Multicollinearity and maximum entropy estimators

@inproceedings{Paris2001MulticollinearityAM,
  title={Multicollinearity and maximum entropy estimators},
  author={Quirino Paris},
  year={2001}
}
Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfalls of their own. The ridge estimator is not generally accepted as a vital alternative to the ordinary least−squares (OLS) estimator because it depends upon unknown parameters. The generalized maximum entropy estimator depends upon subjective exogenous information. This paper presents a novel maximum entropy estimator that does not depend upon any additional information. Monte Carlo experiments show… CONTINUE READING

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