Estimating network economies in retail chains: a revealed preference approach


  • The authors would like to thank Arie Beresteanu, Tim Bresnahan, Jeremy Fox, Paul Grieco, Tom Holmes, Shakeeb Khan, Sanjog Misra, and Andrew Sweeting for their helpful comments. We have also greatly benefited from the thoughtful suggestions of participants in the NBER Winter IO Meetings, Duke University Applied Microeconometrics Lunch, Minnesota Applied Micro Workshop, Triangle Econometrics Conference, and seminar participants at Rochester, Texas A&M, University of Texas Austin, Wisconsin, University of Texas at Dallas, Virginia Tech, and the Yale School of Management. Any remaining errors and omissions are our own.


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 Wal-Mart benefits most from local chain economies, whereas Target shows a greater ability to respond to rival competition. Kmart exhibits neither of these strengths. We explore these results with counterfactual simulations highlighting these offsetting effects and find that local chain economies play an important role in securing Wal-Mart's industry leader status.