Structural Change and Forecasting Long-Run Energy Prices
AbstractThe authors test the statistical significance of Pindyck’s (1999) suggested class of econometric equations that model the behaviour of long-run real energy prices. The models postulate meanreverting prices with continuous and random changes in their level and trend, and are estimated using Kalman filtering. In such contexts, test statistics are typically non-standard and depend on nuisance parameters. The authors use simulation-based procedures to address this issue; namely, a standard Monte Carlo test and a maximized Monte Carlo test. They find statistically significant instabilities for coal and natural gas prices, but not for crude oil prices. Out-of-sample forecasts are calculated to differentiate between significant models.
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Bibliographic InfoPaper provided by Bank of Canada in its series Working Papers with number 04-5.
Length: 28 pages
Date of creation: 2004
Date of revision:
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Econometric and statistical methods;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-02-23 (All new papers)
- NEP-COM-2004-02-23 (Industrial Competition)
- NEP-ETS-2004-02-23 (Econometric Time Series)
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