Recalibrating probabilistic forecasts to improve their accuracy
The accuracy of human forecasters is often reduced because of incomplete information and cognitive biases that affect the judges. One approach to improve the accuracy of the forecasts is to recalibrate them by means of non-linear transformations that are sensitive to the direction and the magnitude...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2022-01-01
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| Series: | Judgment and Decision Making |
| Subjects: | |
| Online Access: | http://journal.sjdm.org/21/210914/jdm210914.pdf |
| _version_ | 1827844468640841728 |
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| author | Ying Han David V. Budescu |
| author_facet | Ying Han David V. Budescu |
| author_sort | Ying Han |
| collection | DOAJ |
| description | The accuracy of
human forecasters is often reduced because of incomplete information and
cognitive biases that affect the judges. One approach to improve the accuracy
of the forecasts is to recalibrate them by means of non-linear transformations
that are sensitive to the direction and the magnitude of the biases. Previous
work on recalibration has focused on binary forecasts. We propose an extension
of this approach by developing an algorithm that uses a single free parameter
to recalibrate complete subjective probability distributions. We illustrate the
approach with data from the quarterly Survey of Professional Forecasters (SPF)
conducted by the European Central Bank (ECB), document the potential benefits
of this approach, and show how it can be used in practical applications. |
| first_indexed | 2024-03-12T08:42:20Z |
| format | Article |
| id | doaj.art-d4c0477c5fe7451582cb138bdfe7b463 |
| institution | Directory Open Access Journal |
| issn | 1930-2975 |
| language | English |
| last_indexed | 2024-03-12T08:42:20Z |
| publishDate | 2022-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Judgment and Decision Making |
| spelling | doaj.art-d4c0477c5fe7451582cb138bdfe7b4632023-09-02T16:43:21ZengCambridge University PressJudgment and Decision Making1930-29752022-01-0117191123Recalibrating probabilistic forecasts to improve their accuracyYing HanDavid V. BudescuThe accuracy of human forecasters is often reduced because of incomplete information and cognitive biases that affect the judges. One approach to improve the accuracy of the forecasts is to recalibrate them by means of non-linear transformations that are sensitive to the direction and the magnitude of the biases. Previous work on recalibration has focused on binary forecasts. We propose an extension of this approach by developing an algorithm that uses a single free parameter to recalibrate complete subjective probability distributions. We illustrate the approach with data from the quarterly Survey of Professional Forecasters (SPF) conducted by the European Central Bank (ECB), document the potential benefits of this approach, and show how it can be used in practical applications.http://journal.sjdm.org/21/210914/jdm210914.pdfforecasting recalibration extremization brier score human forecasting subjective probability distributionsnakeywords |
| spellingShingle | Ying Han David V. Budescu Recalibrating probabilistic forecasts to improve their accuracy Judgment and Decision Making forecasting recalibration extremization brier score human forecasting subjective probability distributionsnakeywords |
| title | Recalibrating
probabilistic forecasts to improve their accuracy |
| title_full | Recalibrating
probabilistic forecasts to improve their accuracy |
| title_fullStr | Recalibrating
probabilistic forecasts to improve their accuracy |
| title_full_unstemmed | Recalibrating
probabilistic forecasts to improve their accuracy |
| title_short | Recalibrating
probabilistic forecasts to improve their accuracy |
| title_sort | recalibrating probabilistic forecasts to improve their accuracy |
| topic | forecasting recalibration extremization brier score human forecasting subjective probability distributionsnakeywords |
| url | http://journal.sjdm.org/21/210914/jdm210914.pdf |
| work_keys_str_mv | AT yinghan recalibratingprobabilisticforecaststoimprovetheiraccuracy AT davidvbudescu recalibratingprobabilisticforecaststoimprovetheiraccuracy |