Debt Risk of Green Bonds Issued by Local Governments in Shandong Province Based on KMV-Logistics Mixed Early Warning Model

Abstract

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In recent years, China’s green development has entered a new stage with profound changes in development conditions. Progress in development has put forward higher requirements for the safe and stable operation of the financial and economic environment. This paper predicts the default probability of the scale of green bond debt that should be repaid by municipal governments in Shandong Province from 2020 to 2022 and combines the KMV-Logistics mixed model to provide new ideas for the existing local government debt early warning indicator system. This paper draws the following main conclusions: On the whole, it is predicted that the debt situations faced by local governments in Shandong Province in issuing green bonds from 2020 to 2022 are as follows: the municipalities with high debt risks in 2020 include Dezhou, Liaocheng, and Zaozhuang; the cities with high debt risk in Shandong Province in 2021 include Linyi, Heze, Dezhou, and Weihai; the cities in Shandong Province with high debt risk in 2022 include Dezhou, Heze, Rizhao, and Zaozhuang, among which, Zaozhuang and Dezhou have been in high-risk states for three consecutive years. Therefore, in order to reasonably control the debt risks faced by local governments in Shandong Province issuing green bonds, it is necessary to take multiple measures to strengthen the supervision of local government debt borrowing methods, dynamically monitor and prevent local government debt risks, and effectively strengthen the management of local government debt funds.

Keywords

• green bond debt risk warning
• KMV model
• principal component analysis
• logistics model
• risk handling