Incumbent Response to Entry by Low-Cost Carriers in the U.S. Airline Industry

30  Download (0)

Full text

(1)

Incumbent Response to Entry by

Low-Cost Carriers in the U.S. Airline Industry

Kerry M. Tan

June 2011

Abstract

This paper studies the price response of incumbents to entry by low-cost carriers in the U.S. airline industry. Previous theoretical papers suggest that entry leads to two opposing effects on incumbent price. Airlines might respond to competition by lowering prices to compete harder for existing customers or they might increase prices to exploit their brand-loyal customers. This paper tests which effect is more prominent in the airline industry. Based on a sample of four low-cost carrier entrants, I find that legacy carrier incumbents respond differently than low-cost carrier incumbents to new low-cost carrier entry. Legacy carriers decrease their mean airfare, 10th percentile airfare, and 90th percentile airfare before and after entry by a low-cost carrier. However, low-cost carriers do not significantly alter their pricing strategy. The differing incumbent responses can be attributed to the finding that low-cost carrier entrants tend to match the price set by rival low-cost carriers in the quarter of entry and tend to enter with a lower price than that of legacy carrier incumbents. This paper also extends the findings of previous studies on the effect of competition and price dispersion. Namely, entry does not affect the dispersion in short-run prices set by incumbent carriers, which contrasts with the key long-run result in Gerardi and Shapiro (2009) and Borenstein and Rose (1994).

I would like to thank Matt Lewis for his guidance and helpful advice. I would also like to thank Jim Peck, Huanxing Yang, Nancy Rose,

Adam Shapiro, David Mills, Bill Dupor, Michael Sinkey, and participants of the Rising Stars: Airlines session at the 2011 International Industrial Organization Conference for their suggestions and comments.

(2)

1

Introduction

When a firm enters a market consisting of a brand-loyal segment and a price-sensitive seg-ment, there are two effects on the incumbents’ pricing strategy: the competitive effect and the displacement effect. Once the entrant enters, the incumbent would continue to decrease prices in order to keep customers because the incumbent firm’s individual demand curve decreases and becomes more elastic due to an increase in the number of substitutes. Klemperer (1987) and Perloff and Salop (1985) refer to this as the competitive effect. On the other hand, Rosenthal (1980) and Hollander (1987) provide the theoretical foundation for the displacement effect, in which entry can actually cause incumbents to increase their prices due to the existence of the two market segments. If entrants are known to cater toward price-sensitive consumers, then incumbents may be best served by increasing prices. In effect, these incumbents will focus their attention on their brand-loyal consumers, who will continue purchasing from them even if an entrant offers lower prices. This strategy will maximize profits whenever the increase in price dominates the effect of the quantity decrease. Since both effects can occur simultaneously, the net effect on prices depends on which effect is more prominent.

The growth of several low-cost carriers over the past decade allows for the ability to study whether the competitive effect or the displacement effect is more important in the airline indus-try. This paper focuses on two types of airlines:1 legacy carriers and low-cost carriers. Legacy carriers are airlines that operate a hub-and-spoke network2 and were founded prior to the

in-dustry’s deregulation in 1978, while low-cost carriers implement a point-to-point network3and

emerged after deregulation. The purpose of this paper is to study the price response of both legacy carrier and low-cost carrier incumbents when a low-cost carrier enters a new route.

The key result of the paper is that legacy carrier incumbents react differently than low-cost carrier incumbents to entry by low-cost carriers. First, legacy carrier incumbents significantly decrease average one-way airfares the quarter before and the quarter after actual entry by a low-cost carrier. Moreover, low-low-cost carrier incumbents do not seem to significantly respond to entry by a rival low-cost carrier. Second, I study how the incumbents’ distribution of prices changes due to entry by a low-cost carrier. The 10th percentile prices decrease by about the same amount as the 90th percentile prices so that no significant change occurs to the overall price distribution of the airfares. As such, there is no statistically significant change to price dispersion. Prices

1I use the terms “airlines" and “carriers" interchangeably throughout the paper.

2A hub-and-spoke network concentrates passengers from several satellite airports (spokes) at a major airport

(hub) en route to their final destination airport.

(3)

decrease all along the distribution of prices almost equally so that price dispersion does not change. Finally, low-cost carrier entrants are likely to enter with an average price that is around the average price of low-cost carrier incumbents and less than that of legacy carrier incumbents. Hence, one reason why low-cost carrier incumbents do not significantly respond to entry by a rival low-cost carrier is because the entrant tends to match the price of the low-cost carrier incumbent. Meanwhile, there is downward pressure on legacy carrier incumbents’ prices since the entrant sets a price that is likely to be lower than their price. Although both the story based on the competitive effect and the displacement effect seem to be plausible in the airline industry, the results support the claim that the competitive effect dominates the displacement effect.

Three papers closely relate to this present work. Goolsbee and Syverson (2009) examine the effect of potential competition by Southwest Airlines on rivals’ pricing strategies. They find that carriers decrease their prices when they face potential competition with Southwest Airlines, suggesting that incumbents decrease their prices when entry is merely threatened. They estimate a two-way fixed effects model, incorporating time dummies to estimate the effects of potential competition on prices. In effect, they conduct an event study by examining the incumbents’ prices before, during, and after Southwest Airlines enters both airports of a route. I expand upon their work by modifying their estimation strategy so that I can examine the effect of actual competition4when entry actually occurs by not only Southwest Airlines but also other low-cost

carriers.

Gerardi and Shapiro (2009) investigate how an airline’s ability to price discriminate on a given route is affected by competition. They find that price dispersion decreases with competition, in stark contrast to Borenstein and Rose (1994). Both my paper and these previous papers studies how a firm responds to competition. However, the previous literature is interested in estimating the effect of competition on price dispersion in the airline industry as a whole, whereas this paper examines how price dispersion changes upon entry by a low-cost carrier. Naturally, endogeneity problems arise with these types of studies. I try to minimize the endogeneity problem by looking at entry as opposed to a smooth measure of competition, such as the route-level

Herfindahl-4It is important to note the differences between the different types of competition in the airline industry. Suppose

that Southwest Airlines operates at the San Diego International Airport (SAN) and the San Francisco International Airport (SFO). Suppose further that Southwest Airlines services the SAN-SFO route. Actual competition exists when two airlines service the same route at the same time. United Airlines is said toactually competewith Southwest Airlines if United also services the SAN-SFO route at the same time as Southwest Airlines. Now suppose that Southwest Airlines also operates at the Los Angeles International Airport (LAX), but does not service the SAN-LAX route. Potential competition exists when a firm operates at two airports but does not service the route linking both airports that is served by another airline. United Airlinespotentially competeswith Southwest Airlines if United services the SAN-LAX route at the same time that Southwest Airlines operates at both airports but does not service the SAN-LAX route.

(4)

Hirschman Index. Moreover, the previous literature assumes that the effect of competition is the same for all airlines, while I allow the effect of entry on price dispersion to vary across different airlines. I am interested in how the incumbents respond to entry by each low-cost carrier.

One of the key results of this paper is that an increase in competition does not lead to a sig-nificant change in the incumbent’s price dispersion, which differs from the findings from both Gerardi and Shapiro (2009) and Borenstein and Rose (1994). This can be attributed to the differing identification strategy in this paper from the two previous studies, which regress measures for price dispersion on several control variables, including various proxies for competition. Their key findings stem from the sign and strength of the estimated coefficient for the competition variables. In effect, they are estimating the long-run effect of competition on rival’s price distri-bution. The major difference in the analysis of this study to the previous literature is that this paper uses entry as opposed to the route-level Herfindahl-Hirschman Index to identify competi-tor’s response to competition. I analyze the pricing behavior right around entry by performing an event study that captures the short-run effect of competition on price dispersion. By inves-tigating how the Gini coefficient and the tails of the price distribution change around the entry period, this paper is able to shed new light on the effect of competition on the price distribution of rival firms.

The paper is structured in the following manner. Section 2 presents background information on the airline industry and the potential entry effects of low-cost carriers. Section 3 describes the data used for this study. Section 4 provides the empirical analysis. I explain the empirical strategy used to estimate the entry effects and discuss the results. Concluding remarks are made in section 5.

