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Forecasting unemployment

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  • Geraint Johnes

Abstract

Results are reported of a forecasting competition between linear autoregressive, GARCH, threshold autoregressive and neural network models of the UK monthly unemployment rate series. Evidence is uncovered suggesting the existence of nonlinearities in the series.

Suggested Citation

  • Geraint Johnes, 1999. "Forecasting unemployment," Applied Economics Letters, Taylor & Francis Journals, vol. 6(9), pages 605-607.
    • Handle: RePEc:taf:apeclt:v:6:y:1999:i:9:p:605-607
    DOI: 10.1080/135048599352709
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    Citations

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    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Mihai Mutascu & Scott W. Hegerty, 2023. "Predicting the contribution of artificial intelligence to unemployment rates: an artificial neural network approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(2), pages 400-416, June.
    3. Umi Mahmudah, 2017. "Predicting unemployment rates in Indonesia," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 9(1), pages 20-28, April.
    4. G Johnes, 2005. "Skills and earnings revisited," Working Papers 573993, Lancaster University Management School, Economics Department.
    5. Floros, Ch., 2005. "Forecasting the UK Unemployment Rate: Model Comparisons," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(4), pages 57-72.
    6. 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.
    7. Elena Olmedo, 2014. "Forecasting Spanish Unemployment Using Near Neighbour and Neural Net Techniques," Computational Economics, Springer;Society for Computational Economics, vol. 43(2), pages 183-197, February.
    8. Adriana AnaMaria Davidescu & Simona-Andreea Apostu & Liviu Adrian Stoica, 2021. "Socioeconomic Effects of COVID-19 Pandemic: Exploring Uncertainty in the Forecast of the Romanian Unemployment Rate for the Period 2020–2023," Sustainability, MDPI, vol. 13(13), pages 1-22, June.
    9. Christos Katris, 2020. "Prediction of Unemployment Rates with Time Series and Machine Learning Techniques," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 673-706, February.

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