The impact of air and rail transportation on environmental pollution in Turkey: a Fourier cointegration analysis

N. Beşer, Asiye Tütüncü, Murat Beşer, Cosimo Magazzino
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Abstract

PurposeThis paper aims to investigate the influence of air and rail transportation on pollution in Turkey from 1970 to 2020.Design/methodology/approachFourier Autoregressive Distributive Lags (ADL) and Fourier Fractional ADL cointegration tests (Banerjee et al., 2017; Ilkay et al., 2021) are employed to analyze the relationship be-tween the variables. Cointegration tests that take into account soft transitions under structural changes are implemented. Structural change issues are crucial for this topic since the changes in countries’ environmental policies and transportation habits are shaped by the decisions taken in relation to environmental regulations. Finally, for robustness purposes, we tested the estimated equation with a completely different methodology. Thus, a Machine Learning (ML) analysis is conducted, through a Ridge Regression (RR).FindingsThe findings obtained by applying Fourier Autoregressive Distributive Lags (FADL) and Fourier Fractional ADL cointegration tests, which can control for structural changes, reveal the existence of a long-term relationship between the variables. In addition, FMOLS estimates emphasize that economic growth and air transport can lead to increased pollution in the long run, while rail transport reduces it. Moreover, the statistically significant trigonometric terms indicate the existence of a smooth structural change among the variables. Robustness checks are performed through a Machine Learning (ML) analysis, which roughly confirms the previous results.Originality/valueTo our knowledge, existing research in Turkey focuses mainly on road transport, while the impact of rail and air transport on pollution has not yet been investigated. As such, this study will be a significant addition to the academic literature.
土耳其航空和铁路运输对环境污染的影响:傅立叶协整分析
本文旨在研究 1970 年至 2020 年土耳其航空和铁路运输对污染的影响。本文采用傅立叶自回归分布滞后(ADL)和傅立叶分数 ADL 协整检验(Banerjee 等人,2017 年;Ilkay 等人,2021 年)来分析变量之间的关系。协整检验考虑了结构变化下的软过渡。结构变化问题对本课题至关重要,因为各国环境政策和交通习惯的变化是由与环境法规相关的决策决定的。最后,为了稳健起见,我们采用完全不同的方法对估计方程进行了测试。结果应用傅立叶自回归分布滞后(FADL)和傅立叶分数 ADL 协整检验(可控制结构变化)得出的结果显示,变量之间存在长期关系。此外,FMOLS 估计结果表明,从长期来看,经济增长和航空运输会导致污染加剧,而铁路运输则会减少污染。此外,具有统计意义的三角项表明变量之间存在平稳的结构变化。我们通过机器学习(ML)分析进行了稳健性检验,结果大致证实了之前的结果。因此,本研究将是对学术文献的重要补充。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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