Economic growth, energy consumption and CO2 emissions in OECD (Organization for Economic Co-operation and Development)'s transport sector: A fully modified bi-directional relationship approach

Saboori, Behnaz; Sapri, Maimunah; Baba, Maizan

doi:10.1016/j.energy.2013.12.048

Cited by 267 publications

(127 citation statements)

References 31 publications

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“…With respect to the first model, regarding railway transport, in short-run, we noticed a bidirectional causal link between the share of CO 2 emissions from railway transport in total carbon dioxide emissions from transport and GDPC, similar to [107]. Besides, the empirical results provided support for a one-way causality link running from investments in railway transport infrastructure to CO 2 _rail.…”

Section: Cointegration and Causality Examinationsupporting

confidence: 59%

“…In relation to air pollutants, the share of CO 2 emissions from railway transport in total carbon dioxide emissions from transport negatively influenced GDPC (Equation (1)), as in Table 8. Nevertheless, the share of CO 2 emissions from international maritime bunkers in total carbon dioxide emissions had a positive influence on GDPC (Equation (3)), consistent with [107]. Since the variables were cointegrated, we could estimate the panel vector error correction model to assess the direction of the causality [62].…”

Section: Cointegration and Causality Examinationmentioning

confidence: 99%

“…The transport sector reveals itself as a fundamental factor towards economic growth, ensuring the efficient distribution of resources and mobility for people [107]. This paper examined the relationship between the main types of transport, related investments, specific air pollutants, and sustainable economic growth for EU-28 countries over 1990-2016.…”

Section: Concluding Remarks and Policy Implicationsmentioning

confidence: 99%

“…Therefore, transport infrastructure, related investments, emissions of carbon dioxide, and economic growth has a long-run relationship in the EU-28 countries. For robust statistical estimates, we employed a non-parametric approach, namely a panel with a fully modified ordinary least squares (henceforth "FMOLS") estimator as in [5,59,65,77,82,107], but also an alternative parametric method, respectively a dynamic ordinary least squares estimator (henceforth "DOLS"), as in [5]. The FMOLS is the desirable econometric way to assess the long-run parameter estimates that handle both the endogeneity and serial correlation concerns [59], whilst DOLS covers the lagged first difference [77].…”

Section: Cointegration and Causality Examinationmentioning

confidence: 99%

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Empirical Evidence from EU-28 Countries on Resilient Transport Infrastructure Systems and Sustainable Economic Growth

et al. 2018

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This paper examines the nexus between the main forms of transport, related investments, specific air pollutants, and sustainable economic growth. The research is important since transport may act as a facilitator of social, economic, and environmental development. Based on data retrieved from Eurostat, Organisation for Economic Co-operation and Development (OECD), and World Bank, the output of fixed-effects regressions for EU-28 countries over 1990-2016 reveals that road, inland waterways, maritime, and air transport infrastructure positively influence gross domestic product per capita (GDPC), though a negative link occurred in the case of railway transport. As concerning investments in transport infrastructure, the empirical results exhibit a positive impact on economic growth for every type of transport, except inland waterways. Besides, emissions of CO 2 from all kind of transport, alongside other specific air pollutants, negatively influence GDPC. The fully modified and dynamic ordinary least squares panel estimation results reinforce the findings. Further, in the short-run, Granger causality based on panel vector error correction model pointed out a unidirectional causal link running from sustainable economic growth to inland waterways and maritime transport of goods, albeit a one-way causal link running from the volume of goods transported by air to GDPC. As well, the empirical results provide support one-way short-run links running from GDPC to investments in road and inland waterway transport infrastructure. In addition, a bidirectional short-run link occurred between carbon dioxide emissions from railway transport and GDPC, whereas unidirectional relations with economic growth were identified in the case of carbon dioxide emissions from road and domestic aviation. In the long-run, a bidirectional causal relation was noticed between the length of the railways lines, investments in railway transport infrastructure, and GDPC, as well as a two-way causal link between the gross weight of seaborne goods handled in ports and GDPC.

