effects of tourism economics essay

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• Published: 05 January 2021

The relationship between tourism and economic growth among BRICS countries: a panel cointegration analysis

• Haroon Rasool   ORCID: orcid.org/0000-0002-0083-4553 1 ,
• Shafat Maqbool 2 &
• Md. Tarique 1  

Future Business Journal volume  7 , Article number:  1 ( 2021 ) Cite this article

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Tourism has become the world’s third-largest export industry after fuels and chemicals, and ahead of food and automotive products. From last few years, there has been a great surge in international tourism, culminates to 7% share of World’s total exports in 2016. To this end, the study attempts to examine the relationship between inbound tourism, financial development and economic growth by using the panel data over the period 1995–2015 for five BRICS (Brazil, Russia, India, China and South Africa) countries. The results of panel ARDL cointegration test indicate that tourism, financial development and economic growth are cointegrated in the long run. Further, the Granger causality analysis demonstrates that the causality between inbound tourism and economic growth is bi-directional, thus validates the ‘feedback-hypothesis’ in BRICS countries. The study suggests that BRICS countries should promote favorable tourism policies to push up the economic growth and in turn economic growth will positively contribute to international tourism.

Introduction

World Tourism Day 2015 was celebrated around the theme ‘One Billion Tourists; One Billion Opportunities’ highlighting the transformative potential of one billion tourists. With more than one billion tourists traveling to an international destination every year, tourism has become a leading economic sector, contributing 9.8% of global GDP and represents 7% of the world’s total exports [ 59 ]. According to the World Tourism Organization, the year 2013 saw more than 1.087 billion Foreign Tourist Arrivals and US $1075 billion foreign tourism receipts. The contribution of travel and tourism to gross domestic product (GDP) is expected to reach 10.8% at the end of 2026 [ 61 ]. Representing more than just economic strength, these figures exemplify the vast potential of tourism, to address some of the world´s most pressing challenges, including socio-economic growth and inclusive development.

Developing countries are emerging as the important players, and increasingly aware of their economic potential. Once essentially excluded from the tourism industry, the developing world has now become its major growth area. These countries majorly rely on tourism for their foreign exchange reserves. For the world’s forty poorest countries, tourism is the second-most important source of foreign exchange after oil [ 37 ].

The BRICS (Brazil, Russia, India, China and South Africa) countries have emerged as a potential bloc in the developing countries which caters the major tourists from developed countries. Tourism becomes major focus at BRICS Xiamen Summit 2017 held in China. These countries have robust growth rate, and are focal destinations for global tourists. During 1990 to 2014, these countries stride from 11% of the world’s GDP to almost 30% [ 17 ]. Among BRICS countries, China is ranked as an important destination followed by Brazil, Russia, India and South Africa [ 60 ].

The importance of inbound tourism has grown exponentially, because of its growing contribution to the economic growth in the long run. It enhances economic growth by augmenting the foreign exchange reserves [ 38 ], stimulating investments in new infrastructure, human capital and increases competition [ 9 ], promoting industrial development [ 34 ], creates jobs and hence to increase income [ 34 ], inbound tourism also generates positive externalities [ 1 , 14 ] and finally, as economy grows, one can argue that growth in GDP could lead to further increase in international tourism [ 11 ].

The tourism-led growth hypothesis (TLGH) proposed by Balaguer and Cantavella-Jorda [ 3 ], states that expansion of international tourism activities exerts economic growth, hence offering a theoretical and empirical link between inbound tourism and economic growth. Theoretically, the TLGH was directly derived from the export-led growth hypothesis (ELGH) that postulates that economic growth can be generated not only by increasing the amount of labor and capital within the economy, but also by expanding exports.

The ‘new growth theory,’ developed by Balassa [ 4 ], suggests that export expansion can trigger economic growth, because it promotes specialization and raises factors productivity by increasing competition, creating positive externalities by advancing the dispersal of specialized information and abilities. Exports also enhance economic growth by increasing the level of investment. International tourism is considered as a non-standard type of export, as it indicates a source of receipts and consumption in situ. Given the difficulties in measuring tourism activity, the economic literature tends to focus on primary and manufactured product exports, hence neglecting this economic sector. Analogous to the ELGH, the TLGH analyses the possible temporal relationship between tourism and economic growth, both in the short and long run. The question is whether tourism activity leads to economic growth or, alternatively, economic expansion drives tourism growth, or indeed a bi-directional relationship exists between the two variables.

To further substantiate the nexus, the study will investigate the plausible linkages between economic growth and international tourism while considering the relative importance of financial development in the context of BRICS nations. Financial markets are considered a key factor in producing strong economic growth, because they contribute to economic efficiency by diverting financial funds from unproductive to productive uses. The origin of this role of financial development may is traced back to the seminal work of Schumpeter [ 50 ]. In his study, Schumpeter points out that the banking system is the crucial factor for economic growth due to its role in the allocation of savings, the encouragement of innovation, and the funding of productive investments. Early works, such as Goldsmith [ 18 ], McKinnon [ 39 ] and Shaw [ 51 ] put forward considerable evidence that financial development enhances growth performance of countries. The importance of financial development in BRICS economies is reflected by the establishment of the ‘New Development Bank’ aimed at financing infrastructure and sustainable development projects in these and other developing countries. To the best of the authors’ knowledge, no attempt has been made so far to investigate the long-run relationship Footnote 1 between tourism, financial development and economic growth in case of BRICS countries. Hence, the present study is an attempt to fill the gap in the existing literature.

Review of past studies

From last few decades there has been a surge in the research related to tourism-growth nexus. The importance of growth and development and its determinants has been studied extensively both in developed and developing countries. Extant literature has recognized tourism as an important determinant of economic growth. The importance of tourism has grown exponentially, courtesy to its manifold advantages in form of employment, foreign exchange production household income and government revenues through multiplier effects, improvements in the balance of payments and growth in the number of tourism-promoted government policies [ 21 , 41 , 53 ]. Empirical findings on tourism and economic development have produced mixed finding and sometimes conflicting results despite the common choice of time series techniques as a research methodology. On empirical grounds, four hypotheses have been explored to determine the link between tourism and economic growth [ 12 ]. The first two hypotheses present an account on the unidirectional causality between the two variables, either from tourism to economic growth (Tourism-led economic growth hypothesis-TLGH) or its reserve (economic-driven tourism growth hypothesis-EDTH). The other two hypotheses support the existence of bi-directional hypothesis, (bi-directional causality hypothesis-BC) or that there is no relationship at all (no causality hypothesis-NC), respectively. According to TLEG hypothesis, tourism creates an array of benefits which spillover though multiple routes to promote the economic growth [ 55 ]. In particular, it is believed that tourism (1) increases foreign exchange earnings, which in turn can be used to finance imports [ 38 ], (2) it encourages investment and drives local firms toward greater efficiency due to the increased competition [ 3 , 31 ], (3) it alleviates unemployment, since tourism activities are heavily based on human capital [ 10 ] and (4) it leads to positive economies of scale thus, decreasing production costs for local businesses [ 1 , 14 ]. Other recent studies which find evidence in favor of the TLGH hypothesis include [ 44 , 52 ]. Even though literature is dominated by TLGH, few studies produce a result in support of EDTH [ 40 , 41 , 45 ]. Payne and Mervar [ 45 ] posit that tourism growth of a country is mobilized by the stability of well-designed economic policies, governance structures and investments in both physical and human capital. This positive and vibrant environment creates a series of development activities which proliferate and flourish the tourism. Pertaining to the readily available information, bi-directional causality could also exist between tourism income and economic growth [ 34 , 49 ]. From a policy view, a reciprocal tourism–economic growth relationship implies that government agendas should cater for promoting both areas simultaneously. Finally, there are some studies that do not offer support to any of the aforementioned hypotheses, suggesting that the impact between tourism and economic growth is insignificant [ 25 , 47 , 57 ]. There is a vast literature examining the relationship between tourism and growth as a result, only a selective literature review will be presented here.

Banday and Ismail [ 5 ] used ARDL cointegration model to test the relationship between tourism revenue and economic growth in BRICS countries from the time period of (1995–2013). The study validates the tourism-led growth hypothesis for BRICS countries, which evinces that tourism has positive influence on economic growth.

Savaş et al. [ 54 ] evaluated the tourism-led growth hypothesis in the context of Turkey. The study employed gross domestic product, real exchange rate, real total expenditure and international tourism arrivals to sketch out the causality among variables. The result reveals a unidirectional relationship between tourism and real exchange rate. The findings suggest that tourism is the driving force for economic growth, which in turn helps turkey to culminate its current account deficit.

Dhungel [ 15 ] made an effort to investigate causality between tourism and economic growth, In Nepal for the period of (1974–2012), by using Johansen’s cointegration and Error correction model. The result states that unidirectional causality exists in the long run, while in short run no causality exists between two constructs. The study emphasized that strategies should be devised to attain causality running from tourism to economic growth.

Mallick et al. [ 36 ] analyzed the nexus between economic growth and tourism in 23 Indian states over a period of 14 years (1997–2011). Using panel autoregressive distributed lag model based on three alternative estimators such as mean group estimator, pooled mean group and dynamic fixed effects, Research found that tourism exerts positive influence on economic growth in the long run.

Belloumi [ 8 ] examines the causal relationship between international tourism receipts and economic growth in Tunisia by using annual time series data for the period 1970–2007. The study uses the Johansen’s cointegration methodology to analyze the long-run relationship among the concerned variables. Granger causality based Vector error correction mechanism approach indicates that the revenues generated from tourism have a positive impact on economic growth of Tunisia. Thus, the study supports the hypothesis of tourism-driven economic growth, which is specific to developing countries that base their foreign exchange earnings on the existence of a comparative advantage in certain sectors of the economy.

Tang et al. [ 58 ] explored the dynamic Inter-relationships among tourism, economic growth and energy consumption in India for the period 1971–2012. The study employed Bounds testing approach to cointegration and generalized variance decomposition methods to analyze the relationship. The bounds testing and the Gregory-Hansen test for cointegration with structural breaks consistently reveals that energy consumption, tourism and economic growth in India are cointegrated. The study demonstrated that tourism and economic growth have positive impact on energy consumption, while tourism and economic growth are interrelated; with tourism exert significant influence on economic growth. Consequently, this study validates the tourism-led growth hypothesis in the Indian context.

Kadir and Karim [ 24 ]) examined the causal nexus between tourism and economic growth in Malaysia by applying panel time series approach for the period 1998–2005. By applying Padroni’s panel cointegration test and panel Granger causality test, the result indicated both short and long-run relationship. Further, the panel causality shows unidirectional causality directing from tourism receipts to economic growth. The result provides evidence of the significant contribution of tourism industry to Malaysia’s economic growth, thereby justifying the necessity of public intervention in providing tourism infrastructure and facilities.

Antonakakis et al. [ 2 ] test the linkage between tourism and economic growth in Europe by using a newly introduced spillover index approach. Based on monthly data for 10 European countries over the period 1995–2012, the findings suggested that the tourism–economic growth relationship is not stable over time in terms of both magnitude and direction, indicating that the tourism-led economic growth (TLEG) and the economic-driven tourism growth (EDTG) hypotheses are time-dependent. Thus, the findings of the study suggest that the same country can experience tourism-led economic growth or economic-driven tourism growth at different economic events.

Oh [ 41 ] verifies the contribution of tourism development to economic growth in the Korean economy by applying Engle and Granger two-stage approach and a bivariate Vector Autoregression model. He claimed that economic expansion lures tourists in the short run only, while there is no such long-run stable relationship between international tourism and economic development in Korea.

Empirical studies have pronouncedly focused on the literature that tourism promotes economic growth. To further substantiate the nexus, the study will investigate the plausible linkages between economic growth and international tourism while considering the relative importance of financial development in the context of BRICS nations. The inclusion of financial development in the examination of tourism-growth nexus is a unique feature of this study, which have an influencing role in economic growth as financial development has been theoretically and empirically recognized as source of comparative advantage [ 22 ].

This study employs panel ARDL cointegration approach to verify the existence of long-run association among the variables. Further, study estimated the long-run and short-run coefficients of the ARDL model. Subsequently, Dumitrescu and Hurlin [ 16 ] panel Granger causality test has been employed to check the direction of causality between tourism, financial development and economic growth among BRICS countries.

Database and methodology

Data and variables.

The study is analytical and empirical in nature, which intends to establish the relationship between economic growth and inbound tourism in BRICS countries. For the BRICS countries, limited studies have been conducted depicting the present scenario. Therefore, present study tries to verify the relevance of tourism in economic growth to further enhance the understanding of economic dynamics in BRICS countries. The data used in the study are annual figures for the period stretching from 1995 to 2015, consisting of one endogenous variable (GDP per capita, a proxy for economic growth) and two exogenous variables (international tourism receipts per capita and financial development). The variables employed in the study are based on the economic growth theory, proposed by Balassa [ 4 ], which states that export expansion has a relevant contribution in economic growth. Further, this study incorporates financial development in the model to reduce model misspecification as it is considered to have an influencing role in economic growth both theoretically and empirically [ 22 , 33 ].

