摘要翻译：
最近的研究表明，自20世纪70年代以来，美国个人收入的波动性（例如，预期平方变化）显著上升。这种趋势的现有度量方法是从个体的异质性中抽象出来的，有效地估计了平均波动率的增加。我们分解了平均波动率的这种增加，发现它远远不能代表大多数人的经历：对于绝大多数个人来说，波动率没有系统性的上升。平均波动率的上升几乎完全是由预期收入最不稳定的人的收入波动率急剧上升所驱动的，这些人的收入波动率事先由过去的大幅收入变化所确定。我们证明，自营职业者和那些自我认同为风险承受能力的人更有可能拥有如此不稳定的收入；这些群体的收入波动比一般人口增加得多。这些结果给人们可能从平均波动率上升中得出的政策含义增添了色彩。虽然PSID汇总统计的基本结果是显而易见的，但提供波动率分布动态的完整表征是一个方法学挑战。我们用马尔可夫分层Dirichlet过程解决了这些困难，该过程建立在非参数贝叶斯统计文献的基础上。
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英文标题：
《Changes in the Distribution of Income Volatility》
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作者：
Shane T. Jensen and Stephen H. Shore
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最新提交年份：
2008
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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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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英文摘要：
  Recent research has documented a significant rise in the volatility (e.g., expected squared change) of individual incomes in the U.S. since the 1970s. Existing measures of this trend abstract from individual heterogeneity, effectively estimating an increase in average volatility. We decompose this increase in average volatility and find that it is far from representative of the experience of most people: there has been no systematic rise in volatility for the vast majority of individuals. The rise in average volatility has been driven almost entirely by a sharp rise in the income volatility of those expected to have the most volatile incomes, identified ex-ante by large income changes in the past. We document that the self-employed and those who self-identify as risk-tolerant are much more likely to have such volatile incomes; these groups have experienced much larger increases in income volatility than the population at large. These results color the policy implications one might draw from the rise in average volatility. While the basic results are apparent from PSID summary statistics, providing a complete characterization of the dynamics of the volatility distribution is a methodological challenge. We resolve these difficulties with a Markovian hierarchical Dirichlet process that builds on work from the non-parametric Bayesian statistics literature.
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PDF链接：
https://arxiv.org/pdf/0808.1090