A State Space Approach to Extracting the Signal From Uncertain Data
提出一种两阶段估计方法，利用历史修订数据估计测量方程参数，再通过状态空间模型的最大似然估计从不确定的宏观经济数据中提取真实信号，适用于处理官方数据修订问题。
Most macroeconomic data are uncertain—they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper sets out an approach for extracting the signal from uncertain data. It describes a two-step estimation procedure in which the history of past revisions is first used to estimate the parameters of a measurement equation describing the official published estimates. These parameters are then imposed in a maximum likelihood estimation of a state space model for the macroeconomic variable.