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Asymmetries, outliers and structural stability in the US gasoline market

Author

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  • Bagnai, Alberto
  • Mongeau Ospina, Christian Alexander
Abstract
By using a recently developed nonlinear cointegration methodology, and a sample that encompasses more than thirty years of monthly data, we investigate whether the transmission of crude oil price variations to gasoline prices in the US market is asymmetric, i.e.,depends on the sign of the change in the explanatory variable, considering both the long- and the short-run. The model is further extended by taking separately into account the effects of extreme and mild changes in crude oil prices. This allows us to verify whether and to what extent the size and shape of any observed asymmetry in pricing is affected by the presence of outliers. Moreover, given the substantial length of the sample considered, we test for the possible presence of multiple structural breaks of unknown timing in the cointegrating vector. Our results indicate that the relationship between the prices of gasoline and crude oil has undergone a single structural break in the late 2008, and that after the break extreme observations have a non-negligible role in shaping asymmetry.

Suggested Citation

  • Bagnai, Alberto & Mongeau Ospina, Christian Alexander, 2018. "Asymmetries, outliers and structural stability in the US gasoline market," Energy Economics, Elsevier, vol. 69(C), pages 250-260.
    • Handle: RePEc:eee:eneeco:v:69:y:2018:i:c:p:250-260
    DOI: 10.1016/j.eneco.2017.11.014
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    2. Arthur Thomas & Olivier Massol & Benoît Sévi, 2019. "How are day-ahead prices informative for predicting the next day’s consumption of natural gas?," Post-Print hal-04319396, HAL.
    3. Byers, J.W. & Popova, I. & Simkins, B.J., 2021. "Robust estimation of conditional risk measures using machine learning algorithm for commodity futures prices in the presence of outliers," Journal of Commodity Markets, Elsevier, vol. 24(C).
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    5. Ederington, Louis H. & Fernando, Chitru S. & Hoelscher, Seth A. & Lee, Thomas K. & Linn, Scott C., 2019. "A review of the evidence on the relation between crude oil prices and petroleum product prices," Journal of Commodity Markets, Elsevier, vol. 13(C), pages 1-15.
    6. Chen, Chaoyi & Polemis, Michael & Stengos, Thanasis, 2018. "On the Examination of Competition in the Petroleum Industry: A Pooled Panel Threshold Analysis," MPRA Paper 89671, University Library of Munich, Germany.
    7. Cheng, Sheng & Cao, Yan, 2019. "On the relation between global food and crude oil prices: An empirical investigation in a nonlinear framework," Energy Economics, Elsevier, vol. 81(C), pages 422-432.
    8. Zhang, Wenbei & Luckert, Marty & Qiu, Feng, 2023. "Asymmetric price transmission and impulse responses from U.S. crude oil to jet fuel and diesel markets," Energy, Elsevier, vol. 283(C).
    9. Ranjit Kumar Paul & Tanmoy Karak, 2022. "Asymmetric Price Transmission: A Case of Wheat in India," Agriculture, MDPI, vol. 12(3), pages 1-17, March.
    10. Chen, Chaoyi & Polemis, Michael & Stengos, Thanasis, 2019. "Can exchange rate pass-through explain the asymmetric gasoline puzzle? Evidence from a pooled panel threshold analysis of the EU," Energy Economics, Elsevier, vol. 81(C), pages 1-12.
    11. Hamid Baghestani & Jorg Bley, 2020. "Do directional predictions of US gasoline prices reveal asymmetries?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(2), pages 348-360, April.
    12. Bakhat, Mohcine & Rosselló, Jaume & Sansó, Andreu, 2022. "Price transmission between oil and gasoline and diesel: A new measure for evaluating time asymmetries," Energy Economics, Elsevier, vol. 106(C).
    13. Bumpass, Donald & Douglas, Christopher & Ginn, Vance & Tuttle, M.H., 2019. "Testing for short and long-run asymmetric responses and structural breaks in the retail gasoline supply chain," Energy Economics, Elsevier, vol. 83(C), pages 311-318.

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    More about this item

    Keywords

    Asymmetric cointegration; Nonlinear autoregressive distributed lag model; Asymmetric price adjustment; Pass-through; Gasoline price; US gasoline market;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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