2

Industry Background and Potential Effect of Entry

The competitive structure of the U.S. airline industry has gone through several changes since deregulation in 1978. Airlines have since experienced more flexibility in their route network and pricing strategies. It is easier to enter routes that were once heavily regulated by the Civil Aeronautics Board. As a result, there has been an influx of entry in the past two decades by low-cost carriers. These airlines include AirTran Airways, JetBlue Airways, Southwest Airlines, and Spirit Airlines. Low-cost carriers are able to charge low prices due to their efficient cost structure, benefitting from the implementation of a point-to-point network, usage of non-unionized labor, and operation of the same type of aircraft.5 This is in stark contrast to legacy carriers, which

(5)

were founded and operated prior to deregulation. They implement a hub-and-spoke network, use mostly unionized labor, and operate with a variety of different aircrafts. The major legacy carriers include American Airlines, Continental Airlines, Delta Air Lines, Northwest Airlines, United Airlines, and US Airways. Legacy carriers get their name because they were founded and operated prior to deregulation.

Low-cost carriers have gained market share in the airline industry, particularly in the past decade. In 1997, low-cost carriers flew over 37 million passengers total and accounted for 21.4% of the market share of all passengers flying domestically. In 2007, the number of passengers flying with low-cost carriers increased to over 75 million passengers, resulting in a 36.2% market share of all domestic travel. This growth can be partly attributed to the expansion of the low-cost carriers’ route network. Among the top 1000 most traveled routes, there were 494 instances of entry from 1993:Q1 to 2007:Q4 by low-cost carriers, with AirTran Airways entering 224 routes, JetBlue Airways entering 68 routes, Southwest Airlines entering 150 routes, and Spirit Airlines entering 52 routes. Each route consists of a particular one-way airport-pair. For example, two routes were considered to be entered when Southwest Airlines started flying from Orlando In-ternational Airport to Philadelphia InIn-ternational Airport and vice versa in 2004:Q2. This paper examines four currently operating low-cost carriers (AirTran Airways, JetBlue Airways, South-west Airlines, and Spirit Airlines), who have grown substantially over the past two decades and who remain significant players in the airline industry today. I only examine the entry effects of low-cost carriers; I do not study the entry effect of legacy carriers because the data indicates that these carriers did not enter a significant number of routes in this time period.

Previous research has studied the effect of brand loyalty on the demand for flying. Borenstein (1989) and Gilbert (1996) describe how airlines employ marketing schemes in the form of frequent flier programs in order to create and strengthen consumers’ brand loyalty for that particular airline. Consumers enroll in an airline’s frequent flier program and accumulate credit each time they fly with that particular airline. Members can redeem their credit for free flights, upgrades, or other rewards from that airline. Brand-loyal consumer effectively experience a switching cost upon enrollment in a particular carrier’s frequent flier program. Kim, Shi, and Srinivasan (2001) explore how these marketing programs can create two market segments: brand-loyal consumers and price-sensitive consumers.6 Brand-loyal consumers tend to be members of a particular airline’s frequent flier program and become disposed to purchasing more flights on that airline. Price-sensitive consumers simply look to fly with the airline charging the lowest

6Kim, Shi, and Srinivasan refer to the brand-loyal consumers and price-sensitive consumers as the heavy-user

(6)

price for a given route. Borenstein (1989) explains how consumers are inclined to participate in a particular airline’s frequent flier program when they live in that airline’s hub city. For example, Delta Air Lines uses Hartsfield-Jackson Atlanta International Airport as a hub. Consumers in Atlanta are more likely to not only fly with Delta but also enroll in Delta’s frequent flier program in order to benefit from the wide selection of markets serviced out of Atlanta. This ultimately serves to hook passengers to that particular airline, who can exploit their brand-loyal segment by increasing prices without the fear of losing a significant amount of their market base. In other words, members of an airline’s frequent flier program will continue to purchase from that carrier even if they were charged a higher price because these consumers want to obtain an award after purchasing a certain amount of trips from that airline. Therefore, brand loyalty serves as a switching cost for consumers.

There is empirical evidence for the displacement effect in industries which parallel the airline industry. Using data on the pharmaceutical industry, Grabowski and Vernon (1992) found that entry by generic drugs induced firms selling branded prescription drugs to target consumers with inelastic demand, leaving generic drugs to focus on consumers with more elastic demand. This led to an increase in the price of branded drugs, exemplifying the case when the displacement effect is more prominent than the competitive effect. The airline industry can be considered analogous to the prescription drug market in the sense that brand loyalty is prevalent in both industries with incumbent carriers similar to branded prescription drugs and low-cost carrier entrants akin to generic drugs.

I ask whether incumbent airlines segmented the market in a similar fashion once a low-cost carrier entered a route. The displacement effect dominates if incumbent airlines focus solely on brand-loyal consumers, resulting in an increase of the incumbent’s price. Incumbents can focus on the brand-loyal segment of the market and allow entrants to service the price sensitive market segment. However, entry by low-cost carriers could lead to stronger competition for price sensitive consumers, leading to a decrease in the incumbent’s price. Furthermore, the decrease in price at the low end of the price distribution could lead incumbents to also decrease prices at the high end of the distribution in order to prevent brand-loyal consumers from becoming more price sensitive. If there was a substantial difference between full fares and discount fares, then brand-loyal consumers would substitute between competing carriers. This paper sets out to investigate whether competition for price sensitive consumers induces price competition for brand-loyal consumers as well.

The competitive effect also seems to be a credible story behind how incumbents respond to entry by low-cost carriers. Morrison (2001) and Vowles (2001) both document evidence that

(7)

incumbents decrease price when Southwest Airlines enters a new market – the so-called South-west Effect. This supports the claim that the competitive effect could dominate the displacement effect. However, given the nature of the airline industry, it is plausible that the displacement ef-fect dominates as in the pharmaceutical industry. Therefore, it could be argued that incumbents would increase their price in response to entry by a low-cost carrier. This paper serves to em-pirically test whether the competitive effect story or the displacement effect story characterizes the entry effect of low-cost carriers in the U.S. airline industry.

3

Data

The data used for this paper was collected from the Airline Origin and Destination Survey (DB1B), which is published quarterly by the Bureau of Transportation Statistics. It is a ten per-cent sample of airline tickets from carriers flying domestic routes. From this database, I collect information on the origin, destination, non-stop distance between endpoints, ticketing carrier, market fare,7and number of passengers paying a particular market fare. The market fare is the

one-way price paid by a passenger for a specific origin-destination route on a particular carrier. The average price, P¯, for a specific route serviced by a particular airline is thus defined by the following equation: P¯ =

P

ipi∗ni

N , wherepi represents each particular market fare paid by

pas-sengers on the route,ni represents the amount of people who paid that particular market fare,

andN is the total number of people flying on that route.

I eliminate all observations where the market fare is less than $10 or the distance was equal to zero. Observations with an unidentified ticketing carrier were dropped. Only observations related to nonstop flights were kept. Observations pertaining to carriers who have less than 1% of the traffic on a given route were eliminated. Finally, the sample was restricted to the 1000 routes with the highest number of passengers from 1993:Q1 to 2007:Q4. The dataset contains in-formation on 2.67 trillion passengers over the 15 year time period, which corresponds to roughly 45 million passengers per quarter.8

In order to be identified as an instance of actual entry, the entrant must have not operated on the route for twelve quarters prior to the quarter of entry and remain on the route for two quarters after entry. The entrant must also service at least 100 passengers in the quarter of entry. Two robustness checks on the identification of entry were performed. There are some cases in

7Market fare is calculated by the Bureau of Transportation Statistics as the itinerary yield multiplied by the

number of miles flown.

8This paper focuses on the effect of six legacy carriers and four low-cost carriers. The total number of passengers

(8)

which two or more low-cost carriers entered a particular route within the sample period. One concern would be that the incumbents would respond to the first entrant, but not necessarily to the second entrant. The first robustness check isolates the first-entrant response by identifying entry only if there was no low-cost carrier servicing the route prior to entry. Another concern may arise if incumbents attempt a predatory pricing scheme in order to deter entry.9 Since my identification rule is that the entrant must remain on the route for only two subsequent quarters after entry, the price response would capture the initial price decrease and subsequent price increase consistent with a predatory pricing scheme. The second robustness check rules out predatory pricing effects by requiring that the entrant must continue to operate on the route for at least eight quarters after entry. The results for each robustness check remain qualitatively consistent with the main results of this paper.

