The COVID-19 travel shock hit tourism-dependent economies hard

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Gian maria milesi-ferretti gian maria milesi-ferretti senior fellow - economic studies , the hutchins center on fiscal and monetary policy.

August 12, 2021

The COVID crisis has led to a collapse in international travel. According to the World Tourism Organization , international tourist arrivals declined globally by 73 percent in 2020, with 1 billion fewer travelers compared to 2019, putting in jeopardy between 100 and 120 million direct tourism jobs. This has led to massive losses in international revenues for tourism-dependent economies: specifically, a collapse in exports of travel services (money spent by nonresident visitors in a country) and a decline in exports of transport services (such as airline revenues from tickets sold to nonresidents).

export of services

This “travel shock” is continuing in 2021, as restrictions to international travel persist—tourist arrivals for January-May 2021 are down a further 65 percent from the same period in 2020, and there is substantial uncertainty on the nature and timing of a tourism recovery.

We study the economic impact of the international travel shock during 2020, particularly the severity of the hit to countries very dependent on tourism. Our main result is that on a cross-country basis, the share of tourism activities in GDP is the single most important predictor of the growth shortfall in 2020 triggered by the COVID-19 crisis (relative to pre-pandemic IMF forecasts), even when compared to measures of the severity of the pandemic. For instance, Grenada and Macao had very few recorded COVID cases in relation to their population size and no COVID-related deaths in 2020—yet their GDP contracted by 13 percent and 56 percent, respectively.

International tourism destinations and tourism sources

Countries that rely heavily on tourism, and in particular international travelers, tend to be small, have GDP per capita in the middle-income and high-income range, and are preponderately net debtors. Many are small island economies—Jamaica and St. Lucia in the Caribbean, Cyprus and Malta in the Mediterranean, the Maldives and Seychelles in the Indian Ocean, or Fiji and Samoa in the Pacific. Prior to the COVID pandemic, median annual net revenues from international tourism (spending by foreign tourists in the country minus tourism spending by domestic residents overseas) in these island economies were about one quarter of GDP, with peaks around 50 percent of GDP, such as Aruba and the Maldives.

But there are larger economies heavily reliant on international tourism. For instance, in Croatia average net international tourism revenues from 2015-2019 exceeded 15 percent of GDP, 8 percent in the Dominican Republic and Thailand, 7 percent in Greece, and 5 percent in Portugal. The most extreme example is Macao, where net revenues from international travel and tourism were around 68 percent of GDP during 2015-19. Even in dollar terms, Macao’s net revenues from tourism were the fourth highest in the world, after the U.S., Spain, and Thailand.

In contrast, for countries that are net importers of travel and tourism services—that is, countries whose residents travel widely abroad relative to foreign travelers visiting the country—the importance of such spending is generally much smaller as a share of GDP. In absolute terms, the largest importer of travel services is China (over $200 billion, or 1.7 percent of GDP on average during 2015-19), followed by Germany and Russia. The GDP impact for these economies of a sharp reduction in tourism outlays overseas is hence relatively contained, but it can have very large implications on the smaller economies their tourists travel to—a prime example being Macao for Chinese travelers.

How did tourism-dependent economies cope with the disappearance of a large share of their international revenues in 2020? They were forced to borrow more from abroad (technically, their current account deficit widened, or their surplus shrank), but also reduced net international spending in other categories. Imports of goods declined (reflecting both a contraction in domestic demand and a decline in tourism inputs such as imported food and energy) and payments to foreign creditors were lower, reflecting the decline in returns for foreign-owned hotel infrastructure.

The growth shock

We then examine whether countries more dependent on tourism suffered a bigger shock to economic activity in 2020 than other countries, measuring this shock as the difference between growth outcomes in 2020 and IMF growth forecasts as of January 2020, just prior to the pandemic. Our measure of the overall importance of tourism is the share of GDP accounted for by tourism-related activity over the 5 years preceding the pandemic, assembled by the World Travel and Tourism Council and disseminated by the World Bank . This measure takes into account the importance of domestic tourism as well as  international tourism.

Among the 40 countries with the largest share of tourism in GDP, the median size of growth shortfall compared to pre-COVID projections was around 11 percent, as against 6 percent for countries less dependent on tourism. For instance, in the tourism-dependent group, Greece, which was expected to grow by 2.3 percent in 2020, shrunk by over 8 percent, while in the other group,  Germany, which was expected to grow by around 1 percent, shrunk by 4.8 percent. The scatter plot of Figure 2 provides more striking visual evidence of a negative correlation (-0.72) between tourism dependence and the growth shock in 2020.

tourism dependence

Of course, many other factors may have affected differences in performance across economies—for instance, the intensity of the pandemic as well as the stringency of the associated lockdowns. We therefore build a simple statistical model that relates the “growth shock” in 2020 to these factors alongside our tourism variable, and also takes into account other potentially relevant country characteristics, such as the level of development, the composition of output, and country size. The message: the dependence on tourism is a key explanatory variable of the growth shock in 2020. For instance, the analysis suggests that going from the share of tourism in GDP of Canada (around 6 percent) to the one of Mexico (around 16 percent) would reduce growth in 2020 by around 2.5 percentage points. If we instead go from the tourism share of Canada to the one of Jamaica (where the share of tourism in GDP approaches one third), growth would be lower by over 6 percentage points.

Measures of the severity of the pandemic, the intensity of lockdowns, the level of development, and the sectoral composition of GDP (value added accounted for by manufacturing and agriculture) also matter, but quantitatively less so than tourism. And results are not driven by very small economies; tourism is still a key explanatory variable of the 2020 growth shock even if we restrict our sample to large economies. Among tourism-dependent economies, we also find evidence that those relying more heavily on international tourism experienced a more severe hit to economic activity when compared to those relying more on domestic tourism.

Given data availability at the time of writing, the evidence we provided is limited to 2020. The outlook for international tourism in 2021, if anything, is worse, though with increasing vaccine coverage the tide could turn next year. The crisis poses particularly daunting challenges to smaller tourist destinations, given limited possibilities for diversification. In many cases, particularly among emerging and developing economies, these challenges are compounded by high starting levels of domestic and external indebtedness, which can limit the space for an aggressive fiscal response. Helping these countries cope with the challenges posed by the pandemic and restoring viable public and external finances will require support from the international community.

Read the full paper here.

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Tourism Teacher

10 Economic impacts of tourism + explanations + examples

Disclaimer: Some posts on Tourism Teacher may contain affiliate links. If you appreciate this content, you can show your support by making a purchase through these links or by buying me a coffee . Thank you for your support!

There are many economic impacts of tourism, and it is important that we understand what they are and how we can maximise the positive economic impacts of tourism and minimise the negative economic impacts of tourism.

Many argue that the tourism industry is the largest industry in the world. While its actual value is difficult to accurately determine, the economic potential of the tourism industry is indisputable. In fact, it is because of the positive economic impacts that most destinations embark on their tourism journey.

There is, however, more than meets the eye in most cases. The positive economic impacts of tourism are often not as significant as anticipated. Furthermore, tourism activity tends to bring with it unwanted and often unexpected negative economic impacts of tourism.

In this article I will discuss the importance of understanding the economic impacts of tourism and what the economic impacts of tourism might be. A range of positive and negative impacts are discussed and case studies are provided.

At the end of the post I have provided some additional reading on the economic impacts of tourism for tourism stakeholders , students and those who are interested in learning more.

 Foreign exchange earnings

Contribution to government revenues, employment generation, contribution to local economies, development of the private sector, infrastructure cost, increase in prices, economic dependence of the local community on tourism, foreign ownership and management, economic impacts of tourism: conclusion, further reading on the economic impacts of tourism, the economic impacts of tourism: why governments invest.

Tourism brings with it huge economic potential for a destination that wishes to develop their tourism industry. Employment, currency exchange, imports and taxes are just a few of the ways that tourism can bring money into a destination.

In recent years, tourism numbers have increased globally at exponential rates, as shown in the World Tourism Organisation data below.

