工业机器人对劳动生产率增长和经济趋同的贡献:生产前沿方法

IF 2.3 4区 经济学 Q3 BUSINESS
Andreas Eder, Wolfgang Koller, Bernhard Mahlberg
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引用次数: 0

摘要

本文以1999 - 2019年19个发达国家和16个新兴国家为样本,研究了工业机器人对劳动生产率增长和跨国经济趋同的贡献。为了回答我们的研究问题,我们通过将工业机器人作为一个单独的生产要素来扩展非参数生产前沿框架。我们发现机器人化对我们样本中所有国家的劳动生产率增长都有积极的贡献。在金融危机之后的一段时间(2009年至2019年),机器人资本深化对生产率增长的贡献变得越来越重要。在1999年至2019年期间,我们发现了一些证据:1)无条件β-收敛(初始生产率水平较低的国家增长更快),2)生产率水平在经济体之间的分散减少(σ-收敛),3)劳动生产率分布的去极化(从双峰分布转向单峰分布)。“传统”物质资本的积累是β趋同的主要驱动力。机器人资本深化显著促进了经济趋同和劳动生产率分布的去极化,但其对劳动生产率分布整体转移的影响不大,并受到“传统”实物资本深化和技术变革等其他生产率增长驱动因素的主导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The contribution of industrial robots to labor productivity growth and economic convergence: a production frontier approach

The contribution of industrial robots to labor productivity growth and economic convergence: a production frontier approach

This paper investigates the contribution of industrial robots to labor productivity growth and cross-country economic convergence in a sample of 19 developed and 16 emerging countries over the period 1999 to 2019. To answer our research questions, we extend the non-parametric production frontier framework by considering industrial robots as a separate production factor. We find a positive contribution of robotization to labor productivity growth for all countries in our sample. In the period after the financial crisis (2009 to 2019) the contribution of robot capital deepening to productivity growth gained in importance. Over the period 1999 to 2019 we find some evidence of i) unconditional β-convergence (countries with lower initial productivity levels grow faster), ii) a reduction in the dispersion of productivity levels across economies (σ-convergence) and iii) a depolarization (shift from bimodal to unimodal distribution) of the labor productivity distribution in our sample. Accumulation of ‘traditional’ physical capital is the main driver of β-convergence. Robot capital deepening significantly contributed to economic convergence and the depolarization of the labor productivity distribution, but its effect on the entire shift of the labor productivity distribution is modest and dominated by other drivers of productivity growth such as ‘traditional’ physical capital deepening and technological change.

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来源期刊
CiteScore
3.10
自引率
6.20%
发文量
30
期刊介绍: The Journal of Productivity Analysis publishes theoretical and applied research that addresses issues involving the measurement, explanation, and improvement of productivity. The broad scope of the journal encompasses productivity-related developments spanning the disciplines of economics, the management sciences, operations research, and business and public administration. Topics covered in the journal include, but are not limited to, productivity theory, organizational design, index number theory, and related foundations of productivity analysis. The journal also publishes research on computational methods that are employed in productivity analysis, including econometric and mathematical programming techniques, and empirical research based on data at all levels of aggregation, ranging from aggregate macroeconomic data to disaggregate microeconomic data. The empirical research illustrates the application of theory and techniques to the measurement of productivity, and develops implications for the design of managerial strategies and public policy to enhance productivity. Officially cited as: J Prod Anal
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