2010-31
Time Effect of Low-Cost Carrier Entry and Social
Welfare in US Large Air Markets
Hideki Murakami

Time Effect of Low-Cost Carrier Entry and Social Welfare in US Large Air Markets
Hideki Murakami*

Graduate School of Business, Kobe University, 2-1, Rokkodai, Nada, Kobe, Hyogo,
Japam

Abstract
In this study we empirically analyzed the airfare level at which most low-costcarriers (LCCs) entered the market, what impacts LCCs had on the airfares ofincumbent carriers, whether the impacts differed depending on how many LCCs existed
in a market and on whether LCC(s) entered a full-service carrier (FSC)’s hub airport oran adjacent airport, whether the low-airfare impact continued for the years following
entry, and finally what are the welfare implication of LCCs’ entries. We modeled andestimated the simultaneous demand and price (pseudo-supply) equation to derive thesefour economic impacts of LCCs’ entries by using published data of 1998. Our main
findings are: (1) overall, LCCs entered with very low airfare, and their entry lowered thefull-service carrier’s airfare, but the impacts of entries depended on individual LCCs;(2) neither the number of LCCs nor the location of entry by LCC(s) had different
impacts; (3) the impact of LCCs’ entries did not differ between the entry year and thesecond year; (4) the social welfare gains are substantial, and 90% of welfare gains comefrom the gain in consumers surplus.
Key Words: LCC, impact on airfare, time effect of entry, social welfare

1. Introduction

There have been many studies on the economic impact of low-cost carriers (LCCs) entry
into the air transportation market. Morrison and Winston (1995) empirically showed that
Southwest Airlines forces its competitors to reduce their fares. 1 Dresner et al. (1996) andMorrison (2001) have measured the airfare-reduction effect of LCC entry into the primary andadjacent markets by incorporating LCC dummy variables in their econometric work. Vowles(2000) empirically analyzed the U.S. domestic air markets that includes a number of LCCs andfound that Southwest Airlines, other LCCs, and the market share of LCCs had statisticallysignificant effects on the decrease in carriers’ airfares. Alderighi et al. (2004) estimated the price* Tel.: +81 78 8036941; fax: +81 78 803 6977.
1

E-mail address: hidekim@panda.kobe-u.ac.jp
Morrison and Winston (1995), pp. 132-156.
1

equations derived from oligopoly theories and found that competitions between European LCCs
and FSCs reduced all classes of FSCs’ airfares. Pitfield (2005, 2008) studied the airfare changes
after LCC entry in a time series analysis. Goolsbee and Syverson (2005) analyzed theincumbent’s strategy to deter the threat posed by new entrants, and Oliveira and Huse (2009)
studied the effects of LCC entries on the incumbents’ responses. In a study on inter-firm rivalry
between LCCs and FSCs, Murakami (2010, forthcoming) empirically estimated the conduct
parameters of airline industries in Japan and estimated the welfare effect caused by LCCs’
entries. Methods to derive the conduct parameter of airline industries were introduced by
Brander and Zhang (1990, 1993), and have been developed by Oum, Zhang, and Zhang (1993),
and Fischer and Kamerschen (2003), who analyzed the situation in the United States, and by
Fageda (2006), who analyzed the situation in Spain. Furthermore, Fu, Lijensen and Oum (2006)
incorporated duopolistic inter-firm rivalry explicitly into their LCCs vs. full-service carriers(FSCs) competition study, and also as well as incorporating the effect of pricing behavior of an
unregulated-monopoly airport on the downstream competition between LCCs and full-service
carriers. Hofer et al. (2008) introduced the concept of “price-premium” as part of the LCC issue.
In our empirical analyses we attempted to analyze:(1) at what airfare level LCCs entered,(2) what impacts LCCs had on the airfares of incumbent carriers,(3) whether the impacts differed depending on how many LCCs existed in a market and onwhether LCC(s) entered an FSC’s hub airport or an adjacent airport,(4) whether the impacts of LCC entry continued for the years following entry,(5) the increase in social welfare, as opposed to previous studies that focused on the consumers
surplus only.
Many authors have studied the topics (1), (2), and (3), but none of the previous studies
have answered question (4) or (5). Previous authors have been interested in the “first year”
impacts of new entry on airfares and consumers surplus. The distinguishing features of thepresent study are that we revealed the impact of the second years of new entries by LCCs, andwe computed social welfare by using rigid statistical methods. In addition, we performed morerigid statistical analysis of topics(1), (2), and (3) than was performed in previous studies.
In the next section we will model the simultaneous equations for each carrier’s demand
and a pseudo-supply equation to estimate the impact of LCC entry on the incumbent carrier’s
airfares, the time effect of LCC entry on airfares, and the effect of LCC entry on social welfare.
In Section 3 we show the data, and in Section 4 we present the empirical results and performseveral analyses of the impacts of LCC entry on FSCs’ behaviors. In Section 5 we discuss
welfare implications, and in Section 6 we present concluding remarks.

