因子份额分组变异:在错配中的应用

Jose Asturias, Jack Rossbach
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引用次数: 0

摘要

微观工厂数据的一个显著特征是,一个行业内不同工厂的要素成本份额存在显著差异。我们开发了一种方法,将这种变化分解为特质和特定于群体的成分,并使用聚类分析来恢复群体的数量和成员资格,使用要素成本份额在公司之间分散的中断。我们将我们的方法应用于智利工厂层面的数据,发现群体特定的差异约占公司间因素份额变化的三分之一。我们用一个经济模型来激励我们的结果,在这个模型中,特定群体的差异可能源于生产技术的差异或影响不同企业群体的扭曲。我们对研究结果的几种可能解释进行了评估,并认为我们的发现与多种生产技术引起的群体特异性变异的解释最为一致。在这种解释下,忽略群体将消除错误分配带来的收益夸大了大约三分之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Grouped Variation in Factor Shares: An Application to Misallocation
A striking feature of micro-level plant data is the presence of significant variation in factor cost shares across plants within an industry. We develop a methodology to decompose this variation into idiosyncratic and group-specific components and to use cluster analysis to recover the number and membership of groups using breaks in the dispersion of factor cost shares across firms. We apply our methodology to Chilean plant-level data and find that group-specific variation accounts for approximately one-third of the variation in factor shares across firms. We motivate our results with an economic model in which group-specific variation can arise from differences in production technologies or through distortions that affect different groups of firms. We evaluate several potential explanations for our results and argue that our findings are most consistent with the interpretation of group-specific variation arising from the presence of multiple production technologies. Under this interpretation, ignoring groups overstates the gains from eliminating mis-allocation by roughly one-third.
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