R-squared 0.995479
Adjusted R-squared 0.992465
S.E. of regression 304.8541
Sum squared resid 836424.1
Log likelihood -109.6174
Durbin-Watson stat 2.559488
Mean dependent var 65317.00
S.D. dependent var 3511.968
Akaike info criterion 14.57718
Schwarz criterion 14.91519
F-statistic 330.2853
Prob(F-statistic) 0.000000
A glance at these results would suggest that we have the collinearity problem, for the R2 value is very high, but quite a few variables are statistically insignificant (Xi, X2, and X5), a classic symptom of multicollinearity. To shed more light on this, we show in Table 10.8 the intercorrelations among the six regressors.
372 PART TWO: RELAXING THE ASSUMPTIONS OF THE CLASSICAL MODEL
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