Comparison of HP Filter and the Hamilton’s Regression

In this paper we examine if the use of Hamilton’s regression filter significantly modifies cyclical components concerning unemployment in Greece compared with those using Hodrick–Prescott double (HP). Hamilton suggested a order to overcome some drawbacks HP filter, which contains presence false cycles, bias end sample, and ad-hoc assumptions for parameters’ smoothing. Thus, our examines two widely used detrending methods extraction components, including techniques deterministic as well stochastic detrending. Using quarterly data macroeconomic model decomposition, indicate that trend cycle led larger volatilities than from filter. The dynamic forecasting occurred both autoregressive forecasting, yields steady forecasts wide variety non-stationary procedures, along its constraints at time series. results showed is better all assessment measures.