Detecting Cyclical Turning Points: the ABCD Approach and Two Probabilistic Indicators
نویسندگان
چکیده
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. In this paper we first discuss the concept of detection and propose the ABCD strategy of the COE to identify the relevant cyclical turning points. Second, we introduce a couple of indicators able to nowcast and to forecast those turning points. Both indicators are probabilistic and are based on two different approaches. The first one is computed by using the turning point detection algorithm of Neftçi (1984) and aims at forecasting the fluctuations of the growth cycle. The second one is grounded on the Markov-Switching model proposed by Hamilton (1989) and is used to detect peaks and troughs of the classical cycle in real time. The paper will review the performance of those indicators which have been disseminated into the public by the COE since 1996. The analysis of those leading and coincident indicators will focus particularly on the United States and the Eurozone cyclical turning points.
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