The annual data for all the variables have been collected from the World Development Indicators (WDI, 2016) database. The variables used in the study includes gross domestic product per capita (GDP) in constant ($US2010) used as a proxy for economic growth (EG), international tourism receipts per capita (TR) in current US$ as it is widely accepted that the most adequate proxy of inbound tourism in a country is tourism expenditure normally expressed in terms of tourism receipts [ 32 ] and financial development (FD). In line with a recent study on the relationship between financial development and economic growth by Hassan et al. [ 19 ], financial development is surrogated by the ratio of the broad money (M3) to real GDP for all BRICS countries. Here we use the broadest definition of money (M3) as a proportion of GDP– to measure the liquid liabilities of the banking system in the economy. We use M3 as a financial depth indicator, because monetary aggregates, such as M2 or M1, may be a poor proxy in economies with underdeveloped financial systems, because they ‘are more related to the ability of the financial system to provide transaction services than to the ability to channel funds from savers to borrowers’ [ 26 ]. A higher liquidity ratio means higher intensity in the banking system. The assumption here is that the size of the financial sector is positively associated with financial services [ 29 ]. All the variables have been taken into log form.

Unit root test

To verify the long-run relationship between tourism and economic growth through Bounds testing approach, it is necessary to test for stationarity of the variables. The stationarity of all the variables can be assessed by different unit root tests. The study utilizes panel unit root test proposed by Levin et al. [ 35 ] henceforth LLC and Im et al. [ 23 ] henceforth IPS based on traditional augmented Dickey–Fuller (ADF) test. The LLC allows for heterogeneity of the intercepts across members of the panel under the null hypothesis of presence of unit root, while IPS allows for heterogeneity in intercepts as well as in the slope coefficients [ 48 ].

Panel ARDL approach to Cointegration

After checking the stationarity of the variables the study employs panel ARDL technique for Cointegration developed by Pesaran et al. [ 23 ]. Pesaran et al. [ 23 ] have introduced the pooled mean group (PMG) approach in the panel ARDL framework. According to Pesaran et al. [ 23 ], the homogeneity in the long-run relationship can be attributed to several factors such as arbitration condition, common technologies, or the institutional development which was covered by all groups. The panel ARDL bounds test [ 46 ] is more appropriate by comparing other cointegration techniques, because it is flexible regarding unit root properties of variables. This technique is more suitable when variables are integrated at different orders but not I (2). Haug [ 20 ] has argued that panel ARDL approach to cointegration provides better results for small sample data set such as in our case. The ARDL approach to cointegration estimates both long and short-run parameters and can be applied independently of variable order integration (independent of whether repressors are purely I (0), purely I(1) or combination of both. The ARDL bounds test approach used in this study is specified as follows:

where Δ is the first-difference operator, \(\alpha_{0}\) stands for constant, t is time element, \(\omega_{1} , \omega_{2} \;\;{\text{and}}\;\; \omega_{3}\) represent the short-run parameters of the model, \(\emptyset_{1} , \emptyset_{2} ,and \emptyset_{3}\) are long-run coefficients, while \(V_{it}\) is white noise error term and lastly, it represents country at a particular time period. In the ARDL model, the bounds test is applied to determine whether the variables are cointegrated or not.

This test is based on the joint significance of F -statistic and the χ 2 statistic of the Wald test. The null hypothesis of no cointegration among the variables under study is examined by testing the joint significance of the F -statistic of \(\omega_{1} , \omega_{2} ,\omega_{3}\) .

In case series variables are cointegrated, an error correction mechanism (ECM) can be developed as Eq. ( 2 ), to assess the short-run influence of international tourism and financial development on economic growth.

where ECT is the error correction term, and \(\varPhi\) is its coefficient which shows how fast the variables attain long-term equilibrium if there is any deviation in the short run. The error correction term further confirms the existence of a stable long-run relationship among the variables.

Panel granger causality test

To examine the direction of causality Dumitrescu and Hurlin [ 16 ] test is employed. Instead of pooled causality, Dumitrescu and Hurlin [ 16 ] proposed a causality based on the individual Wald statistic of Granger non-causality averaged across the cross section units. Dumitrescu and Hurlin [ 16 ] assert that traditional test allows for homogeneous analysis across all panel sets, thereby neglecting the specific causality across different units.

This approach allows heterogeneity in coefficients across cross section panels. The two statistics Wbar-statistics and Zbar-statistics provides standardized version of the statistics and is easier to compute. Wbar-statistic, takes an average of the test statistics, while the Zbar-statistic shows a standard (asymptotic) normal distribution.

They proposed an average Wald statistic that tests the null hypothesis of no causality in a panel subgroup against an alternative hypothesis of causality in at least one panel. Following equations will be used to check the direction of causality between the variables.

Estimation, results and Discussion

Descriptive statistics.

Table  1 presents descriptive statistics of variables selected for the period 1995–2015. The variable set includes GDP, FD and TR for all BRICS countries. Brazil tops the list with GDP per capita of 4.18, while India lagging behind all BRICS nations. In the recent economic survey by International Monetary Fund (IMF report 2016), India was ranked 126 for its per capita GDP. India’s GDP per capita went up to $7170 against all other BRICS countries which were placed in the above $10,000 bracket. China has the highest tourism receipts in comparison to other BRICS countries. China is a very popular country for foreign tourists, which ranks third after France and USA. In 2014, China invested $136.8 billion into its tourist infrastructure, a figure second only to the United States ($144.3 billion). Tourism, based on direct, indirect, and induced impact, accounted for near 10% in the GDP of China (WTTC report 2017).

Stationarity results

Primarily, we employed LLC and IPS unit root test to assess the integrated properties of the series. The results of IPS and PP tests are presented in Table  2 . Panel unit root test result evinces that FD and TR are stationary at level, while GDP per capita is integrated variable of order 1. The result exemplifies that GDP per capita, Tourism receipts and Financial Development are integrated at 1(0) and 1(1). Consequently, the panel ARDL approach to cointegration can be applied.

Cointegration test results

In view of the above results with a mixture of order integration, the panel ARDL approach to cointegration is the most appropriate technique to investigate whether there exists a long-run relationship among the variables [ 42 ]. Table  3 illustrates that the estimated value of F-statistics, which is higher than the lower and upper limit of the bound value, when InEG is used as a dependent variable. Hence, we reject the null hypothesis of no cointegration \(H_{0 } : \emptyset_{1} = \emptyset_{2} = \emptyset_{3} = 0\) of Eq. ( 1 ). Therefore, the result asserts that international tourism, financial development and economic growth are significantly cointegrated over the period (1995–2015).

Subsequently, the study investigates the long-run and short-run impact of international tourism and financial development on economic growth. Lag length is selected on the principle of minimum Bayesian information criterion (SBC) value, which is 2 in our case. The long-run coefficients of financial development and tourism receipts with respect to economic growth in Table  4 indicate that tourism growth and financial development exerts positive influence on economic growth in the long run. In other words, an increase in volume of tourism receipts per capita and financial depth spurs economic growth and both the coefficients are statistically significant in case of BRICS nations in the long run. The results are interpreted in detail as below:

The elasticity coefficient of economic growth with respect to tourism shows that 1% rise in international tourism receipts per capita would imply an estimated increase of almost 0.31% domestic real income in the long run, all else remaining the same. Thus, the earnings in the form of foreign exchange from international tourism affect growth performance of BRICS nations positively. This finding of our study is in consonance with the empirical results of Kreishan for Jordan [ 30 ], Balaguer and Cantavella-Jordá [ 3 ] for Spain and Ohlan [ 43 ] for India.

Further our finding lend support to the wide applicability of the new growth theory proposed by Balassa which states that export expansion promote growth performance of nations. Thus, validates TLGH coined by Balaguer and Cantavell-Jorda [ 3 ] which states that inbound tourism acts a long-run economic growth factor. The so called tourism-led growth hypothesis suggests that the development of a country’s tourism industry will eventually lead to higher economic growth and, by extension, further economic development via spillovers and other multiplier effects.

Likewise, financial development as expected is found to be positively associated with economic growth. The coefficient of financial development states that 1% improvement in financial development will push up economic growth by 0.22% in the long run, keeping all other variables constant. The empirical results are consistent with the finding of Hassan et al. [ 19 ] for a panel of South Asian countries. Well-regulated and properly functioning financial development enhances domestic production through savings, borrowings & investment activities and boosts economic growth. Further, it promotes economic growth by increasing efficiency [ 7 ]. Levine [ 33 ] believes that financial intermediaries enhance economic efficiency, and ultimately growth, by helping allocation of capital to its best use. Modern growth theory identifies two specific channels through which the financial sector might affect long-run growth; through its impact on capital accumulation and through its impact on the rate of technological progress. The sub-prime crisis which depressed the economic growth worldwide in 2007 further substantiates the growth-financial development nexus.

In the third and final step of the bounds testing procedure, we estimate short-run dynamics of variables by estimating an error correction model associated with long-run estimates. The empirical finding indicates that the coefficient of error correction term (ECT) with one period lag is negative as well as statistically significant. This finding further substantiates the earlier cointegration results between tourism, financial development and economic growth, and indicates the speed of adjustment from the short-run toward long-run equilibrium path. The coefficient of ECT reveals that the short-run divergences in economic growth from long-run equilibrium are adjusted by 43% every year following a short-run shock.

The short-run parameters in Table  5 demonstrates that tourism and financial development acts as an engine of economic growth in the short run as well. The coefficient of both tourism receipts per capita and financial development with one period lag is also found to be progressive and significant in the short run. These results highlight the role of earnings from international tourism and financial stability as an important driving force of economic growth in BRICS nations in the short run as well.

Further, a comparison between short-run and long-run elasticity coefficients evince that long-run responsiveness of economic growth with respect to tourism and financial development is higher than that of short run. It exemplifies that over time higher international tourism receipts and well-regulated financial system in BRICS nations give more boost to economic growth.

Analysis of causality

At this stage, we investigate the causality between tourism, financial development and economic growth presented in Table  6 . The result shows bi-directional causal relationship between tourism and economic growth, thereby validates ‘feedback hypothesis’ and consequently supported both the tourism-led growth hypothesis (TLGH) and its reciprocal, the economic-driven tourism growth hypothesis (EDTH). The bi-directional causality between inbound tourism and GDP, which directs the level of economic activity and tourism growth, mutually influences each other in that a high volume of tourism growth leads to a high level of economic development and reverse also holds true. These results replicate the findings of Banday and Ismail [ 5 ] in the context of BRICS countries, Yazdi et al. [ 27 ] for Iran and Kim et al. [ 28 ] for Taiwan. One of the channels through which tourism spurs economic growth is through the use of receipts earned in the form of foreign currency. Thus, growth in foreign earnings may allow the import of technologically advances goods that will favor economic growth and vice versa. Thus, results demonstrate that international tourism promotes growth and in turn economic expansion is necessary for tourism development in case of BRICS countries. With respect to policy context, this finding suggests that the BRICS nations should focus on economic policies to promote tourism as a potential source of economic growth which in turn will further promote tourism growth.

Similarly, in case of economic growth and financial development, the findings demonstrate the presence of bi-directional causality between two constructs. The findings validate thus both ‘demand following’ and supply leading’ hypothesis. The findings suggests that indeed financial development plays a crucial role in promoting economic activity and thus generating economic growth for these countries and reverse also holds. Our findings are in line with Pradhan [ 48 ] in case of BRICS countries and Hassan et al. [ 19 ] for low and middle-income countries. This suggests that finance development can be used as a policy variable to foster economic growth in the five BRICS countries and vice versa. The study emphasizes that the current economic policies should recognize the finance-growth nexus in BRICS in order to maintain sustainable economic development in the economy. The empirical results in this paper are in line with expectations, confirming that the emerging economies of the BRICS are benefiting from their finance sectors.

Finally, two-sided causal relationship is found between tourism receipts and financial development. That is, tourism might contribute to financial development and, in return, financial development may positively contribute to tourism. This means that financial depth and tourism in BRICS have a reinforcing interaction. The positive impact of tourism on financial development can be attributed to the fact that inflows of foreign exchange via international tourism not only increases income levels but also leads to rise in official reserves of central banks. This in turn enables central banks to adapt expansionary monetary policy. The positive contribution of financial sector to tourism is further characterized by supply leading hypothesis. Further, better financial and market conditions will attract tourism entrepreneurship, because firms will be able to use more capital instead of being forced to use leveraging [ 13 ]. Hence, any shocks in money supply could adversely affect tourism industry in these countries. Song and Lin [ 56 ] found that global financial crisis had a negative impact on both inbound and outbound tourism in Asia. This result is in consistent with Başarir and Çakir [ 6 ] for Turkey and four European countries.

Stability tests

In addition, to test the stability of parameters estimated and any structural break in the model CUSUM and CUSUMSQ tests are employed. Figs.  1 and 2 show blue line does not transcend red lines in both the tests, thus provides strong evidence that our estimated model is fit and valid policy implications can be drawn from the results.

