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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 that may explain hub-and-spoke networks: 1 travelers may value the services associated with the scale of operation of an airline in the hub airport; 2 operating costs and entry costs in a route may decline with the airline-s scale of operation in the 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 methodological contributions, we propose and apply a method to reduce the dimension of the state space in dynamic games, and a procedure to deal with the problem of multiple equilibria when using a estimated model to make counterfactual experiments. 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 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.



Item Type: MPRA Paper -

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

Language: English-

Keywords: Airline industry; Hub-and-spoke networks; Entry costs; Industry dynamics; Estimation of dynamic games; Counterfactual experiments in models with multiple equilibria.-

Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - GeneralL - Industrial Organization > L9 - Industry Studies: Transportation and Utilities > L93 - Air TransportationL - Industrial Organization > L1 - Market Structure, Firm Strategy, and Market Performance > L13 - Oligopoly and Other Imperfect MarketsC - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation ModelingL - Industrial Organization > L1 - Market Structure, Firm Strategy, and Market Performance > L10 - GeneralC - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C35 - Discrete Regression and Qualitative Choice Models ; Discrete Regressors ; ProportionsC - Mathematical and Quantitative Methods > C7 - Game Theory and Bargaining Theory > C73 - Stochastic and Dynamic Games ; Evolutionary Games ; Repeated Games-





Autor: Aguirregabiria, Victor

Fuente: https://mpra.ub.uni-muenchen.de/16739/







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