r” THESIC am LIBRARY i Michigan State University i I —— This is to certify that the dissertation entitled The Relationship Between Unionization and Market Structure in the Food Retailing Industry: 1967-1980 presented by Diane Cynthia Smith has been accepted towards fulfillment of the requirements for Masters degree in Agricultural Economics 52/574414 40 S/u/t/ Major professfét James D. Shaffer Date December 19, 1983 .MSU is an Affirmative Action/Equal Opportunity Institution 0-12771 )V1ESI_J RETURNING MATERIALS: Place in book drop to LJBRARJES remove this checkout from All-[jll-L your record. FINES will be charged if book is returned after the date stamped below. FE3182005 052 9 05 THE RELATIONSHIP BETWEEN UNIONIZATION AND MARKET STRUCTURE IN THE FOOD RETAILING INDUSTRY: 1967-1980 By Diane Cynthia Smith A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Department of Agricultural Economics 198N ABSTRACT THE RELATIONSHIP BEWTEEN UNIONIZATION AND MARKET STRUCTURE IN THE FOOD RETAILING INDUSTRY: 1967-1980 By Diane Cynthia Smith This thesis attempts to statistically test the first part of Galbraith's theory of counterveiling power, that power attracts power, by exploring the relationship between unionization and market structure in the food retailing industry. Four-firm concentration ratios are used to proxy actual market structure, and unionization is measured by summing the share of unionized market shares in each of the markets. Union data was collected by use of a survey. Regression analysis was used to test the alternative models presented. Results were inconclusive. ACKNOWLEDGMENTS I would like to express my appreciation of all those who have helped me with this project. My special thanks to Dr. Ronald Cotterill and to my committee; Dr. James Schaffer, Dr. Harold Riley, and Dr. Peter Schmidt. I am also indebted to the Department of Agricultural Economics at the University of Connecticut for providing support services. I would also like to express my thanks to friends and family, without whom this would not have been possible. ii TABLE OF CONTENTS LIST OF TABLESOOOOOOOOOOOOOOOOOOO0..00....OOOOOOOOOOOOOOOOOOV LIST OF FIGURESOOOOOOOOOOOOOO...O...I0.0000000000000000000Vii Chapter page I. PROBLEM STATEMENTOOOOOOOOO0.0.0.0.0...OOOOOOOOOOOOOOOO1 II. THE UNITED FOOD AND COMMERCIAL WORKERS INTERNATIONAL UNION.OOOOOOOOOOOOOOOOOOOOOOO 3 The History of Unionization in the Food Retailing Industry.......................... 3 Influence of the Industry's Structure on Unionization................................ 5 The Influence of the Industry's Development on the Union.............................. 10 The Influence of the Political Legal Environment on Unionization............... 13 Present Concerns of the UFCW...................... 18 III. UNIONIZATION AND MARKET STRUCTURE: DATA COLLECTION AND DESCRIPTIVE ANALYSIS ..................... 25 Sample Selection and Survey Procedure ............ 26 Descriptive Analysis: Unionization of Operators.. 33 Descriptive Analysis: Unionization in Markets.... 41 Unionization in Markets: 1980................ 42 IV. THEORY AND MODEL SPECIFICATIONS ..................... ”9 Introduction ..................................... 49 Theory of Counterveiling and Coalesing Power...... 50 Union Model Specification ........................ 5“ Models to Predict Unionization ................... 59 Concentration Model Specification ................ 60 Model to Predict Concentration ................... 65 iii page V. EMPIRICAL RESULTS IOOOOOOOOIOOOOOOOOOOOOOOOOOOOOOOOOOO 68 Empirical Results of Union Models ................. 70 Empirical Results of Concentration Model .......... 77 Empirical Results of Simultaneous and Recursive MOdelsOOOOIOOOOOOOOOOOOIOOOOOOOOOOCOOOOOOOOOOO 86 C0n01USion OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOCOOO 93 Appendix 0 QUESTIONAIRE IOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO 9“ A B. UFCW BARGAINING REGIONS DEFINED ...................... 95 C. LARGE FOOD CHAINS .................................... 97 D . AN ESTIMATION OF UNIONIZATION USING ORDINARY LEAST SQUARES: ASUPPLEMENT I.0.0..0.00.00.00.00000000098 BIBLIOGRAPHY OOOOOOOOOOOOOOOOO....0.00000000000000000000000 99 iv 3.7. 3.8. 3.9. 3.10. 3.11. 3.12. 5.1. 5.2. 5.3. 5.“. LIST OF TABLES page Jurisdictional Breakdown of RCIA Membership: 1960..u Index of Wage Rates for Selected Job Classifications: Effective Jan. 1, 1980........22 Geographic Dispersion of Markets in Sample.........27 Operator Unionization and Type of Store............3u Operator Unionization and Market Share.............35 A Geographic Comparison of Operator Unionization...37 Operator Unionization and Right-to-Work LegiSlationOOOOOOOOOO0..0.00.0.0000000000000000038 Unionization and Market Share Given RTW LegiSlationOOOOOOO0......O...0.0.0.000000000000039 Market Unionization and Market Size................43 Market Unionization and State Unionization.........uu Market Unionization and Geographic Region..........45 Market Unionization and Right-to-Work Legislation..fl6 Market Unionization (PCTUN80) and CR4: 1980........A7 Market Unionization (UN80) and CR”: 1980...........M8 Descriptive Statistics for Variables...............69 Estimation of Unionization (PCTUN80) Using Ordinary Least Squares..........................71 An Estimation of the Summation of Unionized Market Shares in a Market (UN80) Using OLS.............74 Estimation of Concentration in 1977 OLS............78 Estimation of Concentration in 1980 Using OLS.....81 Estimation of Unionization and Concentration Using a Simultaneous Equation Model............89 Estimation of Unionization and Concentration Using Recursive Model Number One...............90 Estimation of Unionization and Concentration Using Recursive Model Number Two...............91 Estimation of Unionization and Concentration Using Recursive Model Number Three.............92 An Estimation of Unionization Using Ordinary Least Squares: A Supplement...................98 vi Figure 3.1 LIST OF FIGURES Comparison of Distributions for the Population and Sample vii 29 Chapter I PROBLEM STATEMENT In 1956 John Kenneth Galbraith published a theory of counterveiling power in his book American Capitalism, setting off a new and yet to be resolved round in the debate over the efficacy of the market as a regulatory force in the American economy. Galbraith postulated that when one side of the market was organized so that it could exert market power, the other side would organize in response to it and offset the market power, resulting in an approximate competitive solution. There are two parts to this theory; the first hypothesis is that power attracts power, and the second deals with the behavior resulting from the first. This thesis attempts to statistically test the first part of his theory, power attracts power, by examining the relationship between four-firm concentration and unionization in the food retailing industry between 1967 and 1980. Thus, this study analyzes the impact of unionization as a structural phenomena and does not examine the impact of union strength on wage and benefit packages. The share of sales unionized in a market was determined by surveying the top ten firms in each market for 131 Standard Metropolitan Statistical Areas (SMSA's) in the l 2 United States. The United Food and Commercial Worker's International Union (UFCW) supplied data missing from the survey. Market share data was collected from Metro Market's Grocery Distribution Guides. Census data supplied four-firm concentration ratios. Merger data was obtained from a University of Wisconsin data file and from Food Institute's Weekly Digests. The statistical relationship was explored using several models and estimation techniques. Both the extent of unionization and the level of concentration were first estimated using ordinary least squares as a technique. Then the two equations were modeled as systems using simultaneous equation and recursive models. These models were estimated by three stage least squares and two stage least squares, respectively. Policy implications are presented last. Chapter two presents a brief history of the UFCW as well as a discussion of their present concerns. Descriptive tables about unionization in the food retailing industry can be found in chapter three. Chapter four presents theory and model specifications. The last chapter presents the empirical results and policy conclusions. Chapter II THE UNITED FOOD AND COMMERCIAL WORKERS INTERNATIONAL UNION THE HISTORY OF UNIONIZATION IN THE FOOD RETAILING INDUSTRY Several unions have competed for the right to represent employees in the food retailing industry over the years. The industry, however, is largely represented by two major unions which have prospered; the United Food and Commercial Workers Union, and the Teamsters Union. The UFCW was created by a merger of the Retail Clerks International Association (RCIA) and Amalgamated Meatcutters and Butcher Workmen (Butchers) on June 7, 1979. Most union employees in food retailing stores have been organized by the RCIA or by the Butchers; the Teamsters Union primarily organized drivers and warehousemen, although on occasion they organized all the retail store employees. Because this happened infrequently, the history presented here will focus on the RCIA and the Butchers.1 The RCIA, founded in 1888, is the oldest union in the retail trade. It covers several jurisdictions, as table 2.1 illustrates. To understand the history of the RCIA, one There has been very little written about the history of these two unions. The information reported in this section is taken from Michael Harrington's The Retail Clerks and from David Brody's The Butcher Workmen. 3 . A must keep in mind the structure and evolution of the retailing industry. The industry developed unevenly, with the food chain store leading the modernization and rationalization of the retail industry. Since the food retailing sector was the first to be modernized, its membership was concentrated in large numbers in a small number of stores, compared to other sectors of retailing. As a result the union developed its early strength in the food retailing segment, and as Table 2.1 suggests, food retailing remains its strongest department. The scope of history reviewed here will be in relation to the food sector of retailing. TABLE 2.1 Jurisdictional Breakdown of RCIA Membership: 1960 Food and Drug Stores ”3.0% Department and Variety Stores 12.0% Apparel and Shoe Stores 11.0% Hardware and Furniture Stores 11.0% Other Stores 23.0% The Amalgamated Meatcutters and Butcher Workmen's Union was formed on January 26, 1897. Its history can easily be divided into two seperate movements; one to unionize workers in packinghouses, and the other to unionize workers in retail positions. Since this paper focuses on the food retailing industry, only the movement to unionize meatcutters in the retail trade will be addressed. The history of unionization in the retail sector can be viewed as behavior in reaction to the structure and development of the food retailing industry within the framework of a political economy. The structure of the industry focuses on the physical aspects of the industry such as geographic dispersion, the type of employee found in the industry, and the nature of the workplace. The development of the industry deals with the evolution of the industry, dividing the history into several stages marked by two major technological innovations; the development of the chain store and the development of the supermarket. The framework of a political economy refers to the political legal environment which defines an organization's opportunity set. Influence pf the Industry's Structure pp Unionization Unionization in the retail sector has historically been influenced by several factors related specifically to the structure of the developing retail industry.2 These include geographic dispersion, the type of employee found, and the structure of relationships within the workplace. Michael Harrington, The Retail Clerks, ed. Walter Galenson, Studies of Comparitive Union Governments (New York: John Wiley and Sons, Inc., 1962), p. 7. 6 Retailing was widely dispersed during the organizing era of the 1930's, contrasted to the automobile industry, located in Michigan, or the steel industry, located around the great lakes. Geographic dispersion caused much variation in union structure and standards, partly because situations and needs varied across the country, but also because modern communication systems were not as developed. National union strength was harder to achieve in retailing because strike negotiations tended to be localized; a strike in a Kroger store in Michigan, for example, did not affect a Kroger store in Texas. A strike's impact on a large, multimarket retail firm was much less than a strike's impact on a steel firm or auto firm. Manufacturers were forced to deal with a strike if the union struck the company; in retailing that was not the case. Multimarket retailers could choose to wait out the strike, surviving off of other stores, and although sales lost in the struck store were lost for good, the chain store still had a cash flow from other stores. Manufacturers in the steel or auto industry were forced to deal with the strike, but most sales were delayed rather than lost. Over the years union locals representing retail employees have grown 111 size and have become more standard, but they definitely are not part of a unified national union strategic bargaining framework. During the first stage of food retailing, the pre-1920 chain era, food retailing was characterized by small dry 7 goods stores and small butcher shops. The* small stores presented the early union movement with an organizational problem for neither was the type of employee found in the shop conducive to being organized nor the structure of relationships within the workplace conducive to unionization. Employees worked long hours side by side with proprietors, with 80 hour work weeks being common. Many aspired to positions of joint ownership or proprietorship themselves. These factors were all unfavorable to unionization. The early union movement, however, advocated a shorter work ‘week through early closing, movements and holiday closing movements. Many proprietors held the same interest as their employees, so unionism had an easier start than would have been expected. As clerks found the early closing campaign to tna an attractive issue, membership in the RCIA soared from approximately 3,000 in 1890 to 50,000 in 1903. The RCIA then moved into a new phase characterized by decline and stagnation. Harrington attributes this to a renewed burst of white collar aspiration within the industry.3 Even with strong leadership and sickness and death benefits, the RCIA barely held together during this period which ended around 1920. The end of World War I brought a resurgence of union growth for the Clerks, but again it was followed by a decline during the 1920's and early 1930's. 8 The Butchers also organized around the work schedule, fighting for both early closing and Sunday closing. As with the Clerks, retail owners agreed with the worker associations and cooperated with them to reestablish industry standards. When the business cyle hit recessions, however, interests between the retailers and the union diverged, and an unpleasant environment often resulted. The retailers expected and were prepared for strikes, but the meatcutters did not use strike tactics because the owners' shops would stay' open anyways. The union used consumer boycotts which in large effect depended on the disunity of the retailers. If half of the stores were struck, consumers could shop at the other stores but if all stores were struck, consumers could not enforce the boycott for they would not be able to purchase groceries. Although retailers tried to organize themselves through retailer associations, the efforts were sporadic for effective organization was too costly both in time and in money. The effectiveness of the consumer boycott was undermined by several factors. During the pre-1920 period, the Butchers found their locals plagued with internal problems common to all. These included recruiting local leadership, stabilizing the membership, and regulating the labor supply. Since locals were autonomous, each local had to evolve painfully through the same process to achieve stability. 