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The Potential Entry Defense in Airline Mergers
Andrew Sweeting James Roberts
Duke University
September 2012
PRELIMINARY
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 1 / 45
Introduction
Possible defenses for horizontal mergers between direct competitors inconcentrated markets:
substantial merger-speci�c e¢ ciencies (Horizontal Merger Guidelines2010, Section 10)
probable exit of assets absent a merger (Guidelines 2010, Section 11)
the potential entry defense (Guidelines 2010, Section 9)
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 2 / 45
IntroductionPotential Entry Defense
Guidelines, p. 28:
A merger is not likely to enhance market power if entry intothe market is so easy that the merged �rm and its remainingrivals in the market, either unilaterally or collectively, could notpro�tably raise price or otherwise reduce competition comparedto the level that would prevail in the absence of the merger.Entry is that easy if entry would be timely, likely, andsu¢ cient in its magnitude, character, and scope to deter orcounteract the competitive e¤ects of concern.
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 3 / 45
IntroductionOur Contribution
we develop a static model of entry-and-competition to assess thelikelihood and su¢ ciency of post-merger entrythere are two alternative interpretations of the �potential entrydefense�:
1 the existence of potential entrants constrains incumbents evenwithout entry (�contestability�)
2 the existence of potential entrants disciplines incumbents because ananti-competitive merger would induce entry and this will constrainprices
our model only allows us to consider the second interpretationconsistent with post-1992 interpretations of the Guidelines (Baker2003)consistent with the argument that contestability theory �simply doesnot conform to the fact in a de-regulation world consisting of hubairports�.
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 4 / 45
Our Aims
develop and estimate an empirical model of entry and competition
perform merger counterfacuals allowing for endogenous entry
critically we want to allow for selection
i.e., �rms with lower (marginal) costs or better products are more likelyto have entered before the mergerallows us to explain a stylized fact that count of potential entrantsreduces prices (Morrison and Whinston (1987), Kwoka and Shumilkina(2010))
why may selection be important?1 important in determining whether entry is likely and how e¤ective itwill be (example)
2 role in explaining why little post-merger entry is observed in practice
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 5 / 45
Existing Literature on Entry and Mergers
discussion of how ease of entry should be interpreted and measured
Schmalensee (1987)
theoretical analyses of how entry a¤ects the pro�tability and welfareimplications of mergers
Cournot: Spector (2003), Werden and Froeb (1998)Bertrand: Werden and Froeb (1998), Cabral (2003)assume no selection
dynamic games:
Gowrisankaran (1999)Marino and Zabojnik (2006)assume no selection
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 6 / 45
IntroductionOur Conceptual Contribution
Our key conceptual contribution concerns the role of selection in entry :
suppose potential entrants are heterogenous in marginal costs and/orproduct quality
a plausible entry process is likely to select the best �rms into theindustry pre-merger
the remaining potential entrants post-merger will tend to be relativelyweak
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 7 / 45
IntroductionOur Conceptual Contribution
Surprisingly, selection on marginal costs and/or quality has been assumedaway in:
the theoretical literature considering mergers with entry
almost all of the empirical �entry�literature
even though heterogeneity is usually necessary to explain post-entrymarket shares and pricesexceptions: auctions, models with non-structural outcome equations
limited previous empirical research considering mergers and entry(e.g., Collard-Wexler (2011))
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 8 / 45
IntroductionApplication: Airline Mergers
numerous, high-pro�le, on-going
the potential entry defense has been used successfully in airlinemergers
for most routes, there are several non-competing carriers who alreadyserve the endpoints
these are assumed to be well-placed potential entrants
PED was explicitly cited by the Dept of Transportation when itapproved all mergers pre-1989PED has also been explicitly referred to by the Dept of Justicepost-1989the existence of slot constraints has led to approvals conditional on slotdivestitures (e.g., United/Continental, Eastern/Texas Air)
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 9 / 45
IntroductionApplication: Airline Mergers
but on the most a¤ected routes, prices rise post-merger and entrydoesn�t happen
Borenstein (1990), Kim and Singal (1993), Peters (2006): prices rise7-29%new evidence from recent mergers ...
