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Time lags in the pass-through of crude-oil prices: Big data evidence from the German gasoline market

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  • Frondel, Manuel
  • Vance, Colin
  • Kihm, Alex
Abstract
This note investigates the pass-through of global Brent oil notations to fuel prices across the oligopoly of retail majors in Germany. We assemble a high-frequency panel data set that encompasses millions of price observations and allows us to distinguish effects by brand. Upon establishing a cointegrating relationship between fuel and crude-oil prices using daily data, we estimate an error-correction model (ECM) and find that (1) the pass-through of oil prices critically depends on the number of time lags included in the ECM, (2) strict adherence to classical information criteria for determining lag length yields extremely long pass-through durations, and (3) the estimated impulse response functions are virtually identical across brands, irrespective of the lag count, suggesting a high degree of competition among brands.

Suggested Citation

  • Frondel, Manuel & Vance, Colin & Kihm, Alex, 2015. "Time lags in the pass-through of crude-oil prices: Big data evidence from the German gasoline market," Ruhr Economic Papers 573, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    • Handle: RePEc:zbw:rwirep:573
    DOI: 10.4419/86788659
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    References listed on IDEAS

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    1. Joakim Westerlund, 2007. "Testing for Error Correction in Panel Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(6), pages 709-748, December.
    2. Michael D. Noel, 2007. "Edgeworth Price Cycles, Cost-Based Pricing, and Sticky Pricing in Retail Gasoline Markets," The Review of Economics and Statistics, MIT Press, vol. 89(2), pages 324-334, May.
    3. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    4. Haucap, Justus & Heimeshoff, Ulrich & Siekmann, Manuel, 2015. "Price dispersion and station heterogeneity on German retail gasoline markets," DICE Discussion Papers 171, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    5. Zhongmin Wang, 2008. "Collusive Communication and Pricing Coordination in a Retail Gasoline Market," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 32(1), pages 35-52, February.
    6. Matthew Lewis & Michael Noel, 2011. "The Speed of Gasoline Price Response in Markets with and without Edgeworth Cycles," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 672-682, May.
    7. Damiaan Persyn & Joakim Westerlund, 2008. "Error-correction–based cointegration tests for panel data," Stata Journal, StataCorp LP, vol. 8(2), pages 232-241, June.
    8. Matthew S. Lewis, 2009. "Temporary Wholesale Gasoline Price Spikes Have Long-Lasting Retail Effects: The Aftermath of Hurricane Rita," Journal of Law and Economics, University of Chicago Press, vol. 52(3), pages 581-605, August.
    9. Maskin, Eric & Tirole, Jean, 1988. "A Theory of Dynamic Oligopoly, II: Price Competition, Kinked Demand Curves, and Edgeworth Cycles," Econometrica, Econometric Society, vol. 56(3), pages 571-599, May.
    10. Eckert, Andrew, 2003. "Retail price cycles and the presence of small firms," International Journal of Industrial Organization, Elsevier, vol. 21(2), pages 151-170, February.
    11. Michael D. Noel, 2011. "Edgeworth price cycles," The New Palgrave Dictionary of Economics,, Palgrave Macmillan.
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    Cited by:

    1. Frederik von Waldow & Heike Link, 2024. "Spatial Competition and Pass-through of Fuel Taxes: Evidence from a Quasi-natural Experiment in Germany," Discussion Papers of DIW Berlin 2086, DIW Berlin, German Institute for Economic Research.
    2. Frondel, Manuel & Horvath, Marco & Vance, Colin & Kihm, Alexander, 2019. "Increased market transparency in Germany's gasoline market: What about rockets and feathers?," Ruhr Economic Papers 810, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    3. D. O. Olayungbo & T. A. Ojeyinka, 2022. "Crude oil prices pass-through to retail petroleum product prices in Nigeria: evidence from hidden cointegration approach," Economic Change and Restructuring, Springer, vol. 55(2), pages 951-972, May.
    4. Haucap, Justus & Heimeshoff, Ulrich & Siekmann, Manuel, 2016. "Selling gasoline as a by-product: The impact of market structure on local prices," DICE Discussion Papers 240, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    5. Horvath, Marco, 2019. "Germany's market transparency unit for fuels: Fostering collusion or competition?," Ruhr Economic Papers 836, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    6. Siekmann, Manuel, 2017. "Characteristics, causes, and price effects: Empirical evidence of intraday Edgeworth cycles," DICE Discussion Papers 252, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    7. Lesage, James P. & Vance, Colin & Chih, Yao-Yu, 2016. "A Bayesian heterogeneous coefficients spatial autoregressive panel data model of retail fuel price rivalry," Ruhr Economic Papers 617, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    8. Eibelshäuser, Steffen & Wilhelm, Sascha, 2017. "Markets Take Breaks: Dynamic Price Competition with Opening Hours," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168247, Verein für Socialpolitik / German Economic Association.

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    More about this item

    Keywords

    retail markets; competition; error-correction model;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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