Arbeitspapier

Calibrated Forecasting and Merging

Consider a general finite-state stochastic process governed by an unknown objective probability distribution. Observing the system, a forecaster assigns subjective probabilities to future states. The resulting subjective forecast merges to the objective distribution if, with time, the forecasted probabilities converge to the correct (but unknown) probabilities. The forecast is calibrated if observed long-run empirical distributions coincide with the forecasted probabilities. This paper links the unobserved reliability of forecasts to their observed empirical performance by demonstrating full equilvalence between notions of merging and of calibration. It also indicates some implications of this equilvalence for the literatures of forecasting and learning.

Language
Englisch

Bibliographic citation
Series: Discussion Paper ; No. 1144R

Classification
Wirtschaft

Event
Geistige Schöpfung
(who)
Kalai, Ehud
Event
Veröffentlichung
(who)
Northwestern University, Kellogg School of Management, Center for Mathematical Studies in Economics and Management Science
(where)
Evanston, IL
(when)
1995

Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Arbeitspapier

Associated

  • Kalai, Ehud
  • Northwestern University, Kellogg School of Management, Center for Mathematical Studies in Economics and Management Science

Time of origin

  • 1995

Other Objects (12)