Identifying firms' tax loss carry-forward status: The accuracy of database-ariven methods

Martina Rechbauer

No 201, arqus Discussion Papers in Quantitative Tax Research from arqus - Arbeitskreis Quantitative Steuerlehre

Abstract: Due to data restrictions, empirical tax research commonly relies on database-driven methods as a means of identifying firms' tax loss carry-forward (TLCF) status. Employing a panel of listed Italian parent companies, I am the first to empirically examine the accuracy of database-driven methods in predicting the availability and the amount of TLCF at single-firm level. In order to assess the accuracy of database-driven identification methods, I compare firms' true TLCF status, as determined based on IFRS statement information, to the TLCF status predictions of the methods examined. I find that database-driven methods do not perform well in predicting the availability of TLCF. They perform poorly in predicting the amount of TLCF available to firms. Empirical studies that rely on database-driven identification methods might thus not be able to derive reliable results regarding the impact of TLCF. My findings thus indicate that there is a strong need for firm-specific TLCF information provided by local authorities in empirical tax research.

Keywords: identification; tax loss carry-forwards; database-driven methods (search for similar items in EconPapers)
JEL-codes: C81 H25 K34 (search for similar items in EconPapers)
Date: 2016
New Economics Papers: this item is included in nep-bec
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/129105/1/849551234.pdf (application/pdf)

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:zbw:arqudp:201

Access Statistics for this paper

More papers in arqus Discussion Papers in Quantitative Tax Research from arqus - Arbeitskreis Quantitative Steuerlehre
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().