To what extent are pollutant emission intensified by international tourist arrivals? Starling evidence from G7 Countries

Authors: Gyamfi, B.A., Bein, M.A., Adedoyin, F.F. and Bekun, F.V.

Journal: Environment, Development and Sustainability

eISSN: 1573-2975

ISSN: 1387-585X

DOI: 10.1007/s10668-021-01765-7

Abstract:

A large volume of environmental science and pollution research has focused on the contributions of various forms of energy consumption to emissions. However, little attention is given to the impact of human activities such as tourism. Hence, this study investigates the impact of tourist arrivals, energy use, and economic growth on CO2 emissions in the G7 countries for the period 1995–2018. The study employed the use of dynamic panel estimations, namely dynamic ordinary least square, fully modified ordinary least squares and panel pooled mean group-autoregressive distributed lag model (PMG-ARDL) estimation techniques to establish long-run and short-run relationships between the study variable of interest, while the Dumitrescu Hurlin non-causality test was used to test for causality direction among the variables outlined. Empirical findings from the regression revealed that economic growth, tourism and energy use are strong drivers of emission levels in the G7 bloc, while the causality analysis revealed that there is unidirectional causality from CO2 to energy use, CO2 to economic growth (GDP) and GDP to tourist arrivals. These outcomes imply that tourism, energy use and economic growth have no direct effect on emissions, but rather emissions predict economic growth and energy use. Furthermore, tourist arrivals predict energy use; economic growth predicts tourism. Overall based on the study of empirical outcomes, we suggest that to achieve more significant results in reducing emissions, governments of the G7 countries should continue to emphasize green tourism as well as increase the share of renewable energy in their regional energy mix. More policy direction was outlined in the concluding section of this study.

http://eprints.bournemouth.ac.uk/36036/

Source: Scopus

To what extent are pollutant emission intensified by international tourist arrivals? Starling evidence from G7 Countries

Authors: Gyamfi, B.A., Bein, M.A., Adedoyin, F.F. and Bekun, F.V.

Journal: ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY

eISSN: 1573-2975

ISSN: 1387-585X

DOI: 10.1007/s10668-021-01765-7

http://eprints.bournemouth.ac.uk/36036/

Source: Web of Science (Lite)

To what extent are pollutant emission intensified by international tourist arrivals? Starling evidence from G7 Countries

Authors: Gyamfi, B.A., Bein, M.A., Adedoyin, F.F. and Bekun, F.V.

Journal: Environment, Development and Sustainability

DOI: 10.1007/s10668-021-01765-7

http://eprints.bournemouth.ac.uk/36036/

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114592866&doi=10.1007%2fs10668-021-01765-7&partnerID=40&md5=7d48d73bbaa708fef65609308d6e827f

Source: Manual

To what extent are pollutant emission intensified by international tourist arrivals? Starling evidence from G7 Countries

Authors: Gyamfi, B.A., Bein, M.A., Adedoyin, F.F. and Bekun, F.V.

Journal: Environment, Development and Sustainability

ISSN: 1387-585X

Abstract:

A large volume of environmental science and pollution research has focused on the contributions of various forms of energy consumption to emissions. However, little attention is given to the impact of human activities such as tourism. Hence, this study investigates the impact of tourist arrivals, energy use, and economic growth on CO2 emissions in the G7 countries for the period 1995–2018. The study employed the use of dynamic panel estimations, namely dynamic ordinary least square, fully modified ordinary least squares and panel pooled mean group-autoregressive distributed lag model (PMG-ARDL) estimation techniques to establish long-run and short-run relationships between the study variable of interest, while the Dumitrescu Hurlin non-causality test was used to test for causality direction among the variables outlined. Empirical findings from the regression revealed that economic growth, tourism and energy use are strong drivers of emission levels in the G7 bloc, while the causality analysis revealed that there is unidirectional causality from CO2 to energy use, CO2 to economic growth (GDP) and GDP to tourist arrivals. These outcomes imply that tourism, energy use and economic growth have no direct effect on emissions, but rather emissions predict economic growth and energy use. Furthermore, tourist arrivals predict energy use; economic growth predicts tourism. Overall based on the study of empirical outcomes, we suggest that to achieve more significant results in reducing emissions, governments of the G7 countries should continue to emphasize green tourism as well as increase the share of renewable energy in their regional energy mix. More policy direction was outlined in the concluding section of this study.

http://eprints.bournemouth.ac.uk/36036/

Source: BURO EPrints