Welfare Effects of the Allocation of Airlines in Different Terminals
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The costs of a peak-load demand: An application to Gran Canaria airport Ofelia Betancor Juan Luis Jiménez M. Pilar Socorro Economics of Infrastructure and Transport Group (EIT) Universidad de Las Palmas de Gran Canaria Colección Estudios Económicos 12-08 Serie Economía de las Infraestructuras CÁTEDRA Fedea – Abertis ISSN 1988-785X www.fedea.es The costs of a peak-load demand: an application to Gran Canaria airport ∗ Ofelia Betancor†, Juan Luis Jiménez, and M. Pilar Socorro Economics of Infrastructure and Transport Group (EIT), Universidad de Las Palmas de Gran Canaria. Las Palmas de Gran Canaria, Spain. March 2008 Abstract Many airports around the world suffer from peak-load demand problems. To meet demand at the peak periods, airports need to over-invest in capacity. However, the costs associated with the peak-load problem are not only those related to the new investment but much more extensive affecting other economic agents. We use data from the airport in Gran Canaria where the peaks in capacity are associated with tourist arrivals and departures. We estimate the costs that demand peaks impose not only on agents located inside the airport, but also to the society in general. The aim of this paper is to provide a methodology for analyzing the costs imposed on those agents and to explore alternative airport policies. Keywords: airports, peak-load demand, costs JEL Classification: L13, L50, L93 ∗ We would like to thank our colleagues Ginés de Rus and Javier Campos for their helpful comments and suggestions. We are also grateful to Alejandro Hermida, Isabel Santana and Augusto Voltes for their assistance. Our special thanks to the AENA personnel and all the interviewees for generously cooperating with us. This research was undertaken with support from the European Commission within the DIFFERENT project. The usual disclaimer applies. † Corresponding author: [email protected] 1 1 INTRODUCTION Many airports around the world suffer from peak-load demand problems. In general, peak-load problems refer to the existence of economically non-storable commodities whose demand varies periodically. Thus, with uniform prices over time, the quantity demanded rises and falls periodically. To meet demand at the peak periods would then require firms to over-invest in capacity that will be under-utilized over the remainder of the cycle. Since the capacity is costly, this over-investment in capacity is the basis for the peak-load problem and the motivation for using prices to mitigate this inefficiency. The early literature on peak-load pricing used to link public utility pricing to economic efficiency and marginal cost, using the main results of the growing field of applied welfare economics. Clear examples are the works of Bye (1926 and 1929), Lewis (1941), Boiteux (1949 and 1951), Houthakker (1951), Little (1953), Steiner (1957), and Hirshleifer (1958). Peak-load pricing in transport has been traditionally linked to congestion problems. Congestion at airports occurs when there are “too many” users in the system (e.g. terminal or runways), that consequently assume a higher generalized cost for their trip. If we can identify who causes congestion and when it appears, we will be able to charge them in order to internalize the costs they impose on other users. If the congestion problem only appears in certain periods of time (e.g. hours, days,…), the internalization is conducted through peak-load pricing mechanisms. On the contrary, when congestion arises due to a suboptimal effort exerted by airports’ managers, airports’ agents or even airlines, (e.g. lack of personnel available to handle luggage), other type of congestion pricing mechanism should be applied (Nombela et al., 2004). Thus, peak-load pricing in air transport could be regarded as a particular type of congestion pricing. There are some papers applying the peak-load pricing principles to the air transport industry. We can mainly distinguish the papers of Morrison (1983), Morrison and Winston (1989), Arnottt et al. (1993), Daniel (1995, 2001), Daniel and Pahwa (2000), Brueckner (2002 and 2005), Adler and Berechman (2003), and Janic (2005). Although the economic literature concerning peak-load pricing is rather extensive, there is no paper in the literature estimating the real costs of the peak-load problem. While there is an incentive to spread services throughout the day because it lowers the costs of the land-side workforce and facilities and reduces airside congestion (Abeyrathne, 2000), most papers find a justification for the application of peak-load pricing policies just in the reduction of the inefficiency created by the over-investment in capacity. Few papers quantify the costs of peak periods for specific airlines (see Frank et al., 2005, and Kemppainen et al., 2007). However, in this paper we show that the costs of the peak-load problem might be much more extensive, affecting not only to agents inside the airport, but also to other related sectors of the economy. In particular, we use data from the airport in Gran Canaria in