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Spillover analysis of tourist movements within Europe
Abstract
A tourist visiting one country is also likely to visit attractive places in neighboring countries, and it is likely to generate a spillover effect. This study analyzed this effect among the top nine tourist destination countries of the European union employing a method proposed by Barunik and Krehlik (2018) which consider frequency domain connectedness to examine spillover across countries using VAR relationship modeling. It is found that the overall spillover effect for the medium-term horizon is very high amongst the nine EU countries, but it diminished from 66.00% for the medium term to 15.81% for the long term. Spillover measures can become a useful tool for cross-country analysis of tourism variables.
... The introduction of new techniques and the outbreak of the pandemic have prompted researchers to reconsider the relationship between different tourism stocks' markets and destinations (Gokmenoglu & Hadood, 2019;Hadi et al., 2022Hadi et al., , 2023. Another stream of this research focuses on tourist spillovers between countries (Chang et al., 2020;Mitra et al., 2019) or within regions (Mitra et al., 2019). ...
... The introduction of new techniques and the outbreak of the pandemic have prompted researchers to reconsider the relationship between different tourism stocks' markets and destinations (Gokmenoglu & Hadood, 2019;Hadi et al., 2022Hadi et al., , 2023. Another stream of this research focuses on tourist spillovers between countries (Chang et al., 2020;Mitra et al., 2019) or within regions (Mitra et al., 2019). ...
This study aims to identify the sources of spillovers affecting tourism tokens and classify the type of assets to which they correspond. Using daily data for different asset classes from June 2018 through November 2022, we employ a TVP-VAR methodology to test the connectedness between two tourism tokens, two leading travel equity indices, and the two dominant cryptocurrencies, namely, Bitcoin and Ethereum. The findings show that tourism tokens are relatively independent of fluctuations in the traditional sources affecting the travel and leisure sector, such as the U.S. dollar, the price of oil, or travel equity indices. These results hint that tourism tokens are more closely related to cryptocurrencies rather than pure travel goods. The results may help decision-makers in the travel and hospitality industries considering the use of tourism tokens identify the potential forces impacting them. ARTICLE HISTORY
... The benefits created by tourism may include job creation, new businesses and post-industrial rejuvenation. The destinations which tourists visit can also benefit from spillover effects generated in adjacent regions, especially those along popular routes (Mitra, Chattopadhyay, & Jana, 2019;Yang, Fik, & Zhang, 2017, 2013. However, in many ways, there is a somewhat limited understanding of the notion of tourist dispersal. ...
... While geographical spread may infer the "breadth" of dispersal, the length of stay may reveal the "depth" of dispersal, which may imply more expenditure spent or greater impact in a particular area. In understanding tourist dispersal benefits or impacts, tourist dispersal and spillover are relative - research has been conducted at varying spatial levels, such as at the global (Mitra et al., 2019), national (Lacher & Nepal, 2013), regional, and local levels (Lau & McKercher, 2006). ...
Dispersal of tourist is a growing policy concern in Australia and New Zealand, as well as other tourist-dependent nations. However, the understanding of this field is limited. This paper summarises literature of the last three decades based on 58 shortlisted journal articles published between 1980 and 2019. Based on prior research, this paper contributes to the field by proposed an improved conceptual definition of tourist dispersal. Typical dispersal patterns are also explored, alongside with an outline of key intervening factors. For future researchers, we outlined new and old data collection methods, and also the corresponding analytical approaches. There is a growing trend to use more advanced tracking methods to address the limitation of prevailing approaches, such as tourist survey or travel diaries. Quantitative approaches have been the mainstay of research but qualitative approaches are also able to capture unique aspects of tourist psychology and motives to disperse. Significant gaps remain in existing knowledge and the potential for dispersal to improve destination fortunes and tourist experience are still unknown. Future research ought to combine various approaches by combining datasets and also methodologies.
... First, the univariate global Moran's I value of domestic tourism flows and PM 2.5 were all greater than zero from 2001 to 2015 and passed the 1% level significance test (the p-value is omitted in the figure), indicating that the domestic tourism flows and PM 2.5 had a significant positive spatial correlation; that was, the domestic tourism flows or PM 2.5 of a region was affected by the domestic tourism flows or PM 2.5 of the surrounding area. This result regarding domestic tourism flows was consistent with the conclusions of Yang and Fik [18] and those of Mitra et al. [49], thus laying the foundation for the use of the GTWR model below. ...
As haze pollution intensifies, its impact on tourism is becoming increasingly obvious. However , limited studies have analyzed the impacts of haze pollution on tourism. To explore the contribution rate and impact of PM 2.5 pollution on tourism flows, panel data on 341 prefecture level cities in China from 2001 to 2015 were used. The results illustrated that the changes in PM 2.5 pollution and domestic tourism flows showed a similar partial-most anti-phase main spatial pattern in space, as well as other spatial patterns of PM 2.5. From a regional perspective, the contribution rate of PM 2.5 to domestic tourism flows was less than that of traditional factors, such as GDP, GDP_500, and 45A, but larger than that of the Airport factor. The contribution rate of the interaction between PM 2.5 and 45A on domestic tourism flows was the largest. From a local perspective, PM 2.5 pollution had a negative impact on domestic tourism flows in northern China, while it had a positive impact in other regions. The classic environmental Kuznets curve (EKC) hypothesis showed applicability to the Chi-nese tourism industry, and the is of great significance for comprehensively understanding the impact of PM 2.5 pollution on tourism flows and for promoting the sustainable development of domestic tourism.
