Code Sharing and Merger: Continental, Delta and
Northwest
Caixia Shen1
Shanghai University of Finance and Economics
January 2015
Abstract
When Delta joined code sharing between Continental and Northwest in 2003, these three legacy
carriers formed the only three-way U.S. domestic code sharing partners. In 2008, Delta and
Northwest announced to merge. The merger was granted by Department of Justice six months
later. This paper analyzes the effects of the three-way code sharing and the effects of the merger
between these two previous code sharing partners. I find both competitive effects and anticompetitive effects of code sharing, i.e. mean market price decrease in non-hub markets and price
increase in hub-to-hub markets. Meanwhile, passenger volume increases significantly. Moreover,
rivals’ responses are to move price in the same the direction as code sharing partners. I find an
increase in HHI and a reduction in traffic after merger. Specifically, HHI increases for over 1,000
points in markets where merging airlines were either duopolist or with a third carrier. Pre-merger
code sharing markets experience an increase in HHI due to the disappearance of code sharing
contract. Low cost carrier entry mitigates merger effects.
1
shencaixia@gmail.com. Address: 777 Guoding Road, Yangpu District, Shanghai, China 200433. I think Sambuddha
Ghosh, Jordi Jaumandreu, Marc Rysman for their support. I also thank the editor and two anonymous referees for
their comments. All errors are my own.
1
Except American, five of the six legacy carriers, Continental, Delta, Northwest, United and US
Air, have all been involved in code sharing among one another in 2003. A code sharing contract
involves two parties: marketing carrier and ticketing carrier. The controversy about code sharing
among these legacy airlines originates from the fact that the marketing carrier sets the prices for
code-sharing tickets which are operated by the operating carrier. The concern of the anticompetitive effects comes from the significant number of overlapping routes among partners.
Code sharing between one legacy carrier and one small regional carrier has been extensively
practiced for decades in U.S. domestic markets. The following pairs of legacy carriers announced
their intention to create alliance in early 1998-Continental and Northwest; Delta and United; and
American and US Airways. Only the Continental and Northwest code sharing were approved by
Department of Justice in 1998. Five years later, Department of Justice grants the two alliances:
CO/DL/NW and US/UA.
The related literature for code sharing starts with two theoretical papers: Brueckner (2001) and
Park (1997). Brueckner (2001) build up a theoretical model of code sharing and find that code
sharing increases competition on interline city pair markets but reduces competition on hub-tohub city pair markets. Park (1997) examine the effects on firms' outputs and profits, air fare, and
economic welfare of two types of airline alliances: complementary and parallel alliances. He
finds that the complementary alliance is likely to increase economic welfare, while the parallel
alliance decreases it.
This paper tries to test the theory presented in the above two papers by analyzing the three way
code-sharing agreement among Northwest, Continental and Delta. One of the contribution of this
paper is to separately analyze the code-sharing effects on prices between hub-to-hub markets and
non-hub markets. A hub-to-hub market means that the origin airport is a hub for one partner and
the destination is a hub for another partner. I find that code sharing creates anti-competitive
effects, i.e. the mean market price is increased by 4.2% in code sharing markets post-codesharing, while non-hub markets experiencing 1.5% decrease in the average price. This finding is
consistent with previous theoretical prediction (Brueckner 2001), although most empirical
research suggests competitive effects of code sharing between large airlines (for example, Ito and
Lee 2007).
To test Park (1997), I separately look at nonstop tickets and the ones with connections. Nonstop
code-sharing tickets are the parallel ones and tickets with connections are complementary. I find
that in non-hub markets the percentage decrease in average prices is more for nonstop tickets
than that for tickets with connections. Also, I find that DL/NW and DL/CO code sharing
contracts increase traffic by 8% on average, with around 5% increase in passengers on nonstop
flights. The evidence that code-sharing decreases prices and increases passengers on nonstop
flights may not support Park (1997). However, it may also shed lights on the differences between
international alliance and U.S. domestic alliance.
The finding in this paper that the existence of anti-competitive effects in hub-to-hub markets is
somewhat novel compare to the previous results in the literature. The previous empirical work
includes Ito and Lee (2007), Gayle (2008) and Armantier and Richard (2006), suggesting no
evidence for anti-competitive effects due to the NW/DL/CO agreement. The difference between
2
this study and the previous ones is that I look at hub-to-hub markets separately. This paper finds
the competitive effects of NW/DL/CO in non-hub markets, which is consistent with the previous
findings.
This paper also analyzes the effects of merger between Delta and Northwest in 2008. This has
raised interesting questions as they were code sharing partners prior to the merger.
Topics on U.S. Airline merger can be traced back to Borenstein (1990). He evaluates the anticompetitive effects of two airline mergers: Northwest/Republic and Trans World/Ozark in 1986.
