The ABC mechanism: an incentive compatible payoff mechanism for elicitation of outcome and probability transformations
- PDF / 1,689,013 Bytes
- 28 Pages / 439.37 x 666.142 pts Page_size
- 4 Downloads / 189 Views
The ABC mechanism: an incentive compatible payoff mechanism for elicitation of outcome and probability transformations Yi Li1 Received: 6 March 2019 / Revised: 2 September 2020 / Accepted: 17 October 2020 © Economic Science Association 2020
Abstract When it comes to experiments with multiple-round decisions under risk, the current payoff mechanisms are incentive compatible with either outcome weighting theories or probability weighting theories, but not both. In this paper, I introduce a new payoff mechanism, the Accumulative Best Choice (“ABC”) mechanism that is incentive compatible for all rational risk preferences. I also identify three necessary and sufficient conditions for a payoff mechanism to be incentive compatible for all models of decision under risk with complete and transitive preferences. I show that ABC is the unique incentive compatible mechanism for rational risk preferences in a multiple-task setting. In addition, I test empirical validity of the ABC mechanism in the lab. The results from both a choice pattern experiment and a preference (structural) estimation experiment show that individual choices under the ABC mechanism are statistically not different from those observed with the one-round task experimental design. The ABC mechanism supports unbiased elicitation of both outcome and probability transformations as well as testing alternative decision models that do or do not include the independence axiom. Keywords Experimental design · Payoff mechanism · Incentive compatibility · Decision theory under risk JEL Classification C90 · D80 · D81
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s1068 3-020-09688-2) contains supplementary material, which is available to authorized users. * Yi Li [email protected] 1
Department of Accounting, Economics and Finance, School of Business, Slippery Rock University, 1 Morrow Way, Slippery Rock, PA 16057, USA
13
Vol.:(0123456789)
Y. Li
1 Introduction Archer is recruited as a human subject to participate in an economic experiment. His job is to make choices in a series of tasks. His primary concern is how much he gets paid. If Archer is told he will earn $20 flat, he might go through the tasks as fast as possible without even reading the options. If Archer is told he will get paid for all his choices combined, he may construct a portfolio with all the decisions and optimize as he progresses. However, those are not what experimentalists want. We want subjects to reveal their preferences truthfully in every task. Archer’s “singletask preference” between options A and B refers to Archer’s ranking of the options revealed by his choice in a single-task setting; this has been called “true preference” in earlier literature (Starmer and Sugden 1991; Cubitt et al. 1998). How can we ensure Archer’s choices in a many-decisions setting are consistent with his “singletask preference” in each decision (also known as incentive compatibility)? We must find an incentive compatible payoff mechanism. Let us focus on exper
Data Loading...
