la(), which is from the plm package. It
would probably require substantial effort to get this to work.
Best,
John
> -Original Message-
> From: Miluji Sb [mailto:miluj...@gmail.com]
> Sent: Thursday, September 6, 2018 8:52 AM
> To: Fox, John
> Cc: r-help mailing list
>
Dear Ista,
Thanks for your reply. I tried both "prediction" and "margins" but neither
of them seem to work with plm.
Sincerely,
Milu
On Thu, Sep 6, 2018 at 3:04 PM Ista Zahn wrote:
> You might be interested in the "prediction" and "margins" packages.
>
> --Ista
>
> On Wed, Sep 5, 2018 at 6:3
You might be interested in the "prediction" and "margins" packages.
--Ista
On Wed, Sep 5, 2018 at 6:30 PM Miluji Sb wrote:
>
> Dear all,
>
> I am running the following panel regression;
>
> plm1 <- plm(formula = log(y) ~ x1 + I(x1^2) + heat*debt_dummy + tt, data =
> df, index=c("region","year"))
Dear John,
Apologies for not providing reproducible example. I just tried with a plm
example but ran into the same issue;
library(plm)
data("Produc", package = "plm")
zz <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data = Produc,
index = c("state","year"))
Ef.hd <- Effect(c("pc", "e
to answer your question.
Best,
John
> -Original Message-
> From: Miluji Sb [mailto:miluj...@gmail.com]
> Sent: Thursday, September 6, 2018 5:37 AM
> To: Fox, John
> Cc: r-help mailing list
> Subject: Re: [R] Marginal effects with plm
>
> Dear John,
>
>
Dear John,
Thank you very much for the solution and the suggestion. I have tried the
following;
plm1 <- plm(formula = log(gva_ind) ~ poly(x1, 2, raw=TRUE) +
heat*debt_dummy + tt, data = df, index=c("region","year"))
Ef.hd <- Effect(c("heat", "debt_dummy"), plm1)
But get the following error; -
Dear Milu,
Depending upon what you mean by "marginal effects," you might try the effects
package. For example, for your model, try
(Ef.hd <- Effect(c("heat", "debt_dummy"), plm1))
plot(Ef.hd)
A couple of comments about the model: I'd prefer to specify the formula as
log(y) ~ p
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