Competitive responses to low cost carrier entry
Robert Windle *, Martin Dresner
1University of Maryland, Robert H. Smith School of Business, College Park, MD 20742, USA
Received 10 December 1997; received in revised form 28 June 1998; accepted 14 November 1998
Abstract
Recent research has found that the entrance of a low cost carrier leads to lower prices on routes it has entered. This paper extends this analysis by examining the impact of route entry by a discount carrier, ValuJet into an established carrier's hub, Delta, and by examining price changes on routes not entered by the low cost carrier. We found that Delta lowered its fares on competitive routes terminating in Atlanta and on routes ¯owing through its Atlanta hub in response to competition by ValuJet. We did not ®nd evidence that Delta increased fares on non-competitive routes (either those terminating in Atlanta or ¯owing through Atlanta) to compensate for lost revenues on the competitive routes. This ®nal result runs counter to the conjectures of the DOT and supports the argument that ®rms practice rational economic pricing in their hub-and-spoke networks.#1999 Elsevier Science Ltd. All rights reserved.
1. Introduction
In the past year, American consumers have saved an estimated $6.3 billion in airline fares because of the competition brought about by new low cost, low fare airlinesÐup from only $1 billion in savings eight years ago. . .. Indeed, there has been a revolution going on in American airline travel (Pena, 1996).2
Most research has suggested that ``low cost'' or ``discount'' air carriers have been instrumental in substantially lowering prices on domestic air routes in the United States. Writers from Bailey
1366-5545/99/$ - see front matter#1999 Elsevier Science Ltd. All rights reserved. P I I : S 1 3 6 6 - 5 5 4 5 ( 9 8 ) 0 0 0 2 5 - 8
PART E
Transportation Research Part E 35 (1999) 59±75
* Corresponding author. Tel.: +1-301-405-2187; e-mail: rwindle@rhsmith.umd.edu
1 Tel.: +1-301-405-2204; e-mail: mdresner@rhsmith.umd.edu
2 Based on 614.6 million passengers carried by US airlines in 1996, the $6.3 billion savings amounts to $10.25 per
et al. (1985) and Strassmann (1990), with data from the early 1980s, to Windle and Dresner (1995) and Dresner et al. (1996), using data from the 1990s, have consistently found low cost carriers to signi®cantly lower air fares.3As a result, researchers have concluded that the entry of
low cost carriers into markets results in increased consumer welfare.4
There are, however, at least two reasons why consumer welfare bene®ts may be overstated. First, the most recent studies of entry by low cost carriers have been dominated by the impact of Southwest Airlines on fares. Southwest Airlines focuses on short haul routes into underutilized or secondary airports, and as a result often does not directly compete with established carriers. In addition Southwest enters markets with relatively high frequencies compared to other new entrants. As a result Southwest may be atypical of low cost carriers. A second reason is advanced in a study by the US Department of Transportation (1996). The study suggests that in short haul markets where low cost carriers do not compete, established carriers signi®cantlyincreasedprices in the 1994±1995 time period. This raises the possibility that established carriers are balancing price reductions on routes with low cost carrier competition with price increases on routes with-out competition from low cost carriers.5 In a hub and spoke system this alteration of the price
structure may be undertaken to pay for the costs of operating the hub.6This result, however, runs
counter to rational economic theory. Economic theory would suggest that carriers attempt to pro®t maximize on all routes at all times. Therefore, a rational carrier would not seek to raise prices on route A to compensate for lost revenues on route B (due to the entrance of a low cost carrier) since prices would already be at the optimal point on route A.
This paper addresses the con¯ict between rational economic theory and the ®ndings suggested by the DOT, and also investigates the impact of low cost competition, other than Southwest, on prices into an established carrier's hub airport. The purpose of the paper is to provide at least some preliminary evidence as to whether or not the consumer welfare bene®ts of low cost carriers have been overstated in previous research. Speci®cally, the questions addressed in this paper are: (1) Do established carriers signi®cantly lower their prices when faced with competition into their hub airports by a low cost carrier, other than Southwest? and (2) Have established carriers been able to increase prices on routes where the discount carriers do not compete, thereby reducing welfare gains? Measurement of consumer bene®ts from the entry of low cost carriers is important, since it is these perceived bene®ts that help guide policy on the facilitation of access by carriers into crowded airports.7We continue this discussion in Section 3 of the paper.
