The impact of the current economic crisis on the geography of air traffic volumes: A European and worldwide empirical analysis

Paper submitted to the 2011 ERSA Congress Dr Frédéric Dobruszkes(a), Dr Gilles Van Hamme(b)

March 2011 (a) CNRS, UMR 8504 Géographie-cités, 13 rue du Four, F – 75006 Paris, France, Tel. +33 1 40 46 40 01, Fax +33 1 40 46 40 09, f.dobruszkes@parisgeo.cnrs.fr (b) Free University of Brussels / Université libre de Bruxelles (ULB), Faculty of Sciences, IGEAT, Boulevard du Triomphe CP 246, 1050 Brussels, Belgium, Tel. +32 2 650 50 74, Fax + 32 2 650 50 92, gvhamme@ulb.ac.be Abstract This paper presents a systematic analysis of the evolution of the air services during the recent economic crisis. Through a regression analysis, we show that at the country scale, the evolution of the supply is highly dependent on economic growth, confirming the cyclical nature of the air sector. However, many countries deviate from this general trend. The qualitative analysis of some of these deviating figures shows the diversity of air sector situations across countries. National specificities and airline strategies seem to influence the intensity of the crisis. We argue that the intensity of the crisis in the US is due to the structural oversupply of the air sector. Through other cases, especially the Middle East, we show that hubbing strategies might reduce the impact of the crisis, or at least make it less dependent upon local economic dynamics. In contrast with other authors, we found no positive impact of the share of low-cost carriers on the supply during the crisis, despite their success in some specific contexts like in Morocco. Keywords Air transport; Crisis; Global crisis; Air transport shocks; Airlines strategies

1. Introduction The recent economic crisis (2007-?) has been the most intense and dramatic since the 1930s. The recession has reached nearly all economic sectors and all parts of the world. One of the most spectacular geographical features of this crisis is that it has hit the heart of the system, namely, the financial centres of London and New York (French et al., 2009). This is precisely why the crisis has diffused so quickly to become a truly global crisis. However, “global” does not mean “homogeneous”. The most developed countries of the triad have been hit harder than emerging countries, while the latter were subject to permanent economic instability resulting in several crisis episodes in the last 20 years (for example, Mexico in 1994-95, the Southeast Asia crisis of 1997 and Argentina in 2000). To be more precise, the margins of the core economies —mainly in Europe— have been the most affected by the economic crisis (Ireland, Baltic countries, Greece, Spain, etc.). In this paper, we focus on how and where the global economic crisis has hit the airline industry. We already know that traffic and revenues of airline companies are very cyclical, which means that they are closely related to the economic conjuncture (Hätty and Hollmeier, 2003; Button, 2009; Franke and John, 2011). In the last decades, economic and/or geopolitical crises greatly affected the air sector, the most spectacular examples being the first Gulf War in 1991 and the combination of economic crisis and the September 11th terrorist attack in 2001, which of course had a greater impact on the airline industry than on the rest of the economy (Alderighi and Cento, 2004). The

current crisis is a new episode in this succession of crises and rapid recoveries, as stated by International Air Transport Association (IATA):

“The recent cyclical downturn was the deepest experienced by the commercial airline industry since the 1930s. Early 2009 marked the low point for international air travel markets. From the early-2008 peak to the early-2009 trough, premium travel fell 25%. Economy travel fell 9%, the decline softened by a shift to cheaper seats.” (IATA 2010 Annual report).

Indeed, after the recovery period between 2003 and 2007, the recent crisis resulted in severe drop in all IATA indicators between 2007 and 2009 (Figure 1). While profits were negative in 2008 and 2009, their decline has been much more moderate than traffic and revenue indicators, showing the capacity of the sector to adapt to the new economic context in order to limit the damages.

Figure 1. Indicators of air services at global level, 2001-2009 Source: IATA Fact Sheet, Industry Statistics, August 2010.

Although the cyclical character of the airline industry is well known, we found no systematic geographical analysis of crisis in the airline industry, even concerning previous recessions. However, the airline crisis is not spatially homogenous, as we may infer from the optimism shown by the head of Emirates airlines:

“Compared to what it was at this time in 2008, the airline industry in 2009 was in a terrible state. I do not include Emirates in this because we did not share the view of the industry. As a result of our own strategies with regard to growing our business, increasing our network, increasing our fleet and increasing the number of points we served and carrying 20% more passengers than the prior year, we can prove the point.” (Tim Clark, President of Emirates Airlines, interviewed by Air Transport News, 12 September 2010).

The main purpose of this paper is to describe how this global economic crisis has affected the airline industry and to determine whether the geography of the economic recession explains the spatial pattern of the crisis in the airline industry. While we show that the geography of the crisis in

the airline industry well reflects the geography of the crisis in general, we also insist on all deviations to this general trend in order to highlight the geographical specificities of the airline industry in times of recession. Indeed, we attempt to understand why in some countries, the airline industry seems to be affected more than we might expect from the countries’ economic evolutions, showing how the industry responds to specific local features related, for example, to airline company strategies. The rest of the paper is structured as follows. In section 2, we present the state of the art concerning the impacts of crises on the airline industry. Section 3 presents data and methods, which are applied in section 4 to describe and understand the geography of the crisis in the airline industry. We conclude in section 5.

