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The performance of the Canadian food, beverages and tobacco processing industries : an extension of the… Maundu, Maingi 1990

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T H E P E R F O R M A N C E OF T H E C A N A D I A N F O O D , B E V E R A G E S A N D T O B A C C O PROCESSING INDUSTRIES: A N E X T E N S I O N OF T H E P R O F I T - C O S T M A R G I N M O D E L T O A PRICING M O D E L . By MAINGI MAUNDU B.A. University of Nairobi A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES AGRICULTURAL ECONOMICS We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA March 1990 © MAINGI MAUNDU, 1990 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of AQ&» C U*t / U#J\L gCLONoPnicJS The University of British Columbia Vancouver, Canada DE-6 (2/88) Abstract This study was undertaken to achieve three major objectives: 1. to estimate an econometric structure-profitability model for Canadian food, bever-ages and tobacco processing industries; 2. to estimate a structure-price model of the sector to compare with the profit model; and 3. to make inferences about the performance of the sector, with reference to market power and industry efficiency. The above objectives were accomplished by comparing empirical regression results of the two models by using the following approach. First, the statistical significance of the estimated coefficients* was used to determine which factors should be considered of importance in explaining performance. Secondly, the signs on the estimated coefficients were used to determine the direction of the influence of market structure on performance. Lastly, a comparison of the size and statistical significance of the difference in the respec-tive coefficients was used to determine which of the two performance indexes (profitability and prices) is most affected by market structure. From the study four broad conclusions were arrived at. Seller concentration and advertising do have an increasing effect on profitability, but this influence does not derive from market power (price increases). Instead, increases in these factors appear to promote price competition. However, tariff protection has an increasing effect on both profitability and prices. Furthermore, the net effect of tariffs is significantly larger on prices than on profitability. ii Industry growth and market isolation factors have an increasing effect on profitabilty. But they have no significant influence on relative prices. Exports have a decreasing effect on profitability and prices. Increases in input prices may lead to increases in ouput prices. Two broad implications can be drawn from the above results. First, price competition and industry efficiency can be enhanced by (either condoning or encouraging) high market shares, advertising, exports and industry growth. Secondly, although tariffs can increase industry profitability, they may also lead to relatively larger increases in domestic output prices. Similarly, changes in input prices may lead to increases in output prices. Therefore, high tariffs and input prices may serve as barriers to competition, and allow inefficiency to persist in an industry. ui Table of Contents Abstract ii List of Tables viii List of Figures ix Acknowledgement x 1 I N T R O D U C T I O N 1 1.1 Problem Statement 2 1.2 Objectives of the Study 4 1.2.1 Sub-objectives: 4 1.3 Research Approach 5 1.4 Plan of the Thesis 5 2 O L I G O P O L Y THEORIES. 7 2.1 CLASSICAL OLIGOPOLY THEORY 7 2.1.1 Barriers to Entry and New Competition 11 2.2 THEORETICAL MODEL 17 2.2.1 Case I - Exclusive Domestic Market 17 2.2.2 Case II. Open market Environment 19 2.2.3 Pricing model 22 3 E V I D E N C E O N T H E S-C-P RELATIONSHIP. 25 iv 3.1 Background to the Structure-Conduct-Performance Model 25 3.1.1 Introduction 25 3.1.2 Industry Performance and Market Structure 26 3.2 Literature Review 29 3.2.1 Introduction 29 3.2.2 Studies in U.S. and other Countries 30 3.2.3 Canadian Studies 32 3.2.4 Firm Level and Product Group Studies 33 4 The Canadian Manufacturing Sector. 36 4.1 Description and Trends 36 4.2 The Food, Beverage and Tobacco Processing Sector 37 4.2.1 Introduction. . 37 4.2.2 Trends in other major Variables 38 4.3 Food, Beverages and Tobacco Intra-Industry Structure 41 4.3.1 Meat and meat processing industry - SIC 1011 41 4.3.2 Poultry Processing - SIC 1012 42 4.3.3 Fish Product Industry - SIC 1021 42 4.3.4 Fruit and Vegetable Canners and Preservers - SIC 1031 44 4.3.5 Frozen Fruit and Vegetable Processing Industry - SIC 1032 . . . . 44 4.3.6 The Dairy processing Industry - SIC 1041, 1049 45 4.3.7 Flour and Breakfast Cereals Products-SIC 1051, 1052 46 4.3.8 The Feed Industry - SIC 1053 46 4.3.9 Vegetable Oil mills - SIC 1061 46 4.3.10 Biscuit Manufactures - SIC 1071 47 4.3.11 Bread and other Bakery products Industry - SIC 1072 47 v 4.3.12 Confectionery Manufacturers - SIC 1082, 1083 48 4.3.13 Cane and Beet sugar Processing Industry - SIC 1081 48 4.3.14 Miscellaneous Food Industries-SIC 1091, 1092, 1093, 1099 49 4.3.15 Soft Drinks Industry - S.I.C. 1111 49 4.3.16 Distillery products - SIC 1121 50 4.3.17 Brewery Industry - SIC 1131 50 4.3.18 Wineries - S.I.C. 1141 51 4.3.19 Leaf Tobacco, Tobacco Products Industries-SIC 1211, 1221 . . . . 51 5 Database and Regression model. 53 5.1 Data Base 53 5.2 Model Specification and defination of variables . 56 5.2.1 Regression Model 56 5.2.2 Variables 57 6 M O D E L E S T I M A T I O N and RESULTS. 63 6.1 Estimation Approach 63 6.2 The Profit-Cost-Margins Model 63 6.3 The Pricing Equation 64 6.4 Evaluation of the two Model Estimates, with Reference to Market Power and Industry Efficiency 65 6.5 Wrap-up of the Results and Comparison with Other Studies 68 7 S U M M A R Y and CONCLUSIONS, and LIMITATIONS. 71 7.1 Summary and Conclusions 71 7.2 Limitations and Recommentations for Further Research 73 vi Bibliography 75 Appendix A Canada/U.S. Output Value & Quantity Data- 1982 97. vii List of Tables 1 Canada: Industry Definitions; 1980 SIC 79 2 Number of Firms - 1970-85. 80 3 Number of Establishments - 1970-85 81 4 Production Labour - 1970-85 82 5 Production Labour Wages: 1970-85. - Million $ 83 6 Costs of Fuel and Electricity - 1970-85. - ('000 $) 84 7 Cost of Raw Materials and Supplies - 1970-85 (million $) 85 8 Value of Shipments - 1970-85 (Million S) 86 9 Value Added - 1970-85 (Million $) 87 10 Canadian Four-Firm Concentration Ratios. 1970-85. (%) 88 11 Industry Classification by Concentration 89 12 Database: PCM, PR and RPI 90 13 Database: Market Structure Variables 91 14 Regression Results: Average PCM & PR Equations 92 15 Regression Results: Annual PCM-Structure Equations 93 16 Statistical t-test for Ha: Ai = 5; 94 17 Summary of the Regression Results 95 18 Results of Other Structure-Performance Studies 96 v i i i List of Figures 2.1 The 'Kinked' Demand Curve 4 10 2.2 The Limit Price 13 3.3 Components of Consumer Loss Due to Monopoly. 27 ix Acknowledgement I am very grateful to Dr. Tim Hazledine, my Thesis Supervisor, whose vision, guidance and encouragement have imensely contributed to the completion of this thesis. A great deal of appreciation and thanks also go to Gwynne Sykes for her tremendous help in sorting out computing mysteries and location of research material. Finally, I would like to thank the other two members of my Thesis Committee (Dr. George Kennedy and Dr. G.C. Van Kooten) and Teachers at the Department of Agri-cultural Economics for all assistance which came in all forms and times. x Chapter 1 I N T R O D U C T I O N The Canadian food, beverages and tobacco processing sector has several features which distinquish it from mainstream manufacturing activity. First, it is characterised by having some of the factors often associated with unusual market power, actual or potential. Among its industries are to be found some with the highest market shares and barriers to competition in manufacturing, and these features have been on the increase over the years. Secondly, among its ranks are to be found some of the most profitable industries in Canadian manufacturing. These characteristics have important welfare and performance implications, which this study will attempt to unravel. The question often asked in structure-conduct-performance (SCP) studies is the source of differences in profitability among industries. Two opposing schools of thought have emerged to explain this problem: those who believe that market structure variables should be looked into as serving to bestow market power on industries, which in turn exploit it to set prices higher than would be attainable in a competitive market; and those who associate high profits to existence of firms of superior performance in an industry, producing at relatively low costs. A large volume of empirical work relating market structure to industrial performance has been done in the U.S., Canada and several other OECD countries [Collins and Preston (1966); Esposito and Esposito, (1971); Pagoulatos and Sorensen, (1976); Parker and Connor (1979); Scherer, (1980); Lyons, (1981); Rizvi and Uhm, (1982); Jones, Laudadio and Percy, (1973, 1977); Hazledine (1978); and Schmalensee, (1976) ]. Although most of 1 Chapter 1. INTRODUCTION 2 these studies have looked into manufacturing as a whole, some have been done specifically for the food processing sector, especially for the U.S. (Imel and Helmberger, 1971; Collins and Preston, 1966; Rogers, 1978; Parker and Connor, 1979). In Canada, most of the studies have considered manufacturing as a whole (De Silva, 1971; McFetridge, 1973; Jones, Laudadio and Percy, 1973, 1977), with a few isolating food processing, either as a separate sector or combined with manufactured agricultural inputs, for analysis (Hazledine, 1978; Rizvi and Ulm, 1982). Most of the Canadian studies on food processing have relied for the most part on data available in the early 1970s and before. Such data was in most cases available in broad industry classifications, and therefore subject to various aggregation anomalies; such as lumping together heterogeous groups of products (unrelated in production and demand) into the same SICs (Khemani, 1980, pp. 8.). This problem has been partly overcome with revision of the SIC in 1980. Altogether data for up to 26 industries (compared to 22 in the 1970 SIC) are available (20 of them food processing, 4 beverages, and two tobacco processors). Perhaps even more important has been non availability of industry price and cost data, which could provide a more direct (and better) source of information about the pricing behavior (and hence performance and efficiency) of manufacturing industries. 1.1 Problem Statement. The purpose of this study is to find out if there is sufficient empirical evidence to sup-port the hypotheses that Canadian food, beverages and tobacco processing industries wield considerable market power, and whether this characteristic is significant enough to classify it as an oligopolistic sector. In particular, attempts have been made to find out whether the sector's performance can be traced to the market environment (structure) Chapter 1. INTRODUCTION 3 in which the industries operate. The other question we attempt to answer is whether the Canadian sector's pricing behavior shows any significant departure from competition, here considered the bench-mark of efficiency. To what extend is the domestic market environment a possible source of this relative difference? It is hypothesised that the U.S. market is relatively more com-petitive, and thus any price differential between the two markets will partially provide an appropriate measure of the degree of oligopoly pricing or power in the Canadian sector. A partial explanation advanced to support this claim is that the U.S. consumer goods market is large, in terms of the size of its domestic demand (population and income), compared to the small Canadian population. Technology permitting, demand related barriers are likely to be lower in a larger market. In the absence of centralized price-setting authority in either country, market structure can be considered as the major force behind any differences between the two1. The problem is reformulated into the following working hypotheses, a test of which would in effect act as a guide and evidence for answers to the problems: 1. Prices and profitability would tend to be higher in an industry with higher seller concentration, high entry barriers, and rapid growth in industry demand; factors perceived to be sources of market power. 2. Prices will tend to be higher in industries with higher relative input prices. 3. Geographical isolation affords a 'natural' barrier to competition to local industries and hence provides them leeway in price setting and higher profitability. 4. High tariff protection acts as an additional barrier to entry, and thus protection from foreign competition. Hence it would be expected that industries with higher 1An exception is the price and entry controls at the provincial level in Canada on liquour, wine and beer industries. (Khemani, 1984, pp. 48) Chapter 1. INTRODUCTION 4 tariff rates would tend to enjoy relatively higher prices and profitability. 5. Imports have a negative influence on prices and profitability. 6. The impact of export competition on domestic industry pricing behaviour and profitability is indeterminate a priori. 1.2 Objectives of the Study. The main objective of this study is to estimate empirical models for the Canadian food, beverages and tobacco sector which could be used to assess the relationship between various market structure variables and the performance (prices and profitability) of the sector. 1.2.1 Sub-objectives: The sub-objectives of the research are to: 1. provide a general description of the state and trend of the sector over the period between 1970 and 1985; 2. derive Canada/U.S industry selling price indexes compatible with the current Cana-dian SICs (1980); 3. estimate an econometric structure-profitability model for Canadian food, beverages and tobacco processing industries. 4. estimate an equivalent structure-price model for Canadian industries to compare with the profits model. 5. Use the estimated models to test various hypotheses, and make inferences about the performance of the sector; and Chapter 1. INTRODUCTION 5 6. draw implications of the results for industry competition policy. 1.3 Research Approach. To test the hypotheses stated above, 26 industries were selected for the study (Table 1.). The first task was to assemble data for the various variables. From the available Census of Manufactures data profit-cost margins (PCM) were derived. Thence, Canada/U.S. industry output price indexes were derived (Appendix A.). Using these variables as measures of performance, two sets of regression equations were estimated. One set related profit-cost margins to various market structure variables. The other set constitutes regression equations for the pricing model. The first set of results, was used to analyse and draw inferences about the relationship between profitability and market structure. Similarly, the estimated equations of the pricing model were used to determine if there is sufficient evidence to suggest that the Canadian industry selling price regime is different from the U.S, and if the market structure of the domestic sector (Canada) provides any evidence as to the source of such differences. Then by comparing the statistical results of the two models, inferences about industry efficiency and market competition were made. 1.4 Plan of the Thesis. The study is organised into eight chapters, inclusive of the introductory chapter. Chapter 2, which comprises two sections, includes a general review of the oligopoly problem. Section 2.1 provides a review of some of the traditional oligopoly theories encountered in the literature. In section 2.2, a more rigorous treatment of the theoretical foundation of the structure-conduct-performance (S-C-P) model is presented. Section 2.2 is composed of three sub-sections; where sub-section 1 looks at the domestic market situation; 2 the Chapter 1. INTRODUCTION 6 international market; and in 3 a pricing model is considered. In chapter 3, the evidence on the S-C-P relationship is considered. Included in this chapter are two sections; section 3.1 which looks at the S-C-P approach and motivation, and section 3.2 which includes a review of previous studies where the approach was put into use. Section 3.2 consists of four sub-sections; where 1 is devoted to an introduction; 2 to U.S. specific studies; 3 to Canadian cases; and sub-section 4 looks at firm-level and product-group level studies. A detailed description of the state and trends in the Canadian manufacturing sector and the food, beverages and tobaco processing industries in particular is presented in chapter 4. Section 4.1 looks at the whole manufacturing sector and relates it to the food and kindred processing sector. Section 4.2 looks at the trend of the major aggregate production-related variables of the sector, while section 4.3 looks at individual industries. A description of the data and regression model specification used in the study is presented in chapter 5. Section 5.1 is devoted to the analysis of the nature and sources of the data. Section 5.2 deals with the regression model and definition of variables, in addition to any a priori expectations of the regression results. Estimation results are presented in chapter 6, where section 6.1 outlines the estimation approach, section 6.2 reports the PCM results, and 6.3 the PR results. A synthesis and wrap-up of the results of the two model estimates is provided in section 6.4. The results of the current study are compared to other case studies in section 6.5. A summary, conculsions and limitations of the study are presented in chapter 7. Chapter 2 O L I G O P O L Y THEORIES. 2.1 C L A S S I C A L O L I G O P O L Y T H E O R Y . There exist well founded theories for analysing perfect competition and pure monopoly markets. In the model of perfect competition, every market is characterised by many small buyers and sellers acting independently, free entry and exit, a homogeneous prod-uct, and an excellent product and market information. In the other extreme, a market dominated by a single firm is described as a monopoly. If there are a few firms selling the same product, or products which are close substi-tutes, the market would appropriately be described as an oligopoly. The bulk of market structures lie in this intermediate group. Although the role of an individual firm may be quite significant, its output and pricing behavior is also influenced by the actions, explicit or implicit, of the other firms in the industry. Oligopolistic market conduct is complex and involves many dimensions of a firm's behavior. Unlike pure competition and monopoly, there is no single theory for the oligopoly market. The difficulty is that the theory of interdependent action which is central to oligopoly is a much more difficult problem than the theory of independent ac-tion, peculiar to perfect competition and monopoly. Some of these theories are reviewed below. Take the case of a firm contemplating expansion of its output. In doing so it will have to take into consideration the possible reactions of its rivals. If we assume there 7 Chapter 2. OLIGOPOLY THEORIES. 8 are N firms in the industry, under what conditions will their actions be consistent? They will be consistent when the choices each firm makes are compatible with the others' expectations. A possible outcome will be a case where a typical firm assumes that its rivals will not respond to its action. This deduction, first attributed to Cournot, implies that each firm chooses to market the quantity of output that maximizes its own profits, assuming rival firms' output levels remain fixed. Assuming firm l's output is xi and that of the other firms (combined) is x2, then the price consumers are willing to pay, P, will depend on aggregate supply, P(xy + x2). Firm 1 wishes to maximize its profits, taking the other firms output as fixed, by chosing X\. Max P(xi 4- x2)x! - C(ii) The solution to this problem must satisfy : P'{x\ + x2)x\ + P(x\ + x2) - C'(x\) = 0 or [P(z\ + x2) - C\x\)\IP(x\ + x7) = -(l/ea) where ei is firm l's perceived price elasticity of demand. Thus, if the firm's share of aggregate industry output is very small, then its demand curve will likely be highly elastic. This would restrict its power to change its price level. In the limit, the absolute value of ei would tend to infinity, implying that the firm can not effectively influence market price (McCain, 1981, pp. 309). Similarly, the analogous condition must hold for any other firm 'i' in the industry. A consistent outcome will obtain if Xi = x^, for all firms. An alternative assumption is that each firm may take the others' price level to be fixed, an approach initially investigated by Bertrand and later extended by Edgeworth (B-E model) in the 19th. century (McCain, 1981, pp.312). Each firm will choose its own price on the assumption that other firms will not change theirs. If firm 1 raises its price above that of its rivals, it will lose all its customers to them. Chapter 2. OLIGOPOLY THEORIES. 