Catering to Environmental Premium in Green Venture Financing: Evidence from a Bert-Based Deep Learning Approach

Abstract

We apply a deep learning approach of Bidirectional Encoder Representations from Transformers (BERT) on the Crunchbase description of each venture and glossaries of environmentally related terms set out in the Global Reporting Initiative (GRI) Standards to identify “green ventures.” We find that pre-IPO investors cater to a higher environmental premium, measured by the log difference in the average market-to-book ratios of green and brown stocks, via increasing investments in green ventures in later financing stages. In particular, pre-IPO investors speed up the exit process to capitalize on the high environmental premium. In contrast, green ventures in seed financing rounds receive less funding, possibly due to capital, time, and effort constraints of the pre-IPO investors. Finally, we document that more experienced pre-IPO investors and those that are in closer proximity to green ventures are more responsive to the environmental premium.

Keywords: Catering, Environmental premium, Green ventures, BERT, Deep learning, Pre-IPO investors

JEL Classification: D22, G20, G23, G24, L26