the status of the core in the airline industry: the case of the european market

MANAGERIAL AND DECISION ECONOMICS

Manage. Decis. Econ. 19: 43–54 (1998)

The Status of the Core in the AirlineIndustry: The Case of the European Market

Andreas Antoniou*

The Phillips College, Nicosia, Cyprus

INTRODUCTION

There is a growing unease among Europeaneconomists regarding the extent of the economicbenefits of a complete liberalization of the Eu-ropean airline industry. The euphoria that fol-lowed the early positive repercussions of thederegulation of the domestic US industry hasgradually given way to a more sober and evenappraisal of the true long-term costs and benefitsof such a policy. The soaring levels of concentra-tion via external growth, the increased congestionaround large hubs, the erosion in the quality ofthe service offered and the deterioration of indus-trial relations climate are some of the costs weigh-ing heavily against complete deregulation USstyle.1

A key to understanding the real economic is-sues underlying this debate is to fathom the mar-ket forces shaping the structure of the industry.Although economists have made great efforts to-wards accomplishing this goal, perhaps because ofthe US experience several crucial policy argumentremain unsettled. One such issue is the need toreconcile, or indeed to promote, enhanced compe-tition, on the one hand, with the oligopolisticstructure and cooperative behaviour that are of-ten the outcome of this policy, on the other.

Clearly this is not a new debate in economics oreven specific to this industry. However, recentlyseveral remarkable contributions in the literaturehave brought fresh perspectives and insights intothis problem. The thrust of the argument revolvesaround the status of the core of an industry and,in particular, the existence therein of at least onefeasible allocation of resources that could be at-

tained through competition. The lack of such anallocation will mean that cooperation may be theonly course of action left to the market partici-pants that will ensure a non-zero level of output.

In this paper we start with the premise thatinternational airlines cooperate on the non-do-mestic segments of their networks. We want toinvestigate to what extent the observed coopera-tive behaviour is more compatible with the rent-seeking collusion-cartel theory or with the need ofairlines to remedy the emptiness of the core. In-deed, by looking at the market entry conditionsand demand and cost conditions, the two compet-ing theories offer opposing predictions as to thesuccess of the cooperation agreements. Thus, it ispossible to test which of the two theories betterexplains the observed cooperative behaviour.

The rest of this paper is organized as follows:In the next section we review the main argumentsof the alternative school of thought that bases itsarguments on the status of the core and its rele-vance to the international airline industry. In thethird section we focus on the European segmentof this industry and propose to test the empty-core hypothesis versus the more traditional collu-sion-based argument. In the final section wediscuss some of the findings and draw main con-clusions of the analysis.

COOPERATIVE BEHAVIOUR IN THEINTERNATIONAL AIRLINE INDUSTRY

Empty-Core: an Alternative to Collusion

Telser (1978, 1985, 1988, 1991, 1994) has consis-tently argued that in the case of the stylized(neoclassical) industry, which he called the ‘Viner* Correspondence to: PO Box 5091, 1306 Nicosia, Cyprus.

CCC 0143–6570/98/010043-12$17.50© 1998 John Wiley & Sons, Ltd.

44 A. ANTONIOU

Industry’, and under fairly standard demand con-ditions, the core will be empty. In particular,unless industry demand is exactly equal to eitherthe MES of the firm/plant (in the case of asingle-plant monopolist) or an integer number ofthe unit-cost-minimizing output (for a multiple-firm industry) the core will be empty. This meansthat under these conditions the industry will notreach a competitive equilibrium.

In general, the necessary condition for a non-empty core, and therefore the existence of a com-petitive equilibrium, is that the industry unit costis a non-increasing function of industry output, inother words in the presence of either constant orincreasing returns to scale. Under any other cir-cumstances some form of cooperation may lead toa more efficient allocation of resources than unre-stricted competition. This result calls for twocomments.2 First, the relevant reference curve isthe industry as opposed to the firm unit costcurve. In particular, Telser (1991) shows that aflat-bottomed unit cost function at the firm level isneither a necessary nor a sufficient condition for anon-empty core, and thus the existence of a com-petitive equilibrium.3

Second Telser (1978, 1985), Sharkey (1982) andBittlingmayer (1982, 1985) have argued that com-petition (alone) yields an efficient allocation onlyto the extent that it is the process whereby aggre-gate demand at market level is equated to aggre-gate capacity. However, in the case of uncertainor fluctuating demand, the presence of avoidablefixed costs (due to sizeable indivisibilities and/orsizeable MES capacity) and thus increasing re-turns to scale will inhibit the ability of the firm tooptimally adjust its capacity (ex ante) or its out-put (ex post). As long as these changes in demandare wider (or more frequent) than the supplyresponses of the active firms, the industry will becharacterized by either excess capacity or excessdemand. This, in turn, will lead to a continuouschange in the number of active firms in the indus-try and therefore to a persistently unstable com-petitive market.

