Extracting nonlinear signals from several economic indicators
AbstractWe 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 InfoPaper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 8865.
Date of creation: Feb 2012
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Other versions of this item:
- Maximo Camacho & Gabriel Perez-Quiros & Pilar Poncela, 2012. "Extracting non-linear signals from several economic indicators," Banco de Espaï¿½a Working Papers 1202, Banco de Espa�a.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- E27 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-03-28 (All new papers)
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- Gabriele Fiorentini & Enrique Sentana, 2013. "Dynamic Specification Tests For Dynamic Factor Models," Working Papers wp2013_1306, CEMFI.
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