金融学院知识库

       绿色信贷是绿色金融的重要组成部分，是我国实现可持续发展和“双碳”战略目标的重要手段。国内绿色信贷余额保持高速增长，有助于满足国内绿色经济和低碳发展的融资需求，实现双碳和高质量发展目标。对于重污染企业而言，绿色信贷政策的实施对其具有较大的影响，是一把双刃剑。近年来绿色信贷政策作为学界研究的热点，关于绿色信贷政策的研究，从微观层面来看，对于推动重污染企业转型升级具有实际意义，从宏观层面来看，为实现可持续发展和碳达峰、碳中和的战略目标提供经验借鉴。
       本文运用双重差分法，以2009年至2020年A股上市企业相关数据为样本，将重污染企业划分为实验组，非重污染企业划分为对照组，研究绿色信贷政策对重污染企业经营绩效的影响。本文创造性地将政策实施后的时间划分为短期和长期两个阶段，并对政策时段和企业的产权性质做了异质性分析。通过替换被解释变量、对模型进行安慰剂检验、PSM-DID等方法对模型的稳健性进行检验，并引入环保投入作为中介变量，对模型做中介效应分析。根据实证检验的结果，本文得出了以下三个结论：（1）绿色信贷政策在长期可以对重污染企业经营绩效产生正向影响，但是在短期内会产生负向影响。（2）绿色信贷政策对产权性质不同的重污染企业经营绩效影响不同，对于非国有企业的正向影响更大。（3）企业的环保投入强度在绿色信贷政策对重污染企业经营绩效的影响中具有部分中介效应。最后，本文根据已有的研究内容，从企业、银行和政府三个角度提出了相关政策建议。

     Green credit is an important part of green finance and an important means for China to achieve sustainable development and the "double carbon" strategic goal. The rapid growth of domestic green credit balances is conducive to meeting the financing needs of domestic green economy and low-carbon development, and to achieving the goals of dual carbon and high-quality development. For heavily polluting enterprises, the implementation of green credit policies has a significant impact on them, and is a double-edged sword. In recent years, green credit policy has become a hot topic in academic research. From the micro level, the research on green credit policy has practical significance for promoting the transformation and upgrading of heavily polluting enterprises. From the macro level, it provides experience and reference for achieving sustainable development, carbon peak, and carbon neutral strategic goals.
     This article uses the Difference-in-Differences method, using the relevant data of A-share listed companies from 2009 to 2020 as a sample, to divide heavily polluting enterprises into experimental groups and non heavily polluting enterprises into control groups, to study the impact of green credit policies on the operating performance of heavily polluting enterprises. This article creatively divides the time after the implementation of the policy into two stages: short-term and long-term, and analyzes the heterogeneity of the policy period and the nature of enterprise property rights. The robustness of the model was tested by replacing the explained variables, conducting a placebo test on the model, PSM-DID, and other methods. Environmental protection investment was introduced as an intermediary variable to conduct mechanism analysis on the model. Based on the results of empirical testing, this paper draws the following three conclusions: (1) Green credit policies can have a positive impact on the operating performance of heavily polluting enterprises in the long term, but will have a negative impact in the short term. (2) Green credit policies have different impacts on the operating performance of heavily polluting enterprises with different property rights, and have a greater positive impact on non-state owned enterprises. (3) The intensity of environmental investment by enterprises has a partial mediating effect on the impact of green credit policies on the operating performance of heavily polluting enterprises. Finally, based on the existing research content, this article puts forward relevant policy recommendations from the perspectives of enterprises, banks, and governments.