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The article examines factors of economic growth in Russia over more than a decade (2011–2021). The focus is on evaluating new factors, including specific ones, which have influenced the development dynamics of the period under review. Models of cyclic dynamics and macroeconomic factor models are used as research tools.The authors consider possibilities for estimating potential GDP using two approaches: through the selection and elimination of short-term cyclic fluctuations and based on the construction of factor models. The paper discusses the matter of substantiating potential GDP, taking into account changes in the ratio of factors that form it, including the external economic factor. It is noted that for a more detailed analysis of specific factors, there has to be a transition to monthly and quarterly data treatment, which is done using the example of cyclic dynamics models and factor models. The nature of the impact of specific factors by specified periods, including the post-crisis period of 2011–2014, the 2014 to 2017 period, when Western countries imposed sanctions, as well as the impact in 2020–2021 of the factor associated with the coronavirus pandemic, are revealed. To be specific, for the latest period of development of the domestic economy, the paper demonstrates how three waves of COVID-19 correlate with the three waves of its impact on economy. Meanwhile, despite the increase of the coronavirus waves up to the fourth wave, their direct and conjugated impact decreased exponentially. At the same time, the impact was differentiated by industry sectors. A number of industry sectors during this period gained a significant impetus to accelerate development, which will affect the subsequent change in the structure of production.Strengthening the role of new specific factors now enhances the relevance and need to apply and develop these methods, including the active use and development of import matrices as part of the input-output tables. In this regard, the authors consider some directions in development of methods for addressing new factors at the present stage.

The return of the economy to normal development conditions in the post-coronavirus period implies not only the understanding of the new content and the relationship between quality and growth dynamics but also the advancement of methods for analyzing and forecasting economic dynamics and growth factors at macroeconomic, inter-sectoral and sectoral levels. The article examines the possibilities of using two main research tools for these purposes: inter-industry models based on the Input-Output tables, and macroeconomic and industry factor models.The authors not only cover a long history of the application of classical models of this type but also demonstrate new directions of their use in solving specific tasks of analysis and forecasting in a market economy based on the analysis of a modern system of «Input-Output» tables and development of the investment and fixed assets block model. In addition, the development of macroeconomic analysis methods that can be implemented through the sharing of inter-industry and factor models is highlighted. Based on factor models evaluation, the authors identify unique characteristics of individual periods of development of the Russian economy in the first 20 years of this century, the evolution of dynamic trends and reveal the role of main economic growth factors, as well as anticipated limitations of these factors in the long-term period. Using the research findings and taking into account requirements of the new wave of technology, the conclusion is made about the crucial role of the growing investments in innovation and infrastructural sectors of the economy and enhancing the efficiency of investment activities, but this applies even more to improving the quality of human capital. Formalized and non-formalized aspects of its assessment are noted. The latter address the problems of training and nurturing highly-skilled specialists (doers), but above all of unlocking the creative potential of the young generation, which have yet to create a new technological and social structure. The article also proposes the solution for several instrumental and methodological issues related to the development and use of models of this type. It is shown that sharing of cross-sectoral models, macroeconomic and sectoral factor functions allow for a more comprehensive approach to the analysis and forecasting of the economy, it links growth factors to production, and reflects the direct and inverse relationship between demand and supply. Directions for modeling of the necessary fixed capital investments coupled with production dynamics, support of the production facilities and carry-over (incomplete) construction, which, are according to the authors, an important step towards building a dynamic cross-industry balance.