9 Recruiting leadership was a problem because the most talented individuals were apt tx> be promoted into management, out of the rank and file, or they became proprietors. Also, many officials were dishonest, and they absconded with the funds. Locals finally solved the problem of leadership by hiring professional business agents. The second problem was stabilizing union membership. Meatcutters were not "natural" union members because they usually worked next to the owners of the shops, and they expected to become proprietors themselves. Once the union helped decrease the length of the work week, meatcutters tended to drop out of the union. A. third problem was regulating the labor supply. An informal system of apprenticeship existed but the real problem came from an outside influx of meatcutters. Some locals were strong enough to resist but it remained a problem until everyone was unionized. By the 1920's the meatcutter's union was established and fully engaged in the collective bargaining process. The Butchers estimated that it's retail meatcutter members numbered 10,000 in 1920, roughly 16.6 percent of total membership. They were concentrated in large numbers in northern California, the northwest, Chicago, Saint Louis, Saint Paul, and in lessor numbers in Scranton, Evansville, Dubuque, and the New York City Metropolitan Area. Only 8.0 percent of all retail meat employees were organized. 10 The Influence pf the Industry's Development pp the Union The chain store movement began in the ninteenth century but it did not get into full swing until the 1920's. The movement centered on the integration of supply channels for retail stores. It left the retail units basically unchanged, but prices were lower because of improved distribution techniques, economies of scale, and cheaper centralized management. It was during this period that many of the present large national food chains rose to national prominence including Atlantic & Pacific Tea Company (A&P), Safeway, Kroger, and National Tea. As chain stores mounted in popularity they expanded their line of goods to carry perishable foods, including meat, rather than just staple goods. A&P started experimenting with meat departments in 19211. By 1929, about one-third of the chain stores were combination stores. The combination store movement became known as the supermarket movement. As the chain store movement peaked in the 1930's, chain stores handled about one third of the grocery business nationwide, and the supermarket movement was in full swing. This introduced modern mass retailing as we know it today, with large, low overhead per unit of sales stores, several departments, self service, and cash-and-carry policies. The RCIA's membership declined throughout this period until 1933 when it had but 5,000 members. The Butchers continued to unionize but progress was still slow. The 11 chain store movement affected the unions in several ways. Since the industry itself was undergoing a period of intense competition and consolidation of "Mom 8: Pop" stores into chain stores, the industry as a whole did not prosper. Along with a mass production system of distribution, chain management developed personnel policy partly to discourage unionization, by providing limited benefits called "welfare programs" for the workers. These factors acted to decrease union enrollment. However, with the development of the chain store came a "blue-collar" position for the employee. Where once the employee was a salesperson who interacted to a significant degree with the customer, chain store organization and national advertizing by brand manufacturers, who presold products to consumers, changed that. Employees became more like material handlers, and their relationships became less personal with customers. This development increased the level of alienation as defined by Ollman,"I and other social scientists inspired by the works of Karl Marx. The result was an increase in unionization for social and psychological reasons as well as economic security, although there was a time lag between the chain movement and the resulting unionization. Bertell Ollman, Alienation: Marx's Conception _o_f_‘ Man _i_p Capitalist Society, 2nd ed. (Cambridge: Cambridge University Press, 1976), p. 35. 12 The Butchers felt threatened by the potential concentration of economic power in a few large multimarket chains. Chains, however, became more susceptible to consumer boycotts because the retail trade no longer had a united front since small retailers hated the chains. During the 1920's strong locals began unionizing the chains. Safeway was the most receptive to unionization and developed friendly relations with the union. Centralized management in the chains brought a new organizing tactic to both unions; organizing from the top down. The Butchers promised industrial peace, fair demands, and honored contracts in exchange for management permiting labor, and when possible, encouraging labor, 1x) organize. By 1933, Safeway had a master agreement with the Butchers covering Northern California aux! the Northwest. Other chains, such as National Tea and Kroger were more reluctant, but they had informal agreements. A&P rigidly opposed unions in any form. The most critical factor when attempting to unionize a chain in a locality was whether the competition was organized. "Competitive considerations made local organizing work a crucial counterpoint of the tactic of unionizing through the employer".5 David Brody, The Butcher Workmen: A Study pf Unionization, Wertheim Publications in Industrial Relations (Cambridge: Harvard University Press, 196“), p. 132. 13 The Influence pf the Political Legal Environment pp Uniofiization The political legal environment in the United States changed during the 1930's, shifting institutional power in favor of unions. Previous to this change, courts had a tendency to grant anti-organizational and anti-strike injunctions to employers threatened by labor unions. Courts also upheld yellow dog contracts which were agreements that the employee would not join a labor union as a condition of employment. The Norris-Lagaurdia Act of 1932 made yellow dog contracts unenforcable and also restricted employer's use of injunctions as a weapon against organizing. The real foundation of present labor legislation, however, was the Wagner Act of 1935. This act established the National Labor Relations Board (NLRB) and defined unfair labor practices. The Wagner Act gave workers the right to organize, to bargain, and to strike with legal sanction. The NLRB's purpose was to act as a court to settle labor-management disputes. This legislation gave unions more economic power, and membership increased from 1935 on in most union movements even though it was the Depression. As the chain store movement drew to a close, the unions were employing several organizing tactics including joint and strategic alliances. Joint alliances existed when two unions joined together to implement unionizing, such as the Teamsters and the Butchers. Strategic alliances refer to "an alliance between a 'dependent' union (one dependent on 14 outside assistance for achievement of its goals) and a union that is economically self-sufficient and able, because of strategic position in the same industy or process as the dependent union, to provide it with economic aid".6 Strategic alliances existed between the Clerks and the Teamsters and between the Clerks and the Butchers. The Clerks have historically been in a weak position because they have a low skill level; consequently, they have relied on the Teamsters and the Butchers for economic clout both to unionize and to achieve wage gains. These strategic alliances caused 23 problem with jurisdictional boundaries from the very beginning of the RCIA. In addition to this problem, the Butchers and the Clerks have always competed for employees. As the retail industry evolved and new products were introduced like canned meats, the fight became more embittered. The AFL moderated negotiations and with the election of James Suffridge as President of the RCIA in 19”“, the RCIA strengthened, no longer needing strategic alliances. By the mid-50's, jurisdictional boundary problems died down. The union movement accelerated in the late 1930's and continued to grow throughout the 19H0's, partly because of the change in the political legal environment. The RCIA rose~ to 'become one of ‘the largest unions in the United Martin S. Estey, "The Strategic Alliance as a Factor in Union Growth," Industrial and Labor Relations Vol. 9, No. 1 (October 1955I, p. A2. 15 States. Harrington attributes the rise of the union to the modernization of the industry and to the election of Suffridge as president. Suffridge became invoved with the RCIA in the late 1930's when he started using aggressive organizing tactics on the West Coast, primarily in the San Francisco Bay Area. Before Suffridge became active in the union, the union was characterized as small, unaggressive, and insecure. C.C. Coulter was the top official and had been since 1926. In 1937 a New York City local criticized the RCIA administration, and eventually called for a convention, the most recent convention having been held in 19211. Coulter responded by strengthening his position of power and structuring the union to secure his position against internal political opposition. When Suffridge took over, he found the position to be exceptionally powerful. Suffridge immediately' implemented an aggressiver organizational plan that included hiring new organizers, establishing geographic divisions, establishing organizational conferences, and holding RCIA conventions regularly. In the mid-50's Suffridge continued to modernize the union adding a research department. During this period the retail sector began standardizing chain stores. The union began requiring accountability and administrative precision from locals. Many locals Inerged, consolidating strength and improving efficiency. 16 The Butchers made rapid gains during the 1930's under the umbrella of the Wagner Act and related New Deal legislation. A&P held out, however, with only Seattle organized before 1936. The union was preparing to launch a large organizing effort against them in the late 1930's but events worked out so this was not necessary. A&P's existence was threatened by anti-chain legislation on the national level. The specific bill was the Patman Bill and it was structured so that A&P would be taxed one half of a billion dollars annually. The chain needed organized groups to help defeat the legislation, specifically, the Butchers and the larger labor organization, the AFL. They agreed to lend their support if A&P consented to unionization. By 1940, the west and midwest divisions were thoroughly organized adding 6,000 union members from the 9,200 meatcutters who worked for A&P. Many of the newly unionized A&P stores were strategically important for the union. A&P was often the leading competitor in :a market, and their nonunion status limited the ability of the union to bargain for higher wages among unionized competitors. Both the RCIA and the Butchers were structured so local unions had a great deal of autonomy. The national administration, refered tx> as the "international", had the power to approve or disapprove strikes, mainly because they controlled strike funds. The international had the power to say "no" to the locals, but not the power to make them say 17 "yes". This meant that at times when a major settlement could take place between the union and a chain, there might exist one or two locals who would not accept the contract because they felt that they could get a better wage. The Butchers international noted frustration at times with locals who placed their interest above the union as a whole. In 1938 a local union would not agree to wage concessions for small low volume markets, although the international was advocating it. It resulted in Safeway closing 170 small unprofitable markets, finally forcing the local union to see its viewpoint. Firms still use the weapon of exiting a market when bargaining. In the late 1970's, Kroger carried through on a threat to close all of its stores in Western Michigan if the union did not agree to wage concessions. After World War II, the political climate in the country was not as favorable to unionism. The AFL and CIO merged in 1955, and unionism as a whole settled down. The Butchers union continued to grow throughout the 19A0's and 1950's. A substantial part of this growth came from other unions merging into the Butchers union. In 1979, the Butchers and the Clerks merged, creating the UFCW. The union is in the process of merging and restructuring and as of 1981, an organizational chart did not exist. The research department is trying to merge and assemble reliable data bases. Approximately 1,300,000 18 people belong to the UFCW as of 1980.7 The next section of this chapter illustrates the present status of unionization for the food retailing industry. PRESENT CONCERNS 9: THE UFCW At the UFCW's 1980 Retail Food Conference the union focused upon three major issues; increasing market concentration and corporate power, increasing ownership of the U.S. food retailing industry by foreign firms, and technological 8 developments. The union identified these as the most threatening problems its membership faced. The first two major concerns, increasing market concentration and corporate power, and increasing ownership of the U.S. food retailing industry by foreign firms, are interrelated. There has been a trend toward increasing concentration in the food retailing industry since the chain store movement in the 1920's. A heavy period of mergers and acquisitions took place between 19A9 and 1965, ending only because the Federal Trade Commission (FTC) issued decrees against several major companies prohibiting acquisitions for ten years unless the chains had the prior approval of the 7 U.S. Bureau of the Census, Statistical Abstract pf the United States: 1981, (Washington, D.C.: Superintendent of Documents Printing Office, 1981), p. A11. 