R help - May 2010 - Regressions with fixed-effect in R

Hi there,

Maybe people who know both R and econometrics will be able to answer
my questions.

I want to run panel regressions in R with fixed-effect. I know two
ways to do it.
First, I can include factor(grouping_variable) in my regression equation.
Second, I plan to subtract group mean from my variables and run OLS
panel regression with function lm().

I plan to do it with the second way because the number of groups is
large, which incur computational problems inverting large
model-matrix.

I am interested in the R-squared and adjusted R-squared out of these
regressions.

Do I need to adjust my R-squared after I run OLS regressions with
demeaned variables?

Are there any functions that specifically deal with fixed-effects?

Thanks.

Best,
Jia

There is the plm package for linear panel models. Further, since estimation
of fixed effects models rests on the within-subject or -object variance, the
R-squared of interest is typically the within R-squared, not the overall or
between R-squared. Read up about it before you use it though.

Daniel

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On 5/11/10, chen jia <chen_1002 at fisher.osu.edu>
wrote:
>  Are there any functions that specifically deal with fixed-effects?
>
Other than plm and its vignette, you may want to check this document [1].
Liviu

[1] http://cran.r-project.org/doc/contrib/Farnsworth-EconometricsInR.pdf

Dear Daniel

On 5/11/10, Daniel Malter <daniel at umd.edu>
wrote:
>  R-squared of interest is typically the within R-squared, not the overall
or
>
Could you point to an example on how to compute the within R-squared
in R, either via lm() or plm()?
Thank you
Liviu

Thanks. I have the PDF document that you suggest. It is very brief on
fixed-effect in panel regressions.

I will look into plm package.

Best,
Jia

On Tue, May 11, 2010 at 8:19 AM, Liviu Andronic <landronimirc at
gmail.com> wrote:
> On 5/11/10, chen jia <chen_1002 at fisher.osu.edu> wrote:
>> ?Are there any functions that specifically deal with fixed-effects?
>>
> Other than plm and its vignette, you may want to check this document [1].
> Liviu
>
> [1] http://cran.r-project.org/doc/contrib/Farnsworth-EconometricsInR.pdf
>


-- 
                         Ohio State University - Finance
                                   248 Fisher Hall
                                    2100 Neil Ave.
                              Columbus, Ohio  43210
                             Telephone: 614-292-2830
                       http://www.fisher.osu.edu/~chen_1002/

Dear Liviu,

we're still working on measures of fit for panels. If I get you right,
what you mean is the R^2 of the demeaned, or "within", regression. A
quick and dirty function to do this is:

pmodel.response<-plm:::pmodel.response.plm # needs this to make the
method accessible

r2<-function(x, adj=TRUE) {
  ## fetch response and residuals
  y <- pmodel.response(x, model="within")
  myres <- resid(x)
  n <- length(myres)

  if(adj) {
    adjssr <- x$df.residual
    adjtss <- n-1
    } else {
    adjssr <- 1
    adjtss <- 1
    }

  ssr <- sum(myres^2)/adjssr
  tss <- sum(y^2)/adjtss
  return(1-ssr/tss)
  }

and then
> r2(yourmodel)
Hope this helps
Giovanni

------------------------------

Message: 13
Date: Tue, 11 May 2010 13:21:02 +0100
From: Liviu Andronic <landronimirc at gmail.com>
To: Daniel Malter <daniel at umd.edu>
Cc: r-help at r-project.org
Subject: Re: [R] Regressions with fixed-effect in R
Message-ID:
	<AANLkTikvI6_-QVH-Odr31EiipPuq1sRa0-qconQZHtAV at mail.gmail.com>
Content-Type: text/plain; charset=UTF-8

Dear Daniel

On 5/11/10, Daniel Malter <daniel at umd.edu>
wrote:
>  R-squared of interest is typically the within R-squared, not the
overall or
>
Could you point to an example on how to compute the within R-squared
in R, either via lm() or plm()?
Thank you
Liviu

--------------------------------

Giovanni Millo
Research Dept.,
Assicurazioni Generali SpA
Via Machiavelli 4, 
34132 Trieste (Italy)
tel. +39 040 671184 
fax  +39 040 671160