R help - Dec 2012 - I need intercept in plm model

Hi,R 2.15.2 plm() function on Windows 7
when i perform a plm regression, i can't manage to obtain the intercept, but
I need it.it gives me just the beta coefficient.
my formula: fixed <- plm(deltaS ~ L1.deltaS + L2.deltaS, data=Mody_R,
index=c("country_id", "date"), model="within")
my output: Coefficients :           Estimate Std. Error t-value  Pr(>|t|)   
L1.deltaS -0.063576   0.017950 -3.5419 0.0004031 ***L2.deltaS -0.068272  
0.017966 -3.8001 0.0001474 ***---
I tried adding "-0", "+1", "intercept=TRUE"
Thanks,Matteo 		 	   		  
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Dear Matteo,

a fixed effects (within) model does not have a single intercept: it has
N. I suggest you have another look at FE models' theory. 

Some confusion often stems from Stata (misleadingly, IMHO) reporting an
"intercept" which is actually the average of the individual
intercepts,
which you can recover in R as 'mean(fixef(<yourmodel>))'.
Remember,
though, that this isn't "the intercept" of the estimated model in
the
usual sense of the term. If you "need" an intercept, then you must
review your specification.

Best,
Giovanni

--------------- original message
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Message: 1
Date: Sat, 29 Dec 2012 14:47:33 +0100
From: matteo ognibene <ognibenematteo at hotmail.it>
To: <r-help at r-project.org>
Subject: [R] I need intercept in plm model
Message-ID: <DUB105-W4934C48C713500BA3FAF6CB63E0 at phx.gbl>
Content-Type: text/plain


Hi,R 2.15.2 plm() function on Windows 7
when i perform a plm regression, i can't manage to obtain the intercept,
but I need it.it gives me just the beta coefficient.
my formula: fixed <- plm(deltaS ~ L1.deltaS + L2.deltaS, data=Mody_R,
index=c("country_id", "date"), model="within")
my output: Coefficients :           Estimate Std. Error t-value
Pr(>|t|)    L1.deltaS -0.063576   0.017950 -3.5419 0.0004031
***L2.deltaS -0.068272   0.017966 -3.8001 0.0001474 ***---
I tried adding "-0", "+1", "intercept=TRUE"
Thanks,Matteo 		 	   		  
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?
Ai sensi del D.Lgs. 196/2003 si precisa che le informazi...{{dropped:12}}

Hi,R 2.15.2 plm() function on Windows 7
I have a problem with the variance estimation in a random effect model
I used this formula to get my result, and it works:reg <- deltaF ~ L1.deltaF
+ L2.deltaF + deltaCDS + L1.deltaCDS + L2.deltaCDS + L3.deltaCDS +
deltaUS_Yields + deltaZ + L1.deltaZ + L2.deltaZfixed <- plm(reg, data=Mody_R,
na.action = na.exclude, index=c("country_id", "datestata"),
model="random")
but when i split my dataframe into several groups it gives me this
error:"Error in swar(object, data, effect) :   the estimated variance of
the individual effect is negative"
The code i used to split the dataframe is:SplitMody <- split(Mody_R,
Mody_R$period)SplitFixed <- lapply(SplitMody, function(Mody_R) plm(reg,
data=Mody_R, na.action = na.exclude, index=c("country_id",
"datestata"), model="random"))
I want to point the all the code works perfectly in a within model, and I tried
using all the random.method for the variance estimation.In addition I used the
same model in Stata and it works... (the results are identical for a within
model in R and Stata)
I'll be really gratefull if someone can help me.
Thanks,Matteo 		 	   		   		 	   		  
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