Missing Events in Event Studies: Identifying the Effects of Partially Measured News Surprises
研究了宏观经济新闻发布中，资产价格跳跃不仅反映头条数字的意外，还反映其他未观测到的新闻因素，并用卡尔曼滤波估计模型，发现加入一个潜在因子后，事件窗口内的收益率曲线方差几乎全被新闻解释。
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.