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The purpose of this paper is to investigate the tourism-led growth hypothesis in Laos.

The authors test the tourism-led growth hypothesis using autoregressive distributed lag (ARDL) cointegration estimation (Pesaran et al., 2001) and Granger causality tests.

The results of this paper show that when tourism is forcing variable, there is no long-run relationship between tourism development and economic growth. The Granger causality test demonstrates that there is a uni-directional causality running from economic growth in tourism.

The empirical results and policy recommendation may be useful for other small developing countries.

This study is the first study to investigate the relationship between tourism development and growth in Laos, using a relatively new econometric approach – ARDL bound testing.

The aim of this chapter is to examine the role of real exchange rates in the relationship between tourist arrival and economic growth in Malaysia over the period of 2000–2018. We disaggregate Malaysian tourists into six geographical regions, namely Asia, Singapore, Europe, Pacific region, Americas, and Africa. Using a non-linear autoregressive distributed lag model, we find that the appreciation of real exchange rates with positive growth of economy plays a prominent role in influencing international tourist arrivals from Singapore, other Asian countries, Pacific region, Europe, and Americas. Our study suggests that real appreciation is important in providing some insights into the effectiveness of growth-led-tourism policies. In line with this, some implications are provided at the end of this chapter.

Tourism–economy relationship in India has been studied extensively in the past literature using a single equation approach. However, the present paper diverted from this trend and examined the tourism–economy relationship using the specific to general modelling approach over the 1990–2018 time period. The study also accounts for the influence of merchandise trade, capital formation, foreign investment inflows and inflation on economic growth to achieve the robustness of the coefficient estimates.

To achieve the objective, the study utilised a specific to general modelling strategy. First, the regression equation includes only three core variables: gross domestic product (GDP), international tourist receipts and international tourist expenditures. Next, the authors include other control variables in the regression equation one by one, leading us to test five model types for investigating the cointegration among the variables. As for the estimation technique, the authors employed autoregressive distributed lag (ARDL) approach.

The paper's findings highlight that tourism receipts and expenditures exert a positively significant impact on economic growth. Moreover, including the additional independent variables does not substantially change the tourism and economic growth relationship. The existence of one-way causality from tourism expenditures to economic growth supports the tourism-led growth hypothesis. These findings highlight the rationale for intervention by the government and policymakers to promote tourism potential and facilities to accelerate the overall growth performance of the country. While the existence of one-way causal effect from economic growth to tourism revenues supports the growth-led tourism development hypothesis, implying that economic expansion is necessary for tourism development.

This research article tried to present a comprehensive picture of India's tourism–economy relationship. However, the present study is organised as an aggregate economy-level analysis. It assumed that the aggregate tourism sector is homogenous. However, different tourism sectors exert different levels of influence on the economy. The authors expect future research can take the disaggregated analysis of the tourism–economy relationship.

This study provides valuable insights into the tourism-led growth hypothesis in India. The study highlights comprehensive intervention by the government and policymakers for accelerating tourism development to invigorate the overall growth performance of the country over the long run. The principal recommendation emerging from the present research is that the tourism growth potential can be depended upon to stimulate the economic performance of the Indian economy.

The present study diverted from the previous empirical studies by following a specific to general modelling strategy. First, the regression model includes only three core variables such as economic growth, tourism receipts and tourism expenditure. Next, the authors include other control variables in the regression equation one by one, leading us to test five model types for investigating the cointegrating relationship among the variables. GDP growth rate is used as a dependent variable in all five specifications. The idea is to expand the model to capture every feature of the data generating process.

The purpose of this paper is to explore the long-run relationship and causality between economic activity and inbound tourism in the context of the Indonesian economy with a new quantitative methodology.

This research applies a new modified bounds testing approach of Pesaran et al. (2001) by Kripfganz and Schneider (2018) with the period of observation from 1974 to 2017.

The results suggest that there is a unidirectional causality from economic activity to inbound tourism.

This research applies the linear autoregressive distributed lag (ARDL) model and only uses bivariate variables to examine the existence of the tourism-led growth hypothesis. Further studies for the Indonesian case may apply a nonlinear ARDL model. Also, the addition of other socio-economic variables, especially those related to domestic tourism activity, can be applied to improve the model.

This work will provide an alternative quantitative methodology for scholars in studying the relationship between tourism and economic variables.

The findings in this research can complement touristic-public policy decision, and the methodology may be important for knowledge transfer.

This is the first quantitative study to measure tourism-led growth hypothesis in Indonesia by using the latest modified bounds testing approach.

This study aims to examine the relationship between tourism development and economic growth while considering exports simultaneously. Governments in many countries have been developing and deploying strategies to attract tourism receipts as a means for economic growth. However, assessing the potential impact of tourism on economic growth among large economies is still in its infancy.

Using a vector error correction model framework, this study examines the relationship among exports, gross domestic product (GDP) and tourism receipts (including international tourism receipts and domestic tourism receipts in two separate models) with macro data that covers two recent decades (1994-2013) in China.

The empirical findings confirm the existence of a long-term equilibrium relationship in each of these two tri-variate models. The empirical findings reveal that (1) both tourism-led-growth and export-led-growth hypotheses are supported, (2) the growth rate of tourism receipts exhibit a higher relevance with GDP growth than export growth and (3) the growth rate of international tourism shows a higher relevance with GDP growth than domestic tourism growth.

Using macroeconomic data collected by the Chinese government, the current study employs an advanced econometric methodology to explore the potential benefits of tourism on economic growth in China.

The purpose of this paper is to study the direction of the causality between tourism development and economic growth in Lebanon between 1995 and 2013, after taking into consideration terrorist incidents and their intensities. These are considered as exogenous shocks that affect tourism development and economic growth instantaneously and with a lag.

