Extracting Nonlinear Signals from Several Economic Indicators
39 Pages Posted: 1 Mar 2012
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: Suggested Citation
Do you have a job opening that you would like to promote on SSRN?
Extracting Nonlinear Signals from Several Economic Indicators
This is a CEPR Discussion Paper. CEPR charges a fee of $8.00 for this paper.
If you wish to purchase the right to make copies of this paper for distribution to others, please select the quantity.