... Given the similar climatic conditions, macroeconomic factors, Schengen visa, and others, long-haul tourists who take a single trip to the European Union tend to visit multiple countries. Romao and Nijkamp (2019) and Mitra et al. (2019) have demonstrated significant spatial effects among European countries. The monthly tourism demand data are available from the Eurostat website (http://ec.europe.eu/eurostat), ...
Tourism demand forecasting is a crucial prerequisite for effective and efficient tourism management. This study develops a novel model based on deep learning methods for precise demand forecasting, namely, spatial-temporal fused graph convolutional network (ST-FGCN). ST-FGCN generates forecasts based on spatial effects extracted using graph convolutional network and temporal dependency captured through long short-term memory. A data-driven spatial matrix is used in our model to strengthen forecasting performance further. Two markedly different forecasting experiments verify the effectiveness of our model. Empirical results suggest that incorporating spatial effects can remarkably reduce forecasting errors. Furthermore, our model shows good applicability for data with different time granularity and different periods: before and during the COVID-19 pandemic.
... Collaborative efforts between regions could be developed on the basis of so-called "tourism spillovers", which may be defined as those impacts that one region inadvertently causes for another (Yang & Wong, 2012). The impact of spillover effects on tourism demand has become a trending topic in the tourism literature in recent years (Mitra et al., 2019;Balli et al., 2015;Yang & Fik, 2014;Yang & Wong, 2012), especially thanks to the great advances in transport, which have enabled the indirect effects of tourism to take on a greater scope (Li et al., 2016). A part of this literature has focused on detecting the factors favouring the indirect effect of tourist flows between regions. ...
Spain is one of the most visited countries in the world. However, given that the number of tourist arrivals hugely differ among Spanish regions, notable tourist regional inequalities are perceived in this country. In this context, spatial econometric techniques can be used as an instrument to understand these regional disparities. In particular, this work analyses the existence of regional spillovers in Spain, while also identifying the degree of sensitivity of the different regions to fluctuations in the general trends of the domestic and foreign tourist arrivals. Our results reveal (i) that the tourist arrivals are persistent over time, (ii) the presence of spatial dependence between regions in terms of domestic and international tourism —the latter being greater— and (iii) the existence of heterogeneity between regions in terms of sensitivity to tourist arrivals. These findings may favor the design of a common strategy to promote the alleviation of current regional inequalities as well as better tourism strategies to face tourism changes, either as general trends or unexpected events.
... The concept spillover effect has been discussed in broad contexts to understand the impact of one seemingly unrelated event and its associated entity (e.g., an organization, a region, a country) on the other (Yang & Wong, 2012). Spillover effects have been applied to, inter alia, brand extension (Balachander & Ghose, 2003), product promotion (Parshakov, Naidenova, & Barajas, 2020), service failures (Schumann, Wünderlichb, & Evanschitzkyc, 2014), tourism (Mitra, Chattopadhyay, & Jana, 2019;Yang & Wong, 2012), economy (Cheung & Ping, 2004), finance (Buckley, Clegg, & Wang, 2010), entrepreneurship (Aarstad, Haugland, & Greve, 2010) and real estate (Lin, Rosenblatt, & Yao, 2009). No research to date has attempted to understand the likely spillover effects exerted by travellers' airport service experience on their destination choice. ...
The study applies the spillover effect and complexity theories to examine the relationship between customers' service experience at the airports and their destination choice. Symmetrical and asymmetrical methods are proposed to test this relationship to reveal the complexity theory underlying the spillover effects. Symmetrical testing is manifested in structural equation modelling and regression analysis whereas the asymmetrical method in fuzzy-set qualitative comparative analysis. The data were collected from departure passengers in multiple airports in Australia and India. The results from symmetrical and asymmetrical testings differ significantly. A positive spillover effect is confirmed; however complex relationships are shown between customers’ service experience at the airports and their destination choice. Discussion and implications of the study findings are presented to conclude this paper.
... The implications of the results suggest that equity portfolio investors and equity risk managers should carefully and continuously monitor changes in stock market expectations, using the most cutting-edge 1 We are thankful to the anonymous referees for their suggestion to incorporate the frequency connectedness approach. The approach has sought enormous attention in recent years, however, some of the recent studies are: Mitra et al. (2019) spillover analysis for tourist movements in Europe; Tiwari et al. (2020) for causal connectedness between energy, food, industry, agriculture, and metals; Liu and Hamori (2020a) for spillovers analysis of clean energy stocks in the US and Europe; Jiang at al. (2020) for various industries in China; Zhang et al. (2020) for energy products and financial conditions; Liu et al. (2020) examine the influence of Fossil Fuel commodities on electricity markets; Liu and Hamori (2020b) investments in renewable energy stocks with ESG index. Zhang and Hamori (2021) examine the extent of returns and volatility spillovers between crude oil and significant equity markets during the early phases of COVID-19 Pandemic; Mensi et al. (2021) commodity futures and stock market connectedness. 2 The relevant studies are: Bašta and Molnár (2018), Antonakakis et al. ...
