how exchange rate affect tourism

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Moderation analysis of exchange rate, tourism and economic growth in Asia

Bosede Ngozi Adeleye

1 Dept of Accountancy, Finance and Economics, University of Lincoln, Lincoln, United Kingdom

2 Lincoln International Business School, University of Lincoln, Lincoln, United Kingdom

Jimoh Sina Ogede

3 Dept of Economics, Olabisi Onabanjo University, Ago-Iwoye, Nigeria

Mustafa Raza Rabbani

4 Dept of Accounting and Finance, British University of Bahrain, Sar, Kingdom of Bahrain

Lukman Shehu Adam

5 Dept of Economics and Development Studies, Kwara State University, Malete, Nigeria

Maria Mazhar

6 School of Economics, Quaid-i-Azam University, Islamabad, Pakistan

Associated Data

All relevant data are within the paper and its Supporting Information files.

This study brings novelty to the tourism literature by re-examining the role of exchange rate in the tourism-growth nexus. It differs from previous tourism-led growth narrative to probe whether tourism exerts a positive effect on economic growth when the exchange rate is accounted for. Using a moderation modelling framework, instrumental variables general method of moments (IV-GMM) and quantile regression techniques in addition to real per capita GDP, tourism receipts and exchange rate, the study engages data on 44 Asian countries from 2010 to 2019. Results from the IV-GMM show that: (1) tourism exerts a positive effect on growth; (2) exchange rate depreciation hampers growth; (3) the interaction effect is positive but statistically not significant; and (4) results from EAP and SA samples are mixed. For the most part, constructive evidence from the quantile regression techniques reveals that the impact of tourism and exchange is significant at lower quantiles of 0.25 and 0.50 while the interaction effect is negative and statistically significant only for the SA sample. These are new contributions to the literature and policy recommendations are discussed.

1. Introduction

The tourism and hospitality industry has experienced development and expansion making it one of the biggest and fastest-growing sectors [ 1 ]. Many countries and destinations have grown in popularity, resulting in an increase in the number of visitors and tourism receipts. The tourism sector has the potentials to make significant contributions to economic growth and development through a variety of channels. It is a “currency earning sector” that permits the use of human and physical capital stock to drive innovation and development. Simultaneously, the tourism sector is either directly or indirectly related to other sectors like transportation, accommodation, or retailing through trickledown effect [ 2 ]. It also influences spending, and expands trade and global competitiveness [ 3 ]. International tourism, in particular, is a source of foreign exchange generation which improves the balance of payment position [ 4 ] and eases the acquirement of advance technologies and capital goods that can be used in other manufacturing processes [ 5 , 6 ]. Furthermore, it plays an important role in stimulating investments in new infrastructure and enhancing competition thereby creating jobs and improving overall living standard [ 2 ].

Similarly, the exchange rate influences economic growth. In this paper, an improvement/increase in the exchange rate indicates the appreciation of a domestic currency against a foreign currency. It is a significant indicator of economic progress as it essentially mirrors the competitiveness between a domestic economy and the rest of world. The exchange rate reflects a standard exchange among purchasers and merchants of foreign currency in the foreign exchange market of a particular country. Particularly, non-oil trades, oil exporters, international tourist expenditures, and foreign remittances all drive inflow of foreign currency. According to Rapetti et al. [ 7 ] the growth effect of exchange rate specifically the real exchange rate (RER) is both growth-amplifying and growth-dwindling. The exchange rate can significantly affect a country’s balance of payments position particularly if the country’s reliance on imported goods is high. In these circumstances, a more competitive RER would aid in relieving foreign exchange bottlenecks that would otherwise stymie the development process.

The connection between tourism and the exchange rate is not far-fetched. International tourism receipts are significant sources of foreign exchange earnings and highly linked to the exchange rate. Changes in exchange rates greatly affect tourism demand in a destination as changes in the exchange rate will have an impact on the currency value of the country of origin. Any adjustments in the exchange rate will prompt an appreciation or depreciation of the tourist’s currency, affecting transportation costs and the tourist’s decisions to visit the country. Thus, the exchange rate has an impact on the number of tourists’ visits as well as tourism receipts [ 8 ]. Less flexible exchange rates are supposed to advance global exchange and tourism by lessening vulnerability in worldwide transactions, wiping out exchange costs, and expanding market transparency. Furthermore, the exchanges rate mimics the relative price differential (as it affects global economic environment, purchasing power and overall wealth of tourists), which tourists have insufficient information about since they make travel arrangements in their own currency in advance before leaving their country. In this way, low-uncertainty exchange rate regimes could promote international tourism flows [ 9 ] that in turn speed up the development process through foreign direct investment and globalization [ 10 ].

Tourism as a commodity is very susceptible to exchange rate shocks which affects tourists’ inclination to visit a foreign country. We, therefore, hypothesize that changes in the exchange rate will influence the impact of tourism on economic growth. To the best of our knowledge, this is the first study to empirically test this hypothesis. That is, does the exchange rate tilt the tourism-growth dynamics? To probe the discourse, an unbalanced panel data on 44 Asian economies from 2010 to 2019 comprising tourism receipts, per capita GDP (proxy for economic growth), official exchange rate and a set of control variables is used. To ensure the robustness of the results, a blend of econometrics techniques is deployed. To control for possible endogeneity of the tourism variable, the instrumental variable technique nested within the generalised method of moments (IV-GMM) is used [ 11 – 13 ]. Lastly, the quantile estimator [ 14 – 16 ] is used in the event that the dependent variable has a non-normal distribution. This empirical approach makes the study novel and holistic in ensuring a critical examination of its core arguments. The rest of the paper is structured as follows: section 2 discusses the literature; section 3 outlines the data and empirical model; section 4 discusses the results, and section 5 concludes.

2. Literature review

Tourism activities are considered as one of the most important sources of economic growth and foreign exchange earnings around the globe [ 2 , 6 , 17 ]. The literature on tourism development and its impact on exchange rate and economic growth has increased exponentially in the last three decades [ 18 , 19 ]. The studies on tourism and growth nexus have proliferated mainly due to the fact that international tourism has grown over the years despite some ephemeral shocks [ 20 ]. The tourism growth literature mainly focuses on the causal relationship between tourism and economic growth [ 19 , 21 – 23 ] whereas, tourism and exchange rate literature focus mainly on exchange rate volatility and tourist flows [ 24 – 26 ]. We divide our literature review into two parts; the first part consists of available literature on tourism and economic growth whereas, the second part consists of tourism and exchange rate.

2.1 Tourism and economic growth

This section discusses the literature on tourism economics focusing on economic growth and tourism nexus. From a theoretical perspective, Lanza and Pigliaru [ 27 ] were among the first to document the tourism-growth nexus. They find that countries with high tourism sectors experienced high economic growth. They developed a Lucas type-two sector model where tourism is taken as one of the sectors which depends on the endowments of natural resources such that countries with abundant natural resources have high growth potential and achieve a faster rate of growth. Perles-Ribes et al. [ 28 ] studied the tourism and economic growth nexus using autoregressive distributed lag (ARDL) and Toda-Yamamoto model for the period 1957 to 2014 taking into consideration the economic crises. Their findings revealed a bi-directional relationship between economic growth and tourism development. There are many studies proposing the hypothesis that growth of tourism in the country is directly linked to economic prosperity [ 29 ]. The study reports that there is bidirectional causality between tourism and economic growth. Fuinhas et al. [ 22 ] report that in the long run, high frequency of tourist arrivals in the country leads to positive economic growth. In another study, Naseem [ 30 ] concludes that in the long run, tourism receipts, number of tourist arrivals, and total expenditure have a strong positive relationship with economic growth. The study empirically examined the data from Saudi Arabia and validated the popular hypothesis that tourism leads to economic growth in the country. Similar findings were obtained by [ 31 – 35 ], where they concluded that tourism has a positive impact on the economic growth of the country. The study by Sahni et al. [ 36 ] used a quantile regression approach and concluded that tourism growth has a more pronounced effect on economic growth below the threshold and above the threshold. The study further concluded that countries with lower economic growth have more benefits from tourism development. The study by Selvanathan et al. [ 37 ], applied ARDL, vector error correction model (VECM) and panel frameworks and concluded that in the long run tourism development positively contributes to growth. Tourism development is the significant predictor of the economic growth and financial development at frequency rather than the low frequency [ 38 ]. On the contrary, Croes et al. [ 39 ], revealed that tourism development has a very short term effect on economic development and a negative and indirect link to human development. Similar findings were obtained by Kyara et al. [ 23 ] where it was revealed that there is a unidirectional causality relationship between tourism development and economic growth.

2.2 Tourism and exchange rate

The effects of exchange rate on tourism development can differ across the country, territory and within the tourism jurisdiction [ 38 ]. The real and nominal appreciation of the currency leads to a negative impact on the tourism development in the country [ 40 ]. Exchange rate has asymmetric impact on tourism on tourism development in developing countries such as, India, Bangladesh, Pakistan and Nepal in the short run [ 41 ]. Boskurt et al. [ 42 ] applied dynamic common correlated effects (DCCE) approach in their study on demand and exchange rate shocks on tourism development and concluded that effects of the exchange rate shocks are temporary on the tourism development. To examine the response of tourism demand to exchange rate fluctuation in South Korea, Chi [ 43 ] used ARDL model and concluded that tourists are sensitive to the appreciation of the Korean Won, whereas they are insensitive to its depreciation. The findings of the study imply that foreign visitors in Korea are loss averse and with increase or decrease in the exchange rate volatility tend to affect the tourism demand in an asymmetric manner. Dogru et al. [ 44 ] used ARDL approach to examine the trade balance and exchange rate taking evidence from tourism development. The study concluded that depreciation and appreciation of the US Dollar affects the bilateral tourism with Canada, Mexico, and the United Kingdom (UK). The study further concluded that in the long-run the appreciation of the US dollar negatively affects the tourism trade balance with Canada and the UK while it does not affect the tourism development with Mexico in the long-run. A study by Belloumi [ 45 ], examined tourism receipts and exchange rate nexus in Tunisia and concluded that there is a cointegrating relationship between tourism and economic growth. An increase in foreign direct investment (FDI) and appreciation of the exchange rate contracts the tourism demand of the country while in the long-run the depreciation of domestic currency and decrease in FDI inflow results in more tourist inflow [ 41 ]. Similar findings were obtained by [ 46 ] and [ 47 ] where they revealed that reduction in FDI inflow and depreciation of foreign exchange rate results in positive tourism development.

2.3 Tourism, exchange rate and economic growth

There are few studies that investigated the nexus of exchange rate, tourism development and economic growth [ 23 , 48 , 49 ]. Primayesa et al. [ 50 ] probed the dynamic relationship among real exchange rate, economic growth and tourism development in Indonesia using variance decomposition and impulse response function approach. The study revealed that in explaining the tourism shock in Indonesia, the real exchange rate is less important than the economic growth. The study further concluded that the shock of economic growth and real exchange rate has a positive effect on tourism activity in the short- and long-term. Harvey et al. [ 25 ] applied bounds testing approach to cointegration and error-correction modelling to examine whether tourism development and exchange rate promote the economic growth in Brunei Darussalam, Indonesia, Malaysia, and the Philippines. The study revealed the Philippines is the only country that has the positive long-run and short-run impact from the tourism industry and exchange rate.

