Dear R Experts---

Sorry for all the questions yesterday and today. I am trying to use Yves  
Croissant's pgmm function in the plm package with Blundell-Bond moments. I  
have read the Blundell-Bond paper, and want to run the simplest model  
first, d[i,t] = a*d[i,t-1] + fixed[i] + u[i,t] . no third conditioning  
variables yet. the full set of moment conditions recommended for  
system-GMM, which is (T-1)*(T-2)/2+(T-3), in which the u's interact with  
all possible lagged y's and delta y's.

I believe that pgmm operates by demanding that "firm" (i) and "year" (t) be  
the first two columns in the data set.

library(plm)
NF=20; NT=10
d= data.frame( firm= rep(1:NF, each=NT), year= rep( 1:NT, NF),  
x=rnorm(NF*NT) );

# the following fails, because dynformula magic is required; learned this  
the hard way
# v=pgmm( x ~ lag(x), data=d, gmm.inst=~x, lag.gmm=c(2,99),  
transformation="ld" )

formula= dynformula( x ~ 1, list(1)); # this creates x ~ lag(x)
v=pgmm( formula, data=d, gmm.inst=~x, lag.gmm=c(2,99), transformation="ld" )

Error in solve.default(suml(Vi)) :
system is computationally singular: reciprocal condition number =  
8.20734e-20

obviously, I am confused. when I execute the same command on the included  
UKEmpl data set, it works. however, my inputs would seem perfectly  
reasonable. I would hope that the procedure could produce a lag(x)  
coefficient estimate of around 0, and then call it a day.

could someone please tell me how to instruct pgmm to just estimate this  
simplest of all BB models?


[My ultimate goal is to replicate what another author has run via "xtabond2  
d ld, gmm(L.(d), lag(1 3)) robust" in Stata; if you know the magic of  
moving this statement into pgmm syntax, I would be even more grateful.  
Right now, I am so stuck on square 1 that I do not know how to move towards  
figuring out where I ultimately need to go.]

regards,

/iaw

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