More recently, Pirrong (1992) has shown thatthe core may be empty even if entry is unimpor-tant. Thus, if the plant marginal cost curves arediscontinuous or even rise very sharply and aver-age cost is decreasing (due, in particular, to plantcapacity constraints) then, as long as there arerelatively numerous (with respect to capacity)small buyers, i.e. a variable demand, the core will

be empty, regardless of potential entry. Indeed,(marginal) cost discontinuities associated with avariable demand means that the firm must operatethe plant below the MES so that marginal costpricing will result in losses.4

The discontinuity of the plant marginal costcurves due to capacity constraints means thateven very large markets could be unstable as itmight be cheaper to operate an extra plant ratherthan increase the rate of utilization of the onescurrently in use.

Telser’s theory and its policy implications havebeen studied, applied and tested in the context ofvarious market structures. In particular, there areseveral examples and applications in Telser’s ownwork (see, in particular, the examples in Telser,1978, the analysis of sales quota in Telser, 1985,and especially Chapters 7 and 8 in Telser, 1988).Bittlingmayer (1982, 1985, 1990), Sharkey (1982),Baumol et al. (1982), Sjostrom (1989), Pirrong(1992) and more recently McWilliams and Keith(1994)5 have also drawn on Telser’s work to vari-ous degrees.

In particular, if the cost and demand conditionsin a market are such that the core is empty, thena stable positive level of output implies some formof cooperation between active firms. Notice thatcooperation is only one of several possible alter-native ways of solving the empty-core problem:formal cartel, monopoly, long-term contracts,mergers are others. The point here is to devise anallocation mechanism that will ensure efficientproduction while covering costs.

Therefore contrary to the commonly acceptedwisdom, Sjostrom (1989) argued that observedcooperative behaviour does not necessarily implythe presence of an inefficient rent-seeking cartel.Rather, agreements which look like cartels may bean economically efficient way to solve the emptycore problem. Deriving a set of alternative differ-ing implications from these two competing views,the author tested them in the context of confer-ences in the ocean shipping industry. His conclu-sion, although cautious, is unequivocal: the carteltheory must be rejected in favour of the empty-core explanation.

The robustness of Sjostrom’s results were en-hanced by Pirrong (1992), who corroboratedSjostrom’s findings on the liner shipping segmentof the industry using a different approach, fordifferent time periods on different routes. Fur-thermore, Pirrong introduced a felicitous distinc-

© 1998 John Wiley & Sons, Ltd. Manage. Decis. Econ. 19: 43–54 (1998)

45STATUS OF THE CORE IN THE AIRLINE INDUSTRY

tion between linear and bulk shipping, the formertypically referring to relatively small shipments(representing only a small fraction of the vessels’total capacity) while the latter often utilize theentire capacity of the freighter.

The theoretical interest in the relative size of theconsignment (with respect to capacity) stems fromthe fact that for liner shipping the demand is‘finely divisible’, while the bulk shipping demandis ‘indivisible’. Indeed, to the extent that shippersfacing an indivisible, and thus a more stable,demand are able to use their vessels more effec-tively hence alleviating the indivisibility and dis-continuity problem on the production side (bybetter matching demand and supply), the core hasfewer chances of being empty and the market ismore likely to be competitive.

Cooperation in the International Airline Industry

Notwithstanding the current trend towards dereg-ulation of several internal markets and the liberal-ization of some bilateral (and multilateral)agreements, the international airline industry re-mains heavily regulated. Indeed, the InternationalAir Transport Association (IATA) has tradition-ally (since its creation in 1945) been considered,and remains, the epitome of monopolistic be-haviour through cartelization. Strictly speaking,of course, IATA cannot be considered a cartelsince it only sets tariffs for member airlines, whilecapacity, entry and output level are determinedoutside the association. Indeed, the granting ofentry rights in a market is the prerogative of thenational governments, while capacity offered andlevel of output are usually spelled out in bilateralagreements between companies.

Nevertheless, IATA tariffs remain the referencepoints in most bilateral agreements, even betweencountries whose airlines do not belong to theassociation. Furthermore, although its public im-age has been tarnished during recent years (withseveral companies refusing to join or leaving theassociation) and even if it has introduced moreflexible tariff-setting rules with a more open inter-nal structure, IATA remains the dominant price-setting player in international aviation (seeDoganis, 1991, Chapters 2–4).

In addition, although the USA has signed since1978 a series of bilateral agreements which haveliberalized entry, capacity and the price-settingprocess6, this has had a limited effect outside

North Atlantic routes. Thus it would be fair toassume that the world airline market still has allthe features of heavy regulation where firms coop-erate directly (through IATA) or indirectly(through their respective civil aviation authorities)in view of setting prices, preventing entry and exitand controlling capacity and output. Under thesecircumstances, a prima facie case could be madearguing that the world airline market is monop-olized through collusion.