3. Data and methodology

This study uses data on nine variables sourced from World Development Indicators (WDI) for 44 countries located in East Asia and the Pacific (EAP) and South Asia (SA) from 2010 to 2019. Availability of sufficient data on the variables of interest–per capita GDP, tourism receipts, and official exchange rate—justify the inclusion of a country in the sample and to explore the heterogeneity of the sample countries, we disaggregate the full sample into EAP with 36 countries and SA having 8 countries. The countries are East Asia and the Pacific (36): American Samoa, Australia, Brunei Darussalam, Cambodia, China, Fiji, French Polynesia, Guam, Hong Kong SAR, China, Indonesia, Japan, Kiribati, Korea, Dem. People’s Rep., Korea, Rep., Lao PDR, Macao SAR, China, Malaysia, Marshall Islands, Micronesia, Fed. States, Mongolia, Myanmar, Nauru, New Caledonia, New Zealand, Northern Mariana Islands, Palau, Papua New Guinea, Philippines, Samoa, Singapore, Solomon Islands, Thailand, Timor-Leste, Tonga, Vanuatu, Vietnam. South Asia (8): Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, Sri Lanka.

3.1 Dependent variable

Real GDP per capita is the proxy for economic growth. Studies on tourism-growth nexus have widely used it [ 51 – 53 ] likewise, those on exchange rate-growth relationship [ 54 , 55 ].

3.2 Main explanatory variables

From World Development Indicators, International tourism, receipts (% of total exports) is defined as: expenditures by inbound visitors including payments to foreign carriers for international transport. In other words, this composite variable captures the spendings of inbound tourists to Asia and the Pacific, among others. In line with the literature [ 56 – 60 ], tourism receipts which is the first main explanatory variable is proxied by tourism receipts in current US dollars. Existing literature have found a positive relationship between different dimensions of tourism and economic growth [ 61 – 65 ]. The second key explanatory variable is exchange rate [ 42 , 66 – 68 ]. The exchange rate captures the competitiveness of a country in the international market [ 69 – 73 ]. Lastly, to address the study questions, an interaction term of tourism receipts with exchange rate (TRPT*XR) is included to determine if exchange rate moderates the impact of tourism on growth.

3.3 Control variables

The set of control variables align with those used in growth models: mobile phone subscription [ 5 , 74 , 75 ], individuals using the Internet [ 76 , 77 ], labour force participation [ 78 ] (Niebel, 2018), foreign direct investment net inflows [ 79 ], domestic credit to the private sector [ 80 – 83 ] and services trade [ 84 , 85 ]. We expect positive coefficients in line with existing literature. Table 1 details the variables used.

Source: Authors’ Compilation from World Bank [ 86 ] World Development Indicators (WDI)

3.4 Empirical model

We specify two baseline linear models that expresses economic growth as a function of tourism receipts, exchange rate and a set of control variables which satisfies the first objective:

Where, ln PC it = natural logarithm of per capita GDP; ln TRPT it = natural logarithm of tourism receipts; XR it = official exchange rate; Z ′ it and K ′ it = vector of control variables in natural logarithms; α i , γ i = parameters to be estimated; φ t , δ t = year dummies (which controls for common shocks such as the global financial crises of 2007–2009), and u it , e it = general error term. To satisfy the second objective, we add an interaction term ( TRPT*XR ) to Eq [ 1 ] and the model becomes:

Where, R ′ it = vector of control variables in natural logarithms; η i = parameters to be estimated; ω t = year dummies (which controls for common shocks such as the global financial crises of 2007–2009), and v it = general error term. From Eq [ 3 ], η 3 provides two information. First, the sign of the coefficient indicates if exchange rate exerts a significant moderation effect on economic growth. That is, whether the interaction of both variables intensifies or hinders growth. Secondly, the magnitude of the coefficient may sustain or sway the impact of tourism on growth which is derived as:

3.5 Estimation techniques and strategy

Specifically, our econometric strategy consists of a three-step procedure. First, we examine linear impact of tourism on economic growth. Next, we estimate the linear effect of exchange rate on economic growth. Lastly, we perform the moderation analysis to show the interaction effect on economic growth. We engage these analyses using two techniques: the instrumental variables-two-step generalised method of moments (IV-GMM) techniques and the quantile estimator [ 14 – 16 ]. Specifically, the IV-GMM technique is used to correct for cross-sectional dependence, endogeneity, autocorrelation and heteroscedasticity in the data [ 11 , 87 ]. It uniquely deploys the ivreg2 routine in Stata version 16 developed by Baum, Schaffer, and Stillman [ 12 , 13 ]. The routine performs several variants of single-equation linear regression models including the generalized method of moments (GMM). Hence, the GMM variant which implements the two-step feasible GMM estimation (that is, gmm2s option) is adopted to ensure that our results are devoid of endogeneity, heteroscedasticity and autocorrelation [ 12 ]. On the other hand, the quantile regression is deployed to examine the potentially differential effects of tourism and exchange rate at different levels of growth. The quantile regression model is a defined solution to minimize the equation for the θ th regression quantile, 0< θ <1 and expressed thus:

Where, y t is the dependent variable and x t is a k x 1 vector of explanatory variables.

4. Results and discussions

4.1 summary statistics and correlation analysis.

The upper panel of Table 2 contains the correlation matrix’s results, illustrating the relationship between the regressors and the outcome variables. Our findings indicate a negative correlation between per capita GDP and official exchange rate, implying that rising income will decrease the exchange rates in Asia. Likewise, individuals use the internet and the official exchange rate. Trade in services is negatively associated with tourism receipts, official exchange rate, FDI, and MOB. These findings suggest that increasing individuals using the internet and trade in services will impact the official exchange rate, tourism receipts, FDI, and MOB.

*** p<0.01

** p<0.05

* p<0.1

ln = Natural logarithm; PC = per capita GDP; TRPT = tourism receipts; XR = Official exchange rate; DC = Domestic credit to the private sector; LAB = labour force participation rate; FDI = foreign direct investment; MOB = mobile phone subscriptions; NET = individuals using the Internet; TRS = trade in services; 9.08E+09 = 9,080,000,000.00

Source: Authors’ Computations

The lower panel of Table 2 indicates the summary statistics for the variables from 2010 to 2019. The average of per capita GDP, tourism receipts, official exchange rate, domestic credit to the private sector, labour force participation, foreign direct investment, mobile phone subscriptions, internet users, and trade in services are 12398.47, 9080000, 1295.02, 71.42, 69.06, 1540000, 92490468, 38.86, and 30.269, respectively, from the entire sample. At the same time, the standard deviation provides information on the deviation from sample averages.

4.2 IV-GMM results

Table 3 displays results for the instrumental variables-two-step generalised method of moments (IV-GMM). Across the Full, EAP, and SA samples, tourism receipts and exchange rate are instrumented with their first difference and level terms. Limiting to the variables of interest, the summary of the linear models from the full sample shows tourism receipts as a significant positive predictor of economic growth. The findings indicate that a percentage change leads to 0.88% rise in economic growth, on average, ceteris paribus . We argue that a well-structured tourist sector together with investments in modern infrastructure will boost growth supporting Tugcu [ 88 ], Alfaro [ 89 ], Calero and Turner [ 90 ], Cheng and Zhang [ 91 ], and Scarlett [ 92 ] all of which argue in favour of tourism-driven growth. The exchange rate shows a significant negative effect on growth. According to the findings, a percentage-point change in the exchange rate results in a 0.00005% drop in economic growth. The reason for this is not far-fetched. Exchange rate fluctuations influence potential travellers’ decisions to alter their destination or shorten their vacation resulting in revenue loss for economies. This may result in adjustments to visitors’ travel plans while in a particular nation [ 93 ]. These findings corroborate those of Lin, Liu, and Song [ 94 ], Meo et al. [ 95 ], Sharma and Pal [ 96 ], Chi [ 43 ], and Seraj and Coskuner [ 97 ]. For EAP countries, tourism increases economic growth by 0.62%, on average, ceteris paribus . On the other hand, the coefficient of the exchange rate is negative and significant at 1 per cent, which supports the argument of Vieira et al. [ 98 ] and Seraj and Coskuner [ 97 ]. These studies contend that local currency appreciation will decrease the spending power of international tourists with consequent decline on tourism demand and economic growth. In South Asia, the effect of tourism on growth is positive but statistically not significant but exchange rate significantly boosts growth by 0.007%, on average, ceteris paribus . This finding contradicts Seraj and Coskuner [ 97 ] and suggests that currency appreciation is growth-enhancing. For the moderation models, columns [ 3 , 6 , 9 ] reveal that the interaction effect is positive but statistically not different from zero for the full and EAP samples while it decreases growth in South Asia which contradicts Sharma, Vashishat, and Rishad [ 99 ]. In other words, the conditional effect of tourism on growth reduces when exchange rate appreciates in South Asia.

t -statistics in (); -5.40e-05 = 0.0000540; ln = Natural logarithm; PC = real per capita GDP; TRPT = tourism receipts; XR = Official exchange rate; DC = Domestic credit to the private sector; LAB = labour force participation rate; FDI = foreign direct investment; MOB = mobile phone subscriptions; NET = individuals using the Internet; TRS = trade in services.

On the reliability of the instruments used to validate the robustness of our estimations, we controlled for identification and exclusion restrictions which are indispensable for robust GMM estimations [ 12 , 13 ]. Having used the IV-GMM estimation in ivreg2 , the appropriate test of overidentifying restrictions and testing the validity of instruments used is the Hansen J statistic: the GMM criterion function. From the lower panel of Table 3 , the p -value of the Hansen-J statistic across the six models ranges between 0.085 and 0.3874 which is clearly above 0.05. Hence, it fails to reject the null hypothesis of instruments validity indicating that the instruments used are valid and robust to our analysis.

4.3 Quantile regression results

Table 4 presents the quantile regression results across the 25th, 50th, and 75th quantiles of economic growth. The topmost panel displays the full sample results where tourism significantly improves growth at the 25 th and 50 th quantiles by 0.23% and 0.12%, respectively. Noticeably, the positive effect of tourism receipts declines along the distribution. On the other hand, exchange rate appreciation shows a reducing effect on growth at the 25 th and 50 th quantiles by -0.000051% and -0.000059%, respectively. This reducing effect is larger at the 50 th quantile indicating that economic growth vulnerable to exchange rate fluctuations. Following our findings, we hypothesise that variations in the official exchange rate affects tourist purchasing decisions and economic growth in the long-run [ 100 ]. On the interaction effect, we find no significant impact on growth corroborating the results shown in Table 3 .

I-statistics in (); ln = Natural logarithm; PC = per capita GDP; TRPT = tourism receipts; XR = Official exchange rate; DC = Domestic credit to the private sector; LAB = labour force participation rate; FDI = foreign direct investment; MOB = mobile phone subscriptions; NET = individuals using the Internet; TRS = trade in services.

The results of East Asia and the Pacific displayed in the middle panel indicate that tourism significantly increases growth at the 25 th and 50 th quantiles by 0.44% and 0.31%, respectively. A reducing positive effect is observed similar to that of the full sample. Also, exchange rate appreciation shows a reducing effect on growth at the 25 th and 50 th quantiles by -0.000061% and -0.000067%, respectively. Similar to the full sample, this reducing effect is larger at the 50 th quantile and we find no significant interaction effect on growth. From the lowest panel, the results from South Asia indicate that tourism significantly increases growth at the 50 th and 7 th quantiles by 0.17% and 0.19%, respectively. An increasing positive effect is observed contrary to the full and EAP samples. Likewise, exchange rate appreciation increases economic growth across all the quantiles, though with a declining trend from 0.0087% to 0.0075%. Contrary to the full and EAP samples, a significant negative interaction effect is observed across the quantiles supporting the results shown in Table 3 .

