测量生产率离散:一种使用lsamy α稳定分布的参数化方法

Jangho Yang, T. Heinrich, Julian Winkler, F. Lafond, P. Koutroumpis, J. Farmer
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引用次数: 6

摘要

企业之间的生产率水平和增长是极不相同的。已有大量文献解释生产率冲击的起源、分散、演变及其与商业周期的关系。我们详细考察了劳动生产率水平和增长的分布,并观察到它们表现出沉重的尾巴。我们建议使用四参数Levy稳定分布来建模这些分布,这是由广义中心极限定理推导出来的自然候选分布。我们表明,它比几种标准替代方案更适合,并且在时间、国家和行业方面具有显著的一致性。在所有考虑的样本中,尾部参数使得分布的理论方差无穷大,因此样本标准差随样本量的增大而增大。我们发现了一个一致的正偏度,左右尾巴之间的行为明显不同,生产力和规模之间的正关系。分布方法允许我们测试不同的分散度量,并发现生产力分散在过去十年中略有下降。
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Measuring Productivity Dispersion: A Parametric Approach Using the Lévy Alpha-Stable Distribution
Productivity levels and growth are extremely heterogeneous among firms. A vast literature has developed to explain the origins of productivity shocks, their dispersion, evolution and their relationship to the business cycle. We examine in detail the distribution of labor productivity levels and growth, and observe that they exhibit heavy tails. We propose to model these distributions using the four parameter Levy stable distribution, a natural candidate deriving from the generalised Central Limit Theorem. We show that it is a better fit than several standard alternatives, and is remarkably consistent over time, countries and sectors. In all samples considered, the tail parameter is such that the theoretical variance of the distribution is infinite, so that the sample standard deviation increases with sample size. We find a consistent positive skewness, a markedly different behaviour between the left and right tails, and a positive relationship between productivity and size. The distributional approach allows us to test different measures of dispersion and find that productivity dispersion has slightly decreased over the past decade.
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