Tourism, smallness and insularity: a suitable combination for quality of life in Small Island Developing States (SIDS)?

Island Studies Journal, 14(2), November 2019, pages 61-80 61 Tourism, smallness and insularity: a suitable combination for quality of life in Small Island Developing States (SIDS)? Miguel Puig-Cabrera Facultad de Turismo y Finanzas, Universidad de Sevilla, Spain [email protected] (corresponding author) Concepción Foronda-Robles Facultad de Turismo y Finanzas, Universidad de Sevilla, Spain [email protected] Abstract: As Small Island Developing States (SIDS) turn into a focus of attention for tourists and foreign investment, tourism becomes one of the primary sources of wealth in these economies. This increasing relevance of tourism in SIDS in turn becomes an opportunity not only to enhance the residents’ quality of life but also to combat the existing vulnerabilities of SIDS. The main goal of this research is to measure the effects of tourism on the quality of life of residents in SIDS according to: 1) the degree of tourism development, 2) the allocation of public and private resources to promote the tourism sector, and 3) the direct opportunities that tourism offers to the populations in SIDS. In order to do so, an empirical analysis has been carried out based on a panel database containing data from 28 SIDS during the period 2005-2016. The findings suggest that tourism development becomes a driving force for enhancing the residents’ quality of life. It is also proven that government expenditure has a positive effect on the population, with a repercussion four times greater than that of private investment. Finally, work precarity appears to be a reality in SIDS. Keywords: islands, private investment, quality of life, Small Island Developing States (SIDS), small economic size, tourism development https://doi.org/10.24043/isj.95 • Received March 2019, accepted August 2019 © 2019—Institute of Island Studies, University of Prince Edward Island, Canada. Introduction Small Island Developing States (SIDS) are characterized by their small size. This condition intrinsically implies a series of factors that make these destinations more vulnerable, which are: a) smallness: the population, land area, and/or GDP are small; b) insularity and remoteness: a lack of effective and efficient transport; c) being prone to natural disasters; d) environmental vulnerability and fragile ecosystems; e) dependence on foreign economies; and f) the need for greater flexibility in order to adapt to global changes (Briguglio, 1995; Moghal & O’Connell, 2018; Naudé et al, 2009). Miguel Puig-Cabrera & Concepción Foronda-Robles 62 These features give rise to a situation of persistent socioeconomic volatility (Jackman, 2014; Read, 2018), which conditions the residents’ quality of life (QoL) (McAlber et al, 2005; Shareef & McAleer, 2005), and a vulnerability that directly harms this QoL may be present in most SIDS if appropriate measures are not taken (Scheyvens & Momsen, 2008). Although tourism activity no doubt has a considerable effect on any destination, regardless of its size, location, and sociopolitical circumstances, tourism represents an area of strength for SIDS. Forecasts for the global tourism market suggest that by the year 2030 emerging destinations and SIDS will have acquired a greater market share than traditional destinations (UNWTO, 2018a). In 2014, the SIDS Accelerated Modalities of Action (SAMOA) Pathway (UN, 2014) recognized tourism as an important route to job creation, income generation, education, poverty reduction, and sustainable development in these economies. Subsequently, the First World Conference on Tourism for Development (UNWTO, 2016) highlighted the need to measure the real effects of tourism on residents’ QoL in emerging destinations so that some of the main goals of Agenda 2030 might be achieved. The inclusion of tourism in Agenda 2030 implies the expectation that this activity will enhance residents’ QoL by contributing to the accomplishment of some of