Fagiolo, Giorgio Napoletano, Mauro Piazza, Marco Roventini, Andrea
Year of Publication:
LEM Working Paper Series 2009/14
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.
Statistical Distributions Detrending HP Filter Bandpass Filter Normality Fat Tails Time Series Exponential-Power Density Business Cycles Dynamics