The paper explores the role of tourism demand and cultural World Heritage Sites on the regional economic resilience among European Union countries. The results pinpoint to the importance of cultural World Heritage Sites in keeping the regional economic resilience. The results on tourism demand are not unambiguous—domestic tourist arrivals play a significantly positive role while inbound tourist arrivals negatively affect regional economic resilience. Cultural tourism, defined as the joint effect of tourism and cultural sites, decreases the negative effect of inbound tourism, pinpointing that the cultural sites play an essential role in attracting inbound tourists in the less prosperous periods.
This research analyzed the behavior of receptive tourism in Ecuador and its relationship with the United States’ economy. An index was developed to measure instability and crisis levels as well as the vector autoregressive models - VAR, cointegration as well as hypothesis tests through vectors. The findings indicate that Ecuador endured a crisis 12 out of 19 years; on the other hand, while the United States entered a crisis, the figures of Ecuadorian tourism improved. Likewise, the GDP’s inverse growth movement influenced the reduction in the number of tourists. Therefore, expenditure capacity decided the touristic destination, not so Ecuador’s internal cost index. Finally, it was proven that the average expenditure of a foreign tourist was reduced across time.
This study explores the time and frequency spillover relationship between the political risk (PR) of major importers and exporters and the stock returns of China's rare earths (RER) by using the spillover index proposed by Diebold and Yilmaz (2012, 2014) (D&Y (2012, 2014)) and Baruník and Křehlík (2018) (B&K (2018)). The research results indicate that the average total spillovers between PR and RER are 35.55%, in which short-term spillovers play a dominant role with the average proportion of 71.21%. In particular, the spillover index increases significantly during major financial and political events, including the global financial crisis, European debt crisis, China-Japan diplomatic event, the crisis between Russia and Ukraine, the announcement of WTO dispute resolution about rare earths (REs) and the US presidential election. In addition, Myanmar has the largest PR index, which is also the biggest contributor in the spillover network regardless of time periods. In terms of RER, it is a net receiver of spillovers from PR, which obtains more spillovers from importing countries than exporting countries. Generally, Japan, Estonia, Myanmar and the Netherlands are the top spillover emitters to RER while Germany, France, Japan and India are the main spillover receivers from RER. Moreover, Japan emits evidently more spillovers to RER in the long term and during major political event.
This study examines the spillover role of the implied volatilities of oil, gold, and the stock market with US equity sectors. Using time and frequency-based spillover methods, we find that the market’s expectation of oil price volatility (OVX) spillovers less strongly on the US sectoral returns than the market’s expectation of US stock market volatility (VIX), which exhibits the dominant spillover role. The market’s expectation of gold price volatility (GVZ) has a zero range spillover effect on the sectoral returns and is the most weakly affected by them, suggesting that gold can be used to hedge downside risk in all 10 US equity sectors considered. We also find that the US equity sectors’ spillovers on the VIX and OVX strengthen because of the coronavirus (COVID-19) outbreak.
This study conducts spatial-temporal forecasting to predict inbound tourism demand in 29 Chinese provincial regions. Eight models are estimated among a-spatial models (autoregressive integrated moving average [ARIMA] model and unobserved component model [UCM]) and spatial-temporal models (dynamic spatial panel models and space-time autoregressive moving average [STARMA] models with different specifications of spatial weighting matrices). An ex-ante forecasting exercise is conducted with these models to compare their one-/two-step-ahead predictions. The results indicate that spatial-temporal forecasting outperforms the a-spatial counterpart in terms of average forecasting error. Auxiliary regression finds the relative error of spatial-temporal forecasting to be lower in regions characterized by a stronger level of local spatial association. Lastly, theoretical and practical implications are provided.
This study analyzes return and volatility spillovers across global crude oil markets for 1 January 1991 to 27 April 2018, using an empirical technique from the time and frequency domains, and makes four key contributions. First, the spillover tables reveal that the West Texas Intermediate (WTI) futures market, which is a common indicator of crude oil indices, contributes the least to both return and volatility spillovers. Second, the results also show that the long-term factor contributes the most to returns spillover, while the short-term factor contributes the most in terms of volatility. Third, the rolling analyses show that the time-variate connectedness in terms of returns tends to be strong, but there was no noticeable change from 1991 to April 2018 in terms of volatility. Finally, the major events between 1991 and April 2018, namely the Asian currency crisis (1997–1998) and the global financial crisis (2007–2008), caused a rise in the total connectedness of returns and volatility.
