Predictive powers of tests of risk and loss Aversion in a principal-agent context: an Experiment
| dc.contributor.author | Abken, Amre | |
| dc.date.accessioned | 2018-05-28T08:22:46Z | |
| dc.date.available | 2018-05-28T08:22:46Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | The goal of this experimental study is to demonstrate that the test of loss-aversion has a superior predictive power than the standard test of risk-aversion over behavior in risky situations that involve potential losses, e.g. agent's decision in a principal-agent context. Since participant's loss-aversion and risk-aversion affect the results of the loss-aversion test in one direction, the results of that test contains combined information on agent's preferences regarding risks and losses. On the other hand, test of risk- aversion only reflects the attitude towards risks and becomes redundant for prediction of agent's behavior in principal-agent setting when test of loss-aversion is conducted. A three-stage experiment consisted of eliciting a proxy for the curvature of agent's utility curve over wealth, eliciting a proxy for the loss-aversion of an agent, and eliciting the willingness of an agent to take a costly action for an uncertain reward. | en_US |
| dc.identifier.citation | Abken, Amre. (2018) Predictive powers of tests of risk and loss Aversion in a principal-agent context: an Experiment. Nazarbayev University School of Humanities and Social Sciences | en_US |
| dc.identifier.uri | http://nur.nu.edu.kz/handle/123456789/3193 | |
| dc.language.iso | en | en_US |
| dc.publisher | Nazarbayev University School of Sciences and Humanities | en_US |
| dc.rights | Attribution-NonCommercial-ShareAlike 3.0 United States | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/us/ | * |
| dc.subject | risk-aversion | en_US |
| dc.subject | loss-aversion | en_US |
| dc.title | Predictive powers of tests of risk and loss Aversion in a principal-agent context: an Experiment | en_US |
| dc.type | Master's thesis | en_US |
| workflow.import.source | science |