An Information Theoretic Approach to Estimation in the Case of Multicollinearity

Marco van Akkeren

Computational Economics, 2003, vol. 22, issue 1, 22 pages

Abstract: We propose a data-based extremum formulation that extends theempirical-likelihood and information-theoretic methods of estimation andinference. It is demonstrated how this method may be used in a general linearmodel context to mitigate the problem of an ill-conditioned design matrix. Adual loss criterion function, which can be biased in finite samples, producesan estimator that is consistent and asymptotically normal. Limiting chi-squaredistributions are obtained that may be used for hypothesis testing andconfidence intervals. Empirical-risk sampling experiments suggest theestimator has excellent finite-sample properties under a squared error lossmeasure. Copyright Kluwer Academic Publishers 2003

Keywords: empirical-likelihood; semiparametric models; extended estimating equations; Kullback–Leibler information criterion; Lagrange multiplier; pseudo-likelihood ratio tests (search for similar items in EconPapers)
Date: 2003
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DOI: 10.1023/A:1024571428545

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