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Extracting non-linear signals from several economic indicators

Author

Listed:
  • Maximo Camacho

    (Universidad de Murcia)

  • Gabriel Perez-Quiros

    (Banco de España)

  • Pilar Poncela

    (Universidad Autónoma de Madrid)

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.

Suggested Citation

  • Maximo Camacho & Gabriel Perez-Quiros & Pilar Poncela, 2012. "Extracting non-linear signals from several economic indicators," Working Papers 1202, Banco de España.
    • Handle: RePEc:bde:wpaper:1202
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    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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