2. Carrier-specific simultaneous equations
An initial activity was to construct a carrier-specific simultaneous demand and pseudosupply equation system to estimate the economic impact of LCCs’ entries. Joskow et al. (1994)
found that new carriers enter with low airfares, and incumbents respond by cutting airfares tomaintain their traffic. Dresner et al. (1996) estimated simultaneous demand and price (pseudo2

supply) equations that incorporate the directly and indirectly competing LCC dummy variables.
To ascertain the consumer welfare effect, we used the method of Dresner et al. and estimated thecarrier-specific demand equation as well as the pseudo-supply equation in log-linear forms. Our
empirical model to obtain the economic effects of low-cost entry is as follows:[Demand equation]

 

7

1

ln QiL   0   1 ln piL   2 ln INCi   3 ln POPi    4N MKTN  u iLN 3

  0,   0,   0,   0
1

2

N
4

3

[Pseudo-supply equation] 

ln piL   0  1 ln QiL   2 ln MCiL   3 ln HERFi   4 ln MCDi   5 D1LCC1i   6 D1LCC 2 i  7 D1LCR1i   8 D1LCR 2 i   9 D 2 LCC1i   10 D 2 LCC 2 i   11 D 2 LCR1i  12 D 2 LCR 2 i
22  13t LCCPE (WN ) tD   14t LCRPE (WN ) tD   15 LCCPE (WN )1T  16 LCRPE (WN )1T
t 1

t 1

  17 LCCPE ( HP)   18 LCRPE ( HP) 2D   iL
D
2

(2)

 ,   0,  ,  ,  ,  ,  ,  ,  ,  ,  ,  ,  ,  ,  ,  ,   0
2

3

4

5

6

7

8

9

10

11

t
12

t
13

14

15

16

where p iL and Q iL are the average airfare and output at route i , respectively.

17

18

INC i is theLiarithmetic average of per-capita income of route i . MC is the route marginal cost that wederived following the method used by Brander and Zhang (1990, 1993) and Oum, Zhang, andZhang (1993)2. Since many authors have used the distance as a proxy variable of marginal costand have found that this variable positively affects a carrier’s airfare, we considered bothmarginal cost and distance as explanatory variables of the pseudo-supply equation, and chose theone that fit better.
Mason et al. (1992) noted that if a firm’s structure is asymmetric (e.g., high-cost or lowcost) compared with that of competing firms, it needs a longer time for the market to reachcooperative equilibrium than if the firms are symmetric. Their discussions are followed by our
variable MCDi , which is the standard deviation of marginal cost. If MCDi is sufficiently large,
there may be at least one LCC, and carriers in a market will hardly agree on colluding.
Therefore, the parameter will have a negative effect on the market airfare, and, vice-versa, apositive effect on market output.

2 The way of deriving

MC iL is as follows: Disti 
MCiL  AC L (3) DistiL AFL where AC L is the aggregate average cost of carrier L , Dist i is the distance of route i , andAFLL is the average distance flown by airline L.
3

POPi is the arithmetic average of O/D population. MKTN is a binary variable that takes
1 for the market where N carriers compete, and the benchmark markets of this binary variable isduopoly markets. For example, MKT3 is the binary variable that takes 1 for triopoly markets
and zero otherwise. This MKTN variable is introduced to control the market size in the demand
equation, and the parameters of this variable could be positive or negative. In the negative case,for example, if too many carriers enter a market and compete for limited demand, the demandthat each carrier faces could be smaller than what each carrier would face in a duopoly market.
HERFi is the Herfindahl index, and higher HERFi means that the market is more concentrated.
Since high concentration may lead to strong market power, the parameter will be positive. The
variables u iL and  iL are error terms of carrier-specific output and pseudo-supply equations,
respectively. D1LCC1 , D1LCC 2 , D2LCC1 , and D2LCC 2 are binary variables that represent
the presence of LCC(s). D1LCC1 takes 1 if an LCC originates at the primary airport and 0
otherwise, and D1LCC 2 takes 1 if two LCCs exist in the primary airport, for example, the caseof connecting two secondary airports such as Southwest’s Houston/Hobby-Chicago Midway, andthe case of connecting primary and secondary airports such as Air Tran’s Atlanta/HartsfieldChicago Midway. The definition of a primary airport in our analysis is that it is the largest airport
where full-service carrier(s) are mainly based in a certain area, regardless of the airport size orwhether an LCC(s) is(are) present in the airport.