5. Conclusion and policy recommendation

This current study highlights the role of exchange rate in influencing the effect of tourism on economic growth in Asia. To the best of our knowledge, this is the first study that critically evaluates the influence of exchange rate on the tourism-growth nexus. That is, it gauges the nonlinear effect of tourism on economic growth when the exchange rate is accounted for. This position differs from other tourism-growth studies [ 22 , 27 – 30 , 101 , 102 ] that investigated the direct and linear effect of tourism on economic growth but aligns with Adeleye et al. [ 103 ] who examined a similar nexus on Sri Lanka. For the most part, these studies affirm that tourism exerts a direct and positive effect on economic growth. However, we expand the frontiers of knowledge having recognized that the exchange rate is an important macroeconomic policy instruments for promoting sustainable economic growth and encouraging tourism flows as it serves as an essential factor influencing the decision of tourists regarding tourism destinations. To this end, this paper examines the moderating effect of exchange rate and tourism receipts on economic growth in Asia from 2010 to 2019. From the full sample, findings from IV-GMM and quantile regressions techniques revealed that tourism significantly boosts economic growth, and the exchange rate indicates a negative effect. Deductively, we conclude that tourism is growth-enhancing which supports the tourism-led growth conjecture and that exchange rate appreciation is also growth-reducing. On the interaction effect, though the coefficient is positive but statistically insignificant it suggests that currency appreciation may possess inherent potentials in sustaining the positive effect of tourism on economic growth. Results from the East Asia and the Pacific and South Asia are diverse.

Based on the findings, the following recommendations are made for the government and stakeholders in Asia: (1) Provide a sound and efficient financial system which does not only provide adequate funding for promoting the tourism sector but also ensure easy accessibility to aid foreign tourist’s transaction. (2) Initiate investment incentive policies for the tourism sector which will reduce the operating cost, investment outlay and provide security for the investment of tourist investors. (3) Initiate a well-managed exchange rate system that supports tourism flows and economic growth. For further studies and subject to data availability, the role of government regulation, real exchange rate and competitiveness in relation to the tourism-growth dynamics may be undertaken.

Supporting information

Funding statement.

The author(s) received no specific funding for this work.

Data Availability

• PLoS One. 2022; 17(12): e0279937.

Decision Letter 0

30 Aug 2022

PONE-D-22-18174Moderation analysis of exchange rate, tourism and economic growth in AsiaPLOS ONE

Dear Dr. Adeleye,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. 

In view of the referees’ feedback and my own reading of your paper, we believe your paper is some way from being publishable. In particular, there are serious doubts about the underlying hypotheses on which the research is based, as well as about the methodology used.

While we consider the issues identified to be major in nature, we are willing to offer you a chance to rework the paper if you feel able to address them fully and robustly. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Partly

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Reviewer #2: N/A

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Reviewer #3: No

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Reviewer #1: Idea of the paper and statistical parts have been performed appropriately and rigorously. And there is no problem. But some formal parts have mistakes and errors. Some of them:

1- Abstract part should be improved.

2- Too many references. Can be reduced according to the journal index (Scopus, Sci, ssci etc.)

3- No need to citations in Data and Methodology parts. They must be in Literature Review part.

4- In text there are citation errors. For example more than 3 authors use et al. Some parts it is true but some parts wrong.

5- Some citations are missed in references especially in page 12.

6- Use "literature review" instead of "Review of literature".

7- At conclusion part comparisons with previous studies can be made.

Reviewer #2: The paper attempts to examine “moderation analysis of exchange rate, tourism and economic growth in Asia”. After reviewing, I find that this paper is interesting. The paper is readable ragarding the case of economic growth in Asian in the background of exchange rate, tourism and their interactive association.

See the attachment

Reviewer #3: The paper under consideration looks at the impact of tourism on GDP growth and the interactions of the impact with exchange rate. In my opinion this paper has important shortcomings that will prevent it from being published in the current form. My suggestion is rejection. The issues that lead to my decision are as follows:

1. The paper largely ignores the growth regression literature and certainly aims to be a part of it.

2. The value added generated in the tourism sector is in fact part of the overall value added of the economy. This is largely correlated with the international tourism. What sense does it have to regress GDP on a component of it? We can find out quite precisely what is the EXACT contribution of tourism to GDP and GDP growth.

3. The models are estimated by GMM. However, what are the instruments? The paper does not seems to use any sort of Arellano-Bond, Arellano Bower System-GMM. So the description is vague. And in particular, the panel System-GMM methods are mainly used to solve the endogeneity caused by the lagged dependent variable and not the inherent endogeneity of the economic problem posed here. So this part clearly needs clarification and justification. It does not suffice to write that „results are devoid of endogeneity, heteroscedasticity and autocorrelation.”

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PONE-D-22-18174R1Moderation analysis of exchange rate, tourism and economic growth in AsiaPLOS ONE

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I feel satisfied with this version and your replies on my comments. Therefore, I have decided the acceptance for this paper.

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PONE-D-22-18174R2Moderation analysis of exchange rate, tourism and economic growth in AsiaPLOS ONE

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Reviewer #3: Now with the paper specifying the actual method and the choice of instruments, the only thing that is lacking is providing test statistics to check for the validity of instruments, i.e., the J statistic or equivalent and the discussion on the validity of instruments. The authors seem to treat the IV-GMM technique as a solution to several econometric problems but they do not check whether the problems have been indeed solved.

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• Travel Tips

How Does The Exchange Rate Affect Tourism In The UK

Published: December 12, 2023

Modified: December 28, 2023

by Valeda Bowyer

• Plan Your Trip
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Introduction

Welcome to the United Kingdom, a country of rich history, stunning landscapes, and vibrant culture. As a popular tourist destination, the UK welcomes millions of visitors each year, contributing significantly to its economy. However, the travel industry is not immune to the fluctuations of the global economy, particularly in relation to exchange rates.

The exchange rate is the value of one currency in terms of another currency and plays a crucial role in shaping the tourism industry. It has the power to influence travel decisions, affect tourist spending patterns, and impact the overall competitiveness of a destination. Understanding the relationship between exchange rates and tourism demand is essential for both travelers and industry professionals.

In this article, we will explore the intricate relationship between exchange rates and tourism in the UK. We will delve into the economic factors that influence tourism, the significance of exchange rate fluctuations, and the effects they have on tourists’ behavior. Additionally, we will examine case studies that highlight the tangible impact of exchange rate changes on UK tourism and discuss strategies for mitigating the effects of exchange rate volatility.

Whether you are a curious traveler or a tourism industry enthusiast, this article will provide valuable insights into the fascinating world of exchange rates and their role in shaping tourism in the UK. So let’s embark on this journey together and explore the interplay between currency fluctuations and the travel industry.

Economic Factors Influencing Tourism in the UK

Before we dive into the specifics of exchange rates, it is important to understand the broader economic factors that influence tourism in the UK. The travel industry is highly sensitive to macroeconomic conditions, as travelers adjust their plans based on levels of disposable income, employment rates, and overall economic stability.

Disposable income plays a significant role in determining the extent to which individuals can afford to travel. During periods of economic prosperity, with rising incomes and low unemployment rates, people may have more discretionary funds available for vacations and travel experiences. Conversely, during economic downturns, when income levels stagnate or decline and unemployment rates rise, people tend to cut back on leisure travel and prioritize essential expenses.

Another important factor influencing tourism in the UK is the state of the global economy. The strength or weakness of major international economies can impact travel decisions and patterns. For example, if the economies of key source markets, such as the United States and European countries, are buoyant, it is likely to result in an increase in tourist arrivals to the UK. On the contrary, if these economies experience a downturn, it could lead to a decrease in visitor numbers.

Furthermore, geopolitical factors, such as wars, political instability, and natural disasters, can profoundly affect tourism. These events can lead to travel advisories, border restrictions, or a perception of unsafe travel, which can deter tourists from visiting the UK. Conversely, positive geopolitical developments and favorable international relations can boost tourism by fostering a sense of security and promoting the country as a desirable destination.

Government policies and regulations also impact tourism in the UK. Initiatives such as visa regulations, taxation policies, and marketing campaigns can shape travel trends. For instance, the implementation of visa relaxation programs or streamlined visa processes can attract more visitors by reducing barriers to entry. On the other hand, stricter visa requirements can create more hurdles for potential visitors.

Overall, a multitude of economic factors collectively influence tourism in the UK. From individual disposable incomes to global economic trends and government policies, these factors shape the demand for travel and play a crucial role in the fluctuation of tourist arrivals. Understanding these economic variables is fundamental in comprehending how exchange rates impact tourism in the UK, which we will explore in the subsequent sections.

The Exchange Rate and Its Importance

The exchange rate is the value at which one currency can be exchanged for another. It is a fundamental component of international trade and plays a crucial role in shaping the tourism industry. The exchange rate determines the cost of travel, influences tourist spending power, and affects the competitiveness of a destination in the global market.

For tourists, the exchange rate has a direct impact on the affordability of travel. When a traveler converts their home currency into the currency of their destination, they are subject to the prevailing exchange rate. A favorable exchange rate can make travel more affordable and appealing, as the amount of foreign currency they receive in exchange for their own currency is higher.

Moreover, the exchange rate influences the purchasing power of tourists. A stronger exchange rate enables tourists to buy more goods and services in the destination country, increasing their overall spending power. Conversely, a weaker exchange rate reduces purchasing power, potentially leading to a decrease in tourist spending and a shift towards more budget-conscious travel habits.

The exchange rate also affects the competitiveness of a destination within the global tourism market. A favorable exchange rate can make a country more attractive to international visitors, as it offers them better value for their money. This can lead to an increase in tourist arrivals and boost the tourism industry’s contribution to the national economy. On the other hand, an unfavorable exchange rate may make a destination less competitive, as it becomes relatively more expensive compared to other countries.

In addition to its impact on tourists, the exchange rate has implications for businesses operating in the tourism sector. Fluctuations in exchange rates can affect the costs and revenues of tourism enterprises. For example, a stronger domestic currency can increase the cost of imported goods and services, potentially impacting the profitability of tourism-related businesses that rely on such inputs. On the other hand, a weaker domestic currency can boost export-oriented tourism sectors by making their products or services more affordable in international markets.

It is worth noting that exchange rates are not fixed and can fluctuate due to various factors, including economic indicators, interest rates, inflation rates, and market speculation. These fluctuations can occur on a daily, weekly, or long-term basis, creating both challenges and opportunities for the tourism industry.

In the next section, we will examine the relationship between exchange rates and tourism demand to gain a deeper understanding of how changes in exchange rates can influence travel behavior and tourist preferences.

The Relationship between Exchange Rates and Tourism Demand

The exchange rate plays a pivotal role in shaping tourism demand, as it directly affects the cost of travel and the affordability of visiting a particular destination. Changes in exchange rates can have both positive and negative impacts on tourism demand, influencing the decision-making process of potential travelers.

