Calibration-Based Predictive Distributions: An Application of Prequential Analysis to Interest Rates, Money, Prices, and Output
Some techniques of probability forecasting are applied to time-series data on interest rates, money stock, consumer prices, and output. A sequential method for debiasing (recalibrating) predictive distributions and outcomes is developed, and the authors estimated sequences of unadjusted and recalibrated distributions are tested for calibration. After recalibration, the calibration hypothesis cannot be rejected for most of the time-series and forecast horizons. Furthermore, traditional point forecasts can be improved when the forecasts are derived from recalibrated distributions. Copyright 1989 by the University of Chicago.
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