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A State Space Approach to Extracting the Signal from Uncertain Data

Alastair Cunningham, Jana Eklund, Chris Jeffery, George Kapetanios () and Vincent Labhard ()
Additional contact information
Alastair Cunningham: Bank of England
Chris Jeffery: Bank of England
George Kapetanios: Queen Mary, University of London and Bank of England

No 637, Working Papers from Queen Mary University of London, School of Economics and Finance

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.

Keywords: Real-time data analysis; State space models; Data uncertainty; Data revisions (search for similar items in EconPapers)
JEL-codes: C32 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba, nep-ecm and nep-ets
Date: 2009-02
References: View references in EconPapers View complete reference list from CitEc
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https://www.qmul.ac.uk/sef/media/econ/research/workingpapers/archive/wp637.pdf (application/pdf)

Related works:
Journal Article: A State Space Approach to Extracting the Signal From Uncertain Data (2009) Downloads
Working Paper: A State Space Approach to Extracting the Signal from Uncertain Data (2009) Downloads
Working Paper: A state space approach to extracting the signal from uncertain data (2007) Downloads
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