pbgtest {plm}

Breusch–Godfrey Test for Panel Models

Description

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

Usage

pbgtest(x, ...)

## S3 method for class 'panelmodel'
pbgtest(x, order = NULL, type = c("Chisq", "F"), ...)

## S3 method for class 'formula'
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",

...

further arguments (see lmtest::bgtest()).

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,

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 (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.

Value

An object of class "htest".

Note

The argument order defaults to the minimum number of observations over the time dimension, while for lmtest::bgtest it defaults to 1.

Author(s)

Giovanni Millo

References

Breusch TS (1978). “Testing for autocorrelation in dynamic linear models.” Australian Economic Papers, 17(31), 334–355.

Godfrey LG (1978). “Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables.” Econometrica, 46(6), 1293–1301.

Wooldridge JM (2002). Econometric Analysis of Cross–Section and Panel Data. MIT Press.

Wooldridge JM (2010). Econometric Analysis of Cross–Section and Panel Data, 2nd edition. MIT Press.

Wooldridge JM (2013). Introductory Econometrics: a modern approach, 5th edition. South-Western (Cengage Learning). Sec. 12.2, pp. 421–422.

See Also

For the original test in package lmtest see lmtest::bgtest(). See pdwtest() for the analogous panel Durbin–Watson test. See pbltest(), pbsytest(), pwartest() and pwfdtest() for other serial correlation tests for panel models.

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")