3333 Cd 00 .0500 073.5 J O 0.3 VIVJO waldo .0331. (700;) 4.34.5 5134 fill.“ I721 ~7118 $037 7“). 7311. V0 U33 3 u 933d T3 U9 743.0 50% u T771 #403 7.3.04 92.73 ’75 4 :73 a $023 3777 443). 7777 I777 7777 $.3.33 1.71.2.4 . 3““...4 To.“ 4444 1234 1.11.1 5010.6 JQOU USOJ 273$ [6 0.3 JUUJ 7730 #1763 36 tsu 0371 368 J11! 32 0280 41.un 3.59 040.3 131 I003 7.3] IQ * Q .47 34.1.). 7777 T777 1110. 0 0.0.0 T532). .9 “ ..Q B 771710 44.9“ .078 ‘1‘ 65.0.5 VQJJ JSUU 1.7.38 rods JOUU UQUO r730 .0 013 6483 3039 1453 3.638 W .093) 3 $01! “21.3 T 4.33 V000 [777 I. ‘7.)- 3.44.4 1.1101 .4 4‘ 4 011.2 .152)- $838 JOOU 0500 1.733 {063 JOUJ UUOU 0).“0 0.). O“ 31! 1133 3249 £735 «360 , 7.1-7.3 Q.O.|2 T14.) , 3‘32 T777 T777 7771 53.53 1.2.4). QQQJ [1'11 .4‘44 U‘UJJ U 091 017.3 208 0.3 042.6 .31-7 3.33 12). U097 10 .. 3.5 13 1a}— ”4 3.3.31 0.1.9 5 d7 11 0361 7085 cOBu 30.3 23 9.39.) .l )- 2 1. 3&32 F777 T777 T111 ’99; [222 an“ 4 71.71 +444 JUUU J 000 r72a U49 1%] [J] {600 0 VJ O7). 900 40000 J 070 U «I 777.3 75.07 0739.3 “.337 314 T1» 34.375 T777 r777 I111 JUQU 7111.7 421—2 Jguu 1111' 94$4 r 4.36;]33 0......234. 2222(2233433. 65.65 533.6 5538 JOUOGVUOJOUQ JSVOUSOUu5J§ 2736(7Jdo732. 1°02r0657667 9000 Joand 4002 908 .37}. 23 1 JJBO 44 .JQ.‘ 26 ‘l 97 42 2.1. 6317.1 J49 HfJQ U 4.4. .J [17 I. qlql 3435 I777 r777 11’. 71'). 1711 fitéz H U Q .9 71.17 +444 3673. 533.1. 6885 3000A 3000 IJBJ 9939 JOJJ .0007 8 .3 2 JQUQ. d 053. 6623. 9566 Q .3001 r. .7‘ 7. .b a «I. I 3. 2 U977Jd37b959 62.37 5562 [737 2 fiddo 83 .V 0 E711! [.0 ‘3 116 1! £007 12.50 3 #3.].3 [777 fi77l T111 .2223 7117. [222 Jung“ 1"“ ~4¢$ 7012. JQQU 3386 U000 U030 6273 3766 U U00 U000 538.0 [10 .6 4.337 .71339 67111... 76070 [d .30 7.3.0 D 734.4 763 .II do 00 U9 U“ 50.63 :uui C7 “9 1 379“ U“ 4.3 .0445 W432. .. 5631 .6833 663d 3.1—7.3 J067 1.1! 917.39 00 U1. ‘111 i563 .1777 .7771. 1' 3111' r 1.224... 3 .9 U an 1.11.1 ‘34“ 0.0 3.0 0.3 JJ .00 0:3 [3 “I.“ (49' 73 T1 62 32 ’WI 94 W4 42 a“ TI." Iu367390123436737012445o?O90 {4&4444535553555366006600067 5588886508885366583356550585 JOOOOJJOUOOUJOOOJUOOUUOJuUOQ W0500050U0500300uSOUJDOSbUOS 527362738273d736273847671327 3706370037663063760576300076 JUJUOOOUUUOUJJVOJUJOJUQJQOUJ JOJJU369TO$IZOOUJ1OQJJOUuOOu 955d 96: 5 1637 37d 5 .0“ Z “21 3 5300215637S7I76194060623J13d 38750095352U91080360 b 23a 6680756915304 1 2353 6 1 1 640213534125T 121d 7 2 7.1.1.2....- 41 4! 1- $5385952u10700072634T709u001 ru77d36299280 2365756 5 134 $1.. .98 “079202.: a 35397 )7 2 1.1.7. 127/2970.09] “7* g :5 ‘u1l3.37 1| 8.573 “4.944365 2.333 «I15 cl 4 2‘ R30000u0U0070000*UQOuUUOJOUJ. Q 5 Q I3 2 A 1 7 o 400049347592100701743095T13953 3 787 b «7469 38061 29778U 3 270713917 17427 01771J J 152468] 2W337 62:17 I1. “4121... 0324 07.05 0.» ..v a 731 + 721.3 {’7 Q3 15 470.716.7391 U700 13.303 3933 .4 .40—79 53.39.4540 3063 b 1.3 .817 J70... 1.03.... 3291392460022 333733731329u b75758 U8 DUSST 31.73 .I 5 222 1 Fo¢75¢13950117813fl330é1b3003 [.3 o 070117 277.3 31.! 2 1.1.3 42122 Tl 117.l {3Q325Q3H3u3443‘5u3‘3424$354 f7777777 7777777777777777777 T2235271171777222 0.0 0.0771.)— 3114 .Q T1111222433...33.3334uMJIJQJ 222222222222 2222 4222 ‘22 2W2). 2 Kuuuau4u4uuuuuuuuuuéuuha “QR ~44¢4Q+4¢44444¢4¢44¢446~144Q Q4 153 APPENDIX C--Continued 573 d74 00 05 27 79 ..U.U S 34 77 3.3 22 4n .‘1, 3 0783 01.2 34.36 Twin/77.50.558.05 586608865886 U‘UUJJUJO U000 U UU.3CU.30.U.U.3\U 352733730273 037 0 0.36 0 37.0 0 A 0.00 v 00.0 U 1.0va J U31 U0 U0 UUO.U 7). .37 1S 3796J373$91J 3 “33.3227 318.3 17.1.0.6).161.’ ,0 0.5 4 3 00420032T949 .5 0 11 0.3.33 )2... 20 .1073. .42 5Q.2.023 33 1111 . J.UU.JVU.3,U.U 000.U .3 7 2 .I. . .IJ10. 3911v 7 U0 J I 2.0 033 5 ..I 51323.3 I 532 H34 ‘11 277.1 3733 0.0.3.1 3 2633753730 1. 3.0 4.2.32 02.39 1 0 2.24 “ .07)..» “.3 ‘fi‘11 .411 110 Q 0 0,0,0T 0.55 5 3 35111111 1.. 2.3.» 3.144 372343 7n!77777777~l.l 3511T17-).J_111 . 31.3.3 3.3.3.3? 0 0.0 .22 .2); 22227.22‘2 ~404304uiuuu 1411111111111 v.4 “J i 41 $4.04.» 34 F5.’\01.234.n~ 07d 03899.39? ’99 5083553035050 UJJUJGOOJJJU 0.0.3.0 .3OU 03.00 5273.!730 273d 37,0 0 O 0.3.! 0 0.3 ..UJUU 0.00 J 00 U.J 437.3 U000 000.0 923 33,0 434 T7213634fi741 1 3 3172 37 U1 0 216946585 2 1 /.371 .3072 1 .1113 1 107.595 U1.b U03.U 37“ 42.30. 0 31 309 1113 SJ 4 191.914.» 215 11.1223 11 000000000030 V..u.,nv.G\UJ1I4..\U JOQJ Q 18.3 7 3.31 113 1 3.3.3 772.0 I731 .311 9,417 3702 2439219303 7 92.7 2.0.9.0 3.0.0 121233.» 0 2.3 3.57 0338.0 2 3.2.2 .1122 12.-.. 33 .233 23 414 3 43.1. 3 Q J... I777/7.17 1777 12421111. 12.22). 6656F777I777 [22222222222 luau.“ HuQuuvfinnJQ 1111111T-111 4.94M Q44434§4 r0151: 7 U 00 3999. J .v.U.U 0.3.01! 67.1.2. f 0 07 JuJJ JIUOU 3.61.3 3453 1.075 11 3670 “M1 80 11 0.000 1.005 36?...» 391 4 36 .33 Jibd T~Aunnvn5 3.... 37. .92 0435 I777 333 Q rI777 [222 440 #10 .0000 U001 1999 .3999 JOUU 0.00.0 Q 037 0 0.3 0 JJ 00 00010 0000 .0000 J052 4 .963 3.592 2349 7. 20.0 J3SU .33.U fi.J 61 1 1. I TRY/.7 3.390 49.7 3.04 434 020 32.... 3% Q 1 ..Q J “abtlagd TZVJQ567QL 71111111. 3999999 ..7 00 000.000 )000300500500050 1352r36732736273 O7 0 0.37.0 O. JOUQJOUJ JOO§IUUO 013 208 63 397509“?- .| a.‘.U.U77_ .5 114.2 1. 22 0009700Q Q 12 p33 15 12 uUOUJJOJJOuJUVOU 1 .9 IJJUI4O31OJ7ZOOJ 33 02 O2 19 3“ U4 3,. 0.0 .11 (a1 1 1079T350033003Q2 23.091.49.33 9.00.077. 510215554 3232 1 20763002 03 . 2 1115 23 [334 b123 2 2.3.02 077. 1165 1122 rvii/.3 032% 3.3 332.343 .1777 1777.17777777. ¢ 4Q11111 T4222313 f77dd€39V9999999 2222222222222222 fiuuufiuuuuufluu4uu 14110111111111.1111 +$J+JQ$4J4QJQ+QQ r234 1.11 701234507890 [22222.22 £223 3999;999:399 .00 do JUUOUOUU 00.30 .330 0300.3 627627327327 370570070076 JOUUJJJJUJJJ JOJU30000000 #21:.va 4724JUDGAU 12 049 703d [3 741 3728 1 .331 I23 3 1 007049003803 .31.. Id.J 3,4 1 4 4 773 J1. 1 11 :5}- .48 Cl 000000000000 300709700370 3 5’77 918 a 7I80 026 222 .1377 0394.3197 1713613 I496 u747613 {368 .121 UUQ 3427 .11 3 3512...! 077 1726 6.33/~11 11 .1 ..5423435J354 [77777771777 3111 [2.411111 1000 JJG11122 111 11117111 222222222222 TuQJQ4QUSu44 .1111 11111111 ¢Q+44$Ju$w4$ 4: .44.. 1 $999 0.000 J .000 35.va 0.3.33 11 «4 {85’ 2530 bQub 3 1336 a“ 6.501 (3.037 117.1- 0 (U7 11.4.}. 21 11 U .UUJ 1:200 010 11 (4)25“ Ia’77 T177 11 22.00 #11 22.22 31.30 0008. 57 678 012f456f69df234567d .333 0441040JQ4535553555 3999fi9993999339979993999 JOUOJOOOUOOQUUGJJJaJuooo JOUOWUUOUOUUUOUOUUOUuOUU 3000 0003000500030003000 109.33 9.33 09.33.09.330 153.0953 1 11 11.1 11.1 11.1 11.1 11 22000005260J00000v040000 f22 Q37l7 22 1 2500000030001500000J0000 J1 03 91 0 f7 80 Gd 8 I“ 1.4 33 30090461929404232035J405 0295 .3272 1.038 I79 0 1.. U30 T350 .2092 1370 3,012 0234 3 0.17 v .w .09 105355951652125603032172 391231903542197534365011 r0). 