Measuring and controlling for the compromise effect when estimating risk preference parameters

Jonathan P. Beauchamp (), Daniel Benjamin, David Laibson and Christopher F. Chabris
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Jonathan P. Beauchamp: George Mason University
Christopher F. Chabris: Geisinger Health Systems

Experimental Economics, 2020, vol. 23, issue 4, No 6, 1069-1099

Abstract: Abstract The compromise effect arises when being close to the “middle” of a choice set makes an option more appealing. The compromise effect poses conceptual and practical problems for economic research: by influencing choices, it can bias researchers’ inferences about preference parameters. To study this bias, we conduct an experiment with 550 participants who made choices over lotteries from multiple price lists (MPLs). Following prior work, we manipulate the compromise effect to influence choices by varying the middle options of each MPL. We then estimate risk preferences using a discrete-choice model without a compromise effect embedded in the model. As anticipated, the resulting risk preference parameter estimates are not robust, changing as the compromise effect is manipulated. To disentangle risk preference parameters from the compromise effect and to measure the strength of the compromise effect, we augment our discrete-choice model with additional parameters that represent a rising penalty for expressing an indifference point further from the middle of the ordered MPL. Using this method, we estimate an economically significant magnitude for the compromise effect and generate robust estimates of risk preference parameters that are no longer sensitive to compromise-effect manipulations.

Keywords: Compromise effect; Cumulative prospect theory; Loss aversion; Risk preferences (search for similar items in EconPapers)
JEL-codes: B49 D03 D14 D83 G11 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (12)

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DOI: 10.1007/s10683-019-09640-z

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