Bias, Information, Noise: The BIN Model of Forecasting

75 Pages Posted: 7 Apr 2020 Last revised: 7 Oct 2020

See all articles by Ville Satopää

Ville Satopää

INSEAD - Technology and Operations Management

Marat Salikhov

Yale School of Management

Philip Tetlock

University of Pennsylvania

Barb Mellers

University of Pennsylvania, Psychology; University of Pennsylvania, Wharton School

Date Written: February 19, 2020

Abstract

A four-year series of subjective-probability forecasting tournaments sponsored by the U.S. intelligence community revealed a host of replicable drivers of predictive accuracy, including experimental interventions such as training in probabilistic reasoning, anti-groupthink teaming, and tracking-of-talent. Drawing on these data, we propose a Bayesian BIN model (Bias, Information, Noise) for disentangling the underlying processes that enable forecasters and forecasting methods to improve – either by tamping down bias and noise in judgment or by ramping up the efficient extraction of valid information from the environment. The BIN model reveals that noise reduction plays a surprisingly consistent role across all three methods of enhancing performance. We see the BIN method as useful in focusing managerial interventions on what works when and why in a wide range of domains. An R-package called BINtools implements our method and is available on the first author’s personal website.

Keywords: Bayesian Statistics, Judgmental Forecasting, Partial Information, Shapley Value, Wisdom of Crowds

Suggested Citation

Satopää, Ville and Salikhov, Marat and Tetlock, Philip and Mellers, Barb, Bias, Information, Noise: The BIN Model of Forecasting (February 19, 2020). Available at SSRN: https://ssrn.com/abstract=3540864 or http://dx.doi.org/10.2139/ssrn.3540864

Ville Satopää (Contact Author)

INSEAD - Technology and Operations Management ( email )

Boulevard de Constance
77 305 Fontainebleau Cedex
France

Marat Salikhov

Yale School of Management ( email )

165 Whitney Ave
New Haven, CT 06511

HOME PAGE: http://maratsalikhov.com

Philip Tetlock

University of Pennsylvania ( email )

Philadelphia, PA 19104
United States

Barb Mellers

University of Pennsylvania, Psychology ( email )

3815 Walnut Street
Philadelphia, PA 19104-6196
United States

University of Pennsylvania, Wharton School ( email )

3641 Locust Walk
Philadelphia, PA 19104-6365
United States

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