Loss aversion

About: Loss aversion is a research topic. Over the lifetime, 2898 publications have been published within this topic receiving 115198 citations.

An Evolutionary Model of Bounded Rationality and Intelligence

Abstract: Background: Most economic theories are based on the premise that individuals maximize their own self-interest and correctly incorporate the structure of their environment into all decisions, thanks to human intelligence. The influence of this paradigm goes far beyond academia–it underlies current macroeconomic and monetary policies, and is also an integral part of existing financial regulations. However, there is mounting empirical and experimental evidence, including the recent financial crisis, suggesting that humans do not always behave rationally, but often make seemingly random and suboptimal decisions. Methods and Findings: Here we propose to reconcile these contradictory perspectives by developing a simple binarychoice model that takes evolutionary consequences of decisions into account as well as the role of intelligence, which we define as any ability of an individual to increase its genetic success. If no intelligence is present, our model produces results consistent with prior literature and shows that risks that are independent across individuals in a generation generally lead to risk-neutral behaviors, but that risks that are correlated across a generation can lead to behaviors such as risk aversion, loss aversion, probability matching, and randomization. When intelligence is present the nature of risk also matters, and we show that even when risks are independent, either risk-neutral behavior or probability matching will occur depending upon the cost of intelligence in terms of reproductive success. In the case of correlated risks, we derive an implicit formula that shows how intelligence can emerge via selection, why it may be bounded, and how such bounds typically imply the coexistence of multiple levels and types of intelligence as a reflection of varying environmental conditions. Conclusions: Rational economic behavior in which individuals maximize their own self interest is only one of many possible types of behavior that arise from natural selection. The key to understanding which types of behavior are more likely to survive is how behavior affects reproductive success in a given population’s environment. From this perspective, intelligence is naturally defined as behavior that increases the probability of reproductive success, and bounds on rationality are determined by physiological and environmental constraints.

Statistical discrimination in labor markets: An experimental analysis

Abstract: This article reports results from controlled laboratory experiments designed to study second-moment (that is, risk-based) statistical discrimination in a labor market setting. Since decision makers may not view risk in the same way as economists or statisticians (that is, risk = variance of distribution), we also examine alternative measures of risk: the support of the distribution and the probability of earning less than the expected (maximum) profits for the employer. Our results indicate that employers made statistically discriminatory wage offers consistent with loss aversion in our full sample (though the result is driven by the male employer subsample). If one can transfer these results outside of the laboratory, they indicate that discrimination estimates based only on first-moment (mean-based) discrimination are biased. The public policy implication is that efforts and legislation aimed at reducing discrimination of various sorts face an additional challenge in trying to identify and limit relatively hidden, but significant, forms of statistical discrimination.

Investor Irrationality and Self-Defeating Behavior: Insights from Behavioral Finance

Abstract: The efficient markets hypothesis (EMH) has posited investment decision-makers as rational, utility-maximizing individuals. Cognitive psychology, on the other hand, suggests that human decision processes are susceptible to several illusions: those caused by heuristic decision-making processes, as well as those arising from the adoption of "mental frames." Unfortunately, these heuristics may lead to cognitive illusions that include: representativeness, overconfidence, anchoring, gambler's fallacy, loss aversion, regret aversion, and mental accounting, among others. Behavioral finance proponents argue that heuristic-driven bias and framing effects cause market prices to deviate from fundamental values. This field amalgamates theories from financial economics, psychology, and sociology in an attempt to construct a more “complete” model that incorporates the idiosyncrasies of human behavior in financial markets. This paper argues that understanding of the findings of this research benefits individual investors the most as it seeks to create awareness of the various human biases and the high costs they impose on their portfolios.

Social Reference Points and Risk Taking

Abstract: We test whether social reference points impact individual risk taking. In a laboratory experiment, decision makers observe the earnings of a peer subject before making a risky choice. We exogenously manipulate the peer earnings across two treatments. We find a significant treatment effect on risk taking: decision makers vary their risk taking in order to surpass or stay ahead of their peer. Our findings are consistent with a social-comparison-based, reference-dependent preference model that formalizes relative concerns via social loss aversion. Additionally, we relate our findings to the impact of private reference points on risk taking.