Plot of CUSUM

Plot of CUSUMQ

Summary and concluding remarks

A rigorous study of the relationship between tourism and economic growth, through the tourism-led growth hypothesis (TLGH) perspective has remained a debatable issue in the economic growth literature. This study aims to empirically investigate the relationship between inbound tourism, financial development and economic growth in BRICS countries by utilizing the panel data over the period 1995–2015. The study employs the panel ARDL approach to cointegration and Dumitrescu-Hurlin panel Granger causality test to detect the direction of causation.

To the best of authors’ knowledge, this is the first study which explored the relationship between economic growth and tourism while considering the relative importance of financial development in the context of BRICS nations. The empirical results of ARDL model posits that in BRICS countries inbound tourism, financial development and economic growth are significantly cointegrated, i.e., variables have stable long-run relationship. This methodology has allowed obtaining elasticities of economic growth with respect to tourism and financial development both in the long run and short run. The result reveals that international tourism growth and financial development positively affects economic growth both in the long run and short run. The coefficient of tourism indicates that with a 1% rise in tourism receipts per capita, GDP per capita of BRICS economies will go up by 0.31% in the long run. This finding lends support to TLGH coined by Balaguer and Cantavell-Jorda [ 3 ] which states that inbound tourism acts a long-run economic growth factor. The so called tourism-led growth hypothesis suggests that the development of a country’s tourism industry will eventually lead to higher economic growth and, by extension, further economic development via spillovers and other multiplier effects.

Likewise, 1% improvement in financial development, on average, will increase economic growth in BRICS countries by 0.22% in the long run. The result seems logical as modern growth theory identifies two channels through which the financial sector might affect long-run growth: first, through its impact on capital accumulation and secondly, through its impact on the rate of technological progress. The sub-prime crisis which hit the economic growth Worldwide in 2007 further substantiates the growth-financial development nexus.

The negative and statistically significant coefficient of lagged error correction term (ECT) further substantiates the long-run equilibrium relationship among variables. The negative coefficient of ECT also shows the speed of adjustment toward long-run equilibrium is 43% per annum if there is any short-run deviation. The estimates of parameters are found to be stable by applying CUSUM and CUSUMQ for the time period under consideration. Therefore, inbound tourism earnings and financial institutions can be used as a channel to increase economic growth in BRICS economies.

Further, Granger causality test result indicates the bi-directional causation in all cases. Hence, the causal relationship between international tourism and economic growth is bi-directional. And, consequently this empirical finding lends support to both the tourism-led growth hypothesis (TLGH) and its reciprocal, the economic-driven tourism growth hypothesis (EDTH). This means that tourism is not only an engine for economic growth, but the economic outcome on itself can play an important role in providing growth potential to tourism sector.

The Granger causality findings provide useful information to governments to examine their economic policy, to adjust priorities regarding economic investment, and boost their economic growth with the given limited resources. Thus, it is suggested that more resources should be allocated to tourism industry and tourism-related industries if the tourism-led growth hypothesis holds true. On the other side, if economic-driven tourism growth is supported then more resources should be diverted to leading industries rather than the travel and tourism sector, and the tourism industry will in turn benefit from the resulting overall economic growth. And, when bi-directional causality is detected, a balanced allocation of economic resources for the travel and tourism sector and other industries is important and necessary. The policy implication is that resource allocation supporting both the tourism and tourism-related industries could benefit both tourism development and economic growth.

To sum up, the major finding of this study lends support to wide applicability of the tourism-led growth hypothesis in case of BRICS countries. Thus, in the Policy context, significant impact of tourism on BRICS economy rationalizes the need of encouraging tourism. Tourism can spur economic prosperity in these countries and for this reason; policymakers should give serious consideration toward encouraging tourism industry or inbound tourism. BRICS countries should focus more on tourism infrastructure, such as, convenient transportation, alluring destinations, suitable tax incentives, viable hostels and proper security arrangements to attract the potential tourists. Most of these countries are devoid of rich facilities and popular tourist incentives, to get promoted as important destination and in the long-run promotes economic growth. Further, they need a staunch support from all sections of authorities, non-government organizations (NGOs), and private and allied industries, in the endeavor to attain sustainable growth in tourism. Both state and non-state actors must recognize this growing industry and its positive implication on economy.

For future research, we suggest that researchers should consider the nonlinear factor in the dynamic relationship of tourism and economic growth in case of BRICS countries. Further one can go for comparative study to examine the TLGH in BRICS countries.

Availability of data and materials

Data used in the study can be provided by the corresponding author on request.

There are no fixed definitions of short, medium and long run and generally in macroeconomics, short run can be viewed as 1 to 2 or 3 years, medium up to 5 years and long run from 5 years to 20 or 25 years.

Abbreviations

autoregressive distributed lag model

Brazil, Russia, India, China and South-Africa

United Nations World Tourism Organization

World Travel & Tourism Council

gross domestic product

world development indicators

tourism-led growth hypothesis

export-led growth hypothesis

economic-driven tourism hypothesis

augmented Dickey–Fuller test

error correction model

error correction term

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Rasool, H., Maqbool, S. & Tarique, M. The relationship between tourism and economic growth among BRICS countries: a panel cointegration analysis. Futur Bus J 7 , 1 (2021). https://doi.org/10.1186/s43093-020-00048-3

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Overtourism Effects: Positive and Negative Impacts for Sustainable Development

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• Ivana Damnjanović 7  

Part of the book series: Encyclopedia of the UN Sustainable Development Goals ((ENUNSDG))

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Responsible tourism ; Tourism overcrowding ; Tourism-phobia ; Tourist-phobia

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Tourism today is paradoxically dominated by two opposite aspects: its sustainable character and overtourism. Since its creation by Skift in 2016 (Ali 2016 ), the term “overtourism” has been a buzzword in media and academic circles, although it may only be a new word for a problem discussed over the past three decades.

Overtourism is a complex and multifaceted phenomenon destructive to tourism resources and harmful to destination communities’ well-being through overcrowding and overuse (Center for Responsible Travel 2018 ; International Ecotourism Society 2019 ) as certain locations at times cannot withstand physical, ecological, social, economic, psychological, and/or political pressures of tourism (Peeters et al. 2018 ). Overtourism is predominantly a problem producing deteriorated quality of life of local communities (Responsible Tourism n.d. ; The International Ecotourism Society 2019 ; UNWTO 2018...

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Damnjanović, I. (2020). Overtourism Effects: Positive and Negative Impacts for Sustainable Development. In: Leal Filho, W., Azul, A.M., Brandli, L., Lange Salvia, A., Wall, T. (eds) Industry, Innovation and Infrastructure. Encyclopedia of the UN Sustainable Development Goals. Springer, Cham. https://doi.org/10.1007/978-3-319-71059-4_112-1

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Economic effects of tourism and its influencing factors

An overview focusing on the spending determinants of visitors, zusammenfassung.

Zahlreiche Studien belegen die ökonomische Bedeutung des Tourismus, die mit Hilfe verschiedener theoretischer Konzepte und Methodenansätze analysiert werden kann. Dieser Einführungsbeitrag in das Themenheft gibt einen Überblick über die unterschiedlichen Konzepte zu den wirtschaftlichen Wirkungen des Tourismus und arbeitet deren wichtigste Einflussfaktoren heraus. Häufig werden der räumliche Maßstab sowie die Kostenseite des Tourismus übersehen. Besonderes Augenmerk richtet der vorliegende Beitrag auf einen weiteren, entscheidenden Einflussfaktor ökonomischer Effekte, die Besucherausgaben. Die Rolle des Ausgabeverhaltens der Besucher wird unter Rückgriff auf einen umfassenden Literaturüberblick vorgestellt. Auf diese Weise ist es möglich, auf verallgemeinerbare und systematische Weise die wichtigsten Treiber des Ausgabeverhaltens von Besuchern zu identifizieren.

The economic relevance of tourism has been proven by numerous studies using various theoretical constructs and methodological approaches. This introduction to the special issue provides an overview of the different concepts of the economic effects of tourism and distinguishes their most relevant influencing factors. Often overlooked influences are the geographical scale and the cost side of tourism. A special focus of this paper lies on a further determinant of economic impact of utmost importance: visitor spending. The role of visitors’ expenditure behavior is comprehensively reviewed using an extensive literature base. Thus, we are able to identify the most important driving factors of visitor expenditure in tourism in a generalizable and systematic way.

1 Introduction

Tourism is often regarded (and used by regional developers and funding institutions) as an economic development path for structurally weak, peripheral areas, as a cure-all providing jobs and income, capital inflow and finally stopping outmigration by creating a positive socio-economic perspective for the future. However, more often than not these high hopes fall short and either the number of visitors or the resulting economic contribution or even both do not meet earlier expectations ( Vogt 2008 ; Blake et al. 2008 , p. 115; Lehmeier 2015 ; Mayer, Job 2016 ). In order to put these expectations on more realistic grounds, respectively to choose more suitable development strategies, a deeper understanding of the mechanisms is required: What influences the economic outcomes of tourism and can these determinants in turn be optimized by decision makers? However, before dealing with this question, it appears necessary to first clarify what the economic consequences of tourism activities actually are – as stakeholders tend to become confused by different concepts like economic contribution, impact or benefits, gross turnover, value added, or economic value (see section 2 )–, how they occur, how different measures vary and what costs have to be taken into account. In practice, these considerations should lead to a more realistic picture of tourism as a means of regional development and to better-reasoned strategies.

There are also additional reasons why the topic of the economic effects of tourism is very relevant for both academic research and practitioner-oriented consultancy: First, and in contrast to other sectors whose economic relevance is not contested, respectively broadly recognized (like car manufacturing in Germany for instance), tourism stakeholders need to underline the economic relevance of tourism in order to emphasize lobby efforts regarding financial resources, laws, planning, regulation, taxation and subsidies ( Hall, Page 2006 , p. 155; Stabler et al. 2010 , p. 199). There is a danger as Crompton ( 2006 , p. 67) puts it: “Most economic impact studies are commissioned to legitimize a political position rather than to search for economic truth”. Second, due to the complex structure of the different branches forming the tourism sector huge empirical efforts are required to measure the economic relevance of tourism for these sub-sectors and branches as well as for the national/regional economy in total. This complexity opened up the path for an own field of research dealing with economic analysis in tourism which has achieved considerable progress over the years. Third, studies evaluating the economic effects of tourism provide the only quantifiable results of tourism impact in monetary terms compared to image, infrastructure or competence effects of tourism where several other variables intervene ( Bieger 2001 ).

For these reasons, this special issue presents recent progress in the field of economic effects of tourism and its influencing factors by researchers from the German-speaking community. As an introduction to this special issue, this article provides an overview of the different measures of the economic importance of tourism and summarizes the influencing factors on the economic contribution of tourism using a self-developed framework ( Section 2 ). One of the most important drivers is the spending behavior of visitors. Thus, this paper offers a comprehensive review of studies dealing with the different determinants of visitor spending by systematizing the influences and drawing generalizable conclusions ( Section 3 ). Finally, this paper provides an outline of the special issue ( Section 4 ).

2 Economic effects of tourism and its influencing factors – an overview

2.1 definitions and differentiations.

The economic effects of tourism are often divided into tangible (quantitative or directly quantifiable in monetary values) and intangible (qualitative or not directly quantifiable) effects ( Woltering 2012 , p. 68; Metzler 2007 , p. 33). The positive tangible and intangible effects correspond to the benefits of tourism for societies and economies. Dwyer et al. ( 2010 , p. 222) point out that economic benefits of tourism equal neither the economic impact of tourism nor the economic contribution of tourism (see Figure 1 ). The notion of economic benefits of tourism require that a territorial entity or citizen has to be better off with tourism than without tourism. Thus, it is the net benefits that have to be analyzed, which encompass both the consideration of the costs of tourism development as well as the opportunity costs of tourism activities ( Dwyer et al. 2010 , p. 222) – defined as forgone income from alternative investment possibilities ( Job, Mayer 2012 ). This notion is related to the often neglected difference between real and distributive effects ( Hanusch 1994 , p. 8 f.; Schönbäck et al. 1997 , p. 4 f.): real effects lead to an overall improvement in the private households’ supply of goods and thus to a positive influence on the overall welfare level. In contrast, distributive effects sum up all monetary changes in the aftermath of a measure where the gains in one sector of the economy mirror the corresponding losses in another – the general welfare level remains constant ( Mayer 2013 , p. 93). Other negative economic effects of tourism for destinations are rising prices due to imported inflation and increasing demand ( Bull 1991 , p. 135) as well as potentially rising taxes because governments need to finance costly tourism infrastructure ( Stynes 1997 , p. 15).

Economic contribution, impact and benefit of tourism and influencing factors. Source: own draft, based on Ennew 2003 and Dwyer et al. 2010 , p. 213 ff.