2. The impact of the crisis on air transport: a state of the art Analyses of the recent crisis are relatively scarce, at least from a geographical point of view. Most of the literature has focused on finance: Aalbers (2009a) analyzed the mortgage market at the origin of the crisis; Lizieri (2009) focused on the real estate markets; and other authors have analyzed the evolutions of financial geography (French et al., 2009; Lee et al., 2009; Derudder et al., in press) or, more specifically, geographical and geopolitical issues related to the financial crisis (Carroué, 2009). Geographical analyses of the recession in the real economy are much more difficult to carry out due of lack of data at the intra-national level, although there are some exceptions (Davezies, 2010; Lennert, 2010). We found no papers focusing on the geographical impact of the crisis on air services. To understand the processes related to the crisis in this sector, we must go back to analyses of previous crises, especially the crisis of 2001 to 2002, for which there is abundant literature. A first series of research analyses the impact of September 11th on the level of airline supply and demand. Ito and Lee (2005) assess the impact of the September 11th attacks on intra-US demand, controlling for the poor macro-economic context and seasonal effects. They found a transitory, negative demand shock of more than 30% and an ongoing negative demand shift of 7.4% that cannot be explained by the aforementioned or other factors. Gillen and Lall (2003) analyze the channels through which airline industry shocks are propagated across countries. Through the analysis of a sample of airline companies, they conclude that US companies were hit much harder by the September 11th crisis than Asian ones, with European companies lying in between. As for propagation effects, they found a trade effect larger than the alliance effect. They also found that low-cost companies have been less affected and have better recovered from the crisis. Golaszewski (2003) studies the links between costs of infrastructure service providers and crisis and traffic declines. Because service providers have important fixed costs, they might be tempted to raise their prices in the case of traffic downturn, to the detriment of airlines. Indeed, the latter faces a strong elasticity of demand relative to prices and cannot thus easily pass on this rise in their own rates. In such a context, short distance flights are more affected, because the fixed charges are proportionally higher than for long-distance flights. A second series of papers focus more specifically on airline companies’ strategies during the crisis. Hätty and Hollmeier (2003) recall how quickly airline companies are affected by economic crises. Yet, they cannot react as rapidly as they would like in the case of conjuncture reversal, because “market exit barriers prove to be extraordinary high.” Hence, flexibility is a key factor for airlines to absorb crisis impacts, as the authors illustrate through the case of Lufthansa. In the 1990s, this airline managed to obtain higher flexibility from both employees and suppliers. This strategy allowed the carrier to rapidly reduce its supply after September 11th and thus to limit the financial impacts of the crisis. However, again no spatial analysis was undertaken. Alderighi and Cento (2004) focus on the same issue of airline strategies to respond to the crisis but restrict their analyses to European companies in the transatlantic market. They show that companies reduce their capacities through different ways, for instance, by limiting frequencies, using smaller planes, or closing routes. However, these adaptations have a cost, which explains the relative inertia of the supply and a preference for price adjustments. These adjustment costs vary according to the airlines

and their flexibility. They found that expectations on the duration of the crisis and the level of adjustment costs are the main factors explaining the strategies of airline companies after September 11th. In this analysis, the geographical dimension is limited to a single table showing the evolution of the supply for a selection of North American airports. A last series of studies focus more on how airline companies recovered from the September 11th crisis than on its immediate impact. Rupp et al. (2005) analyze how airline carriers restarted business after the closing of US airports. They show that the potential revenue per flight is the main driver of the companies’ decisions, although airport concentration, hubbing, and various logistical factors also play a role. Masse (2002) analyzes more in-depth aircrafts movements from six Canadian airports. While he notes the high variability from an airport to another and from a market segment to another, flights between Canada and US have been affected for a longer period than national and intercontinental flights. These papers contribute to the analysis of the impact of the economic crisis on the airline industry, despite their focus on limited segments of the airline market (for example, flights with or inside the US market). As such, they might help to understand the processes behind the geography of the airline industry crisis, but no publication exists proposing an exhaustive geographical analysis of this crisis, whatever the scale. Though, the recent global crisis has not been spatially homogeneous (Aalbers, 2009b; French et al., 2009), so we might expect the same for the airline industry. This paper attempts to fill in this gap. We work under the basic hypothesis that the geography of the crisis in the airline industry is closely related to the geography of economic recession. Most of the aforementioned studies show how the airline industry is closely related to the global economic activity through different channels. Some authors have more explicitly described the close relationship between gross domestic product (GDP) growth and evolutions in the airline industry. For example, Doganis (2002: 197) shows that at the world scale, the annual evolution of airline industry (through revenue passenger kilometres) is closely correlated to GDP growth. Using Granger's causality test, Fernandes and Pacheco (2010) find that in Brazil during the 1966 to 2006 period, there was a unidirectional relationship between economic growth and domestic air transport demand with high elasticity in the short term. In a second step of the analysis, we introduce other explanatory factors, such as the airline dynamics in the previous period. More importantly, in a third step, we try to understand deviations to the general trend using contributions from the literature.