the Sustainable Development Goals (SDGs) for SIDS, such as: a) affordable and clean energy (Praene et al, 2018; Surroop et al, 2018); b) a reduction in inequality by attracting foreign investment and having efficient coordination of public initiatives (Sari, 2017); c) tackling climate change (Hess & Kelman, 2017; Robinson, 2017); and d) the sustainable use of marine resources (Alder et al, 2018; Kapmeier & Gonçalves, 2018). QoL can traditionally be defined as “the ability of people to lead the kind of life they have reason to value. It is the enhancement of the capability to live better and richer lives, through more freedom and opportunity” (Anand & Sen, 2000). The literature addresses QoL from two different perspectives: in terms of its objective and its subjective dimension (Ridderstaat et al, 2016). The first involves objective properties such as conditions and resources, which are independent of a person’s awareness (Karimi & Brazier, 2016; Lotfi & Koohsari, 2009). The subjective or emotional dimension is composed of feelings and perceptions about life based on emotions (Andereck & Nyaupane, 2011; Genc, 2012; Uysal et al, 2016). Given the peculiarities of SIDS, the tourism-QoL interaction becomes crucial (McElroy, 2006; Seetanah, 2011). Thus, tourism becomes not only a driver for the improvement of QoL, but also an opportunity to turn the vulnerabilities of these economies into a global competitive advantage (UNWTO, 2015, 2018b) in order to boost economic development. With only 1% of the world’s population living in SIDS, tourism in these states attracts approximately 3.75% of the global share, and in many cases accounts for more than 20% of the national GDP (UNWTO, 2015). The main objective of this study is to measure the effects of tourism on residents’ QoL in SIDS according to: 1) the degree of tourism development, 2) the allocation of public and private resources to promote the tourism sector, and 3) the direct opportunities that tourism offers to the populations in SIDS. To this end, an empirical analysis has been carried out based on a panel database containing data from 28 SIDS over the period 2005-2016. After this introduction, there is a literature review, together with a presentation of the hypotheses to be tested. The third section describes the data collection and the study sample used in this work. The fourth section explains the methods used to carry out the panel data Island Studies Journal, 14(2), November 2019, pages 61-80 63 analysis. The fifth section contains the findings of the analysis as well as the discussion of these findings; this section also contains some recommendations for Destination Management Organizations (DMOs). Finally, a set of conclusions is provided. Literature review Due to their size, SIDS require greater momentum than other economies to boost economic development (McGillivray et al, 2010). Numerous studies address the causal relationship tourism-QoL in a bidirectional fashion. Thus, tourism is analyzed both in terms of its effects on residents’ QoL (Andereck & Nyaupane, 2011; Kim et al, 2013; Uysal et al, 2016), and as a consequence of enhancing QoL (Ridderstaat et al, 2016; Woo et al, 2015; Yu et al, 2016). Several hypotheses have been formulated in the existing literature in order to analyze the interaction between key elements of the tourism-QoL nexus in SIDS, these elements being: 1) the degree of tourism development, 2) the allocation of public and private resources to promote the tourism sector, and 3) the direct opportunities that tourism offers to the populations in SIDS. The QoL-tourism development (QoL-Develop) interaction Tourism has always been associated with economic development (Cannonier & Burke, 2018; Chou, 2013; Fahimi et al, 2018), thus affecting residents’ QoL (Ridderstaat et al, 2016; Schubert et al, 2011). Some authors suggest that tourism development contributes to economic prosperity and development (Read, 2018; Singh, 2008; UNWTO, 2018b). However, others stress that this activity tends to aggravate