Previous research shows that individuals make systematic errors when judging exponential growth, which has harmful effects for their financial well-being. This study analyzes how far individuals are aware of their errors and how these errors are shaped by arithmetic and conceptual problems. Whereas arithmetic problems could be overcome using computational assistance like a pocket calculator, this is not the case for conceptual problems, a term we use to subsume other error drivers like a general misunderstanding of exponential growth or overwhelming task complexity. In an incentivized experiment, we find that participants strongly overestimate the accuracy of their intuitive judgment. At the same time, their willingness to pay for arithmetic assistance is too high on average, often much above the actual benefits a calculator provides. Using a multitier system of task complexity we can show that the willingness to pay for arithmetic assistance is hardly related to its benefits, indicating that participants do not really understand how the interplay of arithmetic and conceptual problems shape their errors in exponential growth tasks. Our findings are relevant for policymaking and financial advisory practice and can help to design effective approaches to mitigate the detrimental effects of misperceived exponential growth.

中文翻译：

---

对指数增长的误解：人们是否意识到自己的错误？

先前的研究表明，个体在判断指数增长时会犯系统错误，这会对他们的财务状况产生有害影响。这项研究分析了个人对错误的了解程度以及这些错误是如何由算术和概念问题形成的。尽管可以使用诸如袖珍计算器之类的计算辅助工具来解决算术问题，但对于概念性问题却并非如此，我们用这个术语来包含其他错误驱动程序，例如对指数增长或压倒性的任务复杂性的普遍误解。在激励实验中，我们发现参与者强烈高估了他们直观判断的准确性。同时，他们平均支付算术协助的意愿太高，通常远高于计算器提供的实际收益。使用任务复杂性的多层系统，我们可以证明支付算术协助的意愿与其收益几乎没有关系，这表明参与者并不真正理解算术和概念问题之间的相互作用如何影响指数增长任务中的错误。我们的发现与决策和财务咨询实践有关，可以帮助设计有效的方法来减轻误解的指数增长的不利影响。