Nguyen Duc Trung, Oanh Tran Thi Kim, Bui Thanh Dan, Dao Le Kieu Oanh
Ho Chi Minh University of Banking, Ho Chi Minh City, Viet Nam.
University of Finance - Marketing, Ho Chi Minh City, Viet Nam.
Heliyon. 2024 Aug 22;10(16):e36639. doi: 10.1016/j.heliyon.2024.e36639. eCollection 2024 Aug 30.
This study examines the linkage of green finance and green growth under the regulatory role of green energy and green production in 52 countries worldwide from 2005 to 2019. Applying the Bayesian regression and GMM regression, the results of these two methods are similar. When ignoring the regulatory role of green energy and green production, green finance negatively impacts green growth. This result is entirely opposite when considering the regulatory role of green energy and green production, green finance impacts green growth positively. However, Bayesian regression is more effective when providing different posterior probability intervals and probability ranges for independent variables to affect the dependent variable. Specifically, the probability that green financial growth has a negative impact on green growth is above 75.86 %. Similarly, under the role of green energy, the probability that green finance growth has a positive impact on green growth is 80.45 % and under the role of green production, this probability is 76.64 %. These findings imply that countries should build a financial system associated with the goal of green energy and green production, thereby helping the economy become greener.
本研究考察了2005年至2019年期间，在全球52个国家绿色能源和绿色生产的监管作用下，绿色金融与绿色增长之间的联系。运用贝叶斯回归和广义矩估计回归，这两种方法的结果相似。当忽略绿色能源和绿色生产的监管作用时，绿色金融对绿色增长有负面影响。而在考虑绿色能源和绿色生产的监管作用时，结果则完全相反，绿色金融对绿色增长有积极影响。然而，当为自变量提供不同的后验概率区间和概率范围以影响因变量时，贝叶斯回归更为有效。具体而言，绿色金融增长对绿色增长产生负面影响的概率高于75.86%。同样，在绿色能源的作用下，绿色金融增长对绿色增长产生积极影响的概率为80.45%，在绿色生产的作用下，这一概率为76.64%。这些研究结果表明，各国应建立与绿色能源和绿色生产目标相关的金融体系，从而帮助经济实现更绿色发展。
