# neverhpfilter Package

## Introduction

In the working paper titled “Why You Should Never Use the
**H**odrick-**P**rescott Filter”, James D.
Hamilton proposes a new alternative to economic time series filtering.
The `neverhpfilter`

package provides
functions and data for reproducing his solution. Hamilton (2017)
<doi:10.3386/w23429>

Hamilton’s abstract offers an excellent introduction:

- The HP filter produces series with spurious dynamic relations that
have no basis in the underlying data-generating process. (2) Filtered
values at the end of the sample are very different from those in the
middle, and are also characterized by spurious dynamics. (3) A
statistical formalization of the problem typically produces values for
the smoothing parameter vastly at odds with common practice, e.g., a
value for \(\lambda\) far below 1600
for quarterly data. (4) There’s a better alternative. A regression of
the variable at date \(t + h\) on the
four most recent values as of date \(t\) offers a robust approach to detrending
that achieves all the objectives sought by users of the HP filter with
none of its drawbacks.

## Getting Started

Install from CRAN on R version >= 3.5.0.

`install.packages("neverhpfilter")`

Or install from the Github master branch on R version >=
3.5.0.

`devtools::install_github("JustinMShea/neverhpfilter")`

Load the package

`library(neverhpfilter)`

## Package Documentation

The package consists of 2 estimation `functions`

, 12
economic `xts`

objects, an `xts`

object containing
Robert Shiller’s U.S. Stock Markets and CAPE Ratio data from 1871 to
Present, and a `data.frame`

containing the original filter
estimates found on table 2 of Hamilton (2017)
<doi:10.3386/w23429>

Documentation for each can be found here:

Finally, a vignette recreating the estimates of the original work can
be found in Reproducing
Hamilton.