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A Dynamic Oligopoly Game of the US Airline Industry: Estimation and Policy Experiments

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  • Victor Aguirregabiria
  • Chun-Yu Ho

Abstract

This paper studies the contribution of demand, costs, and strategic factors to the adoption of hub-and-spoke networks in the US airline industry. Our results are based on the estimation of a dynamic oligopoly game of network competition that incorporates three groups of factors which may explain the adoption of hub-and-spoke networks: (1) travelers value the services associated with the scale of operation of an airline in the hub airport (e.g., more convenient check-in and landing facilities); (2) operating costs and entry costs in a route may decline with an airline's scale operation in origin and destination airports (e.g., economies of scale and scope); and (3) a hub-and-spoke network may be an effective strategy to deter the entry of other carriers. We estimate the model using data from the Airline Origin and Destination Survey with information on quantities, prices, and entry and exit decisions for every airline company in the routes between the 55 largest US cities. As a methodological contribution, we propose and apply a simple method to deal with the problem of multiple equilibria when using the estimated model to predict the effects of changes in structural parameters. We find that the most important factor to explain the adoption of hub-and-spoke networks is that the cost of entry in a route declines very importantly with the scale of operation of the airline in the airports of the route. For some of the larger carriers, strategic entry deterrence is the second most important factor to explain hub-and-spoke networks.

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Bibliographic Info

Paper provided by University of Toronto, Department of Economics in its series Working Papers with number tecipa-337.

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Length: 49 pages
Date of creation: 29 Sep 2008
Date of revision:
Handle: RePEc:tor:tecipa:tecipa-337

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Related research

Keywords: Airline industry; Hub-and-spoke networks; Entry costs; Industry dynamics; Estimation of dynamic games; Counterfactuals with multiple equilibria;

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References

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  1. Ariel Pakes & Michael Ostrovsky & Steve Berry, 2004. "Simple Estimators for the Parameters of Discrete Dynamic Games (with Entry/Exit Samples)," NBER Working Papers 10506, National Bureau of Economic Research, Inc.
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Citations

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Cited by:
  1. Johannes Van Biesebroeck & Aamir Hashmi, 2007. "Market Structure and Innovation: A Dynamic Analysis of the Global Automobile Industry," 2007 Meeting Papers 362, Society for Economic Dynamics.
  2. Aguirregabiria, Victor & Nevo, Aviv, 2010. "Recent developments in empirical IO: dynamic demand and dynamic games," MPRA Paper 27814, University Library of Munich, Germany.
  3. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
  4. 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.
  5. Riccardo DiCecio & Levon Barseghyan, 2010. "Entry Costs, Industry Structure, and Cross-Country Income and TFP Differences," 2010 Meeting Papers 964, Society for Economic Dynamics.
  6. Aguirregabiria, Victor & Ho, Chun-Yu, 2010. "A dynamic game of airline network competition: Hub-and-spoke networks and entry deterrence," International Journal of Industrial Organization, Elsevier, vol. 28(4), pages 377-382, July.
  7. Michaela Draganska & Sanjog Misra & Victor Aguirregabiria & Pat Bajari & Liran Einav & Paul Ellickson & Dan Horsky & Sridhar Narayanan & Yesim Orhun & Peter Reiss & Katja Seim & Vishal Singh & Raphael, 2008. "Discrete choice models of firms’ strategic decisions," Marketing Letters, Springer, vol. 19(3), pages 399-416, December.
  8. Victor Aguirregabiria & Junichi Suzuki, 2013. "Identification and Counterfactuals in Dynamic Models of Market Entry and Exit," Working Papers tecipa-475, University of Toronto, Department of Economics.
  9. Doraszelski, Ulrich & Escobar, Juan, 2008. "A Theory of Regular Markov Perfect Equilibria in Dynamic Stochastic Games: Genericity, Stability, and Purification," CEPR Discussion Papers 6805, C.E.P.R. Discussion Papers.
  10. Carlos Daniel Santos, 2009. "Recovering the Sunk Costs of R&D: the Moulds Industry Case," CEP Discussion Papers dp0958, Centre for Economic Performance, LSE.
  11. Naoaki Minamihashi, 2011. "Prevention of Competition by Competition Law: Evidence from Unbundling Regulation on Fiber-Optic Networks in Japan," ISER Discussion Paper 0804, Institute of Social and Economic Research, Osaka University.
  12. Aguirregabiria, Victor, 2009. "Estimation of Dynamic Discrete Games Using the Nested Pseudo Likelihood Algorithm: Code and Application," MPRA Paper 17329, University Library of Munich, Germany.
  13. Joao Macieira, 2010. "Oblivious Equilibrium in Dynamic Discrete Games," 2010 Meeting Papers 680, Society for Economic Dynamics.
  14. Jia Yan & Xiaowen Fu & Tae Oum, 2008. "Exploring Network Effects of Point-to-Point Networks: An Investigation of the Spatial Entry Patterns of Southwest Airlines," Working Papers 2008-21, School of Economic Sciences, Washington State University.
  15. Joao Macieira, 2007. "Extending the Frontier: A Structural Model of Investment and Technological Competition in the Supercomputer Industry," Working Papers e07-10, Virginia Polytechnic Institute and State University, Department of Economics.
  16. Stephen Martin, 2012. "Market Structure and Market Performance," Review of Industrial Organization, Springer, vol. 40(2), pages 87-108, March.

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