Low frequency filtering and real business cycles
从时域和频域详细讨论Hodrick-Prescott滤波器，将其视为指数平滑滤波的推广，并质疑其作为唯一趋势消除方法的广泛使用，通过美国时间序列和实际经济周期模型模拟展示其如何显著改变持久性、波动性和共动性的度量。
This paper discusses in detail the Hodrick-Prescott (1980) filter from time and frequency domain perspectives, motivating it as a generalization of the exponential smoothing filter. We show that the HP filter — when applied to large samples — contains a centered fourth difference and hence renders stationary time series that are ‘difference-stationary’ and, indeed, integrated of higher order. However, our application of the HP filter to U.S. time series and to the simulated outcomes of real business cycle models leads us to question its widespread use as a unique method of trend elimination. We provide examples of how HP filtering dramatically alters measures of persistence, variability, and comovement.