8 United Food and Commercial Workers International Union's Research Office, The Retail Food Industry : How The Union Sees It (Washington, D.C.: United Food and Commercial Workers International Union's Research Office, (1981)), p. 1. 19 FTC.9 Since the last decree expired, merger and acquisitions have begun again. In 1978 Lucky acquired Tampa Wholesale and the A7 Kash 'n Karry Stores operated by it. Grand Union acquired the Colonial and the Weingarten chains. In 1982, Kroger acquired the Dillon chain, moving it from the third largest to the largest food retailer in the nation. The union feels threatened because when a chain acquires another, some stores are closed and union jobs are lost, many times to nonunion independents. The union reports that Grand Union closed 100 stores after taking over Colonial and 1,000 workers lost their jobs to nonunion Winn-Dixie who picked up the business. Another problem in acquisitions is that as a firm acquires more stores, the union is forced to deal with a firm wielding increasing amounts of economic power. Foreign firms are increasing their ownership in the U.S. 10 food retailing industry' for several reasons, including; the attraction by the decline of the dollar in relation to 11 their currencies, the United States industry is more profitable than the European industry, the U.S. imposes less restrictions on industry, retailers are free to pursue 9 Bruce W. Marion et al., The Food Retailing Industry: Market Structure, Profits, and Prices, Praeger Special Studies (New York: Praeger Publishers, 1979). D. 19. 10 Bruce W. Marion and Howard J. Nash, "Foreign Investment in U.S. Food Retailing Industry," American Journal .3: Agricultural Economics, Vol. 65, No. 2 (May 1983), p. 413} ___' _—- ‘—_ '— 1‘ Ibid., p. u1u. 2O profitable growth in the U.S., and there are no political risks compared to many other countries. The union estimates that ten percent of the industry is now foreign controlled. The union states "...multinationals create economic instability for workers...weaken workers bargaining power...disguise their operations, ownership and control...(and) have earned a reputation of ruthlessness based on their general business behavior."12 Both the large U.S. and foreign firms threaten the union because of their large economic base, because they adopt technological innovations faster than other groups of stores, and because they are trying to increase the amount of part-time help in stores at the expense of the full-time worker. Furthermore, the international companies are a source of labor saving innovations such as the boxstore idea (Aldi-Benner). This leads up to the last major issue, concern over technological change. Three major changes have taken place; scanning, boxed beef, and store design. Scanners are electronic computers which read Universal Product Codes (UPC). It is estimated that they are operating in 2,200 retail food stores in the United States. Winn-Dixie, Publix, Kroger, and Giant have made policy decisions to use scanners. Scanners cut labor costs in a United Food and Commercial Workers International Union's Research Office, The Retail Food Industry 1 How The Union Sees IE, p. 12. 21 variety of ways, and they provide an excellent data base for management decisions. They reduce labor costs by checking out customers faster. If prices don't have to be put on items (many states still require that they do), more jobs are eliminated. Two thirds of the stores with scanners use them to schedule work, about sixty percent to account for coupons, fifty' percent. for shrink analysis, and thirteen percent for shelf allocation. The union is not only threatened by this technological development, but it is also frustrated because it does not have any raw data to determine such elementary policy issues such as how many jobs are being lost because of the innovation or how much it increases the productivity of the worker. The union has asked for the data in negotiations with the chains using scanners but no one has complied. This information imbalance puts the UFCW at a disadvantage when bargaining for new contracts. Boxed beef is also a major concern for the union. In the early 1970's most beef arrived at retail stores in carcass form. Now most beef arrives sealed in cry-o-vac bags, in boxes, with only final slicing necessary before it goes into the meat case. Many meatcutters' jobs have been lost at the plants and wholesale level because of the new cutting and processing technology. There also has been some decrease at retail level. New developments in the vmrks include meat packaged for the consumer at the plant level, with UPC codes 22 and prices attached. This would totally elimate the need for meatcutters at the retail level. Meatcutters are important for all retail workers because they are used 1K) give the union some bargaining leverage. Skilled workers have emu advantage over unskilled workers because they cannot be easily replaced. Meatcutters are used to increase everyone elses wages in a store by a wage index13 similar to the one presented below in table 2.2. This means that when the meatcutters increase their wages by a dollar per hour, a wrapper would automatically increase his by eighty-five cents per hour. This makes the meatcutter a focal point in bargaining. TABLE 2.2 Index of Wage Rates for Selected Job Classifications: Effective Jan. 1, 1980 Job Classification Ipdgx Journeyman Meat Cutter 100% Wrapper/Weigher 85% Head Cashier 92% Journeyman Clerk 85% Store design, the last of the technological innovations, is important because the merchandising of items affect employment levels and job loads. Recent new formats include 13 Ibid., p.30. 23 boxstores cu“ limited assortment stores, super stores, and warehouse stores. In these formats retailers employ less full-time workers, and less workers overall, by increasing volume per workday.1u Box stores are run by part-time personnel. There is a trend in the industry towards high volume, low hours, and more part-time help. Related to this is the issue concerning the closing of many supermarkets. The union quotes that the industry believes twenty percent of all supermarkets are unnecessary. If closed, the UFCW estimates that 250,000 workers would lose their jobs. The Union expresses its job as protecting the membership. They wish to negotiate broader area agreements with major corporations to counter increased economic power, along with closing notice language, severence pay, and store closing pensions for older workers. To bargain effectively with multinational retailers, including American firms such as Safeway with international holdings as well as foreign firms with U.S. subsidiaries, they would strenghten international labor ties. Innovations would be dealt with by trying to set up technological adjustment funds supported by company contributions and shorter work weeks for full-time employees. 1" Ibid., p.31. 2A This section has presented the concerns and desires of the union. Desires aside, the reality of the late seventies and early eighties has been economic recessions and union givebacks, not a time of prosperity and union strength. Chapter III UNIONIZATION AND MARKET STRUCTURE: DATA COLLECTION AND DESCRIPTIVE ANALYSIS Little research has been done describing the relationship between unionization and market structure in the food retailing industry. This analytical void primarily exists because there is no readily available secondary source data that measures the extent of unionization in the food retailing industry. Therefore, the data collection phase of this research encompassed two parts. First market structure data was gathered from Metro Market Studies' Grocery Distribution Guides and from Bureau of Census' Census of Retail Trade for selected years. Second, a three stage survey procedure was used to measure unionization. This analysis views unionization as a structural variable. Just as market structure is described by structural variables as four-firm concentration, a measure for unionization should also be based on a structural concept. Unionization as a: structural variable should not be confused with performance measurements of union strength such as an index of wage and benefit packages. An area may be fully unionized and maintain a strong union but not be able to obtain much in the way of 25 26 benefits and increased wages15. A case in point is Southern Illinois in the 1960's. The people of Southern Illinois are traditionally of strong union sentiment, dating back to the mineworkers. The food retailing industry' was fully unionized and maintained a strong union but to no avail. The union could not achieve any gains because the area was poor and the food retailing industry was not modernized, resulting in a situation where there was nothing to gain. There are several conceivable structural measures of union extent such as the proportion of employees unionized in a market or the percentage of market shares unionized. Although it is preferable to be as precise and comprehensive as possible when constructing any variable, a trade-off exists with the costs involved in collecting data. Therefore, the only variables used to measure the extent of unionization :hi ea market are based on summing unionized market shares. SAMPLE SELECTION AND SURVEY PROCEDURE The markets included as part of this study represent most of the United States with the exception of Hawaii, Alaska, and New England. Hawaii and Alaska are excluded because their isolated location puts these states in a favorable position for exploitive behavior which distorts the food system economy. If studied, they should be examined as case 15 Harrington, The Retail Clerks, p. 58. 27 studies, not as part of an econometric model. New England was excluded because of inconsistencies with Census data. Table 3.1 presents the percentage of markets represented in this study from each region as defined by UFCW bargaining regions. Each region is represented by at least one-half of the markets in it, with the exception of New England and Hawaii for reasons noted above. TABLE 3.1 Geographic Dispersion of Markets in Sample Percentage Number of Number of Of Markets Markets Markets In A Region Geographic Included In Metro Included Region In Study Studies In Sample Southeast 30 45 66.7% Mid-Atlantic 21 26 80.8% N.E. Central 2” 34 70.6% N.W. Central 10 20 50.0% South Central 18 36 50.0% Northwest 5 7 71-"% West 17 22 77.3% N.Y.-N.Jers. 6 8 75.0% New England 0 1A 0.0% Hawaii 0 1 0.0% Total 131 213 61.5% The typical SMSA in our sample had an average of $649,AN6,282 grocery store sales in 1977. The average SMSA's grocery store sales for the population is $390,033,632. Figure 3.1 compares the distribution of markets, classified by the amount of grocery store sales in 28 1977, for the population and the sample. Of the 277 SMSA's composing the population, 67 of them have) grocery sales under 100 nfillion dollars. Eighty-seven more SMSA's have sales ranging between 100 and 200 million,dollars. The sample does not contain any markets with sales below 100 million dollars, and has only’ 24 SMSA's with sales between 100 and 200 million dollars. For SMSA's with sales over 200 million dollars, the sample is highly representative of each category. The reason why the sample does not contain many of the smaller markets is twofold; many of the SMSA's are newly created since the 1967 and 1972 census, and Metro Market Studies supplies data for only 218 of the SMSA's. The unionization questionaire and survey procedure were planned to obtain the information needed at the lowest transaction cost to the firm being surveyed. The questionaire can be found in Appendix A. Questions were asked to find out if an operator was unionized in 1967 and in 1980.16 The survey sample was limited to the top ten operators, ranked by local market share, in each of the one hundred thirty-one SMSA's. A firm operating in more than one market is counted seperately for each market it operates in. Metro 16 In each market, a firm may operate any number of stores. Each of these stores may or may not be unionized. Only one questionaire was sent, ususally to a firm's heaquarters. Depending on how the firm answered the questionaire, all stores are assumed to be unionized or not unionized. 90‘ Number XXXXXXX of SMSA's“ X X in Range ‘ X X ‘ X X 80‘ X x “ X X X X X X ‘ X X 70“ X X “ X X ‘XXXXXX X “ X X “ X X 60“ X X “ X X “ X X “ X X “ X X 50“ x X “ X X A X X “ X X ‘ X X 40“ X X “ X X ‘ X X x X . . X i 30‘ X i . X . x X . c I ..... I A I I 20‘ i * c I I I I I I " I I 10“ l I c I I “ I I c I I c I I 210’" ‘166' to 200 Figue 3J; "2.01)"~ to 300 29 XXX : POPULATION DISTRIBUTION ——- : SAMPLE DISTRIBUTION !