pdwtest {plm} | R Documentation |
Test of serial correlation for (the idiosyncratic component of) the errors in panel models.
pdwtest(x, ...) ## S3 method for class 'panelmodel' pdwtest(x, ...) ## S3 method for class 'formula' pdwtest(x, data, ...)
x |
an object of class |
data |
a |
... |
further arguments to be passed on to |
This Durbin–Watson test uses the auxiliary model on (quasi-)demeaned data taken
from a model of class plm
which may be a pooling
(the default),
random
or within
model. It performs a Durbin–Watson test
(using dwtest
from package lmtest) on the residuals of the
(quasi-)demeaned model, which should be serially uncorrelated under the null of
no serial correlation in idiosyncratic errors. The function takes the demeaned
data, estimates the model and calls dwtest
. Thus, this test does not take
the panel structure of the residuals into consideration; it shall not be confused
with the generalized Durbin-Watson test for panels in pbnftest
.
An object of class "htest"
.
Giovanni Millo
Durbin, J. and Watson, G.S. (1950), Testing for Serial Correlation in Least Squares Regression. I, Biometrika, 37(3/4), pp. 409–428.
Durbin, J. and Watson, G.S. (1951), Testing for Serial Correlation in Least Squares Regression. II, Biometrika, 38(1/2), pp. 159–177.
Durbin, J. and Watson, G.S. (1971), Testing for Serial Correlation in Least Squares Regression. III, Biometrika, 58(1), pp. 1–19.
Wooldridge, J.M. (2002) Econometric Analysis of Cross Section and Panel Data, MIT Press, p. 288.
Wooldridge, J.M. (2010) Econometric Analysis of Cross Section and Panel Data, 2nd ed., MIT Press, p. 328.
dwtest
for the Durbin–Watson test in lmtest,
pbgtest
for the analogous Breusch–Godfrey
test for panel models, bgtest
for the Breusch–Godfrey test for
serial correlation in the linear model. pbltest
,
pbsytest
, pwartest
and pwfdtest
for
other serial correlation tests for panel models.
For the Durbin-Watson test generalized to panel data models see pbnftest
.
data("Grunfeld", package = "plm") g <- plm(inv ~ value + capital, data = Grunfeld, model="random") pdwtest(g) pdwtest(g, alternative="two.sided") ## formula interface pdwtest(inv ~ value + capital, data=Grunfeld, model="random")