Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.E.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
Inc[t]	1.06171	0.266674	3.981302	0.001365	0.000683
Price[t]	-1.382985	0.083814	-16.500598	0	0
Constant	130.706587	27.094293	4.824137	0.00027	0.000135
Variable	Elasticity	S.E.*	T-STAT H0: |elast| = 1	2-tail p-value	1-tail p-value
%Inc[t]	0.812882	0.204175	-0.916462	0.374942	0.187471
%Price[t]	-0.784635	0.047552	-4.529043	0.000472	0.000236
%Constant	0.971754	0.201436	-0.140225	0.89048	0.44524
Variable	Stand. Coeff.	S.E.*	T-STAT H0: coeff = 0	2-tail p-value	1-tail p-value
S-Inc[t]	0.238708	0.059957	3.981302	0.001365	0.000683
S-Price[t]	-0.98933	0.059957	-16.500598	0	0
S-Constant	0	0	0	1	0.5
*Note	computed against deterministic endogenous series
Variable	Partial Correlation
Inc[t]	0.728698
Price[t]	-0.975241
Constant	0.790181
Critical Values (alpha = 5%)
1-tail CV at 5%	1.77
2-tail CV at 5%	2.14

Multiple Linear Regression - Regression Statistics
Multiple R	0.975337
R-squared	0.951282
Adjusted R-squared	0.944322
F-TEST	136.683086
Observations	17
Degrees of Freedom	14
Multiple Linear Regression - Residual Statistics
Standard Error	5.563356
Sum Squared Errors	433.312979
Log Likelihood	-51.647054
Durbin-Watson	2.018549
Von Neumann Ratio	2.144708
# e[t] > 0	9
# e[t] < 0	8
# Runs	7
Runs Statistic	-1.242299

Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error	36.412855
Akaike (1973) Log Information Criterion	3.591188
Akaike (1974) Information Criterion	36.277152
Schwarz (1978) Log Criterion	3.738226
Schwarz (1978) Criterion	42.023365
Craven-Wahba (1979) Generalized Cross Validation	37.583269
Hannan-Quinn (1979) Criterion	36.811266
Rice (1984) Criterion	39.392089
Shibata (1981) Criterion	34.485116

Multiple Linear Regression - Analysis of Variance
ANOVA	DF	Sum of Squares	Mean Square
Regression	2	8460.936433	4230.468217
Residual	14	433.312979	30.950927
Total	16	8894.249412	555.89058823529
F-TEST	136.683086
p-value	0

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