IDEAS home Printed from https://ideas.repec.org/a/eee/jebusi/v58y2006i2p168-180.html
   My bibliography  Save this article

Forecasting output using oil prices: A cascaded artificial neural network approach

Author

Listed:
  • Malik, Farooq
  • Nasereddin, Mahdi

Abstract

No abstract is available for this item.

Suggested Citation

  • Malik, Farooq & Nasereddin, Mahdi, 2006. "Forecasting output using oil prices: A cascaded artificial neural network approach," Journal of Economics and Business, Elsevier, vol. 58(2), pages 168-180.
  • Handle: RePEc:eee:jebusi:v:58:y:2006:i:2:p:168-180
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148-6195(05)00073-1
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hamilton, James D., 1996. "This is what happened to the oil price-macroeconomy relationship," Journal of Monetary Economics, Elsevier, vol. 38(2), pages 215-220, October.
    2. Alan A. Carruth & Mark A. Hooker & Andrew J. Oswald, 1998. "Unemployment Equilibria And Input Prices: Theory And Evidence From The United States," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 621-628, November.
    3. Hooker, Mark A., 1996. "What happened to the oil price-macroeconomy relationship?," Journal of Monetary Economics, Elsevier, vol. 38(2), pages 195-213, October.
    4. Arturo Estrella & Frederic S. Mishkin, 1998. "Predicting U.S. Recessions: Financial Variables As Leading Indicators," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 45-61, February.
    5. Hutchinson, James M & Lo, Andrew W & Poggio, Tomaso, 1994. " A Nonparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks," Journal of Finance, American Finance Association, vol. 49(3), pages 851-889, July.
    6. Hamilton, James D & Kim, Dong Heon, 2002. "A Reexamination of the Predictability of Economic Activity Using the Yield Spread," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(2), pages 340-360, May.
    7. Hamilton, James D., 2003. "What is an oil shock?," Journal of Econometrics, Elsevier, vol. 113(2), pages 363-398, April.
    8. Ashley, R & Granger, C W J & Schmalensee, R, 1980. "Advertising and Aggregate Consumption: An Analysis of Causality," Econometrica, Econometric Society, vol. 48(5), pages 1149-1167, July.
    9. Raymond, Jennie E & Rich, Robert W, 1997. "Oil and the Macroeconomy: A Markov State-Switching Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(2), pages 193-213, May.
    10. Loungani, Prakash, 1986. "Oil Price Shocks and the Dispersion Hypothesis," The Review of Economics and Statistics, MIT Press, vol. 68(3), pages 536-539, August.
    11. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    12. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    13. James L. Pierce & Jared J. Enzler, 1974. "The Effects of External Inflationary Shocks," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 5(1), pages 13-62.
    14. Norman R. Swanson & Halbert White, 1997. "A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 540-550, November.
    15. Mork, Knut Anton, 1989. "Oil and Macroeconomy When Prices Go Up and Down: An Extension of Hamilton's Results," Journal of Political Economy, University of Chicago Press, vol. 97(3), pages 740-744, June.
    16. Hooker, Mark A., 1996. "This is what happened to the oil price-macroeconomy relationship: Reply," Journal of Monetary Economics, Elsevier, vol. 38(2), pages 221-222, October.
    17. John Cooper, 1999. "Artificial neural networks versus multivariate statistics: An application from economics," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 909-921.
    18. Davis, Steven J. & Haltiwanger, John, 2001. "Sectoral job creation and destruction responses to oil price changes," Journal of Monetary Economics, Elsevier, vol. 48(3), pages 465-512, December.
    19. Hamilton, James D, 2001. "A Parametric Approach to Flexible Nonlinear Inference," Econometrica, Econometric Society, vol. 69(3), pages 537-573, May.
    20. Burbidge, John & Harrison, Alan, 1984. "Testing for the Effects of Oil-Price Rises Using Vector Autoregressions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(2), pages 459-484, June.
    21. Gisser, Micha & Goodwin, Thomas H, 1986. "Crude Oil and the Macroeconomy: Tests of Some Popular Notions: A Note," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 18(1), pages 95-103, February.
    22. Robert S. Pindyck, 1980. "Energy Price Increases and Macroeconomic Policy," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-20.
    23. Tkacz, Greg, 2001. "Neural network forecasting of Canadian GDP growth," International Journal of Forecasting, Elsevier, vol. 17(1), pages 57-69.
    24. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters,in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
    25. Rotemberg, Julio J & Woodford, Michael, 1996. "Imperfect Competition and the Effects of Energy Price Increases on Economic Activity," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 28(4), pages 550-577, November.
    26. Daniel, Betty C., 1997. "International interdependence of national growth rates: A structural trends anakysis," Journal of Monetary Economics, Elsevier, vol. 40(1), pages 73-96, September.
    27. Friedman, Benjamin M & Kuttner, Kenneth N, 1992. "Money, Income, Prices, and Interest Rates," American Economic Review, American Economic Association, vol. 82(3), pages 472-492, June.
    28. Chatfield, Chris, 1993. "Neural networks: Forecasting breakthrough or passing fad?," International Journal of Forecasting, Elsevier, vol. 9(1), pages 1-3, April.
    29. Kiseok Lee & Shawn Ni & Ronald A. Ratti, 1995. "Oil Shocks and the Macroeconomy: The Role of Price Variability," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 39-56.
    30. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    31. Keane, Michael P & Prasad, Eswar S, 1996. "The Employment and Wage Effects of Oil Price Changes: A Sectoral Analysis," The Review of Economics and Statistics, MIT Press, vol. 78(3), pages 389-400, August.
    32. Lee, Kiseok & Ni, Shawn, 2002. "On the dynamic effects of oil price shocks: a study using industry level data," Journal of Monetary Economics, Elsevier, vol. 49(4), pages 823-852, May.
    33. Robert M. Solow, 1980. "What to Do (Macroeconomically) When OPEC Comes," NBER Chapters,in: Rational Expectations and Economic Policy, pages 249-267 National Bureau of Economic Research, Inc.
    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. Koutroumanidis, Theodoros & Ioannou, Konstantinos & Arabatzis, Garyfallos, 2009. "Predicting fuelwood prices in Greece with the use of ARIMA models, artificial neural networks and a hybrid ARIMA-ANN model," Energy Policy, Elsevier, vol. 37(9), pages 3627-3634, September.
    2. Jammazi, Rania & Aloui, Chaker, 2012. "Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling," Energy Economics, Elsevier, vol. 34(3), pages 828-841.

    More about this item

    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:eee:jebusi:v:58:y:2006:i:2:p:168-180. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/jeconbus .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.