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Asymmetric CEO confidence and CSR: A nonlinear panel ARDL-PMG approach

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  • Zribi, Wissal
  • Boufateh, Talel

Abstract

The aim of this paper is to elucidate the relationship between managerial overconfidence/underconfidence and corporate social responsibility including the three ESG (environmental, social and governance) factors. Using an asymmetric nonstationary panel model, we detect the overconfidence (under confidence) component through positive (negative) overinvestment (underinvestment) changes. The Shin et al. (2014) nonlinear ARDL approach in panel form is used to construct our asymmetric panel ARDL-PMG model, and a sample of 68 large French companies over the period 2006-2016 is used. The asymmetric results first prove that a manager’s behavior seems to impact CSR only in the long term. Our asymmetric results also prove that CSR reacts positively to both managerial overconfidence and under-confidence shocks; Regardless of the personal traits of their manager, large companies have to be socially responsible. We then focus on the relationship between these two behavioral biases on each CSR dimension. We find a significant and negative impact of under confident leaders on the environmental dimension but a nonsignificant impact of overconfident leaders. For the governance dimension, we detect a positive effect of managerial overconfidence and managerial under confidence. However, we find a negative impact of overconfident and under confident leaders on the social dimension of CSR. According to these asymmetric findings, recommendations have been given in terms of the CSR strategy.

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  • Zribi, Wissal & Boufateh, Talel, 2020. "Asymmetric CEO confidence and CSR: A nonlinear panel ARDL-PMG approach," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    • Handle: RePEc:eee:joecas:v:22:y:2020:i:c:s1703494920300232
    DOI: 10.1016/j.jeca.2020.e00176
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    3. Alves, P.R.L., 2022. "Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 480-499.

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