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José Francisco Perles-Ribes* (corresponding autor) ( Ana Belén Ramón-Rodríguez* ( Antonio Rubia-Serrano** ( Luis Moreno-Izquierdo* (

*Department of Applied Economic Analysis, University of Alicante ** Department of Financial Economics and Accounting, University of Alicante

Faculty of Economics and Business Sciences University of Alicante Campus San Vicente del Raspeig 03080 Alicante Tel: 96 590 36 09 Fax: 96 590 93 22 Corresponding author details: José Francisco Perles-Ribes ( or Particular adress: Urb. Manzanera 13-R 03710 Calpe (Alicante) Tlf: +34 635 617 159


This paper considers the influence of economic crises on Spain’s tourism competitiveness. This competitiveness is measured by its share in world tourism. Analysing a period of forty years, the permanent effects of temporary or structural economic crises on competitiveness are observed. Furthermore, it identifies the economic transmission mechanisms operating and links them to the most relevant explanatory models of tourism destination competitiveness. The main conclusion obtained is that the effects of shocks on competitiveness are not neutral and that the negative effects are more persistent in highly intensive crises. This effect works through two basic transmission mechanisms: the reduction of internal and external tourism demand and falling investment.

Key words: Economic crisis, tourist destination competitiveness, permanent shocks, economics transmission mechanisms.


1.-INTRODUCTION. Spain is one of the world’s most popular tourism destinations. However the evolutionary process leading to its position has not been linear but has experienced peaks and troughs in parallel with the behaviour of the economy as a whole. At the time of writing this document, Spain was beating records in terms of international inbound tourism in a context of deep economic recession. However, the current situation should not lead us to believe that Spanish tourism is not affected by economic crises and recessions. On the contrary, a contemplation of the sector throughout history reveals that crises usually have a negative impact on Spain’s tourism competitiveness (see figure one). Depending on the intensity of the crisis, this impact can be reflected in the country’s share in the global tourism market. The objective of this study is to explain the mechanisms linking the economic crises with the competitiveness of tourism destinations.

Figure one about here



Crises and their management constitute a popular topic for tourism researchers, and many studies on the characteristics of crises and the action taken to overcome them have been carried out (Henderson, 1999). Apart from their intensity or duration, a crucial aspect of the effects of crises on tourism destination competitiveness resides in their symmetrical or asymmetrical nature. In abstract terms, asymmetries will depend on the geographical scope of the shocks – global or regional -, and whether they affect the tourists’ countries of origin, the different competing destinations or both. Figure two illustrates different types of crisis and the possible consequences that they have on destinations. Within the context of a globalisation of the tourism sector, regional crises are more likely to generate asymmetric effects than global crises. Similarly, due to the higher number of parameters susceptible to being affected, those shocks that affect both markets of origin and destination are most likely to generate asymmetric effects.

Figure two about here

The economic history of tourism between 1970 and the present day shows that all of the types of crises considered have transpired. In Spain, at the very end of the 1970s, Almagro (1979) experienced difficulties when adjusting univariate models of tourism demand, attributing the atypical values which he observed in the volumes of inbound and outbound tourists to the crises of the 1970s and the events of 1975. Sanuy (1983) pointed out that not all Spanish regions have been affected equally by the crisis; and that the crisis modifies the behaviour of demand, increasing the price sensitivity of tourists,


reducing long-distance trips and increasing “last-minute” reservations which constitute some of the potential structural effects of crises on tourism.

The crisis of the late 1980s and early 1990s opened a debate regarding whether the sun and beach mass tourism model had exhausted its potential with the emergence of a new type of post-Fordist consumer. This phenomenon in Spain is described in Aguiló, Alegre & Sard (2005). In summary, the opening-up process triggered by the fall of the “iron curtain”, together with the emergence of new competitors and the reduction of inbound tourists culminated in an exhaustion of Spain’s tourism model. Aware of this, the government implemented programmes to adapt the tourism supply to the new changes, including the Plan Marco de Competitividad del Turismo Español (Plan Futures) [Framework Plan for Competitiveness in Spanish Tourism], with respect to business and environmental aspects (Pellejero, 2004). Moreover, the 9/11 crisis exposed a series of latent problems with respect to its international tourism industry, including an international oligopoly in the wholesale travel agency industry, the singularity of the passenger air transport sector, changes in tourism demand trends and other specific structural problems regarding the Spanish supply (Cañada, 2004).

However, the crisis that has attracted most attention from tourism economists is, without a doubt, the current global financial crisis, with studies carried out by Papatheodorou, Roselló & Honggen (2010), Ritchie, Amaya and Frechling (2010), Sheldon and Dwyer (2010), Smeral (2010) and Song & Shanshan (2010) among others. These studies once again reveal the geographic and time asymmetries of the consequences of the crisis. In Spain, this crisis has exposed the structural deficiencies of the tourism development model. The poor results of 2009 are due to a higher number of 4

competitors and the tourism activities of emerging countries that constitute large markets (Instituto de Estudios Turísticos IET, 2010). This trend was reversed in 2011 and 2012, although it is evident that the results are explained more by anomalous circumstances affecting the competing destinations in North Africa than by any real improvements in the competitive advantages of Spain as a tourism destination.