This study develops a global vector autoregressive (global VAR or GVAR) model to quantify the cross-country co-movements of tourism demand and simulate the impulse responses of shocks to the Chinese economy. The GVAR model overcomes the endogeneity and over-parameterisation issues found in many tourism demand models. The results show the size of co-movements in tourism demand across 24 major countries in different regions. In the event of negative shocks to China’s real income and China’s tourism price variable, almost all of these countries would face fluctuations in their international tourism demand and in their tourism prices in the short run. In the long run, developing countries and China’s neighbouring countries would tend to be more negatively affected than developed countries.
Purpose
The purpose of this paper is to review recent studies published from 2007 to 2015 on tourism and hotel demand modeling and forecasting with a view to identifying the emerging topics and methods studied and to pointing future research directions in the field.
Design/methodology/approach
Articles on tourism and hotel demand modeling and forecasting published mostly in both science citation index and social sciences citation index journals were identified and analyzed.
Findings
This review finds that the studies focused on hotel demand are relatively less than those on tourism demand. It is also observed that more and more studies have moved away from the aggregate tourism demand analysis, whereas disaggregate markets and niche products have attracted increasing attention. Some studies have gone beyond neoclassical economic theory to seek additional explanations of the dynamics of tourism and hotel demand, such as environmental factors, tourist online behavior and consumer confidence indicators, among others. More sophisticated techniques such as nonlinear smooth transition regression, mixed-frequency modeling technique and nonparametric singular spectrum analysis have also been introduced to this research area.
Research limitations/implications
The main limitation of this review is that the articles included in this study only cover the English literature. Future review of this kind should also include articles published in other languages. The review provides a useful guide for researchers who are interested in future research on tourism and hotel demand modeling and forecasting.
Practical implications
This review provides important suggestions and recommendations for improving the efficiency of tourism and hospitality management practices.
Originality/value
The value of this review is that it identifies the current trends in tourism and hotel demand modeling and forecasting research and points out future research directions.
Hospitality constituencies need accurate forecasting of future performance of hotels in specific destinations to benchmark their properties and better optimize operations. As competition increases, hotel managers have urgent need for accurate short-term forecasts. In this study, time-series models incorporating several tourism big data sources, including search engine queries, website traffic, and weekly weather information, are tested in order to construct an accurate forecasting model of weekly hotel occupancy for a destination. The results show the superiority of ARMAX models with both search engine queries and website traffic data in accurate forecasting. Also, the results suggest that weekly dummies are superior to Fourier terms in capturing the hotel seasonality. The limitations of the inclusion of multiple big data sources are noted since the reduction in forecasting error is minimal.
The proliferation of multidestination trips provides valuable opportunities for regions to benefit from spillover effects generated by other regions nearby. To better understand the spatial patterns of multidestination travel, we propose a two-stage distance-based model. Results suggest that long-haul tourists (i.e., those who travel far from home) tend to choose a subsequent destination that is closer to the previous destination but farther away from their residences. In addition to sociodemographic and tripographic factors, we recognize the importance of spatial structure effects in determining the travel distance for a multidestination trip. Based on the model estimates, we propose a tourism spillover index to reflect a region’s potential to receive spillover benefits from multidestination tourists leaving a particular region. Finally, we discuss implications for marketing strategies to enhance the attraction potential of specific destinations.
International tourism is susceptible to fluctuations and shocks. The spillovers of international inbound tourism between Australia and New Zealand have been one of the key issues for both governments and tourism authorities to address. This paper used a bivariate GARCH model to investigate the spillovers of international tourist arrivals between Australia and New Zealand from seven countries (Canada, China, Germany, Japan, Korea, United Kingdom, and United States). The monthly international tourist arrivals between 2000 and 2012 were used for the empirical analysis. The findings suggested a significant spillover of Chinese and Japanese tourists from New Zealand to Australia, whereas New Zealand’s tourism demand from China and Japan was not significantly affected by that of Australia. However, New Zealand’s inbound tourism from Canada, Germany, and United States was significantly affected by tourism demand from those countries to Australia. Furthermore, symmetric spillovers between Australia and New Zealand (in both directions) existed for UK tourists.
In this paper, we have investigated the linkages between the international tourism demands across tourism regions in New Zealand. The big portion of the international tourists is visiting the big hubs of the New Zealand (namely, Auckland, Wellington and Christchurch). However, big bulks of the tourists are also visiting the other parts of New Zealand as well. However, it is not certain whether the tourists visiting other regions are spilled over from these big hubs or they visit these regions as the main destination. To investigate this question, we examined the impact of the spillovers from these hubs to other regions of New Zealand. We employed a multivariate AR-GARCH model to estimate the spillover effects for both New Zealand's North Island and South Island regions. In particular, we quantified and compared the magnitudes of the main hubs on the volatility of the international tourism demand of the other regions. We found that the spillovers from the main centres are by and large important for a number of Regional Tourism Organisations (RTOs), thereby suggesting that both expected guest night and volatility spillovers are important in explaining New Zealand's international hotel guest nights. We also quantified that, on average, 52% of the volatility in a South region tourism demand is explained by the volatility in tourism demand of Christchurch, whereas this rate is much lower in North Island which is around 25%. However, this is quite an evidence for the integration of the international tourism demand spillovers among New Zealand regions.
