plm Hausman-Taylor model

Dear all-

I am have trouble in using the model="ht" option in function plm from the plm 
library.  I am using
Package: plm Version: 1.1-1; R version 2.8.1 (2008-12-22) running on a FC-8 
linux machine.

Here is what I am trying to do:

##----------------------------------------------------------------------------
R> ###Prob 6  Chapter 3 Use R! Applied Econometrics with R (Kleiber & 
Zeileis)
R> ## hlp(PSID1982) => cross section data for 1982 only  Need panel data I 
guess
R> ## found full set on STATA web site
R> ## http://www.stata-press.com/data/r10/psidextract.dta
R> ## STATA results in Sec 2 of: folk.uio.no/erikbi/ECON5120_H07_Note19.pdf
R> library("foreign")
R> fulldat <- read.dta("~/Desktop/psidextract.dta")
R> library("plm")
R>
R> fulldat.plm = plm.data(fulldat,index=c("id","t"))
R>
R> earn_plm <- plm(lwage~ occ+ south+ smsa+ ind+ exp+ exp2+ wks+
+                 ms+ union+ fem+ blk+ ed | exp+ exp2+ wks+ ms+ union+ ed,
+                 data = fulldat.plm,model="ht")
Error in names(result) <- nf : attempt to set an attribute on NULL

I have tried several variations and some other data sets (not so easily 
reproducible for others as this one) but have yet to obtain an error free 
result.

This seems to be a bug in "plm". traceback() shows:

R> traceback()
4: lev2var(data[, -c(K - 1, K)])
3: plm.ht(formula, data)
2: switch(model, within = plm.within(formula, data, effect), between = 
plm.between(formula,
        data, effect), pooling = plm.pooling(formula, data), random = 
plm.random(formula,
        data, effect, random.method, inst.method), ht = plm.ht(formula,
        data), fd = plm.fd(formula, data))
1: plm(lwage ~ occ + south + smsa + ind + exp + exp2 + wks + ms +
        union + fem + blk + ed | exp + exp2 + wks + ms + union +
        ed, data = fulldat.plm, model = "ht")

lev2var() is a function internal to "plm" and it apparently fails if there 
are no factors in the data. (The result is NULL and lev2var() tries to 
assign names to it; these are character(0) but still this fails with the 
error message you have quoted above.) Maybe Yves can clarify this.

A workaround for your example is to code the dummy variables as factors 
(which might also be more useful in other situations). For example:

R> for(i in c(3:9, 11)) fulldat[[i]] <- factor(fulldat[[i]])
R> fulldat.plm = plm.data(fulldat,index=c("id","t"))
R> earn_plm <- plm(lwage~ occ+ south + smsa+ ind + exp + exp2 + wks +
+    ms + union + fem + blk + ed | exp + exp2 + wks + ms + union + ed,
+    data = fulldat.plm, model = "ht")

Of course, more meaningful factor levels would be desirable but at least 
this works. It gives similar results to those that you refer to above, but 
they are not identical. Maybe Yves can something more about the 
differences to Stata.

hth,
Z

Thanks in advance for any help
    Ron
--
R. R. Burns
Retired
Oceanside, CA