Nothing Special   »   [go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/p/bca/bocawp/04-5.html
   My bibliography  Save this paper

Structural Change and Forecasting Long-Run Energy Prices

Author

Listed:
  • Jean-Thomas Bernard
  • Lynda Khalaf
  • Maral Kichian
Abstract
The 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.

Suggested Citation

  • Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian, 2004. "Structural Change and Forecasting Long-Run Energy Prices," Staff Working Papers 04-5, Bank of Canada.
  • Handle: RePEc:bca:bocawp:04-5
    as

    Download full text from publisher

    File URL: https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp04-5.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kim, Chang-Jin & Nelson, Charles R, 1989. "The Time-Varying-Parameter Model for Modeling Changing Conditional Variance: The Case of the Lucas Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 433-440, October.
    2. Hamilton, James D., 2003. "What is an oil shock?," Journal of Econometrics, Elsevier, vol. 113(2), pages 363-398, April.
    3. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    4. Jean-Marie Dufour & Abdeljelil Farhat & Lucien Gardiol & Lynda Khalaf, 1998. "Simulation-based finite sample normality tests in linear regressions," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 154-173.
    5. van Amano, Robert A & Norden, Simon, 1998. "Exchange Rates and Oil Prices," Review of International Economics, Wiley Blackwell, vol. 6(4), pages 683-694, November.
    6. Saphores, J.D. & Khalaf, L. & Pelletier, D., 2000. "On Jumps and ARCH Effects in Natural Resource Prices. An Application to Stumpage Prices from Pacific Northwest National Forests," Papers 00-03, Laval - Recherche en Energie.
    7. Robert S. Pindyck, 1999. "The Long-Run Evolutions of Energy Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 1-27.
    8. Marwan Chacra, 2002. "Oil-Price Shocks and Retail Energy Prices in Canada," Staff Working Papers 02-38, Bank of Canada.
    9. Zellner Arnold, 2002. "My Experiences with Nonlinear Dynamic Models in Economics," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(2), pages 1-18, July.
    10. Donald W. K. Andrews, 2000. "Inconsistency of the Bootstrap when a Parameter Is on the Boundary of the Parameter Space," Econometrica, Econometric Society, vol. 68(2), pages 399-406, March.
    11. Jean-Daniel Saphores & Lynda Khalaf & Denis Pelletier, 2002. "On Jumps and ARCH Effects in Natural Resource Prices: An Application to Pacific Northwest Stumpage Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(2), pages 387-400.
    12. Jean-Marie Dufour, 1997. "Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models," Econometrica, Econometric Society, vol. 65(6), pages 1365-1388, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Xun & Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method," Energy Economics, Elsevier, vol. 31(5), pages 768-778, September.
    2. Stanislav Radchenko, 2005. "The Long-Run Forecasting of Energy Prices Using the Model of Shifting Trend," Econometrics 0502002, University Library of Munich, Germany.
    3. repec:bla:rdevec:v:14:y:2010:i:s1:p:499-519 is not listed on IDEAS
    4. Massimiliano Serati & Gianni Amisano, 2008. "Building composite leading indexes in a dynamic factor model framework: a new proposal," LIUC Papers in Economics 212, Cattaneo University (LIUC).
    5. Khalaf, Lynda & Kichian, Maral, 2005. "Exact tests of the stability of the Phillips curve: the Canadian case," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 445-460, April.