9 Similarly if it lowers its price slightly below its rivals', it will get all the customers. It is evident that, in this model, all firms will have to charge the same price, say P". If P* is above its marginal cost, then for positive z, a firm can steal all customers from its rivals by charging (P~ — z) and still make a profit. But in practice we expect its rivals to react by lowering their price level to match that of firm 1 if they are to remain in the market at all. In the limit, matching price strategies will lead all firms remaining in the industry to equate their price to their marginal costs, thus generating the competitive equilibrium outcome. A variant of the Cournot model is the Leadership-follower model where one firm makes the key pricing decisions and the others follow consistently. The leader may be the largest (dominant), or the lowest cost firm in the market, and able to set price, allowing the other smaller firms to sell as much as they want at that price. By taking the residue share of the market, the leader behaves like a monopoly surrounded by a fringe of competitive firms. Another oligopoly model, which also exploits the concept of interdependence, was proposed by Sweezy. Sweezy (Kinked demand curve model) argues that firms would react differently to a price change, depending on whether the price change is either upward or downward (Scherer, 1980 pp.165). If a firm raises its price, its rivals will acquire new customers. If on the other hand it lowers its price, its rivals will lose customers. Accordingly, the reaction to a gain in business (new customers) is indeed welcome by rivals, and thus calls for no particular action. However, loss of business (due to price cuts) will invite reaction. Assume the initial equilibrium price is P" (figure 2.1 below), with firm i selling Qi. If it cuts its price, the rivals all make cuts of similar magnitute, and firm i experiences a movement downward along its demand curve, D. However if, instead, it raises price, its rivals take no retaliatory action: The firm would experience a movement upward along Chapter 2. OLIGOPOLY THEORIES. 10 Quantity Figure 2.1: The 'Kinked' Demand Curve. its demand curve. Thus firm i conceives its demand curve to consist of two portions; a relatively more elastic segment 'dk' for a price rise, and a less elastic segment 'kD' for a price decrease, with a kink at point k. As long as the marginal cost curve (MC) crosses the marginal revenue curve ('ab and MR') at the discontinuity (be), price P" and output Qi remain optimal choices. Any moderate rise or decrease in costs which does not distort the marginal cost curve to levels outside the discontinuity will not affect the firm's output and pricing decision. It is this argument on which the Kinked demand curve model derives its proposition that prices will be quite stable in oligopoly markets. A strong criticism of this model is that it does not explicitly tell where the demand curve, the lank or the stable price will be, and how the price is formed. Chapter 2. OLIGOPOLY THEORIES. 11 Instead of acting independently, firms in an oligopolistic market can improve their lot by colluding, or forming a cartel (Varian, p.100). This way, individual firms surrender their output and pricing roles to a centralized decision making agency to which they all subscribe. Optimal output decision will require maximization of the industry's aggregate profit by choosing £ xi '• However a common problem with a collusive market arrangement is weakness of adherence to the joint output restraint. Cost differences will make it difficult to negotiate a satisfactory joint output policy, to which each participant subscribes equally. A partial solution to this problem is possible if there are fewer firms in an industry, making it easier to coordinate their actions and police each others' behavior well enough to prevent serious cheating. .In summary, traditional oligopoly theory derives its strenghth on two assumptions, one of which is common to perfect competition and monopoly: Profit maximization by all firms in an industry; and each firm's parceived interest to the possible reaction of its incumbent rivals. But the empasis in oligopoly studies has shifted tremendously to include entry prevention behavior of new firms. 2.1.1 Barriers to Entry and New Competition. The models reviewed above have considered the interdependence problem among incum-bent firms. However, threat of entry and competition by potential firms is another factor these firms have to consider. An industry can only ignore this factor if there are sufficient Max P E ^ - E C ( x i ) Chapter 2. OLIGOPOLY THEORIES. 12 and effective barriers to entry1. How effective barriers are is indicated by the ability of the incumbent firm(s) to raise and sustain prices higher than the average cost of production, without inducing entry. The height of such barriers (translated into costs) will vary from industry to industry. In one extreme, firms could be able to set their price and output up to the monopoly level, without triggering entry. Or an industry may be characterised by entry barriers so low such that any slight increase in price above average costs will attract new firms. A critical price level, or 'limit price' 2 , can be assumed to exist below which existing firms worry only about their fellow operating rivals. Consider the simple monopoly industry, with an horizontal long-run cost curve -LRAC - and demand curve, DD' (figure 2.2 below.). In the absence of threat of entry, the solution to the firm's problem is straightforward: operate at the monoply equilibrium output, Qm, and charge price Pm. However, if we relax the above assumption, such that there exists a price level Pi which coincides with the minimum average cost curve of potential entrants, but lower than Pm, the monopoly solution may not be sustainable in the long run. The best he can do is to charge P; and offer a relatively higher output, Q\. Under these conditions, the firm can continue to earn above-normal profits, and still forestall entry. In the limit, a price equivalent to the incubent firm's long-run average cost curve (LRAC) will yield a 'free' entry or perfectly competitive market. The problem facing firms in an industry where above-normal profits are attainable is whether to go ahead and maximize them in the short period, and hence attract new firms, or adopt entry prevention strategies. The later option entails that incumbent firms adopt 1 Barriers to entry have been variously defined as the constraints potential firms face in trying to enter a market. Joe S. Bain: 'Barriers to New Competition'. Harvard University Press, Cambridge. 1956. pp. 3. 2Waterson (1984) defines this as the price below which the industry is not profitable enough to attract new firms to enter, pp. 57 Figure 2.2: The Limit Price. Chapter 2. OLIGOPOLY THEORIES. 14 a price-policy which is not attractive to new competitors. This is done by restraining price to levels below what would obtain in a non-threat market environment. Therefore, rather than maximize profits per se, as in perfect competition or monopoly, they do so by stretching their earnings over the long-term. How will potential entrants react to the barriers erected by incumbent firms? A new firm will have to consider whether the post-entry price will cover its average cost of production. Also new firms have to conjecture whether old firms will likely change their output shares and accomodate them. If neither of these conditions is met, then entry prevention would be effective. Product differentiation is often the most cited indicator of barriers to new competition. Such differentiation requires that buyers have non-identical preferences among competing outputs of various sellers. Usually demand elasticities (Own price, cross-price and income elasticities) would provide some evidence of the degree of product differentiation. A perfectly elastic demand curve would imply that products from all firms are perfect substitutes and thus non-differentiated. Advertising, as a persuasive tool, is one of the means used by firms to create and maintain such differences in their products (Scherer, 1980, pp. 376). It may also serve an informative role to consumers about the availability, quality and prices of goods (MacMil-lan and Pazderka, 1989.). The relationship between advertising and industry performance can be explored by considering the impact of a firm's level of advertising expenditure on its profitability (via increasing its ability to change price) by use of the simple model3 shown below: (1)* = PQ(P,A)-C(Q1A) Profit (7r)maximization requires that the effects of a change in advertising expenditure 3Adapted from Douglas Needham's article: 'Market Structure and Firm's Research and Development Behaviour'. The Journal of Industrial Economics, Vol. 23, No. 4, (1975) pp. 253. Chapter 2. OLIGOPOLY THEORIES. 15 on total revenue be equal, i.e. (2) dv/dA = PdQ/dA - 8C(Q,A)/dA = 0, and (3) PdQ/dA = MC(dQ/dA) + 1, where MC is marginal cost (or dC/dQ) Therefore: (4) (P-MC)/P = (A/PQ)(l/ea) where ea = (dQ/dA).(A/Q) is the advertising elasticity of demand. What expression (4) shows is that advertising can have some positive effects on price mark-up over costs, depending on the good's responsiveness. If the product has a high elasticity of advertising (ea), relatively lower promotion expenses would be needed to bring about a given increase in sales. For instance, in a study of U.S. food manufacturing industries in 1978, Connor (1979) found that the huge expenditures required to launch new consumer food products rep-resent the principal barrier to entry in an existing market. In order to break into the market, new firms have to spent more per customer in promotional campaigns than would an established firm. Economies of scale in advertising also work in favour of large firms, in so far as they are able to spread their expenses over a large output. It would suffice to deduce that high advertising outlays, as a pre-requisite for breaking into a market, will act as a barrier to entry and for firms to be induced to incur such expenditures there must be an opportunity to compensate them, in the form of profits. There are other factors which can affect an industry's discretion to change the limit price (Pi) (in figure 2.2 above), either upwards or downwards. These include foreign trade and trade policies, and prices of inputs. Imports act as substitutes to domestic products, and play down market power associated with domestic concentration. A highly concentrated industry would find its ability to influence prices much curtailed if imports are priced at levels relatively lower (along the limit price scale) than domestic prices. Tariffs can act as shelters from foreign competition to an industry. In effect, they Chapter 2. OLIGOPOLY THEORIES. 16 would afford domestic producers a price advantage, equivalent to the duty imposed (over and above other transfer costs) on competing imports. This suggests that the higher the tariff rates (and other non-tarrif trading restrictions), the higher would be the limit price domestic firms could charge, and hence high profit rates. In the extreme, a total ban on imports, or a patent will bestow monopoly power to the lucky firm(s). Khemani (1980, pp. 6), in his study of the structure of Canadian manufacturing industries, noted that tariff protection's main result is to segregate the domestic market from the larger North American and international market. Product prices are also perceived to be highly correlated with input prices. Higher input prices will be reflected in aggregate production costs, and eventually producers have to take these into account in setting consumer prices. Not only do these costs affect individual firms at the domestic market, but they also have important implications on an industry's competitiveness in import-export trade. However, the deductive approach, found useful in analysing other markets, is not as powerful in oligopoly (Scherer, 1980, pp. 152). It leaves us with a long list of models, each of which is applicable only in limited circumstances, under strict assumptions. Due to this limitation, many studies of oligopoly behaviour have relied less on deduction and more on results. One of these possibilities is to give up the theoretical approach entirely, and rely strictly on observation. In practice, observational approaches have posed and investigated hypotheses about the relationship between industry structure and performance. A general look at the theoretical foundation of this approach (the structure-performance model) is given below. Chapter 2. OLIGOPOLY THEORIES. 17 2.2 T H E O R E T I C A L M O D E L . Pricing and output policies are two of the most important sources of evidence which can be looked at to infer the behaviour of firms in different settings. A firm's behaviour will depend on the structure of its market; on whether it sells exclusively in the domestic market and the kind of competition it faces, or whether it faces foreign competition, both in form of imports and as an exporter. We can identify two possible scenarios faced by the typical firm: 1. it produces and sells exclusively in the domestic market, and faces no competition from imports, or 2. it may sell in both the domestic and the world markets, in addition to facing competition from imports in its home base. 2.2.1 Case I - Exclusive Domestic Market. Consider an industry composed of N firms, producing a homogeneous product. Following Cowling and Waterson (1976), a typical firm would seek to maximize its profits, 7TJ: (5) TX{ = PQi - c(Qi) The inverse demand function can be written as: P = f(Q); where Q = E? = 1 Qi, P is the industry selling price, Qi is the firm's output and c(Qi) is its total production costs function. Profit maximization requires that: (6) dTd/dQi =P + Qif'(Q){dQ/dQi) - c'{Qi) = 0 and (7) dQ/dQi = 1 + dZ&i Qj/dQi = 1 + k Chapter 2. OLIGOPOLY THEORIES. 18 Substituting for dQ/dQi in (6), multiplying through by Qi and summing across the N firms gives: (8) PQ + Zf'(Q)Qi + Zf'(Q)Qi<i>i -Zc'(Qi)Qi = o or (9) [PQ - £ c(Qi)Qi\IPQ = (H + <f>)/eh where YJ{Q\IQ) = H is the Herfindahl index of concentration; HQl^i/ 12 Ql — $ Is the conjectural industry output variation, and eh is industry price elasticity of demand. Several terms in the above expressions need some special attention. f'{Q) in (8) indicates how firm T assumes the market price will respond to changes in its output. Two values of this term may be used to classify a particular market. If f'(Q) is zero, then the result represents a competitive market, where changes in a single firm's output level has virtually no effect on aggregate industry price. Similarly if the term takes a value of one, then the industry will approximate a monopolistic market. The other term of importance is <j>, which captures how firm 'i' predicts its rivals will respond by changing their output. Various hypothetical values of this conjectural variation term can be used to classify some of the market structures cited in traditional firm theory. A value of zero implies the competitive market. In other words, a single firm's output would be too insignificant to warrant any meaningful response by other firms in the industry, and thus it ignores them in its decisions. A value of one implies the Cournot solution, where the typical firm conjectures that others will not change their output. Therefore an industry's profitability would tend to be positively correlated to industry concentration, and inversely related to industry elasticity of demand. An expression relating producer mark-up of price over costs and the number of firms Chapter 2. OLIGOPOLY THEORIES. 19 in the industry can also be derived. Assuming that all firms in the industry face an identical variable cost structure4, the first order condition for profit maximization would be: (10) dvi/dQi = P + Qif'(Q)(dQ/dQi) -Ec'(Qi) = 0, and (11) dQ/dQi = 1 + dZjtiQj/dQi = l+1>i Substituting for (11) in (10), summing across the N firms, and replacing Y2 Qtyi/ E Qi = V7 gives (12) [P-c'{Qi)]/P = (l+i,)/Neh The left handside of (12) shows that producer mark-up of price over marginal costs would be inversely correlated to the number of firms in the industry, and the industry's elasticity of demand, other things being equal. This result, however, does not contradict the one found in (9) above, between margins and concentration, as both firm numbers and market shares are indeed related. Fewer firms imply fewer participants in the market and increased important role of individual firms in industry activities (or market shares), and hence ease of market coordination (collusion). 2.2.2 Case U. Open market Environment. In this case, a firm can choose to produce and sell in either the domestic market or the world market, or in both. It also faces competition from imports. Following Lyons' model (1976), a typical firm's profit function becomes: (13) 7T; = PdQid + PwQix — c(Qid + Qix) — t(Qix), where Qid and Qix are firm i's sales in the domestic and the world markets, respectively; Pd and Pw are domestic and world market prices, respectively; c(Qid + Qix) are the total production costs; and 4This assumption implies that all firms will in effect be of identical size at industry equilibrium. Chapter 2. OLIGOPOLY THEORIES. 20 t{Qix) is any transfer costs associated with exporting, such as transport and tariffs. The respective inverse demand functions for domestic and export sales are: (14) Pd = f(Qd + Qm) (15) Pw = g(Qx + Qw), where Qx is aggregate exports by domestic firms, Qm is total imports and Qw is the supply by the rest the world. Considering the domestic market first, the first order conditions for profit maximiza-tion are: (16) dizJdQid = Pd + Qidf'{Qd + Qm)d[Qd + Qm)/dQid - c'(Qid + Qix) = 0, and (17) d[Qd + Qm}/dQid = 1 + dZ^iQjd/dQid + dQm/dQid = 1 + Ti+Pi Sustituting for (17) in (16) and multiplying through by Qid and summing across the N firms yields: (18) [PdQd - E c'(Qid + Qix)Qid]/PdQd = [Hd(l + r + p)/em][Qi/(Qd + Qm)} where T = TQ2idTi/ZQ2id™d p = £ Qhpi/ E Q}d are conjectural output variation indexes, distinquished by source of output (domesti-cally produced and imported, respectively); Hd = £(Q2d/Qd) , or the Herfindahl index of domestic market concentration; and em = — [Pd/(Qd + Qm)]/f'(Qd + Qm) is the industry elasticity of demand in the open domestc market. Expression (18) suggests that an industry's profit margins in the domestic market are positively correlated to industry concentration (Hd), but inversely related to domestic price elasticity of demand (em). If imports were effectively excluded from the domestic market, either by high transfer costs or other restrictive trading practices5, the conjectural 5these may include high tariff rates or non-tariff barriers, such as outright bans. Chapter 2. OLIGOPOLY THEORIES. 21 import term, p, would be zero, implying that the industry's output decisions are only affected by domestic intra-industry and market variables. Turning to the export market, the first order conditions are: (19) din/dQi. = PW + Qixg'(Qx + Qw)d[Qx + Qw}/dQix - c'{Qid + Qix) - t\Qix) = 0; and (20) d\Qx + Qw}/dQix = 1 + d Yt&i Qjx/dQix + 8Qw/dQix = l + Xi + ui Substituting for (20) in (19), and multiplying through by Qix and summing across the N firms yields: (21) [p w g,-Ec'(g i d +g i »)^ x -Ei'(Q i a : )^x]/Pu,gx = Jf/x(i+A+/x)/eu)[^/(gx + <3„,), where A = E QIKI E QI and M = E<3LM«/EQL ; e» = -[Pw/(Q* + Q„)}/g'{Q* + Qw) is the world price elasticity of demand; and Hx = JliQix/Ql) i f i a n Herfindhal index of export concentration. Therefore, from expression (21), profit-cost margins of an industry engaged in exports would be directly correlated to its share of total world supply. Similarly, profit rates would be inversely related to the world elasticity of demand. Since an individual country's industry share of aggregate world exports is likely to be quite small, the demand curve facing it would be very elastic (i.e. high absolute elasticity index). Lastly, firms are presumed to be less interested in individual sources of profits, and thus the distinction between domestic and export markets is rather artificial. Therefore, an appropriate aggregate industry profit-structure equation can be obtained by summing (18) and (21), to give the following: (22) U/(PdQd + PWQX) = [Hd(l + r + p)/em[Qd/(Qd + Qx)}]PdQd/(PdQd + PWQX) + [Hx(l +X+ v)/ew[Qx/(Qx + Q„}}PwQx/(PdQd + PWQX) 6 6II is defined as the sum of profits on domestic and export sales, or the sum of left-hand sides of Chapter 2. OLIGOPOLY THEORIES. 