Partition Dependence and Carryover Biases in Subjective Probability Assessment Surveys for Continuous Variables: Model-Based Estimation and Correction

Venkata R. Prava (), Robert T. Clemen (), Benjamin F. Hobbs () and Melissa A. Kenney ()
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Venkata R. Prava: Department of Geography and Environmental Engineering, Johns Hopkins University, Baltimore, Maryland 21218
Robert T. Clemen: Fuqua School of Business, Duke University, Durham, North Carolina 27708
Benjamin F. Hobbs: Department of Geography and Environmental Engineering, Johns Hopkins University, Baltimore, Maryland 21218
Melissa A. Kenney: Earth System Science Interdisciplinary Center/Cooperative Institute for Climate and Satellites-Maryland, University of Maryland, College Park, Maryland 20740

Decision Analysis, 2016, vol. 13, issue 1, 51-67

Abstract: As probability elicitation becomes widely used, methods other than one-on-one interviews are being used to elicit expert probabilities. This paper considers biases that may arise when probabilities are elicited in an online or workbook setting. We develop a prescriptive model in which the elicited probability is a convex combination of the expert’s underlying probability with elements of partition dependence and two anchors arising from responses to previous questions (“carryover” bias). Our model, applied to two data sets, allows us to estimate the amount of the various biases in a set of elicited probabilities from experts. We find that both the format of the questions—whether they appear on the same or separate pages/screens—and the ordering of the questions can affect the amount of bias. Our research addresses biases in the presence of multiple anchors and provides guidance on manipulating the availability of anchors. The results demonstrate the persistence of anchoring even with careful questionnaire design; thus, the proposed model-based methods are useful to suggest corrections for the resulting biases.

Keywords: cognitive biases; expert elicitation; subjective probability assessments; partition dependence bias; logical carryover bias; order effect; anchoring bias; previous response carryover (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ordeca:v:13:y:2016:i:1:p:51-67

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