There are a number of reasons for this growth including improvements in technology, increases in disposable income, the growth of budget airlines and consumer desires to travel further, to new destinations and more often.

tourism economic dependence

Here are a few facts about the economic importance of the tourism industry globally:

  • The tourism economy represents 5 percent of world GDP
  • Tourism contributes to 6-7 percent of total employment
  • International tourism ranks fourth (after fuels, chemicals and automotive products) in global exports
  • The tourism industry is valued at US$1trillion a year
  • Tourism accounts for 30 percent of the world’s exports of commercial services
  • Tourism accounts for 6 percent of total exports
  • 1.4billion international tourists were recorded in 2018 (UNWTO)
  • In over 150 countries, tourism is one of five top export earners
  • Tourism is the main source of foreign exchange for one-third of developing countries and one-half of less economically developed countries (LEDCs)

There is a wealth of data about the economic value of tourism worldwide, with lots of handy graphs and charts in the United Nations Economic Impact Report .

In short, tourism is an example of an economic policy pursued by governments because:

  •      it brings in foreign exchange
  •      it generates employment
  •      it creates economic activity

Building and developing a tourism industry, however, involves a lot of initial and ongoing expenditure. The airport may need expanding. The beaches need to be regularly cleaned. New roads may need to be built. All of this takes money, which is usually a financial outlay required by the Government.

For governments, decisions have to be made regarding their expenditure. They must ask questions such as:

How much money should be spent on the provision of social services such as health, education, housing?

How much should be spent on building new tourism facilities or maintaining existing ones?

If financial investment and resources are provided for tourism, the issue of opportunity costs arises.

By opportunity costs, I mean that by spending money on tourism, money will not be spent somewhere else. Think of it like this- we all have a specified amount of money and when it runs out, it runs out. If we decide to buy the new shoes instead of going out for dinner than we might look great, but have nowhere to go…!

In tourism, this means that the money and resources that are used for one purpose may not then be available to be used for other purposes. Some destinations have been known to spend more money on tourism than on providing education or healthcare for the people who live there, for example.

This can be said for other stakeholders of the tourism industry too.

There are a number of independent, franchised or multinational investors who play an important role in the industry. They may own hotels, roads or land amongst other aspects that are important players in the overall success of the tourism industry. Many businesses and individuals will take out loans to help fund their initial ventures.

So investing in tourism is big business, that much is clear. What what are the positive and negative impacts of this?

economic impacts of tourism

Positive economic impacts of tourism

So what are the positive economic impacts of tourism? As I explained, most destinations choose to invest their time and money into tourism because of the positive economic impacts that they hope to achieve. There are a range of possible positive economic impacts. I will explain the most common economic benefits of tourism below.

man sitting on street near tree

One of the biggest benefits of tourism is the ability to make money through foreign exchange earnings.

Tourism expenditures generate income to the host economy. The money that the country makes from tourism can then be reinvested in the economy. How a destination manages their finances differs around the world; some destinations may spend this money on growing their tourism industry further, some may spend this money on public services such as education or healthcare and some destinations suffer extreme corruption so nobody really knows where the money ends up!

Some currencies are worth more than others and so some countries will target tourists from particular areas. I remember when I visited Goa and somebody helped to carry my luggage at the airport. I wanted to give them a small tip and handed them some Rupees only to be told that the young man would prefer a British Pound!

Currencies that are strong are generally the most desirable currencies. This typically includes the British Pound, American, Australian and Singapore Dollar and the Euro .

Tourism is one of the top five export categories for as many as 83% of countries and is a main source of foreign exchange earnings for at least 38% of countries.

Tourism can help to raise money that it then invested elsewhere by the Government. There are two main ways that this money is accumulated.

Direct contributions are generated by taxes on incomes from tourism employment and tourism businesses and things such as departure taxes.

Taxes differ considerably between destinations. I will never forget the first time that I was asked to pay a departure tax (I had never heard of it before then), because I was on my way home from a six month backpacking trip and I was almost out of money!

Japan is known for its high departure taxes. Here is a video by a travel blogger explaining how it works.

According to the World Tourism Organisation, the direct contribution of Travel & Tourism to GDP in 2018 was $2,750.7billion (3.2% of GDP). This is forecast to rise by 3.6% to $2,849.2billion in 2019.

Indirect contributions come from goods and services supplied to tourists which are not directly related to the tourism industry.

Take food, for example. A tourist may buy food at a local supermarket. The supermarket is not directly associated with tourism, but if it wasn’t for tourism its revenues wouldn’t be as high because the tourists would not shop there.

There is also the income that is generated through induced contributions . This accounts for money spent by the people who are employed in the tourism industry. This might include costs for housing, food, clothing and leisure Activities amongst others. This will all contribute to an increase in economic activity in the area where tourism is being developed.

tourism economic dependence

The rapid expansion of international tourism has led to significant employment creation. From hotel managers to theme park operatives to cleaners, tourism creates many employment opportunities. Tourism supports some 7% of the world’s workers.

There are two types of employment in the tourism industry: direct and indirect.

Direct employment includes jobs that are immediately associated with the tourism industry. This might include hotel staff, restaurant staff or taxi drivers, to name a few.

Indirect employment includes jobs which are not technically based in the tourism industry, but are related to the tourism industry. Take a fisherman, for example. He does not have any contact of dealings with tourists. BUT he does sell his fish to the hotel which serves tourists. So he is indirectly employed by the tourism industry, because without the tourists he would not be supplying the fish to the hotel.

It is because of these indirect relationships, that it is very difficult to accurately measure the economic value of tourism.

It is also difficult to say how many people are employed, directly and indirectly, within the tourism industry.

Furthermore, many informal employments may not be officially accounted for. Think tut tut driver in Cambodia or street seller in The Gambia – these people are not likely to be registered by the state and therefore their earnings are not declared.

It is for this reason that some suggest that the actual economic benefits of tourism may be as high as double that of the recorded figures!

All of the money raised, whether through formal or informal means, has the potential to contribute to the local economy.

If sustainable tourism is demonstrated, money will be directed to areas that will benefit the local community most.

There may be pro-poor tourism initiatives (tourism which is intended to help the poor) or volunteer tourism projects.

The government may reinvest money towards public services and money earned by tourism employees will be spent in the local community. This is known as the multiplier effect.

The multiplier effect relates to spending in one place creating economic benefits elsewhere. Tourism can do wonders for a destination in areas that may seem to be completely unrelated to tourism, but which are actually connected somewhere in the economic system.

tourism economic dependence

Let me give you an example.

A tourist buys an omelet and a glass of orange juice for their breakfast in the restaurant of their hotel. This simple transaction actually has a significant multiplier effect. Below I have listed just a few of the effects of the tourist buying this breakfast.

The waiter is paid a salary- he spends his salary on schooling for his kids- the school has more money to spend on equipment- the standard of education at the school increases- the kids graduate with better qualifications- as adults, they secure better paying jobs- they can then spend more money in the local community…

The restaurant purchases eggs from a local farmer- the farmer uses that money to buy some more chickens- the chicken breeder uses that money to improve the standards of their cages, meaning that the chickens are healthier, live longer and lay more eggs- they can now sell the chickens for a higher price- the increased money made means that they can hire an extra employee- the employee spends his income in the local community…

The restaurant purchase the oranges from a local supplier- the supplier uses this money to pay the lorry driver who transports the oranges- the lorry driver pays road tax- the Government uses said road tax income to fix pot holes in the road- the improved roads make journeys quicker for the local community…

So as you can see, that breakfast that the tourist probably gave not another thought to after taking his last mouthful of egg, actually had the potential to have a significant economic impact on the local community!

architecture building business city

The private sector has continuously developed within the tourism industry and owning a business within the private sector can be extremely profitable; making this a positive economic impact of tourism.

Whilst many businesses that you will come across are multinational, internationally-owned organisations (which contribute towards economic leakage ).

Many are also owned by the local community. This is the case even more so in recent years due to the rise in the popularity of the sharing economy and the likes of Airbnb and Uber, which encourage the growth of businesses within the local community.

Every destination is different with regards to how they manage the development of the private sector in tourism.

