The dynamic impacts of renewable energy and tourism investments on international tourism: Evidence from the G20 countries

Lu, Zhou; Gozgor, Giray; Lau, Chi Keung; Paramati, Sudharshan Reddy Article The dynamic impacts of renewable energy and tourism investments on international tourism: Evidence from the G20 countries Journal of Business Economics and Management (JBEM) Provided in Cooperation with: Vilnius Gediminas Technical University (VILNIUS TECH) Suggested Citation: Lu, Zhou; Gozgor, Giray; Lau, Chi Keung; Paramati, Sudharshan Reddy (2019) : The dynamic impacts of renewable energy and tourism investments on international tourism: Evidence from the G20 countries, Journal of Business Economics and Management (JBEM), ISSN 2029-4433, Vilnius Gediminas Technical University, Vilnius, Vol. 20, Iss. 6, pp. 1102-1120, https://doi.org/10.3846/jbem.2019.10181 This Version is available at: https://hdl.handle.net/10419/317368 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ *Corresponding author. E-mail: luzho[email protected]du.cn Journal of Business Economics and Management ISSN 1611-1699 / eISSN 2029-4433 2019 Volume 20 Issue 6: 1102–1120 https://doi.org/10.3846/jbem.2019.10181 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. © 2019 The Author(s). Published by VGTU Press THE DYNAMIC IMPACTS OF RENEWABLE ENERGY AND TOURISM INVESTMENTS ON INTERNATIONAL TOURISM: EVIDENCE FROM THE G20 COUNTRIES Zhou LU 1*, Giray GOZGOR2, Chi Keung Marco LAU3, Sudharshan Reddy PARAMATI4 1Tianjin University of Commerce, Tianjin, China 2Istanbul Medeniyet University, Istanbul, Turkey 3Department of Accountancy, Finance and Economics, University of Huddersfield, the United Kingdom 4School of Business, University of Dundee, Dundee, the United Kingdom Received 31 July 2018; accepted 15 April 2019 Abstract. This paper investigates the effects of the renewable energy consumption and the tourism investments along with the per capita gross domestic product (GDP), the real effective exchange rate, and trade openness on both tourism revenues (total tourism contribution to GDP) and international tourist arrivals in the sample of the G20 members. The annual data from 1995 to 2015 and the panel econometric techniques are utilized to achieve the objectives of the current paper. The results for the long-run elasticities from the panel fully modified ordinary least squares (FMOLS) estimations suggest that the renewable energy uses and tourism investments have a considerable positive impact on both the tourism revenues and the tourist arrivals. Given these results, it is argued that promoting both renewable energy and tourism investments should be considered as the major driving forces of tourism development in the G20 countries. Given these arguments, policymakers should initiate more of sustainable tourism development policies, which may assist those countries to expand the tourism industry further. Keywords: tourism development, international tourist arrivals, tourism investments, renewable energy, panel data estimation techniques. JEL Classification: Z32, Q42, C32. Introduction The tourism industry has significantly grown in both emerging and advanced economies during the last few decades. Thanks to the decline of the communication and the transportation costs, international tourist arrivals, across the globe, have increased from 278 million in 1980 to 1.2 billion in 2015 (the World Tourism Organization [UNWTO], 2017). In addiCopyright © 2019 The Author(s). Published by VGTU Press This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Journal of Business Economics and Management, 2019, 20(6): 1102–1120 1103 tion, international tourism generated $1.26 trillion in earnings and 10% of the world’s gross domestic product (GDP) in 2015 (UNWTO, 2017). Further, it is well argued in the literature that the tourism industry has a direct and positive impact on economic growth by enhancing the production level. Overall, the development of the tourism industry is considered an engine of economic growth in both emerging and advanced economies. This approach is known as the “tourism-led growth” hypothesis and several papers have emphasized that tourism is a key sector of the economy and their findings have illustrated the positive effects of tourism on economic growth (see e.g., Dwyer, Forsyth, & Spurr, 2004; Lim, 1997; Oh, 2005; Song, Dwyer, Li, & Cao, 2012). However, the above-mentioned significant development of the tourism industry is related to a hike in energy demand, which can cause growth in the level of CO2 emissions (Gössling & Peeters, 2015). Energy consumption in tourism consists of three main components: transportation, accommodation, and other activities. Indeed, tourism activities require a significant amount of energy consumption, which is mostly based on fossil fuels. Given that fossil fuels are the main source of CO2 emissions, the first theoretical underpinning is that tourism activities can lead to a higher level of energy consumption and CO2 emissions. A number of empirical papers (e.g. Scott, Peeters, & Gössling, 2010) have confirmed this theoretical expectation. Given that environmental degradation has been considered as the main reason for climate change and global warming, a number of international institutions and organizations have been raising the issue of global warming due to the high-level consumption of fossil fuel energy and raising CO2 emission levels across the globe (Hoogendoorn & Fitchett, 2018)1. The second theoretical underpinning is if the energy requirement of tourism activities comes from renewable energy consumption, then this can suppress the level of CO2 emissions. However, there could be a reverse causal relationship; i.e. CO2 emissions and energy consumption can drive tourism indicators. For instance, a higher level of fossil fuel consumption and a higher level of CO2 emissions may adversely affect the growth of the tourism industry. Therefore, it is very important to understand the dynamic role of whether renewable energy consumption plays a role in tourism development. In addition to that, the previous studies have failed to address the nexus between renewable energy uses and tourism development. At this stage, the effects of renewable energy on tourism development are three folds: the “direct effect”, the “sustainability effect”, and the “savings effect” (Irsag, Puksec, & Duic, 2012; Otgaar, 2012; Shi et al., 2013). The first effect can be defined as the “direct effect” i.e. renewable energy can create a less-polluting environment in destination countries that can attract more tourists across the world. According to this effect, renewable energy has not only decreased the dependency on fossil fuel energy or enhancing environmental quality, but also increased the number of visitors in specific areas. At this stage, the linkage between renewable energy and tourism introduces an attractive element of tourism by implementing new technologies (power plants) (Otgaar, 2012). It is important to note that the investments in the tourism sector can 1 A recent study, by Mardani, Streimikiene, Cavallaro, Loganathan, and Khoshnoudi (2019), provides a very comprehensive literature review on the nexus between economic growth and CO2 emissions. The significance of this study is that it provides detailed review on 175 of research papers covering the period from 1995 to 2017. Therefore, it is a comprehensive literature review paper. 1104 Z. Lu et al. The dynamic impacts of renewable energy and tourism investments on international ... simultaneously achieve two objectives, which is, improving the tourism-related infrastructure and enhancing environmental quality by investing in renewable energy projects. Therefore, increasing investments in the tourism industry can help to build hotels, restaurants, and other infrastructure such as, energy efficiency technologies, solar energy, etc. that adds value to improve the environmental quality and all these factors positively affect the growth of the tourism industry. For this purpose, the current paper aims to analyse the effect of tourism investments on tourism development in the G20 countries using various panel data estimation techniques. The second channel can be defined as the “sustainability effect”; i.e. renewable energy requires an application of new technologies, and this can create a long run (stable) relationship between energy demand and tourism development, which is significantly related to the sustainability of tourism development (Irsag et al., 2012). The third channel of renewable energy on tourism development can be defined as the “savings effect” (Shi et al., 2013). Indeed, several papers have analysed the impact of the application of new technologies of renewable energy sources on energy cost savings opportunities in tourism. Furthermore, they have emphasized the positive and the direct environmental effect (energy cost saving effect) of the applications of renewable energy sources (Irsag et al., 2012; Michalena, Hills, & Amat, 2009; Shi et al., 2013; Yang, Li, Zheng, & Zhang, 2008). All of these issues make it interesting to analyse the relationship between renewable energy and tourism activities, which is the subject of the current paper. Given that, the current paper aims to analyse the effect of renewable energy on tourism development by considering other potential determinants, such as the per capita GDP, the level of trade openness, and the real effective exchange rates. Indeed, environmental degradation can affect tourism and specifically, and can reduce the tourism activities and tourism revenue. Therefore, it is analysed whether the less-polluting countries (i.e. higher consumption of renewable energy) attract more tourists across the globe, and this is the main argument in the current paper. Given that, it is aimed to analyse to what extent a cleaner environment (the indication of renewable energy consumption) promotes tourism development (in terms of tourism revenue and tourist arrivals) in the sample of the G20 countries for the period from 1995 to 2015. In addition, it is further built the analysis based on the role of tourism investment (total investments in the travel and tourism sector) on the tourism development. Therefore, to achieve the objectives, the study employs various robust panel econometric techniques. More specifically, the paper applies the panel unit root tests to explore the order of integration of the variables and the panel cointegration test is employed to identify the long-run association among the considered models. The paper also applies the panel FMOLS method and heterogeneous panel non-causality test to examine the long-run estimates and the short-run causalities, respectively. The novelty of this paper is that it is the first of its kind to explore the effects of renewable energy and tourism investments on tourism development in a sample of the G20 