[R] issues in plm using random effect model

[Kailas Gokhale]

Dear Sir,

Thank you for accepting my request for registration on this site.
I am trying to solve panel data problems using plm package , but while
suing random effect model i am getting following messege saying
"

Warning message:In sqrt(sigma2) : NaNs produced

"

In some other cases i am getting message saying where TSS = NA , that I am
not understanding
I am sending you my code along with out put.

Kindly help me .

I am sending you my code and output for your kind reference. data file is
also attached


rm(list=ls())
library(MASS)
library(bdsmatrix)
library(zoo)
library(nlme)
library(sandwich)
library(car)
library(lmtest)
library(plm)

data1<- read.csv(file.choose(),header=TRUE,sep=",")
D<-na.omit(data1)
attach(D)
Pdata<-plm.data(D, index=c("CT","T"))

pool11<- plm(Y~X1+X2,data = Pdata, model="pooling")
# pool21<- plm(Equity.dividend.1~ Profit.after.tax.1+ LaggedDivd.1+
log(Size.1)+factor(CompanyName)-1,data = Pdata, model="pooling")
fixed.mod1<- plm(Y~X1+X2,data = Pdata, model="within")
rand.mod1<- plm(Y~X1+X2,data = Pdata, model="random")


summary(pool11)
summary(fixed.mod1)
summary(fixef(fixed.mod1))
summary(rand.mod1)


##################output####################

Oneway (individual) effect Pooling Model

Call:
plm(formula = Y ~ X1 + X2, data = Pdata, model = "pooling")

Unbalanced Panel: n=6, T=4-6, N=34

Residuals :
   Min. 1st Qu.  Median 3rd Qu.    Max.
-19.400  -9.810  -0.648   8.490  23.900

Coefficients :
             Estimate Std. Error t-value  Pr(>|t|)
(Intercept) 25.229162   6.858418  3.6786 0.0008847 ***
X1           0.016438   0.046905  0.3504 0.7283744
X2          -2.231250   2.220346 -1.0049 0.3227198
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Total Sum of Squares:    5082
Residual Sum of Squares: 4892.7
R-Squared:      0.037241
Adj. R-Squared: 0.033955
F-statistic: 0.599566 on 2 and 31 DF, p-value: 0.55529>
summary(fixed.mod1)Oneway (individual) effect Within Model

Call:
plm(formula = Y ~ X1 + X2, data = Pdata, model = "within")

Unbalanced Panel: n=6, T=4-6, N=34

Residuals :
    Min.  1st Qu.   Median  3rd Qu.     Max.
-24.0000  -8.0400  -0.0795   6.6300  25.1000

Coefficients :
    Estimate Std. Error t-value Pr(>|t|)
X1  0.065306   0.060090  1.0868   0.2871
X2 -3.082215   2.514602 -1.2257   0.2313

Total Sum of Squares:    4791.9
Residual Sum of Squares: 4380.7
R-Squared:      0.085822
Adj. R-Squared: 0.065628
F-statistic: 1.22042 on 2 and 26 DF, p-value: 0.31146>
summary(fixef(fixed.mod1))  Estimate Std. Error t-value  Pr(>|t|)
A  33.2672    10.4360  3.1877 0.0014340 **
B  21.9300     9.2930  2.3598 0.0182831 *
C  27.6590     7.9522  3.4781 0.0005049 ***
D  21.9369     9.4271  2.3270 0.0199647 *
E  17.6243     8.6149  2.0458 0.0407766 *
F  23.8578     9.2198  2.5877 0.0096625 **
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1>
summary(rand.mod1)Oneway (individual) effect Random Effect Model
   (Swamy-Arora's transformation)

Call:
plm(formula = Y ~ X1 + X2, data = Pdata, model = "random")

Unbalanced Panel: n=6, T=4-6, N=34

Effects:
                 var std.dev  share
idiosyncratic 168.49   12.98  1.117
individual    -17.60      NA -0.117
theta  :
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
-0.6366 -0.6366 -0.6366 -0.5983 -0.6366 -0.3106

Residuals :
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
-21.000 -11.400   0.913   0.114   9.040  24.000

Coefficients :
              Estimate Std. Error t-value  Pr(>|t|)
(Intercept) 26.3963638  6.5706835  4.0173 0.0003482 ***
X1          -0.0066621  0.0433425 -0.1537 0.8788364
X2          -2.1087903  2.1533566 -0.9793 0.3350111
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Total Sum of Squares:    5548.4
Residual Sum of Squares: 5382.1
R-Squared:      0.037133
Adj. R-Squared: 0.033856
F-statistic: 0.479037 on 2 and 31 DF, p-value: 0.62389Warning
message:In sqrt(sigma2) : NaNs produced



with warm regards
kailas D. Gokhale