Springer Texts in Business and Economics
Dependent Variable: LNEN
Analysis of Variance
|
Sum of |
Mean |
|||
|
Source |
DF |
Squares |
Square F Value Prob > F |
|
|
Model |
1 |
30.82384 |
30.82384 13.462 |
0.0018 |
|
Error |
18 |
41.21502 |
2.28972 |
|
|
C Total |
19 |
72.03886 |
||
|
Root MSE 1.51318 R-square 0.4279 DepMean 9.87616 Adj R-sq 0.3961 |
||||
|
C. V. |
15.32158 |
|||
|
Parameter Estimates |
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|
Parameter |
Standard T for HO: |
|||
|
Variable |
DF |
Estimate |
Error Parameter=0 |
Prob > |T| |
|
INTERCEP |
1 |
1.988607 |
2.17622656 0.914 |
0.3729 |
|
LNRGDP |
1 |
0.743950 |
0.20276460 3.669 |
0.0018 |
b. Plot of Residual *LNRGDP 2
 |
-I
<
-2
1/0
33
-4 -6
6 8 10 12 14
LNRGDP
As clear from this plot, the W. Germany observation has a large residual. c. For Ho; " = 1 we get t = (" - l)/s. e.(") = (0.744 - 1)/0.203 = -1.26. We do not reject Ho.
e. Dependent Variable: LNEN
|
Sum of |
Mean |
||||
|
Source |
DF |
Squares |
Square |
F Value |
Prob > F |
|
Model |
1 |
59.94798 |
59.94798 |
535.903 |
0.0001 |
|
Error |
18 |
2.01354 |
0.11186 |
||
|
C Total |
19 |
61.96153 |
|||
|
Root MSE 0.33446 R-square |
0.9675 |
||||
|
DepMean 10.22155 Adj R-sq |
0.9657 |
||||
|
C. V. |
3.27211 |
||||
|
Parameter Estimates |
|||||
|
Parameter |
Standard |
T for HO: |
|||
|
Variable |
DF |
Estimate |
Error |
3arameter= |
0 Prob > |T| |
|
INTERCEP |
1 |
-0.778287 |
0.48101294 |
-1.618 |
0.1230 |
|
LNRGDP |
1 |
1.037499 |
0.04481721 |
23.150 |
0.0001 |
|
Analysis of Variance |
|
Plot of Residual*LNRGDP |
-0.6 -0.8
SAS PROGRAM
Data Rawdata;
Input Country $ RGDP EN;
Cards;
Data Energy; Set Rawdata; LNRGDP=log(RGDP); LNEN=log(EN); Proc reg data=energy;
Model LNEN=LNRGDP;
Output out=OUT1 R=RESID;
Proc Plot data=OUT1 hpercent=85 vpercent=60; Plot RESID*LNRGDP=‘*’;
run;
