Non-standard Debt Contracts Default and the Pricing of Municipal Corporate Bonds
Promoting the market-oriented transformation of local government financing vehicles(LGFVs)is a crucial step in China's efforts to mitigate and manage local implicit debt risks.Over the past decade,LGFVs have played a pivotal role in financing infrastructure development and social welfare projects through the issuance of municipal corporate bonds(MCBs)and non-standard debt instruments,which contribute to regional economic growth and social development.However,since LGFVs primarily invest in public welfare projects that generate limited and unstable cash flow,they struggle to manage debt independently.As a result,local governments have accumulated significant implicit debts,while crowding out of financial resources has driven up private sector financing costs,posing threats to China's high-quality economic development.Although MCBs have not experienced any substantial defaults in recent years,frequent defaults on non-standard debt contracts of LGFVs have aroused wide attention.On one hand,such defaults severely destabilize financial markets.On the other hand,they shake investors'rigid payment expectations,leading to the re-pricing of LGFV formal debts,i.e.,MCBs.The non-standard debt default events promote the market-oriented transformation of LGFVs,accelerate the exposure of implicit debt burdens on local governments,and curb excessive local government borrowing.Based on data on MCB issuance and non-standard debt defaults by LGFVs from 2015 to 2022,this paper uses a multi-period difference-in-differences(DID)model to assess the impact of LGFV non-standard debt defaults on MCB pricing and the market-oriented transformation of LGFVs in China.The findings reveal that after the first occurrence of non-standard default in a region,the issuance spread of MCBs by local LGFVs rises sharply.This effect is more pronounced in areas with strong implicit guarantee expectations and heavy reliance on real estate investment.The mechanism analyses indicate that non-standard defaults speed up the exposure of LGFVs'credit risks,reducing investors'reliance on implicit guarantees and incorporating these risks more accurately into MCB pricing.These changes help correct the long-standing overpricing of MCBs and effectively activate market-based pricing mechanisms.Additionally,non-standard defaults have prompted LGFVs to lower operational risks and improve investment efficiency.Further analysis shows that non-market-oriented bailouts by local governments after non-standard default events may reinforce investors'rigid payment expectations,further distorting MCB pricing.The findings offer valuable empirical support for China's market-based debt resolution policies since 2023.This study makes contributions from three perspectives.Firstly,this paper sheds light on the market-oriented transformation of LGFVs by examining how non-standard debt defaults influence their financing costs.The analysis clarifies the short-term and long-term economic consequences of credit risk exposure for these entities.Secondly,the study offers valuable insights for academia,related industries,and regulators by addressing the challenge of disentangling bond pricing from issuers'fundamentals and macroeconomic conditions,given the implicit guarantee premium.This paper quantifies the implicit cost of rigid payment expectations and demonstrates how non-standard defaults affect MCB pricing and its long-term impact.These findings provide fresh perspectives on assessing LGFV risks and offer practical policy guidance for local governments in debt resolution and risk management.Thirdly,this paper focuses on the unique characteristics of LGFVs and the risks tied to non-standard debt defaults,which is an area underexplored in existing literature.Developing a theoretical framework and providing empirical evidence,this paper bridges a critical gap and lays the foundation for future studies in this field.
non-standard debt contracts defaultmunicipal corporate bondsissuance spreadoverpricinglocal government financing vehicles
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NSTL
万方数据
