Izvorni znanstveni članak
https://doi.org/10.1080/1331677X.2022.2089709
Novel research methods on evaluating the nexus between environment and energy use: evaluating the role of tourism in the pre-COVID period
Junyi Niu
Sažetak
Since the fossil fuels are the principal energy sources across the
globe, it is considered as the major reason for environmental degradation.
Although, the fossil fuel consumption contributes to
maintain industrial production, which is a key factor of economic
growth, yet tourism is also among the key sources of revenue for
China in the pre-Covid-19 pandemic. However, after the emergence
of this novel pandemic, both fossil fuel consumption and tourism
are severely affected that slowdowns China’s economic progress
and could have influence on environmental quality. This study
investigates the impact of traditional fossil fuel, economic growth,
and tourism on carbon emissions level in China over the period
1995–2020. Using time series estimating approaches, all the variables
are found stationary at first difference. Due to irregular distribution
of data, this study employed the novel Quantile-on-Quantile
regression. The estimated results reveal that consumption of fossil
fuel significantly enhances the level of carbon emissions in China.
Whereas the impact of economic growth and tourism on carbon
emission is mixed. The influence of both the variables is found
positive in the lower and medium quantiles, while negative in the
upper quantiles. This study also employed the pairwise Granger
causality test, that validates two-way causal nexus between fossil
fuel consumption—carbon emission and economic growth—carbon
emissions. While one way causality from tourism to carbon
emissions is evident in the empirical results. This study suggests
lowering of fossil fuel consumption by using the alternative energy
sources and increase tourism stringent environmental regulations
for environmentally destructive tourism activities.
Ključne riječi
Fossil fuel; carbon emission; economic growth; tourism; quantile-on-quantile regression; causality
Hrčak ID:
304175
URI
Datum izdavanja:
31.3.2023.
Posjeta: 159 *