After inspecting the data, this study uses Autoregressive Distributed Lag (ARDL) bounds testing approach to cointegration by Pesaran, Shin, and Smith (2001) to examine the long-run relationshipbetween the variables of the study. The ARDL technique has various advantages over other cointegration tests. These cointegration tests can be used irrespective of the stationary variables whether they are I (0), I (1) or the correlation of both (Pesaran and Shin 1998). The ARDL method has worked out small sample properties (Haug 2002). The ARDL exceeded the Johansen and Juselius technique because of its small sample properties (Pesaran, Shin, and Smith 2001). There is no endogeneity problem in the ARDL approach and is free from residual correlation because of the selection of suitable lag selection. The ARDL method made easy to distinguish between dependent and independent variables. Therefore, for I(2) variables the Computed F-statistics of Pesaran and Shin, (2001) table will be invalid (Ouattara 2004) .
With advances in time series econometric techniques, more recent studies have tended to focus on vector error-correction model (ECM) and the cointegration approach. Masih and Masih (1996) used cointegration analysis to study this relationship in a group of six Asian countries and found cointegration betweenenergyuse and GDP in India, Pakistan, and Indonesia. No cointegration is found in the case of Malaysia, Singapore and the Philippines. The flow of causality is found to be running from energy to GDP in India and from GDP to energy in Pakistan and Indonesia. Using trivariate approach based on demand functions, Asafu-Adjaye (2000) tested the causal relationshipbetweenenergyuse and income in four Asian countries using cointegration and error- correction analysis. He found that causality runs from energy to income in India and Indonesia, and a bi- directional causality in Thailand and the Philippines. Stern (2000) undertakes a cointegration analysis to conclude that energy is a limiting factor for growth, as a reduction in energy supply tends to reduce output. Yang (2000) considers the causal relationshipbetween different types of energy consumption and GDP in Taiwan for the period 1954–1997. Using different types of energy consumption he found a bi-directional causality betweenenergy and GDP. This result contradicts with Cheng and Lai (1997) who found that that there is a uni-directional causal relationship from GDP to energyuse in Taiwan.
development of green tourism is of great interest for this region on both the economic and environmental sides. As recommended by the United Nations Environment Program (2011), public-private partnerships can spread the costs and risks of large green tourism investments. In addition, administrative fees related to these projects can be reduced by public authorities by offering favorable interest rates and in- kind support, such as technical, marketing, or business administration assistance; iii) the long-run dynamic bidirectional causal relationshipbetween the number of tourist arrivals and renewable energy consumption indicates that a policy designed to the development of the tourism sector could be a good supportive strategy for the expansion of the share of renewable energy in the total energy mix. On the other side, encouraging the use of renewable energy enhances the venue of tourists to this region. Finally, one extension of our work could be the study of the relationshipbetweentourism and renewable energy by including other variables, while considering other countries or a panel of countries.
consumption is one of the most intrigues issues in the literature of energy economics. The current literature that investigates the causal link between these variables is not only very recent, but also highly limited. However, the relationshipbetweenemissions and renewable energy consumption merits further consideration, given that internationaltourism is one of the motivating factors that may have positively contributed to economic growth as well as to the reduction of environmental quality. In the case of Turkey, the long-run relationshipbetweeninternationaltourism and real GDP has been investigated by Katircioglu (2009). Using bounds tests and the Johansen cointegration approach, he finds the absence of any long-run equilibrium between tourist variables and economic growth.
Because of the lack of econometric studies in relevance to the link betweentourism and renewable energy, the goal of this study is to remedy this lack and to explore the causal relationships between renewable energy consumption, the number of tourist arrivals, the trade openness ratio, economic growth, foreign direct investment (FDI), and carbon dioxide (CO 2 ) emissions for a panel of 22 Central and South American countries, spanning the period 1995–2010. The empirical findings document that the variables under investigation are cointegrated. Short-run Granger causality tests illus- trate unidirectional causalities running from: (i) renewable energy to CO 2 emissions and trade; (ii) tourism to trade and FDI; and (iii) economic growth to renewable energy and tourism. In the long run, there is evidence of bidirectional causality between renewable energy, tourism, FDI, trade, and emissions. Thus, renewable energy and tourism are in a strong long-run causal relationship. Moreover, long-run estimates for the whole panel and for the three income panel groups considered (Lower Middle, Upper Middle, High) highlight that tourism, renewable energy, and FDI contribute to the reduction of emis- sions, while trade and economic growth lead to higher carbon emissions. Therefore, attracting foreign direct investment, encouraging the use of renewable energy, and tourism development, particularly green tourism, are good policies for this region to combat climate change.
