Classified Regulatory Policy and the Perform ance of Local Government Financing Platforms——Evidence from the Exit of Financing Platforms from List-based Management System
In order to categorize and transform local government financing platforms(LGFPs)and modernize China's financial governance,it is imperative to improve the performance of LGFPs.China has implemented a number of regulatory policies to standardize LGFPs'management and encourage the transformation of companies with stable operating income and cash flow.One important regulatory tool representing the classified regulatory policy is the China Banking Regulatory Commission's(CBRC)LGFP list-based management system.We employ the staggered difference-in-differences model to estimate the effect of CBRC's regulatory policy on the performance of LGFPs using manually collected data from 2010 to 2018,with the withdrawal from the list-based management system as a quasi-natural experiment.Additionally,we explore mechanisms through which classified regulatory policy influences the performance of LGFPs and the heterogeneous effects from the perspectives of regional marketization,debt ratio,credit rating,and business type of LGFPs.Our main findings are as follows.(1)Classified regulatory policy is conducive to promoting the performance of LGFPs.The aforementioned conclusion holds after a number of tests,including parallel trend tests,exclusion of samples from municipalities directly under the central government,exclusion of other policies,alternative estimation methods,and placebo tests.In terms of the calendar effect,this positive association becomes apparent primarily since 2015.(2)The classified regulatory policy significantly improves the performance of LGFPs located in more marketized provinces,as well as LGFPs with higher debt ratios,credit ratings,and operational business,but not conducive to improving the performance of LGFPs for public welfare activities.(3)The mechanism analysis demonstrates that the classified regulatory policy can promote the performance of LGFPs through revenue improvement,cost control and operating efficiency enhancement.(4)The extended analysis reveals that LFGPs have optimized the debt structure following their departure from the list-based management system,with an increase in the percentage of long-term debt but a loss in their long-term solvency.The conclusions carry significant policy implications.(1)The classified regulatory policy needs to be further improved in order to support LGFPs'development and transformation.(2)It is imperative to investigate multifaceted approaches to improve LGFPs'capacity for sustainable development and to encourage the transformation of their classification through performance-targeted assessment management.(3)It is crucial to strengthen the debt risk management of LGFPs,prevent and resolve such risks.We make three potential contributions to the literature.(1)This study assesses the impact of CBRC's regulatory policy on the performance of LGFPs from the perspective of classified regulation,providing empirical evidence for understanding the effectiveness of classified regulatory policy.(2)While most previous studies have focused on the causes of the debt risk of LGFPs and the impact of regulatory policies on their debt risk,we examine the impact of classified regulatory policy on the performance of LGFPs and explore its intrinsic mechanism.Moreover,we investigate the heterogeneous effects of classified regulatory policy from regional marketization,debt ratio,credit level,and business type of LGFPs.(3)The results of this study not only reveal the effectiveness of classified regulatory policy on the long-term development of LGFPs,but also examine the impact of classified regulatory policy on the debt scale and solvency of LGFPs.Our findings also provide insightful policy recommendations for further understanding the effectiveness of regulatory policies and accelerating the pace of classified transformation of LGFPs.
Classified RegulationLocal Government Financing PlatformList-based Management SystemStaggered Difference-in-differences Model
万方数据
