IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/110166.html
   My bibliography  Save this paper

The Effect of Covid-19 Outbreak on Turkish Diesel Consumption Volatility Dynamics

Author

Listed:
  • Ertugrul, H. Murat
  • Güngör, B. Oray
  • Soytas, Ugur

Abstract

We analyze the effect of the COVID-19 outbreak on volatility dynamics of the Turkish diesel market. We observe that a high volatility pattern starts around mid-April, 2020 and reaches its peak on 24/05/2020. This is due to the government imposed weekend curfews and bans on intercity travels. Two policy suggestions are provided. First is a temporary rearrangement of profit margins of dealers and liquid fuel distributors; and, second is a temporary tax regulation to compensate lost tax revenue.

Suggested Citation

  • Ertugrul, H. Murat & Güngör, B. Oray & Soytas, Ugur, 2020. "The Effect of Covid-19 Outbreak on Turkish Diesel Consumption Volatility Dynamics," MPRA Paper 110166, University Library of Munich, Germany, revised 2020.
    • Handle: RePEc:pra:mprapa:110166
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/110166/1/MPRA_paper_110166.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Li, Jingrui & Wang, Rui & Wang, Jianzhou & Li, Yifan, 2018. "Analysis and forecasting of the oil consumption in China based on combination models optimized by artificial intelligence algorithms," Energy, Elsevier, vol. 144(C), pages 243-264.
    2. Abdul Rashid & Ozge Kandemir Kocaaslan, 2013. "Does Energy Consumption Volatility Affect Real GDP Volatility? An Empirical Analysis for the UK," International Journal of Energy Economics and Policy, Econjournals, vol. 3(4), pages 384-394.
    3. Li, Zheng & Rose, John M. & Hensher, David A., 2010. "Forecasting automobile petrol demand in Australia: An evaluation of empirical models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(1), pages 16-38, January.
    4. Zhu, Suling & Wang, Jianzhou & Zhao, Weigang & Wang, Jujie, 2011. "A seasonal hybrid procedure for electricity demand forecasting in China," Applied Energy, Elsevier, vol. 88(11), pages 3807-3815.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bing, Tao & Ma, Hongkun, 2021. "COVID-19 pandemic effect on trading and returns: Evidence from the Chinese stock market," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 384-396.
    2. Wang, Hui & Shen, Huayu & Tang, Xiaoyi & Wu, Zuofeng & Ma, Shuming, 2021. "Trade policy uncertainty and firm risk taking," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 351-364.
    3. Padhan, Rakesh & Prabheesh, K.P., 2021. "The economics of COVID-19 pandemic: A survey," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 220-237.
    4. Łukasz Gębski, 2021. "The Impact of the Crisis Triggered by the COVID-19 Pandemic and the Actions of Regulators on the Consumer Finance Market in Poland and Other European Union Countries," Risks, MDPI, vol. 9(6), pages 1-15, June.
    5. Sui, Bo & Chang, Chun-Ping & Jang, Chyi-Lu & Gong, Qiang, 2021. "Analyzing causality between epidemics and oil prices: Role of the stock market," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 148-158.
    6. Krzysztof Dmytrów & Joanna Landmesser & Beata Bieszk-Stolorz, 2021. "The Connections between COVID-19 and the Energy Commodities Prices: Evidence through the Dynamic Time Warping Method," Energies, MDPI, vol. 14(13), pages 1-23, July.
    7. Daniel Stefan Armeanu & Stefan Cristian Gherghina & Jean Vasile Andrei & Camelia Catalina Joldes, 2023. "Evidence from the nonlinear autoregressive distributed lag model on the asymmetric influence of the first wave of the COVID-19 pandemic on energy markets," Energy & Environment, , vol. 34(5), pages 1433-1470, August.
    8. Chen, Yin-E & Li, Chunyan & Chang, Chun-Ping & Zheng, Mingbo, 2021. "Identifying the influence of natural disasters on technological innovation," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 22-36.
    9. Narayan, Paresh Kumar & Devpura, Neluka & Wang, Hua, 2020. "Japanese currency and stock market—What happened during the COVID-19 pandemic?," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 191-198.
    10. Naidu, Dharmendra & Ranjeeni, Kumari, 2021. "Effect of coronavirus fear on the performance of Australian stock returns: Evidence from an event study," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
    11. LI, Yang & Luo, Jingqiu & Jiang, Yongmu, 2021. "Policy uncertainty spillovers and financial risk contagion in the Asia-Pacific network," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    12. Zorana Zoran Stanković & Milena Nebojsa Rajic & Zorana Božić & Peđa Milosavljević & Ancuța Păcurar & Cristina Borzan & Răzvan Păcurar & Emilia Sabău, 2024. "The Volatility Dynamics of Prices in the European Power Markets during the COVID-19 Pandemic Period," Sustainability, MDPI, vol. 16(6), pages 1-16, March.
    13. Güngör, Bekir Oray & Ertuğrul, H. Murat & Soytaş, Uğur, 2021. "Impact of Covid-19 outbreak on Turkish gasoline consumption," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    14. Feng, Gen-Fu & Yang, Hao-Chang & Gong, Qiang & Chang, Chun-Ping, 2021. "What is the exchange rate volatility response to COVID-19 and government interventions?," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 705-719.