However, the contributions by Telser and hisdisciples reviewed briefly in the previous subsec-tion cast some serious doubts on the theoreticalvalidity of such a case. In fact, Telser (Telser,1978, pp. 47–54; Telser, 1988, p. 90; Telser, 1994),repeatedly uses airline markets as possible exam-ples of industries with empty cores and Bittling-mayer (1990) seems to endorse this view.Furthermore, and more surprisingly (consideringthe interest that this industry has attracted), thereis to date no study that this author is aware ofthat empirically verifies either the empty-core oreven the cartel–collusion theory.

Indeed, the operations of a scheduled airlineentails, at least in the short run, sizeable fixedavoidable and considerable adjustment costs.These costs are primarily due to three factors.First, much like a vessel, the capacity of an air-craft is to a large degree fixed7 which implies that‘plant’ marginal costs are likely to rise veryrapidly well before full capacity, i.e. maximumpayload, is reached. Indeed, aerodynamics aresuch that it is possible to increase range and speedwithout reducing the payload capacity only untilthe ‘range at maximum payload’ is reached. Thus,up to that point productivity (measured in avail-able tonne-km per hour) increases. However, be-yond that distance, range performance can onlyincrease at the expanse of payload and eventuallyspeed, thus reducing hourly productivity. The ef-fective maximum range of an aircraft is reachedwhen its fuel tanks are full and it is no longerpossible to increase its range by reducing payload(known as ‘payload at maximum range’). Giventhat roughly two-thirds of airline operating costsare either indirect (i.e. do not depend on therealization of a particular flight) or fixed8 (such asengineering overheads, fleet related or labour con-tractual obligations), unit costs will decrease asproductivity increases. However, with productiv-ity decreasing, unit costs taper off and marginalcosts will start increasing well before the payloadat maximum range is reached.


46 A. ANTONIOU

Secondly, ceteris paribus, unit cost (although byno means total cost!) decreases with the size of theaircraft and the length of stage. The substitutabil-ity of the various ‘plants’ is further hindered bythe fact that the unit cost advantages of aircraftsize and stage length seem to reinforce each other,which explains why wide-bodied planes are oftenused over longer hauls and ‘thick’ (i.e. busy)routes.9

These two factors lead to the same conclusion.The typical unit cost curve is U-shaped as sectordistance increases, with marginal cost risingsharply as payload restrictions become binding.Furthermore, more recent evidence seems also tosuggest a third factor may be at play: the exis-tence of substantial common costs and thuseconomies of scope, at the network level (hencethe ‘hub and spoke’ network structure), for vari-ous types of service (e.g. First Class, Business,Tourist, Apex, Freight), and relative to the sizeand composition of the fleet. Thus, once an airlinehas committed itself to a particular fleet composi-tion, has determined the network it must serve,has allocated its planes to specific routes, haspublished its timetable and frequencies, and hasmarketed and promoted its scheduled services, itcannot change its output without incurring sub-stantial adjustment costs.

In fact there are sizeable financial advantages incommitting capacity, often several months priorto the actual flight date, at the real risk of operat-ing with excess capacity. This risk is aggravatedby the fact that the demand for internationalairline services is notoriously uncertain, volatileand unstable. Indeed, not only is it dependent onfactors such as fares, income levels, general eco-nomic conditions, socio-economic characteristicsand the patterns of travel of the future passengers,it is also influenced by overall geopolitical, social,cultural and demographic factors that are wellbeyond the control of airlines. This explains whymany airlines are investing extensive financial re-sources in the development and use of computerreservation systems (CSR) and yield managementtechniques in an attempt to better match theirsupply to future demand.10 Thus, both cost anddemand characteristics are such that it is at leasttheoretically conceivable that in the internationalairline market there are no sustainable prices andthat the core is empty.

This is a falsifiable and thus testable proposi-tion which could be empirically verified. If this

proposition is verified, it might explain why IATAhas been able to survive for so many years as aprice-setting cartel in an unstable industry whichhas experienced considerable technologicalchanges and has undergone profound structuralchanges (in terms of its composition, size, andentry); why international airlines do not seem toearn excessive (monopoly) profits;11 and why at-tempts to deregulate and/or liberalize airline mar-kets (both in the USA and in Europe) have led tosubstantial consolidation and the emergence of‘mega carriers’.

This last point deserves some further elabora-tion. Bittlingmayer (1985), in his study of theeffects of the US antitrust policy on the 1898–1902 merge wave in manufacturing, challengedthe traditional monopoly–collusion–cartel expla-nation in favour of the empty core theory. Indeed,the author argued that the enactment of the Sher-man Antitrust Act (in 1890) forbidding collusion(and the anti-price-fixing decisions that followedin 1897, 1898, 1899) has raised the cost of cartelsto such an extent, making mergers more profitable(or less costly).