When the exchange rate of a country’s currency strengthens, meaning it appreciates against other currencies, it generally leads to an increase in the number of international tourists. A stronger currency makes traveling to that country more affordable for foreigners, as they receive more local currency in exchange for their own currency. This can stimulate tourism demand, attract more visitors, and provide a boost to the local economy.

On the other hand, when the exchange rate of a country’s currency weakens, meaning it depreciates against other currencies, it can lead to a decrease in tourism demand. A weaker currency makes traveling to that country more expensive for foreigners, as they receive less local currency in exchange for their own currency. This can deter potential visitors, especially those on a tight budget, and result in a decline in tourist arrivals.

However, it is important to note that the relationship between exchange rates and tourism demand is not solely dependent on the direction of currency fluctuations. Other factors come into play, such as income levels, travel preferences, and the overall attractiveness of a destination.

For example, even if a country’s currency weakens, making it more expensive for foreign tourists, it may still experience an increase in tourism demand if other factors outweigh the impact of the exchange rate. These factors could include unique attractions, cultural experiences, safety, infrastructure, and promotional efforts. Conversely, even if a country’s currency strengthens, it may not see a substantial increase in tourism demand if other elements are not enticing enough for potential visitors.

It is also worth noting that the relationship between exchange rates and tourism demand is not always immediate or linear. Changes in travel patterns and tourist preferences may take time to adjust to fluctuations in exchange rates. Tour operators, travel agencies, and individuals may need time to assess and respond to changes in currency values. Moreover, long-term exchange rate trends and stability can also influence tourism demand, as travelers may feel more confident and secure when there is predictability in currency values.

Understanding the relationship between exchange rates and tourism demand is crucial for travel industry professionals and policymakers. It allows them to anticipate and adapt to changes in currency values, develop effective marketing strategies, and implement relevant policies to attract and retain tourists.

In the following section, we will explore the impact of exchange rate fluctuations on tourists’ behavior and spending habits to gain further insights into how changes in currency values can influence individual travel decisions.

Impact of Exchange Rate Fluctuations on Tourists’ Behavior

Exchange rate fluctuations have a significant influence on tourists’ behavior, shaping their travel decisions, spending habits, and even destination choices. These changes in currency values can create both challenges and opportunities for travelers, impacting various aspects of their travel experience.

One key impact of exchange rate fluctuations is on the affordability of travel. When a currency strengthens, making it more valuable compared to other currencies, travelers from that country will find it cheaper to visit foreign destinations. This can lead to an increase in outbound travel, as individuals take advantage of their stronger currency to explore new places or revisit favorite destinations. Conversely, when a currency weakens, it becomes more expensive for travelers from that country to go abroad, potentially leading to a decrease in outbound travel.

The changes in currency values also affect tourists’ spending power. A stronger currency means that travelers can enjoy more purchasing power in their destination country. They are likely to have more disposable income for accommodation, dining, shopping, and other activities. On the other hand, a weaker currency reduces purchasing power, forcing travelers to be more budget-conscious and potentially limit their spending. This can impact the overall tourism revenue generated by a destination and shape the type of experiences and accommodations that tourists seek.

Exchange rate fluctuations can also influence the destination choices of travelers. When a currency strengthens, it makes traveling to countries with weaker currencies more affordable and attractive. This can lead to an increase in visitors to these destinations, as they offer more value for money. Conversely, a weaker currency can deter tourists from visiting countries with stronger currencies, as they might perceive them as expensive or not offering good value. This can result in a shift in tourist flows and impact the market share of different destinations.

Moreover, exchange rate fluctuations can influence the timing and duration of trips. When a currency weakens, travelers may choose to extend their stay in a destination they have already arrived in to maximize the value of their money. On the other hand, a stronger currency might prompt tourists to reduce the duration of their stay or postpone their travel plans to a later time when the exchange rate is more favorable. These adjustments in travel behavior can have implications for businesses in the tourism industry, such as accommodations, restaurants, and attractions.

It is important to note that the impact of exchange rate fluctuations on tourists’ behavior is not uniform for all travelers. Factors such as individual budgets, travel preferences, and personal financial circumstances play a significant role in shaping how individuals respond to changes in currency values. Some travelers may be less sensitive to exchange rate fluctuations and prioritize other factors, such as safety, cultural experiences, or specific attractions, when making their travel decisions.

Understanding the impact of exchange rate fluctuations on tourists’ behavior is crucial for tourism businesses and destinations. By analyzing these effects, industry professionals can develop strategies to attract and retain visitors, tailor marketing efforts to specific target markets, and adjust pricing and offerings to align with travelers’ preferences and budgets.

In the next section, we will delve into case studies that examine the effects of exchange rate changes on UK tourism, providing real-life examples of how currency fluctuations can influence tourist behavior and industry dynamics.

Case Studies: Effects of Exchange Rate on UK Tourism

To understand the tangible impact of exchange rate changes on UK tourism, let’s explore some case studies that exemplify how currency fluctuations can influence tourist behavior and industry dynamics.

Case Study 1: The Impact of a Weaker Pound

In the aftermath of the Brexit referendum in 2016, the British pound experienced a significant depreciation against major currencies. This led to a boost in tourism to the UK, as international visitors found it more affordable to explore the country. The weakened pound made accommodations, dining, shopping, and attractions comparatively cheaper for tourists, attracting a surge in visitor numbers. As a result, the UK witnessed a notable increase in tourism revenue, benefiting various sectors of the economy.

Case Study 2: The Effect of a Stronger Pound

In contrast, when the British pound becomes stronger, it can impact the inflow of tourists to the UK. For example, during periods when the pound strengthened against the euro, UK destinations became relatively more expensive for European travelers. This led to a decline in tourist arrivals and affected the tourism industry’s contribution to the economy. To counteract this trend, tourism authorities and businesses often adjust their marketing strategies and pricing models to entice visitors and maintain competitiveness.

Case Study 3: The Influence of Exchange Rates on Travel Behavior

Exchange rate fluctuations not only affect the choice of destination but also impact travel behavior within the UK. When the pound weakens, domestic tourism may gain popularity as residents prefer to explore their own country rather than traveling abroad. This shift in behavior can benefit local destinations, attractions, and hospitality businesses, stimulating the domestic tourism market and boosting regional economies.

These case studies highlight the profound influence that exchange rate fluctuations can have on UK tourism. A weaker currency can attract more international visitors by offering better value for their money, while a stronger currency can make the UK relatively more expensive, potentially impacting tourism demand. Additionally, exchange rates can influence both outbound and domestic travel behavior, affecting the flow of tourists and revenue distribution within the tourism industry.

By examining these real-life examples, it becomes evident that monitoring and addressing exchange rate fluctuations is crucial for tourism stakeholders in the UK. Navigating the effects of currency volatility requires a thoughtful approach, including targeted marketing campaigns, pricing adjustments, and proactive industry collaboration to maintain the country’s competitiveness in the global tourism market.

In the next section, we will explore the broader implications of exchange rate fluctuations on the tourism industry in the UK and discuss strategies to mitigate the effects of currency volatility.

Implications of Exchange Rate on Tourism Industry in the UK

The exchange rate has significant implications for the tourism industry in the UK, affecting various stakeholders and shaping the overall competitiveness and profitability of the sector. Understanding these implications is crucial for industry professionals and policymakers to effectively navigate the challenges and opportunities associated with currency fluctuations.

1. Competitiveness:

The exchange rate directly impacts the competitiveness of the UK as a tourism destination. A favorable exchange rate can make the country more affordable and attractive to international visitors, leading to an increase in tourist arrivals and boosting the tourism industry’s contribution to the local economy. Conversely, an unfavorable exchange rate can make the country relatively more expensive, potentially deterring visitors and reducing market share. Maintaining a competitive exchange rate is vital in ensuring the sustainability and growth of the tourism industry in the UK.

2. Revenue Distribution:

Exchange rate fluctuations can lead to shifts in revenue distribution within the tourism industry. A weaker currency may result in an increase in domestic tourism as residents opt to explore their own country rather than travel abroad. This can benefit local destinations, attractions, and hospitality businesses. On the other hand, a stronger currency can impact the inflow of international tourists, affecting revenue generated by businesses reliant on international visitors. Finding the right balance and diversifying revenue sources can help mitigate the effects of exchange rate volatility.

3. International Collaboration and Partnerships:

Exchange rate fluctuations necessitate increased collaboration and partnerships within the tourism industry. Tourism businesses, destination management organizations, and government entities need to work together to address the challenges posed by currency volatility. This can include joint marketing efforts, pricing adjustments, and partnerships with commercial banks and foreign exchange providers to offer competitive exchange rates and minimize the impact on tourists’ spending power.

4. Investment and Business Confidence:

Exchange rate stability is crucial for attracting foreign investment in the tourism industry. A stable currency provides a predictable environment for businesses, reducing the risk associated with currency fluctuations. On the other hand, volatile exchange rates can deter investors and hinder the development of tourism infrastructure and services. By implementing policies that promote exchange rate stability and providing support to the tourism industry during periods of currency volatility, the UK can enhance business confidence and foster a favorable investment climate.

5. Industry Adaptation and Resilience:

Exchange rate fluctuations require the tourism industry to adapt and build resilience. Businesses must continually assess their pricing strategies, monitor currency trends, and develop contingency plans to navigate potential challenges. Diversifying target markets, focusing on niche segments, and offering unique experiences can reduce reliance on specific currencies and mitigate the impact of exchange rate fluctuations on business performance.

By recognizing these implications, the tourism industry in the UK can be better prepared to respond to exchange rate fluctuations and develop strategies to mitigate their effects. It requires close collaboration between businesses, industry associations, and government entities to ensure a sustainable and resilient tourism sector that can withstand currency volatility and thrive in an ever-changing global market.

In the next section, we will explore strategies for mitigating the effects of exchange rate volatility in the tourism industry and maintaining a competitive edge in the global market.

Strategies for Mitigating the Effects of Exchange Rate Volatility

Exchange rate volatility poses challenges to the tourism industry in the UK, but there are strategies that businesses and destinations can employ to mitigate its effects and maintain a competitive edge in the global market:

1. Diversify Target Markets:

Relying too heavily on a single market can leave tourism businesses vulnerable to fluctuations in that market’s currency. Diversifying target markets can help spread the risk and reduce the impact of exchange rate volatility. This involves identifying and investing in emerging markets, collaborating with travel agents and tour operators from different regions, and tailoring marketing efforts to attract a diverse range of international visitors.

2. Implement Dynamic Pricing:

Dynamic pricing allows tourism businesses to adjust prices in response to changes in exchange rates. By closely monitoring currency fluctuations, businesses can modify their pricing strategies to maintain competitiveness and attract customers. This may involve offering discounts during periods of currency appreciation or adjusting prices for different markets to maximize revenue and keep tourists engaged.

3. Offer Value-Added Experiences:

Providing unique and value-added experiences can help tourism businesses differentiate themselves and attract visitors, regardless of exchange rate fluctuations. Focusing on quality service, personalized experiences, and showcasing the unique aspects of the destination can create an emotional connection with travelers and make them more willing to spend, regardless of the exchange rate.

4. Collaborate with Financial Institutions:

Forming partnerships with commercial banks and foreign exchange providers can enable tourism businesses to provide competitive exchange rates to visitors. By offering convenient and favorable currency exchange services, businesses can enhance customers’ purchasing power and mitigate the impact of exchange rate fluctuations on their spending habits.