In order to illustrate the effects of crises on tourism competitiveness in Spain, Table one shows the variation average of the Spanish tourism market share in for growth and crisis periods of the Spanish economy. It can be observed that the negative variations, both in absolute and relative terms, in periods of crisis are higher than the positive values recorded during economic growth periods. The evolution of tourism competitiveness in Spain measured by its share in the global market is therefore characterised by its structure, by an underlying declining trend which is explained by the natural emergence of new competing destinations within a context of an accelerated globalisation of the tourism sector and by the maturity of its main tourism product (sun and beach), in accordance with the destination lifecycle model (Butler, 1980). This structural trend is taking place alongside the circumstantial effects of cyclical variations in the Spanish economy and crisis periods in both Spain and the principal markets of origin. This is intensifying the natural loss of competitiveness of Spanish tourism, raising doubts regarding reinvestment in the industry during times of economic growth.

Table one about here



Competitiveness is one of the most topical concepts of tourism economics. The literature on the subject provides a wide range of economic and business determinants. When they are related to economic evolution, these determinants constitute transmission mechanisms between the economic climate and competitiveness. Similarly, the literature also offers numerous arguments for using market share as an appropriate indicator of revealed competitiveness. Applied to tourist destinations, competitiveness seems to be linked to the capacity of a destination to provide goods and services that are superior in aspects valued by tourists to those offered by competitor destinations (Dwyer & Kim, 2003).

3.1.-Competitiveness Models and Transmission Mechanisms.

There are many explanatory models of tourist destination competitiveness (Buhalis, 2000; Crouch & Ritchie, 1999; Dwyer & Kim, 2003; Hassan, 2000; Heath, 2003; Poon, 1993; etc.). In general, these conceptual models are based on more or less common and widely accepted definitions and consider different ranges of comparative and competitive advantages. Their differences lie in the emphasis that they give to specific aspects, such as sustainability (Crouch & Ritchie, 1999 or Hassan, 2000), adapting to developing countries (Heath, 2003) or small islands (Craigwell, 2007), etc. Almost all the models introduce economic and non-economic elements when explaining competitiveness and almost all of them base their theoretical substance on the ideas of


Porter (1991).

Bearing in mind the wide range of theories, it is relatively simple to select a series of elements to establish a connection between economic cycles and crises and the competitiveness of tourism destinations. Table two describes the main determinants of tourist destination competitiveness for the principle explanatory models and selects (bold marked) the economic elements which, in our opinion, comprise the basis of the mechanisms that will be explained below. It should be remembered that this study explores economic elements, ignoring other determinants which, although fundamental for the competitiveness of destinations, are not considered as economic or business elements as they are not influenced by economic policy.

Table two about here

3.2.-Measures and Indicators of Tourism Competitiveness.

According to Omerzel & Mihalic (2008), there is no optimal and universal model of competitiveness that can be applied to all destinations. Neither is there a generally accepted measure of competitiveness. In this context Mazanec, Wöber & Zins (2007) are right when they point out the need to take steps to transform purely defining models and systems into truly explanatory models from an analytical point of view. Of the existing definitions, the best suited for this study is that of D’Hauteserre (2000), who defines the competitiveness of a tourism destination as its capacity to maintain its position (market share) or improve it over time. According to this concept, one way to determine the success of a destination is to analyse its direct performance in the markets


through a market share analysis.

However, the use of market share as an indicator of competitiveness is not exempt from debate. Some authors such as D’Hauteserre (2000), Craigwell, Worrell & Smith (2006) or Mazanec et al. (2007) regard this variable as a direct measurement of competitiveness and incorporate it in their studies on its own or together with other elements constituting latent variables. Other authors, however, e.g. Costa, Gomà & López (2006); Cracolici, Nijkamp & Rietveld (2006); Crouch & Ritchie (1999); Dwyer, Forsyth & Dwyer (2010) and Enright & Newton (2004) consider market share to be a measure of revealed competitiveness or the final historical results of underlying competitive activity (in prices, differentiation or other elements). All in all, the association between competitiveness and market share is evident, which in our opinion justifies, together with the availability of data existing for a relatively long period of time, the use of this variable as an indicator of tourism competitiveness in Spain.

In any event, a reduction in market share does not necessarily imply a decrease in levels of development or the health of a tourist destination (Vanhove, 2011). This is because firstly, the progressive increase in market share of emerging destinations can be seen as a natural phenomenon as many countries are increasing their levels of development, and secondly, the growth of destinations is not unlimited and the territory has a maximum reception capacity.


4.-TRANSMISSION MECHANISMS OF CRISES ON TOURISM COMPETITIVENESS This section explains the causes and mechanisms that relate economic cycles to the competitiveness of tourist destinations. They are summarised in Figure three, which distinguishes between transmission mechanisms which operate on the demand side and those which operate on the supply side. The former affect the destination’s competitiveness immediately and translate into a rapid reduction in the market share of the destination if the deviation of tourists between competing destinations occurs during the crisis. The reduction in demand can also indirectly affect competitiveness through the potential impacts on the profitability of tourism companies, associated and auxiliary sectors, the levels of rivalry and the negative effects on the government which will collect less tax associated to tourism consumption and profits, lowering its capacity to invest in generic and specific advanced factors for the sector. The latter have a delayed effect on competitiveness in the medium and long term, reinforcing natural trends of losses or gains in competitiveness depending on whether the destination is an emerging market or a mature market such as Spain by reducing the capacity to create advanced factors in crisis-hit destinations which will have a lower competitive position in the medium and long term in comparison to other destinations unaffected by the crisis.