22 The left-hand side of (22) is now the familiar profit-cost margin, expressed as a function of both domestic and foreign trade related variables. 2.2.3 Pricing model. Profit-cost margin data for estimation and testing of model (22) is available in most cases. But profits per se are but a small clue to the actual performance of an industry. There is need to consider the role of cost efficiency in explaining profitability. Relatively high profit rates may not be a result of firms' exploiting their market power, but partially a result of specific-firm efficiency. This implies existence of efficient firms in the industry, capable of producing at low costs. Therefore of more interest is the pricing-performance of industries (and even more important specific firms), which may be a better clue to whether firms exploit their market power to push prices above their competitive level. To investigate this aspect, the relevant price-cost margin model will be of the form: (23a) TT{ = (Pi - Ci)/Ci = f(Zi), or (23b) Pi = Ci.f(Zi) + Ct; where Zi is a vector of market structure variables; P; and C; are the price and costs of industry i, respectively. Estimation of (23a) (or 23b) requires one to assume that all industries are cost effi-cient; i.e. (23c) d = C = Pc, where C reflects an industry's lowest point on its average cost curve and Pc is the competitive market price. In other words, cost (C;) is asssumed to be independent of market structure (Zi). This will ensure that estimated regression coefficients are indeed statistically unbiased, expressions 18 and 21 respectively. Chapter 2. OLIGOPOLY THEORIES. 23 But if C{ is dependent of Zi, then the assumption of cost efficiency may no longer be valid; i.e. (23d) d = h(Zi). By exploiting this dependency concept, one can infer the influence of market structure on cost efficiency. Hence, if (23d) is true and one ignores it and estimates (23b), the coefficients on the structural variables, Z,, will be larger than those obtained in the coresponding structure-profit model, (22). This result will imply that market structure exerts relatively larger and stronger influence on price levels than they do on profitability. If, on the other hand, the estimated coefficients on (23b) are relatively smaller than those on (22), this suggests that changes in market structure bring about bigger changes in profitability than they do on price levels. It is from these two statistical outcomes that inferences about market power and efficiency can be made. The former outcome suggests that changes in market structure can affect an industry's performance at two levels: costs and prices. Some market structure factors are perceived to impose higher production costs, which are eventually translated into higher prices, with little effect, if any, being experienced in profitability (an example of X-inefficiency). The latter outcome suggests that profitability resulting from changes in market struc-ture is attained at a relatively low (or invariant) cost structure, and hence firms can maintain their past price levels, or even lower them. Thus, changes in market structure could either enhance or reduce efficiency, or be neutral. Empiricaly, the biggest limitation to assessing whether actual prices deviate from what would be perceived as true competitive levels is lack of information on the latter. A solution to this problem could be found if we can obtain a direct measure of the com-petitive price. This would enable estimation of both models, and capture the deviations of actual prices from the competitive levels. Thence we can use the results to test if the price-structure hypotheses holds, as oligopoly theory predicts. Chapter 2. OLIGOPOLY THEORIES. 24 A partial solution to the data problem would be to use a substitute for the elusive competitive price. An example is the prices of non-branded goods, here considered rela-tively competitive, against which to compare the prices of branded foods7. But in Canada, such data (distinquishing branded and non-branded goods) are not readily available. Under certain assumptions the U.S. price regime could be considered as a candidate for the competitive price. A basic assumption would be that U.S. indus-tries are larger, less concentrated and more efficient (and hence competitive), than their Canadian counterparts, in general. However, caution is needed in making this general-ization because it may not be valid for all U.S. food industries, for some are concentrated and indeed believed to wield market power. But as long as this power is not correlated, industry by industry, with market power in its Canadian counterpart, then the U.S. price will be a reasonable instrumental variable for the competitive price. Therefore the model to be estimated would be (24a) P{ = P-.g(Zi) , or (24b) Pi/P: = g(Zi) ; where P[ is the U.S. selling price for industry i. It is also possible that U.S. pricing behaviour is sensitive to some of the U.S.-specific market structure characteristics. Hence, an improvement in the analysis could be made by estimating and testing a larger model, involving structural variables of both markets (U.S. and Canada); i.e. (25) Pi/P; = k(Zi,Z'i)] in which Z[ is a vector of U.S. structural variables. A review of the application of some of the concepts analysed in this chapter in studies in manufacturing (and food processing in particular) is presented below. For a review of a case study in U.S. food manufacturing, see Chapter 3.2.4. Chapter 3 E V I D E N C E O N T H E S-C-P RELATIONSHIP. 3.1 Background to the Structure-Conduct-Performance Model. 3.1.1 Introduction. Basic concerns in industry performance when viewed from society's perspective are: is the right quantity and variety of goods and services being produced efficiently? With failure of traditional theory to provide an empirically testable model to tackle this fundamental question, attention has been diverted to market structure as possible evidence of market behaviour in oligopolistic markets. By market structure, we mean such things as the number of firms in the industry, the extent to which the industry is dominated by one or a few firms, the existence and degree of barriers to entry and other factors believed to affect competition. Consequently these factors will affect market conduct. On the other hand, the concept of perfomance describes the level and flexibility of prices, profitability, technical and cost efficiency. To tackle an empirical problem, the hypothesis to be studied is that some aspects of the structure of a market determine aspects of its performance. The usual procedure has been to express the hypothesis in terms of statistical relationships between the structure and the performance of the industry. Then the statistics can be examined to see if the predicted relationship does exist. This is the Industrial Organization (10) approach. In most structure-profit studies, the standard model is: 25 Chapter 3. EVIDENCE ON THE S-C-P RELATIONSHIP. 26 (26) 7r = f(CR,B,D) 1 where IT is a measure of profitability, expressed as a function of seller concentration (CR), barriers to entry (B), and market demand conditions (D). Such studies may be either inter-industry or intra-industry, where the former compare different industries, and the latter distinct submarkets or firms within an industry. The cost and price structure of a firm would provide most of the information necessary to evaluate its performance (profitability and cost efficiency). Athough it may be possible to observe prices and output in a monopolistic or a oligolistic market, we can neither observe nor say precisely how the market would function if it were competitive. This is mainly due to non availability of sufficient information, especially costs of production data for most industries2. In an attempt to overcome some of the restrictive assumptions of traditional oligopoly models, Industrial Organization studies have turned to inferring conduct from market structure or performance, and a large output of such studies is now available. But there still remains some unsettled disagreement about the causal relationship between structure, conduct and performance (Roger, 1977). Some of the typical questions raised are: 'do structural factors (such as seller concentration) cause profitability or vice versa?'; 'Is it high profit rates which cause or enable firms to commit more funds to advertising campaigns, or does it take advertising to earn higher profit rates?'. 3.1.2 Industry Performance and Market Structure. Persistently high profits in an industry have been proposed to be a good measure of monopoly pricing (Parker and Connor, 1979 pp.627). The ultimate loss in consumer welfare can be investigated by looking at the cost structure of an hypothetical firm in a 1Almarin Phillips: A Critique of Empirical Studies of Relations between Market Structure and prof-itability; The Journal of Industrial Economics; Vol. 24 No. 4; June 1976. 2 Such information is of strategic importance to a firm, and it would not serve its interests to have it divulged to rivals. Chapter 3. EVIDENCE ON THE S-C-P RELATIONSHIP. 27 Pc T* d c A \ F E \ AC1 • i j • \ d : > L • yuancicy Qm Qc Figure 3.3: Components of Consumer Loss Due to Monopoly. monopolised industry. Figure 3.3 depicts the differences in performance we would expect between a monopolistic and a competitive market. A firm in a competitive industry would attain equilibrium when it operates at output levels at which average costs are at the minimum and equal to price ( Qe and Pc, respectively). But in a monopolistic industry, the firm would restrict output to Qm and realise price Pm. Total consumer welfare loss due to monopoly is equivalent to the area PmPcFC. This can be apportioned into three types: the triangle CAF which is equivalent to a dead weight loss, neither reallocated to the producer nor to the consumer; and the area PmPcAC which would represent an income transfer from consumer. This triangle can be futher decomposed into excess profits earned by the producer (PmXBC) - indeed Chapter 3. EVIDENCE ON THE S-C-P RELATIONSHIP. 28 a net transfer from consumer to producer - and XPCAB, which is the wasteful excess production costs imposed by a monopoly. This overcharge (sometimes referred to as the X-inefficiency) reflects higher costs faced by a firm due to its non-optimal manage-ment practices and excessive expenditures (such as advertising and excess plant capacity) made by firms to sustain their market power (Parker and Connor, 1979, pp.629). It is the contention among many Industrial Organisation studies that firms in concentrated industries are more prone to these malpractices. Other hypotheses may contest the above proposition (concentration causes profits, or that dominant firms exploit their market power). It may be that concentration and profits are both the results of some other cause. In particular, the role of specific firm efficiency may increase with firm size (economies of scale), and hence concentration. In other words, a firm may be able to sustain high profits without resorting to exploiting its market power to increase prices. In the forefront of this school of thought is Demsetz (1973), who argues that superior performance (profits) should not necessarily be seen as a product of oligopolistic market coordination, but rather as a prerequisite to a firm's acquisition of a large share of the market. Thus it could be that large firms are more efficient (low costs) and hence are more profitable. The arguments behind the Demsetz-efficiency model could be explored by looking at how large firms come to establish dominance in their particular market, and what differences could be observed in the new environment. Some of the sources of this pro-cess include internal growth (expansion), mergers and acquisition of other lesser efficient firms. These events only attract public attention in so far as they reduce competition and efficiency in the industry (Skeoch, 1976). For instance, the principal factor cited to explain the decline in number of firms in the U.S food industry in the 1950s and 1960s was the elimination of small, inefficient-sized plants (Connor, 1979, pp. 229). According Chapter 3. EVIDENCE ON THE S-C-P RELATIONSHIP. 29 to Demsetz's approach, such events are welcome, if efficiency is enhanced with increas-ing firm size distribution. A similar argument underlines Canadian competition policy (Khemani, 1980, pp. 7; 1984, pp.43.). It may be easy to detect existence of high profitability in an industry. But to establish the causality (or lack of it) relationship between it and either market power or efficiency is a problem, as indicated by the lively debate occasioned by Demsetz's article. A sample of some of the empirical studies which back up the structure-performance hypotheses are reviewed below. 3.2 Literature Review. 3.2.1 Introduction. Since Bain's pioneering work on the structure-conduct-performance problem, appeared in 1951 (Relation of profit rate and industry concentration), a lot of interest has been focused on this subject. The new attempts have been done mainly to improve on Bain's basic model by considering multiple structural relationships. Among the reasons advo-cated for the new impetus are the many differences across countries and changes which have occured in the manufacturing sector and market, caused, in part, by emergence of new production and marketing organisations, such as the appearance of the large multi-product conglomerate, large and efficient chain-marketing networks and increased role of international trade in the last 40 years. Among the new factors which have been exam-ined and found to play important roles are capital intensity (Collins and Preston, 1966; McFetridge, 1973; Schmalensee, 1976; Parker and Connor, 1979;), import and export variables (Cowling and Waterson, 1976; Lyons, 1981; Rizvi and Ulm, 1982), product dif-ferentiation (advertising) and other entry barriers (Comanor and Wilson, 1967; Scherer, 1980), and geographical dispersion factors. Below is a review of some of these studies. Chapter 3. EVIDENCE ON THE S-C-P RELATIONSHIP. 30 3.2.2 Studies in U.S. and other Countries. Collins and Preston (1966) found a strong relationship between structural variables and performance in the U.S. food processing industry, using data for 32 industries in 1958. The variables they included in their basic model, including the level of seller concen-tration, capital output ratio, advertising and indexes for geographical dispersion and growth of demand were found to significantly explain observed inter-industry differences in profitability (indexed by profit-cost margins). In addition to domestic market structure variables, the role of foreign trade in prof-itability studies has also been investigated in several other studies. Among these is a study by Esposito and Esposito (1971) on 77 manufacturing industries (43 of these con-sumer goods industries and 34 producer goods industries) in the U.S. They showed that less restrictions on trade (and hence actual or potential foreign competition) encourages competitive pricing behavior in domestic industries. In industries where there is threat of actual or potential foreign entry, domestic firms exercise caution in their pricing de-cisions, and thus have to content with prices lower than what would obtain in a closed economy. They showed that import competition3 exerts a significant negative influence on industry profitability in the aggregate sample (77 industries), but it was insignificant in the producer goods and consumer goods sub-samples. Pagoulatos and Sorensen (1976) extended Esposito's work in international trade by considering the role of export opportunities and foreign direct investment. Using 1967 U.S data on 88 industries, the regression results for the traditional domestic market variables (seller concentration and product differentiation) and export competition supported their hypothesised positive significance. The same result was also found to exist between the variable introduced to capture the efffects of foreign direct investment4 on profit-cost 3Indexed by the ratio of imports to domestic value of shipments. Represented by a measure of multi-nationals' activities - i.e percentage foreign component of total Chapter 3. EVIDENCE ON THE S-C-P RELATIONSHIP. 31 margins. Although non-tariff barriers were found to exert significant positive influence on profitability, nominal tariff rates5 were not. This led them to conclude that perhaps the effects of tariff protection are more reflected in price levels (changes) but not necessarily on profit rates. There are many other similar studies done for the U.S. food processing industries, the most recent being by Rogers (1987). A major difference between this one and previous cases is that Rogers estimated the structure-profits relationship in consecutive census years (1954-1977). His main aim was to establish whether the relationship is stable during inflationary periods. Concentration was not statistically significant in the 1954-67 period, when prices were relatively stable. Thereafter, the size of the coefficient on concentration increased, and became significant. The effect of product differentiation 6 on price-cost was also positive. Based on these results, Rogers concluded that the structure-profitability relationship grew stronger and more significant over time, and is less affected by business cycles. Outside North America, Holtermann (1971) did a study of U.K. manufacturing, sim-ilar to the U.S. case studies but with a few innovations. In addition to the widely used profit-cost margin, various definitions of rate of return on assets and labour, and labour productivity growth, as measures of performance, were considered. Data for 113 indus-tries in 1963 rendered support to the study's hypothesised relationship between market power7 and barriers to entry8 and performance. The major finding in this study was a strong and positive relationship between total factor productivity and concentration. Lyons (1981) improved Holtermann's study by integrating foreign trade into a basic economic activity in the largest firms within the industry. 5 Nominal tariff rate was used as variable; and a dummy variable was introduced to capture non-tariff barriers. 6Proxied by media advertising-to sales ratio. 7Proxied by the 5-firm concentration ratio. 8 Measured by advertising to sales ratio, ratio of average employment by the first half of the largest firms, capital output ratio and rate of investment Chapter 3. EVIDENCE ON THE S-C-P RELATIONSHIP. 32 structure-performance model, and applied it to data for 118 U.K. manufacturing indus-tries. He found the variable for export intensity had a significant positive effect on profit margins. On the other hand, import competition (like entry of new firms) was found to lead to a decrease in profitability. The results on the impact of import competition in the U.K. data is consistent with the findings of Esposito and Esposito, and Pagoulatos and Sorensen's studies in the U.S. market. 3.2.3 Canadian Studies. In Canada, Jones, Laudadio and Percy (1973), in a study of 31 consumer good and 29 pro-ducer good industries, showed that different structural variables have different impacts on profits depending on whether the industry produces consumer or producer goods. Concentration and profit margins where found to be positively correlated when all the industries are looked at together, but the results differ for separate treatments. Other variables (foreign competition, growth of demand, economies of scale, regional concentra-tion and specialisation) were insignificant, with the exception of product differentiation9. But when each group was considered separately, the results were mixed. Regional con-centration, growth of demand and advertising were the only significant variables in the consumer goods sector (positive relationship). National concentration, advertising, for-eign competition, demand (negative) and specialization, were significant in the producer goods sector. Rizvi and Uhm (1982) went a step further and looked at data for 25 farm input and food processing industries in the 1970s, using profit-cost margins (PCM) and changes in consumer prices as indexes of performance. An important finding of their study was a negative, but insignificant, relationship between concentration and profit margins. The 9Indexed by advertising to sales ratio. Chapter 3. EVIDENCE ON THE S-C-P RELATIONSHIP. 