similar to: Taking a lead in panel data

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, 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

> a <- data.frame(name=c(rep("a",5), rep("b",5)), year=c(1989:1993, 1989:1993), var=c(1:10)) > str(a) > b <- pdata.frame(a, index=c("name","year")) > str(b) Now, I want to convert b into a data frame and have a structure similar to a. How do I do that? -- Apoorva Gupta Consultant National Institute of Public Finance and Policy

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 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 R-user, a few weeks ago I consulted the list-serve with a similar question. However, my task changed a little but sufficiently to get lost again. So I would appreciate any help on the following issue. I use the plm package and work with firm-level data in a panel. I would like to eliminate all firms that do not fulfill the requirement of having an observation in every variable used for at

Hi everyone. I have two questions. I’ve found some other questions and answers similar to these but they didn’t solve my problem. I’m working with a panel of firm/years observations (see my reproducible example). I’m using the plm package. My panel not only is unbalanced but also have some gap’s in years. #reproducible example

Dear R users What would be the best way to approach estimating a panel regression with twoways random effects, on unbalanced data? Unfortunately, the "plm" package has no implementation of twoways random effects for unbalanced data. Currently I'm considering two approaches: - extend "plm" to cover this type of panel regression. (For the authors, cc'ed:) Would

Hello, I have a problem with Hausman test. I am performing my analysis with these commands: > library(plm) > data<-read.csv2("paolo.csv",header=TRUE) > data< pdata.frame(data,index=c("FIRM","YEAR"),drop.index=TRUE,row.names=TRUE) > RECEIV~LSIZE+LAGE+LAGE2+CFLOW+STLEV+FCOST+PGROWTH+NGROWTH+TURN+GPROF+GPROF2 >

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

Note the typo in your 3rd line: data < Don't know if this means anything... Bert On Feb 11, 2018 7:33 AM, "PAOLO PILI" <paolo.pili at student.unife.it> wrote: > Hello, > > I have a problem with Hausman test. I am performing my analysis with these > commands: > > > library(plm) > > data<-read.csv2("paolo.csv",header=TRUE) >

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

you are right about the 3rd line but it doesn't help me for my problem. I remove the 3rd line but there is still the same problem: Error in solve.default (dvcov): the system is numerically unique: reciprocity condition value = 1.63418e-19 Paolo 2018-02-11 16:54 GMT+01:00 Bert Gunter <bgunter.4567 at gmail.com>: > Note the typo in your 3rd line: data < > > Don't

Hi everyone and thank you for the help you could give me. My data is in a spreadsheet. The 1st column identifies the firm (with the fiscal number), the columns 2 to 11 have the variable value for 11 years. I have many variables (files like this). Each file has about 40.000 firms (rows). I transformed all the files in txt files. The data is a panel data, like this: firm revenu2007 revenue2006

Hello to all on the list, I'm trying to estimate a fixed effects model from a large (unbalanced) panel data set. I have no problems when using only an individual effect or only a time effect, but I get an error message when I try for a "twoways" effect. Here is some of the code: paneldata27 is the entire panel data set: > dim(paneldata27) [1] 1178831 8 >

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

Hi everyone, I’m working with a panel of firm/years observations. My panel not only is unbalanced but also have some gap’s in years. For example, firm 1 has 1999, 2000, 2001, 2004, 2005, firm 2 has 2000, 2001, 2003, 2005, and so on. I’m using the plm package and what I’m asking is how can I handle with this gap’s ? Thank you very much, Cecília Carmo Universidade de Aveiro

Dear R users, I have a question here library(AER) library(plm) library(sandwich) ## take the following data data("Gasoline", package="plm") Gasoline$f.year=as.factor(Gasoline$year) Now I run the following regression rhs <- "-1 + f.year + lincomep+lrpmg+lcarpcap" m1<- lm(as.formula(paste("lgaspcar ~", rhs)), data=Gasoline) ###Now I want to find the

Hello Everyone (Quick) question: Does anyone know a package/command or simply a way of creating a table of different panel data estimations (estimated using /*plm()*/ ) just as *mtable()* does for models estimated with /*lm()*/? It seems *mtable* (and *apsrtable* equally) only support /*lm*/ and some other classes but unfortunately not /*plm*/. I am pretty sure others must have encountered this

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,