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Missing Events in Event Studies: Identifying the Effects of Partially Measured News Surprises

机译:事件研究中缺少事件:确定部分测量的新闻惊喜的影响

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摘要

Macroeconomic news announcements are elaborate and multidimensional. We consider a framework in which jumps in asset prices around announcements reflect both the response to observed surprises in headline numbers and to latent factors, reflecting other news in the release. Non-headline news, for which there are no expectations surveys, is unobservable to the econometrician but nonetheless elicits a market response. We estimate the model by the Kalman filter, which efficiently combines OLS and heteroskedasticity-based event study estimators in one step. With the inclusion of a single latent surprise factor, essentially all yield curve variance in event windows are explained by news.
机译:宏观经济新闻公告是详细和多维的。我们考虑了一个框架,其中围绕公告的资产价格跳跃反映了对指挥号码和潜在因素的响应,反映了释放中的其他新闻。非标题新闻,没有预期调查,无法对经济学家无法获得,但仍然引发市场反应。我们通过卡尔曼滤波器估计模型,其在一步中有效地结合了基于OLS和异源性基础的事件研究估计。随着单一潜在的惊喜因素,基本上,事件窗口中的所有收益曲线方差都是通过新闻解释的。

著录项

  • 来源
    《The American economic review》 |2020年第12期|3871-3912|共42页
  • 作者单位

    Department of Economics Bilkent University CEPR CESIfo and CFS;

    Department of Economics Bilkent University;

    Department of Economics Johns Hopkins University and NBER;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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