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 10 / 45
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
58 60 62 64 66 68 70 72 74
Chan
ge in
Log
Pric
es
Effect of Delta Northwest MergerDL/NW Pricing on Non-Stop Routes of Most Concern
compared with all other Non-Stop Routes
Delta-Northwest -95% CI +95% CI
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
58 60 62 64 66 68 70 72 74
Chan
ge in
Log
Pric
es
Effect of United Continental MergerUA/CO Pricing on Non-Stop Routes of Most Concern
compared with all other Non-Stop Routes
United-Continental -95% CI +95% CI
IntroductionPotential Entry Defense in Airline Mergers
Indeed, the possibility of potential competition was thelinchpin for many of the DOT�s decisions approving mergersbetween carriers. Potential competition ... could be relied uponto discipline carriers, even those with dominant market shares: ifa dominant carrier sought to raise fares above competitive levelsor reduce service below competitive levels, new carriers couldeasily enter, especially if they already had some operations at thea¤ected airports. (Nannes (2000))
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 11 / 45
What Happens After Airline Mergers?Limited Entry
# of A¤ected Cases of Cases ofMerger Hub-Hub Routes Direct Entry Connecting EntryUA/CO 11 WN: EWR-DEN AA: HOU-DEN
(slots divested) AA,DL: HOU-SFOAA,DL,WN: EWR-SFO
DL/NW 6 none AA: ATL-DETUA,AA: ATL-MSP
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 12 / 45
Outline for Today�s Talk
1 Literature Review and Our Model2 Data3 Estimation4 Preliminary Results and an Illustrative Counterfactual
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 13 / 45
Entry Models in IO
the canonical IO entry model speci�es a potential entrant�s(�reduced form�) expected pro�t as
πim = Ximβi �∑ αijYj + εim
example: Berry (1992), with ∑ αijYj = α ln(Nm)
example: Ciliberto and Tamer (2009), heterogenous competitione¤ects
εim re�ects heterogeneity only in entry or �xed costs
using post-entry outcome (price, quantity) requires allowing forquality and marginal cost heterogeneity
one reason for only using entry dataa workaround assumes that quality and marginal cost heterogeneityonly revealed post-entry (e.g., Eizenberg (2011))
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 14 / 45
Our Approach
set up a complete information (entry, competition) game withobserved and unobserved heterogeneity
rich model relative to the existing literatureincorporates a standard model of di¤erentiated products competition
propose an implementable estimation procedure
�full solution�(but not NFXP)can handle �equilibrium selection�
analyze mergers as an application, comparing implications with morestandard models
current �ndings (example) consistent with lack of entry after mergersallowing for exercise of market power
focus on short-run entry and exit
set of potential entrants �xedwill not consider network recon�gurationconsistent with short-run, �timely�focus of merger analysis
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 15 / 45
ModelOverview
2 stage, static modelentry/product choice: s 2{DIRECT,CONNECTING}
will assume a carrier can only o¤er one type of service
price competition with nested logit demand
a given market m,de�ned as city-to-city, directionalsample are hub-to-hub markets
set of potential entrants are those carriers with presence at bothendpointsmarket characteristics: market size Mm , distance Dm , jet fuel price,slot constraint, price sensitivity (αm) and demand nesting parameters(λm)carrier characteristics: origin and average origin-destination presence,type: τ 2{LEGACY,LOW COST}
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 16 / 45
ModelCompetition Stage: Demand
Bertrand price competition with nested logit demand (�y/no �y)
consumer utility from carrier j o¤ering non-stop service:
unon-stopijm = µjm � αmpjm + ζFLYi + (1� λm)εijm
µjm � N(Xµjmβµ,τ(j), σ
2µ,τ(j))
αm � LogN(X αmβα, σ
2α)
λm � TrN(X λmβλ, σ
2λ, 0.2, 0.95)
consumer utility if carrier j o¤ered connecting service:
uconnectingijm = unon-stopijm � ψjm
ψjm � TrN(Xψjmβψ,τ(j), σ
2ψ,τ(j), 0,∞)
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 17 / 45
ModelCompetition Stage: Costs
linear marginal costs of carrying passengers for each type of service:
csjm � TrN(X cjmβc ,s ,τ(j), σ2c ,s ,τ(j), 0,∞)
�xed cost of entering for each type of service
Fsjm � TrN(X FjmβF ,s ,τ(j), σ2F ,s ,τ(j), 0,∞)
we assume that variables such as fuel costs and distance a¤ectmarginal costs
we assume that variables such as slot constraints and presence a¤ect�xed costs
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 18 / 45
ModelCompetition Stage: Summary
our model allows for considerable cross-market and cross-carrierheterogeneity in both qualities and costs