    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. Khalaf, Lynda & Saphores, Jean-Daniel & Bilodeau, Jean-Francois, 2003. "Simulation-based exact jump tests in models with conditional heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 28(3), pages 531-553, December.
    2. Khalaf, Lynda & Kichian, Maral, 2005. "Exact tests of the stability of the Phillips curve: the Canadian case," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 445-460, April.
    3. Khalaf, Lynda & Saphores, Jean-Daniel & Bilodeau, Jean-François, 2000. "Simulation-Based Exact Tests with Unidentified Nuisance Parameters Under the Null Hypothesis: the Case of Jumps Tests in Models with Conditional Heteroskedasticity," Cahiers de recherche 0004, GREEN.
    4. Lynda Khalaf & Maral Kichian, 2003. "Testing the Stability of the Canadian Phillips Curve Using Exact Methods," Staff Working Papers 03-7, Bank of Canada.
    5. Atems, Bebonchu & Kapper, Devin & Lam, Eddery, 2015. "Do exchange rates respond asymmetrically to shocks in the crude oil market?," Energy Economics, Elsevier, vol. 49(C), pages 227-238.
    6. Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian & Sebastien Mcmahon, 2008. "Forecasting commodity prices: GARCH, jumps, and mean reversion," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 279-291.
    7. repec:bla:rdevec:v:14:y:2010:i:s1:p:499-519 is not listed on IDEAS
    8. Vincent Brémond & Emmanuel Hache & Tovonony Razafindrabe, 2016. "The Oil Price and Exchange Rate Relationship Revisited: A time-varying VAR parameter approach," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(1), pages 97-131, June.
    9. Young-Joo Kim & Myung Hwan Seo, 2017. "Is There a Jump in the Transition?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 241-249, April.
    10. Joëts, Marc & Mignon, Valérie & Razafindrabe, Tovonony, 2017. "Does the volatility of commodity prices reflect macroeconomic uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 313-326.
    11. Dufour, Jean-Marie, 2006. "Monte Carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics," Journal of Econometrics, Elsevier, vol. 133(2), pages 443-477, August.
    12. Jean-Thomas Bernard & Ba Chu & Lynda Khalaf & Marcel Voia, 2019. "Non-Standard Confidence Sets for Ratios and Tipping Points with Applications to Dynamic Panel Data," Annals of Economics and Statistics, GENES, issue 134, pages 79-108.
    13. Doko Tchatoka, Firmin & Dufour, Jean-Marie, 2020. "Exogeneity tests, incomplete models, weak identification and non-Gaussian distributions: Invariance and finite-sample distributional theory," Journal of Econometrics, Elsevier, vol. 218(2), pages 390-418.
    14. Iwaisako, Tokuo & Nakata, Hayato, 2017. "Impact of exchange rate shocks on Japanese exports: Quantitative assessment using a structural VAR model," Journal of the Japanese and International Economies, Elsevier, vol. 46(C), pages 1-16.
    15. Chevillon, Guillaume & Rifflart, Christine, 2009. "Physical market determinants of the price of crude oil and the market premium," Energy Economics, Elsevier, vol. 31(4), pages 537-549, July.
    16. Hillard G. Huntington, 2017. "The Historical Roots of U.S. Energy Price Shocks," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    17. Jung, Young Cheol & Das, Anupam & McFarlane, Adian, 2020. "The asymmetric relationship between the oil price and the US-Canada exchange rate," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 198-206.
    18. Dufour, Jean-Marie & Khalaf, Lynda, 2002. "Simulation based finite and large sample tests in multivariate regressions," Journal of Econometrics, Elsevier, vol. 111(2), pages 303-322, December.
    19. Kumeka, Terver Theophilus & Uzoma-Nwosu, Damian Chidozie & David-Wayas, Maria Onyinye, 2022. "The effects of COVID-19 on the interrelationship among oil prices, stock prices and exchange rates in selected oil exporting economies," Resources Policy, Elsevier, vol. 77(C).
    20. Lizardo, Radhamés A. & Mollick, André V., 2010. "Oil price fluctuations and U.S. dollar exchange rates," Energy Economics, Elsevier, vol. 32(2), pages 399-408, March.
    21. Huang, Ho-Chuan, 2005. "Diverging evidence of convergence hypothesis," Journal of Macroeconomics, Elsevier, vol. 27(2), pages 233-255, June.

    More about this item

    Keywords

    Econometric and statistical methods;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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

    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:bca:bocawp:04-5. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bocgvca.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.