The results of the long-run equilibrium relationship are presented in Table 2 below. It shows that the coefficient of LGDP is 61.02, which is positive and significant at the level of 1%. It means that a 1% increase in per capita real GDP will increase per capita emissions by 61.02% in the long- run. The coefficient of LGDP2 is negative (-2.92) and statistically significant at the level of 1%. This shows that when the real GPD per capita reach a certain level a 1% increase of its level will reduce the per capita emissions by 2.92%.
This study employs annual data for a selected OPEC and non-OPEC countries covering the period 1990 to 2014. This particular period has been chosen simply because the required data are not available for earlier periods for all selected countries. The non-OPEC countries chosen in this study are some oil rich countries to compare with the selected OPEC countries. In order to account for changes in variables attributable to changes in population structure (population growth), all variables have been transformed to per capita basis. The variables considered in the study are as follows: IVA is industrial value added per capita indicating a GDP indicator for industrial production sector for each country; IVA time series are PPP adjusted in constant 2010 US dollars. REC represents renewable energy consumption per capita measured in metric tons. CO2 is an indicator of emissions per capita that is measured in metric tons. The data on these variables are obtained from World Bank open data base. ROP is real oil price that is measured using the spot price on West Texas Intermediate (WTI) crude oil in constant 2010 US dollars based on data available from BP Statistical Review of World Energy (2017). WTI has a long history being used as a benchmark for oil prices. The panel of selected OPEC and non-OPEC countries are a natural panel; because they share common economic and political attributes (i.e., each country in OPEC is developing, and the most of them are poor and non-democratic nations, but non-OPEC countries are developed, wealthy and democratic) ; and consequently, likely each group share some common growth rates in variables as a panel.
Estimation based on the use of non-stationary variables can lead to spurious regressions and inferences, whereby asymptotic normality is assumed when the asymptotic distribution is actually non-standard, and relies on simulated critical values. A convenient method of addressing this issue is to use first differences of the variables to render them stationary. Nevertheless, taking first differences could harm the long run relationship among the key variables. It is preferable to check the long run relationship to ensure that the variables are non-stationary. The Engle and Granger approach (1987)  is traditionally used to test for the existence of a long run equilibrium cointegrating relationship.
such research are however contradictory and in many cases researchers failed to establish the inverted U rela- tionship with real life data. A similar yet detailed branch of research attempts to analyze the link betweenenergy consumption and output, suggesting that economic de- velopment and output may be jointly determined and the direction of causality between these two variables needs to be tested. Following the seminal work of Kraft and Kraft , several others including Masih and Masih , Yang , Wolde-Rufael , Narayan and Singh , Narayan and Russell  tested the energy consumption and economic growth nexus with a variety of techniques and for different panel of countries. The recent studies in the area of growth-pollution-energy consumption nexus however attempt to link these two branches of literatures while combining them in a single multivariate framework. Ang , Soytas, Sari and Ewing , Halicioglu , Tamazian and Rao  initiated this combined line of research. Among the recent literature involving the test- ing of EKC, Lean and Smyth  found non-linear rela- tionship between emission and real output. The finding of Akbostanci, Turut-Asik and Tunc  on Turkish economy was however different from that of Lean and Smyth  as the former found an increasing relation- ship between carbon emissions and income in the long run when they looked at cointegration between carbon emissions and per capita income for Turkish economy. Their panel time series analysis of 58 provinces of Tur- key on the contrary, revealed an N-shaped relationship for SO 2 and PM10 (two pollutants commonly referred in
The increase of greenhouse gases (GHG) in which CO2emissions constitute the principal component, is of major environmental problems of all societies. Economic growth impels intensive use of resources and as a result, more residues and wastes thrown in the nature that could lead to environmental degradation. This article tries to trace the eventual relationshipbetweentrade openness and environmental degradation in Iran. For this purpose, a multivarate model is employed in which economic growth and trade openness are related to CO2emissions for the period of 1971-2006. By carring out the Granger causality test, there appeared a unidirectional relation from trade openness to CO2emissions. To analyze the variables’ relationships, the approach of GMM is applied. Results indicate that economic growth has a significant negative effect on carbon dioxcide emissions. But, the impact of trade openness on carbon dioxcide emissions is significantly positive.