3 For example, Windle and Dresner (1995) found that the entry of low cost carrier Southwest Airlines onto a route
lowered fares by an average of 48%. Other studies that found low cost carriers substantially lowered fares include Bennett and Craun (1993), Whinston and Collins (1993), and Morrison and Winston (1995).
4 For example, a recent study conducted by the US Department of Transportation (1996) compared fares in markets
served by low cost carriers to fares in markets without service by low cost carriers. The study found that fare dier-ences between the two market categories, combined with the very large number of passengers that now travel in mar-kets with low cost service, mean that consumer savings are very large (p. 9).
5 An alternate explanation was that prices rose after the demise of Continental Airline's low cost unit, CaLite. 6 For example, US Airways president, Rakesh Gangwal, stated that the airlines's hub at Batimore lost $220 million
dollars between 1990 and 1997. The airline was in the process of reducing ¯ights into its Baltimore hub and reducing its Baltimore work force in order to make the hub pro®table (see Phillips, 1997).
7 For example, established carriers could be ordered to sell slots or gate space to low cost carriers in order to spur
The rest of the paper is structured as follows: Section 2 reviews research on airline entry and outlines the basis for this research. Section 3 presents the model and describes the data used for this paper. Section 4 presents our results. Finally, Section 5 draws conclusions from the research.
2. Literature review8
There has been considerable research on the determinants of prices and/or trac on US domestic air routes, including how the presence of low cost carriers or new entrants aects prices and trac.9 Three early studies used data from the ®rst few years following the deregulation of
the US air system. Bailey et al. (1985), using 1980±1981 data, and Strassmann (1990), using 1980 data, both found that newly certi®ed carriers had a negative and signi®cant impact on US domestic yields. Using data from the period 1980±1984, Whinston and Collins (1992) showed that prices fell, on average, by 34% on 15 routes entered by the pioneer low cost carrier People Express. Additional studies were conducted using data from the most successful low cost carrier, Southwest Airlines, and from the surge of new low cost entrants in the 1990s. Bennett and Craun (1993) presented graphs illustrating that when Southwest entered certain California markets, there was a dramatic increase in trac and a signi®cant drop in yields. Windle and Dresner (1995) found that the entry of Southwest Airlines onto a route decreased fares, on average, by 48% and resulted in increases in passengers of 200%. Morrison and Winston (1995) found that when a low cost carrier (either Southwest or America West) exited from a route, fares increased. The average magnitude of the fare increase was 8.5% when Southwest exited and 3.1% when America West exited, measured 5 years after the exit.
Three recent papers explicitly addressed competitive eects arising from new entry. Dresner et al. (1996) examined competitive eects from the entry of Southwest Airlines onto two routes, to Cleveland and Chicago, from Baltimore±Washington International Airport (BWI). The authors found that not only did prices decrease signi®cantly on the routes Southwest entered, but they also fell on competitive routes to Cleveland and Chicago from the other two Washington/Balti-more area airports, and on routes to other destinations from BWI.10 Richards (1996) found that
pricing strategies diered between carriers operating on those routes which Southwest competed, on those routes on which Southwest was a potential entrant (operated at one of the endpoints), and on the routes in which Southwest was not deemed to be a potential entrant. Richards con-cluded that actual or potential entry by Southwest had a negative impact on yields. Finally, the US Department of Transportation (1996), as part of a larger analysis of low cost carriers, exam-ined the competitive responses of established carrier Delta Airlines to the entry of low cost car-riers on routes from two of Delta's hubs, Atlanta and Salt Lake City. The study found that on the Salt Lake City routes, Delta lowered fares to compete with low cost carriers and increased its passenger totals as a result. Delta's fares, for example, fell 33% on the routes where it competed
8 This section draws material from Dresner et al. (1996).
9 Papers in this ®eld not explicitly dealing with the price or trac eects of low cost carriers include: Moore (1986);
Borenstein (1989); Hurdle et al. (1989); Morrison and Winston (1989); Berry (1990); US General Accounting oce (1991); and Peteraf and Reed (1994).