Borenstein finds that each merger induces substantially increased concentration at a major hub;
evidence suggesting both price increase and capacity reduction. Kim and Singal (1993) examines
price change associated with 14 airline mergers during 1985-1988. Overall they find that both
merging and unmerging airlines significantly increased their fare after merger. More recently,
Benkard, Bodoh-Creed and Lazarev (2010) simulates the dynamic effects of horizontal mergers.
One of their findings is that the initial anti-competitive effects of merger should be mitigated by
low cost carrier entry. Luo (2013) analyzes the price effect of merger between NW/DL, and Lee
(TAMU working paper) also addresses the merger effects on prices, considering all U.S. airline
mergers between 2006 and 2010.
Another contribution of this paper to study the NW/DL merger, taking into account the codesharing effects. As we expect, this merger creates an increase in market concentration and a
decrease in passenger volume. The results also suggest that the disappearance of code sharing
due to merger augments HHI. This result supports the competitive effects of code sharing. I find
that the increase in HHI (Herfindahl-Hirschman Index) varies across markets, according to the
pre-merger competitiveness. More specifically, I find an increase of over 1,000 points in HHI in
markets that previously had Delta and Northwest either competing each other or with a third
carrier. The increase in HHI is lower when pre-merger competitiveness is higher. The main
difference of this paper from Lee (TAMU, working paper) and Luo (2013) is that I analyze codesharing together with merger. When measuring the merger effect, I look at different markets with
and without code-sharing before merger, and markets with low cost carrier entry.
Finally, my finding supports the evidence from Benkard, Bodoh-Creed and Lazarev (2010). Low
cost carriers’ entry plays a role in mitigating the anti-competitive merger effects. However, I find
that the anti-competitive merger effect has a larger magnitude, at least in markets which had high
market concentration before merger. The entry of low cost carrier can reduce more than half of
anti-competitive effect by merger in the monopoly or duopoly markets.
This paper is organized as follows. In section 2, I list the timeline of CO/DL/NW code sharing
and merger between DL/NW. In section 3, I report the data source. In section 4, I summarize
statistics on variables. Section 5 contains the results, and Section 6 concludes.
2 The timeline of Continental/Northwest/Delta Code Sharing and
merger between Delta and Northwest
The timeline of code sharing among Continental, Northwest and Delta is listed below:
3


1998 Code sharing between CO/NW
2003 Code sharing among CO/NW/DL
Code sharing between Continental and Northwest started in 1998. In June 2003 Delta join the
code sharing and formed the only three-way U.S. domestic code sharing, following another code
sharing between legacy airlines: United and US Air in January 2003.
On April 14, 2008, following merger talks first reported on January 15, 2008, both Delta and
Northwest Airlines announced that they would merge to create the world's largest airline under
the Delta name. On September 26, 2008 it was announced that both Delta and Northwest's
shareholders had approved the merger. After a six-month investigation, government economists
concluded the merger would likely drive down costs for consumers without curbing competition.
On October 29, 2008, the United States Department of Justice approved the merger between
Delta Air Lines and Northwest. Below listed the steps of transition of Northwest into Delta:




In airports where Northwest and Delta operate in separate terminals, one airline moves to
another's terminal. For example, in Los Angeles International Airport, NWA, which had
a smaller operation, moved into Delta's Terminals 5 and 6 from its previous home in
Terminal 2 on June 30, 2009
Northwest WorldPerks was merged into Delta SkyMiles on October 1, 2009
As of 31 December 2009, 216 of NWA's 303 aircraft have been painted in Delta livery.
Northwest's three US Hubs have been fully rebranded and gates have been consolidated
along with other US airports. Some routes are being transferred to Delta from Northwest
and to Northwest from Delta depending on the route.
Operating certificates were merged on December 31, 2009. Reservations systems were
merged on January 31, 2010; officially retiring the Northwest brand.
3 Data
The source of data for this study is the Airline Origin and Destination Survey (DB1B), which is
published by the U.S. Department of Transportation (DOT).2 This is a 10% random sample of
airline tickets from U.S. reporting carriers. Each observation contains detailed information on fare,
ticketing/operating carriers for each coupon, origin/connecting/destination airports, and the
number of passengers travelling on the itinerary, in a given quarter for every year. The sample
selection criteria are listed below.
