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Стресс-тестирование в статистическом моделировании деловой активности в условиях шоков конъюнктуры
The authors proposed an original method of stress testing in statistical modeling of business activity based on the results of business tendency surveys to study possible scenarios for the development of crisis dynamics triggered by external unforeseen supply and demand shocks, as in the case of the COVID-19 pandemic. In addition, the article provides an overview of existing approaches in the field of stress testing and the construction of stress indices with an emphasis on methods based on vector autoregressive models and their various modifications. Thus, the aim of the article is to adapt existing methods of macro-level stress testing for their use on the basis of results of business tendency surveys.
The basis for empirical calculations was the data from business tendency surveys of the leaders of Russian manufacturing enterprises, reflecting their combined estimates of the current state of business activity. The methods used in the article included: firstly, the formation of four composite indices based on the results of business tendency surveys from 2008 to March 2020, reflecting various aspects of business activity of enterprises: demand index, production index, financial index and employment index; secondly, the construction of the BVAR (Bayesian vector autoregression) model and its application for studying and comparing various forecast scenarios of index reactions to market shocks.
The results included forecasts of the dynamics of the indices with four possible shock scenarios implemented: short-term shock, V-shaped shock, W-shaped shock, and U-shaped shock. Moreover, for each of the scenarios, cases of a shock of demand, a shock of production, and a simultaneous shock of demand and production were separately presented.
Conclusions from the results of this study indicate the key role of demand in the dynamics of all the indices under consideration, the W-shaped shock, as the worst of the considered scenarios, as well as the relatively greater sensitivity of the employment index to the demand index and the finance index to the production index.