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首页> 外文期刊>Econometric Theory >EXPLOITING INFINITE VARIANCE THROUGH DUMMY VARIABLES IN NONSTATIONARY AUTOREGRESSIONS
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EXPLOITING INFINITE VARIANCE THROUGH DUMMY VARIABLES IN NONSTATIONARY AUTOREGRESSIONS

机译:通过非稳态自回归中的哑变量探索无限方差

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We consider estimation and testing in finite-order autoregressive models with a (near) unit root and infinite-variance innovations. We study the asymptotic properties of estimators obtained by dummying out "large" innovations, i.e., those exceeding a given threshold. These estimators reflect the common practice of dealing with large residuals by including impulse dummies in the estimated regression. Iterative versions of the dummy-variable estimator are also discussed. We provide conditions on the preliminary parameter estimator and on the threshold that ensure that (i) the dummy-based estimator is consistent at higher rates than the ordinary least squares estimator, (ii) an asymptotically normal test statistic for the unit root hypothesis can be derived, and (iii) order of magnitude gains of local power are obtained.
机译:我们考虑在具有(接近)单位根和无限方差创新的有限阶自回归模型中进行估计和检验。我们研究了通过消除“大型”创新(即超过给定阈值的创新)而获得的估计量的渐近性质。这些估计量通过在估计的回归中包括脉冲假人来反映处理大残差的常规做法。还讨论了虚拟变量估计量的迭代形式。我们在初步参数估计量和阈值上提供了条件,以确保(i)基于哑元的估计量在比普通最小二乘估计量更高的速率下保持一致,(ii)单位根假设的渐近正态检验统计量可以是推导得出;(iii)获得本地功率的数量级增益。

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