How to interprete the results of quantile regression panel data models of R

Question

How to interprete the results of panel data models of R? I estimate a adapted form of Koenker's (2004) suggestion for a quantile regression approach with panel data, for my data:

   rq.fit.panel <- function(X,Y,s,w,taus,lambda)

   {
require(SparseM)
    require(quantreg)

 K <- length(w)
if(K != length(taus))
stop("length of w and taus must match")
 X <- as.matrix(X)
     p <- ncol(X)
     n <- length(levels(as.factor(s)))
     N <- length(y)
if(N != length(s) || N != nrow(X))
stop("dimensions of y,X,s must match")
     Z <- as.matrix.csr(model.matrix(~as.factor(s)-1))
     Fidelity <- cbind(as(w,"matrix.diag.csr") %x% X,w %x% Z)
     Penalty <- cbind(as.matrix.csr(0,n,K*p),lambda*as(n,"matrix.diag.csr"))
     D <- rbind(Fidelity,Penalty)
     y <- c(w %x% y,rep(0,n))
 a <- c((w*(1-taus)) %x% (t(X)%*%rep(1,N)),
 sum(w*(1-taus)) * (t(Z) %*% rep(1,N)) + lambda * rep(1,n))
 rq.fit.sfn(D,y,rhs=a)

}enter code here

 bdeduc2<-read.table("dados_rq.txt", header=T) 
 z<-c("inter","ne","no","su","co")
 X<-bdeduc2[,z]
 y<-bdeduc2$scoreedu
 s<-bdeduc2$uf
 w<-c(0.1,0.25,0.5,0.25,0.1)
taus<-c(0.1,0.25,0.5,0.75,0.9)
lambda<-1

But I don't know identify the results below:

$coef
 [1]  1.02281339 -0.18750668 -0.13688807 -0.04180458 -0.01367417  1.02872440 -0.18055062 -0.13003224 -0.03829135 -0.01409369  1.03377335 -0.16649845 -0.11669812
[14] -0.03854060 -0.01438620  1.03851101 -0.15328087 -0.10440359 -0.03871744 -0.01465492  1.04330584 -0.14660960 -0.09670756 -0.03465501 -0.01430647 -0.29187982
[27] -0.21831160 -0.11295134 -0.21530494 -0.15664777 -0.13840296 -0.03224749 -0.11692122 -0.11237144 -0.15112171 -0.10385352 -0.08385934 -0.16090525 -0.30349309
[40] -0.16121494 -0.03106264 -0.16299994 -0.03182579 -0.22271685 -0.08251486 -0.29031224 -0.19680023 -0.20004209 -0.05601186 -0.21140762 -0.04254752 -0.01864703

$ierr
[1] 0

$it
[1] 16

$time
[1] 0

##summary rq

 summary(rq)

     Length Class  Mode   
coef 52     -none- numeric
ierr  1     -none- numeric
it    1     -none- numeric
time  1     -none- numeric

Answer 1

It looks like you fit the regression and saved it, then are trying to look at it in a new session without the quantile regression package loaded (it is giving you the list summary, not the object summary that is in the package).

Make sure that the package used to create your object is loaded, then do summary again to see if that gives you meaningful output.