There are three carrier classifications in the DB1B: reporting carrier, operating carrier, and ticketing carrier. Reporting carrier refers to the carrier who submits the information to the Bu-reau of Transportation Statistics. Operating carrier refers to the carrier who conducted the actual service of air transportation. Ticketing carrier refers to the carrier who issued the passenger the ticket for the flight. In most cases, the three are the same. However, there are cases in which the three are different. For instance, a regional airline could operate the flight under a code-share agreement with the ticketing carrier. The scope of this paper focuses on how the entry by a low-cost carrier affects the incumbents’ prices. The brand name competition is based at the ticketing-level rather than at the operating-level. Moreover, the consumer’s decision on a reservation is based on the ticketing carrier. In other words, consumers often ignore who the op-erating carrier is or the fact that the flight is a codeshare flight with another carrier. At the time that the reservation is made, passengers base their purchase on who they purchase the ticket from. For these reasons, I use the ticketing carrier classification here.

4

Empirical Analysis

In order to take a preliminary look at incumbent response to entry by low-cost carriers, I analyze the average prices set by incumbents and the entrant in the quarter of actual entry. I report the frequency and percentage that an entrant enters with an average price higher than, equal to, or lower than that set by the incumbents. In order to do this, I create a price window of $20 around the average price set by each incumbent.10 Price matching occurs if the entrant’s

9See Elzinga and Mills (2005) for details on the

Spirit Airlines v. Northwest Airlinespredatory pricing case.

10The average price in the sample is $170.35 so the $20 price window accounts for roughly a 10% cushion in

(9)

average price is within the incumbent’s $20 price window in the quarter of entry. In order for the entrant to have been determined to set a price higher (lower) than the incumbent’s price, the en-trant’s average price must be at least $20 greater than (less than) the incumbent’s price. In order to check the robustness of the results, price windows of $10, $15, $25, and $30 were calculated. The results are qualitatively similar. The quantitative differences between price windows stem from the fact that the percentage of price matching increases as the size of the window increases. Table 2 in the Appendix summarizes the results using a $20 price window.

Low-cost carrier entrants tend to set an average price that is lower than the legacy carrier incumbents’ average price in the quarter of entry. For example, Southwest Airlines enters at an average price that is lower than American Airlines’s price on 44 of 76 (57.9%) instances of entry. In other words, Southwest Airlines is likely to undercut American Airlines’s average price in the quarter that they enter that route, conditional on the fact that American Airlines is an incumbent carrier. It is very rare for a low-cost carrier to set a price that is higher than that of a legacy carrier incumbent. In fact, Southwest Airlines sets a price that is at least $20 higher than the average price set by United Airlines on only 7 of 110 (6.4%) of the routes that Southwest Airlines entered and United Airlines is an incumbent. The results suggest that legacy carrier incumbents may face downward pressure on their prices since they are being undercut by low-cost carrier entrants.

Low-cost carrier entrants tend to price match the average price set by low-cost carrier in-cumbents. On 19 of 35 (54.3%) of the routes in which Southwest Airlines enters and AirTran Airways is an incumbent, Southwest Airlines ends up setting an average price that is within $20 of AirTran’s price. The results for the other low-cost entrants suggests that they are more likely to price match rival low-cost carriers than incumbent legacy carriers, whose prices tend to be more expensive than low-cost carriers. Therefore, low-cost carrier incumbents might not need to change their prices since there is weak price competition from the entering low-cost carrier. The differing responses by legacy carrier incumbents and low-cost carrier incumbents foreshadow the results presented in this section of the paper.

I study three different responses to entry in order to give a more complete analysis on the entry effect of low-cost carriers. First, I examine how incumbents change their mean airfare before and after actual entry by a low-cost carrier. Second, I investigate how the incumbents’ price distribution of airfares is affected by that entry. In particular, I look at how the tails of the distribution (10th percentile airfare and 90th percentile airfare) change before and after entry. I also examine the entry effect on the incumbent’s Gini coefficient, which serves as a proxy for price dispersion. The Gini coefficient is commonly used11 as the measure for fare inequality

(10)

to reflect the fact that different passengers end up paying different prices for the same flight serviced by a particular carrier. The Gini coefficient is constructed to be between zero and one, where inequality increases as the Gini coefficient increases. In other words, a Gini coefficient of zero represents perfect equality, whereas a Gini coefficient of one signifies perfect inequality. In the context of the airline industry, a Gini coefficient of zero means that everyone pays the same price for a specific route serviced by a particular carrier, whereas an increase in the carrier’s Gini coefficient shows that there is more price dispersion on a particular route. Finally, I investigate whether low-cost carrier entrants set their price below, at, or above the incumbents’ prices when they enter a new route.

4.1

Estimation Strategy

Following the estimation strategy in Goolsbee and Syverson (2008), I use a two-way fixed effects model to identify the entry effects on incumbents’ prices. Four dependent variables were used, including the logged mean airfare (lnprice), the logged 10th percentile price (lnp10), the logged 90th percentile price (lnp90), and the log-odds ratio of the Gini coefficient (loddGini)12. Following Gerardi and Shapiro (2009), the log-odds ratio of the Gini coefficient is used to account for the fact that the Gini coefficient is bounded between zero and one. I control for the carrier’s market share on the route, the arithmetic mean of the market share for a carrier at the two end-points, the Herfindahl Index of the route, the arithmetic mean of the Herfindahl Index at the two endpoints, and the geometric mean of metropolitan statistical area (MSA) population of the two endpoints. The market share variables are both based on the number of passengers. MSA population data were obtained from Local Area BEARFACTS published by the Bureau of Eco-nomic Analysis. I also include carrier-route fixed effects and carrier-year-quarter fixed effects. I cluster the standard errors by route-carrier to account for correlation between a route-carrier combination over time. Table 1 in the Appendix provides summary statistics.

The basic specification is as follows:

yijt=γij +µt+

12

X

τ=−12

βτentryj,t0+τ +Xijtα+ijt, (1)

whereyijtis eitherlnpriceijt,lnp10ijt,lnp90ijt, orloddGiniijtfor carrierion routej in timet,

γij is the carrier-route fixed effects, µtis the year-quarter fixed effects,entryj,t0+τ are the time

in their estimation strategy.

12The log-odds ratio of the Gini coefficient (G) is defined asloddGini=lnh G

(1−G)

i

(11)

dummies that specify the lag/forward of the low-cost carrier actually entering a route, andXijt

are the control variables explained above.

The two-way fixed effects model contains 25 time dummies that account for 12 quarters before actual entry to 12 quarters after actual entry, including the actual quarter of entry.13 The estimates of the time lags/forwards of entry show the relative sizes of logged one-way average airfare in the dummy period versus its average value in the excluded period (the thirteenth to sixteenth quarters before entry). Table 3 summarizes the results of the time dummies for each low-cost carrier entrant in the case where all incumbent carriers (legacy carriers, low-cost carriers, and other carriers14) are accounted for. Column 3 depicts the results of all incumbent

carriers to entry by Southwest Airlines. Since the dummies are mutually exclusive, an incumbent sets a price that is 12.24% lower,15 on average, in the time period immediately after actual entry

(t0 + 1) relative to the excluded period (the thirteenth to sixteenth quarters before entry). In

other words, the estimates are not additive.

In order to track the price changes by incumbents in response to entry by a particular carrier, I create price paths based on the coefficients of the time dummies in the two-way fixed effects model. The price data is based only on incumbents’ prices so we can interpret the results as the incumbents’ pricing response to entry by a particular carrier. I transform the estimates in order to interpret the coefficients as relative percent change in price.16 The term “relative"

can be interpreted as being relative to prices in the excluded time period. Entry occurs at time period 0 with negative time values signifying the quarter before actual entry and positive time values signifying the quarter after actual entry. The solid line is the transformation of the point estimates from the model with the dotted lines representing the 95% confidence interval. If prices are constant throughout (no change in prices by incumbents), then this can be considered as the incumbents not responding to entry by any sort of price changes. If prices are less than zero and statistically significant before actual entry, then this provides evidence for preemptive price cutting.

