Keywords: Markov switching, total factor productivity, multifactor productivity
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
Full paper (143 KB PDF)
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Last update: December 18, 2001