摘要
本文以财政收入预测数据、土地出让收入预算、GDP预测数据、当前债务余额期限结构为输入变量,流动性约束和债务风险指标约束为约束条件,构建出以遗传算法为核心的微观现金流模型以估算未来总体举债规模区间,并形成不同期限的发债策略组合。实证结果表明,该微观现金流模型有助于地方政府在约束条件下合理规划举债规模,从而帮助地方政府有效地进行债务管理。
Using fiscal revenue forecast data,land transfer revenue budget,GDP forecast data and the current debt balance maturity structure as input-variables,liquidity constraints and debt risk indicator constraints as constraints,this paper constructs a micro-cash flow model with genetic algorithm to estimate the range of the future overall debt scale and form a portfolio of bond issuance strategies with different maturities.The empirical study finds that the micro-cash flow model reasonably promotes the local government to plan the scale of borrowing under the constraint conditions and effectively enhances the debt management of the local government.
作者
林赛燕
LIN Saiyan(Digital Development Strategy Research Ceter,Party School of Zhejiang Provincial Committee of CPC,Hangzhou 310018,China)
出处
《财经论丛》
CSSCI
北大核心
2020年第12期33-39,共7页
Collected Essays on Finance and Economics
基金
浙江省哲学社科规划课题(19NDJC291YB)。
