TY - JOUR
T1 - Prince
T2 - An improved method for measuring incentivized preferences
AU - Johnson, Cathleen
AU - Baillon, Aurélien
AU - Bleichrodt, Han
AU - Li, Zhihua
AU - van Dolder, Dennie
AU - Wakker, Peter P.
N1 - JEL Classification: C91, D81
Funding Information:
Helpful discussions with Chen Li are gratefully acknowledged. Johnson thanks Social Philosophy and Policy Foundation for supporting her as a Research Scholar.
Publisher Copyright:
© 2021, The Author(s).
Funding Information:
Helpful discussions with Chen Li are gratefully acknowledged. Johnson thanks Social Philosophy and Policy Foundation for supporting her as a Research Scholar.
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/2
Y1 - 2021/2
N2 - This paper introduces the Prince incentive system for measuring preferences. Prince combines the tractability of direct matching, allowing for the precise and direct elicitation of indifference values, with the clarity and validity of choice lists. It makes incentive compatibility completely transparent to subjects, avoiding the opaqueness of the Becker-DeGroot-Marschak mechanism. It can be used for adaptive experiments while avoiding any possibility of strategic behavior by subjects. To illustrate Prince’s wide applicability, we investigate preference reversals, the discrepancy between willingness to pay and willingness to accept, and the major components of decision making under uncertainty: utilities, subjective beliefs, and ambiguity attitudes. Prince allows for measuring utility under risk and ambiguity in a tractable and incentive-compatible manner even if expected utility is violated. Our empirical findings support modern behavioral views, e.g., confirming the endowment effect and showing that utility is closer to linear than classically thought. In a comparative study, Prince gives better results than a classical implementation of the random incentive system.
AB - This paper introduces the Prince incentive system for measuring preferences. Prince combines the tractability of direct matching, allowing for the precise and direct elicitation of indifference values, with the clarity and validity of choice lists. It makes incentive compatibility completely transparent to subjects, avoiding the opaqueness of the Becker-DeGroot-Marschak mechanism. It can be used for adaptive experiments while avoiding any possibility of strategic behavior by subjects. To illustrate Prince’s wide applicability, we investigate preference reversals, the discrepancy between willingness to pay and willingness to accept, and the major components of decision making under uncertainty: utilities, subjective beliefs, and ambiguity attitudes. Prince allows for measuring utility under risk and ambiguity in a tractable and incentive-compatible manner even if expected utility is violated. Our empirical findings support modern behavioral views, e.g., confirming the endowment effect and showing that utility is closer to linear than classically thought. In a comparative study, Prince gives better results than a classical implementation of the random incentive system.
UR - http://www.scopus.com/inward/record.url?scp=85111505566&partnerID=8YFLogxK
U2 - 10.1007/s11166-021-09346-9
DO - 10.1007/s11166-021-09346-9
M3 - Article
VL - 62
SP - 1
EP - 28
JO - Journal of Risk and Uncertainty
JF - Journal of Risk and Uncertainty
SN - 0895-5646
IS - 1
ER -