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Section: Cointegration and Causality Examinationsupporting

confidence: 59%

Section: Cointegration and Causality Examinationmentioning

confidence: 99%

Section: Concluding Remarks and Policy Implicationsmentioning

confidence: 99%

Section: Cointegration and Causality Examinationmentioning

confidence: 99%

See 2 more Smart Citations

Empirical Evidence from EU-28 Countries on Resilient Transport Infrastructure Systems and Sustainable Economic Growth

et al. 2018

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“…Such rapid urbanization has generated a multitude of problems and opportunities for not only the economy, but also the environment as urban transport accounts for more than one-fifth of global carbon dioxide emissions (Liddle, 2013). The growth rate of transport energy use -three quarters of which consumed on the road -is projected to increase 2% annually (Saboori et al, 2014). This means that good understandings of road energy use are required to provide insight into the development of more sustainable cities, although the connections between urbanization and environmental impacts are not clear (Brian C O'Neill, 2012;Ergas et al, 2016;Li and Lin, 2015;Liddle, 2014;Ponce De Leon Barido and Marshall, 2014;Poumanyvong and Kaneko, 2010;Ramana Gudipudi and Kropp, 2016).…”

Section: Introductionmentioning

confidence: 99%

Does urbanization lead to less energy use on road transport? Evidence from municipalities in Norway

Liu

Huang

Kaloudis

et al. 2017

Transportation Research Part D: Transport and Environment

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The relationship between urbanization, energy use, and CO2 emissions has been extensively studied in recent years, however little attention paid to the differences in urban forms. Previous studies implicitly assume that the urban form is homogenous across different urban areas. Such an assumption is questionable as urban form can have many different facets. This paper investigates the effects of urbanization on the road transport energy use by considering different urban forms from a dataset of (3) there is a non-linear (quadratic) relationship between road energy use per capita and urban population. This implies that an increase in total municipality population over a specific turning point can result in a decrease in road energy use per capita. However, (4) the ratio of urban residential buildings with private gardens has a negative and significant influence on road transport energy use.This implies that there may be a trade-off between compact and sprawl city development strategies, highlighting that sustainable energy use requires further investigation.

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Air pollution driving factors analysis: Evidence from economically developed area in China

Sun

2016

Env Prog and Sustain Energy

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Rapid economic growth is usually accompanied by rising air pollution in China, especially in the economically developed regions. Beijing is the capital of China, which is selected as a study case in this article. The aim of this study is to authenticate if the Environmental Kuznets curve (EKC) hypothesis exists between air pollution and economic growth in Beijing over the period of 1990–2013, and to understand the driving factors of the air pollution by utilizing the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model. To avoid the multicollinearity of the driving factors, ridge regression is utilized. CO2, SO2 and dust emissions are served as the air pollution indicators. Results show that, both CO2 and SO2 emissions, contribute to an agreement to the EKC hypothesis, while dust emissions do not. Besides, the turning point of SO2 emissions has already achieved in 1999, whereas that of CO2 emissions will be achieved in 2026. Population, urbanization, and industry structure are introduced into the STIRPAT model. In the STIRPAT model, CO2, SO2 and dust emissions all follow the EKC hypothesis, while only SO2 emissions achieved the turning point in 2006, nevertheless, that of CO2 and dust emissions will be achieved in 2023 and 2070, respectively. Population, urbanization, and industry structure factors all contribute a positive impact on CO2 emissions. However, the three factors all exert negative influence on the SO2 and dust emissions. Finally, policies on addressing air pollution problems in Beijing have been discussed. © 2016 American Institute of Chemical Engineers Environ Prog, 35: 1231–1239, 2016

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Economic growth, energy consumption and CO2 emissions in OECD (Organization for Economic Co-operation and Development)'s transport sector: A fully modified bi-directional relationship approach

Cited by 267 publications

References 31 publications

Empirical Evidence from EU-28 Countries on Resilient Transport Infrastructure Systems and Sustainable Economic Growth

Empirical Evidence from EU-28 Countries on Resilient Transport Infrastructure Systems and Sustainable Economic Growth

Does urbanization lead to less energy use on road transport? Evidence from municipalities in Norway

Air pollution driving factors analysis: Evidence from economically developed area in China

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