On 3/17/10, Achim Zeileis <achim.zeil...@uibk.ac.at> wrote:
> Here, you compare apples and oranges. gr_fe1 is of class "plm" and
> gr_fe1_null is of class "lm". This does not fly.
>
> gr_fe1_lm <- lm(invest ~ 0 + value + capital + firm + year, data = pgr)
> anova(gr_fe1_lm, gr_fe1_null)
>
> which does the job.
>
Indeed, I see.
> In short:
> - plm(..., model = "within") offers a convenient approach of what
> is usually done in this kind of analysis.
>
Unfortunately plm(..., effect="twoways", model = "within") fails on my
particular unbalanced panel data (100% CPU and the task never
finishes); there are no such issues with "individual" or "time". Worse
is that I cannot replicate the issue on dummy data.
> - You can replicate everything by hand using lm() but have to take
> care of everything yourself. But you do get the same results.
>
> - Don't mix the two approaches.
>
I wanted to avoid displaying >2000 individuals in the regression
coefficients, the reason for trying the mix-up. I also tried to do the
trick using a plm() model for the null, too, but there is no anova
method for these.
> gr_fe1 <- plm(invest ~ value + capital, data = pgr,
+ model = "within", effect="twoways")
> gr_fe1_null <- plm(invest ~ 0 + firm + year, data = pgr, model = "pooling")
> anova(gr_fe1_null, gr_fe1)
Error in UseMethod("anova") :
no applicable method for 'anova' applied to an object of class
"c('plm', 'panelmodel')"
And having checked the source, I wouldn't venture to implement one.
I'm still a bit stuck on how to proceed. Thank you
Liviu
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