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EKC hypothesis testing and environmental impacts of transportation infrastructure investments in China, Turkey, India, and Japan

  • Green Energy, Innovation, Government Spending, Sustainable Tourism & Production under Climate Change and Pollution
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Abstract

A key strategy for social development and sustainable urban expansion is building sustainable and affordable transport systems. In this study, we aim to test the validity of the environmental Kuznets curve (EKC) hypothesis and reveal the impact of infrastructure investment in transportation systems in China, Turkey, India, and Japan over the period 1995–2020 on environmental degradation. According to dynamic ordinary least squares (DOLS) method analysis, per capita GDP and per capita GDP3 have a significant positive impact on per capita CO2 emission, while per capita GDP2 has a significant adverse impact on per capita CO2 emission. These results confirm the validity of the N-shaped EKC assumption, while inconsistent with the results of the FMOLS technique, showing that per capita GDP is significantly positive, while per capita GDP2 and per capita GDP3 have a significant negative impact on per capita carbon emissions. Moreover, as clarified by the fully modified ordinary least squares (FMOLS) and DOLS methods, road infrastructure investment (RO), aviation infrastructure investment, trade openness, and foreign direct investment (FDI) have significant positive effects, while railway infrastructure investment (RA) has a significant negative effect on per capita carbon emission. Country-level estimates of per capita carbon emission-based DOLS strategies in the model show that only China and Japan have N-shaped EKC hypothesis. Road infrastructure investment, aviation infrastructure investment, and trade openness have significant positive effects, while railway infrastructure investment has a significant negative effect on per capita CO2 emission in selected central and east Asian countries. The latest electrified rail systems are well thought out and less polluting, so the contribution of rail infrastructure investment to the transport mix can support sustainable and safe transport systems at city center and intercity levels and reduce environmental pollution in central and east Asian countries. Moreover, the implementation of the basic environmental settings of trade agreements should be strengthened to condense the growing impact of free trade on environmental pollution.

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Fig. 1

Source: The Intergovernmental Panel on Climate Change 2022

Fig. 2

Source: International Energy Association. IEA and IPCC (2014) Summary for Policymakers

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Data availability

The data that support the findings of this study are openly available in World Development Indicator page published by (World Bank, 2020), at https://databank.worldbank.org/source/world-development-indicators and OECD database website at https://data.oecd.org/

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Authors and Affiliations

  1. Academy of Management, Guangdong University of Science and Technology, Dongguan, China

    Wennan Wang

  2. Department of Finance, School of Economics, Xiamen University, Xiamen, China

    Wennan Wang & Shugeng Dai

  3. Institute of economics and management, Northeast Agricultural university, Harbin, China

    Arshad Ali

  4. Faculty of Social Sciences, University of Gdansk, Gdańsk, Poland

    Hoatian Wang

  5. School of Public Economics and Administration, Shanghai University of Finance and Economics, Shanghai, China

    Yu Feng

Authors
  1. Wennan Wang
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  2. Arshad Ali
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  3. Hoatian Wang
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  4. Yu Feng
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  5. Shugeng Dai
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Contributions

A.A. (Ali), W.W (Wang), and H.W (Wang) contributed to the conceptualization of the study, analysis, design, and conclusions; reviewed the manuscript; and approved the final submission. Y.F. (Feng) and S.D. (Dai) conceptualized the study, reviewed, curated the software data, edited, and searched the literature.

Corresponding author

Correspondence to Shugeng Dai.

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Wang, W., Ali, A., Wang, H. et al. EKC hypothesis testing and environmental impacts of transportation infrastructure investments in China, Turkey, India, and Japan. Environ Sci Pollut Res 30, 81600–81615 (2023). https://doi.org/10.1007/s11356-023-27580-3

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