Network Effects, Congestion Externalities, and Air Traffic Delays: Or Why Not All Delays Are Evil

We examine two factors that explain air traffic congestion: network benefits due to hubbing and congestion externalities. While both factors impact congestion, we find that the hubbing effect dominates empirically. Hub carriers incur most of the additional travel time from hubbing, primarily because they cluster their flights in short time spans to provide passengers as many potential connections as possible with a minimum of waiting time. Non-hub flights at the same hub airports operate with minimal additional travel time. These results suggest that an optimal congestion tax might have a relatively small impact on flight patterns at hub airports. Disciplines Aviation | Management and Operations | Real Estate This journal article is available at ScholarlyCommons: http://repository.upenn.edu/real-estate_papers/80 Network Effects, Congestion Externalities, and Air Traffic Delays: Or Why Not All Delays Are Evil By CHRISTOPHER MAYER AND TODD SINAI* We examine two factors that explain air traffic congestion: network benefits due to hubbing and congestion externalities. While both factors impact congestion, we find that the hubbing effect dominates empirically. Hub carriers incur most of the additional travel time from hubbing, primarily because they cluster their flights in short time spans to provide passengers as many potential connections as possible with a minimum of waiting time. Non-hub flights at the same hub airports operate with minimal additional travel time. These results suggest that an optimal congestion tax might have a relatively small impact on flight patterns at hub airports. (JEL L2, L5, L9, D6) Over the last few years, air traffic delays have garnered increasing attention. The year 2000 produced record delays with more than onequarter of all flights arriving at least 15 minutes behind schedule. With infrastructure improvements being years away and conventional wisdom holding that delays are caused by congestion externalities, proposed policy remedies have focused on economic solutions such as congestion pricing. However, selecting the appropriate remedy depends crucially on what is causing congestion and delays. In this paper, we try to determine the economic underpinnings of air traffic congestion. One potential cause of greater travel times is the classic congestion externality, also known as the “tragedy of the commons.” According to this hypothesis, congestion occurs because most airports allow unlimited landings and takeoffs and airlines schedule flights without valuing the fact that their traffic will increase travel time for other airlines. Failure to internalize the true marginal cost of adding a flight leads to congestion at airports and flights being delayed. The standard solutions are to use a Pigouvian tax, such as pricing by time of day or the length of a queue, or to restrict traffic and assign property rights by selling ownership of scarce landing slots at congested airports. Previous empirical research has focused on these solutions, suggesting that a congestion tax would have substantial efficiency gains in reducing the level of delays [Alan Carlin and R. E. Park (1970); Steven Morrison and Clifford Winston (1989); Joseph I. Daniel (1995); Daniel and Munish Pahwa (2000)]. One problem with the congestion externality explanation for delays, however, is that it is not consistent with the delay pattern across all U.S. airports. In the “tragedy of the commons,” it is usually assumed that there are multiple agents who do not take into account the externality that they create for others. While congestion externalities might explain why airports without a * Mayer: The Wharton School, 314 Lauder-Fischer Hall, University of Pennsylvania, 256 South 37th Street, Philadelphia, PA 19104 (e-mail: [email protected]); Sinai: The Wharton School, 308 Lauder-Fischer Hall, University of Pennsylvania, 256 South 37th Street, Philadelphia, PA 19104, and National Bureau of Economic Research (e-mail: [email protected]). We are especially indebted to Jeff Butler of the U.S. Department of Transportation for providing the flight data used in this paper. We also wish to thank two anonymous referees, Betsy Bailey, Judy Chevalier, Glenn Ellison, David Genesove, Ed Glaeser, Richard Golaszewski, Joseph Gyourko, Dorothy Robyn, Andrew Samwick, Joel Waldfogel, Clifford Winston, and seminar participants at Cornell University, Dartmouth College, Harvard University, MIT, NBER, University of British Columbia, University of Chicago, University of Pennsylvania, and Yale University for helpful comments. This material is based upon work supported by the National Science Foundation under Grant No. 0214410 and the Zell/ Lurie Real Estate Center at The Wharton School. The excellent research assistance of Sam Chandan, James Knight-Dominick, and Dou-Yan Yang is appreciated. 1 See models in William S. Vickrey (1969) and Richard Arnott (1979) as examples of transport systems with inef-