nep-knm New Economics Papers
on Knowledge Management and Knowledge Economy
Issue of 2021‒10‒18
two papers chosen by
Laura Ştefănescu
Centrul European de Studii Manageriale în Administrarea Afacerilor

  1. Organization of Knowledge and Taxation By Marek Kapicka; Ctirad Slavik
  2. Robots versus labor skills: a complementarity/substitutability analysis By M. Battisti; M. Del Gatto; A. F. Gravina; C. F. Parmeter

  1. By: Marek Kapicka; Ctirad Slavik
    Abstract: This paper studies how labor income taxation interacts with the organization of knowledge and production, and ultimately the distribution of wages in the economy. A more progressive tax system reduces the time that managers allocate to work. This makes the organization of production less efficient and reduces wages at both tails of the distribution, which increases lower tail wage inequality and decreases upper tail wage inequality. The optimal tax system is substantially less progressive than the current one in the United States. However, if wages were exogenous, the optimal tax progressivity would be much higher.
    Keywords: inequality; wages; knowledge based hierarchies; income taxation;
    JEL: E6 H2 D8 L23
    Date: 2021–09
    URL: http://d.repec.org/n?u=RePEc:cer:papers:wp705&r=
  2. By: M. Battisti; M. Del Gatto; A. F. Gravina; C. F. Parmeter
    Abstract: The rise of artificial intelligence and automation is fueling anxiety about the replacementof workers with robots and digital technologies. Relying upon a (country-sector-year) constructed measure of robotic capital (RK), we study the extent of complementarity/substitutabilitybetween robots and workers at different skill levels (i.e., high-, medium- and low-skilled workers). The analysis points to a higher elasticity of substitution (EoS) - i.e., higher substitutability - between RK and unskilled labor, compared to skilled labor. Furthermore, we find evidence of polarizing effects, according to which middle-skilled workers, typically employed in intermediate routine and/or codifiable tasks, are the most vulnerable to robotization. Results turn out to be robust to using different - i) definitions of EoS; ii) computations of RK; iii) samples of countries and industries (WIOD vs EU KLEMS data); iv) skill grouping.
    Keywords: Automation;robotization;elasticity of substitution;technology;polarization
    Date: 2021
    URL: http://d.repec.org/n?u=RePEc:cns:cnscwp:202104&r=

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