3. Data and methods In order to explain the spatial dynamics of air services, we used the evolution of the total airline supply as the dependent variable and the evolution of GDP as the main independent variable, controlling for other potentially explanatory variables. Hence, we regressed evolution of airline supply on GDP growth through multiple linear regressions. All regressions were weighted by the total supply in 2008. We will now describe our major variables in depth. The evolution of the airline industry (dependent variable) comes from data on air services rather than demand. The data were derived from the databases produced by the OAG firm, which describes scheduled air services throughout the world in an exhaustive and geographically disaggregated manner. For each flight, they indicate the operating airline as well as the frequency and number of seats powered, among other things. We used evolutions from January 2008 to January 2010, which covers the most intense phase of the crisis. January 2008 lies before the major drop of airline supply, while January 2010 situates before the recovery observed during the year 2010. The main reason for using these data on the supply is their availability at the world level and their decomposition according to airports and airlines. These data enabled us to work at any scale and to separate low-cost and traditional airlines. Using data on airline supply rather than on demand allowed us to analyse companies’ strategies as a response to the crisis. Our main independent variable is the evolution of GDP for the period covered by indicators on air transport. Data come from the International Monetary Fund (IMF) and have been deflated to be

expressed in constant values. We obtained data for 181 countries on air services and GDP growth during the most intense period of the recession. We first grouped together all airports within the same city1, considering the number of available seats from all cities in the world2. Then, we switched to the country level for linear regression because we lacked refined data on GDP growth below the national level at world scale. Also, the evolutions of airline supply were rather homogenous within countries during the crisis. We will come back on this important issue of scale (see section 4.1). We also controlled for other variables. We consider spatial airline dynamics during the period before the crisis. An alternative hypothesis to explain why some areas resist or decline more than others would be that these differences during the crisis are only the prolongation of what happened before the crisis. Moreover, we controlled for each country’s belonging to a global macro-region3, because the spatial dynamics of the air services during the crisis are also dependent on this macro-regional scale. By using this Boolean control variable, we can be sure that the correlations observed between air services and GDP are also relevant at the national level and not only the result of macro-regional dynamics, as some figures might suggest (see section 4). Finally, we controlled for the structure of the supply (the share of domestic and inter-regional supply), which might have an impact on how the crisis affected the air industry.

4. Assessing the impact of the economic crisis on air services

4.1. The main drivers of the geography of the crisis in the airline industry Figure 2 shows huge geographical contrasts in the evolution of the airline supply between January 2008 and January 2010. On the one hand, most cities of the developed world (Western Europe, North America, Japan), Taiwan, Central America, Caribbean islands and former USSR face a stagnation or decline in their supply. On the other hand, cities of China and Southeast Asia, the Middle East, Maghreb and South America still see their air services increasing. We observe more diversity in the evolutions of cities in Africa, India and Oceania. As a first approximation, evolutions in the geography of air transportation during the crisis are well in line with the one of the global economic recession, more severely affecting the economies of Europe, Northern America, and Japan than those of emerging countries. Another important geographical feature of the airline crisis is the relative homogeneity that we observe at the national level and, to a certain extent, at the macro-regional scale. Through a variance analysis4, we estimated that 55% of the variations in the air dynamics of all cities across the world between 2008 and 2010 depend on the country to which these cities belong, while the intra-national variations only account for 45% of this total variation. This relative intra-national homogeneity justifies switching to the national level in our analysis. In Figure 3, we show the evolution of the supply at the country level.

1 To give one example, Rome includes Rome da Vinci Airport (formerly Rome Fiumicino Airport) and Rome

Ciampino Airport. 2 Note the high correlations between the evolution of airline supply through the number of seats or through the

number of flights or seats-km (ASKs) (respectively R=0.96 and 0.95). 3 This division of the world corresponds to 11 macro-regions: Africa, Central America and Caribbean, North

America, South America, East and Southeast Asia, Commonwealth of Independent States, Europe, India and surroundings, Maghreb, Middle East, Oceania and Pacific.

4 Variance analysis breaks down the variations at the most detailed level into the different hierarchical levels. In this case, the total variation between cities in the world has been divided into the variations of cities within countries and countries in the world.

Figure 2. Evolution in air services between January 2008 and January 2010 (at the city level)

Source: own calculations from OAG

Figure 3. Evolution in air services between January 2008 and January 2010

(at the country level) Source: own calculations from OAG

To explain the geography illustrated by Figure 3, we simply assessed the correlation between the evolution of the supply (2008 to 2010) and GDP growth between 2007 and 2009 at the country

level5 (Figure 4). Correlation is high (R=0.67), which means that 45% of the geographical variation of the airline supply is described by variations in GDP growth. However, as stated previously, several other factors might explain this geography; these factors must be controlled. As shown in Figures 5A and 5B, during the period before the crisis, evolutions were already diverging at the macro-regional level. Interestingly enough, these figures also show that the evolutions during the crisis are not necessarily in line with those observed during the previous period. Yet, it is important to control for the air transport dynamics existing before the crisis. Because of the homogeneity observed within macro-regions, we also decided to control for countries belonging to the macro-region6. Moreover, because domestic/international and intra-/interregional air services react differently in periods of recession, we also controlled for the geographical structure of the supply.