Similarly, D 2LCC1 takes 1 for an LCC if an LCC enters the adjacent secondary airport
such as Dallas-Lovefield and Chicago Midway airport and 0 otherwise, and D 2LCC 2 takes 1
if two LCCs enter. We assume that the positive price elasticity of demand is larger for LCCs
than for FSCs, since FSCs usually have tools to prevent passengers from switching from FSCs
to LCCs, such as mileage services. As for the pseudo-supply equation, the signs of theparameters of D1LCC1 , D1LCC 2 , D 2LCC1 , and D 2LCC 2 would be negative if LCC(s)take(s) the capacity-expanding or airfare-discounting strategy.  1 can be negative, positive, orzero. If a carrier supplies at its short-run marginal cost curve,  1 will be positive, and if it does
so on its declining average cost curve, it will be negative. If a carrier supplies at minimum
efficient scale, it will be zero.

D1LCR1 , D1LCR 2 , D 2LCR1 , and D 2LCR 2 are binary variables that represent thepresence of the competing carrier(s) of LCC(s). Like D1LCC1 and other binary variables
explained above, the former number represents either the primary airport (this is one) or thesecondary airport (this is two), and the latter number represents the number of LCC(s) thatcompete with the FSC(s). For example, D1LCR1 takes 1 for FSC(s) if it(they) originate(s) at
the primary airport and compete(s) with one LCC and 0 otherwise, and D 2LCR 2 takes 1 for(a) FSC(s) if it(they) remotely compete(s) with two LCCs that exist in the adjacent secondary
airport. The signs of the parameters of these binary variables would also be negative if rival
carriers are involved in the competition between LCCs.
LCCPE and LCRPE are binary variables that are intended for measuring how the
airfares of a newly entered LCC and its rival’s airfares change over time. In 1998, Southwest
Airlines entered the Chicago Midway – Manchester (New Hampshire), Chicago Midway –Birmingham (Alabama), and Chicago Midway – St. Louis markets. LCCPE (WN )1D takes 1 forSouthwest in Chicago Midway-Manchester. The superscript and the subscript stand for the4market type and the year from the new entry, respectively. For example, the superscript “D”
means that this route is a duopoly market and the subscript 1 means the first year ofSouthwest’s entry. LCCPE (WN )1T takes 1 for Southwest in Chicago – Birmingham andChicago – St. Louis markets. The superscript “T” means that these two routes are bigger thantriopolies. LCRPE (WN )1D and LCRPE (WN )1T take 1 for all the other carriers in these threeroutes. The year 1998 is the second year of Southwest’s entry into Chicago Midway – Jackson(Mississippi) and America West’s entry into Dallas/Fort Worth – Long Beach. Therefore,
LCCPE (WN ) 2D and LCRPE (WN ) 2D take 1 for Southwest Airlines and all the other carriers in
Chicago – Jackson, respectively. LCCPE ( HP ) 2D and LCRPE ( HP) 2D are created in the sameway. The effect of these “time dummy” variables is removed from the LCC dummy variables
such as D1LCC1 described previously.
As noted above, higher HERFi means that the market is more concentrated, and sincehigh concentration may lead to strong market power, the parameter will be positive. In addition,
HERFi and the route-basis marginal cost of a carrier, MC ik , are also endogenous variables.
Bailey, Graham, and Kaplan (1985) suggested that the market concentration is also an
endogenous variable which is determined by output, distance, and other exogenous factors suchas the existence of slot controls, and our analysis follows their suggestions. The marginal cost is
the function of output and also the independent variable of pseudo-supply equation, so
theoretically we have to use the instrument variable of marginal cost. To test the null hypothesisthat neither Ln( HERFi ) nor Ln ( MC ik ) is correlated with the error term  i , we carried out theHausman test for each variable and subsequently rejected both of the null hypotheses at the 1%
level of significance (  (21)  7.41 and 23.38 , respectively). In total, our structural equations have
five endogenous variables, but we show the demand and the pseudo-supply equations only,
because the estimated results of the remaining equations are out of the scope of this paper. We
also computed the carrier’s average cost in order to deduce producers’ profits and loss, andderived the social welfare by adding producers’ profits and consumers surplus.