nations. Further, it also uses the most recent available data set and robust panel econometric framework for the empirical analyses. Given that, our study provides long-run estimates and short-run causalities among the selected variables. Our results established that the growth in renewable energy uses and tourism investments play an important role in promoting tourism Journal of Business Economics and Management, 2019, 20(6): 1102–1120 1105 development in the G20 nations. Hence, we argue that higher renewable energy leads to low level of carbon emissions, while higher tourism investments assist the tourism companies to build new infrastructure facilities, which all play a substantial role in the promotion of tourism development. These findings indicate that the policy makers of the G20 nations should further strengthen the policies that assist these economies to reduce the use of fossil fuel and attract higher tourism investments. The detailed policy implications and contributions are discussed in the results section. The remainder of the paper is organised as follows. Section 1 reviews the previous literature on the relationships between international tourism and energy variables as well as the role of energy and tourism investments as drivers of international tourism. Section 2 explains the nature of the empirical model, the data, and the econometric methodology. Section 3 provides the empirical results and implements various robustness checks for the validity of the benchmark findings. Section 4 discusses the findings in detail and potential policy implications. Finally, last section provides the conclusion. 1. Literature review 1.1. The relationship between international tourism and energy variables The first theoretical expectation is that tourism activities lead to a higher level of energy consumption and CO2 emissions. This hypothesis has been confirmed by the findings of the empirical papers (e.g. Gössling, 2002; Gössling et al., 2005). For example, the analysis of Gössling (2002) in 2001 demonstrates that tourism-related activities can negatively affect the environment and the role of energy use is particularly important across the globe. The findings indicate that air travel has the greatest impact on pollution. Likewise, Gössling et al. (2005) implement the empirical exercises based on the data for Australia, Canada, Finland, New Zealand, and the United States (U.S.) in 2002, and they indicate the significant carbon dioxide emissions due to the tourism-related activities. Similarly, using the impulse-response analysis and the variance decompositions, Katircioglu (2014) demonstrates that tourism development is positively related to both the energy consumption and the level of carbon dioxide emissions in Turkey for the period from 1960 to 2010. Considering the bottom-up approach, Tang, Shang, Shi, Liu, and Bi (2014) find that the development of the tourism industry leads to a hike in the level of CO2 emissions in China for the period from 1990 to 2012. Using the data on international tourist hotels, Tsai, Lin, Hwang, and Huang (2014) show that the development of the tourism industry is positively related to the energy consumption and the level of CO2 emissions in Taiwan2. At this stage, environmental degradation is considered to be the main reason for climate change and global warming, especially during the last two decades. The second theoretical underpinning is if the energy requirement of tourism activities comes from clean energy plants (the renewable energy consumption) then it plays an important role in minimizing the adverse effect of the tourism industry on the environment by reducing fossil fuel consumption and CO2 emis2 Samut (2017) and Yazdani-Chamzini, Fouladgar, Zavadskas, and Moini (2013) highlight the significance of renewable energy and propose an alternative model for the renewable energy. 1106 Z. Lu et al. The dynamic impacts of renewable energy and tourism investments on international ... sion growth. According to Scott (2011), although the sustainability of tourism development requires a significant energy use, it does not necessarily cause a hike in CO2 emissions (even it can suppress the level of CO2 emissions by implementing more clean energy plants and technology). Paramati, Alam, and Chen (2017) examine the effect of tourism development on CO2 emissions across the panels of developed and developing economies. Their findings show that the tourism growth leads to further environmental degradation across the economies. In another study, Paramati, Shahbaz, and Alam (2017) suggest that the tourism development has a varying impact on the environment. More specifically, authors indicate that the tourism has a positive impact on CO2 emissions in Eastern European Union (EU), while it has a negative effect in Western EU countries. Overall, this branch of the literature illustrates that there is a causal relationship that runs from tourism to CO2 emissions and energy consumption. The effects of the tourism development on CO2 emissions and energy consumption is statistically significant; however, their nature of the association varies among the countries. 