GEORGE MASON UNIVERSITY SCHOOL OF LAW

SLOTTING CONTRACTS AND CONSUMER WELFARE

Joshua D. Wright

06-14

Forthcoming in Antitrust Law Journal

GEORGE MASON UNIVERSITY LAW AND ECONOMICS RESEARCH PAPER SERIES

This paper can be downloaded without charge from the Social Science Research Network at http://ssrn.com/abstract_id= 897394

Preliminary draft, do not cite without permission of the author. 08/25/06.

SLOTTING CONTRACTS AND CONSUMER WELFARE

Joshua D. Wright♦♦♦♦

Abstract

Slotting contracts involve manufacturer payments for retail shelf space. Slotting

is an increasingly important part of the competitive process in many product

markets, and has been the subject of congressional hearings, agency

investigations, antitrust litigation, and scholarly debate. However, very little is

known about the competitive consequences of slotting. This paper uses a unique

data set consisting of slotting contracts at military commissaries prior to an

exogenously imposed slotting ban to identify the impact of slotting on consumer

welfare. This natural experiment provides a rare opportunity to directly observe

the crucial policy counterfactual in the real world: would banning slotting

contracts increase consumer welfare? The analysis measures the impact of

slotting, at both the product and category levels, on prices, output, and product

variety. I find no evidence that slotting is anticompetitive. To the contrary,

slotting is associated with “brand-shifting” without category level effects.

Because slotting payments are passed on to consumers in competitive retail

markets, the results imply that competition for shelf space with slotting contracts

increase consumer welfare.

♦ Assistant Professor, George Mason University School of Law. I thank Bernard Black, Kenneth Elzinga, Bruce Johnsen, Benjamin Klein, Jonathan Klick, Latika Hartmann, Tom Hazlett, Keith Hylton, Kate Litvak, J.J. Prescott, Adam Rennhoff, Alison Sexton, Paul Stancil, and especially Wesley Hartmann for helpful comments and suggestions. Earlier versions of this paper were presented at the George Mason University Levy Workshop, the University of Texas Law School Center for Law, Business, and Economics, the International Industrial Organization Conference, and the Southeastern Association of Law Schools Conference. Brandy Wagstaff provided excellent research assistance. The Department of Defense Commissary Agency generously provided the dataset. Jay Manning and Robert Vitikacs of the Commissary Agency provided insight into commissary operations and the data. The George Mason Law and Economics Center provided financial support. All errors are my own.

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1 Introduction

Slotting arrangements govern shelf space relationships between

manufacturers and retailers. These contract arrangements typically take the form

of a payment to the retailer in exchange for some form of promotional

consideration ranging from merely stocking the product to special displays or

preferred shelf location, such as an end-aisle display or “eye-level” shelf space.

Slotting arrangements have been the focus of government investigations,1

litigation,2 proposed legislation,3 and scholarly debate.4 Analogous payments

such as “payola” in the music industry have also resulted high profile

investigations, including Sony’s recent settlement prohibiting all future

payments for radio music spins resulting from New York Attorney General Eliot

1 The Federal Trade Commission has also expressed a considerable amount of interest in slotting allowances, holding a workshop culminating in the issuance of a report and a subsequent study on the competitive concerns of the practice. See FEDERAL TRADE COMM’N, REPORT ON THE FEDERAL TRADE

COMMISSION WORKSHOP ON SLOTTING ALLOWANCES AND OTHER MARKETING PRACTICES IN THE

GROCERY INDUSTRY (2001) [hereinafter FTC Report]; FEDERAL TRADE COMM’N STAFF STUDY, SLOTTING

ALLOWANCES IN THE RETAIL GROCERY INDUSTRY: SELECTED CASE STUDIES IN FIVE PRODUCT CATEGORIES (Nov. 2003) [hereinafter FTC Study] (examining the use of grocery slotting allowances in five product categories: fresh bread, hot dogs, ice cream, shelf-stable pasta, and shelf-stable salad dressing).

2 A variety of slotting allowance related issues have been raised in antitrust litigation. See Conwood Co. v. United States Tobacco Co., 290 F.3d 768 (6th Cir. 2002) (holding firm liable for combination of exclusionary conduct including product destruction, misleading retailers, and payments for exclusive product display space); R.J. Reynolds Tobacco Co. v. Philip Morris, Inc. (RJR II), 199 F. Supp. 2d 363 (M.D.N.C. 2002) (rejecting a claim that Philip Morris’s shelf space payment program violated the Sherman Act), aff’d per curiam, 67 F. App’x 810 (4th Cir. 2003); El Aquila Food Prods. v. Gruma Corp., 301 F. Supp. 2d 612 (S.D. Tex. 2003), aff’d, 131 F. App’x 450 (5th Cir. 2005); American Booksellers Ass’n v. Barnes & Noble, Inc., 135 F. Supp. 2d 1031 (N.D. Cal. 2001); FTC v. H.J. Heinz Co., 116 F. Supp. 2d 190 (D.D.C. 2000) (analyzing whether a reduction in slotting fees might be an efficiency in the context of horizontal merger analysis), rev’d, 246 F.3d 708 (D.C. Cir. 2001); Intimate Bookshop, Inc. v. Barnes & Noble, Inc., 88 F. Supp. 2d 133 (S.D.N.Y. 2000); FTC v. McCormick, FTC Docket No. C-3939 (2000) (settling charges that McCormick’s shelf space payments in the spice market violated the Robinson-Patman Act); Coca-Cola Co. v. Harmar Bottling Co., 111 S.W.3d 287 (Tex. App. 2003) (shelf space payments in violation of state antitrust laws). Slotting fees and other forms of shelf space payments were also central to Coca-Cola’s recent settlement with the European Commission that limits the amount of shelf space that Coca-Cola can purchase from retailers, as well as Coca-Cola’s ability to offer rebates conditioned on exclusivity or specified levels of sales. See Undertaking, Case Comp/39.116/B-2-Coca-Cola. 3 See Sen. B. 582 (Cal. 2005) (Figueroa), available at http://www.leginfo.ca.gov/pub/bill/sen/sb_0551-0600/sb_582_bill_20050411_amended_sen.pdf (as amended). 4 Section 2 summarizes this literature.

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Spitzer’s efforts.5 Despite the substantial resources invested into studying,

litigating, and investigating slotting arrangements, we know surprisingly little

about the real world competitive consequences of the practice.6 The need for

empirical evidence is heightened because the antitrust doctrine governing these

practices is notoriously unsettled, inconsistent, and controversial.7 At least one

cause of the doctrinal uncertainty surrounding vertical distribution

arrangements more generally is the lack of empirical evidence capable of guiding

sensible antitrust policy.8 This paper seeks to fill that void by presenting

evidence that slotting contracts are pro-competitive in practice.

The paper proceeds as follows. Section 2 reviews the theoretical and

empirical literature on slotting arrangements, focusing on Klein and Wright’s

5 See, e.g., Press Release, Office of N.Y. Attorney Gen. Eliot Spitzer, Sony Settles Payola Investigation (July 25, 2005), available at http://www.oag.state.ny.us/press/2005/jul/jul25a_05.html (Sony BMG agrees to cease all payments for radio exposure, disclosed or otherwise, and to pay $10 million to the Rockefeller Philanthropy Advisors as a result of allegations that its payments “were designed to manipulate record charts, generate consumer interest in records and increase sales”). Similar payments occur in other retail environments, including record stores, drug stores, convenience stores, and book stores. See, e.g., Iris Rosenthal, Slotting Fees Continue to Spark Controversy in Retailing, 135 DRUG TOPICS 81 (January 21, 1991); James Surowiecki, Paying to Play, THE NEW YORKER, July 12, 2004; and Jeffrey A. Trachtenberg, Borders Sets Out to Make the Book Business Bussinesslike, WALL STREET JOURNAL, May 20, 2002, at B1. 6 Attempts to empirically document the competitive consequences of slotting contracts have not been fruitful. See, e.g., FTC Study, supra note 1, at 62 (“Our ability to comment about the relevance of the various theories of slotting based on our study is limited.”); U.S. GEN. ACCOUNTING OFFICE, SLOTTING