33 specification using price change, like the PCM one, also yielded weak results. But for-eign ownership of manufacturing activity and income elasticity were, however, positively correlated to profit margins. De Silva's study (1971), like Rizvi and Uhm's, used changes in producer selling price as the depended variable, on 26 manufacturing industries' data for 1961-67. Concentration was found to play an insignificant role. The more recent study by Hazledine (1978), unlike the above cases, looked exclu-sively at data for 19 Canadian food processing industries for the period 1961-74. An additional innovation in this study was inclusion of 'surplus'10 as an alternative index of performance. Although a linear specification of his model yielded insignificant results between concentration and profit margins, a non linear specification (i.e. used CR4 and its square as variables) gave significant results on both PCM and 'surplus'. All the studies (reviewed above) have used aggregate industry level data which no doubt suppress intra-industry characteristics and differences. But others have gone a few steps further and looked at data at various levels of disaggregation, such as at the firm level [Imel and Helmberger, (1971); Dalton and Penn (1976), Rogers, (1978)] and at the product group level (Parker and Connor - 1979). 3.2.4 Firm Level and Product Group Studies. Connor and Parker used food processing data disaggregated into two categories (one for private label products and the other national brands), in an attempt to show the effect of market structure on different pricing practices by large and small firms. Private (or Own) brands were taken to approximate a competitive market regime, relative to national brand manufactures which are priced at a premium. By assuming away quality 10Defined as the ratio of an industry's profits to a weighted sum of capital stock, inventories and wage bill. Chapter 3. EVIDENCE ON THE S-C-P RELATIONSHIP. 34 differences between the two product groups (considered minimal and insignificant), any difference in their prices would approximate monopoly overcharge by national brand manufactures. Using this price difference11 on 1976 data for 41 product groups, they found a strong relationship existed between it and other variables (seller concentration, import competition, and advertising intensity - disaggregated into T.V advertising and advertising by the largest 200 food processing companies). Imel and Helmberger related direct after-tax company profit rates (as dependent vari-able) to firm-specific market structure variables, in addition to other variables common to an industry, for 99 U.S. food processing companies in the 1959-67 period. Concentration12 and various indexes for barriers to entry13 were found to be important explanatory vari-ables of variation in profit rates among companies. A similar approach to Imel and Helmberger's study was used by Rogers in 1978 (Con-nor, et al. 1985, Table D-2 pp. 335-336), but this time using before-tax company profit rates for 60 food processing companies during the the 1964-1970 period (which coincides with part of the Imel and Helmberger's study). There was a significant improvement in the results (including significance of concentration and product differentiation-related variables). Dalton and Penn looked at a 1950 sample data of 97 large U.S. food industries, employing rate of return on equity14 as a measure of firm profitability. Their study mainly sought to find out if the relationship between concentration and profitability reported in many previous studies is a continuous association. Their results established a critical level of concentration (45% for a 4-firm concentration and 60% for an 8-firm concentration), at and above which the concentration-profitability relationship assumes n I n place of the traditional profit/cost margin 1 2 measured by CR4, or the largest firm's market sales share/ share of the 4-largest firms 13advertising-to-sales ratio, expenditures on Research and Development-to-industry sales ratio. 14measured by the ratio of net income-after-taxes to owner's equity averaged over the period 1949-54. Chapter 3. EVIDENCE ON THE S-C-P RELATIONSHIP. 35 positive significance. This brief review of previous empirical studies reveals that much of the inter-industry variation in performance can be explained by factors related to market power, barriers to entry, and foreign trade and tariff protection. There are other similar studies whose results are close to the few examples cited above15. A closer look at the Canadian manufacturing sector is presented below. 15For a summary, see Connor and Parker, (1985), Table D-2 pp. 356-357. Chapter 4 The Canadian Manufacturing Sector. 4.1 Description and Trends. In this section, a brief analysis of the Canadian manufacturing sector between the 1970 and 1985 period is provided. The number of firms in manufacturing increased by 11.2% between 1970 and 1981. The number of plants grew over the years, from 31,928 in 1970 to 36,854 in 1985, a 15% increase (Table 3). But the percentage of all firms in manufacturing accounted for by the food and kindred sector was on the decline, from 17.2% in 1970 to 11.6% in 1981. By 1985, it reached an all time low of 9.7%. Employment in production related activities has been fairly stable in manufacturing. Total employment grew by 11.8% (Table 4). The share of the food and kindred sector of total manufacturing employment remained fairly constant over the years, at an average of 12.3%. In contrast, the wage bill grew more rapidly, at an average annual rate of 10.3%, compared to the growth rate of labourforce of 0.8%. The share of food and kindred sector of this total remained fairly stable, at 11.5%, over the years (Table 5). Expenditure on fuel and electricity increased by about 125%. This increase was most rapid between 1974 and 1978, a period dominated by high crude oil prices instigated by the OPEC1 cartel then. The food sector's share was fairly stable, at about 10% on average (Table 6). 1 Organization of Petroleum Exporting Countries. 36 Chapter 4. The Canadian Manufacturing Sector. 37 Expenditure on raw materials and supplies also experienced rapid growth. From a total of $ 25.7 billion in 1970, it increased to over $ 40 billion in 1985, a 55.6% increase (Table 7). This increase (for all manufacturing) is relatively higher than the 46.5% registered by the food and kindred sector alone during the same period. Real value of shipments in all manufacturing industries increased by 60.3%, from $ 46.4 billion in 1970 to $ 74.3 billion in 1985. Food and kindred sector grew at a relatively slower rate of 31.8%. The sector's average share of all manufacturing was 18%, but a gradual decline from a high of 19.8% in 1970 to an all time low of 16.3% in 1985 is notable (Table 8). Value added in all manufacturing increased by 43.1%, with the food and kindred sector experiencing a relatively slower growth rate of 22.9%. Its share of total manufacturing was fairly stable over the years, at an average level of 14.5% (Table 9). Therefore, compared to other sectors of the economy, the food, beverages and tobacco sector has grown at a slower rate, in terms of employment, value of sales and contribution to value added to processed goods. 4.2 The Food, Beverage and Tobacco Processing Sector. 4.2.1 Introduction. The food, beverages and tobacco processing sector plays an important role in the Cana-dian economy. During the 1970-85 period, it accounted for an average of 18% of total manufacturing sales and 14.5% of value added. The sector's real value of shipments in-creased from $ 7.5 billions in 1970 to over 10.2 billions in 1985, an increase of 36.3%. Its share of other aspects of production, such as employment, value added, exports and material inputs, have also remained important over the years. Chapter 4. The Canadian Manufacturing Sector. 38 4.2.2 Trends in other major Variables. Number of Firms and Establishments. The number of food, beverage and tobacco processing firms declined from 3022 in 1970 to 2809 in 1985, a 7% decrease (Table 2). But this trend was not uniform across the board. The number of firms increased in eight industries, declined in ten and remained unchanged in two. Among the most notable declines were in dairy processing, soft drinks, feeds and biscuit industries. Substantial increases occurred in wineries and the leaf tobacco industry. The number of plants in the sector decreased substantially, from 5805 in 1970 to 3557 in 1985, a decline of about 38.7%. This downward trend reached the lowest level in 1983, when there were only 3509. Like in firms, these changes affected industry groups differently, with some experienc-ing increases in plant numbers (Table 3). Out of 26 industries, 15 registered decreases. This was most marked in the dairy processing, cane and beet sugar, and feed industries. Elsewhere, some industries experienced remarkable increases. Notable here is the wine industry. Value of Shipments and Value Added. Aggregate real value of shipments increased from $9.17 billion in 1970 to about $12.09 bil-lion in 1985, an increase of over 31.8%. Among the industries which performed extremely well were vegetable oils (257%), frozen fruits and vegetables (166%) and the wine indus-try (98%). Some other industries experienced declines in their real value of shipments, such as the bakery industry, the leaf tobacco processing and the biscuits industries. Aggregate real Value added increased by about 22% during the period under review. The pattern of performance followed closely the one in value of shipments (Table 9), with vegetable oil, frozen fruits and vegetables and wine industries registering substantial Chapter 4. The Canadian Manufacturing Sector. 39 growth. Industry Concentration. Use of the degree of seller concentration has developed as one of the most popular indica-tors of market power in industry. And in Canada, like in many other countries, its level and trend forms an important input in evaluating industry anti-competitive behaviour, and in design of competition policy. Several indexes have been proposed to measure this factor, among which is the four-firm concentration ratio (CR4) and the Herfindahl index (H). The weighted average CR4 for the Canadian food and kindred sector has been on a general increasing trend during the period under review; averaging 60% (Table 10). From 57.6% in 1970, it increased to 61.2% in 1985. In contrast, the weighted average for all manufacturing was 53% in 1970, indicating a significant degree of concentration in the food and kindred sector. Among the three subsectors, the tobacco subsector is the most concentrated (average CR4 of 98.6%) followed by beverages (76.1%), with food processing trailing at 50.2%. In contrast, U.S. had a CR4 of 46.5% in 1977, compared to Canada's 63.8%. But what infomation does the magnitude of concentration convey? Scherer (1980) suggested a critical lower bound CR4 of 40%, above which exploitation of market power may effectively distort prices and bring payoffs to firms engaged in collusion. In Canada, average concentration ratios (CR4), range from as low as 26% in the feed industry to a high level of 99% in the tobacco products industry. Application of Scherer's criterion places 16 of the 20 industries2 in the Canadian sector in the upper limit, overwhelmingly suggesting that the potential for exercising market power exists. A similar deduction would also be reached using the 1980 SIC data for 1985, with 22 of the 26 industries 21970 SIC data. Chapter 4. The Canadian Manufacturing Sector. 40 having ratios of over 40%. In contrast, only 13 of the 26 U.S. industrial groups surpass the 40% mark. Other studies have proposed similar versions of Scherer's approach, mainly by defin-ing broad clusters of industry groups in the continuum between atomistic competition and monopoly. The most widely applied approach in the Canadian market, which was proposed by Rosenbluth (1957) and later adopted by the Canadian Department of Con-sumer and Corporate Affairs, groups industries into four broad categories. Concentration ratios higher than 75% would be considered very high and present the case for a potential 'tight' oligopoly. Between 50% and 75%, though still considered high, such an industry would be described as a oligopoly. Other industries with ratios lower than 50% but higher than 25% could qualify as possible cases of 'loose' oligopoly. Industries with ratios well below 25% are considered fairly competitive. In the 1970 SIC data, non of the 20 industries qualify to be considered atomistic (Table 11). Seven of these were in the 75-100% 'tight' oligopoly category, another seven were classified in the high concentration category and the remaining 6 as moderate. For the 1980 SIC, the proportionate distribution of the 26 industries remain fairly unchanged. 35% and 31% of the industries fall under the 'tight' oligopoly class and the high oligopoly category, respectively. Of the remainder, 8 are in the 'loose' oligopoly category, with only the feed industry qualifying as a potential competitive industry. There are other suggested classifications, two of which are briefly considered here3. Meehan and Duchesneau (173) estimated a critical lower bound 8-firm concentration of 70% at which the concentration-profit relationship becomes significant. However their suggested 55% at the 4-firm level yielded weak results. Dalton and Penn's study, though using a different specification of profitabilty (firm level rate of return on equity) from Meehan and and Duchesneau's came up with threshold levels of 45% and 60%, at the 3for a general review of these, see article by Dalton and Penn (1976), cited in chapter 3. Chapter 4. The Canadian Manufacturing Sector. 41 4-firm and 8-firm aggregation levels respectively. Therefore despite the variety in market classifications, the Canadian food, beverages and tobacco processing sector appeals to meet many of the criteria suggested which place market power within reach, other thighs equal. A brief description of the 26 industries is presented below. 4.3 Food, Beverages and Tobacco Intra-Industry Structure. 4.3.1 Meat and meat processing industry - SIC 1011. This industry comprises establishments primarily engaged in abattoir operations and meat packing. It is the largest 4-digit industry in the Canadian food and kindred sector, acounting for an average of 24% of value of shipments and 13% of all value added. Its importance can also be judged by its contribution to aggregate value of output, value added and purchase of inputs. In 1970, the industry processed over 600,000 tonnes of cattle, worth $740 million, and about the same volume of hogs valued at about $405 million. Currently, four firms hold a major share of the industry 4 . The meat processing industry is characterised by a large and growing number of firms and pants, and low concentration. Holloway and Goddard (1988, pp. 207) have shown that large firms tend to be more efficient than small ones, especially if they produce both fresh and processed meat. Also attempts at price leadership by Canada Packers in the early 1970s were ineffective (Green,1980, pp. 100). Indeed the small size of the domestic market relative to the U.S. and modest meat trade restrictions between the two countries suggest the ernomous role played by foreign trade in Canadian price determination5 (Higginson et. al. 1988.). Other more recent studies have shown that 4Canada Packers, Burns Meat, Gainers and Intercontinental 5An exception was the countervailing duty of $0,053 per lb imposed on Canadian processed pork exports by U.S. in April 1985 in protest against Canada's subsidies to her producers, but revoked in Chapter 4. The Canadian Manufacturing Sector. 42 Canadian meat product prices are largely determined in the U.S market, and are on average equal to the U.S. price adjusted for differences in foreign exchange and transfer costs (Coleman and Meilke, 1988 pp.402). Thus meat processing can be described as a highly competitive industry. 4.3.2 Poultry Processing - SIC 1012 Poultry processing comprises establishments engaged in slaughtering, eviscerating and packing or canning poultry; chickens and turkeys being the most important (85% of all poultry processed). The combined volume of chickens and turkey processed increased from 622,000 tonnes in 1970 to 688,000 in 1984, valued at $205 and $285 miUions, re-spectively. An important feature of this industry is the strong influence exercised by input (poul-try) suppliers through the widely practised production quota system, reiforced by high tariff protection (Hazledine, 1989, pp. 36). This factors have important implications on the cost structure (high cost inputs) of the processors and their competitiveness in the world market. Given the large number of firms and establishments involved in the sector and the low CR4 (36.8%), low entry barriers, in addition to existing competition from large U.S. manufactures, it would be safe to describe the poultry industry as highly competitive 4.3.3 Fish Product Industry - SIC 1021 Included in this industry are establishments whose principal activity is the canning, salting, freezing and pickling of fish as well as producing fish meal, seal oils, and seaweed products. The industry is concentrated in two major raw fish producing regions: the East Coast groundfish processing industry and the B.C salmon canning industry. Julyi Chapter 4. The Canadian Manufacturing Sector. 43 Regionally, the Pacific region dominates the fish canning subsector (84%) while the Eastern region produces 76% of total fresh fish, 84% of frozen fish, almost all cured fish, and 89% and 87% offish meal and marine oil, respectively6. The industry is characterised by a relatively small number of large integrated firms and a much larger number of smaller operations, and differentiated cost and profitability structure (with large firms more profitable). Over 65% of value of Canadian processsed fish products is destined for the export market, in addition to exports of raw and semi-processed fish. The U.S., which meets only 10% of its demand from domestic sources, provides the biggest market for Canadian fish, and thus exerts tremendous pressure on prices, both at wholesale and retail level. Therefore major movements in U.S. prices are subsequently transmitted back and forth between the two markets, regardless of supply demand balances in Canada7. Declining raw fish supply, caused by overfishing by foreign fleets (from Japan, Taiwan and Korea) and local fishermen, is one of the major problems facing the industry in the 1980s, especially in the Atlantic region. The dominant firms (Fishery Products International Ltd. and Clearwater Fine Foods Ltd.) have witnessed rapid drops in raw fish supply, leading to fish plant closures and layoffs. Despite these problems, new firms are still setting up, thus compounding the already low plant capacity utilisation8 (55%). Low and declining market shares, and dependency on international markets, in addition to the stiff competition for raw materials places the industry among the competitive category. 6Food Prices Review Board, Fish and Fish Products Industry, 1975. 7Food Prices Review Board, 1975. 8The Financial Post, June, 12 1989. Chapter 4. The Canadian Manufacturing Sector. 44 4.3.4 Fruit and Vegetable Canners and Preservers - SIC 1031 This industry comprises establishments primarily engaged in processing fruits and vegeta-bles. Important products of the industry are canned or processed fruits and vegetables, vegetable and fruit juices, soups and pickles Because of the high proportion of fresh produce imported from the U.S., fruit and vegetable price movements in Canada reflect to a substantial degree the corresponding pattern of U.S. prices. This factor, in addition to seasonal factors tend to dominate prices in both markets 9 . The large number of firms and strong competition from soft drinks in the industry's juices market and low concentration levels (average CR4 of 39.7%) would suggest this industry is highly competitive. 