Collaborative Research: Meta-Analysis of Empirical Estimates of Loss-Aversion

合作研究：损失厌恶实证估计的荟萃分析

• 批准号: 1757282
• 负责人: Alexander Brown
• 金额: $ 3.82万
• 依托单位: Texas A&M University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1757282&HistoricalAwards=false
• 关键词: Collaborative; Research; Meta; Analysis; Empirical

Losses hurt more than gains feel good. This principle, known as ??loss-aversion??, is a foundational principle in behavioral economics, which uses psychology to improve economic prediction and advice. Loss aversion is applied to understand several policy issues, including international trade and stock market trades. It has also been used as a tool by governments and businesses to design ??nudges?? to help people make better decisions. The value of ??loss aversion?? depends on specific events and circumstances in which it is applied. As a result, several calculated values of loss aversion exist, creating confusion and uncertainty for its use in research and policy. This proposed research will collect all calculated values of loss aversion, categorize and summarize, and placed them in a central repository for easy reference. The results of this research activity will improve the usefulness of loss aversion in research and policy development. This will establish the US as the global leader in loss aversion research and application as this will be the only such study in the world. Aversion to losses is measured by a number ??, which is thought to be about 1.5-2 times higher than the value of gains. This range of values is based on prominent examples, but there are actually several hundred published studies measuring ??. Our proposed meta-analysis involves finding and identifying every paper that has a statistical estimate of ??, recording all those estimates, then summarizing their results. Scientists can then see for the first time whether the assumed range of ??=1.5 to 2 is correct. The proposed research will also measure how much ?? varies for different groups of people and based on differences in scientific methods (e.g., controlled lab experiments vs. inferences from everyday decisions). This evidence can help behavioral insights teams customize nudges for particular groups of people, using more precise assumptions about the appropriate value of ??. The meta-analysis also illustrates how to cumulate scientific knowledge effectively, to overcome possible concerns about the reproducibility of science. This research also contributes to the efforts to increase reproducibility of scientific research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

损失的伤害比收益良好。该原则被称为“损失 - 损失”，是行为经济学的基础原则，它使用心理学来改善经济预测和建议。损失规避用于了解几个政策问题，包括国际贸易和股票市场交易。 政府和企业也将其用作工具来设计微笑？帮助人们做出更好的决定。 损失避免的价值？取决于应用其应用的特定事件和情况。 结果，存在几种计算出的损失厌恶值，从而在研究和政策中造成混乱和不确定性。 这项拟议的研究将收集所有计算出的损失厌恶值，分类和总结，并将其放置在中央存储库中以方便参考。 这项研究活动的结果将提高损失厌恶在研究和政策发展中的实用性。 这将确立美国成为损失厌恶研究和应用的全球领导者，因为这将是世界上唯一的研究。 对损失的厌恶是通过数字来衡量的，它被认为比收益值高约1.5-2倍。这种值范围是基于突出的例子，但实际上有数百个已发表的研究测量？ 我们提出的荟萃分析涉及查找和确定具有统计估计值的每篇论文，记录所有这些估计，然后总结其结果。然后，科学家可以首次查看假设的= 1.5至2的假定范围是正确的。拟议的研究还将衡量多少？不同的人群的不同，并且基于科学方法的差异（例如，受控实验室实验与日常决策的推论）。 这些证据可以帮助行为洞察力团队为特定人群定制午睡，并使用有关适当值的？荟萃分析还说明了如何有效地累积科学知识，以克服对科学可重复性的可能担忧。 这项研究还有助于提高科学研究的可重复性的努力。该奖项反映了NSF的法定使命，并被认为是通过基金会的知识分子优点和更广泛的影响评估标准来评估值得支持的。