Figure 4. Evolution in air services evolution vs. evolution of GDP by country

Source: own calculations from OAG datasets and IMF.

5 Correlations have also been calculated with GDP evolutions for 2008-2009, 2008-2010 and 2007-2010. However,

the highest correlations are found with the 2007-2009 period, in line with the idea that the air industry takes some months to adapt to the new conjuncture.

6 If correlations between GDP growth and airline supply persist when controlling for macro-regions, this means that variations from one country to another can be explained by GDP growth at national level (or decline) and that the overall correlation is not only due to contrasts between macro-regions. Indeed there are two scales of analysis: at the first level, the economic crisis explains the contrasts between macro-regions; at the second level, within each macro-region, the differences between countries can also be explained by economic differentials.

Figure 5A. Evolution in air services by macro-region (I), 1991-2010

Source: own calculations from OAG

Figure 5B. Evolution in air services by macro-region (II), 1991-2010

NB: Y range differs from the figure 5A. Source: own calculations from OAG

Therefore, we undertook a multiple regression to explain the evolutions of air transport at the national level, with GDP growth, the evolution of the airline supply in the 2003 to 2008 period, the share of domestic and interregional seats in the total supply, and Boolean variables relative to the

country’s belonging to 11 macro-regions as independent variables. Table 1 shows that GDP growth is the most significant variable to explaining the evolution of air services at national level. The geographical structure of the supply also proves to be significant, especially the share of domestic supply. In contrast, the variable “evolutions during the previous period” is not significantly related to air dynamics at the national level. This clearly demonstrates that the geography of the air crisis is mainly a response to the economic crisis and not to trends which are inherent to the air sector; that is, evolutions during the crisis do not prolong what happened before.

B Std. Error Beta stand. coeff. Signif.2007-2009 GDP evolution 2.161 0.306 0.422 0.0002003-2008 seats evolution 0.003 0.020 0.007 0.8882008 domestic supply (%) 14.394 5.722 0.226 0.0132008 inter-regional supply (%) 22.632 12.058 0.158 0.062Africa 4.725 6.607 0.036 0.476Central America & Caribbean -9.378 6.214 -0.089 0.133North America -9.756 4.400 -0.254 0.028South America 25.101 5.329 0.290 0.000East and South-East Asia 12.448 4.571 0.282 0.007CIS 3.045 6.764 0.023 0.653Europe 5.659 5.048 0.130 0.264India & surroundings -7.557 5.999 -0.075 0.210Maghreb 8.281 11.041 0.035 0.454Middle East 27.983 5.738 0.318 0.000R = 0.861. R² = 0.741.

Table 1. Linear regression on the evolution of the number of seats by country between 2008 and 2010

Since the geographical structure of the supply has a significant impact on how the air industry behaves during the crisis, it is interesting to distinguish between the different market segments. Before 2008, the growth of the international supply on the world scale was twice that of the domestic supply (Table 2). During the crisis, however, both markets stagnated, meaning that the crisis more severely hit the international supply. Table 2 also shows that the domestic supply at the world level did not decline thanks to the very high dynamics of the domestic supply in South America, Eastern and South-eastern Asia, and the Middle East. These strong domestic dynamics mainly concern the biggest markets of China and Brazil but also exist in the Philippines, Turkey, Colombia, etc.

International Domestic 2003-2008 2008-2010 2003-2008 2008-2010Africa 7% 4% 8% 3%Central America & Caribbean 4% -1% 5% -12%North America 3% -2% 1% -8%South America 6% 2% 2% 17%East and South-East Asia 7% 0% 7% 10%CIS 16% 5% 22% -4%Europe 9% -4% 3% -4%India & surroundings 15% 5% 26% 1%Maghreb 13% 14% -7% -2%Middle East 13% 17% 9% 13%Oceania - Pacific 5% 4% 9% -1%World 8% 0% 4% 0%

Table 2. International vs. domestic annual growth rates according to the number of seats Source: own calculations from OAG datasets.

Surprisingly, if we change the scale by distinguishing intra- and inter-regional air dynamics, we find the opposite conclusion: during the crisis, the intra-regional supply declined on the world scale, while the interregional air services have seen their growth slowing down (Table 3). Overall, the domestic supply was affected less by the crisis than the international supply within macro-regions, while the inter-regional supply continues to grow but at a slower rate than before. However, the growth of the inter-regional supply only benefits some regions, such as the Middle East, Maghreb, and India.

