ABSTRACT FLYING UNDER THE RADAR: MULTIMARKET CONTACT AND TACIT COLLUSION IN THE U.S. AIRLINE INDUSTRY by Henry Jameson Shaneyfelt This paper serves to identify the effects of multimarket contact on tacit collusion through the measures of average price and price dispersion. The assertion of the theoretical literature is that higher levels of multimarket contact are corollary to firms relaxing competitive pricing. It is consequently an expectation that higher prices and more price discrimination will be seen within markets comprising of firms simultaneously competing with rival firms in many markets. Implementing methods used in Evans and Kessides (1994) and Ciliberto and Williams (2014), I employ gate-use data to instrument for the average multimarket contact variable and address any potential bias from endogeneity. Additionally, squared gate-use instruments, which are novel to the existing literature, are included in the analysis. When implementing this new methodology, I find a significant positive relationship between multimarket contact and average price with estimates matching the existing literature. Using the same methodology, a significant positive relationship is found between multimarket contact and price dispersion which has hitherto not been observed. The results of this paper indicate that collusive behavior is indeed present within markets with higher levels of multimarket contact. FLYING UNDER THE RADAR: MULTIMARKET CONTACT AND TACIT COLLUSION IN THE U.S. AIRLINE INDUSTRY Thesis Submitted to the Faculty of Miami University in partial fulfillment of Master of Arts in Economics by Henry Jameson Shaneyfelt Miami University Oxford, Ohio 2021 Advisor: Dr. Charles Moul Reader: Dr. Mark Tremblay Reader: Dr. Peter Nencka © 2021 Henry Jameson Shaneyfelt This thesis titled FLYING UNDER THE RADAR: MULTIMARKET CONTACT AND TACIT COLLUSION IN THE U.S. AIRLINE INDUSTRY by Henry Jameson Shaneyfelt has been approved for publication by Farmer School of Business and Department of Economics ____________________________________________________ Dr. Charles Moul ____________________________________________________ Dr. Mark Tremblay ____________________________________________________ Dr. Peter Nencka Table of Contents 1 Introduction ................................................................................................................................ 1 2 Literature Review ...................................................................................................................... 2 2.1 Theory ................................................................................................................................... 2 2.2 Empirical ............................................................................................................................... 3 2.3 Contemporary WorK ............................................................................................................. 4 3 Data ............................................................................................................................................. 4 3.1 Data Sources ......................................................................................................................... 5 3.2 Observations ......................................................................................................................... 6 3.3 Dependent Variables ............................................................................................................. 7 3.4 Control Variables .................................................................................................................. 7 3.5 Multimarket Contact Variable .............................................................................................. 8 3.6 Endogeneity of the Multimarket Contact Variable ............................................................... 8 3.7 Instrumental Variables ........................................................................................................ 10 4 Results ....................................................................................................................................... 11 4.1 Models................................................................................................................................. 11 4.2 OLS Regressions ................................................................................................................. 12 4.3 IV First Stage Regressions .................................................................................................. 13 4.4 IV Second Stage Regressions ............................................................................................. 14 5 Limitations ................................................................................................................................ 15 6 Conclusion ................................................................................................................................ 16 Appendix ...................................................................................................................................... 17 References .................................................................................................................................... 30 i List of Tables Table 1: Observed Airports and Airlines ...................................................................................... 19 Table 2: Comparing Used Gates with ACP Gate Ownership ....................................................... 20 Table 3: Summary Statistics ......................................................................................................... 22 Table 4: Number of Common Markets in 2016-Q2 ...................................................................... 23 Table 5: Prices & Multimarket Contact (OLS) ............................................................................. 25 Table 6: Price Dispersion & Multimarket Contact (OLS) ............................................................ 26 Table 7: Multimarket Contact & Gates (OLS) ............................................................................. 27 Table 8: Prices & Multimarket Contact (2SLS) ........................................................................... 28 Table 9: Price Dispersion & Multimarket Contact (2SLS) ........................................................... 29 ii List of Figures Figure 1: Cumulative Market Share of Sampled Airlines Over Time .......................................... 21 Figure 2: Non-Monotonicity Between Contact and Gates ............................................................ 24 iii Dedication I would like to dedicate this paper to my parents, Paul and Jill, who have never ceased to support me in my academic pursuits. iv Acknowledgements I would like to thank Dr. Charles Moul for all the help he has provided to me as an advisor. Without his guidance and trust in my ideas, this paper simply could not have happened. v 1 Introduction Collusion is an intricate game. While it can beget considerable gains for those who execute it well, it can just as easily devastate those who fail to do so. Optimizing firms within a market undoubtedly find the proposition of collusion attractive, but maintaining a cartel through threats of punishment is by no means a simple task. The main reason for this is that historically the threats within a single market are typically not substantial enough to deter defection. However, the modern-day economy is seeing an increasing number of firms competing with rival firms in numerous differing markets at a given time. An intriguing attribute of this newly structured economy is the ability for firms to interact with rivals across markets. Aggressive pricing of a firm in one market may now result in a rival firm responding in a different, mutually served market. This occurrence, known as multimarket contact, has been a topic of interest for many economists who posit that it substantially increases the probability of collusive behavior. While this may seem difficult to follow at first blush, the intuition behind this theory makes it clear why this outcome is a plausible possibility. The general notion driving this theory is that multimarket contact creates the potential for larger-scale retaliations to firms who may try deviating from collusive outcomes. For the sake of example, imagine there are two firms, A and B, that simultaneously compete in markets 1, 2, and 3. If firm A were to attempt to deviate from a collusive outcome in market 1 by cutting prices, firm B could retaliate by not just dropping prices in market 1 but by also dropping prices in markets 2 and 3. Lest this outcome be realized, firm A will find it optimal to price less aggressively (i.e., collude) in all simultaneously served markets. Such is the essence of tacit collusion, where non-competitive outcomes are not explicitly coordinated but mutually understood and maintained. As the multimarket contact between two firms increases, the potential retaliation does the same. Due to this, firms that experience higher levels of multimarket contact may be less likely to behave competitively. As this probability of tacit collusion rises, theory indicates that monopolistic behavior is more likely to be observed. The specific characteristics of this behavior that I consider are higher prices and greater price discrimination. These serve as strong indicators for tacit collusion, as they would be impossible to occur in a competitive setting. Within a market