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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