Alternatively, the market-failure theory sug-gests that cartels initially (and mergers subse-quently) were not endeavours to earn or maintainmonopoly profits but rather alternative coopera-tive attempts to solve the empty-core problem.Bittlingmayer found both theoretical merit andsufficient empirical support in favour of this latterview, especially in the cases of the railroads, andiron and steel industries.

Pirrong (1992) argues that the role of the cartelis to act as a ‘superfirm’ in order to set prices andallocate output to each plant. He, along withTelser, further argues that setting price floorsalone often results in excess capacity and ineffi-ciencies, especially when there are indivisible costsand there are plants of varied sizes and costs inoperation. In addition, uncontrolled entry willundermine the ability of the cartel to efficientlyallocate output, thus providing an incentive tobuyers and sellers alike to prevent unwanted en-try. At any rate the threat of entry will preventthe cartel from earning monopoly rents.

In the context of the international airline indus-try, although IATA is one such cartel whichcontrolled only fares (and, to a certain extent,quality of service), nevertheless entry and alloca-tion of output is determined by stringent bilateralsand heavy regulation. Thus the empty-core hy-



pothesis might help to explain why for manyyears IATA has been successful in maintainingstability, growth, and relatively low profitability,while enjoying a certain prestige even amongconsumers.

TESTING THE EMPTY-CORE VERSUSCOLLUSION-CARTEL HYPOTHESIS: THE

CASE OF THE EUROPEAN UNION (EU)AIRLINE INDUSTRY

In this section we propose to test whether theempty-core hypothesis outlined above offers abetter explanation of the observed cooperativebehaviour among EU airlines than the more tradi-tional explanation based on the rent-seeking col-lusive model.12 We first outline the main featuresof the EU aviation industry and argue why thisparticular segment of the international airlineconstitutes a good testing ground for testing theempty-core versus collusion theory. Then we pro-pose to test which of the two competing theoriesbetter explains the cooperative behaviour betweenairlines in this market.

The EU Aviation Industry

The stated objective of achieving a coherent inter-nal EU market has generated considerable interestamong economists and politicians alike, in bothEurope and elsewhere. In the case of the aviationindustry this meant the adoption by the EUCouncil (of transport ministers) of a series ofmeasures, known as the First (in 1987) and Sec-ond (in 1990) Aviation Packages,13 with a view toliberalize that industry.

In terms of both the stated objectives and theactual measures taken, this liberalization processdoes not aim at applying, even mutatis mutandis,the US deregulation experience within the EU.14

Rather, it is hoped that by introducing a series ofgradual reforms, greater competition will eventu-ally lead to more efficient airline operations withlower fares and better service for users. Someobservers are rather sceptical of this gradualistapproach, favouring a more radical style whileothers find some merit in it.15

In addition to these efforts to liberalize theinternal EU market via a multilateral agreement,there are already in place a series of very liberalbilaterals between some member states.16 Indeed,

the UK has signed a series of very liberal bilateralagreements with some of its EU partners whoshare its free-market attitude, which include theNetherlands, the Irish Republic, Belgium, andGermany. These liberal bilaterals had mixed ef-fects in terms of entry and fares, depending on thedemand characteristics of the markets concernedand the extent to which charter services presenteda credible threat to scheduled operations.17

Notwithstanding these significant changes, un-less and until the EU-wide multilateral packagesare fully implemented, which are not expectedbefore the end of the decade, the EU market (and,by extension, the European market) will remaintidily regulated. The choice of this particular seg-ment of the international aviation industry as atesting ground for the empty-core hypothesis wasmotivated by the following considerations.

To begin with, by its sheer size and centralgeopolitical position (with extensive links withEastern Europe, Africa, and Asia) the EU avia-tion industry is at the heart of international avia-tion. Indeed, EU airlines are already among thedominant players in IATA, and with the imple-mentation of the two above-mentioned aviationpackages the EU industry will eventually becomethe largest, most developed and homogeneousliberal market outside the USA.

In addition, on many routes scheduled airlinesare already experiencing significant competitionfrom non-scheduled operators, especially on holi-day destinations on the Mediterranean. Indeed,charter operators have significantly lower directand indirect operating costs and are able to usetheir planes more productively by increasing seatdensities and load factors. According to one esti-mate by the UK Civil Aviation Authority, thesecost advantages can be up to 40% compared tothe costs of scheduled airlines (see Doganis, 1991,pp. 189–192).

However, the greatest advantage that manycharters enjoy is on the demand side through theircontractual agreements with large tour operators.These contracts mean that Inclusive Tour Opera-tors (which include travel–board–meal) will bookand pre-pay, often several months in advance,entire planes for round trips to specific destina-tions at predetermined prices, dates and times.This not only improves the cash flow of charters,but, more importantly for us here, reduces signifi-cantly the uncertainty on the revenue side.18 Thus,to the extent that the holiday segment dominates


48 A. ANTONIOU

the total traffic to these destinations, the presenceof charters on these routes may very well be anindication that the demand on these markets islargely ‘indivisible’.19 Thus this feature of the EUmarket will allow us to explicitly test the effects ofthe demand-side conditions on the status of thecore.

