I study delays and congestion patterns in U.S. hub airports during periods of high flight volume. I find that these periods are longer when the share of flights operated by the hub airline is greater, and these longer periods exhibit shorter delays. These results lend support to recent theoretical work on congestion, implying that hub-airlines take into account the impact of their scheduling decisions on the congestion that they bear. The results may suggest that congestion management solutions implemented at hub airports dominated by one airline could have only a limited impact on congestion in general.

"We examine two factors that might explain the extent of air traffic delays in the United States: network benefits due to hubbing and congestion externalities. Airline hubs enable passengers to cross-connect to many destinations, thus creating network benefits that increase in the number of markets served from the hub. Delays are the equilibrium outcome of a hub airline equating high marginal benefits from hubbing with the marginal cost of delays. Congestion externalities are created when airlines do not consider that adding flights may lead to increased delays for other air carriers. In this case, delays represent a market failure. Using data on all domestic flights by major US carriers from 1988-2000, we find that delays are increasing in hubbing activity at an airport and decreasing in market concentration but the hubbing effect dominates empirically. In addition, most delays due to hubbing actually accrue to the hub carrier, primarily because the hub carrier clusters its flights in short spans of time in order to maximize passenger interconnections. Non hub flights at hub airports operate with minimal additional travel time by avoiding the congested peak connecting times of the hub carrier. These results suggest that an optimal congestion tax would have a relatively small impact on air traffic delays since hub carriers already internalize most of the costs of hubbing and a tax that did not take the network benefits of hubbing into account could reduce social welfare"--National Bureau of Economic Research web site.

The likely resurgence of air traffic in the U.S. means that airport congestion is a problem that must soon be confronted by policy makers. As part of their policy response, it is probable that some form of congestion pricing will be imposed at selected U.S. airports in the relatively near future. The theory developed in this paper, which extends the results of Brueckner (2002), provides an important guide for the formulation of congestion pricing rules. In particular, the theory says that the congestion tolls levied on the various airlines at a particular airport should generally be different, with the tolls being inversely related to a carrier's airport flight share. Internalization of airport congestion is the reason for this inverse relationship. In operating another peak flight, a carrier takes account of the congestion damage imposed on the other flights it operates. If these flights account for a large share of the airport's traffic, then most of the congestion created by the additional flight is internalized, justifying a low toll. By contrast, if the carrier operates only a few of the airport's flights, then little internalization occurs, and a high toll is needed to force the carrier to take into account the congestion damage it causes. The resulting flight-share rule is easy to implement, and it could help policymakers design proper toll systems at U.S. airports.