“The economic contribution of tourism refers to tourism’s economic significance – to the contribution that tourism-related spending makes to … Gross Domestic (Regional) Product, household income, value added, foreign exchange earnings, employment” ( Dwyer et al. 2010 , p. 11, p. 213 f.). One common approach to quantify this economic contribution of tourism is Tourism Satellite Accounts (TSA) ( Spurr 2006 , Frechtling 2010 ). However, TSA as an accounting approach only measure direct effects ( Fig. 1 ), while indirect and induced effects have to be assessed using modeling approaches like input-output-(IO) models ( Ahlert 2003 , p. 19) or more recent advancements (see 2.3). This means that results of TSA and IO approaches are not directly comparable.

“While the economic contribution of tourism measures the size and overall significance of the industry within an economy, economic impact refers to the changes in the economic contribution resulting from specific events or activities that comprise ‘shocks‘ to the tourism system. This should not be confused with the contribution itself” ( Dwyer et al. 2010 , p. 216). These changes are brought about by new/non-regular tourism expenditure injected into a destination. Watson et al. (2007) provide two related definitions of economic impact underlining this understanding: “Economic impacts are the net changes in new economic activity associated with an industry, event, or policy in an existing regional economy” (p. 142). “Economic impact is the best estimation at what economic activity would likely be lost from the local economy if the event, industry, or policy were removed” (p. 143). In our case, this refers to tourism activities, such as a special event, a specific attraction or the shut-down of a previously popular accommodation. Thus, technically, the difference between the analysis of the economic contribution and the impact of tourism lies in the scope of the analysis (overall significance vs. the effect of “shocks”/”changes”) and not in the methods.

Central to both the evaluation of the economic contribution and the impact of tourism is the concept of leakages , occurring in the form of imported intermediate input from outside the country/region but also in the form of profit transfer to external headquarters or tax payments to a government. This means that not the complete share of tourism expenditure leads to income at the destination ( Hjerpe, Kim 2007 , p. 144 f.). On the national level, only the leakages to foreign countries are of interest while on a regional/ local level the share of income remaining in the survey area is crucial. This share is termed capture rate in English ( Stynes 1997 ) or “Wertschöpfungsquote“ in German ( Küpfer 2000 , p. 107 ff.; Job et al. 2009 , p. 33) and can be defined as “tourist expenditures minus leakage“ ( Hjerpe, Kim 2007 , p. 145). A similar concept is the Regional Purchase and Absorption Coefficient (RPC), defined as “the percentage of demand for a sector’s output from within the study area that is supplied by production within the study area” ( Watson et al. 2008 , p. 575). The higher the RPC, respectively the higher the capture rate, the higher the share of tourism income occurring in the survey area ( Hjerpe, Kim 2007 , p. 145; Watson et al. 2008 , p. 575). That means, from an economic geography perspective only the money actually remaining in the survey region is relevant.

As explained above, the economic contribution/impact of tourism refers to the actual expenditures of visitors. In economic valuation terminology, these expenditures represent the visitors’ revealed willingness to pay (WTP) and thus, a (quasi-)market price for recreation ( Moisey 2002 , p. 235 f.; Küpfer 2000 , p. 36). Based on this notion, one aspect is often overlooked, the value of the recreational experience , referring to the consumer surplus of visitors measured in their maximum WTP for visiting a destination/attraction minus their actual expenditure. In other words, the consumer surplus of visitation equals the difference between the visitors’ WTP and the actual expenditure. This is because visitors’ expenditures do not completely reveal their maximum WTP, which differs individually. Consequently, the economic impact only constitutes a subset of the tourism benefits and it does not equal the economic value of recreational use. This aspect is especially important where tourism attractions share characteristics of public goods, such as protected areas which do not charge entrance fees, etc. The recreational value can be estimated, for example, with the help of the travel cost method ( Carlsen 1997 ; Moisey 2002 ; Mayer, Job 2014 , p. 77).

2.2 Spatial aspects of the economic effects of tourism

The economic effects of tourism occur and are measurable on different spatial scales, from the global, continental, national to the regional and local level. Also the relevance of the effects vary along these scales. For instance, on the national level, the effects on the foreign exchange earnings are of great importance. Zooming in to the regional/ local level job creation and leakages become increasingly relevant ( Metzler 2007 , p. 33).

Not only the spatial scale should be taken into account but also the location where expenditures occur and which actors actually profit. Referring to Freyer ( 2011 , p. 41 ff.) we can distinguish between (a) the source area of tourists, (b) the travel area and (c) the destination. Each area has a differing mix of expenditure categories and empirical problems. Ad (a): in the source area, travelers seek information, book their trip and buy equipment. However, it is often problematic to assign expenditures for equipment to a specific trip or holiday. Ad (b): while on the trip, travelers spend money for gas, food, road toll, accommodation for stopovers, etc. Two problems occur: First, most transport expenditures are booked and paid for in advance in the source area and the area crossed by airplanes, trains or ships does not gain any benefits. Second, if one wants to assign the travel expenses to a specific attraction the multiple-trip bias has to be considered (round trips) ( Freeman 2003 , p. 421 f.). Ad (c): at the destination, tourists pay for accommodation, gastronomy, groceries, activities, souvenirs, services, etc. Thus, for a regional economic analysis (for instance of events or specific attractions), the spatial limitation, respectively the size of the destination are crucial influencing factors (see below) “because a good proportion of total spending by spectators might not [have] been incurred within the community” ( Gelan 2003 , p. 411). Furthermore, for these evaluations of attractions or events mostly only the expenditure at the destination is considered while expenditure on the trip or in the source area is disregarded. In general, the economic impact of an event/ attraction is likely inversely related to the distance from its location in space ( Gelan 2003 ). Additional insights into the spatial aspects of the economic effects of tourism can be found in several, mostly case study contributions (e.g. Connell, Page 2005 ; Daniels 2007 ; He et al. 2008 ) which cannot be presented here in detail due to space constraints. However, there is to date no comprehensive review of these works and it would be worth compiling.

2.3 Factors influencing economic effects of tourism

This sub-section presents the factors influencing the economic effects of tourism and discusses the input variables for its analysis. Loomis, Caughlan ( 2006 , p. 33 ff.) sum up the basic requirements for any analysis of the economic contribution/impact of tourism: (a) number of visitor days; (b) spending amounts per visitor; (c) types of visitors and trip purposes; and (d) an economic model to calculate multiplier effects. In addition, there is a moderating effect of the spatial limitation of the survey area.

Ad (a): The number of visitor days is often confused with the number of visitors which could be identical in some cases but most often both measures differ. For overnight tourism also the length of stay, the number of visits to specific attractions or the frequency of an activity have to be taken into account. In this issue, Arnberger et al. (2016) discuss the methods of visitor counting in detail.

Considering visitation it is debatable whether economic impacts of tourism should be used on a national scale, because those of domestic tourism represent distributive effects only ( Küpfer 2000 , p. 68 f.). These visitors would have spent their vacation in their home country anyway or would have visited another destination there instead. Only incoming tourists provide additional input for the national economy ( Schönbäck et al. 1997 , p. 191; Baaske et al. 1998 , p. 159 f.). However, one might argue that a domestic trip can avoid a trip abroad which would lead to leakage from the national economy ( Mayer, Job 2014 , p. 79).

Similarly, it is contested whether local residents in the survey areas should be included in the regional economic assessments. Some maintain that locals should be excluded as their expenditures are considered a re-circulation of preexisting income in the region ( Dwyer et al. 2004 , p. 313 f.; Loomis, Caughlan 2006 ; Crompton et al. 2001 , p. 81). Conversely others argue that ignoring locals’ expenditures will lead to an underestimate of total impacts ( Johnson, Moore 1993 , p. 287). Locals could also spend their money outside their home region again leading to leakages ( Ryan 1998 , p. 345).

Ad (b) Expenditure : Stynes, White (2006) sum up the most important dos and don’ts when it comes to analyzing visitors’ spending behavior, while Frechtling (2006) reviews several methods and models used to estimate visitor expenditures. The third section of this article deals with the influences on expenditure patterns in detail. In addition, Butzmann (2016) analyzes the expenditures of nature tourists in his contribution to this issue.

Ad (c) Trip purpose : In order not to overestimate the economic contribution of specific attractions/ activities the trip purpose has to be analyzed. It is decisive that only those expenditures are considered which are spent in addition to the money spent anyway at the destination as the spenders would have traveled there even if the attraction in question did not exist ( Dixon, Sherman 1990 , p. 155 ff.; Küpfer 2000 ; Job et al. 2009 ; Loomis, Caughlan 2006 , p. 33 ff.).

Ad (d) Multipliers : Economic models are inevitably necessary to estimate the indirect and induced economic effects of tourism and are often regarded as the most complex part of the evaluation process. The evolution of methodologies started with comparatively simple multipliers ( Archer 1977 ) and continued with superior input-output models (IO) ( Fletcher 1989 ). The latter, however, exhibit methodological shortcomings owing to restrictive assumptions like the “free, unrestricted flow of resources to [...] the economy. [...] As a result, it [the IO model] does not capture the feedback effects, which typically work in opposite directions to the initial change“ ( Dwyer et al. 2004 , p. 307; Armstrong, Taylor 2000 , p. 56 ff.). As important improvements to the IO social accounting matrices (SAM) ( Wagner 1997 ) and computable general equilibrium models (CGE) [1] ( Dwyer et al. 2004 ) were proposed, which are able to incorporate resource restrictions and feedback effects ( Zhang et al. 2007 ). The CGE are most likely the most advanced group of multiplier models overcoming many of the overestimation effects of IO-models ( Blake 2005 ; Song et al. 2012 ), even though they still have their drawbacks. These include some restrictive assumptions like constant returns to scale in production functions and perfect markets ( Croes, Severt 2007 ), high input data quality requirements and related costs or the not very vivid presentation of results ( Pfähler 2001 ). Thus, when comparing CGE models to conventional IO Klijs et al. (2012) conclude that CGE models are inferior in terms of transparency (the predictability of results), efficiency (data, time and cost) and comparability (standardization of model structure, complexity and assumptions). In addition, the analysis of past data is beyond the scope of CGE models because they “simulate what will happen in the economy as a consequence of external shocks, but do not state what has already happened” ( Ivanov, Webster 2007 , p. 380). Further (dis)advantages of the modeling approaches are discussed in the academic literature ( West 1995 , Dwyer et al. 2010 , Chap. 7-9, Pratt 2015 , p. 151).

The magnitude of multiplier effects is decisively influenced by three factors ( Archer 1977 : 29 ff., Archer, Fletcher 1996 : p. 58 ff., Wall 1997 , p. 447; Hall, Page 2006 , p. 155): (1) The size of the survey area to which the multiplier refers because the possibilities for economic autarky largely depend on this size. The number of potential spending rounds is also influenced. The larger the survey area, the larger the multipliers and the lower the leakages. (2) The level of economic development of a region: “The more that the inputs of enterprises can be acquired locally, the smaller will be the leakage and the larger will be the multiplier“ ( Wall 1997 , p. 447). However, there is no automatism for higher multipliers due to complex interregional value chains nowadays. (3) The expenditure structure: the higher the locally produced share of goods/ services, the higher also the resulting direct and indirect effects.

The sensitivity of the economic contribution of tourism to changes in these influencing factors is seldom analyzed, one important exception being Woltering ( 2012 , p. 249 ff.). Finally, all estimation approaches necessarily rely on reliable empirical data input about the number of visitors and their expenditures. Without those appropriate measures, even the most detailed, theoretically sound economic model would provide misleading results ( Tyrrell et al. 2001 , p. 94). Besides, Crompton et al. ( 2001 , p. 80 ff.) stress that “economic impact analysis is an inexact process, and output numbers should be regarded as a ‘best guess’ rather than as being inviolably accurate”. This quotation refers to the inherent problems of all economic valuation approaches, as does the lack of comparability of TSA and IO results: estimations of the economic effects of tourism should not be regarded as incontestable, because they are open to interpretation and misuse ( Crompton 2006 ). Consequently, a critical assessment of different economic valuation studies should take into account who is estimating which values using which approaches and models based on which assumptions and data input funded by whom. As issues of power and attempts to influence results can never be completely excluded it would be a task for a critical (economic) geography of tourism in the sense of Britton (1991) to deal with these related questions.

The following section focuses on one of the four basic requirements for any economic evaluation of tourism, variable expenditure. Along with visitor days spending behavior is the most influential driver of the economic effects of tourism and, thus, warrants special attention. Section 4 makes clear how the other influencing factors on the economic importance of tourism are addressed in this special issue.

3 Tourist expenditure: an overview of spending drivers

3.1 general issues.

