Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.E.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
prijs[t]	18976.837935	2532.22675	7.494131	0	0
Constant	7959.146927	2812.275594	2.830145	0.006824	0.003412
M1[t]	15259.770625	1743.036886	8.754703	0	0
M2[t]	11317.146673	1738.463398	6.509856	0	0
M3[t]	16094.000769	1729.008495	9.308225	0	0
M4[t]	12674.36478	1727.306643	7.337646	0	0
M5[t]	10293.121832	1728.240865	5.955838	0	0
M6[t]	14883.058959	1726.375784	8.620985	0	0
M7[t]	7832.447244	1725.211459	4.539993	3.9E-05	2E-05
M8[t]	4356.496371	1724.750523	2.52587	0.01497	0.007485
M9[t]	6813.612238	1724.750885	3.950491	0.00026	0.00013
M10[t]	9518.316736	1725.167046	5.51733	1E-06	1E-06
M11[t]	5390.380277	1725.345089	3.124233	0.003051	0.001526
Variable	Elasticity	S.E.*	T-STAT H0: |elast| = 1	2-tail p-value	1-tail p-value
%prijs[t]	0.513624	0.068537	-7.096559	0	0
%Constant	0.221268	0.078183	-9.960405	0	0
%M1[t]	0.035352	0.004038	-238.885839	0	0
%M2[t]	0.026219	0.004028	-241.78217	0	0
%M3[t]	0.037285	0.004006	-240.34156	0	0
%M4[t]	0.029363	0.004002	-242.55811	0	0
%M5[t]	0.023846	0.004004	-243.804835	0	0
%M6[t]	0.03448	0.004	-241.409515	0	0
%M7[t]	0.018146	0.003997	-245.65925	0	0
%M8[t]	0.010093	0.003996	-247.740237	0	0
%M9[t]	0.015785	0.003996	-246.315564	0	0
%M10[t]	0.022051	0.003997	-244.688353	0	0
%M11[t]	0.012488	0.003997	-247.055631	0	0
Variable	Stand. Coeff.	S.E.*	T-STAT H0: coeff = 0	2-tail p-value	1-tail p-value
S-prijs[t]	0.491305	0.065559	7.494131	0	0
S-Constant	0	0	0	1	0.5
S-M1[t]	0.760122	0.086824	8.754703	0	0
S-M2[t]	0.563731	0.086597	6.509856	0	0
S-M3[t]	0.801676	0.086126	9.308225	0	0
S-M4[t]	0.631337	0.086041	7.337646	0	0
S-M5[t]	0.512722	0.086087	5.955838	0	0
S-M6[t]	0.741357	0.085994	8.620985	0	0
S-M7[t]	0.390151	0.085936	4.539993	3.9E-05	2E-05
S-M8[t]	0.217006	0.085913	2.52587	0.01497	0.007485
S-M9[t]	0.3394	0.085914	3.950491	0.00026	0.00013
S-M10[t]	0.474128	0.085934	5.51733	1E-06	1E-06
S-M11[t]	0.268506	0.085943	3.124233	0.003051	0.001526
*Note	computed against deterministic endogenous series
Variable	Partial Correlation
prijs[t]	0.737839
Constant	0.381583
M1[t]	0.787324
M2[t]	0.688582
M3[t]	0.805181
M4[t]	0.730698
M5[t]	0.655827
M6[t]	0.782687
M7[t]	0.552134
M8[t]	0.345718
M9[t]	0.499277
M10[t]	0.626966
M11[t]	0.414686
Critical Values (alpha = 5%)
1-tail CV at 5%	1.68
2-tail CV at 5%	2.01

Multiple Linear Regression - Regression Statistics
Multiple R	0.90043
R-squared	0.810775
Adjusted R-squared	0.762462
F-TEST	16.781769
Observations	60
Degrees of Freedom	47
Multiple Linear Regression - Residual Statistics
Standard Error	2727.070023
Sum Squared Errors	349534812.79822
Log Likelihood	-552.469387
Durbin-Watson	2.094637
Von Neumann Ratio	2.130139
# e[t] > 0	27
# e[t] < 0	33
# Runs	35
Stand. Normal Runs Statistic	1.131293

Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error	9048241.607897
Akaike (1973) Log Information Criterion	16.011102
Akaike (1974) Information Criterion	8985318.209618
Schwarz (1978) Log Criterion	16.464877
Schwarz (1978) Criterion	14145076.180271
Craven-Wahba (1979) Generalized Cross Validation	9493928.822043
Hannan-Quinn (1979) Criterion	10730478.483565
Rice (1984) Criterion	10280435.670536
Shibata (1981) Criterion	8349998.305735

Multiple Linear Regression - Analysis of Variance
ANOVA	DF	Sum of Squares	Mean Square
Regression	12	1497654238.0518	124804519.83765
Residual	47	349534812.79822	7436910.9106
Total	59	1847189050.85	31308288.997458
F-TEST	16.781769
p-value	0

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