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Estimating Network Economies in Retail Chains: A Revealed Preference Approach

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  • Paul B. Ellickson
  • Stephanie Houghton
  • Christopher Timmins

Abstract

We measure the effects of chain economies, business stealing, and heterogeneous firms' comparative advantages in the discount retail industry. Traditional entry models are ill-suited for this high-dimensional problem of strategic interaction. Building upon recently developed profit inequality techniques, our model admits any number of potential rivals and stores per location, an endogenous distribution network, and unobserved (to the econometrician) location attributes that may cause firms to cluster their stores. In an application, we find that Kmart and Target benefit most from local chain economies; Wal-Mart's advantage is more global. We explore these results with counterfactual simulations highlighting these offsetting effects.

Suggested Citation

  • Paul B. Ellickson & Stephanie Houghton & Christopher Timmins, 2010. "Estimating Network Economies in Retail Chains: A Revealed Preference Approach," NBER Working Papers 15832, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:15832
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Eduardo Morales & Gloria Sheu & Andrés Zahler, 2014. "Gravity and Extended Gravity: Using Moment Inequalities to Estimate a Model of Export Entry," NBER Working Papers 19916, National Bureau of Economic Research, Inc.
    2. Maican, Florin & Orth, ´Matilda, 2013. "Entry Regulations, Product Differentiation and Determinants of Market Structure," Working Paper Series 984, Research Institute of Industrial Economics.
    3. Sumon Datta & K. Sudhir, 2013. "Does reducing spatial differentiation increase product differentiation? Effects of zoning on retail entry and format variety," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 83-116, March.
    4. Erdmann, Anett, 2014. "Hotelling meets Holmes : the importance of returns to product differentiation and distribution economies for the firm's optimal location choice," UC3M Working papers. Economics we1420, Universidad Carlos III de Madrid. Departamento de Economía.
    5. Andres Aradillas-Lopez & Adam Rosen, 2013. "Inference in ordered response games with complete information," CeMMAP working papers CWP33/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Nathan Yang, 2012. "Burger King and McDonald’s: Where’s the Spillover?," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 19(2), pages 255-281, July.
    7. Sumon Datta & K. Sudhir, 2012. "Does Reducing Spatial Differentiation Increase Product Differentiation? Effects of Zoning on Retail Entry and Format Variety," Cowles Foundation Discussion Papers 1851, Cowles Foundation for Research in Economics, Yale University, revised Sep 2012.
    8. Mitsukuni Nishida, 2012. "Estimating a Model of Strategic Network Choice: The Convenience-Store Industry in Okinawa," Economics Working Paper Archive 594, The Johns Hopkins University,Department of Economics.
    9. Nathan Yang, 2011. "An Empirical Model of Industry Dynamics with Common Uncertainty and Learning from the Actions of Competitors," Working Papers 11-16, NET Institute.
    10. Victor Aguirregabiria & Gustavo Vicentini, 2006. "Dynamic Spatial Competition Between Multi-Store Firms," Working Papers tecipa-253, University of Toronto, Department of Economics.
    11. Peter Arcidiacono & Patrick Bayer & Jason R. Blevins & Paul B. Ellickson, 2016. "Estimation of Dynamic Discrete Choice Models in Continuous Time with an Application to Retail Competition," Review of Economic Studies, Oxford University Press, vol. 83(3), pages 889-931.
    12. Jeremy T. Fox & Natalia Lazzati, 2012. "Identification of Potential Games and Demand Models for Bundles," NBER Working Papers 18155, National Bureau of Economic Research, Inc.
    13. Jeremy Fox & Natalia Lazzati, 2013. "Identification of discrete choice models for bundles and binary games," CeMMAP working papers CWP04/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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    JEL classification:

    • L0 - Industrial Organization - - General

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