Cunningham, Alastair Eklund, Jana Jeffery, Chris Kapetanios, George
Year of Publication:
Working Paper // School of Economics and Finance, Queen Mary, University of London 637
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.
real-time data analysis state space models data uncertainty data revisions