通过征收机器人税减轻自动化对劳动力的替代效应：来自调查实验的证据

IF 3.2 3区经济学 Q1 ECONOMICS

Economics of Innovation and New Technology Pub Date : 2023-12-14 DOI:10.1080/10438599.2023.2293031

Emanuela Carbonara, Chiara N. Focacci, Enrico Santarelli

引用次数: 0

摘要

我们研究了税收如何影响自动化与就业动态之间的关系。我们对居住在美国的 2000 名企业家进行了一项调查实验，结果表明，税收对自动化和就业动态之间的关系具有重要影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Mitigating the labor displacing effects of automation through a robot tax: evidence from a survey experiment

We examine how taxation might influence the relationship between automation and employment dynamics. The results obtained through a survey experiment with 2,000 entrepreneurs residing in the U.S. s...

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Economics of Innovation and New Technology ECONOMICS-

CiteScore

7.20

自引率

3.00%

发文量

期刊介绍： Economics of Innovation and New Technology is devoted to the theoretical and empirical analysis of the determinants and effects of innovation, new technology and technological knowledge. The journal aims to provide a bridge between different strands of literature and different contributions of economic theory and empirical economics. This bridge is built in two ways. First, by encouraging empirical research (including case studies, econometric work and historical research), evaluating existing economic theory, and suggesting appropriate directions for future effort in theoretical work. Second, by exploring ways of applying and testing existing areas of theory to the economics of innovation and new technology, and ways of using theoretical insights to inform data collection and other empirical research. The journal welcomes contributions across a wide range of issues concerned with innovation, including: the generation of new technological knowledge, innovation in product markets, process innovation, patenting, adoption, diffusion, innovation and technology policy, international competitiveness, standardization and network externalities, innovation and growth, technology transfer, innovation and market structure, innovation and the environment, and across a broad range of economic activity not just in ‘high technology’ areas. The journal is open to a variety of methodological approaches ranging from case studies to econometric exercises with sound theoretical modelling, empirical evidence both longitudinal and cross-sectional about technologies, regions, firms, industries and countries.