pwartest {plm} | R Documentation |
Test of serial correlation for (the idiosyncratic component of) the errors in fixed-effects panel models.
pwartest(x,...) ## S3 method for class 'panelmodel': pwartest(x, ...) ## S3 method for class 'formula': pwartest(x, data, ...)
x |
an object of class formula or of class panelmodel , |
data |
a data.frame , |
... |
further arguments to be passed on to linear.hypothesis or to vcovHC . |
As Wooldridge (2003, 10.5.4) observes, under the null of no serial correlation in the errors, the residuals of a FE model must be negatively serially correlated, with cor(hat{u}_{it}, hat{u}_{is})=-1/(T-1) for each t,s . He suggests basing a test for this null hypothesis on a pooled regression of FE residuals on their first lag: hat{u}_{i,t}=α + delta hat{u}_{i,t-1} + eta_{i,t}. Rejecting the restriction delta = -1/(T-1) makes us conclude against the original null of no serial correlation.
pwartest
estimates the within
model and retrieves
residuals, then estimates an AR(1) pooling
model on them. The
test statistic is obtained by applying linear.hypothesis()
to the
latter model to test the above restriction on delta, setting the
covariance matrix to vcovHC
with the option
method="arellano"
to control for serial correlation.
Unlike the pbgtest
and pdwtest
, this test does not rely on
T-asymptotics and has therefore good properties in ``short''
panels. Furthermore, it is robust to general heteroskedasticity.
An object of class "htest"
.
Giovanni Millo
Wooldridge, J.M. (2002) Econometric analysis of cross-section and panel data, MIT Press, 10.5.4, page 274.
pwfdtest
, pdwtest
, pbgtest
, pbltest
,
pbsytest
.
data("EmplUK", package="plm") pwartest(log(emp) ~ log(wage) + log(capital), data=EmplUK)