Should Governments Tax Companies' Use of Robots? Automated Workers, Technological Unemployment, and Wage Inequality.

Author:Ionescu, Luminita
 
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  1. Introduction

    Automation influences the skilled-unskilled wage inequality. (Zhang, 2019) The present taxation system stimulates automation by supplying employers with privileged tax interpretation for robot workers. (Abbott and Bogenschneider, 2018) Robotic taxation dissimulates the intrinsic friction between innovation tax and employment tax schemes. (Kisska-Schulze and Davis-Nozemack, 2020)

  2. Conceptual Framework and Literature Review

    A rise in automation brings about the substitution effect and the capital redistribution one (Zhang, 2019), by enabling companies to bypass employee and employer wage taxes demanded by taxing authorities, in addition to allowing them to apply for accelerated tax depreciation on capital expenses for automated workers (Campbell et al., 2017; Georgiou and Rocco, 2017; Havu, 2017; Hoffman and Friedman, 2018; Mircica, 2018; Mirica (Dumitrescu), 2018; Pilkington, 2017; Popescu Ljungholm, 2017, 2018; Vochozka et al., 2018; Popescu, 2018), and generating diverse indirect incentives for machine workers. (Abbott and Bogenschneider, 2018) A robot tax to delay the consequences of automation would necessitate that employers who substitute personnel with robots to be charged a tax, the resulting funds being then utilized to take care of displaced labor force and decrease repercussions of such job loss. (Claus, 2019)

  3. Methodology and Empirical Analysis

    Building my argument by drawing on data collected from The Boston Consulting Group, eMarketer, MIT Sloan Management Review, Morar Consulting, Narrative Science, National Post, NBR Institute, OECD, Pew Research Center, Squiz, Statista, and YouGov, I performed analyses and made estimates regarding leading advantages of artificial intelligence for international organizations (%), the most important benefit that an artificial intelligence-powered solution should provide (%), jobs with high potential for automation or significant change in task (%), U.S. workers worried they might lose their job to advancing technology (%), U.S. workers who expect artificial intelligence will affect the workforce in the next five years (%), and U.S. workers who say they would strongly oppose/oppose/favor/strongly favor certain policies in the event that robots and computers are capable of doing many human jobs (%). The results of a study based on data collected from 4,200 respondents provide support for my research model. Using the structural equation modeling and employing the probability sampling...

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