similar to: issues in plm using random effect model

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.

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 (

Hello Giovanni I made a minor modification to your function, which now allows to compute the within R-sq in Twoways Within models (see below). However I ran into an issue that I have already encountered before: whenever I try to fit Twoways Within models on my unbalanced data, the process is strangely slow and I usually terminate it either after ~15min or when my CPU hits 100C. This is similar to

I have an unexpected result with the functions lag() and diff() in the plm (panel data) package when used with transform(). These plm-specific functions are supposed to generate lags and first differences within each panel. lag() does not work properly the first time (it reproduces the same series--this is a common time series pitfall), BUT then it does work properly when it is run a second

Hi all, I installed all required packages for plm, but pdata.frame is not a recognized function on R to start with. I followed the first page of "introduction to plm" by Croissant&Millo, Here are the messages: * > library(plm) Loading required package: kinship Loading required package: survival Loading required package: splines Loading required package: nlme Loading required

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:

Hello, I am working on a data set (already as a plm.data object) located here: http://econsteve.com/arch/plmWithDensity.Robj With the following R session: > library(plm) ... >load("plmWithDensity.Robj") >model <- plm(RATE ~ density08, data=plmWithDensity) Error: subscript out of bounds I am not understanding the "subscript out of bounds" error, as this is a

Hello list, I'm following the paper (http://www.jstatsoft.org/v27/i02/paper) on how to use "plm" to run panel regressions, and am having trouble with what I believe should be something very basic. When I run the command (p.9 in the paper): R> dynformula(emp~wage+capital,log=list(capital=FALSE,TRUE),lag=list(emp=2,c(2,3)),diff=list(FALSE,capital=TRUE)) I see: emp ~ wage +

Hello everyone, I am working with plm package and I have problem with random and within models, which are giving errors which says "empty model". However, the model is not empty. In the source code for plm.fit, where the error originates it says something like (writing from the top of my head...) X <- model.matrix(formula,data, lhs=1,...) if (ncol(X) == 0) stop("empty

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 all, I've just migrated from STATA to R for runing panel regressions and I was very happy to discover the plm package. However, I have a problem when trying to access the "Total Sum of Squares" and "Residual Sum of Squares" on this output: > summary(output) Oneway (individual) effect Within Model Call: plm(formula = Y ~ X1 + X2, data = db, model =

Hello list, I'm following the paper (http://www.jstatsoft.org/v27/i02/paper) on how to use "plm" to run panel regressions, and am having trouble with what I believe should be something very basic. When I run the command (p.9 in the paper): R> dynformula(emp~wage+capital,log=list(capital=FALSE,TRUE),lag=list(emp=2,c(2,3)),diff=list(FALSE,capital=TRUE)) I see: emp ~ wage +

Hello, I am using {plm} to estimate panel models. I want to estimate a model that includes fixed effects for time and individual, but has a random individual effect for the coefficient on the independent variable. That is, I would like to estimate the model: Y_it = a_i + a_t + B_i * X_it + e_it Where i denotes individuals, t denotes time, X is my independent variable, and B (beta) is the

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

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

Dear R users, I am using plm packege in R to build my model, but from the result I can't quite figure out what it is... Can anyone tell me why? Am I missing something? R Results: *> ar1<-plm(formula=ADOP~lag(ADOP,1)+PE+WOR, + data=well, effect="time",model="within") > summary(ar1)* Oneway (time) effect Within Model Call: plm(formula = ADOP ~ lag(ADOP, 1) + PE

Hello, although I searched for a solution related to my problem I didn?t find one, yet. My skills in R aren?t very large, however. For my Diploma thesis I need to run a GMM estimation on a dynamic panel model using the "pgmm" - function in the plm-Package. The model I want to estimate is: "Y(t) = Y(t-1) + X1(t) + X2(t) + X3(t)" . There are no "normal" instruments

In the course of some work I have been doing for Revolution Analytics I have had the necessity of modifying the plm function so that it would not die halfway through fitting. In particular, I was able to more than halve the runtime (for my particular run) and improve its memory usage with three small modifications: 1.) Replacing throughout apply(X, 2, mean) with colMeans, similarly with

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