On Wed, 17 Mar 2010, Liviu Andronic wrote:
Dear Achim
On 3/16/10, Achim Zeileis <achim.zeil...@uibk.ac.at> wrote:
Hence, when saying summary() different models with "no effects" are
assumed. For gr_fe the model without effects just omits value/capital but
keeps the firm-specific interecepts. For gr_lm not even the intercept is
kept in the model. Thus:
gr_fe_null <- lm(invest ~ 0 + firm, data = pgr)
gr_lm_null <- lm(invest ~ 0, data = pgr)
What would be the more useful "no effects" model in the plm(...,
effect="twoways") case? Considering the same setting,
library("AER")
data("Grunfeld", package = "AER")
library("plm")
gr <- subset(Grunfeld, firm %in% c("General Electric", "General Motors", "IBM"))
pgr <- plm.data(gr, index = c("firm", "year"))
I am fitting a "twoways" model and an "individual" with manually
specified time effects.
gr_fe1 <- plm(invest ~ value + capital, data = pgr,
+ model = "within", effect="twoways")
[snip]
Following the reasoning in your previous e-mail, I assume that the
(more useful) "no effects" model used in the "twoways" case is
gr_fe1_null <- lm(invest ~ 0 + firm + year, data = pgr)
Yes.
However I cannot replicate the F-statistic: 107.246.
anova(gr_fe1_null, gr_fe1)
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.
In short:
- plm(..., model = "within") offers a convenient approach of what
is usually done in this kind of analysis.
- 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.
Best,
Z
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