Estimation Of The Cyclical Component Of Economic Time Series
The objective of this paper is to show an alternative technique to smooth time series from Monte Carlo Simulations. The technique considers that time series can contain more than one structural break, coming from movements in coefficients of trend or from intercept. The Hodrick-Prescott Filter (HP) does not provide identification of such possible breaks in order to smooth trend from the series to analyze its cyclical component. If the series are relatively stable, this problem may not have relevant implications. Otherwise, for economies relatively unstable, trend movements may interfere in the specification of the cyclical component, and Hodrick-Prescott smoothing could lead empiricists to achieve simplistic forms to economic cycles. In the context, we present an empirical methodology that allows structural breaks in any point of time, from coefficients or from intercepts. We apply this recursive technique to different models with variations in trend, from coefficients and from intercepts, using series simulated by Monte Carlo. Moreover, we compare the results of both techniques to the Brazilian GDP.
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