Dear R community,and especially Giovanni Millo,

 

For my master's thesis i need to simulate a panel data with the fixed
effects correlated with the predicor, so i run the 

the following code:

 

 

set.seed(1970)

#######################Panel data simulation with alphai correlated with
xi#####################################

n <- 5

t <- 4 

nt <- n*t

pData <- data.frame(id = rep(paste("JohnDoe", 1:n, sep = "_"), each =
t),time = rep(1981:1984, n))

 

rho <-0.95

alphai <- rnorm(n,mean=0,sd=1)#alphai simulation

x<- as.matrix(rnorm(nt,1))#xi simulation

akro <- kronecker(alphai ,matrix(1,t,1))#kronecker of alphai            


cormat<-matrix(c(1,rho,rho,1),nrow=2,ncol=2)#correlation matrix

cormat.chold <- chol(cormat)#choleski transformation of correlation
matrix                                                                  


akrox <- cbind(akro,x)                                                  


ax <- akrox%*%cormat.chold                                              


ai <- as.matrix(ax[,1]) 

pData$alphai<-as.vector(ai)                                             


xcorr <- as.matrix(ax[,2:(1+ncol(x))])

pData$xcorrei<-as.vector(xcorr)

pData$yi <- 5 + pData$alphai + 5* pData$xcorrei + rnorm(nt)

##########################panel data
frame##################################

library(plm)

pData <- pdata.frame(pData, c("id", "time"))

pData

 

I think the panel is correctly generated, but my doubt is about the
simulation of the correlated variables:

 

alphai <- rnorm(n,mean=0,sd=1)#alphai simulation

x<- as.matrix(rnorm(nt,1))#xi simulation

akro <- kronecker(alphai ,matrix(1,t,1))#kronecker of alphai            


cormat<-matrix(c(1,rho,rho,1),nrow=2,ncol=2)#correlation matrix

cormat.chold <- chol(cormat)#choleski transformation of correlation
matrix                                                                  


akrox <- cbind(akro,x)                                                  


ax <- akrox%*%cormat.chold                                              


ai <- as.matrix(ax[,1]) 

pData$alphai<-as.vector(ai)                                             


xcorr <- as.matrix(ax[,2:(1+ncol(x))])

This method is correct or is there a better way to do this?

 

Must generate a variable xi correlated with the alphai, for various
values of rho:

For example rho=(0,0.5,0.6,0.8,0.95,0.99)

how do I simulate the xi associated with each value of rho and put in
the data frame at once?

tried various ways without success.

Please give your opinion and suggestions to improve my simulation. Tank
you,

best regards

 

 

                               Carlos Brás



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