    15. Kai-Hua Wang & Chi-Wei Su, 2021. "Asymmetric Link Between COVID-19 and Fossil Energy Prices," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 1(4), pages 1-5.
    16. Prabheesh KP, 2021. "Dynamics of Foreign Portfolio Investment and Stock Market Returns During the COVID-19 Pandemic - Evidence From India," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 1(2), pages 1-5.
    17. Narayan, Paresh Kumar, 2022. "Evidence of oil market price clustering during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 80(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Güngör, Bekir Oray & Ertuğrul, H. Murat & Soytaş, Uğur, 2021. "Impact of Covid-19 outbreak on Turkish gasoline consumption," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    2. Xiao, Liye & Shao, Wei & Liang, Tulu & Wang, Chen, 2016. "A combined model based on multiple seasonal patterns and modified firefly algorithm for electrical load forecasting," Applied Energy, Elsevier, vol. 167(C), pages 135-153.
    3. Rao, Congjun & Zhang, Yue & Wen, Jianghui & Xiao, Xinping & Goh, Mark, 2023. "Energy demand forecasting in China: A support vector regression-compositional data second exponential smoothing model," Energy, Elsevier, vol. 263(PC).
    4. Yu, Feng & Xu, Xiaozhong, 2014. "A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network," Applied Energy, Elsevier, vol. 134(C), pages 102-113.
    5. Samet G nay, 2015. "Markov Regime Switching Generalized Autoregressive Conditional Heteroskedastic Model and Volatility Modeling for Oil Returns," International Journal of Energy Economics and Policy, Econjournals, vol. 5(4), pages 979-985.
    6. W H Boshoff, 2012. "Gasoline, Diesel Fuel And Jet Fuel Demand In South Africa," Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 36(1), pages 43-78, April.
    7. Baratsas, Stefanos G. & Niziolek, Alexander M. & Onel, Onur & Matthews, Logan R. & Floudas, Christodoulos A. & Hallermann, Detlef R. & Sorescu, Sorin M. & Pistikopoulos, Efstratios N., 2022. "A novel quantitative forecasting framework in energy with applications in designing energy-intelligent tax policies," Applied Energy, Elsevier, vol. 305(C).
    8. Abdollahi, Hooman & Ebrahimi, Seyed Babak, 2020. "A new hybrid model for forecasting Brent crude oil price," Energy, Elsevier, vol. 200(C).
    9. Besma Talbi, 2015. "Energy Intensity and Economic Growth in the MENA Region: Analyses of Panel Heterogeneous," Bulletin of Energy Economics (BEE), The Economics and Social Development Organization (TESDO), vol. 3(4), pages 169-175, December.
    10. An, Ning & Zhao, Weigang & Wang, Jianzhou & Shang, Duo & Zhao, Erdong, 2013. "Using multi-output feedforward neural network with empirical mode decomposition based signal filtering for electricity demand forecasting," Energy, Elsevier, vol. 49(C), pages 279-288.
    11. Al-Ghandoor, Ahmed & Jaber, Jamal & Al-Hinti, Ismael & Abdallat, Yousef, 2013. "Statistical assessment and analyses of the determinants of transportation sector gasoline demand in Jordan," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 129-138.
    12. Nugroho, Andry Satrio, 2015. "Analisis Ketahanan Minyak di 15 Negara Pengimpor Minyak Tahun 2010 [Analysis of Oil Vulnerability in 15 Oil Importing Countries in 2010]," MPRA Paper 88901, University Library of Munich, Germany.
    13. Xuejun Li & Minghua Jiang & Deyu Cai & Wenqin Song & Yalu Sun, 2024. "A Hybrid Forecasting Model for Electricity Demand in Sustainable Power Systems Based on Support Vector Machine," Energies, MDPI, vol. 17(17), pages 1-16, September.
    14. Mohcine Bakhat & José M. Labeaga & Xavier Labandeira & Xiral Lñpez, 2013. "Economic Crisis and Elasticities of Car Fuels: Evidence for Spain," Working Papers fa15-2013, Economics for Energy.
    15. Ali K k & Erg n Y kseltan & Mustafa Hekimo lu & Esra Agca Aktunc & Ahmet Y cekaya & Ay e Bilge, 2022. "Forecasting Hourly Electricity Demand Under COVID-19 Restrictions," International Journal of Energy Economics and Policy, Econjournals, vol. 12(1), pages 73-85.
    16. Wai-Ming To & Peter Ka Chun Lee & Tsz-Ming Lai, 2017. "Modeling of Monthly Residential and Commercial Electricity Consumption Using Nonlinear Seasonal Models—The Case of Hong Kong," Energies, MDPI, vol. 10(7), pages 1-16, June.
    17. Sudeshna Ghosh, 2019. "Environmental Pollution, Income Inequality, and Household Energy Consumption: Evidence from the United Kingdom," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-31, June.
    18. Safari, Ali & Davallou, Maryam, 2018. "Oil price forecasting using a hybrid model," Energy, Elsevier, vol. 148(C), pages 49-58.
    19. Pan, Xunzhang & Wang, Lining & Dai, Jiaquan & Zhang, Qi & Peng, Tianduo & Chen, Wenying, 2020. "Analysis of China’s oil and gas consumption under different scenarios toward 2050: An integrated modeling," Energy, Elsevier, vol. 195(C).
    20. Herrera, Gabriel Paes & Constantino, Michel & Tabak, Benjamin Miranda & Pistori, Hemerson & Su, Jen-Je & Naranpanawa, Athula, 2019. "Long-term forecast of energy commodities price using machine learning," Energy, Elsevier, vol. 179(C), pages 214-221.

    More about this item

    Keywords

    Diesel Consumption; ARIMA Models; ARCH Family Models; Covid-19 pandemic;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:110166. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.