Summary:
Green finance is an important strategy for establishing a more ecologically sustainable civilization, according to the 19th CPC National Congress. As active participants in green credit policy, Chinese commercial banks play a crucial role in the relationship between economic growth and the environment. For commercial banks, cost efficiency, resource allocation, and risk control have a key impact on the national economy and social stability as a whole. Although green finance has attracted increasing public attention in recent years, the cost efficiency of the green credit policy remains under-studied. Therefore, this paper focuses on whether commercial banks sacrifice their original cost-efficiency targets in implementing the green credit policy, and whether this policy can result in a win-win situation. We discuss the cost efficiency of the green credit policy from the perspective of resource allocation. The paper analyzes the mechanism of cost effects, credit risk management and reputation, respectively, based on relevant economic theories and academic references, and it offers three hypotheses, as follows: H1: Green credit policy can lower banks' cost efficiency by way of the cost effects mechanism. Compared with normal loans, green credit increases environmental audit costs, incurs the cost of training personnel in both ecology and finance, and leads to opportunity costs from transferring loans to green industries (Hu and Zhang, 2016; Ma and Jiang, 2009). Therefore, even if the balance for green credit increases, the profits will be eaten up due to increasing costs. H2: Green credit policy has a positive impact on bank cost efficiency through the credit risk management mechanism. Commercial banks continuously optimize their risk management tools and adjust credit structures when they implement green credit policy to boost green industries and industrial structures and guide reasonable resource allocation. They can also include environmental risk factors in credit rating systems to avoid bank losses. H3: Green credit policy has a positive impact on bank cost efficiency through the reputation mechanism. Previous research finds that having a reputation for environmentally responsible behavior makes companies more competitive (Ma and Jiang, 2009). Bank competitiveness is strengthened by the brand effect and product differentiation of the green credit policy, and, at the same time, the social contribution ratio can be elevated by increasing the credit inputs of green industries for the fullest positive effect of the reputation mechanism (Liu et al., 2017). The paper samples data from 73 Chinese commercial banks during the period 2005-2017. First, it uses the stochastic frontier approach to measure bank cost efficiency. Second, it uses the propensity score matching difference-in-differences method to empirically analyze the net effects of green credit policy on bank cost efficiency. Third, it examines trends in the net effects of green credit policy by applying the marginal dynamic test method. Lastly, it confirms the hypothesis that the green credit policy will lower cost efficiency due to cost effects while also having positive effects that result from credit risk management and the reputation mechanism. Furthermore, we find that the net effects of the green credit policy have a U shape: the negative net effects of the policy worsened from 2007 to 2013 but have flattened out since 2014. Therefore, the gains will overcome the losses by implementing the policy with positive credit risk management and the reputation mechanism in the long run. Several major suggestions are made based on these empirical results. First, commercial banks should develop their information disclosure system for green credit to reduce the relevant costs, such as setting up a unified information management platform linking the central bank, the China Banking and Insurance Regulatory Commission, the environmental sector and commercial banks. Second, commercial banks should enhance credit risk management by improving the legal system of green finance and establishing collateral agencies. Lastly, commercial banks should engage in green finance to improve their reputation, such as by establishing internal green credit systems according to the Equator Principles and taking environmental risk into consideration when pricing loans.
丁宁, 任亦侬, 左颖. 绿色信贷政策得不偿失还是得偿所愿?——基于资源配置视角的PSM-DID成本效率分析[J]. 金融研究, 2020, 478(4): 112-130.
DING Ning, REN Yinong, ZUO Ying. Do the Losses of the Green-Credit Policy Outweigh the Gains?A PSM-DID Cost-Efficiency Analysis Based on Resource Allocation. Journal of Financial Research, 2020, 478(4): 112-130.
Aizawa Motoko and Yang Chaofei. 2010.“Green Credit, Green Stimulus, Green Revolution? China's Mobilization of Banks for Environmental Cleanup”,Journal of Environmental Management,19(2):119~144.
[24]
Akhigbe,A, J.E. McNulty .2003. “The Profit Efficiency of Small US Commercial Banks”, Journal of Banking & Finance, 27(2):307~325.
[25]
Altunbas Y., E.P.M. Gardener, P. Molyneux and B. Moore. 2001. “Efficiency in European Banking”,European Economic Review, 45(10):1931~1955.
[26]
Biswas Nigamananda. 2011. “Sustainable Green Banking Approach: The Need of the Hour”,Business Spectrum, 1(1):32~38.
[27]
Cilliers J E., Diemont Emma, Derk-Jan Stobbelaar and Wim Timmermans. 2011.“Sustainable Green Urban Planning: the Workbench Spatial Quality Method”,Journal of Place Management and Development , 4(2):214~224.
[28]
Guo Peiyuan. 2014. “Financial Policy Innovation for Social Change: a Case Study of China's Green Credit Policy”,International Review of Sociology, 24(1):69~76.
[29]
King G. Robert and Levine Ross. 1993. “Finance and Growth: Schumpeter Might Be Right”,Quarterly Journal of economics, 108(3):717~737.
[30]
Maudos,J.,J.M.Pastor, and J. Quesada.2002.“Cost and Profit Efficiency in European Banks”,Journal of International Financial Markets, Institutions and Money,12(1):33~58.
[31]
Rime, B. and K.J. Stiroh. 2003. “The Performance of Universal Banks: Evidence from Switzerland”,Journal of Banking & Finance, 27(11):2121~2150.
[32]
Rosenbaum, P.R. and D.B. Rubin. 1985. “Constructing a Control Group Using Multivariate Matched Sampling Methods that In-corporate the Propensity Score”,American Statistician,39 (1): 33~38.
[33]
Rosenbaum, P.R., Rubin, D.B. 1983. “The Central Role of the Propensity Score in Observational Studies for Causal Effects”, Biometrika,70(1):41~55.
[34]
Sonia Labatt and Rodney R. White. 2002. Environmental Finance: A Guide to Environmental Risk Assessment and Financial Products , published by John Wiley and Sons.
[35]
Williams, C.A. 2013. “Regulating the Impacts of International Project Financing:The Equator Principles”,Proceedings of the ASIL Annual Meeting,107(2).