The purpose of this study is to compare the predictive accuracy of various uni- and multivariate models in forecasting international city tourism demand for Paris from its five most important foreign source markets (Germany, Italy, Japan, UK and US). In order to achieve this, seven different forecast models are applied: EC-ADLM, classical and Bayesian VAR, TVP, ARMA, and ETS, as well as the naïve-1 model serving as a benchmark. The accuracy of the forecast models is evaluated in terms of the RMSE and the MAE. The results indicate that for the US and UK source markets, univariate models of ARMA(1,1) and ETS are more accurate, but that multivariate models are better predictors for the German and Italian source markets, in particular (Bayesian) VAR. For the Japanese source market, the results vary according to the forecast horizon. Overall, the naïve-1 benchmark is significantly outperformed across nearly all source markets and forecast horizons.
The main purpose of this research is to investigate and estimate the spillover effects in inbound and domestic tourism flows to 341 cities in mainland China. In conjunction with this, the key determinants of tourism flows are also studied in the spatial econometric model. The results confirm the existence of spillover effects in both inbound and domestic tourism flows, and suggest that physical infrastructure factors, tourist attractions, and the SARS outbreak are significant determinants of inbound and domestic tourism flows. In addition, it is found that although the degree of openness to inbound tourists is important for inbound tourism flows, a city’s income is the key to enhancing domestic tourism flows. Significant differences in spillover effects and determinants of tourism flows are also discovered between cities in different regions.
The study investigates the influence of tourism on economic growth and CO2 emissions. In the empirical analysis, unit root and cointegration tests using panel data of European Union countries from 1988 to 2009 are performed to examine the long-run equilibrium relationship among tourism, CO2 emissions, economic growth and foreign direct investment (FDI). Results from panel cointegration techniques and fixed-effects models indicate that a long-run equilibrium relationship exists among these variables. Furthermore, tourism, CO2 emissions and FDI have high significant positive effect on economic growth. Economic growth, in turn, shows a high significant positive impact on CO2 emissions while tourism and FDI incur a high significant negative impact on CO2 emissions.
We propose several connectedness measures built from pieces of variance decompositions, and we argue that they provide natural and insightful measures of connectedness among financial asset returns and volatilities. We also show that variance decompositions define weighted, directed networks, so that our connectedness measures are intimately-related to key measures of connectedness used in the network literature. Building on these insights, we track both average and daily time-varying connectedness of major U.S. financial institutions' stock return volatilities in recent years, including during the financial crisis of 2007-2008.
Using a generalized vector autoregressive framework in which forecast-error variance decompositions are invariant to variable ordering, we propose measures of both total and directional volatility spillovers. We use our methods to characterize daily volatility spillovers across U.S. stock, bond, foreign exchange and commodities markets, from January 1999 through January 2010. We show that despite significant volatility fluctuations in all four markets during the sample, cross-market volatility spillovers were quite limited until the global financial crisis that began in 2007. As the crisis intensified so too did the volatility spillovers, with particularly important spillovers from the stock market to other markets taking place after the collapse of Lehman Brothers in September 2008.
Small Island Tourism Economies (SITEs) are developing sovereign countries that rely on tourism as a source of exports, and need a consistent inflow of foreign investment in order to facilitate economic growth. Access to international capital markets helps SITEs smooth out their consumption over time, while absorbing adverse domestic production shocks. This paper provides a comparison of tourism growth, country risk returns and their associated volatilities (or uncertainty) for 2 SITEs, namely Cyprus and Malta. Monthly data are available for both international tourist arrivals and composite country risk ratings compiled by the International Country Risk Guide (ICRG) for the period May 1986 to May 2002. The time-varying conditional variances of tourism growth and country risk returns for the 2 SITEs are analysed using multivariate models of conditional volatility. Empirical results show that Cyprus and Malta are complementary destinations for international tourists. Changes to tourism patterns in Cyprus lead to changes to tourism patterns in Malta. Hence, tour operators and national tourism promotion authorities in Cyprus and Malta should collaborate closely in marketing and promoting joint tourism products. Moreover, foreign entities interested in investing in the tourism sectors of Cyprus and Malta should consider investment projects that span a long period of time. The performance of the tourism sector and the associated composite risk are independent of each other for the two countries. However, there is a direct relationship between the tourism sectors of Cyprus and Malta and their respective country risk settings.
Eighty-four post-1990 empirical studies of international tourism demand modeling and forecasting using econometric approaches are reviewed. New developments are identified and it is shown that applications of advanced econometric methods improve the understanding of international tourism demand. An examination of the 22 studies which compare forecasting performance suggests that no single forecasting method can outperform the alternatives in all cases. However, the time-varying parameter (TVP) model and structural time series model with causal variables perform consistently well.
