Gasoline and diesel demand in the EU: Implications for the 2030 emission goal

Aklilu, Abenezer Zeleke

doi:10.1016/j.rser.2019.109530

Cited by 27 publications

(17 citation statements)

References 15 publications

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“…Additionally, the Hellenic Ministry of Environment and Energy finds that petrol and diesel fuel availability up to 2030 and beyond will be adequate to meet demand [65]. Furthermore, according to a study [110], for petrol and diesel fuels demand in 2030, in Greece, minimum additional measures will be needed affecting fuel price and therefore fuel availability. So, the availability of fuel up to 2030 was not considered as another factor in this study.…”

Section: Discussionmentioning

confidence: 99%

Transportation and Air Quality Perspectives and Projections in a Mediterranean Country, the Case of Greece

Spyropoulos

Nastos

Moustris

et al. 2022

Land

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This study provides a thorough review and analysis of the evolution of the Greek vehicle fleet over the last ~30 years, which is next used for the generation of high granularity fleet projections, the assessment of associated air pollution and the estimation of relevant environmental benefits by 2030. The integrated methodology developed takes also into account vehicle clustering and the Brown’s Double Simple Exponential Smoothing technique that, together with the adoption of COPERT-based emission factors, allow for the estimation of the anticipated emissions in 2030. Expected 2030 emissions levels suggest a reduction across all pollutants compared to 2018, ranging from 3.7% for PM10 to 54.5% for NMVOC (and 46% for CO, 14% for SO2, 28% for NOX and 21% for CO2). We find that Greece is on track with national goals concerning the reduction of air pollution from the transportation sector, which designates the positive contribution anticipated by EVs and new, “greener” vehicles, and sets new challenges for the further improvement of the sector beyond the 2030 outlook.

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Section: Discussionmentioning

confidence: 99%

Transportation and Air Quality Perspectives and Projections in a Mediterranean Country, the Case of Greece

Spyropoulos

Nastos

Moustris

et al. 2022

Land

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“…Authors in [ 19 ] studied the demand for gasoline and diesel in Europe. The Autoregressive-Distributed Lag (ARDL) model has been used to measure the short-run and long-run costs along with income elasticities for diesel and gasoline demands.…”

Section: Methodsmentioning

confidence: 99%

Self-organizing Maps and Bayesian Regularized Neural Network for Analyzing Gasoline and Diesel Price Drifts

Sujatha

Chatterjee

Priyadarshini

et al. 2022

Int J Comput Intell Syst

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Any nation’s growth depends on the trend of the price of fuel. The fuel price drifts have both direct and indirect impacts on a nation’s economy. Nation’s growth will be hampered due to the higher level of inflation prevailing in the oil industry. This paper proposed a method of analyzing Gasoline and Diesel Price Drifts based on Self-organizing Maps and Bayesian regularized neural networks. The US gasoline and diesel price timeline dataset is used to validate the proposed approach. In the dataset, all grades, regular, medium, and premium with conventional, reformulated, all formulation of gasoline combinations, and diesel pricing per gallon weekly from 1995 to January 2021, are considered. For the data visualization purpose, we have used self-organizing maps and analyzed them with a neural network algorithm. The nonlinear autoregressive neural network is adopted because of the time series dataset. Three training algorithms are adopted to train the neural networks: Levenberg-Marquard, scaled conjugate gradient, and Bayesian regularization. The results are hopeful and reveal the robustness of the proposed model. In the proposed approach, we have found Levenberg-Marquard error falls from − 0.1074 to 0.1424, scaled conjugate gradient error falls from − 0.1476 to 0.1618, and similarly, Bayesian regularization error falls in − 0.09854 to 0.09871, which showed that out of the three approaches considered, the Bayesian regularization gives better results.

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“…Several studies compile existing estimates of demand elasticity of gasoline, diesel and crude oil (see for example Hamilton 2009, Caldara et al 2016, Hössinger et al 2017, Aklilu 2020). These estimates are derived using different methods over different time periods and locations.…”

Section: Elasticity Of Demandmentioning

confidence: 99%

What is the effect of EU’s fuel-tax cuts on Russia’s oil income?

Gars

Spiro

Wachtmeister

2022

Preprint

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Following the oil-price surge in the wake of Russia’s invasion of Ukraine, many countries in the EU are cutting taxes on petrol and diesel. Using standard theory and empirical estimates, we assess how such tax cuts influence the oil income in Russia. We find that a tax cut of 20 euro cents per liter increase Russia’s oil profits by around 11 million Euros per day in the short run and long run. This is equivalent to 4100 million Euros in a year, 0.3% of Russia’s GDP or 7% of its military spending. We show that a cash transfer to EU citizens, with an equivalent fiscal burden as the tax cut, reduces these side effects to a fraction.

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Gasoline and diesel demand in the EU: Implications for the 2030 emission goal

Cited by 27 publications

References 15 publications

Transportation and Air Quality Perspectives and Projections in a Mediterranean Country, the Case of Greece

Transportation and Air Quality Perspectives and Projections in a Mediterranean Country, the Case of Greece

Self-organizing Maps and Bayesian Regularized Neural Network for Analyzing Gasoline and Diesel Price Drifts

What is the effect of EU’s fuel-tax cuts on Russia’s oil income?

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