1.2. Drivers of international tourism: the role of energy and tourism investments There could also be a reverse causal relationship; i.e. (renewable) energy consumption can drive international tourism indicators. The current paper aims to test a hypothesis on whether renewable energy and tourism investments are the potential drivers of international tourism. The main idea of the related hypothesis comes from the “direct”, the “sustainability”, and the “savings” effects that have been discussed in the introduction section. At this point, a number of researchers have also investigated the effect of environment on tourism. For example, Bode, Hapke, and Zisler (2003) indicate that increasing level of greenhouse gases is reflected in climate change, and thus it negatively affects the tourism industry. According to their findings, holiday facilities should be supplied with different sources of energy (e.g. solar and wind energy), which releases almost no greenhouse gases. In short, they suggest that the level of CO2 emissions (as the main source of greenhouse gas emissions) should be decreased for ensuring the sustainability of tourism development. Similarly, Shi et al. (2013) indicate that not only solar and wind energy sources, but also the energy from the waste biomass (green waste) can be used for promoting tourism attractions. Their estimations for 385 tourist attractions in 16 cities of the Yangtze River Delta of China indicate that there is a positive development in the region’s tourism industry as the energy from the green waste increases. In short, Liu et al. (2011) and Shi et al. (2013) document that renewable energy sources are positively related to the tourism industry development in the regions of China. A recent study by Paramati, Alam and Lau (2018) investigate the impact of tourism investments on tourism development and CO2 emissions in a sample of 28 EU countries. Authors utilize annual data from 1990 to 2013 and employ several robust panel econometric techniques. Their results confirm that tourism investments have positive and negative effects on tourism development and CO2 emissions in the EU nations. This implies that the growth in tourism investments work in favour of sustainable tourism development in the EU countries. Similarly, Alam and Paramati (2017) examine the effect of tourism investments on tourism development and CO2 emissions in a sample of 10 major tourism based economies. Their findings establish that tourism investments not Journal of Business Economics and Management, 2019, 20(6): 1102–1120 1107 only promote tourism development but also play an important role in reducing the level of CO2 emissions. Likewise, Hoogendoorn and Fitchett (2018) argue that climate change has a considerable negative impact on the rapidly growing tourism industry in several African countries. Given that, the African countries are relatively poor countries and their economic growth depend on tourism receipts, the effect of climate change on the tourism industry is even more crucial in these countries. To conclude the above literature review, there is a lack of empirical findings for the impact of renewable energy consumption on tourism development. Most of the existing literature analyse the causal relationship between the variables of tourism development, carbon dioxide emissions, and energy consumption, but ignores their dynamic linkages and a possible reverse causality. For this purpose, the current paper aims to fill this gap by analysing not only the effects of GDP per capita, the real effective exchange rates, the trade openness, but also the renewable energy consumption, and the tourism investments on tourism development in the G20 countries for the period from 1995 to 2012. The findings derived from the current paper will add significant value to the body of knowledge on the role of renewable energy uses and tourism investments in tourism development. Furthermore, the paper provides substantial policy recommendations, which would be crucial for the policy and practice. 2. Model specification, data, and methodology 2.1. Empirical models and data This section describes the methodology that is used to investigate the dynamic association between renewable energy consumption, tourism development, and tourism investments. For this purpose, the paper aims to achieve two main objectives: First, it aims to examine the effect of renewable energy consumption on tourism development; and second, it explores the impact of the tourism investment on the tourism development in the sample of the G20 countries using annual data from 1995 to 2015. To achieve the first objective, the paper develops the following model: 1 ,2,3 ,4,, it it it it it it TD REER PI REC TO=α+β +β +β +β + , (1) where, TD, REER, PI, REC, and TO represent the total tourism contribution to GDP in billion USD, the real effective exchange rate index (2010= 100)3, the GDP per capita (constant 2010 USD), the renewable energy consumption (TJ), and the trade openness (% of GDP), respectively. ei denotes the error term in the model, and the subscripts i and t denote country and year, respectively. Eq. (1) implies the output (revenue) of tourism sector depends on the real the effective exchange rates, the GDP per capita, the renewable energy consumption, and the trade openness. Among controls, GDP per capita captures the “income effect”, the real effective exchange rate captures the “price effect”, and trade openness addresses the role of economic globalization in the international tourism demand (Ongan & Gozgor, 2018). Renewable energy is the main variable of interest. 3 The real effective exchange rates data on Argentina, India, Indonesia, and Turkey was not available from the World Development Indicators (WDI); hence, these data are collected from the Federal Reserve Bank of St. Louis. 