3. The data

We used the data of the scheduled operations by city-pair route by firm, which are crosssectional data of the year 1998 collected from DB1A, comprised of 10% samples of the U.S.
domestic flight data. We used the data of airfares actually purchased by passengers (this, in turn,means that we omitted “zero-price airfares” and passengers who obtained these airfares from ourdataset). We omitted carriers that did not have 10% market share in duopoly markets and thosethat did not have 5% share in triopoly or greater markets. Carriers with no IATA shown in
DB1A were also omitted. These carriers are reported as carrier XX in DB1A. However, when
we computed HERFi ,we considered the market share of carrier XX as long as its market share
met the conditions explained above. Flight data represent outbound and non-connecting flightsfrom the six largest U.S. airports and their regions3: New York/Newark area, (JFK, LaGuardia,
3

We omitted the connecting passengers because, in general, LCCs do not have hub and spoke
systems. There were few cases in which an LCC competed with FSCs in the two-segment
5Newark), Washington D.C. area (National, Dulles, Baltimore), Atlanta/Hartsfield, Dallas/Fort
Worth area (DFW and Love Field), and Los Angeles. Our dataset consists of 180 duopoly
markets, 138 triopoly markets, 56 four-carrier-operating markets, 19 five-carrier-operating
markets, 7 six-carrier-operating markets, and 4 seven-carrier-operating markets. Our datacontains the routes where FSCs compete with each other as well as the routes where LCCs and
FSCs compete. The former routes are introduced as the benchmark of dummy variables that are
intended to show the impact of price wars between LCCs and FSCs, which are explained in thelast section.
In this study we were especially interested in the changes in airfare and welfare caused by
the competition between the top-three mega carriers vs. formidable LCCs such as Southwest
Airlines, Air Tran, and “mid-cost” carriers such as America West Airlines. Therefore, we
selected the following large hub airports that compete with adjacent secondary airports wherethese LCCs are based: Dallas-Fort Worth (American Airlines), Chicago O`Hare (American
Airlines and United Airlines), and two airports in Washington D.C (American Airlines andUnited Airlines and other mega carriers). We also selected Los Angeles International Airportand Atlanta/Hartsfield Airport, where LCCs and FSCs compete in an airport, to demonstrate thedifference of competitive impacts against the case where carriers compete remotely. Threeairports in the New York area, which had few flights of LCCs, are included in the dataset as thebenchmark samples to investigate the degree of impact of LCCs’ entries. This means that there
are no LCC dummy variables introduced for these three airports. We acknowledge that there
may be room for further analysis by expanding the number of data samples and updating the year,
and we will do these analyses in the next study. As for the method to determine whether a
primary airport competes with an adjacent secondary airport, we followed the market
classification done in DB1A.

Table 1The descriptive statistics of continuous variables
Mean

S.E.

Minimum

Maximum

MedianPassengers

155010.0

191486.3

10660.01143550.082185.0

Airfare

175.3

62.6

49.4

354.4

172.7

Population

3274440.1

1701878.1

161757.0

11792430.2

2958991.6

Per capita income

31907.3

2933.526047.838346.732238.4

Herfindahl index

49.8

13.7

15.3

81.9

50.4

Distance (miles)

1223.0

804.4

94

4975

1016

Note: Airfare and income are in 1998 U.S. dollars. The source of the cost data is the Air
Carrier Financial Reports, Form 41 Financial Data. Per-capita individual income andpopulation data are from Regional Accounts Data, Bureau of Economic Analysis.

connecting markets in such a way as “airport A – a mega carrier’s hub (or adjacent airport) –airport B”.
6We used the population that is filed in the Primary Metropolitan Statistical Area data
(PMSA, an urbanized county or set of counties that have strong social and economic links toneighboring communities) for each city. The cost and demographic data are also the data for theyear 1998. The descriptive statistics of continuous variables are shown in Table 1.

4. Empirical results: Carrier-specific impact of low-cost entry
We investigated how the impacts of low-cost entry on an FSC’s behaviors differ when(an) LCC(s) enter(s) a primary or secondary airport, and whether the number of LCCs affects the
FSC’s behaviors. We analyzed the inter-firm rivalry of 21 carriers, and 9 out of the 21 carriers
were LCCs. Now not a few LCCs, such as ATA 4 and Jetblue, have entered long-distancemarkets and provide small frills and airfares do not much differ from those of FSCs in certain
routes. However, around 1998, LCCs still persisted in their original business domains such asproviding no frills, serving markets of short or medium distance, issuing no mileage service, andso on. Therefore, we expect the economic impacts such as the degree of airfare-discounting may
be stronger in past years, and this is why we chose the data of 1998 to see the economic impactsof the entries of “pure LCCs”.

Table 2
Summary of parameters of LCCs and their rivals’ dummy variables in the pseudo-supply equation
S.E.

