Journal of Economics Finance and Administrative Science (Jun 2019)

Should banks be averse to elections? A GMM analysis of recent elections in Ghana

  • Mohammed Yaw Broni,
  • Mosharrof Hosen,
  • Hardi Nyagsi Mohammed,
  • Ganiyatu Tiamiyu

DOI
https://doi.org/10.1108/JEFAS-03-2018-0029
Journal volume & issue
Vol. 24, no. 47
pp. 47 – 65

Abstract

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Purpose - Actions of incumbent politicians and firms’ managers during election years have been cited as sources of many problems that afflict economies and business entities. Given the controversies surrounding the impact of elections on firms’ soundness, this paper poses a question of whether banks should be averse to elections. Specifically, this study aims to investigate the impact of elections on the profitability and efficiency of banks. Design/methodology/approach - Based on the authors’ knowledge, this is maiden analysis in this context for Ghana where relatively advanced appropriate GMM technique has been used on annual data from 2012 to 2016. Findings - This study reveals that banks make higher returns in election years. Additionally, the authors report that government’s economic policies in election years are detrimental to management efficiency, though insignificant. Practical implications - From an emerging economy perspective, this study would guide policymakers in designing policies that respond to, or minimize, the impact of elections on bank performance. The result of this analysis would also substantiate the market reaction to the changes in the economic, political and financial conditions. Originality/value - This analysis suggests that firms’ performances in an election year depend on policies and political institutions in place. The authors argue that Ghana, with its exemplary democratic credentials and strong institutions, living alongside a high perception of corruption, is different. The contribution to literature is, first, by limiting this work to the banking sector of Ghana and, second, by incorporating the behaviors of incumbent governments and individuals in the regression specification model.

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