Moreover, since some of the most importantintra-EU routes already operate under very liberalconditions, they offer the opportunity to test theeffects of entry on the possibility of reaching anequilibrium.

Data Description and Model Specification

The Data Data for 1989 were collected on 24European destinations (see Table 1). Since one-waytraffic between every city-pair was considered adifferent observation, this amounted to 462 routesor data points.20 These include all major EUdestinations, as well as several key regional air-ports, a total of 17 cities.21 In addition, seven majorEFTA destinations were also included in order toassess the effects of a possible enlargement of theEU that would incorporate these countries22 (seeTable 1).

The fact that we used one-way route-based thaneither round-trip or firm-based data means that we

are in fact underestimating the true extent ofeconomics of density (likely to be present in theformer) and network economies (enjoyed by thelatter). Given that both these cost characteristicsreduce the changes of reaching an equilibrium, weare in fact underestimating the likelihood of thecore being empty.

The Specification23 Following Sjostrom (1989),the effectiveness of the inter-airline cooperativeagreement will be measured by the share of outputsupplied, on each route, by the airlines concerned.Admittedly, this is not the only possible way toevaluate the effectiveness of the agreement. Withinthe broader IATA context, fare stability, quality ofservice, the provision of facilitating services tomembers (such as the ‘clearing house’ facilities andconsulting services), and the collection and treat-ment of data are some of the other benefits that areenjoyed by all member airlines. However, the nexusof intra-European bilaterals goes well beyond theseall-encompassing fixtures and clearly aims at com-plementing and supplementing them with provi-sions that pertain to the control of output andcapacity within the European context. Thus, thesuccess of these endeavours will primarily bereflected in the market shares of the airlines in-volved.

Therefore, we propose to consider the two com-peting theories by comparing which fits the databetter. In particular, we will first define the set ofregressors and then discuss the expected signs underthe competing theories. We will then be able tocompare the two sets of expected signs with theactual results of the regression.

The basic unit observation for the dependentvariables was the revenue passenger carried by ascheduled airline on the above European routes,contained in International Civil Aviation Organi-zation (1989). Thus non-passenger, non-scheduled,and domestic traffics were excluded from the sam-ple but scheduled passengers en route to otherdestinations were included. Based on these data, wewere able to define and compile the following trafficshares (as a percentage of total traffic) carried by:EU airlines, EUSHR ; EFTA airlines, EFTASHR ;other (i.e. non-EU or EFTA) IATA companies,OIATA. The list of possible regressors is given inTable 2, and include the following variables:

1. RED : restricted entry dummy, equal to 0 if theroute was part of a liberal bilateral, as perTable 3

Table 1. List of European destina-tions included in the sample

Amsterdama

Athensa

Barcelonaa

Brusselsa

Copenhagena

Dublina

Dusseldorfa

Frankfurta

GenevaHamburga

HelsinkiLisbona

Londona

Madrida

Manchestera

Milana

Nicea

OsloParisa

ReykjaivikRomea

StockholmViennaZurich

a EU destination.



Table 2. List and definitions of variables used

Dependent variablesShare of EU-airlines in Total RouteEUSHRTraffic (%)Share of EFTA airlines in Total RouteEFTASHRTraffic (%)

EUSH EUSHR+EFTASHROIATA Share other IATA-airlines in Total

Route Traffic (%)EUSHR+OIATAROUTAL

RegressorsMarket relatedRED Restricted Entry Dummy, equals 0 if

‘liberal’ routeNumber of Firms operating on routeNOF

Demand relatedCHD Charter Dummy, equal to 0 of North–

South routeVariability of Demand proxyVAR

Cost relatedAAD Airport to Airport Distance (km)

Passenger Seats AvailablePSAPassenger Load Factor (%)PLFTotal Number of Flights on RouteTNF

Table 4. Expected signs under alter-native theoretical models

Cartel–collusionVariable Empty-core

RED +−NOF − −CHD + −

+ −VARAAD + −PSA + −

−+PLF+ −TNF

6. PSA : passenger seat available, also as in Inter-national Civil Aviation Organization (1989)

7. PLF : passenger load factor, equal to Rev-enue–Passengers Carried/PSA on each route,in percentages (International Civil AviationOrganization, 1989)

8. TNF : total number of flights, on the route(International Civil Aviation Organization,1989)

For most of these variables, the a priori signs ofthe respective parameters will be different underthe two competing theories, thus allowing us torest one against the other.

