Artikel

Economic policy uncertainty and executive turnover

This paper examines whether economic uncertainty increases executive turnover. The negative perception perspective and business change theory suggest that executives are more likely to leave their jobs during periods of corporate distress. However, the additive effects of internal and external risk are thought to prompt firms to carefully consider executive turnover, thereby reducing the likelihood of executive changes. Based on the literature, we propose a check-and-balance hypothesis for the relationship between external uncertainty and executive change, according to which the optimal superposition of the internal and external risks stemming from increased external uncertainty would be to avoid a wave of executive departures. Using a sample of Chinese A-share listed companies from 2010 to 2019 and the China economic policy uncertainty index of Baker et al. (2013), we examine the impact of economic policy uncertainty on executive turnover and our results support the check-and-balance hypothesis. Our findings enhance our understanding of how economic policy uncertainty affects executive turnover, and enrich the literature on corporate risk management and strategic management.

Language
Englisch

Bibliographic citation
Journal: China Journal of Accounting Research ; ISSN: 1755-3091 ; Volume: 14 ; Year: 2021 ; Issue: 1 ; Pages: 83-100 ; Amsterdam: Elsevier

Classification
Management
Subject
Economic policy uncertainty
Executive turnover
Risk taking
Director-manager duality

Event
Geistige Schöpfung
(who)
Huang, Hong
Liu, Haiyu
Yang, Baohua
Event
Veröffentlichung
(who)
Elsevier
(where)
Amsterdam
(when)
2020

DOI
doi:10.1016/j.cjar.2020.11.003
Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Huang, Hong
  • Liu, Haiyu
  • Yang, Baohua
  • Elsevier

Time of origin

  • 2020

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