[R] Adjusting for autocorrelation in a panel model

[David Kennedy]

Dear Millo

Thank you for the prompt and honest answer.

Please accept my appreciation for developing the 'plm' package and for the excellent documentation associated with it.  It was a great place for me to start, and it made my initial forays into panel data analysis a lot easier.

You have given me an example of a random effects model with MA(4) errors.

I actually want to fit a fixed effects model with MA(4) errors.  Could you advise on how the Grunfeld formula would be modified to make it into a fixed effects model?  Or could you advise of any documentation that explains the 'nlme' package from an econometrician's perspective?  

-----Original Message-----
From: Millo Giovanni [mailto:Giovanni_Millo at Generali.com] 
Sent: Wednesday, 23 February 2011 12:46 a.m.
To: david.dmk at ihug.co.nz
Cc: R-help at r-project.org; Yves Croissant
Subject: [R] Adjusting for autocorrelation in a panel model

Cheers
David


Dear David,

short answer: no. Although an MA(4) correlation structure makes perfect
sense in an econometric panel model, the treatment of (relatively) rich
covariance structures in a likelihood framework is done so well in the
'nlme' and 'lme4' packages that we decided not to duplicate
functionality and specialize in OLS- and GLS-based semiparametric
methods instead.

If I am not mistaken, what you want may be done in 'nlme' along these
lines (usual Grunfeld example, RE + MA(4) errors):

> library(nlme)
> mod <- lme(inv ~ value + capital, data = Grunfeld,
+  random = ~ 1 | firm, correlation = corARMA(q=4, form = ~ year |
firm))
> summary(mod)
Linear mixed-effects model fit by REML
 Data: Grunfeld 
       AIC      BIC    logLik
  2080.698 2110.247 -1031.349

Random effects:
 Formula: ~1 | firm
        (Intercept) Residual
StdDev:     85.3411  61.4331

Correlation Structure: ARMA(0,4)
 Formula: ~year | firm 
 Parameter estimate(s):
    Theta1     Theta2     Theta3     Theta4 
1.02717687 0.72128293 0.20164003 0.03955776 
Fixed effects: inv ~ value + capital 
                 Value Std.Error  DF  t-value p-value
(Intercept) -30.417581 29.772699 188 -1.02166  0.3083
value         0.085603  0.007226 188 11.84669  0.0000
capital       0.304009  0.026718 188 11.37854  0.0000
 Correlation: 
        (Intr) value 
value   -0.220       
capital -0.219 -0.144

Standardized Within-Group Residuals:
         Min           Q1          Med           Q3          Max 
-2.507368276 -0.308055815  0.006783496  0.236507068  4.513481803 

Number of Observations: 200
Number of Groups: 10 
> 

This is a quick modification of the example on top of page 38 in our
paper here http://www.jstatsoft.org/v27/i02. Please refer to it for more
on plm vs. nlme (but be aware: back then I wrote that nlme didn't
support unbalanced panels, which was incorrect: it does!).

Lastly, yu're perfectly right: the asymptotics of pggls is inappropriate
in your case.

Best wishes,
Giovanni

------------- original message -----------------

Message: 107
Date: Tue, 22 Feb 2011 16:09:48 +1300
From: "David Kennedy" <david.dmk at ihug.co.nz>
To: <r-help at r-project.org>
Subject: [R] Adjusting for autocorrelation in a panel model
Message-ID: <00b701cbd23d$f7200560$e5601020$@dmk at ihug.co.nz>
Content-Type: text/plain

I am working with panel data.  I am using the plm package to do this.

 

I would like to do be able to adjust for autocorrelation, as one does
with
glm models and correlation structures (eg corr=corARMA(q=4)) .  In
particular, I want to employ MA(4) error structure.

 

Is there a way of doing this with the plm package?

 

(Note: I do not really want to use the pggls function for various
reasons.
One of those reasons is that it will be rare for n >> T.)

 

Thanks to anyone who can help.

 

Cheers

David


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

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


Ai sensi del D.Lgs. 196/2003 si precisa che le informazi...{{dropped:13}}