FEES: EFFORTS TO STUDY THESE PAYMENTS IN THE GROCERY INDUSTRY (2000) (testimony of Lawrence J. Dyckman before the Senate Committee on Small Business), available at http://www.gao.gov/archive/2000/ rc00295t.pdf) (“In short, despite repeated attempts over the last 8 months, we have been unsuccessful in gaining the cooperation needed from the industry to conduct this study.”). 7 See Joshua D. Wright, Antitrust Law and Competition for Distribution, 23 YALE J. ON REG. 169 (2006); William A. Kovacic, The Modern Evolution of U.S. Competition Policy Enforcement Norms, 71 ANTITRUST L.J. 377 (2003) (noting that federal vertical restraints and monopolization policy have exhibited the greatest disparities in enforcement activity over the last three decades). 8 Two recent surveys echo this concern and conclude that while further research is critical to sound policy in this area, the balance of evidence tips in favor of a presumption of legality. See James C. Cooper, et al., Vertical Antitrust Policy as a Problem of Inference, 23 INT’L J. INDUS. ORG. 639 (2005); Francine Lafontaine & Margaret Slade, Exclusive Contracts and Vertical Restraints: Empirical Evidence and Public

Policy, HANDBOOK OF ANTITRUST ECONOMICS (Paolo Buccirossi ed., Cambridge: MIT Press, forthcoming).

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promotional services theory.9 Section 3 discusses the institutional foundations of

the empirical analysis: military commissaries, their product allocation decisions,

regulatory environment, the shelf space contracts, and the ban on those contracts

imposed at the end of 2001. Section 4 presents the data set. Section 5 presents

the empirical analysis and results and Section 6 concludes by examining the

implications of the evidence for antitrust policy.

2 The Economics of Slotting Contracts10

Slotting contracts involve manufacturer payments for shelf space and are

prevalent in markets with retail distribution. The contracts occasionally include

exclusive terms limiting the space available to a rival, but generally require the

retailer to commit a particular quantity or quality of shelf space to the supplier’s

product without any exclusive commitments.11 For example, Coca-Cola might

pay a retail chain $1000 for prominent display using “eye-level” shelf space for

six months. Alternatively, Coca-Cola might pay for the same shelf space by

allowing the retailer a discount from the wholesale price or other quantity-based

rebate, though the term “slotting fee” sometimes is reserved exclusively for the

use of upfront, lump-sum payments. The use of upfront, lump-sum payments

increased dramatically in the mid-1980s, both in terms of the number of products

9 The promotional services theory of slotting contracts is originally presented in Benjamin Klein & Joshua D. Wright, The Economics of Slotting Contracts, J.L. & ECON. (forthcoming 2007) [hereinafter Klein & Wright]. 10 This section draws substantially upon the discussion of competing slotting theories and evidence in Klein and Wright, supra note 9. 11 The FTC Study, supra note 1, at 57, reports that exclusivity was not prevalent in the five product categories studied (fresh bread, hot dogs, ice cream, shelf-stable pasta, and shelf-stable salad dressing). Benjamin Klein, Kevin M. Murphy & Joshua D. Wright, Exclusive Dealing and Category Management in Retail Distribution (unpublished working paper, 2006), provides a pro-competitive explanation for why retailers, effectively acting as bargaining agents for their consumers by internalizing each consumer’s independent buying decision, may offer exclusive shelf space in a product category as a way to lower prices.

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covered and the magnitude of payment,12 though all forms of shelf space

contracts have attracted antitrust scrutiny.

While there have been a number of theoretical attempts to explain slotting

contracts as either efficiency-enhancing or anticompetitive, these explanations

have been fundamentally inconsistent with slotting data. As a result, very little

is known about the competitive consequences of shelf space contracts. This

Section summarizes the theoretical and empirical attempts to explain the use of

slotting contracts.

2.1 Theoretical Literature

Some economic models consider the possibility that manufacturers or

retailers strategically utilize slotting contracts to exclude rivals. The conventional

anticompetitive explanation contemplates manufacturers using shelf space

payments to disadvantage rivals by increasing their costs and increase barriers to

entry, ultimately increasing prices and reducing product variety.13 This

exclusionary theory of slotting has been the focus of the bulk of antitrust

litigation involving promotional payments,14 and in its “deep pockets” variant,

12 FTC Report, supra note 1, at 4, 11 & nn.18-19. 13 See FTC Report, supra note 1, at 34-41; FTC Study, supra note 1, at 3-4 (citing Greg Shaffer, Slotting

Allowances and Optimal Product Variety, ADVANCES IN ECONOMIC ANALYSIS & POLICY, Vol. 5, No. 1, Art. 3 (2005)). A second anticompetitive explanation suggests that slotting payments increase the cost of retail distribution and therefore favor incumbent firms who will be willing to pay more for the shelf space than competitors because a monopolist incumbent earning the monopoly rate of return will systematically outbid a potential entrant seeking to earn a competitive rate of return. See Steven C. Salop, Strategic Entry

Deterrence, 69 AM. ECON. REV. 335 (1979); FTC Study, supra note 1, at 3-4. These models depend on the presence of very large scale economies in manufacturing. An alternative possible concern is that a manufacturer may engage in predatory overpayment for shelf space. This is a condition that is difficult to identify and distinguish from the normal competitive process. See Benjamin Klein, Exclusive Dealing as

Competition for Distribution “On the Merits,” 12 GEO. MASON L. REV. 119 (2004).

14 See, e.g., Conwood Co. v. United States Tobacco Co., 290 F.3d 768 (6th Cir. 2002); Bayou Bottling, Inc. v. Dr. Pepper Co., 725 F. 2d 300, 303 (5th Cir. 1984); El Aquila Food Prods. v. Gruma Corp., 301 F. Supp. 2d 612, 621 (S.D. Tex. 2003), aff’d, 131 F. App’x 450 (5th Cir. 2005); RJR II, 199 F. Supp. 2d 363 (M.D.N.C. 2002), aff’d per curiam, 67 F. App’x 810 (4th Cir. 2003); Louisa Coca-Cola Bottling Co. v. Pepsi-Cola Metro. Bottling Co., 94 F. Supp. 2d 804, 816 (E.D. Ky. 1999); Beverage Mgmt., Inc. v. Coca-Cola Metro. Bottling Corp., 653 F. Supp. 1144, 1153-54 (S.D. Ohio 1986); FTC v. McCormick, FTC Docket No. C-3939 (2000).

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depends on the assumption that capital markets are imperfect.15 Other highly

stylized theoretical models argue that slotting allowances are a mechanism by

which retailers with bargaining power are assumed to be able to use the

payments to exclude rivals by preventing them from selling a manufacturer’s

product.16

These anticompetitive theories of slotting are fundamentally inconsistent

with the evidence. The exclusionary theories of rival foreclosure involve at least

two necessary conditions for competitive harm not present for many slotting

contracts: they are typically not of sufficient duration to create risk of competitive

harm and frequently cover products that do not exhibit significant economies of

scale. The exclusionary theories also fail to explain the dramatic increase in the

prevalence of slotting beginning in the mid 1980s. The retailer bargaining power

explanations of slotting are equally inconsistent with the fact that small retailers

without any bargaining power use slotting and a large retailer, like Wal-Mart,

does not accept lump-sum, upfront fees.17 Perhaps more damning of the retailer

15 The Federal Trade Commission proffered a “portfolio effects” version of this argument, which was ultimately endorsed by the Supreme Court, to successfully challenge a conglomerate merger between Procter & Gamble and Clorox. The FTC argued that the post-merger firm would be able to utilize Procter & Gamble’s substantial advertising budget to more efficiently purchase preferred shelf space for Clorox products. Procter & Gamble Co., 63 F.T.C. 1465 (1963). Economists have recently revived these “deep-pockets” arguments, which depend on imperfect capital markets, in the context of slotting allowances. See Paul N. Bloom, et al., Slotting Allowances and Fees: Schools of Thought and the Views of Practicing

Managers, 64 J. MKTG. 92 (2000); Greg Shaffer, Slotting Allowances and Optimal Product Variety, ADVANCES IN ECONOMIC ANALYSIS & POLICY, Vol. 5, No. 1, Art. 3 (2005). 16 See, e.g., Leslie M. Marx & Greg Shaffer, Upfront Payments and Exclusion in Downstream Markets (unpublished paper, Aug. 2005); Patrick Rey, Jeanine Thal, & Thibaud Vergé, Slotting Allowances and Conditional Payments (unpublished paper, March 2005). Both papers present models where retailers with bargaining power demand slotting fees to increase their profits because slotting has the anticompetitive effect of excluding other retailers. These models are discussed in greater detail in Klein & Wright, supra note 9. 17 Klein & Wright, supra note 9, explain why Wal-Mart accepts promotional shelf space payments primarily in the form of lower wholesale prices rather than per unit time payments.