Demand and supply sides are not independent; there is important interaction between them with expectations being the main element connecting the two mechanisms. These expectations either aggravate or moderate the above-mentioned effects and will be examined in more detail below.


Figure three about here

4.1- Demand Mechanisms

Establishing the determinants and predicting the volume of demand has been one of the main focuses of researchers in tourism economics for some time. In addition to the many studies that have been carried out, there are also several reviews and compilations regarding the determinants, functional forms and data used when analysing tourism demand. Our perspective of how demand mechanisms operate is based on the reviews of Crouch (1995), Li, Song & Witt (2005), Lim (1997), Witt &Witt (1995) and Song & Li (2008).

4.1.1.-The Reduction in Disposable Income.

According to Lim (1997), tourism demand modelling is usually based on a function in which the dependent variable is the demand of international tourism services between an origin and a destination, and the explanatory variables are the level of income in the country of origin; the transport costs between the origin and the destination; the relative prices between the country of origin, the destination and competing destinations; the exchange rate of the currencies; and a wide range of qualitative factors that affect the destination. With respect to income (usually measured in real gross domestic product (GDP) or real GDP per capita), in theory, it is expected that as income increases the demand for luxury goods and services also increases. Furthermore, it can be expected that tourism demand is not only influenced by current income but also its historical


evolution, given that changes in income may take some time to affect tourism demand (Lim, 2007).

Some studies, e.g. Song, Witt & Jensen (2003), identify income as a principal determinant of tourism demand. Not surprisingly, the omission of this highly relevant variable of demand can be disastrous for research (see Witt & Witt, 1995 for their criticism on this matter). The majority of studies analyse demand in terms of elasticities. Income elasticity of demand varies both with the different origins and destinations considered (Divisekera, 2003), and with the products and segments analysed. Moreover, elasticity is influenced by the prevailing economic climate (see Durbarry & Sinclair, 2003; White, 1985). However, in general terms, tourism demand is usually tremendously elastic, whereby disposable household income immediately affects demand in this sector – see Crouch (1995), Li et al (2005), Smeral & Weber (2000) and Smeral &Witt (1996) for income elasticities of greater than one in several cases. Under these circumstances, it can be assumed that economic crises have a negative effect on the competitiveness of destinations. However, the set of interactions that occur are more complex than we would expect, and the final effect of the crises on the market shares depends on whether these crises are symmetrical or asymmetrical.

In general, economic shocks reduce disposable household incomes. When a crisis is asymmetric, and does not have an impact (or its effects are not sustained over time) in all areas of the world in the same way, for the same length of time or in the same intensity, there will be differentiated effects on tourism competitiveness. These effects, aggravated by the income elasticity mentioned above, are manifested in rapid changes


in shares of the global market of the different destinations. With respect to crises such as the current situation with a much more intense impact on the United States and Europe than East Asia or parts of South America, from a theoretical point of view, it is predicted that the market share of destinations in the US and Europe will fall rapidly and those in the latter-mentioned regions will increase.

With respect to Spain, in the short term and only in terms of demand, three reactions may be expected from European tourists who have experienced a reduction in their disposable income. First, they may forego their holidays, staying in their place of origin – highly probably, given that the profile of Spain’s tourism demand is one with a medium-low income, and particularly if the reduction in income is also combined with unemployment -. Second, they may prefer to substitute their previous trips to longdistance destinations, choosing Spain as their destination over other competitors – this is less likely as precisely the high income segments of demand are those that are less affected by the crisis -. Or three, they may prefer to substitute their previous trips to long distance destinations and those in the Spanish market with holidays in cheaper and nearer destinations (Turkey, Morocco, etc.) – highly probable. The final result is inconclusive, and will depend on the predominant effect, although it seems logical to believe that Spain will experience a reduction in the level of its tourism demand. Apart from these immediate effects on market share, there are other pernicious effects for the competitiveness of destinations in the medium and long term caused by the fall in demand due to the relationships between the different determinants of the diamond model of competitive advantage.


4.1.2.-Evolution of Prices and Exchange Rates.

According to Lim (1997), relative prices are the second most common explanatory variable in modelling the functions of tourism demand. As a proxy for relative prices, many empirical studies use consumer price index (CPI) ratios between the origins and destinations adjusted for the exchange rate between them. However, there are cases where the two variables are introduced separately in the estimate (Lim, 1997). In the same way as income, some writers, (e.g. Dwyer, 2001 or Edwards, 1995), consider prices to be the key variable of competitiveness. In theory, it would be expected that a decline in the price competitiveness of a destination is translated into a significant reduction in its demand (Dwyer et al., 2010). Therefore, a crisis which causes an overall increase in prices in the destination will ultimately affect its demand and, depending on the price evolution experienced by its competitors, its global market share.

