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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。

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分类依据与纠错

AI 根据所提供的论文材料归类:摘要直接研究单位根、共同随机趋势与协整检验,并给出多变量利率时间序列应用。

反馈分类问题

正在核对关联版本…

代码、数据与补充材料

正在核对对应版本的资源…

关注这篇论文的作者
James H. Stock
Mark W. Watson

共同趋势检验

研究问题
多个含单位根的时间序列共享多少随机趋势,如何检验协整阶数,并分别处理有漂移和无漂移情形?
方法与思路
作者提出两种基于滞后回归矩阵特征根的检验,分别通过有限阶VAR估计和自协方差修正处理干扰参数。
材料陈述的贡献
摘要称,两种检验具有渐近相似性,提供临界值与功效模拟,并在美国战后利率数据中得到支持协整的证据。
阅读关注点
应核对趋势数与协整秩的关系、漂移处理、VAR阶数及修正项设定,并核查摘要中趋势维数的不一致表述。
阅读边界
仅据OpenAlex索引摘要,稿件版本未注明;趋势数与序列数的大小关系及后续维数表述不一致,需查原PDF,不能据此推导。

原文摘要

Cointegrated multiple time series share at least one common trend. Two tests are developed for the number of common stochastic trends (i.e., for the order of cointegration) in a multiple time series with and without drift. Both tests involve the roots of the ordinary least squares coefficient matrix obtained by regressing the series onto its first lag. Critical values for the tests are tabulated, and their power is examined in a Monte Carlo study. Economic time series are often modeled as having a unit root in their autoregressive representation, or (equivalently) as containing a stochastic trend. But both casual observation and economic theory suggest that many series might contain the same stochastic trends so that they are cointegrated. If each of n series is integrated of order 1 but can be jointly characterized by k > n stochastic trends, then the vector representation of these series has k unit roots and n — k distinct stationary linear combinations. Our proposed tests can be viewed alternatively as tests of the number of common trends, linearly independent cointegrating vectors, or autoregressive unit roots of the vector process. Both of the proposed tests are asymptotically similar. The first test (qf ) is developed under the assumption that certain components of the process have a finite-order vector autoregressive (VAR) representation, and the nuisance parameters are handled by estimating this VAR. The second test (qc ) entails computing the eigenvalues of a corrected sample first-order autocorrelation matrix, where the correction is essentially a sum of the autocovariance matrices. Previous researchers have found that U.S. postwar interest rates, taken individually, appear to be integrated of order 1. In addition, the theory of the term structure implies that yields on similar assets of different maturities will be cointegrated. Applying these tests to postwar U.S. data on the federal funds rate and the three- and twelve-month treasury bill rates provides support for this prediction: The three interest rates appear to be cointegrated.

笔记与分组
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