1 111 {0450265U8022u383384138u T702 1335 0637 J 821 337.3 037 2 500T152Zd71983711u71334 64521531919U84622700502 CH 1 2 81 22012853977 2:43 35 2). 441111111 w6706513¢3700703d553J7d7 30790785565 d972b63 3 1 Gui/3.31.69 .373 3990.076 3 CU 2.3“ 1.3 2 1.1 2.14 1 1 31023086I62$2d48f8672933 221708066458811211267732 .3536 u 093 015.: 25863 0.21 379... 1.53.5 075 0126209111 2 0 J 751 4| 1.‘ 1 1 1 76701713576018340535T329 150035373504J71050233060 029,: 3.37"» 3H uUlZdBE u .62 277 4 194410410234’76727343235 00.3“ 0321. 3 C173 3.3.01.7.313 U113 4 39 4323227222111111 uUO719J0f320023627¢7v733 U‘U21 Jon-3.1.1.311 27.0 353\vJCJ.04 UO Rhianna/22.221111 1T 11 325432503254325032523253 T777I777F777T777I777I777I 1777177717771777F7771777 .1111 1111 1111.!111 111?. 1111 005355111122f2331344T655 2222 [2222222 2.2222... 5.22222 1.222 2222 [22222222222 2222 11111111,.111111111111 111 666600656660006606660666 ’0 3.0 7’3 .00 V0 30 J”, W1 U39 J0 U S 98 ’1- T3 JV; 1 08 7 9.1. I7 32 UO .3 32 .4 To 00 Tu 154 APPENDIX C-—Continued “— 54 77 77 1] rU.° 2.-.- 22 11' .00 - 0000 J J. 3 .4 [77.] [77.] T1-'1 0677 1.1.2). 2222 .1111 0 0,06 F890. a507. 1939 0.000. 0.330 ...‘11 .4000 3.30.3. 0177. 30 ’2 I77). I 0.713. 211 1000 5543 I777 7’11“ T f111 final-3‘2 .. -5 ‘2 T711- 0 0.0.0 I236. I777. .199 3 JOOO U000 J0.US 1.3.3.0. 4'11 JUJU 00.01 .0 1,036 .0721 [0.013 [401an 11 11.03 r: 470 24.0.0 F573 T.J.J.J 15.3.0 D..J.D—D r55 “3 [77.] 1‘41.- 1. fi“... 2222 [2.22 111.1 06.0.0 0000. fb78WUIZ3ub6T89U .1777. 51383665569 199..) 3999 399 7 3999 JUUJUUOUUOUUOOUO UUJJUJOJOOUOUOJO 000.3 000.30005 000.3 SaddiaJJvJJquJu 111 111 ‘11 10.1. 00.00 UJOUQ .VQJ «00) 00 0). 300.30 00 0 0000 7 .b 0.3 7 o 8 c 1 4:391. 12Q575963633 35.41 3.1.02.0 057 0551 384935552.DQ)2362 17.29 1.3.3 0.0 J3 2 J b 1 TI 111 0018 04.29.0533 v.42). J 014 2430.32 1 u DI 054 3J1 04 939139.41. 104 4032301917Qa1 37.50 $.23... 232123233 1 U087 70.00 007 00 0.00 o 7.35 o o J 25 . J 1 74 J o 5.... J) UZZSTOJJ [Hubf53054013 02327.41 «5.0.1:..13 O 331%.“) 123 .32 a .091 7v 3 ’6 613.353 7J2}. i. ..., 05.15.57 0062 22 U6 4071 349.36973 3376 3123 4 0.0 0.13.57 3350 B634 3.3.5.22 4 4141 1 341270.31 333 3 *167 55b 0 .u 7.... 4.4... w +331... 1.341. 5.3 J J ...303 2.3-0.3. I777/77777771777 1.1.1...) J W 4 4 4.3.3.3 3 O Q 0 71111111111171111 2222222222222222 .2222 2222222). 2.22). 11113111111111111 o 0 0.0.0.0 D 0.0 D O 0 0,0 0.0 .23. $999 $393 .000 0 000.0 JJJU 7.3 33 111 -JJQJ .0000 .761 4.0.05 0 3.0 71 fOJO ~ us 111 a 77 .0500 403 J 3599 T1. .71 I .040 17 49 x4.U7-I 6?)» 1777 07103 1111. 7.21/94 .2222 .1111 0.000 3678 7.799 .7999 600 0 .0000 30.0.0 095} 1. 1'1! 0.00.0 3.0 0...! J42.) 1735 22.). 171 325.0 0 .40“ O 131., 797.0 1 00.00 0J0J 010-11 377.3 40.4454 71 $5 .111 3.07.0 T111... J23 .4 7777 6699 T111 2.4).). 7.27. 1111 0.0.0 .53. .70 00. 9000 111, 0.01.00 0000 3000 10., 33 1 11 0000 0000 7J1; 32 .09137 «toflO .b T679 393:... 924.3 .3565 0.000 00.0 0 417.31 7.091 32 011 1 372.3 1. x004}. 1. -511 3254 7777 9 ’JJ 11 1111 T22). 2.2.79 111 0.003 34.3 0 fid.U\uJ 000.0 1111 0 000 0.000 3.000 0953 fil11. .0000 30.0.0 7 019 07 ,01 0.0 1 4610 .4123 05 3.37..) fil.3.‘3 .151! Ual 0.0 9322 T111 37:34 7777 7011 1111' T111 ‘27-). W22).- ‘1... 3°00 r1890. 3001 00 U 0 1|“1 0000 00.0 b 3000 u 3.33 7 11 0 0.010 7030 4.03.6 10.33 .0830 .6311 4744 £3.38 ~13: 2221 00.0 0 .3400 U1. 10 13.. 3““1 [90.6 079.5 0.54.3 1.9.7.1 U .07-1 I\‘11 3.2.31 7777 112s‘ 11111 .1111 1.7.2). 4.47.2 11.1 999; T23u367dTO12 11111111....222 0 00 0.000 0 000 T111 41111 11 UUGOJOOUUUOO U0000n9000000 3000 3.000 005.0 09.311.031.31) 3.1.0.3 1.. 4111 11.1.11.- 0000000003 1.6 777 .0000 00003000 236973613555 71 711992-752 lb 34 27 T57 “9 Q 9 H ..O O. 13 I7QWL37301701 TQOJOUG O7 0 JJQS 34 .01. 0 48.47 04 62 O 111 1| 1! 0.0an 0038 4077 .42 08.35 90 “12 O 11731.1 OJJQJUvIJJOO 9 11 D 1 1 3 gJU‘uUQuoOqQ 0.3710q443 311.4 [63843724231 3.57.4.4 360.50 07.5 111 .33 4 1. 37532367T031 T1 111 $5 9 0 5254.325...» 341...). I777 7777777 ,,~23,JTJ.J..9.0.C.0 0.0 111111117111. fil11£ 41‘ “I 111 222222222222 222222222222 111111111111! ooooobéoOOOé 456 222 0000 #111 0000 UUOO 005.0 3309 111i J0.U0 0000 799.5 1421 E491 0993 5332 0921! 1.571 Jsug 34017 2.7522 0007 01.0.3 .330 33 u 1 1 3.311 0.53 4 9.671 0118 0.0.0:... 55%.? Oh. o 9 3.43). 7777 1111.1! 2.4.42 2222 2.1.2?— 1.111 0661 367d 5333. 0000 11“ r0.0.U U00 0 0.0 30 33 09 111. 0~V0 0 J00 U 0753 3900 3.379 JDZO 1.11 5.077 4334 T75u° 0 o 0.3 uOUU Iddd 73.40 04 9.1. N325 3‘39; «.411 JdOQ 1.111 3432 #777 +1890 7.1.30 222.... .3333. UOJCJOUJ 10111 111 00 00 000 .0000 00.00 .005 H. 00.30 33 0 .3 .3 JO, 11.]. 1.11 00.00 00.0 0 00.00 0032 9 O 08 31 0.37.4 fuse? 99.95.0330 3:163 31.33.. 3.5613 ’1. S TOISJUIZ 0.b29 0“}..1 4 07. V 0. .13 0 07.3 3.1.14.0 1.111 1.7.751 .0001 0 0.09 .0 1 5 «w 050010.393 43 .3 53.1. 35 2 37a! to.) .4 3,06 0 331 V J1 O7 033.“ 94 564:le .U23.J.U}-b19 72 123.551.}. 5~I.O1 0.093 L.‘..‘3 lb.‘7‘..\u 3444.43.43}. j7771777 1.22.).- 1.33....— 2222 422“ 1.2222222 (22222352 1111111 W.b.°.0.0 0,3,0 444 2.22). 1.22.)— 2222 TI 1 11 06.0..0 7.0125036 I...O J~4444+u¢¢ .0 000 00.0.0 U J j‘ll‘-‘ 11111-1 .0 000 0.000 00 .0 00 0 00.00 0.0 V 0.30 00.30 00 3:303 31. J.3 3.3 111 111171 .0000 U 000 03 0.000 0.000.010 10.335.103.48 99.72.43“ 1 3”! 537 n4 32 O 4.2 3243...) IJ ,4 53 111... 1 1| 0.492300“ 05 3.2.27 .1 00% 2.3.“; .0 1.0.3 céb J OT3 1. J 00.0 0 0.0.0 00 JJOOJOObri 0.4.3 .70 3.3 1 J OJ40810375 #200104 5.1.0 oSZb '2 1.07 79fil)‘ 4:3 2 J7 51111 1 )1 3.3.34 31 H3 31 71141.11! bat-1111 363). 34.93.33 f777i777l7 3.333 0.667fi13 zzzzrzzjyaz [222.22.22 2222222222 T1117111T11 9066 090.900 155 APPENDIX C--Continued 9U1234 30783U12 45555535553660 UUJOUUUU.U\UUUO.U 111111.1111.1111 CUUOJOJUOO 000 U UU UUUUU UUU JQUU 1v DJUJSJUU‘U 3.UU.J 1. J 35 J U 7.3.31. J.).D3 11 111 1111. 11 UUUUUU UUUJ UUU U JJ7OJJuUOUVéUd .U .4 .D 1 93654Q172UJQZ3 8‘: 03.3.’J17676,46 1.3.9.321 (1443.0 [U18 ‘14).11810747 J339 11111 7.1 ,OIO‘D O76fi640 V587 4 519.461.],1?) 134.3 0.422.0J361‘4f514 67624439351969 12 1). 3.4 bOQUUuJ070uoOU 9 8 U \U 3 1 (I .44.; U U0.U U109 7.30U 003 31452 0.43 .4177 U 11.]- 1;..‘71 774 +1U54:..9 1.7UJ JO73JOJZ976074 7.0 03:47. 0995 1.7 4.1. 7.1... J3.J7. 1.50.3 0.5.09 .123 b111 111 5n» nus 479JUJI725 3.54 O 111111T 33 4JZSQJ¢55UJ254 7777777777/777 5 UaU.U.U UW12‘41211 111 11111 7.2.)? 47.7143.)— £12,233 2.4235247. 67.2.4121). 