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market power theories is the fact that the growth in slotting fees has not been

associated with an increase in retailer profitability.18

The literature includes three pro-competitive theories of slotting contracts,

each claiming that the growth in slotting can be explained by the increase in new

supermarket products. Each of these theories has limited ability to explain

slotting contracts on established products, and, as I will demonstrate, also do not

explain slotting for new products.

The first of these theories asserts that the increase in new products

proportionally increases the transaction costs imposed on retailers, such as

entering new product information into a computer, warehousing the new

products, and physically placing the new products on the shelf.19 This

explanation fails because slotting payments are significantly greater in

magnitude than these costs, and it incorrectly predicts that slotting payments

will be consistent in magnitude across markets and do not cover established

products where additional transaction costs are likely to be minimal.

The second pro-competitive theory asserts that slotting compensates

retailers for the risks associated with dedicating shelf space to a new and

unproven product.20 These signaling models generally test the proposition that

slotting payments assist retailers in identifying successful products because

manufacturers are assumed to have superior information. Again, these models

are inconsistent with the fact that slotting contracts are observed with established

products and products with stable demand. Further, the models do not consider

18 See Klein & Wright, supra note 9. 19 See, e.g., Laurie Freeman, Paying for Retail Shelf Space, ADVERTISING AGE, Feb. 13, 1986, at 31. 20 See, e.g., Wujin Chu, Demand Signaling and Screening in Channels of Distribution, 11 MKTG. SCI. 324 (1997); Preyas S. Desai, Multiple Messages to Retain Retailers: Signaling New Product Demand, 19 MKTG. SCI. 381 (2000); Martin A. Lariviere & V. Padmanabhan, Slotting Allowances and New Product

Introductions, 16 MKTG. SCI. 112 (1997); FTC Study, supra note 1, at 1-2; K. Sudhir & Vithala R. Rao, Do

Slotting Allowances Enhance Efficiency or Hinder Competition?, 43 J. MKTG. RESEARCH 137 (May 2006).

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why manufacturers adopt this particular form of contract to solve this

informational problem, rather than an alternative arrangement such as an

introductory price allowance or product failure fees. The most significant failure

as a theoretical matter for the first two explanations is that they fail to address

the critical economic question about these increased costs: why do manufacturers

compensate retailers for the increased costs in the form of a fixed fee rather than

consumers paying for these costs in the form of higher prices?

Mary Sullivan presents a third pro-competitive theory of slotting related

to the increase in new products that does address this fundamental question.21

Specifically, Sullivan contends that manufacturer payments to retailers for the

growth of new products have increased because the resulting increase in

supermarket shelf space costs per dollar of sales does not benefit consumers.

Sullivan’s argument hinges on the unrealistic assumptions that consumers do not

value brand extensions that do not reduce consumer search costs and do not

demand product variety. Because consumers are assumed not to be willing to

compensate supermarkets through increased margins or greater sales when

supermarkets increase product variety, slotting fees are necessary, according to

Sullivan, to allow supermarkets to recover their higher costs of providing

increased shelf space for stocking new products.

Contrary to Sullivan’s model, however, consumers are generally willing to

pay for increased variety that raises supermarket operating costs. Brand

extensions can generate significant value for consumers.22 Inter-retailer

competition should result in supermarket compensation for this consumer

benefit in the form of an increased margin and/or increased sales. This means

21 Mary Sullivan, Slotting Allowances and the Market for New Products, 40 J.L. & ECON. 461 (1997). 22 See, e.g., Jerry Hausman, Valuation of New Goods Under Perfect and Imperfect Competition, in THE ECONOMICS OF NEW GOODS 209-67 (Bresnahan & Gordon eds., 1997).

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consumers “pay” for the increased costs of increased shelf space per dollar of

sales in an increased supermarket margin, even if there is no decrease in search

costs. Therefore, the growth in the number of new products would not require a

separate slotting contract to compensate supermarkets for their higher selling

costs.

2.2 Empirical Literature

There is also very little evidence regarding the competitive effects of

slotting contracts. The lack of evidence is explained primarily by firms’ rational

disinclination to share information in the present antitrust climate, and also

because slotting fees involve payments that are difficult to disentangle from

other trade promotion spending. For these reasons, most empirical

investigations of slotting have relied on aggregate level data and surveys rather

than actual slotting contracts.23 While these studies have provided useful

information regarding slotting trends and their implications, there have been

very few detailed studies of the use of slotting contracts at the firm level. These

exceptional studies uniformly reject the notion that slotting is anticompetitive.

For example, Rennhoff estimates a structural model of manufacturer

competition for retailer shelf space with slotting allowances.24 A structural

model imposes assumptions about the behavior of economic agents

(manufacturers, retailers, and/or consumers) to derive a relationship between

endogenous and exogenous variables that may be observed by an empirical

researcher as opposed to “reduced-form” estimation, which takes what is an

23 See, e.g., Sullivan, supra note 21 (using aggregate level data on the supply and demand for new products); Klein & Wright, supra note 9 (showing that the growth in slotting contracts over the past twenty years is consistent with the aggregate increase in manufacturer margins and prevalence of branded products across product categories). 24 Adam Rennhoff, Paying for Shelf Space: An Investigation of Merchandising Allowances in the Grocery Industry (working paper, on file with author, July 2004).

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essentially “theory-free” approach. While Rennhoff does not directly observe

actual slotting contracts, he observes the magnitude of the manufacturer’s

merchandising allowances. Rennhoff estimates consumer demand in a single

product category, ketchup, and demonstrates that products enjoying placement

in premium shelf space experience increased demand.25 By imposing

assumptions about the strategic interactions of manufacturers and retailers,

Rennhoff’s model predicts that average retail prices are lower with slotting

allowances than they would be under a slotting ban.

Sudhir and Rao observe some data on allowances offered for new

products to a single, large supermarket chain in the northeastern United States

over a six-month period from June 1986 to February 1987.26 While they do not

observe the magnitude of the slotting payment, they observe whether a slotting

allowance was paid, and rely on survey results from a questionnaire completed

by the retail buyer assessing various manufacturer and product attributes.

Sudhir and Rao conclude that slotting is, on balance, pro-competitive because it

shifts new product risk from retailers to manufacturers, but that it also softens

retail competition. However, as Klein and Wright demonstrate, the growth in

slotting has not been correlated with an increase in retailer profitability.27

The study most closely related to ours is Bronsteen, Elzinga, and Mills’

examination of the competitive impact of Philip Morris’s “Retail Leaders”

program, which involved shelf space contracts specifying payments in exchange

for the supply of varying levels of display space and store signage in the cigarette

industry. Bronsteen, Elzinga, and Mills’ case study examines, and rejects, the

25 This is consistent with findings in the marketing literature. See, e.g., Xavier Drezè, et al., Shelf

Management and Space Elasticity, 70 J. RETAILING 301 (1994); Charles Areni, et al., Point-of-Purchase

Displays, Product Organization, and Brand Purchase Likelihoods, 27 J. ACAD. MKTG. SCI. 428 (1999). 26 Sudhir &. Rao, supra note 20. 27 Klein & Wright, supra note 9.