observedunobserved
allowing for heterogeneity at the time of competition is necessary torationalize observed prices and market shares
with nested logit demand and each �rm o¤ering a single product,uniqueness of a Bertrand Nash pricing equilibrium (conditional onentry) follows from Mizuno (2003)
uniqueness might fail if:
�rms o¤ered multiple products�rms make frequency/capacity choices and consumers valuefrequency/capacity
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 19 / 45
ModelEntry/Product Choice Stage
information: all potential entrants are assumed to know the value ofall product qualities, marginal costs and �xed costs when they takeentry and product choice decisions
this contrasts with earlier work (e.g., Eizenberg (2011)) where it isassumed that (at least some portion of these) are not observed untilafter entryselection on qualities and marginal costs arises in our setting becausethese are known
sequential entry: entrants move in order of average endpoint presencechoose one from menu of {no entry, enter & direct, enter &connecting}
we can handle alternative models of the �entry process�:sequential entry with a probabilistic ordersequential entry with an unknown (to the researcher) order (bounds)simultaneous move with unknown selection of a pure strategyequilibrium (bounds)
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 20 / 45
Data
Traditional airline data sources:
DB1B O&D Survey database which is a 10% sample of passengeritineraries
domestic, return tickets with prices less than $50, tickets more than$2000�ticketing carrier�
T100 Flight Segment data
used for calculating presencecarriers �ying non-stop
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 21 / 45
DataSample Markets and Time Period
period: Q2 2004-2008
prior to DL/NW and UA/CO mergers
markets: hub-to-hub markets
focus in recent merger casestypically large, but concentrated with the hub carriers providing mostof the servicewe identify 24 hub cities which serve at least 40 destinations, onecarrier serves at least 20 destinations, and are considered hubs in someother studieswe then exclude hub-hub pairs that are less than 200 miles apart, orbecause unusually many or few people appear to travel
the results today are based on city-city markets
we will try airport-airport markets as well
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 22 / 45
DataMarket Size
common to use arithmetic or geometric average population
but, this gives implausible variation in market shares, some of itpredictable
instead, we predict the number of people travelling between citiesusing a regression with explanatory variables (i) total number ofpeople travelling to the destination, (ii) total number of peopletravelling from the origin and (iii) non-stop round trip distance
market size is then de�ned as equal to 3.5 * the predicted value
we drop markets where the combined market share is every less than5% or ever greater than 80%
the restrictions give us 473 city-pair markets
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 23 / 45
DataCarriers
Our estimation approach can handle up to 9 carriers per market
American (AA), Continental (CO), Delta (DL), Northwest (NW),United (UA), US Airways (US) are named legacy carriers
Southwest (WN) is named low-cost carrier
aggregated �other legacy�
aggregated �other low cost�
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 24 / 45
DataService Type, Prices and Market Shares
a carrier can be counted as an entrant if it carries at least 15 DB1Bpassengers in a quarter
counts as direct if
carries more passengers direct than connectingit o¤ers at least one non-stop �ight
otherwise counts as connecting
price and market shares are calculated using only the type of servicethat we consider entered:
average price of DB1B passengers
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 25 / 45
DataPresence
previous work has shown the importance of airport presence for entrydecisions
we de�ne presence of carrier j in a city y as
# of cities served by j non-stop at least once per day from y# of cities served by anyone non-stop at least once per day from y
varies from being almost zero to 1 (e.g., Continental at Houston)
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 26 / 45
Table: Summary Statistics for 2004-2008 Hub-to-Hub Sample
Variable Obs Mean Std Deviation 10th Percentile 90th Percentile
Potential Entrants
Legacy 2,365 6.89 0.31 6 7
LCC 2,365 1.55 0.50 1 2
Entrants
Direct 2,365 2.15 1.15 1 4
Connecting 2,365 2.57 1.65 0 5
Hub Status 21,285 0.25 0.44 0 1
if �y direct 5,086 0.62 0.48 0 1
Mean Fare
Direct 5,086 $373.51 $119.26 $238.14 $538.04
Connecting 6,090 $365.96 $87.87 $260.72 $480.64
Market Share
