Calibrated Forecasting and Merging

Ehud Kalai

No 1144, Discussion Papers from Northwestern University, Center for Mathematical Studies in Economics and Management Science

Abstract: Consider a general finite-state stochastic process governed by an unknown objective probability distribution. A forecaster, observing the system, assigns subjective probabilities to future states. The subjective forecast merges to the objective distribution if, with time, forecasted probabilities converge to the (unknown) correct probabilities. The forecast is calibrated if observed long-run empirical distributions coincide with their forecasted probabilities. This paper links the unobserved reliability of forecasts to their observed empirical performance by showing full equilvalents between notions of merging and calibration.

Date: 1995-12
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Related works:
Working Paper: Calibrated Forecasting and Merging (2010)
Journal Article: Calibrated Forecasting and Merging (1999)
Working Paper: Calibrated Forecasting and Merging (1995)
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