A State Space Approach to Extracting the Signal From Uncertain Data
A State Space Approach to Extracting the Signal From Uncertain Data
复制标题
从不确定数据中提取信号的状态空间方法
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
Vincent Labhard
中科院分区：
文献类型：
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作者：
Alastair Cunningham;Jana Eklund;C. Jeffery;G. Kapetanios;Vincent Labhard
大多数宏观经济数据都是不确定的——它们只是估计，而不是对潜在经济变量的完美衡量。这种不确定性的一个症状是统计机构倾向于根据新的资料或方法上的进步来修正它们的估计。本文提出了一种从不确定数据中提取信号的方法。它描述了一个两步估计过程，其中首先使用过去修订的历史来估计描述官方公布估计的测量方程的参数。然后将这些参数施加到宏观经济变量的状态空间模型的最大似然估计中。
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.