Direct 5,086 12.1% 8.3% 2.9% 23.9%
Connecting 6,090 1.6% 2.4% 0.2% 3.5%
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 27 / 45
DataPatterns of Entry in the Data: Direct vs. Connecting
Mkt Size TercileDirect Entrants Small Medium Large
Short 1.2 2.1 3.2Distance Tercile Medium 1.4 2.2 3.0
Long 1.2 2.1 3.0
Mkt Size TercileConnecting Entrants Small Medium Large
Short 1.9 1.4 1.4Distance Tercile Medium 2.5 2.4 2.6
Long 3.1 3.7 4.0
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 28 / 45
Estimation
Berry (1992) and Ciliberto and Tamer (2009) estimate by solvingentry games at each guess of the parameters
they don�t have post-entry competitionthey have fewer parametersthey have a binary choiceC&T have only 6 �rms
a nested �xed point approach in our setting (post-entry competition,three choices, nine carriers) won�t work
the non-linearity of second stage outcomes in unobservables makesthe application of two-step methods problematic
we therefore use the Simulated Method of Moments Approach, usingimportance sampling to approximate the simulated moments
suggested by Ackerberg (2009)previously used in our work on second price and �rst price auctions
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 29 / 45
EstimationSimulated Method of Moments with Importance Sampling
the idea is to solve for a large number of games once and thenreweight these solved games during estimation
the parameters we want to estimate are the β and σ (Γ) parametersthat determine the distributions of qualities, price and nestingcoe¢ cients and costs
to take a simple example:
for a set of draws of the {αm ,λm , µjm ,ψjm , csjm ,F
sjm} parameters
(θsim) we can calculate the prices, market shares and entry decisions ofeach carrierif we take a large number of these sets of draws, we can thenapproximate a particular moment by:
E (hm(θ,Xm)jbΓ) � 1S ∑ hm(Xm , θsim)
f (θsim jXm , bΓ)g(θsim jXm)
where g is the importance density from which the draws θsim are taken
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 30 / 45
EstimationSimulated Method of Moments
apart from this di¤erence in how expectations are calculated as theparameters change, implementation is standard, i.e.,
minΓH 0M (Γ)WHM (Γ)
where
HM (Γ) =1M ∑
m[(ym � E (hm(θ,Xm)jbΓ) l(zm)]
and W is a weighting matrix and the zs are instrumentsthe objective function is smooth in the parameters despite thediscreteness of the entry decisionstwo limitations:
requires heterogeneity in all of the structural parametersin practice ability to estimate covariances of the structural parametersis limited
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 31 / 45
EstimationMoments and Instruments
For each carrier we try to form moments based on their entry-typedecision, price and market-share interacted with:
indicators for six market size-distance pairings (S/M/L x short/long)
indicators for high/medium/low presence at the origin
indicators for whether other carriers have above average presence atthe origin
indicator for high/medium/low average presence (across origin anddestination)
indicator for whether origin or destination are slot constrained
fuel price x a dummy for short/long routes
we will add market-speci�c moments to try to identify market �xede¤ects in demand
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 32 / 45
Identi�cationIntuition
the full parametric structure of the model is imposed duringestimationhowever, the arguments for identi�cation would be based on exclusionrestrictions:
for example, the characteristics (e.g., presence) of other carriers willa¤ect their entry decisions and equilibrium pricesfactors, such as slot constraints, that are assumed to a¤ect �xed costs,will also a¤ect entry decisionsmovements in fuel prices (large during our period) could alsopotentially help to identify demand coe¢ cients
the covariance of market shares and prices (conditional onobservables) will play a role in identifying the relative importance ofunobserved heterogeneity in qualities and marginal costs
e.g., positive (negative) covariance suggests more heterogeneity inqualities (marginal costs)
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 33 / 45
Identi�cationIntuition
the level of �xed costs will be identi�ed by the amount of entry
heterogeneity in �xed costs will be identi�ed from how qualities andcosts of entrants vary with market size
if �xed costs are quite similar across carriers, we should only get the�best�entrants in small markets
but, we have only limited variation in the number of potential entrants
an exception is Southwest, which was growing into new hubs duringthe sample
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 34 / 45
EstimationHow Could We Weaken the Sequential Known Order of Entry Assumption?
