Locally robust panel Lagrange Multiplier tests for spatial dependence
Locally robust panel Lagrange Multiplier tests for spatial dependence
Locally robust LM tests for spatial lag (error) correlation sub spatial error (lag) correlation in panel models
slmtest(x,...)## S3 method for class 'formula'slmtest(formula, data, listw, model="pooling", test=c("lme","lml","rlme","rlml"), index=NULL,...)## S3 method for class 'plm'slmtest(x, listw, test=c("lme","lml","rlme","rlml"),...)
Arguments
formula: an object of class formula
data: a data.frame or pdata.frame containing the variables in the model
x: an object of class plm
listw: either a matrix or a listw representing the spatial structure
model: a character value specifying the transformation to be applied to the data.
test: one of c("lme","lml","rlme","rlml"), the test to be performed.
index: either NULL (default) or a character vector to identify the indexes among the columns of the data.frame
...: additional arguments to be passed
Details
This tests are panel versions of the locally robust LM tests of Anselin et al. (1996), based on a pooling assumption: i.e., they do not allow for any kind of individual effect. Therefore it is advisable to employ a within transformation whenever individual effects cannot be ruled out.
It must be kept in mind that these locally robust procedures have been designed for situations in which the "other" effect is not of substantial magnitude, and can behave suboptimally otherwise.
Four tests are available to be chosen through the test
argument: "lml" for "LM lag" and, respectively, "lme"
for "LM error" are the standard, non-robust versions, obtained simply pooling the cross-sectional versions; "rlml" and "rlme"
are, respectively, the locally robust test for lag, allowing for a spatial error; and for error, allowing for a spatial lag.
The model argument, specified according to the standards of plm, is passed on internally and employed to determine the panel data transformation to be applied before calculating the test. Defaults to "pooling" (no transformation).
Returns
an object of class htest
References
Anselin, L., Bera, A.K., Florax, R. and Yoon, M.J. (1996) Simple diagnostic tests for spatial dependence. Regional Science and Urban Economics, 26 (1), 77-104. Elhorst, J.P. (2014) Spatial Panel data Models, in Spatial Econometrics (Springer) 37-93.
Author(s)
Giovanni Millo
Examples
data(Produc, package="plm")data(usaww)fm <- log(gsp)~log(pcap)+log(pc)+log(emp)+unemp
## robust LM test for spatial error sub spatial lag## model on original data, pooling hypothesisslmtest(fm, data=Produc, listw = usaww, test="rlme")## model on within-transformed (time-demeaned) data,## eliminates individual effectsslmtest(fm, data=Produc, listw = usaww, test="rlme", model="within")