Crouch (1995), Durbarry & Sinclair (2003), Patsouratis, Frangouli & Anastasopoulos (2005) and Witt & Witt (1995) among others, are some empirical studies that highlight the negative price elasticity of demand. Buisán (1997), González & Moral (1995, 1996) and Padilla (1988) reveal that price competitiveness with respect to both the outbound markets and competitors, is the most relevant variable in explaining international inbound demand to Spain. They also identify two stages in Spanish tourism price evolution. The first stage lasted until the mid 1980s when the behaviour of prices contributed positively to tourism demand; and the second stage, when Spain had joined the European Common Market, and tourism demand was affected negatively by the


behaviour of prices, the appreciation of the peseta and the loss in popularity of Spain as a tourist destination.

During periods of crisis tourists are highly price sensitive. Therefore, neither increasing prices nor forcing their control (action taken through price wars with no improvements in the efficiency of tourism companies), will favour competitiveness. During an asymmetrical shock, such as the present situation, three differentiated scenarios can be defined. Firstly, with respect to destinations within crisis-stricken areas; if there is an overall price increase in all the destinations – stagflation - , the increased sensitivity of clients to price will induce them to choose cheaper alternatives. This will lead to a reduction in the market shares of the more expensive crisis-hit destinations and increase those of cheaper destinations whether they are affected by the crisis or not. These results will be more or less pronounced depending on which destinations increase their market shares (whether they are among the most expensive or cheapest destinations), and which lose market share, as the degree of asymmetry of the crisis is such that the prices in some of the affected destinations increase while in others they decrease. Finally, if prices stagnate or deflation occurs in the area hit by the crisis, and in the unaffected area prices continue to experience normal growth rates, the impact on market shares will once again depend on the final price differentials between the destinations of the two areas. The region affected by the crisis may attract tourists from the unaffected area who are drawn by the low prices.

Similarly to income, apart from these short-term effects on demand flows caused by price variations, there are other medium and long term effects on competitiveness when


price wars arise from the crisis which are not justified with improvements in efficiency in the tourism companies and which sacrifice business profitability. This has a harmful effect on the creation of factors as in the case of income. The impact of price variations on competitiveness can be managed through economic policy measures, at least temporarily, by alterations in the exchange rate of the different currencies. However, this is impossible when a destination forms part of a fixed exchange rate commitment or a single currency, as in the case of Spain since 1999.

4.1.3.-Expectations and other elements.

Expectations aggravate or mitigate the effects mentioned above and are the connecting link between demand and supply mechanisms. On the demand side, expectations during recessions are associated to unemployment and adverse psychological effects caused by the continual negative news reported by the media, leading to a contraction of tourism demand in those countries affected by the crisis. Therefore, negative expectations in both countries of outbound tourism and in the destination, paralysing domestic tourism, are harmful for the competitiveness of the destination, and depending on their intensity may generate reductions in its global market share.

There are other elements, such as travel costs, tourism marketing budgets or internal demand, which can aggravate or mitigate the above-mentioned effects. All of these elements, which are modified during periods of recession, can act as transmission mechanisms of competitiveness. However, they do not fall within the scope of this study, although they are no less relevant for tourism competitiveness.


4.2- Supply Mechanisms

Supply mechanisms describe the effect that shocks have on investment and may be derived in three different ways: an increase in input costs associated with many economic crises; credit crunches in the case of financial shocks; and a reduction in the usual business confidence during periods of recession. The joint action of these elements alters business and government investment in the domestic economy and foreign direct investment (FDI) from abroad, modifying the relative working capital composition of tourism products in the different destinations. This affects their competitiveness in the medium and long term. These mechanisms have become more prominent since the 1990s, with increased globalisation and the gradual deregulation of goods, services and capital markets, including tourism.

The causes and determinants of investment as a whole and of FDI in more specific terms, like demand, are widely discussed in economic literature, which also includes many reviews. This study has taken into account the contributions of Dwyer and Forsth (1994), Dwyer et al (2010), Endo (2006), Fontagné and Pajot (1997), Hill and
Jongwanich (2009) among others. Domestic investment, both corporate and

governmental, increases during growth periods of the cycle and decreases during periods of crisis. Therefore, the effects of this mechanism are not generated because investment is higher in absolute terms during periods of crisis than during economic growth periods, but because in comparative terms, those destinations unaffected by the crises can invest relatively more, experiencing less variability in investment than crisishit destinations.


During an asymmetric shock, international investment flows, both in the form of FDI and in the form of portfolio investment, will seek opportunities in destinations unaffected by the crisis. Some investment is even made in unaffected areas by the crisisstricken destinations; see Levy-Yeyati, Panizza & Stein (2003). In this respect, the investment flows generated in periods of crisis are less relevant than the influence that shocks have on investment decisions, as in the case of the internationalisation of the Spanish hotel industry during the Spanish tourism crisis from the mid to late 1980s. (Ramón, 2002). There may be a delay in the materialisation of opportunities detected during periods of crisis which take shape in the subsequent growth phase, although the important point is that the decision will have been made during the recession. One final element to be considered resides, as in the case of demand, in the regional nature of many crises. In this case, apart from the potential flow of investment between affected destinations towards those that have not been hit by the crisis, there are also investment flows between blocks of unaffected countries. This situation is currently visible, for example, between emerging countries and is sufficient to alter the distribution of market shares of the different destinations in the medium term, depending on how they have been affected by the crisis.