5. Invest in Technology and Innovation:

Utilizing advanced technology and innovative solutions can help tourism businesses streamline operations, improve efficiency, and manage costs effectively. Adopting digital payment platforms, implementing revenue management systems, and utilizing data analytics can assist in optimizing pricing strategies, forecasting demand, and identifying new market opportunities, making businesses more resilient to currency fluctuations.

6. Focus on Domestic Tourism:

During periods of currency volatility, emphasizing domestic tourism can help mitigate the effects of exchange rate fluctuations. Collaborating with local tourism boards and associations to highlight the unique attractions and experiences that can be enjoyed within the country can encourage residents to explore their own backyard, stimulating domestic tourism and reducing the reliance on international visitors.

7. Government Support and Policy Interventions:

Policies and initiatives from the government can play a crucial role in mitigating the effects of exchange rate volatility. Providing monetary incentives, tax breaks, and financial assistance to tourism businesses during periods of currency fluctuations can help cushion the impact on their operations. Additionally, collaborating with financial institutions to offer favorable loan terms and exchange rate hedging options can further support the tourism industry.

By implementing these strategies, businesses and destinations in the UK can minimize the effects of exchange rate volatility and maintain competitiveness in the global tourism market. A combination of proactive measures, innovative approaches, and supportive policies can build resilience and ensure long-term sustainability in the face of currency fluctuations.

In the final section, we will conclude our discussion on the impact of exchange rates on tourism in the UK and summarize the key insights obtained throughout this article.

Exchange rates play a significant role in shaping the tourism industry in the United Kingdom. The value of currencies impacts travel decisions, tourist spending patterns, destination competitiveness, and revenue distribution within the sector. Understanding the relationship between exchange rates and tourism demand is crucial for industry professionals and policymakers in navigating the challenges and opportunities presented by currency fluctuations.

Economic factors, geopolitical events, and government policies all contribute to fluctuations in exchange rates. These fluctuations can have both positive and negative effects on tourism demand, depending on the direction and magnitude of the currency movements. A stronger currency can attract more international visitors by making travel more affordable, while a weaker currency can impact tourism demand due to decreased purchasing power for foreign tourists.

Exchange rate fluctuations also influence tourists’ behavior, including their destination choices, spending habits, and travel duration. These changes in behavior can have implications for various tourism-related businesses and revenue distribution within the industry. Furthermore, exchange rate volatility requires businesses and destinations to adapt and develop strategies for mitigating its effects.

To mitigate the effects of exchange rate volatility, tourism businesses and destinations can diversify target markets, implement dynamic pricing strategies, offer unique experiences, collaborate with financial institutions, invest in technology and innovation, focus on domestic tourism, and seek government support and policy interventions.

By effectively addressing exchange rate fluctuations and capitalizing on the opportunities they present, the UK tourism industry can maintain competitiveness, attract visitors from diverse markets, and contribute to the country’s overall economic growth. Strategic planning, collaboration, and adaptation are essential for navigating the complexities of currency volatility and maximizing the benefits of a dynamic and ever-changing global tourism market.

In conclusion, exchange rates are not merely numbers on a screen; they are powerful variables that shape the tourism landscape. By understanding and responding to the implications of exchange rate fluctuations, the UK can harness the potential of its vibrant tourism industry and continue to enchant visitors from around the world.

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The role of exchange rate on hotelier’s pricing decision and business performance: the case of Switzerland, a small open economy

• Research Article
• Open access
• Published: 28 November 2023
• Volume 23 , pages 206–216, ( 2024 )

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• Isabella Blengini 1 &
• Cindy Yoonjoung Heo 1  

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This study focuses on the role of the exchange rate on hotelier’s pricing decision and business performance. This study explores the way hospitality industry practitioners react to exchange rate fluctuations and monetary policy interventions on the FOREX market. By analyzing monthly performance data of hotels in Switzerland between January 2000 and April 2021, this study finds the presence of two structural breaks in the economy, due, respectively, to the central bank’s intervention on the exchange rate market and to the COVID 19. The findings of this study suggest that hoteliers pay close attention to fluctuations in the exchange rate as well as to monetary policies. These findings should raise individual hoteliers’ awareness about their competitors’ behavior and help them better define their strategic decisions in terms of pricing.

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Avoid common mistakes on your manuscript.

Introduction

The tourism and hospitality sectors are highly vulnerable to various external factors, ranging from competition, weather conditions, natural disasters, political and legal issues, to macro economic factors. Among the existing external factors, economic variables, such as inflation and exchange rates, play a key role behind demand volatility and uncertainty in the tourism sector globally (Ongan and Gozgor 2018 ; Wu and Wu 2019 ). As these external factors are difficult to manage let alone control, it is important for industry practitioners to promptly react to those shocks, whenever they hit the market.

The role of exchange rate on tourism demand has been examined in the literature. In particular, several studies focused on the relationship between exchange rate fluctuations and international tourist demand (e.g., Aalen et al. 2019 ; Corgel et al. 2013 ; De Vita and Kyaw 2013 ; De Vita 2014 ; Karimi et al. 2019 ; Peng et al. 2015 ). Webber ( 2001 ) pointed out that tourism is one particular commodity that is likely to be affected by exchange rate fluctuations. Exchange rate fluctuations in fact may affect international tourists’ destination choice and impact their intended duration of stay and expenditure (Wang et al. 2008 ). Nevertheless, little research has explored how exchange rate fluctuations affect the strategic decisions (e.g., pricing) and business performance of tourism service providers (e.g., hotels). This study focuses on the special case of Switzerland and analyzes how exchange rate fluctuations are related to the pricing decisions and business performance of the Swiss hospitality sector, with a particular emphasis on hotel classes. Switzerland is a particularly interesting case because it is physically inside the European Monetary Union, but operates under its own currency, the Swiss franc. The hospitality industry is one of the important pillars of the Swiss economy. During the last decade, political and economic instability all over the world have reinforced the “safe haven” status of Switzerland, which resulted in a sequence of appreciations of the Swiss franc. In order to protect the most export-oriented sectors, the Swiss National Bank (SNB) introduced an exchange rate floor between September 2011 and January 2015, which limited currency appreciations above the limit of 1.2 Swiss franc per euro (Fig.  1 ). Such policy can indicate signs of reduced uncertainty to the markets and give guidance in a period of uncertainty.

Source https://www.macrotrends.net

Nominal exchange rate between the Swiss franc and the euro (number of Swiss francs for 1 euro). *A reduction in the value of the exchange rate means that the Swiss franc is appreciating.

The goal of this paper is twofold: First, this study explores the relationship between the exchange rate and the performance of hotels categorized by class; second, it tests whether the intervention of the SNB on the exchange rate market generated a structural break in the economy, i.e., a structural change in the relationship among economic variables. In order to do so, the study compares the relationship between performance and exchange rate during the period of intervention of the SNB with the one observed when the exchange rate is completely free to fluctuate. This sheds light on whether policy interventions affect the natural relationship between market variables and create structural breaks in the economy. Furthermore, the recent COVID 19 outbreak has brought major economic disruption in the tourism industry. By analyzing the monthly performance data of hotels in Switzerland over the period from January 2000 to April 2021, this study finds the presence of two structural breaks in the economy, due-respectively- to the central bank intervention on the exchange rate market between 2011 and 2015, and to COVID 19.

The remainder of the paper is organized as follows: the next section provides a literature review on the importance of the exchange rate on international tourism demand.

The theoretical framework and the empirical model are outlined in " Theoretical framework " and " The empirical model " sections, and data and the main descriptive statistics are presented in " Data and descriptive statistics " section. " Empirical analysis " section treats the issue of instrumental variables and analyzes the results of the empirical analysis, and the last section concludes.

Related literature

One of the central themes analyzed by the macroeconomic literature is the relationship between exchange rate and production. If one country’s currency becomes stronger, this implies that the residents of the country increase their purchasing power abroad, while, at the same time, the country loses its competitivity abroad. The theory predicts that these two combined effects generate a reduction in the level of production of the country which experienced the appreciation of the currency. Nevertheless, the empirical evidence does not always confirm these theoretical predictions.

Among the most influential studies in macroeconomics, Baxter and Stockman ( 1989 ) found that the exchange rate regime has little systematic effect on the business cycle properties of macroeconomic aggregates, including gross domestic product (GDP). Flood and Rose ( 1995 ) confirm these findings and suggest that the exchange rate “appears to have a life of its own”. Obstfeld and Rogoff ( 1995 ), observing the weak relationship between exchange rates and other macroeconomic aggregates, introduce the “exchange rate disconnect puzzle”. Unlike previous literature, they find that the degree of correlation between exchange rate and GDP varies depending on the level of development of the country. Developing countries display stronger correlations than developed ones, which might be explained by their heterogeneous economic structures and by the different types of shocks that they face. They find for all the countries a high correlation between exchange rate and trade flows (imports and exports). Finally, Di Nino et al. ( 2011 ) conduct a panel analysis including several countries for the period between 1861 and 2011. They observe asymmetric effects of (real) exchange rate movements for developing and developed countries. Additionally, in the second part of their paper, they focus their attention only on Italy, underlying how the impact of the exchange rate changes depending on the sector.

The importance of the exchange rate is widely recognized in the literature on international tourism demand. International tourists tend to choose destinations in which the exchange rate is more favorable (Wang et al. 2008 ) and the variations of exchange rates may affect tourists’ expenditure and duration of stay (Gao et al. 2018 ). A substantial number of studies have included some form of exchange rate variable in their models of tourism demand (e.g., Bond et al. 1977 ; Gao et al. 2018 ; Karimi et al. 2019 ; Webber 2001 ), but the research has reached mixed conclusions. According to Crouch ( 1994a )’s analysis of the literature on the topic, while many studies find that the exchange rate has significant effects on tourism demand (e.g., Cheng et al. 2013 ; Eilat and Einav 2004 ; Saayman and Saayman 2013 ; Vogt 2008 ), other studies find no relationship between exchange rate and tourism demand (e.g., Gao, et al. 2018 ; Vanegas and Croes 2000 ; Quadri and Zheng 2010 ). Furthermore, some scholars argue that exchange rate effects are different, depending on the countries considered (e.g., Croes and Vanegas 2005 ).

De Vita ( 2014 ) and Webber ( 2001 ) look at the exchange rate regime and at the volatility of the exchange rate and emphasize the importance of maintaining a relatively stable exchange rate in order to attract international tourist arrivals. Quadri and Zheng ( 2010 ) study how the bilateral exchange rate affects international tourist arrivals to Italy and find no effect in 11 out of the 19 countries being studied. Falk ( 2014 ) specifically analyzes the case of Switzerland and studies how exchange rate appreciations affected Swiss alpine resorts over the period 2007–2011. His findings suggest that Swiss franc appreciations have strongly affected Alpine destinations, while cities and lake destinations have registered a much weaker effect. In his analysis, he looks at the nominal exchange rate and at a modified measure of real exchange rate, including the price index of competitors instead of the price index of the origin country. Aalen et al. ( 2019 ), using a panel of hotel overnight data from Norway, find that the nominal exchange rate affects hotel occupancy with a lag of two/three quarters. Vogt ( 2008 ) concludes that exchange rate volatilities along with real income greatly influence inbound tourist arrivals in the U.S. Stettler ( 2017 ), using highly disaggregated data collected in 141 Swiss communities, finds that real exchange rate appreciations do not affect touristic demand in cities nearly as much as they do in touristic communities. Furthermore, he underlines that, among European tourists, German, Dutch and Belgian visitors seem to react to the Swiss franc’s appreciations much more strongly than French and Italian ones. Finally, Corgel et al. ( 2013 ) study how demand for U.S. hotel rooms responded to (real) dollar fluctuations. Their findings suggest that exchange rates have a minor effect on hotel demand and that the exchange rate affects luxury, upper upscale and upscale segments more than lower-price hotels.

