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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