4.3.5 Frozen Fruit and Vegetable Processing Industry - SIC 1032 This industry constitutes establishments engaged in processing and freezing of fruits and vegetables, fruit juice concentrates and french fried potatoes. Its activities are closely related to those of the above one (SIC 1031) in most aspects, except for its small size and high growth potential. The number of firms involved has fluctuated around 30. Due to increasing preference for fresh produce around the year, the level of activities of this industry have been growing rapidly over the recent past. Value of sales jumped from $72.1 million in 1970 to over $191 million in 1985 (166%). Value added grew even more rapidly, by 201% during the same period. The industry's frozen fruit subsector is dominated by two firms10 which have interests in other soft drinks industries in Canada and U.S. Stiff competition among the big players 9Food Prices Review Board - September 1974: Food price trends in Canada and U.S. A U.S. - Canada Comparison 1970-74. 10Tropicana Products, a Subsidiary of Seagram - Montreal, and Minute Maid, a Subsidiary of Coca-Cola company. Chapter 4. The Canadian Manufacturing Sector. 45 for dominance of the market and protection of their market shares has been on the increase11. Unlike its counterpart above, concentration has been rising, achieving an average CR4 of 60.9%. This factor alone would tempt one to place the industry among the class of oligopolistic industries. But low barriers to entry, power of distribution chains and competition from generic producers and imports strongly play down any potential market power, leading to moderate competition among sellers of branded goods. 4.3.6 The Dairy processing Industry - SIC 1041, 1049. This industry includes establishments primarily engaged in processing raw milk and cream. Since 1982, the industry has been redefined to distinquish establishments pri-marily engaged in fluid milk (SIC 1041), from those engaged in other dairy activities (SIC 1049). Important features of this industry is its regional distribution and raw milk quota system, operated according to raw material source and product market, and non-tariff trade barriers (Hazledine, 1989.). Most of the secondary processing plants are also owned and controlled by the primary producers (farmers groups). Competition is high, among dairy processing firms and other non-alcoholic bever-ages. A large, but declining, number of firms and establishments is also involved. To boost sales various provincial milk marketing boards have, in the recent past, engaged in promotional activities. Studies have shown that increasing expenditure on fluid milk promotion would increase consumption and sales revenues net of advertising costs, es-pecially through attracting consumers from other non-alcoholic beverages (Goddard and Tielu, 1988, pp. 261). Low size distribution of firms and entry barriers would suggest that the industry is competitive. "Financial Post, June, 13 1989. Chapter 4. The Canadian Manufacturing Sector. 46 4.3.7 Flour and Breakfast Cereals Products-SIC 1051, 1052. This industry comprises establishments engaged in milling wheat and other cereal grains, blending flour, and processing cereal grains into cereal breakfast preparations. On revision of the SIC in 1980, the industry was grouped into cereal grain flour (1051), and prepared breakfast cereals (1052). Although the breakfast cereals industry is highly concentrated, product heterogeneity, stiff non-price competition (especially advertising) among local producers and imports, mainly from the U.S; substantially reduce the po-tential market power of firms to a moderate level. On the other hand, profit rates and entry barriers are quite low in the flour milling industry, puting it among the competitive category. 4.3.8 The Feed Industry - SIC 1053 This industry comprises establishments primarily engaged in producing balanced feeds and premixes or feed concentrates for poultry, hogs, cattle and pets. Other products include animal and vegetable proteins, vitamins and antibiotics. The industry is closely linked to the grain flour industry, from where most of its raw materials originate. The large number of firms involved, low concentration and barriers to entry suggest the industry is competitive. 4.3.9 Vegetable Oil mills - SIC 1061 This industry comprises establishments primarily engaged in manufacturing vegetable oils. Important raw materials are soybean, and flaxseed and rapeseed ('Canola') which has recently emerged as the most prominent. Some of the leading firms are Canada Packers Ltd; Proctor and Camble Co; Fine Foods, Kraft, and Stardard Brands Ltd. High tariff protection rates (10% on crude oils and 17% on refined oils) enables Canadian Chapter 4. The Canadian Manufacturing Sector. 47 firms to earn larger processing margins than their U.S. counterparts 1 2 . The future of this industry is bright, with its product having gradually emerged as the main substitute for animal oil and fat products, of which the popularity has been on the decline due to health concerns. Despite high seller concentration levels (average CR4 of 72.7%) and a small number of firms, other factors serve to reduce or enhance the industry's market power potential. First, the capital intensive nature of oil processing posses a potential barrier to entry. Similarly, the ban on margarine imports (which accounts for about 40% of edible oil products) is another source of barrier to entry (Rigaux, 1976, pp. 54-69). On the other hand the major impact on oil processing comes from the industry's heavy reliance on soybeans imports from the U.S. (about 35% of its needs). Thus any major changes in the larger U.S. soybean market is easily felt in other oils, leading Canadian prices to strongly reflect the U.S. price structure. Therefore it would be more appropriate to categorise this industry as competitive. 4.3.10 Biscuit Manufactures - SIC 1071 This industry comprises establishments which manufacture as their principal products biscuits, crackers, and similar 'dry' bakery products. Concentration and profit levels are quite high which, in addition to a relatively small number of firms and stiff non-price competition (advertising), would suggest that the industry is highly oligopolistic. 4.3.11 Bread and other Bakery products Industry - SIC 1072 This industry covers establishments engaged in manufacturing bread, cakes and other related perishable bakery products. 12Regaux, L. R: The Canadian Edible Oils Industry. Food Prices Review Board. 1976 Chapter 4. The Canadian Manufacturing Sector. 48 Over the years, the number of firms has declined enormously. The number of large plants decreased by over 75%, from 1921 in 1970 to 473 in 1985. One of the main sources of this trend is the proliferation of small bakeries selling their produce across the counter, whose output is not recorded in this industry. Unlike in the U.S. market the Canadian bakery industry is less affected by interna-tional wheat price changes (and hence flour prices) since it benefits from a cheaper wheat flour input13. Despite low seller concentration, a large number of firms and low barriers to entry (widely accessible technology), individual firms can still earn reasonable profit rates by producing specialty goods which sell at a premium price (Hazledine, 1989.). 4.3.12 Confectionery Manufacturers - SIC 1082, 1083. This industry consists of establishments engaged in producing candies of all types. In 1980, the industry was re- classified into two: chewing gum (SIC 1082) and sugar and chocolate confectionary (SIC 1083). This industry is among the most highly concentrated (CR4 of 92%). Through a series of acquisitions in the 1980s, three firms have become the key players, accounting for well over 90% of the domestic market14. Despite stiff competition (mainly advertising), the enormous market share of a few firms suggests a potentially 'tight' oligopolistic industry. 4.3.13 Cane and Beet sugar Processing Industry - SIC 1081. This industry comprises firms primarily engaged in processing raw cane and beet sugar into granulated sugar, liquid sugar and sucrose. Some of the leading firms in this indus-try are Redpath, Atlantic Sugar, B.C. sugar, Quebec Sugar, St. Lawrence Sugar, and Westcane Sugar Refineries. "resulting from Canadian wheat subsidy. Food Price Review Board-september 1974. 14William Neilson, which purchased Caramilk and Crunchie from Cadbury Schweppes; Hershey Canada Inc. which acquired Effem Ltd. from Nabisco; and Rowntree Ltd.). Chapter 4. The Canadian Manufacturing Sector. 49 Canada depends to a large extend on imported raw cane sugar, with minimal tariffs imposed. In turn, cane sugar refineries price their products on basis of the London Daily Price, by adding a processing margin that covers costs and returns on capital. Over the years, Redpath has emerged as the acknowledged domestic price leader on whose daily price quotations other firms follow15. Under the price leadership system and substantial capital intensity (as a barrier to entry), the structure of the Canadian Sugar processing industry could be viewed as potentially oligopolistic. 4.3.14 Miscellaneous Food Industries-SIC 1091, 1092, 1093, 1099. This industry includes firms primarily engaged in processing foods not elsewhere clas-sified. Since 1970, it has been defined to include establishments manufacturing baking powder, flavouring extracts, macaroni, starch, yeast, spaghetti, 'health foods' and other food specialities, roasting coffee, blending and packaging teas. The industry was redefined under the 1980 SIC into several four digit level industries. Tea and coffee industry are grouped under SIC 1091, dry pasta products as 1092, potato chips, pretzel and popcorn as 1093, and malt and malt flour industry as 1094. Other industries not elsewhere classified are under SIC 1099. Although the heterogeneous nature of this industry prior to 1982 precludes any useful unified analysis, concentration levels in the first three industries in the new SIC are quite high, suggesting a potentially oligopolistic market. 4.3.15 Soft Drinks Industry - S.I.C. 1111 This industry includes establishments primarily engaged in manufacturing non-alcoholic beverages and carbonated mineral waters, or concentrates and syrups for manufacture of carbonated beverages. 15Food Prices Review Board: Sugar Prices II - The Canadian Sugar Refining Industry. 1975. Chapter 4. The Canadian Manufacturing Sector. 50 Consolidation of minor plants into large efficient establishments has led to a sharp decline in small firms16. The number of firms fell by 54.2%, from 330 in 1970 to 151 in 1985. Larger firms fair better in profits than small ones. The market is dominated by two firms; Coca-Cola Co. and Pepsicola Co., the parent company (Atlanta) of the former accounting for 35% of world soft drinks sold17. Although non-price competition (as partially indicated by intense advertising cam-paigns) and concentrations are high (54.2% in 1970 increasing, to 67.2% in 1985), dif-ferentiated cost efficiency and profitability by firm size places the industry among the competititive category, but with heterogeneity. 4.3.16 Distillery products - SIC 1121 This industry comprises establishments primarily engaged in the manufacture of potable spirits such as whisky, brandy, rum and gin. Although the industry is characterised by high concentration (average CR4 of 98.2%) and a relatively small number of firms, intense competition from imported spirits plays down the potential market power of the industry. 4.3.17 Brewery Industry - SIC 1131 This industry comprises establishments primarily engaged in manufacture of beer, in-cluding ale, porter, stout and other malt liquors. The industry was dominated by three firms (Labbat, Molson and Carling O'Keefe), which achieved their dominant production share (94%) through a series of mergers be-ginning in the the 1930s (Clarke, 1989). Labbat controls 42% of the domestic market while Molson and Carling O'Keefe take up another 52%. 16production and delivery equipment is more efficiently utilized in a large establishment 17Blue Book of Canadian Business, 1985. Chapter 4. The Canadian Manufacturing Sector. 51 The structure of the Canadian beer industry provides a classic example of an oligopolis-tic industry. Concentration levels run high, in addition to various provincial liquor control restrictions and high tariff rates. The CR4 increased from 94% in 1970 to a peak of 99.1% in 1979, and then declined gradually to 97.7% in 1985. Indeed with the conclusion of the proposed Molson - Carling O'Keefe merger, the industry's concentration has reached an even higher level (Clarke, 1989). 4.3.18 Wineries - S.I.C. 1141 This industry comprises establishments primarily engaged in producing wines and cider with alcoholic content. There are two categories of firms in this industry, distinquished by size and ownership. On one side are the small family-operated firms, which specialise in vintage wines, and on the other the large firms which, in addition to engaging in primary production of their own label wine, also bottle imported wines. The market shares (average CR4 of 70.7%) were on the upward trend in the early 1970s, from an all time low of 63.9% in 1972, to a high of 77% in 1976. But differences in cost structure and profitability between large and small firms suggests that firms still claim some market power through specialization. 4.3.19 Leaf Tobacco, Tobacco Products Industries-SIC 1211, 1221 These industries include firms primarily engaged in processing raw tobacco, and manu-facturing cigarettes, cigars, tobacco and snuff. The industries' activities are concentrated in the two major raw material source provinces: Ontario and Quebec. The number of firms has remained quite stable over the years. The industries are dominated by three companies; Imperial Tobacco Ltd., Rothmans Inc. and RJR-Macdonald Inc., which accounts for about 55%, 28% and 17% of the Chapter 4. The Canadian Manufacturing Sector. 52 domestic cigarette market, respectively18. Production activities showed an upward trend in the 1970s, especially sales and value added. But the recent concerted anti-smoking campaign prompted by health concerns and higher taxes seem to be swaying the market, as indicated by decline in sales, especially in the 1980s. High and increasing market shares (CR4 of 90%) indicate a potential case for a 'tight' oligopolistic market. 18 Globe and Mail, July 26, 1989. pp. B9. Chapter 5 Database and Regression model. 5.1 Data Base The Standard Industrial Classification (SIC) used in the census of manufacturing activ-ities has been revised twice during the 1970-1985 period. Data and industry definitions for the 1970-1981 sub-period are based on the 1970 SIC version, constituting 20 indus-tries, while the 1980 SIC comprises 26 industries (Table 1). Most of the data used for deriving variables is obtained from various annual census of manufactures publications by Statistics Canada. Profit-cost margins (PCM) and market growth of demand (GROW) variables are constructed from data available in the 1982-85 period (Table 12). PCM is the value of shipments, less production costs (labour, raw materials and supplies, and energy costs), weighted by industry value of shipments. The industry growth variable is defined as the average annual growth rate of industry value of shipments during the 1982-85 period. The Canada/U.S. industry price index was derived from primary product ouput-value data for 1982. In each Canadian industry, product groups were identified and their output-value data matched to those of equivalent U.S. industries. This data was used to estimate product group prices. To aggregate to the industry level, the derived Canada/U.S. product price ratios, each weighted by its share of the respective Canadian industry shipments, were summed up to obtain unadjusted industry price indexes. Fi-nally, Canadian sales tax and transportation expenses were removed, to obtain adjusted 53 Chapter 5. Database and Regression model. 54 Canada/U.S. price indexes (PR). The detailed proceedure is shown below. PRi = shCijiPcj/Pu^KVSci - TXi)/VSa]/1.2l, where shdj is product 'j's share of Canada's value of shipments for industry 'i'; PCJ is Canada's derived price for product 'j' and PUJ is the corresponding derived product price for the U.S. An exchange rate of 1.21 was used to convert U.S.S to Can.S. VSci and TXi are Canada's value of shipments and sales tax and transport expenses, for industry 'i', respectively, and'm' is the number of products in industry 'i'. The primary data and derivation of PR are given in appendix A. Canadian concentration ratios (CR4) were obtained by taking the simple average of annual concentration ratios during the 1981-85 period. The foreign trade related variables (TRF, XPEN and MPEN) were derived from 1982 data. Tariff protection (TRF) is the total industry duty on imports, weighted by total value of dutiable imports. U.S. tariff protection (USTRF) is the total tariff on imports from the U.S., weighted by total value of dutiable imports from the U.S. Export competition (XPEN) is the value of all industry exports, weighted by the value of shipments. Import competition (MPEN) is the total value of all industry imports, weighted by the total value of domestic demand, which includes domestically produced goods and imports. Relative input price indexes (RPI) were constructed from 1982 raw materials quantity-value data, using the following weighing approach: RPI = shK * RPK + shL * RPL + shE * RPE + shM * RPM, where shK, shL, shE and shM are the shares of total industry costs accounted for by expenditures on capital services, labour, energy and raw materials, respectively. RPK, RPL, RPE and RPM are the relative Canada/U S. price ratios of capital services, labour services, energy, and raw materials, respectively. The price ratios are weighted sums of individual input prices. For instance, RPM was derived as follows: Chapter 5. Database and Regression model. 55 RPM =Z?SiRPi, where Si and RP{ are the share of total raw material costs and price of input 'i', respectively. There is no adequate Canadian advertising data. In its place, U.S. advertising (US-ADS) was used as a proxy for Canadian advertising. However, due to differences in SICs between the two countries, a shipment-weighted average of 1977 U.S. advertising-to-sales ratios was used to construct USADS, as shown below: USADSi = YZiADSj * VSil £? VSj], where ADSj and VSj are the advertising-to-sales ratio, and value of shipments for U.S. industry 'j', and 'i' is the approximate Canadian SIC. The data for constructing USCR4 is obtained from the 1982 U.S. Census of Manufac-tures. A Box-Cox transformation of U.S. concentration was used to aggregate the U.S. data to the Canadian SIC level, as shown below. USCRAi = [.53((-2.625 + .498(£- 5 3 - l)/.53) + .574(A;53 - l)/.53))]1/-53, where A{ is the U.S. Number of enterprises-weighted CR4, and B{ is the U.S. value of shipments-weighted CR4, equivalent to the Canadian SIC 'i'. The regional dummy variable (RG) was constructed such that industries deemed to possess regional markets are assigned a value of one, and zero otherwise. Four indus-tries (SICs 1041, 1072, and 1111) were classified as regional, on the basis of either the perishable or bulky nature of their products. Although the basic sample comprises 26 industries, some were dropped for various reasons. In estimating the PCM model, the Leaf tobacco processing industry (SIC 1211) was omitted because of inconsistencies noticed in deriving the dependent variable. Sim-ilarly, the two tobacco industries and the distillery industry were excluded in estimating the PR model, because no adequate sales tax and transport costs data1 were available xSuch data is classified as confidential. Chapter 5. Database and Regression model. 56 to construct adjusted price indexes. A summary of the database is provided in Tables 12 and 13. 