DYNAMIC SCORING OF TAX REFORMS IN THE EUROPEAN UNION
Salvador Barrios (),
Mathias Dolls,
Anamaria Maftei,
Andreas Peichl,
Sara Riscado,
Janos Varga and
Christian Wittneben
Munich Reprints in Economics from University of Munich, Department of Economics
Abstract:
In this paper, we present the first dynamic scoring exercise linking a microsimulation and a dynamic general equilibrium model for Europe. We illustrate our novel methodology analyzing hypothetical reforms of the social insurance contributions system in Belgium. Our approach takes into account the feedback effects resulting from adjustments and behavioral responses in the labor market and the economy-wide reaction to the tax policy changes essential for a comprehensive evaluation of the reforms. We find that the self-financing effect of a reduction in employers' social insurance contribution is substantially larger than that of a comparable reduction in employees' social insurance contributions.
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (15)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
Journal Article: DYNAMIC SCORING OF TAX REFORMS IN THE EUROPEAN UNION (2019)
Working Paper: Dynamic Scoring of Tax Reforms in the European Union (2018)
Working Paper: Dynamic scoring of tax reforms in the European Union (2018)
Working Paper: Dynamic scoring of tax reforms in the European Union (2017)
Working Paper: Dynamic scoring of tax reforms in the European Union (2017)
Working Paper: Dynamic scoring of tax reforms in the European Union (2016)
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:lmu:muenar:78244
Access Statistics for this paper
More papers in Munich Reprints in Economics from University of Munich, Department of Economics Ludwigstr. 28, 80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Tamilla Benkelberg ().