More specifically (see Table 4) for the firstcategory of regressors, relating to market entryconditions, under the collusion–cartel hypothesisthe entry dummy RED is clearly expected to havea positive effect of effectiveness of the agreementwhile the prediction of the empty-core theory isthat potential entry can be either irrelevant or hasa negative effect. However, in the case of NOFboth theories agree that this variable should havea negative effect on the likelihood of success of anagreement.

The two theories offer conflicting predictionsregarding the sing of the demand-related vari-ables, namely CHD and VAR. Indeed, theNorth–South routes are dominated by traffic onorganized tours which is at the lower end of themarket and where demand is fairly indivisible.The traffic on the other routes is more likely to bea less skewed mixture of promotional fares24 (i.e.‘Excursion’, ‘APEX’, ‘Super APEX’, ‘Stand-by’),and Economy (i.e. passengers visiting friends andrelatives—holiday markers), in favour of Execu-tive/Business and First Class passengers, whichimply a more lucrative market but a more finelydivisible demand. If this is true, then the empty-

2. NOF : number of firms (i.e. airlines) on theroute (International Civil Aviation Organiza-tion, 1989)

3. CHD : charter dummy, equal to zero if North–South route

4. VAR : variability of demand, measured using aproxy, namely the average (across all airlinesserving the route) share (in percentage) ofEconomy passengers in the total number ofpassengers carried by the airline. The datawere collected from International Air Trans-port Association (1989)

5. AAD : airport to airport distance in km, givenin International Civil Aviation Organization(1989)

Table 3. List of liberal intra-European bilaterals

UK–FRANCEUK–BELGIUMUK–NETHERLANDSUK–EIREUK–GERMANYUK–SWITZERLANDFRANCE–SWITZERLANDFRANCE–GERMANYFRANCE–SPAINGERMANY–SPAIN

Sources : Doganis (1991) and Abbott andThompson (1991).


50 A. ANTONIOU

core hypothesis predicts that on the latter routesagreement will be more likely, while in the collu-sion–cartel model profitable markets makes entrymore attractive and therefore agreement lessostensible.

Turning to VAR, and to the extent that thepassengers in the non-Economy class are by con-struction25 Business and/or First Class passengers(i.e. a more predictable, stable and lucrative de-mand) the theory of the core predicts that agree-ment is more likely to be observed in marketsdominated by Economy-class passengers. The col-lusion model, on the other hand, predicts that thevariability of demand raises the operating cost ofthe cartel thus reducing the likelihood of anagreement.

The two theories also predict conflicting signsfor the parameters of the four other cost-relatedregressors, AAD, PSA, PLF and TNF. Indeed, thequick tapering of the unit cost curve with distancemeans that marginal costs are more likely tobecome discontinuous as the length of haul (mea-sured by AAD) increases, thus increasing thelikelihood of an empty-core. By the same token,long-haul routes are, ceteris paribus, moreprofitable and thus more vulnerable to entrywhich, under the collusion–cartel model, makesagreement more precarious.

PSA is a measure of total capacity offered on aroute. The theory of the core suggests that thepresence of excess capacity diminishes the changesof reaching an equilibrium. Furthermore, withplant marginal costs discontinuous, the points ofdiscontinuity in the industry average total costcurve function (i.e. where it is perfectly inelastic)are likely to increase as industry capacity in-creases. In both instances the sign of PSA shouldbe positive. The collusion model predicts that ascapacity increases the costs of policing, detectingand coordinating the cartel will increase, whichreduces the chances of agreement.

PLF is a measure of the intensity of plantutilization, and as such, following our discussionabove, it will be positively linked to the likelihoodof an agreement in the empty-core theory. Bybeing positively related to profitability it attractsentry and therefore reduces the chance of anagreement under the collusion model. By the sametoken, it incites incumbent cartel members tocheat, thus further reducing the changes of anagreement.26

TNF is a measure of the frequency of service,another determinant of cost. High frequencies ofservice are usually accompanied by excess capac-ity and therefore an increased chance of the corebeing empty. Alternatively, high frequencies areoften present on ‘thick’ routes which are moresusceptible to entry and for which the cost ofmonitoring a collusive agreement are high, thusagain making an agreement less viable.

Estimation Results

Reported regression results are based on only 438observations points which are described in Table5. Computer package Micro TSP (PC) version 7.1was used for estimation of the mode. Given thenature of the data it was necessary to correct forheteroskedasticity and therefore we used OLS es-timates with White covariance.27

Results pertaining to EU airlines only (depen-dent variable EUSHR) suggest that our modeland data are compatible with the empty-core hy-pothesis: all but one parameter have the signpredicted by that theory.28 The one exception(CHD) could be due to the fact that ‘southern’routes are not necessarily dominated by promo-tional traffic as was posited above; or are notmore so than the remaining routes. This is rein-forced by the fact that the other demand-relatedparameter, VAR, is significant and has the pre-

Table 5. Summary statistics

Variable Mean St. dev. Max. Min.

