similar to: Attribute Length Error when Trying plm Regression

Hello, I am trying to conduct a Hausman test to choose between FE estimators and RE estimators. When I try to run: library(plm) fixed <- plm(ROS ~ DiffClosenessC +ZZiele + AggSK + nRedundantStrecken + Degree + KantenGew + BetweennessC + SitzKappazitaet, data=Panel,index=c("id","time"),model="within") summary(fixed) fixef(fixed) random <-plm(ROS ~

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,

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

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",

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(),

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

Dear R-helpers, I have a very simple question and I really hope that someone could help me I would like to estimate a simple fixed effect regression model with clustered standard errors by individuals. For those using Stata, the counterpart would be xtreg with the "fe" option, or areg with the "absorb" option and in both case the clustering is achieved with "vce(cluster

Hi there, Maybe people who know both R and econometrics will be able to answer my questions. I want to run panel regressions in R with fixed-effect. I know two ways to do it. First, I can include factor(grouping_variable) in my regression equation. Second, I plan to subtract group mean from my variables and run OLS panel regression with function lm(). I plan to do it with the second way because

Hi, I am trying to run a panel regression using 88 observations and 9 variables. In-built Hausman Test did not work, then I found a code for auxiliary regression method for the Hausman test. The panel models are: fe=plm(gd ~ l+g+o+c+g1+h+n+r, model = "within", data = new.frame,index = c("id")) re=plm(gd ~ l+g+o+c+g1+h+n+r, model = "random", data = new.frame,index =

I have met into this problem when I tried to run panel regression by plm. My code: library(plm) indus <- read.csv(file="full.csv",header=TRUE) industry<-as.data.frame(indus) reg<-lm(LnTSO2 ~ LnPGDP + LnPGDP2 + LnSOES + LnCOES + LnLIMD + LnSHOLD + LnPRIV + LnFIEs + LnEXP + LnIMP + LnLEXRE + LnVALTAX + LnIND1 + LnIND2 + LnIND3 + LnIND4 + LnIND5 + LnIND6 + LnIND7 +

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, How could I see the source code of functions in an R package? If we type ?function_name , we will see documentations of the function_name. If we type function_name, is what returns just the source code? Could we just save it in an .R file and modify as we want? However, it seems that sometimes the source code is hidden (or stored elsewhere?) As an example, could we see the source

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

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)

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:

dear readers---I struggled with how to do nice fixed-effects regressions in large economic samples for a while. Eventually, I realized that nlme is not really what I needed (too complex), and all I really wanted is the plm package. so, I thought I would share a quick example. ################ sample code to show fixed-effects models? in R # create a sample panel data set with firms and years

Hello again Max. A correction to my response from yesterday. Things were better than they seemed. I thought it over, checked Arellano's panel book and Driscoll and Kraay (Rev. Econ. Stud. 1998) and finally realized that vcovSCC does what you want: in fact, despite being born primarily for dealing with cross-sectional correlation, 'SCC' standard errors are robust to "both