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plaintiffs’ theory in the antitrust dispute against Philip Morris, which asserted

that the Retail Leaders program would result in higher Philip Morris prices

relative to rival brands.28 One important characteristic of this important case

study is that it measures the impact of actual slotting contracts on retail prices.

The present study improves upon the case study approach by broadening the

analysis to include hundreds of product markets, and most importantly, by

exploiting the exogenously imposed “natural experiment” resulting from the

slotting ban to estimate the impact of slotting on retail prices, as well as category

level output and product variety.

While the existing empirical studies unequivocally contradict the

predictions of the anticompetitive theories, they leave significant room for

improving our understanding of the impact of slotting contracts on consumer

welfare across product markets.

2.3 The Promotional Services Theory of Slotting Contracts29

The promotional services theory of slotting contracts recognizes that the

supply of retail shelf space is a form of promotion that increases some

consumers’ reservation values for a product without generating significant inter-

retailer effects. In contrast to abstract economic models of retailing that assume

that retailers exist only to reduce search costs, the promotional services theory

begins with the empirical reality that retailers have some discretion over product

mix and shelf space allocation, and that these decisions influence consumer

purchasing behavior.

Retailer supply of premium shelf space creates “promotional sales” that

would not occur without the promotion. These promotional sales are

28 Peter Bronsteen, et al., Price-Competition and Slotting Allowances, 50 ANTITRUST BULL. 267 (2005); RJR II, 199 F. Supp. 2d 363 (M.D.N.C. 2002), aff’d per curiam, 67 F. App’x 810 (4th Cir. 2003). This case is discussed in Wright, supra note 7, and Klein & Wright, supra note 9. 29 This section summarizes the theory originally presented in Klein & Wright, supra note 9.

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particularly profitable for manufacturers of products with relatively large

margins of wholesale price over marginal cost. But the fact that manufacturer

profits are increasing in the supply of promotional shelf space is not a sufficient

condition to generate slotting contracts. It merely sets the foundation for the

fundamental economic question regarding slotting contracts: why do

manufacturers and retailers find it necessary to enter into slotting contracts?

That is, why do manufacturers not simply sell products to retailers at wholesale

prices and allow competitive retailers to determine independently which

products to feature?

The promotional services theory addresses this question by identifying a

general incentive incompatibility between manufacturers and retailers with

respect to the supply of the desired quantity and quality of promotional shelf

space. There are two primary economic reasons for this incentive

incompatibility: (1) manufacturer margins over marginal cost are large relative to

retailer margins on the same product; and (2) increasing the supply of

promotional shelf space allocated to a particular brand does not generate

significant inter-retailer effects. These conditions are very realistically satisfied in

many settings involving differentiated products distributed through retailers to

consumers. Klein and Wright demonstrate that when the supply of premium

shelf space generates profitable incremental manufacturer sales without shifting

sales between retailers relative to a reduction in price, slotting contracts are a

consequence of the normal competitive process.

The intuition driving the theory is straightforward. Because the retailer’s

decision to allocate eye-level shelf space to Coke or Pepsi creates significant

profits for the favored manufacturer, but does little to shift inter-retailer sales or

increase retailer traffic, the manufacturer must compensate the retailer to ensure

the joint profit-maximizing allocation of shelf space.

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Klein and Wright also address a second important economic question that

has received a good deal of attention from antitrust regulators: why do

manufacturers sometimes rely on per unit time payments rather than wholesale

price discounts or rebates? Klein and Wright show that a per unit time payment

offers a significant advantage over wholesale price discounts because the latter

create the incentive for retailers to lower the price of the manufacturer’s product,

undermining the manufacturer’s shelf space payments. The promotional

services theory, therefore, predicts that wholesale price discounts will be an

efficient method to compensate retailers for the provision of promotional shelf

space when there is not significant inter-retailer competition on the particular

product.

The promotional services theory suggests that slotting contracts increase

consumer welfare because payments are passed on to consumers in the highly

competitive retail environment.30 The key to understanding this prediction is the

fact that shelf space payments are increasing a supermarket’s traffic or sales.

One can expect competitive supermarkets to pass on slotting payments in the

form of lower prices and higher quality, thereby increasing store traffic and the

“price” the retailer can collect for its shelf space. In a competitive retail

environment, supermarkets that do not pass on rents earned from shelf space

payments in the form of lower prices or increased non-price amenities that

consumers value will sacrifice significant sales and also will collect lower shelf

space payments in the future. Because shelf space payments are ultimately to be

30 See, e.g., Joshua Wright, Vons Grocery and the Concentration-Price Relationship in Grocery Retail, 48 UCLA L. Rev. 743 (2001) (demonstrating that competition in the grocery retail market has remained vigorous despite substantial increases in concentration over the past two decades).

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completely dissipated regardless of their particular form, shelf space payments

can be expected to increase consumer welfare.31

3 DeCA Commissaries

The Department of Defense operates grocery retail stores, called

commissaries, for active and retired military personnel and their families. The

Defense Commissary Agency (“DeCA”), formed in 1991, manages these

commissaries and is responsible for product assortment decisions, negotiations

with suppliers, pricing, and day-to-day operations. DeCA operates 275

commissaries, 171 within the 48 contiguous United States, and 104 located

elsewhere throughout the world. 32 Annually, DeCA commissaries generate

approximate $5 billion in revenue. While commissaries are somewhat similar to

traditional supermarket chains in terms of store content, management, and

competitive dynamics,33 there are some important and obvious differences

between commissaries and conventional private sector supermarkets. For

example, commissaries typically offer fewer items, compete less rigorously on

non-price dimensions, and are open for fewer hours. Table 2 summarizes some

key differences between private supermarkets and commissaries.

The most prominent difference between supermarkets and commissaries

is that the latter are not-for-profit operations. DeCA’s operating expenses are

31 Klein & Wright, supra note 9 (demonstrating that retailer profitability remained constant between 1980-2003, the time period during which shelf space payments dramatically increased in both frequency and magnitude).

32 A list of the geographic locations of the commissaries is available at http://www.commissaries.com/ realign_maps/alpha_list.cfm. 33 Commissary stores, according to 10 U.S.C. § 2484(a), are “similar to commercial grocery stores and may sell merchandise similar to that sold in commercial grocery stores.” DeCA’s 1995 total sales of $5.4 billion made it the tenth largest supermarket chain in the United States that year. Demographic Section, EXCHANGE AND COMMISSARY NEWS, Oct. 15, 1996, at 86. A 1995 study estimates that in Hampton Roads, Virginia, local commissaries accounted for approximately 8.4% of all grocery retail sales, making DeCA the third leading retail chain in the region. Stephanie Stoughton, Supermarkets Fight Commissary

Proposal, THE VIRGINIAN-PILOT, Sept. 8, 1995, at D1 (citing Food World study).

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paid primarily through its annual appropriation of approximately $1 billion. The

DeCA mission is “to provide a significant non-pay compensation benefit to

military families.”34 Specifically, DeCA seeks to generate 30% in savings for

military families relative to conventional supermarkets.35

It is also important to note that commissaries are generally not isolated

from inter-retailer competition. A 1975 General Accounting Office examination

of 27 urban commissaries found that each one had at least four grocery stores

within a five mile radius.36 The significant growth in the number of

supermarkets over the past 30 years suggests that the number of grocery stores

in these areas has increased.37 For instance, a 1975 study found that each of 27

urban commissaries examined had at least four grocery stores within five miles.

Significantly, however, private manufacturers compete, and contract, for shelf

space at both commissaries and supermarkets.

