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Transcription:

Young Researchers Seminar 2009 Torino, Italy, 3 to 5 June 2009 Hubs versus Airport Dominance (joint with Vivek Pai)

Background Airport dominance effect has been documented on the US market Airline with a dominant position at an airport charges more for flight into/from that gateway: As compared to what it charges over the remainder of its network As compared to other airlines flying into the same airport What is behind this effect?

Background Traditional explanation: airport dominance = market power However, customers (especially frequent fliers) living around a dominated airport can view service by dominant carrier as higher quality : Access to a network of non-stop flights; Reinforced by loyalty programs (FFP); This issue has not been considered in previous research. In the end, it is not clear how much of observed dominance effect is quality based versus market power based.

Idea Separate quality component of airport dominance effect from market power component. Pick airports serving as hub for two carriers: Atlanta (Delta and AirTran) Delta dominates; Denver (United and Frontier) United dominates; Dallas-Ft. Worth (American and Delta) American dominates; Delta dismantled its hub several years ago; Phoenix (America West and Southwest) neither dominates; Chicago O Hare (American and United) neither dominates. These five airports combined handle one in six flights within the US. Use simple difference-in-differences to get the effects we are interested in.

Previous Studies Borenstein (1989) First study of airport dominance effects; Suggested reasons frequent flier programs and then prevalent feature of ticket distribution market. Borenstein (1991) Shows dominant carrier has larger market share of passengers traveling from the respective airport than to the same. Evans, Kessides (1993) Airport dominance is a more important source of market power than route dominance Marin (1995) Analysis of some European markets no dominance effect observed

Previous Studies Berry, Carnal, Spiller (2006) Structural model Airport dominance effect applies to business travelers Lee, Luengo-Prado (2005) Difference in differences Airport dominance premium can be explained by passenger mix Bilotkach (2007) Estimates airport dominance effect for several transatlantic routes Lederman (2008) FFP partnerships help non-dominant carriers get dominance premium Consistent with our story

Destinations Served by Main Carriers Atlanta Denver Dallas Chicago Phoenix DL FL UA F9 AA DL AA UA HP WN July 1999 124 30 86 17 120 58 91 88 53 32 July 2000 134 29 80 20 120 63 96 96 54 37 July 2001 138 32 83 29 118 65 93 103 56 38 July 2002 138 36 80 29 119 60 96 84 55 43 July 2003 137 38 81 30 116 66 82 91 58 41 July 2004 137 42 75 36 126 72 109 116 56 42 July 2005 154 45 75 39 135 6 110 119 56 45

Identification General Dominant airline s price for trips to/from the hub includes: Airline effect; Hub effect (quality based) Dominance effect (market power based) Same price for non-dominant hub operator includes: Airline effect; Hub effect (quality based) Same price for third airlines only includes: Airline effect; To control for airline effects for dominant airline and nondominant hub operator, use fares they charge for flights through the airport.

Identification General With fare or yield as dependent variable, the effects we are looking for are identified as follows: Quality based hub effect difference between HubOperator*Non-Stop interaction and OtherCarrier*Non-Stop interaction Market power based dominance effect difference between DominantAirline*Non-Stop interaction and NonDominantHubOperator*Non-Stop interaction For airports with two hub operators and no dominant carrier; no dominance effect should be observed

Data DB1B the ultimate data source for airline pricing research Collected quarterly by US Department of Transportation 10% sample of tickets issued in the quarter We use DB1B for 1999-2005 Roundtrips only, within lower 48 states, one stop at most in either direction To, From or THROUGH one of the five airports in sample Restricted economy class itineraries only Over 85% of all itineraries ticketed as such Most consistent category across airlines and time Fares less than 2 cents per mile in 2000 prices ($100 LA-NY roundtrip) dropped Only markets where 100 or more passengers are observed in a given year Result over 600,000 observations; 5400 directional airport-pair markets

Dependent Variable Natural logarithm of passenger-weighted mean fare Natural logarithm of passenger-weighted mean yield Fares in year 2000 dollars Weighing at airline-routing level (regional carriers merged with respective major carriers): Directional Also obtained standard deviation: Passenger-weighted mean plus standard deviation fare Passenger-weighted mean plus standard deviation yield

Model and Controls Directional airport-pair market fixed effects Same airport-pair market includes multiple possible routings between the cities Controls dummies and interactions Airline Year Quarter Year-quarter Non-stop flight Controls continuous variables HHI separately for non-stop and one-stop services one stop services irrespective of routing Distance (total roundtrip) Airline s market share (separately for non-stop and one-stop) Geometric average for endpoints population

Instruments Concentration and Market Share are endogenous; need instruments HHI same lagged one year Market share more complicated: Airline s average market share for flights to/from a given airport excluding the current service. In spirit of using other markets characteristics to instrument for endogenous variables. Correlation with market share = 0.51

Results Airport dominance effect is more pronounced in average fares than at the right end of distribution Hub effect is more pronounced for high fares Estimated airport dominance effect is lower in instrumental variables regressions More stable results (and better fit) for yield than price Considerable variation across the airports REVERSE results for Dallas Some specifications report dominance effect for Phoenix where it should not exist

Magnitude Yield as dependent variable, entire sample, IV Average yield: Hub operator s premium over other airlines yields 8.3 percent Dominant hub operator s premium over non-dominant 5.5 percent High yield: Hub operator s premium 18 percent (consistent with higher valuation of quality by presumably less price sensitive customers) Non-dominant hub operators yield is 6 percent above dominant. Shows up only in IV regressions; FE gives 10 percent dominance premium

Implications Most of what is observed as airport dominance premium appears to be premium for access to network, presumably reinforced by frequent flier programs Airport dominance premium has been detected: Applies more to average traveler In contrast to other studies suggesting business travelers are the ones paying dominance premium Most of what business travelers pay is the quality based hub premium.