Despite the complexity of the mechanisms described, the end result on competitiveness is less ambiguous than that observed in the case of demand, given that the majority of effects indicate a greater loss of competitiveness of destinations affected by crises than those which are not. The following section analyses how supply mechanisms work with an emphasis on their influence on FDI.


4.2.1.-Increase in Input Costs

As previously mentioned with respect to prices, experience shows that many economic shocks go hand in hand with cost increases (energy, raw materials etc.), which affect profitability and reduce profit margins and the capacity to invest in creating competitive factors. This was the case of the energy crises of the 1970s, the crisis at the beginning of the 1990s and the initial phases of the current global financial crisis. When increases in operating costs cannot be transferred to clients without reducing demand, there is a fall in corporate profitability which threatens the viability of tourism companies and associated and auxiliary companies. This induces companies in the affected destination to diversify risks in other markets, possibly fostering a flow of investment from crisishit destinations towards unaffected destinations. If this fall in profitability caused by increased costs is combined with a stagnation of demand generated by the recession, it is likely that international financial investors will cease to invest in affected destinations, favouring those experiencing growth.

In the short and medium term, as investment flows foster the movement of tourists from one destination to another (an effect described in Dywer & Forsyth, 1994), the market share of the destinations will change, whereby those of unaffected destinations will increase to the detriment of the crisis-stricken destinations. In the long term, the lower relative levels of investment in creating factors in the crisis-hit areas compared to those of destinations unaffected by the crisis will enhance the competitiveness of the latter


and reduce that of the former. Therefore, the effects which were initially considered as being temporary will persist over time.

4.2.2.-Credit Squeezes for Corporations, Households and Governments

A second element derived from crises which can potentially affect the competitiveness of tourist destinations are the credit crunches associated to many of them. Economic or financial shocks usually derive increased capital costs and financial restrictions for corporations, households and governments. This alters investment patterns which can modify the medium-term competitiveness of tourist destinations. Investment in tourism is particularly sensitive to the prevailing tourism situation and that of the economy as a whole. A stable economic environment stimulates investment, particularly in projects with long or very long returns related to the increase in production capacity of the company. On the contrary, uncertainty and economic downturns tend to reduce this type of investment and replace it with a simple renewal of the most obsolete assets.

The increase in interest rates increases financial costs for corporations and governments and has a negative impact on tourism and non-tourism investment projects, and is detrimental to other more attractive financial alternatives. With respect to the corporate sector, if companies cannot reinvest their declining profits in creating factors, they will have no incentive to seek external financing to do so, as the little money available will be lent with an interest rate that will render the projects unfeasible. In short, less available and more costly credit reduces investment by all economic agents in advanced factors, with a negative impact on competitiveness of crisis-hit destinations in the


medium and long term. When this availability is asymmetric, the effects on competitiveness will be differential between destinations and will be reflected in their shares of the world tourism market.

4.2.3.-Loss of Business Confidence

A loss of business confidence is the equivalent on the supply side of expectations on the demand side. When a loss in confidence is coupled with negative demand expectations the effects of the crisis on competitiveness are multiplied. When there is no business confidence there is no investment and it is difficult for private companies to create advanced factors. The concurrence of the negative effects of expectations on competitiveness is highly visible in the present financial crisis, where the levels of both business and consumer confidence are very low. As in the case of demand, the authors of this study acknowledge the existence of other elements that may influence competitiveness. The most relevant is the response of government authorities to the crisis which will depend on the situation of public finances and the economic policies implemented. Tourism investment programmes could play a predominant role in this response. However, due to limited space, this study will not address these effects in detail.


4.3-FDI and tourism competitiveness

The main effects of these supply mechanisms on the competitiveness of destinations operate through FDI. Over the last few decades there has been unprecedented growth in FDI and international trade, carried out mainly by transnational companies, whereby the service sector and the tourism industry within it constitute a principal engine of this growth (Economic Commission for Latin America ECLAC, 2003).

According to Endo (2006), the apparent demand of FDI for tourism is high. Today, capturing investment for tourism is one of the main activities of investment promotion agencies (IPA's) in developing countries. With respect to supply, the majority of FDI comes from more developed countries. The results reveal positive relationships between FDI and competitiveness in the industrial case of Fontagné & Pajot (1997), and although Dwyer & Forsth (1994) express reservations in the case of tourism (leakages) there are no reasons to believe that the situation in the tourism sector is any different. It is evident that not all FDI in tourism has the same effect on the productive fabric and growth of the recipient countries (Alfaro, 2003), however its transforming potential and influence on competitiveness is more prominent in smaller countries. Therefore, Moore & Craigwell (2008) find a bilateral relationship between tourism demand flows and FDI inflows to small islands. The higher levels of tourism activity stimulate larger FDI inflows and through the provision of infrastructure in accommodation and attractions, FDI facilitates the boom and development of tourism.