Some destinations do not allow multinational organisations for fear that they will steal business and thus profits away from local people. I have seen this myself in Italy when I was in search of a Starbucks mug for my collection , only to find that Italy has not allowed the company to open up any shops in their country because they are very proud of their individually-owned coffee shops.

Negative economic impacts of tourism

Unfortunately, the tourism industry doesn’t always smell of roses and there are also several negative economic impacts of tourism.

There are many hidden costs to tourism, which can have unfavourable economic effects on the host community.

Whilst such negative impacts are well documented in the tourism literature, many tourists are unaware of the negative effects that their actions may cause. Likewise, many destinations who are inexperienced or uneducated in tourism and economics may not be aware of the problems that can occur if tourism is not management properly.

Below, I will outline the most prominent negative economic impacts of tourism.

woman holding tomatoes

Economic leakage in tourism is one of the major negative economic impacts of tourism. This is when money spent does not remain in the country but ends up elsewhere; therefore limiting the economic benefits of tourism to the host destination.

The biggest culprits of economic leakage are multinational and internationally-owned corporations, all-inclusive holidays and enclave tourism.

I have written a detailed post on the concept of economic leakage in tourism, you can take a look here- Economic leakage in tourism explained .

road landscape nature forest

Another one of the negative economic impacts of tourism is the cost of infrastructure. Tourism development can cost the local government and local taxpayers a great deal of money.

Tourism may require the government to improve the airport, roads and other infrastructure, which are costly. The development of the third runway at London Heathrow, for example, is estimated to cost £18.6billion!

Money spent in these areas may reduce government money needed in other critical areas such as education and health, as I outlined previously in my discussion on opportunity costs.

glass bottle of cola with empty bottle on white surface

One of the most obvious economic impacts of tourism is that the very presence of tourism increases prices in the local area.

Have you ever tried to buy a can of Coke in the supermarket in your hotel? Or the bar on the beachfront? Walk five minutes down the road and try buying that same can in a local shop- I promise you, in the majority of cases you will see a BIG difference In cost! (For more travel hacks like this subscribe to my newsletter – I send out lots of tips, tricks and coupons!)

Increasing demand for basic services and goods from tourists will often cause price hikes that negatively impact local residents whose income does not increase proportionately.

Tourism development and the related rise in real estate demand may dramatically increase building costs and land values. This often means that local people will be forced to move away from the area that tourism is located, known as gentrification.

Taking measures to ensure that tourism is managed sustainably can help to mitigate this negative economic impact of tourism. Techniques such as employing only local people, limiting the number of all-inclusive hotels and encouraging the purchasing of local products and services can all help.

Another one of the major economic impacts of tourism is dependency. Many countries run the risk of becoming too dependant on tourism. The country sees $ signs and places all of its efforts in tourism. Whilst this can work out well, it is also risky business!

If for some reason tourism begins to lack in a destination, then it is important that the destination has alternative methods of making money. If they don’t, then they run the risk of being in severe financial difficulty if there is a decline in their tourism industry.

In The Gambia, for instance, 30% of the workforce depends directly or indirectly on tourism. In small island developing states, percentages can range from 83% in the Maldives to 21% in the Seychelles and 34% in Jamaica.

There are a number of reasons that tourism could decline in a destination.

The Gambia has experienced this just recently when they had a double hit on their tourism industry. The first hit was due to political instability in the country, which has put many tourists off visiting, and the second was when airline Monarch went bust, as they had a large market share in flights to The Gambia.

Other issues that could result in a decline in tourism includes economic recession, natural disasters and changing tourism patterns. Over-reliance on tourism carries risks to tourism-dependent economies, which can have devastating consequences.

tourism economic dependence

The last of the negative economic impacts of tourism that I will discuss is that of foreign ownership and management.

As enterprise in the developed world becomes increasingly expensive, many businesses choose to go abroad. Whilst this may save the business money, it is usually not so beneficial for the economy of the host destination.

Foreign companies often bring with them their own staff, thus limiting the economic impact of increased employment. They will usually also export a large proportion of their income to the country where they are based. You can read more on this in my post on economic leakage in tourism .

As I have demonstrated in this post, tourism is a significant economic driver the world over. However, not all economic impacts of tourism are positive. In order to ensure that the economic impacts of tourism are maximised, careful management of the tourism industry is required.

If you enjoyed this article on the economic impacts of tourism I am sure that you will love these too-

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  • In 2022, the Travel & Tourism sector contributed 7.6% to global GDP ; an  increase of 22%  from 2021 and only  23%  below 2019 levels.
  • In 2022, there were  2 2 million new jobs , representing a 7.9% increase on 2021, and only 11.4% below 2019.
  • Domestic visitor  spending  increased by 20.4%  in 2022, only 14.1% below 2019.
  • International visitor spending  rose by 81.9% in 2022, but still 40.4% behind 2019 numbers.

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What research does WTTC carry out?

Each year, WTTC and Oxford Economics produce reports covering the economic contribution of our sector in 185 countries, for 26 economic and geographic regions, and for more than 70 cities. We also benchmark Travel & Tourism against other economic sectors and analyse the impact of government policies affecting the sector such as jobs and visa facilitation.

Visit our Research Hub via the button below to find all our Economic Impact Reports, as well as other reports on Travel and Tourism.

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  • Open access
  • Published: 24 February 2024

Modeling the link between tourism and economic development: evidence from homogeneous panels of countries

  • Pablo Juan Cárdenas-García   ORCID: orcid.org/0000-0002-1779-392X 1 ,
  • Juan Gabriel Brida 2 &
  • Verónica Segarra 2  

Humanities and Social Sciences Communications volume  11 , Article number:  308 ( 2024 ) Cite this article

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Metrics details

  • Development studies

Having previously analyzed the relationship between tourism and economic growth from distinct perspectives, this paper attempts to fill the void existing in scientific research on the relationship between tourism and economic development, by analyzing the relationship between these variables using a sample of 123 countries between 1995 and 2019. The Dumistrescu and Hurlin adaptation of the Granger causality test was used. This study takes a critical look at causal analysis with heterogeneous panels, given the substantial differences found between the results of the causal analysis with the complete panel as compared to the analysis of homogeneous country groups, in terms of their dynamics of tourism specialization and economic development. On the one hand, a one-way causal relationship exists from tourism to development in countries having low levels of tourism specialization and development. On the other hand, a one-way causal relationship exists by which development contributes to tourism in countries with high levels of development and tourism specialization.

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Introduction

Across the world, tourism is one of the most important sectors. It has undergone exponential growth since the mid-1900s and is currently experiencing growth rates that exceed those of other economic sectors (Yazdi, 2019 ).

Today, tourism is a major source of income for countries that specialize in this sector, generating 5.8% of the global GDP (5.8 billion US$) in 2021 (UNWTO, 2022 ) and providing 5.4% of all jobs (289 million) worldwide. Although its relevance is clear, tourism data have declined dramatically due to the recent impact of the Covid-19 health crisis. In 2019, prior to the pandemic (UNWTO, 2020 ), tourism represented 10.3% of the worldwide GDP (9.6 billion US$), with the number of tourism-related jobs reaching 10.2% of the global total (333 million). With the evolution of the pandemic and the regained trust of tourists across the globe, it is estimated that by 2022, approximately 80% of the pre-pandemic figures will be attained, with a full recovery being expected by 2024 (UNWTO, 2022 ).

Given the importance of this economic activity, many countries consider tourism to be a tool enabling economic growth (Corbet et al., 2019 ; Ohlan, 2017 ; Xia et al., 2021 ). Numerous works have analyzed the relationship between increased tourism and economic growth; and some systematic reviews have been carried out on this relationship (Brida et al., 2016 ; Ahmad et al., 2020 ), examining the main contributions over the first two decades of this century. These reviews have revealed evidence in this area: in some cases, it has been found that tourism contributes to economic growth while, in other cases, the economic cycle influences tourism expansion. Moreover, other works offer evidence of a bi-directional relationship between these variables.

