Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.E.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
belt[t]	-395.811146	38.605577	-10.252693	0	0
Constant	2165.226393	43.631881	49.624869	0	0
M1[t]	-442.550697	61.373686	-7.210756	0	0
M2[t]	-617.8125	61.326238	-10.074195	0	0
M3[t]	-567.25	61.326238	-9.249711	0	0
M4[t]	-680.4375	61.326238	-11.095373	0	0
M5[t]	-543.125	61.326238	-8.856323	0	0
M6[t]	-598.875	61.326238	-9.765396	0	0
M7[t]	-523.25	61.326238	-8.532237	0	0
M8[t]	-508.375	61.326238	-8.289682	0	0
M9[t]	-455.5625	61.326238	-7.428509	0	0
M10[t]	-316.1875	61.326238	-5.155827	1E-06	0
M11[t]	-116.625	61.326238	-1.901715	0.058815	0.029407
Variable	Elasticity	S.E.*	T-STAT H0: |elast| = 1	2-tail p-value	1-tail p-value
%belt[t]	-0.028387	0.002769	-350.924004	0	0
%Constant	1.296304	0.026122	11.343061	0	0
%M1[t]	-0.022079	0.003062	-319.373631	0	0
%M2[t]	-0.030823	0.00306	-316.762868	0	0
%M3[t]	-0.028301	0.00306	-317.587352	0	0
%M4[t]	-0.033948	0.00306	-315.74169	0	0
%M5[t]	-0.027097	0.00306	-317.98074	0	0
%M6[t]	-0.029878	0.00306	-317.071668	0	0
%M7[t]	-0.026105	0.00306	-318.304826	0	0
%M8[t]	-0.025363	0.00306	-318.547382	0	0
%M9[t]	-0.022728	0.00306	-319.408555	0	0
%M10[t]	-0.015775	0.00306	-321.681236	0	0
%M11[t]	-0.005819	0.00306	-324.935349	0	0
Variable	Stand. Coeff.	S.E.*	T-STAT H0: coeff = 0	2-tail p-value	1-tail p-value
S-belt[t]	-0.444952	0.043399	-10.252693	0	0
S-Constant	0	0	0	1	0.5
S-M1[t]	-0.423445	0.058724	-7.210756	0	0
S-M2[t]	-0.591141	0.058679	-10.074195	0	0
S-M3[t]	-0.542761	0.058679	-9.249711	0	0
S-M4[t]	-0.651062	0.058679	-11.095373	0	0
S-M5[t]	-0.519677	0.058679	-8.856323	0	0
S-M6[t]	-0.573021	0.058679	-9.765396	0	0
S-M7[t]	-0.50066	0.058679	-8.532237	0	0
S-M8[t]	-0.486428	0.058679	-8.289682	0	0
S-M9[t]	-0.435895	0.058679	-7.428509	0	0
S-M10[t]	-0.302537	0.058679	-5.155827	1E-06	0
S-M11[t]	-0.11159	0.058679	-1.901715	0.058815	0.029407
*Note	computed against deterministic endogenous series
Variable	Partial Correlation
belt[t]	-0.608259
Constant	0.965525
M1[t]	-0.474438
M2[t]	-0.601523
M3[t]	-0.568681
M4[t]	-0.638354
M5[t]	-0.551976
M6[t]	-0.589559
M7[t]	-0.537695
M8[t]	-0.526694
M9[t]	-0.485427
M10[t]	-0.359588
M11[t]	-0.140726
Critical Values (alpha = 5%)
1-tail CV at 5%	1.65
2-tail CV at 5%	1.96

Multiple Linear Regression - Regression Statistics
Multiple R	0.814751
R-squared	0.66382
Adjusted R-squared	0.641282
F-TEST	29.454359
Observations	192
Degrees of Freedom	179
Multiple Linear Regression - Residual Statistics
Standard Error	173.456795
Sum Squared Errors	5385619.467492
Log Likelihood	-1255.643961
Durbin-Watson	0.707935
Von Neumann Ratio	0.711642
# e[t] > 0	84
# e[t] < 0	108
# Runs	45
Stand. Normal Runs Statistic	-7.424827

Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error	32124.417797
Akaike (1973) Log Information Criterion	10.377164
Akaike (1974) Information Criterion	32117.752459
Schwarz (1978) Log Criterion	10.597724
Schwarz (1978) Criterion	40043.585398
Craven-Wahba (1979) Generalized Cross Validation	32272.367834
Hannan-Quinn (1979) Criterion	35118.819699
Rice (1984) Criterion	32443.490768
Shibata (1981) Criterion	31848.552624

Multiple Linear Regression - Analysis of Variance
ANOVA	DF	Sum of Squares	Mean Square
Regression	12	10634411.402299	886200.950192
Residual	179	5385619.467492	30087.259595
Total	191	16020030.869792	83874.507171684
F-TEST	29.454359
p-value	0

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