Empirical studies in the hospitality and tourism literature have extensively discussed the role of the exchange rate, but, to the best of the authors’ knowledge, they have all agreed on one main point: the dependent variable. The dependent variable considered has always been a quantity, mostly represented by tourist arrivals and hotel occupancy. Unlike the previous literature, this study explores how exchange rate fluctuations affect hoteliers’ response and their business performance.

In the hospitality industry, the room rate (average daily rate, ADR) has a crucial role in the performance of hotels. High occupancy (i.e., total number of overnight stays) does not always indicate a positive impact on business performance (i.e., revenue and profit). Therefore, estimating the impact of exchange rate on hotel demand may show only limited implications. Instead, Revenue per Available Room (RevPAR), which is calculated by multiplying a hotel's ADR by its occupancy rate, is commonly used as a performance metric in the hospitality industry. This study focuses on how exchange rate affects the hotelier’s pricing decision (ADR) and, indirectly, the business performance (RevPAR, which is highly correlated with ADR, as shown in Table 3 ) of hotels categorized by class in Switzerland. We find it interesting to study the pricing strategy, because occupancy and ADR are influenced by different sets of agents. Occupancy can be seen as the result of consumers’ decisions, while ADR is a strategic variable chosen by hotel managers. As the literature has mostly focused on occupancy rates, our analysis will allow us to better understand whether different sets of agents react differently to the same shock. Last but not least, the Swiss experience is used to infer how hoteliers’ incentives are affected by an exchange rate that is under the control of the monetary authority. Switzerland represents an interesting case also because it is a small open economy highly focused on exports and imports. To the best of the authors’ knowledge, the role of exchange rate related to monetary policy in the hospitality sector has not received a lot of attention yet. Blengini and Heo ( 2020 ) explored how hotels adopting different business models react to macroeconomic shocks, including exchange rate fluctuations. According to Blengini and Heo ( 2020 ) mostly chains and independent hotels react to exchange rate fluctuations, while franchise hotels are not affected in any significant way. Finally, Inchausti-Sintes and Pérez-Granja ( 2022 ), where, adopting a dynamic stochastic general equilibrium modeling (DSGE) approach, they compare the effects of different monetary policies on the macroeconomic variables of three touristic islands. Rather than considering a macroeconomic setting, this study follows a more microeconomic approach, specifically focusing on the hospitality industry and looking at the effects of the monetary policy for exchange rate on hoteliers’ pricing decision and on equilibrium occupancy rates.

Theoretical framework

In order to justify the empirical model, the study moves from the structural form of a simple theoretical model, where the individual hotel operates in monopolistic competition. The demand function is the following:

where \({Q}_{t}^{\mathrm{D}}\) represents the quantity of rooms demanded, \(a\) is a constant, \(p\) is the price of a room, and \(b\) the slope of the demand function. \({d}_{t}\) represents time-varying variables (for example macroeconomic variables like GDP and exchange rate that can affect demand and supply) and \(c\) are the coefficients associated with these time-varying variables.

In equilibrium, ADR (the equilibrium price) and Occupancy (the equilibrium quantity normalized by the number of rooms available) can be expressed as follows:

where \({\alpha }_{1}\) and \({\alpha }_{2}\) are the two intercepts, while \({{f}_{1}\delta }_{t}\) and \({{f}_{2}\delta }_{t}\) are the time-varying macroeconomic variables and their coefficients.

Note that all the coefficients and variables appearing in the reduced form model are a combination of the ones initially used in the structural form model.

More precisely:

where m is a constant marginal cost.

The empirical model

The analysis focuses on the equilibrium room price, ADR. As already shown, ADR can be expressed as a function of a set of constants, time-varying terms, including macroeconomic variables that shift hotel demand and supply, plus an error term.

In the empirical model, we underline heterogeneity among classes and focus on the relationship between the dependent variable, ADR, and a specific macroeconomic time-varying variable: the exchange rate. Footnote 1 We emphasize the role of class heterogeneity because they define different sub-markets characterized by heterogeneous levels of price elasticities. As a result, the economic intuition suggests that the same exchange rate shock should have significantly different effects on the prices fixed in the different classes, mainly depending on firms’ market power and on consumers’ willingness to pay.

The reduced form equation can be rewritten as follows:

With i  = Luxury, Upper Upscale, Upscale, Upper Midscale, Midscale and Economy.

The regression includes a constant, \(\alpha ,\) the exchange rate, ER, which is a time-varying variable that does not change with classes, the parameter \(\beta\) that describes the relationship between the dependent variable and the exchange rate, which is common to all the classes; \({\gamma }_{i}\) describes the specific relationship between the dependent variable and the exchange rate for each class i . In practice, we test if the slope of each regression is significantly different among classes or not. Consider for example the luxury class. The relationship (the slope) between the dependent variable and the exchange rate is defined by ( \(\beta\) \(+ {\gamma }_{\mathrm{luxury}}\) ). And that logic applies to all the other classes. In this specification, each class has a specific slope. Finally \({\mu }_{t}\) —which is a time fixed effect, i.e., a dummy variable common to all classes—is included. Being aware that other macroeconomic variables besides the exchange rate could affect our dependent variable, our modelling choice to address this issue was to use time (monthly) dummies instead of specific macroeconomic variables, which is a highly flexible and less arbitrary approach, as the literature suggests.

The most interesting feature of the model is represented by the interaction term \({\gamma }_{i}{\mathrm{lnER}}_{t}\) . This is the model that allows us to answer the first question: do exchange rates appreciations affect hotel classes differently?

Data and descriptive statistics

The analysis included herein used monthly data for Switzerland over the period running from January 2000 to April 2021. The period considered is composed of 256 months (1353 observations). The data concerning hotel performance indicators have been supplied by Smith Travel Research (STR). ADR is denominated in local currency, the Swiss franc, and categorized by class, according to STR classification: Luxury, Upper Upscale, Upscale, Upper Midscale, Midscale and Economy. We have observations for the whole period for luxury and upper scale hotels, while the number of observations is smaller for midscale and economy hotels.

As shown in Table 1 , the data suggest that during the period considered the average occupancy rate for the hotels in the sample was 62%, while average ADR was around CHF 220 CHF and average RevPAR, which combines occupancy and average price, was approximately CHF 133. Looking more in detail at the summary statistics by class, the highest average ADR and RevPAR are observed in luxury hotels immediately followed by Upper Upscale hotels. In terms of rooms sold, Midscale hotels register the highest occupancy ratio (around 66%) followed by Upper Upscale, Upscale and Economy hotels. Footnote 2

This study’s main exogenous variable is the real exchange rate between Switzerland and its main trading partners. The real effective exchange rate index is calculated by the Swiss National Bank (SNB) as a weighted average of bilateral exchange rates, using a variable group of countries that is updated annually. The weighting method applied uses the International Monetary Fund (IMF) approach and takes into account export and import flows as well as so-called third-market effects. The index formula used is a chained Törnqvist index. Footnote 3 The real exchange rate (RER) index measures the real external value of the Swiss franc and is calculated as the nominal exchange rate (NER) index adjusted for price developments in Switzerland and abroad. RER is frequently used as an indicator for assessing the price competitiveness of an economy in the literature. A rise in the index value indicates an appreciation in the Swiss franc.

As Table 2 shows, the data suggest that the highest average values for the three performance indicators are observed at the very beginning of the sample in 2000 Footnote 4 and 2001. Not surprisingly, 2020 looks as the worst year in terms of occupancy rate (at around 30%), ADR and RevPAR (respectively at around CHF 197 and CHF 60). It is also worth noting that in 2020, there is an increase in the real exchange rate (RER) index, indicating a strengthening of the Swiss franc.

In the depths of the financial crisis, which started in 2007 in the US and then moved to Europe until 2012/2013, there is a contraction in occupancy rate, ADR and RevPAR, especially between 2009 and 2014. Additionally, between September 2011 and January 2015, the SNB intervened on the financial markets introducing an exchange rate floor to limit Swiss franc appreciations versus the euro. During that period, the real exchange rate stabilizes and slightly depreciates. Furthermore, during the SNB intervention, there is a strengthening of the occupancy rate, which goes from 63 to 66% and a slight weakening of the ADR, which moves from CHF 217 in 2011 to CHF 210/211 towards the end of the intervention. During this period, RevPAR slightly fluctuates and reaches CHF 135 in 2014. After the Swiss National Bank abandoned its exchange rate floor in January 2015, and the economic recovery in Europe and in the US, the Swiss franc appreciates markedly. In this period the occupancy rate, as well as ADR and RevPAR slightly weaken, to recover in the following years.

Table 3 displays pairwise correlations between variables. Intuitively there is a negative correlation between occupancy and average price (ADR). RevPAR displays a small and positive correlation with occupancy, while it is strongly correlated with ADR, which is a result that we also constantly observe in the analysis. RER is negatively correlated with the three performance indicators. More precisely, they show a weak correlation with ADR and RevPAR and a stronger one with Occupancy. The table also shows the nominal exchange rate (NER), which displays a very high correlation with the RER. Additionally, the correlation between performance indicators and RER is very similar to the correlation between performance indicators and NER, which explains our choice to include only the RER in our regressions.

As already mentioned, in the analysis time dummy variables have been included. This allows to control for seasonality and, at the same time, avoids introducing other macroeconomic variables, still controlling for changes in the environment that took place over time.

Empirical analysis

After controlling for autocorrelation, i.e., the correlation between one variable and its previous values, we found that the dependent variable as well as the exchange rate (the independent variable) have a problem of autocorrelation. To find the optimal number of lags to be included in the regressions, Schwarz's Bayesian information criterion (SBIC) was used, the Akaike's information criterion (AIC), and the Hannan and Quinn information criterion (HQIC), which suggested to use one lag for the dependent as well as for the independent variable. Hence, the regressions have been modified as follows:

Given that in principle exchange rates are daily variables, it seems reasonable to imagine that they affect the hotel performance indicators with a one-month delay. Even though the goal of the paper is not to test for the causality between exchange rate and hotel performance, it is worth noting that the model nests a Granger test. If the parameters \(\beta\) and \(\gamma\) prove significant, de facto we are saying that the exchange rate Granger-causes the endogenous variable under study. We do not test for reverse causation, i.e., causality going from hotel performance indicators to exchange rate, because economically it is unreasonable to imagine that one sector in the economy is able to affect a macroeconomic variable like the exchange rate.

Room demand and supply are included in the specifications as control variables. The combination of demand and supply, as defined by STR, determine the occupancy rate, which affects ADR, as shown in our simple theoretical model. We preferred to include demand and supply separately instead of working directly with the occupancy rate to better evaluate the effects of the two components on the dependent variable.

Given that study sample includes the period of the pandemic, we ran the same regression over the whole period as well as over the two sub-periods before January 2020 and from January 2020 and April 2021, which we named “pre-COVID” and “COVID” period.

