In the paper we aim to introduce a statistical dating and detection of turning points giving them a first economic interpretation. The main advantage of the proposed approach is represented by the fact that classical and growth cycles are jointly considered both in the dating and in the detecting stage. A key result of this choice is a better description of different economic phases as well as a more accurate investigation of the economic cyclical behaviour. The proposed approach considerably improves the relevance of information delivered to users in comparison with a standard analysis based only on classical or growth cycle components. Copyright � 2008 The Authors. Journal compilation � 2008 Blackwell Publishing Ltd and The University of Manchester.
The intricate issue of detecting and forecasting turning points of macroeconomic cycles has been one more time well illustrated recently with the global downturn experienced by most countries around the world in 2000-2001. Governments and Central Banks are very sensitive to economic indicators showing signs of deterioration in order to adjust their policies sufficiently in advance to avoid more deterioration or a recession. These indicators require at least two qualities: they must be reliable and they must provide a readable signal as soon as possible.
Summary" [...] in many situations a decision does not have to be made immediately, but can be delayed until additional information has been acquired. Sequential analysis seems particularly applicable to the problem of predicting turning points in the business cycle" (Palash and Radecki, 1985). Elaborating on this idea, we propose a new approach to predict cyclical turning points in the Euro-zone using the Neftçi's approach. The output is a probability index for a forthcoming economic turning point.
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