the atmosphere would be eliminated due to the use of renewable energies instead of fossil fuels. Energy investments in the island will be increased and regular maintenance of the installed energy systems will be needed. Therefore, employ- ment opportunities for specialized staff will be created. Installation of renewable energy systems will create economic benefits in the small size enterprises and to the households installing these systems. Know-how regarding the transforma- tion of a small Greek island to a zero carbon island, which is currently lacking in Greece, will be acquired. The new know-how could be transferred to other small or bigger Greek islands, multiplying the benefits in the country. The use of dif- ferent renewable energy technologies in a small area could create an attractive educational pole and students could visit the island for educational purposes at- tending seminars in the summer. At the same time conferences in the field of renewable energy sources could be organized with study visits in the existing re- newable energy systems. The zero carbon footprint of the island would increase its attractiveness to environmentally conscious tourists, increasing their visits to the island and the local income due to tourism.
This paper aims to give a contribution on the still questioned bell-shaped relationshipbetween carbon dioxide polluting emissions and economic growth, which is commonly known in the literature as the Environmental Kuznets Curve hypothesis. In particular, it develops a panel analysis for a group of 77 countries, including 22 OECD and 55 NON- OECD units, over the period 1971-2006. We specify the estimated model by taking into account the role of electric power consumption and compare the performance of alternative panel estimators for a quadratic and cubic specification of the empirical model. Our findings seem to go in favor of the EKC relationship for the entire sample. However, this outcome is not confirmed when moving the analysis at sub-sample level where results highlight a non homogeneous picture across different groups of nations.
tain the status quo. The rationality of imposing carbon tariffs on Chinese imports is to eliminate the difference in the stringency of the climate change regulations be- tween China and the EU. However, we have shown in our study that the trading pattern is actually not domi- nated by the pollution haven effect, but by the compara- tive advantage in factor endowments. Therefore, it will be fundamentally distortive to use the carbon tariffs in order to correct the trading pattern that is caused by labor and capital endowments, l et al. one that this kind of in- tervention might be against the principles of free trading.
about 40-45% of 2005 level could be attained in 2020 in China. Even though the structure conducted scenario simulation to determine the impacts of economic growth rates on the energy consumption and carbon dioxide emissions, some vital variables (population dimensions, technology) were neglected in the determination of environmental impacts. Consumption is not the only driving forces of environmental impacts. Xu and Lin (2015) analyse the driver-trigger of carbon dioxide emissions in China’s transport sector. A nonlinear inverted U-shaped curve was found to exist suggesting evidence of Environmental Kuznets Curve (EKC) in the sector, as in economic growth depending heavy on road and air transport in the early stage, but deepening on emission-free train-transport at the later stage due to the speed of technological progress at different times. Urbanization is also found to exhibit pattern of EKC. Zhang, Wu, Liu, Huang, Un, Zhou, Fu and Hao (2014) use a PEMs method to collect 60 light-duty passenger vehicles (LDPVs) data on-road fuel consumption and CO2emissions for China. The study found about 30% gap between on- road fuel consumption and type-approval values. The results among many others, found diesel LDPVs to have a 22% energy saving advantage against gasoline counterparts while the literature also reports a strong correlation between fuel consumption and average speed, that is, a reduction in traffic congestion has effect of mitigating distance-based fuel consumption. Loftus, Cohen, Long, and Jenkins (2015) carried out feasibility studies on global decarbonisation argue that historical carbon intensity and energy intensity rates need to improve and normalized energy technology capacity deployment rates are important benchmarking comparators to examine the relative feasibility of global decarbonisation scenarios for decision makers.
economies (trading sector) and by a national emissions tax in the rest of their economies (nontrading sector). Applicable are also emissions taxes overlapping with the trading scheme that can either be freely chosen or are inert. Welfare-maximizing governments determine tax rates and the tradable-permits budget. It is shown that efficiency requires not to levy overlapping emissions taxes and to set the tax rate in the nontrading sector equal to the permit price. In the small-country case emissions control turns out to be efficient if tax rates in the trading sector are flexible. Otherwise it is second-best to violate cost effectiveness and to choose an excessive endowment of tradable permits. If countries are large and optimal tariffs cannot be applied, emissions taxes or subsidies (!) are shown to serve as a perfect surrogate; efficiency cannot be attained unless there is a central authority mandating cost effectiveness and banning overlapping taxes. Fiscal externalities are specified and the countries’ welfare in the large and small country case is compared.
