DISCUSSION PAPER SERIES No. 5063 ALLIANCES IN THE AIR: SOME WORLDWIDE EVIDENCE Philippe Gagnepain and Pedro L Marín INDUSTRIAL ORGANIZATION ABCD www.cepr.org Available online at: www.cepr.org/pubs/dps/DP5063.asp www.ssrn.com/xxx/xxx/xxx ISSN 0265-8003 ALLIANCES IN THE AIR: SOME WORLDWIDE EVIDENCE Philippe Gagnepain, Universidad Carlos III de Madrid and CEPR Pedro L Marín, Economic Bureau of the Spanish Prime Minister, Universidad Carlos III de Madrid and CEPR Discussion Paper No. 5063 May 2005 Centre for Economic Policy Research 90–98 Goswell Rd, London EC1V 7RR, UK Tel: (44 20) 7878 2900, Fax: (44 20) 7878 2999 Email: [email protected], Website: www.cepr.org This Discussion Paper is issued under the auspices of the Centre’s research programme in INDUSTRIAL ORGANIZATION. Any opinions expressed here are those of the author(s) and not those of the Centre for Economic Policy Research. 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Citation and use of such a paper should take account of its provisional character. Copyright: Philippe Gagnepain and Pedro L Marín CEPR Discussion Paper No. 5063 May 2005 ABSTRACT Alliances in the Air: Some Worldwide Evidence* We consider an empirical model of worldwide airlines’ alliances that we apply to a large set of companies for the period 1995-2000, with special attention to US and EU carriers. From the estimation of a cost, capacity and demand system that accounts for cross-price elasticities, we attempt to shed light on several interesting issues: First, we analyse whether alliance members’ networks are complements or substitutes. Second, we construct price-cost margins and test several hypothesis of non-cooperative behaviour such as individual Nash and joint price setting within the alliance. We suggest that current alliances’ pricing habits are not uniform and range from individual Nash to more competitive behaviours. JEL Classification: L11, L13, L41 and L93 Keywords: airline, alliances, cross-price elasticities and Nash behaviour Philippe Gagnepain Pedro L Marín Department of Economics Department of Economics Universidad Carlos III de Madrid Universidad Carlos III de Madrid Calle Madrid, 126 Calle Madrid, 126 28903 Getafe 28903 Getafe SPAIN SPAIN Tel: (34 91) 624 5732 Email: [email protected] Fax: (34 91) 624 9329 Email: [email protected] For further Discussion Papers by this author see: For further Discussion Papers by this author see: www.cepr.org/pubs/new-dps/dplist.asp?authorid=157947 www.cepr.org/pubs/new-dps/dplist.asp?authorid=131657 *We would like to thank Jordi Jaumandreu for his suggestions and Quim Beltrán for superb research assistance. Funding from the Fundación Ramón Areces and Ministerio de Educación y Ciencia (SEJ2004-00670) is gratefully acknowledged. Submitted 25 April 2005 1 Introduction We analyze worldwide airline alliances and propose an empirical model that allows us to evaluate cross price demand elasticities for all pairs of airline carri- ers. We determine whether alliances partners can be regarded as complements or substitutes. We also evaluate price cost margins for each alliance and shed light on whether these margins obey to some Nash pricing behavior. There is increasing evidence suggesting that strategic alliances between oth- erwise independent firms have become commonplace in a wide variety of indus- tries. According to Oster (1994), a strategic alliance could be defined as an arrangement in which two or more firms combine resources outside the market in order to accomplish a particular task or set of tasks. By coordinating their services or production processes, alliance partners can offer greater convenience to consumers, as well as engage in cooperative pricing, while enjoying antitrust immunity. Strategic alliances in the airline industry have attracted more antitrust at- tention than any others. Many types of alliances have been adopted by airlines, ranging from agreements that involve relatively little cooperation such as fre- quent flyer programs to agreements commonly known as code sharing practices that involve the sharing of costly assets such as planes, terminals, counters, crews and more (see Oum and Park, 1997, for more details on the forms of alliances in the airline industry). Code sharing arrangements have been until very recently the most popular form of alliance adopted by airlines. In this case, two companies operating two connecting routes offer an interline trip that is ticketed as if the two components were served by one single airline. Economic studies focusing on the effect of airline alliances on welfare have 2 identified various counter powered effects. If the corresponding networks of the alliance members offer the possibility of connecting many routes, they can be regarded as complements. In this case, firms cooperate on routes that were not individually served before, but are created by connecting networks. Accordingly, after the alliance, both prices and costs will fall and both buyers and sellers will be better off. In contrast, if the corresponding networks of alliance members used to overlap for a large number of routes, they can be regarded as substitutes (parallel alliances). In this case, the firms share planes on routes that they both used to served individually. This results in softer competition, and therefore, higher prices. (see Brueckner, 2001, and Chen and Ross, 2000). In this paper, we focus on the five major alliances that were operating be- tween 1995 and 2000. Our aim is twofold. First, we empirically analyze whether the network of individual alliance members is a substitute or a complement for the other alliance member’s network. This is an interesting issue, since it allows appraising the social relevance of existing alliances. To do so, we estimate a cost, capacity, and demand system for airline companies, accounting for cross- price elasticities. The latter entails proposing a original procedure in the specific context of the airline industry that allows reducing the number of cross price elasticity parameters to be estimated. In particular, we account for connecting and overlapping route between airline carriers’ networks. Second, we retrieve cost and demand parameters, construct marginal costs, and derive price-cost margins for each carrier and alliance. We want to test whether they correspond to a non-cooperative behavior under alternative hy- pothesis, e.g., companies act individually, or there is joint price setting within the alliance. We use data for a large set of world-wide companies for the period 3 1995-2000, with special attention to US and E.U. carriers, which normally con- stitute the main alliance partners. The data are mainly retrieved from IATA and ICAO official statistics as well as the carriers annual reports. The rest of the paper is organized as follows: The next section presents the cost, capacity, and demand system under consideration. Section 3 focuses on the empirical implementation of the model. In particular, functional forms and the estimation procedure are presented. We develop in this section the procedure we use in order to model the price demand interactions between the different companies’ networks of our dataset. Section 4 is dedicated to the description of the dataset and the construction of the variables. Section 5 presents the estimation results. Section 6 proposes an evaluation of competitive forces in the industry, which entails determining the pricing rules set by the different airline alliances. Section 7 concludes. 2 Determining the ingredients of the model In what follows we specify a model of airlines’ behavior that entails estimating the demand faced by each carrier as well as its technology. A modelling approach followed by several authors consists in assuming that firms make individual deci- sions for each route they serve.1 This approach allows for route specific policies. The advantage of this is that it takes into account route characteristics that may affect firms’ behavior, such as the number and identity of the competitors or the length and density of the route. An alternative approach followed in previous contributions assumes that companies take corporate decisions that affect their 1See Borenstein (1989) for the American domestic market, among others, and Mar´ın (1995) for the European international market. 4 entire network.2 Leaving aside reasons related to data availability, we believe that the second approach is more appropriate for the purpose of this paper. Airlines serve a large number of interconnected routes that form a network. Sometimes con- sumers buy a company’s service in one single route (what is known as a direct flight) but very often they buy sets of (normally two or three) interconnected routes (indirect flights through one or two hubs). Additionally, when buying a ticket in an individual route, frequent consumers take into account the com- pany’s network size and characteristics, since this affects the flexibility to make further interconnections if needed, exchange tickets, take alternative routes and even enjoy frequent flyer prizes and discounts. In other words, scope economies among routes and network effects (almost) impose a common policy to all the routes served by a given carrier.