Distinct international organizations (OECD, 2010 ; UNCTAD, 2011 ) have suggested that not only does tourism promote economic growth, it also contributes to socio-economic advances in the host regions. This may be the real importance of tourism, since the ultimate objective of any government is to improve a country’s socio-economic development (UNDP, 1990 ).

The development of economic and other policies related to the economic scope of tourism, in addition to promoting economic growth, are also intended to improve other non-economic factors such as education, safety, and health. Improvements in these factors lead to a better life for the host population (Lee, 2017 ; Todaro and Smith, 2020 ).

Given tourism’s capacity as an instrument of economic development (Cárdenas-García et al., 2015 ), distinct institutions such as the United Nations Conference on Trade and Development, the United Nations Economic Commission for Africa, the United Nations World Tourism Organization and the World Bank, have begun funding projects that consider tourism to be a tool for improved socio-economic development, especially in less advanced countries (Carrillo and Pulido, 2019 ).

This new trend within the scientific literature establishes, firstly, that tourism drives economic growth and, secondly, that thanks to this economic growth, the population’s economic conditions may be improved (Croes et al., 2021 ; Kubickova et al., 2017 ). However, to take advantage of the economic growth generated by tourism activity to boost economic development, specific policies should be developed. These policies should determine the initial conditions to be met by host countries committed to tourism as an instrument of economic development. These conditions include regulation, tax system, and infrastructure provision (Cárdenas-García and Pulido-Fernández, 2019 ; Lejárraga and Walkenhorst, 2013 ; Meyer and Meyer, 2016 ).

Therefore, it is necessary to differentiate between the analysis of the relationship between tourism and economic growth, whereby tourism boosts the economy of countries committed to tourism, traditionally measured through an increase in the Gross Domestic Product (Alcalá-Ordóñez et al., 2023 ; Brida et al., 2016 ), and the analysis of the relationship between tourism and economic development, which measures the effect of tourism on other factors (not only economic content but also inequality, education, and health) which, together with economic criteria, serve as the foundation to measure a population’s development (Todaro and Smith, 2020 ).

However, unlike the analysis of the relationship between tourism and economic growth, few empirical studies have examined tourism’s capacity as a tool for development (Bojanic and Lo, 2016 ; Cárdenas-García and Pulido-Fernández, 2019 ; Croes, 2012 ).

To help fill this gap in the literature analyzing the relationship between tourism and economic development, this work examines the contribution of tourism to economic development, given that the relationship between tourism and economic growth has been widely analyzed by the scientific literature. Moreover, given that the literature has demonstrated that tourism contributes to economic growth, this work aims to analyze whether it also contributes to economic development, considering development in the broadest possible sense by including economic and socioeconomic variables in the multi-dimensional concept (Wahyuningsih et al., 2020 ).

Therefore, based on the results of this work, it is possible to determine whether the commitment made by many international organizations and institutions in financing tourism projects designed to improve the host population’s socioeconomic conditions, especially in countries with lower development levels, has, in fact, resulted in improved development levels.

It also presents a critical view of causal analyses that rely on heterogeneous panels, examining whether the conclusions reached for a complete panel differ from those obtained when analyzing homogeneous groups within the panel. As seen in the literature review analyzing the relationship between tourism and economic development, empirical works using panel data from several countries tend to generalize the results obtained to the entire panel, without verifying whether, in fact, they are relevant for all of the analyzed countries or only some of the same. Therefore, this study takes an innovative approach by examining the panel countries separately, analyzing the homogeneous groups distinctly.

Therefore, this article presents an empirical analysis examining whether a causal relationship exists between tourism and economic development, with development being considered to be a multi-dimensional variable including a variety of factors, distinct from economic ones. Panel data from 123 countries during the 1995–2019 period was considered to examine the causal relationship between tourism and economic development. For this, the Granger causality test was performed, applying the adaptation of this test made by Dumistrescu and Hurlin. First, a causal analysis was performed collectively for all of the countries of the panel. Then, a specific analysis was performed for each of the homogeneous groups of countries identified within the panel, formed according to levels of tourism specialization and development.

This article provides information on tourism’s capacity to serve as an instrument of development, helping to fill the gap in scientific research in this area. It critically examines the use of causal analyses based on heterogeneous samples of countries. This work offers the following main novelties as compared to prior works on the same topic: firstly, it examines the relationship between tourism and economic development, while the majority of the existing works only analyze the relationship between tourism and economic growth; secondly, it analyzes a large sample of countries, representing all of the global geographic areas, whereas the literature has only considered works from specific countries or a limited number of nations linked to a specific country in a specific geographical area, and; thirdly, it analyzes the panel both individually and collectively, for each of the homogenous groups of countries identified, permitting the adoption of specific policies for each group of countries according to the identified relationship, as compared to the majority of works that only analyze the complete panel, generalizing these results for all countries in the sample.

Overall, the results suggest that a relationship exists between tourism and development in all of the analyzed countries from the sample. A specific analysis was performed for homogeneous country groups, only finding a causal relationship between tourism and development in certain country groups. This suggests that the use of heterogeneous country samples in causal analyses may give rise to inappropriate conclusions. This may be the case, for example, when finding causality for a broad panel of countries, although, in fact, only a limited number of panel units actually explain this causal relationship.

The remainder of the document is organized as follows: the next section offers a review of the few existing scientific works on the relationship between tourism and economic development; section three describes the data used and briefly explains the methodology carried out; section four details the results obtained from the empirical analysis; and finally, the conclusions section discusses the main implications of the work, also providing some recommendations for economic policy.

Tourism and economic development

Numerous organizations currently recognize the importance of tourism as an instrument of economic development. It was not until the late 20th century, however, when the United Nations World Tourism Organization (UNWTO), in its Manila Declaration, established that the development of international tourism may “help to eliminate the widening economic gap between developed and developing countries and ensure the steady acceleration of economic and social development and progress, in particular of the developing countries” (UNWTO, 1980 ).

From a theoretical point of view, tourism may be considered an effective activity for economic development. In fact, the theoretical foundations of many works are based on the relationship between tourism and development (Ashley et al., 2007 ; Bolwell and Weinz, 2011 ; Dieke, 2000 ; Sharpley and Telfer, 2015 ; Sindiga, 1999 ).

The link between tourism and economic development may arise from the increase in tourist activity, which promotes economic growth. As a result of this economic growth, policies may be developed to improve the resident population’s level of development (Alcalá-Ordóñez and Segarra, 2023 ).

Therefore, it is essential to identify the key variables permitting the measurement of the level of economic development and, therefore, those variables that serve as a basis for analyzing whether tourism results in improved the socioeconomic conditions of the host population (Croes et al., 2021 ). Since economic development refers not only to economic-based variables, but also to others such as inequality, education, or health (Todaro and Smith, 2020 ), when analyzing the economic development concept, it has been frequently linked to human development (Pulido-Fernández and Cárdenas-García, 2021 ). Thus, we wish to highlight the major advances resulting from the publication of the Human Development Index (HDI) when measuring economic development, since it defines development as a multidimensional variable that combines three dimensions: health, education, and income level (UNDP, 2023 ).

However, despite the importance that many organizations have given to tourism as an instrument of economic development, basing their work on the relationship between these variables, a wide gap continues to exist in the scientific literature for empirical studies that examine the existence of a relationship between tourism and economic development, with very few empirical analyses analyzing this relationship.

First, a group of studies has examined the causal relationship between tourism and economic development, using heterogeneous samples, and without previously grouping the subjects based on homogeneous characteristics. Croes ( 2012 ) analyzed the relationship between tourism and economic development, measured through the HDI, finding that a bidirectional relationship exists for the cases of Nicaragua and Costa Rica. Using annual data from 2001 to 2014, Meyer and Meyer ( 2016 ) performed a collective analysis of South African regions, determining that tourism contributes to economic development. For a panel of 63 countries worldwide, and once again relying on the HDI to define economic development, it was determined that tourism contributes to economic development. Kubickova et al. ( 2017 ), using annual data for the 1995–2007 period, analyzed Central America and Caribbean nations, determining the existence of this relationship by which tourism influences the level of economic development and that the level of development conditions the expansion of tourism. Another work examined nine micro-states of America, Europe, and Africa (Fahimi et al., 2018 ); and 21 European countries in which human capital was measured, as well as population density and tourism income, analyzing panel data and determining that tourism results in improved economic development. Finally, within this first group of works, Chattopadhyay et al. ( 2022 ), using a broad panel of destinations, (133 countries from all geographic areas of the globe) determined that there is no relationship between tourism and economic development.