EUSHR 80.89 28.40 100.00 0.00

EUSH 95.36 10.23 100.00 33.00

50.06100.004.4098.80ROUTAL

0.81 0.00RED 1.000.39

NOF 3.27 2.80 19.00 1.00

CHD 0.67 0.48 1.00 0.00

VAR 63.07 20.94 100.00 0.00

AAD 158.001137.71 578.65 2996.00

PSA 108.00188 800.61 264 839.50 2 294 278.00

87.0010.6656.25 13.00PLF

1.0011 825.001667.19TNF 1353.40



Table 6. Regression results

Regressors Dependent variable (t-values in parentheses)

EUSHR EUSH ROUTAL

Constant 81.12a 79.51a 104.32a

(6.43) (10.22) (38.32)RED −8.52a −0.672.50

(−2.54) (1.37) (−1.59)−0.80a−1.65a−0.66NOF

(−1.00) (−4.23) (−4.53)CHD −1.76b−20.73a −1.75

(−1.67)(−1.09)(−5.23)VAR 0.0120.28a −0.017

(1.19)(3.89) (−0.66)0.01a −0.0010.003bAAD

(−0.85)(1.76)(3.55)2.61E-05−2.34E-05bPSA 4.67E-05a

(2.49) (−1.66) (0.67)PLF 0.19 0.31a −0.05

(−1.38)(1.05) (2.84)0.0010.005a0.01aTNF(0.78)(2.50)(3.10)

R2 0.17 0.15 0.05Adj. R2 0.13 0.030.16

7.7714.71SER 32.68F 2.64a9.36a11.27a

a Significant at 5%.b Significant at 10%.

Union. During that time, most airlines were fac-ing strong competitive pressures from US andSouth-east Asian carriers, the prospects of a pro-longed recession in OECD countries and uncer-tainty regarding the intra-EU regulatoryframework in which they were expected to oper-ate. Thus, the three factors presented in our ear-lier discussion on cooperation amonginternational airlines were still very much at play.In addition, as was pointed out, the type of dataused is in fact underestimating the true likelihoodof the core being empty. Nevertheless, the modelremains statistically significant.

Our results offer empirical support to theempty-core hypothesis as a credible alternativetheoretical framework to analyse the Europeanairline industry. This would seem to indicate thatthe hitherto observed cooperation between Eu-ropean airlines should not be misconstrued as aneffort to collude in view of monopolizing theindustry but is rather more compatible with at-tempts to solve the empty-core problem.

In addition, to the extent that large NorthAtlantic routes become more competitive andwith the imminent liberalization of several intra-European routes, the ability of airlines to effi-ciently allocate the control output throughbilaterals is seriously undermined. Thus, Telser’stheory predicts that horizontal mergers amongEuropean airlines, and the formation of super-firms such as the ‘mega carriers’, would appear tobe the best feasible rational course of action avail-able to solve the empty-core problem, pre-empt-ing complete deregulation.

Acknowledgements

The author would like to thank Professor Paul Rubin and twoanonymous referees for their suggestion, and Professor L.Tester for his comments on an earlier version of this paper. Allremaining errors are mine.

NOTES

1. For an assessment of the US experience the readeris referred to Bailey (1992) and, more recently,Bailey and Dong (1995).

2. The precise mathematical condition for non-emptycore is sub-homogeneity of the industry total costfunction (see Telser, 1991 pp. 239–240).

3. In this regard, Telser (1991), pp. 226–227, takesexception to the opposite view expressed by Bau-mol et al. (1982).

dicted sign. In fact, a total of six parameters aresignificant while the other two have t-valuesgreater than one.

The results using the combined market sharesof the EU and EFTA companies (dependent vari-able EUSH) are less supportive of Telser’s hy-pothesis. Now, four of the eight parameters havethe ‘right’ sign, three are no longer significant andthe R2’s and F-value drop. In fact, if we add upthe shares of all IATA companies (ROUTAL) theoverall performance of the model deterioratesnoticeably.

EVALUATION AND CONCLUSIONS

The fact that Telser’s empty-core hypothesis per-forms so well in the context of the EU airlines isremarkable in many respects. First, it is preciselyin the context of these airlines that the case forthe alternative collusion-cartel hypothesis is mostcommonly put forward, and indeed has itsstrongest justification on purely a priori theoreti-cal grounds. Furthermore, the data are based on1989 observations, a year well before the ‘1993dateline’, or the Maastricht treaty on European


52 A. ANTONIOU

4. Notice that the fact that Pirrong’s analysis is interms of firm marginal cost does not contradictTelser’s complaint mentioned in the previous note.Indeed, discontinuity in firm cost curves means thatthe industry cost curves are also discontinuous andtherefore Telser’s argument carries through, seePirrong (1992), p. 99, and especially no. 10.

