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 triggered by external unforeseen supply and demand shocks, as in the case of the COVID-19 pandemic. The article also 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 article aims to adapt existing methods of macro-level stress testing for their use based on the 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 of the study, forecasts of the dynamics of indices were obtained as a reaction to four possible shock scenarios: short-term, V-, W-, and U-shaped. Moreover, for each of the scenarios, cases of shocks from the side of demand, production and their simultaneous impact are presented.The conclusions based on the results of this study point to the key role of demand in the dynamics of all the considered indices and to the relatively greater sensitivity of the employment index in relation to the demand index and the finance index in relation to the production index. W-shaped shock was the worst of the four scenarios considered.Conclusions based on the study results indicate the vital role of demand in the dynamics of all the indices under consideration, the Wshaped shock, as the worst of the considered scenarios, as well as the relatively higher sensitivity of the employment index to the demand index and the finance index to the production index.
The purpose of the article is to analyze the technological expectations of managers of Russian enterprises from the manufacturing industry in the face of changes in the external economic environment. Firstly, the authors have calculated a specially developed «index of fulfillment» of technological expectations, reflecting the ratio of the expectations of the introduction of digital technologies formed in the previous period and an increase in the real level of implementation. Secondly, using regression analysis, the authors investigated the mechanisms of the formation of technological expectations of managers in various conditions: non-crisis 2018, pre-crisis 2019, and crisis 2020. The influence of the three mechanisms was tested in intertemporal context: the «inertial» one, which presupposes the preservation of the expectations formed in the past in the current period; «adaptive» which involves adjusting expectations in accordance with the current dynamics of technology implementation; «predictive» which implies the connection of expectations with the future level of implementation.The basis for empirical calculations was the data of annual business tendency surveys of digital activity of Russian manufacturing enterprises for 2018–2020. The aggregate sample of surveyed enterprises for three years included more than 3000 enterprises from 23 manufacturing industries. The paper studied patterns of implementation of 19 digital technologies, most of which, according to specialists, belong to Industry 4.0.The results obtained indicate that technological expectations are characterized by great heterogeneity in terms of feasibility. Regression analysis showed that all three identified mechanisms can play a role, but their influence varies. In particular, when a crisis occurs, the adaptive mechanism plays a key role, and the inertial mechanism becomes irrelevant.The results of this study indicate that Russia is characterized by the initial and transitional nature of digital transformation in the manufacturing industry, with technological development achieved through «breakthroughs» rather than a steady process of modernization. The main conclusion of the work is that external uncertainty greatly affects the evolution of technological expectations, destroying their continuity from previous plans and negatively affecting the predictive capabilities.
The article presents results of analysis of the predictive potential of short-term forecast estimates of employment level in the small business segment by four sectors of the Russian economy: manufacturing, construction, wholesale and retail trade.From the authors’ point of view, one of the promising sources of data for such estimates can be found in market observations of entrepreneurial activity, which now are a common source of economic information in national as well as international practice. These surveys play an important role in measuring the dynamics of employment in countries and industries, being a supplementary statistical tool.The objective of the work was to prove the existence of a stable statistically significant relationship between the predicted estimates of employment based on business (market) surveys and the dynamics of the corresponding statistical macro-aggregates in various sectors, and applicability of predictive models of employment change based on results of business (market) surveys.The novelty of the presented results (authors’ contribution) resides in the fact that for the first time, using an expanded sample (over 14 thousand respondents), were studied the possibilities of predicting labour market indicators in small businesses based on leading data from business surveys, examining separately retail trade, wholesale trade, construction, and manufacturing. According to the results obtained based on the Granger causality and pseudo-out-of-sample analysis, in all the industries under consideration, entrepreneurial assessments and expectations are effective predictive indicators for forecasting employment dynamics in the short term (two to four months) and identifying turning points in employment growth in the small business segment. The most sensitive predictive estimates were found in the retail and wholesale sectors, with the best results obtained for wholesale trade. For this reason, the authors recommend using the employment expectations indicator primarily in these sectors to monitor the level of employment and unemployment.
This paper presents the results of measuring cross-sectoral economic and technological effects, allowing to determine the degree of dependence between the segments that produce digital technologies and implement them. The basis for empirical calculations was the survey data of leaders among Russian IT companies and retail organizations on the current state of digital and business activity.The purpose of the work is to identify the presence and establish the strength of the relationship between these segments in terms of existing localized industry effects, expressed in the transfer of technology from the IT segments to retail. The authors of the work identified and tested several specific hypotheses, the general meaning of which was to suggest that retail trade in the current stage of economic development in Russia is susceptible to emerging trends in the rapidly changing IT services sector that can quickly and efficiently respond to the growth of the IT companies digital activity by increasing investments in digital technologies and increasing the intensity of their application in business processes.In particular, hypotheses were tested regarding the impact of business activity in the IT services segments on the growth of electronic commerce turnover, the use of online marketplaces, Big data technologies, virtual and augmented reality technologies in retail trade organizations, as well as hypotheses suggesting a connection between the development of mobile applications in the IT segments and the use of mobile technologies, expectations regarding the growth of electronic goods turnover in retail organizations.The obtained results confirmed the majority of the hypotheses put forward, thereby supporting the authors' general assumption about the existence of specific effects of the development of the IT segments on intersectoral technological transfers, revealed the existing specifics of penetration and spread of modern technological trends in trade, and also showed that the IT is currently important component in the process of digital transformation of Russian retail trade organizations.
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