REDISTRIBUTIVE TAXATION WITH SKILL BIASED TECHNOLOGIES
Pietro Reichlin
No 16226, CEPR Discussion Papers from C.E.P.R. Discussion Papers
Abstract:
I study the optimal redistributive tax structure on capital and labor in a version of the Judd (1985)’s model supplemented by skill biased technology and perfect correlation between skills and wealth. Assuming that the planner is forced to implement a log-linear (progressive) tax and transfer function of pre-tax labor income (often used in public finance), and that low skilled households are hand to mouth consumers, I show that the optimal long-run capital tax rate is positive and the labor marginal tax rate can be positive or negative, depending on demand elasticities as well as on the impact of capital on the skill premium. A positive capital tax serves the purpose of reducing tax distortions arising from redistribution, and it survives for any parametrization of the log-linear tax scheme except for a fully progressive system.
Keywords: Dynamic; optimal; taxation (search for similar items in EconPapers)
JEL-codes: E21 E62 H2 H21 (search for similar items in EconPapers)
Date: 2021-06
References: Add references at CitEc
Citations:
Downloads: (external link)
https://cepr.org/publications/DP16226 (application/pdf)
CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org
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:cpr:ceprdp:16226
Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP16226
orders@cepr.org
Access Statistics for this paper
More papers in CEPR Discussion Papers from C.E.P.R. Discussion Papers Centre for Economic Policy Research, 33 Great Sutton Street, London EC1V 0DX.
Bibliographic data for series maintained by (repec@cepr.org).