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Giorgio Fagiolo, Mauro Napoletano, Marco Piazza and Andrea Roventini
 
''Detrending and the Distributional Properties of U.S. Output Time Series''
( 2009, Vol. 29 No.4 )
 
 
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.
 
 
Keywords: statistical distributions, detrending, HP filter, bandpass filter, normality, fat tails, time series, Exponential-Power density, business cycles dynamics.
JEL: C1 - Econometric and Statistical Methods: General
E3 - Prices, Business Fluctuations, and Cycles: General (includes Measurement and Data)
 
Manuscript Received : Oct 27 2009 Manuscript Accepted : Dec 23 2009

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