Commissaries also face a unique regulatory environment. For instance,

commissaries do not sell private-label products, which have earned an increasing

share of conventional supermarket sales in recent years.38 The most important

34 U.S. GEN. ACCOUNTING OFFICE, DEFENSE COMMISSARIES, REPORT TO THE SENATE COMMITTEE ON

SMALL BUSINESS AND ENTREPRENEURSHIP 5 (Dec. 2002) [hereinafter Defense Commissaries]. 35 This estimate appears to be overstated. Because private retailers sell some items at higher margins than commissaries, which are limited to a 5% fixed margin, such savings would only be possible if commissaries purchased at significantly lower costs than large private supermarket chains. While the Robinson-Patman Act does not apply to commissaries, which would allow manufacturers the opportunity to offer different prices to commissaries, a Congressional Budget Office study suggests that manufacturers do not do so. CONGRESSIONAL BUDGET OFFICE, THE COSTS AND BENEFITS OF RETAIL ACTIVITIES AT

MILITARY BASES (Oct. 1997). 36 U.S. GEN. ACCOUNTING OFFICE, THE MILITARY COMMISSARY STORE (1975). 37 The number of supermarkets has increased about 20% during this time period, from 26,997 in 1972 to 34,252 in 2004. Annual Report of the Grocery Industry, PROGRESSIVE GROCER (various years). 38 Private label sales had captured up to 20.7% of supermarket unit sales and 16.9% of dollar sales according to the Private Label Manufacturers Association (citing Information Resources, Inc.). The absence of private label products does not appear to have compromised DeCA’s bargaining power vis-à-vis manufacturers as DeCA generally secures “most-favored nation” pricing provisions with all suppliers. Defense Commissaries, supra note 34.

15

regulatory constraint involves commissary pricing: commissaries sell food and

household items tax free at cost plus a 5% surcharge over the wholesale price.39

3.1 Commissary Shelf Space Decisions

Commissary shelves are not unlike those in private supermarkets. Both

offer a similar range of products,40 though commissaries are smaller than today’s

largest supermarkets by approximately 25% in terms of square footage, and carry

about 40% fewer Stock Keeping Units (“SKUs”) than the average supermarket.41

This is explained, in part, by the fact that commissaries do not sell beer, wine, or

general merchandise items. Commissaries typically offer a comparable number

of products per category. Commissaries also keep more limited hours than

supermarkets, averaging 48 hours per week in 1996 compared to 131 hours for

supermarkets.42

DeCA purchases typically involve a competitive bidding process, though

federal law exempts the purchase of brand name products from such bidding.43

39 10 U.S.C. § 2484(d) reads in pertinent part:

(d) Uniform sales price surcharge.--The Secretary of Defense shall apply a uniform surcharge equal to five percent on the sales prices established under subsection (e) for each item of merchandise sold in, at, or by commissary stores.

As discussed infra, the fixed retail margin allows direct observation of the impact of the slotting ban because manufacturers cannot substitute towards alternative methods of paying for shelf space, such as reducing the wholesale price. 40 Federal law enumerates the categories of products that commissaries may sell, including: health and beauty aids, meat and poultry, fish and seafood, produce, food and non-food grocery items, bakery goods, dairy products, tobacco products, delicatessen items, frozen foods, and magazines and other periodicals. 10 U.S.C. § 2484(b). Commissaries may sell non-enumerated products as the “Secretary of Defense may authorize” upon notification of Congress, but are not authorized to carry beer & wine, greeting cards, and most general merchandise items. Id. at § 2484(c). 41 Defense Commissaries, supra note 34. 42 Annual Report of the Grocery Industry, PROGRESSIVE GROCER (April 1996). 43 See 10 U.S.C. § 2304(c)(5). This is to be compared to bidding procedures that are imposed for non-brand products set forth in Section 2304 mandating a sealed bid auction where feasible. DeCA may also

16

The “brand name exception” is triggered only where the commercial item “is

regularly sold outside of commissary stores under the same brand name as the

name by which the commercial item will be sold in, at, or by commissary

stores.”44

DeCA’s purchasing practices for brand name products are similar to the

negotiations of a large chain of private supermarkets. These practices include,

for example, entry into category management relationships with suppliers.45

DeCA adopted category management in the mid 1990s, and accordingly, engages

in intensive data-based analysis of nearly all of the 170 product categories.46

DeCA assigns category managers and buyers to each category who meet with

suppliers during a category review. Suppliers present DeCA with sales data,

product selection recommendations, and display recommendations.47 DeCA

escape the competitive procedures for product purchase under a number of other scenarios, including “unusual and compelling urgency,” or national emergency. Id. at § 2304(c)(2). 44 10 U.S.C. § 2484(f). The term “regularly sold outside of commissary stores” is to be interpreted by evaluating “sales of the item on a regional or national basis by commercial grocery or other retail operations consisting of multiple stores.” Id. It is worth noting that DeCA sales do not include new product introductions, therefore negating the possibility that these contracts are caused by new product risk. 45 Category management typically involves designating a category captain in a product category and conferring upon the captain some power to provide input and otherwise participate in the retailer’s shelf space allocation decisions. Klein, Murphy, and Wright analyze this arrangement, showing that category management is a mechanism for controlling dealer free-riding incentives while allowing for greater product variety than exclusive dealing. Klein, Murphy & Wright, supra note 11. 46 DeCA utilizes data from Information Resources, Inc. (“IRI”), a data source commonly employed by private supermarkets. 47 DeCA notes that the suppliers making such presentations include both “leading” manufacturers such as Kraft, General Mills, and Pepsi, as well as other companies and distributors. DeCA describes its category management review process in eight steps, as follows: (1) DeCA announces a category review and invites companies supplying products to provide information and analysis; (2) DeCA conducts meetings with interested manufacturers, brokers, and distributors at DeCA’s headquarters in Fort Lee, Virginia; (3) DeCA’s category manager obtains IRI and scanner data on product performance; (4) DeCA analyzes IRI data as well as data presented by participating suppliers and prepares a schedule of category decisions indicating assortment decisions; (5) DeCA officials develop and sign-off on shelving plans called “plan-o-grams” illustrating how products will be arranged on the shelves. These plans are carried out with the assistance of the participating suppliers and distributors; (6) DeCA releases category review decisions and solicits comments from participating companies; (7) DeCA responds in writing to each company that

17

states that it “relies on market data” that it obtains from independent sources

and that “large suppliers do not select the products that commissaries sell,” but

notes that suppliers such as Kraft Foods, Inc., and General Mills, Inc., and other

companies in the category often have input on display considerations.48

One obvious limitation of the study is that it involves non-profit

commissaries rather than private supermarkets. This fact raises some questions

regarding the external validity of the results. However, this concern is somewhat

mitigated by three observations. First, the manufacturers offering slotting

contracts to both private supermarkets and commissaries are both profit

maximizing enterprises. Second, the unique regulatory framework imposed on

DeCA, such as fixed retail margins, actually enhances the ability to isolate

changes in manufacturer behavior by holding retailer behavior constant. In

other words, because commissary retailers cannot re-optimize by shifting sales to

higher margin products after the slotting ban, since all products are sold at the

fixed 5% margin, the estimates herein measure the “true” effect of the ban.

Third, as discussed, one might expect the consumer benefits from shelf space

payments to be even larger in the private supermarket context, since the

payments are a significantly greater percentage of total revenue in private

supermarkets than in commissaries. This suggests that these estimates might

underestimate the pro-competitive effects of slotting in private supermarkets.

3.2 DeCA’s Slotting Contract Ban

DeCA’s report to Senator Christopher Bond, the Ranking Member of

Senate Committee on Small Business and Entrepreneurship, states that:

objects to DeCA’s decisions; and (8) DeCA removes all deleted items from the stock system after 90 days. Defense Commissaries, supra note 34, at app. III. 48 Id.

18

DeCA does not require its suppliers to pay for shelf space in

commissaries, the agency accepts and stocks products for sale without

charging slotting fees. However, in recent years the agency participated

in a small number of promotional arrangements, called “performance

based agreements,” under which suppliers paid a negotiated fee for

preferred product display space . . .. The revenue from these performance

based agreements . . . has been used to fund commissary construction.