5.2 Model Specification and defination of variables 5.2.1 Regression Model This section specifies a model of the determinants of industry performance. The vari-ables used are also discussed, in addition to a priori expectations of their estimated coefficients. The general model proposed to explain the association of performance and market structure variables is: Yi = a + ftSd + Zk OkBi + £, I'M + £ m u>mDi + ipRPh + <j>USCR4i + e{ where Y{ = [PCMi, or PRi] defines one of the measures of industry 'i's performance, and: PCMi=(value of shipments-wages-Other costs)/Value of shipments; PRi — Canada/ U.S. output price index for industry 'i'. SCi = [CRAi or Hi) defines the level of seller concentration where: CRAi — The industry's share of total output accounted for by the largest four firms in industry i; and Hi is the Herfindhal index of concentration. B = [ADSi, KORi] are barriers to entry-related variables where: AD Si=(Industry's Advertising expenditure)/Industry shipments; K0Ri=IndustTy value of fixed assets /Industry shipments; F = [XPENi,MPENi,Trfi,USTrfi] where: XPEN,= Value of domestic exports/Total Value of an industry's shipments; Chapter 5. Database and Regression model. 57 MPENi = Value of imports/Value of domestic demand2; Trfi = Ratio of total import duty collected on imports to total value of dutiable imports, from all sources; UStrfi = Ratio of total import duty collected on imports from the U.S. to value of dutiable imports from the U.S. D = [Growi, RGi], defines demand related variables, where: Grow i = Et=i[(5t+ 1-5,)/5 t]/4 and S is the value of shipments of industry 'i' in year t; RGi= A dummy variable, taking a value of one if an industry is perceived as regional, and a value of 0 if otherwise. RPIi is the relative Canada-U.S. industry input price index. a, 8, 0, V>, <*>, f and cb are regression parameters, and e is an error term. 5.2.2 Variables Performance:-Variations in profit rates (proxied by P C M or profit-cost margins) are the traditional measure of inter-industry differences market power, as noted in section 3.1.1. The price difference between Canadian and U.S., or any other country's products would, partially, provide a relative measure of competitiveness and efficiency between industries. Taking the U.S. price to approximate a competitive market, it is proposed that the lower the-Canada/U.S. difference, the more competitive the relevant industry. 2Here, domestic demand is taken to include consumption of both domestically produced goods and imports. Chapter 5. Database and Regression model. 58 Seller Concentration (CR4 or H):-The level of seller concentration (as measured by either CR4 or H) measures the pos-sibility for collusion among competitors, and hence will act as a proxy of the degree of monopoly power. It is proposed that as concentration increases, coordination of joint profit maximization arrangements and pricing (among large firms) become easier and profits and prices are expected to be higher. However if an inverse relationship holds be-tween seller concentration and price levels, then an argument that concentration increases industry efficiency could be advanced. Barriers to Competition:-(1) Advertising Intensity:-Product differentiation has been identified as the major barrier to competition in the food and beverage processing sector, and it is assumed to be created and maintained by advertising. Advertising is assumed to serve either two roles. It may serve as persuasive and hence act as a tool for increasing market power, by increasing product differentiation. In so doing, it would be geared towards making demand for a given product less elastic. Alternatively, it could be perceived as informative. In the latter role, lack of adequate product information is seen as a barrier to competition and advertising is assumed to break this barrier and thus increase competition. The two roles will have opposite effects on performance, with the latter serving to increase competition and hence lower price levels, while the former entrenchs entry barriers and therefore increases market power (and hence prices and profitability). If advertising is viewed purely as persuasive, then the coefficient on advertising in a profit-structure regression will be greater than one. A negative coefficient is expected for C h a p t e r 5. D a t a b a s e and Regression m o d e l . 59 the informative role. The total effect will be determined by the relative importance of these two. If the two effects exert about equally the same influence, then the coefficient on advertising would be close to zero. A comparison of the statistical relationship between advertising and profitability and prices could be used to make inferences about efficiency. If the advertising variable comes up with a positive sign in a structure-profit equation while a negative outcome emerges in a structure-pricing equation, then advertising could be perceived as an efficiency-enhancing tool. (2) Capital Intensity (KOR):-This variable provides control, or adjustments, for differences in capital intensity among industries, resulting from different technological feasibilities or requirements. It is found necessary to account for this because the available data from which profit margins are derived usually do not isolate returns on fixed assets. A high capital-output ratio implies more funds are tied up in the production process, and hence profit rates have (it is assumed) to be high to include a normal return on investments and depreciation. Foreign Trade. (1) Export Competition (XPEN):-This variable captures relative competitiveness of the domestic industry and the rest of the world. More exports could signify efficiency in an industry, thus precipitating a positive relationship between it and profitability. On the other hand, the domestic market may indeed be relatively more profitable3. Therefore, if a proportionately larger share of an industry's output is exported, a negative relationship between this variable and performance may obtain. This possibility is considered more likely due to Canada's 3This may, for instance, be due to a price edge provided to indigeneous producers by trade protection policies and other 'home base' advantages. Chapter 5. Database and Regression model. 60 heavy reliance on export markets. (2) Import Competition (MPEN):-As a factor of performance, imports are perceived to play two roles. First, import competition is introduced as a correction for domestic concentration. Other things equal, the effect of this variable on performance would be the opposite of that of seller concen-tration (negative). Secondly, more imports could be indicative of a relatively lucrative industry, and hence a profitable domestic market. Threat of more imports would be a message to do-mestic firms to restrain prices at relatively lower prices than otherwise. This way, foreign competition provides an incentive for domestic firms to be more efficient, suggesting a positive relationship between profits and imports. Therefore, it is not possible to predict, a priori, the sign the import penetration variable will take in a regression equation. (3) Tariff Protection (Trf and USTrf):-Tariff related variables are introduced to measure the degree of protection from foreign competition enjoyed by domestic firms. Possible impact of tariffs on imports from the U.S. is considered to be of particular importance to Canada, due to the large proportion of Canada's trade accounted for by imports from the U.S. An industry may be accorded tariff protection either because of its inefficiency relative to foreign firms, or for other nationalistic goals. In the first case, it is possible for such firms to sustain relatively higher production costs and survive, though still earn low profit margins. Alternatively, tariff protection will simply increase barriers to entry, and profitability. A negative correlation between tariff rates and industry profitability is likely in the former case, while a positive outcome is predicted for the later. In this model, the positive effect is perceived to outweigh the negative effects and thus suggest a positive relationship. Chapter 5. Database and Regression model. 61 Demand Variables. (1) Industry growth (Grow):-This variable (which measures short-term industry growth) is included to control for above-normal profit rates at times when changes in demand outstrip growth in production capacity. It is assumed that if an industry is operating at, or near, full capacity, rapid growth in its market will affect its price levels and profit rates positively, in the short run. (2) Geographical Market Dispersion or Segmentation (RG):-This variable is considered useful for adjusting national concentration, especially if the market is segmented into a clear regional supply and demand pattern. Concentration data is available at the national level, and in cases where an industry's market is clearly local or regional, such aggregate indexes may underestimate the significance of the concentration variable. This is the case in industries producing perishable and (or) bulky products4. Regional concentration is expected to reinforce the impact of the national concentration variable. On the other hand, geographical isolation may limit an industry's access to a larger market. Therefore isolation may influence profitabilty negatively. U.S. Market Structure Variables - U S C R 4 . In addition to domestic market variables, industry concentration in the U.S. (USCR4) is another variable perceived to affect relative prices between the two countries. Concen-tration in the U.S. may increase efficiency in its domestic market and hence affect U.S. prices negatively. However if increases in U.S. concentration increase market power to its domestic firms, then prices will likely be affected positively. If we assume that Canadian 4Examples include milk, soft drinks and bread. Chapter 5. Database and Regression model. 62 prices are higher, then increases in U.S. prices will lower the difference between the two. Hence the sign of the coefficient in the PR model is indeterminate, a priori. Input prices - RPI. Changes in production costs are perceived to influence output prices positively. High production costs (either as a result of industry inefficiency or input costs) generally reduce an industry's range over which it can lower prices, and still make profits. A positive relationship is anticipated between RPI and PR. Chapter 6 M O D E L E S T I M A T I O N and R E S U L T S . 6.1 Estimation Approach. The principal regression tool used in this study is Ordinary Least Squares. In addition to linear specification of all explanatory variables in both models, a quadratic form of CR4 was tried in equation lb. Tables 14 and 15 show the results of multiple regression for both models. 6.2 The Profit-Cost-Margins Model. This section discusses the results that emerge from the PCM model estimation. Six regression equations were estimated for this model, two of which are for average margins (PCMavg), and the rest for annual sub-periods (1982-85). Equation la. includes all the variables proposed to influence industry profitability. Seller concentration (CR4), advertising (USADS) and tariff protection (TRF) emerged with positively signed and significant coefficient estimates (at 2.5%, 0.5% and 5% level, respectively). Export competition came out with a negative coefficient, and was signif-icant at the 5% level. Import competition (MPEN), industry growth (GROW) and the regional dummy variable (RG) were found insignificant. The variables specified in this equation explain 71% of the observed variation in industry profit-cost margins (R2)-An estimate of the model with a non-linear specification of seller concentration yielded equation lb. On the basis of statistical significance of the largest number of variables, 63 Chapter 6. MODEL ESTIMATION and RESULTS. 64 this equation yielded the best fit for the PCM model. MPEN, GROW and RG emerged significant (at 1%, 10% and 10%, respectively.). The other variables found significant in equation la. were also significant in this equation. Altogether, these variables explain about 73% of the variation in profit margins. The R2 adjusted for degrees of freedom (R2) increased from 0.58 to 0.60. U.S. specific tariff protection (USTRF) was also considered, in place of general tariffs, and the results were similar to those of equation la. Another feature of the estimates is the similarity in results for both the average PCM model (PCMAVG) and the annual sub-periods (equations 3a., 3b., 3c, and 3d.). Analysis of the results show little annual variation in the relationship. This leads one to conclude that the structure-profit relationship is reasonably stable, at least as attested by the similarity in the results of the 4-year period sub-models, reported in Table 15. 6.3 The Pricing Equation. The results of the pricing model estimates are also presented in Table 14, as equations 2a. and 2b. In addition to all the the explanatory variables used in the PCM model, U.S. seller concentration (USCR4) and relative Canada/U.S. input prices (RPI) were also included in this model. Equation 2a. includes all the proposed explanatory variables. Canadian seller con-centration (CR4), advertising (USADS) and export competition (XPEN) came out with negatively signed and significant coefficients (the former two at 10% and the latter at 2.5% levels, respectively). TRF, MPEN and RPI had positively signed and significant coefficients (at 0.5%, 10% and 2.5% levels, respectively). The other variables were not significant (including USCR4, GROW, and RG). Altogether the variables considered in this equation explain about 58% of the observed variation in relative prices between Chapter 6. MODEL ESTIMATION and RESULTS. 65 Canada and the U.S., with a R2 adjusted for degrees of freedom equal to 0.29. The model was reestimated, using only the variables found significant in 2a. Similar statistical results (in terms of significance and signs of variables) were obtained. Although the unadjusted R2 drops slightly to 0.57, the fit of the regression, corrected for degrees of freedom, rises to 0.41 from 0.29. 6.4 Evaluation of the two Model Estimates, with Reference to Market Power and Industry Efficiency. In this section, the relative performance of each variable in both models is evaluated, and the results compared and contrasted. The statistical significance, magnitude and the signs of the estimated coefficients forms the basis for the comparative analysis of the results. Table 16 reports the statistical test of the difference between coefficients of the two model estimates. The coefficient on CR4 was positively signed in the PCM model (equation la.), while it was negative in the PR estimate. Using the size of the two coefficients, a t-test of the difference between the coefficients of the two models reveal that the influence of seller concentration on prices and profitability is significantly different (Table 16). The negative coefficient on CR4 in the PR equations suggest that seller concentration has a decreasing effect on Canadian price levels, relative to those of the U.S. On the other hand, a positive coefficient in the PCM equation leads to the conclusion that increases in concentration would lead to increases in profitability. The two results, combined, suggest that increases in seller concentration do not give market power to industries to enhance their profit maximization goal through price increases, but rather act as a source of market competition. And in the absence of tangible evidence of market power in pricing behaviour of the sector, industry efficiency can be advanced as a possible source Chapter 6. MODEL ESTIMATION and RESULTS. 66 of profitability in Canadian food processing industries. A similar conclusion to that on CR4 can also be drawn regarding the advertising variable (USADS). By contrasting USADS's negative coefficient in the PR equations to its positive outcome in the PCM model, inferences about market competition can be made. The results imply that increases in advertising expenditure would play an informative role, rather than a persuasive one, and hence promote price competition. One can only assume that the positive advertising-profitabity statistical relationship is not generated by price increases, but possibly by increase in sales. The above proposition is based on the assumption that USADS can be used as a proxy for actual Canadian advertising intensities. However, if we drop this assumption, a different interpretation of the results can be made. Increases in U.S. advertising will be perceived to promote price competition in Canadian industries, and hence the negative coefficient on USADS in the PR model. Similarly, changes in U.S. advertising may precipitate some positive efficiency effect on Canadian industries. If prices are destined to fall with increases in USADS, then Canadian industries would feel pressured to increase their efficiency if they are to withstand imminent onslaught into their domestic market. It is also possible that U.S. advertising has an increeasing effect on the U.S. price level. The TRF variable was consistently significant and positively signed in both model estimates. Its coefficient was also significantly larger in the PR model than in the PCM model, at the 0.5% level of significance (Table 16). An important conclusion of this result is that tariffs simply appear to promote further increases in price differences between Canadian processed products and those of other countries. This way, increases in tariffs would be considered as a barrier to price competition. Similar statistical results (to those for TRF) were also obtained for the U.S. specific tariff variable (USTRF). This outcome supports the hypotheses of the important role Chapter 6. MODEL ESTIMATION and RESULTS. 67 played by Canada-U.S. trade policies, and their significant influence on domestic indus-try performance. Imposition of higher tariff rates on imports from the U.S. would tend to allow Canadian industries greater freedom in setting their local prices, and earn relatively higher profits. However, the fact that Canadian prices will increase by a higher magni-tude than profitability points to the possibility of tariff-induced inefficiency creeping into protected industries. Industry growth (GROW) was not significant in the PR model, although it was in the PCM model (equation lb.). These outcomes suggest that changes in demand do not necessarily have any pronounced influence on pricing behaviour. However profitability would tend to be higher in industries with higher rates of growth in consumer demand. The coefficient on the RG variable was positive in the PCM model, but negative and insignificant in the PR equations. This result rules out market power (in pricing) in isolated markets. Hence profitability in industries with regional market characteristics can not be traced to higher price levels. Export competition (XPEN) has a negative and significant influence on both prof-itability and relative prices. However, the absolute size of the coefficient in the PR model is statistically larger than that in the PCM model (at least at the 5% level of significance). This suggests that changes in the level of exports have stronger depressing effects on domestic prices than on profitability. The negative signs on the coefficients may be interpreted in terms of trade rationalisation. Is it the case that firms in the export market are constrained to set prices in both domestic and foreign markets at fairly equal levels? In special cases where foreign markets are more competitive than the domestic base, increases in the share of exports of total production will tend to pull down the aggregate industry price. Consequently, aggregate unit profit rates will also tend to be lower where relatively competitive and low priced foreign markets claim a bigger share of total industry output. Chapter 6. MODEL ESTIMATION and RESULTS. 68 The import competition variable (MPEN) emerged significantly positive in PCM's equation lb. and the PR estimates. This result (positive relationship) is against a priori expectations. Furthermore, the size of this coefficient was significantly larger in the PR model than in the PCM equations. However, a negative relationship between imports and domestic price levels and profitability presumes that the causality runs from imports to prices (and profitability). A reversal of this relationship, such that imports become the dependent variable, will require a different interpretation of the results. In other words, industries with higher prices and profit rates will attract more imports, and hence a positive relationship is anticipated. Therefore, the positive relationship found in this study may be a result of simultaneity problem between the independent (MPEN) and the dependent variables (PCM and PR). The variable introduced to capture the influence of relative input prices (RPI) on output pricing (PR) was consistently significant and larger that one, by about 0.13 in equation 2a. and 0.21 in equation 2b. This result implies that a given increase in input prices will cause a relatively larger increase in output prices. For instance, a 10% increase in input prices could lead to a 13% increase in output prices. Although U.S. seller concentration (USCR4) was proposed as a possible explanatory variable of relative prices, its coefficient was statistically insignificant. This may im-ply that concentration in the U.S. market has no apparent influence on U.S. pricing behaviour. 