Do Airlines Pad Their Schedules?

Abstract

We analyze how schedule times, actual flight times and on-time performance have changed in the U.S. airline industry between 1990 and 2016. We find schedule times have increased in most years, with the largest increases after 2008. Actual flight times and total travel times have also increased but by less than schedule times and the gap has grown over time. This has resulted in reduced arrival delays even though flights are, in fact, taking longer to complete. We discuss the implications of these findings for quality provision and information disclosure within the airline industry.

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Notes

  1. 1.

    Regulation 14 CFR Part 234.

  2. 2.

    Source: ”14 CFR Part 234 Revision of Airline Service Quality Performance Reports and Disclosure Requirements” published by the Department of Transportation in 2007.

  3. 3.

    Throughout the paper, we will use the terms “arrives” and “arrival time” to refer to the time that a plane arrives at the gate.

  4. 4.

    Forbes et al. (2015) show that airlines systematically speed up flights that are projected to arrive right at or above the 15-min threshold. These types of threshold effects have also been documented in other contexts as well: for example, see Neal and Schanzenbach (2010), on education.

  5. 5.

    Consumers presumably care about how late a flight is compared to its scheduled arrival time (the metric the DOT measures); but they also care about total schedule time. Airlines can improve on the first dimension by deteriorating the second.

  6. 6.

    For example, see stories in the Wall Street Journal (Mccartney 2010) and USA Today (Frank 2013).

  7. 7.

    Other work on airline on-time performance has estimated how on-time performance impacts demand (Forbes 2008) and how entry and competition affect on-time performance, for example, Mazzeo (2003) Prince and Simon (2014), Prince and Simon (2017) and Cao et al. (2017).

  8. 8.

    It is not clear how consumers value early arrivals. Arriving early allows consumers to make connections and not miss any planned events. However, it often wastes time that could have otherwise been allocated to other activities.

  9. 9.

    We exclude the first two years of data after the disclosure requirement took effect to avoid any changes in scheduling practices that were an immediate response to the program.

  10. 10.

    A number of airlines disappear from the data due to mergers. We deal with mergers in the following way. Suppose airline A and airline B merge and maintain the brand of airline B. For routes that were served by airline A but not served by airline B before the merger, we continue to give flights on these routes airline A’s fixed effect after the merger (despite the fact that these flights appear with airline B’s code in the data after the merger). This will ensure that the same flights are compared to each other over time. For routes served by airline B before and after the merger, we use airline B’s fixed effect before and after the merger. For routes that were served by both airlines A and B before the merger, we assign airline B’s code to all of their flights on this route after the merger.

  11. 11.

    A route is a directional city-pair from a particular origin airport to a particular destination airport.

  12. 12.

    Total travel time is actual flight time plus departure delay or—put differently—the time between when consumers expected to leave and when they actually arrived.

  13. 13.

    These measures do not include international flights.

  14. 14.

    We do not adjust our congestion measures for the number of runways at an airport because our empirical estimation includes route fixed effects. Our results are robust to including squared and cubed terms of the congestion variables and to using dummy variables that indicate the quantiles of the congestion variable at an airport within a year.

  15. 15.

    For variables that are dummy variables—such as whether or not a flight arrived less than 15 min after its scheduled arrival time—the collapsed variable will measure the fraction of the airline’s flights on the route in the month that arrived less than 15 min after their scheduled arrival time.

  16. 16.

    Except for the last year which is 2016 instead of 2015.

  17. 17.

    The online appendix can be found at https://sites.google.com/site/silkeforbes/home/publications

  18. 18.

    We have also estimated all of our specifications with the use of logged dependent variables, and the results are qualitatively similar.

  19. 19.

    Departure in the early morning, between 5 am and 10 am, is the omitted group.

  20. 20.

    The top 30 or 50 airports are determined by the U.S. Federal Aviation Administration’s ”Calendar Year 2016 Preliminary Revenue Enplanements at Commercial Service Airports”.

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Correspondence to Mara Lederman.

Appendix

Appendix

See Tables 7, 8 and 9.

Table 7 Sample split by distance
Table 8 Alternative samples
Table 9 Fuel price control

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Forbes, S.J., Lederman, M. & Yuan, Z. Do Airlines Pad Their Schedules?. Rev Ind Organ 54, 61–82 (2019). https://doi.org/10.1007/s11151-018-9632-1

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Keywords

  • Airlines
  • Information disclosure
  • On-time performance