Technological Change and Preferences for Redistribution
David Hope,
Julian Limberg and
Nina Sophie Weber
No g38xc_v1, SocArXiv from Center for Open Science
Abstract:
Technological change has fundamentally transformed the US labour market in recent decades, with high-earning jobs becoming increasingly focused on nonroutine, complex tasks. While existing research shows that inequalities are perceived as fairer and demand for redistribution is lower when incomes are earned through effort rather than luck, the nature of the effort tasks performed has received little attention. In this paper, we provide a first experimental test of whether fairness perceptions and preferences for redistribution differ when top earners gain their incomes through luck, routine work, or complex work. We find that the desired tax rate on top earners is up to 5.3 percentage points lower for the complex work treatment than the routine work treatment and that high incomes from complex work are perceived as fairer and more deserved. Interestingly, performance on complex tasks is also more likely to be seen as the result of inherited intelligence, suggesting that meritocratic preferences might prove inconsistent beyond the simple luck versus effort distinction. In an additional survey experiment, we find that higher earning individuals are perceived to have more complex jobs, pointing to a novel explanation for falling top income tax rates in an era of rapidly rising top incomes shares.
Date: 2023-02-19
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://osf.io/download/63ecd64bb3fed60680e34915/
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:g38xc_v1
DOI: 10.31219/osf.io/g38xc_v1
Access Statistics for this paper
More papers in SocArXiv from Center for Open Science
Bibliographic data for series maintained by OSF ().