22.23.22 542213.22 111111 111 1'11 .b.0,.0.0 O O 0.0 0.0 06.0 0 3450 6.0 b6 UHU‘U‘U 11011 UJOO UU UU 3U UU 93:3)... TI 11 U UUU WOOD I171 11.1.2! 3195 790 O 1 [.351 O Via,“ 36 31 3491 “3‘2 1- 0800 D 3 VU\U‘Jnv r“ 4). L U861 S332 3074 (474794 52.3 Q 7777 11 1—2 333 J 4222 2222 111.1 6.0 3,0 [~09U 0’0 07 U.UUU 1'1“ UUUU JU.U U DUUJ U".3J T 11 J‘UU J USUOU U.O J9 4 Q1 4 I27“). 7 007 “a... Raw/“3 557 U 3.1.1 U 17U b 7.1 OJ UnUUd 7 9 UUU U 5570 [064 0352 3404 4.4.07 425 4 2). la). J£JJ 7777 L 1.33 31.37. ‘2 (we £2254 1111 0.0.0.0 234 777 uOJO 1111 U0 U0 UUUO DUUU U234; T11 JJ.U\J U U.U\U 51 U9 ’91.) ’U 4.0 3.00 J (.11 4310 0.3 Ux. 004)— ‘3 O7 «UNUUU OGUU ‘1 1° V7‘.’ U617 07.0.5 \d.’ DU 5.‘2\L 603}. 7. £11 545..» 7777 33»; 3333 Ital 2222 111... 0.0 0,0 ‘11], r92. .3673 7012 777778835835 JOOOUJUUJOOJ .1111 11111111 uOOduOuOUQOO U UUU UrU U0 U.UU U J.UU\U DUUU .U.D\.U\U .233 U955JU9 3 11 w. 1111 1 JQOuuodOUUQO JJUQUOOUJQOO JUO7537SJ99J 3,0154 Q “17. 707 0403J96Q OUJ I. .0). *176T4 Q 066278353650 0242 47 2.10% 141932 0996 T39u19 6’54 fil 11 1 11 U UUO VUUO UUUUUUJJ U002 3 4 1 ’8 09.117353“). 1.0064951) 61.2.3 6527 3.4.65 590,.» J357117). 1.971 1- 11 ‘1 2111 0053 ‘24 ..o 3090 11117111 1 1 325412554325 177777777777 3 +.DS 3:) O7 7778 1471.3. . 1331‘ 333 4)./:1. 4 1.222).).2 222«‘22222222 1111 14 1| 111 O 0.0 0 9.0.0.0 066.0 4 id»! U4 6559. JUUO [24. Q. 1939 UUUU 1‘ 1 0..va U.U0 0050A 3193 111 A UUU.U UOJO JQ07_ T0 7 J: . 33 3000 (J w ’- U U.UU UUU.U 9. 3 UUUU IQU7A 00 7 £2 FJ 4 JCJSRJ. 1 3“3.& I777; JOUJ 11.111 («1433 Jazz.)- [22;- 7111 0.6,0 O 111 U UUU DUOU DUUJA 09.33 ‘1 UUUJ J..U.U° fizz 5.0.0 39“ 311 U503 UUUU .UU)52 864 788 211 [9.09 1 J2.) o [777 11.42 11.11 5333 1.).22 £222 111 0,06 (+44. 3.07.5 3‘17) U0.UU I111 JOUO UUUU DUUU J353 I ‘1 UJUU J000 I614 6235 £46 19“ U346 6.36 104 21 .4 31 uJSO 1.1.(4 «J 5&54 [777 1.211 71 (:34 .Q 1222 1.222 1111 065,0 SUOU 0111‘ 1111A U000; U030 DU‘U‘U. J9.3.J v.11 U U.U\.U UUUO 393.3 30 b b 529.44 4.U33 1 3 (dunes 713“ 9760 1.1.95 r02 OII UUSU 2). 7.9 11 JUJQ .07 0 4 1‘3 . GJU‘U . £290 J90?- [119 . 1315 Ob33 Jig). I. J254 r777 a1zz WQQQ [22,). 1.2.1.2 Til-11.! fio 6.0 O 4.310; UUUA 1111A 1111‘ 0000. JUOUL 3000, J 353 '- 11A JUUJ 0000 [.727 0527: J31...) «4629. I 1 U053 UUU U. 6 .3 TUUUA 3 9 J T.770. BSQ7 (4203 5029 11.4.2 U.317. J 22 («7:3 .9 I777. 4233. 3444 £222 (222* '11... 0.0690 r890; U001; 1111A 1111, UUUU UOUO 3U U0. U953 '11 U000 U000. J97i $415. 43“.] r655. 11 Dugo OUSb D967. .42 V009 03 31 1‘. .US‘J 63 1S 1311 1.5%», 5251. W79Q4 12“ L131. [.411 3256 r777. 1343 T44“ T222 .222 T111 oooog W234, 111. r111A "I1A U000. JUUU DUU UA vUuflo.qJ.~J. Ill." UOU J Taco U a 0955. 3140A 3599 1679 T2 ”p308 31 O U73 0 4.5.31 (312. U7UU lU57. 5.451.! 022.3 JJ72 3723. r112. 71.3 J} «42.35. 7777. “.412. 1.95.3 1.222 £222 1111. ishvb T6789O12 v...11u.1.l3=./:/. r1111111 11111111 UUUUUUO U UUUUUUU U UUUOOQOU 33545353 T1111111 VUOOOQUJ UU.U,U U U\U\U 38326072 13 65 2v 06 ..D 31 11 1| ,0 U 2 JSS90J9§ U840 “a 3.3 09 03 0609 2d 4121 UBOUUUOG 3 o 9 1 .44 JR; UUJ‘UU .9 r3 79 3.4 .35. ‘1 4 3Q31OJ69 59.75 HQ 39 OS “0 I961 93 1.1. .42 n- 3.3851108 4.4 11 DQ5Q5454 I777777Z I12L3311 O6 06 0.077 (4222222 [2222222 1111111 ,0 666 06,0 (2)-)— U581... DQJJ 1V111 1 0.47.4 779 359 $90 336 J1 J5 025 158 934 Q. U046 7 381 [1+6 3737. 464 5.35 62J.D J)70 O I.3\J\U [.31 I. .037 23‘). f095 0634 333.3 3.5).«7 x7005 3 CU). 1. 07 0 323 1. U..3). 4.33.0 9.1 1523 J “:37 “’ .°.I‘ .539 UUUU 1U U0 UUU 111 3432 1777 1777 111 7000 £000 [.111 1341.3 06 O O A). 1.3 3157 U.3}_1 59 d .0 1237.0 «1.9—3.0 3 TUSE J Q 1.3 6.3.37 0057 Z765 T aUUU 7777 1111 0111 3000 1111 4333 0666 J333 UOUBJ UUSJ‘UU.) [517 U U00 3802 3.3,). 4: 39 331 9597 08.35 H19 O JOZJ 3 Odfiv UUO.U JUUxJ 1.5236 0310 7 .1 .3 U 34:). Ju7-1 18\U 07.3 J 07% 11111 ,35u3 1114! 1321 7777 7777 1111 1.1.21 UUUJU 11.11, 3333 6 0.4039 3120‘ 5U}: 2 J456169U123 ab 0 J3 1111 1111 111111 U8 8‘ ,J3 UU 1‘UU 3.3 11 ‘4 Q1 00 55 JZ 77 T7 71 do 11 33 0.0 156 APPENDIX C--Continued 7 .4. 1...). ollq' 1'1. .JIV 75 24 ill. 1| J . ‘1 39.4 .4).— 3J7 ..J3 90 J IéZJI 1.4 77 77 1.9.. 3.4 3.014 J “ J 4 1111 711.1 V630 07.1.3 J J). 4 11“ 3.9.37 034.3 3.0 46 ,oo UOJJJ U.UU V J 471: 1. O 0.4 031! U «Ix/51' 0 )3 0 31)., 336$ 0.1.3.! 112 1 72 oo 3..» 77 J.6.I J 77.317 7777 1111 464.3 . UOUJ T111 333J 0.0 D 0 3 375 355.3 111!!! 1111!. J53.U 517.3 13./.4 #111 647/. 061.4 052.3 r305 UOJJ Z 4 *0 27.35 hula/fie 12./.2). O Q a J 31.3 37 71- JUOU J.U.U .U 0.,“ “axle 1470 3 Q 01...)— 7571.. «.499 J34). Jz1+ T777 r777 T111. 5339 .0000 1111 . -I'I.’ J33?— , r\U1./~ 3.06 O 1".“ T117] .0300 17.35 J24... r11! ‘001. 1.0.3 5 32.35 17 U090 7 O70 13.64. 3.4.51 T6 b.J 41010.4 .U .U..U0 U370 £1. J]. r777 T117 Tidd 11' JUUU 1111p 34.30.] UQTUTZI...“ 6.» Q4 4Q“.3.D.D.D.D VI1I11ITI11|1|1I1I¢I1 1111717197111! 0 030 053U08.J0 017.3 6175 4.1.1.5 JJ24 J37.“ J32.» 711711111111... U994£dU9 1.151. U 0.07 061.733....0 71.5 Q J95.) J79 d ...,/.2 1| 11.3 UJAuO JOUJ00.UPJ VI 1| v 1| 3807119.); 19333 64.93] 3 03 32.50 1. 01.5 J7 43 o 009 O U93 039 .u J63! U 324.41). 22233 431uu9033a60 4.3.! 5 0 94! D.) O 9 .1. “at 7H... ‘4 el- 11' 53.0 U U0 U00 0030 U0 SiuJ407T47U ‘31. «I .9 a. “5 13¢.“ Q 7.] .3 3‘ I. .3 1| 7.37.330.Dd J 41: 0 T94£3J77 3.9.3 3 U9 9U 9 4.3039 07 0.1.5.7 0 0.4.4.. 697. 4 0301...... 24.44.... ..I 4| 0000 J7 U33)...» ..v 34.4“ Q44 J.» 4.9.4. 7...qu 4 (.21.. ..a 21. Q 777777771777 777777777777 10110111111111. 3.350 06.07 7773 JO V0 0000 0.0.00 71011111151111: 333333J3J333 600006600000 1-.. :J O 0.0 D $.33... O 00 O r 4.3 .0 O 0°..O .011. «I r1.-1. 6.1.03 17.38 4443 [I111 J¢.’8 I1 ’7 1.7 .0 T.‘ U000 0.602 1.55.0 V O). u» 77.4.2 quxU U fill-7.“... 7117 .Iqt1rq/ T111 J31) T111 U000 7.4-7 «I. 3333 9’0 0 O U0 ..vo 119.3 0 034.0 I 41511 7 .33 1. 3). 000“ .UOU.U b37. 1......4 T334 I777 T777 111' T222 Tllcldl V000 71:.qu J333 0 O O .J H23“. 777. Tina-.111... j111’. 5008. f561. 4&33 I111 ’59)- J1“? 0720. 13.12 J VOWU 01-1-3 13.3.6 J O 0.1 [.459 Q.J7Jql 3302 dd 9 31 J . U 0 0.4 I. 007. T U93 Jd O7 5332 31a9 54.2 7432 1777. .I 777 T111. 1.333 T111 UU~UU 1'11] 55.33. 0 0 06 00.09 .00 JO .7710 D 68.9 wsmm Y713 .12. T. “dam/e r3777 I777 T111! JQ44 1011!!! U U03 1.1.11- (.31.... U 0 0 .J {01.2 lduad .6117 J4507590 55885539 11111011.!l U527 . 111411 1006 [5.51 4431.. 1'11... 097.U 745}. 257 111.! v U00 [22.1 7477 3.370 .1. cl UZrOflU 701! 97.3 “11! 1|.1l1l J U.U‘.J 1111111 J008300§ 158175.510 4 4.1.32 433 11"1111 z) 5 0.3.9 .v U7 vqu.O§J.nv.i.1‘J1-. 