ABSTRACT

This paper applies a Qual VAR approach to generate a continuous banking crisis indicator from an underlying latent variable using a Markov Chain Monte Carlo algorithm. Four decades of banking crises are assessed by accounting for the evolutionary nature of precursors, as measured through periodic, regional, and developmental effects using a representative sample of countries. Aggregate results from forecast error variance decomposition show that banking sector variables explain nearly half of total variation, external sector a third and real sector a fifth. Findings suggest that recursive out-of-sample forecasts up to 12-months preceding a banking crisis render vital early warning signals, and as based on quarterly data, support expeditious response times. In out-of-sample forecasting, the Qual VAR outperforms a probit model. Improved forecasting performance may assist banking oversight departments and support remediation efforts of policymakers to adequately and timeously respond to banking crises.

摘要

本文应用 Qual VAR 方法，使用马尔可夫链蒙特卡罗算法从潜在变量生成连续银行危机指标。四个十年的银行危机是通过考虑前体的演化性质来评估的，前体的演化性质是通过使用具有代表性的国家样本通过周期性、区域和发展影响来衡量的。预测误差方差分解的综合结果表明，银行业变量解释了近一半的总变化，外部部门占三分之一，实体部门占五分之一。调查结果表明，银行危机前长达 12 个月的递归样本外预测可提供重要的预警信号，并且基于季度数据，支持快速响应时间。在样本外预测中，Qual VAR 优于概率模型。