*' : BOTH DISTRIBUTIONS X X X I I I I I I I I *XXXXXX I _____ I * *XXXXXX I I ..... lxxxxAXIlllllfililllxxxxxx I I I ..... I I I ..... I I I I I I I I I I I I I f I I I I I I I I I I I I I I I ’360' “Add“ ‘566“ "760‘ 1,666 “7'66 to to to to to PLUS "00 500 700 1,000 1,500 -3125 RANGE or SMSA, GROCERY STORE SALES (000,000)- Comparison of Distributions for the Population and Sample 30 Market's 1981 Grocery Distribution Guide was used to determine the top ten operators in each market. Voluntary and cooperative wholesale groups were excluded from the ten operators chosen because they are made up of many retail firms who behave independently from one another. Convenience stores were also excluded because they serve a distinctly different retail function than full line grocery stores. From the standpoint of the competitive process, convenience stores ck) not compete with supermarkets for a consumers major food buying trips. Furthermore, they are all nonunion establishments, providing no variation for this study to examine. Thus, chains and independent grocery stores, which are predominately supermarkets, comprise the sample. Although there are 131 SMSA's, the sample contains only 1,010 operators. This is because in some of the smaller SMSA's fewer than ten operators account for nearly all grocery sales. Progressive Grocer reports in it's 48th Annual Report pf the Grocery Industry (1981) that 116.6 percent of grocery sales in the U.S. are sold by chain stores, A7.7 percent by independent stores, and 5.6 percent by convenience stores. Supermarkets of $1,000,000 in sales or more account for 77.3 percent of all grocery store sales. Chain supermarkets account for A6.6 percent and independent supermarkets account for the remaining 30.7 percent. 31 Our sample accounted for 64.0 3percent. of’ all grocery store sales in the United States. Chain supermarkets accounted for 56.9 percent and independent supermarkets accounted for the remaining 7.1 percent of sales17. The difference between the population and the sample exists for several different reasons. The population is for the entire United States, whereas the sample only examines stores in SMSA's. Furthermore, the sample includes only SMSA's that have been in existence for at least 5 years if not 10 years and these are the larger SMSA's. Lastly, the sample includes the 10 largest operators in an SMSA. All of these factors act to push up the percentage of chain operators in the sample relative to the population. The unionization data collection was carried out in three steps; a telephone survey' to the largest food retailing firms, a mail survey to the remainder of the sample, and the UFCW's follow-up providing any missing data for 1980. The methodology used to determine these numbers is as follows. Market shares for chain operators and independent operators included in the sample were summed in each SMSA. The total shares of chain operators and of independent operators were then multiplied by the grocery store sales of all establishments in the SMSA as reported by the Bureau of the Census. This identified dollar sales for chain operators and for independent operators included in the sample for each SMSA. Dollar sales for chains and for independents were summed across markets, giving the total amount of grocery store sales accounted for in the sample, as well as the division of sales between chain operators and independent operators in the sample. Percentages were then calculated using U.S. sales as a denominator. 32 The telephone survey was conducted during the early weeks of July, 1981 and covered the thirty-five largest food retailing firms in the United States. These firms have stores in several SMSA's, so obtaining information from their headquarters substantially decreased the number of mail questionaires administered. The telephone survey provided answers for thirty-two percent of the total sample being surveyed. The mail questionaire was administered in three mailings during late July, midAugust, and early September, 1981. Addresses were found in AT&T Telephone Books and in Progressive Grocer's Marketing Guidebook 1981: The Blue Book pf Grocery Distribution Forty-one percent of the operators surveyed replied, providing additional union information for twenty- six percent of the total sample. The UFCW provided information for the remaining forty-two percent of the sample, completing a data set describing unionization in 1980. Between the telephone survey and the questionaire, data for 1967 was obtained for approximately 60.0 percent of the operators. The UFCW was not willing to supply the missing information about unionization in 1967. Therefore, data describing unionization in 1967 was incomplete and could not be used. 33 DESCRIPTIVE ANALYSIS: UNIONIZATION Q: OPERATORS Of the 1,010 operators surveyed in 131 SMSA's, 57.9 percent are unionized. A great amount of variation in unionization exists among operators which is attributable in part to the type of firm (chain or independent), the size of the operator's market share, and the operator's geographic location. Table 3.2 presents the relationship between the number of operators unionized and the type of firm. It was expected that there would be a large difference in the percentage of unionization between chains ankl independents. Chains are defined as grocery retailers who operate eleven or more stores. Independent retailers operate ten are unionized and dividing that number by the total summation of market shares surveyed for each of the 131 SMSA's. The second measure is the most likely alternative; the sum: of unionized operator's market share (UN80). The ratio measure (PCTUN80) may slightly inflate the actual percentage of unionized market share because the smallest stores with the least market share are the least likly to be unionized and they are the most likly to be excluded from the survey. On the other hand, if the survey misses a large operator who is unionized because that business is incorporated into in a wholesaling group's reported market share and it was not able to be broken out, the ratio measure will more accurately reflect actual union stength than the raw sum. The two measures are highly 42 correlated as the product moment correlation of .827 indicates, and they are significant at the one percent level. Unionization lg Markets: 1980 The second section of this chapter suggested that the degree of unionization in markets may be related to several factors. This section will examine those hypotheses. Table 3.7 presents data on the relationship between the level of unionization in a market and the size of the market. Segal (1964) suggested that the degree of urbanization was correlated with unionization. Market size is used as a proxy for urbanization and it is measured by grocery store salesin 1977.19 It was expected that larger cities wouLd be more unionized than smaller cities. This seems true but the amount of variation explained between the two variables is small, with a correlation coefficient of .286, although significant at the one percent level. Table 3.8 presents data on the relationship between the extent of unionization in local food retailing markets and the percent of the state's workforce that was unionized in 1978. State union share is ineasured as ea percentage of employees unionized in nonagricultual establishments. One would expect a positive association between the two. For 19 The actual census data series used is the 1977 Grocery store sales of establishments with payroll. This is a subset of a larger series of all grocery store sales. 43 TABLE 3.7 Market Unionization and Market Size ---------- Size of Market--—-------- Percent ($1,000,000) of the 100 200 300 500 Market to to to to 1,000 Unionized 200 300 500 1,000 Plus Total 0-20 4 4 2 2 1 13 16.7% 12.1% 6.9% 8.7% 4.6% 9.9% 20-40 3 6 4 2 1 16 12.5% 18.2% 13.8% 8.7% 4.6% 12.2% 40-60 6 7 7 6 1 27 25.0% 21.2% 24.1% 26.1% 4.6% 20.6% 60-80 3 4 6 5 3 21 12.5% 12.1% 20.7% 21.7% 13.6% 16.0% 80-90 3 5 2 2 4 16 12.5% 15.2% 6.9% 8.7% 18.1% 12.2% 90+ 5 7 8 6 12 38 20.8% 21.2% 27.6% 26.1% 54.5% 29.0% Total 24 33 29 23 22 131 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% states less than 20.0 percent of the work force unionized, markets unionized. and markets, 40 percent these of the states percent unionized or more. are workforce less than unionized. .366, signifcant at the one percent level. 60.0 approximately 74.0 percent of the food retailing percent The reverse is true for states with between 20 those approximately 75.0 percent of the markets are 60.0 The correlation coefficient is Table 3.9 presents the relationship between unionization and operator section. geographic location. unionization Southeast which is Market was the least unionization presented in unionized parallels last and the 44 TABLE 3.8 Market Unionization and State Unionization Percent --Percent of the State Unionized—- of the Between 20 Market Less than and Unionized 20 Percent 40 Percent O- 20 11 2 22.0% 2.4% 20- 40 12 4 24.0% 4.9% no. 60 14 13 28.0% 16.1% 60- 80 8 13 16.0% 16.1% 80- 90 4 12 8.0% 14.8% 90-100 1 37 2.0% 45.7 Total 50 81 100.0% 100.0% Northwest, West, and New York - New Jersey area are the most unionized. Table 3.10 presents the relationship between the level of unionization and the absence or presence of right-to-work legistlation. When right-to-work legislation is in effect, the level of unionization is eXpected to be substantially less than in states where legislation is not in effect. As table 3.12 indicates, where right-to—work leglislation is in effect, approximately 78.3 percent of the market is less than 60.0 percent unionized. In markets where right-to-work legislation does not exist approximately 75.2 percent of the market is greater than 60.0 percent unionized. The 45 TABLE 3.9 Market Unionization and Geographic Region ---Percent of the Market Unionized--- 0 20 40 60 80 90 Geographic to to to to to to Region 20 40 60 80 90 100 Total Southeast 10 8 8 3 1 0 30 33.3% 26.7% 26.7% 10.0% 3.3% 0.0% 100.0% Mid-Atl. 1 4 6 5 2 3 21 4.8% 19.1% 28.6% 23.8% 9.5% 14.3% 100.0% N.E. Cntr. 1 0 5 6 5 7 24 4.2% 0.0% 20.8% 25.0% 20.8% 29.2% 100.0% N.W. Cntr. 1 0 2 2 2 3 10 10.0% 0.0% 20.0% 20.0% 20.0% 30.0% 100.0% s. Central 0 4 5 3 3 3 18 0.0% 22.2% 27.8% 16.7% 16.7% 16.7% 100.0% Northwest 0 0 0 0 1 4 5 0.0% 0.0% 0.0% 0.0% 20.0% 80.0% 100.0% West 0 0 1 2 0 14 17 0.0% 0.0% 5.9% 11.8% 0.0% 82.3% 100.0% N.Y.-N.J. 0 0 0 0 2 4 6 0.0% 0.0% 0.0% 0.0% 33.3% 66.7% 100.0% Total 13 16 27 21 16 38 131 9.9% 12.2% 20.6% 16.0% 12.2% 29.0% 100.0% correlation between unionization anui the absence of legislation is level. .568 and is significant at the one percent Table 3.11 shows the relationship between the percentage of the market unionized and market structure as measured by the four-firm decreased sample size inconsistencies in data. concentration of ratio 118 is (CR4) used for because of Segal (1964) suggested that highly concentrated markets would be highly unionized since it is to the unions advantage to organize large firms. The 46 TABLE 3.10 Market Unionization and Right-to-Work Legislation Percent of the RTW RTW Market Leg is Leg is Unionized Present Absent Total 0- 20 11 2 13 23.9% 2.3% 9.9% 20- 40 11 5 16 40- 60 13 14 27 28 3% 16.5% 20.6% 60- 80 7 14 21 15.2% 16.5% 16.0% 80- 90 3 13 16 6.5% 15.3% 12.2% 90-100 1 37 38 2 2% 43.5% 29.0% Total 46 85 131 100.0% 100.0% 100.0% percentage of the market unionized was not correlated to CR4, as expressed by the product moment correlation of -.035 with a significance of .705. Although no relationship was found to exist in 1980 to support that hypothesis, one may exist when other factors are controlled for in the study. The last table in this chapter' is 'table 3.12' and it presents the relationship between the alternative measure of unionization (UN80) and market structure as measured by four-firm concentration in 1980. A weak positive relationship exists between the two variables, with a product moment correlation of .16, significant at the ten percent level. 117 TABLE 3.11 Market Unionization (PCTUN80) and CR4: 1980 Percent --Four Firm Concentration Ratio-- of the 0 40 50 60 Market to to to to Unionized 40 50 60 100 Total 1980 0- 2O 1 2 4 5 12 4.4% 5.7% 11.4% 20.0% 10.2% 20- 40 5 2 4 3 14 21.7% 5.7% 11.4% 12.0% 11.9% 40- 60 6 8 7 5 26 26.1% 22.9% 20.0% 20.0% 22.0% 60- 80 3 7 6 4 20 13.0% 20.0% 17.2% 16.0% 16.9% 80- 90 4 2 4 1 11 17.4% 5.7% 11.4% 4.0% 9.3% 90-100 4 14 10 7 35 17.4% 40.0% 28.6% 28.0% 29.7% Total 23 35 35 25 118 100.0% 100.0% 100.0% 100.0% 100.0% The relationship between union strength in a market and several factors have been examined in this section. The strongest relationships existed between unionization and the presence cu? right-to-work legislation, geographic region, the percentage of nonagricultural workers in the state who were ‘unionized, and inarket size. Concentration presented inconclusive associations with unionization. These will all be examined further in the next chapter. Market Summation of Market Shares Unionized 1980 0- 15 15- 25 25- 35 35- 45 45- 60 60-100 Total Unionization (UN80) and CR4: 48 TABLE 3.12 1980 --Four Firm Concentration Ratio-- 0 to 40 LA) 13.0% 26.1% 21.7% 13.0% 13.0% 13.0% WWWU'IO 100.0% 40 to 50 N 5.7% 11.4% 4.1: 20.0% \0 25.7% 22.9% 14.3% 35 100.0% CD 50 to 60 11.4% 11.4% 11.4% 20.0% 9 25.8% 7 20.0% 35 100.0% 60 to 100 16.0% 12.0% 20.0% 8.0% 16.0% 7 28.0% 25 100.0% Chapter IV THEORY AND MODEL SPECIFICATIONS INTRODUCTION Industrial organization theory has yet 13) provide a universally accepted explanation of how market structure and unionization interact with one another. John Kenneth Galbraith developed a theory of counterveiling power in American Capitalism which postulates a possible relationship. However, there has been no empirical test of the hypotheses. Several economists, including Weiss (1966) and Hendricks (1975), examined the effect of unionization and market structure on wage levels. This, however, is not the same issue as examined in this thesis. Weiss and Hendericks both examined how product market structure and unionization affected a performance variable, wages. This thesis examines how the level of unionization and other elements of market structure, most notably seller concentration, are related. The next section of this chapter is devoted to explaining Galbraith's theory of counterveiling power. The remaining sections will specify models to test the hypotheses. 