43601730 w «Isl 1| J.U.UO\U.U\V\U 4720.37.92 1227u590 Q 55 2.9 u» .07 +51: 61.1.9.3 u‘11111 JOUOUUQZ J ,0 D 9 .5 .U 1 U.UU UJxUU.U .40 J7 60.0.0 0 5.). .5 4 .3 2 33225297 40.683 02 o 57.13 0703 5.0.6752 U7 41.111111 ..Iu332113 11111111 T4331432 f7777777 F7777777 I1111111' 36566777 11111111 JOOOOOOO 71.111711 43333333 0 0,0.0 O 06.0 01.2 U00 222 111 [960 5 .0 3.3 4333 310 870 Ju1d 7223 01.61.. 7.359 (.5 In .427 63.... 3,0 I...» J17J 33.49 1.221 rI:-.1unu 0%.... 0 «1,090 1340 39.04 T. I126). 1. 03., .3212. an7~2 T23Q367b 3.599 393.3 [‘11 71011 17111 «I11! I0085083 T.3.0‘l 16107 2433(3323430 T111 .01-Iliu- 64556174 02.03 * 3., U I. 0.5“ [.457 (333.41 1 J..U~U.U Jooo 62.04 396.0 b396 0510 a 433 JJ81 U). 1. 1.235 TI J000J877 633 759 1.). 00 U0 30.00 JOJO J7..va v‘ 1" xi 5 4b 1. 351:7 1007 3083 33 04 J72? 3811 ¢b4u.463 T 37653788 T. T “3.41.321 I777 1777 {7771777 T11111- 1.1.140 rdaaiuggg 1171 1.111 UOOOUJOU 771.] 1.1.1.1! J3JJJ3J3 0 06.0 0.0 D O 36501390123¢507810125w JOOOUOOII111I111122242 1.12.4 4.22.2. [1.2244424242 c1. 7111:1111r111l ..Iclqlil 1|4|4J cl 1960T190T19oul190019J1 3665396535663596059035 43064400443u0435u44ub 3.4.3 1.4.3.3 £33.... 5).. J J 3.1.3.... J). ZdaufJJOJJOJUO473deD4 .I 3 5.59 5.03.7th U SJJZ I Z oOOOuOJGUdOUuOuOuOOvTQ 5 I 5326TJUJJZJ7JUJOUJ3233 17630 2 316U 2776 76£9u 5554 J103 £11b: 5735 dZJw 1.4965 1 TI 372060009000u000307d04 497 o J 1: J3 0 1.. O T. 390 a 5 052 Z oJOOVUOOJJOUVO7OJUI9U¢ Wu #0 .57 .3 7 3 1 J 36300470300400uouJ04W5 360 4550 26J 43 b 913 59.! 9 0.0x. ,07 5). 1 905» 11 719 9406.470523700933595Fb 1473f475431434:73359£7 1.2 49.3551 B5553 9). 020.4 J“ 3146396535733 21 Sui“ 001' O 3 12 T1 211 u467 5419 .641 72 333031 JO U5 ‘2 3% .27.3.J.J .43.... J 4 HE...) J J .02332 ..I. 034104310432109341W3TU {7777777f777i777a77777 T7771777l777l777i777r7 1.1111111 1110111111111. 1.1 d1111333f444Tu55355666 UOOOUOJOUOOOUOUOUUJOUU 1.222 4222 1.2 ‘2}. 1.222222 ,9 ‘ 4333J33353333J3JJJJ3 J 0606060066660306669000 157 APPENDIX C--Continued .3 o7 0.1 0 434.3070 24.4.4.4.) .J33.333.3 , 4.4.4-4 4.42.4474 4.4 1111111 7111 3111 . 0011.3 031 .7 031 0.3.39 0 0.39 0.039 . .J 0 04 33.04 4.3 04 534333333333 30074960J01~ 7/7 12 1). -JuUUJUJOuJOU 35347309140370 04594“ 311“ .442:1 u 49 319 ..4 1.3 1 1 47.00 0000 .0000 7.3 0 125 4 0 0 .II quOuOUdUUOO JJUUJUJ0095323 .7 343.3 QedJo 074.4 3 1 0.37.3 0.0 33 0 007 .I 317 3.4 3 0.317 33.03 I.“ 9 320 0 )7 o r...» 074.63 711' 1 cl: :d39u05zJ64u 3.4). 434544 4111 41.0 H 31.1 “.3410 {77777777777 fi?77{7777777 #111] 1111‘. ['11 77730009 7990 1 U 000 00.00 .0000 4.422 1.22.). 42.4). aisJIJBJJJJJ , 0 0.000.000.0000 .0000 00 0.0 000.0 137d J 0...» I 433‘ 4.42 {Aid 5?; [[21 QS4J 7.111 f441$ 7777 I777 TIC-I11 0001 111-1' 7000 1222 $333 0666 00.00 10.437). A4 3Q91 12»4 3309 1445 3300 1440 7TWfi71Ld7 G 40 34 30 J T003 [.0 00 W000. .0000. 0.400 .51 74.52) 64'.sz 71 .23 -4 3432 7777. 7777. r111 3355. 1.11.1 0030 42.4.4 33.3.3 0 0.0.0 Izrf’ 1465 1449 Juév J¢93 2021fl12§0 3306 I’ J J J J..0J..J 07.1.0 .46 4000 0.000 JJO9. J73). 320 A 1 £224 134.0 7777. .777. 111 00.0. T111. .0000 .444. 249 000 m g fu./4.a.....9p3 07.0 3.3.3.3.3.3.3_3 14 42 47.). 47. 71111111 19196 090 3.096 0.365. 3 0.043040. JJJJ33J~J 000.00 013. 00137653 0 00.000. 47 J 0000 0.42 {9.0 03071 7‘4937770 47727111 [. 422.4215 -7777777 r17777777 1.1.1.1111“ .1. 00030000 442).).‘444 33333333 05 O 06.0.0.0 43 4 777 .4‘42 :11“. .0000 400.» 0437 i329 . .7910 v0123450T890 3.006006 0 0007 4.4.4 4 44.124444}. 11117111T111 .00 0000000000 u046T0466u46 $1.720 “7.4 0472 3 4.75 13933390 310379051906 11 1 1 051210000000 1.1.00 .4 41.313 072 47.0.0 4.0000000 4.33.4.3 2.57. T “9: 722 3 O 1 03.04 047370.497 .93 01.11.011.133 1.3171491 070 O F02d30013171 ..3 0.4 .011). 4 11 795.47.37.40 00.02 3.0.3.017.3.40_1.7..37 077 4 4313 1297 10.3910700 398.0 0302 0.330321“ 7.111 436973050069 YOO .993.“ 310 1!.U 3371.. 33 3O .46 0912 3 Y. Z133J3740078 79.04 “0003.439 0941 “01 3 4040 .004 .0 O 13 31.1. 0 333.4 0 351 057184443 767371314329 «58043141513 1.078 01.33 3.24.00 .3507. .4357 0.3.9 0 12224 0000033014 027 10.400 00 0 0). 474.4 0 0.0 0.0 0112 4111 T1117 93.41 04.1.1 0.4.41. [77717777777 [77717777777 1111111111111 300.001.11.122). 1422274223.. 4.4.4.4 111111111111 711171111111 777717777777 11. 0.00.0 uUOJ 6.41). 2000 1 O 9 O 0037 3.799 T 0432 7777 7777 11.111 2333 2.4.4.). 111-1.- 7111!. 7777 3673T0123430 4.7777 5335.505 424.144.4749. 4424 11111111T111 0000 0.0000000 0400..» 05004 O“ 18u372643726 6934,63349d9 5791 03791007 11 11 TJOUUUQJJJJJ JddOuOUOuOUO .0 2 182006800300 27.78“ 3.0 J 1 .1 0.000 UQOOUOOO 9 7 6 005434703340 07 26 7691 3 16 363 2 110635405500 3631412931 24065553 20+]...I3 31¢ 11! 1| 397607763820 OdJ63594 791 4|»? 301560.05 “0 9.303 33 7. 11 11 49.5.3 320.0 0“ “0 417459011124 11 1 1.3634101» 3410 77777777T777 777717777777 111.111.11.1111 334 43 Q 0.3.3335 44222222422). 11117111111al 7111—1111-1111 777777777777 5309 424.)- 000.0 4372 jlva 5100 1‘! 003.0 I 7 0 000 0 .000 r39 3 0 0.9.34 7.0 0.0 1.1 4360 £224 .321 777 7777 1111 0060 .4222 11411 7777 .7999 4.42). [830T4303b73 3.397 4.4).). 0.000 0.000 0 000 30.0.9 040 + 0437 [637 73.4..) 63.49 7910 3710 11 «I1 #00 0 0 J 00.0 .0000 [300 4.0 71 1.0 00.03 203 401.0 0 7950 .33 “14.). 06332062 1197 TO 1111 1.800 37 2931! 1410 1 VOUOJUUU 80009704 H1 30 3 I .4“ C. ). 0.09702.0 0 [.403 011 0 093.331Q94032 T3Q4£122 11 1 7507,0 O 004 33.3 9.0311 003.41.03.14 77777777 7777777 11110111 07777799 24224222 11111111 1.1.1.1 111. 7777 777 005% 1|“442 7777 7777 11.11 300.0 ‘11 4422 111.11 1111141 7777 00 0300.00 1.00.4 00 0.0 4037.343 03435334 04.1.0 0791 11 1 VOUUTOOJ JOUJTJUU IOJJJJQU 30000300 5 i 4 053d4997 30032b3 424425 719.0 061.3 U675‘922 711011 41‘42 1|. 7.! 44 4.4 0). 1.3.9.0 [1.1). 4.30.3 4.493 1 ~14“ 71.043 [777 r777 T111 01011 -111 4.34.142 111 10811 7777 701L3450?d90 70.01.. 000.0 433333335333 flan-11.1111. 71:11 .1111 .11-110 T111 00.01 00 .00 36Q0 1284 3593 4679 0000 \0 0 ,0 JOOO 000.0 000.0 14742). 7.1 «11.. 1111 I777 158 APPENDIX C--Continued 3Q 1|1| 3.9 Q|1I 00 47 5.07.0 1.111 J3.J.J. .I-IOIICIIQ' 0000 O Q.UO 4d IH‘J U’.J/~ 57.041! .41 J0 0)— is 057010 L A 40 [017 2530 ~2744 052.» ~«3J9 37.59 «411“ I 0|” :5 1.11 .. 30.00 We, 1% 0100 7 ./. J0123$50. 12222222. 5333 .4333 1111111011 00000000 3.0 ..4 U.U 4.0 “A [2303720 5093.190): 00791 007 I... 11! J00 00 00.0 01.00 0‘0 00 0 1:90 06 “71 [87 .Q 099.)— nd.°137 1.3;0. 111.3772 6. 353.6911? 5.0 43.41400 0301 bDSIQul T:J03.Juw *5. 1.121. 4.1111. 00 00 0000 3 Q 00000.0 3““ (J11- 1‘ . T 59.0.3336 -. 01:14.33 .030 77 .4 “Sq/rU 1* J b 4.31 1.75 fil¢|21lldn¢11l . 5.30.3024 U7 V1904.