IDEAS home Printed from https://ideas.repec.org/a/ayb/jrnerl/13.html
   My bibliography  Save this article

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

Author

Listed:
  • H. Murat ErtuÄŸrul
  • B. Oray Güngör
  • UÄŸur SoytaÅŸ

    (Asia Pacific Applied Economics Association)

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

  • H. Murat ErtuÄŸrul & B. Oray Güngör & UÄŸur SoytaÅŸ, 2021. "The Effect of the COVID-19 Outbreak on the Turkish Diesel Consumption Volatility Dynamics," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, vol. 1(1), pages 1-4.
    • Handle: RePEc:ayb:jrnerl:13
    DOI: 2021/06/16
    as

    Download full text from publisher

    File URL: https://erl.scholasticahq.com/api/v1/articles/17496-the-effect-of-the-covid-19-outbreak-on-the-turkish-diesel-consumption-volatility-dynamics.pdf
    Download Restriction: no
    File URL: https://libkey.io/2021/06/16?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    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. 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.
    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. 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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Narayan, Paresh Kumar, 2022. "Evidence of oil market price clustering during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 80(C).
    14. 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.
    15. 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.
    16. 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).

    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. Melo, Patricia C. & Ramli, Ahmad Razi, 2014. "Estimating fuel demand elasticities to evaluate CO2 emissions: Panel data evidence for the Lisbon Metropolitan Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 30-46.
    6. Cen, Zhongpei & Wang, Jun, 2019. "Crude oil price prediction model with long short term memory deep learning based on prior knowledge data transfer," Energy, Elsevier, vol. 169(C), pages 160-171.
    7. 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.
    8. 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.
    9. Atul Anand & L. Suganthi, 2017. "Forecasting of Electricity Demand by Hybrid ANN-PSO Models," International Journal of Energy Optimization and Engineering (IJEOE), IGI Global, vol. 6(4), pages 66-83, October.
    10. Vu, D.H. & Muttaqi, K.M. & Agalgaonkar, A.P., 2015. "A variance inflation factor and backward elimination based robust regression model for forecasting monthly electricity demand using climatic variables," Applied Energy, Elsevier, vol. 140(C), pages 385-394.
    11. 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).
    12. Alobaidi, Mohammad H. & Chebana, Fateh & Meguid, Mohamed A., 2018. "Robust ensemble learning framework for day-ahead forecasting of household based energy consumption," Applied Energy, Elsevier, vol. 212(C), pages 997-1012.
    13. Tang, Ling & Yu, Lean & Wang, Shuai & Li, Jianping & Wang, Shouyang, 2012. "A novel hybrid ensemble learning paradigm for nuclear energy consumption forecasting," Applied Energy, Elsevier, vol. 93(C), pages 432-443.
    14. Gulasekaran Rajaguru & Safdar Ullah Khan, 2021. "Causality between Energy Consumption and Economic Growth in the Presence of Growth Volatility: Multi-Country Evidence," JRFM, MDPI, vol. 14(10), pages 1-26, October.
    15. Wang, Zheng-Xin & Wang, Zhi-Wei & Li, Qin, 2020. "Forecasting the industrial solar energy consumption using a novel seasonal GM(1,1) model with dynamic seasonal adjustment factors," Energy, Elsevier, vol. 200(C).
    16. Hajirahimi, Zahra & Khashei, Mehdi & Etemadi, Sepideh, 2022. "A novel class of reliability-based parallel hybridization (RPH) models for time series forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    17. Abdollahi, Hooman & Ebrahimi, Seyed Babak, 2020. "A new hybrid model for forecasting Brent crude oil price," Energy, Elsevier, vol. 200(C).
    18. 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.
    19. Tulin Guzel & Hakan Cinar & Mehmet Nabi Cenet & Kamil Doruk Oguz & Ahmet Yucekaya & Mustafa Hekimoglu, 2023. "A Framework to Forecast Electricity Consumption of Meters using Automated Ranking and Data Preprocessing," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 179-193, September.
    20. Nazneen Ferdous & Abdul Pinjari & Chandra Bhat & Ram Pendyala, 2010. "A comprehensive analysis of household transportation expenditures relative to other goods and services: an application to United States consumer expenditure data," Transportation, Springer, vol. 37(3), pages 363-390, May.

    More about this item

    Keywords

    diesel consumption ; arima models; arch family models; covid-19 pandemic;
    All these keywords.

    JEL classification:

    • O - Economic Development, Innovation, Technological Change, and Growth

    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:ayb:jrnerl:13. 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: Asia-Pacific Applied Economics Association (email available below). General contact details of provider: https://edirc.repec.org/data/apaeaea.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.