Aggregate productivity, economic fluctuations, and export orientation: Evidence from India

IF 5 2区 经济学 Q1 ECONOMICS
Diti Goswami (Assistant Professor)
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引用次数: 0

Abstract

Understanding the cyclicality in aggregate productivity helps answer whether the economy allocates resources efficiently or not. The paper analyses the sources of aggregate productivity growth, such as direct efficiency gain within-plants, allocative efficiency gain, and gains due to entry and exit during economic fluctuations. In particular, we exploit the economic shock of the Great Recession to analyse the validity of the 'Cleansing’ or ‘Scarring’ effect of recession and 'Schumpeterian Darwinian Selection' for Indian manufacturing. The rise and fall of within-plant and net-entry effects during the economic fluctuations explains the pro-cyclicality of productivity growth. Plants in export-oriented industries are crucial in explaining the pro-cyclicality. Negative external shock to exporting sectors during 2008–09 shifted resources from more productive to less productive plants. The relatively productive exporters exited the markets following the global crisis, scarring the economy. Nonetheless, the positive effect from the net-entry exit of plants during the economic downturn makes the 'Schumpeterian approach of Darwinian Selection' valid.

综合生产力、经济波动和出口导向:印度的证据
了解总生产率的周期性有助于回答经济是否有效地分配了资源。本文分析了总生产率增长的来源,如工厂内部的直接效率增益、分配效率增益以及经济波动期间的进入和退出所带来的增益。特别是,我们利用大衰退对经济的冲击,分析了衰退的 "清洗 "或 "伤痕 "效应以及 "熊彼特达尔文式选择 "对印度制造业的有效性。在经济波动期间,工厂内部效应和净进入效应的上升和下降解释了生产率增长的顺周期性。出口导向型产业的工厂是解释顺周期性的关键。2008-09 年期间,出口部门受到的外部负面冲击使资源从生产率较高的工厂转移到生产率较低的工厂。生产率相对较高的出口商在全球危机后退出了市场,给经济造成了创伤。尽管如此,经济衰退期间工厂净进入退出所产生的积极影响使 "熊彼特达尔文选择法 "成为现实。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
9.60
自引率
4.90%
发文量
159
期刊介绍: Structural Change and Economic Dynamics publishes articles about theoretical, applied and methodological aspects of structural change in economic systems. The journal publishes work analysing dynamics and structural breaks in economic, technological, behavioural and institutional patterns.
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