We provide a simple and intuitive measure of interdependence of asset returns and/or volatilities. In particular, we formulate and examine precise and separate measures of "return spillovers" and "volatility spillovers". Our framework facilitates study of both non-crisis and crisis episodes, including trends and bursts in spillovers; both turn out to be empirically important. In particular, in an analysis of 19 global equity markets from the early 1990s to the present, we find striking evidence of divergent behaviour in the dynamics of return spillovers vs. volatility spillovers: return spillovers display a gently increasing trend but no bursts, whereas volatility spillovers display no trend but clear bursts. Copyright © The Author(s). Journal compilation © Royal Economic Society 2009.
This paper investigates the dynamic connectedness between gold, sukuk and Islamic equities at multiple investment horizons, it also computes optimal hedge ratios and portfolio weights for these assets. Our findings suggest that gold hedges the risk of sukuk in the short and medium terms, and that gold plays an average but stable role in hedging and diversifying Islamic equities across all investment horizons. Moreover, we document a diversification benefits of portfolios combining gold and Islamic equities in the short term. These empirical findings highlight the important role that gold plays in the diversification and hedging of Islamic assets.
We propose a new framework for measuring connectedness among financial variables that arise due to heterogeneous frequency responses to shocks. To estimate connectedness in short-, medium-, and long-term financial cycles, we introduce a framework based on the spectral representation of variance decompositions. In an empirical application, we document the rich time-frequency dynamics of volatility connectedness in U.S. financial institutions. Economically, periods in which connectedness is created at high frequencies are periods when stock markets seem to process information rapidly and calmly, and a shock to one asset in the system will have an impact mainly in the short term. When the connectedness is created at lower frequencies, it suggests that shocks are persistent and are being transmitted for longer periods. © The Author(s) 2018. Published by Oxford University Press. All rights reserved.
This paper analyzes the volatility spillovers across four global asset classes namely, stock, sovereign bonds, credit default swaps (CDS) and currency from September 2009 to September 2016, using both a time-domain and a frequency-domain framework. When the Diebold and Yilmaz (2012) methodology is applied, the estimated total connectedness index is 5.08%, suggesting a low level of connection among the four markets. Furthermore, the results show that the stock and CDS markets are net transmitters of volatility, while foreign exchange and bond markets are net receivers of the spillovers. When the Barunik and Krehlik (2018) frequency-domain analysis is carried out, the results indicate, first, that at higher frequencies, the degree of connectedness increases, and, second, that the net transmitter of volatility spillovers across the markets is contingent on the frequency under consideration.
This article explores the extent to which changes to long-term interest rates in major advanced economies have influenced long-term government bond yields in emerging Asia. To gauge long-term interest spillover effects, the article uses vector autoregressive (VAR) variance decompositions with high frequency data. Our results reveal that sovereign bond yields in emerging Asia responded significantly to changes to US and eurozone bond yields, although the magnitudes were heterogeneous across countries. The size of spillovers varied over time. The pattern of these variations can partially be explained by the implementation of different unconventional monetary policy measures in advanced countries.
This study explores the effect of economic policy uncertainty (EPU) in four countries or regions (China, Japan, Europe, and the United States) on the contagion risk of investments in the global stock market. The stock returns of 22 stock markets worldwide are analyzed to determine which region’s EPU exhibits the greatest effect on regional systematic risk in the global stock market and on volatility risk in individual stock markets. First, all of the samples, the markets of different continents and the spillover indices of the developed and emerging markets, are calculated to observe the dynamic correlation among these markets with the aim of quantifying regional systematic risk and further examining the contagion risk effect of EPU. The results indicate the following: EPU in China is the most influential, and its contagion risk spreads to different regional markets, except for Europe; the effect of EPU in the United States is inferior to that in China; EPU in Japan merely influences contagion risk in emerging markets; contagion risk in European markets is not influenced by the four EPU indices; and EPU in Europe is not influenced by contagion risk in the global stock market. However, according to the volatility risk in each market, the EPU in Europe and China respectively influence Asian countries and European countries the most. These results may be attributable to the extremely high trade dependence among these countries because the performance of international enterprises is mainly determined by the economic policies of their trading partners.
This study examines the antecedents of destination loyalty and its relation to destination image, consumer travel experience, and destination satisfaction in the tourism context. This study raises important questions concerning how destination image, consumer travel experience, and destination satisfaction affect destination loyalty. This research attempts to identify three key antecedents of loyalty in the tourism context. The study empirically tests predicted relationships by using personal interview data from 475 foreign tourists. The conceptual model investigates the relevant relationships among the research constructs by using fuzzy-set Qualitative Comparative Analysis (fsQCA) and structural equation modeling (SEM) approach. Findings from the research sample support the argument that destination image, consumer travel experience, destination satisfaction are the key determinants of destination loyalty. Furthermore, destination image and consumer travel experience influence destination satisfaction. The study also discusses theoretical and managerial implications of research findings for marketing the tourism products globally.
This paper is aimed to test the causality relationship between the cycles of tourism and economic development for the case of Spain using quarterly time-series data on gross domestic product, the number of nights spent in Spanish tourist accommodations and real exchange rates from 1980 to 2013. A distinction between nights spent by foreign and national tourists is also made. Although no evidence of causality is found on preliminary results, structural breaks affecting the relationships between the variables are detected. Causality from economic growth towards tourist activity is found until 1985. Results also confirm bidirectional causality from 2000 onwards. Copyright © 2014 John Wiley & Sons, Ltd.
