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Up Around the Bend: Linear and nonlinear models of the UK economy compared

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  • Geraint Johnes

Abstract

A variety of methods - including vector autoregression (Bayesian and nonBayesian) and neural networks - are used to construct models of the UK economy, and their forecasting performance is compared.

Suggested Citation

  • Geraint Johnes, 2000. "Up Around the Bend: Linear and nonlinear models of the UK economy compared," International Review of Applied Economics, Taylor & Francis Journals, vol. 14(4), pages 485-493.
  • Handle: RePEc:taf:irapec:v:14:y:2000:i:4:p:485-493
    DOI: 10.1080/02692170050150156
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    References listed on IDEAS

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    1. Geraint Johnes, 1999. "Forecasting unemployment," Applied Economics Letters, Taylor & Francis Journals, vol. 6(9), pages 605-607.
    2. Osborn, Denise R, et al, 1988. "Seasonality and the Order of Integration for Consumption," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 50(4), pages 361-377, November.
    3. M. A. Salisu & V. N. Balasubramanyam, 1997. "Income and price elasticities of demand for alcoholic drinks," Applied Economics Letters, Taylor & Francis Journals, vol. 4(4), pages 247-251.
    4. Hackl, Peter & Westlund, Anders H., 1996. "Demand for international telecommunication time-varying price elasticity," Journal of Econometrics, Elsevier, vol. 70(1), pages 243-260, January.
    5. Peter Young, 1999. "Recursive and en-bloc approaches to signal extraction," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(1), pages 103-128.
    6. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
    7. Hill, Tim & Marquez, Leorey & O'Connor, Marcus & Remus, William, 1994. "Artificial neural network models for forecasting and decision making," International Journal of Forecasting, Elsevier, vol. 10(1), pages 5-15, June.
    8. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    9. Holden, K. & Broomhead, A., 1990. "An examination of vector autoregressive forecasts for the U.K. economy," International Journal of Forecasting, Elsevier, vol. 6(1), pages 11-23.
    10. Mills, Terence C, 1991. " Nonlinear Time Series Models in Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 5(3), pages 215-242.
    11. Sexton, Randall S. & Dorsey, Robert E. & Johnson, John D., 1999. "Optimization of neural networks: A comparative analysis of the genetic algorithm and simulated annealing," European Journal of Operational Research, Elsevier, vol. 114(3), pages 589-601, May.
    12. Tim Hill & Marcus O'Connor & William Remus, 1996. "Neural Network Models for Time Series Forecasts," Management Science, INFORMS, vol. 42(7), pages 1082-1092, July.
    13. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    14. Haefke, Christian & Helmenstein, Christian, 1995. "Forecasting Austrian IPOs: An Application of Linear and Neural Network Error-Correction Models," Economics Series 18, Institute for Advanced Studies.
    15. Fildes, Robert, 1992. "The evaluation of extrapolative forecasting methods," International Journal of Forecasting, Elsevier, vol. 8(1), pages 81-98, June.
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    Citations

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    Cited by:

    1. G Johnes, 2005. "Skills and earnings revisited," Working Papers 573993, Lancaster University Management School, Economics Department.
    2. repec:lan:wpaper:4407 is not listed on IDEAS
    3. Jane Binner & Rakesh Bissoondeeal & Thomas Elger & Alicia Gazely & Andrew Mullineux, 2005. "A comparison of linear forecasting models and neural networks: an application to Euro inflation and Euro Divisia," Applied Economics, Taylor & Francis Journals, vol. 37(6), pages 665-680.
    4. repec:lan:wpaper:4408 is not listed on IDEAS
    5. G Johnes, 2003. "Curriculum," Working Papers 541985, Lancaster University Management School, Economics Department.
    6. repec:lan:wpaper:4839 is not listed on IDEAS
    7. repec:lan:wpaper:4535 is not listed on IDEAS
    8. Michael Dietrich, 2006. "Neural networks and the evolution of firms and industries: An application to UK SIC34 and SIC72," Working Papers 2006007, The University of Sheffield, Department of Economics, revised May 2006.

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