13It is important to maintain “clean" windows so particular care was exhibited to ensure that no other carrier

entered that route within the 25 quarter window. This reduced the number of entered markets in the sample, but would ensure consistent and accurate regression estimates.

14Not all carriers are characterized as either a legacy carrier or a low-cost carrier. For example, ATA Airlines is

a charter airline yet was an incumbent when Southwest Airlines entered the Los Angeles International Airport to Philadelphia International Airport route in 2004:Q2.

15The percent change relative to the excluded period is found by exp(-0.1306) - 1 = -0.1224.

16The point on the figure associated with the relative price change by all incumbents a quarter after Southwest

(12)

4.2

Incumbent Price Response to Entry: Mean Airfare

Incumbent airlines can potentially respond to entry by low-cost carriers in either one of two ways. The incumbent could decrease their prices before entry occurs in order to enforce the brand loyalty of their consumers, while increasing their attractiveness to price-sensitive con-sumers. Prices could continue to drop even after entry occurs as the incumbent responds to the decrease in their respective demand due to an influx of substitutes. In other words, the compet-itive effect could lead to a strengthening of price competition between the incumbents and the entrant. Conversely, entry could induce incumbents to actually increase prices so that they could exploit the switching costs inherent in the brand-loyal market segment. This so-called displace-ment effect can occur when the effect of an increase in prices can more than offset the effect of a decrease in quantity so that profits ultimately increase. I check to see which of these stories holds true in the airline industry by examining how the incumbents’ mean airfare changes before and after actual entry by a low-cost carrier.

Figure 1 illustrates the price paths for all incumbents (legacy carrier, low-cost carriers, and other carriers) in response to entry by either AirTran Airways (Figure 1(a)), JetBlue Airways (Fig-ure 1(b)), Southwest Airlines (Fig(Fig-ure 1(c)), and Spirit Airlines (Fig(Fig-ure 1(d)). These price paths es-sentially graph out the time dummies from the regression results summarized in Table 3. Again, these estimates can be interpreted as the percentage price change relative to the excluded period (the thirteenth to sixteenth period before entry). Following the literature on the Southwest Ef-fect, I focus my analysis on the price response in the quarter before to the quarter after actual entry occurs. Morrison (2001) and Vowles (2001) both examine price changes the quarter before and the quarter after actual entry by Southwest Airlines. They find that incumbents significantly decrease their prices before and after entry by Southwest Airlines. I broaden their analysis to examine the type of price effect induced by entry by other low-cost carriers.

Each price path in Figure 1 shows the percentage price change relative to the excluded period (the thirteenth to sixteenth period before actual entry) for the twelve quarters before entry to the twelve quarters after entry. According to Figure 1(c), incumbents do not significantly change their average prices until Southwest Airlines actually enters the route. Moreover, incumbents’ mean airfare steeply decreases in the quarter of entry and the first quarter after entry. In fact, the solid line shows that incumbents’ prices decrease 12.24% on average in the quarter following entry by Southwest Airlines. Based on the 95% confidence intervals (the dotted lines), Figure 1(c) shows that this decrease is statistically significant. This key result corroborates the previous findings in the literature. Namely, incumbents decrease their prices in response to entry by Southwest Airlines. However, I want to determine whether this effect is induced by other

(13)

low-cost carrier entrants.

(a) Entrant: AirTran Airways (b) Entrant: JetBlue Airways

(c) Entrant: Southwest Airlines (d) Entrant: Spirit Airlines

Figure 1: Incumbent Response to Entry: Mean Airfare

Further examination of the other price paths in Figure 1 shows that incumbents tend to decrease their mean airfares the quarter before entry, the quarter of entry, and the quarter after entry. It appears as though each of these low-cost carriers exemplify the competitive effect as incumbent prices are decreasing in response to entry. Southwest Airlines had the largest average entry effect, with the aforementioned result of inducing incumbents to decrease prices by 12.24%, on average, the quarter after actual entry. Other low-cost carriers had similar, yet weaker effects. AirTran Airways induced a decrease of 10.81%, while incumbents also reacted to entry by JetBlue Airways and Spirit Airlines, but only by a modest amount of 5.57% and 5.36%, respectively. Nevertheless, each low-cost carrier induced incumbents to decrease their prices before and after actual entry. Therefore, incumbents face downward pressure on their prices, which provides evidence that the competitive effect dominates the displacement effect.

The results from Table 2 in the Appendix suggest that it is worthwhile to examine the varia-tions in the entry response of legacy carrier and low-cost carrier incumbents. Figure 2 shows the relative price response of legacy carrier incumbents to entry by low-cost carrier, whereas Figure 3 shows the price response of low-cost carrier incumbents. Figures 2 and 3 correspond with the regression results in Table 4 and 5, respectively. In both cases, the dependent variable is logged mean airfare, thus, the interpretation of the price paths is the same as in Figure 1.

(14)

(a) Entrant: AirTran Airways (b) Entrant: JetBlue Airways

(c) Entrant: Southwest Airlines (d) Entrant: Spirit Airlines

Figure 2: Legacy Carrier Incumbent Response to Entry: Mean Airfare

(a) Entrant: AirTran Airways (b) Entrant: JetBlue Airways

(c) Entrant: Southwest Airlines (d) Entrant: Spirit Airlines

Figure 3: Low-Cost Carrier Incumbent Response to Entry: Mean Airfare

Based on the price paths in Figure 2, legacy carriers respond to entry by low-cost carriers by dramatically decreasing their average airfares. In fact, there is a more pronounced price drop than the effect shown in Figure 1, which considers all incumbents servicing the entered route

(15)

when the entrant actually enters. It is important to note that the analysis is based on examin-ing the price response one quarter before to one quarter after actual entry. Again, these price decreases are relative to the prices in the excluded period, which consists of the thirteenth to sixteenth quarter before entry. Southwest Airlines induces incumbents to decrease their average prices by 13.09%. However, AirTran Airways induces an even stronger effect than that of South-west as incumbents cut their mean airfare by an average of 13.31% the quarter after AirTran Airways actually enters a route. Entry by JetBlue Airways and Spirit Airlines invokes legacy carrier incumbents to decrease their prices by 7.07% and 7.98%, respectively. All of these ef-fects are larger than their respective effect implied by Figure 1. Furthermore, these relative price changes are all significant at the 5% level. This sharp price drop is evidence that the competitive effect describes the response of legacy carriers to entry by low-cost carriers.

The existing literature focuses on the strong entry effect of Southwest Airlines. Over the past decade, other low-cost airlines have entered the industry and are currently major carriers in the industry. JetBlue Airways and AirTran Airways demonstrate how other low-cost carriers can mirror the entry effects exhibited with Southwest Airlines. The upshot is that the Southwest Effect can no longer be considered as a special case relevant to one particular airline, particularly as it pertains to legacy carrier incumbents. Rather, the entry effect pertains to low-cost carriers in general.

Figure 3 shows that low-cost carrier incumbents do not significantly alter their mean airfare when either a low-cost carrier enters the route. These price paths are in stark contrast with Figure 2, where it was shown that legacy carrier incumbents significantly decrease their mean price. Therefore, legacy carrier incumbents (Figure 2) react differently than low-cost carrier incumbents (Figure 3) in their response to entry by a low-cost carrier.

The differing response by legacy carriers and low-cost carriers can be rationalized by the frequency of price matching by low-cost carrier entrants. Recall that Table 2 shows that low-cost carrier entrants are likely to undercut legacy carrier incumbents, yet match the price of low-cost carrier incumbents. The competitive effect story predicts that incumbents would decrease their price after entry occurs in response to an increase in price competition from the entrant, whereas the displacement story would induce a price increase by the incumbent. The results support the claim that the competitive effect story applies to legacy carrier incumbents; however, low-cost carrier incumbents are not susceptible to either effect.