The sample observations are selected by the following criteria: 1) tickets within U.S. continental;
2) roundtrip tickets with at most four coupons; 3) ticket prices, which are adjusted by CPI into
2002 value3, falling in between $25 and $2,000; 4) ticketing/operating carriers are both U.S.
carriers for each segment; 5) airport pairs (i.e. markets) which have 10 passengers per day (90 in
2
3
http://www.transtats.bts.gov/databases.asp?Mode_ID=1&Mode_Desc=Aviation&Subject_ID2=0
http://data.bls.gov/cgi-bin/cpicalc.pl
4
one quarter); 6) tickets purchased within quarter I in 2002 and 2004 for code sharing analysis,
quarter I in 2008 and 2010 for merger analysis.4
3.1 Market level statistics of CO/DL/NW Code Sharing
Table 1 shows the percentage of code-shared markets. The sample consists of 4,487 common
markets in both 2002 and 2004 where at least10 passengers travelling per day. Since Continental
and Northwest started code sharing in 1998 and Delta joined in 2003, I count the number of
markets in which code sharing tickets between Delta and Continental and between Delta and
Northwest are observed. 1,572 markets (35% of all markets) involve code sharing with Delta, and
2,560 markets (57% of all markets) involve the three-way code sharing.
Since US Airways and United also started code sharing in 2003, it is necessary to include this
alliance into the analysis. For markets where both the three-way code sharing and US-UA code
sharing take place, the competitive effects of alliances are expected stronger. 1,735 markets (39%
of all markets) are code shared by United and US Airways. The overlapping markets with both
US-UA code sharing and DL-CO (or DL-NW) are 726, accounting 16% of all markets.
Table 1: Percentage of code-shared markets
No. Percentage %
Code-shared Markets (CO-DL-NW)
2560 57%
Code-shared Markets (DL)
1572 35%
Code shared Markets (US-UA )
1735 39%
Code shared Markets (US-UA and DL ) 726 16%
Total No. Markets
4487 100%
In order to understand better the incentives of the three-way code sharing, I report in table 2 which
CO/DL/NW alliance’s hub-to-hub markets are code-shared. Hub-to-hub markets are the airport
pairs when the origin airport is one code sharing partner’s hub and the destination airport is another
partner’s hub. Delta has hub airports: ATL, CVG, and SLC; Continental has hub airports: CLE,
EWR and IAH; Northwest has hub airports: DTW, MEM and MSP.
Table 2: Hub-to-Hub Code Sharing Markets
CO-DL
DL-NW
CO-NW
CLE-SLC and SLC-CLE
ATL-MEM and MEM-ATL CLE-MSP and MSP-CLE
CLE-ATL and ATL-CLE
ATL-MSP and MSP-ATL
EWR-DTW and DTW-EWR
EWR-SLC and SLC-EWR CVG-MSP and MSP-CVG EWR-MSP and MSP-EWR
EWR-ATL and ATL-EWR SLC-DTW and DTW-SLC MEM-EWR and EWRMEM
IAH-CVG and CVG-IAH SLC-MSP and MSP-SLC
IAH-MEM and MEM-IAH
IAH-ATL and ATL-IAH
CVG-DTW
IAH-MSP and MSP-IAH
4
According to the merger timeline, the first quarter seems to be a reasonable sample period.
5
IAH-SLC and SLC-IAH
CVG-EWR
ATL-DTW
IAH-DTW and DTW-IAH
All hub airports are observed code sharing activities. Notice that the market is defined as
directional airports pair. Most of routes between each airline’s hubs are code-shared in both
directions with a few exceptional cases. For example, Delta and Northwest code-shared in CVGDTW market, but not in DTW-CVG. In the next section, price and traffic changes in hub-to-hub
markets after code sharing will be analyzed in details.
Since we already know hub-to-hub airports are mostly code-shared, to understand the incentives
of code sharing, it is interesting to know whether hub-to-nonhub markets are also code-shared. In
practice, I define a market to be code-shared if I observe at least one code-shared segement/trip
leg within this market. 32% of observed code-shared markets falls into the category of hub-to-nonhub. In other words, most code-shared markets do not involve hub airports of the alliances. Hence,
it is important to summarize which routes are code-shared.
3.2 Route level statistics of CO/DL/NW Code Sharing
Table 3 reports code sharing details at the route level. Northwest operates on 439 and 472
directional routes for Continental and Delta, respectively. Continental operates on 245 and 269
directional routes for Delta and Northwest, while Delta operates on 238 and 283 directional routes
for Continental and Northwest.
The statistics mentioned above suggest that Northwest operates on almost double the number of
directional routes as its partners. While Continental and Delta operate evenly for their partners,
Northwest plays dominate role in operating. In other words, Continental and Delta play equally
strong roles as ticketing carriers in this three-way code sharing agreement.
Table 3: Number of Code Sharing Routes
CO(TK) DL(TK) NW(TK)
CO (OP)
245
269
DL (OP) 238
283
NW(OP) 439
472
Note: OP means operating carrier; TK means ticketing carrier.
