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arXiv 2307.02470econ.GNphysics.soc-phq-fin.ECstat.AP
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从统计物理学视角看经济不平等

Statistical Physics Perspective on Economic Inequality

JQI, Department of Physics, University of Maryland(马里兰大学量子信息实验室,物理系)

Victor M. Yakovenko

AI总结:

本文从统计物理学视角研究经济不平等,验证多国收入指数分布、美国收入二元阶层结构,发现全球人均能耗与碳排放不平等在2010年后饱和于G=0.5,符合最大熵原理预测,具深远社会与气候政策意义。

摘要:

本文是笔者为《劳特利奇复杂经济学手册》(2023)撰写的核心成果的补充材料。基于三篇近期论文,本文从统计物理学的视角提出了一种研究经济不平等的非常规思路。其中一节展示了全球67个国家收入呈指数分布的实证证据。在物理学家通过类比玻尔兹曼-吉布斯(Boltzmann-Gibbs)能量分布提出该分布、并在多国实证数据中得到验证之前,主流经济学家对指数分布并不熟悉。另一节回顾了美国收入分配的二元阶层结构:指数规律描述了占人口大多数的下层群体的收入分布,而收入分布的顶端尾部(上层群体)则符合帕累托(Pareto)幂律,二者之间没有明确定义的中产阶级。因此,仅用三个参数就能很好地拟合整个收入分布。本文分析了1983年至2018年间这些参数的历史演变及不平等趋势。最后,本文利用1980年至2017年的实证数据,研究了人均能源消耗和人均CO₂排放层面的全球不平等情况。以基尼系数G衡量的全球不平等程度在2010年左右之前持续下降,但随后在G=0.5的水平上趋于饱和。这一饱和水平是基于最大熵原理在理论上预测得到的,且预测时间远早于全球不平等下降放缓在数据中显现的时间。该效应归因于全球化推动世界经济加速融合,使其达到最大熵状态,进而导致全球经济停滞。这一发现对社会与地缘政治稳定以及应对气候变化的努力具有深远影响。

英文摘要:

This article is a supplement to my main contribution to the Routledge Handbook of Complexity Economics (2023). On the basis of three recent papers, it presents an unconventional perspective on economic inequality from a statistical physics point of view. One section demonstrates empirical evidence for the exponential distribution of income in 67 countries around the world. The exponential distribution was not familiar to mainstream economists until it was introduced by physicists by analogy with the Boltzmann-Gibbs distribution of energy and subsequently confirmed in empirical data for many countries. Another section reviews the two-class structure of income distribution in the USA. While the exponential law describes the majority of population (the lower class), the top tail of income distribution (the upper class) is characterized by the Pareto power law, and there is no clearly defined middle class in between. As a result, the whole distribution can be very well fitted by using only three parameters. Historical evolution of these parameters and inequality trends are analyzed from 1983 to 2018. Finally, global inequality in energy consumption and CO2 emissions per capita is studied using the empirical data from 1980 to 2017. Global inequality, as measured by the Gini coefficient G, has been decreasing until around 2010, but then saturated at the level G=0.5. The saturation at this level was theoretically predicted on the basis of the maximal entropy principle, well before the slowdown of the global inequality decrease became visible in the data. This effect is attributed to accelerated mixing of the world economy due to globalization, which brings it to the state of maximal entropy and thus results in global economic stagnation. This observation has profound consequences for social and geopolitical stability and the efforts to deal with the climate change.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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