10 Prices to other cities from BWI may have declined due to limit pricing by existing carriers on those routes. It may
with low cost competitor Morris Air, but did not either rise or fall, on average, on routes where Morris did not compete. On the other hand, the study found that Delta's fares and passenger count changed only modestly on the Atlanta routes after the entry of low cost carrier ValuJet. The study's authors attributed this more moderate response by Delta, in part, to the lower market shares achieved by ValuJet on the Atlanta routes, as compared to those achieved by Morris on the Salt Lake City routes. ValuJet, therefore, did not pose the same degree of competitive threat to Delta in Atlanta as Morris posed in Salt Lake City.11
In summary, the substantial literature on new entry points strongly to the impact that low cost carriers have on prices and trac on the routes that they enter. In recent years, the results of these studies have been dominated by the entry and growth of Southwest Airlines. The DOT study suggests that low cost entry may not always result in lower fares, particularly when entry occurs at an established carrier's hub. Evidence on the eects of entry by low cost carriers on routes other than those entered is not as substantial or as clear. There is some evidence indicating that new entry by low cost carriers lowers prices on competing routes out of nearby airports and on other routes from the same airport. Other evidence suggests that established carriers response to entry depends on how signi®cant a threat is posed by the new entrant. This paper will attempt to clarify these issues by examining the entry of ValuJet into the Atlanta market and its impact on Delta's fares on routes where ValuJet competes directly and on other Delta routes utilizing the Atlanta hub.
3. Model and data
The research to date, with three exceptions cited above, has focused on the eects of the pre-sence of low cost carriers on the routes entered by the low cost carriers. None of the previous research has focused on the potentialnetworkeects from low cost carrier entry. The established carriers do not only operate point-to-point routes, but operate networks, often referred to as hub-and-spoke systems. It could be that the positive consumer bene®ts experienced on the routes entered by the low cost carriers may be partially oset by price increases on other routes in the established carrier's network. If the established carriers increase prices on ``non-competitive'' routes in their system, this would provide evidence to support the DOT's (1996) ®ndings of price increases on these type of routes.
As an example, refer to Fig. 1. An established carrier operates a hub-and-spoke network con-necting four cities, A, B, C, and D, through the hub city H. Possible origin and destination routes are as follows: A±B, A±C, A±D, B±C, B±D, C±D, A±H, B±H, C±H, and D±H.12Carriers operate
11 A second partial explanation for these results could have been that the authors had a shorter time series of data to
assess the competitive eects in Atlanta, compared to Salt Lake City. Morris started operations in Salt Lake City in the second quarter of 1993, while ValuJet began operations in Atlanta in the ®rst quarter of 1994. The authors were able to examine the eects of new entry in Salt Lake City for 10 quarters and in Atlanta for only seven quarters.
12 The term ``route'' refers to an origin±destination route; that is the entire journey of a passenger from an origin to a
on route segments, but passengers ¯y on origin±destination (O±D) routes, although the two can coincide. Airlines charge prices on O±D routes, not on route segments, and as a result the reac-tion of an incumbent will consist of changes in O±D prices. Assume that a low cost carrier oper-ates on two route segments into the hub city, A±H and C±H. In order to compete with the low cost carrier on these O-D routes, the established carrier must lower its prices. To the extent that O±D passengers comprise a small portion of the passengers on this route segment (¯ow through passengers ¯ying on to other cities may dominate), the established carrier may or may not react to the low cost competition. The established carrier also competes on the ¯ow-through O±D route, A±C, and may have to lower prices on this route, as well. In order to justify the operation of the hub, H, the network through H must return revenues sucient to cover the hub's costs. As a result of this loss in revenue, the established carrier may seek to raise prices on the other O±D routes not aected by the low cost entry. These routes include the ¯ow-through O±D routes A±B, A±D, and B±C (the low cost carrier operates on only one of the two route segments); the ¯ow through O±D route B±D (the low cost carrier operates on neither of the route segments); and the O±D routes B±H and D±H on which the low cost carrier does not compete.
