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Oil price forecastability and economic uncertainty

Author

Listed:
  • Stelios D. Bekiros
  • Rangan Gupta
  • Alessia Paccagnini

Abstract

Information on economic policy uncertainty does matter in predicting the change in oil prices. We compare the forecastability of standard, Bayesian and time-varying VAR against univariate models. The time-varying VAR model outranks all alternative models over the period 2007:1–2014:2.

Suggested Citation

  • Stelios D. Bekiros & Rangan Gupta & Alessia Paccagnini, 2015. "Oil price forecastability and economic uncertainty," Open Access publications 10197/7345, School of Economics, University College Dublin.
  • Handle: RePEc:ucn:oapubs:10197/7345
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    File URL: http://hdl.handle.net/10197/7345
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    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

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