A Composite Generalized Cross-Entropy Formulation in Small Samples Estimation
AbstractThis article introduces a maximum entropy-based estimation methodology that can be used both to represent the uncertainty of a partial-incomplete economic data generation process and to consider the direct influence of learning from repeated samples. Then, a composite cross-entropy estimator, incorporating information from a subpopulation based on a small sample and from a population with a larger sample size, is derived. The proposed estimator is employed to estimate the local area expenditure shares of a sub population of Italian households using a system of censored demand equations.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Econometric Reviews.
Volume (Year): 27 (2008)
Issue (Month): 4-6 ()
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