Table 3. Parameter estimates, standard error estimates, and statistical significance of parameters of normal
and non-normal error regression models for corn and soybean prices.
_____OLS |
______AR(1)_____ |
SUR-AR(I) |
NSUR-AR(I) |
NNSUR-AR(I) | |||||
Par. Est. |
S.E. Est. |
Par. Est. |
S.E. Est. |
Par. Est. |
S.E. Est. Par. Est. |
S.E. Est. Par. Est. S.E. Est. | |||
θc |
— |
— |
— |
— |
— |
— |
— |
— |
0.9446 0.2875** |
μ c |
— |
— |
— |
— |
— |
— |
— |
— |
— — |
Bco |
3.0840 |
0.1423** |
3.0860 |
0.2263** |
3.0817** |
0.2273 |
3.1351 |
0.1600** |
3.1722 0.1065** |
Bc1 |
-1.5611 |
1.3432ns |
-1.4552 |
2.1317ns |
-1.4237ns |
2.1879 |
-2.1217 |
0.5563** |
-2.3509 0.3929** |
Bc2 |
-1.0001 |
2.6509ns |
-1.3787 |
4.1937ns |
-1.4244ns |
4.3186 |
— |
— |
— — |
σc |
0.3490 |
— |
0.2811 |
— |
0.2818** |
0.0282 |
0.2821 |
0.0282** |
0.2990 0.0804** |
pc |
— |
— |
0.5460 |
0.1185** |
0.5347** |
0.1111 |
0.5353 |
0.1112** |
0.5688 0.0987** |
θs |
— |
— |
— |
— |
— |
— |
— |
— |
0.5677 0.1600** |
μ s |
— |
— |
— |
— |
— |
— |
— |
— |
15.7161 5.0376** |
Bso |
5.2544 |
0.3246** |
5.3045 |
0.4998** |
5.2899 |
0.4291** |
5.3262 |
0.4172** |
5.3607 0.3347** |
Bs1 |
11.8443 |
3.0636** |
11.5373 |
4.7101** |
11.6223 |
4.0533** |
11.1429 |
3.8273** |
10.1967 2.8094** |
Bs2 |
-25.4146 |
6.0462** |
-25.0758 |
9.2701** |
-25.1588 7.9850** |
-24.1720 |
7.4968** |
-21.4259 5.3032** | |
σs__ |
0.7960 |
— |
0.6587 |
— |
0.6645 |
0.0677** |
0.6645 |
0.0677** |
0.7369 0.1603** |
ps__ |
— |
— |
0.5132 |
0.1214** |
0.4066 0.1227** |
0.4073 |
0.1232** |
0.4484 0.0763** | |
pcs |
— |
— |
— |
— |
0.3598 0.1310** |
0.3597 |
0.1311** |
0.4644 0.1158** | |
MVCLF |
33.86 |
MVCLF |
36.98 ] |
MVCLF |
36.92 |
MVCLF 52.54 | |||
R2 |
R2c=0.44 |
R2s=0.28 |
R2c=0.61 R2s=0.48 |
R2c=0.61 R2s=0.47 R2c=0.61 R2s=0.47 |
R2c=0.61R2s=0.47 |
Notes: MVCLF stands for the maximum value reached by the concentrated log-likelihood function. Par.
Est. and S.E. Est. refer to the parameter and standard error estimates, respectively. The parameter and
standard error estimates corresponding to Bci and Bsi, and to Bc2 and Bs2 have been divided by 100 and
10000, respectively. * and ** denote statistical significance and the 90 and 95% level, respectively,
according to two-tailed t tests. The R2’s are calculated by dividing the regression sums of squares (based on
the autocorrelated {AR(1)} predictions) by the total sums of squares, i.e. it are the square of the correlation
coefficients between the AR(1) predictions and the observed corn (c) and soybean (s) prices.
26
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