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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。

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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。

分类依据与纠错

AI 根据所提供的论文材料归类:摘要分析宏观数据修订的时间序列可预测性,并明确考察结构断点及经济周期阶段差异。

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
Norman R Swanson
Dick van Dijk

统计发布机构做对了吗?数据理性与经济周期不对称

研究问题
工业生产和生产者价格指数的早期发布是否有效利用已有信息?研究关注数据何时变得理性,以及衰退和结构变化如何影响修订可靠性。
方法与思路
作者分析各变量的完整修订历史,检验剩余修订能否由自身历史及公开经济金融信息预测,并区分季节调整、周期阶段和结构断点。
材料陈述的贡献
摘要称,未季调数据约三至四个月后趋于理性,季调数据至少六至十二个月仍存在问题;衰退期修订更波动,忽略非线性可能造成错误推断。
阅读关注点
应核对数据理性的检验定义、各发布时间与修订终点的处理,以及周期划分和结构断点如何改变预测性检验的结论。
阅读边界
仅据所给OpenAlex摘要,不能核实样本范围和检验规格;理性成立的时间与修订可预测性如何按变量、版本及阶段区分,仍需查全文。

原文摘要

This article provides new evidence on the rationality of early releases of industrial production (IP) and producer price index (PPI) data. Rather than following the usual practice of examining only first available and fully revised data, we examine the entire revision history for each variable. Thus we are able to assess, for example, whether earlier releases of data are in any sense “less” rational than later releases, and when data become rational. Our findings suggest that seasonally unadjusted IP and PPI become rational after approximately 3–4 months, whereas seasonally adjusted versions of these series remain irrational for at least 6–12 months after initial release. For all variables examined, we find evidence that the remaining revision is predictable from its own past or from publicly available information in other economic and financial variables. In addition, we find a clear increase in the volatility of revisions during recessions, suggesting that early data releases are less reliable in tougher economic times. Finally, we explore whether nonlinearities in economic behavior manifest themselves in the form of nonlinearities in the rationality of early releases of economic data, by separately analyzing expansionary and recessionary economic phases and by allowing for structural breaks. These types of nonlinearities are shown to be prevalent and in some cases to lead to incorrect inferences concerning data rationality when they are not taken into account.

笔记与分组