Identifying Noise Shocks: A VAR with Data Revisions
提出一种新的VAR识别策略，利用计量经济学家的事后信息优势，通过数据修订来识别产出增长早期发布中的噪声冲击，发现噪声冲击的影响在性质上类似但量级上小于需求冲击。
Abstract We propose a new Vector Autoregression (VAR) identification strategy to study the impact of noise, in the early releases of output growth figures, which exploits the informational advantage of the econometrician. Economic agents, uncertain about the underlying state of the economy, respond to noisy early data releases. Econometricians, with the benefit of hindsight, have access to data revisions as well, which we use to identify noise shocks. A surprising report of output growth produces qualitatively similar but quantitatively smaller effects than a demand shock. We also illustrate how a noise shock cannot be identified unless ex‐post information is used.