It is now important to consider the distribution of the code-shared routes. How many of these codeshared routes pass through at least one hub airport? Table 4 illustrates the distribution. Consistent
with the incentive to extend the networks of alliance partners, I observe most code-shared routes
involve at least one hub as an end-point airport. More specifically, 100% of code-shared routes
between Continental and Northwest have at least one hub as end point airport. This happens
possibly because code-shared routes are well established and developed over time, and the CO/NW
code-sharing started in 1998. Between Delta and Continental, around 90% of the routes are
involving at least one hub. Within Delta and Northwest, the latter operates more and most airports
are Northwest’s hub.
6
Table 4: Distribution of Code Sharing Routes
CO(TK)- CO(TK)- DL(TK)- DL(TK)DL(OP) NW(OP) CO(OP) NW(OP)
Origin=OP_HUB
30%
50%
44%
35%
Destination=OP_HUB
31%
49%
43%
34%
Origin=TK_HUB
6%
2%
4%
2%
Destination=TK_HUB
23%
1%
3%
3%
Origin&Dest=OP_HUB 2%
2%
2%
1%
Origin&Dest=TK_HUB 0%
0%
0%
0%
Total Percentage for 88%
100%
92%
73%
having at Least One
Hub
Total Routes Number
238
439
245
472
NW(TK)CO(OP)
50%
50%
1%
1%
2%
0%
100%
NW(TK)DL(OP)
27%
28%
5%
33%
1%
1%
91%
269
283
Another observation is that the code-shared routes are generally involved with just one hub not
two. The pattern is that the operating carrier brings passengers into (or from) its own hub from
(or into) a non-hub airport (neither of operating carrier nor of ticketing carrier).
For each pair of code-sharing alliances, Table 5 reports the number of directional where they
overlap. In particular, the diagonal shows the total directional routes for each pair. Among the
routes in which Northwest operates for both Continental and Delta, there are over 60% (290) routes
overlap. Continental operates 90 overlapping directional routes for both Delta and Northwest,
while Delta only operates on 57 similar routes. When the role of operating and ticketing switches,
Delta and Northwest operate on 72 overlapping directional routes; Continental and Delta engages
on 39 directional routes and Continental and Northwest only overlaps on 11 directional routes.
Table 5: Number of Overlapping Code Sharing Routes
CO(TK)- CO(TK)- DL(TK)- DL(TK)- NW(TK)- NW(TK)DL(OP) NW(OP) CO(OP) NW(OP) CO(OP)
DL(OP)
CO(TK)-DL(OP)
238
CO(TK)-NW(OP)
439
DL(TK)-CO(OP)
39
245
DL(TK)-NW(OP)
290
472
NW(TK)-CO(OP)
11
90
269
NW(TK)-DL(OP) 57
72
283
3.3 Market structure before DL/NW merger
To analyze the merger effects, it is necessary to check overlapping routes between Continental
and Northwest before merger. From the timeline information, the merger is announced in April
2008 and the operating certificates were merged on December 31, 2009. I use first quarter data in
2008 and 2010. There is no operating carrier observed under Northwest’s name in 2010 data.
To identify the change in competition between carriers before and after merger, I first report in
Table 6 the11 big airline carriers observed in 2008. The first six legacy carriers; Alaska Airlines,
7
and four low cost carriers comprise the rest. Southwest is the largest low cost carriers, which
plans to acquire its rival Air Tran in 2011.
The markets most effected by Delta/Northwest merger are those in which merging airlines were
the only carriers or had only one competitor before merger. Table7 reports the number of such
markets. Delta sells tickets in 2,515 markets, of which 38 markets are monopoly. Northwest
markets in 1,204 markets with 35 monopoly markets. Delta and Northwest do not overlap in
many markets, only 8 duopoly markets. In 57 markets Delta and Northwest compete with a third
carrier; 147 markets in which merging carrier compete with another two carriers. I expect
markets with less competitor pre-merger intend to increase more in price post-merger.
Table 6: The Eleven Big Carriers
Carriers
American (AA)
Continental (CO)
Delta (DL)
Northwest (NW)
United (US)
US Airways (UA)
Southwest (WN)
Alaska (AS)
JetBlue (B6)
Air Tran (FL)
Frontier (F9)
It is also interesting to analyze whether the markets with code sharing pre-merger would become
less competitive. 1,104 markets have code sharing between Delta and Northwest in 2008.
Delta
Northwest
DL+NW
Codeshare
Table 7: No. of Competitors for Merging Airlines in 2008
No. of Competitors
Total No.
