IDEAS home Printed from https://ideas.repec.org/p/mib/wpaper/298.html
   My bibliography  Save this paper

Oil Price Forecastability and Economic Uncertainty

Author

Listed:
  • Stelios Bekiros
  • Rangan Gupta
  • Alessia Paccagnini

Abstract

Information on economic policy uncertainty (EPU) does matter in predicting oil returns especially when accounting for omitted nonlinearities in the relationship between these two variables via a time-varying coe¢ cient approach. In this work, we compare the forecastability of standard, Bayesian and TVP-VAR models against the random-walk and benchmark AR models. Our results indicate that over the period 1900:1-2014:2 the time-varying VAR model with stochastic volatility outranks all alternative models.

Suggested Citation

  • Stelios Bekiros & Rangan Gupta & Alessia Paccagnini, 2015. "Oil Price Forecastability and Economic Uncertainty," Working Papers 298, University of Milano-Bicocca, Department of Economics, revised Apr 2015.
    • Handle: RePEc:mib:wpaper:298
    as

    Download full text from publisher

    File URL: http://repec.dems.unimib.it/repec/pdf/mibwpaper298.pdf
    File Function: First version, 2015
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2014. "Forecasting UK GDP growth and inflation under structural change. A comparison of models with time-varying parameters," International Journal of Forecasting, Elsevier, vol. 30(1), pages 129-143.
    2. Kang, Wensheng & Ratti, Ronald A., 2013. "Structural oil price shocks and policy uncertainty," Economic Modelling, Elsevier, vol. 35(C), pages 314-319.
    3. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    4. Antonello D'Agostino & Luca Gambetti & Domenico Giannone, 2013. "Macroeconomic forecasting and structural change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 82-101, January.
    5. James D. Hamilton, 2009. "Causes and Consequences of the Oil Shock of 2007-08," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 40(1 (Spring), pages 215-283.
    6. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    7. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    8. Bekiros, Stelios D. & Paccagnini, Alessia, 2015. "Macroprudential Policy And Forecasting Using Hybrid Dsge Models With Financial Frictions And State Space Markov-Switching Tvp-Vars," Macroeconomic Dynamics, Cambridge University Press, vol. 19(7), pages 1565-1592, October.
    9. Nikolaos Antonakakis & Ioannis Chatziantoniou & George Filis, 2014. "Dynamic Spillovers of Oil Price Shocks and Policy Uncertainty," Department of Economics Working Papers wuwp166, Vienna University of Economics and Business, Department of Economics.
    10. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2014. "Dynamic spillovers of oil price shocks and economic policy uncertainty," Energy Economics, Elsevier, vol. 44(C), pages 433-447.
    11. Jones, Paul M. & Olson, Eric, 2013. "The time-varying correlation between uncertainty, output, and inflation: Evidence from a DCC-GARCH model," Economics Letters, Elsevier, vol. 118(1), pages 33-37.
    12. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    13. Kang, Wensheng & Ratti, Ronald A., 2013. "Oil shocks, policy uncertainty and stock market return," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 305-318.
    14. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    15. Baumeister, Christiane & Liu, Philip & Mumtaz, Haroon, 2013. "Changes in the effects of monetary policy on disaggregate price dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 543-560.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bonaccolto, G. & Caporin, M. & Gupta, R., 2018. "The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 446-469.
    2. Aloui, Riadh & Gupta, Rangan & Miller, Stephen M., 2016. "Uncertainty and crude oil returns," Energy Economics, Elsevier, vol. 55(C), pages 92-100.
    3. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2017. "Oil price shocks and policy uncertainty: New evidence on the effects of US and non-US oil production," Energy Economics, Elsevier, vol. 66(C), pages 536-546.
    4. Bekiros, Stelios & Gupta, Rangan & Majumdar, Anandamayee, 2016. "Incorporating economic policy uncertainty in US equity premium models: A nonlinear predictability analysis," Finance Research Letters, Elsevier, vol. 18(C), pages 291-296.
    5. Gil-Alana, Luis A. & Gupta, Rangan & Olubusoye, Olusanya E. & Yaya, OlaOluwa S., 2016. "Time series analysis of persistence in crude oil price volatility across bull and bear regimes," Energy, Elsevier, vol. 109(C), pages 29-37.
    6. Mehmet Balcilar & Stelios Bekiros & Rangan Gupta, 2017. "The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method," Empirical Economics, Springer, vol. 53(3), pages 879-889, November.
    7. Balcilar, Mehmet & Gupta, Rangan & Wohar, Mark E., 2017. "Common cycles and common trends in the stock and oil markets: Evidence from more than 150years of data," Energy Economics, Elsevier, vol. 61(C), pages 72-86.
    8. Tunc, Ahmet & Kocoglu, Mustafa & Aslan, Alper, 2022. "Time-varying characteristics of the simultaneous interactions between economic uncertainty, international oil prices and GDP: A novel approach for Germany," Resources Policy, Elsevier, vol. 77(C).
    9. Yingce Yang & Junjie Guo & Ruihong He, 2023. "The Asymmetric Impact of the Oil Price and Disaggregate Shocks on Economic Policy Uncertainty: Evidence From China," SAGE Open, , vol. 13(2), pages 21582440231, June.
    10. Yuan, Di & Li, Sufang & Li, Rong & Zhang, Feipeng, 2022. "Economic policy uncertainty, oil and stock markets in BRIC: Evidence from quantiles analysis," Energy Economics, Elsevier, vol. 110(C).
    11. Song, Lu & Tian, Gengyu & Jiang, Yonghong, 2022. "Connectedness of commodity, exchange rate and categorical economic policy uncertainties — Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    12. Stavros Degiannakis & George Filis, 2019. "Forecasting European economic policy uncertainty," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 94-114, February.
    13. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    14. Dash, Saumya Ranjan & Maitra, Debasish, 2021. "Do oil and gas prices influence economic policy uncertainty differently: Multi-country evidence using time-frequency approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 397-420.
    15. Selmi, Refk & Mensi, Walid & Hammoudeh, Shawkat & Bouoiyour, Jamal, 2018. "Is Bitcoin a hedge, a safe haven or a diversifier for oil price movements? A comparison with gold," Energy Economics, Elsevier, vol. 74(C), pages 787-801.
    16. Sheng, Xin & Gupta, Rangan & Ji, Qiang, 2020. "The impacts of structural oil shocks on macroeconomic uncertainty: Evidence from a large panel of 45 countries," Energy Economics, Elsevier, vol. 91(C).
    17. Cai, Yifei & Wu, Yanrui, 2019. "Time-varied causality between US partisan conflict shock and crude oil return," Energy Economics, Elsevier, vol. 84(C).
    18. Kang, Wensheng & de Gracia, Fernando Perez & Ratti, Ronald A., 2019. "The asymmetric response of gasoline prices to oil price shocks and policy uncertainty," Energy Economics, Elsevier, vol. 77(C), pages 66-79.
    19. Mawuli Segnon & Rangan Gupta & Stelios Bekiros & Mark E. Wohar, 2018. "Forecasting US GNP growth: The role of uncertainty," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 541-559, August.
    20. Bampinas, Georgios & Panagiotidis, Theodore & Papapanagiotou, Georgios, 2023. "Oil shocks and investor attention," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 68-81.

    More about this item

    Keywords

    Oil prices; Economic policy uncertainty; Forecasting;
    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
    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mib:wpaper:298. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Matteo Pelagatti (email available below). General contact details of provider: https://edirc.repec.org/data/dpmibit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.