Table 4 shows that results depend on the period considered. If we consider the whole sample, including pre-COVID and COVID sub-periods, a Swiss franc appreciation significantly increases ADR in the luxury segment and reduces it in the economy segment. Nevertheless, it is worth underlying that during the COVID period, many of the traditional economic relationships broke up. In fact, the results suggest that during this period exchange rate appreciations, room demand and supply do not produce any effects on ADR. When only the pre-COVID period is considered, a Swiss franc appreciation negatively affects ADR for midscale and economy hotels.

Overall, midscale and economy hotels react to exchange rate appreciations in a quite sophisticated way. Knowing that their guests are relatively highly sensitive to price increases, midscale and economy hotels may reduce their ADR when it is objectively necessary, which is to say when they are losing competitive edge abroad.

Instrumental variable analysis

To control for any endogeneity problems, Footnote 5 we use instrumental variables (IV) to approximate the RER. Following the literature, we use Swiss international official reserves (IR) to predict exchange rate movements. IR pass all the weak instruments tests, indicating that they are good instruments for RER. The correlation between RER and IR is quite high (0.83). Additionally, we conduct a weak instrument test to demonstrate that IR is a good and strong instrument to explain our endogenous variable, RER (Table 5 ).

In Table 6 we show the results of our two-stage-least-squares regressions (2SLS) done over the three periods, as already done in Table 4 . We controlled for heteroskedasticity-robust standard errors. The results suggest that a Swiss franc appreciation generates significant effects only if we consider the pre-COVID period. A 1% appreciation reduces ADR in all the classes, with the only exception of the luxury class. Data suggest that the ADR reduction is stronger in lower classes. Intuitively, classes characterized by a more price-elastic demand reduce their prices in a relatively stronger way to compensate for the currency appreciation.

Exchange rate fluctuations: monetary policy

As mentioned in the introduction, one of the goals of this study is to study the effects of the exchange rate fluctuations on the hospitality industry. In Switzerland, the minimum exchange rate of CHF 1.20 per euro between 6 September 2011 and 15 January 2015 was the major monetary policy instrument that the SNB used to limit the appreciation of the Swiss franc. In this last section of the paper, we conduct a Chow test in order to verify whether the SNB’s intervention between September 2011 and January 2015 generated a structural break in the parameters of the model. A Chow test is a test of whether the true coefficients in two linear regressions on different data sets are equal (Chow 1960 ). This approach is typically used in the field of econometrics with time series data to determine if there is a structural break in the data at some point. By structural break we mean a change in the fundamental relationship between variables. Did the awareness that the SNB was protecting the Swiss franc from extreme appreciations, change the relationship between exchange rate movements and hotel performance? In other terms, during the SNB intervention, did hotels change their pricing strategies, knowing that the risk of franc appreciation was relatively low? Our results confirm the existence of a structural break in the relationship between the exchange rate and ADR in the pre-COVID period.

Table 7 shows the results of OLS, IV, IV with SNB intervention and IV without SNB intervention regressions, only considering the period before COVID. When the exchange rate is free to fluctuate (non-intervention period), exchange rate appreciations lower the ADR in all the classes, with the only exception of the luxury class. During the period of the SNB intervention, instead, paradoxically we observe an increase in ADR in all the classes but the Economy class. This increase is stronger the higher the hotel class. A possible interpretation of this result is that the SNB intervention created an expectation of stability in the hotel industry that reduced the responsiveness of hoteliers to Swiss franc appreciations. Surprisingly enough, during the central bank intervention, hoteliers not only did not react in the expected way to Swiss franc appreciations, but actually took advantage of those to increase their own prices.

Several scholars have studied the role of the exchange rate on international tourism demand, while the topic has been less explored in the hospitality literature. In a break with extant literature, this study focuses on ADR, which represent a more strategic variable controlled by hotel managers. Furthermore, we categorize hotels by class to verify whether the same shock produces differentiated effects in the industry, as the economic intuition would suggest. We study the special case of Switzerland, which experienced a sequence of important currency appreciations as well as an explicit and strong intervention of the Central Bank to limit them.

This study finds the presence of a structural break in the economy, due to the central bank intervention on the exchange rate market. During the period when the exchange rate floor was in place, hotels’ performance was not affected by exchange rate appreciations. On the contrary, when the exchange rate was free to fluctuate, hoteliers promptly reacted to currency appreciations. The awareness that the SNB was protecting the Swiss franc from strong appreciations, induced hoteliers not to reduce ADR, which stands in contrast to their behavior when the exchange rate has been free to fluctuate. Interestingly enough, this finding suggests that hoteliers pay close attention to economic variables' fluctuations as well as to economic policies. This implies that the policymaker, using her policy instruments, can affect hoteliers’ incentives and induce them to adopt optimal behaviors. Further, given that the last period of observations includes the first wave of COVID 19, this study verifies the stability of the study’s results over the COVID (i.e., between January 2020 and April 2021) and non-COVID period (i.e., before January 2020) suggesting the existence of a structural break in the economy between these two periods. In other words, during the COVID period the traditional relationships between economic variables broke.

This study’s main results suggest that the sample of hotels act in a quite sophisticated way in terms of pricing decisions. Hoteliers belonging to different classes on average react differently to real exchange rate appreciations. In the pre pandemic period we observe that currency appreciations induce all classes, but the luxury one, to reduce their prices. Nevertheless, during the pandemic, strong price reductions have been observed in the luxury sector. These reductions were most likely not related to currency appreciations, but rather to other strategic considerations.

We find that hotel managers’ expectations concerning exchange rate fluctuations have a huge impact on the performance of hotels. We find a structural break in the economy, indicating that prices are negatively affected by exchange rate appreciations during periods of high uncertainty. On the other hand, during the intervention of the SNB to limit the Swiss franc’s appreciations, hoteliers felt less exposed to currency risk and reduced their tendency to lower prices despite the Swiss franc’s appreciations.

The COVID 19 pandemic has triggered a massive shock in the tourism industry and the tourism and hospitality sector continue to be one of the sectors hardest hit by the COVID 19 pandemic. While many countries started to develop recovery measures to support the tourism and hospitality sector, policy makers already should consider the longer-term implications of the COVID 19 pandemic and prepare for actions to support the sustainable recovery of tourism. Therefore, the findings of our study are especially interesting in the current period, which has been characterized by strong policy interventions aimed at containing the diffusion of COVID 19. The findings of this research suggest that government’s policies could be used to reduce economic uncertainty. This study is valuable in the sense that it allows us to gain awareness on how hoteliers’ pricing decisions are related to exchange rate fluctuations as well as to policy interventions to manage economic uncertainty. On the one hand this analysis can help the individual hotelier gain awareness and understand how on average the market is behaving during policy interventions; on the other hand, it can shed light on the potential for policymaking.

Nevertheless, the paper presents some limits that should be explored in future research. First, the size of the sample is relatively small, and hotels are not fairly represented across classes. STR data are collected on a voluntary basis which that STR can provide data only for a group of hotels that decide to participate. For questions of privacy, STR does not provide disaggregated data, but only an average by group, under the condition to have at least five observations for each group of hotels. Overall, the data tend to be biased towards upper scale classes. Our database represents around 35% of the total number of upper scale hotels in Switzerland (luxury, upper upscale and upscale), while only 7% of the total number of lower scale hotels in Switzerland (upper midscale, midscale and economy). In the analysis, we focus our attention on the specific case of Switzerland. From a certain point of view, Switzerland is a very interesting case, because it is a small open economy, extremely focused on the international trade and on the exchange rate policy. At the same time, we recognize that it could be interesting to extend the analysis to other countries, which could allow at the same time to verify the solidity of our findings and reduce the aforementioned sample issue.

We encourage future study to extend the analysis in several directions. For example, one interesting extension of the study would consist in including additional regressors besides the exchange rate, like Airbnb’s presence on the market and oil prices, and some features that specifically characterize the hotels considered (size, location, business model), which is commonplace in the hedonic pricing literature. One other possibility, especially in the light of the most recent events, would be to include other policy interventions and evaluate if and how they have affected the hospitality industry performance.

Data availability

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

We express everything in terms of logarithms so that the estimated coefficients can be interpreted as elasticities.

Note that the large number of missing observations for midscale and economy hotels might affect average occupancy.

The Törnqvist index is a specific changing-weight index, which has been termed a superlative index by several index number theorists (Diewert 1976 ).

In 2018, the highest value for the average ADR is around CHF 260. Nevertheless, for 2018 only first quarter data were available.

The Durbin–Wu–Hausman test for endogeneity suggests that OLS and IV coefficients are systematically different. In other words, the test suggests the existence of endogeneity and the need to use IV.

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Acknowledgment

The authors wish to thank Smith Travel Research ( STR ) for providing portions of the data used for this study.

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Blengini, I., Heo, C.Y. The role of exchange rate on hotelier’s pricing decision and business performance: the case of Switzerland, a small open economy. J Revenue Pricing Manag 23 , 206–216 (2024). https://doi.org/10.1057/s41272-023-00461-7

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Exchange Rate trends, how do they impact hotel performance?

November 12, 2020 •

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In this report we analyze how exchange rate fluctuations affect the hospitality industry. We consider the case of Switzerland, which is a small open economy located in the heart of the European monetary union.

Switzerland is a very special country because, thanks to its stability, it has always been considered a safe haven where international investors put their resources when there is economic turmoil and uncertainty in the rest of the world. The combination of these two features - a high degree of openness and a currency which has a tendency to appreciate - makes Switzerland a very interesting case study. Why? Because a strong currency reduces the ability of Switzerland to trade.

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In general, exchange rate fluctuations affect any generic sector exposed to trade with foreign countries, as follows:

In particular, Hospitality and Tourism industries fall into the category of export-oriented sectors because they export services. When we export goods, we physically move a good from the country where it has been produced to a foreign country where it is going to be consumed. In the case of services, instead, we export a service whenever the consumer (resident in a foreign country, the tourist) physically goes to the country of the producer, where he/she consumes the service. Consider for example a German resident going on holiday to the UK. Any night spent in a UK hotel is considered as an export from UK to Germany.

As explained in Table 1, a stronger Swiss franc not only reduces Germans’ incentives to go to Switzerland for their holidays, but also stimulates Swiss people to go to Germany for their vacation, given their relatively high purchasing power abroad.

Switzerland has historically been perceived as a “safe haven”. During turmoil, investors have a tendency to buy Swiss francs which produces the effect of strengthening the currency. In Figure , we show an index which represents the exchange rate between the Swiss franc and several other currencies. An increase in the index is an appreciation of the Swiss franc. As you can observe, we had strong appreciations during and after the 2008 Great Recession, as well as during the COVID-19, which was born as a health crisis, but soon turned into an economic crisis.

Figure 1: Nominal exchange rate between the Swiss franc and a set of other currencies

Figure 2: Exchange rate between CHF and Euro. How many CHF for 1 Euro.