Logic tells us that in the race to capture international funds for investment, unaffected destinations are those which benefit during periods of crisis. However, empirical evidence reveals that even crisis-stricken countries or destinations may receive an inflow of international capital in the form of FDI. This, together with the regional nature of investment in tourism, clearly favours emerging destinations as opposed to the more mature markets in their efforts to increase their competitiveness (Stern, 1993). Hill &
Jongwanich (2009) point out that, paradoxically, FDI inflows can increase during periods

of crisis, although with a flight of capital in the short term. This can be explained by the different reasons behind the two types of investment. In the case of Thailand, these authors observe that during the Asian crisis inflows and outflows of FDI behaved differently. Inflows grew strongly and outflows dropped sharply, leading to an improvement in Thailand’s competitiveness in the medium and long term.

With respect to the current crisis, United Nations Conference on Trade and Development UNCTAD (2009) indicates that 2008 marked the end of a growth period in world FDI between 2003 and 2007 and confirmed its asymmetry, as it has had a greater impact on developed countries (which have suffered sharp declines in FDI) than on developing countries. It also reveals that in the current crisis the impact experienced by different countries has depended on their different degrees of international openness. Finally, it emphasises the relevance of the supply channels described, pointing out that the reduction in access to credit, negative outlooks and risk aversion have been the main causes of the decline in global FDI flows, highlighting the strength of emerging economies as new sources of FDI.



This section will carry out an empirical analysis of the afore-mentioned effects, using the time framework of 1970-2010, a period in which the country reached its tourism maturity and when the decreasing trend in Spain’s market share in international tourism began. There are forty one annual observations available, constituting a small sample size. Table three lists the variables considered, the source used and the observations pertaining to each case. The methodology applied is the estimation of models through least square linear regression (OLS).

Table three about here

5.1.-Effects of Economic Crises on Spain’s Tourism Competitiveness

Table four presents the results of different regressions of Spain’s market share with respect to representative variables of the economic cycle and crises. In the first model (model one) the market share taken in logarithms is regressed against a time trend, a quadratic trend and the logarithmic difference of Spain’s GDP and dummy variables for the crises considered. In model one all the coefficients have the expected signs. The coefficient associated to the trend reflects the declining direction of market share which is also directly affected by the economic situation (positive coefficient of GDP) and negatively by the economic crises. A lag of between one and three years has been


considered with three years required to render the dummy of the global financial crisis of 2008 significant. The diagnostic model finds that the error term is serially correlated (also true in models two and five). This required the consideration of standard deviations consistent with this result.

The rest of the models incorporate a lag of the dependent variable in order to eliminate this correlation. The incorporation of the lag variable and the disregard of heterokedastic and autorcorrelation consistent errors (HAC) reduced the number of significant parameters in the models. Model two is a dynamic model which introduces a lag of the dependent variable, eliminates static model trends and maintains the variables associated to the crisis. The result obtained is that the lag of the dependent variable absorbs the explanatory capacity of the economic situation. However, a negative and significant sign is observed for the crises of 73 and 79 and the current crisis of 2008. Model three is a combination of static and dynamic specification with a satisfactory econometric adjustment (R-squared adjusted by 0.76), but there is no reference made to the effects of the crisis. Therefore, model four introduces dummies that control the effect of the crisis. This model is estimated with standard OLS and HAC consistent errors (model five). With these deviations both the economic situation and the other variables associated to crises become significant.

Table four about here


5.2.-Modelling Competitive Transmission Mechanisms.

Table five presents three models that attempt to show the influence of the channels analysed (demand and investment) on Spain’s tourism market share. Given that the results of the analyses have revealed a very low correlation between FDI and the representative variables of tourism investment that are normally used in the literature (evolution of the number of hotels or hotel beds), models have been estimated which, together with FDI, incorporate these variables for the Spanish case. However, all the models obtained with these hotel variables have generated poor results which can be attributed to either errors in measuring the hotel variables or the poor quality of these variables as proxies of tourism investment in the case of Spain. Finally, the variation in the apparent consumption of cement was chosen as an approximate variable of tourism investment, considering that this variable represents the magnitude of Spain’s residential tourism phenomenon.

Table five about here

In model six market share is regressed against a linear and quadratic trend and the representative variables of tourism investment and demand. In order to avoid problems of endogeneity with the dependent variable and to capture more details of tourism demand, Spain’s tourism income was used as the international demand variable as opposed to the number of visitors. With respect to investment, inflows and outflows of FDI in Spain have been taken. In model six, all the coefficients have the expected sign and are significant (except the FDI outflows). In model seven the income variable has a


lag of one period and the variation in cement consumption is added also with a lag of one period. In this model, as in the previous one, all the coefficients have the expected sign. The FDI inflow variable is significant on the third lag, while the FDI outflow variable is not significant with any reasonable lag. Finally, model eight, is presented simply to illustrate the negative effects that the growth of competitors (Turkey has been taken as the most representative example), have on Spain’s share of the tourism market.

5.3.-Transmission Channels and Economic Crisis.

In order to complete the analysis, the effects of crises on demand and Spanish FDI are evaluated. Three models (see table six) in which representative variables of the channels are estimated against the economic evolution and characteristic dummies of the different crises. Model nine explains the variation of demand using the variation in the number of visitors as a dependent variable. This is a model without a constant. The introduction of a constant renders the influence of GDP on tourism demand negative, contradicting economic theory and a large part of the empirical literature on tourism demand. In this model the positive coefficient associated to the current economic crisis is striking, however, this can be explained by the effects caused by the Arab Spring, given the lags adopted for each variable. Model ten is similar to the previous model but uses income from tourism in real terms as a dependent variable. Finally, model eleven, also without a constant (here the constant is insignificant in all the models estimated), shows that the inflow of FDI is directly affected by economic evolution.