(16)

4.3

Incumbent Price Response to Entry: 10th Percentile Airfare, 90th

Percentile Airfare, and Gini Coefficient

Different passengers who fly on the same flight may pay markedly different fares. As such, it is possible that entry by a low-cost carrier could affect the price distribution of airfares set by incumbent carriers. Borenstein and Rose (1994) show that price dispersion increases as routes become more competitive. The intuition is that entry can induce incumbents to decrease their discount price (i.e. the 10th percentile airfare) to attract price-sensitive consumers, while keep-ing their full-fare price (i.e. the 90th percentile airfare) high, resultkeep-ing in an increase in price dispersion. Gerardi and Shapiro (2009) conclude that price dispersion actually decreases when there is more competition in the route. The intuition here is that an increase in competition erodes the incumbent carriers’ market power, which mitigates the ability for these airlines to effectively price discriminate. Therefore, price dispersion is smaller in markets that are more competitive. In this section, I discuss the effect of entry by low-cost carriers on the incumbents’ price distribution of airfares.

The price paths in this section are constructed based on regression results using either the logged 10th percentile airfare, logged 90th percentile airfare, or the log-odds ratio of the Gini coefficient as the dependent variable. As in Gerardi and Shapiro (2009), the 10th percentile airfare is intended to control for the effect on discount tickets, whereas the 90th percentile airfare proxies for full-fare prices. These two dependent variables effectively account for changes at the tails of the price distribution. The Gini coefficient measures the price dispersion of a carrier’s prices on a specific route in a particular time period, and is between zero and one. Since the Gini coefficient emphasizes the middle of the price distribution, a full analysis of the entry effect on incumbents’ price distribution involves analyzing the effects on the tails as well.17

Figure 4 shows that legacy carrier incumbents slash their 10th percentile prices immediately before and immediately after entry. In the quarter after Southwest Airlines actually enters a route, legacy carrier incumbents decreased their 10th percentile prices by 11.56%, on average, relative to the excluded period (the thirteenth to sixteenth quarter before entry). Other low-cost entrants induced similar effects, with legacy carrier incumbents dropping prices by an average of 8.09%, 7.49%, and 7.69% when AirTran Airways, JetBlue Airways, and Spirit Airlines entered the route, respectively. These results suggest that legacy carrier incumbents significantly decrease their discount prices in response to entry by a low-cost carrier.

(17)

(a) Entrant: AirTran Airways (b) Entrant: JetBlue Airways

(c) Entrant: Southwest Airlines (d) Entrant: Spirit Airlines

Figure 4: Legacy Carrier Incumbent Response to Entry: 10th Percentile Airfare

(a) Entrant: AirTran Airways (b) Entrant: JetBlue Airways

(c) Entrant: Southwest Airlines (d) Entrant: Spirit Airlines

Figure 5: Low-Cost Carrier Incumbent Response to Entry: 10th Percentile Airfare

The analysis from Section 4.2 shows that the response by legacy carrier incumbents differs from that of low-cost carrier incumbents, as far as changes to mean airfare is concerned. Figure 5 shows that the low-cost carriers do not significantly alter their 10th percentile prices in response

(18)

to entry by a rival low-cost carrier. Just as with mean airfares, the results for 10th percentile airfares show a stark contrast in the response by low-cost carriers from that of legacy carriers to entry by a low-cost carrier.

The displacement effect implies that incumbents’ prices should increase in response to entry. Particular attention should be made to the effect on 90th percentile prices as the displacement effect predicts that since the incumbent is focused on their brand-loyal market segment, they can profitably increase their full fare price. These consumers will still purchase from the incumbent since they would face a switching cost if they purchase from another carrier. If the 90th percentile prices increase, then the displacement effect story is confirmed.

(a) Entrant: AirTran Airways (b) Entrant: JetBlue Airways

(c) Entrant: Southwest Airlines (d) Entrant: Spirit Airlines

Figure 6: Legacy Carrier Incumbent Response to Entry: 90th Percentile Airfare

Figure 6 indicates the displacement effect does not characterize airline fare competition well, particularly as it pertains to legacy carriers. Legacy carrier incumbents decrease their full fare prices on average. This effect is large for all the entrants. Southwest Airlines induces legacy carrier incumbents to decrease their 90th percentile prices by 14.86%, which is actually a stronger effect than that of the 10th percentile prices. Legacy carriers also significantly decrease their prices in response to the other low-cost carrier entrants. Legacy carriers decreased their 90th percentile price by 14.68% and 14.05% in the quarter after actual entry by AirTran Airways and Spirit Airlines, respectively. Interestingly, these effects are of larger magnitudes than that on the 10th percentile prices. Full fare prices charged by legacy carriers decreased by 3.35%, on average,

(19)

in response to entry by JetBlue Airways. Although this is not as strong as their effect on 10th percentile prices, entry by JetBlue Airways still put downward pressure on the incumbents’ full fare prices. Therefore, the displacement story does not hold for legacy carrier incumbents.

(a) Entrant: AirTran Airways (b) Entrant: JetBlue Airways

(c) Entrant: Southwest Airlines (d) Entrant: Spirit Airlines

Figure 7: Low-Cost Carrier Incumbent Response to Entry: 90th Percentile Airfare

The results of the effect of entry by a low-cost carrier on low-cost carrier incumbents’ full fare prices are illustrated in Figure 7. In contrast to the results for legacy carrier incumbents, low-cost carriers do not strongly respond to entry. The analysis on entry by Southwest Airlines continues to show the pronounced effect that they have on incumbents’ prices. As with mean airfare and discount prices, low-cost carrier incumbents do not alter their full fares in the same manner as legacy carrier incumbents in response to entry by low-cost carriers.

In order to examine the overall effect of entry on the incumbent’s price distribution, I cal-culated the log-odds ratio of the carrier’s Gini coefficient, which measures the carrier’s price dispersion at the route level. It may be the case that there is price polarization, i.e. prices in the middle of the price distribution are pushed toward the tails, which would cause the Gini coeffi-cient to increase and may be evidence for the displacement effect. I use the log-odds ratio as the dependent variable in the estimation strategy discussed in Section 4.1 and plot the transforma-tion of the time dummies, similar to the price paths constructed above. Subsequently, Figures 8 and 9 can be interpreted as the evolution of the incumbent’s price dispersion in the entered route over time.

(20)

(a) Entrant: AirTran Airways (b) Entrant: JetBlue Airways

(c) Entrant: Southwest Airlines (d) Entrant: Spirit Airlines

Figure 8: Legacy Carrier Incumbent Response to Entry: Gini Coefficient

(a) Entrant: AirTran Airways (b) Entrant: JetBlue Airways

(c) Entrant: Southwest Airlines (d) Entrant: Spirit Airlines

Figure 9: Low-Cost Carrier Incumbent Response to Entry: Gini Coefficient

Figures 8 and 9 show that the Gini coefficient for the prices set by legacy carriers and low-cost carriers, respectively, do not significantly respond to entry by a low-low-cost carrier. Again, the percentage change in the Gini coefficient is relative to the excluded period (the thirteenth

(21)

to sixteenth period before entry). Recall that legacy carrier incumbents decrease both their 10th percentile and 90th percentile prices, on average, in response to entry by a low-cost carrier. Al-though the 90th percentile prices decrease more than the 10th percentile prices, the total effect on the Gini is negligible. In other words, the Gini coefficient for legacy carriers does not sig-nificantly change immediately before and after entry because both tails of the price distribution decrease. The mean average airfare decreases as well, indicating downward pressure on the en-tire price distribution. On the other hand, low-cost carriers do not significantly respond to entry by a rival low-cost carrier. Generally speaking, there is no effect on the mean airfare, 10th per-centile airfare, or the 90th perper-centile airfare. Consequently, there is no significant effect on price dispersion by low-cost carrier incumbents.

Under the displacement story, prices should increase in response to entry. Incumbents focus on their brand-loyal market segment and therefore increase prices to those consumers so that the increase in price offsets the effect of the decrease in quantity. Under the right demand conditions, this would lead to increased profits. Therefore, we would expect that there would be an increase in price dispersion as full fare prices should increase with little to no effect on discount fares. As seen in Figures 8 and 9, the Gini coefficient does not change, which is contrary to what we would expect from the displacement story. On the other hand, the competitive effect implies that prices should decrease as incumbents are focused on strengthening the brand loyalty of their consumers before entry occurs and face downward pressure on prices as price competition increases after entry occurs. The competitive effect is supported by the fact that legacy carrier incumbents’ prices decrease all along their distribution of prices, resulting in an insignificant change of the Gini coefficient.

