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Every year millions of Muslims go to Saudi Arabia to fulfil pilgrimage worship, thus Saudi Arabia is such a religious centre brings with it various consequences. In this context, this paper investigates the nexus between CO2 emissions, economic growth, energy consumption and pilgrimage tourism in Saudi Arabia for the period of 1968-2017. The dynamic ordinary least squares (DOLS) and fully-modified ordinary least squares (FMOLS) methods are employed in this study. FMOLS results prove that energy consumption, number of pilgrims and oil prices have a positive effect on CO2 emissions and GDP has a negative effect on it, while DOLS results imply that only energy consumption has a positive effect on carbon emissions. In addition, there is unidirectional causality from CO2 to pilgrimage tourism and from pilgrimage tourism to oil, and there is bidirectional causality between pilgrimage tourism and GDP. Therefore, the environmental cost of pilgrimage tourism is inevitable. Reflections of pilgrimage visits to Saudi Arabia as a belief tourism are dealt with for the first time in this paper. In addition, our more specific purpose is to determine the environmental impacts of Muslims performing the pilgrimage, during their religious worship.

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Comprehending the determinants of renewable energy (RE) deployment has preoccupied the energy literature as well as policymakers internationally due to countries' overall shift away from fossil fuels in the energy mix.As stated in the literature, empirical studies that analyze the determinants of RE deployment use a number of different indicators for RE. The effect of an ambiguous choice of the proxy might produce various outcomes and thus create inconsistencies in the policy recommendations. This study aims at filling this gap in the literature comparing and contrasting not only the use of RE indicators but also, for robustness purposes, using indicators at aggregate and per capita forms for a global sample, developed countries, and developing countries. For the empirical purpose, this study employs two econometric techniques: the pooled ordinary least squares with robust SEs and the augmented mean group estimator, which account for cross- Highlights• This study uses a number of renewable energy indicators to analyze the determinants of renewable energy deployment.

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