0
1
2
3
4
5
6
Markets
2515
38
293
575
570
458
300
187
1204
35
108
203
243
222
180
131
748
8
57
147
174
155
125
62
1104
7
74
62
20
4 Model
4.1 Code Sharing regression: variable definitions and statistics
I use method of regressions on variables in first differences. The dependent variables in code
sharing regressions are the percentage changes in fares and traffic from the pre-alliance period to
post-alliance period for each market. That is, the dependent variables in the model are:
8
1) ln(average fare post-codesharing/average fare pre-codesharing)5
2) ln(total traffic post-codesharing/average traffic pre-codesharing)
The explanatory variables are as follows:
1)
2)
3)
4)
code sharing dummy for Continental, Delta and Northwest
code sharing dummy for United and US Airways
entry dummy by LCC6
dummy for CO-DL-NW alliance airlines’ hub-to-hub markets
First, the main advantage of using first difference regression is to steer clear off the endogeneity
issue. Any problem from missing variables which are constant in both years will disappear. Second,
any constant variable (for example, market distance) across two years do not to be included into
the regression.
Code sharing dummy is to indicate which markets experience the three-way code sharing effects.
Entry dummy by LCC is defined as one if there is at least 5% market share of low cost carriers
after code sharing and less than 5% before. This entry dummy is treated as exogenous. The hubto-hub market dummy is to test whether the code sharing effects are different in CO/DL/NW
alliance’s hub-to-hub airports. Previous literature in theory suggested hub-to-hub may have anticompetitive effects.
Finally, I separately calculate the dependent variables for nonstop tickets. It is interesting to
decompose the code sharing price effects for nonstop tickets. Whether the competitive price effect
of code sharing comes from nonstop tickets or connecting tickets shall be tested.
Table 8: Variable Statistics-Code Sharing
Variable
Log Ratio Fare
Log Ratio Fare-CO/DL/NW
Log Ratio Fare-rival
Log Ratio Nonstop Fare
Log Ratio Nonstop FareCO/DL/NW
Log Ratio Nonstop Fare-rival
Log Ratio Passengers-All
Log Ratio Passengers-Nonstop
CO-DL-NW Code sharing
US-UA Code sharing
Code Sharing
Markets
Mean SD
-.0110 .1696
-.0003 .2101
.0043 .1989
-.0295 .2320
-.0315 .2235
Non-Code
Sharing Markets
Mean
SD
.0072
.1813
.0117
.3071
.0194
.2096
.0013
.2181
-.0104
.2253
All Markets
Mean
.0008
.0070
.0140
-.0078
-.0196
SD
.1775
.2732
.2060
.2228
.2247
-.0262
.0903
.0800
1.000
.4618
.0034
.0057
.0065
.0000
.3461
-.0040
.0354
.0283
.3503
.3866
.2321
.5552
.8908
.4771
.4870
.2448
.5632
1.007
.0000
.4986
5
.2272
.5487
.8357
.0000
.4758
Passenger weighted fare percentage change.
6. Low cost carriers include JetBlue (B6), Frontier (F9), AirTran (FL) and Southwest (WN).
9
LCC Entry
Hub-to-Hub Markets
.0693
.0318
.2541
.1755
.0319
.0000
.1757
.0000
.0450
.0158
.2073
.1248
I construct three versions of the dependent variables: 1) all carriers; 2) CO/DL/NW alliance carriers
and 3) its rival carriers.
The statistics summary of variables in code sharing analysis regression is reported in table 8. The
absolute value of ticket fares in 2004 are adjusted by CPI into 2002 values. The overall ratio fare
suggests 1% fare reduction in code sharing markets with almost 1% increase on average in noncode sharing markets. In CO/DL/NW code sharing markets, partners’ average fare in each market
slightly decreased, while their rivals’ average market fare slightly increased. Nonstop tickets fare
decreases are more significant. Within alliance markets, nonstop tickets fares are reduced on
average 3%, which is equal to $11 given the average nonstop ticket price is 370 in 2004. In nonalliance markets, nonstop ticket prices slightly goes up after code sharing.
The interesting observation is that the alliance partners CO, DL and NW reduce prices for nonstop
flights for 3% and 1% in code sharing and non-code sharing markets, while their rivals only
decrease nonstop flight tickets in code sharing markets for 2.6% but not non-code-sharing markets.
From this statistics, we observe some rival response to the competition induced by the three-way
code sharing. The later analysis will address more results on this point.
The overall traffic/passenger is increased by 3.5% after code sharing. The incremental is 9% in
code sharing markets. 8% of this increase is contributed by nonstop flight passengers. The threeway code sharing effect on traffic is significant and large as non-code sharing markets experience
less than 1% increase at the same time.