1108 Z. Lu et al. The dynamic impacts of renewable energy and tourism investments on international ... In addition, it is also aimed to explore the impact of the tourism investment on the tourism development by applying the following specification: 1 ,2,3,4,, , it it it it it it TD REER PI TI TO=α+β +β +β +β + (2) where TI is the tourism investments in billion USD. Finally, it is proceeded to provide two additional robustness checks by replacing the tourism revenue (TD) with international tourist arrivals in millions (TA): 1 ,2,3 ,4,, ; it it it it it it TA REER PI REC TO=α+β +β +β +β + (3) 1 ,2,3,4,, . it it it it it it TA REER PI TI TO=α+β +β +β +β + (4) The related data on REER, PI, TO and TA are obtained from the World Development Indicators (WDI), while data on REC is sourced from the dataset for the Sustainable Energy for All. Finally, data on TD and TI are collected from the World Travel and Tourism Council (WTTC). In addition, the definition of the variables and the data source are provided in Appendix. 2.2. Econometric methodology The long-run relationship among variables is examined through the panel cointegration methodology. Furthermore, it is investigated the long-run effect of renewable energy consumption on tourism development by employing a non-parametric approach, i.e. the panel FMOLS estimation technique. Finally, it is implemented the panel non-causality test to establish the short-run causalities among these variables. Firstly, the seminal paper by Nelson and Plosser (1982) about the presence of unit root in time series has led to a significant theoretical and applied research since the 1980s. Scholars have recognized the importance of unit root tests in empirical estimation. Hence, a number of panel unit root tests have been developed. Given that, it firstly analysed the unit root characteristics of the data through the use of panel unit root tests. More specifically, it is applied three panel unit root tests, such as the Levin, Lin, and Chu (LLC) (2002), Im, Pesaran, and Shin (IPS) (2003), and the Augmented Dickey-Fuller (ADF) (Maddala & Wu, 1999) for identifying the order of integration of the variables. Secondly, the long-run equilibrium relationship between the variables of interest is examined using the panel cointegration method. The current paper applies the Fisher-type Johansen cointegration methodology. Unlike the conventional cointegration tests based on the Engle-Granger approach (Engle & Granger, 1987; Engle & Yoo, 1987), the Fisher-type test follows the Johansen’s approach, which allows for more than one cointegrating relationship. Both the Trace test and the Maximum-eigenvalue (Max-Eigen) test are able to test the number of cointegrating vectors when there are more than two variables in the cointegrating system. Based on the test statistics of the Trace and the Max-Eigen, it can be determined and identified the presence of cointegrating vectors. The panel cointegration technique is more suitable for the sample because the time dimension of each country is relatively short. Therefore, the use of panel cointegration technique not only produces the asymptotically unbiased estimators but also considers the parameters that are free from nuisance. Hence, unbiased Journal of Business Economics and Management, 2019, 20(6): 1102–1120 1109 findings can be obtained regarding the cointegrating relationships, which are asymptotically free from heterogeneity in the short term. Thirdly, a long-run cointegrating vector was also estimated from Eq. (1) to Eq. (4), to uncover the long-run tourism development elasticities. It is applied the nonparametric approach of the panel FMOLS estimation technique to avoid the problem of nuisance parameters due to the possible existence of serial correlation and endogeneity among the variables that are considered in the model (Pedroni, 2001a, 2001b). The advantage of the panel FMOLS is that it illustrates the consistent analysis of a common value for the cointegrating vector (Pedoni, 2001b). Finally, it is attempted to examine the dynamic bivariate causal relationships between the variables in a panel setup, while taking into account heterogeneity across countries. It is applied the heterogeneous panel non-causality test of Dumitrescu and Hurlin (2012) to examine the causal relationships in the short-run and to test the validity of the null hypothesis of homogeneous non-causality against the alternative hypothesis of heterogeneous non-causality. 3. Empirical findings and discussion 3.1. Preliminary analysis of the data The current paper begins the preliminary analysis with the summary statistics on the selected variables of the sample countries. The summary statistics are displayed in Table 1. Among the G20 countries, the total contribution of the tourism sector (TD) to the GDP is highest in the U.S., while other higher tourism revenue countries are China, Germany, and Japan, respectively. Relatively, South Africa, Indonesia, Turkey, Argentina, Korea, Saudi Arabia, and Russia have lower tourism revenues. Similarly, France receives the highest average international tourists (TA) per year and the second and the third position occupied by the U.S. and China. On the other hand, Argentina, Brazil, and India received less than 5 million international tourists per year. The statistics also show that both the U.S. and China have more than 40 billion USD