similar to: Unexpected result with lag() et diff() in plm package.

I am trying to make R-1.8.1 on (SunOS shell1 5.8 Generic_108528-15 sun4u sparc SUNW,UltraAX-i2). I did ./configure make Configure output seems ok. The make proceeds until the following line appears, repeated indefinitely (until I break): ./config.status: ./confstat28489-19881/subs.frag: cannot overwrite existing file I suspect that this may involve write permissions (and maybe the umask set in

Dear R-help, I have a four-part question about regression, matrices, and sandwich package. 1) In the sandwich package, I would like to better understand the meat() function. >From the bread() documentation, for a simple OLS regression, bread() returns (1/n * X'X)^(-1) That is, for a simple regression (per the documentation on bread()): MyLM <- lm(y ~ x) bread(MyLM)

Dear all, This seems to be working, but I'd like to make sure that I'm not doing anything wrong. I am using by() to construct a complicated summary statistic by several factors in my data (specifically, the 90-50 income ratio by city and race). cityrace.by <- by(microdata, list(microdata$city,microdata$race), function (x) quantile(x$income, probs=0.9) / quantile(x$income, probs=0.5)

I didn't see you got an answer posted to this question: You can't modify a pdata.frame object. Your transforms turn it back to a normal data frame and diff and lag won't work as expected. Try: Grunfeld.p <- pdata.frame(Grunfeld,c("firm","year")) tmp <- transform(Grunfeld.p, d.value = diff(Grunfeld.p$value,1)) tmp <- cbind(tmp, l.value =

Dear R users I get different F-statistic results for a "within" model, when using "time" or "twoways" effects in plm() [1] and when manually specifying the time control dummies [2]. [1] vignette("plm") [2] http://cran.r-project.org/doc/contrib/Farnsworth-EconometricsInR.pdf Two examples below: library("AER") data("Grunfeld", package =

Dear R users, I wish to manually demean a panel over time and entities. I tried to code the Wansbeek and Kapteyn (1989) transformation (from Baltagi's book Ch. 9). As a benchmark I use both the pmodel.response() and model.matrix() functions in package plm and the results from using dummy variables. As far as I understood the transformation (Ch.3), Q%*%y (with y being the dependent variable)

Hello Cecilia, nice hearing from you again. I must restate a couple of my old hints, though ;^) 1) please always put the authors c/c, as we are not guaranteed to browse through the r-help every day 2) please provide reproducible examples. As example(pooltest) keeps working fine, as do some other cases I tried (Grunfeld data etc.), I don't know what the problem is but evidently your data are

Hi list, has anyone succeeded in using pgmm() on any dataset besides Arellano/Bond's EmplUK, as shown in the vignette? Whatever I try, I eventually get a runtime error because of a singular matrix at various points in pgmm.diff() (which gets called by pgmm()). For example, when estimating a "dynamic" version of the Grunfeld data: data(Grunfeld, package="Ecdat") grun

Dear R users What would be the best way to approach estimating a panel regression with twoways random effects, on unbalanced data? Unfortunately, the "plm" package has no implementation of twoways random effects for unbalanced data. Currently I'm considering two approaches: - extend "plm" to cover this type of panel regression. (For the authors, cc'ed:) Would

Hi everyone. I have two questions. I’ve found some other questions and answers similar to these but they didn’t solve my problem. I’m working with a panel of firm/years observations (see my reproducible example). I’m using the plm package. My panel not only is unbalanced but also have some gap’s in years. #reproducible example

Dear all I am working on unbalanced panel data and I can readily fit a "pooling" model using plm(), but not a "within" or "random" model. Reproducing the examples in vignette("plm") and in the AER package I encountered no such issues. ##unfortunately I cannot disclose the data, and it is too big anyway > dim(ibes.kld.exp.p[x.subs , ]) [1] 13189 34

Hello, I am trying to use the plm package for panel econometrics. I am just trying to get started and load my data. It seems from most of the sample documentation that I need to use the pdata.frame function to get my data loaded. However, even after installing the "plm" package, my R installation cannot find the function. I am trying to follow the example in plmEN.pdf (

Dear All, I'm looking to perform an ANOVA between two nested panel fixed effects models. I tried with anova, as well as with waldtest. anova tells me there is no method available for plm objects, while waldtest tells me my models are not nested. I think they are instead. The difference between the two models is that in the second I let the regression coefficients of a given variable variate

Hello, I am switching to R from Stata and I am having particular trouble with the transition from Stata's 'xtabond' and 'ivreg' commands to the "plm" package. I am trying to replicate some of the dynamic panel data work using the UK Employment data in Arellano and Bond (1991) and available as 'EmplUK' under the 'plm' package. I have been

Hi, I've been trying out the plm package, which seems like a great boon to those who want to analyze panel data in R. I haven't started to use the estimation functions themselves - for now I am just interested in having a robust way to deal with lags in unbalanced panel data, since it is such a royal pain to deal with all the special cases. However, In my tests, I found behavior that

Hello. Just a quick follow-up, for other 'plm' users on the list: - the problem turned out to be logs of zero values hidden in the big dataset - trying log(xx) would not reveal the problem, because log(0)=-Inf is a valid result in log() while it is an invalid input to plm() --> it is always advisable to try lm(yourformula, yourdata) as a first diagnostic check when plm(yourformula,

Dear plm Package users, I use the plm package a lot but I have not updated it for some times. Now I realized the following difficulty with the summary.plm function (demonstrated with the example from the ?plm documentation). library(plm) data("Produc", package="Ecdat") estimation_method<-"within" estimation_effect<-"individual" zz

Dear Sir, Thank you for accepting my request for registration on this site. I am trying to solve panel data problems using plm package , but while suing random effect model i am getting following messege saying " Warning message:In sqrt(sigma2) : NaNs produced " In some other cases i am getting message saying where TSS = NA , that I am not understanding I am sending you my code along

Dear Kailas Gokhale, The negative individual variance is not a problem with your code or plm. It a property of your data. Please check the posts of Giovanni Millo on this topic: [R] R: plm random effect: the estimated variance of the individual effect is negative Millo Giovanni Giovanni_Millo at Generali.com Sat Jan 5 10:10:01 CET 2013 You can find the posts in the archive by rseek.org.

Dear R users, I have an unbalanced panel with an average of I=100 individuals and a total of T=1370 time intervals, i.e. T>>I. So far, I have been using the plm package. I wish to estimate a FE model like: res<-plm(x~c+v, data=pdata_frame, effect="twoways", model="within", na.action=na.omit) ?where c varies over i and t, and v represents an exogenous impact on x