Studies performed with large country samples that attempt to determine the causal relationship between tourism and economic development by analyzing countries that do not necessarily share homogeneous characteristics, may lead to erroneous conclusions, establishing causality (or not) for panel sets even when this situation is actually explained by a small number of panel units.

Second, another group of studies have analyzed the causal relationship between tourism and economic development, considering the previous limitation, and has grouped the subjects based on their homogeneous characteristics. Cárdenas-García et al. ( 2015 ) used annual data from 1990–2010, in a collective analysis of 144 countries, making a joint panel analysis and then examining two homogeneous groups of countries based on their level of economic development. They determined that tourism contributes to economic development, but only in the most developed group of countries. They determined that tourism contributes to economic development, both for the total sample and for the homogeneous groups analyzed. Pulido-Fernández and Cárdenas-García ( 2021 ), using annual data for the 1993–2017 period, performed a joint analysis of 143 countries, followed by a specific analysis for three groups of countries sharing homogeneous characteristics in terms of tourism growth and development level. They determined that tourism contributes to economic development and that development level conditions tourism growth in the most developed countries.

Finally, another group of studies has analyzed the causal relationship between tourism and economic development in specific cases examined on an individual basis. In a specific analysis by Aruba et al. ( 2016 ), it was determined that tourism contributes to human development. Analyzing Malaysia, Tan et al. ( 2019 ) determined that tourism contributes to development, but only over the short term, and that level of development does not influence tourism growth. Similar results were obtained by Boonyasana and Chinnakum ( 2020 ) in an analysis carried out in Thailand. In this case of Thailand (Boonyasana and Chinnakum, 2020 ), which relied on the HDI, the relationship with economic growth was also analyzed, finding that an increase in tourism resulted in improved economic development. Finally, Croes et al. ( 2021 ), in a specific analysis of Poland, determined that tourism does not contribute to development.

As seen from the analysis of the most relevant publications detailed in Table 1 , few empirical works have considered the relationship between tourism and economic development, in contrast to the numerous works from the scientific literature that have examined the relationship between tourism and economic growth. Most of the works that have empirically analyzed the relationship between tourism and economic development have determined that tourism positively influences the improved economic development in host destinations. To a lesser extent, some studies have found a bidirectional relationship between these variables (Croes, 2012 ; Kubickova et al., 2017 ; Pulido-Fernández and Cárdenas-García, 2021 ) while others have found no relationship between tourism and economic development (Chattopadhyay et al., 2022 ; Croes et al., 2021 ).

Furthermore, in empirical works relying on panel data, the results have tended to be generalized to the entire panel, suggesting that tourism improves economic development in all countries that are part of the panel. This has been the case in all of the examined works, with the exception of two studies that analyzed the panel separately (Cárdenas-García et al., 2015 ; Pulido-Fernández and Cárdenas-García, 2021 ).

Thus, it may be suggested that the use of very large country panels and, therefore, including very heterogeneous destinations, as was the case in the works of Biagi et al. ( 2017 ) using a panel of 63 countries, as well as that of Chattopadhyay et al. ( 2022 ) working with a panel of 133 countries, may lead to error, given that this relationship may only arise in certain destinations of the panel, although it is generalized to the entire panel.

This work serves to fill this gap in the literature by analyzing the panel both collectively and separately, for each of the homogenous groups of countries that have been previously identified.

The lack of relevant works on the relationship between tourism and development, and of studies using causal analyses to examine these variables based on heterogeneous panels, may lead to the creation of rash generalizations regarding the entirety of the analyzed countries. Thus, conclusions may be reached that are actually based on only specific panel units. Therefore, we believe that this study is justified.

Methodological approach

Given the objective of this study, to determine whether a causal relationship exists between tourism and socio-economic development, it is first necessary to identify the variables necessary to measure tourism activity and development level. Thus, the indicators are highly relevant, given that the choice of indicator may result in distinct results (Rosselló-Nadal and He, 2020 ; Song and Wu, 2021 ).

Table 2 details the measurement variables used in this work. Specifically, the following indicators have been used in this paper to measure tourism and economic development:

Measurement of tourist activity. In this work, we decided to consider tourism specialization, examining the number of international tourists received by a country with regard to its population size as the measurement variable.

This information on international tourists at a national level has been provided annually by the United Nations World Tourism Organization since 1995 (UNWTO, 2023 ). This variable has been relativized based on the country’s population, according to information provided by the World Bank on the residents of each country (WB, 2023 ).

Tourism specialization is considered to be the level of tourism activity, specifically, the arrival of tourists, relativized based on the resident population, which allows for comparisons to be made between countries. It accurately measures whether or not a country is specialized in this economic activity. If the variable is used in absolute values, for example, the United States receives more tourists than Malta, so based on this variable it may be that the first country is more touristic than the second. However, in reality, just the opposite happens, Malta is a country in which tourist activity is more important for its economy than it is in the United States, so the use of tourist specialization as a measurement variable classifies, correctly, both Malta as a country with high tourism specialization and to the United States as a country with low tourism specialization.

Therefore, most of the scientific literature establishes the need to use the total number of tourists relativized per capita, given that this allows for the determination of the level of tourism specialization of a tourism destination (Dritsakis, 2012 ; Tang and Abosedra, 2016 ); furthermore, this indicator has been used in works analyzing the relationship between tourism and economic development (for example, Biagi et al., 2017 ; Boonyasana and Chinnakum; 2020 ; Croes et al., 2021 ; Fahimi et al., 2018 ).

Although some works have used other variables to measure tourism, such as tourism income, exports, or tourist spending, these variables are not available for all of the countries making up the panel, so the sample would have been significantly reduced. Furthermore, the data available for these alternative variables do not come from homogeneous databases, and therefore cannot be compared.

Measurement of economic development. In this work, the Human Development Index has been used to measure development.

This information is provided by the United Nations Development Program, which has been publishing it annually at the country level since 1990 (UNDP, 2023 ).

The selection of this indicator to measure economic development is in line with other works that have defended its use to measure the impact on development level (for example, Jalil and Kamaruddin, 2018 ; Sajith and Malathi, 2020 ); this indicator has also been used in works analyzing the relationship between tourism and economic development (for example, Meyer and Meyer, 2016 ; Kubickova et al., 2017 ; Pulido-Fernández and Cárdenas-García, 2021 ).

Although some works have used other variables, such as poverty or inequality, to measure development, these variables are not available for all of the countries forming the panel. Therefore the sample would have been considerably reduced and the data available for these alternative variables do not come from homogenous databases, and therefore comparisons cannot be made.

These indicators are available for a total of 123 countries, across the globe. Thus, these countries form part of the sample analyzed in this study.

As for the time frame considered in this work, two main issues were relevant when determining this period: on the one hand, there is an initial time restriction for the analyzed series, given that information on the arrival of international tourists is only available as of 1995, the first year when this information was provided by the UNWTO. On the other hand, it was necessary to consider the effect of the Covid-19 pandemic and the resulting tourism sector crisis, which also affected the global economy as a whole. Therefore, our time series ended as of 2019, with the overall time frame including data from 1995 to 2019, a 25-year period.

Previous considerations

Caution should be taken when considering causality tests to determine the relationships between two variables, especially in cases in which large heterogeneous samples are used. This is due to the fact that generalized conclusions may be reached when, in fact, the causality is only produced by some of the subjects of the analyzed sample. This study is based on this premise. While heterogeneity in a sample is clearly a very relevant aspect, in some cases, it may lead to conclusions that are less than appropriate.