we can weaken our equilibrium selection assumptionsin particular, we can still use importance sampling to approximatelower and upper bound moments (as in Ciliberto and Tamer (2009)by calculating outcomes for
all possible orders (sequential)all possible pure strategy equilibria (simultaneous)this is computationally quick
in Monte Carlos with a limited number (e.g., 18 parameters) aCT-style approach for searching for bounds also works pretty well
we get tight boundsre�ects the fact that there are rarely more than 3 outcomes that can besupported as equilibriafor the same reason, an estimated probabilistic order of entry gives veryimprecise estimates on the order determining mechanism
the problem is having con�dence in the bounds derived as the numberof parameters increases
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 35 / 45
Carrier Qualities Carrier Characteristics Price CoefficientsCarrier Fixed Effects Market Distance Constant -0.731American -0.015 Legacy Carriers 0.141 Distance -0.018Continental -1.030 Low Cost Carriers 0.206 Variance (transformed scale parameter) 0.039Delta -0.060Northwest -0.429 Origin Presence Nesting CoefficientUnited 0.021 Legacy Carriers 2.324 Constant 0.747US Airways -0.385 Low Cost Carriers 0.389 Std Deviation 0.086Southwest -0.231`Other Legacy Carrier' -1.535 Std Deviation in Quality Draw`Other Low Cost Carrier' -1.675 Legacy Carrier * Long Route 1.030
* Short Route 0.634Low Cost Carrier * Long Route 0.863 * Short Route 0.640
Connecting PenaltyConstant 1.019Distance -0.186
TABLE 4: Parameter Estimates from a 5 Year Panel (Preliminary) - DEMAND PARAMETERS(Std. Errors will be calculated using a bootstrap)
Legacy, Direct Service Legacy, Connecting ServiceConstant 2.220 Constant 1.376Distance 0.682 Distance 0.639Jet Fuel Price -0.017 Jet Fuel Price 0.040Std Deviation 0.934 Std Deviation 1.108
Low Cost Carrier, Direct Service Low Cost Carrier, Connecting ServiceConstant 1.260 Constant -0.011Distance 0.974 Distance 1.237Jet Fuel Price -0.182 Jet Fuel Price -0.052Std Deviation 1.035 Std Deviation 1.589
Legacy Direct 254.40Legacy Connecting 173.52Low Cost Direct 156.42Low Cost Connecting 55.55
Mean marginal cost ($) for 500 mile route
TABLE 4: Parameter Estimates from a 5 Year Panel (Preliminary) - MARGINAL COSTS(Std. Errors will be calculated using a bootstrap)
Legacy, Direct Legacy, ConnectingConstant 3.935 Constant 0.752Distance 0.051 Distance -0.057Presence 0.366 Presence -0.083Slot Constraint (same for connecting) -0.120 Slot Constraint (same for direct) -0.120Standard Deviation 0.494 Standard Deviation 0.843
Low Cost, Direct Low Cost, ConnectingConstant 3.832 Constant 0.376Distance 0.131 Distance 0.049Presence -0.807 Presence 0.202Slot Constraint (same for connecting) 0.170 Slot Constraint (same for direct) 0.170Standard Deviation 0.453 Standard Deviation 0.306
