Most supermarket firms choose to position themselves by offering either everyday low prices (EDLP) across several items or offering temporary price reductions (promotions) on a limited range of items. While this choice has been addressed from a theoretical perspective in both the marketing and economic literature, relatively little is known about how these decisions are made in practice, especially within a competitive environment. This paper exploits a unique store level data set consisting of every supermarket operating in the United States in 1998. For each of these stores, we observe the pricing strategy the firm has chosen to follow, as reported by the firm itself. Using a system of simultaneous discrete choice models, we estimate each store's choice of pricing strategy as a static discrete game of incomplete information. In contrast to the predictions of the theoretical literature, we find strong evidence that firms cluster by strategy by choosing actions that agree with those of its rivals. We also find a significant impact of various demographic and store/chain characteristics, providing some qualified support for several specific predictions from marketing theory.EDLP, promotional pricing, positioning strategies, supermarkets, discrete games

This paper presents empirical evidence that endogenous fixed costs play a central role in determining the equilibrium structure of the supermarket industry. Using the framework developed in Sutton (1991), I construct a model of supermarket competition where escalating investment in firm level distribution systems is driven by the incentive to produce a greater variety of products in every store. Using the observed networks of store and warehouse locations, I identify 51 distinct geographic markets covering nearly the entire United States and empirically verify their relative independence. Employing a store level census, I demonstrate that the industrial organization of these markets is a natural oligopoly in which a small number of firms (between 4 and 6) capture the majority of sales, regardless of market size. While the total number of firms does scale up with the size of the market, the expansion is limited to a competitive fringe of low quality stores.

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Many discrete decisions are made with an eye towards how they will affect future outcomes. Formulating and estimating the underlying models that generate these definitions is difficult. Conditional choice probability (CCP) estimators often provide simpler ways of estimating dynamic discrete choice problems. Recent work shows how to frame dynamic discrete choice problems in a way that is conducive to CCP estimation and that CCP estimators can be adapted to handle

and Yale for useful comments. Timothy Schwuchow provided excellent research assistance. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.