The research history of tourists’ spending patterns is comparatively short. Wang and Davidson (2010) highlight that apart from a study undertaken in the 1970s ( Mak et al. 1977a , b ) the research community started focusing on the issue only in the 1990s. Most of these studies have been case studies ( Xiao, Smith 2006 ), so conclusions referring to a larger population cannot be drawn ( Gerring 2007 ). For a validation of such findings they can be triangulated by comparing results with those from case studies at different sites ( Decrop 1999 ). Brida, Scuderi (2012) , however, point out the problems of generalizing such empirical findings, as different models, dependent variables and regressors using inter alia different scales of measure are employed. Mak et al. (1977a) showed, furthermore, that different spending measurement methods (spending diaries vs. recall after their return home) lead to different results. Considering the caveats mentioned this chapter aims at outlining the most significant findings on expenditure patterns using a narrative review approach. Sampling of studies was based on a systematic research in the web of knowledge® provided by Thompson Reuters; search terms were “tourism* expenditure* determinants”, “tourism* expenditure behavior”, “tourism* expenditure”, combined with tourism forms (nature tourism, mountain tourism) in addition. We have included only destination-based studies in the analysis and omitted studies comprising expenditure in the areas of origin. Database entries up to December 2015 have been taken into account. 50 papers fulfilled the criteria and form the basis for the following evaluation.

To obtain a quick overview, it helps to systematize the predictor variables analyzed. Following Pouta et al. (2006) and Woltering (2007) , we systematize drivers of expenditure of the empirical studies into tourist-, travel- and destination-based variables analyzed. Omitted are macroeconomic variables such as the GDP or the price level in the countries of origin, destination and competing destinations (analyzed e.g. by Saayman, Saayman 2015 ); they are mainly relevant for explaining spending behavior of international tourists in different countries.

Tables 1 - 3 summarize the findings from previous studies regarding the statistical significance and the signs of the independent variables. The statistical methods used range from variance analyses to regression methods (OLS or quantile regression) or more advanced econometric techniques (double-hurdle, Heckit and similar methods). Moreover, the expenditure variable varies and takes the level or the log form ( Thrane 2014 ). Some studies apply several statistical models in the same paper to compare results (being usually but not in all cases quite similar); only the first mentioned model is included here. Studies differ, furthermore, regarding how they define spending (average per person or group, respectively per day or journey). Moreover, few studies not only measure spending at the destination itself but also in the country or region of origin (e.g. Alegre et al. 2011 ). In these cases, only expenditure at the destinations or total spending has been considered. Further studies do not use a single expenditure variable but differentiate spending in categories such as accommodation or food and beverages (e.g. Marcussen 2011 , Brida et al. 2013 ). If these studies include a total expenditure indicator only this variable is analyzed, if not, the variables considered are indicated.

Tourist-based drivers of visitor expenditure

Significant results (p < 0.05):+ = positive  - = negative  o = neutral

s. = significant categorical variable; n.s. = tested, but results not significant; p. (= partly)/m. (= mostly) s.: categorical variable with some but not all significant feature characteristics / … with significant feature characteristics except for one.

Significant results (p < 0.05): + = positive  - = negative  o = neutral; n.s. = tested, but results not significant; s. = significant categorical variable; p. (= partly)/m. (= mostly) s.: categorical variable with some but not all (not) significant feature characteristics / … with significant feature characteristics except for one.

d.v.: dependent variable; (1) group spending per stay; (1a) group spending per day; (2) individual spending per stay; (2a) individual spending per day; (3) not specified, probably group spending per day; (4) total travel spending per stay; (5) spending per day; (6) overnight; (7) dayvisitor

Destination-based drivers of visitor expenditure

Significant results (p < 0.05): + = positive - = negative o = neutral

s. = significant, categorical variable; n.s. = tested, but results not significant; p. (= partly) s. = categorical variable with some but not all significant feature

3.2 Tourist-based variables

Tourist-based variables relate to the travelers themselves and are based upon variables identified as decisive for consumption decisions in general ( Meffert 2000 ). They include socio-demographic variables such as age, gender, marital status, income, education and profession, and geographical variables reflecting the spatial and economic structure in the visitors’ region of origin ( Table 1 ). In many studies, age has been tested as a predictor variable with ambiguous results: in 11 out of 31 studies age was not found to influence spending in a statistically significant way, in seven studies spending depends positively on the age of visitors and four times a negative relation was found. The findings of Aguilo Perez, Juaneda Sampol (2000) , Pouta et al. (2006) , Thrane, Farstad (2011) or García-Sánchez et al. (2013) suggest that age might not be related to expenditure in a linear but curvilinear way. That means low spending is found in the youngest and the oldest age segments whereas high spenders are middle aged. Gender and marital status do not seem to predict spending in general ( Lawson 1994 ; Wang et al. 2006 ); this is reflected in the large share of non-significant results in the studies reviewed even though, for example, Mak et al. (1977b) found the latter variable to be significant. In contrast, income can generally be regarded as a reliable predictor ( Fish, Waggle 1996 ): consistent with economic theory the relationship between income level and tourism expenditure is positive in 21 out of 29 studies with Agarwal and Yochum (1999) , Downward, Lumsdon (2003) , Fredman (2008) as well as Thrane, Farstad (2011) reporting inelastic relations. This means with growing income, tourism expenditure increases as well but at a lower rate. Profession and level of education are only significant occasionally (possibly due to multicollinearities with the income variable), whereas the country of origin tends to be a good indicator of spending levels. The type of residential location does not seem to influence travel expenditure.

3.3 Travel-based variables

Table 2 summarizes the results of visitor expenditure studies regarding observable characteristics of the journey. The sign of group size seems to vary ambiguously: 10 out of 29 studies report positive signs, 14 studies negative signs, and two different signs according to the dependent variable ( Kozak et al. 2008 ; Marcussen 2011 ). The most straightforward explanation for the varying sign is the dependent variable. With group spending, expenditure tends to rise the larger the group, whereas with individual spending expenditure tends to fall due to cost-sharing.

The effect of travel length depends on the exact specification of the dependent variable as well. It is usually positive when total travel expenditure is analyzed. The influence of length of stay tends to be negative with per day expenditure as a dependent variable. Non-linear effects can be observed: for longer trips the generally positive relationship between length of stay and total expenditure becomes weaker, a diminishing positive effect was observed, theoretically explained by economies of scale ( Thrane, Farstad 2011 ; Aguilo Perez, Juaneda Sampol 2000 ; Roehl, Fesenmaier 1995 ).

The variable visitor type (vacationists vs. day trippers) has a significant influence as day trippers spend significantly less than overnight visitors due to lack of accommodation expenditure. The type of accommodation is usually a significant variable as well. As expected, commercial accommodation (i.e. hotels) is generally economically most relevant, followed by rented apartments, with campgrounds and friends/ relatives generating the lowest expenditures (e.g. Agarwal, Yochum 1999 ; Fredman 2008 ; García-Sánchez et al. 2013 ). Interestingly, Kastenholz (2007) found camping tourists to be the heaviest spenders in nature tourism destinations in Portugal, and Kozak et al. (2008) reported a negative relationship between hotel accommodation and spending in Turkey, which might be explained by the sun-and-sand character of the destination. Individually organized travelers tend to spend more than package tourists in the destination region. In visitor surveys, however, it remains unclear which part of the package tour expenses paid in the region of origin flows to the destination. Only eight studies measured the influence of the means of transportation on visitor spending. In most cases the influence on expenditure levels is significant. Following Downward, Lumsdon (2004) and Svensson et al. (2011) visitors traveling by car spent more than those using public transport, whereas Fredman (2008) , Marcussen (2011) , Thrane, Farstad (2011) , Abbruzzo et al. (2014) report higher expenditure by visitors using planes and trains. The number of visits to a destination usually reflects loyalty to a destination as well as familiarity with the place and insider knowledge, with more visits possibly associated with less spending ( Alegre, Juaneda Sampol 2006 ). However, eight of the 13 studies with significant results for this predictor found that repeaters spent more. The existence of potential nonlinear effects has not been controlled for, yet. The variable travel motives often produces significant results as motives tend to be very heterogeneous and can be both push and pull motives.

Activities are not a straightforward predictor of visitor spending because, as with motives, results depend on the heterogeneity of activities sampled. In general, there seems to be a tendency for more infrastructure-related activities to influence higher expenditure. Kozak et al. (2008) find, for example, that those tourists who rate the standard of nightlife and entertainment as very important are heavy spenders.

3.4 Destination-based variables

Table 3 sums up the impact of destination-based factors on spending. According to Mak et al. (1977a) , Leones et al. (1998) , Lee (2001) and Pouta et al. (2006) distance to the destination and visitors’ expenditure are positively related. The perception of prices at the destination affects spending as well. Aguilo Perez, Juaneda Sampol (2000) found that visitors, who regard the destination as expensive tend to spend more. Abbruzzo et al. (2014) focused on satisfaction with the price level and figured out that those tourists spent more who had a positive opinion of the price level but the opposite was also true. Satisfaction with the holiday had a positive effect on visitor spending ( Aguilo Perez, Juaneda Sampol 2000 ; Craggs, Schofield 2009 ; Serra et al. 2015 ). The characteristics of a destination or site are only testable if the sample covers different destinations/sites at a destination. Lee (2001) and Díaz-Pérez et al. (2005) analyzed the influence of various types of boating trips and accommodation on different Canary Islands and obtained some significant results. Abbruzzo et al. (2014) show that visitors at famous destinations in Uruguay spent significantly more than tourists who stayed in other places. Brida et al. (2013) demonstrated that different spending levels of visitors for food and beverages were related to different Christmas markets in Northern Italy. Territorial effects of tourist spending were also found by Svensson et al. (2011) for Andalusia: visitors in cities caused larger turnover than those in rural areas and both types spent more than tourists at coastal destinations. Likewise Thrane, Farstad (2011) found that depending on the urbanity, respectively location size and remoteness the expenditures of Norwegian domestic tourists vary significantly with visitors in rural and mountain/wilderness settings spending the least. Pouta et al. (2006) tested the influence of the supply of outdoor services and recreation opportunities on expenditure at a destination level. Downhill skiing possibilities are associated with a probability for higher expenditure, while berry and mushroom picking opportunities are related to a low spending level. These findings show, that, as expected the roles of outdoor activities and their supply are strongly connected.

Finally, the seasonal effect is unclear. In two studies low-season tourists spent more than high-season visitors, but in other studies the opposite was observed. Three studies did not find any statistically significant results.

3.5 Discussion and implications

To sum up, the most significant tourist-based determinant of tourism spending is income no matter how operationalized. This finding fits well in general microeconomic theory that postulates the importance of income for demand. Profession and education did not achieve significant results in many cases. A better proxy for income seems to be the country of origin. Gender, marital status, and the type of residential location are not drivers of tourism expenditure according to most of the studies. This shows that these variables influence neither spending capacities nor preferences. Age, in contrast, determines spending in some studies, but not, if included as a linear metric variable. This might be due to a link between age and income with middle aged groups earning and spending the most, but this might also be caused by a correlation of age groups with specific interests and activities, which differ in price. Future analyses could therefore limit tourist-based variables to income and age. However, although economic factors are decisive as they permit people to travel, they cannot fully explain tourist expenditure. Several travel-based variables increase the explanatory power of spending models. Group size obviously influences the amount of spending in a significant way. Apparently, scale effects occur, leading to cost savings. Economies of scale also come into effect with length of stay of tourists. Nevertheless, for destination organizations it might be more efficient, from a cost-benefit perspective, to convince tourists to stay longer (as difficult as that may be) than to make great efforts to attract more visitors. Comparing vacationists and day-trippers, the dominant role of accommodation as a spending variable becomes evident. Overnight tourists spend significantly more. Higher sales are generated with specific types of accommodation, in detail dependent on destinations. Concerning the impact of the trip organization it might be interesting from a regional economic perspective to take a closer look at the share of all-inclusive prices paid by package tourists that actually becomes effective at destinations. Due to inconsistent results concerning the transportation mode, conclusions cannot be drawn. It could be assumed that specific means of transportation are related to the place of origin of tourists and the distance to destination. So, transportation mode might be a proxy for the country of origin, the GDP and the income. The influence of means of transportation on spending levels would thus depend on the destination.

Further investigation is needed for the relation between the number of visits and spending levels as results are quite contradictory. Moreover, the travel motives and activities examined are very heterogeneous so that clear results are missing, although infrastructure related activities seem to have a positive influence. Therefore, it might be interesting to compare the impact of specific travel activities on expenditure at specific types of destinations (such as monumental cities, mountains, sun and sea).

We suggest that the incorporation of variables related to supply and characteristics of destinations would help to further understand spending behavior as demand usually also depends on attributes of supply and satisfaction with it. Especially regarding the characteristics of destinations the findings show a significant impact on the spending level. Further research is needed to verify these results. Particular attention should be paid to differentiate destination characteristics if implications for destination management are to be provided. The same holds true for the influence of season on expenditure as existing results do not provide a clear picture. According to microeconomic theory, high expenditure levels would be expected for high seasons (when demand is high for scarce resources) but some findings contradict this assumption. Future studies should thus analyze the impact of season together with travel motives, activities and destination characteristics.

In conclusion, this review showed that several travel- and destination-based variables are under-researched and future studies should devote special attention to these factors. Further practical implications are very difficult to make at this aggregate level without referring to specific destinations (cp. Mayer, Vogt 2016 ).

4 Outline of the special issue

The remaining articles of this special issue either center on the factors influencing the economic effects of tourism or deal with the actual economic outcome of tourism activities.