“ “.3 .h " 1.110 63.41 0 f7777777 T1122 In)“ 6 1111‘.‘ 11.1 1.2222 £2.2— 17777777 I777 I777 189.0. .43 “+4 073 701-.)— 2223.33353535844 5333 JJJ3 J33 J J 433 r1114|1|1l1l #1111111- uOuJuJuOJJOOUOOO uJub¢000+6403640 437263$37£d4l256 «4.49.5 4.). J 4 7.04...) 7.693 3108?1510379v379 J000fi10030300000 1 .4: JOOO U000 J 000 0 U .0“ a 2 4 7 4:01.11 31 *3 {1001 $40500 IQQSI9O7O71 955 JO1OUSJZU12 05d 197). 371.3(3). 01 J 1‘ 1 1| 1610u00300095264 [20 0 7 7.41.0 J55“ 24323 1590 23179 2 a! 1'1 ddCduQDUJSUOuOuu 4 56 3 36 J03); I737 J71: J 09.07 17 0501 40 2 O 0 765044 J5 549 2 4 11 53640$20331Jo723 d7 90 051.: 0.39.3 1 4 .01. (t: “.3 3936.0 U 5.441. 3.30 s¢73i015£502v431 101110 71 90 1,44! 0.).“ 0 I913 J99... 3775 J33H~1111244~b7¢ 4321054311044104 I777 I777 I777 I777 5313556550511112 1.111! 1.111 111122222 (2224222‘2222222 7511-11111 Tuql1l1l T1014... T‘clcl. T111! 111 I777 777 J U..UU 13.42 [.242 {41.02 5037 41.55 0 .91 3 0399 J 37.1.3 7 000 0 (4:97., 0771. 1.0 913 4 1 6.433 5.195 U 42 J {-111}. 5370 J 4.3.3 5210 r777 r. .4). A 1.9.3.). [22‘ 111]- 11} I777 F09 0 wig“ 3.070 4 4 “SAD—35.3 355.5 4333J333J3J3 .1111. J111Ir1|1l1 0.000 0.0st T000 uuo¢04QOu4bw 72.0 “‘08.“ 372.0 1.30 3 599}. 1.9.03 1087i779TUB7 rlcl. T1 000.0fw00‘0 00.00 T.0.3J000.,U 000.0 1’ 2 1 0201. .0303 .3990 055 a: 1| 33.07 757‘OI0 «I D 1:3 12.01. «I 1 1.650 .0003 000.0 I. 30' 1 0.09 5 03.8 7 a‘ 000 0 0000 0.691. 010.0 1,790.3 0.003 J1.‘\U 33 62 n» O7J3b 097 4.). fol. A 1 4|. 4337u i5... 0 I 42 o 9J0! J 043573.3VI)..9J T. .405 02 7 I Q07 Yail—«I1. 4| ..0 33““ 1'31! 975143730957 1.1.31 4). 11.- 11 321040043210 17771777I777 533314560600 [.222 £27.2f.).).2 1222‘2227222 14.115117111011211 111.. 111T1101| 777 777T777 .3012 .3 c.06 1333 T111 0 000 0 0.46 4.07.4 Jlid ’10 Va ..qu 00.00 0 0‘00 J017 0.000 0000 411010 0.0 00 31.1.3 060 D 1 037).. .7 4: ’2 4|.- 4321.. T777 T111 3333 4. ‘2}. 1111 11.11 r 26 0006 J333 [11:] 0000 40.4 0 Uanlz $34.3 I908 0.0.00 0.00 0 5006 I. 4 $00 ”a q 07 U 000 T00 0 01034 O 3 000 3.01.1! .09 111.35 3.)..3.) U421! I777 r1111 jquJ T111 T111 T777 1222 189.0 0.0.07 J3J3 1.111. 0000 {OUR du37 2319 ’91.“ «I1 00~00 JJJO 1522 JOOO 0007 .3 2 I704 f799 .641 » 08‘94 11901! 10443.) 091nl 09 J.» 1339 032 4 00.32 7777 1.222 .0 .9an 7222 11.1.1! 1111!. I777 23.”: 777. £333. I111A T00 0. 540% [~047A 6939 3799 J000 0.00 00.00 U000 [352 (400 ll “.4v1 {17.0‘ I9U7~ W013”. .4! 101-3 T312 .2150 5.0 «I 4.033 3.4 T: 771 1233 339..» [242 T1110 [111b- r1777 0000 400“ 0“37. 1329 191: U 11 0000 .00 VJ 0000 U000 J093 7b 3 U“ 05 [“311 [5.33 333 045.0 r5..06 33 3. {70.04 111.. i432 I777 5422 T 5.5:) 1. 4‘42 T111 1‘1! 777 [1.11AT1III1IAI111A UOOOUQUU ¢OQOGJQ6 6473J372 31923298 1901.11.02! 1|... 1...! uOUJVJOJ JOJOJQOO. uOJOTbQJ 78 63 1 uOUOJUOQ JOUUuZUO J 7 z £642T646 J602f093 £511i941 1C .3‘11 b642iudo 0.0027573 45113659 1 SIZZ ~9u44225 1'1! UQ234321 I777/777 J4455666 Juu0fi4¢a [2221221 11.11.1111 111lrlc|4|11 777I777 3678fi012?456?8901236 r777. 888888 688399999 333333.43333333333333 {1111111 JOOOOOJO DQOUQSQO (6417230 6932.?693 67910373 1.1 00000000 1 7 0 0.0xv00 00 00947537 28 ~229 59.0378 1 00000000 1 ..b 2 40.0000 0 0 71! 0.3 2 0.000-0900 :4“ O7 ...0 045 4.03 ?|236671 F05 0939 .91: )5 «I1! 13 r b “.JIOU‘EKL 42./.2 ‘43). 0432104 7777777 £2111111| 3 366 06.31! (222222). 11111011.. 11111111 {7777777 3 04""J 70 9.19910 J.J.J.JJQ [1.11.7.1 0001000 04 0..» 00 572.0 .44 [9.094). 1| 0.07121. T1 «I. U0 U0 00 00 05 J0 .447. 37 3 7.47).- )3. ‘.0“0 9 00.35 “a 41.an {Van‘wv 09 ’37 1' «.1xU 9 7’71 10 0000 00 0.037 00 .30 4.4 2 0 0.0 NJJ 71.43 1 3740 ”9 1803 is 1 7.01.0.3 3° |.L..‘1I 101. 1.7.10.4.) (7771...! T7777? 1.22412 1111111: T111v‘1 T777T7 159 APPENDIX C—-Continued 160 APPENDIX C--Continued 161 APPENDIX C--Continued 7 5 77 .3.) «11.. 72 43 .J 1’ 21! .Nast. .U../. .3 J Wail ...W 3 7 «I ..o o ‘1" 1'1 33 SD 77 T J17.- .I .ded .3 3.3—3 1'11] 1272 910.01.! ~414wa 3.134. 61- ‘1' .3400 U000 «343 I-I77 T111 :33” v-111 1 1.11 33315 5.5.5.3 71777. {s u 5.56 .0 55.3.3 1:41.11 {720 0615 +631 5395 £11 JJJJ J00 u 31.0.1.1! 33 O1. (49 b9 035 .43 w 5 05.00 31.0 0 4|! * 43.3 r4777. I117 1 J11Xv 1).). T1115 333.... 5554 {77.5 r 1°93U 55.33 3.355 11.1.1 UUUO 3005 I3J7 #44 u» JUUQ 0.0 Uau (.330 [046 6179.3 08.09 .4573 T11! {31.5 I 085 83.3.9 0.029 57.4 72.1.1 TUNU .3 O 0 J1! U253 0 031.7 .714 49 557 0.419 9.1.51. 3 03.) £7 49 1627 3W5¢l ..VOWUQ U.U UIO .00 03 T11 $324 1777 F77 T11n foacl [1.22 111. Q“ Q Q 388d 1.4.3 uh 5 O7 8 413.399.3449 35515.3555. 111111111 JQQOOJO.U JS.D\U U550. (417301714 j.) .‘ .W “.3 .* u 0.00 U|v\U U\U .UxUOJUJU UPJ U717234fi411l 5001sz U7 0.435.073 No 1.365 097.1 3.1-3 .45 1.1. 30643.J9_3 ‘1 U1- 1—5.‘ 1.. (3.04u297 3110 ..UuQ-IAUS 15“»32231 1 VEOOJQ U0 0 Q J.U7.d~l U.U.J £470... a. $579 gas/Q1. 1 is 694.01.) I 07 “28.3.3 71.03.0971! 45.50:) 047 .188 5913.3 4 T Jul-43533.0 37.93 de.U U J111111' 3.5 33.2.5.» 3 f777777z {7777777 11111111! Tia/«223.333 V.‘qlaxjg/Rlaalfllu 2 [111111110 “Bud“4*“ 301213440. 1000J000 36 O O ..O 0.0 [11.1. 111.! UJQUJUOO J50.U .30 US. J7JJI3J1 3 4“ w J 44.3 J\U\UJJJJ\U J..UOJ VUJ.U IdeT-J.3.U .3725 375.0 1. 5.08;..37)‘ rS—Drb T11..‘ 0401. 703“ 40.13 100% {1:32 3097 7H3 3519.6 .3 #10 0.35.3 U U U7 .UxUUU a). 9 .0de LU.37 14065290 U 9 1- + 'I “0.44 «O1 J ...UO 4 35 1| J 43% .4243 .0 O 9 O Q 0.31 1591 010.341 1269 4“}57 J9 07 7.56.0 1'11 11004501 U I» O O .I 55.0 fi333T111 4.432 Vigil-.5 71107.! I777 T777111; T111. F4414 7.1.11 [222422; 111-«1.1.11.1 3 44 HQQQQ 6638.53.03 535.3 dddd r590 U001 O..D0.0 [.111 .0000 305.3 r3107 j4.34 J..UU\U VJ UxU..U F..J~IS («19.3 4198 6.... 02.. T7. r608 6359 U 4 9 2. I .037 35 UUOU 5000 J133 9.353 .4591 34004! r1711 T591 b.3)~3 71 435.4 f??? ‘23..) T111 7222 T11] fl .9 Q Q .638 1.23.4 .1111 0.00.0 T111 T000 0.3.3 017 $4.34 00 U0 000.0 .4409 [3.311 n) 0 Sub 0570 1112 l¢u39 U) “RYU 32371 v.52...» TUBZ 00.00 U .331 027.4 2242 [5.52 7.6.3.3 U0:.5 1.12.!- 1.1. 5.1.5“ I777 (4.31.1 T12£ 1.222 filial...- B Q 9 4 .3638 56787012. 1411.! 7222 coéoobbo 11.11- .1111... 00000000 I055 0050 F101? 2073 fi45¢juo4 JOOuJUJO UdOdvUJU 5571 r451..., U251I469 fo75573d 1.901 17040 [311 T1 1 75755823 1.1.23 0 0 110.314 41' UbBZUdS ‘11.. I. 908 J uUd u 0 Q aoOQJ’Jd 03 B 9 I ..u .d 310 1 A32J02J9 J7331423 0691050 093469u 4022 4 L 1 :370u775 014:4 U511. .11 32545243 r777i777 T1ZZZZQ4 12221422 1.2.42 4.422 111... T111 BQQBFQQQ ddBS 335 f+56F59Ur2343o7dvu1lf450. [222122353333333J44uv444 oobbbéoboOGOObobbbbébébo .1111! 1:111 [‘11 .6111! 