Difference
between one
and twocarrier(s) 5Parameters
One LCC at Primary Airport (D1LCC1)-0.444

0.032

None

Two LCCs at Primary Airport (D1LCC2)-0.5220.044

at 5% level

FSC at Primary competing with one LCC Airport (D1LCR1)-0.188

0.029

None

FSC at Primary Airport competing with two LCCs (D1LCR2)-0.1940.032

at 5% level

One LCC at Secondary Airport (D2LCC1)-0.549

0.064

None

Two LCCs at Secondary Airport (D2LCC2)-0.5870.068

at 5% level

FSC at Primary competing with one LCC at Secondary Airport (D2LCR1)-0.175

0.056

None

FSC at Primary competing with two LCCs at Secondary Airport (D2LCR2)-0.2170.064 at 5% levelWe simultaneously estimated equation (1) and (2) by an iterative 3SLS method and theresults are shown in Table 6 in the Appendix. Table 2 is the summary of parameters of LCCs
and their rivals’ dummy variables which are picked up from Table 6. Table 2 tells us that the
airfare wars between LCCs and FSCs led to significant discounts in LCC airfares compared withthe benchmarked FSCs.
4

ATA filed for Chapter Eleven and discontinued its operation in April 2008.
The Wald tests that tested the hypothesis that two parameters are equal were not rejected at the
5% level.

57

The results shown in Table 2 are fairly consistent with the results of Dresner et al.
(1996), who also introduced dummy variables to represent the number of competitive carriers.
Our analysis reveals that the additional entries do not statistically affect the rival’s airfares
comparing the parameter of “D1LCR1 and D1LCR2”, and “D2LCR1 and D2LCR2”. We alsofind that an LCC’s airfare level at the primary airport and that at the secondary airport do notstatistically differ. We tested the hypothesis that the parameter of D1LCC1 and that of D2LCC1
are equal, and we found that this hypothesis can be rejected with a P-value equal to 0.132 by theWald test, and this result also holds for other cases including FSCs (these are the comparisons
between “D1LCC2 and D2LCC2”, “D1LCR1 and D2LCR1”, and “D2LCR2 and D2LCR2” where
P-values of the Wald test range from 0.396 to 0.834).
Our next area of interest was to determine whether the airfare levels of each carrier
differed between primary and secondary airports. To do this analysis, we replaced all the carrierrelated dummy variables (D1LCC1, D1LCC2, D2LCC1, D2LCC2, D1LCR1, D1LCR2, D2LCR1,
and D2LCR2) of Model 1 in Table 6 in the Appendix with each carrier’s dummy variable, andre-estimated the carrier-specific structural equations using the same data and the same estimation
method. We called this Model 2, and it is also presented in the Appendix, and the summary of
the parameters of carrier dummy variables is shown in Table 3.
The method for introducing each carrier’s dummy variable was as follows. In the caseof Southwest (WN), for example, we introduced WN1, WNR1, WN2, and WNR2. WN1 takes 1 forSouthwest Airlines operating in the primary airport, and WNR1 takes 1 for the FSCs that arecompeting with Southwest at the primary airport. Similarly, WN2 takes 1 for Southwest Airlines
operating in the secondary airport, and WNR2 takes 1 for the FSCs that are remotely competingwith Southwest Airlines at the primary airport. This method of introducing carrier dummy
variables was used for all the carriers shown in Table 3, except for Spirits Airlines (NK), Tower
Airlines (FF), and Frontier Airlines (F9). These three airlines did not operate in the secondary
airports in our dataset, so we did not have NK2, NKR2, FF2, FFR2, F92, or F9R2.
Table 3 tells us that Southwest’s low-airfare strategy at the primary airports led to very
low airfares, and the same was true in the secondary airports. FSCs also lowered their airfares tocope with the competition from Southwest Airlines. The degree of declines in airfares was
statistically the same between the primary and the secondary airports, and this result held forboth Southwest Airlines and the FSCs. These results for Southwest Airlines were not necessarily
followed by other LCCs, however. It was almost common for LCCs other than Southwest
Airlines to operate with very low airfare at the primary airports. However, America West
Airlines (HP) seems to have used the low-airfare strategy only when it entered the secondary
airport (that is, Chicago Midway). America West cannot be regarded as a true LCC, because its
average airfares were almost the same as those of typical FSCs. However, since America Westis based at Chicago Midway, where other LCCs such as Southwest Airlines and Air Tran operate,
it may have to discount its airfares to compete with these carriers. We cannot recognize its lowairfare impact on the airfares of FSCs that operate in Chicago O’Hare airport. ATA (TZ),
Vanguard Airlines (NJ), which used Chicago Midway airport as a hub, and Air Tran (FL)entered the secondary airports with low airfares, but the impacts of their entries on their rivals’
airfares at the secondary airports were much weaker than that of Southwest Airlines due to theirsmall market shares at the secondary airports. Kiwi International Airlines (KP) seems to havetaken the low-airfare strategy only when it competed with FSCs directly at the primary airports,
8and when it entered the secondary airports, it took various kind of, or ad-hoc, strategies, since its
parameter in the third column and third row is comparatively large but insignificant.

