similar to: PLM package PGGLS strange behavior

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

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 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

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 +

I am working with panel data. I am using the plm package to do this. I would like to do be able to adjust for autocorrelation, as one does with glm models and correlation structures (eg corr=corARMA(q=4)) . In particular, I want to employ MA(4) error structure. Is there a way of doing this with the plm package? (Note: I do not really want to use the pggls function for various

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, my data set is data.frame(id, yr, y, l, e, k). I would like to estimate Lee and Schmidts (1993, OUP) model in R. My colleague wrote SAS code as follows: ** procedures for creating dummy variables are omitted ** ** di# and dt# are dummy variables for industry and time ** data a2; merge a1 a2 a; by id yr; proc sysnlin maxit=100 outest=beta2; endogenous y; exogenous l e k

Hello, I have estimated the coefficients for my model using the 'pggls' function from the 'plm' package. Now I want to see the relative influence of those X's. How can some please tell me how to standardize those my results in R? Thank you! -- View this message in context: http://r.789695.n4.nabble.com/Standardize-GLS-coefficients-in-R-tp4671371.html Sent from the R help

Dear R Experts--- Sorry for all the questions yesterday and today. I am trying to use Yves Croissant's pgmm function in the plm package with Blundell-Bond moments. I have read the Blundell-Bond paper, and want to run the simplest model first, d[i,t] = a*d[i,t-1] + fixed[i] + u[i,t] . no third conditioning variables yet. the full set of moment conditions recommended for system-GMM,

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:

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

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

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 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

Thanks a lot for the quick answerd I received and that helped me to solve my first (simple) problem with the plm package. Unfortunatley, here's another one: I do not know why, but I'm unable to estimate a simple model in the form y ~ 1 + x When I try > zz <- plm(y ~ 1 + x , data=mydata) I obtain Errore in X.m[, coef.within, drop = F] : numero di dimensioni errato which means