Our primary focus in this paper will be to examine the impact of low cost entry on the O±D routes where entry occurs and on other routes where O±D entry has not occurred. As illustrated in Fig. 1, the O±D routes of an established carrier operating a hub-and-spoke network in com-petition with a low cost carrier on some, but not all, route segments may be divided into ®ve classi®cations: (1) routes into the hub in competition with the low cost carrier; (2) routes into the hub without low cost carrier competition; (3) routes that ¯ow through the hub in competition with the low cost carrier on both route segments; (4) routes that ¯ow through the hub with the low cost carrier operating on only one of the route segments; and, (5) routes that ¯ow through the hub in which the low cost carrier operates on neither of the route segments. In order to estimate the eects of low cost carrier entry on all ®ve route classi®cations, we propose the following general model:
Yieldf Route Classification;Other Exogenous Route Factors;Endogenous Route Factors 1
where Yield is the weighted average price on a route charged by the established carrier,13Route
Classi®cation refers to the ®ve types of routes described above, Other Exogenous Route Factors refer to route characteristics likely to aect yields, such as the distance of the route, and Endo-genous Route Factors refer to factors likely to aect the established carrier's yields, such as the number of passengers on a route, directly controllable by the established carrier.
In order to estimate our model, we needed to choose a route network that had competition between an established carrier and a low cost entrant. Given the data requirements, it was deci-ded to analyze only one competitive network. In a number of hub cities, a low cost carrier and a major carrier operate at dierent airports (e.g. Midway and O'Hare in Chicago), a situation we felt could confound our analysis.14 We, therefore, chose to analyze the eects of low cost carrier
competition for a network where two carriers both hubbed at the same airport. We also did not want to choose a competitive network where the low cost carrier was Southwest Airlines. Pre-vious research (Windle and Dresner, 1995) found that Southwest may not be typical of discount carriers, given that it tends to enter markets with greater densities and lower prices than other low cost carriers.
The hub city chosen for the analysis was Atlanta, where established carrier Delta's network has been competing with low cost carrier ValuJet's network since 1993, with the exception of a brief period in 1996 when the operations of ValuJet were suspended by US regulatory authorities for safety concerns.15Data were gathered on all routes ¯owing through Atlanta and terminating in
Atlanta where Delta averaged at least one passenger per day in the second quarter of 1996. All data were based on US Department of Transportation Database 1a ®gures, processed for us by Data-base Products Inc. In total, data were gathered on 458 ¯ow-through routes and 119 routes termi-nating in Atlanta on a quarterly basis from the fourth quarter of 1993 to the third quarter of 1996. Table 1 indicates the cities served by ValuJet on routes from Atlanta for the period of our analysis. For example, ValuJet operated on the Philadelphia±Atlanta route from the second quarter of 1994 until the second quarter of 1996 and on the Boston±Atlanta route from the sec-ond quarter of 1995 until the secsec-ond quarter of 1996. Note that ValuJet ceased operations during the third quarter of 1996 due to US government actions based on safety concerns following a fatal accident on 11 May 1996.16
The Atlanta hub was chosen for analysis despite the ®ndings (cited above) of the US Depart-ment of Transportation (1996) that Delta did not greatly alter its fares in response to competition from ValuJet on routes in which it directly competed with ValuJet. The Department of Trans-portation's ®ndings were based on an analysis of data as of the third quarter of 1995. We found a marked decline in Delta's prices on routes competitive with ValuJet, but only beginning in the
13 The weights used were number of passengers traveling at each price point.
14 For example, if Southwest entered a route between Midway in Chicago and Cleveland, this route might not be
considered to be directly competitive to United's route between Chicago O'Hare and Cleveland.