In this work, a collective causal analysis has been performed on all of the countries of the panel, which consists of 123 countries. However, given that it is a broad sample including countries having major differences in terms of size, region, development level, or tourism performance, the conclusions obtained from this analysis may lead to the generalization of certain conclusions for the entire sample set, when in fact, these relationships may only be the case for a very small portion of the sample. This has been the case in other works that have made generalized conclusions from relatively large samples in which the sample’s homogeneity regarding certain patterns was not previously verified (Badulescu et al., 2021 ; Ömer et al., 2018 ; Gedikli et al., 2022 ; Meyer and Meyer, 2016 ; Xia et al., 2021 ).

Therefore, after performing a collective analysis of the entire panel, the causal relationship between tourism and development was then determined for homogeneous groups of countries that share common patterns of tourism performance and economic development level, to analyze whether the generalized conclusions obtained in the previous section differ from those made for the individual groups. This was in line with strategies that have been used in other works that have grouped countries based on tourism performance (Min et al., 2016 ) or economic development level (Cárdenas-García et al., 2015 ), prior to engaging in causal analyses. To classify the countries into homogeneous groups based on tourism performance and development level, a previous work was used (Brida et al., 2023 ) which considered the same sample of 123 countries, relying on the same data to measure tourism and development level and the same time frame. This guarantees the coherence of the results obtained in this work.

From the entire panel of 123 countries, a total of six country groups were identified as having a similar dynamic of tourism and development, based on qualitative dynamic behavior. In addition, an “outlier” group of countries was found. These outlier countries do not fit into any of the groups (Brida et al., 2023 ). The three main groups of countries were considered, discarding three other groups due to their small size. Table 3 presents the group of countries sharing similar dynamics in terms of tourism performance and economic development level.

Applied methodology

As indicated above, this work uses the Tourist Specialization Rate (TIR) and the Human Development Index (HDI) to measure tourism and economic development, respectively. In both cases, we work with the natural logarithm (l.TIR and l.HDI) as well as the first differences between the variables (d.l.TIR and d.l.HDI), which measure the growth of these variables.

A complete panel of countries is used, consisting of 123 countries. The three main groups indicated in the previous section are also considered (the first of the groups contains 36 countries, the second contains 29 and the last group contains 43).

The Granger causality test ( 1969 ) is used to analyze the relationships between tourism specialization and development level; this test shows if one variable predicts the other, but this should not be confused with a cause-effect relationship.

In the context of panel data, different tests may be used to analyze causality. Most of these tests differ with regard to the assumptions of homogeneity of the panel unit coefficients. While the standard form of the Granger causality test for panels assumes that all of the coefficients are equal between the countries forming part of the panel, the Dumitrescu and Hurlin test (2012) considers that the coefficients are different between the countries forming part of the panel. Therefore, in this work, Granger’s causality is analyzed using the Dumitrescu and Hurlin test (2012). In this test, the null hypothesis is of no homogeneous causality; in other words, according to the null hypothesis, causality does not exist for any of the countries of the analyzed sample whereas, according to the alternative hypothesis, in which the regression model may be different in the distinct countries, causality is verified for at least some countries. The approach used by Dumitrescu and Hurlin ( 2012 ) is more flexible in its assumptions since although the coefficients of the regressions proposed in the tests are constant over time, the possibility that they may differ for each of the panel elements is accepted. This approach has more realistic assumptions, given that countries exhibit different behaviors. One relevant aspect of this type of tests is that they offer no information on which countries lead to the rejection of the lack of causality.

Given the specific characteristics of this type of tests, the presence of very heterogeneous samples may lead to inappropriate conclusions. For example, causality may be assumed for a panel of countries, when only a few of the panel’s units actually explain this relationship. Therefore, this analysis attempts to offer novel information on this issue, revealing that the conclusions obtained for the complete set of 123 countries are not necessarily the same as those obtained for each homogeneous group of countries when analyzed individually.

Given the nature of the variables considered in this work, specifically, regarding tourism, it is expected that a shock taking place in one country may be transmitted to other countries. Therefore, we first analyze the dependency between countries, since this may lead to biases (Pesaran, 2006 ). The Pesaran cross-sectional dependence test (2004) is used for the total sample and for each of the three groups individually.

First, a dependence analysis is performed for the countries of the sample, verifying the existence of dependence between the panel subjects. A cross-sectional dependence test (Pesaran, 2004 ) is used, first for the overall set of countries in the sample and second, for each of the groups of countries sharing homogeneous characteristics.

The results are presented in Table 4 , indicating that the test is statistically significant for the two variables, both for all of the countries in the sample and for each of the homogeneous country clusters, for the variables taken in logarithms as well as their first differences.

Upon rejecting the null hypothesis of non-cross-sectional dependence, it is assumed that a shock occurs in a country that may be transmitted to other countries in the sample. In fact, the lack of dependence between the variables, both tourism and development, is natural in this type of variables, given the economic cycle through the globalization of the economic activity, common regions visited by tourists, the spillover effect, etc.

Second, the stationary nature of the series is tested, given that cross-sectional dependence has been detected between the variables. First-generation tests may present certain biases in the rejection of the null hypothesis since first-generation unit root tests do not permit the inclusion of dependence between countries (Pesaran, 2007 ). On the other hand, second-generation tests permit the inclusion of dependence and heterogeneity. Therefore, for this analysis, the augmented IPS test (CIPS) proposed by Pesaran ( 2007 ) is used. This second-generation unit root test is the most appropriate for this case, given the cross-sectional dependence.

The results are presented in Table 5 , showing the statistics of the CIPS test for both the overall set of countries in the sample and in each of the homogeneous clusters of countries. The results are presented for models with 1, 2, and 3 delays, considering both the variables in the logarithm and their first differences.

As observed, the null hypothesis of unit root is not rejected for the variables in levels, but it is rejected for the first differences. This result is found in all of the cases, for both the total sample and for each of the homogeneous groups, with a significance of 1%. Therefore, the variables are stationary in their first differences, that is, the variables are integrated at order 1. Given that the causality test requires stationary variables, in this work it is used with the variation or growth rate of the variables, that is, the variable at t minus the variable at t−1.

Finally, to analyze Granger’s causality, the test by Dumitrescu and Hurlin ( 2012 ) is used. This test is used to analyze the causal relationship in both directions; that is, whether tourism contributes to economic development and whether the economic development level conditions tourism specialization. Statistics are calculated considering models with 1, 2, and 3 delays. Considering that cross-sectional dependence exists, the p-values are corrected using bootstrap techniques (making 500 replications). Given that the test requires stationary variables, primary differences of both variables were considered.

Table 6 presents the result of the Granger causality analysis using the Dumitrescu and Hurlin test (2012), considering the null hypothesis that tourism does not condition development level, either for all of the countries or for each homogeneous country cluster.

For the entire sample of countries, the results suggest that the null hypothesis of no causality from tourism to development was rejected when considering 3 delays (in other works analyzing the relationship between tourism and development, the null hypothesis was rejected with a similar level of delay: Rivera ( 2017 ) when considering 3–4 delays or Ulrich et al. ( 2018 ) when considering 3 delays). This suggests that for the entire panel, one-way causality exists whereby tourism influences economic development, demonstrating that tourism specialization contributes positively to improving the economic development of countries opting for tourism development. This is in line with the results of Meyer and Meyer ( 2016 ), Ridderstaat et al. ( 2016 ); Biagi et al. ( 2017 ); Fahimi et al. ( 2018 ); Tan et al. ( 2019 ), or Boonyasana and Chinnakum ( 2020 ).

However, the previous conclusion is very general, given that it is based on a very large sample of countries. Therefore, it may be erroneous to generalize that tourism is a tool for development. In fact, the results indicate that, when analyzing causality by homogeneous groups of countries, sharing similar dynamics in both tourism and development, the null hypothesis of no causality from tourism to development is only rejected for the group C countries, when considering three delays. Therefore, the development of generalized policies to expand tourism in order to improve the socioeconomic conditions of any destination type should consider that this relationship between tourism and economic development does not occur in all cases. Thus, it should first be determined if the countries opting for this activity have certain characteristics that will permit a positive relationship between said variables.