investments per year in the tourism and travel sector (TI). On the other hand, a number of other countries have less than 5 billion USD investments in tourism, such as South Africa and Mexico. As expected, China, India, and the U.S. have the highest renewable energy consumption (REC) among the G20 countries, whereas Saudi Arabia has the least renewable energy consumption. The average trade openness (TO) level is significantly higher in Korea, Saudi Arabia, and Canada, while it is lowest in Brazil, the U.S., and Japan. Finally, the countries like Australia, the U.S., Canada, and Japan have more than 40K USD per capita GDP (PI), whereas India has less than 2K USD per annum. Overall, the G20 countries have more than 210 billion USD in revenue from the tourism sector, while they also receive more than 21 million international tourists per year on average. In the next step, it is provided the average annual growth rates for the considered variables of the paper using the annual data from 1995 to 2015. The average growth rates are displayed in Table 2. 1116 Z. Lu et al. The dynamic impacts of renewable energy and tourism investments on international ... 4. Discussion of the findings and policy implications Given the findings of the long-run estimations, it is drawn a number of policy implications, which are useful for the implementation of sustainable tourism development policies with respect to the G20 members. More specifically, the findings established that the growth in renewable energy consumption positively contributes to tourism development in terms of tourism revenues and international tourist arrivals. These results advise that the low level of CO2 emissions due to the higher level of renewable energy consumption attracts more international tourists. Hence, renewable energy consumption not only attracts a large number of international tourists but also helps the tourism industry to generate more income from these tourists (Otgaar, 2012). Consequently, the value added by the tourism sector to the GDP significantly increases over time. Therefore, the policymakers of the G20 economies should realize that the higher level of renewable energy consumption has several positive implications for the economy and society. For instance, increasing renewable energy consumption helps to avoid the use of fossil fuel energy, which is more carbon intensive. Consequently, promoting renewable energy helps to reduce the level of carbon dioxide emission in the country (Shi et al., 2013). A lower level of environmental pollution may attract more international tourists and may provide employment and income opportunities for the local communities. Hence, renewable energy provides an opportunity for the tourism industry to grow further and potentially assist those economies to address some of the basic socioeconomic issues, such as unemployment and income inequality. Given these arguments, policymakers should initiate more of sustainable tourism development policies, which may assist those countries to expand the tourism industry further. Furthermore, the results indicate that the growth in tourism investments also positively contributes to tourism revenues and international tourist arrivals in the G20 countries. These results imply that tourism investments play an important role in promoting the tourism industry. The tourism investments may help to the tourism industry to build new hotels and restaurants, use of more energy efficient and renewable energy sources, adopt more environment-friendly transportation activities, and may also be using print and electronic media to advertise the tourism-related activities that they might be carrying out. Therefore, sustainable tourism investments might have played a significant role in minimizing the adverse effect of the tourism industry on the environment and might have developed attractive infrastructure developments in the tourism sector. These all factors may be positively contributed to the tourism industry to develop further in terms of revenue and attract more international tourists (Irsag et al., 2012). Given the positive effect of tourism investments on tourism revenue and international tourist arrivals, policymakers need to further introduce tourism investment policies, which should attract more investments in the tourism industry. Conclusions The G20 countries are considered as the major players in global tourism development. For instance, according to the data of the UNWTO (2017), the G20 economies accounted 47 percent, 74 percent, and 66 percent of global international tourist arrivals, tourism investments, and tourism revenues in 2012, respectively. These statistics indicate that the G20 Journal of Business Economics and Management, 2019, 20(6): 1102–1120 1117 countries play a significant role in the global tourism economy and that’s why the current paper focuses on the G20 countries. The previous studies in the tourism literature have mainly focused on the effect of tourism on economic development and the environment. However, it is not very clear to what extent renewable energy consumption and tourism investments promote tourism development. For this purpose, the current paper aimed to investigate the effects of renewable energy consumption and tourism investments on tourism revenues and international tourist arrivals in the G20 countries. Using the annual data from 1995 to 2015, the current paper employed the panel unit root tests, the panel