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) ~ poly(x1, 2) + heat*debt + tt or log(y) ~ poly(x1, 2, raw=TRUE) +
heat*debt + tt (assuming that debt_dummy is a precoded dummy regressor for a
factor debt).
I hope this helps,
John
--------------------------------------
John Fox, Professor Emeritus
McMaster University
Hamilton, Ontario, Canada
Web: socialsciences.mcmaster.ca/jfox/
> -----Original Message-----
> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Miluji
> Sb
> Sent: Wednesday, September 5, 2018 6:30 PM
> To: r-help mailing list <r-help@r-project.org>
> Subject: [R] Marginal effects with plm
>
> 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"))
>
> where 'df' is a pdata.frame. I would like to obtain marginal effects of
> 'y'
> for the variable 'x1'. I have tried the packages 'prediction' and
> 'margins'
> without luck.
>
> Is it possible to obtain marginal effects with 'plm'? Any help will be
> highly appreciated. Thank you.
>
> Error in UseMethod("predict") :
> no applicable method for 'predict' applied to an object of class
> "c('plm', 'panelmodel')"
>
> Sincerely,
>
> Milu
>
> [[alternative HTML version deleted]]
>
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