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A Composite Generalized Cross-Entropy Formulation in Small Samples Estimation

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  • R. Bernardini Papalia
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    Abstract

    This 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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    File URL: http://www.tandfonline.com/doi/abs/10.1080/07474930801960469
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Econometric Reviews.

    Volume (Year): 27 (2008)
    Issue (Month): 4-6 ()
    Pages: 596-609

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    Handle: RePEc:taf:emetrv:v:27:y:2008:i:4-6:p:596-609

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    Related research

    Keywords: Generalized cross-entropy; Microeconometric models; Repeated samples; Small sample estimation;

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    Cited by:
    1. Rosa Bernardini Papalia & Silvia Bertarelli, 2013. "Nonlinearities in economic growth and club convergence," Empirical Economics, Springer, vol. 44(3), pages 1171-1202, June.
    2. Rosa Bernadini Papalia & Silvia Bertarelli, 2013. "Identification and Estimation of Club Convergence Models with Spatial Dependence," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 37(6), pages 2094-2115, November.

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