1.11.11 ‘qlclcl. JOOUUOJOUOOJUOOuGOOOuddd. U350uSSQUOOOJOOUUUOOuCOO. J173J1730J95009DU950U950. {344fi544u260.2004004200¢. 1'11 Iii-I‘lilclldlu‘ 111.1! UOQJJUJJJJUOJUOUJUOUvJ1» 4 9 3 2 UUOJJOOUU739uOUJUOOBT39O 207 7‘07 915 nl 11.3 43 Z 33 1353163735431259J3565337 17345564‘373112133200525 3.038 5036 5.69 O 652.... 1337 1.437 615 63 95 5501 1.057 doflu “1,1079 1 535.u310453b76 2.42.1111. U66717365339IQ3101JQT568 806ub444140768706415470 “do r$71.0 6526b039 5904 47.41 307.368041229542836504 1... 111 T704 3653 0863 i5“ 44342z21 JUOUJOOOu021F1OURJJOO971 9udT2 24 U711 3.52.1. 4| J 11.68 2 .4 1! uJUQuUJOd956£992uJ35i650 1. U91. 9511.. Q). HaUS 04013839 3%!193 0.11.3098 1|] 12d )5.‘.‘ 1 1 £150 55 05 A4751. 07.03443 4656 . T o +1 a). U? 57). 03723 024 a v 1.93 J11958b24355m499336756£9 042162ur87d 69135660169 Z31 £121T802 [1.9 o 0313 .0311. 77.0 #:4331111: .14ch 380dd5363000964511880102 jSO Dianna... u UU 3629 3183 563 .U.UU§SSU .1221. 1:11! 1:11! 4543£543£43254323525f325 T777I777I777i777l777 777 3111T2224777I777f777l777 «11111111711111.1111: r333 1.41.31. 00011112223533“ 12224222533JJ333J3315333 111111111111111111111111 FundaQU4uu4u4Quuflu4QauQu 58ddddd$5365635538866563 U.U..UO U000 U095. WZJQ 1|“. JOQO U000 gao3‘ 72,)- O. 631...» 5013 71.1.10 02.01. 41179. 5277 0&1? 7987. U9 UN. 7. 1.. [992 4512 633 098 1 .07 U5 {42.4.3 332).. .2520 11! 0.0 T111. 5004 {7 Dab ‘22). 343; 1777. T111 T111! JJJKJ. 1:11.011 4 “Q .9 5.5.5.5 1690.1.434u “.44—3.3.3.3.) 06:0 0 U,O o O [1114(111A 0000 0000 0095 +200 {1110. TJOQ JJOO. 5594 5810 IQ 0.677 51.1.11 121.! 92.65 657 445. $884 587b UUOQ UJO.U 9779 a “7.1 331.3 LOU). .3008 ‘51 $.30 .o 3.07 b. 5 +32. 1777. Fax—«‘2 11.11 .1333 T4111! 3 Q 4 Q dd 5.5 3.07 d 35.35. 0 0,0,0 5.111.. 6000 0000 v095 +20J [11“ Judd J.U.U.U 5.4 01.. avaqlz 751.3 C 5712. 1.2). 3230. .075 .4457 ‘97! 22. IUUU VUUJ Ib91l [1‘57 «UJ3 3030 5055 J02...- J “.35 343). 1777. 5333 11.141 5333 T1110! U “ .u nu 5.55.5 .1J1.)..J4 3,06 90,0 0 O 0 COO ‘11111 JJQOU.U UOOOJO 009500 T4003; ‘11111 J00uuo .400 .J.U0 103.639 576 0.01 T895 +14 £50.37 0 «I 412 r783a01| mddqlpdg. .5331). .J.526U [2 .432 1. quUJQ JJJJJJ I712$0 37.34.07 3 O3“ 03 02.9an 533%..» nu Thizxa.) 9J3}. 43 363254 177777 .4“ .H “.324 r11111 JJ333J T1111' 3 4 .9 4 w .4 5.5.5de 162 APPENDIX C--Continued .30 O 5 O 0 191 JJ 00 2) 10 ‘1‘ cl.’ 7S 3...; 434 J). 1go1é 1307‘. «11 d—.J ...7 \j "J 9 ”a .J.J 7.11 U 4 ‘55 -w Jo ,U .9' a 33.09 3.39 4 “9714 0472 71.43 .4 070 321-1. 1111 v00 u U J00 T234 7777 06 b o fith-Iqll JO 00 VU‘UfiJ‘U U095 42d 0 7.111 uOQU JJQO T705 [.31-.40 lead). .4.D.H.J 0.0.449 r,.wr./..O 7251. 1.7 ’23 0.000 .00:qu I334 1738 3303 3}...» O 11 3‘53 J .41 3614.4 1777 [777 10111 J33.) T7101 .‘J94¢ 3388 4676 777 6.0.0 0 1111! JQQJ U000 J9S.J Z V J“ 1111 J U00 TV\U\UU [639 0380 £084 734 UJO‘U U U.U\U U 003 T4JT 6099 4303 5.41!“ .4 5.4.5 r1777 38 «YU 1 1111 1333 1111 4 4..“ U 5853 4a) 1012 T563 0606 7:110... fooo U000 (U 35.0 1. JO 4 1‘11 0000 U.U.U_U ..w 4.37 5 07.0 7.0.4 9376 U0“ 0 39 3 UJUU .UO 00 $37..) 7777 JOJ1 1111 1.111]- 3335 Talc-I1. 1» “4 b 71.6.5.3 4J.U\J 1. J1. .9 30.0.3 33:77 77.3 7 42;1 Yd Brad 7U1 9‘1J 7514 4Q“ 1000 . JUqu‘J 1.074 I71 0 5‘5 .— O 7534 4770 ‘U3J7 3.0.3.0 1| 1.34 J 1.777 T1171 1| 17.2... ‘13}.an 74071 6 u Q Q 3336 [330 ddda’ 0 O 0.0 v-111 U.UU U UOUJ J09...) 4 4J.U 1‘17 VUUUJ JOKU J 6237 a 223 .J.Q1I Q) 7174 £.I~1l 1| 56:0 3 [23) [24.03. ‘117. 3 O Y) .4...) 0“ 0.5.34 ‘d J.\‘d./~ 1222 £222 33.33 7.1.1.11 + #94 fiudfid aZJu 9.19 066: 711.1. 0000 JJOO 3350 $Jd¢ 1.19.1. JJJO 1v U\U\U 0.31. U; rl7n(d.lb .43:pr 0764 JQHUQ 3. 1 JJ0 4 u 3 JJJ u 0.31J r73J.’ 3 J5 7 U7 0 3 «a33 T2£1 33355 vi 777 5334 7.2).). 3333 Tel-1'1 H ..w Q J 73.5875 3307.4.) 3999 0.0 00 V1111 JOJJ 00 U J J9.DJ ZUJ}. 1111 JQOU J70 U 912..) JUO O 7.72:) 3.3.0 .75—00 Jst ’3“ i “7 J0.,U .J U UMJ‘U 0655 7320 EU75 #83 fi 1 .330“ 731‘ 43.4.4 7777 Q .435 ‘22.).- 3.3133 111.1 .4 Q ”Q * T1553 ’01.}. 3000 0777 -111 UOJQ 0000 3009 U420 1‘17 0000 UJUAJ J97“ 5.023 J51!) 7.13 c 3 J3 3.1.7.3 H “.3 $13.93 7777 51101 43.3 J 333‘4 1.114.- 9 H Qua 5565 5.9..) O 0000 I777 I111 J.UOIU U000 DU,U9 04}. J 101.11. V00 V 41034... I as .3 .0 11,61. .7643 57.39 3p3.0,0 I111 32 3.: 3.07.3 U.S..» .4 111.: 15./.10 UOUJ «763 7.1.7. 91.7 .3 3669 +501 3752 Jafiyzu 34.43 3.372 J .9 45 123“?) II~I77 7.422 JIJJqJ 3333 1.111 44“ Q 7636 rabgo UUJI. {0777. T11] V000 UQU\V 50 U9 YUHWLJ 1.7110 1.000 UUJU 042.3 T73u lei/.1! I24). I 1'). 0.3200 0.5 OS 31.3 .U 0072 T111 (U 00 V- 5 OOJU 1 59 U.) Ava/~51: 0414 (J13.J -155 7.4).. ¢ ...3 $34 {777 1.333 533.1. JJ33 11.5.01 3 “Q Q Q 053.5 F434 T111 7777 fi1n1-1I U000 $000 Dd‘rlvg JJdJ 1111' UJUJ J60) 7.3.47. I1.b~/ 3192 3001.. T122 5.039 43 4 “ 1.3)..) w,0u..J I.‘3 UUO‘U \U 1. Tons 93D 443 5 7.3.3 9 [702 r! “7 ‘0 43.4.3.3 3&5.)- J38.» 321 {343 f777 5‘44 3333 3333 Till-)- “ 94.9 5.635 378. 11‘! I777. I11l1l VQJ V 000.0 30.09. V 420 7111-4 vxu UJ U\U\.J\U J(Jriqli .017 b. J227 0 .1. dado VOUQ 730) 1 3 41:7 [17) [221! I ll. TItOOb 1 7a.3‘.<~J I777 i 55.3 5333 14333 .0111. 3 4 4 ..u 70 .0353 101).. 1222 I777 711... JOOQ Judd 3095 Jzod [14.1. JUU‘U 3000 Q902 144,7 {900 6 Uxuos 3.. U0 ’0 J.Jd U 81' 1‘ 04177 [2.54 1|~°x73 b 3375 Z 43). 1777 3.0.0 0 .4333 (4.1.3.... 1.111! Q Q .4 4 538:3 BIBLIOGRAPHY 10. ll. BIBLIOGRAPHY Books, Journals and Periodicals "Antitrust Implications of Network Television Quantity Advertising Discounts," (Student Note), Columbia Law Review 65 (November 1965): 1213-1255. Backman, Jules. Advertising and Competition. New York: New York University Press, 1967. Bain, Joe S. Barriers to New Competition. Cambridge, Mass.: Harvard University Press, 1956. Blair, John M. Economic Concentration, Structure, Behavior and Public Policy. New York: Harcourt Brace Jovanovich, Inc., 1972. Blake, H. M. and Blum, Jack A. "Network Television Rate Practices; A Case Study in the Failure of Social Control of Price Discrimi- nation." The Yale Law Journal 74 (July 1965). Blank, David M. "Television Advertising: The Great Discount Illusion or Tonypahdy Revisited." Journal of Business 41 (January 1968): 10-38. ' Blank, David M. "Tonypandy Once Again.’ Journal of Business 42 (January 1969): 104-112. Borden, Neil B. The Economic Effects of Advertising. Chicago: Irwin, 1942. Boyer, Kenneth D. "Informative and Goodwill Advertising." The Review of Economics and Statistics 56 (November 1974): 541-548. Brush, Brian C. "The Influence of Market Structure on Industry Advertising Intensity." Journal of Industrial Economics 25 (September 1976): 55—67. Cable, John. "Market Structure, Advertising Policy, and Intermar- ket Differences in Advertising Intensity." In Market Structure and Corporate Behavior, pp. 105-124. Edited by Keith Cowling. London: Gray-Mills Ltd., 1972. 