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不良贷款能否有回收是其定价、日常管理和回收策略的决定因素之一,而宏观经济和处置时效则是影响不良贷款能否有回收的双重利刃。本文依据我国最大的不良贷款数据库——LossMetricsTM数据库,利用logistic模型族对清收时间跨度为2001-2008年的不良贷款零回收强度的动态变化影响因素进行了研究,并在研究中针对不同的样本分别建立了子模型和全模型,对多个模型的结果进行了对比。在全时间跨度模型中分析了GDP增速与零回收强度的直接关系;并把单笔贷款回收处置时间跨度分为小于12个月、12-22个月、23-60个月和超过60个月四组子样本,针对子样本分别建立模型,分析影响其各自零回收强度因素的区别。结果表明:GDP增速在大部分模型与零回收强度为显著负相关关系;在大部分子模型中不良贷款的有效抵质押因素显著,但在不同处置时间的子模型中显著情况有所不同。通过对零回收强度的研究可更好的结合宏观经济和处置时间来制订有效科学的回收策略。
The recovery of non-performing loans is one of the determinants of their pricing, routine management and recycling strategies, while the macroeconomy and the disposal of aging are the dual advantages that affect the recovery of non-performing loans. Based on the LOSSMetrics (TM) database, the largest non-performing loan database in China, this paper uses the logistic model family to study the factors influencing the dynamic changes of non-performing loans (NPLs) with a recovery period of 2001-2008 on a non-performing loan basis. The sub-model and full-model are respectively established, and the results of multiple models are compared. In the full-time span model, the direct relationship between GDP growth and zero recovery intensity was analyzed. The time span of single loan recovery and disposal was divided into less than 12 months, 12-22 months, 23-60 months and more than 60 Month four sub-samples, respectively, for the sub-sample models were established to analyze the impact of their respective zero recovery strength of the difference. The results show that the GDP growth rate is significantly negatively correlated with the zero recovery intensity in most models. In most sub-models, the effective collateral pensions of non-performing loans are significant, but the significant differences are found in the sub-models with different disposal times. Through the study of the strength of zero recovery can be combined with macroeconomic and disposal time to develop an effective and scientific recovery strategy.