The code sharing dummy is 0.35; 1,572 markets. I only count markets which have code sharing
with CO/DL and DL/NW. The reason to exclude markets with code sharing between Continental
and Northwest is that this alliance is existed since 1998. To measure code sharing effects in 2004
compared that in 2002, Delta is the only new partner in the three-way alliance.
LCC entry happens in 4.5% of all markets in 2004, i.e. 202 markets.7 7% of code sharing markets
has LCC entry; 110 markets. The alliance hub-to-hub markets are 50 in total, which is 1.5% of all
markets. For this dummy variable, I only count hub-to-hub markets in which code sharing happens.
The goal is to test whether code sharing has different price effects in hub-to-hub markets.
4.2 Merger regression: variable definitions and statistics
First, I decompose the average change in market concentration ratio (HHI: Herfindahl–
Hirschman Index) before and after merger. More specifically, I consider a set of markets which
possibly have different changes in HHI. These markets are separated by the number of
competitors to Delta and Northwest in 2008 (before merger). The set of markets include, markets
7 The definition of LCC entry dummy is that in the market there are at least 5% of passengers fly on Low cost
carriers post-alliance while there is less than 5% passengers or no passenger fly on low cost carriers pre-alliance.
10
in which existing the following number of competitors to Delta and Northwest in 2008 (premerger) 1) zero or one; 2) two; 3) three; 4) four; 5) five; 6) six; 7) seven and markets where there
is 8) code sharing between Delta and Northwest; 9) low cost carrier entry. That is, the dependent
variable is:
1) Net Change in market HHI between 2010 and 2008.
The explanatory variables are markets in 2008 where:
1)
2)
3)
4)
5)
6)
7)
8)
9)
Delta and Northwest have zero or one competitor
Delta and Northwest have two competitors
Delta and Northwest have three competitors
Delta and Northwest have four competitors
Delta and Northwest have five competitors
Delta and Northwest have six competitors
Delta and Northwest have seven competitors
Delta and Northwest codeshare
Entry of low cost carriers
Second, I project the percentage changes in fares and traffic from the pre-merger to post-merger
onto the change of HHI. The dependent variables are
1) ln(average fare post-merger/average fare pre-merger)8
2) ln(total traffic post-merger/average traffic pre-merger).
Table 9: Variable Statistics-Merger
Variable
Mean
Change in HHI
-.0055
Log Ratio Fare
-.0207
Log Ratio Fare- DL/NW
-.0296
Log Ratio Fare-rival
-.0195
Log Ratio Nonstop Fare
-.0101
Log Ratio Nonstop Fare-DL/NW -.0350
Log Ratio Nonstop Fare-rival
-.0035
Log Ratio Passengers-All
-.1118
Log Ratio Passengers-Nonstop
-.2192
DL/NW Code Sharing
.2402
Low Cost Carrier Entry
.0644
No. Competitor Variable
Comp_0&1
.0141
Comp_2
.0319
Comp_3
.0378
Comp_4
.0337
8 Passenger weighted fare percentage change.
11
SD
.1375
.1689
.2811
.1735
.2204
.2494
.2108
.3153
.7505
.4272
.2454
.1180
.1759
.1908
.1805
Comp_5
Comp_6
Comp_7
Total No. Markets
.0271
.0134
.0043
4596
.1626
.1153
.0658
Table 9 reports the summary of statistics of variables in the merger regression. On average, the
change in market HHI is close to zero (decreased by 55 points), which means overall the market
structure does not change significantly despite of the merger between Delta and Northwest. It has
2% fare reduction across all markets, with Delta and Northwest’s fare decreased 3%. Delta and
Northwest nonstop flight fare reduced by 3.5% while their rivals’ stay still. The total passenger
volume reduced by 11%, and most strikingly nonstop flights passengers decreased by 22%. Since
the sample period is first quarters in 2008 and 2010, the large reduction in nonstop passengers may
relate to the recent economic recession. 24% of markets experienced some level of code sharing
between merging airlines in 2008. Low cost carriers enter in about 6% of markets. Similar
definition of LCC entry dummy in code sharing regression applies here.
The number of markets with different number of competitors to merging airlines before merger
has reported in Table 7. Here I repeat it in dummy framework. About 1.4% markets with zero or
one competitor; 3-4% markets with two or three or four or five competitors; 1.3% markets with 6
competitors and 0.4% markets with 7 competitors.
5 Results
Regression results from code sharing and merger analysis will be presented separately.
5.1 Effects of CO/DL/NW Code Sharing
Table 10 reports the results from regressions on average fares in all tickets for the CO/DL/NW
three-way alliance. The first column reports the results from a model which only includes a code
sharing dummy for CO/DL/NW alliance. I find that the three-way alliance reduce 2% on ticket
price overall, which is equal to $7 given the average market price is $355 in 2004. The second
column takes into account the price effects from US/UA alliance and LCC entry; 3% reduction
on average. For over 700 markets in which both code sharing alliances in place, the average
markets price decreases by 4.5%, equivalently $16. However, there is no evidence showing LCC
entry reduces air fares. The coefficient is not significant neither large in magnitude.