cointegration analysis, the panel FMOLS estimations, and the heterogeneous non-causality test procedure to examine the order of integration of the variables, the long-run relationship, the long-run elasticities, and the short-run causality relationships, respectively. The empirical results showed that renewable energy consumption played an important role in enhancing tourism revenue and attracting international tourist arrivals. The results also indicated that tourism investments played a considerable role in tourism development. These results implied that both renewable energy consumption and tourism investments are important drivers of tourism development in the G20 countries. Given these results, it is argued that international tourists might have given more preferences to visit the countries that have less environmental pollutions. Therefore, renewable energy consumption might be a driving force of tourism development. In addition, it is argued that tourism investments also played an important role to promote the tourism industry. For example, tourism investments help to build attractive infrastructures, such as hotels, restaurants, and travel vehicles, as well as other eco-friendly infrastructures, such as energy efficiency, emission control technologies, and access to renewable energy sources. In such a way, tourism investments not only attract international tourists but also work effectively to reduce the adverse effect of the tourism industry on the environment. Given these arguments, it is suggested the policymakers of the G20 economies to initiate sustainable tourism policies in the form of tourism investments, use of more renewable energy sources, and adopting eco-friendly tourism activities. These all factors will further assist those economies to move towards sustainable tourism development. However, the results are obtained from the G20 countries, and this is the limitation of the current study. Furthermore, the potential drivers of sustainable tourism development can be different for each country and this limits the implications. Therefore, future studies on the related subject can focus on other developing economies and developed countries by using panel data or a time-series analysis. Acknowledgements The authors acknowledge the financial supports from National Social Science Fund of China (Grant Number: 16BJY052). 1118 Z. Lu et al. The dynamic impacts of renewable energy and tourism investments on international ... References Alam, M. S., & Paramati, S. R. (2017). The dynamic role of tourism investment on tourism development and CO2 emissions.Annals of Tourism Research,66, 213-215. https://doi.org/10.1016/j.annals.2017.07.013 Bode, S., Hapke, J., & Zisler, S. (2003). Need and options for a regenerative energy supply in holiday facilities. Tourism Management, 24(3), 257-266. https://doi.org/10.1016/S0261-5177(02)00067-5 Dumitrescu, E.-I., & Hurlin, C. (2012). Testing for granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450-1460. https://doi.org/10.1016/j.econmod.2012.02.014 Dwyer, L., Forsyth, P., & Spurr, R. (2004). Evaluating tourism’s economic effects: New and old approaches. Tourism Management, 25(3), 307-317. https://doi.org/10.1016/S0261-5177(03)00131-6 Engle, R., & Granger, C. W. J. (1987). Co-Integration and error correction: representation, estimation, and testing. Econometrica, 55(2), 251-276. https://doi.org/10.2307/1913236 Engle, R., & Yoo, B. S. (1987). Forecasting and testing in co-integrated systems. Journal of Econometrics, 35(1), 143-159. https://doi.org/10.1016/0304-4076(87)90085-6 Gössling, S. (2002). Global environmental consequences of tourism. Global Environmental Change, 12(4), 283-302. https://doi.org/10.1016/S0959-3780(02)00044-4 Gössling, S., & Peeters, P. (2015). Assessing tourism’s global environmental impact 1900–2050. Journal of Sustainable Tourism, 23(5), 639-659. https://doi.org/10.1080/09669582.2015.1008500 Gössling, S., Peeters, P., Ceron, J.-P., Dubois, G., Patterson, T., & Richardson, R. B. (2005). The ecoefficiency of tourism. Ecological Economics, 54(4), 417-434. https://doi.org/10.1016/j.ecolecon.2004.10.006 Hoogendoorn, G., & Fitchett, J. M. (2018). Tourism and climate change: A review of threats and adaptation strategies for Africa. Current Issues in Tourism, 21(7), 742-759. https://doi.org/10.1080/13683500.2016.1188893 Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53-74. https://doi.org/10.1016/S0304-4076(03)00092-7 Irsag, B., Puksec, T., & Duic, N. (2012). Long term energy demand projection and potential for energy savings of Croatian tourism-catering trade sector. Energy, 48(1), 398-405. https://doi.org/10.1016/j.energy.2012.06.069 Katircioglu, S. T. (2014). International tourism, energy consumption, and environmental pollution: The case of Turkey. Renewable and Sustainable Energy Reviews, 36, 180-187. https://doi.org/10.1016/j.rser.2014.04.058 Levin, A., Lin, C. F., & Chu, C. