Dynamic incentive contracts for ESG investing
Yuqian Zhang and
Zhaojun Yang
Journal of Corporate Finance, 2024, vol. 87, issue C
Abstract:
We develop a continuous-time model in which an ESG investor hires a manager to run a project and incentivizes the manager to fulfill ESG responsibilities. The manager’s private efforts and ESG investing determine the project’s cash flow and ESG performance subject to random shocks. We derive the optimal contract and its implementation after introducing carbon credits following the cap-and-trade program in practice. We provide comparative static analysis and empirical implications. The results demonstrate that ESG investing enhances contract efficiency. The more significant the carbon emission reduction, or the less the cost of ESG investing, the higher the contract efficiency, the average q, the marginal q, and the optimal investment–capital ratios, implying that ESG investing mitigates inefficiencies arising from information asymmetry and enhances investment values. Our model predictions are partially verified by empirical facts.
Keywords: ESG investing; Moral hazard; Dynamic contracts; Carbon credits; Contract implementation (search for similar items in EconPapers)
JEL-codes: D81 D82 E24 J41 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0929119924000762
Full text for ScienceDirect subscribers only
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:eee:corfin:v:87:y:2024:i:c:s0929119924000762
DOI: 10.1016/j.jcorpfin.2024.102614
Access Statistics for this article
Journal of Corporate Finance is currently edited by A. Poulsen and J. Netter
More articles in Journal of Corporate Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().