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Efficiency of linear estimators under heavy-tailedness: convolutions of [alpha]-symmetric distributions

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  • Ibragimov, Rustam
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    This paper focuses on the analysis of efficiency, peakedness, and majorization properties of linear estimators under heavy-tailedness assumptions. We demonstrate that peakedness and majorization properties of log-concavely distributed random samples continue to hold for convolutions of [alpha]-symmetric distributions with [alpha] > 1. However, these properties are reversed in the case of convolutions of [alpha]-symmetric distributions with [alpha]

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    Paper provided by Harvard University Department of Economics in its series Scholarly Articles with number 2623749.

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    Date of creation: 2007
    Publication status: Published in Econometric Theory
    Handle: RePEc:hrv:faseco:2623749
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    1. Jensen, D. R., 1997. "Peakedness of linear forms in ensembles and mixtures," Statistics & Probability Letters, Elsevier, vol. 35(3), pages 277-282, October.
    2. An, Mark Yuying, 1998. "Logconcavity versus Logconvexity: A Complete Characterization," Journal of Economic Theory, Elsevier, vol. 80(2), pages 350-369, June.
    3. Rustam Ibragimov, 2005. "Portfolio Diversification and Value at Risk Under Thick-Tailedness," Harvard Institute of Economic Research Working Papers 2086, Harvard - Institute of Economic Research.
    4. Rustam Ibragimov, 2005. "Optimal Bundling Strategies For Complements And Substitutes With Heavy-Tailed Valuations," Harvard Institute of Economic Research Working Papers 2088, Harvard - Institute of Economic Research.
    5. Rustam Ibragimov, 2005. "A Tale of Two Tails: Peakedness Properties in Inheritance Models of Evolutionary Theory," Harvard Institute of Economic Research Working Papers 2092, Harvard - Institute of Economic Research.
    6. Rustam Ibragimov, 2005. "Demand-Driven Innovation and Spatial Competition Over Time Under Heavy-Tailed Signals," Harvard Institute of Economic Research Working Papers 2087, Harvard - Institute of Economic Research.
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