Efficiency of linear estimators under heavy-tailedness: convolutions of [alpha]-symmetric distributions
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]
|Date of creation:||2007|
|Publication status:||Published in Econometric Theory|
|Contact details of provider:|| Postal: Littauer Center, Cambridge, MA 02138|
Web page: http://www.economics.harvard.edu/
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- Jensen, D. R., 1997. "Peakedness of linear forms in ensembles and mixtures," Statistics & Probability Letters, Elsevier, vol. 35(3), pages 277-282, October.
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- An, Mark Yuying, 1998.
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- 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.
- 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.
- 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.
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