University of Pennsylvania, Philadelphia, PA 19104.
Princeton University, Princeton, NJ 08544.
Proc Natl Acad Sci U S A. 2023 Mar 7;120(10):e2208661120. doi: 10.1073/pnas.2208661120. Epub 2023 Mar 1.
Do larger incomes make people happier? Two authors of the present paper have published contradictory answers. Using dichotomous questions about the preceding day, [Kahneman and Deaton, Proc. Natl. Acad. Sci. U.S.A. , 16489-16493 (2010)] reported a flattening pattern: happiness increased steadily with log(income) up to a threshold and then plateaued. Using experience sampling with a continuous scale, [Killingsworth, Proc. Natl. Acad. Sci. U.S.A. , e2016976118 (2021)] reported a linear-log pattern in which average happiness rose consistently with log(income). We engaged in an adversarial collaboration to search for a coherent interpretation of both studies. A reanalysis of Killingsworth's experienced sampling data confirmed the flattening pattern only for the least happy people. Happiness increases steadily with log(income) among happier people, and even accelerates in the happiest group. Complementary nonlinearities contribute to the overall linear-log relationship. We then explain why Kahneman and Deaton overstated the flattening pattern and why Killingsworth failed to find it. We suggest that Kahneman and Deaton might have reached the correct conclusion if they had described their results in terms of unhappiness rather than happiness; their measures could not discriminate among degrees of happiness because of a ceiling effect. The authors of both studies failed to anticipate that increased income is associated with systematic changes in the shape of the happiness distribution. The mislabeling of the dependent variable and the incorrect assumption of homogeneity were consequences of practices that are standard in social science but should be questioned more often. We flag the benefits of adversarial collaboration.
更高的收入会让人更幸福吗？本文的两位作者给出了相互矛盾的答案。[Kahneman 和 Deaton 在《美国国家科学院院刊》上发表的文章]使用关于前一天的二分问题报告了一种扁平化模式：幸福感随着对数（income）的增加而稳步增加，直到达到一个阈值，然后趋于平稳。[Killingsworth 在《美国国家科学院院刊》上发表的文章]使用连续量表的经验抽样报告了一种线性-对数模式，其中平均幸福感随着对数（income）的增加而持续上升。我们进行了对抗性合作，以寻找对这两项研究的一致解释。对 Killingsworth 的经验抽样数据的重新分析仅证实了最不幸福人群的扁平化模式。在更幸福的人群中，幸福感随着对数（income）的增加而稳步上升，甚至在最幸福的人群中加速上升。互补的非线性因素促成了整体的线性-对数关系。然后，我们解释了为什么 Kahneman 和 Deaton 夸大了扁平化模式，以及为什么 Killingsworth 没有发现它。我们建议，如果 Kahneman 和 Deaton 用不幸福而不是幸福来描述他们的结果，他们可能会得出正确的结论；由于上限效应，他们的衡量标准无法区分幸福感的程度。这两项研究的作者都没有预料到收入的增加会与幸福感分布形状的系统变化有关。因变量的错误标记和同质性的错误假设是社会科学中标准但应该更经常受到质疑的做法的结果。我们强调对抗性合作的好处。
