The effects of mandatory IFRS adoption and conditional conservatism on European bank values

Panayotis Manganaris, Charalambos Spathis and Apostolos Dasilas

Journal of International Accounting, Auditing and Taxation, 2015, vol. 24, issue C, 72-81

Abstract: This study examines the relationship between the value relevance of accounting information and the conditional conservatism of the European banking sector. Using a bank data set from 15 European countries we study the value relevance of accounting information before and after mandatory IFRS adoption, as well as the extent to which conditional conservatism and value relevance coexist in this context. Our findings suggest that conditional conservatism is positively (negatively) related to value relevance prior to (post) mandatory IFRS adoption. This finding validates the IASB's objectives of higher value relevance and lower conservatism. Additional analyses provide evidence that country-specific features not only affect the potential increase in accounting quality, but also the relationship between value relevance and conditional conservatism.

Keywords: Value relevance; Conditional conservatism; IFRS; Banking sector; Europe (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1061951815000075
Full text for ScienceDirect subscribers only

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:eee:jiaata:v:24:y:2015:i:c:p:72-81

DOI: 10.1016/j.intaccaudtax.2015.02.004

Access Statistics for this article

Journal of International Accounting, Auditing and Taxation is currently edited by R. Larson

More articles in Journal of International Accounting, Auditing and Taxation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().