Inter-regional Intra-regional 2003-2008 2008-2010 2003-2008 2008-2010Africa 7% 3% 8% 4%Central America & Caribbean 4% 0% 5% -10%North America 4% -1% 1% -8%South America 6% 2% 2% 15%East and South-East Asia 5% 2% 7% 7%CIS 16% 5% 20% -3%Europe 7% 2% 6% -4%India & surroundings 14% 7% 26% 1%Maghreb 14% 13% -5% 1%Middle East 12% 17% 11% 15%Oceania - Pacific 5% 4% 8% 0%World 7% 4% 5% -1%

Table 3. Inter- vs. intra-regional annual growth rates according to the number of seats Source: own calculations from OAG datasets.

4.2. Interpreting the deviations from the model The model presented in the previous section accounts for 74% of the geographical variations of air transportation during the crisis. This means that many countries deviate from the general trend, some having better dynamics and others declining more than foreseen by the model. Figure 6 classifies countries according to the evolution of air transport during the crisis and the amplitude of deviations to the model. Since we cannot discuss all cases, we instead provide ad hoc explanations for a sample of situations. In doing so, we cover potential explanations related to national specificities, company strategies,

and particular differentiations between domestic and international or intra- and interregional air services.

Figure 6. Air services dynamic vs GDP dynamic: a typology.

Source: own calculations from OAG datasets and IMF. 4.2.1. USA: the amplification of a pre-existing crisis Between January 2008 and 2010, both domestic and international supplies severely dropped more than expected in the US (Table 4). During this period, 739 routes were suppressed, and only 347 new routes were created, mostly in the domestic market. However, the general decrease of the supply was mainly due to the rationalization of existing services, accounting for 76% of the decrease in seats7. This process of rationalization was undertaken by national companies rather than foreign ones. From the literature, we derive several explanations to these specific dynamics.

7 Authors’ own calculations from OAG datasets.

International Domestic Inhabitants 2003-2008 2008-2010 2003-2008 2008-2010 (Millions, 2007)Angola 14% 25% -19% INF 17.6Brazil 9% 0% 2% 21% 190.1Ireland 15% -12% 22% -12% 4.4Latvia 83% 30% N.C. N.C. 2.3Morocco 25% 17% 2% 5% 31.2Nigeria 7% 19% 10% 37% 147.7Qatar 30% 15% N.C. N.C. 1.1Romania 34% 6% 22% 8% 21.5Turkey 14% 32% 35% 21% 73.0United Arab Emirates 17% 15% -20% N.C. 4.4USA 3% -2% 1% -8% 308.7World 8% 0% 4% 0% 6670.8

N.C.: not concerned. INF: infinite (growing from scratch or nearly scratch)

Table 4. Annual growth rates according to the number of seats for selected countries Source: Own calculation from OAG datasets.

First, according to Button (2009), the US air market is characterized by a structurally declining demand, because of additional security measures put in place following September 11, 2001. This involved both additional time and inconvenience for passengers. As a result, we can hypothesize that the 2008 to 2010 crisis forced companies to suddenly adapt their supply to a structurally declining demand. Second, we must explain why US companies did not sufficiently adjust to the new conditions of air demand in the previous period. Actually, many US companies were already suffering before being hit by the recent crisis, because they never really recovered from the previous crisis (2001 to 2002). Most of the legacy airlines (Delta, Northwest, United, US Airways, etc.) were under so-called Chapter 11 bankruptcy protection. They escaped from bankruptcy only because of specific legal protections, which gave these companies the time to restructure their activities under the supervision of a bankruptcy court (Gong, 2007). In such a context where debts or contracts can be more easily cancelled, airline supply did not necessarily well adjust to the demand, resulting in a structural oversupply before the crisis (Goetz and Vowles, 2009). Third, as shown in Table 5, US companies are characterized by weak shares of their activities on inter-regional market, which are supposed to be more profitable (Franke and John, 2011) and to allow better resistance to the crisis, including for North America (Table 3). Finally, US companies have higher proportions of older planes, which are easier to draw back from activities (Morrell, 2011).

According to Carriers from Seats Seats-km USA 12% 25% USA - Main legacy airlines (AA, CO, DL, NW, UA, US) 15% 31% Canada 14% 42% France 30% 79% Morocco 78% 91% UK 21% 65% United Arab Emirates 72% 92% World 16% 46%

Table 5. Share of inter-regional air services (2008) Source: Own calculation from OAG datasets.

