An Integrated Model of the Data Measurement and Data Generation Processes with an Application to Consumers' Expenditure

An integrated model is defined as one that not only models the data generation process (DGP) but also models the data measurement process. A natural framework for such an integrated model is the state space approach, with the optimal combination of preliminary vintages of data and predictions from the data generation process model being obtained by application of the Kalman filter. The author shows that substantial reductions in the mean square error of preliminary vintages of data on consumers' expenditure can be obtained from this approach. This provides further evidence that preliminary vintages are not efficient forecasts of the final vintage. Copyright 1995 by Royal Economic Society.

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