英文标题：
《Is it a power law distribution? The case of economic contractions》
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作者：
Salvador Pueyo
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最新提交年份：
2013
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英文摘要：
One of the first steps to understand and forecast economic downturns is identifying their frequency distribution, but it remains uncertain. This problem is common in phenomena displaying power-law-like distributions. Power laws play a central role in complex systems theory; therefore, the current limitations in the identification of this distribution in empirical data are a major obstacle to pursue the insights that the complexity approach offers in many fields. This paper addresses this issue by introducing a reliable methodology with a solid theoretical foundation, the Taylor Series-Based Power Law Range Identification Method. When applied to time series from 39 countries, this method reveals a well-defined power law in the relative per capita GDP contractions that span from 5.53% to 50%, comprising 263 events. However, this observation does not suffice to attribute recessions to some specific mechanism, such as self-organized criticality. The paper highlights a set of points requiring more study so as to discriminate among models compatible with the power law, as needed to develop sound tools for the management of recessions.
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中文摘要：
理解和预测经济衰退的第一步是确定它们的频率分布，但它仍然不确定。这个问题在类似幂律分布的现象中很常见。幂律在复杂系统理论中起着核心作用；因此，目前在经验数据中识别这种分布的局限性是追求复杂性方法在许多领域提供的见解的主要障碍。本文通过介绍一种具有坚实理论基础的可靠方法，即基于泰勒级数的幂律范围识别方法，来解决这个问题。当应用于39个国家的时间序列时，该方法揭示了相对人均GDP收缩的明确幂律，其范围从5.53%到50%，包括263个事件。然而，这种观察不足以将衰退归因于某些特定机制，例如自组织临界性。本文强调了一系列需要进一步研究的问题，以便区分符合幂律的模型，这是开发管理衰退的合理工具所必需的。
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分类信息：

一级分类：Physics 物理学
二级分类：Adaptation and Self-Organizing Systems 自适应和自组织系统
分类描述：Adaptation, self-organizing systems, statistical physics, fluctuating systems, stochastic processes, interacting particle systems, machine learning
自适应，自组织系统，统计物理，波动系统，随机过程，相互作用粒子系统，机器学习
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一级分类：Physics 物理学
二级分类：Data Analysis, Statistics and Probability 数据分析、统计与概率
分类描述：Methods, software and hardware for physics data analysis: data processing and storage; measurement methodology; statistical and mathematical aspects such as parametrization and uncertainties.
物理数据分析的方法、软硬件：数据处理与存储；测量方法；统计和数学方面，如参数化和不确定性。
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一级分类：Quantitative Finance 数量金融学
二级分类：General Finance 一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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一级分类：Statistics 统计学
二级分类：Applications 应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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