  This paper analyzes the estimation of econometric models by penalizing the
sum of squares of the residuals with a factor that makes the model estimates
approximate those that would be obtained when considering the possible simple
regressions between the dependent variable of the econometric model and each of
its independent variables. It is shown that the ridge estimator is a particular
case of the penalized estimator obtained, which, upon analysis of its main
characteristics, presents better properties than the ridge especially in
reference to the individual boostrap inference of the coefficients of the model
and the numerical stability of the estimates obtained. This improvement is due
to the fact that instead of shrinking the estimator towards zero, the estimator
shrinks towards the estimates of the coefficients of the simple regressions
discussed above.