6.5 Wrap-up of the Results and Comparison with Other Studies. A summary of the results of this study is presented in Table 17. Two equations from the current study and a sample of other related studies is presentd in Table 18. Although these studies considered other variables, in addition to some in the current study, several Chapter 6. MODEL ESTIMATION and RESULTS. 69 similarities can be noted between them. The role of seller concentration is emphasized by its inclusion in almost all profitability studies. It is reported statistically significant and positive in the current study and the two U.S. case studies. However, it is not in the Canadian case study by Rizvi and Uhm. Collins and Preston had also estimated a critical lower bound CR4 of about 20%, on and above which the influence of seller concentration begins to manifest itself as a source of market power. In the current study, a critical CR4 of 51% was estimated (from equation lb.), far much higher than Collins and Preston's for the U.S. sector. Parker and Connor's private-manufactured label price differential equation is com-pared to the PR model of the current study. While concentration appears to exert a positive influence on U.S. relative prices of manufactured prices, the opposite outcome was arrived at in the Canadian PR model. The statistical results on the advertising variable is another area of similarity between the current profitability model and the U..S. cases. In both cases, it is established that advertising does have a positive role to play in boosting profitability. However the relationship differs for the pricing models. While it appears to affect prices negatively, and hence promote price competition in the Canadian sector, it emerges as a powerful barrier to competition in the U.S. Pdiff model. Another possible area of comparison between the current study and the U.S. cases is the performance of industry growth (GROW). It was reported significant and positively signed in Connor and Parker's PCM model as well as in the current one. However, it appears to play an insignificant role in pricing behaviour, in both countries. There is also a major difference in the results of the import competition variable (MPEN) in the pricing models. While imports showed a negative effect on U.S. manufactured food prices, the opposite relationship appears to exist in the Canadian market. Another area of comparison is in the difference in the influence of geographical location Chapter 6. MODEL ESTIMATION and RESULTS. 70 factors (RG), or regional concentration on industry profitability. In the U.S., RG exerts a negative influence, while a positive relationship exists in the Canadian sector. In summary, the explanatory power (as indicated by the R2) of the variables considered in the current study lies within a reasonable range of other similar studies. Chapter 7 S U M M A R Y and CONCLUSIONS, and LIMITATIONS. 7.1 Summary and Conclusions. Industry Competition policies are for the most part designed to promote and maintain competition and fair business practices, and, if necessary, check the adverse economic effects associated with anticompetitive firm behaviour. This is important, especially if such activities involve active price-fixing conspiracies and inefficiency. Most industry performance studies have generally been undertaken to generate an information base upon which effective industry policies can be build, and their performance evaluated. From the public interest point of view, industry performance is evaluated in terms of how and at what costs and prices industries deliver goods and services. Efficiency is assumed to be achieved if this objective is met at the lowest cost and prices. Firms pocket the difference between the two, as profit. The current study looked at what role market structure possibly plays in explaining the observed variation in profitability and prices across industries. These factors can be later looked into as possible public policy tools for effecting changes in the market. The discussion in the foregoing chapter (6) suggests that the performance of the Canadian food, beverages and tobacco processing sector can be partially explained by market factors peculiar to its operating environment. Three broad factors identified to provide support to the structure-performance hypotheses are domestic industry concen-tration, foreign trade competition, and the state and trend in domestic market demand. 71 Chapter 7. SUMMARY and CONCLUSIONS, and LIMITATIONS. 72 In particular, factors such as seller concentration, advertising, tariff protection and ex-port competition emerged as the most influential determinants of industry profit-cost margins and relative prices. Perhaps the most important result of this study regards the statistical relationship between seller concentration and performance. In most previous studies, identification of concentration as a source of market power has been more or less unanimous. However, the results of this study suggest that an alternative to this traditional view of the relationship is necessary. Its reported negative influence on relative prices points to a possible link between it, price competition and efficiency. Similarly, advertising has been viewed as a barrier to entry and competition in an industry, and capable of allowing incumbent firms to set and maintain prices higher than competitive. However, the current study suggests the opposite. Advertising appears to have a strong decreasing effect on prices, and hence could be viewed as promoting price competition. Hence the association of high profitability with large advertising expenditures may not be resulting from higher prices, but perhaps from higher aggregate sales. This way, advertising may be perceived as serving to expand total market demand, without any increase in price levels. Indeed, advertising appears to force industries to lower prices. Relative input costs are another area of concern in evaluating industry performance. Preliminary analysis of input prices data imply that the majority of Canadian industries face relatively higher production costs than their U.S. counterparts. This study confirmed our earlier hypotheses that output prices may be adversely affected by production costs. Furthermore charges in output prices in response to changes in input prices may exceed the later. And by extension, if output prices increase by more than it is necessary to compensate for higher production costs, then it is possible that a positive relationship exists between RPI and profitability. Chapter 7. SUMMARY and CONCLUSIONS, and LIMITATIONS. 73 Another implication of this study relates to the concept of performance and its mea-surement. In addition to the traditional profit performance criteria, due attention should be paid to pricing behaviour. This additional dimension is considered important, for it is in pricing where market power is first manifested, at least in the eyes of the con-sumer. As noted in section 3.1.2, the mere existence of profits in an industry need not automatically imply exploitation of market power. Given this possibility, relative pricing behaviour provides an alternative choice variable, which does not condemn profitability outright by ignoring the role of efficiency. In case of need for public corrective intervention, governments are well equiped to influence some of the market structure factors identified above. These include tariffs and foreign trade. For instance, since there is strong evidence from the study that tariffs on imports appear to allow domestic firms to set prices higher than normal, changes in that area may be an appealing corrective policy option. 7.2 Limitations and Recommentations for Further Research. Several market factors considered important in the structure-performance model were not incorporated in this study, mainly due to lack of adequate data. These include capital assets and changes in consumer income and tastes. Another area of interest is the role of existing government regulations on trade, both at the provincial and the national levels. 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Table 1: Canada: Industry Definitions; 1980 SIC SIC Industry 1011 Meat & meat processing. 1012 Poultry processing. 1021 Fish processing. 1031 Fruit &; vegetable proc. &: Canning. 1032 Frozen fruit &z vegetable processors. 1041 Fluid milk processing. 1049 Other dairy products 1051 Cereal grain flour 1052 Prepared breakfast cereals. 1053 Feeds industry. 1061 Vegetable oil mills. 1071 Biscuit industry. 1072 Bread & other bakery products 1081 Cane & beet sugar industry. 1082 Chewing gum industry. 1083 Sugar & chocolate confectienery. 1091 Coffee and tea industry. 1092 Dry pasta products industry. 1093 Potato chip, pretzel & popcorn. 1099 Other food products industries 1111 Soft drinks manufacturers. 1121 Distillery products industry. 1131 Brewery products industry. 1141 Wineries. 1211 Leaf tobacco products industry. 1221 Tobacco products industry. Source: Statistics Canada; Census of Manufactures; Various publications. 79 Table 2: Number of Firms - 1970-85. % Growth SIC 1970 1980 1985 (1970-85) 1011 404 489 486 20.3 1012 86 70 68 -20.9 1021 249 283 299 20.1 1031 184 154 153 -16.8 1032 33 27 29 -12.1 1041* 612 281 82 -1049 - - 161 -1051* 33 32 16 -1052 - - 16 -1053 633 488 430 -32.1 1061 9 8 9 0 1071 31 22 21 -32.3 1072 - - 412 -3.3 1081 7 8 5 -25.6 1082 - - 6 -1083* 132 100 92 -1091 - - 22 -1092 - - 16 -1093 - - 31 -1099* 227 245 224 -1111 330 189 151 -54.2 1121 13 17 16 23.1 1131 9 8 11 22.2 1141 13 19 30 130.8 1211 6 7 8 33.3 1221 11 10 11 0.0 Total 3022 2457 2901 -0.4 * For 1970 and 1980, the 1970 SIC is used in defining industries. Source: Stat. Canada. Census of Manufactures; cat. 31-422. 80 Table 3: Number of Establishments - 1970-85. %Growth SIC 1970 1975 1980 1985 (1970-85) 1011 453 477 547 535 18.1 1012 102 88 90 96 -5.9 1021 344 325 376 390 13.4 1031 238 208 233 187 -21.3 1032 34 38 33 35 2.9 1041* 880 519 456 164 -1049 - - - 230 -1051* 51 48 49 39 -• 1052 - - - 19 -1053 789 643 609 554 -29.8 1061 10 8 10 11 10.0 1071 42 40 33 31 -26.2 1072 1921 1599 1487 473 -75.4 1081 14 15 13 9 -35.7 1082 - - - 7 -1083* 129 93 109 92 -1091 - - - 32 -1092 - - - 22 -1093 - - - 33 -1099* 273 245 312 269 -1111 395 288 238 187 -52.7 1121 27 31 33 30 11.1 1131 42 44 41 41 -2.4 1141 22 31 32 46 109.1 1211 10 10 9 10 0.0 1221 19 17 16 15 -21.1 Total(FBT) 5805 4767 4726 3557 -38.7 " AU Man. 31928 30100 35495 36854 15.4 FBT/A11 Man. 18.2 15.8 13.3 9.7 -* For 1970, 1975 & 1980, the 1970 SIC is used in defining industries Source: Stat. Canada, cat. 31-422. 81 Table 4: Production Labour - 1970-85. % Growth SIC 1970 1975 1980 1985 1970-85 1011 22182 24621 26610 24099 8.6 1012 6489 7022 8708 9325 43.7 1021 16782 14223 23065 23744 41.5 1031 12014 11726 9716 8896 -26.0 1032 2463 3295 3429 4219 71.3 1041 14083 13780. 14097 6283 -1049 • • - - 8237 -1051* 3278 3268 3322 1829 -1052 - - - 1961 -1053 5359 5991 5979 5942 9.0 1061 524 503 905 771 47.1 1071 5275 5467 4748 4595 -12.9 1072 19129 17533 17971 14381 -24.8 1081 2276 2048 1847 5487 -1982 - - 855 -1083* 7954 6865 7411 6342 -1091 - - - 1426 -1092 - - - 2132 -1093 - - - 880 -1099* 10735 11508 14003 8773 -1111 6071 6432 6133 5956 -1.9 1121 3136 3192 2876 2123 -32.3 1131 5324 7011 7419 8571 61.0 1141 522 606 743 795 52.3 1211 1257 1069 675 387 -69.2 1221 6064 5471 4732 3751 -38.1 Total(FBT) 150917 151631 164389 156809 3.9 All Manuf. 1167063 1271786 1346187 1305159 11.8 FBT/ALMAN(%) 12.9 11.9 12.2 12.0 -* 1970, 1975 & 1980 figures refer to the 1970 SIC. Source: Census of Manufactures -Various Publications. Stat. Canada. 82 Table 5: Production Labour Wages: 1970-85. - Million $. % Growth SIC 1970 1975 1980 1985 (1970-85) 1011 153 195 211 184 19.8 1012 28 39 54 58 107.6 1021 60 77 138 111 84.6 1031 55 64 60 56 2.0 1032 9 17 17 21 129.8 1041* 82 99 114 53 -1049 - - - 63 -1051* 23 26 28 17 -1052 - - - 18 -1053 29 39 43 40 36.8 1061 3 4 8 8 147.8 1071 25 34 30 30 19.2 1072 95 106 114 90 -5.8 1081 16 17 15 14 -10.8 1082 - - - 6 -1083* 37 37 42 34 -1091 - - 11 -1092 - - - 13 -1093 - - - 6 -1099* 62 76 95 61 -1111 33 43 46 46 36.5 1121 26 28 27 22 -15.4 1131 45 70 80 89 99.0 1141 3 5 6 7 102.6 1211 6 6 4 3 -50.7 1221 44 45 42 41 -5.9 Total(FBT) 835 1027 1174 1101 31.9 All Man. 7232 8879 10221 10015 38.5 FBT/ALMAN(%) 11.5 11.6 11.5 11.0 -* 1970, 1975 & 1980 figures refer to the 1970 SIC. Source: Census of Manufact Various Publications. Stat. Canada. 83 Table 6: Costs of Fuel and Electricity - 1970-85. - ('000 $) % Growth SIC 1970 1975 1980 1985 (1970-85) 1011 11391 14930 22132 22736 99.6 1012 2412 3019 5153 6282 160.4 1021 5723 7335 13558 12256 114.2 1031 4912 5443 7547 8604 75.2 1032 1354 3047 5401 5364 296.2 1041 21943 21655 26146 12817 -1049* - - - 15705 -1051* 2620 2526 3954 2856 -1052 - - - 2507 -1053 7288 7185 11643 15357 110.7 1061 1428 1946 4413 5318 272.4 1071 1308 1563 2132 2500 91.1 1072 11091 9424 11618 14107 27.2 1081 3096 4554 6458 6619 113.8 1082 - - - 491 -1083* 2124 2302 3354 3221 -1091 - - - 1712 -1092 - - - 4126 -1093 - - - 687 -1099* 8387 11516 20124 30377 262.2 1111 6284 6394 7336 8061 28.3 1121 5062 6336 9961 8795 73.7 1131 4728 7288 10210 12272 159.6 1141 380 498 736 844 122.1 1211 571 574 565 568 -0.5 1221 1471 1557 2288 2889 96.4 Total(FBT) 103573 118092 174729 200546 93.6 All Manuf. 903264 1082634. 1811936 2032330 125.0 FBT/ALMAN(%) 11.5 10.9 9.6 9.9 -*-1970, 1975 & 1980 figures refer to the 1970 SIC. Source: Census of Manufact Various Publications. Stat. Canada. 84 Table 7: Cost of Raw Materials and Supplies - 1970-85 (million $). SIC 1970 1975 1980 1985 % Growth (1970-85) 1011 1684 1754 2070 2171 28.9 1012 226 233 268 361 59.7 1021 232 190 339 385 65.4 1031 288 207 240 366 27.1 1032 42 47 60 106 152.0 1041* 999 1147 1192 1488 48.9 1049 - - - 872 -1051* 217 165 210 235 -1052 - - - 199 -1053 457 422 578 733 60.5 1061 103 104 201 317 208.8 1071 65 59 58 81 25.4 1072 229 156 171 223 -2.7 1081 133 248 201 91 -31.6 1082 - - - 22 -1083* 122 98 127 139 -1091 - - - 170 -1092 - - - 62 -1093 - - - 30 -1099* 442 394 541 536 -1111 161 165 181 373 131.6 1121 117 82 89 111 -5.3 1131 104 91 109 212 104.3 1141 23 19 28 43 91.8 1211 166 109 82 143 -13.8 1221 181 100 120 181 0.1 Total(FBT) 5991 5789 6865 8779 46.5 All Manuf. 25700 30690 40675 40002 55.6 FBT/ALMAN(%) 23.3 18.9 16.9 21.9 * For 1970, 1975 & 1980, the 1970 SIC is used in defining industries. Source: Census of Manufactures - Various Publications. Stat. Canada. 85 Table 8: Value of Shipments - 1970-85 (Million $). % Growth SIC 1970 1975 1980 1985 (1970-85) 1011 2061 2382 2878 3010 46.0 1012 284 276 411 492 73.4 1021 355 313 450 481 35.5 1031 472 489 520 523 10.7 1032 72 118 161 192 165.8 1041* 1369 1519 1657 749 -1049 - - - 955 -1051* 306 308 319 221 -1052 - - - 129 -1053 586. 727 930 1012 72.8 1061 123 141 309 439 257.0 1071 137 141 125 105 -23.5 1072 503 460 444 369 -26.8 1081 204 222 166 171 -16.6 1982 - - 49 -1083* 240 220 253 155 -1091 - - - 228 -1092 - - - 143 -1093 - - - 42 -1099* 782 901 1057 753 -1111 358 350 354 433 21.1 1121 344 425 433 374 8.7 1131 399 403 444 444 11.2 1141 42 57 81 83 98.4 1211 151 180 147 111 -26.5 1221 376 420 482 416 10.6 Total(FBT) 9166 10051 11620 12078 31.8 All Manuf. 46381 54943 64908 74345 60.3 FBT/ALMAN(%) 19.8 18.3 17.9 16.3 -* 1970, 1975 & 1980 figures refer to the 1970 SIC. Source: Census of Manufact Various Publications. Stat. Canada. 86 Table 9: Value Added - 1970-85 (Million $). % Growth SIC 1970 1975 1980 1985 (1970-85) 1011 363 443 451 499 37.6 1012 58 65 93 127 120.1 1021 126 111 147 176 39.4 1031 182 191 198 224 23.1 "1032 29 49 73 86 201.1 1041* 346 335 361 224 -1049 - - - 217 -1051* 87 86 88 46 -1052 - - - 75 -1053 122 130 167 217 77.2 1061 19 15 36 46 145.1 1071 71 65 62 55 -22.0 1072 263 233 230 201 -23.2 1081 70 31 27 67 -3.8 1082 - - - 35 -1083* 119 103 122 35 -1091 - - - 90 -1092 - - - 90 -1093 - - - 17 -1099* 338 332 413 300 -1111 192 156 158 181 -5.8 1121 247 284 269 220 -11.0 1131 293 268 310 304 3.9 1141 22 32 42 43 94.3 1211 16 17 12 4 -74.3 1221 191 244 278 255 33.9 Total(FBT) 3152 3191 3538 3875 22.9 AU Man. 20048 22434 25434 28684 43.1 FBT/ALMAN(%) 15.7 14.2 13.9 13.5 -* 1970, 1975 & 1980 figures refer to the 1970 SIC. Source: Census of Manufact Various Publications. Stat. Canada. 87 Table 10: Canadian Four-Firm Concentration Ratios. 1970-85. (%). Average SIC 1970 1976 1980 1983 1985 1981-5 1011 54.8 49.5 42.4 40.6 35.9 38.8 1012 37.0 39.0 36.3 37.4 35.9 36.2 1021 39.8 49.0 44.0 46.0 47.1 46.0 1031 41.7 39.3 39.0 38.8 40.7 39.9 1032 - - 72.7 63.2 60.9 65.3 1041 - - - 41.9 48.5 46.2 1049 - - - 48.1 47.7 47.6 1051 - - - 79.7 78.5 78.8 1052 - - - - 72.9 72.6 1053 29.5 27.2 25.7 26.3 23.1 24.6 1061 78.5 - 71.4 76.5 68.2 70.7 1071 68.1 73.6 79.9 83.8 78.8 80.6 1072 31.6 31.9 33.5 38.6 45.0 41.9 1081 - - 92.0 - - 92.0 1082 - - - - - -1083 - - - 70.2 64.7 67.5 1091 - - - 65.9 70.3 68.9 1092 - - - 88.3 88.9 88.4 1093 - - - 88.0 - 88.0 1099 33.7 37.8 33.8 35.4 33.3 34.6 1111 54.5 61.2 61.4 64.4 67.2 65.0 1121 86.5 78.2 74.9 75.5 77.0 75.8 1131 94.0 - 99.0 98.2 97.7 98.2 1141 64.4 77.7 72.0 68.7 65.6 69.2 1211 - - 97.4 97.2 - 97.3 1221 97.2 98.4 99.6 99.5 99.4 99.5 Avrg.(Food) 46.7 44.2 48.0 56.9 55.3 -Avrg.Bever. 74.8 72.3 76.8 76.7 76.8 -FBT 57.6 54.9 58.5 62.5 61.2 -Source: Census of Manufactures; Statistics Canada, cat. 31-401. 88 Table 11: Industry Classification by Concentration. Description of No. No. Avrg. CR4 Concentration 1970 (%) 1985 (%) 1970-85 (%) 75-100 Very High:'Tight' Oligopoly 7 35 9 35 9 35 50-75 High: Oligopoly 7 35 8 31 8 31 25-50 Moderate:'Loose' Oligopoly 6 30 8 31 9 35 Below 25 'Low': Atomistic - - 1 4 - -Total 20 - 26 - 26 -Source: Table 10. 89 Table 12: Database: PCM, PR and RPI. SIC PCM82 PCM83 PCM84 PCM85 PCMavrg PR RPI 1011 8.37 10.01 10.72 9.60 9.68 107.00 1.051 1012 13.40 13.04 12.26 13.86 13.14 160.80 1.291 1021 17.64 18.31 17.64 17.04 17.66 104.20 1.145 1031 29.10 33.57 31.50 31.89 31.52 168.90 1.304 1032 30.07 34.29 35.19 36.27 33.96 100.60 0.958 1041 18.38 19.49 20.33 23.92 20.53 136.50 1.036 1049 15.25 15.63 13.69 16.93 15.38 108.30 1.122 1051 14.76 15.98 13.22 14.48 14.61 124.00 1.199 1052 45.69 47.20 44.30 45.71 45.72 65.54 1.015 1053 14.25 14.76 14.35 16.81 15.Q4 98.28 1.029 1061 4.16 1.81 6.66 7.79 5.11 100.70 1.185 1071 35.06 36.53 35.51 34.27 35.35 87.32 1.072 1072 34.41 35.88 36.70 35.42 35.60 97.67 1.024 1081 21.27 27.93 28.70 30.08 27.00 90.84 0.805 1082 56.63 59.38 59.65 59.89 58.89 106.00 1.045 1083 38.72 39.95 41.15 37.02 39.21 111.60 1.272 1091 34.71 35.83 34.00 35.51 35.01 95.8 1.062 1092 46.83 49.71 53.96 54.46 51.24 118.30 1.117 1093 34.14 32.28 29.63 28.14 31.05 96.12 1.130 1099 30.62 31.71 30.19 33.40 31.48 111.90 1.220 1111 36.30 34.51 34.70 33.45 34.74 86.37 1.053 1121 48.60 52.32 49.57 51.58 50.52 180.52 1.195 1131 56.27 56.67 56.88 54.69 56.13 140.20 0.951 1141 42.16 40.25 42.73 44.40 42.38 172.60 1.234 1211 -9.26 -4.58 -15.79 41.72 3.02 79.84 0.858 1221 48.14 50.44 51.51 51.13 50.51 78.37 1.071 Mean 30.93 112.22 1.090 PR and RPI are the 1982 Canada/U.S. output price and input price indexes; respec-tively. PCM is the price-cost margin, for 1982 through to 1985. PCMavrg is the average price-cost margin: 1982-85. Source: Stat. Canada; Census of Manufactures. Various Publications; U.S. Census of Manufactures, 1982. 90 Table 13: Database: Market Structure Variables. SIC CR4 MPEN XPEN TRF USTRF GROW RG USCR4 USADS - 1981-5 1982 1982 1982 1982 1982-5 1977 1977 1011 38.8 5.1 13.0 2.7 2.1 1.40 0 17.89 0.24 1012 36.2 2.9 0.3 8.8 8.9 8.93 0 14.02 0.14 1021 46.0 33.4 79.1 9.9 7.4 5.42 0 19.52 0.57 1031 39.9 22.2 4.6 13.0 11.4 5.95 0 29.25 1.21 1032 65.3 32.9 16.2 6.1 5.5 7.19 0 23.91 1.71 1041 46.2 0.0 0.0 15.9 16.2 7.88 1 11.65 0.36 1049 47.6 3.5 9.0 3.1 5.6 5.09 0 22.57 0.54 1051 78.8 2.5 16.9 3.2 2.9 1.81 0 35.04 0.76 1052 72.6 7.6 2.5 9.5 9.6 4.53 . 