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Forecasting GDP Growth Using Artificial Neural Networks

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Author Info
Tkacz, Greg
Hu, Sarah

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Abstract

Financial and monetary variables have long been known to contain useful leading information regarding economic activity. In this paper, the authors wish to determine whether the forecasting performance of such variables can be improved using neural network models. The main findings are that, at the 1-quarter forecasting horizon, neural networks yield no significant forecast improvements. At the 4-quarter horizon, however, the improved forecast accuracy is statistically significant. The root mean squared forecast errors of the best neural network models are about 15 to 19 per cent lower than their linear model counterparts. The improved forecast accuracy may be capturing more fundamental non-linearities between financial variables and real output growth at the longer horizon.

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File URL: http://www.bankofcanada.ca/en/res/wp/1999/wp99-3.pdf
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Paper provided by Bank of Canada in its series Working Papers with number 99-3.

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Length: 33 pages
Date of creation: 1999
Date of revision:
Handle: RePEc:bca:bocawp:99-3

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Related research
Keywords: Econometric and statistical Methods; Monetary and financial indicators;

Find related papers by JEL classification:
C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation
E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. 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. [Downloadable!] (restricted)
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  2. Cover, James Peery, 1992. "Asymmetric Effects of Positive and Negative Money-Supply Shocks," The Quarterly Journal of Economics, MIT Press, vol. 107(4), pages 1261-82, November. [Downloadable!] (restricted)
  3. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November. [Downloadable!] (restricted)
    Other versions:
  4. 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 851-89, July. [Downloadable!] (restricted)
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  5. Donald P. Morgan, 1993. "Asymmetric effects of monetary policy," Economic Review, Federal Reserve Bank of Kansas City, issue Q II, pages 21-33. [Downloadable!]
  6. Rhee, Wooheon & Rich, Robert W., 1995. "Inflation and the asymmetric effects of money on output fluctuations," Journal of Macroeconomics, Elsevier, vol. 17(4), pages 683-702. [Downloadable!] (restricted)
  7. Chung-Ming Kuan & Halbert White, 1992. "Artificial Neural Networks: An Econometric Perspective," University of California at San Diego, Economics Working Paper Series 92-11, Department of Economics, UC San Diego.
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  8. E. Maasoumi & A. Khotanzed & A. Abaye, 1994. "Artificial neural networks for some macroeconomic series: A first report," Econometric Reviews, Taylor and Francis Journals, vol. 13(1), pages 105-122. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. José Luis Torres, . "Modelos Para La Inflación Básica de Bienes Transables y No Transables en Colombia," Borradores de Economia 365, Banco de la Republica de Colombia. [Downloadable!]
    Other versions:
  2. Araújo, E. & Gama, C. A. F., 2004. "Replicando características de ciclos econômicos: um estudo comparativo entre Redes Neurais Artificiais e modelos ARIMA," Ibmec Working Papers wpe_43, Ibmec Working Paper, Ibmec São Paulo. [Downloadable!]
  3. María Clara Aristizábal Restrepo, . "Evaluación asimétrica de una red neuronal artificial:Aplicación al caso de la inflación en Colombia," Borradores de Economia 377, Banco de la Republica de Colombia. [Downloadable!]
  4. Martha Misas & Enrique López & Pablo Querubín, . "La Inflación en Colombia: Una Aproximación desde las Redes Neuronales," Borradores de Economia 199, Banco de la Republica de Colombia. [Downloadable!]
    Other versions:
  5. Christian A Johnson & Rodrigo Vergara, 2005. "The Implementation of Monetary Policy in an Emerging Economy: The Case of Chile," Documentos de Trabajo 291, Instituto de Economía. Pontificia Universidad Católica de Chile.. [Downloadable!]
    Other versions:
  6. Haider, Adnan & Hanif, Muhammad Nadeem, 2007. "Inflation Forecasting in Pakistan using Artificial Neural Networks," MPRA Paper 8898, University Library of Munich, Germany. [Downloadable!]
  7. María Clara Aristizábal Restrepo, 2006. "Evaluación asimétrica de una red neuronal: aplicación al caso de la inflación en Colombia," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 65, pages 73-116, Julio-Dic. [Downloadable!]
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