Unit root tests and structural change when the initial observation is drawn from its unconditional distribution
初始观测来自无条件分布时的单位根检验与结构变化AI 解读 ↓
本页整理公开书目信息,不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成,未完成全文核验,可能有误;具体假设、证明与结论请核对原文。摘要保留来源文本,未经模型改写。
DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要;缺少可靠材料时保留待补状态。
引用量采用 OpenAlex 单条关联记录,不合计多个记录;关联记录可能包含正式发表版本,不等于此版本单独引用。缺失不视为零,引用指标不代表论文质量。
关注作者按书目中的完整姓名匹配,同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列,再参考通用方法与发表日期。
AI 根据所提供的论文材料归类:摘要明确研究结构变化模型中的单位根检验,同时考察初始条件、断点选择与时间序列误差过程。
初始观测来自无条件分布时的单位根检验与结构变化AI 解读 ↓
正在核对关联版本…
正在核对对应版本的资源…
Following Elliott (1999; International Economic Review 40, 767--83.) and Perron and Rodríguez (2003; Journal of Econometrics 115,1--27), we develop unit root tests in the context of structural change models using GLS detrended data ( Elliott, Rothenberg and Stock 1996; Econometrica 64, 813--39) when the initial observation is drawn from its unconditional distribution. We derive the limiting distributions of the M-tests ( Stock, 1999 cointegration, causality and forecasting; Oxford University Press, 137--67; Perron and Ng 1996; Review of Economics Studies 63, 435--463), the ADF statistic and a feasible optimal point test from which we derive the power envelope. Asymptotic power functions are calculated and compared with the case where the initial condition is not random. Finite sample size and power simulations under various forms of error processes are performed using different lag selection methods and two different methods to select the break point. Empirical applications are also provided. Copyright Royal Economic Society 2006