The most interesting result in price regression is that CO/DL/NW’s hub-to-hub market price has
significantly increased since code sharing. See Column (3). The coefficient is 4.2%. Taking into
account the code sharing dummy has negative coefficient 1.5%, the overall price effect on
CO/DL/NW alliance partners’ hub-to-hub markets is positive slightly less than 3%.
The anti-competitive effects are somewhat novel. As far as I know, there has been no empirical
analysis which documented these effects, although theoretical literature has been shown that
code sharing between international airline alliances may hurt consumers in hub-to-hub markets.
From rivals’ response analysis in Column (9), the price increase in hub-to-hub markets mainly
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coming from CO/DL/NW’s rivals’ price increase. The regression results suggest 13% increase in
rivals in hub-to-hub markets, while alliance partners do not increase (or decrease) prices in these
markets (compare to Column (6)).
Another finding is the rivals’ responses are competitive to code sharing partners’ pricing
strategies. Rivals also decrease prices in code sharing markets. This is one important source of
competitive effects of CO/DL/NW code sharing agreement.
Table 10: Code Sharing Price Effects Results – All Tickets
Overall
CO/DL/NW
(1)
(2)
(3)
(4)
(5)
(6)
(7)
CS
-.018* -.015* -.015* -.012
-.011
-.012
-.015*
dummy
(.005) (.005) (.005) (.008) (.009) (.009) (.006)
USUA
-.030* -.030*
-.026* -.026*
(.005) (.005)
(.009) (.009)
LCC
.001
.001
.022
.022
(.013) (.013)
(.020) (.020)
Hub-to.042**
.023
hub
(.025)
(.039)
Intercept .007*
.017* .017* .012*
.021* .021*
.019*
(.003) (.004) (.004) (.005) (.007) (.007) (.004)
Rivals
(8)
-.015*
(.006)
-.015
(.014)
.019*
(.004)
(9)
-.019*
(.006)
-.019*
(.015)
.130*
(.029)
.020*
(.004)
Table 11 reports code sharing price effect results for only nonstop flight tickets. The competitive
price effects on nonstop tickets are stronger than overall. Column (1) & (2) report that the
CO/DL/NW alliance reduces air fare by 3% on average, while almost 7% combining with US/UA
alliances. Given the average nonstop ticket is $395 in 2004, the competitive effects from both
alliances reduces $28 on each nonstop ticket on average.
Table 11: Code Sharing Price Effects Results – Nonstop Flight Tickets
Overall
CO/DL/NW
Rivals
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
CS
-.030* -.026* -.029* -.021** -.020
-.026** -.029* -.027*
dummy
(.009) (.009) (.009) (.013)
(.013)
(.013)
(.010) (.011)
USUA
-.030* -.028*
-.016
-.014
(.008) (.008)
(.014)
(.014)
LCC
-.026
.029
.023
.020
-.098*
(.020) (.020)
(.028)
(.027)
(.027)
Hub-to.064*
.072*
hub
(.032)
(.034)
Intercept .001
.012* .012* -.010
.007
-.008
.003
.006
(.005) (.005) (.005) (.008)
(.009)
(.009)
(.005) (.006)
(9)
-.028*
(.010)
-.098*
(.027)
.047
(.073)
.006
(.006)
Column (3) suggests that nonstop flight tickets in hub-to-hub markets have been increased by 6.4%
after code sharing given everything else equal. Again, cancelling out with code sharing dummy
negative effect, nonstop tickets almost increased by 4%. Column (6) shows these increase is
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coming from alliance partners, not rivals (column (9)). Partners increase 7.2% in nonstop itinerary
fares in hub-to-hub airports, while their rivals have not significantly raised the prices.
Low cost carrier entry has no significant effects overall. However, column (9) reports that
CO/DL/NW alliance partners’ rivals significantly reduce the average price by 9.8% in LCC entry
markets. This is some evidence showing that low cost carriers bring down average market fare.
Table 12 reports Code Sharing effects on traffic on all tickets and nonstop flight tickets. Traffic is
increased by 8.4% after CO/DL/NW code sharing. See column (1). US/UA alliance also increased
traffic by 3% on average. See column (2). Low cost carriers interestingly decrease number of
passengers by 13% overall. This may because consumers in general do not prefer low cost carriers,
hence switch to not flying. Another possible explanation is that Southwest sometimes enters one
market when one major airline exits. In this case, the loss of consumers may due to the exit of a
major airline.