(2009) pointed out that the worldwide contribution of carbon dioxide emissions to GHGs is 58.8%. However, it was unable to resolve the environmental issues in an appropriate manner and came up with a judgmental and adequate roadmap (Sathaye et al. 2006). Nevertheless, the protocol accepted renewable energy sources (RES) as one of the key solutions to climate change and to the increasing energy demand. This threat of global warming attracted researchers to pay their attention in alleviating its effects and suggesting other sources of energy to meet the rising demand to sustained economic growth rate. Global warming depends on worldwide GHGs emissions but the nastiest effects are faced by developing and populous countries 1 , of course they are not main culprit. There is no grantee that use of renewable energy will lead economic growth with rapid speed (Tiwari, 2011a).
This study aims to test a hypothesis that postulate a positive inter- relationshipbetweeninternational flows of tourist, trade and economic growth. Although tourism is one of the major components in the trade of services, and it has been certified by large number of literatures on the strong correlation betweentourism industry and economic development, yet not much is known on the dynamic inter-relationshipbetween these three variables. Closing-up this gaping hole, this study employs the cointegration tests under autoregressive distributed lag (ARDL) structure to investigate a dynamic inter-relationshipbetween economic development, total trade (import and export) and number of tourist arrival for Malaysia and her major tourism partners ((ASEAN countries) . The estimated result based on the long run time series behavior for number of tourist arrival, volume of total trade and economic development’s indicator shows that these three variables are moved in tandem. Interestingly, in the analysis of short run behavior, we find that number of tourist arrival has significantly Granger caused total trade flows at least for some countries. At the same time, in the short-run, we find that both growth in total trade (export and import) and international tourists’ arrival to Malaysia have uni-directionally Granger caused real income growth and there is statistical evidence for internationaltrade to lead tourist arrival.
Even though their significant importance to the national income accounting, not many researches either theoretical or empirical has been carried out to analyze the dynamic linkages between economic growth, tourism industry and internationaltrade together. Existing researches are concentrated on investigating the relationship either betweentrade and growth (including export+ led growth, Bahmani+Oskooee and Alse 1993, import+led growth Deme 2002, or trade+led growth, Jin 1995, and Hatemi and Irandoust 2001, among others), tourism and growth (Balaguer and Jorda (2002), and Oh 2005) or tourism and trade (Al+Qudair 2004 and Fischer and Gil+Alana 2005). Generally, these researchers are unanimously agreed on the solid relationshipbetweentrade and economic growth, or tourism and growth, while no strong ties can be drawn from the trade and tourismrelationship 2 . This study move one step ahead by combining these two
The Wilcoxon test permits to explore the same issue as before. The statistics are T +, T − and the sum of these two, T . The first one is the sum of the ranks of assigned to the ”positive”differences between each couple of observations, the second one is the sum of the ranks assigned to the ”negative”differences . When the two samples are homogeneous, differences between each couple of corresponding observations not only are uniformly distributed among positive and negative values, but al- so their magnitudes are distributed in a symmetric way. Usually when sample size is greater or equal than 25, the Standard Normal approxi- mation of T + is used. Anyway, even if our sample size is smaller than 25, we still use the Standard Normal approximation to do the test. As it is shown in Table N. , we always reject H0,CO 2 : LA countries have decreased the CO2emissions but we can’t reject H0,Oil : LA countries have decreased Oil consumption per capita. Both at the usual levels of significance. We reach this result not only using the Normal approx- imation, but also comparing T + with the critical values presented in the Wilcoxon specific table. Looking at the different magnitudes of the two statistics, T + and T -, (see again Table N. ), it is obvious that the distribution of the differences between each couple of variables is not symmetric in the case of CO2 but it is in the case of Oil Consump- tion. So the statistical results show that emissions have ¨ıncreased”from 1950 to 2000 and that oil consumption has ”decreased”during the last twenty years. As a matter of fact, five of the twelve countries considered showed a fall of the fossil fuel between 1980 and 2000. Nevertheless, the methodology is not perfect and the results could be distorted due to the years considered.