Dear friends,
I have written the following lines in R console wich already exist in pdf
file systemfit:
data( "GrunfeldGreene" )
library( "plm" )
GGPanel <- plm.data( GrunfeldGreene, c( "firm", "year" ) )
greeneSur <- systemfit( invest ~ value + capital, method = "SUR",
+ data = GGPanel )
greenSur
I have obtained the following incomplete results in wich standard errors of
the estimates and their student statistics didn't appear:
systemfit results
method: SUR
Coefficients:
Chrysler_(Intercept) Chrysler_value
Chrysler_capital General.Electric_(Intercept)
0.5043036
0.0695456 0.3085445 -22.4389132
General.Electric_value General.Electric_capital
General.Motors_(Intercept) General.Motors_value
0.0372914 0.1307830
-162.3641052 0.1204930
General.Motors_capital US.Steel_(Intercept)
US.Steel_value US.Steel_capital
0.3827462
85.4232548 0.1014782 0.3999914
Westinghouse_(Intercept) Westinghouse_value
Westinghouse_capital
1.0888770
0.0570091 0.0415065
but when I wrote the following lines:
summary(greeneSur)
I obtained the following results:
systemfit results
method: SUR
N DF SSR detRCov OLS-R2 McElroy-R2
system 100 85 347048 1.39234e+14 0.844042 0.868682
N DF SSR MSE RMSE R2 Adj R2
Chrysler 20 17 3056.98 179.823 13.4098 0.911862 0.901493
General.Electric 20 17 14009.12 824.066 28.7065 0.687636 0.650887
General.Motors 20 17 144320.88 8489.463 92.1383 0.920742 0.911417
US.Steel 20 17 183763.01 10809.589 103.9692 0.421959 0.353954
Westinghouse 20 17 1898.25 111.662 10.5670 0.726429 0.694244
The covariance matrix of the residuals used for estimation
Chrysler General.Electric General.Motors US.Steel
Westinghouse
Chrysler 176.3203 -25.1478 -332.655 491.857
15.6552
General.Electric -25.1478 777.4463 714.745 1064.649
207.5871
General.Motors -332.6546 714.7449 8423.875 -2614.188
148.4426
US.Steel 491.8572 1064.6491 -2614.188 10466.371
642.5712
Westinghouse 15.6552 207.5871 148.443 642.571
104.3079
The covariance matrix of the residuals
Chrysler General.Electric General.Motors US.Steel
Westinghouse
Chrysler 179.82262 2.40867 -369.063 535.399
19.6007
General.Electric 2.40867 824.06559 712.161 1440.477
235.6662
General.Motors -369.06303 712.16059 8489.463 -3160.609
152.8077
US.Steel 535.39937 1440.47700 -3160.609 10809.589
767.9016
Westinghouse 19.60073 235.66620 152.808 767.902
111.6617
The correlations of the residuals
Chrysler General.Electric General.Motors US.Steel
Westinghouse
Chrysler 1.00000000 0.00625711 -0.298702 0.384018
0.138324
General.Electric 0.00625711 1.00000000 0.269251 0.482637
0.776898
General.Motors -0.29870209 0.26925075 1.000000 -0.329933
0.156947
US.Steel 0.38401758 0.48263726 -0.329933 1.000000
0.698954
Westinghouse 0.13832413 0.77689848 0.156947 0.698954
1.000000
SUR estimates for 'Chrysler' (equation 1)
Model Formula: Chrysler_invest ~ Chrysler_value + Chrysler_capital
<environment: 0x03ae6cbc>
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.5043036 12.4874164 0.04038 0.968257
value 0.0695456 0.0183279 3.79452 0.001448 **
capital 0.3085445 0.0280530 10.99864 3.7702e-09 ***
---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
Residual standard error: 13.409796 on 17 degrees of freedom
Number of observations: 20 Degrees of Freedom: 17
SSR: 3056.984521 MSE: 179.822619 Root MSE: 13.409796
Multiple R-Squared: 0.911862 Adjusted R-Squared: 0.901493
SUR estimates for 'General.Electric' (equation 2)
Model Formula: General.Electric_invest ~ General.Electric_value +
General.Electric_capital
<environment: 0x03ae6cbc>
Estimate Std. Error t value Pr(>|t|)
(Intercept) -22.4389132 27.6787930 -0.81069 0.428748
value 0.0372914 0.0133012 2.80360 0.012212 *
capital 0.1307830 0.0239163 5.46836 4.1636e-05 ***
---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
Residual standard error: 28.706543 on 17 degrees of freedom
Number of observations: 20 Degrees of Freedom: 17
SSR: 14009.115084 MSE: 824.065593 Root MSE: 28.706543
Multiple R-Squared: 0.687636 Adjusted R-Squared: 0.650887
SUR estimates for 'General.Motors' (equation 3)
Model Formula: General.Motors_invest ~ General.Motors_value +
General.Motors_capital
<environment: 0x03ae6cbc>
Estimate Std. Error t value Pr(>|t|)
(Intercept) -162.3641052 97.0321612 -1.67330 0.11257
value 0.1204930 0.0234601 5.13609 8.2508e-05 ***
capital 0.3827462 0.0355419 10.76887 5.1724e-09 ***
---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
Residual standard error: 92.138284 on 17 degrees of freedom
Number of observations: 20 Degrees of Freedom: 17
SSR: 144320.876426 MSE: 8489.463319 Root MSE: 92.138284
Multiple R-Squared: 0.920742 Adjusted R-Squared: 0.911417
SUR estimates for 'US.Steel' (equation 4)
Model Formula: US.Steel_invest ~ US.Steel_value + US.Steel_capital
<environment: 0x03ae6cbc>
Estimate Std. Error t value Pr(>|t|)
(Intercept) 85.4232548 121.3481013 0.70395 0.490993
value 0.1014782 0.0594213 1.70778 0.105873
capital 0.3999914 0.1386127 2.88568 0.010269 *
---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
Residual standard error: 103.969173 on 17 degrees of freedom
Number of observations: 20 Degrees of Freedom: 17
SSR: 183763.011429 MSE: 10809.588908 Root MSE: 103.969173
Multiple R-Squared: 0.421959 Adjusted R-Squared: 0.353954
SUR estimates for 'Westinghouse' (equation 5)
Model Formula: Westinghouse_invest ~ Westinghouse_value +
Westinghouse_capital
<environment: 0x03ae6cbc>
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.0888770 6.7886266 0.16040 0.87445869
value 0.0570091 0.0123241 4.62583 0.00024141 ***
capital 0.0415065 0.0446894 0.92878 0.36600569
---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
Residual standard error: 10.56701 on 17 degrees of freedom
Number of observations: 20 Degrees of Freedom: 17
SSR: 1898.249072 MSE: 111.66171 Root MSE: 10.56701
Multiple R-Squared: 0.726429 Adjusted R-Squared: 0.694244
The problem the standard errors and tvalues appear only in the six
individual equations which are not deduced from panel data estimation.
Many thanks in advance
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