TY - JOUR

T1 - Modelling sustainability efficiency in banking

AU - Tan, Yong

AU - Tsionas, Mike G.

N1 - This is the peer reviewed version of the following article:Tan, Y, Tsionas, MG. Modelling sustainability efficiency in banking. Int J Fin Econ. 2022; 27: 3754– 3772. doi: 10.1002/ijfe.2349 which has been published in final form at https://onlinelibrary.wiley.com/doi/10.1002/ijfe.2349 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

PY - 2022/7/31

Y1 - 2022/7/31

N2 - We significantly contribute to the empirical literature by investigating sustainability efficiency in the banking industry and decompose it into internal sustainability and external sustainability in an explicit manner. We fill in the gap of the literature by considering internal sustainability from two perspectives which are banking stability and economic performance. We also extend the current studies by including both banks' social contributions (contributions to the society and the company development) and environmental responsibility to the estimation of external sustainability. Finally, we fill in the gap of the literature by estimating the determinants of bank sustainability efficiency. The findings from the output distance function and the panel vector autoregressive model show that the sustainability efficiency level in the Chinese banking industry (2007–2017) ranges from 0.45 to 0.75 (maximum sustainability efficiency score is 1 and minimum sustainability efficiency score is 0). There is a larger difference in terms of external sustainability efficiency in the sample, while stability is still one of the most serious issues, as reflected by the low stability efficiency score compared to other efficiency concepts. The results also show that internal sustainability efficiency is significantly affected by the firm specific determinants, business environment determinants and economic environment determinants.

AB - We significantly contribute to the empirical literature by investigating sustainability efficiency in the banking industry and decompose it into internal sustainability and external sustainability in an explicit manner. We fill in the gap of the literature by considering internal sustainability from two perspectives which are banking stability and economic performance. We also extend the current studies by including both banks' social contributions (contributions to the society and the company development) and environmental responsibility to the estimation of external sustainability. Finally, we fill in the gap of the literature by estimating the determinants of bank sustainability efficiency. The findings from the output distance function and the panel vector autoregressive model show that the sustainability efficiency level in the Chinese banking industry (2007–2017) ranges from 0.45 to 0.75 (maximum sustainability efficiency score is 1 and minimum sustainability efficiency score is 0). There is a larger difference in terms of external sustainability efficiency in the sample, while stability is still one of the most serious issues, as reflected by the low stability efficiency score compared to other efficiency concepts. The results also show that internal sustainability efficiency is significantly affected by the firm specific determinants, business environment determinants and economic environment determinants.

KW - OR in banking

KW - particle-filtering

KW - sequential Monte Carlo

KW - sustainability

U2 - 10.1002/ijfe.2349

DO - 10.1002/ijfe.2349

M3 - Journal article

VL - 27

SP - 3754

EP - 3772

JO - International Journal of Finance and Economics

JF - International Journal of Finance and Economics

SN - 1076-9307

IS - 3

ER -