To reach the objectives, the authors estimate a vector auto regressive model with exogenous variables, applying a series of unit root tests with and without structural breaks and the Granger causality test.

The findings suggest a positive unidirectional causality running from tourism development to economic growth in the short run. Thus, the authors find evidence for the tourism-led growth hypothesis (TLGH) in Lebanon despite the exposure of the country to frequent terrorist incidents. The impulse response functions reveal that tourism development (economic growth) responds positively to a positive shock to economic growth (tourism development).

The findings call for Lebanese policy makers aiming at promoting growth to design policies that encourage tourism, such as implementing tourism marketing policies and building the needed tourism infrastructure. Such policies will have positive but transitory effects on economic growth. The findings may also be useful for regional representatives of intergovernmental organizations and the offices of statistics of United Nations World Tourism Organization and the World Bank to better understand the tourism industry in Lebanon and similar countries suffering from instabilities.

This paper contributes to the existing literature in three points: despite the importance of the tourism industry to the Lebanese economy, this topic did not receive careful attention in the literature; it takes into consideration the presence of structural breaks and possible nonlinearities in the number of tourist arrivals; and it investigates the TLGH after accounting for instability in the country.

This study empirically examines the moderating role of geopolitical risk on the tourism–economic growth nexus by applying a recent geopolitical risk indicator developed by Caldara and Iacoviello (2022) in a cross-country panel data growth model context for a sample of 24 countries.

A Dummy Variable Least Squares panel data model, nonparametric covariance matrix estimator and SYS-GMM estimation techniques are employed for the analysis. The authors capture the GPR moderating effect by disaggregating the cross-country sample according to low versus high country GPR score and through a GPR interaction coefficient. Several controls are included in the models such as gross fixed capital formation and—consistent with Barro (1990)—government consumption. Trade openness is used to account for the export-led growth effect. In line with neoclassical growth theory (e.g. Barro, 1991), the authors also include the real interest rate, to account for policy makers' commitment to macroeconomic stability, financial depth, as a proxy for financial development, population growth and the level of secondary school education. The authors also control for unobserved country-specific and time-invariant effects.

The research finds that the interaction term of geopolitical risk significantly contributes to the predictive ability of the regression and provides empirical evidence that confirms that only in low geopolitical risk countries international tourism positively and significantly contributes to economic growth. Important theoretical and policy implications flow from these findings.

The study not only contributes to advancing academic knowledge on the tourism–growth nexus, it also has impact beyond academia. Many countries have in the past pursued and many continue to pursue, tourism specialization and/or tourism-led growth strategies based on the theoretically well-established and empirically validated positive link between inbound tourism and economic growth. The findings alert policy makers in such countries to the significant moderating role that geopolitical risk plays in affecting the above-mentioned relationship and to the importance of prioritizing geopolitical stability as a policy precursor for the successful implementation of such strategies.

Although it is a widely accepted fact that climate change can negatively impact on tourism demand and affect the economies at the socio-economic level, empirical studies on the climate change tourism development nexus has been quite scant, especially for the case of island economies that are heavily dependent on tourism. This study aims to supplement the literature on climate change and tourism by empirically assessing the relationship between climate change and tourist arrivals for the case of 18 small island developing states over the period from 1989 to 2016.

This paper uses dynamic panel data techniques, namely, a panel vector autoregressive framework, which accounts for dynamic and endogeneity issues.

The results from the analysis confirm the existence of a significant relationship between climate change and tourism demand in both the long-run and short run. Further analysis shows a bi-directional causality between climatic change and tourism demand while the study also confirms the tourism led growth hypothesis.

This research supplements the literature on the tourism-environment link, especially for tourism dependent island economies.

Results from this study are important to policymakers who should spare no effort to mitigate the effect of adverse climatic change in the context of tourism development.

This study is built on a unique data set for a sample of island economies and interestingly adopts dynamic panel data analysis to account for dynamics and endogenity in the climate change-tourism development nexus.

Based on big data analytical and statistical techniques, this study aims to examine tourists’ shopping experiences at department stores and street markets in Phuket.

A Naïve Bayes machine learning algorithm was used to identify the most frequently used terms in TripAdvisor reviews of both department stores and street markets contributed by the same pool of 729 tourists.

A total of 18 out of 62 terms used were common in reviews of both shopping settings. However, the study found significant differences in the mean use of the 18 common terms and the likelihood of those terms being used in overall positive reviews.

The study’s findings indicate differences in tourist shopping experiences at department stores and street markets. Several concrete recommendations are made, including a greater focus on the linkage to the national characteristic of street markets, and particularly the quality of local fruit, to enhance the tourist shopping experience.

Understanding the differences between shopping malls and street markets from the tourist’s perspective would further enhance the coexistence of shopping malls and street markets in tourism-led growth cities. As such, using reviews of both shopping malls and street markets from an identical pool of tourists, the present study will analyse and compare tourists’ actual shopping experiences, thereby addressing this gap in the research canon via integrated statistical and big data analysis techniques.

The purpose of this paper is to verifying the economic resilience of islands and, in particular, the role of the tourism sector in the reaction to the most recent economic crisis. The analysis concerns insular contexts, such as the greater island regions in the Mediterranean basin.

Static and dynamic panel data techniques are used for a sample of 13 island economies over a period of 16 years.

Results show that the growth factors for regional islands are similar to the ones usually considered for other regions, but the tourism-led growth hypothesis is highly supported. Tourism demand more than supply plays a role together with accessibility. The crisis has reduced the importance of tourism supply, while tourism demand and accessibility have remained crucial for growth together with other traditional engines of growth.

To the best of authors’ knowledge, none of the current works has considered territorial determinants and tourism indicators inside the same framework analyzing growth in island economies by considering the changes occurred during the crisis explicitly.