Arnberger et al. (2016) focus on visitor monitoring methods and exemplify their best practice approaches for the case of the frequentation of three shortdistance recreation areas in and near Vienna, Austria (among others, the Donau-Auen National Park). These detailed analyses of visitation intensities and patterns showcase the essential base for reliable economic contribution/ impact assessments.

The next influencing factor in the logical sense of an economic impact analysis is the expenditure behavior of visitors. While the introductory article concentrates on the general determinants of visitor spending (see Chap. 3) Butzmann (2016) conducts an in-depth analysis of the visitor expenditures in Berchtesgaden National Park situated in the German Alps. He uses two different visitor samples of park visitors to work out an expenditure-, attitude- and behavior-based visitor segmentation employing statistical latent class procedures. This segmentation aims at closing the often bemoaned sustainability-profitability gap in nature tourism by trying to identify economically as well as ecologically favorable visitor groups.

The next contribution by Stettler et al. (2016) demonstrates how economic impact analyses could be practically applied to assess the profitability of several sport events of varying scope, prominence and impact (among others the European Football Championships 2008, jointly hosted by Switzerland and Austria) from a societal perspective: Is it worth investing public funds in these events? Their article also clearly shows the limitations of this approach as the economic impact of event-motivated tourism only constitutes parts of the benefits of these events while the cost side is mostly disregarded.

Finally, Küblböck and Standar (2016) deal with one of the major economic benefits of tourism, the tourism labor market. They analyze the effects and reasons for shortages of a skilled labor force in the hospitality sector in Germany, exemplified with detailed empirical fieldwork in the region Braunschweig-Wolfsburg. In addition, they discuss potential strategies for coping with this apparent problem which could reduce the economic benefits of tourism in the near future.

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TOURISM GRADE 12 NOTES - ECONOMICS STUDY GUIDES

• Key concepts
• Definition of tourism
• The purposes (types) of tourism
• Measuring tourism
• Reasons for growth
• The effects of tourism
• The benefits of tourism
• A South African tourism profile
• Tourism policy suggestions

Tourism is travel for the purpose of leisure, recreation or business. Local tourists travel to different places in their own country. Inbound tourists come to South Africa from other countries. South African tourists who travel overseas are known as outbound tourists. South Africa is a popular tourist destination because of its beauty, wildlife, good weather and its interesting political history.

13.1 Key concepts

These definitions will help you understand the meaning of key Economics concepts that are used in this study guide. Understand these concepts well. Use mobile notes to help you remember them.

Use mobile notes to help you learn these key concepts. Learn more about mobile notes on page xiv in the introduction.

13.2 Definition of tourism

Tourists travel to foreign countries for holidays, business, conferences and to discover more about other countries. Tourism allows people to experience the world. Tourism can be defined as activities of people travelling to places outside their usual environment for less than one year for business, leisure or other purposes without any remuneration. An activity is seen as tourism if it fits in with the following criteria:

• There is a purpose for the visit or activity.
• There is no remuneration (money) earned in the place visited.
• A minimum length of stay is one night.
• A maximum length of stay is one year.
• There is a travelling distance of more than 160 km from the tourist’s home environment.

13.3 The purposes (types) of tourism

• Leisure and recreation: Tourists come to South Africa on holiday, to play sport, to visit friends, and to see the tourist attractions
• Cultural tourism: Tourists come to visit museums and art galleries, e.g. Robben Island and the Apartheid Museum.
• Ecotourism: Tourists visit undisturbed natural areas, e.g. the Richtersveld Cultural and Botanical Landscape, the Cape Floral Region Protected Areas and the Kruger National Park.
• Business and professional: Tourists visit for business meetings and conferences.
• Other: For studies, or medical reasons.

13.4 Measuring tourism

Tourism consists of different activities that should comply with the following:

• There should be a purpose for the visit e.g. camping, business or studies.
• No remuneration should be earned at the tourist destination.
• A minimum length of stay should be one night.
• The maximum length of stay should not exceed one year.
• The travelling distance should exceed 160 km from a person’s residence.

13.5 Reasons for growth

The rapid growth in the tourism industry has resulted in a steady change in the standard of living as well as people’s lifestyles. Tourism is much more evident in the developed than developing countries, although tourism is increasing faster in the developing countries. Local tourism is booming since South Africa is becoming more attractive as tourist destination. Reasons for the growth of the tourism industry are:

• Increased disposable income.
• Less working hours so more time to travel.
• An awareness of leisure and recreation.
• Improved transport, communication and accommodation facilities.
• Increased advertising and promotion.
• Enjoying the benefits of holidays and travel.
• Easily obtainable foreign exchange.
• International: tourism is much more evident in the developed than developing world, but tourism is growing faster in developing countries, e.g. 4.6% growth from 2010 to 2011.
• Foreign arrivals: foreign tourists who visit the country as their destination.
• Those who are stopping over, are called transit tourists or sameday travellers.
• Foreign tourists: come for the experience – visit friends, game farms, enjoy the different cultures, heritage spots or sports activities and events.
• Domestic tourism: South Africans are free to travel locally (domestic tourists) or abroad (outbound tourists). Outbound tourists have the same effect on the Balance of Payments as imports.

13.6 The effects of tourism

Tourism has a significant effect on the economy and the country as a whole. The following 6 areas are greatly affected by tourism: 13.6.1 Employment

• Tourism employs 7% of South Africa’s workforce (approximately 1,12 million people).
• Tourism is the largest provider of jobs because it:
• Is labour intensive.
• Employs many different kinds of skills, e.g. tourist guides, hotel staff.
• Provides immediate employment.
• Provides entrepreneurial opportunities.
• Tourism is the largest earner of foreign exchange because:
• Foreign tourists pay for services in foreign exchange.
• Foreign tourists usually spend more than local tourists.

Use the acronym PIGEEE to help you remember the 6 effects of tourism: P – Poverty I – Infrastructure G – GDP E – Employment E – Environment E – Externalities

13.6.2 Gross domestic product (GDP)

• Tourism has the biggest impact on the services industry.
• Indirect contribution: Tourism is a service-based industry. It is responsible for 65% of the GDP in developed economies and 40% of the GDP in developing countries.
• Direct contribution: Tourism contributes 7,9 % of GDP in South Africa (compared to 12% worldwide).

13.6.3 Poverty Poverty is most evident in rural areas due to a lack of job opportunities. Tourism can alleviate (ease) poverty in the following ways:

• Tourism is a fast and effective mechanism for distributing resources to rural areas to develop them as tourist sites.
• Many prime tourist attractions are located in rural areas.
• Tourist developments in rural areas increase the number of available jobs in areas where there aren’t many jobs.
• Tourism promotes a balanced and sustainable form of development. People are able to earn a living in their home areas, resulting in a reduction in urbanisation and a more balanced population distribution.

13.6.4 Externalities Externalities are costs and benefits that result from a specific activity. Tourism results in both: Positive externalities:

• Tourism attracts large amounts of revenue.
• Tourism leads to an improvement in infrastructure development.
• Tourism can stimulate employment indirectly.
• Tourism can help conserve cultural and natural assets and alleviate poverty, but needs to be carefully planned.

Negative externalities:

• Tourism can cause environmental damage if not managed correctly.
• Tourism can result in a lot of waste and damage to sensitive tourist sites.
• The infrastructure at tourist sites can come under pressure to cater for increased tourist numbers.
• Tourism can lead to increased prices for locals.

13.6.5 The environment Tourism can create environmental stress. It can result in:

• Permanent restructuring of the landscape, e.g. construction work on highways.
• Additional waste products, e.g. biological (sewage) and non-biological (litter) waste.
• Direct environmental stress, e.g. the loss of wildlife species due to safari hunting.
• Effects on population dynamics, e.g. migration and changes in population density in response to the needs of tourist sites.

13.6.6 Investment Tourist destinations require adequate physical (hotel rooms), economic (ATMs) and basic (water and electricity) services infrastructure. This includes:

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• Transport infrastructure, e.g. improved roads are needed to access tourist sites.
• Communication infrastructure, e.g. hotels need telephone lines to take bookings at tourist sites.
• Energy infrastructure, e.g. tourists need electricity at tourist sites.
• Basic services, e.g. clean water and refuse removal.

13.7 The benefits of tourism

South Africa benefits from tourism through the growth in the gross domestic product (GDP), employment and infrastructure development. An additional benefit is that spending by foreign tourists results in an increase in foreign exchange earnings, which has a similar impact on the GDP to an increase in exports. 13.7.1 Households Tourism benefits a household’s prosperity (wealth) in three ways:

• More people earn salaries and wages because of additional job opportunities.
• Infrastructure built for tourists is available both for tourists and local people’s use.
• Skills: A variety of skills is required in the tourism industry.

13.7.2 Businesses Tourism has many benefits for the business sector:

• The economic and basic services infrastructure required for tourism is provided by the public sector.
• Tourism needs superstructure, which consists of businesses that provide accommodation, transport, built attractions, retailing and recreation services.
• Superstructure is normally supplied by the private sector, and the building and running of the superstructure make profits.
• Public and private sector partnerships (PPPs) are used to develop tourist destinations.
• Employment opportunities in entertainment, laundry and transportation.
• Business opportunities in car rental, arts, craft and curio sales.

13.7.3 Government The main benefit to government is in the levying (charging) of taxes. This has two purposes:

• To recover external costs: To compensate the host community for providing infrastructure.
• To raise revenue: Tourists are seen as part of the overall tax base (e.g. airport departure taxes and hotel tourism levies increase the amount of taxes collected).

Use this mnemonic to help you remember the 4 benefits of tourism: H – Households – HOT B – Businesses – BEACHES I – Infrastructure – IN G – Government – GEORGE

13.7.4 Infrastructure development South Africa benefits from tourism because all infrastructure built to support tourism becomes an asset to the country. As a result:

• Residents and visitors enjoy adequate and well-maintained physical and basic services infrastructure.
• The Department of Transport prioritises economic infrastructure. Spatial Development Initiatives and economic corridors focus on tourism, and public and private sector partnerships (PPPs) are used for the development of infrastructure.
• Tourists require social infrastructure – ambulances, medical clinics, police protection services and information services – that becomes a national asset.

13.8 A South African tourism profile

• Aim with visits: most foreign tourists visit South Africa for vacation (94.3%) and business (2%). The major attractions are the coast, wildlife and scenery.
• Local destinations: Destinations link all aspects of tourism – demand, supply, transport, accommodation and marketing. The success of tourism is determined by the variety of destinations as well as the geographical distribution of tourist destinations.
• Local tourists: There has been a steady growth in the number of South Africans travelling domestically.
• Tourists want to understand the indigenous (local) culture, history and environment.
• Tourists seek authentic (genuine) and unique destinations. They want to see how local people live and work.
• The Khoi San are among the world’s oldest people, and their way of life is of interest to many foreign tourists.

World heritage sites:

• Mapungubwe (Limpopo)
• Vredefort Dome (Free State and North West)
• Sterkfontein caves
• Robben Island
• Richtersveld Cultural and Botanical Landscape

Environmental World Heritage Sites:

• iSimangiliso Wetland Park (ecosystems)
• Cape Fynbos Region
• uKhahlamba Drakensberg Park

13.9 Tourism policy suggestions

The Department of Tourism leads and directs tourism policy. The starting point for policy on tourism is the White Paper on Tourism. Tourism policy is also supported and directed by the Tourism Forum, which is an advisory body to the Minister of Tourism. Some tourism policy initiatives include the following:

This is an easy topic. Memorise at least 4 facts under each heading.

13.9.1 Marketing SA Tourism was created to promote tourism internationally and nationally:

• Nationally: SA Tourism persuades South African citizens to travel in their own country.
• Value for money
• The world in one country
• South Africa’s political miracle
• The climate
• The friendliness of South Africa’s people
• The cleanliness and tranquility (peace) of our tourist destinations

13.9.2 Directing tourists’ spatial distribution Three approaches are followed to distribute tourists effectively to the many tourist sites:

• Create representative bodies: Tourist-based industries are linked to form representative bodies. Tourists can then easily access knowledge about all tourist destinations.
• Improve marketing: Tourists receive accurate product descriptions and information about competitive prices. Less well-known destinations are aggressively marketed.
• Improve supporting services: The standards of transport, accommodation and other amenities (facilities and services) are world class.

13.9.3 Taxation Growth in tourism results in increased tourist taxes. Guidelines for levying taxes are:

• Equity: Taxes must be fair, e.g. taxes on air tickets.
• Efficiency: Nature and game reserves charge entry taxes to regulate tourist flows.
• Simplicity: A flat tax rate is used to ensure taxes are easy to pay and administer.

