Hedging ambiguity with pro-social preferences: An illustration from green finance
The paper argues that pro-social preferences can offset ambiguity aversion in green finance by acting as a behavioural hedge. Using ambiguity-based investment models, the authors show socially motivated investors may accept uncertain green assets, lowering effective hurdle rates and supporting private capital flows into sustainable projects.
Please login or join for free to read more.
OVERVIEW
Introduction
The paper examines how pro-social preferences influence investment decisions under ambiguity in green finance. The authors argue that socially motivated investors may tolerate uncertain financial returns because social impact acts as a behavioural hedge against ambiguity. This may help explain continued investment in green projects despite regulatory uncertainty and funding gaps.
Literature review
The report combines ambiguity aversion theory with sustainable finance and impact investing research. Prior studies cited show investors can derive utility from social outcomes alongside financial returns, while ambiguity frameworks such as Gilboa-Schmeidler and Klibanoff-Marinacci-Mukerji explain precautionary behaviour under uncertainty.
The review notes that previous blended finance research focused mainly on structural de-risking. In contrast, this paper argues that behavioural preferences themselves can reduce perceived ambiguity and encourage investment in sustainable assets.
Model
The model assumes investors allocate wealth between a safe asset and a green project with ambiguous financial returns. Social impact returns are treated as risky but less ambiguous. Utility combines financial returns with social utility weighted by the investor’s pro-social preference intensity.
Using Gilboa-Schmeidler and Klibanoff-Marinacci-Mukerji ambiguity frameworks, the paper shows that strong pro-social motives can offset negative financial expectations and reduce effective hurdle rates for green investment.
The authors also introduce “dual asymmetry”, where mild ambiguity exists in social returns as well as financial returns. In this setting, investors hedge across both dimensions, reducing the overall ambiguity premium and increasing willingness to invest in uncertain green projects.
Main results
The analysis finds that pro-social preferences mitigate ambiguity aversion and increase investment in green assets. In the numerical example, the safe asset return is 0.9 while the worst-case green project return is 0.64.
Without pro-social preferences, no investment occurs. Once the pro-social preference parameter reaches approximately 1.2, investment becomes positive. At a value of two, the optimal allocation to the green project rises to about 45 per cent.
Introducing mild ambiguity in social returns increases the optimal allocation to around 50 per cent and lowers the ambiguity premium from 0.26 to 0.20. Under the Klibanoff-Marinacci-Mukerji framework, the ambiguity cost falls from approximately 0.04 to 0.025, increasing allocation to roughly 55 per cent.
Implications for green finance
The paper argues that pro-social preferences may help close green funding gaps by lowering ambiguity premiums and investment hurdles. It suggests blended finance structures and public guarantees may be more effective when targeted at investors with strong social motivations.
The report also highlights standardisation initiatives, including the Task Force on Nature-related Financial Disclosures, as mechanisms to reduce ambiguity around social outcomes and unlock additional private capital.
A calibration exercise estimates that a 10 per cent increase in pro-social intensity could reduce ambiguity costs by 15–20 per cent, potentially mobilising an additional USD200–300 billion annually for green projects globally.
Conclusion
The paper concludes that pro-social preferences act as a behavioural hedge against ambiguity in green finance, supporting investment in sustainable projects that conventional investors may avoid. The authors recommend future empirical testing using fund-level data and further research into how political and regulatory conditions influence ambiguity formation in green finance markets.