Table six about here


6.-CONCLUSIONS Spain is one of the world’s leading tourism destinations. Its evolution has experienced peaks and troughs in line with the overall evolution of the economy. The literature on tourism competitiveness supports the decision to use market share as an appropriate indicator of revealed competitiveness which also enables demand and supply transmission mechanisms to be established between the economic situation and competitiveness. A sufficient historical perspective of the crises in Spain reveals that they usually give rise to structural effects which are reflected in competitiveness with varying degrees of delay. In addition to the intensity or duration of the shocks, a crucial aspect of their effects on destination competitiveness is whether they are symmetrical or asymmetrical.

It can be observed that Spanish tourism competitiveness, measured by its share in the world market, is characterised by a declining trend which is explained by the natural emergence of new competing destinations and by the maturity of the Spain’s principal tourism product. During crisis periods, the cyclical oscillations of the Spanish economy and those of the main outbound markets have given rise to a loss in Spain’s domestic tourism competitiveness, reinforcing the negative structural trend described. This also has a negative effect on reinvestment possibilities during periods of economic growth. The analyses carried out for the Spanish case do not constitute a simple theoretical divagation but are supported by the limited data available. Therefore, this study advances the understanding of interactions between economic cycles and competitiveness, and can advise tourism agents of the effects that crises (often of an exogenous nature) may have on destinations and tourism companies. 27

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Figure 1: Spain’s market share of the international tourism sector.
Spain’s Market Share. Tena (2005) Spain’s Market share. WTO

Author’s own elaboration. Source: Tena (2005) and World Travel Organization WTO (2011).

Figure 2: Symmetrical and asymmetrical crises, potential effects on tourism destinations.
Global crisis Regional crisis







Reduction in international demand Reduction in domestic demand Decline in investment Reduction in international demand Reduction in domestic demand Decline in investment


Reduction in international demand Reduction in domestic demand Decline in investment Reduction in international demand Reduction in domestic demand Decline in investment

Destination Crisis Crisis

Author’s own elaboration.














Figure 3: Transmission mechanisms between crises and tourism competitiveness.


Table 1: Variation in Spain’s share of the tourism market during periods of crisis and economic expansion
Mean absolute values -0.90 -1.15 -0.60 0.25 -0.20 -0.35 Mean interannual variation rates -6.10 -8.61 -4.86 2.31 -1.60 -3.25

Crisis periods Period 1973-1976 Period 1979-1980 Period 1989-1991 Period 2001-2002 Period 2004-2005 Period 2007-2010


Growth periods Period1981-1988 0.14 1.25 Period 1992-1999 0.02 0.35 Period 2000-2006 0.04 0.46 Author’s own elaboration. Source Tena (2005) and National Bureau of Economic Research NBER (2012).

Table 2: Economic determinants of competitiveness. Different models Porter (1991) Crouch-Ritchie (1999) Dwyer and Kim (2003)
Nucleus of resources and Provision of resources Basic factors attraction elements Advanced factors Created resources -Infrastructure -Tourism infrastructure Auxiliary factors and -Qualified workforce -Special events resources -Technology -Infrastructure -Range of available activities -Accessibility -Entertainment Conditions of demand -Volume of demand -Shopping -Accommodation -Level of understanding and exigency -Auxiliary resources: Auxiliary factors and financial institutions, human resources Related and supporting sectors -Related companies: tourist attractions, -General infrastructure capital and knowledge restaurants, etc. -Quality of service -Management -Auxiliary companies: retail outlets, -Accessibility Management of the services, etc. -Accommodation destination. -Market links -Marketing Structure, strategy and rivalry of firms. -Financing and risk capital Management of the -Independent nature -Organisation destination. -Level of rivalry -Organisation of the -Human Resources -Commitment to the area management of the destination -IT/research system -Quality of service -Strategic marketing Government -Investment in providing factors -Tourism policy, planning and -Management of tourists -Tourism promotion development -Control or protection of -Development of human resources Circumstances -Economic crisis resources Tourism policy, planning -Non-economic crisis and development -Environmental management Competitive Localisation conditions Microenvironment. -Localisation -Competitive microenvironment Macro-environment Determinants that increase -Competitive macroenvironment and improve competitiveness Health and safety -Pricing competitiveness Demand conditions. Preferences of the tourists -Recognition of the destination -Image of the destination Author’s own elaboration based on Porter (1991), Croutch and Ritchie (1999), Dwyer and Kim (2003)

Table 3: Empirical analyses, variables used and sources.
Mechanism / Variable Dependent variable Variable Spain’s international tourism market share (Ln) Source Tena (2005) based on IET (Institute of Tourism Studies) data Observations Estimated visitors for Spain / global tourists estimated by the WTO