In other words, it may be a mistake to generalize that tourism contributes to economic development for all countries, even though a causal relationship exists for the entire panel. Instead, it should be understood that tourism permits an improvement in the level of development only in certain countries, in line with the results of Cárdenas-García et al. ( 2015 ) or Pulido-Fernández and Cárdenas-García ( 2021 ). In this specific work, this positive relationship between tourism and development only occurs in countries from group C, which are characterized by a low level of tourism specialization and a low level of development. Some works have found similar results for countries from group C. For example, Sharma et al. ( 2020 ) found the same relationship for India, while Nonthapot ( 2014 ) had similar findings for certain countries in Asia and the Pacific, which also made up group C. Some recent works have analyzed the relationship between tourism specialization and economic growth, finding similar results. This has been the case with Albaladejo et al. ( 2023 ), who found a relationship from tourism to economic growth only for countries where income is low, and the tourism sector is not yet developed.

These countries have certain limitations since even when tourism contributes to improved economic development, their low levels of tourism specialization do not allow them to reach adequate host population socioeconomic conditions. Therefore, investments in tourism are necessary there in order to increase tourism specialization levels. This increase in tourism may allow these countries to achieve development levels that are similar to other countries having better population conditions.

Therefore, in this group, consisting of 43 countries, a causal relationship exists, given that these countries are characterized by a low level of tourism specialization. However, the weakness of this activity, due to its low relevance in the country, prevents it from increasing the level of economic development. In these countries (details of these countries can be found in Table 3 , specifically, the countries included in Group C), policymakers have to develop policies to improve tourism infrastructure as a prior step to improving their levels of development.

On the other hand, in Table 7 , the results of Granger’s causal analysis based on the Dumitrescu and Hurlin test (2012) are presented, considering the null hypothesis that development level does not condition an increase in tourism, both in the overall sample set and in each of the homogeneous country clusters.

The results indicate that, for the entire country sample, the null hypothesis of no causality from development to tourism is not rejected, for any type of delay. This suggests that, for the entire panel, one-way causality does not exist, with level of development influencing the level of tourism specialization. This is in line with the results of Croes et al. ( 2021 ) in a specific analysis in Poland.

Once again, this conclusion is quite general, given that it has been based on a very broad sample of countries. Therefore, it may be erroneous to generalize that the development level does not condition tourism specialization. Past studies using a large panel of countries, such as the work of Chattopadhyay et al. ( 2022 ) analyzing panel data from 133 countries, have been generalized to all of the analyzed countries, suggesting that economic development level does not condition the arrival of tourists to the destination, although, in fact, this relationship may only exist in specific countries within the analyzed panel.

In fact, the results indicate that, when analyzing causality by homogeneous country groups sharing a similar dynamic, for both tourism and development, the null hypothesis of no causality from development to tourism is only rejected for country group A when considering 2–3 delays. Although the statistics of the test differ, when the sample’s time frame is small, as in this case, the Z-bar tilde statistic is more appropriate.

Thus, development level influences tourism growth in Group A countries, which are characterized by a high level of development and tourism specialization, in accordance with the prior results of Pulido-Fernández and Cárdenas-García ( 2021 ).

These results, suggesting that tourism is affected by economic development level, but only in the most developed countries, imply that the existence of better socioeconomic conditions in these countries, which tend to have better healthcare systems, infrastructures, levels of human resource training, and security, results in an increase in tourist arrivals to these countries. In fact, when traveling to a specific tourist destination, if this destination offers attractive factors and a higher level of economic development, an increase in tourist flows was fully expected.

In this group, consisting of 36 countries, the high development level, that is, the proper provision of socio-economic factors in their economic foundations (training, infrastructures, safety, health, etc.) has led to the attraction of a large number of tourists to their region, making their countries having high tourism specialization.

Although international organizations have recognized the importance of tourism as an instrument of economic development, based on the theoretical relationship between these two variables, few empirical studies have considered the consequences of the relationship between tourism and development.

Furthermore, some hasty generalizations have been made regarding the analysis of this relationship and the analysis of the relationship of tourism with other economic variables. Oftentimes, conclusions have been based on heterogeneous panels containing large numbers of subjects. This may lead to erroneous results interpretation, basing these results on the entire panel when, in fact, they only result from specific panel units.

Given this gap in the scientific literature, this work attempts to analyze the relationship between tourism and economic development, considering the panel data in a complete and separate manner for each of the previously identified country groups.

The results highlight the need to adopt economic policies that consider the uniqueness of each of the countries that use tourism as an instrument to improve their socioeconomic conditions, given that the results differ according to the specific characteristics of the analyzed country groups.

This work provides precise results regarding the need for policymakers to develop public policies to ensure that tourism contributes to the improvement of economic development, based on the category of the country using this economic activity to achieve greater levels of economic development.

Specifically, this work has determined that tourism contributes to economic development, but only in countries that previously had a lower level of tourism specialization and were less developed. This highlights the need to invest in tourism to attract more tourists to these countries to increase their economic development levels. Countries having major natural attraction resources or factors, such as the Dominican Republic, Egypt, India, Morocco, and Vietnam, need to improve their positioning in the international markets in order to attain a higher level of tourism specialization, which will lead to improved development levels.

Furthermore, the results of this study suggest that a greater past economic development level of a country will help attract more tourists to these countries, highlighting the need to invest in security, infrastructures, and health in order for these destinations to be considered attractive and increase tourist arrival. In fact, given their increased levels of development, countries such as Spain, Greece, Italy, Qatar, and Uruguay have become attractive to tourists, with soaring numbers of visitors and high levels of tourism specialization.

Therefore, the analysis of the relationship between tourism and economic development should focus on the differentiated treatment of countries in terms of their specific characteristics, since working with panel data with large samples and heterogenous characteristics may lead to incorrect results generalizations to all of the analyzed destinations, even though the obtained relationship in fact only takes place in certain countries of the sample.

Conclusions and policy implications

Within this context, the objective of this study is twofold: on the one hand, it aims to contribute to the lack of empirical works analyzing the causal relationship between tourism and economic development using Granger’s causality analysis for a broad sample of countries from across the globe. On the other hand, it critically examines the use of causality analysis in heterogeneous samples, by verifying that the results for the panel set differ from the results obtained when analyzing homogeneous groups in terms of tourism specialization and development level.

In fact, upon analyzing the causal relationship from tourism to development, and the causal relationship from development to tourism, the results from the entire panel, consisting of 123 countries, differ from those obtained when analyzing causality by homogeneous country groups, in terms of tourism specialization and economic development dynamics of these countries.

On the one hand, a one-way causality relationship is found to exist, whereby tourism influences economic development for the entire sample of countries, although this conclusion cannot be generalized, since this relationship is only explained by countries belonging to Group C (countries with low levels of tourism specialization and low development levels). This indicates that, although a causal relationship exists by which tourism contributes to economic development in these countries, the low level of tourism specialization does not permit growth to appropriate development levels.

The existence of a causal relationship whereby the increase in tourism precedes the improvement of economic development in this group of countries having a low level of tourism specialization and economic development, suggests the appropriateness of the focus by distinct international organizations, such as the United Nations Conference on Trade and Development or the United Nations Economic Commission for Africa, on funding tourism projects (through the provision of tourism infrastructure, the stimulation of tourism supply, or positioning in international markets) in countries with low economic development levels. This work has demonstrated that investment in tourism results in the attracting of a greater flow of tourists, which will contribute to improved economic development levels.

Therefore, both international organizations financing projects and public administrations in these countries should increase the funding of projects linked to tourism development, in order to increase the flow of tourism to these destinations. This, given that an increase in tourism specialization suggests an increased level of development due to the demonstrated existence of a one-way causal relationship from tourism to development in these countries, many of which form part of the group of so-called “least developed” countries. However, according to the results obtained in this work, this relationship is not instantaneous, but rather, a certain delay exists in order for economic development to improve as a result of the increase in tourism. Therefore, public managers must adopt a medium and long-term vision of tourism activity as an instrument of development, moving away from short-term policies seeking immediate results, since this link only occurs over a broad time horizon.