4.2.2. Ireland: the end of a miracle Ireland was characterized by spectacular economic development during the 1990s and 2000s due to an increase in tertiary economic activities in the context of a neo-liberal policy and a new position in the international division of labour. Ireland has attracted numerous back office operations for transnational firms, principally American ones, who chose the Dublin area as the centre of their European operations (Grimes, 2006; Rios-Morales and Brennan, 2009). Recently created air companies actively participated in this development model by looking for flexible labour markets and for a favourable tax system in a general context of internationalisation of the economy. In such a context, air services have developed very quickly because of (1) business travellers, (2) tourist travels due to higher household incomes, (3) visitors to Ireland induced by low-cost airlines and (4) immigrants generating more visits to friends and relatives (Dobruszkes, 2010). However, the crisis severely hit Ireland, and air services have dropped (-23% of seats from 2008 to 2010) more than expected. Even low-cost companies have dramatically reduced their supply: Ryanair and Aer Lingus decreased their number of seats by 19% and 18%, respectively, between January 2008 and January 2010. It seems that the end of the “Irish miracle” has reached all drivers of air services growth. There are fewer business travellers; the drop in household incomes has reduced holiday spending; the migration balance has gone from positive to negative again. However, this will lead to declining demand only if recent immigrants leave the country. All of these elements are reinforced by the insular situation of Ireland, which makes this country more dependent on air flows for international travel. 4.2.3. Brazil and Angola: domestic services as the driver of growth Some emerging or even poor countries have seen their supply increasing more than expected due to the development of the domestic market. This is for example the situation in both Brazil and Angola (Figure 6). In Brazil, the international supply before the crisis was more dynamic than the domestic one. Between January 2008 and 2010, the trend reversed, with domestic supplies growing at an average rate of 10% during these two years. About 70% of this growth in seats is due to the development of existing routes, and 30% are related to the creation of 76 new routes, 52 of which are domestic. In a so-called emerging economy moderately hit by the global economic recession, we can interpret this trend as a catching-up process: in such a huge country where a wealthy middle class has developed rapidly, we observe a shift from road to air services. As for Angola, most of the dynamics are due to the creation or the reopening of domestic routes. In January 2008, there was only one domestic service (Luanda-Lubango); two years later, 20 new connections had been added, 8 of which existed in 2003 but had been suppressed. All domestic routes are exploited by the state-owned airline TAAG Angola Airlines. In an attempt to restore their reputation and reliability, this airline has bought several new planes. This attempt must be understood in the general context of the post civil war period which lasts between 1975 and 2002. During the last few years, economic growth has been very high driven by oil production and, to a lesser extent, by the diamond industry. China has become the main buyer and investor in Angola. Hence, even if the population remains very poor, political/economic national and international elite have the ability to travel by plane. The Angolan case well illustrates the situation of sub-Saharan Africa, where economic and political situations are so diverse and the development of airlines so specific that we observe very diverse dynamics in air services during the crisis. Running multiple regressions only for African countries, we still found an impact of economic evolutions on air dynamics, but it proved to be less significant. Hence, in specific national contexts of Africa, air dynamics are not so closely related to

the economic conjuncture. Most companies are state-owned and may have objectives other than profitability, although this does not mean that they are not profitable. 4.2.4. Morocco: increase in air services boosted by low-cost airlines Morocco is one of the examples where international air services increased despite slowed economic growth during the crisis. This increase is due for 56 % to larger numbers of seats on the 117 existing routes and for 44% to the creation of new routes, almost exclusively toward Europe8. This results from the liberalization agreement on the airspace between EU and Morocco signed in December 2006, which gives both European and Moroccan companies free access to the EU-Morocco international market. This agreement is part of the Moroccan strategy to attract annually 10 millions tourists (Moroccan Government, 2001). As shown in Table 6, five companies have ensured most of the increase in international seats: the flag carrier Royal Air Maroc as well as four low-cost carriers (Ryanair, Easyjet, Jet4You and Transavia France). The liberalization agreement has allowed Royal Air Maroc to consolidate its supply and European low-cost airlines to penetrate this growing market9. In 2010, Ryanair became the second scheduled airline in number of seats for services to Morocco, following the flag carrier Royal Air Maroc.

x 1,000 Seats (January) Airlines 2008 2010 Increase 2010/2008 Royal Air Maroc 346 435 89 1.3 Ryanair 21 81 60 3.8 Easyjet 17 55 39 3.3 Jet4you 36 53 17 1.5 Transavia France 9 18 9 2.0

Table 6. The main airlines that have increased air services from/within Morocco Source: Own calculation from OAG datasets.

Of course, liberalization does not necessarily lead to growth in air services. Dobruszkes and Mwanza (2007) showed that the open skies between the US and several African countries did not result in significant increase. In contrast, we may suppose that the EU-Morocco market provides many more opportunities due to the tourist development at the doors of EU and to the massive Moroccan diaspora residing in European countries. In this context, competitive prices might lead to more frequent trips, deviating tourists from other destinations, and increasing the market share of planes to the detriment of road and sea. 4.2.5. Gulf airlines: State-supported worldwide developments In their attempt to diversify their economies and to invest the accumulated capital originating from the oil rent, governments of the Gulf countries have developed new activities in finance, real estate, tourism or air services. In this context, airlines have been created and benefit from important public support in United Arab Emirates (Emirates Airlines, Etihad Airways), Qatar (Qatar Airways) or Kuwait (Kuwait Airways) (Warnock-Smith and O’Connel, in press). Emirates Airlines and Qatar Airways in particular have rapidly developed their networks, their fleet, and their global supplies in recent years. Huge amounts of money have been invested to buy long-haul planes (for example, 58 A380, 70 A350 and numerous B777 for Emirates Airlines) and to develop airport infrastructures. When compared to the national population that it serves, airlines of the Gulf countries have reached impressive sizes in terms of the number of routes or passengers (Table 7).

