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Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump

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  • Christiane Baumeister
  • Lutz Kilian
  • Thomas K. Lee

Abstract

Appropriate real‐time forecasting models for the US retail price of gasoline yield substantial reductions in the mean‐squared prediction error (MSPE) at horizons up to 2 years as well as substantial increases in directional accuracy. Even greater MSPE reductions are possible by constructing a pooled forecast that assigns equal weight to five of the most successful forecasting models. Pooled forecasts have lower MSPE than the US Energy Information Administration gasoline price forecasts and the gasoline price expectations in the Michigan Survey of Consumers. We also show that as much as 39% of the decline in gas prices between June and December 2014 was predictable. Copyright © 2016 John Wiley & Sons, Ltd.

Suggested Citation

  • Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2017. "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 275-295, March.
  • Handle: RePEc:wly:japmet:v:32:y:2017:i:2:p:275-295
    DOI: 10.1002/jae.2510
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    Cited by:

    1. John Coglianese & Lucas W. Davis & Lutz Kilian & James H. Stock, 2017. "Anticipation, Tax Avoidance, and the Price Elasticity of Gasoline Demand," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 1-15, January.
    2. Gupta, Rangan & Yoon, Seong-Min, 2018. "OPEC news and predictability of oil futures returns and volatility: Evidence from a nonparametric causality-in-quantiles approach," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 206-214.
    3. Sameh Asim Ajlouni & Moh'd Taleb Alodat, 2021. "Gaussian Process Regression for Forecasting Gasoline Prices in Jordan," International Journal of Energy Economics and Policy, Econjournals, vol. 11(3), pages 502-509.
    4. Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2020. "Energy Markets and Global Economic Conditions," CESifo Working Paper Series 8282, CESifo.
    5. Christiane Baumeister & Reinhard Ellwanger & Lutz Kilian, 2016. "Did the Renewable Fuel Standard Shift Market Expectations of the Price of Ethanol?," CESifo Working Paper Series 6282, CESifo.
    6. Christiane Baumeister & Lutz Kilian, 2016. "Lower Oil Prices and the U.S. Economy: Is This Time Different?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(2 (Fall)), pages 287-357.
    7. Binder, Carola Conces, 2018. "Inflation expectations and the price at the pump," Journal of Macroeconomics, Elsevier, vol. 58(C), pages 1-18.
    8. Christiane Baumeister & Lutz Killian, 2016. "Lower Oil Prices and the U.S. Economy: Is This Time Different?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(2 (Fall)), pages 287-357.
    9. Pincheira, Pablo & Jarsun, Nabil, 2020. "Summary of the Paper Entitled: Forecasting Fuel Prices with the Chilean Exchange Rate," MPRA Paper 105056, University Library of Munich, Germany.
    10. 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.
    11. Arunanondchai, Panit & Senia, Mark C. & Capps, Oral Jr, 2017. "Can U.S. EIA Retail Gasoline Price Forecasts Be Improved Upon?," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252717, Southern Agricultural Economics Association.
    12. Feng Xu & Mohamad Sepehri & Jian Hua & Sergey Ivanov & Julius N. Anyu, 2018. "Time-Series Forecasting Models for Gasoline Prices in China," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(12), pages 1-43, December.

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    JEL classification:

    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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