R: Tests of cross-section dependence for panel models
pcdtest
R Documentation
Tests of cross-section dependence for panel models
Description
Pesaran's CD or Breusch-Pagan's LM (local or global) tests for cross sectional dependence in panel models
Usage
pcdtest(x, ...)
## S3 method for class 'panelmodel'
pcdtest(x, test = c("cd", "sclm", "lm", "rho", "absrho"),
w = NULL, ...)
## S3 method for class 'formula'
pcdtest(x, data, index = NULL, model = NULL,
test = c("cd", "sclm", "lm", "rho", "absrho"),
w = NULL, ...)
Arguments
x
an object of class formula or panelmodel, describing the model to be tested
data
a data.frame
index
an optional numerical index, in case data has to be formatted by plm.data
model
an optional character string indicating which type of model to estimate;
if left to NULL, the original heterogeneous specification of Pesaran is used
test
the type of test statistic to be returned. One of "cd" for Pesaran's CD statistic,
"lm" for Breusch and Pagan's original LM statistic,
"sclm" for the scaled version of Breusch and Pagan's LM statistic, or
"rho", "absrho" for average (absolute) correlation coefficient
w
an n x nmatrix describing proximity between observations, with w_ij = a where a is any number such that as.logical(a)=TRUE, if i,j are
neighbours, 0 or any number b such that as.logical(b)=FALSE elsewhere
...
further arguments to be passed on to plm, such as e.g. effect or random.method
Details
These tests are originally meant to use the residuals of separate estimation of one time-series regression for each cross-sectional unit in order to check for cross-sectional dependence. If a different model specification (within, random, ...) is assumed consistent, one can resort to its residuals for testing (which is common, e.g., when the time dimension's length is insufficient for estimating the heterogeneous model). If the time dimension is insufficient and model=NULL, the function defaults to estimation of a within model and issues a warning. The main argument of this function may be either a model of class panelmodel or a formula and dataframe; in the second case, unless model is set to NULL, all usual parameters relative to the estimation of a plm model may be passed on. The test is compatible with any consistent panelmodel for the data at hand, with any specification of effect. E.g., specifying effect=''time'' or effect=''twoways'' allows to test for residual cross-sectional dependence after the introduction of time fixed
effects to account for common shocks. A local version of either test can be computed supplying a proximity matrix (coercible to logical) providing information on whether any pair of observations are neighbours or not. If w is supplied, only neighbouring pairs will be used in computing the test; else, w will default to NULL and all observations will be used. The matrix need not be binary, so commonly used “row-standardized” matrices can be employed as well. nb objects from spdep must instead be transformed into matrices by nb2mat before using.
Value
An object of class "htest".
References
Breusch, T.S. and A.R. Pagan (1980), The Lagrange multiplier test and its applications to model specification in econometrics, Review of Economic Studies, 47, pp. 239–253.
Pesaran, H. (2004), General Diagnostic Tests for Cross Section Dependence in Panels, CESIfo Working Paper 1229.
Examples
data(Grunfeld, package = "plm")
## test on heterogeneous model (separate time series regressions)
pcdtest(inv ~ value + capital, data=Grunfeld,
index = c("firm","year"))
## test on two-way fixed effects homogeneous model
pcdtest(inv ~ value + capital, data=Grunfeld, model="within",
effect="twoways", , index = c("firm","year"))
## test on model object
g <- plm(inv ~ value + capital, data=Grunfeld, index = c("firm","year"))
pcdtest(g)
## scaled LM test
pcdtest(g,test="sclm")
providing 
.