Introduction: Air passenger traffic in the United States showed remarkable growth during the economic expansion of the 1980's. Each day a million and a quarter passengers board commercial flights. The boom coincided with the advent of airline deregulation in 1978. This drastic change in the industry has inspired professional and newspaper articles, graduate student theses, and books which have discussed the causes, effects, costs, and benefits of deregulation with predictably mixed conclusions. Economists, who like to predict the future by exercising econometric models, are finding that conditions in air transportation have become too dynamic (chaotic?) for their models to cope. Certainly the future of the air transportation industry is unclear. There has been, however, an unmistakable trend toward oligopoly, or, as industry spokesmen describe it, "hardball competition among the major airlines." This trend has been accompanied by formations of hub fortresses owned by these survivors. Air traffic has always been concentrated in a few large cities; airplanes will go where there is a demand for them. But airline (rather than traffic) hubs have created artificial demand. Up to seventy percent of travellers boarding airplanes in the hub cities do not live anywhere near these cities - in fact, they may have no idea at which airport they are changing planes. Most passengers do not care, while travel cognoscenti soon learn to avoid certain airports (and airlines which frequent these airports). A hub airport is a frenzy of activity for short periods of time during the day, as complexes of airplanes descend, park and interchange passengers, and take off. Then the airport lies quietly. If observers were to arrive at a major hub between times of complexes, they would be perplexed to hear that "this is one of the most congested airports in the world." Thus congestion and its evil twin, delay, are not constants in the system. Rather, they appear only if a number of conditions conspire to manifest themselves simultaneously, or nearly so. First, the weather must deteriorate from visual flight conditions to instrument flight conditions. Then, this must occur near peak demand conditions at the airport. Of course, some airports in the Unites States are always near peak conditions, among them the so-called slot constrained airports: New York's La Guardia and Kennedy, Washington's National, and Chicago's O'Hare. When weather goes bad at these airports or other major hubs during complexes, ripple effects start nearly all over the country, because some airlines have now designed schedules to maximize utilization of their airplanes. Very little slack time is built into the schedules to account for potential delays, although "block-time creep" exists: the phenomenon that travellers discover when they arrive at their destinations ahead of schedule (if they happen to leave on time). This "creep" protects the airlines from being branded as laggards by the DOT's Consumer On-Time Performance Data hit list. Thus a combination of management practices by airlines (which place great demand on terminal airspace over a concentrated period of time) and mother nature (which provides currently unpredictable behavior of weather near the airport) conspire to limit the capabilities to handle arrivals and departures at various airports below the numbers that had been scheduled. Travellers complain that the schedules aren't being met, and if enough people complain to Congress, or if the travellers themselves happen to be members of Congress, a national problem appears. How much of a problem is this? In 1988 there were 21 airports, according to the FAA, which exceeded 20,000 hours of annual aircraft delay, perhaps 50,000 hours per year, or 140 hours per day. (One, Chicago's O'Hare, exceeded 100,000 hours.) These airports, in turn, averaged 1,000 operations (arrivals and departures) per day, so that each operation would have averaged about 8 minutes of delay. At O'Hare, for example, 6% of all operations experienced in excess of 15 minutes of delay. (In excess means just that - there is no knowledge of how much "in excess" is.) Conversely, this means that at that most congested airport in the United States, 94% of all airplanes arrive or depart with less than 15 minutes of delay. However, airline delay statistics may be similar to the apocryphal story of the Boy Scout troop which drowned wading across a creek which averaged two feet in depth. There are estimates that on a dollar basis, delay accounts for a $3 billion cost to airlines, or a net societal cost of $5 billion if travellers' wasted time is included. Since in their best years U.S. airlines make about $3 billion in profit, reducing delay is a sure-fire way for airlines to climb out of their all too frequent financial morasses, as well as diminishing their passenger frustrations. Even though all of the numbers mentioned in the paragraphs above are subject to substantial caveats, it is indisputable that on certain days during the year the air transportation system seems to come to a crawl, if not a halt. Travellers either find themselves sitting at airport lounges observing cancellation and delay notices appearing on the departure and arrival screens, or sitting in airplanes (on runways or at gates) being told that there is an "air traffic delay." Old-timers grumble that the only difference twenty years of technology improvements has made to the U.S. airspace system is that the wait is now on the ground instead of circling in the air near their destinations. To the casual observer, it would appear that a number of solutions exist to solve this problem. The most obvious is to pour more concrete: more airports, more and longer runways, more taxiways, more gates and terminals. This is analogous to widening highways and building more interstates for ground transportation congestion. The concrete solution, alas, runs into both financial and citizen roadblocks. It is very expensive - the latest airport coming off the drawing boards (Denver International) carries a tag of some $2 billion, with about $400 million of that in bonds being backed by a new funding creature, the Passenger Facility Charge (a head tax of up to 3 dollars assessed to every passenger enplaning at an airport - voluntary or not). The citizen roadblock is community objections to airport noisiness. The bill creating the PFC in 1990 also carried with it a mandate for the FAA to create a national noise policy so that individual airports would not wreak havoc with the whole system by creating their own local operational rules, such as curfews. The bill also attempted to pacify airport neighborhoods by setting a deadline for all U.S. aircraft to be quiet(er) - complying with Stage 3 regulations by the year 2000. More damaging than financial difficulties are the anti-noise sentiments, and the concomitant not-in-my-backyard syndrome, that are at the forefronts of protests of either an alert citizenry, or New Age Luddites, when any expansion plans are made public. Whatever one's view, it is a crowd vocal and seemingly powerful enough in local political circles to stop any large- scale progress to ground solutions of the congestion problem. That, then, leaves the air. It is intuitive that if airplanes were closer spaced than they are now, much more traffic would move through a given area in the same amount of time, and consequently airplanes would land (and take off) quicker, reducing any waiting (queue) time. This obviously increases airport noise levels. There are two problems with this approach. The first trick is to accomplish this safely. Safety has at least two dimensions: there is the physical, i.e., airplanes should not run into each other (or the ground, as a result of weather disturbances and wake vortices); and pilots (and controllers) should feel they are still in control of the situation, even after separation standards are reduced. The first aspect is mostly a matter of technology, the second mostly a matter of human factors. But if traffic moved quicker and noise of the aircraft is not reduced, the same citizens who had vehemently opposed the construction of additional ground facilities would once again rise in righteous anger and demand a stop to the more efficient techniques of flying airplanes which have caused an increase in the noise levels in their neighborhood. They, too, must be considered. This report will attempt to address some of the issues outlined above. The focus will be on technology and where it is best suited to provide an equitable and efficient expansion of capacity in the air transportation system. Ultimately, the discussion will be centered on NASA's potential contributions to solving the capacity problem

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