【摘 要】
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Both estimation methods and measurement errors can have dramatic impact on the outcome of empirical analysis.In this article, we quantify the effects of est
【机 构】
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UniversityofOregon
【出 处】
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IMS-China International Conference on Statistics and Probabi
论文部分内容阅读
Both estimation methods and measurement errors can have dramatic impact on the outcome of empirical analysis.In this article, we quantify the effects of esti mation on prediction generated from time series regression models with and with out measurement errors.The estimators considered are unconditional least squares, maximum likelihood and conditional least squares.The results suggest that although these estimators are asymptotically equivalent, the finite sampling properties of pre dictors based on those estimators can differ substantially, because of differences in finite-sample estimation efficiencies, residual regeneration methods, and the magni tude of the noise-to-signal ratio.
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