49 50 THEORY OF COUNTERVEILING AND COALESING POWER Counterveiling power can be a useful regulatory force in the economy. It works when organized or large buyers and sellers offset each others power and settle upon a market price that approximates the competitive price. Galbraith's theory predicts one side of the market will organize in response to organized power on the other side. Galbraith argued that this result would only break down in a period of excess demand (Galbraith, 1956). He recognized that counterveiling power might then become coalesing power, where the input suppliers to an industry and industry management combine strength and exert market power against purchasers of the industry's products. Critics of Galbraith's theory have pointed out that coalesing power is more widespread and is the inevitable result of such bilateral bargaining in most industries (Adams, 1976). Regardless of whether the outcome is counterveiling or coalesing power, a basic hypothesis necessary for both is the idea that concentrated power on one side of a market engenders a counterpart on the other side. That is the hypothesis which this thesis explores. Segal (1964) assumed that the hypothesis that we seek to test is valid. He then proceeded to reason that in markets of high concentration and high unionization, the union would have considerable power which they would use against firms to increase wages. The firms would in turn exert market power to pass wage increases on to the consumer. Segal 51 completely dismissed the counterveiling power hypothesis for such structural configurations. Segal (1964) also suggested other reasons why concentrated industries would tend. to 'become 'highly unionized. Noncompetitive market structures are usually associated with relatively large size establishments which are potentially more profitable to organize than small ones. Also, the propensity of workers to organize is greater in large firms than in small ones beause of a higher degree of alienation between workers and management. Oligopolistic firms are also under closer public scrutiny than their competitive counterparts. This sometimes makes the firm easier in) unionize because management fears adverse publicity. Oligopoly firms also may have economic rent to share. The concentrated market stucture itself exists because of barriers to entry which function to exclude new firms. In addition, the pricing policy of an Oligopoly structure would benefit a union by assuring more uniform pricing. Increased wages could simply be passed on by uniform price hikes. Nonunion firms would conform to the wage hikes of the unionized market leaders because of the threat of unionization. The reverse effect, the impact of unionization on concentration, is slightly more complicated. If strong unions existed and tried to force wage hikes in the face of a competitive structure, they could succeed only' to the 52 extent of an employment effect. If prices increased, new nonunion firms could enter the market and displace union firms for barriers to entry are low. If the firms had to enter as unionized firms however, there would be no advantage over union firms. Either way, this should not increase market concentration. There is an alternative view about unionization in a market. Northrup and Storholm (1967) suggested that the degree of unionization within a market structure could act as a barrier to entry.20 Labor costs in food retailing are more than fifty percent of total operating costs.21 Unionized workers generally are paid more than nonunion workers, raising the cost of entry to a firm, if a firm had to enter as a unionized establishement. In this way, unionization would act as a barrier to entry, acting to increase. concentration. This suggests that the level of concentration would be dependent on the level of unionization, as well as other structural variables. In summary then, this thesis is an exploration of the first part of Galbraith's theory of counterveiling power; power rises in response to power already in the market. Herbert R. Northrup and Gordon R. Storholm, Restrictive Labor Practices 12 the Supermarket Industry, Assisted by Paul A. Abodeely, Industrial Research Unit Study No. 44 (Philadelphia: University of Pennsylvania Press, 1967), P. 59. 21 Progressive Grocer, 47th Annual Report of the Grocery Industry (New York: Progressive Grocer Company, (1980)), p. i0. 53 This hypothesis will be tested for both the effect of unionization upon concentration and the converse. Moreover, both the lagged effect and the contemporaneous effect will be tested. This sets up four tests of the hypotheses that power rises in response to existing power. The first two tests are that where high concentration exists, unionization occurs in response to it. This can be tested by examining the lagged as well as the contemporaneous effect of four-firm seller concentration on unionization. We hypothesize that where there is high concentration, labor will have unionized in response to it and a high percentage of the market will be unionized. The last two tests of the theory is the effect of unionization on concentration. Since we do not have adequate data on unionization prior to 1980, the test can only examine the contemporaneous relationship. If unionization is positively associated with an increase in concentration, as hypothesized, it suggests that it is a barrier to entry. The next section presents models to test the hypotheses using data from local markets in the food retailing sector. 54 UNION MODEL SPECIFICATION Dependent Variables Percentage pf the Market Unionized 1980 (PCTUN80): Percentage of the market unionized in 1980 was calculated by summing the shares of stores in a SMSA who are unionized and dividing it by the total sum of shares of stores surveyed in that market. The number was then multiplied by 100. Market share data for the survey was obtained from Metro Market's 1981 Grocery Distribution Guide. As was mentioned in chapter three, this measure may slightly overstate the amount of unionization in a market because only the ten largest firms in a market were surveyed and the largest firms are most likely to be unionized. Summation pf Unionized Market Shares 1980 (UN80): This is an alternative specification of unionization in a market. The variable is measured by summing the shares of unionized firms. This variable may slightly understate the level of unionization in the market because the market share of any union firm below the top 10 firms included in the survey will be left out. Independent Variables Right-To-Work Legislation (RTW): This is a binary variable to account for the absence or presence of right-to-work legislation in a state. In the presence of legislation, the variable equals one. The presence of right-to-work legislation gives unions an institutional disadvantage 55 because it builds in a free rider problem. An employee does not have to be a member of the union to reap the benefits that a union may bring forth. In a state without right-to-work legislation, if a union is voted in, all employees must join. This provides more money for the union to operate and that alone will strengthen the union. Most states with right-to-work legislation are located in the Southeast and South Central regions of the country. This variable was hypothesized to have a very strong and negative impact on the level of unionization. Number of Large Food Chains (NFC): This variable measures how many large food chains were in each market in 1967. A large food chain is defined as a firm with total retail sales of $500 million or more in 1972. There are 22 such chains.22 The number of large food chains is hypothesized to be positively related to unionization. Most of the large food chains are unionized for two reasons; they are an easy target for organizing and also, large chains are more apt to be unionized because of accretion clauses that automatically extend representation rights won in one locality to all localities where that firm operates. A&P Exit Variable (EXAP): This variable is a binary variable to account for A&P's unique behavior as a large food chain. A&P retrenched during the 1970's, exiting many markets and usually doing so by pulling out whole divisions 2 See Appendix C for the list of large food chains. 56 rather than just closing unprofitable stores. It is hypothesized that a negative relationship exists between A&P exiting and unionization because it is suspected that many times A&P left its market share to independents who are most likely nonunion firms. Four Firm Concentration Ratio (CR4): This study will employ four different measures of four-firm concentration. Three are Census measures of CR4 covering different years, 1967 (CRC67), 1972 (CRC72), and 1977 (CRC77). The remaining measure (ACR480) is for 1980; it is based on the 1977 census CR4 and adjusted to 1980 by the change in concentration as provided by Metro Market's 1978 and 1981 Grocery Distribution Guide's. This method is used because Metro Market is a reliable source for changes in concentration between years but the most accurate data available for the level of concentration is Census data. As was explained in the theory section, it is expected that concentration will be positively related to unionization for all years. No hypothesis is presented with regard to the relative importance of lagged or contemporaneous concentration. Market Size (MS): Market size was measured by grocery store sales of all establishments in a market in 1972 as reported by the Bureau of Census' Census pf Retail Trade. Market size serves to test the hypothesis that large cities are easier to unionize due to the sophistication and alienation of their workforce. Market size is hypothesized to be .57 positively related to unionization. However, measurement biases of the dependent variables may influence the relationship. There are two alternative measures of unionization. The percentage of the market unionized overstates the extent of unionization in a market; the summation of market shares unionized will most likely understate the extent of unionization. Smaller markets will have a more accurate measure of unionization in either case, because more of the firms in the market were included in the survey. Medium and larger sized markets will not be as accurately represented. If PCTUN80 is the dependent variable, MS is expected to be biased in a positive direction. A positive relationship between unionization and market size is hypothesized regardless of which measure of unionization is used, but PCTUN80 will bias the relationship upwards because the largest firms in a market are the most likely to be union firms and only the largest firms are surveyed in larger markets. If UN80 is the dependent variable, the coefficient for MS is expected to be biased towards zero. This is because the larger the city, the smaller UN80 will be since the top ten firms would comprise such a small amount of the total market share. In summary, both measures of unionization are hypothesized to be positively related to market size but the size of the coefficient and the significance of it will vary because of the bias in measurement. 11' So cl HE 58 Market Growth (MGR): Market Growth was calculated by taking the difference between grocery store sales of all establishments in a SMSA from 1967 to 1977 and deflating the difference by the consumer price index for food at home. This was then divided by grocery store sales in 1967 to yield a percentage term. It is not clear how market growth would influence unionization. New entrants would face easier entry given higher growth rates but there is no way of telling if the new entrants would be union or nonunion firms. Much of the growth occured in the Southeast and South Central regions of the country and many large food chains have been trying to break into those markets. However, it would also be easier for independents, who are probably nonunion. Therefore, no hypothesis concerning the sign of the coefficient is made. Percent pf the State Unionized lg 1978 (PSUN78): This variable is the percentage of the state's nonagricultural workforce unionized as of 1978. It is an alternative to the binary variable right-to-work, and is a proxy for quantifying the population's attitudes about unionization within the state. It is hypothesized to be positive, indicating unionization in retailing is related to the same variables as unionization in other industries. 59 MODELS TO PREDICT UNIONIZATION The complete model used to predict the percentage of the market unionized in 1980 is summarized in equation 4.1. The hypothesized signs of the coefficients are summarized beneath the equation. The model used to predict the summation of market shares unionized in a market for 1980 is the same. 4.1 PCTUN80 = a + a RTW + a NFC + a EXAP + a CR4 a <0 a >0 a (0 3 >0 a MS + a MGR a >0 a 0 where: PCTUN80 = Percentage of the market unionized. UN80 = Summation of unionized market shares. RTW = Binary variable equaling one where there is right-to-work legislation. NFC = Number of large national food chains in the market in 1967. EXAP : Binary variable indicating A&P exited the market. CR4 = Four-firm concentration ratio for one of several years. MS = Market size measured in 1972 grocery store sales. 6O MGR : Market growth from 1967 to 1977, deflated by the consumer price index for food at home and expressed in a percentage term. PSUN78 = Percentage of the nonagricultural workforce unionized. CONCENTRATION MODEL SPECIFICATION Dependent Variables: Four-firm Concentration, 1977 (CRC77) and 1980 (ACR480): Two levels of four-firm concentration will be analyzed; one for 1977 based on Census measures of CR4 in grocery retailing and one for 1980 based on the 1977 Census ratio but adjusted to 1980 by the change in concentration as measured in Metro Market's Grocery Distribution Guides. Control Variables: Initial Four-firm Concentration Ratio 1967 (CRC67): Initial concentration for the period examined, 1967-1980, is measured by 1967 Census data. It is expected that concentration will be positively related to initial concentration but the size of the coefficient will be less than 1.0 since at high initial levels of concentration, a change is more likely to be in a negative direction than at low levels of initial concentration where a change is most likely to be positive. _fl§rket Size (MS): Market size is also a control variable. It is defined as 1972 sales of grocery stores with payroll 61 as reported in the U.S. Census pf Retail Trade. Markets are also conglomerations of urban and suburban territories which have different characteristics. Many times firms operating in suburban markets will not venture into inner city areas. This fosters growth by independents and acts to keep concentration lower. Concentration is also apt to be reported lower than it actually is because the SMSA market area defined is much larger than the actual relevant market. Thus, market size is hypothesized to be negatively related to concentration. Market Growth (MGR): Market Growth was calculated by taking the difference between grocery store sales of all establishments in a SMSA from 1967 to 1977 and deflating the difference by the consumer price index for food at home. This was then divided by grocery store sales in 1967 to yield a percentage term. A high level of market growth is expected todecrease concentration because high market growth allows firms to capture new customers rather than try and compete customers away from market leaders. Market growth is hypothesized to be negatively