Description Usage Arguments Details Value Author(s) References See Also Examples
Nonparametric robust covariance matrix estimators a la Newey and West for panel models with serial correlation.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | vcovNW(x, ...)
## S3 method for class 'plm'
vcovNW(
x,
type = c("HC0", "sss", "HC1", "HC2", "HC3", "HC4"),
maxlag = NULL,
wj = function(j, maxlag) 1 - j/(maxlag + 1),
...
)
## S3 method for class 'pcce'
vcovNW(
x,
type = c("HC0", "sss", "HC1", "HC2", "HC3", "HC4"),
maxlag = NULL,
wj = function(j, maxlag) 1 - j/(maxlag + 1),
...
)
|
x |
an object of class |
... |
further arguments |
type |
the weighting scheme used, one of |
maxlag |
either |
wj |
weighting function to be applied to lagged terms, |
vcovNW
is a function for estimating a robust covariance matrix of
parameters for a panel model according to the
\insertCiteNEWE:WEST:87;textualplm method. The function works
as a restriction of the \insertCiteDRIS:KRAA:98;textualplm covariance (see
vcovSCC()
) to no cross–sectional correlation.
Weighting schemes specified by type
are analogous to those in
sandwich::vcovHC()
in package sandwich and are
justified theoretically (although in the context of the standard
linear model) by \insertCiteMACK:WHIT:85;textualplm and
\insertCiteCRIB:04;textualplm \insertCite@see @ZEIL:04plm.
The main use of vcovNW
(and the other variance-covariance estimators
provided in the package vcovHC
, vcovBK
, vcovDC
, vcovSCC
) is to pass
it to plm's own functions like summary
, pwaldtest
, and phtest
or
together with testing functions from the lmtest
and car
packages. All of
these typically allow passing the vcov
or vcov.
parameter either as a
matrix or as a function, e.g., for Wald–type testing: argument vcov.
to
coeftest()
, argument vcov
to waldtest()
and other methods in the
lmtest package; and argument vcov.
to
linearHypothesis()
in the car package (see the
examples), see \insertCite@ZEIL:04, 4.1-2 and examples belowplm.
An object of class "matrix"
containing the estimate of
the covariance matrix of coefficients.
Giovanni Millo
CRIB:04plm
\insertRefDRIS:KRAA:98plm
\insertRefMACK:WHIT:85plm
\insertRefNEWE:WEST:87plm
\insertRefZEIL:04plm
sandwich::vcovHC()
from the sandwich package
for weighting schemes (type
argument).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | data("Produc", package="plm")
zz <- plm(log(gsp)~log(pcap)+log(pc)+log(emp)+unemp, data=Produc, model="pooling")
## as function input to plm's summary method (with and without additional arguments):
summary(zz, vcov = vcovNW)
summary(zz, vcov = function(x) vcovNW(x, method="arellano", type="HC1"))
## standard coefficient significance test
library(lmtest)
coeftest(zz)
## NW robust significance test, default
coeftest(zz, vcov.=vcovNW)
## idem with parameters, pass vcov as a function argument
coeftest(zz, vcov.=function(x) vcovNW(x, type="HC1", maxlag=4))
## joint restriction test
waldtest(zz, update(zz, .~.-log(emp)-unemp), vcov=vcovNW)
## Not run:
## test of hyp.: 2*log(pc)=log(emp)
library(car)
linearHypothesis(zz, "2*log(pc)=log(emp)", vcov.=vcovNW)
## End(Not run)
|
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