Mean Fixed Costs ($)Legacy Direct 40,152.18Legacy Connecting 7,110.00Low Cost Direct 37,769.11Low Cost Connecting 4,306.41
TABLE 4: Parameter Estimates from a 5 Year Panel (Preliminary) - FIXED COSTS(Std. Errors will be calculated using a bootstrap)
Unconditional UnconditionalPotential Entrants Service Type Mean Price No. of Passengers Implied Mean Implied Mean
CO Direct $336.35 21,060 1.716 1.160 $250.87 $307.20UA Direct $248.69 3,000 0.625 0.087 $211.38 $336.09Frontier Direct $229.34 2,530 0.447 -0.676 $192.56 $241.08AA No entry - - - 0.158 - $336.09DL No entry - - - 0.042 - $336.77US No entry - - - -0.245 - $336.77NW No entry - - - -0.327 - $336.09Other Legacy No entry - - - -0.887 - $338.11
Implied Carrier Qualities and Marginal Costs for IAH to DEN (Q2 2008)
Non-Stop Marginal CostNon-Stop μ
Assume merged firm receives CO's Houston quality and marginal cost, Frontier remains the same as in the dataUse the mean α and λ
Scenario 1: No entryPrediction: average prices increase by 7% ($21)
Scenario 2: Entry allowedCalculate conditional means of quality and cost draws given entry decisions foreach type of serviceProbability of new entry:
Direct 0.07 Connect 0.15Prediction: average prices increase by 6.5% ($20)
Scenario 3: Entry allowed, no selection on qualities, marginal costsAssume non-entrants had same direct qualities asaverage of CO, UA, F9Recalculate conditional fixed costs that lead to observed market structureProbability of new entry:
Direct 0.45Prediction: if entry occurs, prices increase by 3% ($9)
Effects of a UA/CO Merger
Preliminary Estimates
9 �rm model
di¤erent sample: 2008 cross-section of 1,000 non-directional mediumand large routes markets
main features:
sensible demand features: hub carriers valued, people more willing toconnect for long-distance trip, WN highly valued for short-�ightsown-price elasticity around 3marginal costs: direct: average c. $300, increasing $50 per 1000 milesqualities, marginal costs and �xed costs all (too?) heterogenous
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 36 / 45
Legacy Carrier LCC CarriersAA 0.6579 (0.0453) WN 1.5553 (0.1031)CO -0.0436 (0.0499) Other LCC 0.4522 (0.0698)DL 0.7842 (0.0431)NW 0.3447 (0.0444) Distance -0.0864 (0.0326)UA 0.8104 (0.0468) Hub -0.0908 (0.1240)US 0.4408 (0.0457)Other LEG -0.1747 (0.0666) Std Deviation
Short Routes 0.7815 (0.0318)Distance 0.0127 (0.0177) Long Routes 0.6526 (0.0485)Hub 0.9355 (0.0435)
Std Deviation Short Routes 0.6945 (0.0129) Long Routes 0.8015 (0.0199)
Demand Parameters
Qualities
Price Sensitivity Connecting Penalty (both types)Constant 0.3029 (0.0100) ConstantDistance 0.0879 (0.0055) Distance 1.0153 (0.0190)Variance Std Deviation -0.1653 (0.0084) Short Routes 0.0062 (0.0008) 0.3132 (0.0047) Long Routes 0.0255 (0.0030)
Nesting ParameterMean 0.5339 (0.0072)Std Deviation 0.1343 (0.0068)
Other Demand Parameters
Demand Parameters, Cont.