The agency discontinued offering its suppliers performance-based

agreements for 2002 to assure that revenue obtained through these

agreements was not limiting vendors’ ability to reduce product prices and

because the Congress had provided for funding commissary

construction.49

As one can verify with a quick review of the sample contract attached as

Appendix A, the there are no meaningful differences between “performance

based agreements” (“PBAs”) and the slotting contracts observed in private

supermarkets.50

DeCA officials decided not to enter into any PBAs for fiscal year 2002 after

using shelf space contracts in both 2000 and 2001.51 This decision was made after

a number of Senate Small Business Committee hearings, which included a

request that DeCA self-report on its own shelf space allocation practices, and in

particular, its use of slotting. DeCA publicly stated that the shelf space contract

program was terminated because Congress granted separate funding for

commissary construction, obviating the need for additional revenues from the

49 Defense Commissaries, supra note 34, at 2.

50 Senator Bond nonetheless issued a press release announcing that he was “heartened by findings that the Defense Commissary Agency does not accept so-called slotting fees or cash payments from big manufacturers to control prime shelf space and limit the display of competing products produced by small manufacturers.” Press Release, Senate Comm. on Small Bus. 51 DeCA justified the decision to no longer accept trade spending dollars because the revenue needed for commissary construction had been secured through the National Defense Authorization Act of 2002. Defense Commissaries, supra note 34, at 8.

19

contracts. A reasonable interpretation of the sequence of events might be that

DeCA ceased practices as a result of the Senate and Department of Defense

inquiries. Regardless, the ban is exogenous to the bargaining process between

manufacturers and DeCA, which allows empirical examination of the

relationship between shelf space contracts and consumer welfare.

4 The Data

The primary source of data are the 32 actual shelf space contracts in

operation at DeCA commissaries from 2000-01, the two years prior to the slotting

ban. While there are 32 contracts, each individual contract may govern several

different SKUs offered by a given manufacturer across several product

categories. For instance, Procter & Gamble might sell shampoo, dog food, and

soap, and sell several SKUs within each product category. However, the shelf

space obligations governing the promotion of each SKU would appear in a single

contract.

These contracts exhibit significant variation across several dimensions,

including form of payment (fixed, variable, or both), magnitude of payment,

duration, and the performance sought from DeCA. The performance sought

might include supplying an end-cap, a specified amount of shelf space, a display

rack, signage, or other forms of promotional effort. Appendix A contains a

sample slotting contract from the data set. Table 1 summarizes the product

categories where slotting contracts were observed in commissaries, as well as the

total value of the payments accepted by the commissaries in each year.

The data also include a set of “plan-o-grams,” shelf space schematics

which detail the precise shelf layout of SKUs in a product category at DeCA

commissaries during the relevant time period. These plan-o-grams indicate the

number of square inches of shelf space allocated to each product, exactly where

the product is allocated on the shelf, and next to what products. Appendix B

20

contains a sample plan-o-gram setting forth the shelf space allocation for juices in

commissaries in 2005.

I also observe the prices and quantities of each SKU sold by DeCA

commissaries in the United States in product categories where a slotting contract

exists. The dataset covers the sales of 11,688 SKUs in 73 product categories from

2000-03, generating approximately $2.3 billion in revenues. Commissary prices

are set nationally and negotiated annually. Therefore, an observation is a price

and quantity combination during a given year. There are also several unique

institutional details of the commissary system, discussed in Section 4, which

inform the empirics.

5 Do Slotting Contracts Harm Consumers?

Despite the substantial resources that have been invested into

Congressional hearings, a Federal Trade Commission Report and Study, federal

prosecutions in both the United States and the European Union resulting in

settlements, and a growing body of antitrust cases involving slotting contracts, it

remains the case that very little is known about their competitive consequences.

A complete analysis of the consumer welfare benefits associated with slotting

contracts would include the following:

(1) Shelf space payments may reduce the price of the slotted good

directly;

(2) Shelf space contracts may stimulate demand for the slotted

product, creating “promotional sales” and increasing output;

(3) Retailers may use shelf space payments to engage in non-price

competition, i.e., advertising, provision of free parking, wider

aisles, a deli, more cash registers, more employees, etc., in order to

increase store traffic;

21

(4) Retailers may use shelf space payments to subsidize price

competition on “staple” products likely to increase store traffic, i.e.,

milk, bananas, diapers, and other staple items.

The data allow measurement of (1) and (2), but not (3) and (4), which the

promotional services theory suggests are quite important since they increase

store traffic, increase shelf space value, and lead to greater future slotting

payments. On the other hand, the analysis should capture any net

anticompetitive effects of slotting on price, output, or product variety. This

suggests that the estimated effects should be interpreted as an upper bound on

anticompetitive effects.

I take a two-step approach to the consumer welfare analysis. In Section

5.1, I consider the product-level effects to determine whether the slotting ban

affected shelf space composition. Specifically, I examine whether the slotting ban

shifted the unit sales and prices of slotted products relative to non-slotted

products. One can think of this step of the analysis as testing for whether the

slotting ban resulted in compositional changes in shelf space allocation from

slotted to previously non-slotted products. This test alone gives us information

on whether slotting is having an impact on shelf space allocations, but alone is

not sufficient to draw conclusions about consumer welfare. The second step of

the analysis addresses the question of whether these compositional effects

resulted in net injury to consumers. Since the pre-ban shelf space allocation

allows for payments to retailers that are ultimately passed on to consumers,

however, the post-ban allocation can only improve welfare if category output

increases, category level prices fall, or product variety increases. Section 5.2

considers the relationship between slotting and category output, prices, and

product variety.

5.1 Differences-in-Differences Estimation of Product Level Effects

22

The basic strategy for identifying the competitive effects of slotting

contracts is to exploit the natural experiment provided by the slotting ban at the

end of 2001. I compare the effects of the ban on a “control group” consisting of

the non-slotted products within a particular product category to the effects on

the “treatment group,” which consists of the slotted products in the same

product categories. This is the “differences-in-differences” or “double

differences” estimate made possible by the natural experiment.

The intuition behind the strategy is simple: compare the change in prices

on slotted products while controlling for changes that occur in the control group

of non-slotted products in the same stores. Technically, one need not estimate a

regression equation. One could calculate the difference in mean prices for

“slotted” and “non-slotted” products before and after the ban and calculate the

difference between those averages. The regression analog to this procedure is to

estimate the following two equations:

(1)

(2)

Pit (Qit ) is the price (quantity) of a specific SKU, where i indexes whether the

product was slotted or non-slotted, and t indexes whether the observation is

before or after the policy change. Si is a dummy variable that takes on the value

of 1 if the SKU is slotted and zero if it is non-slotted. Therefore, βS measures the

treatment group specific effect to account for average differences between slotted

ln ( ) ( ) ( )

ln ( ) ( ) ( )

it DD i t s i A t it

it DD i t s i A t it

p S A S A

q S A S A

α β β β ε

α β β β ε

= + × + + +

= + × + + +

23

and non-slotted products. At is a dummy variable that takes the value of 1 if the

observation is after the slotting ban and zero if the observation is before the ban.

ΒA therefore measures the time trend common to both groups. α is a constant

which allows for a product-specific fixed effect. Finally, the double differences

estimator is βDD , which measures the true effect of the slotting ban. This

estimate answers the crucial counterfactual: what would happen to the prices

and unit sales of slotted products relative to non-slotted products in a world

without slotting contracts?

5.1.1 Quantity Effects

These regressions capture the possibility that slotting contracts generate

“promotional sales,” thereby increasing unit sales that would not otherwise

occur. If slotting contracts induce promotional sales, one would expect the ban

to reduce the output of the slotted products relative to non-slotted products

which are unaffected by the ban. Significant effects, therefore, represent a shift in

the composition of shelf space before and after the ban towards previously non-

slotted products. Fifteen product categories generate statistically significant

quantity effects at the 10% level, 9 at the 5% level, and 6 at the 1% level.

Consistent with the notion that slotting contracts generate promotional sales, the

output of slotted products relative to non-slotted products decreased in 13 out of

15 of these categories. That is, sales shifted towards the previously non-slotted

products after the ban. Of these categories, on average, relative unit sales of

slotted products declined by 13.36% relative to non-slotted products. Table 3

summarizes the results for the 19 categories with the strongest quantity effects.

