摘要
2005年至2021年,我国房地产政策经历了三轮“放松收紧”的过程。文章基于20082021年第三季度我国A股103家上市房企股票日交易数据和财务数据,运用KMV模型估算出违约距离以度量其违约风险,进一步采用面板模型在控制住房企微观因素的基础上分析了房地产调控政策对房企违约风险的影响。研究发现:从长周期视角看,房地产调控政策有利于降低房企违约风险,也有利于房地产市场健康平稳发展。异质性分析表明,调控政策存在明显的结构效应,调控政策对资产规模最大组别的风险抑制效果并不好,对民营企业和其他所有制性质企业产生负向效果,即会导致违约风险增加。除在政策层面继续坚持“房住不炒”精神、贯彻执行房地产金融审慎管理制度外,还应采取相应的结构性对策:一是针对大型房企应采取“一企一策”措施,防止资本无序扩张;二是监管层应鼓励银行按照运营效率、经营能力等指标开展房企贷款评估,减少放款过程中的所有制歧视现象。
From 2005 to 2021,China’s real estate policies have gone through three rounds of“loosening and tightening”processes.Based on daily trading data and financial data of 103 listed real estate enterprises in China’s A-share market in the third quarter of 20082021,this paper applies the KMV model to estimate the default distance to measure their default risk.At the same time,it uses panel model to analyze the impact of real estate regulatory policies on the default risk of real estate enterprises on the basis of controlling the micro-factors of housing enterprises.It is found that further analysis of real estate regulation policies from the perspective of long-term cycle is conducive to reducing the default risk of real estate enterprises and promoting the healthy and stable development of the real estate market.Heterogeneity analysis shows that there are significant structural effects in regulatory policies.The regulation policy does not have a good effect on the risk inhibition of the largest group of assets,and has a negative effect on private enterprises and other ownership enterprises,resulting in the increase of default risk.At the policy level,while continuing to adhere to the spirit of“housing without speculation”and implementing a prudent management system of real estate finance,we should also take corresponding structural measures.First,we should adopt a“one enterprise,one policy”approach for large real estate enterprises to prevent disordered capital expansion.Second,the regulatory authorities should encourage banks to conduct credit assessment for housing enterprises according to their operational efficiency,operating capabilities and other indicators,so as to reduce ownership discrimination in the lending process.
作者
蔡真
林菁
薄栋
CAI Zhen;LIN Jing;BO Dong(Institute of Finance and Banking,Chinese Academy of Social Sciences,Beijing 100710,China;School of Economics,University of Chinese Academy of Social Sciences,Beijing 102488,China;Guolian Securities Co.LTD,Wuxi 214003,China)
出处
《重庆邮电大学学报（社会科学版）》
2023年第5期115-127,共13页
Journal of Chongqing University of Posts and Telecommunications(Social Science Edition)
基金
中国社会科学院智库基础课题:房地产市场风险监测及对策研究
中国社会科学院创新工程:健全金融监管体制,防范系统性金融风险(2018JRSA01)。
关键词
房地产调控
房企违约风险
KMV模型
面板回归分析
real estate regulation
real estate enterprise default risk
KMV model
panel regression analysis
