College of Geographical Sciences, Qinghai Normal University, Qinghai, China.
School of Economics, Quaid-I-Azam University, Islamabad, Pakistan.
Environ Sci Pollut Res Int. 2022 May;29(24):36273-36280. doi: 10.1007/s11356-021-18138-2. Epub 2022 Jan 21.
The main motivation behind this study is the importance of tourism and ICT industry in the economic development of a country and their potential effects on the country's environmental quality in the digital era. For empirical analysis, the study applies FMOLS, DOLS, and quantile regression techniques for Asian economies. The findings of the study confirmed that tourism and digitalization improve environmental quality in FMOLS and DOLS models. In the basic quantile regression model, the estimates attached to tourism arrival are positive 5 quantile to 40 quantile and then turn negative from 60 quantile and onwards. Likewise, the estimates attached to tourism receipts in the robust quantile regression model are positive from quantile 5 to quantile 20 and negative and increasing from quantile 30 and onwards. Conversely, the estimates of digital infrastructure are insignificant in the basic quantile model at all quantiles except the 95. However, the estimated coefficients of digital infrastructure in the robust model are negative and rising from 40 quantile to 70 quantile and negative and declining from 80 quantile to 95 quantile. In general, we can say that as the tourism and digital sectors grow, the CO emissions decline.
本研究的主要动机是旅游业和信息通信技术产业在国家经济发展中的重要性及其在数字时代对国家环境质量的潜在影响。为了进行实证分析,本研究应用了 FMOLS、DOLS 和分位数回归技术来分析亚洲经济体。研究结果证实,旅游业和数字化在 FMOLS 和 DOLS 模型中均能提高环境质量。在基本分位数回归模型中,旅游入境人数的估计值在第 5 分位数到第 40 分位数之间为正,然后从第 60 分位数开始变为负。同样,旅游收入的估计值在稳健分位数回归模型中从第 5 分位数到第 20 分位数为正,从第 30 分位数开始为负且递增。相反,数字基础设施的估计值在除第 95 分位数以外的所有分位数的基本分位数模型中均不显著。然而,数字基础设施的估计系数在稳健模型中从第 40 分位数到第 70 分位数为负且递增,从第 80 分位数到第 95 分位数为负且递减。总的来说,我们可以说随着旅游和数字部门的增长,二氧化碳排放量下降。