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What drives green banking disclosure? An institutional and corporate governance perspective

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We examine the influence of regulatory guidance and other factors on the green banking disclosure practices of Bangladeshi commercial banks in the period from 2007 to 2014. We find that the issuance of green banking regulatory guidance by the Central Bank of Bangladesh in 2011 positively influences the level of green banking disclosure. We also report that green banking disclosure practices in the banking sector have converged over time and have become a routine process. In addition, we find that corporate governance mechanisms (e.g., board size and institutional ownership) positively affect the level of green banking disclosure. However, our study finds no relationship between the presence of independent directors on the board and green banking disclosure. These results have important implications for the government and other policy-makers.

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  1. For example, Bangladesh is likely to be the most vulnerable and affected country due to climate change (World Bank, 2013).

  2. A similar initiative was also undertaken by the Chinese Banking Regulatory Commission, commencing with the “green credit guidelines” in 2012, with the aim of encouraging banks to enhance their support for a green, low-carbon and recycling economy, thus decreasing environmental and social risks.

  3. These practices are also evidenced in the banks of developing countries. For example, the China Development Bank has provided US$45 billion in cheap lines of credit to solar and wind investments. Furthermore, the Brazilian Development Bank, the Banco Nacional de Desenvolvimento Econômico e Social, became a significant lender to Brazilian bio-fuels and wind projects, and was positioned second globally in identified clean energy deals during 2011 (Parkinson, 2012).

  4. More details are available at:, Accessed Mar. 26, 2017.

  5. The CAMELS rating refers to six factors used in assessing the bank’s performance which are as follows: capital adequacy (C), asset quality (A), management quality (M), earnings (E), liquidity (L) and sensitivity to market risk (S).

  6. Other in-house green activities include the use of e-statements for customers instead of paper statements; making online communications in the best possible manner; greater use of daylight instead of electric lights; using energy-saving bulbs such as LED lights; utilizing video/audio conferencing instead of physical travel; conversion of the bank’s vehicles to using compressed natural gas (CNG) as fuel; efficient use of printer cartridges, photocopier toner and office stationery; sharing information using electronic files, voice mail and email instead of paper memos; common use of table stationery instead of individual supplies; and use of both sides of sheets of paper.

  7. Thirty-nine Bangladeshi-domiciled banks operated from 2007 to 2009, 38 banks operated from 2010 to 2012, while 47 banks operated from 2013.

  8. These comprise four government commercial banks as well as nine new private commercial banks that started operation in the market after 2013 but are not yet listed on the stock exchange.

  9. Moreover, to ensure reliability in the data coding, two coders independently completed the content analysis of the annual reports at two time intervals. The first coder reviewed the entire sample of a banking firm’s annual reports and performed the coding process. The second coder then compared the coded data. All disagreements between the coders were ultimately addressed through re-visiting the annual reports and through consultation.

  10. We also divided the sample observations into two sub-sample periods that occurred after the 2011 issuance of the central bank’s regulatory guidance: 2011–2012 and 2013–2014.

  11. If the VIF is greater than 10, it is considered high (Greene, 2008). With the lowest VIF for all variables in our research model being 1.11 and the highest VIF of 6.69, this suggests that multicollinearity problems are unlikely in our regression models.

  12. To estimate the first stage of each research variable, based on prior research (de Villiers et al., 2011), we used firm size (FSIZE), profitability (ROA), growth (GROWTH), leverage (LEV), market-to-book ratio (MB), stock price volatility (VOL), liquidity (LIQUIDITY) and firm age (FAGE). GROWTH is measured as the percentage change in annual revenue; MB is measured as the ratio of the market value of equity to the book value of equity; VOL is the share price volatility computed from the daily stock returns; and LIQUIDITY is measured as the natural logarithm of the daily shares’ trading volume. All other variables are described in the “Empirical models and definitions of variables” section.

  13. Our argument was that a firm’s prior year’s decision to adopt and report on green banking activities might be able to influence the current year’s decision to adopt and report on green banking activities because withdrawal from this decision could signal to stakeholders that the firm was facing financial or managerial problems (Bose et al., 2017). However, this decision would not influence the extent of the current year’s disclosures.


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We would like to thank the two anonymous reviewers and Senior Editor Professor Seung-Hyun Lee for their helpful guidance throughout the review process.

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Correspondence to Afzalur Rashid.



Table 6 Green Banking Disclosure Index (GBDI)

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Bose, S., Khan, H.Z., Rashid, A. et al. What drives green banking disclosure? An institutional and corporate governance perspective. Asia Pac J Manag 35, 501–527 (2018).

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