The present study investigates the effect of tourism and its spatial correlation on urban economic growth. The study examines 272 prefecture-level administrative units between 2002 and 2011 in China as the sample and a β convergence model as the frame. The conclusions are that tourism development has a substantial impact on urban economic growth in China without decreasing the economic gap among cities. The tourism growth effect contributed primarily in the development of positive spatial correlation that led to spatial spill-overs—a large indirect effect; the direct effect of tourism on local economies was minimal. Introducing spatial correlation analysis of the relationship between tourism and urban economic development avoids reaching misleading conclusions and enables the analysis of both direct and indirect effects of tourism development.
In this study, we examine the dynamic relationship between tourism growth and economic growth, using a newly introduced spillover index approach. Based on monthly data for 10 European countries over the period 1995{2012, our analysis reveals the following empirical regularities. First, the tourism-economic growth relationship is not stable over time in terms of both magnitude and direction, indicating that the tourism-led economic growth (TLEG) and the economic-driven tourism growth (EDTG) hypotheses are time-dependent. Second, the aforementioned relationship is also highly economic event-dependent, as it is influenced by the Great Recession of 2007 and the ongoing Eurozone debt crisis that began in 2010. Finally, the impact of these economic events is more pronounced in Cyprus, Greece, Portugal and Spain, which are the European countries that have witnessed the greatest economic downturn since 2009. Plausible explanations of these results are provided and policy implications are drawn.
This paper examines the size effects of volatility spillovers for firm performance and exchange rates with asymmetry in the Taiwan tourism industry. The analysis is based on two conditional multivariate models, BEKK–AGARCH and VARMA–AGARCH, in the volatility specification. Daily data from 1 July 2008 to 29 June 2012 for 999 firms are used, which covers the Global Financial Crisis. The empirical findings indicate that there are size effects on volatility spillovers from the exchange rate to firm performance. Specifically, the risk for firm size has different effects from the three leading tourism sources to Taiwan, namely USA, Japan, and China. Furthermore, all the return series reveal quite high volatility spillovers (at over 60%) with a one-period lag. The empirical results show a negative correlation between exchange rate returns and stock returns. However, the asymmetric effect of the shock is ambiguous, owing to conflicts in the significance and signs of the asymmetry effect in the two estimated multivariate GARCH models. The empirical findings provide financial managers with a better understanding of how firm size is related to financial performance, risk and portfolio management strategies that can be used in practice.
Decisions regarding appropriate investments in both the public and private sectors, as well as short-term marketing decisions, depend heavily on the accuracy of forecasts of tourism demand. This article reviews both the qualitative and quantitative approaches to demand forecasting in tourism and suggests that the two approaches combined produce more accurate forecasts.
Maldives and Seychelles in the Indian Ocean are small island tourism economies (SITEs), both of which have relatively small populations, territorial sizes, land area and narrow productive bases. The two SITEs are surrounded by vast ocean and have an overwhelming reliance on international tourism for economic development. Variations in international tourist arrivals to these two SITEs have been affected by unanticipated oil shocks, natural disasters, crime and global terrorism, among others. An accurate assessment of the variations in international tourist arrivals, particularly the conditional volatility, is essential for policy and marketing purposes. The conditional mean and conditional variance of the weekly international tourist arrivals to Maldives and Seychelles from 1 January 1994 to 31 December 2003 for the five main tourist source countries are modelled. Multivariate models of uncertainty are estimated and tested. An assessment and interpretation of the estimates are made for policy makers and tour operators to reach optimal decisions on the basis of a portfolio approach to international tourism demand. The paper assesses four sets of country spillover effects between Maldives and Seychelles, namely (i) the own country effects for Maldives and Seychelles; (ii) the country spillover effects from the remaining four countries within each of Maldives and Seychelles; (iii) the own country spillover effects between Maldives and Seychelles; and (iv) the cross-country spillover effects between Maldives and Seychelles. The empirical results for both Maldives and Seychelles are discussed in terms of each of these components.
How much economic stimulus does tourism provide by generating jobs in various local industry sectors? Using data across 43 U.S. metropolitan statistical areas during 1987-2006, we analyze the impact of tourism inflows - proxied by the number of hotel rooms sold - on the employment in 22 non-hotel industries. We estimate a dynamic labor demand model with inter-industry spillover effects, using various estimators including GMM-based dynamic panel methods. We find statistically and economically significant effects – an additional 100 rooms sold per day during a year in a given MSA generates between 2-5 new jobs per non-hotel industry in that area. Subsample analyses across industries indicate that construction, retail, health care, professional and technical services are among the largest beneficiaries of these spillovers.
