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Title: Extracting nonlinear signals from several economic indicators

Author(s): Maximo Camacho, Gabriel Pérez-Quirós and Pilar Poncela

Publication Date: February 2012

Keyword(s): Business Cycles, Output Growth and Time Series.

Programme Area(s): International Macroeconomics

Abstract: We develop a twofold analysis of how the information provided by several economic indicators can be used in Markov-switching dynamic factor models to identify the business cycle turning points. First, we compare the performance of a fully non- linear multivariate specification (one-step approach) with the shortcut of using a linear factor model to obtain a coincident indicator which is then used to compute the Markov-switching probabilities (two-step approach). Second, we examine the role of increasing the number of indicators. Our results suggest that one step is generally preferred to two steps, although its marginal gains diminish as the quality of the indicators increases and as more indicators are used to identify the non-linear signal. Using the four constituent series of the Stock-Watson coincident index, we illustrate these results for US data.

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Bibliographic Reference

Camacho, M, Pérez-Quirós, G and Poncela, P. 2012. 'Extracting nonlinear signals from several economic indicators'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=8865