A consistent estimator of the smoothing operator in the functional Hodrick-Prescott filter

Multivariate trend-cycle extraction with the Hodrick-Prescott filter

The Hodrick-Prescott filter represents one of the most popular method for trend-cycle extraction in macroeconomic time series. In this paper we provide a multivariate generalization of the Hodrick-Prescott filter, based on the seemingly unrelated time series approach. We first derive closed-form expressions linking the signal-noise matrix ratio to the parameters of the VARMA representation of the model. We then show that the parameters can be estimated using a recently introduced method, called "Moment Estimation Through Aggregation (META)". This method replaces the traditional multivariate li…

函数型Hodrick Prescott滤波器

A Functional Hodrick Prescott Filter

我们提出了一个功能版本的Hodrick-Prescott过滤器的功能数据，在一个无限维可分的希尔伯特空间的值。当相关的线性算子是紧的并且数据的基本分布是高斯分布时，我们进一步描述了相关的最优平滑参数。

具有非紧算子的泛函Hodrick-Prescott滤子

On the functional Hodrick-Prescott Filter with non-compact operators

我们研究了一个版本的功能Hodrick-Prescott过滤器，其中相关的运营商不一定是紧凑的，但仅仅是封闭的和密集定义的封闭范围。我们表明，相关的最佳平滑算子保持在紧凑的情况下，当数据的基本分布是高斯的结构。

Boosting: Why You Can Use the HP Filter

The Hodrick-Prescott (HP) filter is one of the most widely used econometric methods in applied macroeconomic research. Like all nonparametric methods, the HP filter depends critically on a tuning parameter that controls the degree of smoothing. Yet in contrast to modern nonparametric methods and applied work with these procedures, empirical practice with the HP filter almost universally relies on standard settings for the tuning parameter that have been suggested largely by experimentation with macroeconomic data and heuristic reasoning. As recent research (Phillips and Jin, 2015) has shown, s…