sandwich: NeweyWest – R documentation

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NeweyWest

Newey-West HAC Covariance Matrix Estimation

Description

A set of functions implementing the Newey & West (1987, 1994) heteroscedasticity and autocorrelation consistent (HAC) covariance matrix estimators.

Usage

NeweyWest(x, lag = NULL, order.by = NULL, prewhite = TRUE, adjust = FALSE, 
  diagnostics = FALSE, sandwich = TRUE, ar.method = "ols", data = list(),
  verbose = FALSE)

bwNeweyWest(x, order.by = NULL, kernel = c("Bartlett", "Parzen",
  "Quadratic Spectral", "Truncated", "Tukey-Hanning"), weights = NULL,
  prewhite = 1, ar.method = "ols", data = list(), ...)

Arguments

`x`	a fitted model object.
`lag`	integer specifying the maximum lag with positive weight for the Newey-West estimator. If set to `NULL` `floor(bwNeweyWest(x, ...))` is used.
`order.by`	Either a vector `z` or a formula with a single explanatory variable like `~ z`. The observations in the model are ordered by the size of `z`. If set to `NULL` (the default) the observations are assumed to be ordered (e.g., a time series).
`prewhite`	logical or integer. Should the estimating functions be prewhitened? If `TRUE` or greater than 0 a VAR model of order `as.integer(prewhite)` is fitted via `ar` with method `"ols"` and `demean = FALSE`. The default is to use VAR(1) prewhitening.
`kernel`	a character specifying the kernel used. All kernels used are described in Andrews (1991). `bwNeweyWest` can only compute bandwidths for `"Bartlett"`, `"Parzen"` and `"Quadratic Spectral"`.
`adjust`	logical. Should a finite sample adjustment be made? This amounts to multiplication with n/(n-k) where n is the number of observations and k the number of estimated parameters.
`diagnostics`	logical. Should additional model diagnostics be returned? See `vcovHAC` for details.
`sandwich`	logical. Should the sandwich estimator be computed? If set to `FALSE` only the middle matrix is returned.
`ar.method`	character. The `method` argument passed to `ar` for prewhitening (only, not for bandwidth selection).
`data`	an optional data frame containing the variables in the `order.by` model. By default the variables are taken from the environment which the function is called from.
`verbose`	logical. Should the lag truncation parameter used be printed?
`weights`	numeric. A vector of weights used for weighting the estimated coefficients of the approximation model (as specified by `approx`). By default all weights are 1 except that for the intercept term (if there is more than one variable).
`...`	currently not used.

Details

NeweyWest is a convenience interface to vcovHAC using Bartlett kernel weights as described in Newey & West (1987, 1994). The automatic bandwidth selection procedure described in Newey & West (1994) is used as the default and can also be supplied to kernHAC for the Parzen and quadratic spectral kernel. It is implemented in bwNeweyWest which does not truncate its results - if the results for the Parzen and Bartlett kernels should be truncated, this has to be applied afterwards. For Bartlett weights this is implemented in NeweyWest.

To obtain the estimator described in Newey & West (1987), prewhitening has to be suppressed.

Value

NeweyWest returns the same type of object as vcovHAC which is typically just the covariance matrix.

bwNeweyWest returns the selected bandwidth parameter.

References

Andrews DWK (1991). “Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation.” Econometrica, 59, 817–858.

Newey WK & West KD (1987). “A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix.” Econometrica, 55, 703–708.

Newey WK & West KD (1994). “Automatic Lag Selection in Covariance Matrix Estimation.” Review of Economic Studies, 61, 631–653.

Zeileis A (2004). “Econometric Computing with HC and HAC Covariance Matrix Estimators.” Journal of Statistical Software, 11(10), 1–17. doi: 10.18637/jss.v011.i10

Examples

## fit investment equation
data(Investment)
fm <- lm(RealInv ~ RealGNP + RealInt, data = Investment)

## Newey & West (1994) compute this type of estimator
NeweyWest(fm)

## The Newey & West (1987) estimator requires specification
## of the lag and suppression of prewhitening
NeweyWest(fm, lag = 4, prewhite = FALSE)

## bwNeweyWest() can also be passed to kernHAC(), e.g.
## for the quadratic spectral kernel
kernHAC(fm, bw = bwNeweyWest)

sandwich

Robust Covariance Matrix Estimators

v3.0-0

GPL-2 | GPL-3

Authors

Achim Zeileis [aut, cre] (<https://orcid.org/0000-0003-0918-3766>), Thomas Lumley [aut], Nathaniel Graham [ctb], Susanne Koell [ctb]

Initial release

2020-10-01