利用生产网络结构识别生产率溢出效应

Samuel Bazzi, A. Chari, S. Nataraj, Alexander D. Rothenberg
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引用次数: 0

摘要

尽管集聚外部性在理论工作中很重要,但其性质、规模和范围的证据仍然难以获得,特别是在发展中国家。确定企业之间的生产率溢出是一项具有挑战性的任务,估计通常至少需要面板数据,而这些数据在发展中国家往往无法获得。在本文中,我们开发了一种新的识别策略,利用生产者关系的网络结构信息来提供生产率溢出规模的估计。我们的策略建立在Bramoulle等人(2009)提出的估算对等效应的策略的基础上,并且是将这一想法首次应用于生产率溢出估算的策略之一。我们通过使用面板数据改进了网络结构识别策略,并通过汇率引起的贸易冲击来验证它,这些冲击提供了额外的识别变化。我们将这一策略应用于印度尼西亚制造商的长面板数据集,以提供对生产率溢出的规模和大小的新估计。我们的研究结果表明,印度尼西亚的制造商之间存在积极的生产率溢出效应,但对全要素生产率溢出效应的估计远远小于基于美国和欧洲公司层面数据的类似估计,而且仅在少数行业中观察到这种效应。
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Identifying Productivity Spillovers Using the Structure of Production Networks
Despite the importance of agglomeration externalities in theoretical work, evidence for their nature, scale, and scope remains elusive, particularly in developing countries. Identification of productivity spillovers between firms is a challenging task, and estimation typically requires, at a minimum, panel data, which are often not available in developing country contexts. In this paper, we develop a novel identification strategy that uses information on the network structure of producer relationships to provide estimates of the size of productivity spillovers. Our strategy builds on that proposed by Bramoulle et al. (2009) for estimating peer effects, and is one of the first applications of this idea to the estimation of productivity spillovers. We improve upon the network structure identification strategy by using panel data and validate it with exchange-rate induced trade shocks that provide additional identifying variation. We apply this strategy to a long panel dataset of manufacturers in Indonesia to provide new estimates of the scale and size of productivity spillovers. Our results suggest positive productivity spillovers between manufacturers in Indonesia, but estimates of TFP spillovers are considerably smaller than similar estimates based on firm-level data from the U.S. and Europe, and they are only observed in a few industries.
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