the poverty of residents (Gascón, 2015; Lee et al, 2014; Scheyvens & Russell, 2012) and worsen their QoL. Pratt (2016) argues that while tourism generates a significant amount of economic activity, the income that remains in the destinations is insubstantial. Suntikul et al (2016) provide empirical evidence at a microeconomic level for the case of Hue (Vietnam), where the residents perceived tourism as an opportunity to benefit the community as a whole without it being enough to enhance their QoL as individuals. In spite of these different hypotheses, there is an absolute consensus on the positive effects of the QoL-Develop interaction in small-size economies such as SIDS (UNWTO, 2015). The greater the number of tourist arrivals and the greater the subsequent increase in incomes, the more positive are the effects of this sector on residents’ QoL in these destinations (Banwayo-Skeete & Skeete, 2015; Croes & Rivera, 2010; Ridderstaat et al, 2016). Taking the above into account, the QoL-Develop interaction is hypothesized as: Hypothesis 1: Tourism development in SIDS contributes to residents’ QoL in a positive way. The QoL-tourism promotion (QoL-Promot) interaction The only way in which tourism can benefit the population in a destination is by developing tourism activity. However, this very development requires enough existing tourism infrastructure and services for tourists not only for when they arrive at the destination, but also to fulfil their needs during the stay (Andrades & Dimanche, 2017). Given its particular characteristics, this situation in SIDS is even more complex (Moghal & O'Connell, 2018). Miguel Puig-Cabrera & Concepción Foronda-Robles 64 The intervention of public and private initiative in a destination is a critical element in making tourism possible. For example, without tourism promotion, the benefits of tourism would not be accessible to the population. The allocation of public or private resources to the tourism sector is essential (Chou, 2013; Uysal et al, 2016), not only as a contribution to an improvement in QoL, but also in order to make a destination more competitive. Foreign investment is a key component in the tourism infrastructure in SIDS, with most of the capital investment coming from outside these economies (UNCTAD, 2018), which import not only capital but also skills and ITC resources (Isik, 2015). For example, SIDS need to develop an effective transport infrastructure so that tourism can be developed by residents (Pentelow & Scott, 2011), or have a first-rate hotel (Prayag et al, 2010). In addition, effective tourism policies and special grants are needed to ensure that the local community can benefit from the tourism sector (Sharpley & Ussi, 2014). To put it shortly, unless there are enough tourism facilities and services in a destination, tourism will not be able to function properly. The QoL-Promot interaction is supposed to affect the populations in SIDS positively, by providing the means by which tourism can be made a reality and the destinations can be made more competitive (Croes, 2013; Crouch & Ritchie, 2012): Hypothesis 2: As tourism promotion in SIDS increases, so does the residents’ access to benefits, this enhancing their QoL. The QoL- job opportunities (QoL-Opport) interaction Tourism acounts for one in every 12 jobs worldwide, either directly or indirectly (UNWTO, 2018b). Some studies have analyzed the tourism-QoL nexus in terms of the number of opportunities (jobs) that tourism offers to residents (Andereck & Nyaupane, 2011; Liburd et al, 2012) in emerging destinations. Others, however, claim that the evidence provided is questionable, as these jobs immerse workers in a precarious environment (Suntikul et al, 2016), and may imply low wages, long working days, stressful conditions, and few opportunities for promotion (Lee et al, 2014). In the case of SIDS, tourism is included in the corresponding policy agendas (Shakeela et al, 2011) as a way of improving residents’ QoL by creating new jobs. The tourism sector also contributes