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

```
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(), …)

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.

`NeweyWest`

returns the same type of object as `vcovHAC`

which is typically just the covariance matrix.

`bwNeweyWest`

returns the selected bandwidth parameter.

`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.

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.
URL http://www.jstatsoft.org/v11/i10/.

# NOT RUN { ## 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) # }