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Loss aversion

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


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Posted ContentDOI
TL;DR: This paper conducted field experiments in rural India in order to measure preferences related to risk, potential loss, and ambiguity, and found that women are significantly more risk averse and loss averse than men, while a greater degree of risk aversion and loss aversion generally suggests that people are more willing to switch to the new, risk-reducing variety.
Abstract: Advances in agricultural development have largely been a direct result of increased usage of new technologies. Among other important factors, farmers' perceptions of risks associated with the new technology as well as their ability or willingness to take risks greatly influences their adoption decisions. In this paper we conduct a series of field experiments in rural India in order to measure preferences related to risk, potential loss, and ambiguity. Disaggregating by gender, we find that on average women are significantly more risk averse and loss averse than men, though the higher average risk aversion arises due to a greater share of women who are extremely risk averse. Through an empirical example, we demonstrate how these parameters affect decisions to adopt new agricultural technologies, specifically drought-tolerant seeds. By combining these results with a discrete choice experiment over new and familiar rice seeds, we find that ambiguity averse individuals are no more likely to remain with the status quo, while a greater degree of risk aversion and loss aversion generally suggests that people are more willing to switch to the new, risk-reducing variety.

30 citations

Journal ArticleDOI
TL;DR: In this paper, it is argued that loss aversion is a property of observable choice behavior and two new definitions of loss averse behavior are advocated under prospect theory, the new properties hold if the commonly used utility-based measures of loss aversion are corrected by a probability-based measure of risk aversion and their product exceeds 1.
Abstract: This paper reviews the most common approaches that have been adopted to analyze and describe loss aversion under prospect theory. Subsequently, it is argued that loss aversion is a property of observable choice behavior and two new definitions of loss averse behavior are advocated. Under prospect theory, the new properties hold if the commonly used utility based measures of loss aversion are corrected by a probability based measure of loss aversion and their product exceeds 1. It is shown that prominent parametric families of weighting functions, while successful in accommodating empirical findings on probabilistic risk attitudes, may not fit well with the theoretical implications of the new loss averse behavior conditions.

30 citations

Journal ArticleDOI
TL;DR: In this article, it is shown that high involvement increases the slope differential between the loss and gain regions of the value function, enhancing loss aversion, and higher involvement is accompanied by higher arousal and cognitive processing which produces stronger negativity in thoughts.

30 citations

Posted Content
TL;DR: In this paper, the authors present evidence from studies examining labor supply responses in "neoclassical environments" in which workers are free to choose when and how much to work.
Abstract: In many occupations workers’ labor supply choices are constrained by institutional rules regulating labor time and effort provision. This renders explicit tests of the neoclassical theory of labor supply difficult. Here we present evidence from studies examining labor supply responses in “neoclassical environments” in which workers are free to choose when and how much to work. Despite the favorable environment the results cast doubt on the neoclassical model. They are, however, consistent with a model of reference dependent preferences exhibiting loss aversion and diminishing sensitivity.

30 citations

Journal ArticleDOI
TL;DR: A Bayesian adaptive algorithm to assess measures of impulsive and risky decision making, implemented as an experimental battery to measure temporal and probability discounting rates together with loss aversion, and tested on a healthy participant sample.
Abstract: Using simple mathematical models of choice behavior, we present a Bayesian adaptive algorithm to assess measures of impulsive and risky decision making. Practically, these measures are characterized by discounting rates and are used to classify individuals or population groups, to distinguish unhealthy behavior, and to predict developmental courses. However, a constant demand for improved tools to assess these constructs remains unanswered. The algorithm is based on trial-by-trial observations. At each step, a choice is made between immediate (certain) and delayed (risky) options. Then the current parameter estimates are updated by the likelihood of observing the choice, and the next offers are provided from the indifference point, so that they will acquire the most informative data based on the current parameter estimates. The procedure continues for a certain number of trials in order to reach a stable estimation. The algorithm is discussed in detail for the delay discounting case, and results from decision making under risk for gains, losses, and mixed prospects are also provided. Simulated experiments using prescribed parameter values were performed to justify the algorithm in terms of the reproducibility of its parameters for individual assessments, and to test the reliability of the estimation procedure in a group-level analysis. The algorithm was implemented as an experimental battery to measure temporal and probability discounting rates together with loss aversion, and was tested on a healthy participant sample.

30 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023105
2022178
2021178
2020184
2019189
2018197