I run the two-way fixed effects regression model using the interquartile range, which cal-culates the difference between the third and first quartiles (i.e. the middle 50th percentile), as the dependent variable. This serves as a robustness check for the Gini coefficient since the in-terquartile range would provide further information about the shape of the price distribution. The results support the analysis on the Gini coefficient.18

These results differ from the key findings in Borenstein and Rose (1994) and Gerardi and Shapiro (2009). Borenstein and Rose (1994) find that price dispersion increases when there is more competition. This would occur if entry induces incumbents respond to entry by decreasing their 10th percentile prices, while keeping their 90th percentile prices high, suggesting that the path for the Gini coefficient should be significantly positive around the time of entry. However, Gerardi and Shapiro (2009) find that an increase in competition would lead to a decrease in price

(22)

dispersion. My results would have corroborated their finding if the path for the Gini coefficient was negative around the time of entry, suggesting that an increase in competition due to the en-try by a low-cost carrier would induce a higher degree of price equality. My results support the claim that competition has no effect on price dispersion since the Gini coefficient does not sig-nificantly change due to entry by a low-cost carrier, which contrasts with the previous findings in the literature.

Both Borenstein and Rose (1994) and Gerardi and Shapiro (2009) determine the effect of com-petition on price dispersion by estimating regression models consisting of a transformation of the Gini coefficient19as the dependent variable, while the independent variables include a proxy

for competition. These papers are interested in the estimated sign and significance of the com-petition variables on price dispersion. Their results suggest a significant, yet contrasting effect. Gerardi and Shapiro attribute their differing results to the fact that they use panel data, while Borenstein and Rose use cross-sectional data. They argue that the results in Borenstein and Rose paper suffer from omitted-variable bias, which they fix by including route-carrier fixed effects.

The identification strategy used in this paper is different than the strategy used by Borenstein and Rose (1994) and Gerardi and Shapiro (2009), which could explain for the salient result. My approach is similar to an event study, in which I identify individual events of entry and estimate the short-run effect of entry on incumbents’ prices. I examine how incumbents react differently to different low-cost carrier entrants around the time of actual entry. I also analyze how the incumbent response differs depending on whether the incumbent is a low-cost carrier and legacy carrier. However, Borenstein and Rose (1994) and Gerardi and Shapiro (2009) focus on a more long-run price effect. They are interested in a more general industry-wide effect of competition on incumbent prices. According to Borenstein and Rose (1994), competition is affected by a change in the Herfindahl Index or the total number of flights on the route, whereas Gerardi and Shapiro identify a change in competition by a change in the Herfindahl Index or the total number of carriers servicing the route. The results in this paper show that price dispersion does not significantly change when competition increases, specifically when a low-cost carrier enters a new route.

19Borenstein and Rose (1994) use logged Gini coefficient as their dependent variable, while Gerardi and Shapiro

(23)

5

Conclusion

This paper studies the incumbent response to entry by low-cost carriers. Legacy carrier incumbents tend to decrease their average airfare, discount fares, and full fare price before and after entry by a low-cost carrier. However, low-cost carriers do not significantly alter their prices in response to entry by a rival low-cost carrier. In both cases, the Gini coefficient does not significantly change, implying that entry does not affect the incumbent’s price dispersion. This paper extends upon the work by Goolsbee and Syverson (2008) by going further to identify how incumbents respond to entry by not only Southwest Airlines, but also other prominent low-cost carriers. The key punch line to the paper is that although the strongest entry response occurs when Southwest Airlines enters a new route, legacy carrier incumbents tend to respond in a similar, yet weaker fashion to other low-cost carriers.

The results suggest that there is no short-run effect of competition on price dispersion. Entry by a low-cost carrier induces legacy carrier incumbents to decrease their 10th percentile, 90th percentile, and mean airfares. Since legacy carrier incumbents decrease prices all along the price distribution, then there was no net change to the overall dispersion of prices. Low-cost carrier incumbents do not alter their price dispersion as they do not significantly respond to entry by a rival low-cost carrier. These findings extend the results in Borenstein and Rose (1994) and Gerardi and Shapiro (2009), who focus on the long-run effect of competition on price dispersion in the industry as a whole.

Legacy carrier incumbents react differently to entry by low-cost carriers than low-cost car-rier incumbents. Low-cost carcar-rier entrants tend to undercut legacy carcar-rier incumbents, while matching the prices of low-cost carrier incumbents. Legacy carriers decrease their prices in re-sponse to the low prices set by a low-cost carrier entrant. This downward pressure on prices was not experienced by low-cost carrier incumbents due to the weak price competition that ensued between rival low-cost carriers. This paper sheds light on a previously unknown phenomena: the strategic interaction between low-cost carrier entrants and rival low-cost carrier incumbents.

(24)

References

Boguslaski, Charles, Harumi Ito, and Darin Lee (2004), “Entry Patterns in the Southwest Airlines Route System",Review of Industrial Organization25, 317-350.

Borenstein, Severin (1989), “Hubs and High Fares: Dominance and Market Power in the U.S. Airline Industry",The RAND Journal of Economics20(3), 344-365.

Borenstein, Severin (1991), “The Dominant-Firm Advantage in Multiproduct Industries: Evidence from the U.S. Airlines",The Quarterly Journal of Economics106(4), 1237- 1266.

Borenstein, Severin (1992), “The Evolution of U.S. Airline Competition",The Journal of Economic

Perspectives6(2), 45-73.

Borenstein, Severin and Nancy Rose (1994), “Competition and Price Dispersion in the U.S. Airline Industry",Journal of Political Economy102(4), 653-683.

Brander, James and Anming Zhang (1990), “Market Conduct in the Airline Industry: An Empirical Investigation",The RAND Journal of Economics21(4), 567-583.

Brueckner, Jan, Nichola Dyer, and Pablo Spiller (1992), “Fare Determination in Airline Hub-and-Spoke Networks",The RAND Journal of Economics23(3), 309-333.

Cornia, Marco, Kristopher Gerardi, and Adam Shapiro (2011), “Price Discrimination and Business-Cycle Risk", working paper.

Elzinga, Kenneth and David Mills (2005), “Predatory Pricing in the Airline Industry: Spirit Airlines v. Northwest Airlines", in John Kwoka, Jr. and Lawrence White (eds.),The

Antitrust Revolution, 5th ed., Oxford University Press.

Evans, William and Ioannis Kessides (1993), “Localized Market Power in the U.S. Airline Industry",The Review of Economics and Statistics75(1), 66-75.

Gerardi, Kristopher and Adam Shapiro (2009), “Does Competition Reduce Price Dispersion? New Evidence from the Airline Industry",Journal of Political Economy117(1), 1-37.

Gilbert, David (1996). “Relationship Marketing and Airline Loyalty Schemes",Tourism

Management17(8), 575-582.

Goolsbee, Austan and Chad Syverson (2008), “How Do Incumbents Respond to the Threat of Entry? Evidence from the Major Airlines", The Quarterly Journal of Economics123(4), 1611-1633.

Grabowski, Henry and John Vernon (1992), “Brand Loyalty, Entry, and Price Competition in Pharmaceuticals after the 1984 Drug Act",Journal of Law and Economics35(2), 331- 350. Hayes, Kathy and Leola Ross (1998), “Is Airline Price Dispersion the Result of Careful Planning

or Competitive Forces?",Review of Industrial Organization13, 523-541.

(25)

Networks". The RAND Journal of Economics28(2), 291-303.

Hollander, Abraham (1987), “On Price-Increasing Entry",Economica54(215), 317-324. Kim, Byung-Do, Mengze Shi, and Kannan Srinivasan (2001), “Reward Programs and Tacit

Collusion",Marketing Science20(2), 99-120.

Klemperer, Paul (1987), “Markets with Consumer Switching Costs", The Quarterly Journal of

Economics102(2), 375-394.

