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An Identification-Robust Test for Time-Varying Parameters in the Dynamics of Energy Prices

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  • Marie-Claude Beaulieu

    ()

  • Jean-Marie Dufour

    ()

  • Lynda Khalaf
  • Maral Kichian

Abstract

We test for the presence of time-varying parameters (TVP) in the long-run dynamics of energy prices for oil, natural gas and coal, within a standard class of mean-reverting models. We also propose residual-based diagnostic tests and examine out-of-sample forecasts. In-sample LR tests support the TVP model for coal and gas but not for oil, though companion diagnostics suggest that the model is too restrictive to conclusively fit the data. Out-of-sample analysis suggests a randomwalk specification for oil price, and TVP models for both real-time forecasting in the case of gas and long-run forecasting in the case of coal

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Bibliographic Info

Paper provided by CIRANO in its series CIRANO Working Papers with number 2011s-22.

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Date of creation: 01 Feb 2011
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Handle: RePEc:cir:cirwor:2011s-22

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Keywords: structural change; time-varying parameter; energy prices; coal; gas; crude oil; unidentified nuisance parameter; exact test; Monte Carlo test; Kalman filter; normality test;

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Cited by:
  1. Rachida Ouysse, 2014. "On the performance of block-bootstrap continuously updated GMM for a class of non-linear conditional moment models," Computational Statistics, Springer, vol. 29(1), pages 233-261, February.

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