13.9.4 Infrastructure Tourism requires economic infrastructure (roads), social infrastructure(ambulances) and basic services (clean water):

• Infrastructure is maintained for the benefit of domestic and foreign tourists, as well as local citizens.
• More infrastructure is required, e.g. water supplies.
• Existing infrastructure must be upgraded, e.g. upgrade dirt roads to tarred roads.
• Use new technology to extend the infrastructure, e.g. build the Gautrain.
• Define the concept tourism. (4)
• Explain the difference between an inbound and an outbound tourist. (4)
• List any THREE World Heritage Sites in South Africa. (3)
• Discuss the effect of tourism on infrastructure. (4 × 2) (8) [19]
• Mapungubwe in Limpopo Vredefort Dome (meteorite) in North West 3 Sterkfontein caves (Mrs Ples and Cradle of Humankind) Robben Island (any 3) (3)
• More infrastructure (e.g. water) 
• Upgrading (e.g. upgrade dirt roads to tarred roads) 
• New technology (e.g. transport)  (8) [19] 

Activity 2 Choose the correct answer from the following alternatives: Tourism is _________ intensive.

Answer to activity 2 A. Labour  [2]

Activity 3 Choose the correct answer from the following alternatives: Tourism benefits the household through_________ .

• Lower incomes
• Lower productivity
• More infrastructure [2]

Answer to activity 3 C. More infrastructure  [2]

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UN Tourism | Bringing the world closer

Secretary-general’s policy brief on tourism and covid-19, share this content.

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Tourism and COVID-19 – unprecedented economic impacts

The Policy Brief provides an overview of the socio-economic impacts from the pandemic on tourism, including on the millions of livelihoods it sustains. It highlights the role tourism plays in advancing the Sustainable Development Goals, including its relationship with environmental goals and culture. The Brief calls on the urgency of mitigating the impacts on livelihoods, especially for women, youth and informal workers.

The crisis is an opportunity to rethink how tourism interacts with our societies, other economic sectors and our natural resources and ecosystems; to measure and manage it better; to ensure a fair distribution of its benefits and to advance the transition towards a carbon neutral and resilient tourism economy.

The brief provides recommendations in five priority areas to cushion the massive impacts on lives and economies and to rebuild a tourism with people at the center. It features examples of governments support to the sector, calls for a reopening that gives priority to the health and safety of the workers, travelers and host communities and provides a roadmap to transform tourism.

• Tourism is one of the world’s major economic sectors. It is the third-largest export category (after fuels and chemicals) and in 2019 accounted for 7% of global trade .
• For some countries, it can represent over 20% of their GDP and, overall, it is the third largest export sector of the global economy.
• Tourism is one of the sectors most affected by the Covid-19 pandemic, impacting economies, livelihoods, public services and opportunities on all continents. All parts of its vast value-chain have been affected. 
• Export revenues from tourism could fall by $910 billion to $1.2 trillion in 2020. This will have a wider impact and could reduce global GDP by 1.5% to 2.8% .
• Tourism supports one in 10 jobs and provides livelihoods for many millions more in both developing and developed economies.
• In some Small Island Developing States (SIDS), tourism has accounted for as much as 80% of exports, while it also represents important shares of national economies in both developed and developing countries.

100 to 120 MILLON

direct tourism jobs at risk

Massive Impact on Livelihoods

• As many as 100 million direct tourism jobs are at risk , in addition to sectors associated with tourism such as labour-intensive accommodation and food services industries that provide employment for 144 million workers worldwide. Small businesses (which shoulder 80% of global tourism) are particularly vulnerable.
• Women, who make up 54% of the tourism workforce, youth and workers in the informal economy are among the most at-risk categories.
• No nation will be unaffected. Destinations most reliant on tourism for jobs and economic growth are likely to be hit hardest: SIDS, Least Developed Countries (LDCs) and African countries. In Africa, the sector represented 10% of all exports in 2019.  

US$ 910 Billon to US$ 1.2 Trillon

in export from tourism - international visitors' spending

Preserving the Planet -- Mitigating Impacts on Nature and Culture

• The sudden fall in tourism cuts off funding for biodiversity conservation . Some 7% of world tourism relates to wildlife , a segment growing by 3% annually.
• This places jobs at risk and has already led to a rise in poaching, looting and in consumption of bushmeat , partly due to the decreased presence of tourists and staff.
• The impact on biodiversity and ecosystems is particularly critical in SIDS and LDCs. In many African destinations, wildlife accounts for up to 80% of visits, and in many SIDS, tourism revenues enable marine conservation efforts.
• Several examples of community involvement in nature tourism show how communities, including indigenous peoples, have been able to protect their cultural and natural heritage while creating wealth and improve their wellbeing. The impact of COVID-19 on tourism places further pressure on heritage conservation as well as on the cultural and social fabric of communities , particularly for indigenous people and ethnic groups.
• For instance, many intangible cultural heritage practices such as traditional festivals and gatherings have been halted or postponed , and with the closure of markets for handicrafts, products and other goods , indigenous women’s revenues have been particularly impacted.
• 90% of countries have closed World Heritage Sites, with immense socio-economic consequences for communities reliant on tourism. Further, 90% of museums closed and 13% may never reopen.

1.5% to 2.8 of global GDP

Five priorities for tourism’s restart.

The COVID-19 crisis is a watershed moment to align the effort of sustaining livelihoods dependent on tourism to the SDGs and ensuring a more resilient, inclusive, carbon neutral, and resource efficient future.

A roadmap to transform tourism needs to address five priority areas:

• Mitigate socio-economic impacts on livelihoods , particularly women’s employment and economic security.
• Boost competitiveness and build resilience , including through economic diversification, with promotion of domestic and regional tourism where possible, and facilitation of conducive business environment for micro, small and medium-sized enterprises (MSMEs).
• Advance innovation and digital transformation of tourism , including promotion of innovation and investment in digital skills, particularly for workers temporarily without jobs and for job seekers.
• Foster sustainability and green growth to shift towards a resilient, competitive, resource efficient and carbon-neutral tourism sector. Green investments for recovery could target protected areas, renewable energy, smart buildings and the circular economy, among other opportunities.
• Coordination and partnerships to restart and transform sector towards achieving SDGs , ensuring tourism’s restart and recovery puts people first and work together to ease and lift travel restrictions in a responsible and coordinated manner.

a lifelive for

SIDS, LDCs and many AFRICAN COUNTRIES

tourism represents over 30% of exports for the majority of SIDS and 80% for some

Moving Ahead Together

• As countries gradually lift travel restrictions and tourism slowly restarts in many parts of the world, health must continue to be a priority and coordinated heath protocols that protect workers, communities and travellers, while supporting companies and workers, must be firmly in place.
• Only through collective action and international cooperation will we be able to transform tourism, advance its contribution to the 2030 Agenda and its shift towards an inclusive and carbon neutral sector that harnesses innovation and digitalization, embraces local values and communities and creates decent job opportunities for all, leaving no one behind. We are stronger together.

RESOURCES FOR CONSEVATION

of natural and cultural heritage

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Economic Factors That Affect Tourism Essay (Assessment)

Introduction, economic factors affecting tourism, reference list.

Tourism is an essential element of economic growth and development of any given country in the contemporary world. A majority of developing countries rely heavily on tourism for government’s revenue. Tourism sector ranks as the leading sector in the creation of jobs, source of foreign exchange, and cultural development in many developing countries.

There are three major types of tourism, which include leisure, exploration, and educational tourism ( Sustaining Tourism 2013). Leisure tourism is the most common type of tourism where tourists visit attractive places for holiday and relaxation purposes.

Exploration tourism is a type of tourism that is often undertaken by researchers and scientists for exploration purposes in different parts of the world (Balaguer & Cantavell-Jorda 2002). Exploration tourism is often associated with discovery tours whereby a tourist is more after discovering new things rather than having pleasure.

Finally, educational tourism is the most common type of tourism that is undertaken by young people in different types of the world. Its main aim lies in educational purposes in a selected destination country and visas expire after the ending of the educational course being undertaken. There are various economic factors affecting tourism industry either directly or indirectly, but they depend largely on the nature of tourism as shown in this essay.

A tour operator should consider various economic factors in the selection of a tourist destination for holidays, education, and exploration. However, some factors are directly related to the economic growth and development of the country of destination, but these factors have an indirect influence in the relationship between economic factors and tourism.

The first economic factor that needs to be considered is the political environment of the destination country (World Bank 2005). Politics play a major role in the growth and development of any country in the world.

Nature of politics determines the behaviours of stock and foreign exchange markets in the sense that stable political environment attract foreign investors, while unstable political arena forces foreign investors to pull out of the economy. The case is the same for tourism whereby stable political environment is conducive for tourism activities, whereas unstable politics pose insecurity threats to the tourism sector (Todaro 2005).

Hence, a prudent tourist operator cannot recommend such a destination due to low demand of international and domestic tourism. Developing nations are worst hit by political crises and especially during the electioneering periods. During such periods, the political environments are unstable and unpredictable, and in most cases, such an environment creates anxiety in economic activities (Lokman & Hatemi 2005).

In such situations, countries with bad historical politics are worst hit by economic downturns as foreign investors and other locals suspend their economic activities for fear of adverse effects of bad politics. Hence, demand for tourism declines rapidly during such periods until when there is an assurance of political stability.

Secondly, international security is a great factor that determines the nature of demand for both foreign and local tourism. International security is mostly determined by two crucial elements, which include political environment and threats of terror.

Political environment that poses a threat to international security comes from civic wars whereby governments engage in local battles with militia and rebels like the current situation in Syria. In such a case, international community is obliged to move into the rescue of the oppressed, and thus posing international security threat (Arellano & Bond 2002).

On the other hand, threats of terror attacks are currently the leading cause of security threat across the world. Any given country is a potential target for terror attacks, but awareness depends on international security intelligence and wherever a warning is issued on potentiality of a country being attacked by terrorists, tourist operators do not recommend for tourism activities in such destinations.

Terrorism attacks have long-term adverse effects on the tourism industry for a county takes a long time to assure foreigners of its security (Ardahaey 2011). In additional to security matters, individual security is also a matter of great concern in selecting a tourist destination. Security has a direct relationship to both the economic growth and development and tourism.

There have been cases where locals have attacked and robbed tourists of their belongings and in such cases, tourist operators do not recommend for such destinations. Tourism sector is very sensitive to security matters and it is always recommendable for governments to ensure that effective security policies are in place for assuring tourism safety.

Thirdly, economic growth and development of a tourist destination is an important factor used in determining a tourist destination by the tourism operators. Economic growth and development is the mother of all other factors of tourism destinations, but looking on the trend, economic recession implies that economic growth is deteriorating and hence a threat to tourism.

In such situations, foreign investors pull out of markets, thus causing a major blow to economic stability. Worst still, economic recession often leads to political instability and in case of economic stability and boom trends, tourists are attracted into an economy.

The fourth important factor of tourism is the nature of the hospitality industry at the tourist destination in question. This aspect mostly affects leisure tourism whereby tourists demand an environment that is peaceful for relaxation. Hospitality is necessary for assurance of security and goodness of wellbeing to tourists ( Visit Britain 2013.

It is important to have excellent hotels that are located nearby the tourist attraction sites in order for tourists to consider such a tourist destination. Hospitality industry is directly related to the economic growth of a country for an economically stable country is capable of offering high quality hospitality services to tourists.

The world’s most developed countries are leading in the hospitality industry, as they are capable of building excellent hotels that offer excellent accommodation facilities to the tourists (Durbarry 2004). This case is very different for most of the third world economies.

The fifth crucial economic factor that affects tourism is the infrastructural conditions in the tourist destination countries. It is necessary to have good infrastructure at the points of tourist accommodation, which would include availability of power, clean water supply, and excellent transport network.

In addition, health infrastructure is also a matter of concern for tourists and it should be considered when selecting the tourism destination. The developed nations are better placed for the provision of good infrastructure that is necessary for tourists than their counterparts.

Tourists require excellent facilities that meet the international standards; unfortunately, such facilities are not easily available in the third world countries (Mason 2002). Third world countries are often forced to allocate more funds to developing the tourism industry than other crucial sectors and thus creating an imbalance of government spending, but the case is different for the developed countries.

The sixth economic factor that affects tourism is the nature of tourist attraction sites in a given destination. For the case of leisure tourism, a tourist is often motivated by the nature of attraction sites at the destination. In the modern world, few tourist attraction sites are in their natural states, thus implying that economic conditions have contributed in the development of major attraction sites in the world (Dieke 2004).

Third world countries enjoy the natural tourist attraction sites such as wildlife, sunny and sandy beaches, and attractive geographical features. Various studies indicate that these countries have done very little to modify these sites from their natural states, but done a lot to conserve them (Cunado & Garcia 2006).

However, the case is different for the majority of developed countries that have artificial tourist attraction sites such as artificial islands, hotels, and mega structures. The difference between the two classes of economy has played a major role in the development of tourist attraction sites.

The seventh economic factor of tourism is the foreign exchange rates at the destination. Foreign exchange and bank interest rates are in most cases determined by demand and supply of foreign exchange in an economy (Greene& William 2000). This aspect has a direct effect to the cost of tourism in a destination.

For the cases of strong local currency, the foreign tourists are required to pay for goods and services and hence may evade such destinations. Studies have shown that third world counties are the cheapest destinations for foreign tourists as they often have weaker currencies when compared to the currencies of the developed countries (Raymond 2001).