15 ValuJet was renamed AirTran on 24 September 1997, after a merger with Orlando Based AirTran Airways. 16 ValuJet was forced to shut down all operations on 18 June 1996. It did not resume operations until 30 September
fourth quarter of 1995, as shown in Fig. 2. Fig. 2 examines Delta's yields for ®ve categories of routes for the period of our analysis, the fourth quarter of 1993 to the third quarter of 1996. The route categories are based on whether or not ValuJet directly competed on a route with Delta as of the second quarter of 1996.17 The ®rst two categories of routes in Fig. 2 are routes that
ter-minate in Atlanta. Note that from the fourth quarter of 1993 until the ®rst quarter of 1996, Delta's yields on routes that (as of the second quarter of 1996) faced competition from ValuJet were higher than on those routes that ValuJet chose not to enter. After the ®rst quarter of 1996, Table 1
Cities served by ValuJet: 1993 4th quarter to 1996 3rd quarter
City Quarters served
93.4 94.1 94.2 94.3 94.4 95.1 95.2 95.3 95.4 96.1 96.2 96.3
Ft. Lauderdale xa x x x x x x x x x x &b
a x, ValuJet on route in 4th quarter of 1993 or enters route in subsequent quarter. b &, ValuJet no longer on route.
17 Direct competition is de®ned as operating on the same route as Delta and, for the ¯ow through routes, having at
Delta's yields on the ``competitive'' routes were lower than on the ``non-competitive'' routes.18 A
good way to interpret the graph is to simply compare the competitive and non-competitive yields for two time periods, say the fourth quarter of 1993 and the second quarter of 1996. In the fourth quarter of 1993, Delta had average yields of about 37 cents/mile on routes that ValuJet would ulti-mately enter compared to 29 cents/mile on routes that ValuJet never entered. By the second quarter of 1996, Delta's yields on the routes now directly competitive with ValuJet had fallen from 37 to 30 cents/mile while yields on the non-competitive routes had increased from 29 to 31 cents/mile.
Delta's yields on three categories of ¯ow-through routes are also shown in Fig. 2 over the period of our analysis. A route is de®ned as ``competitive'' based on whether or not ValuJet was competing with Delta as of the second quarter of 1996 with at least a 4.5% market share on the ¯ow-through route. The graph shows that for the competitive routes, Delta had higher yields than for the non-competitive routes and the routes competitive on only one of two route seg-ments, for almost the entire period of the data set. The yield dierential, however, was almost completely gone by the second quarter of 1996, providing some indication to support our hypothesis that Delta had to lower fares on one-stop routes to compete with ValuJet. The graph, however, does not indicate that Delta raised rates on the non-competitive routes to compensate for the decrease in yields on the competitive routes.
Fig. 2. Delta's yields.
18 Note that the downward trend in Delta's yields on the ``competitive'' routes continued into the third quarter of
Figs. 3 and 4, respectively, compare the trends in Delta's yields on routes terminating in Atlanta, and ¯owing through Atlanta, to national trends.19All yields are indexed to 1.00 for the
fourth quarter of 1993. Fig. 3 clearly shows the decline in Delta's yields towards the latter quar-ters of our analysis on routes competitive with ValuJet. This decline runs counter to both national trends and the trend on routes not competitive with ValuJet. Fig. 3, however, does not show any upward trend in yields on the non-competitive routes. Fig. 4 provides similar results for the ¯ow-through routes. The ®gure shows a signi®cant decline in Delta's yields following the ®rst quarter of 1996 on routes competitive with ValuJet compared to the national trend and to Delta's yields on non-competitive routes. However, again, there does not appear to be an increase in yields on the non-competitive routes to compensate for lost revenues on the competitive routes.
In order to more formally investigate the eect of competition from ValuJet on Delta's yields, an econometric model was estimated to account for route speci®c factors that could in¯uence yields. The following two equations were proposed for each of the ®ve route categories:
Yield01Passengers2RouteDistance3RouteDistanceSquared
4VacationRoute5SlotControlledRouteX
T
t1
tQuartert 2
Fig. 3. Index of Delta's yields on Atlanta routes compared to national trends.
19 National trends were compiled from ``Form 41'' data submitted to the US Department of Transportation, Bureau
Passengers01RouteDistance2RouteDistanceSquared3VacationRoute
4Population
XT
t1
ltQuartert 3
where:
. Yield is Delta's yield on a bi-directional route either terminating or ¯owing through Atlanta. . Passengers is the number of passengers carried by Delta on that route and is endogenous to
the estimation of Yield; thus the need for Eq. (3).