163 :3 up-w-L- 12. l3. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 164 Churchill, Gilbert A., Jr. Marketing_Research: Methodological Foundations. Hinsdale, Illinois: The Dryden Press, 1979. Clark, Darral G. Cumulative Advertising Effects: Sources and Implications. Massachusetts: Marketing Science Institute, 1977. Cohen, Robert J. "Advertising volume expected to top $36.5 billion in 1977." Advertisipg Age, December 27, 1976, pp. 3 and 46. Comanor, William S. and Wilson, Thomas S. "Advertising, Market Structure, and Performance." Review of Economics and Statistics 49 (November 1967): 423-440. Demsetz, Harold. The Market Concentration Doctrine. Washington, D.C.: American Enterprise Institute, 1973. Doyle, Peter. "Advertising Expenditure and Consumer Demand." Oxford Economic Papers 20 (November 1968): 394-416. Edwards, Franklin R. "Advertising and Competition in Banking." Antitrust Bulletin 18 (Spring 1973): 23-32. Ekelund, Robert B., Jr. and Maurice, Charles. "An Empirical Investigation of Advertising and Concentration: Comment." Journal of Industrial Economics 18 (November 1969): 76-80. Ekelund, Robert_B., Jr. and Gramm, William P. "Advertising and Concentration: Some New Evidence." Antitrust Bulletin 5 (Summer 1970): 243-249. Expenditures of National Advertisers in Newspapers. New York: Bureau of Advertising of the American Newspaper Publishers Association, 1967 and 1968. Ferguson, James J. "Anticompetitive Effects of the FTC's Attack on Product Extension Mergers." St. John's Law Review 44 (Spring 1970): 392-415. Ferguson, James M. Advertising and Competition; Theory, Measure- ment, Fact. Cambridge, Mass.: Ballinger Publishing Co., 1974. Friedland, Thomas S. "Possible Resolution of the Advertising- Concentration Debate." Quarterly Review of Economics and Business 14 (Spring 1974): 123-126. "FTC judge: Doctors should be free to advertise." Advertising Age, December 4, 1978, p. 4. Greer, Douglas F. "Advertising and Market Concentration." South- ern Economic Journal 38 (July 1971): 19-32. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 41. 42. 165 Guth, Louis. "Advertising and Market Structure Revisited." Journal of Industrial Economics 19 (April 1971): 179—198. Kaldor, Nicholas. "The Economic Aspects of Advertising." Review of Economic Studies 18 (1949-1950): 1-27. Kelejian, Harry H. and Oates, Wallace E. Introduction to Econo— metrics: Principles and Applications. New York: Harper and Row, 1976. Kerlinger, Fred N. and Pedhazur, Elazer J. Multiple Regression in Behavioral Research. New York: Holt, Rinehart and Winston, Inc., 1973. Kmenta, Jan. Elements of Econometrics. New York: The MacMillan Co., 1971. Lambin, Jean-Jacques. Advertising, Competition, and Market Con- duct in Oligopoly over Time: An Econometric Investigation in Western European Countries. Amsterdam: North-Holland, 1976. Lancaster, Kelvin. Introduction to Modern Microeconomics. Chicago: Rand McNally, 1974. LNA Class/Brand Year-to-Date Expenditures. New York: Leading National Advertisers, Inc., 1970-1975. Maddala, G. S. Econometrics. New York: McGraw-Hill Book Co., 1977. Mann, H. M.; Henning, J. A.; and Meehan, J. W., Jr. "Advertising and Concentration: An Empirical Investigation." Journal of Industrial Economics 16 (November 1967): 34-45. Mann, H. M.; Henning, J. A.; and Meehan, J. W., Jr. "Advertising and Market Concentration: Comment." Southern Economic Journal 39 (January 1973): 448-451. Marcus, Matityahu. "Advertising and Changes in Concentration." Southern Economic Journal 36 (October 1969): 117-121. McGee, John S. In Defense of Industrial Concentration. New York: Praeger, 1971. Mueller, Willard F. and Hamm, Larry G. "Trends in Industrial Market Concentration, 1947 to 1970." Review of Economics and Statistics 56 (November 1974): 511—520. Nelson, Phillip. "Information and Consumer Behavior." Journal of Political Economy 78 (March/April 1970): 311-329. Nelson, Phillip. "The Economic Consequences of Advertising." Journal of Business 48 (April 1975): 213-241. 43. 44. 45. 46. 47. 48. 49. 50. 51. 52. 53. 54. 55. 56. 57. 58. 59. 166 Ornstein, Stanley 1.; Weston, J. Fred; Intriligator, Michael; and Shrieves, Ronald. "Determinants of Market Structure." Southern Economic Journal 39 (April 1973): 612-625. Ornstein, Stanley I. Industrial Concentration and Advertising Intensity. Washington: American Enterprise Institute, 1977. Peterman, John L. "The Clorox Case and Television Rate Structure." Journal of Law and Economics 11 (October 1968): 321-422. Porter, Michael E. "Interbrand Choice, Media Mix and Market Per- formance." American Economic Review 66 (May 1976): 398-406. Printers Ink, February 24, 1967, pp. 9-10. Reekie, W. Duncan. "Advertising and Market Structure: Another Approach." Economic Journal 85 (March 1975): 156-164. Rees, R. D. "Advertising, Concentration, and Competition: A Comment and Further Results." Economic Journal 85 (March 1975): 165-174. Riesz, P. C. "Size Versus Price, or Another Vote for Tonypandy." Journal of Business 46 (July 1973): 396-403. Resnik, Alan and Stern, Bruce L. "An Analysis of Information Con- tent in Television Advertising." Journal of Marketing 41 (January 1977): 50-53. Scherer, Fred M. Industrial Market Structure and Economic Per- formance. Chicago: Rand McNally, 1970. Schmalensee, Richard. On the Economics of Advertising. Amsterdam: North Holland, 1972. Simon, Julian L. Issues in the Economics of Advertising. Urbana: University of Illinois Press, 1970. Stigler, George J. "The Economics of Information." Journal of Political Economy 69 (June 1961): 213—225. Strickland, Allyn D. and Weiss, Leonard W. "Advertising, Concen- tration, and Price-Cost Margins." Journal of Political Economy 84 (October 1976): 1109-1121. Sutton, C. J. "Advertising, Concentration, and Competition." Economic Journal 84 (March 1974): 56-69. Teleki, Margot. "The Negotiating Game: Rate Cut or Straight." Media Scope, October 1969, pp. 41-48. Telser, Lester G. "Advertising and Competition." Journal of Political Economy 72 (December 1964): 537-562. 60. 61. 62. 63. 10. 11. 12. 