5.1.2 Price Effects

These regressions measure the impact of the slotting ban on the price of

the slotted product relative to non-slotted products. It is important to note that

24

these regressions do not measure category level price effects. Generally, the

slotting contract ban had little effect on prices. Price effects are significant (at the

10% level) in just 28 of 73 product categories, with prices increasing after the

slotting ban in 17 of these categories.52 On average, the prices of previously

slotted products increased after the ban by 3.7% relative to non-slotted products.

Table 4 presents the price results for the same 19 product categories appearing in

Table 3 where slotting appears to have had the greatest impact.

There are, however, two important limitations on the product level

estimates. It is possible that commissaries would re-optimize shelf space

allocations after the slotting ban. In other words, retailer behavior might change

in important ways in the absence of slotting contracts. This is important because

such re-optimization would result in changes in the manner in which products in

both the treatment and control groups were displayed after the ban. Because

products that were not slotted prior to the ban might be affected by this post-ban

change in retailer behavior, I am only able to estimate relative effects, i.e., how

the sales of previously slotted products changed relative to non-slotted products.

These qualifications aside, the results provide evidence that slotting contracts

have the intended effect, increasing sales of the slotted product. This result

confirms our intuition that shelf space allocations change when slotting contracts

are present.

A separate economic question is whether this change in shelf space

allocations and sales in a world with slotting contracts generates lower consumer

welfare than the equilibrium without slotting. Because slotting generates

payments that are passed on to consumers, the post-ban allocation can only

improve consumer welfare if it is associated with category level benefits such as 52 Price effects are significant at the 5% level in 21 product categories and significant at the 1% level in 13 categories.

25

lower prices, higher output, or higher product variety to offset this loss of

payments. Section 5.2 examines these category level effects.

5.2 Category Level Effects

To measure the intensity of slotting within a product category, I construct

the variable, “SLOTSHARE,” which is the total category sales attributable to

slotted products before the ban. Because there is substantial variance in slotting

intensity across product categories prior to the ban, it is possible to examine

whether increased slotting affects consumer welfare. Specifically, I estimate the

following equation:

(3)

The crucial policy variable of interest is βDD, which can be interpreted as the

effect of the slotting ban on category output weighted by the intensity of slotting

within the product category. I run similar regressions using category prices and

product variety as the dependent variables and find no evidence to support the

theory that slotting is anticompetitive, or that the ban improved consumer

outcomes by any measure. The category level regressions do not completely

measure the welfare effects of slotting because they cannot fully capture the pass-

through of payments to consumers, which might occur on any number of

margins. The category level regressions should therefore be interpreted as a

lower bound on consumer welfare benefits. Because I find no evidence of

anticompetitive effect at the category level, the results suggest that slotting

contracts increases consumer welfare when one accounts for pass-through.

5.2.1 Category Output

Table 5 summarizes the results from the category output regressions.

There is no evidence that product categories with greater intensity of slotting

ln ( ) ( ) ( )it DD t s A t it

q SLOTSHARE A SLOTSHARE Aα β β β ε= + × + + +

26

experienced any increase or decrease in output relative to those where slotting is

less prevalent. Interestingly, there is a significant negative correlation between

the intensity of slotting and sales. In other words, slotting appears to be more

intense in categories with less sales volume.53

5.2.2 Category Prices

Table 6 summarizes the results from the category level price regressions.

There is no evidence of differential price effects in product categories with

greater slotting shares, or that the slotting ban produced lower prices. In sum,

there is no evidence that slotting contracts impact category level prices.

5.2.3 Category Variety

The FTC Study raises the concern that slotting contracts might reduce

product variety.54 I measure whether product categories with greater slotting

shares experienced different changes in product variety, as measured by the total

number of SKUs in the category, after the slotting ban. Table 7 summarizes the

results, which find no evidence that slotting contracts reduce product variety.

6 Conclusions, Antitrust Implications, and Future Research

The analysis of the slotting contracts governing shelf space relationships

at military commissaries in fiscal years 2000 and 2001 increases our

understanding of slotting contracts and their consequences.55 DeCA’s slotting

contract ban provides a natural experiment which allows systematic analysis of

the effects of slotting on prices, quantities, and product variety at both the

product and category levels. The results suggest that slotting contracts primarily

53 This may be explained by a correlation between lower volume sales categories and high-margin product categories where the promotional services theory predicts slotting will be most profitable. 54 See FTC Study, supra note 1, at 3-4 (citing Shaffer, supra note 15).

55 Bronsteen et al., supra note 28, analyze the competitive effects of actual shelf space contracts associated with Philip Morris’s Retail Leaders’ program.

27

involve “brand-shifting” without any significant impact on category level prices,

output, or product variety. This result is consistent with the promotional

services theory, which suggests that manufacturers with large margins seeking

incremental “impulse sales” must compensate retailers for providing premium

shelf space because consumers are not willing to pay for the full cost of the

promotion.56 The results call into question the proposition, frequently asserted in

antitrust litigation and the economics literature, that slotting contracts are

anticompetitive.

These results should not be interpreted as evidence that slotting has

ambiguous consumer welfare effects despite the fact that the DeCA slotting ban

was not associated with significantly lower category output or higher category

prices. This study systematically underestimates the consumer welfare benefits

of slotting because it does not capture the benefits of slotting revenue passed-

through to consumers. For example, slotting revenues might result in generally

lower retail prices, increased amenities, or other measures to increase store

traffic. While these payments amount to less than 1% of commissary revenue,

these pass-through effects are very significant in private supermarkets, where

slotting revenues are a considerably larger fraction of total revenue.57 The results

therefore suggest that antitrust law should recognize that slotting and other

forms of competition for distribution are “competition on the merits,” and are

unlikely to involve manufacturer exclusion or retailer attempts to extract

monopoly rents.

There are other important economic questions regarding the use of

slotting contracts. For example, this data allows one to measure how slotting

56 This does not imply social inefficiency. See Gary Becker & Kevin M. Murphy, A Simple Theory of

Advertising as a Good or Bad, 108 Q.J. ECON. 941 (1993). 57 Slotting is estimated to contribute to up to 50-75% of net supermarket profits. John Stanton, Rethinking Retailers’ Fees, FOOD PROCESSING, Vol. 60, No. 8, at 32 (1999).

28

contracts influence shelf placement, the impact of slotting on private label

brands, and on smaller firms. The data also allow for a systematic analysis of

firm and industry level determinants of shelf space contracts. Future research

will address these questions.

29

References

Areni, Charles, Duhan, Dale & Kiecker, Pamela, “Point-of Purchase Displays,

Product Organization, and Brand Purchase Likelihoods,” 27(4) Journal of

the Academy of Marketing Science 428-41 (1999).

Becker, Gary and Murphy, Kevin M., “A Simple Theory of Advertising as a Good

or Bad,” 108 Quarterly Journal of Economics 941 (1993).

Bloom, Paul, Greg Gundlach and Joseph Cannon [2000]. “Slotting Allowances

and Fees: Schools of Thought and the Views of Practicing Managers,” 64

Journal of Marketing, 92-108.

Bronsteen, Peter, Elzinga, Kenneth G., & Mills, David, “Price-Competition and

Slotting Allowances,” 50 Antitrust Bulletin 267 (2005).

Chu, Wujin [1992]. “Demand Signaling and Screening in Channels of

Distribution,” 11 Marketing Science (Fall), 327-247.

Cooper, James C.; Froeb, Luke M.; O’Brien, Dan; and Vita, Michael G.

“Vertical Antitrust Policy as a Problem of Inference.” 23 International

Journal of Industrial Organization 639 (2005).

Congressional Budget Office, “The Costs and Benefits of Retail Activities at

Military Bases.” (October 1997).

Desai, Preyas S. [2000]. “Multiple Messages to Retain Retailers: Signaling New

Product Demand,” 19 Marketing Science 381-89.

Dreze, Xavier, Hoch, Stephen P., & Purk, Mary E., “Shelf Management and Space

Elasticity,” 70 Journal of Retailing 301 (1994).

Federal Trade Commission Staff Report [2001], “Report on the Commission

Workshop on Slotting Allowances and Other Marketing Practices in the

Grocery Industry.”

