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Constructing a Coincident Index of Business Cycles Without Assuming a One-Factor Model

Author

Listed:
  • Yasutomo Murasawa
  • Roberto S. Mariano

Abstract

The Stock--Watson coincident index and its subsequent extensions assume a static linear one-factor model for the component indicators. Such assumption is restrictive in practice, however, with as few as four indicators. In fact, such assumption is unnecessary if one poses the index construction problem as optimal prediction of latent monthly real GDP. This paper estimates a VAR model for latent monthly real GDP and other indicators using the observable mixed-frequency series. The EM algorithm is useful for overcoming the computational difficulty, especially in model selection. The smoothed estimate of latent monthly real GDP is the proposed index

Suggested Citation

  • Yasutomo Murasawa & Roberto S. Mariano, 2004. "Constructing a Coincident Index of Business Cycles Without Assuming a One-Factor Model," Econometric Society 2004 Far Eastern Meetings 710, Econometric Society.
    • Handle: RePEc:ecm:feam04:710
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    Cited by:

    1. Cecilia Frale & David Veredas, 2008. "A Monthly Volatility Index for the US Economy," Working Papers ECARES 2008-008, ULB -- Universite Libre de Bruxelles.
    2. Paul Viefers, 2011. "Bayesian Inference for the Mixed-Frequency VAR Model," Discussion Papers of DIW Berlin 1172, DIW Berlin, German Institute for Economic Research.
    3. Urasawa, Satoshi, 2014. "Real-time GDP forecasting for Japan: A dynamic factor model approach," Journal of the Japanese and International Economies, Elsevier, vol. 34(C), pages 116-134.

    More about this item

    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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