Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.E.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
2[t]0.2416190.7921980.3049990.7612010.3806
3[t]0.1814760.1034821.7537040.0835130.041756
4[t]0.1733150.6787480.2553450.7991460.399573
Constant40.2461057.9112375.0872073E-061E-06
VariableElasticityS.E.*T-STAT
H0: |elast| = 1
2-tail p-value1-tail p-value
%2[t]0.2632370.863077-0.8536470.3959830.197992
%3[t]0.1459780.08324-10.25975300
%4[t]0.1962780.768676-1.0455940.2990630.149531
%Constant0.3945070.077549-7.80789900
VariableStand. Coeff.S.E.*T-STAT
H0: coeff = 0
2-tail p-value1-tail p-value
S-2[t]0.3226371.057830.3049990.7612010.3806
S-3[t]0.3561550.2030871.7537040.0835130.041756
S-4[t]0.2722781.0663140.2553450.7991460.399573
S-Constant00010.5
*Notecomputed against deterministic endogenous series
VariablePartial Correlation
2[t]0.034964
3[t]0.197213
4[t]0.029278
Constant0.504006
Critical Values (alpha = 5%)
1-tail CV at 5%1.65
2-tail CV at 5%1.96

Multiple Linear Regression - Regression Statistics
Multiple R0.67925
R-squared0.461381
Adjusted R-squared0.44012
F-TEST21.700529
Observations80
Degrees of Freedom76
Multiple Linear Regression - Residual Statistics
Standard Error5.63774
Sum Squared Errors2415.592613
Log Likelihood-249.822014
Durbin-Watson1.286627
Von Neumann Ratio1.302913
# e[t] > 042
# e[t] < 038
# Runs28
Stand. Normal Runs Statistic-2.910328

Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error33.373319
Akaike (1973) Log Information Criterion3.507673
Akaike (1974) Information Criterion33.370534
Schwarz (1978) Log Criterion3.626775
Schwarz (1978) Criterion37.591374
Craven-Wahba (1979) Generalized Cross Validation33.456961
Hannan-Quinn (1979) Criterion35.002673
Rice (1984) Criterion33.549897
Shibata (1981) Criterion33.214398

Multiple Linear Regression - Analysis of Variance
ANOVADFSum of SquaresMean Square
Regression32069.196262689.732087
Residual762415.59261331.784113
Total794484.78887556.76947943038
F-TEST21.700529
p-value0