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Prediction of final data with use of preliminary and/or revised data
Authors:Roberto S. Mariano  Hisashi Tanizaki
Abstract:In the case of US national accounts the data are revised for the first few years and every decade, which implies that we do not really have the final data. In this paper we aim to predict the final data, using the preliminary data and/or the revised data. The following predictors are introduced and derived from a context of the non-linear filtering or smoothing problem, which are: (1) prediction of the final data of time t given the preliminary data up to time t- 1, (2) prediction of the final data of time t given the preliminary data up to time t, (3) prediction of the final data of time t given the preliminary data up to time T, (4) prediction of the final data of time t given the revised data up to time t -1 and the preliminary data up to time t- 1, and (5) prediction of the final data of time t given the revised data up to time t-1 and the preliminary data up to time t. It is shown that (5) is the best predictor but not too different from (3). The prediction problem is illustrated using US per capita consumption data.
Keywords:revision process  prediction  Kalman filter  Monte Carlo integration filter  final data   revised data  preliminary data
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