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Another perspective on gasoline price responses to crude oil price changes

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  • Rahman, Sajjadur

Abstract

The effects of oil price volatility on the responses of gasoline prices to oil price shocks have received little attention in discussions on the relationship between the prices of crude oil and gasoline. In this paper we consider such effects by using a bivariate structural vector autoregression which is modified to accommodate GARCH-in-mean errors. Our measure of oil price volatility is the conditional variance of the oil price–change forecast error. We isolate the effects of volatility in the price of oil on the price of gasoline and employ simulation methods to calculate nonlinear impulse response functions (NIRFs) to trace any asymmetric effects of independent oil price shocks on the conditional means of gasoline prices. We test whether the relationship between the prices of crude oil and gasoline is symmetric using tests of the null hypothesis of symmetric impulse responses. Based on monthly U.S. data over the period from 1978:1 to 2014:11, our empirical results show that gasoline prices respond asymmetrically to positive and negative oil price shocks. We also find that oil price volatility has a positive effect on the price of gasoline and it contributes to the asymmetries in the transmission of oil price shocks.

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  • Rahman, Sajjadur, 2016. "Another perspective on gasoline price responses to crude oil price changes," Energy Economics, Elsevier, vol. 55(C), pages 10-18.
    • Handle: RePEc:eee:eneeco:v:55:y:2016:i:c:p:10-18
    DOI: 10.1016/j.eneco.2015.12.021
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    10. Karol Szomolanyi & Martin Lukacik & Adriana Lukacikova, 2022. "Estimation of asymmetric responses of U.S. retail fuel prices to changes in input prices based on a linear exponential adjustment cost approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 757-779, June.
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    12. James Ming Chen & Mobeen Ur Rehman, 2021. "A Pattern New in Every Moment: The Temporal Clustering of Markets for Crude Oil, Refined Fuels, and Other Commodities," Energies, MDPI, vol. 14(19), pages 1-58, September.
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    15. Vietha Devia SS, 2019. "Analysis of Crude Oil Price and Exchange Rate Volatility on Macroeconomic Variables (Case Study of Indonesia as Emerging Economic Country)," International Journal of Business and Administrative Studies, Professor Dr. Bahaudin G. Mujtaba, vol. 5(5), pages 257-271.
    16. Lahiani, Amine & Miloudi, Anthony & Benkraiem, Ramzi & Shahbaz, Muhammad, 2017. "Another look on the relationships between oil prices and energy prices," Energy Policy, Elsevier, vol. 102(C), pages 318-331.
    17. Łukasz Warguła & Mateusz Kukla & Piotr Lijewski & Michał Dobrzyński & Filip Markiewicz, 2020. "Influence of Innovative Woodchipper Speed Control Systems on Exhaust Gas Emissions and Fuel Consumption in Urban Areas," Energies, MDPI, vol. 13(13), pages 1-22, June.
    18. Pradeep, Siddhartha, 2022. "Impact of diesel price reforms on asymmetricity of oil price pass-through to inflation: Indian perspective," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    19. Sun, Yuying & Zhang, Xun & Hong, Yongmiao & Wang, Shouyang, 2019. "Asymmetric pass-through of oil prices to gasoline prices with interval time series modelling," Energy Economics, Elsevier, vol. 78(C), pages 165-173.
    20. Zirgulis Aras, 2016. "The Impact of Oil Refinery Market Power on Retail Fuel Prices in the European Union," Ekonomika (Economics), Sciendo, vol. 95(3), pages 37-51, December.

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    More about this item

    Keywords

    Crude Oil; Volatility; Vector Autoregression; Bivariate GARCH-in-Mean;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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