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Long-Term Oil Price Forecasts: A New Perspective on Oil and the Macroeconomy

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Abstract

We examine how future real GDP growth relates to changes in the forecasted long-term average of discounted real oil prices and to changes in unanticipated fluctuationsof real oil prices around the forecasts. Forecasts are conducted using a state-space oil market model, in which global real economic activity and real oil prices share a commonstochastic trend. Changes in unanticipated fluctuations and changes in the forecasted long-term average of discounted real oil prices sum to real oil price changes. We find thatthese two components have distinctly different relationships with future real GDP growth. Positive and negative changes in the unanticipated fluctuations of real oil prices correlatewith asymmetric responses of future real GDP growth. In comparison, changes in the forecasted long-term average are smaller in magnitude but are more influential on real GDP.Persistent upward revisions of forecasts in the 2000s had a substantial negative impact on real GDP growth, according to our estimates.. Classification-JEL: E31, E32, Q43

Suggested Citation

  • J. Isaac Miller & Shawn Ni, 2010. "Long-Term Oil Price Forecasts: A New Perspective on Oil and the Macroeconomy," Working Papers 1012, Department of Economics, University of Missouri.
    • Handle: RePEc:umc:wpaper:1012
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    Cited by:

    1. Turhan, M. Ibrahim & Sensoy, Ahmet & Ozturk, Kevser & Hacihasanoglu, Erk, 2014. "A view to the long-run dynamic relationship between crude oil and the major asset classes," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 286-299.
    2. Claudio Morana, 2013. "The Oil Price-Macroeconomy Relationship Since the Mid-1980s: A Global Perspective," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    3. Ratti, Ronald A. & Vespignani, Joaquin L., 2013. "Liquidity and crude oil prices: China's influence over 1996–2011," Economic Modelling, Elsevier, vol. 33(C), pages 517-525.
    4. Ratti, Ronald & Vespignani, Joaquin, 2012. "Liquidity and crude oil prices: China’s influence over 1996-2011," Working Papers 15062, University of Tasmania, Tasmanian School of Business and Economics, revised 20 Sep 2012.
    5. Zhang, Chuanguo & Chen, Xiaoqing, 2014. "The impact of global oil price shocks on China’s bulk commodity markets and fundamental industries," Energy Policy, Elsevier, vol. 66(C), pages 32-41.
    6. Benk, Szilard & Gillman, Max, 2023. "Identifying money and inflation expectation shocks to real oil prices," Energy Economics, Elsevier, vol. 126(C).
    7. J. Isaac Miller, 2014. "Mixed-frequency Cointegrating Regressions with Parsimonious Distributed Lag Structures," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 584-614.
    8. Bielak, Łukasz & Grzesiek, Aleksandra & Janczura, Joanna & Wyłomańska, Agnieszka, 2021. "Market risk factors analysis for an international mining company. Multi-dimensional, heavy-tailed-based modelling," Resources Policy, Elsevier, vol. 74(C).
    9. Tapia, Carlos & Coulton, Jeff & Saydam, Serkan, 2020. "Using entropy to assess dynamic behaviour of long-term copper price," Resources Policy, Elsevier, vol. 66(C).
    10. Mont'Alverne Duarte, Angelo & Gaglianone, Wagner Piazza & de Carvalho Guillén, Osmani Teixeira & Issler, João Victor, 2021. "Commodity prices and global economic activity: A derived-demand approach," Energy Economics, Elsevier, vol. 96(C).
    11. Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
    12. Richard A. Ashley & Kwok Ping Tsang, 2014. "Credible Granger-Causality Inference with Modest Sample Lengths: A Cross-Sample Validation Approach," Econometrics, MDPI, Open Access Journal, vol. 2(1), pages 1-20, March.
    13. Alexander HARIN, 2014. "Partially Unforeseen Events. Corrections and Correcting Formulae for Forecasts," Expert Journal of Economics, Sprint Investify, vol. 2(2), pages 69-79.

    More about this item

    Keywords

    oil price and the macroeconomy; oil market fundamental; oil price forecasts; Kalman filter;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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