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


  • Mark W. French


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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  • Mark W. French, 2001. "Estimating changes in trend growth of total factor productivity: Kalman and H-P filters versus a Markov-switching framework," Finance and Economics Discussion Series 2001-44, Board of Governors of the Federal Reserve System (U.S.).
  • Handle: RePEc:fip:fedgfe:2001-44

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    References listed on IDEAS

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    Cited by:

    1. Dale W. Jorgenson & Mun S. Ho & Kevin J. Stiroh, 2006. "Projecting Productivity Growth: Lessons from the US Growth Resurgence," Chapters,in: The New Economy and Beyond, chapter 2 Edward Elgar Publishing.
    2. Kahn, James A. & Rich, Robert W., 2007. "Tracking the new economy: Using growth theory to detect changes in trend productivity," Journal of Monetary Economics, Elsevier, vol. 54(6), pages 1670-1701, September.
    3. repec:ehl:lserod:56407 is not listed on IDEAS
    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. 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.
    6. 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 economy: Coi
      ," MPRA Paper 18056, University Library of Munich, Germany.
    7. 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.
    8. White Halbert & Granger Clive W.J., 2011. "Consideration of Trends in Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-40, February.
    9. Gerba, Eddie, 2015. "Have the US macro-financial linkages changed? The balance sheet dimension," LSE Research Online Documents on Economics 59886, London School of Economics and Political Science, LSE Library.
    10. Luigi Bocola & Nils Gornemann, 2013. "Risk, economic growth and the value of U.S. corporations," Working Papers 13-10, Federal Reserve Bank of Philadelphia.
    11. 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.
    12. Stamfort, Stefan, 2005. "Berechnung trendbereinigter Indikatoren für Deutschland mit Hilfe von Filterverfahren," Discussion Paper Series 1: Economic Studies 2005,19, Deutsche Bundesbank.

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