If we focus more specifically on the exchange rate between the Swiss franc and euro and on the period between 2000 and 2018 (Figure 2), we can see that in 2000 the exchange rate between CHF and euro was 1.6 (1.6 CHF for 1 euro), while starting from the world financial crisis in 2008, we observe a progressive strengthening of the Swiss franc. During the crisis, Switzerland was perceived as a safe haven, which explains why investors started to strongly buy Swiss francs. Such a high demand increased the value of the Swiss franc, which almost reached parity with the euro (1 CHF = 1 euro) in 2011. This is why the Swiss National Bank (SNB) intervened in September 2011 introducing a limit to Swiss franc appreciations with respect to the euro. With this intervention, the SNB committed to acting on the forex market with the goal of preventing the exchange rate to go below 1.2 CHF for 1 euro. This intervention lasted until January 2015, when the SNB decided that it was time to let the exchange rate freely fluctuate. As you can see from the picture, that same day, the CHF strongly appreciated and reached parity with the euro (1 CHF for 1 euro).

Having observed the fluctuations in hotel demand and pricing, we study whether these fluctuations are associated to exchange rate movements.

• In order to do so, we classify hotels by geographic market , class (luxury, up upscale, upscale, up midscale, midscale and economy) and type of operation (independent, franchise and chain) and we analyze how the different categories of hotels respond to exchange rate appreciations.
• Additionally, we focus our attention on the intervention of the SNB and we study whether it affected the behaviors of hotels and clients between June 2011 and January 2015. Is it possible that pricing and consumption behaviors changed during the SNB intervention? Is it possible that agents (hotels and consumers) modified their behaviors knowing that the SNB was protecting them?

Hotel performance is surely related to local factors which go beyond hotel class and operation (business model). Northern areas of Switzerland seem to be more exposed to international competition and react more to exchange rate fluctuations. Southern and central areas are more touristic, but somehow seem more protected from international competition. One reason might be that their prices are relatively low with respect to the average Swiss hotel prices (central Switzerland) or another reason might be that their demand is quite rigid (Ticino for example has a relatively high average ADR and does not show any intention to reduce it because of exchange rate appreciations. Mountain regions have an average ADR but a relatively low occupancy).

Nevertheless, our results seem to suggest that chains and higher class hotels (luxury, upscale) have a better ability to insure themselves against exchange rate fluctuations. If necessary, independent hotels also limit their losses, but in a way that is different from chains. Independent hotels simply do not react to shocks at all, while chains are more prone to change prices in response to market forces.

Data suggest that over time the market is expanding in a stronger way in the regions that better react to exchange rate appreciations (Figure 3): Lake Geneva and Northern Switzerland. In fact, even if during the last decade hotels in this region had to face some negative shocks that implied some losses, we should always remember that, on average, their performance is well above the one of all the other parts of Switzerland.

Similarly, we observe in the last twenty years an important increase in luxury and upper scale hotels (Figure 4), and chains (Figure 5), which seems quite consistent with our results.

Figure 3: Evolution of hotels by region between 2000 and 2018

Figure 4: Evolution of hotels by class between 2000 and 2018

We also observe a larger increase in chains and franchises rather than in independent hotels, which still represent the vast majority of hotels in Switzerland.

Figure 5: Evolution of hotels by operation between 2000 and 2018

The present study was conducted before the COVID-19, using data between 2000 and 2018. Nevertheless, its main implications may apply also now. During the first months of this health crisis that soon turned into an economic crisis, the Swiss franc in fact showed a tendency to appreciate towards most of the currencies (Figure 1), replicating a situation similar to the one that we observed during the 2008 crisis. Future research will have to delve deeper into the analysis to understand whether the recent franc appreciations produced similar results on the hotel industry as the ones that we observed during and immediately after the Great Recession of 2008.

Associate Professor in Economics at EHL

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Tourism Review

ISSN : 1660-5373

Article publication date: 13 March 2020

Issue publication date: 25 March 2021

One of the main factors that can impact the cost of holidays to a particular destination is the exchange rate; exchange rate fluctuations impact the overall price of the holiday and should be expected to effect tourism demand. This paper aims to scrutinize the volatility of the real effective exchange rate between the source market relative to the holiday destination and tourism demand volatility, where the influence of disaggregated data is noted.

Design/methodology/approach

The study uses multivariate conditional volatility regressions to simulate the time-varying conditional variances of international visitor demand and exchange rates for the relatively mature Caribbean tourist destination of Barbados. Data on the country’s main source markets, the UK, the USA and Canada is used, where the decision to disaggregate the analysis by market allows the authors to contribute to policymaking, particularly the future of tourism marketing.

The volatility models used in the paper suggests that shocks to total arrivals, as well as the USA and UK markets tend to die out relatively quickly. Asymmetric effects were observed for total arrivals, mainly due to the combination of the different source markets and potential evidence of Butler’s (1980) concept of a tourist area’s cycle of growth. The results also highlight the significance of using disaggregated tourism demand models to simulate volatility, as aggregated models do not adequately capture source market specific shocks, due to the potential model misspecification. Exchange rate volatility is postulated to have resulted in the greater utilization of packaged tours in some markets, while the effects of the market’s online presence moderates the impact of exchange rate volatility on tourist arrivals. Markets should also explore the potential of attracting higher numbers of older tourist, as this group may have higher disposable incomes, thereby mitigating the influence of exchange rate volatility.

Research limitations/implications

Some of the explanatory variables were not available on a high enough frequency and proxies had to be used. However, the approach used was consistent with other papers in the literature.

Practical implications

The results from the paper suggest that the effects of exchange rate volatility in key source markets were offset by non-price factors in some markets and the existence of the exchange rate peg in others. In particular, the online presence of the destination was one of those non-price factors highlighted as being important.

Originality/value

In most theoretical models of tourism demand, disaggregation is not normally considered a significant aspect of the model. This paper contributes to the literature by investigating the impact real effective exchange rate volatility has on tourism demand at a disaggregated source country level. The approach highlights the importance of modeling tourism demand at a disaggregated level and provides important perspective from a mature small island destination.

该研究采用多元条件波动回归来拟合相对成熟的加勒比海旅游目的地巴巴多斯的国际游客需求和汇率的时变条件方差。本研究逐一分析了该国主要客源市场（英国, 美国和加拿大）的数据, 从而为政策制定, 尤其是对今后的旅游营销做出贡献。

汇率是影响到特定目的地度假成本的主要因素之一。汇率波动会影响整体的度假成本, 并会影响旅游需求。基于按客源地分类的数据, 本文详细研究了客源市场相对于度假目的地的实际有效汇率的波动性以及旅游需求的波动性。

本文使用的波动模型表明, 汇率冲击对入境总人数以及美国和英国市场影响短暂。冲击对总入境人数产生的不对称效应, 主要是由于不同的客源市场加总和巴特勒（1980）关于旅游区增长周期概念所致。本文结论还凸显了使用基于客源地数据的旅游需求模型来模拟波动性的重要性, 因为加总数据不能充分捕获具体客源地市场的冲击从而产生模型设定作物。汇率波动会引起某些市场中团体游客的增加, 而目的地的线上热度影响会调节汇率波动对游客人数的影响。市场还应探索吸引更多老年游客的潜力, 因为该群体的可支配收入可能更高, 从而减轻了汇率波动的影响。

由于一些解释变量的数据频率不够高, 本文不得不使用一些替代指标。所使用的方法与文献中的其他论文一致。

该论文的结果表明, 在某些客源地市场, 汇率波动的影响会被某非价格因素所抵消, 而在另一些主要客源地市场, 固定汇率的存在刚好规避了汇率波动产生的影响。目的地的线上热度是重要的非价格因素之一。

在大多数旅游需求理论模型中, 按客源地拆分的数据通常不被视为模型的重要方面。本文的理论贡献则是通过研究实际有效汇率波动对不同客源国的旅游需求的影响强调了旅游需求建模中使用基于客源地数据的重要性, 并以一个成熟的小岛目的地为角度进行了阐述。

Uno de los principales factores que pueden afectar al costo de las vacaciones a un destino en particular es el tipo de cambio; Las fluctuaciones del tipo de cambio afectan a el precio general de las vacaciones y es normal que afecten a la demanda turística. Este documento analiza la volatilidad del tipo de cambio efectivo real entre el mercado de origen en relación con el destino de vacaciones y la volatilidad de la demanda turística, donde se observa la influencia de los datos desagregados.

Diseño/metodología/enfoque

El estudio emplea regresiones de volatilidad condicional multivariadas para simular las variaciones condicionales variables en el tiempo de la demanda de visitantes internacionales y los tipos de cambio para el destino turístico caribeño relativamente maduro de Barbados. Se emplean datos sobre los principales mercados de origen del país, el Reino Unido, los Estados Unidos de América y Canadá, donde la decisión de desagrerar el análisis por mercado permite a los autores contribuir a la formulación de políticas, en particular al futuro del marketing turístico.

Los modelos de volatilidad utilizados en el documento sugieren que los shocks en las llegadas totales, así como en los mercados de los Estados Unidos y el Reino Unido, tienden a desaparecer con relativa rapidez. Se observaron efectos asimétricos para las llegadas totales, principalmente debido a la combinación de los diferentes mercados de origen y la evidencia potencial del concepto de Butler (1980) del ciclo de crecimiento de un área turística. Los resultados también resaltan la importancia de utilizar modelos desagregados de demanda turística para simular la volatilidad, ya que los modelos agregados no capturan adecuadamente los shocks específicos del mercado de origen, debido a la posible especificación errónea del modelo. Se postula que la volatilidad del tipo de cambio influye en una mayor utilización de los paquetes turísticos en algunos mercados, mientras que los efectos de la presencia del mercado en linea (online) moderan el impacto de la volatilidad del tipo de cambio en las llegadas de turistas. Los mercados también deberían explorar el potencial de atraer un mayor número de turistas mayores, ya que este grupo puede tener mayores ingresos disponibles, mitigando así la influencia de la volatilidad del tipo de cambio.

Limitaciones / implicaciones de la investigación

Algunas de las variables explicativas no estaban disponibles en una frecuencia alta y se tuvieron que utilizar proxies. Sin embargo, el enfoque utilizado fue consistente con otros artículos en la literatura.

Implicaciones practices

Los resultados del documento sugieren que los efectos de la volatilidad del tipo de cambio en los mercados de origen clave fueron compensados por factores no relacionados con los precios en algunos mercados y la existencia de la vinculación del tipo de cambio en otros. En particular, la presencia en línea (online) del destino fue uno de esos factores no relacionados con el precio destacados como importantes.

Originalidad

En la mayoría de los modelos teóricos de la demanda turística, la desagregación normalmente no se considera un aspecto significativo del modelo. Este documento contribuye a la literatura al investigar el impacto que la volatilidad efectiva del tipo de cambio real tiene sobre la demanda turística a nivel de país de origen desagregado. El enfoque resalta la importancia de modelar la demanda turística a un nivel desagregado y proporciona una perspectiva importante desde un destino insular pequeño y maduro.

• United Kingdom
• Exchange rate
• Online presence
• Demand volatility
• Small island tourism economies
• Volatility of demand
• Market-specific behavior
• Price competitiveness
• Tour packages
• Currency fluctuations
• United States
• Tipo de cambio
• Volatilidad de la demanda
• Economías pequeñas de turismo isleño
• Comportamiento específico del mercado
• Competitividad de precios
• Paquetes turísticos
• Presencia en línea
• Fluctuaciones monetarias
• Reino Unido
• Estados Unidos

Alleyne, L.D. , Okey, O.-O. and Moore, W. (2021), "The volatility of tourism demand and real effective exchange rates: a disaggregated analysis", Tourism Review , Vol. 76 No. 2, pp. 489-502. https://doi.org/10.1108/TR-09-2019-0373

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