Morrison, Steven (2001), “Actual, Adjacent, and Potential Competition: Estimating the Full Effect of Southwest Airlines,Journal of Transport Economics and Policy35(2), 239-256.

Perloff, Jeffrey and Steven Salop (1985), "Equilibrium with Product Differentiation",The Review

of Economic Studies52(1), 107-120.

Rosenthal, Robert (1980), “A Model in which an Increase in the Number of Sellers Leads to a Higher Price",Econometrica48(6), 1575-1579.

Villa-Boas, J. Miguel (2004), “Consumer Learning, Brand Loyalty, and Competition", Marketing

Science23(1), 134-145.

Vowles, Timothy (2000), “The Effect of Low Fair Air Carriers on Airfares in the US",Journal of

Transport Geography8, 121-128.

Vowles, Timothy (2001), “The Southwest Effect In Multi-Airport Regions",Journal of Air

Transport Management7, 251-258.

Whinston, Michael and Scott Collins (1992), “Entry and Competitive Structure in Deregulated Airline Markets: An Event Study Analysis of People Express", The Review of Economics and

Statistics23(4), 445-462.

Windle, Robert and Martin Dresner (1999), “Competitive Responses to Low Cost Carrier Entry",

(26)

Appendix

Table 1: Summary Statistics

Variable Definition Mean

(Std. Dev.)

priceijt Average one-way market fare for carrieri 170.35

on routejin time periodt (72.68)

giniijt Gini coefficient of carrieri’s prices 0.249

on routejin time periodt (0.089)

distancej One-way distance (in miles) between the endpoints of routej 1196.28

(663.10)

passengersijt Number of passengers for carrieri 1014.65

on routejin time periodt (1641.07)

mktshrrouteijt Market share for carrierion routejin time periodt 0.223

(0.275)

HERF routejt Herfindahl Index for routejin time periodt 0.484

(0.189)

mktshraptijt Arithmetic mean of carrieri’s market share 0.157

at endpoints on routejin time periodt (0.128)

HERF aptjt Arithmetic mean of Herfindahl Indexes 0.247

at endpoints on routejin time periodt (0.079)

popjt Geometric mean of population (in millions) of origin and 4.04

destination airports’ MSA on routejin time periodt (2.43)

Routes Number of routes in the sample 1000

(27)

T able 2: Fr e quency of Price Matching b y Entrant (windo w = incumb ent price ± 20) Entrant’s price > incumb ent’s price Incumb ent American Continental D elta Northw est Unite d US Air way s Air T ran JetBlue Southw est Spirit Entrant Air T ran 10 (8.1%) 8 (8.1%) 4 (2.0%) 8 (8.2%) 7 (6.4%) 10 (6.4%) n/a – 10 (25.0%) 0 (0.0%) JetBlue 1 (2.3%) 3 (9.4%) 5 (8.1%) 4 (22.2%) 4 (11.1%) 3 (6.8%) 2 (11.8%) n/a 2 (100.0%) 0 (0.0%) Southw est 6 (7.9%) 4 (5.2%) 5(3.9%) 4 (5.7%) 2 (2.2%) 6 (5.0%) 2 (5.7%) 0 (0.0%) n/a 4 (50.0%) Spirit 0 (0.0%) 0 (0.0%) 1 (2.2%) 0 (0.0%) 0 (0.0%) 1 (2.5%) 0 (0.0%) – 1 (6.3%) n/a Entrant’s price = incumb ent’s price Incumb ent American Continental D elta Northw est Unite d US Air way s Air T ran JetBlue Southw est Spirit Entrant Air T ran 36 (29.3%) 34 (34.3%) 60 (29.3%) 45 (46.4%) 28 (25.5%) 53 (33.8%) n/a – 25 (62.5%) 6 (75.0%) JetBlue 20 (46.5%) 14 (43.8%) 24 (38.7%) 4 (22.2%) 8 (22.2%) 12 (27.3%) 9 (52.9%) n/a 0 (0.0%) 4 (100.0%) Southw est 26 (34.2%) 25 (32.5%) 48 (37.5%) 35 (50.0%) 23 (25.8%) 49 (40.8%) 19 (54.3%) 2 (50.0%) n/a 4 (50.0%) Spirit 5 (16.7%) 6 (24.0%) 11 (23.9%) 1 (4.0%) 1 (3.3%) 8 (20%) 2 (33.3%) – 5 (31.3%) n/a Entrant’s price < incumb ent’s price Incumb ent American Continental D elta Northw est Unite d US Air way s Air T ran JetBlue Southw est Spirit Entrant Air T ran 77 (62.6%) 57 (57.6%) 141 (68.8%) 44 (45.4%) 75 (68.2%) 94 (59.9%) n/a – 5 (12.5%) 2 (25.0%) JetBlue 22 (51.2%) 15 (46.9%) 33 (53.2%) 10 (55.6%) 24 (66.7%) 29 (65.9%) 6 (35.3%) n/a 0 (0.0%) 0 (0.0%) Southw est 44 (57.9%) 48 (62.3%) 75 (58.6%) 31 (44.3%) 64 (71.9%) 65 (54.2%) 14 (40.0%) 2 (50.0%) n/a 0 (0.0%) Spirit 25 (83.3%) 19 (76.0%) 34 (73.9%) 24 (96.0%) 29 (96.7%) 31 (77.5%) 4 (66.7%) – 10 (62.5%) n/a

(28)

Table 3: Incumbent Price Response to Actual Entry

(Dependent Variable:lnprice; N=263,270)

(1) (2) (3) (4)

Entrant: AirTran Airways JetBlue Airways Southwest Airlines Spirit Airlines Incumbent: All Carriers All Carriers All Carriers All Carriers

t0−12 0.0139 0.0040 0.0236* 0.0159 (0.0072) (0.0137) (0.0100) (0.0148) t0−11 0.0194* 0.0080 0.0183 0.0097 (0.0076) (0.0135) (0.0107) (0.0162) t0−10 0.0105 -0.0242 0.0367* 0.0191 (0.0073) (0.0132) (0.0103) (0.0186) t0−9 0.0107 -0.0408* 0.0044 -0.0059 (0.0080) (0.0181) (0.0108) (0.0167) t0−8 -0.0155* -0.0209 -0.0019 -0.0246 (0.0076) (0.0152) (0.0110) (0.0191) t0−7 -0.0132 -0.0278* 0.0059 -0.0395* (0.0083) (0.0134) (0.0100) (0.0167) t0−6 -0.0302* -0.0481* 0.0326* -0.0275 (0.0089) (0.0171) (0.0103) (0.0186) t0−5 -0.0320* -0.0492* 0.0274* -0.0021 (0.0089) (0.0149) (0.0104) (0.0168) t0−4 -0.0067 -0.0603* 0.0337* -0.0056 (0.0088) (0.0181) (0.0105) (0.0156) t0−3 -0.0237* -0.0126 0.0246* 0.0101 (0.0090) (0.0152) (0.0110) (0.0156) t0−2 -0.0224* -0.0048 0.0262* -0.0210 (0.0087) (0.0157) (0.0122) (0.0157) t0−1 -0.0362* -0.0406* -0.0017 -0.0433* (0.0092) (0.0200) (0.0109) (0.0161) t0 -0.0691* -0.0447* -0.0820* -0.0365* (0.0088) (0.0153) (0.0112) (0.0200) t0+ 1 -0.1143* -0.0573* -0.1306* -0.0551* (0.0102) (0.0155) (0.0120) (0.0224) t0+ 2 -0.1274* -0.1044* -0.1137* -0.0344 (0.0103) (0.0168) (0.0119) (0.0224) t0+ 3 -0.1330* -0.0980* -0.1198* -0.0408* (0.0095) (0.0157) (0.0130) (0.0204) t0+ 4 -0.1131* -0.0676* -0.1230* -0.0466* (0.0095) (0.0165) (0.0121) (0.0182) t0+ 5 -0.1093* -0.0619* -0.1369* -0.0600* (0.0095) (0.0177) (0.0120) (0.0203) t0+ 6 -0.1184* -0.0871* -0.1057* -0.0591* (0.0094) (0.0170) (0.0115) (0.0191) t0+ 7 -0.1145* -0.0914* -0.1131* -0.0364 (0.0094) (0.0152) (0.0118) (0.0247) t0+ 8 -0.0872* -0.0858* -0.1184* -0.0577* (0.0098) (0.0146) (0.0122) (0.0196) t0+ 9 -0.0897* -0.0136 -0.1086* -0.0653* (0.0093) (0.0205) (0.0125) (0.0212) t0+ 10 -0.0887* -0.0121 -0.0883* -0.0782* (0.0101) (0.0205) (0.0118) (0.0200) t0+ 11 -0.0776* -0.0564* -0.1026* -0.0717* (0.0098) (0.0223) (0.0123) (0.0223) t0+ 12 -0.0663* -0.0570* -0.0800* -0.0467* (0.0105) (0.0239) (0.0120) (0.0214)