. RouteDistance and RouteDistanceSquared are control variables to account for route cost dierences that vary by route distance aecting both yields and passenger trac.20
. VacationRoute and SlotControlledRoute are control variables to account for exogenous factors that might aect yields.21Vacation routes have been de®ned as all those routes with
an origin or terminus in Florida, Las Vegas, or Myrtle Beach. It may be that these routes have a mix of personal to business travelers dierent from other Delta routes, and that this dierence may result in lower yields. Slot controlled routes are those originating or terminating
Fig. 4. Index of Delta's yields on Atlanta ¯ow-through routes compared to national trends.
20 Route distances were derived using the ``Great Circle Distance Calculator'' found on the Internet at
www.atlantic-aero.com/aacalc.html.
21 VacationRoute is also a variable in the Passengers equation since, ceteris paribus, vacation routes would attract
at an airport with slot controls.22 It may be that slot controlled airports have higher yields,
after accounting for all other factors.
. Population is the product of the populations of the two endpoint cities on a route.23 The greater the population at the endpoints, the higher the passenger trac.
. Quartert's are time dummies that allow us to track yield and passenger trends within
cate-gories, after accounting for the eects of the other right-hand-side variables.
Given that our primary interest is in the signs of the time dummies (used to determine yield changes in the ®ve route categories), and given that Passengers is an endogenous variable to the estimation of Yield, it was thought best to estimate a reduced form equation. Therefore, the fol-lowing equation was estimated:24
Yield01RouteDistance2RouteDistanceSquared3Population
4VacationRoute5SlotControlledRouteX
T
t1
tQuartert 4
Table 2 presents descriptive statistics on key variables used in the analysis by category of route. The number of observations refers to the number of cases for each category over the 12 quarters of observation. Delta's passengers are the carrier's average passenger total per route for a quar-ter. For example, Delta averaged 4895 passengers per quarter, or about 54 passengers per day, on competitive routes terminating in Atlanta. This total compared to the 2337 passengers per quar-ter, or 26 passengers per day, that ValuJet averaged on the same routes. Route passengers refer to the total passengers on the route, including Delta's and ValuJet's passengers. Note that both Delta's yields and route yields (the average for all carriers) were signi®cantly higher on routes terminating in Atlanta than on ¯ow-through routes. ValuJet's yields were signi®cantly lower than Delta's yields on routes where the two carriers competed. On the ®ve categories of routes, Delta's average market share varied between 40 and 54%. Finally, ValuJet's average market share was 28% on routes terminating in Atlanta and 17% on the ¯ow-through routes, an indication that ValuJet was competing with Delta on both categories of routes.
22 The only slot controlled airport in our sample is New York±La Guardia. 23 Data were derived from US Census Bureau (1995).
24 The variables in (4) are identical to those in (2) except for the inclusion of the exogenous variable, Population,
4. Results
Separate estimations were conducted for each of the ®ve categories of routes, identi®ed above.25 The results for the estimation of Delta's yields for routes terminating in Atlanta, both
competitive and non-competitive, are presented in Table 3. All continuous variables were logged so that the coecients could be interpreted as elasticities. As shown in Table 3, the signs of the coecients for the estimation of Delta's yields on routes competitive with ValuJet appear to be as expected. Distance has a negative coecient and Distance-Squared a positive coecient, indi-cating that yields decrease (but at a decreasing rate) as the length of routes increase. The coe-cient for Population is positive, but insigni®cant, indicating that the populations of the endpoints of the route do not eect yields. The coecient for Vacation Route is negative meaning that vacation routes have lower fares than non-vacation routes. Finally, the coecient for Slot-Con-trolled routes is positive implying that routes with restricted slots at one of the endpoints have higher fares than those without these restrictions.