Federal Trade Commission Staff Study [2003], “Slotting Allowances in the Retail

Grocery Industry: Selected Case Studies in Five Product Categories.”

30

Hausman, Jerry A. [1997]. “Valuation of New Goods under Perfect and

Imperfect Competition in The Economics of New Goods” (Bresnahan and

Gordon, eds.), University of Chicago Press, pp. 209-37.

Klein, Benjamin and Wright, Joshua D., “The Economics of Slotting

Contracts,” forthcoming Journal of Law and Economics (2007).

Klein, Benjamin, “Exclusive Dealing as Competition for Distribution ‘On the

Merits’,” 12 George Mason Law Review 119 (2003).

Klein, Benjamin, Murphy, Kevin M., and Wright, Joshua D., “Exclusive Dealing

and Category Management in Retail Distribution,” unpublished working

paper (2006).

Kovacic, William A., “The Modern Evolution of U.S. Competition Policy

Enforcement Norms,” 71 Antitrust L.J. 377 (2003).

Lafontaine, Francine, & Slade, Margaret, “Exclusive Contracts and Vertical

Restraints: Empirical Evidence and Public Policy.” Forthcoming in

Handbook of Antitrust Economics, Paolo Buccirossi (ed.), Cambridge:

MIT Press.

Lariviere, Martin A. & Padmanabhan [1997]. “Slotting Allowances and New

Product Introductions” 16(2) Marketing Science 112-28.

Marx, Leslie M. & Greg Shaffer [August 2005]. “Upfront Payments and

Exclusion in Downstream Markets”, unpublished paper.

Rennhoff, Adam, “Paying for Shelf Space: An Investigation of Merchandising

Allowances in the Grocery Industry (July 2004), available at

http://www.pages.drexel.edu/~adr24/rennhoffshelf.pdf.

Rey, Patrick, Jeanine Thal & Thibaud Vergé [2005]. “Slotting Allowances and

Conditional Payments,” unpublished paper, March 2005.

Salop, Steven C., “Strategic Entry Deterrence,” 69 American Economic Review

335 (1979).

31

Shaffer, Greg [2005]. “Slotting Allowances and Optimal Product Variety,” 5(1)

Advances in Economic Analysis & Policy: Article 3.

Stanton, John, “Rethinking Retailers’ Fees,” 60(8) Food Processing 32 (1999).

Sudhir, K. & Rao, Vithala, “Do Slotting Allowances Enhance Efficiency or Hinder

Competition?”, 43(2) Journal of Marketing Research 137 (2006).

Sullivan, Mary W., “Slotting Allowances and the Market for New Products,” 40

Journal of Law & Economics 461 (1997).

Wright, Joshua, [2001]. “Vons Grocery and the Concentration-Price Relationship

in Grocery Retail,” 48 UCLA L. Rev. 743.

Wright, Joshua D., “Antitrust Law and Competition for Distribution,”

23 Yale Journal on Regulation 169 (2006).

32

TABLE 1. SUMMARY OF SLOTTING CONTRACTS

Year No. of Agreements Product Categories Estimated Revenue

2000 18 Candy, pet supplies, breakfast foods, butter, margarine, baked goods, cheese, drinks, snack foods and home care products

$1.7 million

2001 14 International products, snack foods, baked goods, drinks, frozen foods, health foods,

kitchen aids, insecticides

$1.2 million

33

TABLE 2. CHARACTERISTICS U.S. OF SUPERMARKETS AND COMMISSARIES (1995)

Average Commissary

Average Supermarket*

Hours Open Per Week

48

131

Stores open Sunday (%)

40

99

Number of Items Stocked

9,600

22,000

Average Customer Transaction**

64 19

Weekly Sales Per Store** 380,000 201,000

Weekly Sales Per Employee**

6,600 3,400

SOURCE: The Costs and Benefits of Retail Activities at Military Bases (Table 2) (citing Congressional

Budget Office based on data from the April 1995 annual report of Progressive Grocer magazine and the

Defense Commissary Agency).

* Supermarket data are for chain stores with annual sales of more than $2 million.

** Commissary sales are adjusted to reflect the commercial retail value of the goods sold.

34

TABLE 3. PRODUCT LEVEL QUANTITY EFFECTS BY CATEGORY

Log (Quantity)

Product Category DD Estimator

(Standard Error) % Change P-Value

Tomato Paste -3.956 (0.766)

-98.086 0.000

Health Food Bars -3.785 (1.033)

-97.729 0.000

Diced Tomatoes -1.695 (0.503)

-81.640 0.001

Pastries 1.567 (0.437)

379.225 0.001

Chili Beans -2.636 (0.860)

-92.835 0.003

Soda -0.978 (0.330)

-62.394 0.003

Tea Mix -2.21 (0.947)

-89.030 0.023

Donuts/Muffins -0.355 (.163)

-29.883 0.030

Pretzels -0.597 (0.284)

-44.954 0.036

Snack Cakes -0.365 (0.191)

-30.580 0.056

Cookies -0.423 (0.239)

-34.492 0.077

Tortilla Chips -0.481 (0.276)

-38.184 0.082

Specialty Pet Food -0.655 (0.366)

-48.056 0.085

Cheese -0.407 (0.236)

-33.436 0.086

Popcorn 1.472 (0.878)

335.794 0.103

Insecticides 0.522 (0.326)

68.540 0.111

Tea Bags -0.631 (0.391)

-46.794 0.112

Coffee Filters 1.598 (0.994)

394.314 0.116

Tea -0.799 (0.551)

-55.022 0.150

35

TABLE 4. PRODUCT LEVEL PRICE EFFECTS BY CATEGORY

Log (Price)

Product Category DD Estimator

(Standard Error) % Change P-Value

Tomato Paste 0.430 (0.016) 53.737 0.008

Health Food Bars -0.567 (0.038) -43.295 0.144

Diced Tomatoes 0.004 (0.019) 0.4 0.836

Pastries -0.064 (0.024) -6.171 0.010

Chili Beans -0.081 (0.047) -7.799 0.089

Soda 0.005 (0.030) 0.518 0.864

Tea Mix 0.047 (0.035) 4.861 0.174

Donuts/Muffins 0.024 (0.014) 2.433 0.080

Pretzels 0.089 (0.018) 9.293 0.000

Snack Cakes 0.004 (0.013) 0.437 0.728

Cookies 0.006 (0.019) 0.604 0.754

Tortilla Chips -0.011 (0.015) -1.101 0.449

Specialty Pet Food

0.003 0.322 0.789 Cheese 0.028

(0.022) 2.83 0.211 Popcorn 0.14

(1.07) 15.081 0.196 Insecticides -0.055

(0.018) -5.315 0.003 Tea Bags -0.004

(0.038) -0.419 0.911 Coffee Filters -0.014

(0.051) -1.422 0.780 Tea -0.045

(0.014) -4.419 0.001

36

TABLE 5. CATEGORY LEVEL QUANTITY EFFECTS

Log (Quantity)

Variable

Coefficient Estimate

(Std. Error) P-Value

Slotshare*After -0.188 (0.500)

0.707

Slotshare -0.636 (0.358)

0.077

After 0 .388 (0.191)

0.042

Constant

14.51614 (0.135)

0.000

Number of Observations 492

37

TABLE 6. CATEGORY LEVEL PRICE EFFECTS

Log (Average Price)

Variable

Coefficient Estimate

(Std. Error) P-Value

Slotshare*After 0.106 (0.164)

0.518

Slotshare -0.042 (0.118)

0.722

After 0.013 (0.063)

0.836

Constant 0.307 (0.045)

0.000

Number of Observations 492

38

TABLE 7. CATEGORY LEVEL VARIETY EFFECTS

(# of SKUs)

Variable

Coefficient Estimate

(Std. Error) P-Value

Slotshare*After 1.019

(41.965) 0.981

Slotshare -10.013

(29.692) 0.736

After -0.631

(16.151) 0.969

Constant 96.641 (11.442)

0.000

Number of Observations 492

39

Appendix A: Slotting Contract Sample

40

41

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Appendix B: Plan-O-Gram Sample

43

44

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