similar to: problem with the plm package (2)

Hi all, I have a problem in installing and using the plm package using R 2.2.0 on windows xp. I installed it from a .zip file downloaded from the CRAN. Apparently everything is ok: > utils:::menuInstallLocal() package 'plm' successfully unpacked and MD5 sums checked updating HTML package descriptions However, when I try to load it: > library(plm) Errore in lazyLoadDBfetch(key,

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 "plm"-Package insiders, [I posted the following observation is April already but unfortunately I am not aware of any answers. With the hope that someone found an answer in the mean time, I ask again:] I realized the following difficulty with the summary.plm function (demonstrated with the example from the ?plm documentation). library(plm) data("Produc",

Dear all- I am have trouble in using the model="ht" option in function plm from the plm library. I am using Package: plm Version: 1.1-1; R version 2.8.1 (2008-12-22) running on a FC-8 linux machine. Here is what I am trying to do: ##---------------------------------------------------------------------------- R> ###Prob 6 Chapter 3 Use R! Applied Econometrics with R (Kleiber

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 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,R 2.15.2 plm() function on Windows 7 when i perform a plm regression, i can't manage to obtain the intercept, but I need it.it gives me just the beta coefficient. my formula: fixed <- plm(deltaS ~ L1.deltaS + L2.deltaS, data=Mody_R, index=c("country_id", "date"), model="within") my output: Coefficients : Estimate Std. Error t-value Pr(>|t|)

Hi all, I a semi-beginner with R and I am working with the plm package to examine a longitudinal dataset. Each individual in this dataset has a longitudinal weight for the probability that he or she remains in the sample. Unfortunately, I have not found an argument to use weights in the plm function? I tried ?weights=? like in standard lm or in nlme or lm4 but it does not work. I asked the

Hi all I want to use plm function on splitted dataset but facing problems while doing it. I did the same for lm function it worked fine but now my problem forces me to use lags into it while in a single set I have multiple type of data, which I believe can only be done with panel data. The code I am using is A = split(mydata, mydata$Unique.ID.Number) Z = lapply(A, function(df){plm(Total.Sales

When using the PLM package (version 1.2-8), I encounter the probem that calling the FGLS estimator evokes strange behavior, when choosing the "random" effects model. After calling the PGGLS function to estimate FGLS, PLM gives me a warning, stating that the "random" model has been replaced with the "pooling" model. I would, however, really like to estimate the random

Hello, I am trying to run a fixed effects panel regression on data containing 5 columns and 1,494 rows. I read the data in as follows: >drugsXX<-read.csv(file="C:\\Folder\\vX.X\\Drugs\\drugsXX_panel.csv", head=TRUE, sep=",") Verified it read in correctly and had a good data.frame: >dim(drugsXX) [1] 1494 5 >drugs XX produce expected data with correct column

Hello, I am trying to use Sweave to write up a report, and I have used the plm package to do some panel models. I am trying to use xtable to make a nice table for my regression objects (returned by the plm command), but I am getting the error: Error in UseMethod("xtable") : no applicable method for "xtable" It seems like I would want to have xtable treat plm objects exactly

hi, i am writing my master thesis and i am dealing with 146474 observations (panel data), i have just learned the R so i am a beginner!! i am trying to use the "plm" package and i have a duplication problem; i have written the following commands to read my data and create my model >dsn<-plm.data(ds, c("stno", "year")) ds=name of my data, stno=individual

Hello, Apologies in advance if this is a stupid question. I am running R on Ubuntu 9. R version 2.9.2 (2009-08-24) I am trying to work with plm. I think the library is installed, as I can do > library(plm) Loading required package: kinship Loading required package: survival Loading required package: splines Loading required package: nlme Loading required package: lattice [1] "kinship

Dear Sir/ Madam, I am writing about the panel data for my bachelor degree. I would really appreciate if You could help dealing with R functions. I am trying to estimate the panel data lm model with plm function. When i include 3dummy variables into the regression it dont appear in the sumarry of the model, but when i estimate a simple lm model it appears. Why is it so? What should i do to

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 +

Hi R-helpers, I want to determine the coefficients of the following regression for several subsets, and I want to save it in a dataframe: The data is in ?regaccdis?, ?regaccdis$caedois? is the column that defines the subsets and the function I have runned is coef(plm(ff,data=regaccdis,na.action=na.omit,model="pooling",subset=(regaccdis$caedois==i))) I?ve created a dataframe named

hey guys I have a panel data set that i want to perform some regressions on. I am using the /plm/ package. I defined a model in the following way: PWBw.pool <- plm(*PWB* ~ log(*I_EQON*) + log(*RD*) + ... + *PAGRI*, data = pfem, na.action=na.exclude, model="pooling") When i run this it gives the following error (the error remains when i use other model = "" specifications

Hi! I noticed that there is a (minor) bug either the command all.equal() or in the "plm" package. I demonstrate this using an example taken from the documentation of plm(): ====================================== R> data("Produc", package="plm") R> zz <- plm(log(gsp)~log(pcap)+log(pc)+log(emp)+unemp, + data=Produc,