similar to: problem with "dynformula" from "plm" package

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 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

Dear Ivo, dear list, (see: Message: 70 Date: Thu, 26 Mar 2009 21:39:19 +0000 From: ivowel at gmail.com Subject: [R] pgmm (Blundell-Bond) sample needed) I think I finally figured out how to replicate your supersimple GMM example with pgmm() so as to get the very same results as Stata. Having no other regressors in the formula initially drove me crazy. This was a case where simpler models are

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 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 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 "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 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,

Hi all, I have estimated a random panel model using plm function. I have a question about the vector of resduals obtained with the object $residuals. example: data("Produc", package = "plm") zz <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, model="random", data = Produc, index = c("state","year")) res<-zz$residuals #

Hi all, what indicates the parameter theta in the summary of a random effect panel model estimated with the plm function? example: data("Produc", package = "plm") zz <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, model="random", data = Produc, index = c("state","year")) summary(zz) Effects: var std.dev

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

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,

In the rockchalk package, I want to provide functions for regression objects that are "well behaved." If an object responds to the methods that lm or glm objects can handle, like coef(), nobs(), and summary(), I want to be able to handle the same thing. It is more difficult than expected to ask a given fitted model object "do you respond to these functions: coef(), nobs(),

Dear all, I am trying to export my fixed effect results to Latex. I am using the plm package with the summary function. However, it does not look like apsrtable, stargazer, or any other package can accompany using the plm package. I am interested in a classic table with the coefficient in one row followed by the standard error in paranthesis in the next row and stars by the coefficient to show

Hi I generate a new dataframe by doing: npl.agg <- aggregate(npl$DensPlants, list(year=npl$year, sim=npl$sim), mean, na.rm=TRUE ) Now I want to plot it by using coplot(npl.agg$x ~ npl.agg$year | npl.agg$sim, type="l") but, as npl.agg$year is seen as a factor, the order of the points on the x-axis (time axis) does not follow the numerical sorting 1...100, but rather the text

Hi I have a table called npl containing results of simulations. It contains about 19000 entries and the structure looks like this: NoPlants sim run year DensPlants 1 6 lng_cs99_renosterbos 1 4 0.00192 . . . it has 43 different entries for sim and year goes from 1 to 100, and run from 1 to 5. I would like to calculate the mean of DensPlants for each

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 am using R 2.11.0 on a Ubuntu machine. I have a time series data set and want to run rolling regressions with it. Any suggestions would be useful. Here are the details: (1) I convert relevant variables into time series objects and compute first differences: vad <- ts(data$ALLGVA/data$GDPDEF, start=1948, frequency=1) emp <- ts(data$ALLEMP, start=1948, frequency=1) vad.dif1 <-

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

Hello all, I am trying to use the tapply function to sum some values and change the column names of the resulting vector. I input Emp Et 1 10565 ACC 2 7515 ADM 3 625 AGF 4 6243 CNS 5 12721 EDU 6 3924 FIN 7 18140 HLH 8 3686 INF 9 15841 MFG 10 243 MIN 11 1864 MNG 12 4664 OSV 13 5496 PRF 14 4988 PUB 15 2166 REC 16 2153 REL 17 16082 RTL 18 3582 TRN 19 757 UTL 20