This aspect explains the major reason why tourists rarely visit economies with strong currencies as they have expensive goods and services to customers. However, the case is different for first class hotel industries, which have standardised the costs of services.

The eighth economic factor that affects tourism is the social factors that have direct effects on the tourism industry. Social factors include health of the locals, public hospitality, and social development in terms of literacy. Social wellbeing depends on the state of a country’s economic status and thus this factor is linked to economic determinants of a tourism destination.

A flourished economy often has good social wellbeing that is conducive for tourism activities in an economy. A country that cannot ensure good health for its citizens cannot be recommended as a destination that is conducive for tourism due to exposure to health risks.

Countries whose citizens are known to be welcoming to tourists such as Kenya are more likely to attract tourists than those countries whose citizens are not welcoming.

Literacy level is crucial for the tourism sector as tourists use international languages for communication (Cunado & Garcia 2006). Illiteracy hinders effective communication between tourists and the locals and this aspect could discourage tourists from visiting a destination.

The growth and development of tourism depends entirely on the economic and development of a tourist destination.

However, other crucial factors affect tourism, and such factors are more related to the social and political aspects that also have a direct relationship with the economic growth and development of a destination. It would be prudent to state that tourism is largely determined by economic factors since economic factors determine all other crucial factors that are necessary for tourism.

Ardahaey, F 2011, ‘Economic Impacts of Tourism Industry’, International Journal of Business and Management , vol. 6 no. 8, pp. 123-145.

Arellano, M & Bond, S 2002, Panel Data Estimation using DPD for O xford, Nuffield College Publishers, Oxford.

Balaguer, J & Cantavell-Jorda, M 2002, ‘Tourism as a Long-run Growth Factor: The Spanish Case’, Applied Economics , vo.34 no. 7, pp.877-884.

Cunado, J & Garcia, F 2006, ‘Real Convergence in Africa in the second-half of the 20th century,’ Journal of Economics and Business, vol.58 no. 8, pp.153-167.

Dieke, P 2004, ‘Tourism in Africa’s Economic Development: Policy Implication’, Management Decision , vol.41 no.3, pp.287-295.

Durbarry, R 2004, ‘Tourism and Economic Growth: The Case of Mauritius’, Tourism Economics, vol.10 no.3, pp.389-401.

Greene, A & William, H 2000, Econometric Analysis, Prentice Hall, London.

Lokman, G & Hatemi, A 2005, ‘Is the tourism-led growth hypothesis valid for Turkey’, Applied Economics , vol.12 no. 2, pp. 499-504.

Mason, J 2002, Qualitative Researching, SAGE, London.

Raymond Y 2001, ‘Estimating the impact of economic factors on tourism: evidence from Hong Kong’, Tourism Economics , vol.7 no. 3, pp.277–293.

Sustaining Tourism : Demand for Sustainable Tourism. 2013. Web.

Todaro, M 2005, Economic Development, Addison-Wesley Publishers, London.

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Visit Britain: Traveller Tips . 2013. Web.

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IvyPanda. (2023, October 29). Economic Factors That Affect Tourism Essay (Assessment). https://ivypanda.com/essays/economic-factors-that-affect-tourism/

"Economic Factors That Affect Tourism Essay (Assessment)." IvyPanda , 29 Oct. 2023, ivypanda.com/essays/economic-factors-that-affect-tourism/.

IvyPanda . (2023) 'Economic Factors That Affect Tourism Essay (Assessment)'. 29 October.

IvyPanda . 2023. "Economic Factors That Affect Tourism Essay (Assessment)." October 29, 2023. https://ivypanda.com/essays/economic-factors-that-affect-tourism/.

1. IvyPanda . "Economic Factors That Affect Tourism Essay (Assessment)." October 29, 2023. https://ivypanda.com/essays/economic-factors-that-affect-tourism/.

Bibliography

IvyPanda . "Economic Factors That Affect Tourism Essay (Assessment)." October 29, 2023. https://ivypanda.com/essays/economic-factors-that-affect-tourism/.

• Equitours' Organization: Tourism Destinations
• Adventure Tourism as a Major Form of Tourism
• Improving Tourism Destinations Competitiveness
• Tourism Changes and Challenges
• Tourism as an Ambassador of Promoting International Peace
• Sustainable Tourism: Divisions among Stakeholders
• Sustainable Tourism Development
• The sustainable tourism in New Zealand

Tourism Essay for Students and Children

500+ Words Essay on Tourism

Tourism Essay – Tourism is a major economic activity that has developed significantly over the years. It’s an activity that can be recognized in both developed and developing nations. In general terms, tourism is the movement of a person from one place to another to visit and mesmerize the beauty of that place or to have fun. Moreover, the concept of traveling is considered a luxury and only people with higher income can afford this luxury.

The Growth of Tourism

Earlier our ancestors used to travel by sea routes as it was a convenient and most affordable medium but it was time taking. Due to, technological advancement we can now easily travel to any place without wasting time we can travel thousands of miles within a few hours. Technological advancement has shrunk the earth into a global village. Besides, the modern modes are much safer than the modes that our predecessors used.

Effect of Tourism on a Country

For any country, tourism generates a lot of money especially a country like India. Due to the Taj Mahal (one of the seven wonders of the world) every year the government raise a huge sum of revenue. Also, because of tourism other industries also bloom. Such industries include transportation, wildlife, arts and entertainment, accommodation, etc.

Moreover, this ultimately leads to the creation of job and other opportunities in the area. But there are some drawbacks too which can affect the lifestyle and cultural value of the country.

Importance of Tourism

Traveling is a tiring and difficult thing and not everyone is able to travel. But at the same time, it’s a fun activity that takes your tiredness away. Travelling adds flavor to life as you travel to different places that have a different culture and lifestyle. Also, it’s an easy way to learn about the culture and tradition of a place. Besides, for many areas, tourism is their main source of income.

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India- A Tourist Attraction

The Taj Mahal is not the only destination in India that attract tourist. Likewise, there are hundreds of tourist destination that is spread over the Indian plateau. India has a large variety of Flora and Fauna. Besides, the equator divides the geographical land of India into almost two equal halves that make India a country where six seasons occurs.

Moreover, in almost every city of India, there is a historical monument made by the rulers in their time period.

Benefits of Tourism

Tourism not only benefits the government but also the people that live in the local area. It also creates a business as well as employment opportunities for the local people which ultimately help the government to earn income.

Benefits Due to Tourism

As we know that tourism contributes a lot to the revenue of the country. Also, the government uses this income for the growth and development of the country. Likewise, they construct dams, wildlife sanctuaries, national parks, Dharamshala and many more.

In conclusion, we can say that tourism is a very productive activity both for the tourist and the government. As they support each other simultaneously. Also, the government should consider improving the conditions of the country as more and more number of tourist visit their country.

Above all, tourism is one of the fastest-growing industry in the world that has changed the scenario of the world.

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Is digital economy the driving force for improving the tourism economic resilience? Evidence from China

• Zhu, Jingmin
• Zhang, Yilu

To explore the innovation-driven of digital economy on tourism economic resilience in China, digital economy and tourism economic resilience are assessed respectively using Principal Component Analysis and the modified TOPSIS model based on panel data of 211 excellent tourism cities from 2000 to 2020. According to a comprehensive explanation of the influence mechanisms, a transmission mechanism model, a panel threshold model and a spatial econometric model are constructed to test the transmission mechanism and spatial spillover effect between digital economy and tourism economic resilience. The findings show that digital economy exerts a significant positive influence on tourism economic resilience through technological carriers, tourism economic growth and human capital, and these three variables also have significant threshold effects. Moreover, the results of spatial Durbin model shows that the digital economy has a significant contribution to local tourism economic resilience, but significantly hinders the tourism economic resilience of neighboring cities.

• Digital economy;
• Tourism economic resilience;
• Transmission mechanism;
• Nonlinear relationship;
• Spatial spillover effect

U.S. Worker Mobility Across Establishments within Firms: Scope, Prevalence, and Effects on Worker Earnings

Multi-establishment firms account for around 60% of U.S. workers' primary employers, providing ample opportunity for workers to change their work location without changing their employer. Using U.S. matched employer-employee data, this paper analyzes workers' access to and use of such between-establishment job transitions, and estimates the effect on workers' earnings growth of greater access, as measured by proximity of employment at other within-firm establishments. While establishment transitions are not perfectly observed, we estimate that within-firm establishment transitions account for 7.8% percent of all job transitions and 18.2% of transitions originating from the largest firms. Using variation in worker's establishment locations within their firms' establishment network, we show that having a greater share of the firm's jobs in nearby establishments generates meaningful increases in workers' earnings: a worker at the 90th percentile of earnings gains from more proximate within-firm job opportunities can expect to enjoy 2% higher average earnings over the following five years than a worker at the 10th percentile with the same baseline earnings.

Authors’ names are ordered alphabetically. The authors thank Terra McKinnish, Brian Cadena, Taylor Jaworski, Ryan Decker, David Hummels, and Stephen Tibbets for helpful comments. Any views expressed are those of the authors and not those of the U.S. Census Bureau. The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data used to produce this product. This research was performed at a Federal Statistical Research Data Center under FSRDC Project Number 1846. (CBDRB-FY24-P1846-R11265). This research uses data from the Census Bureau’s Longitudinal Employer Household Dynamics Program, which was partially supported by the following National Science Foundation Grants SES-9978093, SES-0339191 and ITR-0427889; National Institute on Aging Grant AG018854; and grants from the Alfred P. Sloan Foundation. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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Opinion: Utah’s tourism ripple effect

L ast month, Natalie Randall assumed the role of the managing director of the Utah Office of Tourism and Film . The previous director, Vicki Varela, retired after an unparalleled run of prosperity, including overcoming incredibly unique challenges over the last decade.

Our goal and vision of the Utah Office of Tourism and Film is to attract intentionally prepared visitors to have an unforgettable experience in our great state. We can make a difference by helping prospective visitors plan better, understand how to recreate responsibly and visit with intent — supporting local economies, and ensuring their experience meets and exceeds their expectations.

Tourism boosts Utah’s economic success

Utah has one of, if not the best, economies in the country. Tourism is a major reason why. Tourism plays a significant role in Utah’s economic success. Recent data from the Kem C. Gardner Policy Institute shows visitors spent a record $11.98 billion in Utah in 2022, generating 98,600 direct travel-related jobs and $1.37 billion in direct state and local tax revenue.

A visitor economy provides a means for improvements to our state and our communities. Every year, visitors contribute millions of dollars, expanding Utah’s outdoor recreation infrastructure by paying hotel taxes and adding to the quality and variety of dining options, community events and improved accessibility to local amenities.

With our blend of unique rural and urban areas and unparalleled access to adventure, it’s no wonder the Wasatch Front and our national parks — two very distinct experiences — top the list for economic impact and visitation.

Investing in tourism supports rural Utah

Natalie knows firsthand how vital tourism is at all six corners of the state, having lived in San Juan County. In rural Utah, future generations are considered the No. 1 “export,” as people grow up and leave in pursuit of opportunities. The tourism industry brought Natalie to Monticello after she married a Utahn who left home and returned to start a small guiding outfit, continuing the family tradition of living off the land.

Investing in tourism pays off dividends for all Utahns, especially in rural Utah. The visitor economy allows Utah natives and those returning to fulfill their dreams and improve their quality of life wherever they call home.

Garfield County resident and business owner Tari Cottam shared, “Tourism is a ripple effect. If you bring nice things in, more nice things are going to come.”

The Cottam family, who runs the Canyon Country Lodge near Bryce Canyon National Park, is dedicated to showing guests the best Utah experience possible and has improved the lives of the entire community around them. The Cottams are a shining example of the positive impact of a strong visitor economy.

We welcome people to experience our unparalleled outdoor landscapes and communities, help them find the right accommodations, serve them meals, and guide them to inspiring places. Tourism is the business of hospitality.

Tourism improves the lives of Utahns

Whether you’re a lifelong resident or a more recent transplant, chances are you take advantage of the accessibility that the tourism industry has built for your own travels — from half-day skiing to a quick weekend getaway across the state for a change of scenery. Whether by car or plane, visitors are presented with the opportunity to be absorbed by Utah art and culture and transfixed by our scenic destinations.

According to a statewide resident sentiment survey, more than 70% of Utahns recognize the importance of tourism. Additionally, 72% of residents say tourism positively affects Utah’s overall reputation.

Utah is changing every day. With a maturing visitor economy, the likelihood of a returning Olympics, and a growing population, we have a great responsibility to do right by Utahns.

We’re taking the time to listen, hearing the voices of residents and visitors on community-led approaches, future investments and strategies.

We are striving to create a dynamic visitor economy that will benefit communities and visitors alike for generations to come. We are building a Utah where our children will want to stay, fostering pride among locals and visitors.

We open our Utah home to visitors, and in return, we are granted the ability to make our daily lives even better. Tourism works.

Ryan Starks is the executive director of the Utah Governor’s Office of Economic Opportunity. Natalie Randall is the managing director of the Utah Office of Tourism and Film.