Legacy Carrier LCC Carriers Legacy Carrier LCC CarriersConstant 2.0966 (0.0508) Constant 1.1289 (0.1109) Constant 3.7276 (0.0378) Constant 4.5748 (0.0932)Distance 0.5566 (0.0246) Distance 0.4708 (0.0428) Distance 0.1223 (0.0158) Distance -0.1836 (0.0394)Hub -0.2506 (0.0664) Hub 0.3934 (0.1029) Hub -0.1168 (0.0394) Hub -0.477 (0.1125)Std Deviation 0.9705 (0.0155) Std Deviation 0.7212 (0.0247) Std Deviation 0.4848 (0.0210) Std Deviati 0.6946 (0.0600)
Legacy Carrier LCC Carriers Legacy Carrier LCC CarriersConstant 1.2205 (0.0403) Constant 1.7031 (0.1374) Constant 0.6718 (0.0220) Constant 0.4815 (0.0367)Distance 0.7669 (0.0180) Distance 0.6847 (0.0505) Distance -0.0714 (0.0063) Distance -0.0501 (0.0094)Hub 0.2004 (0.0458) Hub 0.2162 (0.1553) Std Deviation 0.525 (0.0543) Std Deviati 0.2362 (0.0626)Std Deviation 0.7963 (0.0170) Std Deviation 1.1068 (0.0448)
Cost Parameters
Marginal Cost - Direct
Marginal Cost - Connecting
Fixed Cost - Direct
Fixed Cost - Connecting
Illustrative Counterfactual
consider the ATL-DTW market
one of the markets of concern in the DL/NW mergerit actually did experience indirect entry
will use this market to
illustrate selectionperform an analysis of whether a merger is pro�table andwelfare-reducing allowing for entryas an obvious comparison, if one of the merging parties is replaced withan identical new entrant, merger won�t be pro�table (absent synergies)and it won�t a¤ect welfare
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 37 / 45
Illustrative Counterfactual
�rst: calculate the qualities and costs of entrants (for their chosenservice) using the realized P and Q data
second: simulate to �nd the distribution of all other draws that willsupport the observed mkt structure as an equilibrium
third, we can use these draws to perform a counterfactual taking intoaccount selection
or use di¤erent draws to illustrate the non-selection case
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 38 / 45
Illustrative CounterfactualAtlanta-Detroit, 2008, Data
Carrier Hub Service Fare PassengersDelta Y Direct 334.42 15,960Northwest Y Direct 315.77 19,210Airtran Y Direct 263.49 9,870US Airways N Connecting 399.41 330United N Connecting 230.44 160AA N - - -CO N - - -
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 39 / 45
Illustrative CounterfactualAtlanta-Detroit, 2008, Implied Qualities and Marginal Costs
Quality Marginal Cost ($)Carrier Implied Unconditional Implied UnconditionalDelta 4.063 1.455 208 167Northwest 4.068 0.853 184 166Airtran 3.457 1.097 146 310US Airways 1.978 -0.624 296 228United 1.506 -0.435 125 228
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 40 / 45
Illustrative CounterfactualAtlanta-Detroit, 2008, Non-Entrant Qualities and Costs
Direct Quality Direct Marginal Cost ($)Carrier Conditional Unconditional Conditional UnconditionalAmerican 0.51 0.52 207 200Continental -0.47 -0.46 204 200
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 41 / 45
Example CounterfactualAtlanta-Detroit, 2008, DL/NW Merger Simulation
consider a merger of DL and NW
assume they take the average of the pre-merger quality and cost drawsother �rms keep their pre-merger draws
what will be the market structure now? is the merger pro�table?
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 42 / 45
Illustrative CounterfactualAtlanta-Detroit, 2008, Post-Merger Outcome with Selection
because of strong selection (incumbents much better than remainingpotential entrants), entry and upgrading to direct service is rare
when new entry happens it is indirect
the merger reduces consumer surplus
the merger is almost always pro�table
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 43 / 45
Illustrative CounterfactualAtlanta-Detroit, 2008, Post-Merger Outcome without Selection
suppose instead that the potential entrants have quality draws fordirect service like those of the incumbents
entry is now very attractive with or without the mergerif we increase �xed costs of direct service so that won�t enterpre-merger, they will want to enter post-merger
in this case the merger is not pro�table, and the merger may notreduce welfare
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 44 / 45
Conclusions & Insights
acceptance of the �potential entry defense� should require both:
an explanation for why the potential entrants are not in the marketalready
common �xed costs or sunk entry costs may provide this explanation
and an explanation for why the incumbents are in the market ratherthan the potential entrants
�xed costs or sunk entry costs may not provide this explanationshould consider whether marginal costs or qualities drive this selection
we believe that almost any entry process is going to be selective
we develop a highly parametric model to estimate the degree ofselection, and perform counterfactuals
our initial results, and stylized facts in airline mergers, are consistentwith selection
Sweeting (Duke University) The Potential Entry Defense in Airline Mergers 09/12 45 / 45