(29)

Table 4: Incumbent Price Response to Actual Entry

(Dependent Variable:lnprice; N=263,270)

(1) (2) (3) (4)

Entrant: AirTran Airways JetBlue Airways Southwest Airlines Spirit Airlines Incumbent: Legacy Carriers Legacy Carriers Legacy Carriers Legacy Carriers

t0−12 0.0069 0.0003 0.0225 0.0123 (0.0085) (0.0152) (0.0123) (0.0173) t0−11 0.0080 -0.0013 0.0154 0.0117 (0.0088) (0.0149) (0.0130) (0.0195) t0−10 -0.0021 -0.0290 0.0346* 0.0183 (0.0086) (0.0160) (0.0123) (0.0196) t0−9 0.0006 -0.0281 -0.0027 -0.0025 (0.0096) (0.0166) (0.0129) (0.0192) t0−8 -0.0310* -0.0144 -0.0062 -0.0449* (0.0087) (0.0147) (0.0130) (0.0154) t0−7 -0.0360* -0.0276 0.0004 -0.0556* (0.0095) (0.0155) (0.0117) (0.0165) t0−6 -0.0479* -0.0523* 0.0294* -0.0417* (0.0103) (0.0161) (0.0122) (0.0189) t0−5 -0.0478* -0.0620* 0.0250* -0.0032 (0.0103) (0.0175) (0.0123) (0.0169) t0−4 -0.0276* -0.0552* 0.0396* -0.0100 (0.0095) (0.0166) (0.0123) (0.0170) t0−3 -0.0440* -0.0138 0.0241 0.0017 (0.0104) (0.0174) (0.0131) (0.0173) t0−2 -0.0489* -0.0065 0.0324* -0.0247 (0.0093) (0.0184) (0.0147) (0.0181) t0−1 -0.0644* -0.0295 -0.0033 -0.0504* (0.0102) (0.0209) (0.0125) (0.0179) t0 -0.0916* -0.0511* -0.0925* -0.0652* (0.0096) (0.0173) (0.0130) (0.0202) t0+ 1 -0.1428* -0.0734* -0.1403* -0.0831* (0.0103) (0.0166) (0.0139) (0.0248) t0+ 2 -0.1474* -0.1183* -0.1188* -0.0674* (0.0109) (0.0188) (0.0139) (0.0226) t0+ 3 -0.1564* -0.1163* -0.1227* -0.0612* (0.0103) (0.0171) (0.0151) (0.0229) t0+ 4 -0.1368* -0.0789* -0.1185* -0.0660* (0.0102) (0.0181) (0.0142) (0.0201) t0+ 5 -0.1309* -0.0674* -0.1253* -0.0856* (0.0103) (0.0193) (0.0136) (0.0226) t0+ 6 -0.1401* -0.0848* -0.0974* -0.0862* (0.0101) (0.0182) (0.0132) (0.0206) t0+ 7 -0.1405* -0.0852* -0.1086* -0.0718* (0.0099) (0.0170) (0.0139) (0.0218) t0+ 8 -0.1170* -0.0859* -0.1170* -0.0865* (0.0102) (0.0167) (0.0138) (0.0209) t0+ 9 -0.1124* -0.0236 -0.0999* -0.0859* (0.0100) (0.0240) (0.0146) (0.0231) t0+ 10 -0.1090* -0.0149 -0.0928* -0.0963* (0.0110) (0.0242) (0.0136) (0.0219) t0+ 11 -0.1014* -0.0613* -0.1104* -0.0942* (0.0104) (0.0259) (0.0144) (0.0247) t0+ 12 -0.0913* -0.0571* -0.0823* -0.0694* (0.0106) (0.0283) (0.0140) (0.0238)

(30)

Table 5: Incumbent Price Response to Actual Entry

(Dependent Variable:lnprice; N=263,270)

(1) (2) (3) (4)

Entrant: AirTran Airways JetBlue Airways Southwest Airlines Spirit Airlines Incumbent: Low-Cost Carriers Low-Cost Carriers Low-Cost Carriers Low-Cost Carriers

t0−12 0.1307* -0.0110 -0.0148 0.0511* (0.0132) (0.0400) (0.0429) (0.0203) t0−11 0.1263* 0.0457 -0.0950 0.0236* (0.0167) (0.0452) (0.0572) (0.0116) t0−10 0.1370* -0.0067 -0.0648 -0.0058 (0.0219) (0.0395) (0.0566) (0.0267) t0−9 0.0895* -0.0422 -0.1020* 0.0047 (0.0249) (0.0449) (0.0410) (0.0324) t0−8 0.0659* -0.0296 -0.1083* 0.0631* (0.0305) (0.0438) (0.0427) (0.0306) t0−7 0.0704* -0.0592 -0.1203* 0.0434 (0.0252) (0.0405) (0.0436) (0.0398) t0−6 0.0543* -0.1188* -0.0890 0.0341 (0.0215) (0.0475) (0.0456) (0.0456) t0−5 0.0686* -0.0922* -0.1023* 0.0691 (0.0286) (0.0395) (0.0467) (0.0454) t0−4 0.0777* -0.0827 -0.1242* 0.0767 (0.0292) (0.0516) (0.0490) (0.0419) t0−3 0.1177* -0.0981 -0.0968 0.1004* (0.0257) (0.0573) (0.0499) (0.0376) t0−2 0.0943* -0.1449* -0.1387* 0.0684 (0.0234) (0.0460) (0.0490) (0.0359) t0−1 0.0609* -0.1445* -0.0776 0.0441 (0.0233) (0.0471) (0.0631) (0.0438) t0 0.1069* -0.0516 -0.0571 0.0580 (0.0233) (0.0425) (0.0599) (0.0455) t0+ 1 0.1162* -0.1139* -0.1040 0.0763* (0.0232) (0.0333) (0.0545) (0.0297) t0+ 2 0.1134* -0.1070* -0.0982* 0.0365 (0.0254) (0.0374) (0.0497) (0.0311) t0+ 3 0.0832* -0.1225* -0.1270* 0.0293 (0.0360) (0.0485) (0.0551) (0.0431) t0+ 4 0.1153* -0.0741* -0.2183* 0.0452 (0.0310) (0.0373) (0.0446) (0.0306) t0+ 5 0.0825* -0.0709* -0.1957* 0.0829* (0.0309) (0.0352) (0.0454) (0.0319) t0+ 6 0.0654* -0.0870* -0.2146* 0.0640 (0.0307) (0.0348) (0.0575) (0.0369) t0+ 7 0.0564 -0.1541* -0.1840* 0.0505 (0.0351) (0.0385) (0.0500) (0.0433) t0+ 8 0.0881* -0.1190* -0.1881* 0.0857 (0.0359) (0.0342) (0.0464) (0.0453) t0+ 9 0.1224* 0.0010 -0.2821* 0.0058 (0.0343) (0.0436) (0.0467) (0.0340) t0+ 10 0.0847* 0.0073 -0.1791* 0.0056 (0.0322) (0.0307) (0.0474) (0.0418) t0+ 11 0.0912* -0.0221 -0.1488* 0.0382 (0.0304) (0.0350) (0.0468) (0.0416) t0+ 12 0.1506* -0.1140* -0.1580* 0.0129 (0.0370) (0.0440) (0.0469) (0.0452)

Figure

Updating...

References