8 Authors’ own calculation from OAG datasets. Because our statistics cover the month of January, it might be that the

“new creations” were already exploited during the summer in the previous period. 9 Jet4you was initially created by Moroccan investors but is now fully part of the German touristic group TUI.

Emirates Airl. Etihad Airw. Qatar Airw. Air France Brussels Airl.Country UAE UAE Qatar France BelgiumNational population (millions) 4.4 4.4 1.1 61.7 10.52009 Pax (millions) 27.5 6.3 N.A. 71.4 4.72010 passenger aircrafts 142 50 87 390 51In order passenger aircrafts* 139 100 117 N.A. 0January 2010 Cities served 91 58 81 176 58

* Including aircrafts for replacing older ones, excluding options.

Table 7. Selected Gulf airlines and comparison with two European airlines Source: Airlines.

According to Vespermann et al. (2008), three different types of demand are aimed to filling the flights: domestic flights, which are limited by the small population and by the high concentration in capital cities; business travellers and the wealthy, the latter through important development in high standing tourist infrastructures, notably in Dubai; and a hub-and-spokes strategy developed at the world scale, to make Middle East airlines an intermediary between America or Europe and Asia. Indeed, according to the number of seats in 2010, Emirates Airlines and Qatar Airlines have 82% and 67%, respectively, of their supplies in the interregional market, while these figures reach 39% and 30% for British Airways and Air France, respectively10. This strategy, which is supposed to be more efficient, also involves diverting traffic from other carriers. According to Vespermann et al. (2008), two factors give some competitive advantage to Middle East companies compared to incumbent airlines. On the one hand, they have more limited operating costs due to a modern fleet, a lower labour cost, and very limited taxes (corporate income tax, ticket tax and airport charges). On the other hand, their network development toward medium-sized cities allows these companies to limit connecting flights to one instead of two or three. Besides services to global cities, Dubai serves cities like Glasgow, Newcastle, Colombo, Khartoum, Christchurch, and Brisbane. For example, on a Newcastle-Sydney journey, only one connection is necessary with Emirates Airlines, while two connecting flights are necessary with British Airways. Finally, despite the silence of the literature on this issue, high proportions of migrants may contribute to the demand of VFRs (visits to friends and relatives) toward migrants’ countries of origin. The destinations developed toward the Indian subcontinent are certainly solid indications in this direction. In this context, in the United Arab Emirates, the economic crisis did not result in the slowing down air services. As for Qatar, the increase in air supply has been limited to an annual average of 15% instead of the 30% observed before the crisis (Table 4). It appears that the crisis had no impact on the long-term development strategy of Middle East companies, yet these figures raise the question of profitability. In other words, we might question whether the demand and receipts enable Emirates Airlines or similar companies to cover their operating costs or if these developments are only possible because of public grants. It is not easy to answer to this question. According to their annual reports, Emirates airlines have been profitable: their overall load factor reached 66.8% in 2009 with a break even load factor estimated at 64.4%11. No public grants are mentioned in this report. According to Warnock-Smith and O’Connel (in press), Middle East companies receive no public grants but benefit from a good management since their creation; however, the same authors also admit that “Subsidy data for Arab airlines was not available”. In fact, most airlines only produce incomplete figures or no figures at all (Qatar Airways). More fundamentally, the limit between private and public sectors is not that clear-cut in these oil rent countries, where economic power

10 Authors’ own calculation from OAG dataset. Considering the number of available seats-kilometres, shares are

respectively 95%, 93%, 83% and 80%, respectively. 11 The Emirates Group, Annual Report 2009-2010, available at http://www.theemiratesgroup.com/english/facts-

figures/annual-report.aspx.

often directly derives from proximity to political power (Weiffen, 2008). Of course, we see no ideological objection to subsidy air companies in a long-term strategy toward economic diversification. Yet, it might explain why these air markets are not sensitive to the economic conjuncture. 4.2.6. Low-cost and hubbing strategies: the Latvian case While Latvia has been hit by a tragic economic crisis (average annual decrease of 11.5% between 2007 and 2009), its air services continued to increase by 15% each year between January 2008 and January 2010. This growth is mainly to be attributed to Air Baltic, a flag carrier belonging to the Latvian State at 52.6% and to SAS Scandinavian Airlines at 47.2%. In January 1991, just before Latvia became independent, the future Latvian State only had 10 air connections, 7 of which with USSR cities (Moscow accounting then for two-thirds of the total supply). In 1995, Air Baltic was created to serve Latvia; at this time, 20 destinations (mainly with Western Europe) were served; by 2003, the number of destinations had fallen to 15. In 2002, the carrier adopted the low-cost model. Though not all authors classify Air Baltic as a fully low-cost airline, the latter operates with attractive prices to serve Riga as well as for indirect connections going through Riga’s hub (Table 8). Then, the company started to grow; in 2008, 55 lines served Riga, with Air Baltic ensuring 39 among them. Between 2008 and 2010, four new destinations were served, with most of the growth ensured through the reinforcement of existing connections.

