2009/14 | LEM Working Paper Series | |
Detrending and the Distributional Properties of U.S. Output Time Series |
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Giorgio Fagiolo, Mauro Napoletano, Marco Piazza, Andrea Roventini |
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Keywords | ||
Statistical Distributions, Detrending, HP Filter, Bandpass Filter, Normality, Fat Tails, Time Series, Exponential-Power Density, Business Cycles Dynamics.
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JEL Classifications | ||
C1, E3
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Abstract | ||
We study the impact of alternative detrending techniques on the distributional properties of U.S. output time series. We detrend GDP and industrial production time series employing first-differencing, Hodrick-Prescott and bandpass filters. We show that the resulting distributions can be approximated by symmetric Exponential-Power densities, with tails fatter than those of a Gaussian. We also employ frequency-band decomposition procedures finding that fat tails occur more likely at high and medium business-cycle frequencies. These results confirm the robustness of the fat-tail property of detrended output time-series distributions and suggest that business-cycle models should take into account this empirical regularity.
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