to building and strengthening value chains with other activities in a destination, such as agriculture or handicrafts. In small economies like SIDS, this multiplier effect can be even more rewarding (UNWTO, 2015). For the purpose of the current study, the QoL-Opport interaction is supposed to be beneficial to the residents of SIDS: Hypothesis 3: The more the number of jobs related to the tourism sector increases in SIDS, the more the residents’ QoL is enhanced as they are offered new opportunities. Data The effects of tourism on SIDS are still disputed in the academic community (Pratt, 2015). In order to clearly define and resolve this dilemma, the current empirical analysis covers the period 2005-2016 and contrasts the effects of tourism on the QoL of the populations of SIDS. Island Studies Journal, 14(2), November 2019, pages 61-80 65 Although the time period of the research contains three different economic cycles (precrisis, financial crisis, and post-crisis), it has been assumed that tourism is a resilient sector (Cellini & Cuccia, 2015), which means that regardless of the global macroeconomic situation, it tends to grow gradually (WTTC, 2016). Podhorecka (2018) states that in spite of the global recession in the tourism market, in the case of SIDS there has been an increase rather than a decrease in the number of tourists and expenditure, and even the number of jobs linked to this sector. An innovation of this research is that it goes beyond a strictly monetary vision to one of economic development analyzed from a multidimensional perspective (UNDP, 2018) that concerns the population’s access to a better standard of living, as well as to what extent its educational and health needs are covered. Study sample Based on UN (2018) classification, a panel data analysis was carried out for 28 SIDS worldwide, all of which are UN member states, for the period 2005-2016. Figure 1: Study sample. The study sample used for this research was defined by data availability (Figure 1). Thus, 100% of the SIDS analyzed are UN member states (28 out of the 38 existing SIDS that are member states). The coverage of this research is worldwide, and includes SIDS from the Miguel Puig-Cabrera & Concepción Foronda-Robles 66 Atlantic Ocean, the Indian Ocean, the Mediterranean Sea, the South China Sea, the Caribbean and the Pacific Ocean. Although not all island states are consolidated tourism destinations, the main contribution of this paper is to show that, in general, tourism activity contributes to an improvement in the QoL of those island states not only in economic, but also in societal and health terms. Description of variables The variables used in this analysis have been included based on their suitability for measuring the way in which the tourism phenomenon affects residents’ QoL according to: 1) the degree of tourism development, 2) the promotion of this activity by public and private initiatives, and 3) the direct opportunities that it offers to residents (Figure 2). Figure 2: Conceptual scheme of tourism and QoL. The Human Development Index (HDI) was obtained from the United Nations Development Programme (UNDP, 2018) in order to measure the QoL achieved by the populations in the chosen time horizon (2005-2016). According to Anand and Sen’s (2000) statement, this index was created as a proxy for QoL, by measuring longevity, education, and “command over resources to enjoy a decent standard of living” (UNDP, 1990). Thus, the construct of QoL in this research is based on a three-dimensional approach: income, education and health (Haq & Zia, 2013). Since the HDI is a traditional and accepted indicator for measuring QoL (Rahman et al, 2005), it is used in research in different sectors, such as trade (Davies & Quinlivan, 2006) or tourism (Kubickova et al, 2017). The values of the HDI range from 0 to 1 point, with 0 representing the situation closest to underdevelopment (low standard of living, and unsatisfied educational and health needs), and 1 the situation of maximum development (high standard of living, and educational and health needs are met). In order to analyze tourism development in SIDS, two variables have been included: Tourism Arrivals (TA) and Tourism GDP (TGDP). TA was extracted from UNWTO’s (2018a) Compendium of Statistics for all the periods considered in this research. This variable quantifies the total amount of tourists heading to SIDS per year. TGDP was chosen as an indicator that Island Studies Journal, 14(2), November 2019, pages 61-80 67 represents the relevance of tourism within the whole economy of SIDS. The TGDP data was taken from the WTTC (2018) database in billions (bn) of US dollars (real prices). The promotion of tourism by actors in SIDS has been measured from both a public and a private perspective: Private Investment in Tourism (PI) and Government Tourism Expenditures (GTE). PI includes capital investment spent by any of the industries directly involved in the tourism sector (e.g., transport infrastructure, accommodation, and restaurants). GTE refers to government spending on tourism services of two types: cultural (e.g., cultural sites and museums) and natural (e.g., national parks and other natural attractions). Both variables were extracted from the WTTC (2018) database in billions (bn) of US dollars (real prices). There are two other variables that have been included in the empirical analysis: Direct Contribution of Tourism to Employment (DirE) and the Economic Freedom Index (EFI). DirE measures the number of opportunities (jobs) generated by tourism development. The EFI is an index that reflects the political and economic situation in SIDS, with 0 representing the least free situation, and 100 the freest. The latter variable is used in this research as a proxy. DirE was taken from the WTTC (2018) database in thousands of jobs, while the EFI was taken from the Heritage Foundation (2018). Table 1: Summary statistics of the variables used in the regressions. Mean Std. Dev. Min. Max. Obs. HDI 0.673 0.108 0.396 0.930 336 TA* 12.300 1.771 8.268 16.373 336 TGDP * -0.669 1.718 -4.605 3.412 336 PI* -2.475 1.608 -4.715 2.683 336 GTE* -1.215 1.809 -4.605 2.721 336 DirE* 2.684 1.443 -0.011 5.314 336 EFI -0.089 5.374 -41.8 32.8 336 * Variables converted to natural logs in the analysis. Methods Regression model Previous studies suggest that tourism contributes to enhancing the QoL of a destination’s residents (Pilkington et al, 2017; Telfer & Sharpley, 2016; UNWTO, 2018b). The literature also argues that economy size plays a key role in tourism and development (UNWTO, 2015, 2018b): the smaller the economy, the greater its contribution to enhancing the residents’ QoL (Chou, 2013; Dritsakis, 2012). According to the hypotheses formulated in previous sections, the following functional relationships have been put forward: 𝑄𝑄𝑄𝑄𝑄𝑄𝑖𝑖𝑖𝑖 =𝑓𝑓(𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑄𝑄𝐷𝐷𝑖𝑖𝑖𝑖,𝑃𝑃𝑃𝑃𝑄𝑄𝑃𝑃𝑄𝑄𝑃𝑃𝑖𝑖𝑖𝑖,𝑂𝑂𝐷𝐷𝐷𝐷𝑄𝑄𝑃𝑃𝑃𝑃𝑖𝑖𝑖𝑖) (1 Where QoL is the quality of life of the population in SIDS; Develop measures the degree of development of tourism activity; Promot evaluates the promotion of tourism by public and Miguel Puig-Cabrera & Concepción Foronda-Robles 68 private initiatives; Opport is the direct job opportunities that tourism offers to residents; while i is a subindex that refers to the study sample (a total of 28 SIDS) and t is a subindex that refers to the period of time covered in this research (2005-2016). Based on Equation 1, a panel data analysis was carried out on 28 SIDS for the period 2005-2016 using the ordinal least square (OLS) method: 𝐻𝐻𝐷𝐷𝐻𝐻 =𝐴𝐴𝑖𝑖𝑖𝑖 +β₁𝑇𝑇𝐴𝐴𝑖𝑖𝑖𝑖 +β₂𝑇𝑇𝑇𝑇𝐷𝐷𝑃𝑃𝑖𝑖𝑖𝑖 + β₃𝑃𝑃𝐻𝐻𝑖𝑖𝑖𝑖 + β₄𝑇𝑇𝑇𝑇𝐺𝐺𝑖𝑖𝑖𝑖 + β₅𝐷𝐷𝐷𝐷𝑃𝑃𝐺𝐺𝑖𝑖𝑖𝑖 +𝐷𝐷𝑖𝑖𝑖𝑖 (2 Where HDI stands for the Human Development Index; TA for Tourism Arrivals; TGDP for Tourism GDP; PI for Private Investment of Capital in Tourism; GTE for Government Tourism Expenditures; DirE for Direct Contribution of tourism to Employment; A is the sum of individual and temporal effects; and e represents the error term. Tourism research uses TA and TGDP as key variables to measure