The first think one need to do when has a so old version, is update it :-)
After, if the problem remain, try get help with the colleagues.

best

milton

On Thu, Jul 9, 2009 at 10:58 AM, Damien Moore <damienlmoore@gmail.com>wrote:

> Hi List
>
> I'm having difficulty understanding how plm should work with dynamic
> formulas. See the commands and output below on a standard data set. Notice
> that the first summary(plm(...)) call returns the same result as the second
> (it shouldn't if it actually uses the lagged variable requested). The third
> call results in error (trying to use diff'ed variable in regression)
>
> Other info: I'm running R 2.7.2 on WinXP
>
> cheers
>
>
>
> *>data("Gasoline",package="Ecdat")
> >Gasoline_plm<-plm.data(Gasoline,c("country","year"))
> >pdim(Gasoline_plm)
> **Balanced Panel: n=18, T=19, N=342
> *
> *>summary(plm(lgaspcar~lincomep,data=Gasoline_plm**))
> **Oneway (individual) effect Within Model
>
> Call:
> plm(formula = lgaspcar ~ lincomep, data = Gasoline_plm)
>
> Balanced Panel: n=18, T=19, N=342
>
> Residuals :
>    Min.  1st Qu.   Median  3rd Qu.     Max.
> -0.40100 -0.08410 -0.00858  0.08770  0.73400
>
> Coefficients :
>         Estimate Std. Error t-value  Pr(>|t|)
> lincomep -0.76183    0.03535 -21.551 < 2.2e-16 ***
> ---
> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> Total Sum of Squares: 17.061
> Residual Sum of Squares: 6.9981
> Multiple R-Squared: 0.58981
> F-statistic: 464.442 on 323 and 1 DF, p-value: 0.036981
>
> **> summary(plm(lgaspcar~lag(lincomep),data=Gasoline_plm))
> **Oneway (individual) effect Within Model
>
> Call:
> plm(formula = lgaspcar ~ lag(lincomep), data = Gasoline_plm)
>
> Balanced Panel: n=18, T=19, N=342
>
> Residuals :
>    Min.  1st Qu.   Median  3rd Qu.     Max.
> -0.40100 -0.08410 -0.00858  0.08770  0.73400
>
> Coefficients :
>              Estimate Std. Error t-value  Pr(>|t|)
> lag(lincomep) -0.76183    0.03535 -21.551 < 2.2e-16 ***
> ---
> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> Total Sum of Squares: 17.061
> Residual Sum of Squares: 6.9981
> Multiple R-Squared: 0.58981
> F-statistic: 464.442 on 323 and 1 DF, p-value: 0.036981
>
> *
> *>summary(plm(lgaspcar~diff(lincomep),data=Gasoline_plm))*
> *Error in model.frame.default(formula = lgaspcar ~ diff(lincomep), data =
> mydata,  :
>  variable lengths differ (found for 'diff(lincomep)')
> *
>
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>
>
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>
>

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