Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.E.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
x[t]	-226.385034	41.037226	-5.516577	0	0
Constant	2325.828228	44.148716	52.681673	0	0
t^1	-1.764855	0.240551	-7.336707	0	0
M1[t]	-454.904684	53.95579	-8.431063	0	0
M2[t]	-635.461053	53.941479	-11.780564	0	0
M3[t]	-586.663409	53.952742	-10.873653	0	0
M4[t]	-694.556343	53.922166	-12.88072	0	0
M5[t]	-559.008698	53.931287	-10.365202	0	0
M6[t]	-609.464132	53.907141	-11.305814	0	0
M7[t]	-535.603987	53.914117	-9.934392	0	0
M8[t]	-515.434421	53.896405	-9.563429	0	0
M9[t]	-464.386777	53.901237	-8.615512	0	0
M10[t]	-319.717211	53.889963	-5.932778	0	0
M11[t]	-121.919566	53.892648	-2.262267	0.02489	0.012445
Variable	Elasticity	S.E.*	T-STAT H0: |elast| = 1	2-tail p-value	1-tail p-value
%x[t]	-0.016236	0.002943	-334.258695	0	0
%Constant	1.392455	0.026431	14.848018	0	0
%t^1	-0.101962	0.013898	-64.618317	0	0
%M1[t]	-0.022696	0.002692	-363.052471	0	0
%M2[t]	-0.031704	0.002691	-359.801524	0	0
%M3[t]	-0.029269	0.002692	-360.630868	0	0
%M4[t]	-0.034652	0.00269	-358.834454	0	0
%M5[t]	-0.02789	0.002691	-361.287108	0	0
%M6[t]	-0.030407	0.002689	-360.512969	0	0
%M7[t]	-0.026722	0.00269	-361.836276	0	0
%M8[t]	-0.025716	0.002689	-362.329416	0	0
%M9[t]	-0.023169	0.002689	-363.243999	0	0
%M10[t]	-0.015951	0.002689	-366.004523	0	0
%M11[t]	-0.006083	0.002689	-369.656508	0	0
Variable	Stand. Coeff.	S.E.*	T-STAT H0: coeff = 0	2-tail p-value	1-tail p-value
S-x[t]	-0.254491	0.046132	-5.516577	0	0
S-Constant	0	0	0	1	0.5
S-t^1	-0.338746	0.046171	-7.336707	0	0
S-M1[t]	-0.435266	0.051626	-8.431063	0	0
S-M2[t]	-0.608027	0.051613	-11.780564	0	0
S-M3[t]	-0.561336	0.051624	-10.873653	0	0
S-M4[t]	-0.664571	0.051594	-12.88072	0	0
S-M5[t]	-0.534875	0.051603	-10.365202	0	0
S-M6[t]	-0.583153	0.05158	-11.305814	0	0
S-M7[t]	-0.512481	0.051587	-9.934392	0	0
S-M8[t]	-0.493182	0.05157	-9.563429	0	0
S-M9[t]	-0.444338	0.051574	-8.615512	0	0
S-M10[t]	-0.305914	0.051563	-5.932778	0	0
S-M11[t]	-0.116656	0.051566	-2.262267	0.02489	0.012445
*Note	computed against deterministic endogenous series
Variable	Partial Correlation
x[t]	-0.382109
Constant	0.969397
t^1	-0.481858
M1[t]	-0.534208
M2[t]	-0.66189
M3[t]	-0.631766
M4[t]	-0.69457
M5[t]	-0.613511
M6[t]	-0.646499
M7[t]	-0.597232
M8[t]	-0.582596
M9[t]	-0.542482
M10[t]	-0.406319
M11[t]	-0.167178
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	0.861322
R-squared	0.741876
Adjusted R-squared	0.723025
F-TEST	39.353229
Observations	192
Degrees of Freedom	178
Multiple Linear Regression - Residual Statistics
Standard Error	152.41776
Sum Squared Errors	4135148.87029
Log Likelihood	-1230.279896
Durbin-Watson	0.918093
Von Neumann Ratio	0.9229
# e[t] > 0	100
# e[t] < 0	92
# Runs	66
Stand. Normal Runs Statistic	-4.469906

Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error	24925.113158
Akaike (1973) Log Information Criterion	10.123372
Akaike (1974) Information Criterion	24918.651283
Schwarz (1978) Log Criterion	10.360898
Schwarz (1978) Criterion	31599.530877
Craven-Wahba (1979) Generalized Cross Validation	25058.344372
Hannan-Quinn (1979) Criterion	27434.908117
Rice (1984) Criterion	25214.32238
Shibata (1981) Criterion	24678.080281

Multiple Linear Regression - Analysis of Variance
ANOVA	DF	Sum of Squares	Mean Square
Regression	13	11884881.999502	914221.692269
Residual	178	4135148.87029	23231.173429
Total	191	16020030.869792	83874.507171684
F-TEST	39.353229
p-value	0

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