The Distance and Distance-Squared coecients from the non-competitive estimation, are the same signs as those in the competitive regression, although the Distance-Squared coecient is not signi®cant. The Population coecient is negative, and signi®cant, indicating that routes with high populations at the endpoints have lower fares. This result may be due to economies of density; that is high populations can support more frequent service, leading to economies of density and lower yields. The Vacation Route coecient is negative, and signi®cant, while the Slot Controlled coecient is negative (i.e. the wrong sign) but not signi®cant.
The major variables of interest, at least for the purpose of this study, are the time series dum-mies. The dummies for the fourth quarter of 1993 in both estimations, the ®rst period in which we Table 2
Number of observations 201 1224 447 2813 2236
Delta's passengers 4895 1821 529 624 352
ValuJet's passengers 2337 0 203 0 0
Route passengers 9465 2986 1669 2510 1281
Delta's yields ($/mile) 0.327 0.314 0.220 0.206 0.203
ValuJet's yields ($/mile) 0.162 N/A 0.150 N/A N/A
Route yields ($/mile) 0.260 0.293 0.192 0.192 0.192
Delta's market share (%) 54 68 41 40 50
ValuJet's market share (%) 28 0 17 0 0
25 Yields used in the estimation include the federal 10% ticket tax during those periods that this tax was in force and
have observations, have been omitted from the regressions, so all other periods can be compared to this base. As illustrated in Table 3, Delta's yields on competitive routes fell signi®cantly below the base period yields for all four quarters of 1994, and then, again, from the fourth quarter of 1995 to the third quarter of 1996. These results are in contrast to those from the estimation of the non-competitive routes terminating in Atlanta, as also indicated in Table 3. In the ®rst quarter of 1994, Delta's yields on non-competitive routes rose signi®cantly above the base period, and were signi®cantly above the base for three quarters in 1995. Yields were only signi®cantly below base prices in one quarter of the study; that is during the second quarter of 1996.
Fig. 5 tracks the trends in Delta's yields for the competitive and non-competitive routes and compares those trends to a national index. As opposed to the results from Fig. 3, Fig. 5 shows trends in yields after controlling for other in¯uences (e.g. population changes and route speci®c factors for which variables were entered into the estimations of yields). As illustrated in the ®gure, yields on both the competitive and non-competitive routes roughly tracked the national trend through to the third quarter of 1995. After that period, yields on the competitive routes fell about 25%, while yields on the non-competitive routes continued to, at least roughly, track the national trends. The conclusions from the Atlanta estimation results is that Delta's yields appeared to have fallen on the routes in which it competed with ValuJet, even after holding other variables constant, but do not appear to have risen, relative to national trends, on the non-competitive routes.
Table 3
Estimation results on Delta's yields for routes terminating in Atlanta
Variable Competitive routes Non-competitive routes
Coecient estimate T-statistic Coecient estimate T-statistic
Constant 16.451 7.28a 4.430 13.54a
Distance ÿ4.894 ÿ6.59a
ÿ0.882 ÿ8.78a
Distance-squared 0.332 5.42a 0.005 0.66
Population 0.000 0.32 ÿ0.001 ÿ1.80c
Vacation route ÿ0.202 ÿ8.01a
ÿ0.058 ÿ2.13b
Table 4 presents the results of our estimation of Delta's yields for the three categories of ¯ow-through routes. The estimated coecients for the control variables, for the most part, mirrored the results derived in the previous regressions. The coecients for the Distance variable were negative and signi®cant in two of the three estimations, and the coecients for Distance-Squared were positive and signi®cant in two of the estimations, as well. The coecients for Population were negative in all three models, and signi®cant in two of them. The coecients for Vacation were negative and signi®cant in all three of the estimations. Finally, Slot-Controlled route coecients were positive and signi®cant in the two regressions for which the variable was applicable.
In comparing the time dummies, it appears, again, that the competitive routes tend to have more negative and signi®cant coecients (as compared to the base period, 1993, fourth quarter) than do the other route categories. This pattern is evident in Fig. 6. All three route categories tracked, roughly, national trends through to the fourth quarter of 1995 at which time Delta's yields for all three categories fell below national yields. However, among the three categories of routes, it is evident that Delta's yields on the competitive routes fell to about 75% of base yields, while Delta's yields in the one-segment competitive and non-competitive categories fell to only 85 to 90% of the base. Therefore, again while there was evidence that yields on ¯ow-through com-petitive routes fell signi®cantly compared to national trends, there is no counter evidence that Delta raised prices on non-competitive routes to counter this decline in revenues.
