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Analysis of a panel of UK macroeconomic forecasts

Author

Listed:
  • DAVID I. HARVEY
  • STEPHEN J. LEYBOURNE
  • PAUL NEWBOLD

Abstract

This paper looks at unobserved components models and examines the implied weighting patterns for signal extraction. There are four main themes. The first concerns the implications of correlated disturbances driving the components, especially those cases in which the correlation is perfect. The second is about the way in which ARIMA-based methods for trend extraction relate to those based on unobserved components. The third explores the impact of heteroscedasticity and irregular spacing and shows how setting up models with t -distributed disturbances leads to weighting patterns which are robust to outliers and breaks. Finally, a comparison is made between implied weighting patterns with kernels used in non-parametric trend estimation and equivalent kernels used in spline smoothing. It is demonstrated that with irregularly spaced data, the weighting used by conventional spline smoothing techniques is not the same as that obtained from the time series model based approach.

Suggested Citation

  • David I. Harvey & Stephen J. Leybourne & Paul Newbold, 2001. "Analysis of a panel of UK macroeconomic forecasts," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 37-55.
    • Handle: RePEc:ect:emjrnl:v:4:y:2001:i:1:p:s37-s55
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    Cited by:

    1. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
    2. Kajal Lahiri & Gultekin Isiklar, 2010. "Estimating International Transmission of Shocks Using GDP Forecasts: India and Its Trading Partners," Discussion Papers 10-06, University at Albany, SUNY, Department of Economics.
    3. Isiklar, Gultekin & Lahiri, Kajal, 2007. "How far ahead can we forecast? Evidence from cross-country surveys," International Journal of Forecasting, Elsevier, vol. 23(2), pages 167-187.
    4. Isengildina, Olga & Irwin, Scott H. & Good, Darrel L., 2004. "Does The Market Anticipate Smoothing In Usda Crop Production Forecasts?," 2004 Annual meeting, August 1-4, Denver, CO 20145, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Stefan Günnel & Karl-Heinz Tödter, 2009. "Does Benford’s Law hold in economic research and forecasting?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 36(3), pages 273-292, August.
    6. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
    7. Iregui, Ana María & Núñez, Héctor M. & Otero, Jesús, 2021. "Testing the efficiency of inflation and exchange rate forecast revisions in a changing economic environment," Journal of Economic Behavior & Organization, Elsevier, vol. 187(C), pages 290-314.
    8. Bruno Deschamps & Christos Ioannidis, 2014. "The Efficiency of Multivariate Macroeconomic Forecasts," Manchester School, University of Manchester, vol. 82(5), pages 509-523, September.
    9. Isiklar, Gultekin, 2005. "On aggregation bias in fixed-event forecast efficiency tests," Economics Letters, Elsevier, vol. 89(3), pages 312-316, December.
    10. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
    11. Jordi Pons-Novell, 2006. "An analysis of a panel of Spanish GDP forecasts," Applied Economics, Taylor & Francis Journals, vol. 38(11), pages 1287-1292.
    12. Deschamps, Bruno & Ioannidis, Christos, 2013. "Can rational stubbornness explain forecast biases?," Journal of Economic Behavior & Organization, Elsevier, vol. 92(C), pages 141-151.
    13. Gultekin Isiklar & Kajal Lahiri & Prakash Loungani, 2006. "How quickly do forecasters incorporate news? Evidence from cross‐country surveys," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 703-725, September.
    14. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2012. "Disagreement Among Forecasters in G7 Countries," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1081-1096, November.
    15. Jan-Egbert Sturm & Timo Wollmershäuser, 2008. "The Stress of Having a Single Monetary Policy in Europe," CESifo Working Paper Series 2251, CESifo.
    16. Jordi Pons-Novell, 2004. "Behavioural biases among interest rate forecasters?," Applied Economics Letters, Taylor & Francis Journals, vol. 11(5), pages 319-321.
    17. Masahiro Ashiya, 2006. "Testing the rationality of forecast revisions made by the IMF and the OECD," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 25-36.
    18. Harvey, David I. & Newbold, Paul, 2003. "The non-normality of some macroeconomic forecast errors," International Journal of Forecasting, Elsevier, vol. 19(4), pages 635-653.
    19. Dovern, Jonas & Weisser, Johannes, 2011. "Accuracy, unbiasedness and efficiency of professional macroeconomic forecasts: An empirical comparison for the G7," International Journal of Forecasting, Elsevier, vol. 27(2), pages 452-465.
    20. Jordi Pons-Novell, 2003. "Strategic bias, herding behaviour and economic forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 67-77.
    21. Xiao, Jinzhi & Lence, Sergio H. & Hart, Chad, 2014. "Usda And Private Analysts' Forecasts Of Ending Stocks: How Good Are They?," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170642, Agricultural and Applied Economics Association.
    22. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.

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