167 Telser, Lester G. "Another Look at Advertising and Concentration." Journal of Industrial Economics 18 (November 1969): 85-94. Theroux, David J. "Marcus' 'Advertising and Changes in Concentra- tion': A Comment." Unpublished paper, University of Chicago, 1976. Vernon, John M. "Concentration, Promotion, and Market Share Sta- bility in the Pharmaceutical Industry." Journal of Industrial Economics 19 (July 1971): 246-266. Vernon, J. M. and Nourse, R. E. M. "Profit Rates and Market Struc- ture of Advertising Intensive Firms." Journal of Industrial Economics 22 (September 1973): 1-20. Cases and Government Documents "Advertising of Ophthalmic Goods and Services." Federal Register 41 (January 16, 1976). Bigelow v. Virginia, 421 U.S. 809 (1975). Borden, Inc., Case, Docket No. 8978, Federal Trade Commission, August 1976. Docket No. 8883, Federal Trade Commission, April 1972. FTC v. Procter and Gamble Co., 386 U.S. 568 (1967). General Foods Corporation v. FTC. 386 F. 2d. 936 (3d Cir. 1967), cert. denied, 391 U.S. 919 (1968). H. J. Heinz Company v. Campbell Soup Company, Civil Action No. 76— 1306 (W. D. Pa. 1976). John R. Bates and Van O'Steen v. State Bar of Arizona, 97 Sup. Ct. 2691. Linmark Associates, Inc. v. Township of Willingboro, 97 Sup. Ct. 1641 0 Patterson Drug Co. v. Kingery, 305 F. Supp. 821 (W. D. Va. 1969). Terminal-Hudson Electronics v. Department of Consumer Affairs, 407 F. Supp. 1075. U.S. Federal Trade Commission. The Structure of Food Manufactur- ing. Technical Study Number 8, National Commission on Food Marketing, U.S. Government Printing Office, Washington, D.C., 1972. l3. 14. 15. 16. 168 U.S. Senate Committee on the Judiciary. "Hearings on Possible Anticompetitive Effects of the Sale of Network TV Advertising." 89th Congress, 2nd Session, Senate Subcommittee on Antitrust and Monopoly, 1966, parts 1 and 2. U.S. White House Task Force on Antitrust Policy. Report of the White House Task Force on Antitrust Policy, July 5, 1968. (In U.S. Congress, Congressional record. (Daily ed.) v. 115 (1969) no. 87, p. 85642-85659). Virginia State Board of Pharmacy et al., v. Virginia Citizens Consumer Council, Inc., et al., 44 U.S.L.W. 4686. (Also see Brief of Appellants, Brief of Appellees and Brief for Association of National Advertisers, Inc. Amicus Curia for S. Ct. Dkt., No. 74-895). Yang, Charles Y. "Industrial Concentration and Advertising." Hearings before Subcommittee on Antitrust and Monopoly of the committee on the Judiciary, U.S. Senate, Part 5: Concen- tration and Divisional Reporting, Appendix 8. Washington: U.S. Government Printing Office, 1966, pp. 2153-2163. Market Share Data D112, Lip and Eye Beauty Products D113, Perfumes D114, Makeup D115, Manicure Preparations Maxwell Associates. "Maxwell sees 102-12% rise in cosmetics sales for '75." Advertising Age, February 23, 1976, p. 124. Miller, Elaine. "Maxwell reports: Fragrance marketers had 12% gain last year.” Advertising Age, November 29, 1976, p. 52. Synon, Molly. "Scents, face treatments record biggest industry sales gains: Maxwell." Advertising Age, December 23, 1974, p. 4. D121, Toothpaste, Mouthwash Miller, Elaine B. "Aim helps Lever boost its toothpaste share in 1975 lst half: Maxwell." Advertising Age, October 20, 1975, p. 64. 10. ll. 12. 13. 169 D122, Toilet Soap H412, Detergents, Light H413, Detergents, Heavy Maxwell, John C. "Soap, detergent trend: Dollars up, volume down, Maxwell report says." Advertising Age, June 21, 1976, p. 80. Miller, Elaine G. "P & G Soap Shares up in '75 first half: Max- well." Advertising_Age, October 6, 1975, p. 57. Synon, Martha Denver. "Laundry detergent area showed little gain in '74." Advertising Age, April 7, 1975, p. 57. Synon, Molly. "Soap, detergent sales increased 3.8% in '73; liquids gain: Maxwell." Advertising Age, June 17, 1974, pp. 2 and 81. D123, Feminine Hygiene Products "Total domestic sanitary protection market shares.’ Advertisigg Age, September 29, 1975, p. 76. D124, Depilatories, Deodorants Miller, Elaine B. "Non-aerosol deodorants gaining in market share." Advertising Age, November 3, 1975, p. 42. D125, Men's Toiletries Miller, Elaine B. "Shave cream sales jump in 1975 half: Maxwell." Advertising Age, November 17, 1975, p. 32. D141, Hair Treatment Products D142, Shampoos, Rinses Maxwell Associates. "Top Shampoo Brands weaken During lst half, Maxwell says." Advertising Age, January 12, 1976, p. 34. Synon, Molly. "Shampoos, deodorants big gainers as '73 sales climb 10%: Maxwell." Advertising Age, July 22, 1974, p. 3 and 72. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 170 F122, Cereals "FTC cereal data: Companies' brand expenditures." Advertising Age, December 20, 1976, pp. 31-36. Gordon, Richard L. "FTC wants fewer branded cereals, more entries.‘ Advertising Age, April 26, 1976, pp. 2 and 88. Maxwell Associates. "Cereal Dollars up 20% in 1975, Maxwell says." Advertising Age, March 29, 1976, p. 110. Maxwell, John C. "Cereal market to grow 7% in 1974: Maxwell." AdvertisipggAge, April 22, 1976, pp. 2 and 64. F310, Beer Crain Communications Inc. "Advertising Costs for beer, ale, and malt liquor." Advertising Age, September 23, 1974, p. 41. Crain Communications Inc., "Advertising Costs for beer, ale and malt liquor." AdvertisingflAge, November 3, 1975, p. 29. "Leading brewers continued to widen sales lead in 1974." Advertis- ing Age, January 27, 1975, p. 26. National‘Beer Wholesalers' Association. "Sales of 20 leading brewers: 1972-73." Advertising Age, February 4, 1974, p. 16. "Top five brewers dominate '75 market; share near 70%." Advertis- ing Age, January 26, 1976, p. 75. F320, Wine Synon, Martha Denver. "Pop wines are slipping in popularity: Maxwell. " Advertising_Age, May 13, 1974, p. 58. G112, Cigars and Tobacco Maxwell, John C. Jr. "Little cigar was industry's big '71 sales growth item with a 20% overall gain.‘ 1972, p. Advertisipg Age, July 10, 3. Maxwell, John C. Jr. "Costs boost 1973 cigar dollar sales; units slip." Advertising Age, September 16, 1974, pp. 3 and 80. Maxwell, John C. "Cigar industry sales decline; price increase cited." Advertising Age, August 18, 1975, p. 198. 27. 28. 29. 30. 31. 171 G330, Restaurants Howard, Niles. "Market saturation specter looms over fast-food," Advertising Age, February 25, 1974, p. 146. Maxwell, John C. "Fuel shortage is no bar to fast food growth: Maxwell." Advertising Age, June 3, 1974, p. 52. "Top 25 Fast-Food Restaurants sales and market share by company." Advertising Age, June 20, 1977, pp. 3 and 82. G531, Pet Food Maxwell, John C. "Petfood dollar sales rose 16.5% last year." Advertising Age, February 25, 1974, p. 146. Maxwell, John C. "Pet food dollar Sales top $2 Billion in 1974." Advertising Age, April 28, 1975, p. 58. "Illlllllllllllfllf