0 61.95 11.57 1053 24.6 2.6 7.1 5.9 5.9 3.00 0 18.45 1.57 1061 70.7 22.0 21.0 12.4 12.1 11.14 0 42.36 0.77 1071 80.6 6.8 5.9 7.1 8.0 5.05 0 59.00 1.25 1072 41.9 1.8 3.3 11.6 12.1 0.76 1 34.00 0.85 1081 92.0 33.7 9.2 5.6 4.3 -8.48 0 46.31 0.14 1082 68.5 0.8 8.6 16.9 18.1 9.14 0 95.00 11.89 1083 67.5 20.4 6.3 14.0 15.3 6.39 0 34.75 2.03 1091 68.9 39.9 0.7 1.4 1.7 2.96 0 44.00 2.80 1092 88.4 2.9 26.3 10.7 10.4 -2.59 0 42.00 4.22 1093 88.0 7.3 9.7 5.6 7.0 13.64 0 58.00 2.16 1099 34.6 0.0 4.0 6.0 4.9 9.63 0 28.96 0.51 1111 65.0 2.4 0.6 12.7 13.1 10.73 1 11.10 2.83 1121 75.8 25.4 42.8 66.9 73.2 1.03 0 69.56 8.62 1131 98.2 0.9 7.9 39.4 39.2 6.02 0 77.00 3.41 1141 69.2 46.5 0.5 5.9 7.8 5.34 0 51.00 4.99 1211 97.2 4.6 30.8 9.9 9.9 1.71 0 68.00 0.00 1221 99.5 3.1 1.1 35.7 39.3 3.73 0 69.56 6.26 Mean 65.5 12.7 12.6 13.1 13.5 15.75 - 40.82 2.74 The variables are defined in chapter 5.2.1. Source: Industrial Org. & Concentration in Manufacturing, mining & Logging, cat 31-422; Other Census of Manufactures publica-tions. 91 Table 14: Regression Results: Average PCM & PR Equations. Eqtn. la. lb. 2a. 2b. Dep. PCMavg PCMavg PR PR Const. 5.918 30.958 -11.838 -23.413 (0.876) (1.736) (0.230) (0.504) CR4 0.226 -0.814 -0.375 -0.265 (2.514) (1.300) (1.512) (1.254) CRA2 0.008 (1.752) USCR4 0.188 (0.547) USADS 2.318 2.744 -2.468 -1.629 (3.734) (3.901) (1.358) (1.410) TRF 0.233 0.137 1.834 1.894 (2.006) (1.363) (3.332) (4.170) XPEN -0.152 -0.116 -0.444 -0.418 (1.923) (1.872) (2.643) (2.235) MPEN 0.096 0.225 0.632 0.646 (0.976) (2.838) (1.681) (1.805) GROW 0.398 0.612 0.133 (0.777) (1.397) (0.117) RG 4.228 8.842 -5.537 (0.771) (1.502) (0.502) RPI 1.130 1.209 (2.573) (3.253) R2 0.71 0.73 0.58 0.57 R2 0.58 0.60 0.29 0.41 F 5.806 5.500 2.019 3.548 Sample 25 25 23 23 t-statistics are in parentheses. 92 Table 15: Regression Results: Annual PCM-Structure Equations. Eqtn. 3a. 3b. 3c 3d. Dep. PCM82 PCM3 PCM4 PCM5 Cont. 5.614 7.570 3.883 6.602 (0.897) (1.061) (0.566) (0.939) CR4 0.222 0.215 0.252 0.214 (2.655) (2.302) (2.682) (2.287) USADS 2.334 2.392 2.340 2.307 (3.922) (3.754) (3.415) (3.787) TRF 0.217 0.242 0.236 0.239 (1.877) (2.075) (1.849) (2.140) RG 4.405 3.599 4.763 4.158 (0.821) (0.654) (0.798) (0.774) GROW 0.391 0.241 0.477 0.482 (0.797) (0.446) (0.907) (0.925) XPEN -0.149 -0.147 -0.150 -0.164 (1.791) (1.768) (1.825) (2.183) MPEN 0.068 0.076 0.112 0.128 (0.692) (0.734) (1.093) (1.303) R2 0.71 0.69 0.69 0.71 R2 0.59 0.56 0.57 0.59 F 5.866 5.299 5.531 6.008 Sample 25 25 25 25 t-statistics in parentheses. 93 Table 16: Statistical t-test for Ha: A{ — B{. Eqtn. Eqtn. In dep. la. 2a. Calc. Var. Ai Bi t a CR4 0.226 -0.375 -3.401 0.5 USADS 2.318 -2.468 3.727 0.5 TRF 0.233 1.834 4.296 0.25 XPEN -0.152 -0.444 2.325 2.5 MPEN 0.096 0.632 2.074 2.5 GROW 0.398 0.133 0.314 -RG 4.228 -5.537 - -Ai and Bi are the estimated coefficients of the PCM and the PR model; respectively, a is the attained level of significance. The degrees of freedom are 30. 94 Table .17: Summary of the Regression Results. PCM MODEL (lb.) PR MODEL (2a.) Independent Expected Result Signif- Expected Result Signif-Variable Sign Sign icant ? Sign sign icant ? CR4 + + Yes ± - Yes USCR4 * * * ± No USADS + + Yes ± - Yes TRF + + Yes + + Yes XPEN ± - Yes ± - Yes MPEN - + Yes - + Yes GROW + + Yes + + No RG + + Yes + - No RPI * * * + + Yes tests on the coefficients are at the 10% level of significance. * Not used 95 96 Table 18: Results of Other Structure-Performance Studies. Author Collins& Parker & Rizvi Parker& Current Current Preston Connor & Uhm Connor Study Study Period 1958 1972 1971-77 1976 1982-85 1982 Dep. PCM PCM PCM Pdiff. PCMavg PR CR4 -0.27 0.19 -0.825 0.630 -0.814 -0.375 (1.45) (3.49) (.692) (2.443) (1.300) (1.512) cm2 .007 - - -0.005 0.008 -(3.75) (2.443) (1.752) USCR4 - - - - - n.s ADS - 3.70 - 0.909 2.744 -2.468 (3.64) (1.626) (3.901) (1.358) ADS2 - -0.168 - - - -(1.80) TVADS - n.s - 17.194 - -(2.941) 200ADS - - - 0.179 - -(2.665) MES - ns - - - -KOR 0.24 0.232 - - - -(3.68) (5.97) Lnsize - - - -2.426 - -(2.510) Log(firms) - - - -2.038 - -(2.238) TRF - - - - 0.137 1.834 (1.363) (3.332) RG -0.121 -0.085 - n.s 8.842 n.s (4.62) (3.07) (1.502) GROW - n.s - 6.824 0.612 n.s (1.624) (1.397) XPEN - - - - -0.116 -0.444 (1.872) (2.643) MPEN - - - -17.362 0.225 0.632 (2.156) (2.838) (1.681) FOR - - 0.146 - - -(1.99) IE - - 0.116 - - -(2.28) RPI - - - - - 1.130 (2.573) R2 0.8 0.77 d.377 0.72 0.73 0.58 Sample 32 41 20 41 25 23 t-statistics in parentheses; Pdiff:% private label-manufactured brand price difference ; IE:Income elasticity; FOR:foreign ownership; n.s not significant, & '-' not used. Appendix A. PRIMARY OUTPUT VALUE AND (WANT!TV DATA FOR DERIVING THE CANADA/U.S. PRICE INOEK (PRI. Food, Beverages and Tobacco P rocess ing - 1982-C A N A D A I U. S. ft. Value Pc Height ! Value Pu SIC Unit Quant i ty Ct n i l . C t (shCI '.SIC INDUSTRY Quant i t y USt a i l . USt s h C K P c / P u ! M . 1011 S l augh te r i ng I Neat P rocesso r s Beef, hanging f r e s h , c h i l l e d or f rozen 1000 kg 507I9B 1442.4 2B43.66 0.240 Bee f - b l o c l r e a d y , f r e s h , c h i l l e d or f rozen • 249716 B84.7 3542.64 0.147 Ground beef I Hu<iburger*steakettes • 68331 220.4 3201.79 0.037 Fork • 83S84B 2062.B 2454.12 0.343 Lard • 50464 50.6 1002.03 0.009 Mutton I lanb • 6306 27.0 4279.14 0.004 Ed i b l e talloH • 29497 29.0 984.15 0.005 Par i b e l l i e s i h a« s - p i c k l e d , d r y s a l t e d , c u r ed 1000 kg 2693 10.3 3835.33 0.002 Hans - snoVed * p i c n i c hass • 76579 2B9.6 3781.57 0.048 Bacon - uns l t c ed • 5023 16.7 3327.54 0.003 Bacon - s l i c e d • 63573 232.1 3450.59 0.039 Sausage t s i s i 1ar cased products • 1B2533 613.7 3362.14 0.102 Canned neat • 39985 134.4 3340.B8 0.022 Tota l 6013.7 2011 Heat pack ing p l a n t s Hhote Carcass beef 4943300 10397.1 2103.27 0.324 P r i i a l cu ts 494149 1206.4 2441.37 0.213 Boneless beef - i n c l u d i n g husburger 432496 1469.6 2323.81 0.050 Whole ca rcass park 4121110 7895.7 1915.92 0.440 Lard - consucer l Coane r c i a l 3B9731 222.5 570.91 0.015 Nhole ca rcass lanb I H u t t o i 94530 252.6 2672.18 0.007 Ed i b l e t a l l o w t s t e a r i n 260455 119.1 457.28 0.010 Sausages I other prepared teats ' . Sweet p i c k l e d or d ry -cured pork or s a l t e d 100200 249.0 2485.04 0.003 Hats t p i c n i c s - except canned 680995 2051.2 3012 . l t 0.060 S lab bacon 60555 145.6 2404.42 0.004 S l i c e d bacon 637213 1772.3 2781.33 0.051 sausage 1259775 3654.2 2900.68 0.1 !8 Canned i e a t 520457 1548.6 2975.44 0.025 Tota l 30984.1 Unadjusted PRH00 109.22 1012 Pou l t r y P rocess ing Chickens - f r e s h , c h i l l e d or f rozen Turkeys - f r e s h , f rozen or c h i l l e d F r ank f u r t e r s I wieners 1000 kg Tota l 401163 93243 2550 871.5 2172.42 230.7 2474.09 5.5 2142.07 1107.6 0.787 0.208 0.005 2016 Pou l t r y d r e s s i ng p l a n t s Net i c e pack - bulk*t<hole It p a r t s Turkeys - f r y e r r o a s t e r I young 2017 Pou l t r y and egg p roces s i ng F r ank f u r t e r s I Nieners Tota l Unadjusted PRM00 4855665 5210.7 1073.12 717681 990.1 1379.5B 68811 98.5 1431.46 6299.3 1.593 0.374 0.007 163.11 1021 F i s h p rocess ing i ndus t r y F i s h s t i c k s , po r t i ons -p re - cooked ! f r o zen 1000 kg 20839 7B.1 3746.45 1.000 Tota l 78.1 2092 Fresh or f r o zen packaged f i s h Frozen f i s h - e x c l . s h e l l f i s h Tota l Unadjusted PRM00 293414 860.4 2932.38 860.4 105.59 105.59 Appendix A . . . cont inued C A N A D A ! U. S. A. Value Pc Height I Va lue Pu SIC Un i t Quant i ty C» a i l . C» IshCI ISIC INDUSTRY Quant i t y US* n i l l USt shC»(Pc/Pu)»1 .2 l 1031 F r u i t I Vegetable canning I p rese rve rs 203] Canned f r u i t s and vegetab les Beans - canned 1000 kg 91369 96.5 1056.25 0.170 ! Beans - f r e sh l i i a . b l u e l a k e , o t h e r s 399917 156.7 391.83 0.457 Ca r r o t s - canned • mi 4 .3 904.23 0.008 : Ca r ro t s - canned 55422 36.1 651.37 0.011 Corn • 6 t i 7 5 70.B 1061.59 0.124 : Corn 1460983 470.5 322.04 0.410 Peas - canned • 36732 36.3 988.77 0.064 ! Green peas 211370 187.4 B86.60 0.071 Hushroons • 7360 19.4 2638.95 0.034 : Mushroous 46605 128. J 2752.92 0.033 Apple j u i c e • 103052 123.4 473.B7 0.217 : Apple j u i c e 1161204 317.4 273.34 0.534 Orange j u i c e • 82413 61 .0 739.47 0.107 ! Orange j u i c e 1585886 520.1 327.96 0.241 To«ato j u i c e - canned • 97*66 70 .0 718.37 0.123 : Tonato j u i c e 544558 265.8 488.10 0.1B1 Ap r i c o t s • 610 1.0 1612.69 0.002 : Ap r i c o t s 28205 37.7 1336.66 0.002 Apples • 15*75 12.5 808.74 0.022 : • Apples 36222 40.9 1129.15 0.016 01 i ves • 4602 18.0 3918.01 0.032 : O l i v e s - r i p e I green 112442 199.6 1686.21 0.074 J e l l i e s - f r u i t or ber ry • 4805 7.3 1523.32 o.oi3 : J e l l i e s 148644 212.4 1428.92 0.014 Jans • 5611 12.8 2272.50 0.022 ! Jaes - 248118 303.9 1224.B2 0.042 Tooato Sauce • 36049 36 .0 1000.00 0.063 ! Tooato Sauce 1263320 803.6 636.10 0.100 Tota l 569.3 ! Tota l 3670.4 Unadjusted PR'100 180.49 1032 Frozen f r u i t t Vegetab le i ndus t r y S t r a b e r r i e s 1000 kg 6402 13.7 2144.03 0.047 Beans 7991 10.9 1344.49 0.037 B russe l s spouts 4683 4 .8 1454.47 0.023 Ca r r o t s 10B36 6.B 424.33 0.023 Green Peas 31210 33.4 1049.74 0 . U 3 Potatoes products 232296 193,1 B31.48 0.455 Corn 27002 30.1 1113.14 0.102 B r o c co l i 3564 3.4 1000.02 0.012 Tota l 294.8 ! 2037 Frozen f r u i t s and vegetab les S t r awbe r r i e s 142339 94.9 666.72 0.150 Beans -g reen , r egu l a r , f r ench c u t , 1 i i a 190828 190.3 997.23 0.051 B russe l s spouts 24535 36.5 1375.52 0.024 Ca r ro t s 84641 48.9 577.73 0.025 Green Peas 177266 160.0 902.60 0.134 French f r i e d po ta toes 1667604 1167.8 700.29 0.778 Corn - sweet cut I cob 359113 316.9 BB2.45 0.12") B roc co l i I6I8B9 193.8 1197.12 0.010 Tota l 2015.3 Unadjusted PRMO0 107.50 1041 F l u i d t i l t , p rocess ing F l u i d s i l k whole & processed F l u i d s i l k - sk inned 1000 I t Tota l 1024620 U24IO 721.7 6B.0 789,7 704.35 604.60 0.914 0.0B6 2026 F l u i d n i l k F l u i d whole n i l k - Bu I k t packaged f l u i d s k i n n i l k -bu lk I packaged Tota l Unadjusted PRM00 15723504 2066932 6411.3 635.7 7247.0 420.47 307.56 1.53! 0.169 1*0.51 oo Appendix A . . . cont inued C A N A D A ! U. S. A. V i l u e Pc Height ! Value Pu SIC Un i t Quant i t y C« n i l . C» (shCl ISIC INDUSTRY Quant i t y USi n i 11 US» sr .C»(Pc/Pu)M.21 1049 Other d a i r y products i ndus t r y Creamery bu t te r 1000 kg 130173 558.0 4286.76 0.316 2021 Creanery bu t t e r 554473 1850.0 3324.51 0.407 2022 Cheese - na t u r a l and processed Cheese - Cheddar t o the rs • 156279 679.7 4349.42 0.384 Natura l cheese- except co t tage 1671594 5425.4 3345.41 0.497 Process cheese • 68154 337.2 4947.50 0.191 Process cheese 591808 2022.3 3417.14 0.274 Cottage cheese • 28222 5B.B 2082.77 0.033 Cottage cheese 458904 469.4 1458.4? 0.047 Yogurt • 48704 108.5 2227.27 0.041 Yogurt 294022 403.7 1373.03 0.100 Ice creaa a i x - i n c l . n o v e r t i e s • 2711 25.8,9531.68 0.015 Ice c reaa ( i x r e l a t e d p roduc ts 471423 3034.4 6434.48 0.022 Tota l I76B.0 To ta l 13405.4 Unadjusted PR»100 111.45 1051 Cerea l g r a i n H o u r i ndus t r y wheat f l o u r Durui s e i o l i n a & f l o u r Whole wheat or g raha i f l o u r Prepared cake f i x e s ! 2041 F lour I other g r a i n l i l l p roducts 1000 kg 1102552 413.2 374.77 0 . 7 7 4 ! Wieat f l o u r - whi te 10954552 2409.0 238.12 1.218 107071 43.0 401.38 0 . 0 8 0 ! Durun f l o u r I semol ina 808215 192.9 238.47 0.135 56399 17.8 314.12 0 . 0 3 3 ! whole wheat f l o u r 112747 27.B 244.57 0.043 35401 40.0 1686.44 0.112 ! 2045 Cake Nixes 39B225 594 .11491 .87 0.127 Tota l 534.1 ! . To ta l 3423.8 ! Unadjusted PRM00 125.84 1052 Prepared s i x e s V b reak fas t c e r e a l s Break fas t c e r e a l s 1000 kg 139141 290.0 2084.02 2043 Cerea l b reak fas t foods Ready to serve - Corn f l a k e s*o t he r s Nheat f l a k e s I o the r s " R i ce b reak fas t foods ' - Other p r epa ra t i on s To be coo led - F a r i n a I other foods " Other p r epa ra t i on s Tota l Unadjusted PRMO0 319922 811.2 2535.42 2589.44 i 324499 811.1 2484.23 125102 394.2 3151.03 131090 339.5 2589.83 53842 64.3 1545.49 4173 7.2 1725.34 2447.5 44.51 Appendix A . . . cont inued C A N A D A ! U. S. A. Value Pc Height I Va lue Pu SIC Un i t Quant i ty Ct n l . Ct (shCI !SIC INDUSTRY Quant i t y USt n i l l USt 5hCMPc/Pul«1.21 1051 Feeds i ndus t r y P ou l t r y - conp le te Teed H.Tons 2225001 558.2 250.85 0.286 Da i ry - • 1418418 314.6 221.7? 0.161 Swine - conp le te Teed • 2045686 493.6 241.27 0.253 Beef - Coup le te feed 532341 87.8 164.84 0.045 Horse - compete feed H.Tons 5675? 14.2 250.36 0.007 Da i ry Supplement H.Tons 291805 81.1 278.01 0.042 Snine Supplenent • 278491 90.5 324.84 0.046 Beef supplenent • 158006 35.5 224.48 0.018 Chicken feed s upp l . • 126387 39.8 314.SB 0.020 Dog Ii cat food • 290217 238.5 821.69 0.122 Tota l 1953.6 ! 204B Prepared feeds - n .e . c Conplete p ou l t r y feeds 16336115 2919.6 178.72 0.401 Dairy c a t t l e - conp le te 8362605 1475.9 176.49 0.202 Snine feed - conp l e t e 2558378 5B5.9 229.01 0.266 Beef c a t t l e - Complete 3075206 511.4 166.30 0.045 Horse 1 nu le feed - conp l e te I0499BB 204.5 194.95 0.009 Feed supp lenents : Da i ry - supplements I concen t ra tes 1925429 544.3 282.6? 0.041 Swine - supplements I concen t ra tes 3399891 1113.7 327.57 0.046 Beef c a t t l e - s upp l e i t e n t s t c on cen t r a t e s 2751,792 607.7 220.84 0.018 pou l t r y feed s upp l . t cone. 2037649 545.1 267.51 0.024 2047 Dog t ca t - Canned & not canned 5958405 3902.8 655.01 0.153 Tota l 12410.9 Unadjusted PR'IOO 99.65 1061 Vegetab le o i l a i l l s Crude-Cana la , s oybean , sun fU r e tc 1000 kg 170244 99.4 5B3.91 0.201 Ref ined-Cano la , soybean,sunf lwr e tc ' 121002 91.2 753.57 0.184 O i l c a k e , I s e a l - * " ' " 133773B 304.9 227.90 0.615 Tota l 495.5 2075 Soybean o i l c i l l s I other o i l a i l l s C rude -Co t t on seed , soybean ,Sun f l . o i l s 4792525 2073.6 432.67 0.271 Ref ined - Cot tonseed, soybean o i l s I6IB2S3 822.2 508.08 0.273 Soybean ,Cot tonseed ,sun f l . cake 4 l e a l 23497142 4878.1 207.60 0.675 Tota l 7773.9 Unadjusted PRM00 100.76 1071 B i s c u i t i ndus t r y 1000 kg I 2052 Cookies 4 C r a c ke r ; B i s c u i t s - p l a i n \ fancy " 170519 443.6 2601.26 ! Cookies 1806904 4021.3 2225.52 ! Unadjusted PRM00 96.60 1072 Bread \ other bakery products indus t ry ! 2051 Bread, cake I r e l a t e d products Bread 1000 kg 627014 695.3 HOB.97 0 . 7 7 8 ! Bread - nh i t e pan»»hole nheat*rye 3794929 3579. 1 943.13 0.914 P l a i n r o l l s I bans ' 1264B9 198.9 1572.31 0.222 ! Ro l l s - bread type 1233104 1326.4 1075.66 0.325 Tota l 894.2 ! Tota l 4905.5 ! Unadjusted PfltlOO 102.43 Appendix A . . . cont inued C A N A D A : U. S. A. Value Pc Height s Value Pu SIC Un i t Quant i ty CI « i l . C« (shCI ISIC INDUSTRY Quant i t y USt t i l l USt s hCKPc /Pu 1081 Cane t Beet sugar p rocess ing S2042HCane and beet sugar r e f i n i n g Granulated cane I beet S. H.Tons 696211 395.2 567.58 0.747 ! Granulated cane I beet sugar 4747891 3344.7 495.94 0.B7B I c ing sugar - packaged - cane ( beet • 39752 27.2 483.03 0.053 1 Con fec t i oners powdered sugar 345732 205.9 595.55 0.060 Granulated y s i low t brown « 52680 35.2 468.43 0.04B 1 Sof t or brown sugar 244489 163.7 449.56 0.068 Inver t sugar 100787 57.5 570.47 0.112 1 Inver t sugar - cane V beet 395174 234.5 593.41 0.107 Tota l 515.0 1 To ta l 3950.e Unadjusted PRM00 92.08 1092 Chewing gu i i ndus t r y 1 2067 Chewing gun Chewing gun 1000 kg 19714 109.0 5529.02 1 " nond i e t i c 179443 739.0 4118.30 I Unadjusted PRM00 110.95 1083 Sugar d choco la te Banufac turers 1 2045 Confec t ionary products Choco late con fec t i one ry 1000 kg 74106 470.8 6353.09 0.738 1 Chocolate t Choco la te type conf . 880140 3759.7 4271.61 1.09B Sugar con fec t i one ry « 62165 147.0 2485.42 0.262 ! Non-chocolate type conf . 714778 1593.7 2229.64 0.315 437.8 1 Tota l 5353.4 I Unadjusted PRMO0 116.80 1091 Cof fee t tea i ndus t r y 1 2095 Roasted co f f ee Cof fee Roasted 1000 kg 5IB92 328.1 4322.34 0.747 1 Roasted co f f ee - ground 4470(4 3330.7 4993.45 0.971 Tea - b lended, packed f 16405 99.7 6077.77 0.233 ! 2099 Tea - packed i n tea bags, powder. 123016 743.5 4043.95 0.234 Tota l 427.8 I To ta l 4074.2 1 Unadjusted PR*100 99.62 1092 Dry pasta products 1 209B Nacoroni I Saghe t t i Macaron i , s p aghe t t i , V e r m i c e l l i , noodles 1000 kg 112859 129.3 1145.59 1 Macaroni & Saghe t t i I egg noodles 954409 1143.9 1194.04 1 Unadjusted FRMO0 79.16 1093 Potato c h i p , p r e t z e l & Popcorn 1 2099 Food p repa ra t i on s n . e . c . Potato c h i p s , f l a k e s , f r i l l s t other pdcts 1000 kg 59056 307.0 5197.B3 ! Potato ch i p s I s t i c k s 442711 1545.4 3490.77 Unadjusted PRMOO 123.04 Appendix A . . . cont inued C A U. Value Pc Height Va lue Pu SIC Un i t Quant i ty Ct a i l . Ct (shCI SIC INDUSTRY Quant i t y USt n i l l USt shCMPc/Pu 1099 Other Food I ndu s t r i e s '.Other food I ndu s t r i e s Eggs - f rozen 1000 kg 5951 7.7 1290.04 0.008 2017 Frozen eggs 106505 97.1 911.70 0.011 Peanut bu t t e r • zmt> 98.7 3003.94 0.104 2099 Feanut bu t t e r 333258 796.7 2390.64 0.131 Corn s t a r ch - (twheat t o ther g ra ins ) • I2326B 56.3 456.52 0.059 2046 Corn s t a r c h (wheat, r i c e I o the rs ) 2485213 626.7 252.17 0.108 Peanuts - roas ted , s a l t e d e t c • 26568 101.3 3814.66 0.107 Peanuts I other nuts 55*613 1481.1 2670.51 0.153 Shor ten ing * l a r g a r i n e • l a r d • 416029 474.3 1140.18 0.501 2079 Shorten ing I c o o l i n g o i l s 2269255 1870.3 824.19 0.693 Nargar ine • 155874 207.9 1333.94 0.220 Nargar ine 1296108 1217.0 938.96 0.312 Tota l 946.3 Tota l 60B8.9 Unadjusted PRM00 116.43 1111 So f t Dr inks 2086 Bo t t l ed I Canned s o f t d r i n k s Regular - b o t t l e d 1000 I t 1815944 1067.0 587.56 0.701 Non -d i e t i c - b o t t l e d 1206753 733.1 607.50 0.678 Regular - canned • 389645 299.0 767.40 0.196 " - canned 7790666 4515.2 579.57 0.260 Low c a l o r i e - b o t t l e d t 89685 55.1 614.44 0.034 Low c a l o r i e - b o t t l e d 1405181 850.7 605.40 0.037 Low c a l o r i e - canned • 62688 56.4 899.51 0.037 Low c a l o r i e - canned 1680256 967.1 575.57 0.058 P ren i xes - bulk (Ion c a l o r i e t r e gu l a r l • 90459 45.2 499.52 0.030 D r i nk s i n bulk <»pre t i xes l 1320965 517.4 391.68 0.038 Tota l 1522.7 To ta l 7583.5 Unadjusted PRUQ0 88.45 1121 D i s t i l l e r y products : 2085 D i s t i l l e d l i q u o r , except brandy Whisky 1000 I t 130377 543.3 4167.27 0.891 Whisky 547961 1157.4 2104.51 1.763 Gin * 5554 32.5 5855.21 0.053 Gin 116578 162.0 1389.63 0.225 Vodka • 1345 1.2 924.63 0.002 Vodka 379636 462.9 1219.33 0.002 L iqueurs & C o r d i a l s • 3681 33.0 8970.77 0.054 L iqueurs V C a r d i a l s 151779 253.0 1664.90 0.291 Tota l 610.1 Tota l 2035.3 Unadjusted PRH00 189.50 1131 Brewery i ndus t r y 2082 Ha l t beverages Beer, A le etc - b o t t l e 1000 I t 2043108 15*9.7 758.52 0.913 Beer t A le - b o t t l e d 9213377 3964.6 430.31 1.609 Beer, A le etc - canned • 239935 148.5 618.86 0.087 Beer I A l e - canned 14302960 5984.9 418.44 0.129 Tota l 1698.2 To ta l 9949.5 Unadjusted PRH00 143.63 o Appendix A . . . continued C A SIC Value Pc Height I Unit Quantity Ct ail. Ct (shC) ISIC INDUSTRY Value Pu Quantity USt tiill USt shC*!Pc/Pu)*!.21 1141 Slineries Wines - aatured, st i l l , grape fruit Sparkling wines Wines -matured, st i l i , other than grape Cider 1000 It 93443 153.4 1838.66 0.706 23373 53,9 2307.76 0.248 1081 2.0 1809.60 0.009 5112 7.9 1550.18 0.036 Total 217,2 2084 Mines, brandy V brandy spirits Srape wine - white, red J: rose Sparkling wines - natural Si carbonated Other fruit,berrytspecialty+Dessert wines 2099 Cider Total Unadjusted PR*100 2365625 1772.2 749.15 1177:4 247.3 2100.86 389477 345.7 887.60 68887 46.7 677.92 2411.9 1.733 0,273 0.018 0.083 174.20 1211 Leaf tobacco processing Flue-curedlwhole leaf Lamina 1000 kg 1244 5.4 4341.64 0.017 61826 312.6 5056.34 0.983 Total 318.0 2141 Tobacco stesaing I redrying Unstenaed leaf tab. Stewed Tob. & packaged Total Unadjusted PRM00 18824 523451 98.4 5227.29 2733.0 5221.12 2831.4 0.014 0.952 79.64. 1221 Tobacco products Cigarettes - regular Cigarettes - kingsiie Snokino tobacco I 2111 Cigarettes 1000's 35578272 562.4 15.81 0.502 I Cigarettes - regular 30504B52 499.1 16.36 0,446 1 Cigarettes - kingsize I 2131 Chewing & smoking tobacco 1000 kg 5974 58.7 9817.29 0.052 I Saoking tobacco Total 1120.1 I Total I Unadjusted PR*100 319444000 5544.4 17.36 231344000 3959.7 17.12 16375 129.2 7890.15 9633,3 0.457 0.426 0,065 78,37 Source: Census of Manufactures Reports - Canada and U.S. (19821. o 


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