plm (version 1.6-5)

pbgtest: Breusch--Godfrey Test for Panel Models

Description

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

Usage

pbgtest(x, ...)
"pbgtest"(x, order = NULL, type = c("Chisq", "F"), ...)
"pbgtest"(x, order = NULL, type = c("Chisq", "F"), data, model=c("pooling", "random", "within"), ...)

Arguments

x

an object of class "panelmodel" or of class "formula",

order

an integer indicating the order of serial correlation to be tested for. NULL (default) uses the minimum number of observations over the time dimension (see also section Details below),

type

type of test statistic to be calculated; either "Chisq" (default) for the Chi-squared test statistic or "F" for the F test statistic,

data

only relevant for formula interface: data set for which the respective panel model (see model) is to be evaluated,

model

only relevant for formula interface: compute test statistic for model pooling (default), random, or within. When model is used, the data argument needs to be passed as well,

...

further arguments (see bgtest).

Value

An object of class "htest".

Details

This Lagrange multiplier test uses the auxiliary model on (quasi-)demeaned data taken from a model of class plm which may be a pooling (default for formula interface), random or within model. It performs a Breusch--Godfrey test (using bgtest 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, as illustrated in Wooldridge (2002/2010). The function takes the demeaned data, estimates the model and calls bgtest.

Unlike most other tests for serial correlation in panels, this one allows to choose the order of correlation to test for.

References

Breusch, T.S. (1978), “Testing for autocorrelation in dynamic linear models”, Australian Economic Papers, 17(31), pp. 334--355.

Godfrey, L.G. (1978), “Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables”, Econometrica, 46(6), pp. 1293--1301. Wooldridge, J.M. (2002) Econometric Analysis of Cross-Section and Panel Data, MIT Press, pp. 288--291. Wooldridge, J.M. (2010) Econometric analysis of cross-section and Panel Data, 2nd ed., MIT Press, pp. 328--334. Wooldridge, J.M. (2013) Introductory Econometrics: A Modern Approach, 5th ed., South-Western (Cengage Learning), Sec. 12.2, pp. 421--422.

See Also

pdwtest for the analogous panel Durbin--Watson test, 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 original test in package lmtest see bgtest.

Examples

data("Grunfeld", package = "plm")
g <- plm(inv ~ value + capital, data = Grunfeld, model = "random")

# panelmodel interface
pbgtest(g)
pbgtest(g, order = 4)

# formula interface
pbgtest(inv ~ value + capital, data = Grunfeld, model = "random")

# F test statistic (instead of default type="Chisq")
pbgtest(g, type="F")
pbgtest(inv ~ value + capital, data = Grunfeld, model = "random", type="F")

# same output as lmtest::bgtest [see Note]
pbgtest(g, order = 1)
lmtest::bgtest(g, order = 1)