Assessing Local Government Debt Risks in China: A Case Study of Local Government Financial Vehicles

Abstract

Strong credit expansion in China after the recent global financial crisis has brought local government financial vehicles (LGFV) into the spotlight. Rapid growth of LGFV has triggered concern about local government indebtedness, banks ' asset quality and, more broadly, China's medium-term financial stability and sovereign risk. This paper constructs a unique firm-level dataset to evaluate the country's local government debt. We find an uneven distribution of LGFV, which are concentrated in the coastal areas, and a deterioration of their debt repaying ability from 2010 to 2012. We use principal component analysis (PCA) along with multivariate discriminate analysis (MDA) to identify the credit risk of LGFV based on conventional financial variables as well as local governments ' fiscal status. We also estimate the safe boundaries of debt bearing at the provincial government level. The estimations reveal more severe local government debt risks in the middle-western provinces and higher risks associated with LGFV at the municipal and county levels. Although it is very unlikely that there will be a national debt crisis in China, the high risk of LGFV should be noted and effectively controlled by improving the fiscal transparency of local governments and reforming the fiscal system.

Shanghai municipal investment corporation: Extending government power through financialization under state entrepreneurialism

“…In Western studies, scholars have stressed the disciplinary role of financial actors or financial rationales, which is overlooked in the literature of urban studies in China. The literature has only noticed local financial risks as local governments are tied to their financial intermediaries (Bai et al, 2016; Tao, 2015). For example, as chengtou are backed by local governments, the extensive financial activities of chengtou undermine the sustainability of local finance and local development (Chen et al, 2020; Pan et al, 2017).…”

Several explorations on how to construct an early warning system for local government debt risk in China

“…Faced with less than 15 years of local government debt data, Chinese scholars still made valuable explorations on the construction of EWS. Representatives are the BP neural network by Shi et al [ 24 ] and Hong and Liu [ 25 ], the principal component analysis along with a multivariate discriminate analysis by Tao [ 26 ], the CRITIC method combined with the grey relational analysis and TOPSIS method by Liu and Lu [ 27 ], the TOPSIS method with the Delphi method and SVM algorithm by Li et al [ 28 ], the fuzzy evaluation by Xu et al [ 29 ], the analytic hierarchy process (AHP) with an entropy method by Shen and Jin [ 30 ], and the grey prediction model along with the theory of risk energy release by Gao and Zhang [ 31 ].…”

“…Although previous studies have great enlightenments in constructing EWS for public debt risk, there are still some research gaps at the local government debt level, especially for China's local government debt risk. The research gaps are as follows: (1) In terms of local government debt statistics, previous studies mainly construct the EWS for explicit debt of local government; and limit the research object to local government bonds [1,4,29,32], or debt from local government financial vehicles [26,27], or both the two ones [17,28,30,31,33,34]. (2) In terms of early warning indicators, previous studies only select indicators from single and static perspectives.…”

From financial repression to financial crisis? The case of China

“…Financial distress in these firms and industries is so severe that the Economist Intelligence Unit (EIU) () reports that it would take 91 years and 74 years, respectively, for the coal and ferrous‐metal (including steel) smelting industries to pay back their debts. In addition, it is reported that certain local governments, particularly local governments in the Midwestern provinces or at the municipal and county level, face severe debt risks (Tao ). If a bank is exposed to such firms, industries, and regions, when the debtors’ financial situations worsen, it may be dragged into a financial disaster.…”