Table 3Carrier-specific impacts on airfare at primary and secondary airports
LCC’s airfare at Primary/Secondary A.P.
Entry by

FSC’s airfare at Primary A.P.

Primary

SecondaryPrimary

Secondary

KP (Kiwi Int’l)-0.601 (0.183a)-0.391 (0.257)-0.223 (0.127)

0.043 (0.188)

TZ (ATA)-0.247 (0.090a)-0.149 (0.073b)

0.003 (0.052)

0.029 (0.048)

HP (America West)-0.045 (0.043)-0.611 (0.266b)

0.032 (0.031)

0.030 (0.132)

FL (Air Tran)-0.538 (0.048a)-0.486 (0.152a)-0.318 (0.044a)-0.133 (0.094)

NJ (Vanguard)-0.582 (0.092a)-0.583 (0.154a)-0.154 (0.071b)

0.185 (0.103)

NK (Spirit Air)

-0.689 (0.158a)

WN (Southwest)-0.501 (0.061a)

FF (Tower Air)

-0.660 (0.129a)-0.041 (0.087)

F9 (Frontier Air)

-0.360 (0.117a)-0.040 (0.074)-0.332 (0.133b)-0.516 (0.070a)-0.314 (0.035a)-0.320 (0.041a)

Values are the parameters of carrier dummy variables, and standard errors are in parentheses. The “a” and “b”
notations mean that they are statistically significant at 1% and 5%, respectively.

Our last area of interest in this section was whether LCCs maintained their low airfares
until the next year of entry and whether the impact of their entries on their rivals’ airfares
continued. To investigate these two issues, we performed the Wald test to test the hypothesisthat the airfares of the first year of entry equal those of the years following the entries by LCCs.
In our analysis, the parameters of dummy variables WN1 and WN2 stand for the degree ofSouthwest’s airfare discounts from the benchmark carriers’ airfares (that is, the average airfaresof FSCs that do not compete with LCCs), and these parameters are the average values for thecases in which Southwest Airlines entered the markets at least before 1996 and the years ofentries are unknown. Therefore, if, for example, we test the hypothesis that the parameter of
WN2 equal that of LCCPE (WN )1D and find that there is no statistically significant difference
between them, we can explicitly conclude that Southwest’s first-year airfare remains unchanged
over time. We tested the ten hypotheses shown in Table 4 using the Wald test.
Since both Southwest Airline and America West Airlines entered the secondary airportof Chicago (that is, Midway) in this case, we compared the time-effect dummy variables with
WN2, WNR2, HP2, and HPR2. According to the tested results of hypotheses (1), (2), (3), and (7)in Table 4, it is apparent that the airfare levels of Southwest’ first year of entry were maintainedin the second year and the following years, since we can reject no hypotheses with regard tothese cases at the 5% level of significance. The same results were obtained for the case ofSouthwest’s rivals according to the tested results of hypotheses (4), (5), (6), and (8). Therefore,
once Southwest Airlines entered secondary airports, it continued the airfare war with FSCs, andthe airfares of Southwest Airlines and FSCs remained at a low level over time according to the9tested result in (9). America West Airlines also played a role as a low-airfare carrier when it
entered Chicago Midway airport, and its airfare stayed at a low level over time due to the rivalry
with other LCCs in the same airport. However, as we mentioned in the analysis of Table 3, its
entry had no impact on the FSCs that hub in Chicago O’Hare airport, and this was true over time
according to the tested result (10) in Table 4.
Table 4
Results of the time effect test
Chi-squarestatistics

P-value(1) The parameter of WN2 equals that of LCCPE (WN ) 1D

0.029

0.865

(2) The parameter of WN2 equals that of LCCPE(WN ) 2D

0.002

0.962

(3) The parameter of WN2 equals that of LCCPE(WN ) 1T

0.151

0.698

(4) The parameter of WNR2 equals that of LCRPE(WN ) 1D

0.299

0.584

(5) The parameter of WNR2 equals that of LCRPE(WN ) 2D

0.221

0.638

(6) The parameter of WNR2 equals that of LCCPE(WN ) 1T

1.655

0.198

Tested hypotheses(7 )The parameter of LCCPE (WN ) 1D equals that of LCRPE(WN ) 2D

0.024

0.876

(WN ) 1D equals that of LCRPE(WN ) 2D

0.003

0.959

0.003

0.960

2.187

0.139

(8) The parameter of LCRPE(9) The parameter of HP2 equals that of LCCPE( HP ) 2D(10) The parameter of HPR2 equals that of LCRPE( HP ) 2D

