Optimal bond issuance with cost and liquidity constraints for Chinese local governments: a multi-period stochastic programming approach

In recent years, China’s local governments have issued numerous bonds to support the country’s economic development. However, as total debt accumulates, the pressure on debt repayments is gradually increasing. To increase the sustainability of local government debt, we propose a multi-period stochas...

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Vydáno v:Empirical economics Ročník 63; číslo 5; s. 2605 - 2632
Hlavní autoři: Yang, Ruicheng, Li, Li, Jiang, Qi, Qi, Ji
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2022
Springer Nature B.V
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ISSN:0377-7332, 1435-8921
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Shrnutí:In recent years, China’s local governments have issued numerous bonds to support the country’s economic development. However, as total debt accumulates, the pressure on debt repayments is gradually increasing. To increase the sustainability of local government debt, we propose a multi-period stochastic optimization-based approach to determining the portfolio composition of issued bonds, with the goal of minimizing the expected cost under the constraints of liquidity risk and cost deviation risk. Liquidity risk is measured by conditional payment-at-risk ( CPaR ), and cost deviation risk is measured by conditional value-at-risk ( CVaR ). By bounding CVaR and CPaR , local governments can control the levels of cost deviation risk and liquidity risk. To alleviate future liquidity risk, which is caused by the issuance of a large number of long-term bonds to deliberately reduce repayment pressure within a debt planning horizon, we consider an extended liquidity planning horizon to manage both current and future liquidity risk. Based on this, we analyze the efficient frontier and portfolio compositions of issued bond under the constraints of different CVaR and CPaR levels. Compared with actual Chinese local government bond portfolios, the efficient frontier performs better for different issuance strategies.
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ISSN:0377-7332
1435-8921
DOI:10.1007/s00181-022-02210-y