Research on ESG Investment Efficiency Regulation from the Perspective of Reciprocity and Evolutionary Game

Yinglin Wang (), Leqi Chen and Jiaxin Zhuang
Additional contact information
Yinglin Wang: Fujian Agriculture and Forestry University
Leqi Chen: Fujian Agriculture and Forestry University
Jiaxin Zhuang: Fujian Agriculture and Forestry University

Computational Economics, 2024, vol. 64, issue 3, No 12, 1665-1695

Abstract: Abstract According to the information disclosure quality and investment return efficiency of ESG enterprises, this paper establishes a dynamic incentive mechanism based on return regulation considering the reciprocal preferences of enterprises and investors. The strategy evolution path of ESG enterprises is explored from the perspective of external regulation in the investment market. The evolutionary game analysis of ESG investment returns in five scenarios shows that the increase in reciprocal preferences of investors and ESG enterprises will promote enterprises to make high efforts to improve the quality of information disclosure and credit rating behavior. However, with the increase of project return, the degree of reciprocity of investors should be appropriately adjusted, otherwise it is easy to cause speculation of ESG enterprises. In the case of heterogeneous returns, the effects of positive and negative incentives differ greatly, so the incentive mechanism should be set to match the return state of ESG investments.

Keywords: ESG investment; Reciprocal preference; Incentive mechanism; Evolutionary game (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10614-023-10494-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:kap:compec:v:64:y:2024:i:3:d:10.1007_s10614-023-10494-0

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-023-10494-0

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().