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An Artificial Neural Network System of Leading Indicators

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  • Andrew Blake

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Abstract

We construct an artificial neural network to act as a system of leading indicators. We focus on radial basis functions as the architecture and forward selection as the method for determining the number of basis functions in the network. A brief review is given of the advantages of this as a strategy. Using common heuristics to determine scaling, radii and centre population, we find that the results for output growth prediction for six European countries are promising.

Suggested Citation

  • Andrew Blake, 1999. "An Artificial Neural Network System of Leading Indicators," National Institute of Economic and Social Research (NIESR) Discussion Papers 144, National Institute of Economic and Social Research.
  • Handle: RePEc:nsr:niesrd:198
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    Cited by:

    1. Bettina Becker, 2003. "Foreign Direct Investment in Industrial R&D and Exchange Rate Uncertainty in the UK," National Institute of Economic and Social Research (NIESR) Discussion Papers 217, National Institute of Economic and Social Research.
    2. Joseph P. Byrne & E. Philip Davis, 2005. "Investment and Uncertainty in the G7," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 141(1), pages 1-32, April.
    3. Ajimuda Olumide, 2009. "Price Volatility, Expectations and Monetary Policy in Nigeria," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 109-140, May.
    4. Michael McMahon & Gabriel Sterne & Jamie Thompson, 2005. "The role of ICT in the global investment cycle," Bank of England working papers 257, Bank of England.
    5. Christopher F. Baum & Atreya Chakraborty & Boyan Liu, 2010. "The impact of macroeconomic uncertainty on firms' changes in financial leverage," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(1), pages 22-30.
    6. Christopher F. Baum & Andreas Stephan & Oleksandr Talavera, 2004. "Macroeconomic Uncertainty and Firm Leverage," Discussion Papers of DIW Berlin 443, DIW Berlin, German Institute for Economic Research.
    7. Christopher F. Baum & Andreas Stephan & Oleksandr Talavera, 2009. "The Effects Of Uncertainty On The Leverage Of Nonfinancial Firms," Economic Inquiry, Western Economic Association International, vol. 47(2), pages 216-225, April.
    8. Andreas Stephan & Oleksandr Talavera, "undated". "Effects of macroeconomic uncertainty on leverage for US non-financial firms," German Stata Users' Group Meetings 2004 8, Stata Users Group.
    9. Christopher F. Baum & Dorothea Schäfer & Oleksandr Talavera, 2006. "The Effects of Industry-Level Uncertainty on Cash Holdings: The Case of Germany," Discussion Papers of DIW Berlin 638, DIW Berlin, German Institute for Economic Research.
    10. repec:asi:ajoerj:2013:p:633-653 is not listed on IDEAS
    11. Andrew Hallett & Gert Peersman & Laura Piscitelli, 2004. "Investment Under Monetary Uncertainty: A Panel Data Investigation," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 31(2), pages 137-162, June.
    12. Talavera, Oleksandr & Tsapin, Andriy & Zholud, Oleksandr, 2012. "Macroeconomic uncertainty and bank lending: The case of Ukraine," Economic Systems, Elsevier, vol. 36(2), pages 279-293.
    13. Baum, Christopher F. & Caglayan, Mustafa & Stephan, Andreas & Talavera, Oleksandr, 2008. "Uncertainty determinants of corporate liquidity," Economic Modelling, Elsevier, vol. 25(5), pages 833-849, September.
    14. Matthias Kredler, 2005. "Sector-Specific Volatility Patterns in Investment," Macroeconomics 0501016, University Library of Munich, Germany.

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