In this paper, we propose a method for real‐time prediction of recessions using large sets of economic and financial variables with mixed frequencies. This method combines a dynamic factor model for the extraction of economic and financial conditions together with a tailored Markov regime switching specification for capturing their cyclical behaviour. Unlike conventional methods that estimate a single common cycle governing economic and financial conditions or extract economic and financial cycles in isolation of each other, the model allows for a common cycle which is reflected with potential phase shifts in the financial conditions estimated alongside with other parameters. This, in turn, provides timely recession predictions by enabling efficient modelling of the financial cycle systematically leading the business cycle. We examine the performance of the model using a mixed frequency ragged‐edge data set for Turkey in real time. The results show evidence for the superior predictive power of our specification by signalling oncoming recessions (expansions) as early as 3.6 (3.0) months ahead of the actual realization.

中文翻译：

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实时预测经济衰退的经济和金融状况建模*

在本文中，我们提出了一种使用大量混合频率的经济和金融变量来实时预测衰退的方法。该方法结合了用于提取经济和金融状况的动态因素模型，以及用于捕获其周期性行为的量身定制的马尔可夫政权转换规范。与传统方法估计一个共同的经济和金融状况的共同周期或相互隔离地提取经济和金融周期的传统方法不同，该模型允许一个共同的周期，该周期反映了所估计的财务状况的潜在相移以及其他参数。反过来，通过启用对系统地领导业务周期的财务周期的有效建模，可以提供及时的衰退预测。我们使用针对土耳其的混合频率参差不齐的边缘数据集来实时检查模型的性能。结果通过在实际实现之前的3.6（3.0）个月内发信号通知即将发生的衰退（扩张），从而证明了本规范具有超强的预测能力。