Asymptotic distribution of linear unbiased estimators in the presence of heavy-tailed stochastic regressors and residuals
Under the symmetric á-stable distributional assumption for the disturbances, Blattberg et al (1971) consider unbiased linear estimators for a regression model with non-stochastic regressors. We consider both the rate of convergence to the true value and the asymptotic distribution of the normalized error of the linear unbiased estimators. By doing this, we allow the regressors to be stochastic and disturbances to be heavy-tailed with either finite or infinite variances, where the tail-thickness parameters of the regressors and disturbances may be different.
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- Hamerle, Alfred & Liebig, Thilo & Scheule, Harald, 2004. "Forecasting Credit Portfolio Risk," Discussion Paper Series 2: Banking and Financial Studies 2004,01, Deutsche Bundesbank, Research Centre.
- Fecht, Falko & Huang, Kevin & Martin, Antoine, 2005.
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Discussion Paper Series 1: Economic Studies
2005,03, Deutsche Bundesbank, Research Centre.
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- Falko Fecht & Kevin Huang, 2004. "Financial intermediaries, markets, and growth," Econometric Society 2004 North American Summer Meetings 419, Econometric Society.
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