On the other hand, this study reveals that a one-way causal relationship does not exist, by which the level of development influences tourism specialization level for the entire sample of countries. However, this conclusion, once again, cannot be generalized given that in countries belonging to Group A (countries with a high development level and a high tourism specialization level), a high level of economic development determines a higher level of tourism specialization. This is because the socio-economic structure of these countries (infrastructures, training or education, health, safety, etc.) permits their shaping as attractive tourist destinations, thereby increasing the number of tourists visiting them.

Therefore, investments made by public administrations to improve these factors in other countries that currently do not display this causal relationship implies the creation of the necessary foundations to increase their tourism specialization and, therefore, as shown in other works, tourism growth will permit economic growth, with all of the associated benefits for these countries.

Therefore, to attract tourist flows, it is not only important for a country to have attractive factors or resources, but also to have an adequate level of prior development. In other words, the tourists should perceive an adequate level of security in the destination; they should be able to use different infrastructures such as roads, airports, or the Internet; and they should receive suitable services at the destination from personnel having an appropriate level of training. The most developed countries, which are the destinations having the greatest endowment of these resources, are the ones that currently receive the most tourist flows thanks to the existence of these factors.

Therefore, less developed countries that are committed to tourism as an instrument to improve economic development should first commit to the provision of these resources if they hope to increase tourist flows. If this increase in tourism takes place in these countries, their economic development levels have been demonstrated to improve. However, since these countries are characterized by low levels of resources, cooperation by organizations financing the necessary investments is key to providing them with these resources.

Thus, a critical perspective is necessary when considering the relationship between tourism and economic development based on global causal analysis using heterogeneous samples with numerous subjects. As in this case, carrying out analyses on homogeneous groups may offer interesting results for policymakers attempting to suitably manage population development improvements due to tourism growth and tourism increases resulting from higher development levels.

One limitation of this work is its national scope since evidence suggests that tourism is a regional and local activity. Therefore, it may be interesting to apply this same approach on a regional level, using previously identified homogeneous groups.

And given that the existence of a causal relationship (in either direction) between tourism and development has only been determined for a specific set of countries, future works could consider other country-specific factors that may determine this causal relationship, in addition to the dynamics of tourism specialization and development level.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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

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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.

figure 1

Plot of CUSUM

figure 2

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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  • Economic growth
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Path dependence in pro-poor tourism

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  • Volume 24 , pages 973–993, ( 2022 )

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Tourism is a crucial pathway to global poverty reduction and sustainable development. Pro-poor tourism (PPT), which is conducive to the development of the poor, can bring social, environmental, cultural and economic benefits to the poor. The path dependence theory affirms that past choices determine future decisions. Once the path dependence results in a lock-in effect in pro-poor tourism, it is likely to affect pro-poor tourism performance. Here, we quantitatively analyze the characteristics and causes of path dependence in pro-poor tourism in China and investigate how path dependence affects pro-poor tourism performance. We find that the sunk cost (factor input) of pro-poor tourism is a major cause of path dependence. Path dependence in pro-poor tourism takes various forms: cognitive path dependence, institutional path dependence, technological path dependence and economic path dependence. Among these, cognitive dependence and institutional path dependence negatively affect pro-poor tourism performance, whereas technological dependence and economic path dependence positively affect performance. Simultaneously, the factor input of PPT affects PPT performance through the four dimensions of path dependence. The path dependence in PPT mediates the effect of factor input on PPT performance. Our findings reveal the characteristics and regularities of path dependence in the pro-poor tourism strategy implemented by the Chinese government. Findings of this study are important for policymakers that can assist in the implementation of PPT strategies and help improve PPT performance.

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Acknowledgements

The authors want to thank the English editor from Edtage who help us to modify English language problems in this article. Also, we thank postgraduate student Peiliang Yu and PhD student Kehan Shi in the Business School of Guangxi University. They helped to collect data and information in this article. Finally, we appreciate the grant (No. 16XJL006) from the China National Social Science Fund.

This study was funded by China National Social Science Fund (No. 16XJL006).

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Liu, Y., Yu, J. Path dependence in pro-poor tourism. Environ Dev Sustain 24 , 973–993 (2022). https://doi.org/10.1007/s10668-021-01478-x

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PA Department of Community & Economic Development

New Report Reveals that Tourism Generates Over $76 Billion for Pennsylvania’s Economy and Supports 485,000 Jobs

  • March 13, 2024

Governor Shapiro is supporting the nearly 500,000 Pennsylvanians who are a part of the travel and tourism industry by calling for a $15 million increase in funding for tourism in his 2024-25 budget proposal

This major investment in tourism and recreation asset development will drive economic growth, leading to new businesses and jobs and a stronger economy for all Pennsylvanians

Erie, PA – A new report from the Pennsylvania Tourism Office shows the tourism industry in the Commonwealth generated $76.7 billion in economic impact, supported 486,871 jobs, contributed $4.7 billion in state and local taxes, and welcomed 192.4 million visitors in 2022.

The 2022 Economic Impact of Travel and Tourism report provides state, regional, and county level estimates that demonstrate the vital importance of the travel industry to Pennsylvania’s economy. The results of the report were highlighted yesterday by Department of Community and Economic Development Deputy Secretary of Tourism Carrie Fischer Lepore at Visit Erie’s Annual Meeting in Erie, PA.

Governor Josh Shapiro understands that the travel and tourism industry touches every Pennsylvanian by creating economic opportunities while increasing the quality of life. He is committed to boosting the industry to create good jobs, strengthen businesses, and attract people to call Pennsylvania home.

Key 2022 results of the report include:

  • 192.4 million visitors , an increase of more than 12 million from 2021
  • $76.7 billion in total economic impact
  • $4.7 billion in state and local taxes
  • 486,871 jobs supported , which equates to 1-in-16 jobs in the state
  • A $7.5 billion increase in direct visitor spending to reach $45.4 billion – including hotels, restaurants, retailers and other tourism related businesses.

“This report clearly shows that tourism is a significant economic driver in Pennsylvania that injects billions of dollars into our economy and helps to fund transportation, infrastructure, education, public safety programs and other vital services provided by the Commonwealth,” said Fischer Lepore. “Each household in Pennsylvania would need to pay an additional $880 in taxes to replace the tax dollars generated by the tourism industry which were received by state and local governments in 2022. The Shapiro Administration realizes the crucial role that tourism plays in Pennsylvania’s economy, as evidenced by the proposed $15 million increase in funding in the 2024-25 budget proposal.”

Visitor spending — which supports jobs, income, and business sales — generated $9.6 billion in government revenues. State and local taxes alone tallied $4.65 billion in 2022, an increase of $458 million from 2021.

Overnight visitor spending increased by $4.8 billion, with more than 66 million trips resulting in $28 billion in spending. Overnight visitors spent $419 per person, a $31 increase from 2021; while spending on day trips grew to $17.3 billion.

The Economic Impact of Travel and Tourism report is compiled at the Pennsylvania Tourism Office at DCED with information provide by Tourism Economics , an Oxford Economics Company based in Wayne, with data supplied by Longwoods International and STR .

As one of the largest industries in Pennsylvania, Governor Shapiro recognizes the key role tourism plays in the Commonwealth’s economy. Gov. Shapiro’s 2024-25 budget calls for a $15 million increase in funding for tourism. For more information on how the Governor’s proposed budget will create opportunity for all Pennsylvanians, visit Governor Josh Shapiro’s Budget website .

The Pennsylvania Tourism Office, housed within the Department of Community and Economic Development, is dedicated to inspiring travel to Pennsylvania. From iconic attractions to hidden gems, tourism in Pennsylvania helps support the state’s economy and creates jobs for local businesses — all while improving residents’ quality of life.

Need more PA happy travels? Become a fan on Facebook , follow us on X (Twitter) , check out photos on Instagram , share pins on Pinterest , watch us on YouTube , or listen to us on Spotify .

For more information about the Department of Community and Economic Development, visit the DCED website , and be sure to stay up-to-date with all of our agency news on Facebook , X , and LinkedIn .

MEDIA CONTACT: Governor’s Office, [email protected] , 717.783.1116 Penny Ickes, DCED, [email protected]

  • Governor Josh Shapiro tourism

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