There is no evidence showing a decrease in number of travelers in hub-to-hub markets. Although
nonstop flight price is increased, code sharing may compensate the loss of nonstop travelers.
Column (4)-(6) also suggests that passengers fly nonstop increased overall, but not on hub-to-hub
markets.
Table 12: Code Sharing Effects on Traffic
All Tickets
Nonstop Flights Tickets
(1)
(2)
(3)
(4)
(5)
(6)
CS dummy .084*
.084* .090*
.074*
.059** .052**
(.017) (.017) (.018)
(.034)
(.035) (.035)
USUA
.030** .030**
.103*
.105*
(.017) (.017)
(.033) (.033)
LCC
-.130* -.130*
.023
.018
(.040) (.040)
(.082) (.082)
Hub-to-hub
-.117
.139
(.080)
(.132)
Intercept
.005
-.001
-.000
.007
-.028
-.029
(.010) (.011) (.011)
(.019)
(.022) (.022)
5.2 Effects of DL/NW merger
Table 13 reports the change in market concentration before and after merger. I decompose the
contribution on the change of HHI into markets with different number of competitors to Delta and
Northwest in 2008. The dependent variable is the net change in HHI after merger, i.e. HHI in 2010
– HHI in 2008 for each market.
As what we expect, these markets, where Delta and Northwest were duopoly or with a third carrier
in 2008, have highest increase in HHI. On average, the incremental is 1,069 points for each such
market; which in total there are 65 (8 duopoly and 57 triopoly). The HHI in 2008 for duopoly
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markets and triopoly markets were around 7,000 and 5,200 points, respectively. Overall this
merger enhances the concentration rate by 19% for the pre-duopoly or pre-triopoly markets.
Table 13: Decomposition of Change in Market HHI9
Mean
SD
Comp_0&1
.1069* .0170
Comp_2
.0764* .0114
Comp_3
.0483* .0105
Comp_4
.0428* .0111
Comp_5
.0526* .0122
Comp_6
.0294** .0172
Comp_7
.0140
.0301
10
Code Sharing
.0509* .0136
LCC Entry
-.0665* .0081
Intercept
-.0115* .0022
The results also suggest that the effect of merger on market concentration is generally decreasing
with the increase in number of competitors. HHI in markets where there were two other
competitors increases by 764 points. This effect induces these markets concentration ratio over
5,000 points after merger. The effects are all significant at 5% level except for markets in which
there were 6 or 7 other competitors originally. For markets where there were 7 competitors other
than Delta and Northwest in 2008, the merger does not significantly augment HHI.
The interesting observation is that markets in which originally engaging code sharing between
Delta and Northwest experience increase in HHI after merger. The incremental is over 500
points, significantly. This result supports the competitive effects of code sharing. Once the code
sharing partners merge, the competitive effects disappear. Hence, market concentration increases
and so does the competition. The magnitude is comparable to the effects on markets with 3-5
other competitors previously.
Low cost carrier entry reduces HHI by 665 points on average for each market which has LCC
entry. The effect of LCC entry is not so large. For example, a market with Delta, Northwest and
American airlines competing in 2008, suppose Southwest enter in 2010 while Delta and
Northwest merge, the market still become more concentrated rather than more competitive as
merger increases over 1000 points in HHI for but LCC entry reduces only 665. In this case, the
anti-competitive merger effect is stronger than LCC entry effect, even when we exclude the
effect of releasing code sharing contract between merging carriers.
6 Conclusion
This paper analyzes the competitive effects of code sharing between Continental, Delta and
Northwest by comparing price change between 2004 and 2002. There is evidence showing that the
9 Note: the dependent variable is net change in HHI after merger.
10 Markets with code sharing between Delta and Northwest in 2008 with at least 4% passengers fly on its code
sharing tickets.
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competitive effect of code sharing dominates in most markets, while the anti-competitive effect
dominates in code sharing partners’ hub-to-hub markets. Code sharing partners’ rivals’ response
to the competitive effect decrease were to decrease their ticket prices. Meanwhile, Code sharing
increases the passenger volume.
The merger effect of Delta and Northwest also has been examined. Merger induces a significant
increase in market concentration with different levels in markets with different levels
competitiveness pre-merger. In pre-duopoly and pre-triopoly markets, merger creates over 1,000
point increase in HHI. The effect is smaller in more competitive markets pre-merger. Given that
Northwest and Delta did not overlap in many markets before merger, the number effected markets
are not large. Meanwhile, the discharge of code sharing contract due to merger causes median level
of increase in HHI. I also found that Low cost carriers’ entry effect can somehow mitigate the
merger effects on market concentration.
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