related to concentration. Other Independent Variables: Number pf Large Food Chains (NFC): The number of large food chains is measured by the number of food chains in a market whose sales exceeded $500 million in 1972, excluding A&P because of its unique behavior. A list of these firms can be found in Appendix C. This variable is defined with a 62 cut-off point of $500 million because in 1967, chains of this size were involved in several markets, and could potentially cross-subsidize stores. This variable attempts to indicate the nature of a market's conglomerate structure. Conglomerates have the resources to outlast single market firms by cross-subsidizing when competition is intense. They can also outspend smaller firms for advertising which can be a signficant barrier to entry. It is suspected that as a group, conglomerate firms act to increase concentration. Because they are rivals in several markets, intense competition in one market could easily set off retalitory strikes in many others. This provides an incentive to the conglomerates to compete carefully and protect not only their own market shares but other conglomerate firms, too. Therefore, it is hypothesized that a positive relationship exists between the number of large food chains in 1967 and concentration in later years. Summation '9: Unionized Market Shares 1980 (UN80): Unionization was measured by summing the shares of unionized firms in local markets. It is hypothesized that unionization is either neutral or is positively related to concentration, depending on whether it acts as a barrier to entry as was explained in the theory section of this chapter. Conglomerate Mergers, 1967-1976 (CMM76) and 1967—1980 (CMM): This variable is the number of large nonfood chains or 63 foreign food chains that entered a market by merger. Large nonfood retailers are defined as firms with assets of $100 million or more. It is hypothesized that conglomerate mergers will be positively related to concentration for several reasons; potential cross-subsidization, large advertising accounts, multimarket cooperation, and improved efficiency from new innovations by foreign food chains. Horizontal Mergers, 1967-1976 (HMM76) and 1967-1980 (HMM): This variable is a measurement of market share acquired from a firm in the top four in the year of acquistion from 1967 to 1980. If a firm is acquired and it increases the market share of the buying firm enough to put it in the top four- firms, the increase in CR4 is reported for this variable. It is hypothesized that this variable will be positively related to concentration. Entry By Merger, 1967-1976 (EBMM76) and 1967-1980 (EBMM): This variable is measured by the number of large food chains who entered the market by acquiring a firm already in the market. This introduces another conglomerate into the market and is expected to be positively related to concentration for all the reasons noted above concerning the presence of conglomerates in the market. Denovo Entry, 1967-1976 (ENT76) and 1967-1980 (ENTRY): From the basis of standard industrial organization theory, one might expect entry to reduce concentration. However, previous research by Cotterill and Mueller (1979) has shown 64 that de novo entry is positively related to 23 concentration. They suggest that this is due to the competitive struggle that a new conglomerate triggers when it enters a market. The market leaders and possibly the new conglomerate are in the best position to gain in such a struggle. As the smaller share chains and independents lose ground, concentration increases. Since these are opposing theories on the impact of entry, no relationship is hypothesized in this thesis. Exit Top Four, 1975-76 (EXTP476) and 1975-1980 (EXTP4): This variable measures how many large food chains exited who were among the top four-firms at the time of exit. Initially it will reduce concentration although in the long run it is hard to determine its effect. It is hypothesized to be negatively related to concentration. Exit of A&P, 1967-1976 (EXAP76) and 1967-1980 (EXAP): This is a binary variable, specified to equal one when A&P exits a market. No hypothesis is made as to the relationship between the two variables because when A&P exited, it withdrew entire divisions as well as unprofitable stores. [piling Firm in Market (FFRM) : Food Fair, one of the 22 large food chains, filed under Chapter XI of the Bankruptcy laws and left many markets, some in which it was a market leader. It exited at a massive rate during 1978, 1979, Ronald W. Cotterill and Willard F. Mueller, "The Impact of Firm Conglomeration on Market Structure: Evidence for the U.S. Food Retailing Industry," The Antitrust Bulletin . Vol. 5, No 3 (Fall 1980), p.5767‘ 65 1980. This variable is a binary variable pinpointing markets where this happened. It is hypothesized to be negatively related to concentration. Exit 23 Large Food Chains, 1967-1976 (EXIT76) and 1967-1980 (EXIT): This last exit variable is the exit of large food chains net of all the other exit variables. No hypothesis is made of its relationship with concentration because the exiting chains have low market shares, lending no immediate effect on concentration. MODEL 19 PREDICT CONCENTRATION The complete model used to predict concentration in 1977 and in 1980 are summarized in equation 4.2 and 4.3, resepectively. The hypothesized signs of the coefficients are summarized beneath the equation. 4.2 CRC77 a + a UN80 + a NFC + a CMM76 + a HMM76 3 >0 a >0 a >0 a >0 + a EBMM76 + a EXTP476 + a EXAP76 a >0 a <0 a 0 + a EXIT76 + a CRC67 + a MS + a MGR a 0 a >0 a <0 a <0 4.3 ACR480 = a + a UN80 + a NFC + a CMM + a HMM a >0 a >0 a >0 a >0 where: CRC77 ACR480 UN80 NFC HMM76, HMM CMM76, CMM EBMM76, EBMM \ EXTP476, EXTP4 EXAP76, EXAP FFRM EXIT76, EXIT CRC67 MS 66 EBMM + a EXTP4 + a EXAP + a FFRM >0 3 <0 a 0 a <0 EXIT + a CRC67 + a MS + a MGR 0 3 >0 a <0 a <0 Four-firm concentration for 1977. Four-firm concentration for 1980. Summation of unionized market shares in local markets. Number of large national food chains in the market in 1967. A measure for horizontal mergers. The number of conglomerate mergers in a market. The number of times large food chains entered by market extension mergers. The number of large food chains exiting when it was one of the top four-firms in the market. Exit of A&P in the market. Exit of Food Fair in market, 1978-1980. Exit of large food chain net of above. Initial four-firm concentration, 1967. Market size measured in 1972 grocery store sales. 67 MGR : Market growth from 1967 to 1977, deflated by the consumer price index for food at home and expressed in a percentage term. Chapter V EMPIRICAL RESULTS This chapter presents the empirical results of the models developed in chapter four. The first section displays the results for models that estimate the extent of unionization in local food retailing markets. The second section displays the results for models that estimate the level of concentration. The third section recognizes that the levels of unionization and concentration may be simultaneously determined by a set of exogenous explanatory variables. As a second approach to the possible simultaneous nature of the model, two recursive systems are estimated where unionization is a function of lagged concentration, and current concentration is a function of current unionization. A third recursive system is also estimated, where unionization is a function of current concentration, but current concentration is not a function unionization. The last section presents an analysis of the results. Table 5.1 presents descriptive statistics for the data used in this analysis. Three statistics are presented for each variable; the mean, the minimum value, and the maximum value. 68 69 TABLE 5.1 Descriptive Statistics for Variables Variable Mean Minimum Maximum PCTUN80 65.3 2.1 100.0 UN80 40.7 1.5 100.0 RTW .4 0.0 1.0 NFC 2.4 1.0 7.0 CRC67 48.8 24.6 72.2 CRC72 49.8 26.6 80.5 CRC77 52.9 26.0 84.1 ACR480 50.5 23.9 82.3 MS .4 I1 308 MGR 15.3 -4.7 76.7 PSUN78 23.2 6.5 39.2 HMM76 1.0 0.0 14.8 EBMM76 .3 0.0 2.0 CMM76 .3 0.0 3.0 ENT76 1.4 0.0 9.0 EXT76 .4 0.0 3.0 EXAP76 .2 0.0 1.0 EXTP476 .1 0.0 1.0 HMM 1.1 0.0 14.8 EBMM .5 0.0 2.0 CMM 1.0 0.0 4.0 ENTRY 1.6 0.0 10.0 EXIT .7 0.0 3.0 EXAP .3 0.0 1.0 EXTP4 .2 0.0 2.0 FFRM .1 0.0 1.0 70 EMPIRICAL RESULTS 9: UNION MODELS This section explains the level of unionization as a function of several explanatory variables including concentration. Ordinary least squares is the estimation technique. Sample size ranged from 125 tn) 100 markets for the union equations. Table 5.2 displays the six estimated equations for model 4.1, where PCTUN80 is the dependent variable. Equation 5.2.a is a linear model including three independent variables to estimate the percentage of a market unionized. Market size and market growth are both control variables. Right-to-work is the most important variable in terms of explaining unionization. Both right-to-work and market size are of the hypothesized signs and they are statistically significant. There is I“) hpothesis for the relationship between market growth and unionization. Market growth was statistically insignificant. Equation 5.2.b is identical to the one above it except that the variable, number of large food chains is introduced into the model. As expected, it is positively related to the percentage of the market unionized and it is significant at the one percent level. The other variables are quite stable in their relationship to unionization. Equation 5.2.c adds concentration in 1967 to the equation above. It was expected that concentration would be 71 tam.m— ehp.hp cm>.>P .o:.>p cpm.wm .m>.:m OgunuuMum m PNF mNP mm— mm— mmp mmoz mmz. hma. omz. hmz. emz. 0mm. N: 30.: R: Amm.v ONII Amo.pv mm.l Amo.v mm.1 Am>.v ONO- Amo.v Po.l mo: e-Aoo.mv mm.m ouamo.~v mo.o e-Amo.mv No.» c-Apo.~v mp.w oquo.Nv oo.o n~m>.~V >o.op m: Ho>oa acoonoa no» on» as caucuuucmqm + Ho>oa acoonoa o>«u on» as caucuuucmqm nu Ho>oa acoonoa one on» an assauuucwdm - nucoaouuuooo nuaocon one nodauaaaunih nocmscm unmoq agmcuoto mean: Aowzaaomv co~»au«:0uc= no couumauunm c< N.m mqmcb Aom.Pv. cfimo.mv qu~.ov mm. mo.m om.omi Asm.v nfioc.mv nfiom.ov or. 32.0 hb.oml Aom.v IA>~.mv eAmo.ov 0N. mh.o am.0ml Am=.v 3A=~.mv o.~m.wv or. m>.o am.om1 uAmm.mv naao.cv mo.w mm.om1 caho.>v ~m.mmi omzmo< 550:0 NFUmU heomo omz 3km Inuit:innniunnluiiunnoanmuLm> unoccoaoucu null: omzahom m:.w: mm.mm Pm.Pm ma.mm om.oo «z.m5 unoogoucu “managem> acoucoaoa 72 positively related to unionization. Although it does have a positive sign, it is statistically insignificant. Concentration does not appear to have an impact on unionization. Equation 5.2.d uses concentration for 1972 rather than 1967. It has a positive but insignificant sign. Equation 5.2.e uses concentration in 1977 and it is also positive and insignificant. Equation 5.2.f uses concentration in 1980. It is positive and almost significant at the ten percent level. The diferences in results between the two concentration measures in 1977 and in 1980 are probably because of the way the variables are constructed rather than an inherent difference in a contemporaneous versus lagged relationship. Located in Appendix I) are three» additional equations where the percentage of a market unionized is estimated, but using the percentage of unionization in a state's workforce as an explanatory variable. Equation 0.1 is the same equation as 5.2.f. Equation D.2 introduces the new variable. It is negatively related to unionization in the market, contrary to expectations, but this often occurs when two variables are multicollinear. Equation D.3 deletes right-to-work from the equation. The percentage of unionization in the state's workforce then becomes positively related to unionization in the market and significant as hypothesized. 73 The next table presented, Table 5.3, presents regression models that explain the variation in the summation of unionized market shares in a market. Ordinary least squares has been used. Equation 5.3.a is a linear model including three independent variables of which two are control variables. Right-to-work: is negatively and significantly related to unionization (UN80), as hypothesized. Market size is positively related to unionization but barely significant. Market growth is positively and significantly related to unioniztion. The differences in how the independent variables relate to the two measures of unionization will be discussed at the end of this section. Equation 5.3.b is the same as the one above except it introduces the number of large food chains in a market into the equation. It is positively and significantly related to unionization. Equation 5.3.c introduces concentration for 1967 into the equation above. It is positively related to unionization, and significant at tflue ten percent level. Equation 5.3.d changes the concentration measure to 1972 and it is positively and significantly related at the one percent level. Equation 5.3.e changes the concentration measure to 1977 and finds the same relationship as does the concentration measure for 1980 in equation 5.3.f. 74 nzm.o— ehm.op tow.pp aoz.op app.mp upm.op pasnssnpm m ._. omm. .NP «mm. mwp omm. mN. pom. m~_ omm. mm, cow. mmoz mm notcsam unmoq hemcuveo mean: Aomzav nonanm nexus: confiscac: Lo couumauunm c< Ams.v mp. Aam.v Pm. Aom.v up. Amm.pv om. +AP>.FV om. -A>=.Nv mm. m0: “Pm.v oo.p Apm.v o>.F Amm.0 we." apo.v mm.P Asm.v ah.— fizz.F0 >>.= m: Ho>oa acootoa co» on» as caucuuucmum + Ho>oa accuses o>uu on» as assauudcmam .- Ho>oa penance one on» an unmoduucwum - accededuuooo nuances one codenaaaunia .Aom.~c. .Aos.mc .Aps.zv om. oz.o om.hpl efiom.~0 IA>~.mv camo.=v ms. 2m.o mm.>pl cA:Q.N0 cfiop.av camo.=v 0:. 30.0 PP.>pl +Amo.—V eamo.sv cabm.av mm. no.0 mN.>pI .Azm.m0 oaom.:v mh.o mp.