This paper examines the use of combined forecasting methods in tourism forecasting. The use of multiple methods allows more information to be incorporated into the forecasts. The objective of the paper is to show that forecasts of tourism arrivals obtained by combining forecasting models are more accurate (therefore more useful to practicing managers) than single-method forecasts. Several combined forecasts of tourist arrivals in Florida obtained and compared to single-method forecasts gained through econometric or time-series models. Parameter interpretation and forecasting accuracy of both combined and single-method forecasts are discussed. The conclusion of the paper offers a commentary on the usefulness of multimethod approaches to forecasting.
This study investigates the influence of national-cultures on the external information search behavior of travelers from the European Union (EU) member states existing at the time the data were collected. Statistical information from EUROBAROMETER 48 is examined. EUROBAROMETER 48 is a Standard Eurobarometer public opinion survey conducted on behalf of the European Commission at least two times a year in all member states of the EU. This document identifies the population of the respective nationality of EU members, aged 15 years and over, residing in each of the member states. Data were collected between 12 October 1997 and 16 November 1997. First, a series of Kruskal–Wallis tests are conducted to examine the impact of national-cultural on the use of information sources. After determining that the national culture significantly influences a traveler's external information search behavior, a correspondence analysis is utilized to examine information search behavior of the residents and nationals of each EU state. This analysis identifies five distinct market segments based on respondents’ information search patterns. Findings suggest national culture is likely to influence a traveler's information search behavior.
Restaurants and dining out are an important part of the tourism industry and are a major business in their own right. They also have characteristics that make a geographical analysis especially pertinent: They require movement through space, there are strong regional variations in patterns of restaurant development, and location is an important factor in the success of a restaurant. This paper examines two aspects of the geography of the restaurant industry in Canada: national patterns of restaurant development and the tendency to dine out, and local patterns of site selection. Basic patterns are described and possible processes influencing these patterns identified. Recommendations are given for the location of new restaurants of different types
A four-cell typology of pleasure trips is developed based on number of destinations visited and the trip purpose or benefits sought. Five distinctive spatial patterns evolving from this typology are identified that may be adopted by pleasure travelers: single destination, en route, base camp, regional tour, and trip chaining. Four of these involve visiting multiple destinations. Multi-destination visits are a rational behavior pattern and reasons that account for this behavior are discussed. It is suggested that the concept of cumulative attraction offers a conceptual underpinning for explaining such trips. Benefits accruing from a better understanding of multi-destination trip behavior are discussed.RésuméLa conceptualisation des voyages d'agrément à plusieurs destinations. L'article présente une typologie à quatre cellules pour discuter les voyages d'agrément, selon le nombre de destinations et le propos du voyage ou le genre de bénéfices que l'on cherche. A partir de cette typologie, on identifie cinq modèles d'organisation spatiale: destination simple, escale en route, camp de base, voyage régional et enchaînement de voyages. Pour quatre de ces modèles, il s'agit de destinations multiples. On discute les raisons pour lesquelles on entreprendrait un voyage à plusieurs destinations. On suggère que le concept de l'attraction cumulative pourtrait être utile pour expliquer ces voyages. On discute les bénéfices que l'on peut tirer d'une meilleure compréhension du comportement du voyage à destinations multiples.
Gooroochurn N. and Hanley A. (2005) Spillover effects in long-haul visitors between two regions, Regional Studies 39 , 727-739. A new body called Tourism Ireland, funded jointly by the British and Irish Governments, has been set up to promote tourism for the entire island of Ireland. This study investigates whether such an initiative is mutually beneficial for the Republic of Ireland (ROI) and Northern Ireland (NI). It is argued that joint promotion of the island is viable only if interregional tourism demand spillovers are generated. A spillover arises when tourists who visit the ROI also visit NI, and vice versa. The interconnectedness between the two regions' long-haul visitor demand was investigated empirically and it was found that spillovers are significant, albeit asymmetric. NI tourism demand rises 3.2% for every 10% increase in ROI tourism demand, while the latter increases 1.1% for every 10% increase in NI demand.
The aim of this paper is to forecast turning points in international visitor arrivals to the Balearic Islands using the eading indicator approach. The paper prepares two indexes, one for the UK and one for Germany using macro- conomic variables. The UK and Germany are the major tourist markets for the Balearic Islands and represent more han 80% of international visitor arrivals. Previous studies have used econometric models and time-series models to orecast the number of international visitor arrivals, but uncertainty persists.
Study on spatial characteristics and spillover effects of urban tourism efficiency: A case of Yangtze River Delta
- Wang
Single market action plan
- European Union
European Union (1999). Single market action plan. Retrieved January 31, 2019, from http://europa.eu/rapid/press-release_IP-97-478_en.htm.
Study on spatial characteristics and spillover effects of urban tourism efficiency: A case of Yangtze River Delta
- K Wang
- Z F Huang
- Y G Tao
- Y L Fang
Wang, K., Huang, Z. F., Tao, Y. G., & Fang, Y. L. (2013). Study on spatial characteristics and spillover effects of urban tourism efficiency: A case of Yangtze River Delta.
Economic Geography, 33(4), 161-167.
Travel & Tourism Economic
World Travel & Tourism Council (2018). Travel & Tourism Economic Impact 2018.