Table 5. Parameter estimates, standard error estimates, and statistical significance of parameters of normal and
non-normal error regression models for the West Texas cotton basis.
__________________NHAR(4) |
NNHAR(4) |
FNHAR(4) |
FNNHAR(4) | ||||||
Par. |
Var. |
P.E. |
S.E. |
P.E. |
S.E. |
P.E. |
S.E. |
P.E. |
S.E. |
pi |
— |
0.9807 |
0.0687i |
0.9626i |
0.02720i |
0.98904 |
0.06593i |
0.95853 |
0.02773i |
p2 |
— |
-0.2385 |
0.09652 |
-0.i3640 |
0.04i90i |
-0.24666 |
0.09358i |
-0.i3685 |
0.04244i |
-- p3 |
— |
0.i3i9 |
0.0975 |
0.i34i8 |
0.045i8i |
0.i3667 |
0.09606 |
0.i3438 |
0.04602i |
—--- p4 |
— |
-0.i073 |
0.06i23 |
-0.i5764 |
0.03732i |
-0.ii249 |
0.060i73 |
-0.i5605 |
0.03682i |
-- _B0___ |
— |
-i4.5204 |
i2.2673 |
-i3.7478 |
8.60659 |
-i8.26522 |
7.848872 |
-ii.83432 |
6.663783 |
_B__ |
TXP |
0.i930 |
0.5i59 |
-0.ii620 |
0.i3i43 |
0.i8625 |
0.46566 |
-0.i2095 |
0.i2967 |
_B__ |
USP |
0.3022 |
0.2476 |
0.3i76i |
0.i43032 |
0.330ii |
0.23807 |
0.34039 |
0.08453i |
Вз____ |
FP |
0.09i3 |
0.i452 |
0.23745 |
0.08869i |
0.i020i |
0.i3689 |
0.24439 |
0.06782i |
-B__ |
TXBS |
-0.3323 |
0.3043 |
-0.477i5 |
0.258i53 |
-0.32229 |
0.29i86 |
-0.48446 |
0.245362 |
_B__ |
USBS |
0.i800 |
0.3508 |
0.52388 |
0.i6576i |
0.i8375 |
0.343i7 |
0.55098 |
0.i559ii |
_Вб___ |
FBS |
0.0i62 |
0.i053 |
0.i6266 |
0.068242 |
0.03877 |
0.i05i5 |
0.i7332 |
0.04436i |
_B7___ |
FMU |
-0.036i |
0.3599 |
-0.26306 |
0.ii3202 |
0.0226i |
0.i73i4 |
-0.26656 |
0.i0223i |
_B__ |
RRI |
0.0i46 |
0.i479 |
0.03i85 |
0.08302 |
— |
— | ||
_B__ |
STRC |
-i.4566 |
i.2934 |
-i.i5475 |
i.26i64 |
-i.35748 |
i.252i4 |
-i.i3765 |
i.23339 |
Bio |
FDPR |
i.0527 |
0.6739 |
0.43i63 |
0.47683 |
i.03744 |
0.67i4i |
0.35747 |
0.38805 |
Bii |
SD |
-i.099i |
0.4225i |
-0.69499 |
0.23655i |
-i.06572 |
0.4i4i02 |
-0.636i5 |
0.i8ii5i |
Bi2 |
PDi |
2.i954 |
2.36i4 |
i.85i66 |
i.84490 |
i.29i06 |
i.i5962 |
2.38576 |
i.ii5272 |
Bi3 |
PD2 |
i.i976 |
2.6599 |
-0.85989 |
2.30983 |
— |
— | ||
2 |
— |
i6.0036 |
2.8967i |
ii.35527 |
4.i3477i |
i6.i3068 |
3.00359i |
i0.95924 |
3.63400i |
2 σ SD |
SD |
-ii.3i79 |
2.8i22i |
-5.82i20 |
3.8776i |
-ii.505i8 |
2.778i5i |
-5.42047 |
3.343203 |
2 |
PDi |
-0.39i9 |
i.3692 |
-i.76i88 |
i.42804 |
-0.38268 |
i.54083 |
-i.80659 |
i.40307 |
2 σ PD2 |
PD2 |
-3.4360 |
i.0000i |
-3.9i090 |
i.35i65i |
-3.35245 |
i.02i57i |
-3.89927 |
i.3395ii |
-Θ__ |
— |
— |
— |
0.95789 |
0.225i4i |
— |
— |
0.93976 |
0.20077i |
μ. |
— |
— |
— |
0.69869 |
0.250i7i |
— |
— |
0.72557 |
0.26i77i |
—--- ΘSD |
SD |
— |
— |
-i.2i066 |
0.308iii |
— |
— |
-i.i9269 |
0.29i55i |
Θpdi |
PDi |
— |
— |
0.02i53 |
0.i9ii6 |
— |
— | ||
ΘpD2_ |
PD2 |
— |
— |
0.576i8 |
0.i9320i |
— |
— |
0.57207 |
0.i7i90i |
MVLLF |
-352.820 |
-282.353 |
-352.964 |
-282.448 | |||||
R2 |
0.77 |
0.77 |
0.77 |
0.77 |
Notes: NHAR(4), NNHAR(4), FNHAR(4) and FNNHAR(4) refer to the initial normal and non-normal and to the
final normal and non-normal heteroskedastic fourth-order autoregressive models; the parameters (Par.) and
variables (Var.) are as defined in the text; P.E. and S.E. refers to the parameter and standard error estimates; 1, 2,
and 3 denote statistical significance at the 1%, 5% and 10% level, respectively, according to two-tailed t-tests;
MVLLF refers to the maximum value reached by the model’s concentrated log-likelihood function; and the R2 is
calculated by dividing the regression sum of squares (based on the autocorrelated {AR(4)} predictions) by the
total sum of squares, i.e. it is the square of the correlation coefficient between the AR(4) predictions and the
observed basis values.
28
More intriguing information
1. Industrial Cores and Peripheries in Brazil2. The name is absent
3. MANAGEMENT PRACTICES ON VIRGINIA DAIRY FARMS
4. How Offshoring Can Affect the Industries’ Skill Composition
5. Dual Track Reforms: With and Without Losers
6. Has Competition in the Japanese Banking Sector Improved?
7. International Financial Integration*
8. The Global Dimension to Fiscal Sustainability
9. The name is absent
10. The name is absent