>.t aaoo.m0 mm.o—i omam0< b>0m0 N>0¢0 500:0 0&2 35m IniunuiiuuinuuininilnoHomatm> acoucoaoccHunuiaiiulninuuiiuunini owza m.m mqm<9 om.o pm.m co.m mm.pp pm.mm am.wm uaoosoacm u.m.m o.m.m v.m.m o.m.m n.m.m a.m.m .o~na«na> ucoocoaoa 75 Appendix D contains equations using the percentage of a state's workforce unionized as an explanatory variable. The results are approximately the same» for the summation of market shares unionized as they were for the percentage of a market unionized so details will not be discussed. As can be seen, the two measures for unionization result in some different relationships among the variables, mainly concentration and market size, although market growth also differed. There was no hypothesis about the relationship between market growth and unionization. Market growth has a negative coefficient but it is not significantly related to the percentage of the market unionized in any equation. It is positively related to the summation of inarket shares unionized but it is only significant in the first two equations. When measures of concentration are introduced, its significance disappears. Market growth and concentration show a consistent correlation of about .30, significant at the one percent level for all years of concentration. Given how the relationship changes with the variables and measures of unionization, no conlusion is given. The two measures of unionization perform differently in their relationships to concentration and market size. The summation of market shares unionized is positively but insignificantly related to market size, and it is positively 76 and significantly related to concentration. The percentage of the market unionized is positively and significantly related to inarket size, but it is positively' and insignificantly related to concentration. Market size and concentration are negatively and insignificantly correlated for all cases of measurements of concentration. The paradoxical result for the two different measures of unionization may be attributable to measurement biases. In large markets, concentration will not be measured correctly because the area defined as the market is not the relevent area; it incorporates a far too large an area into the relevent market and thus understates concentration. Large markets also will have a great tendency to overstate the percentage of the market unionized. This will bias the hypothesized positive relationship between concentration and unionization towards zero, and tend to overstate a positive relationship ‘between unionization and size, for the dependent variable PCTUN80. Large markets, however, will tend to understate the summation of unionized market shares. This will bias the hypothesized positive relationship between unionization (UN80) and concentration upwards, and understate the positive relationshipl‘between unionization and size. Needless to say, the true relation between unionization and concentration probably lies somewhere between the estimated relationship for the two measures. 77 EMPIRICAL RESULTS 9: CONCENTRATION MODEL This section analyzes the determinents of the level of concentration, one of' which may be the level of unionization. Sample size ranged from 112 to 79 markets. The F-statistics, indicating how good the equations are overall, were significant at the one percent level for all equations. Table 5.4 displays equations where concentration in 1977 is estimated. Table 5.5 portrays equations estimating concentration in 1980. Each equation is examined to see the effect. of' each variable as ii; is added but the interpretation of the results is left for the end of this section. Equation 5.4.a is a linear model including three independent variables which are all control variables. Market size was hypothesized to be negative but it is positive and insignificant. Market growh was expected to be negatively related to concentration but it is positively related and insignificant. The coefficient on concentration in 1967 is positive, is less than one, and is statistically significant at the one percent level. Equation 5.4.b is the same as the one above except with the addition of unionization (UN80) in the equation. The control variables perform as they did in the last equation. Unionization is positively related to concentration and significant at the five percent level. '78 Ho>oa acoonon co» on» as acoOAuacmum + Ho>oH acoonoa o>uu on» as vascuudcmum .- Ao>oa acoosoa one on» so acoOquucmqm - .oucoqoduuooo cuoocon mononuconon :« oLo nodaouuouoia nonosam ammo; anecdote mean: rho. :« codumnucoocoo uo ceauoeguom c< =.m mam.p No.3 ~=.~ mm. mm.~ ms.. pm. om. oo. mm.» n.:.m Amo..0 Asm.v -A=~.av Asm._c -.Amo.~0 Aa=.v +Ams.—v A==.Fv +Aao..v Aom.v Am..v .mm... as mmo. so. ==.,- mo. .m.m s~.~ AP. .o.~ a~.~ am. Nm. co. as.» «.=.m A.P.Fv Amo..0 camo.mv “Po._v Apo.e ..Ao_.~0 Asm..v .nfiam..v Amm.v Aso.v .NN.NP a» «as. o_. es..- No. FA.F Pm. .~.m —~.~ pm. as. oo. no.e a.=.m Asc.Fc leo.ts .l.a.oc . is..v .lss..c .lss..c .Iso..c Ame.c As..c .ao.~F as amp. o.. on..- as. so. m~.~ Po.~ co. co. .o. -.o. m.=.m as...v “so..v .Aom.mv +Aao..0 +Azo..v +Aoa.pv ANA.V Aom.v .Fo.s_ a» awe. op. sm.—- A». F~.~ om.~ me. me. .o. .m.o— e.:.m Ams.v A:~.V naps.ov ..Aa~.mv Apm._c Acm.v Amm..v .mm.s. so Ame. so. cm... as. pm.m am. Po. so. om.» o.=.m Aoc.v As..v .Aom.ov ANN..V Aoo.pv Aom.PV .mm.o. .m ooe. mo. om.- A». mg. as. so. oz.a v.3.m AP=.PV Aoo.v .A.o.av Aoo.v APS.P0 .om.P~ OFF mom. ~.. co. co. mo. mo. mo.m. o.=.m Amm.pv Aap.v uAPp.ov ooANF.Nv .so.s~ N.P mom. ~_. am. so. so. Fo.m. p.=.m Amm.Pv Aom.e .Aso.av .Fm.mm ~P_ was. mp. Ah. so. o~.>. n.=.m oasnupnsm mmoz me me: a: pause osznaxm psn unoccoaoc:Hiiuliuuiinilliniiiiuuiuiiuliunililiiitl ssomo .oapnatn> acopcoaoa 79 Equation 5.4.c introduces the number of large food chains in 1967 into the last equation. It is hypothesized to be positively related to concentration and is; however, it is not significant. The significance of unionization as an explanatory variable drops substantially when the number of large food chains is added in. Market size also becomes very insignificant. Equation 5.4.d introduces horizontal mergers between 1967 and 1976 to the equation above. Horizontal mergers is hypothesized to be positively related to concentration. It is here but it is not significant. Market size changes sign and now show a negative relationship with concentration. The next equation, 5.4.c, introduces, market extention mergers from 1967 to 1976 into the equation. It is hypothesized to be positively related to concentration and is. The horizontal merger variable increases in significance, but the unionization variable decreases. Equation 5.4.f introduces conglomerate mergers into the equation above. It is hypothesized to be positively related to concentration and is. The other merger variables change in explanatory power; horizontal mergers increasing in explaining the variation in concentration and market extension mergers decreasing in explanatory power. The significance of the union variable drops dramatically. Market size is still negatively related to concentration and steadily increasing in significance. 80 Equation 5.4.g introduces the number of firms entering the market de novo from 1967 to 1976. No sign was hypothesized. Here it is positive but insiginificant. The next equation, 5.4.h, adds the number of large food chains exiting the market between 1967 and 1976 except for those in 1975 and 1976 who were among the top four in a market. It was expected to be negatively related to concentration. It is positively related but not significant. Equation 5.4.i introduces a binary variable measuring if A&P exited the market between 1967 and 1976. There was no hypothesis made for this variable because A&P pulled out entire dividions when it retrenched. It is positively related to concentration but not quite significant at the ten percent level. The last equation, 5.4.j, introduces a variable measuring the number of exits in 1975 and 1976 made by firms in the top four market positions. It was hypothsized to be negatively related to concentration but it is positively related, and significant at the ten percent level. Possibly this is because of excess capacity among the leading supermarkets, or a relaxed attitude by the FTC, allowing leading firms to purchase stores from the exiting firm. Table 5.5 displays equations where concentration in 1980 is estimated. Equation 5.5.a is :3 linear model including three independent variables which are all control variables. 81. Ho>oH acooson co» on» an assauudcmum + Ho>o~ acoosoa o>qu on» an acoo~uacmdm a. Ho>oH acoonoa one on» no auscuuucmum o .ou:o«o«uuooo nuoocon mononuconoa cu one oodaoauouois ooApo.NV Aza.0 oAso.mv o-Aoo.~v Amm.v Amo.pv Amm.v +Amo.pv namm.mv Amp.0 +A>m.pv Asm.v Asp.v o:m.m oh mNm. MN. mo.Nl we. om.ol 0m.w oo.N om.l Pb. 00.N mp. >5. m—.— Po. mo.op x.m.m ooAzm.~V Aom.v oAmm.mv Amp.v AwP.—V App.v Aw~.—v ooAbm.~v Amo.v +A-.pv Amm.v Amo.Fv .~:.m as was. om. ma..- am. we.. oz.~ mp. mm. mm.~ we. as. me. mo. mo.m q.m.m -—A>F.Nv Aom.v uAFm.mv Amp.pv Aoo.0 ANN.F0 o-Amm.mv A:F.V +Aph.pv Amm.v ANO.F0 Iow.m ab Poz. 2N. ow.Pl mm. w=.N 00.! Nm. N:.N NN. FF. >0. :0. 0-.p— «.m.m .OANO.NV Amo.wv IANw.mv Amz.v APP.—v noA:P.Nv ANm.v +Amo.pv Amw.v Aoo.Pv azm.o Oh Nwz. mN. @N.NI cm. 00.: ha. mN.N NQ. ON. oo.P =0. 2m.Np £.m.m ooAmo.~v Aum.v voz.mv A>—.—v qump.Nv Amm.0 +Ahc.wv Ao>.0 Ahm.v umo.b m5 own. MN. mo.NI hm. . oz. mN.N cm. 00. ab. :0. mm.Np m.m.m -A==.N0 Amm.v nfihm.m0 o-Awo.pv Aom.v Ae=.pv A~>.0 Aaw.p0 u>>.> m» own. 0N. op.NI mm. :o.N Na. 00. —o. co. 0:.ap u.m.m unapo.mv Amm.0 oA=>.mv Abs.v Aoo.pv amp.pv Aom.pv omc.m Fm mmz. NN. NP.PI Fm. NF.P ma. 0m.P mo. mo.mp o.m.m uoaoo.mv Ahm.0 qup.mv noo.pv Apo.pv Am:.P0 .mo.op pm ozz. MN. wh.l rm. 9:. PN.— 00. Fm.m9 U.m.m u-Aoo.mv Asm.v -AP=.>V Azo.v +Aoo.—v u:o.0p opp was. ON. 0m.l we. :5. ho. mo.mp O.m.m ooaom.~v AFN.V saw:.>0 ocAm~.~v noo.ON NPP oma. 0N. Fm.l 90. mo. 0N.=p n.m.m e.A=N.NV ANN.V cam:.>v oom.mN N—P N—a. PN. Nm. No. No.h— d.m.m Dayna» mmoz Na :02 m: >00m0 Immm zmhxm m acoocoaoccH 11 111111 amazoa .odpndta> peopcoaon nocoscm ammo; apocaono mean: comp ca :Oauonucoocoo no nodumsduom c< m.m mam<9 82 Equation 5.5.b introduces a union variable into the equation above. It is positively related to concentration and significant. Concentration in 1967 and market size perform as hypothesizd. Market growth was hypothesized to be negatively related to concentration but is positively related and significant. The next equation, 5.5.c, introduces the number of large food chains in the market in 1967. It is positively related to concentration as hypothesized but not significant. Unionization drops in significance when the variable is introduced. Equation 5.5.d introduces horizontal mergers from 1967 to 1980 into the equation. This is positively related to concentration but insignificant. Unionization again drops in significance. Equation 5.5.e introduces market extention mergers from 1967 to 1980 into the equation above. It was hypothesized to be positively related to concentration and it is but it is not significant. Unionization drops further in significance. The next equation, 5.5.f, adds a conglomerate merger variable specifying the number of conglomerate mergers from 1967 to 1980 that occured in each market to the equation above. It is positively related to concentration as hypothesized and it is significant at the five percent level. 83 Equation 5.5.g introduces the number of large food chains entering the market de novo from 1967 to 1980. It is positively related to concentration but insignificant. Equation 5.5.h adds the number of large food chains who exited the market between 1967 and 1980 exculding those who exited between 1975 and 1980 who were in the top four of the market. and excluding Food Fair stores «exiting the lnarket between 1978 and 1980. It was hypothesized to be negative and it is, but it is not significant. The next equation, 5.5.i, introduces a tdnary variable measuring A&P's exiting of a market between 1967 and 1980. No hypothesis was made and it is positively related to concentration, but not significant. Equation 5.5.j introduces the number of exits made by firms occupying one of the top four market positions between 1975 and 1980. It was expected to be negatively related to concentration but it is positively related and insignificant. The last equation, 5.5.k, introduces a binary variable measure, the effect of Food Fair leaving many markets during 1978, 1979, and 1980 upon filing bankruptcy under Chapter Eleven. It was hypothesized to be negatively related to concentration and it is. Both. measures of’ concentration basically' maintain the same relationships with the independent variables. Unionization starts (nu; being positively' related to 84 concentration but its significance drops rapidly as other variables are introduced into the equation. It would appear that unionization does not explain concentration levels. The number of large food chains in a market in 1967 is a variable to approximate the conglomerate structure in a market. It is positively related to concentration as hypothesized but it is never significantly related. This may be partly because it is correlated to unionization (.40, significant at the one percent level). The merger variables are all positively correlated with concentration. The horizontal merger variable climbs in significance as othe variables are introduced and stabilizes around the ten percent significance level. The market extention merger variable for 1967 to 1976 starts out significant when explaining concentration in 1977 but falls in significance as other variables are introduced; it is never significant when predicting concentration in 1980. The conglomerate merger variable is significant in all equations. The variabLe for denovo entry peforms differently over time but is mostly insignificant. When measuring the relationship between 1967 aux! 1976, estimating 1977 concentration, entry is never significant. Measured for the longer period used to esitimate concentration in 1980, it climbs in significance and in the fullest model is significant at the ten percent level. 