5. I thank one of the referees for pointing out thisreference.

6. See Kasper (1988, 1989), Feldman (1988), and,more recently, Dresner and Tretheway (1992) for adiscussion of the effects of the US deregulation onthe international market.

7. This is true even if we consider the option ofincreasing the seat density.

8. These include costs that cannot be altered in theshort run, as well as station and ground expenses,passenger services, ticketing, sales promotion, ad-ministration. For more details see the excellentdiscussion on the structure of airline costs and theirdeterminants in Doganis (1991) but also Pavaux(1984), Laprade (1981).

9. See, among others, Morrison and Winston (1985)and, more recently Humphreys (1989), Bittling-mayer (1990) and Antoniou (1991) for a survey.

10. According to one estimate, US companies havebeen able to increase their revenue by 5–10% as aresult of effective yield management (Doganis,1991, pp. 302–307); see also Feldman (1988),Chapters 2 and 3, and Wheatcroft and Lipman(1990), Chapters 9 and 17.

11. Many would argue that the low profitability ofinternational airlines is due to the fact that most ofthem are government or state owned and are thusinefficient. This might very well be the case, butrecent evidence seems to suggest (Antoniou, 1992)that the type of ownership per se, is not a signifi-cant determinant of the profitability of interna-tional airlines.

12. As one of the reviewers points out, ‘[T]he airlineindustry is different from ocean shipping and otherindustries because of the greater involvement ofgovernment in regulating and running airlines.Both the empty-core and rent-seeking model maybe at work. There may be no competitive equi-librium and governments may be holdings prices upto protect an industry with a politically privilegedposition’ (original emphasis). Clearly the point ofthis paper is indeed to test which one of thesemodels dominates in the case of the EU airlineindustry.

13. These measures are outlined and discussed in But-ton and Swann (1989), Vincent and Stasinopoulos(1990), Doganis (1991), Chapter 4, and Stasinopou-los (1992).

14. The study by Wheatcroft and Lipman (1986) andits follow-up by the same authors (1991) offer anexcellent review and a lucid analysis of the Eu-ropean aviation industry in general and the EUsegment in particular. In addition, the collection ofcontributions in Institut du Transport Aerien(1988) offer an interesting assortment of opinions

on the possible effects of the EU liberalization onnon-EU neighbouring countries.

15. See, in particular, McGowan and Trengrove (1986),Sawers (1987) and Doganis (1991).

16. See, for example, Pavaux (1988), Button andSwann (1989), Wheatcroft and Lipman (1990), En-caoua (1991) and Abbott and Thompson (1991).More recently see Roller and Sickles (1994).

17. The effects of these bilaterals on entry, fares andfrequency of service are analysed in Abbott andThompson (1991).

18. Because of last-minute cancellations it is impossibleto eliminate completely uncertainty on the demandside, although the imposition of cancellationpenalties goes a long way in deterring the abuse ofthis practice.

19. One of the referees pointed out that the presence ofcharter flights also ‘implies more sophisticatedbuyers, which aggravates the problem of the empty-core’.

20. Clearly, the total number of possible combinationsare larger, 522 in total, but in several instancesthere was either no regular scheduled service or nodata were available.

21. In the cases of London and Paris with more thanone airport, data were combined into a singleobservation.

22. See the Commission’s recommendations on sched-uled passenger air services with EFTA countriesincluded in Commission of the European Commu-nities (1990a), as opposed to those regarding otherthird countries included in Commission of the Eu-ropean Communities (1990b).

23. In the following discussion it will be assumed thatthe reader is familiar with the traditional oligopolytheory and its implications. If not, Stigler (1964) isstill ‘a must’; see also Sjostrom (1989) and Pirrong(1992).

24. For a definition of the conditions attached to thesefares and discussion see Doganis (1991).

25. Indeed, in the IATA publication used here thereare only three categories of passengers: First, Inter-mediate (i.e. business) and Economy.

26. One should be careful not to confuse the intensityof utilization of an aircraft per flight undertaken,measured here by PLF, and the frequency of ser-vice which is the number of trips per unit of time,i.e. a measure of the extent of aircraft utilization.The two need not be the same.

27. One reviewer has suggested that because the valuesthat the dependent variables can take are confinedto the interval 0 to 100 (%) this would require‘some sort of limited dependent variable [estima-tion] technique (e.g. probit)’. However, given thatour dependent variables are not dichotomous, poly-chotomous or even (ordered) Probit and our sam-ple is neither truncated nor censored (as explainedby Greene (1993), pp. 691–706), these techniquesdo not appear suited to our case.

28. In Table 6 we report only the estimation resultsconcerning EUSHR, EUSH and ROUTAL whichare directly of interest to us. The other variableswere used to calculate these variables.



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the status of the core in the airline industry: the case of the european market

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