Is aggregate income enough to summarize well-being? We address this long-standing question by exploiting a quantitative approach that studies the relationship between gross domestic product (GDP) and a set of economic, social and environmental indicators for nine developed economies. We introduce a mathematical approach to the analysis of economic indicators. By employing dimensionality reduction and time series reconstruction techniques, we quantify the share of variability stemming from a large set of different indicators that can be compressed into a univariate index. We also evaluate how well this variability can be explained if the univariate index is assumed to be respectively the gross domestic product, national income, household income, or household spending. Our results indicate that all the four univariate measures are doomed to fail in accounting for the variability of all the domains. Even if GDP emerges as the best option among the four economic variables, its quality in synthesizing the variability of indicators belonging to other domains is poor (about 35%). Our approach provides additional support for policy makers interested in measuring the trade offs between income and other relevant social, health and ecological dimensions. Finally, our work adds new quantitative evidence to the vast literature criticizing the usage of GDP as a measure of well-being.

总收入足以概括幸福感吗？我们通过采用定量方法来研究九个发达经济体的国内生产总值 (GDP) 与一组经济、社会和环境指标之间的关系来解决这个长期存在的问题。我们引入一种数学方法来分析经济指标。通过采用降维和时间序列重建技术，我们量化了源自大量不同指标的变异性份额，这些指标可以压缩为单变量指数。如果假设单变量指数分别为国内生产总值、国民收入、家庭收入或家庭支出，我们还评估了这种变异性的解释程度。我们的结果表明，所有四个单变量度量都注定无法解释所有领域的变异性。即使 GDP 成为四个经济变量中的最佳选择，其综合其他领域指标变异性的质量也很差（约 35%）。我们的方法为有兴趣衡量收入与其他相关社会、健康和生态维度之间权衡的政策制定者提供了额外支持。最后，我们的工作为批评使用 GDP 作为福祉衡量标准的大量文献添加了新的定量证据。