Duh! Thanks and good advice. I was using 2.7.2 because it was, until
recently, the latest version working with RPy (http://rpy.sourceforge.net/).
Also didn't realize plm was still actively developed.
Interesting that since plm now correctly handles diff and lag operations, it
actually breaks with the behavior of lm:
a=ts(c(1,2,4))
lm(a~diff(a))
Error in model.frame.default(formula = a ~ diff(a), drop.unused.levels =
TRUE) :
variable lengths differ (found for 'diff(a)')
To regress a on its difference, one needs the more laborious:
a=ts(c(1,2,4))
adata=as.data.frame(cbind(a,diff(a)))
colnames(adata)=c(a,diffa)
lm(a~diffa,data=adata)
Call:
lm(formula = a ~ diffa, data = adata)
Coefficients:
(Intercept)diffa
02
From the R help
Fitting Linear ModelsUsing time series
Considerable care is needed when using lm with time series.
Unless na.action = NULL, the time series attributes are stripped from the
variables before the regression is done. (This is necessary as omitting NAs
would invalidate the time series attributes, and if NAs are omitted in the
middle of the series the result would no longer be a regular time series.)
Even if the time series attributes are retained, they are not used to line
up series, so that the time shift of a lagged or differenced regressor would
be ignored. It is good practice to prepare a data argument by
ts.intersectts.union.html(...,
dframe = TRUE), then apply a suitable na.action to that data frame and call
lm with na.action = NULL so that residuals and fitted values are time
series.
On Sat, Jul 11, 2009 at 10:53 PM, milton ruser milton.ru...@gmail.comwrote:
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 damienlmo...@gmail.comwrote:
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 -0.761830.03535 -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) -0.761830.03535 -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)')
*
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.htmlhttp://www.r-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
