[R] PLM falling into the dummy variable trap -- how to fix?

[Andrew Crane-Droesch]

Dear list, CC Dr Croissant,

I'm tryng to use plm with timeXgroup effects (in addition to the twoway 
effects), and running into problems with dummy variables. Eventually I 
want to take advantage of pgmm as well, but first I'd like to solve the 
problem with the non-dynamic version.

An example:

     load(url('http://andrewcd.berkeley.edu/sdat'))
     head(sdat)
     library(plm)
     fem = 
plm(y~T+G:t,data=sdat,effect="twoways",model="within",index=c("ID","t"))
     summary(fem)
     lsdvm = lm(y~ID+T+G:t,data=sdat)
     summary(lsdvm)
     fem$coef

`fem` is the fixed-effects model (fit with plm), and `lsdv` is the 
equivalent least-squares dummy variable model (fit with lm)

It is clear that plm is estimating the coefficients, and indeed that the 
coefficients are identical in the two models, as they should be.  But 
when I go to summarize the results, plm is having a hard time, and I'm 
pretty sure that the reason is the timeXgroup fixed effects, some of 
which need to be auto-omitted because of the dummy variable trap.  (lm, 
for example, seems to know how to automatically remove variables that 
are exact linear combinations of each other).

How do I get around this?  I'd prefer to stay with plm, as it gives much 
more parsimonious output than lm with dummy variables for each 
cross-sectional unit.

Thanks in advance for any help!

Best,
Andrew