Legal certainty in taxation at authorities and courts of law: a nordic view of specialization and unbiasedness

Tjernberg Mats ()
Additional contact information
Tjernberg Mats: Professor in Public Law, Tax Law, Lund University

Nordic Tax Journal, 2016, vol. 2016, issue 1, 17-28

Abstract: Legal certainty is central to taxation decisions. This article describes the current legal situation and discussions in four Nordic countries. Sweden and Finland are specialized in dealing with taxation cases in administrative courts. In Denmark and Norway, no specialization exists in taxation cases. I maintain in this article that legal certainty would benefit from explicit signals from the state about the requirement of special knowledge and unbiasedness in authority and court decisions. These signals could well take the form of specialization in the courts. The need for specialized expertise is particularly extensive in tax law. It is also crucial for the agencies’ officials and judges to be aware that a subjective sense of unbiasedness in decision making does not necessarily mean that the unbiasedness aimed for has been attained. Self-awareness of this kind would ensure that argumentation and grounds for decisions would be made credible and transparent, to the benefit of legal certainty.

Keywords: tax; legal certainty; the Nordic countries; tax authorities; court; specialization; unbiasedness (search for similar items in EconPapers)
Date: 2016
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/ntaxj-2016-0001 (text/html)

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:vrs:notajo:v:2016:y:2016:i:1:p:17-28:n:2

DOI: 10.1515/ntaxj-2016-0001

Access Statistics for this article

Nordic Tax Journal is currently edited by Axel Hilling

More articles in Nordic Tax Journal from Sciendo
Bibliographic data for series maintained by Peter Golla ().