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The asymmetric effect of public private partnership investment on transport CO2 emission in China: Evidence from quantile ARDL approach

Abstract Transportation infrastructure is a pillar of economic development as well as a main contributor to climate change. Therefore, it is necessary to transform the transport sector investment into climate-resilient, low-carbon transportation choices in order to achieve sustainable transportation infrastructure. In case of China, this transformation might be necessary from the perspective of the “New-style Urbanization” strategy, and for fulfilling this strategy, policy realignment is required. To address this policy-level void in the literature, we explore the influence of public private partnerships investment in transport sector, renewable energy consumption, urbanization on transport-induced carbon emissions in China. For this purpose, we apply Quantile Autoregressive Distributed Lagged (QARDL) method during 1990Q1-2018Q4. Based on the results of the study, a multipronged sustainable development goal (SDG) framework has been suggested, under which SDG 11, SDG 13, and SDG 8 are addressed, while using SDG 17 as a vehicle.
- Tsinghua University China (People's Republic of)
- University of Raparin Iraq
- International University Cambodia
- Henan University of Economic and Law China (People's Republic of)
- Goa Institute of Management India
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).136 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 0.1%
