pdwtest: Durbin-Watson Test for Panel Models

In plm: Linear Models for Panel Data

Durbin–Watson Test for Panel Models

Description

Test of serial correlation for (the idiosyncratic component of) the errors in panel models.

Usage

pdwtest(x, ...)

## S3 method for class 'panelmodel'
pdwtest(x, ...)

## S3 method for class 'formula'
pdwtest(x, data, ...)

Arguments

x	an object of class "panelmodel" or of class "formula",
...	further arguments to be passed on to dwtest, e.g., alternative, see lmtest::dwtest() for further details.
data	a data.frame,

Details

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.

Value

An object of class "htest".

Author(s)

Giovanni Millo

References

\insertRef

DURB:WATS:50plm

\insertRef

DURB:WATS:51plm

\insertRef

DURB:WATS:71plm

\insertRef

WOOL:02plm

\insertRef

WOOL:10plm

See Also

lmtest::dwtest() for the Durbin–Watson test in lmtest, pbgtest() for the analogous Breusch–Godfrey test for panel models, lmtest::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().

Examples

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")

plm documentation built on April 11, 2025, 5:52 p.m.