Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/55152 
Year of Publication: 
2009
Series/Report no.: 
Working Paper No. 637
Publisher: 
Queen Mary University of London, Department of Economics, London
Abstract: 
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 are 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.
Subjects: 
real-time data analysis
state space models
data uncertainty
data revisions
JEL: 
C32
C53
Document Type: 
Working Paper

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