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Nonlinear models, composite longer leading indicator and forecasts for UK real GDP

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  • Nadir Ocal

Abstract

This paper examines the role of the Office for National Statistics Composite Longer Leading Indicator, in nonlinear business cycle models for growth rates of UK real gross domestic product (GDP). These models are of the smooth transition regression class, with the transition between “regimes” expressed as functions of lagged changes in the leading indicator. In general, evidence is found of business cycle regime asymmetries, with increases and decreases in the leading indicator implying distinct responses for the dependent variable. Single transition function appears to capture these asymmetries satisfactorily. Nonlinear models provide more accurate one-step ahead forecasts than corresponding linear leading indicator models.

Suggested Citation

  • Nadir Ocal, 2006. "Nonlinear models, composite longer leading indicator and forecasts for UK real GDP," Applied Economics, Taylor & Francis Journals, vol. 38(9), pages 1049-1053.
    • Handle: RePEc:taf:applec:v:38:y:2006:i:9:p:1049-1053
    DOI: 10.1080/00036840500399784
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    1. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
    2. Artis, Michael J, et al, 1995. "Turning Point Prediction for the UK Using CSO Leading Indicators," Oxford Economic Papers, Oxford University Press, vol. 47(3), pages 397-417, July.
    3. 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.
    4. Teräsvirta, Timo, 1996. "Smooth Transition Models," SSE/EFI Working Paper Series in Economics and Finance 132, Stockholm School of Economics.
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    Cited by:

    1. Yuan-Ming Lee & Kuan-Min Wang & T. Thanh-Binh Nguyen, 2008. "A Common-Use Proxy for Economic Performance: Application to Asymmetric Causality between the Stock Returns and Growth," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 7(2), pages 101-124, August.

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