5. Welfare effect

Our final analysis was to compute the change in consumers, producers, and social
welfare. Since we did not have the supply curve under the imperfect competition, we did notcompute the true producer’s surplus. Instead, we computed the carrier’s profit calculated by the
carrier’s route average cost, carrier’s average yields, and the number of passengers for a carrier.
The route average cost was computed by obtaining the product of the route distance and thecarrier’s unit cost (total cost / aggregate RPM). The consumers surplus was computed bycomputing the area of “trapezoids” of our demand equation (1) that are surrounded by the
benchmark airfare, lowered airfare computed from the carrier-related dummy variables,
benchmark output, and increased output due to low-cost competition.
Figure 1 illustrates the change in consumers surplus in a simple way. Trapezoid A is thegain in consumers surplus due to LCCs’ entry in the primary airport, and trapezoid C is also thegain in consumers surplus due to FSCs’ reaction to the LCCs at the primary airport (the FSCs’
airfares are higher than those of the LCCs). Similarly, trapezoids B and D show the cases ofsecondary airports. Since the market output is the sum of the outputs for each carrier, the social

10welfare is the sum of the trapezoids of LCCs and those of FSCs for the entry in the primary andthe secondary airports (that is, A+B+C+D).6
P
Benchmark price

A

B

C

D

FSC’s price at the secondary airport
FSC’s price at the primary airport
LCC’s price at the secondary airport
LCC’s price at the primary airport

0
Carrier-specific demand for LCC
at primary airportqMarket demandFig. 1
Gains in consumers surplus

Table 5
Summary of welfare effect of LCC’s entry on route bases
Gain in

Newly enteredcons. surplus

LCC's profit

Due to:Change in
FSC's profit

Gain in social
welfareAn LCC's entry into Primary Airport

5.33

1.28

-0.48

6.13

An LCC's entry into Secondary Airport

5.05

1.27

-0.34

5.98

Two LCCs' entry into Primary Airport

5.31

1.08

-0.22

6.17

Two LCCs' entry into Secondary Airport

7.29

0.82

-0.88

7.23

Sum of the Gain in Welfare

22.98

4.45

-1.92

25.51

Note: Gains are shown in millions of U.S. dollars.

Table 5 demonstrates the gain in consumers surplus, newly entered LCC’s profit, thechange in FSC’s profit, and the gain in social welfare on route bases. Since we limited thenumber of sample observations by selecting only six airport groups, the amounts themselves may
not be important. However, the results imply, overall, that the gain in consumers surplus is verylarge, and LCCs also benefited by entry.

6

Since we introduce LCC dummy variables, the intercepts of LCCs have to be lower than thoseof FSCs, but for convenience we depict them as shown in Figure 1.
11

FSCs lost profits due to the low-cost entries, and especially their losses due to thecompetition from the adjacent airport were mostly caused by the entry of Southwest. However,since the losses of FSCs were much smaller than the sum of the gain in consumers surplus and
LCC’s profits, the gain in social welfare was apparently large.

6. Summary and conclusion

Our findings regarding the economic impacts of LCCs’ entries are as follows:(1) On average, LCCs operate with very low airfares, and they involve FSCs in airfare wars.
(2) Investigating further, we find that LCCs’ entry impact on FSC airfares depends on
individual LCCs. Only Southwest Airlines always involves FSCs in airfare wars, regardlessof whether it enters primary or secondary airports.
(3) Additional entries of LCC(s) do not affect the degree of airfare wars.
(4) The type of airport, primary or secondary, does not affect the degree of airfare wars when
LCC(s) enter market, on average.
(5) Once Southwest Airlines enters secondary airports, a lasting airfare war with FSCs occurs,
and the airfares of Southwest Airlines and the FSCs remain at a low level over time.
(6) Our findings imply that the gain in social welfare due to LCCs’ entries is substantial, and
90% of welfare gains come from the gain in consumers surplus and the rest comes from theprofit of LCCs. The results also imply that FSCs do not earn profits, which seems to be dueto their high average cost of operation.
Among these findings, (5) and (6) are the most important ones. Southwest Airlines has a large
market share in many cases, so its presence has a big impact on its rivals’ airfares, and this lowairfare impact lasts a long time. On the other hand, other LCCs do not have strong impacts,
especially on rivals at remote airports, and this is due to the fact that these LCCs sometimes have
only a limited number of slots (sometimes their market shares are around 10%). As long as theentries of LCCs generate a gain in social welfare and this gain is accumulated over time, it may
be an important policy to assign more slots to LCCs.
The limitation of this study is, as already mentioned that we need to update the dataset
to a more recent one and increase the number of samples to minimize the possible selection bias.
This will be done in a future study.
[2010.5.26 981]
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Appendix

Table 6
Estimated result of carrier-specific structural equations
Demand Equation
Model 1VARIABLES

