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Extracting Nonlinear Signals from Several Economic Indicators

39 Pages Posted: 1 Mar 2012  

Maximo Camacho

Autonomous University of Barcelona - Department of Economics; Universidad de Murcia - Departamento de Metodos Cuantitativos

Gabriel Pérez-Quirós

Banco de España

Pilar Poncela

Universidad Autónoma de Madrid

Date Written: February 2012

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.

Keywords: Business Cycles, Output Growth, Time Series.

JEL Classification: C22, E27, E32

Suggested Citation

Camacho, Maximo and Pérez-Quirós, Gabriel and Poncela, Pilar, Extracting Nonlinear Signals from Several Economic Indicators (February 2012). CEPR Discussion Paper No. DP8865. Available at SSRN: https://ssrn.com/abstract=2013856

Maximo Camacho (Contact Author)

Autonomous University of Barcelona - Department of Economics ( email )

Avda. Diagonal 690
Barcelona, 08034
Spain

Universidad de Murcia - Departamento de Metodos Cuantitativos ( email )

Campus de Espinardo
30100 Murcia
Spain
+34 968 367 982 (Phone)

Gabriel Pérez-Quirós

Banco de España ( email )

Alcala 50
Madrid 28014
Spain

Pilar Poncela

Universidad Autónoma de Madrid ( email )

Campus Cantoblanco
C/Kelsen, 1
Madrid, Madrid 28049
Spain

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