Table 4
Estimation results on Delta's yields for routes ¯owing through Atlanta
Variable Competitive±both segments CompetitiveÐone segment only Non-competitive Coecient estimate T-statistic Coecient estimate T-statistic Coecient estimate T-statistic
Constant 6.755 2.01b 14.847 23.99a 11.728 10.74a
Distance ÿ1.348 ÿ1.32 ÿ3.932 ÿ21.66a ÿ2.816 ÿ9.23a
Distance-2 0.020 0.26 0.229 17.44a 0.152 7.04a
Population ÿ0.000 ÿ0.37 ÿ0.001 ÿ2.61a
ÿ0.005 ÿ11.20a
Vacation Rte ÿ0.157 ÿ10.00a
ÿ0.237 ÿ31.31a ÿ0.182 ÿ14.30a
Slot-control N/A N/A 0.019 1.68c 0.069 4.56a
1994-1 ÿ0.012 ÿ0.38 0.056 3.21a 0.090 3.34a
1994-2 ÿ0.092 ÿ2.88a
ÿ0.056 ÿ3.18a ÿ0.040 ÿ1.47
1994-3 ÿ0.133 ÿ4.17a
ÿ0.083 ÿ4.72a ÿ0.074 ÿ2.75a
1994-4 ÿ0.052 ÿ1.61 ÿ0.075 ÿ4.28a
ÿ0.089 ÿ3.31a
1995-1 0.065 2.04b 0.063 3.58a 0.026 0.96
1995-2 0.093 2.92a 0.056 3.17a
ÿ0.012 ÿ0.46
1995-3 0.081 2.52b 0.051 2.87a
ÿ0.022 ÿ0.81
1995-4 ÿ0.049 ÿ1.52 ÿ0.016 ÿ0.88 ÿ0.036 ÿ1.34
1996-1 ÿ0.132 ÿ4.11a ÿ0.082 ÿ4.69a ÿ0.048 ÿ1.77c
1996-2 ÿ0.256 ÿ8.00a ÿ0.141 ÿ8.00a ÿ0.124 ÿ4.62a
1996-3 ÿ0.302 ÿ9.44a ÿ0.153 ÿ8.70a ÿ0.111 ÿ4.16a
R-squared 0.78 0.78 0.83
Observations 792 3516 1188
a Signi®cant at the 99% con®dence level. b Signi®cant at the 95% con®dence level. c Signi®cant at the 90% con®dence level.
5. Conclusions
Recent research has found that the entrance of low cost carrier, Southwest Airlines, leads to lower prices on routes it has entered. This paper extends this analysis by examining the impact of entry on routes by another discount carrier, ValuJet, into an established carrier's hub and by examining price changes on routes not entered by the low cost carrier. In order to address this question, we examined the impact of competition by the low-cost carrier ValuJet on yields by the established carrier, Delta, at Delta's hub in Atlanta. We found that Delta lowered its fares on competitive routes terminating in Atlanta in response to competition by ValuJet. In addition, we found that Delta lowered its fares on routes ¯owing through its Atlanta hub to compete with ValuJet. Finally, we did not ®nd evidence that Delta increased fares on non-competitive routes (either those terminating in Atlanta or ¯owing through Atlanta) to compensate for lost revenues on the competitive routes. This ®nal result runs counter to the conjectures of the DOT and sup-ports the argument that ®rms practice rational economic pricing in their hub-and-spoke net-works. Since the carriers are likely already maximizing pro®ts on a route by route basis, they are unable to oset declines in revenue from increased competition on one route by raising prices on another route.
The policy implication from this research is that governments should encourage the entry of low-cost carriers in order to increase consumer welfare. We found no evidence that an established carrier responds to low cost competition by increasing prices on routes without low cost carrier competition. Lower fares were realized both on routes that terminated at a competitive hub as well as on competitive routes that ¯owed through the hub.
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