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1-24. https://doi.org/10.1016/S0304-4076(01)00098-7 Lim, C. (1997). Review of international tourism demand models. Annals of Tourism Research, 24(4), 835-849. https://doi.org/10.1016/S0160-7383(97)00049-2 Maddala, G. S., & Wu, S. (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and Statistics, 61(S), 631-652. https://doi.org/10.1111/1468-0084.61.s1.13 Mardani, A., Streimikiene, D., Cavallaro, F., Loganathan, N., & Khoshnoudi, M. (2019). Carbon dioxide (CO2) emissions and economic growth: A systematic review of two decades of research from 1995 to 2017.Science of the Total Environment, 649, 31-49. https://doi.org/10.1016/j.scitotenv.2018.08.229 Michalena, E., Hills, J., & Amat, J. (2009). Developing sustainable tourism, using a multicriteria analysis on renewable energy in Mediterranean Islands. Energy for Sustainable Development, 13(2), 129-136. https://doi.org/10.1016/j.esd.2009.06.001 Journal of Business Economics and Management, 2019, 20(6): 1102–1120 1119 Nelson, C., & Plosser, C. (1982). Trends and random walks in macroeconomic time series: Some evidence and implications. Journal of Monetary Economics, 10(2), 139-162. https://doi.org/10.1016/0304-3932(82)90012-5 Oh, C.-O. (2005). The contribution of tourism development to economic growth in the Korean Economy. Tourism Management, 26(1), 39-44. https://doi.org/10.1016/j.tourman.2003.09.014 Ongan, S., & Gozgor, G. (2018). Tourism demand analysis: The impact of the economic policy uncertainty on the arrival of Japanese tourists to the USA. International Journal of Tourism Research, 20(3), 308-316. https://doi.org/10.1002/jtr.2182 Otgaar, A. (2012). Towards a common agenda for the development of industrial tourism. Tourism Management Perspectives, 4, 86-91. https://doi.org/10.1016/j.tmp.2012.05.004 Paramati, S. R., Alam, M. S., & Chen, C. F. (2017). The effects of tourism on economic growth and CO2 emissions: a comparison between developed and developing economies.Journal of Travel Research,56(6), 712-724. https://doi.org/10.1177/0047287516667848 Paramati, S. R., Alam, M. S., & Lau, C. K. M. (2018). The effect of tourism investment on tourism development and CO2 emissions: empirical evidence from the EU nations.Journal of Sustainable Tourism,26(9), 1587-1607. https://doi.org/10.1080/09669582.2018.1489398 Paramati, S. R., Shahbaz, M., & Alam, M. S. (2017). Does tourism degrade environmental quality? A comparative study of Eastern and Western European Union.Transportation Research Part D: Transport and Environment,50, 1-13. https://doi.org/10.1016/j.trd.2016.10.034 Pedroni, P. (2001a). Purchasing power parity tests in cointegrated panels. Review of Economics and Statistics, 83(4), 727-731. https://doi.org/10.1162/003465301753237803 Pedroni, P. (2001b). Fully modified OLS for heterogeneous cointegrated panels, in B. H. Baltagi, T.B.Fomby, & R. Carter Hill (Eds.), Nonstationary panels, panel cointegration, and dynamic panels (Advances in Econometrics, Vol. 15, pp. 93-130). Bingley: Emerald Group Publishing Limited. https://doi.org/10.1016/S0731-9053(00)15004-2 Samut, P. K. (2017). Integrated FANP-f-MIGP model for supplier selection in the renewable energy sector. Journal of Business Economics and Management, 18(3), 427-450. https://doi.org/10.3846/16111699.2017.1325777 Scott, D. (2011). Why sustainable tourism must address climate change. Journal of Sustainable Tourism, 19(1), 17-34. https://doi.org/10.1080/09669582.2010.539694 Scott, D., Peeters, P., & Gössling, S. (2010). Can tourism deliver its “aspirational” greenhouse gas emission reduction targets? Journal of Sustainable Tourism, 18(3), 393-408. https://doi.org/10.1080/09669581003653542 Shi, Y., Du, Y., Yang, G., Tang, Y., Fan, L., Zhang, J., Lu, Y., Ge, Y., & Chang, J. (2013). The use of green waste from tourist attractions for renewable energy production: The potential and policy implications. Energy Policy, 62, 410-418. https://doi.org/10.1016/j.enpol.2013.07.126 Song, H., Dwyer, L., Li, G., & Cao, Z. (2012). Tourism economics research: A review and assessment. Annals of Tourism Research, 39(3), 1653-1682. https://doi.org/10.1016/j.annals.2012.05.023 Tang, Z., Shang, J., Shi, C., Liu, Z., & Bi, K. (2014). Decoupling indicators of CO2 emissions from the tourism industry in China: 1990–2012. Ecological Indicators, 46, 390-397. https://doi.org/10.1016/j.ecolind.2014.06.041 Tsai, K.-T., Lin, T.-P., Hwang, R.-L., & Huang, Y.-J. (2014). Carbon dioxide emissions generated by energy consumption of hotels and homestay facilities in Taiwan. Tourism Management, 42, 13-21. https://doi.org/10.1016/j.tourman.2013.08.017 World Tourism Organization (UNWTO). (2017). UNWTO Tourism Highlights, 2017 Edition. Madrid: World Tourism Organization. 1120 Z. Lu et al. The dynamic impacts of renewable energy and tourism investments on international ... APPENDIX Definition of the variables and the data sources Variable Measure Label Data Source Total Tourism Contribution to GDP In Billion US$ TD World Travel and Tourism Council International Tourists Arrival In Million TA World Development Indicators Tourism Investment In Billion US$ TI World Travel and Tourism Council Renewable Energy Consumption TJ REC Sustainable Energy for All Trade % of GDP TO World Development Indicators GDP per Capita Constant Price in 2010 US$ PI World Development Indicators Real Effective Exchange Rate Index, 2010= 100 REER World Development Indicators & Federal Reserve Bank of St. Louis Yang, G., Li, P., Zheng, B., & Zhang, Y. (2008). GHG emission-based eco-efficiency study on tourism itinerary products in Shangri-La, Yunnan Province, China. Current Issues in Tourism, 11(6), 604622. https://doi.org/10.1080/13683500802475943 Yazdani-Chamzini, A., Fouladgar, M. M., Zavadskas, E. K., & Moini, S. H. H. (2013). Selecting the optimal renewable energy using multi criteria decision making. Journal of Business Economics and Management, 14(5), 957-978. https://doi.org/10.3846/16111699.2013.766257