IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article or follow this journal

Forecasting the UK Unemployment Rate: Model Comparisons

  • Floros, Ch.

This paper compares the out-of-sample forecasting accuracy of time series models using the Root Mean Square, Mean Absolute and Mean Absolute Percent Errors. We evaluate the performance of the competing models covering the period January 1971 to December 2002. The forecasting sample (January 1996 – December 2002) is divided into four sub-periods. First, for total forecasting sample, we find that MA(4)-ARCH(1) provides superior forecasts of unemployment rate. On the other hand, two forecasting samples show that the MA(4) model performs well, while both MA(1) and AR(4) prove to be the best forecasting models for the other two forecasting periods. The empirical evidence derived from our investigation suggests a close relationship between forecasting theory and labour market conditions. Our findings bring forecasting methods nearer to the realities of UK labour market.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.usc.es/economet/reviews/ijaeqs244.pdf
Download Restriction: No

Article provided by Euro-American Association of Economic Development in its journal International Journal of Applied Econometrics and Quantitative Studies .

Volume (Year): 2 (2005)
Issue (Month): 4 ()
Pages: 57-72

as
in new window

Handle: RePEc:eaa:ijaeqs:v:2:y2005:i:4_4
Contact details of provider: Web page: http://www.usc.es/economet/eaa.htm

Order Information: Web: http://www.usc.es/economet/info.htm Email:


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.:

as in new window
  1. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  2. Gil-Alana, Luis A, 2001. "A Fractionally Integrated Exponential Model for UK Unemployment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(5), pages 329-40, August.
  3. Philip Rothman, 1998. "Forecasting Asymmetric Unemployment Rates," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 164-168, February.
  4. Parker Randall E. & Rothman Philip, 1998. "The Current Depth-of-Recession and Unemployment-Rate Forecasts," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(4), pages 1-10, January.
  5. Proietti, Tommaso, 2003. "Forecasting the US unemployment rate," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 451-476, March.
  6. Geraint Johnes, 1999. "Forecasting unemployment," Applied Economics Letters, Taylor & Francis Journals, vol. 6(9), pages 605-607.
  7. D. A. Peel & A. E. H. Speight, 2000. "Threshold nonlinearities in unemployment rates: further evidence for the UK and G3 economies," Applied Economics, Taylor & Francis Journals, vol. 32(6), pages 705-715.
  8. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
  9. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:eaa:ijaeqs:v:2:y2005:i:4_4. 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: (M. Carmen Guisan)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.