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Greening the Financial Sector: Evidence from Bank Green Bonds

  • Original Paper
  • Published: 07 December 2022
  • Volume 188 , pages 259–279, ( 2023 )

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  • Mascia Bedendo   ORCID: orcid.org/0000-0003-0611-0860 1 ,
  • Giacomo Nocera 2 &
  • Linus Siming 3  

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Turn green or lose ‘licence to operate’—Deutsche Bank CEO Christian Sewing (Olaf Storbeck, “Turn green or lose ‘licence to operate’, says Deutsche Bank chief,” Financial Times , May 20, 2021).

Banks are expected to play a key role in assisting the real economy with the green transition process. One of the tools used for this purpose is the issuance of green bonds. We analyze the characteristics of banks that issue green bonds to understand: (i) which banks are more likely to resort to these funding instruments, and (ii) if the issuance of green bonds leads to an improvement in a bank’s environmental footprint. We find that large banks and banks that had already publicly expressed their support for a green transition are more likely to issue green bonds. Conditional on being a green bond issuer, smaller banks tend to resort to green bonds in a more persistent manner and for relatively larger amounts, while larger banks issue green bonds on a more occasional basis and for smaller amounts. This heterogeneity is also reflected in our findings that only banks that issue green bonds more intensively improve their emissions and reduce lending to polluting sectors, thus contributing to the decarbonization of the financial sector.

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Our specifications in Columns III–VI do not include country fixed effects since the multinomial logit models suffer from the curse of dimensionality issue when dealing with a large number of fixed effects for these sample sizes, and fail to converge to a solution. This is also the reason why we are unable to include bank fixed effects or country-year fixed effects in our specifications, which could otherwise have served as effective controls for any time-varying environmental policies in different countries. However, the inclusion of country EPI and NDC already contains key information on the countries’ environmental and regulatory specificities.

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Acknowledgements

We are grateful to the editor, two anonymous reviewers, Özlem Dursun-de Neef and seminar participants at the University of Zurich, WHU Otto Beisheim School of Management, the Free University of Bozen-Bolzano, and conference attendants at the CGRM Conference in Rome, the FEBS Conference in Portsmouth, and the FMA European Conference in Lyon, for their helpful comments and useful suggestions. We thank Letizia Ricchiardi for excellent research assistance.

This study is funded by a CRC2021 Sustainability Grant from the Free University of Bozen-Bolzano.

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Mascia Bedendo

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Giacomo Nocera

Faculty of Economics and Management, Free University of Bozen-Bolzano, Universitätsplatz 1, 39100, Bozen, Italy

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Appendix 1: Event study around green bond announcements

In this appendix we perform an event study to test the stock price reaction of green bond issuers around the announcement of the issuance of green bonds. Our sample covers all green bonds issued by publicly listed banks worldwide between January 1, 2013 and October 31, 2020. The announcement dates of green bond issuances as well as the issuers’ daily stock prices are retrieved from Bloomberg. We use a one-factor market model to estimate the “normal” relation between stock and market returns since previous literature has shown that short-horizon event studies are not sensitive to the benchmark specification (Kothari and Warner, 2007 ):

where \({R}_{it}\) is the daily return on the common share of bank i on day t and \({R}_{mt}\) is the daily return on the MSCI World total return index on the same day. In line with Tang and Zhang ( 2020 ), the market model is estimated from 300 calendar days to 50 calendar days prior to the event date \(t=0\) , which coincides with the announcement date. We derive daily abnormal stock returns \({AR}_{it}\) as the difference between raw returns and returns estimated from the market model:

As in Tang and Zhang (2020) and Flammer ( 2021 ), we then compute cumulative abnormal returns \({CAR}_{i}\) for bank i around each event date by aggregating \({AR}_{it}\) from 5 days before to 10 days after (5 days before to 5 days after) the announcement date. The table reports the average CARs computed across the two event windows separately for first-time issues and subsequent issues, with t -statistics in parenthesis. Consistently with the findings from previous studies on corporate green bonds in general, we document, also in banks: (i) a positive stock price response following the announcement of the first green bond issuance; (ii) no stock price response following the announcement of subsequent green bond issuances. This is in line with the signaling argument, as the market learns about the bank’s commitment to green lending with the first-time issue, while the information content of subsequent issues is likely to resemble that of conventional bond issues (see the discussion in Tang and Zhang, 2020 , and Flammer, 2021 ).

  • ∗, ∗∗, and ∗∗∗ denotes significance at the 10, 5, and 1% level

Appendix 2: Variable definitions

Appendix 3: t -tests on treated and control samples.

  • This table reports summary statistics and t -tests for difference in means for treated (green bond issuers) and control (non-green bond issuers) banks from a matched sample. The matching is based on bank characteristics of bond issuers at year-end before the first green bond was issued. All variables are described in Appendix 2.
  • ∗, ∗∗, and ∗∗∗ denotes significance at the 10, 5, and 1% level, respectively.

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Bedendo, M., Nocera, G. & Siming, L. Greening the Financial Sector: Evidence from Bank Green Bonds. J Bus Ethics 188 , 259–279 (2023). https://doi.org/10.1007/s10551-022-05305-9

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Received : 01 May 2022

Accepted : 28 November 2022

Published : 07 December 2022

Issue Date : November 2023

DOI : https://doi.org/10.1007/s10551-022-05305-9

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