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Size corrected Significance Tests in Seemingly Unrelated Regressions with Autocorrelated Errors
Journal of Time Series Econometrics Pub Date : 2017-01-01 , DOI: 10.1515/jtse-2015-0014
Spyridon D. Symeonides , Yiannis Karavias , Elias Tzavalis

Abstract Refined asymptotic methods are used to produce degrees-of-freedom- adjusted Edgeworth and Cornish-Fisher size corrections of the t and F testing procedures for the parameters of a S.U.R. model with serially correlated errors. The corrected tests follow the Student-t and F distributions, respectively, with an approximation error of order Oτ3$$O\left({{\tau ^3}} \right)$$, where τ=1/T$$\tau = 1/\sqrt T $$ and T is the number of time observations. Monte Carlo simulations provide evidence that the size corrections suggested hereby have better finite sample properties, compared to the asymptotic testing procedures (either standard or Edgeworth corrected), which do not adjust for the degrees of freedom.

中文翻译:

在具有自相关错误的看似无关的回归中进行尺寸校正的显着性检验

摘要采用精炼的渐近方法对带有序列相关误差的SUR模型参数的t和F测试程序进行自由度调整的Edgeworth和Cornish-Fisher尺寸校正。校正后的测试分别遵循Student-t和F分布,其近似误差为Oτ3$$ O \ left({{\ tau ^ 3}} \ right)$$,其中τ= 1 / T $$ \ tau = 1 / \ sqrt T $$,T是时间观测的次数。蒙特卡罗模拟提供的证据表明,与不针对自由度进行调整的渐进测试程序(标准或Edgeworth校正)相比,本文建议的尺寸校正具有更好的有限样本属性。
更新日期:2017-01-01
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