Scenario forecasting of the dynamics of Russian production technologies using spatial SAR models

Abstract

Relevance. The development and implementation of advanced production technologies are the most important factors of economic growth and competitiveness in the modern economy. Predicting their dynamics, taking into account the spatial features of localization, is a difficult and time-consuming task. The spatial effects resulting from the impact of the surrounding territories play a significant role in the dynamics of advanced production technologies in the regions of Russia. Accounting for these effects is necessary when constructing scenario models in conditions of strong spatial heterogeneity of the studied processes. Traditional forecasting methods do not take into account spatial interdependencies and are not able to reflect the influence of surrounding regions on the development of technologies. Research objective. Assessment and scenario forecasting of the dynamics of advanced production technologies being developed in the regions of Russia using SAR models that allow taking into account spatial effects between regions. Data and methods. For scenario forecasting of the dynamics of advanced production technologies being developed in the Russian regions, taking into account spatial effects, a methodological approach was developed based on the modeling of the spatial log (SAR) of the processes of their development, autoregressive (ARMA) modeling and forecasting of the key factors of their dynamics. Taking into account spatial effects and heterogeneity, the proposed approach to modeling makes it possible to more accurately predict the dynamics of advanced production technologies in the Russian regions. Results. The developed methodological approach was tested to form predictive scenarios for the dynamics of advanced production technologies being developed in the regions of Russia. In particular, an inertial forecast scenario was developed, assuming the preservation of current trends in the dynamics of the technologies being developed, as well as two extreme possible scenarios – optimistic and pessimistic. With the help of the spatial SAR model, a significant influence of the number of research organizations on the volume of advanced production technologies generated was confirmed, and in the second group of regions, the influence of the number of technicians who conduct research and development was confirmed. The novelty of the study is to take into account the spatial features of the localization of the advanced production technologies being developed, as well as the spatial effects resulting from the impact of the surrounding regions on the creation of new technologies. This approach makes it possible to significantly reduce errors in the formation of forecast scenarios in conditions of significant spatial heterogeneity of the initial data. Conclusions. To intensify the generation of new technologies in the regions of the second group, it is necessary to attract personnel with technical specialties. The dynamics of the technologies being developed in the first group of regions with a powerful research potential are also influenced by the number of research personnel and the amount of attracted financial resources for fundamental and applied research. To increase the activity of these regions in the development of advanced technologies, it is necessary to form and develop relationships with the surrounding regions.