Air Baltic indirect flights via Riga Direct flight and airline Berlin - Kiev 206 € 261 € Ukraine International Airlines Brussels - Vilnius 209 € 212 € Lufthansa 231 € Brussels Airlines Copenhagen - Moscow 243 € 290 € SAS Frankfurt - Tashkent 303 € 606 € Uzbekistan Airways Helsinki - Vienna 175 € 199 € Austrian Airlines Paris - St Petersburg 291 € 299 € Rossiya - Russian Airlines 337 € Air France

Table 8. Comparing fares: indirect vs. direct routes Fares given all taxes, extras and one luggage included for a return flight booked on 20 December 2010 and travelling one month later, using Air Baltic website or Opodo.com for the other airlines.

This case well illustrates how low-cost and hubbing strategies may absorb the impact of the crisis for a given country or airport. If the hubbing strategy is successful, local airport dynamics become less related to local economic conjuncture and more related to the economies of the cities connected through the hub. Figure 2 illustrates that main European hubs (London, Paris, Amsterdam, Frankfurt, Madrid, Zurich, etc.) better resist the crisis than most other European airports, although there are exceptions. Low-cost carriers are also less affected by the crisis than traditional airlines. Southwest in the USA and Ryanair in Europe certainly illustrate this statement, which is reinforced in the case of Ryanair by the importance of the local public grants that it benefits. In Europe, a number of cities continued to increase their supply during the crisis, due to the importance of low-cost airlines (for example Porto, Marseilles, Charleroi, Corsica, etc.). However, looking more in-depth, we observe no correlation in Europe between the share of low-cost airlines and the air dynamics during the crisis (Figure 7); this is notably due to bankruptcies of low-cost companies during this period (e.g. SkyEurope). For cities and regions, the idea that low-cost carriers are the best way to face the crisis is not necessarily true.

Figure 7. Evolution in air service (2008-2010) vs. low-cost share in 2008 for European cities

Source: own calculations from OAG datasets.

5. Conclusions It is well known that air services dynamics are closely related to the economic conjuncture. However, no previous studies have demonstrated the close link between the evolutions of national economies and air transport during periods of recession. During the recent crisis, the higher the economic growth (or the lower the economic decrease), the more dynamic the air services at the national level. Also, at the macro-regional scale, Asian, South American, and Middle Eastern economic growth result in the development of air services, while the reverse is true in Europe, North America, or Japan. This general correlation reflects the airlines’ capacities to adapt to new economic conditions, which result in declining demand for different types of passengers: business travellers because of the economic slow down; tourism because holiday spending is very elastic to evolutions of households’ incomes; etc. However, there are many exceptions to this general trend. First, the US never really recovered from the 2001 crisis. Second, the hubbing strategies employed in some Middle East countries protected them from the crisis, as far as air transport is concerned. However, we have not been able to really uncover what lies behind the apparent success of Middle East companies because of the lack of data on public support to these companies. Third, in some poor or emerging countries, as illustrated by the Brazilian case, the growth in air services is related to the development of domestic flights, which were not sufficiently developed before. Fourth, in many small and poor countries, notably in Africa, the evolution in air services seems to be disconnected from economic conjuncture and better reflects the strategies planned by public companies. Finally, we found no correlation between airport dynamics and the share of low-cost companies though the latter seem to favour the development of air transport in some contexts, like in Morocco. Concerning the impact of economic crises on the airline industry, some questions remain. In our view, the issue of flexibility is central to understanding how the crisis impacts the geography of air transportation. Compared to other means of transport, air transport is more flexible, since airports

are the main infrastructures and procedures are very standardized. Yet we should distinguish between flexibility according to the volume and the geography of the air services, namely operated routes. In the short run, there are no major obstacles to reduce the volume of the supply or to close some routes, though the latter may create some risks in the long run for the companies according to the principle “use your slot or lose it”. In contrast, reshaping supply toward other routes is far more difficult due to local and global constraints. Locally, it is not possible to quickly move the aircrew from one place to another or to dismiss employees in one place to engage others somewhere else. Also, it takes several months to open a new route. In most international markets, airlines remain dependent on bilateral agreements, which often make it impossible to conquer new markets. In this context, it would be interesting to study companies that have been able to adapt to the crisis. In other words, how airlines respond to the crisis should be understood considering the constraints that they face to adapting their supply in its volume and its geography. Another major issue is regional trends during the crisis. Due to the lack of data and methodological issues, we have not been able to analyze the impact of the crisis on the air supply at the regional level. To achieve such an analysis, we need indicators of economic growth at the regional level, which might take several years to become available. Also, such an analysis raises the issue of the pertinent scale to assess the impact of the crisis on the geography of air transport. Ideally, the catchment area of airports — a very complicated issue — is necessary to solve such a complex question. Finally, once the crisis is over, the geography of airline recovery should be studied in detail. More precisely, the question is whether the crisis will have a structural impact on air services by reshaping its geography in the long run.

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