The impact of board characteristics on classification shifting: evidence from Germany

Muhammad Usman*, Rami Salem, Ernest Ezeani, Bilal

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Purpose: This paper aims to examine the relationship between board characteristics (BCs) on classification shifting (CS) among listed non-financial German firms. 

Design/methodology/approach: Using 870 firm-year observations of German non-financial firms from 2010 to 2019 listed on DAX, MDAX and SDAX index, this paper examines the relationship between BCs (board size [BS], board meetings [BM], board independence [BI] and board gender diversity [BGD]) and CS. .

Findings: This study found that managers of German firms use CS and move recurring expenses to non-recurring expenses to inflate their core earnings. Also, this study found that BCs including BS, BI and BGD have a mitigating effect on CS practices of German non-financial firms. However, the number of BMs does not influence earnings management.

Practical implications: This paper recommends that German firms’ board must be constituted with more independent members and female representation because these board mechanisms help to curb CS.

Originality/value: The focus of this study is Germany, which is a bank-oriented economy with low transparency and investor protection. This paper provides new evidence on how BCs impact CS among German firms, whereas previous CS studies focused mainly on market-oriented economies like the USA and the UK.

Original languageEnglish
Pages (from-to)565-582
Number of pages18
JournalInternational Journal of Accounting and Information Management
Volume30
Issue number5
Early online date15 Sept 2022
DOIs
Publication statusPublished - 30 Sept 2022

Keywords

  • Board characteristics
  • Classification shifting
  • Corporate governance
  • Earnings management

ASJC Scopus subject areas

  • Management Information Systems
  • Accounting
  • Economics, Econometrics and Finance(all)

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