Independent variables Domestic economic cycle (ld_PIBSPA) Real GDP of Spain (logarithmic difference) Organisation for Economic Co-operation and Development (OECD) Organisation for Economic Co-operation and Development (OECD) Linear trend Quadratic trend Dummy 1 if t=1973,1974,1975 and 0 otherwise Dummy 1 if t=1978, 1979,1980,1981 and 0 otherwise Dummy 1 if t=1990,1991,1992, 1993 and 0 otherwise Dummy 1 if t=2001 and 0 otherwise Base year 2005

Economic cycle of outbound markets (ld_PIBUK) Trend (time) Quadratic trend (timesq) First oil crisis Second oil crisis (crisis79) Crisis at the beginning of the 1990s (crisis93) Crisis at the beginning of the 2000s, technological bubble 9/11 (crisis2001) Global Financial Crisis (crisis2008)

Real GDP of the UK (logarithmic difference)

Base year 2005 is taken to represent outbound tourist markets

Dummy 1 if t=2007,2008, 2009 and 0 otherwise Demand Mechanism

Income from tourism in Spain in real terms (ITRESP) Spain’s competitiveness Real effective exchange index rate

Bank of Spain

Organisation for Economic Co-operation and Development (OECD)

Supply Mechanism Hotel beds in Spain (Ld_Camasespana) Hotel beds in Spain General Secretariat of (logarithmic difference) Tourism and the Spanish National Statistics Institute (INE) Inflows of FDI in nominal US dollars United Nations Conference on Trade and Development (UNCTAD) Break in the series in 1999

Inflow of FDI into Spain (Ld_FDIinesp)

United Nations Conference on Trade and Development (UNCTAD) Author’s own elaboration. Visitors (overnight visitors and excursionist). Tourist (overnight visitors).

Outflow of FDI from Spain (Ld_FDIoutesp)

Outflows of FDI from Spain in nominal US dollars

Table 4: OLS Estimations. Dependent variable: l_CMERLIBTEN
(1) const time timesq ld_PIBSPA85 crisis73(-1) crisis79 crisis93(-1) crisis2008(-3) l_CMERLIBTE(-1) (2) 0.4980** (0.1736)

(3) 1.338** (0.3495) -0.009750** (0.004043) 0.0001464* (8.184e-05)

(4) 1.596** (0.3747) -0.01734** (0.006007) 0.0002742** (0.0001148) 0.4848 (0.4712) -0.1375** (0.04052) -0.03647 (0.03318) -0.04026 (0.02999) -0.07828 (0.05531)

(5) 1.596** (0.2650) -0.01734** (0.003936) 0.0002742** (8.094e-05) 0.4848* (0.2706) -0.1375** (0.02009) -0.03647 (0.02687) -0.04026* (0.02017) -0.07828** (0.02013) 0.4378** (0.09548) 38 0.8029 66,85

2.820** (0.06233) -0.02980** (0.005630) 0.0004749** (0.0001155) 0.9642** (0.3563) -0.1611** (0.03147) -0.05135 (0.03927) -0.05770** (0.02542) -0.1028** (0.02388)

0.2933 (0.3285) -0.05657* (0.02972) 0.01739 (0.02178) -0.02986* (0.01592) -0.06058** (0.01494) 0.7923** (0.07229)

0.9926** (0.4364)

0.4927** (0.1304) 40 0.7697 61.14

0.4378** (0.1327) 38 0.8029 66.85

n Adjusted R2 lnL

38 0.7379 60.8

38 0.7346 59.94

Author’s own elaboration. Standard deviations in brackets: Models (1), (2) and (5) HAC deviations. Models (3) and (4) OLS standard deviations. * indicates a 10% significance level ** indicates a 5% significance level.

Table 5: Determinant of competitiveness. OLS estimations Dependent variable: l_CMERLIBTEN (6) (7) (8) Const 2.731** 2.707** 2.674** (0.04907) (0.05197) (0.05140) Time Timesq ld_FDIinfes_1 ld_ITRESP ld_FDIoutes_2 ld_FDIinfes_3 ld_ITRESP_1 ld_cemento_1 ld_CAMASTUR_3 N Adjusted R2 lnL 38 0.6185 52.44 37 0.5903 55.19 -0.02447** (0.006154) -0.02294** (0.006008) -0.01266** (0.005359)

0.0004090** 0.0003767** 0.0001392 (0.0001349) (0.0001290) (0.0001183) 0.06711** (0.01729) 0.3407** (0.1331) -0.02958 (0.02270) -0.01781 (0.02339) 0.05712* (0.02926) 0.3066** (0.1023) 0.2699** (0.1030) -0.4478* (0.2527) 37 0.5288 50.84

Author’s own elaboration. Standard deviations in brackets, HAC deviations.* indicates a 10% significance level ** indicates a 5% significance level.

Table 6: Transmission channels. OLS estimates, using observations in period 1973-2010*

Dependent Variable ld_PIBSPA85_1 ld_tce_1 crisis_1 crisis79_1 crisis93_1 crisis2008_1 crisis2008_3 Adjusted R-squared Durbin-Watson

Model 9 ld_VISITSPALIBT 1.08593 (0.00007) -0.34251 (0.00206) -0.0830118 (0.04889) 0.000961401 (0.97393) 0.00652068 (0.32626)

Model 10 ld_ITRESP 0.998248 (0.00567) -0.791841 (0.00206) -0.138815 (

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