order to estimate the costs associated with the peak-load problem. The Gran Canaria airport is characterized for important peaks in arrivals and departures of tourists at given days of the week, which imposes important costs, not only to the airport itself, passengers and airport agents, but also to other sectors such as the bus industry or hotels. Thus, it is not only that the use of the airport capacity and facilities is exacerbated, but also the island accommodation and transport capacity. Our estimate of these costs for the Gran Canaria airport case is 2 almost 12 million euros per year, which would undoubtedly justify a change in charging policies or the allocation of slots.1 In this sense, another objective of the paper is to explore alternative airport pricing schemes in order to induce a more efficient utilization of the airport capacity. The peak-load problem is usually mitigated through peak-load pricing. In practice, the theory of peak-load pricing has had a crucial effect in some sectors, such as the electricity industry, through the introduction of time of day electricity rates and interruptible service offerings. In other sectors, such as the air transport industry, the peak-load pricing theory has been less applied in practice. Indeed, although the use of airports’ facilities is usually characterized by peaks, there are not many examples of airports around the world applying peak-load pricing. The London airports provide a clear exception, applying a peak-load pricing mechanism with time-of-day seasonal pricing not just to aircraft landings but also to passenger terminal usage and aircraft parking. Peak-load pricing in airports would imply pricing at short-run marginal cost. However, Crew et al. (1995) claim that applying peak-load pricing to airports is not as effective as in other industries because of the airline’s grandfather interests in landing slots. The grandfather rights imply that an airline retains its rights to a time in the next period. On the other hand, given the considerable value of some routes and slots relative to the short-run marginal cost of landing or taking-off, the scope for peak-load pricing in order to change times of operation would be quite limited. Schank (2005) also describes problems to be borne in mind when an airport is considering implementing this pricing mechanism. He analyzes three cases: Boston, New York and London. Except for the London case, all airports failed in applying peak pricing mechanisms. There are mainly three reasons: First, the elasticity of demand between peak and off-peak periods may be low. Second, there may be institutional barriers to peak pricing that prevent effective implementation. In general, peak-load pricing affects small aircraft users and General Aviation operators more directly. Thus, it is necessary that an alternative airport exists, in order to attract users diverted as a result of the new pricing structure.2 Finally, it might be extremely hard to calculate marginal costs in an accurate manner. There are not many studies analyzing the elasticity of the demand for aeronautical services. Kanafani and Ghobrial (1985) estimated that the elasticity of demand for flights was between -0.148 and -0.38, while in Australia, it was estimated to fall in the range of -0.1 to -0.225 for interstate flights in the early 1990s (CC, 2002). Doganis (2002) points out two reasons explaining why demand for aeronautical services is so inelastic. First, aeronautical charges represent only a small part of an airline’s total operating costs (generally less than 8% for intra-European routes and 4% for trans- Atlantic routes). However, the ratio of aeronautical charges to total operating costs 1 Button (2002) argues that for airport hubs the expected cost savings are more than off-set by the additional passenger benefits of having convenient concentrations of connecting services. However, this is clearly not the case of Gran Canaria airport. 2 For example, Boston Logan airport failed in implementing a peak-load pricing mechanism because smaller aircraft users challenged it in Court, arguing that those charges did not represent a fair allocation of costs to small aircraft users. The pricing mechanism was found to be discriminatory because there was no acceptable alternative airport for diverted users. As a result of the court’s ruling, the airport was forced to drop the pricing mechanism. All of their subsequent appeal attempts failed. 3 varies from 7.8% to 13.2% for low-cost carriers. For this reason, using price mechanisms to allocate scarce capacity may more strongly affect low-cost carriers. Therefore, though peak-load pricing is an efficient mechanism from a theoretical point of view, sometimes it may be difficult to be implemented. However, the growing importance of low costs carriers in air transport markets, the possibility to extend the differentiated policy to other airport charges as those of handling operations, or even more important, the difficulty to fund huge airport investments based on peak capacity needs, are among the counter arguments to bear also in mind when implementing a new pricing policy aimed to redistribute demand.