85 The exit variables perform differently for the different concentration measures. Variables used if) estimating concentration in 1977 are EXT76, EXAP76, EXTP476. The first of these, EXT76, measures the number of large food chains exiting between 1967 and 1976. It is positively related to concentration and becomes quite significant. as the (other exit variables are introduced into the equation. The second exit variable, EXAP, is a binary variable measuring if A&P left the market between 1967 and 1976. This is positively related to concentration and is significant. The last exit variable used is EXTP476, a measure for the number of large food chains exiting the market in 1975 and in 1976 who were in the top four market positions. This was positively related to concentration but not quite significant at the ten percent level. This may be positively related to concentration because of excess capacity' in the market, indicating the top firms swallowed the exiting firms market share. Variables used to estimate concentration in 1980 for the longer time period, 1967 to 1980, performed differently. These variables were EXIT, EXAP, EXTP4, and FFRM. The varible EXIT, corresponding with EXT76, was mostly negatively correlated but never significant. The second variable, EXAP, was positively correlated but never significant. The third varible, EXTP4, measured the number of chains exiting who held a position in the top four of the market during the time period between 1975 and 1980. It was 86 positively correlated but never significant. The last variable, FFRM, is a binary variable to account for Food Fair exiting in a market between 1978 and 1980 when it filed under the bankruptcy laws. It is negatively correlated with concentration and significant. The control variables differed slightly in performance. Concentration in 1967 was stable for all equations in both models. Market size started out being positively related to concentration but ended up negatively related as explanatory variables were introduced; it was never significant. Market growth was positively related to concentration, but only significanltly related in the equations estimating concentration in 1980. The next section examines how unioniztion and concentraton act when modeled as a system of equations. EMPIRICAL RESULTS OF SIMULTANEOUS AND RECURSIVE MODELS This thesis is an investigation of the statistical relationship between two forces based on a theoretical postulate. Modeling the relationship is an interesting exercise because there is no way of knowing what the model should 'truly' be and one constantly runs the risk of biasing the results by misspecifying the proper relationship, (n' by using improper econometric estimation techniques, or both. 87 Looking first at concentration's effect on unionization, from chapter two, we see that historically there does seem to be a relationship. Statistically, this relationship was validated in the first section of this chapter (see Table 5.3) where concentration was found to be positively related to unionization. Of course, causality is not proved econometrically. It can be argued that the results of the model are invalid because of the estimation technique used. This is :3 valid criticism. But looking for the proper estimation technique raises the question of what exactly is the true relationship between the two variables. Because it can be theorized both that unionization affects and does not affect concentration, several alternative specifications are presented in this section. The first table is :3 simultaneous equation system. The next two tables are recursive systems where unionization is a function of lagged concentration (1972 and 1977) and current concentration is a function of unionization. The last table is a recursive system modeled so current concentration is a function of several variables, none of which are unionization, but unionization is a function of current concentration as well as other variables. Table 5.6 presents a simultaneous equation system. Three stage least squares has been used to estimate it. There are four systems of equations in the table. All four systems contain a fully specified unionzation equation with an 88 endogenous concentration in 1980 variable. The four systems do not all have a fully specified concentration equation but shows the effect of increasing to the full model. Concentration is positively related to unionization but is only weakly significant at the eleven percent level in the last system 5.6.4. Unionization is never significantly related to concentration. Table 5.7 presents the relationship between unionization and concentration using a recursive system. Unionization is estimated using concentration in 1972. When a large sample (111 observations) is used, concentration is positively related but in the small sample, a statistically significant relationship is not verified. Unionization never shows a statistically significant relationship when concentration is regressed upon it. Table 5.8 presents the same as 5.7 but with concentration measured in 1977. Concentration is not related to unionization. Unionization is not related to concentration. Table 5.9 presents a recursive system where concentration in 1980 is used endogenously in the unionization equation but unionization is not included in the concentration equation. System 5.9.4 includes the full concentration equation and the endogenous concentration variable is nearly significant at the ten percent level. The four models provide interesting results. The endogenous unionization variable is never statistically 89 as on «FF P—P mmoz as as F—p mmoz qumo.m0 Ama.v op.F :mhxm Amm.v A>~.V +Amw.Fv Asm.v —o.N N=.I mo.p m3. Amm.v mm. m.v mo. mp. oo.—I Nm.ol onhz.=v oaAwo.~v Abm.v Nm. mN. Fm.l :Aoo.ov +Ao>.—v Aeo.v mm. m—. m—. ofimm.>v o-Amm.mv Apo.0 we. NN. No. Foomo m0: 0: ZNmm Amp.v Asm.v mo.l mm.— Am=.v Apm.v mr. m=.N Aso.v Amm.v mr. m>.F Aoo.v Amm.v mp. mp.— zoz m: Ao>oa acoonoa co» on» as unusuuucmum + Ho>o~ ucoonoa oouu on» yo acoOuuucmum on Ho>oa acoouoo one on» an assauuucmum o ouco«o«uuooo nuoocon one nodunuuouoie o-A>~.~0 nuamo.m0 Awm.—V AmN.pv oe.~ Amm.PV ms.P ooaooato> acoucoaocca Amm.—c Po. Am..v mo. ANN..V mm. ANN..V mm. ow2x0< .ooozm mo._ ao.~ o_.- mz.~_ p.a.o.m Amm..v Ama.—V Lea.v mo. oo.m >..u .m.op n.m.o.m +Aos..v .mo..v ~m.~ m..- so.mp p.~.o.m Asm.v mo. so.mp p.—.o.m omz: 2:: unz .ooozm uaootoscH Aomzmo.o -AFQ.NV No.5 nahh.mv m>.o caew.m0 m>.m 0m: .o~no«no> acoocoaoa camp.m0 mm.ppu $0.. o.:.o.m oA—w.~0 >m.=—I m:.mm o.m.o.m voP.=v oo.>—I cm.op o.~.o.m oahp.:v po.>—I om.op o.p.o.m sax unmatoucH moanoano> ucoocoaoucn Aomzav c0«uou«:0uc: ”oanougo> ucooconoo Hove: cowuoscm nsoocoaaaaam < mean: coduonucoocoo one ceauonucoucs mo cauuoauunm c< o.m mqm¢e Ho>ou acoOLoa so» one no ususauucmum + Ho>oH unooson o>uu on» no auscuuucmam no Ho>oH ucoonoa one on» an unusuudcmdm c oucouoauuooo :uoocon ono ocuuouuounle 90 .Aso.mv +Ams.sv Am=.0 .psmm.sv ”so.v Asc.sv Ass. 0 Amm. s0 “mo. 0 ..A~o. we +sms. .0 Ass. .0 Ame. s. as so. mm. so..- ms.e- mo.s ~:.~ mm.- ms. mo. ma. m on. me. w s..- o..:. p.a.s.m .Aso.sv +Amo.mv ssm.v sso.v Am:.—V Aem._0 Amm..c Aam.v as mm. om. mm..- ~o.. op.s .s. sm.~ a..- mm.os n.m.s.m .Aos.o0 +Amo.sv Amo.0 Aam.sv A=~.0 Pss me. as. mo.- o~.~ mo.- m..ms n.~.s.m oaom.mv oosos.mv Amo.v Aem.—V ._. mm. MN. so. 9.. ss.ms p.s.s.m omz: mmoz seomo mu: m: rams sasxm m acovconovcu uni Aoozzodv owes cu couponucoocoo .oanouso> acoocoaon A:=.0 sz.v Ao~.v oawo.mv cams.~0 as ms. om.~ so. .o.o =m.=s- ~s.- a.=.s.m A::.V Am:.v sm~.v .Amo.mv cams.~0 ms ms. om.m so. so.m =m.=sn ~:.- o.m.s.m Ame.0 Amz.v ooaoo.mv oAmP.zv capp.:v sss as. mm.s mm. s~.s mm.os- mo.s u.~.s.m smo.v Amz.v ensoo.mv nsms.sv -APF.=V sss 3.. mm._ mm. s~.s mm.os- oo.s n...s.m mmoz mu: m: msoze on: as: snootoaca nunuunuuunniunauuiuiuuuuuiiiuulnuinulanuiiimoanmHem> ucoucoaoocmniu Aomzsv ceauouucoucs Fe Hope: o>aonsoom mean: scauonucoocoo oco couuouucouca uo acquoawunm cc >.m mqmch .oanoato> unoocoqon 91 mmOz as as F—p mmoz Hosoa acoogoa no» on» no accenuucwum + Ho>oa acoouoa ooqu on» an acooduucmdm on Hosoa acoonoa one on» an caucuuucmum - oacoaouuuooo naoocon one ocuuouaouoih .Aoo.mv .nfism.sv som.v -Am~.~0 Aoo.v seo.s0 Am~.0 +Ams.s0 soo.v .A::.~0 ansao.sv Amo.v Amm.v mm. mm. 2w.su :m.on s2.s ss.~ sm.i ms. ms. mo.~ as. sm.s no.1 mm._s n.=.m.m .Am~.mv -A~=.~v Amm.v smc.v +Amm.sv +Ass..v sos.v smo.v mm. sm. ao.~i s... mm.s we. em.s soc. so.ms n.m.o.m .Amm.mv +Amm.sv Am=.v A-.v Amm.sv mm. —N. as.1 mm. as. mo.o— n.m.m.m oaom.mv oesoe.sv A~=.v oasm.~0 mm. pm. ms.u sm. ——.os n.s.o.m cox: soomo mu: m: Emma :mpxm mdxm ame axezm :zmm 2:0 2:: on: .oonzm uqoonoacH 1111:1111 uoanodno> acouconooca 11111 Aoozzu<0 ones as codaonucoocoo .oanouna> unoccoaoo Amm.v Amz.v smm.v .Aom.~0 osmo.~v ao. oo.m ow. =s.s sm.=—i mo.os o.=.o.m Amm.0 Am=.0 Amm.v csoe.~0 asoo.~0 mo. oo.~ ow. =s.s pa.=si mo.os o.m.o.m Ame.v Asa.v n-Awo.~0 .sos.m0 .ssm.=0 ms. am.s mm. oo.o mm.osn om.ss o.~.w.m Amm.v Asz.v uoawo.~v osas.mv oas~.:v ms. :m.s mm. eo.o mm.osl om.ss o.s.m.m mu: m: ssozo on: sea snootoucu in:1111111111111In11111111111Iniiuiuliuinliooano“Lo> acoucoaoocu Aomzav ceauouwcoucs m.m m4m<8 me Hoooz o>aonsoom wean: noduotucoocou use :o«»ou«:o«c: uo :oduoaaaom c< .oHnoaLo> acoocoaoo 92 as as «pp FFF mmoz as as P—F wmoz Ho>o~ acoonoa so» on» no auscuuucmfim + Ho>oa acoogoa ooau on» an unusuuucmum no Ho>oa acoogoa one on» as assauuacwum - ouco«o«uuooo zuoocon oLo nodunduouois ooHnofiLo> unoccoqoccmuuu esms.mv o-Amo.wv Aaa.v onnmw.~v Amm.0 Amo. s0 saw. 0 +Ass. s0 Amp. 0 oAam. NV oaAmo. sv Ame. s0 so. NN. ~o.~u :m.ci mm.s mo. m mm. sm. we. N as. NN. s ss.os n.:.o.m Ism~.mv .A==.~v Aem.v Amm.0 +Amo.sv +A~s.sv smm.s0 Nm. sm. mo.~| s—.s sa.s me. s=.— ms.ms n.m.m.m oAsz.ov +Ams.sv Amo.v cosmo.mv .0. ms. os.i mm.s sm.~s n.m.m.m saws.ov oqus.Nv Am=.0 ow. 2N. 3s. eo.ss n.s.o.m soumo mo: m: :mmm smaxm m acoucoaoucu Aomzzo acoucoaon Aom.v Amm.v floo.sv .Aom.~0 camo.mv so.n mm.— on. mm.m ms.m—i oz.s o.=.o.m s~=.0 Amm.v A...V .Am¢.~0 .Ams.~v ms. m:.~ :o. ma.s N:.=s| ms.m~ o.m.¢.m Amm.v Agm.v Amm.sv .Aoo.mv .ANP.=V as. ss.s mm. mo.o o~.osi sm.os o.m.a.m Aom.v A==.v ANN..V .Aom.=c .sms.=v ms. =:.s om. sm.s o~.osi mm.m o.—.m.m om3m0< mu: m: .ooozm um: 39: uaoououcH Aomzsv co~»ou«co«:= .o~no«no> acovcoaon me Hooo: o>docsoo¢ mean: :oHmeucoocoo can ceapmuucoHcs ho couaoaquom c< w.m mamaa 93 significant in relation to concentration. The opposite, however, holds true in both the simultaneous equation model (Table 5.6) and in the recursive model (Table 5.9). Concentration in 1980, an endogenous variable, is positively related to unionization and is nearly significant at the ten percent level. This is a weak relationship but it supports the stronger relationship found using (MAS as an estimation technique. Specifically, the coefficients for the various measures of concentration (1967, 1972, 1977, and 1980) were all positive and statistically significant in equations for the measure summation of the unionized market shares in the market. Moreover, there was no appreciable difference betweeen the different measures, indicating that there appears to be a structural relationship which does not change through time. CONCLUSION Having examined several models which attempt to reveal the nature (H? the relationship between unionization and concentration, the results are inconclusive. This study has done little to clarify the relationship. Unionization was found to be correlated with the type of firm, size of market share held by a firm, market size, absence of right-to-work legislation, and percent of the state workforce unionized. Concentration, however, is also associated with some of these variables. The dynamics of the relationships cannot be explained by the results of this study. APPENDICES Appendix A QUESTIONAIRE Is your firm unionized? yes no Was your firm unionized in 1967? yes no If there was a change in status, please give the year. unionized decertified If your firm is mostly unionized but it is not unionized in certain regions, please check the approprioate regions: Southeast South Central Mid-Atlantic Northeast N.E. Central N.W. Central West Northwest Thank you for your c00peration. 9H Southeast Birmingham Huntsville Mobile Montgomery Ft. Lauderdale Jacksonville Lakeland Melbourne Miami Orlando Pensacola Tampa W. Palm Beach Atlanta Augusta Columbus Macon Savannah Jackson Charlotte Greensboro Raleigh Columbia Chatanooga Knoxville Memphis Nashville Newport News Norfolk Richmond Northwest Eugene Portland Seattle Spokane Tacoma Appendix B E.N. Central Evansville Fort Wayne Gary Indianapolis South Bend Louisville Ann Arbor Detroit Flint Grand Rapids Kalamazoo Lansing Saginaw Allentown Erie Akron Canton Cincinnati Cleveland Columbus Dayton Hamilton Lorain Toledo Youngstown N.Y.-N.J. Jersey City Longbranch Newark New Brunswick Paterson Trenton 95 UFCW BARGAINING REGIONS DEFINED Mid-Atlantic Wilmington Washington Baltimore Trenton Albany Binghamton Buffalo Rochester Syracuse Utica Harrisburg Johnstown Lancaster Northeast, Pa. Philadelphia Pittsburgh Reading York Charleston Huntington W.N. Central Chicago Peoria Rockford Rock Island Des Moines Duluth Minneapolis Appleton Madison Milwaukee South Central Little Rock Denver Wichita Baton Rouge New Orleans Shreve Port Saint Louis Kansas City Omaha Albuquerque Oklahoma City Tulsa Austin Beaumont Corpus Christi Dallas El Paso Houston West Phoenix Tucson Bakersfield Fresno Los Angeles Oxnard Sacramento Salinas San Berdino San Diego San Francisco San Jose Santa Barbara Stockton Vallejo Las Vegas Salt Lake City 96 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. Appendix C LARGE FOOD CHAINS Safeway Kroeger Acme Lucky except Eagle Jewel Winn Dixie Food Fair National Tea except Loblaw Stop & ShOp Fisher except ShOpping Bag, Dominicks, Kantor Albertsons Allied (K-Mart excluded) Finast (Pick N Pay) Arden/Mayfair Colonial Grand Union Giant Dillions Publix Pueblo Vons Waldbaum 97 APPENDIX D An Ietleetlon of Onlonleetlon Dela. Orelnery Leeet Seaereet Dependent 'erleblet PCTUIOO independent Verleele: I Supple-eat .2 .203 .2 -330 .313 .236 Intercept I?! IPC ICIQIO NB HUI PSUITI [.1 £3.05 -3o.96 5.05 .2. 0.30 -.20 (6.26). (2.60). (1.90) (2.09).. (1.05) t.2 11.39 -e3.22 9.26 .el 9.16 -.53 -.ae (5.51). (a.e1)' (1.96).. (2.e3)0 (l.ll)e (2.05).. I.) l8.16 0.0! .ll 0.63 -.]3 .91 (3.33)' (.50) (1.09). (1.0)) (3.10). Depe.Jent 'erleelea 0'60 "' Independent Verleolee--o----------------- Intercept I?! lie ICIOIO I! In- OSIITI 3.! 9.09 -l1.56 6.09 .30 4.66 .15 (l.ll)° (3.101' (2.50). (.51) (.12) ¢.S 29.9! ~29.20 5.99 .5! 3.0! -.oe -.Il (l.13) (3-l51' (3.2!). (.OS) (.ll) (2.06). e.6 -s.61 1.!1 .3! 2.20 .03 .ev (l.2|)' (1-9')'. (.69) (.1!) (1.15).. f-etetletloe ere eeeeeth ooetfleleete ' Sl‘nlfleent et the one pereent level " Slgeltleent at the (lee pereeet level 0 Slgelfloeet et the tee percent level 98 11! 1|0 1|0 ‘10 I Stetletle lS-SO‘ 0.22. I Stetletle 10.3“ 10.220 ‘I ." BIBLIOGRAPHY BIBLIOGRAPHY Adams, Walter. "Corporate Power and Economic Apologetics: A Public Policy Perspective." In Industrial Organization: The New Learning, pp. 360-377. Edited by Michael Mann and Harvey Goldshmidt. New York: Columbia University Press, 1976. American Institute of Food Distribution. Food Institute's Weekly Digest. Fair Lawn, N.J.: American Institute of Food Distribution, 1975-1980. Brody, David. The Butcher Workmen: A Study of Unionization. Wertheim Publications in Industrial Relations. Cambridge: Harvard University Press, 1964. Cotterill, Ronald W., and Mueller, Willard F. "The Impact of Firm Conglomeration on Market Structure: Evidence for the U.S. Food Retailing Industry." The Antitrust Bulletin Vol. 5, No. 3 (Fall 1980): 576-585. Galbraith, John Kenneth. American Capitalism: The Theory of Counterveiling Power, Edition C. Boston: Houghton Mifflin Co., 1956. Harrington, Michael. The Retail Clerks. Edited by Walter Galenson. Studies of Comparative Union Governments. 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