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Non-stop Love: A Study of Entry Barriers in the Airline Industry Using Policy Changes at Dallas Love Field

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Abstract

Exogenous changes in entry barrier conditions faced by firms allow for an analysis of their impact on competition and market structure. This empirical study finds that the policy changes at Love Field airport arising from the repeal of the Wright Amendment in October 2014 led to reduction in airfares on routes between Dallas and cities beyond the neighboring states of Texas, but increase in airfares on routes between Dallas and destinations in Texas and its surrounding states (collectively called the Wright Perimeter). The fare decrease can be attributed to airlines (primarily Southwest) entering non-stop markets from Love Field, whereas the fare increases in the short-haul within Wright Perimeter markets indicates the impact of binding gate constraints. A capacity-constrained entry model is used to explain the opposite effects in different markets.

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Notes

  1. Bureau of Transportation Statistics data, 2013–2014.

  2. Love Terminal Partners et al. (2011) Plaintiffs.

  3. Note that provision (3) allows airlines to operate flights anywhere from DAL, but only in extremely small capacities. Therefore, throughout the WA literature, it is stated that airlines out of DAL were simply not allowed to operate flights anywhere from DAL.

  4. Airlines for America (A4A, 2014).

    Fig. 1
    figure 1

    The Wright Perimeter as of October 2014 (shaded)

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  5. A Dallas news article discusses how gate limitations have led to a conflict between Southwest and Delta: https://www.dallasnews.com/business/business/2016/07/11/southwest-delta-share-dallas-love-field-gate-working.

  6. Airport presence in Berry (1992) is either the mean value of passenger miles across the two cities in the pair, or the mean number of destinations served out of either end points.

  7. “Through ticketing” is the arrangement that allows airlines operating out of DAL to market tickets to destinations beyond the WP, although a stopover needs to be made within the perimeter.

  8. Dallas Morning News (2019).

  9. Reporting carriers in the DB1B include all the major airlines operating domestic routes in the USA.

  10. Note that the market is agnostic to the actual route of travel. So BOS-ORD-DAL is considered the same market as the non-directional BOS-DAL market. A further investigation that accounts for the heterogeneity of the route is performed while investigating the policy impact on non-stop versus multiple stop markets. The results are in the “Appendix”.

  11. A coupon in the DB1B represents a boarding pass.

  12. Follows Kwoka and Shumilkina (2010).

  13. This was done to identify the causal effect in the DiD specification, as the DiD framework relies on the comparison of prices in the prior to the post regime change periods. So markets with no prior or no post would not have a counterpart in a different time period for comparison. This data filtering step did not restrict the capture of new Southwest markets since Southwest (and other impacted carriers) did not enter new markets (non-directional airport pairs) that were completely non-existent in the prior period, but rather only changed the routing, i.e., from one-stop to non-stop, or changed flight frequency.

  14. This follows the logic of gravity models used in urban geography literature.

  15. Some airports in the USA are slot controlled, i.e., restrictions are imposed on airlines operating at that airport from making more than a given number of take-offs and landings.

  16. The definition of an airline’s hub follows the information given on their websites.

  17. A tourist destination was defined using http://travel.usnews.com/rankings/best-usa-vacations/.

  18. Following Kwoka et al. (2016), a low-cost carrier is any of the following: AirTran, JetBlue, Frontier, Allegiant, Spirit and Southwest. Note that markets operated by Southwest are excluded from CONTROL-B since they are not present in CONTROL-A.

  19. The list of hubs is presented in the “Appendix”.

  20. Morrison (2001) and Kwoka and Shumilkina (2010) are examples of past research that evidences similar results.

  21. As an example, a market with end-points that have more connecting markets, or more airlines operating (presenting opportunities of codesharing) may have more airlines.

  22. The robustness of these findings was also checked by constructing arbitrary treatment groups. The findings are reported in Table 15 in the “Appendix”. The arbitrary treatment groups used do not display the same pattern of fare changes as the treatment groups used in the study.

  23. Percent figures rounded off for simplicity.

  24. DAL–WP and DFW–WP are referred as “short-haul” markets since they involve end-point cities that are smaller in distance than DAL–outside WP and DFW–outside WP, which are referred as “long-haul” markets.

  25. It could be argued that airlines could have used various forms of price discrimination to charge different fares to business and leisure passengers even in the ex-ante period. While this is true, the exit of leisure passengers from airline markets in the ex-post period in Dallas-based short-haul markets makes it easier for carriers to devise policies catered only for business passengers.

  26. An analysis of the change in output and capacity in this subset of Treatment 3 validates the claim that the fare rise results from Southwest exiting these markets following the policy changes: these markets had 300 thousand seats, 4589 departures in pre, and 29 thousand seats and 530 departures in post.

  27. E.G. for DAL–VEGAS, the end-point is Vegas, and the average number of markets Southwest operated flights through Vegas during ex-ante year-quarters (i.e., the instrument’s value) was 85.1. Symmetric definitions apply for other two instruments based on passenger count and RPM.

  28. RPM = Number of passengers * Distance travelled. RPM is widely used as a measure of traffic in airline markets.

  29. Note that the percent fare change averages does not take into account the overidentified specification (5).

  30. Note that even before the WA was fully repealed, airlines could serve DAL–outside WP markets in aircrafts with not more than 56 seats (discussed under Introduction). This is responsible for the small number of non-stop total seats and flights in the ex-ante period.

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Acknowledgements

I would like to thank Professors Steven A. Morrison, James Dana and John E. Kwoka for valuable guidance. I am also thankful to Dr. Brian Chezum for contributing to the theoretical framework presented in the paper.

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  1. Northeastern University, Boston, USA

    Pukar KC

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Appendix

Appendix

See Tables 13, 14, 15, 16, 17, 18 and 19.

Table 13 Hubs with respective Airlines
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Table 14 Cities with tourist dummy equalling one
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Table 15 Common abbreviations used in the paper
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Table 16 Investigating heterogeneous effects on non-stop and multiple-stop flights (with fixed effects)
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Table 17 Baseline regression results with fixed effects for alternate treatment groups for checking robustness
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Table 18 Control groups used in the study
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Table 19 Treatment Groups used in the study
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KC, P. Non-stop Love: A Study of Entry Barriers in the Airline Industry Using Policy Changes at Dallas Love Field. Eastern Econ J 46, 379–413 (2020). https://doi.org/10.1057/s41302-019-00165-0

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