ESTIMATION OF EFFICIENT REGRESSION MODELS FOR APPLIED AGRICULTURAL ECONOMICS RESEARCH

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 σ	—	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 σ PDi	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.

More intriguing information

1. Estimating the Technology of Cognitive and Noncognitive Skill Formation
2. Momentum in Australian Stock Returns: An Update
3. CGE modelling of the resources boom in Indonesia and Australia using TERM
4. New urban settlements in Belarus: some trends and changes
5. Demographic Features, Beliefs And Socio-Psychological Impact Of Acne Vulgaris Among Its Sufferers In Two Towns In Nigeria
6. Co-ordinating European sectoral policies against the background of European Spatial Development
7. Stillbirth in a Tertiary Care Referral Hospital in North Bengal - A Review of Causes, Risk Factors and Prevention Strategies
8. THE WAEA -- WHICH NICHE IN THE PROFESSION?
9. The name is absent
10. Short Term Memory May Be the Depletion of the Readily Releasable Pool of Presynaptic Neurotransmitter Vesicles