vcovNW {plm} | R Documentation |
Nonparametric robust covariance matrix estimators a la Newey and West for panel models with serial correlation.
## 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), ...)
x |
an object of class |
type |
one of |
maxlag |
either |
wj |
weighting function to be applied to lagged terms, |
... |
further arguments |
.
vcovNW
is a function for estimating a robust covariance matrix of
parameters for a panel model according to the Newey and West (1987)
method. The function works as a restriction of the Driscoll and Kraay
(1998) covariance to no cross-sectional correlation.
Weighting schemes are analogous to those in vcovHC
in package sandwich
and are justified theoretically (although in the context of the standard linear model) by MacKinnon and White (1985) and Cribari-Neto (2004) (see Zeileis (2004)).
The main use of vcovNW
is to be an argument to other functions,
e.g. for Wald-type testing: as vcov
to coeftest()
,
waldtest()
and other methods in the lmtest
package; and as
vcov
to linearHypothesis()
in the car
package (see the examples). Notice that the vcov
argument may be supplied a function (which is the safest) or a matrix (see Zeileis (2004), 4.1-2 and examples below).
An object of class "matrix"
containing the estimate of the covariance matrix of coefficients.
Giovanni Millo
Newey, W.K. & West, K.D. (1986) A simple, positive semi-definite, heteroskedasticity and autocorrelationconsistent covariance matrix. Econometrica 55(3), pp. 703–708.
library(lmtest) library(car) data("Produc", package="plm") zz <- plm(log(gsp)~log(pcap)+log(pc)+log(emp)+unemp, data=Produc, model="pooling") ## standard coefficient significance test 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) ## test of hyp.: 2*log(pc)=log(emp) linearHypothesis(zz, "2*log(pc)=log(emp)", vcov=vcovNW)