Parameter

SE

Model 2
P-VALUE

ParameterSE

P-VALUE

Airfare-1.164

0.115

0.000

-1.290

0.143

0.000

Per-capita income

1.966

0.330

0.000

1.588

0.392

0.000

Average population

0.760

0.063

0.000

0.849

0.064

0.000

Dummy for triopoly market-0.079

0.076

0.299

-0.127

0.078

0.103

Dummy for 4-firm market-0.151

0.094

0.111

-0.183

0.097

0.059

Dummy for 5-firm market

0.086

0.118

0.735

0.088

0.121

0.467

Dummy for 6-firmmMarket-0.593

0.184

0.001

-0.650

0.187

0.001

Dummy for 7-firm market-0.583

0.238

0.014

-0.543

0.243

0.025

Dummy for LCCs at primary AP-0.495

0.118

0.000

-0.581

0.114

0.000

Dummy for LCCs at econdary AP-0.265

0.159

0.095

-0.310

0.153

0.042

Constant

1.674

1.212

0.167

3.566

1.297

0.006

Pseudo-Supply Equation
VARIABLES

Parameter

OutputRoute marginal cost

7

SE

P-VALUE

ParameterSE

P-VALUE

0.151

0.025

0.000

0.077

0.021

0.000

0.412

0.017

0.000

0.338

0.070

0.000

-0.039

0.028

0.161

0.149

0.037

0.000

Diversity of MC
Herfindahl index

0.161

0.039

0.000

D1LCC1-0.444

0.032

0.000

D1LCC2-0.522

0.044

0.000

D1LCR1-0.188

0.029

0.000

D1LCR2-0.194

0.032

0.000

7 We used distance for Model 1 as a proxy of marginal cost, and it is treated as an exogenous

variable.
14

D2LCC1-0.549

0.064

0.000

D2LCC2-0.588

0.068

0.000

D2LCR1-0.175

0.056

0.002

D2LCR2-0.217

0.064

0.001

KP at Primary Airport-0.601

0.183

0.001

KP at Secondary Airport-0.391

0.257

0.128

KP's Rival at Primary Airport-0.223

0.127

0.079

KP's Rival at Secondary Airport

0.043

0.188

0.818

TZ at Primary Airport-0.247

0.090

0.006

TZ at Secondary Airport-0.149

0.073

0.043

TZ's Rival at Primary Airport

0.003

0.052

0.957

TZ's Rival at Secondary Airport

0.029

0.048

0.542

HP at Primary Airport-0.045

0.043

0.292

HP at Secondary Airport-0.611

0.266

0.022

HP's Rival at Primary Airport

0.032

0.031

0.306

HP's Rival at Secondary Airport

0.030

0.132

0.816

FL at Primary Airport-0.538

0.048

0.000

FL at Secondary Airport-0.486

0.152

0.001

FL's Rival at Primary Airport-0.318

0.044

0.000

FL's Rival at Secondary Airport-0.133

0.094

0.155

NJ at Primary Airport-0.582

0.092

0.000

NJ at Secondary Airport-0.583

0.154

0.001

NJ's Rival at Primary Airport-0.154

0.071

0.031

NJ's Rival at Secondary Airport

0.185

0.103

0.074

NK at Primary Airport-0.689

0.158

0.000

NK's Rival at Primary Airport-0.332

0.133

0.012

WN at Primary Airport-0.501

0.061

0.000

WN at Secondary Airport-0.516

0.070

0.000

WN's Rival at Primary Airport-0.314

0.035

0.000

WN's Rival at Secondary Airport-0.320

0.041

0.000

FF at Primary Airport-0.660

0.129

0.000

FF's Rival at Primary Airport-0.041

0.087

0.637

F9 at Primary Airport-0.360

0.117

0.002

F9's Rival at Primary Airport-0.040

0.074

0.586

15

LCCPE(WN)1 Duopoly-0.641

0.289

0.027

-0.560

0.261

0.032

LCRPE(WN)1 Duopoly-0.076

0.289

0.793

-0.179

0.257

0.485

LCCPE(WN)1 Triopoly-0.633

0.207

0.002

-0.588

0.196

0.003

LCRPE(WN)1 Triopoly-0.379

0.131

0.004

-0.473

0.126

0.000

LCCPE(WN)2 Duopoly-0.602

0.289

0.038

-0.504

0.259

0.051

LCRPE(WN)2 Duopoly-0.201

0.291

0.488

-0.198

0.258

0.443

LCCPE(HP)2 Duopoly-0.793

0.290

0.006

-0.630

0.256

0.014

LCRPE(HP)2 Duopoly-0.532

0.293

0.069

-0.459

0.259

0.076

Constant

1.257

0.254

0.000

2.744

0.371

0.000

Statistics of Model 1

System R-Square=0.560

Statistics of Model 2

System R-Square=0.663

16