Dear Kailas Gokhale,
The negative individual variance is not a problem with your code or plm.
It a property of your data. Please check the posts of Giovanni Millo on
this topic:
[R] R: plm random effect: the estimated variance of the individual
effect is negative
Millo Giovanni Giovanni_Millo at Generali.com
Sat Jan 5 10:10:01 CET 2013
You can find the posts in the archive by rseek.org.
Kind regards,
Nina Schönfelder
-----
FernUniversität in Hagen
Fakultät für Wirtschaftswissenschaft
Lehrstuhl für Volkswirtschaftslehre,
insbes. Makroökonomik
58084 Hagen
E-Mail: nina.schoenfel...@fernuni-hagen.de
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Am 06.06.2017 um 12:00 schrieb r-help-requ...@r-project.org:
Message: 1
Date: Mon, 5 Jun 2017 15:41:23 +0530
From: Kailas Gokhale<kls.gokh...@gmail.com>
To:r-help@r-project.org
Subject: [R] issues in plm using random effect model
Message-ID:
<CAMO91N4oCvTf1ZkHLqQ4t3SAbVw=vylm-6jkt49cpbw+kub...@mail.gmail.com>
Content-Type: text/plain; charset="UTF-8"
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
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