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Estimating changes in trend growth of total factor productivity: Kalman and H-P filters versus a Markov-switching framework

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  • Mark W. French
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    Abstract

    Trend growth in total factor productivity (TFP) is unobserved; it is frequently assumed to evolve continuously over time. That assumption is inherent in the use of the Hodrick-Prescott or Bandpass filter to extract trend. Similarly, the Kalman filter/ unobserved-components approach assumes that changes in the trend growth rate are normally distributed. In fact, however, innovations to the trend growth rate of total factor productivity are far from normal. The distribution is fat-tailed, with large outliers in 1973. Allowing for these outliers, the estimated trend growth rate changes only infrequently. A nonlinear filtering approach is probably better suited to capturing the infrequent past and possible current shifts in trend growth of TFP. One such approach is the Markov-switching model, which is estimated and tested in this paper. The Markov- switching approach appears to have several advantages over repeated Andrews tests.

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    Bibliographic Info

    Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series Finance and Economics Discussion Series with number 2001-44.

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    Date of creation: 2001
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    Handle: RePEc:fip:fedgfe:2001-44

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    Keywords: Productivity ; Econometric models;

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    References

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    Cited by:
    1. James A. Kahn & Robert Rich, 2003. "Tracking the new economy: using growth theory to detect changes in trend productivity," Staff Reports 159, Federal Reserve Bank of New York.
    2. Zheng, Jinghai & Bigsten, Arne & Hu, Angang, 2009. "Can China's Growth be Sustained? A Productivity Perspective," World Development, Elsevier, vol. 37(4), pages 874-888, April.
    3. Dale W. Jorgenson & Mun S. Ho & Kevin J. Stiroh, 2002. "Projecting productivity growth: lessons from the U.S. growth resurgence," Economic Review, Federal Reserve Bank of Atlanta, issue Q3, pages 1-13.
    4. Simon Gilchrist & Masashi Saito, 2008. "Expectations, Asset Prices, and Monetary Policy: The Role of Learning," NBER Chapters, in: Asset Prices and Monetary Policy, pages 45-102 National Bureau of Economic Research, Inc.
    5. Hernandez Martinez, Fernando, 2009. "Efectos del incremento del precio del petróleo en la economía española: Análisis de cointegración y de la política monetaria mediante reglas de Taylor
      [Oil price shocks and the spanish econom
      ," MPRA Paper 18056, University Library of Munich, Germany.
    6. Kierzenkowski, R. & Oung, V., 2007. "L’évolution des crédits à l’habitat en France : une grille d’analyse en termes de cycles," Working papers 172, Banque de France.
    7. Stamfort, Stefan, 2005. "Berechnung trendbereinigter Indikatoren für Deutschland mit Hilfe von Filterverfahren," Discussion Paper Series 1: Economic Studies 2005,19, Deutsche Bundesbank, Research Centre.
    8. Álvaro Aguiar & Manuel M. F. Martins, 2004. "Growth Cycles in XXth Century European Industrial Productivity: Unbiased Variance Estimation in a Time-varying Parameter Model," FEP Working Papers 144, Universidade do Porto, Faculdade de Economia do Porto.

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