the relevance of tourism in a destination (Hafiz et al, 2017; Khan et al, 2017; Pulido-Fernández et al, 2015) and in SIDS (Cannonier & Burke, 2018; Shareef & McAleer, 2005). Thus, in the current study these two variables are used to represent tourism development in SIDS (Develop in Equation 1). In order to measure the promotion of tourism (Promot in Equation 1) in SIDS, two variables have been used in this research for private and then public initiative: PI is considered to be an important component in tourism development research for the evaluation of the effects of private investment on the population (Tang & Abosedra, 2016), especially in SIDS (Duffy et al, 2016; Fauzel et al 2017); and GTE is a crucial variable that measures the effects of government tourism expenditures on the residents of SIDS (Banerjee et al, 2015). DirE is used in tourism and development research as an indicator to evaluate the real opportunities (Opport in Equation 1) of residents to gain access to a better QoL in SIDS (Baum, 2012; Lee et al, 2014; Scheyvens & Russell, 2012). Napierian logarithmic transformation (Ln) was used to induce stationarity in the time series, thus assuring that the statistical properties are all constant over time. This implies Equation 1 being transformed into a level-log model (Grampella et al, 2016). In addition, a deep analysis of the properties of the series was carried out. Pesaran’s (2004) cross-sectional dependence, as well as his unit root (Pesaran, 2007) and cointegration (Westerlund, 2008), was tested. The stationarity test was undertaken in both of its forms: level and first difference. The first difference form (Δ) was used to obtain better parameter estimates of Equation 1: 𝐻𝐻𝐷𝐷𝐻𝐻 =𝐴𝐴𝑖𝑖𝑖𝑖 +β₁Ln𝑇𝑇𝐴𝐴𝑖𝑖𝑖𝑖 +β₂𝑄𝑄𝐿𝐿𝑇𝑇𝑇𝑇𝐷𝐷𝑃𝑃𝑖𝑖𝑖𝑖 + β₃Ln𝑃𝑃𝐻𝐻𝑖𝑖𝑖𝑖 + β₄𝑄𝑄𝐿𝐿𝑇𝑇𝑇𝑇𝐺𝐺𝑖𝑖𝑖𝑖 + β₅𝑄𝑄𝐿𝐿𝐷𝐷𝐷𝐷𝑃𝑃𝐺𝐺𝑖𝑖𝑖𝑖 +𝐷𝐷𝑖𝑖𝑖𝑖 (3) The method used in Equation 2 was panel-corrected standard errors (PCSE), in order to solve issues of contemporaneous correlation (Dufour & Khalaf, 2003), heteroskedasticity (White, 1980) and autocorrelation (Andrews, 1991) among variables. Beck and Katz (1995) showed that the PCSE method offers more precise results than the so-called feasible generalized least square (FGLS) estimator. Multicollinearity among the explanatory variables was also analyzed, in this case by using the values of the variance inflation factors (VIFs). Island Studies Journal, 14(2), November 2019, pages 61-80 69 Table 2: Variance inflation factors. The higher the VIF values, the greater the probability of existing multicollinearity. Even though a VIF value <10 is acceptable for proving a lack of multicollinearity, the VIF values of all of the variables in the model are <3 (Table 2), in this way conforming to a stricter criterion (Hair et al, 1995). Results and discussion All of the regression coefficients in Equation 3 are significant at level 0.01, except for LnGE, which is significant at level 0.05 (Table 3). The Wald chi-square statistics test (Prob>chi2= 0.0000) confirms that the null hypothesis is to be rejected, which means that none of the regression coefficients in the model are equal to zero. The test thus concludes that all of the variables included in the model are not simultaneously equal to zero, as the test creates a statistically significant enhancement in the fit of the model. According to the determination coefficient (R2=0.651), it is to be confirmed that a 65.1% variation of HDI can be explained by the X covariates. Contemporaneous correlation, heteroskedasticity and autocorrelation among variables were corrected using the PCSE method. It is thus confirmed that the model is valid. Table 3: Results of estimations. Coefficient Standard Error a P> | z | LnTA 0.011*** 0.0012 0.000 LnTGDP 0.009*** 0.0025 0.001 LnPI 0.001*** 0.0007 0.005 LnGTE 0.006** 0.0021 0.013 LnDirE -0.009*** 0.0025 0.005 R 2 0.651 Wald chi2 46.32 Prob>chi2 0.0000 aRobust standard errors to heteroskedasticity and serial correlation *p<0.1; **p<0.05; ***p<0.01. 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