Different Shades of Green: Estimating the Green Bond Premium using Natural Language Processing

We document the existence of a premium in the green bond market based on the greenness of green bonds. Using BERT, a natural language processing method for textual analysis, we develop a novel measure for bonds’ greenness and document that a 10 percent increase in the bond’s greenness corresponds to a decrease in annualized yield by between 4.86 to 8.71 basis points. In addition to greener bonds enjoying higher premiums, we find evidence that issuing a green bond has positive spillover effects on the pricing of subsequent conventional bonds’ issuance. Overall, our findings are consistent with firms relying on 'green' debt instruments to lower capital costs and raise cheaper financing.

Keywords: Green bonds, BERT model, Sustainable Finance, Bond premium

JEL Classification: G12, Q56

Suggested Citation: Suggested Citation

Benincasa, Emanuela and Benincasa, Emanuela and Fu, Jonathan and Mishra, Mrinal and Paranjape, Adityavardhan, Different Shades of Green: Estimating the Green Bond Premium using Natural Language Processing (August 23, 2022). Swiss Finance Institute Research Paper No. 22-64, 2022, Available at SSRN: https://ssrn.com/abstract=4198065 or http://dx.doi.org/10.2139/ssrn.4198065