plm (version 2.2-5)

vcovNW: Newey and West (1987) Robust Covariance Matrix Estimator

Description

Nonparametric robust covariance matrix estimators a la Newey and West for panel models with serial correlation.

Usage

vcovNW(x, ...)
# S3 method for plm
vcovNW(
  x,
  type = c("HC0", "sss", "HC1", "HC2", "HC3", "HC4"),
  maxlag = NULL,
  wj = function(j, maxlag) 1 - j/(maxlag + 1),
  ...
)
# S3 method for pcce
vcovNW(
  x,
  type = c("HC0", "sss", "HC1", "HC2", "HC3", "HC4"),
  maxlag = NULL,
  wj = function(j, maxlag) 1 - j/(maxlag + 1),
  ...
)

Arguments

x

an object of class "plm" or "pcce"

…

further arguments

type

the weighting scheme used, one of "HC0", "sss", "HC1", "HC2", "HC3", "HC4", see Details,

maxlag

either NULL or a positive integer specifying the maximum lag order before truncation

wj

weighting function to be applied to lagged terms,

Value

An object of class "matrix" containing the estimate of the covariance matrix of coefficients.

Details

vcovNW is a function for estimating a robust covariance matrix of parameters for a panel model according to the NEWE:WEST:87;textualplm method. The function works as a restriction of the DRIS: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 MACK:WHIT:85;textualplm and CRIB:04;textualplm @see @ZEIL:04plm.

The main use of vcovNW is to be an argument to other functions, 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). Notice that the vcov and vcov. arguments allow to supply a function (which is the safest) or a matrix @see @ZEIL:04, 4.1-2 and examples belowplm.

References

CRIB:04plm

DRIS:KRAA:98plm

MACK:WHIT:85plm

NEWE:WEST:87plm

ZEIL:04plm

See Also

sandwich::vcovHC() from the sandwich package for weighting schemes (type argument).

Examples

# NOT RUN {
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)

# }

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