# [R] Prediction with two fixed-effects - large number of IDs

Miluji Sb milujisb at gmail.com
Sat Jun 17 21:21:04 CEST 2017

```Dear Jeff,

Thank you so much and apologies for the typo in I() - it was silly.

I will try the biglm package - thanks!

Sincerely,

Milu

On Sat, Jun 17, 2017 at 9:01 PM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us>
wrote:

> I have no direct experience with such horrific models, but your formula is
> a mess and Google suggests the biglm package with ffdf.
>
> Specifically, you should convert your discrete variables to factors before
> you build the model, particularly since you want to use predict after the
> fact, for which you will need a new data set with the exact same levels in
> the factors.
>
> Also, your use of I() is broken and redundant.  I think formulas
>
> lny ~ id + year + x1 + I(x1^2) + x2 + I(x2^2)
>
> or
>
> lny ~ id + year + x1^2 + x2^2
>
> would obtain the intended prediction results.
>
> --
> Sent from my phone. Please excuse my brevity.
>
> On June 17, 2017 11:24:05 AM PDT, Miluji Sb <milujisb at gmail.com> wrote:
> >Dear all,
> >
> >I am running a panel regression with time and location fixed effects:
> >
> >###
> >
> >reg1 <- lm(lny ~ factor(id) + factor(year) + x1+ I(x1)^2 + x2+ I(x2)^2
> >,
> > data=mydata, na.action="na.omit")
> >###
> >
> >My goal is to use the estimation for prediction. However, I have 8,500
> >IDs,
> >which is resulting in very slow computation. Ideally, I would like to
> >do
> >the following:
> >
> >###
> >reg2 <- felm(lny ~ x1+ I(x1)^2 + x2+ I(x2)^2 | id + year , data=mydata,
> >na.action="na.omit")
> >###
> >
> >However, predict does not work with felm. Is there a way to either make
> >lm
> >faster or use predict with felm? Is parallelizing an option?
> >
> >Any help will be appreciated. Thank you!
> >
> >Sincerely,
> >
> >Milu
> >
> >       [[alternative HTML version deleted]]
> >
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