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Framing of time and subjective likelihood judgments

Predicting future events is a constant human endeavor.  In many domains, this necessarily involves subjective judgments of probabilities of future events, since well-defined data-generating processes often do not exist (Braun & Yaniv, 1999; Vaughan & Spouge, 2002).  For example, consider predicting the price of oil or the level of Dow Jones Industrial Average one year from today, or the outcome of a political process, or the risk of a climatic event.  It has been extensively shown that subjective assessments of probabilities of such uncertain events is often severely and systematically biased due to various cognitive factors such as representativeness, availability, anchoring, and so on, not just for the laymen but also for experienced “experts” (Tversky& Kahneman, 1974).

Project Team
Kanchan Mukherjee and Kriti Jain
Sponsor
IIM Bangalore
Select Project Type
Ongoing Projects
Project Status
Ongoing (Initiated in August 2021)
Funded Projects Functional Area
Organizational Behavior & Human Resources Management

Framing of time and subjective likelihood judgments

Project Team: Kanchan Mukherjee and Kriti Jain
Sponsor: IIM Bangalore
Project Status: Ongoing (Initiated in August 2021)
Area: Organizational Behavior & Human Resources Management
Abstract:

Predicting future events is a constant human endeavor.  In many domains, this necessarily involves subjective judgments of probabilities of future events, since well-defined data-generating processes often do not exist (Braun & Yaniv, 1999; Vaughan & Spouge, 2002).  For example, consider predicting the price of oil or the level of Dow Jones Industrial Average one year from today, or the outcome of a political process, or the risk of a climatic event.  It has been extensively shown that subjective assessments of probabilities of such uncertain events is often severely and systematically biased due to various cognitive factors such as representativeness, availability, anchoring, and so on, not just for the laymen but also for experienced “experts” (Tversky& Kahneman, 1974).