The article deals with the methodological issues of data preparation for the human capital block of the dynamic input-output model of the Russian economy and analyzes the results of a long-term forecast prepared based on this model.
The study reviews approaches to macro-economic and macro-territorial modelling presented in international and Russian economic publications. We focus on opportunities to improve forecasting the development of economic system in Russia at the macro-economic, inter-sectoral and inter-regional levels. We described dynamic macro-economic, inter-sectoral and inter- regional models developed in the Institute of Economics and Industrial Engineering of the Siberian Branch of the Russian Academy of Sciences (IEIE SB RAS). We analyse more in details three complex models proposed in IEIE SB RAS: CAISI (comprehensive analysis of inter-sectoral information), SRNES (synthesis of regional and national economic systems) and CSNES (coordination of sectoral and national economic solutions). We consider theoretical foundations of the complex models and their application in analysing and forecasting economic system development at various levels. The three complex models are based on different basic models that influence their development. IEIE SB RAS has been developing a two-level system of forecasting models, which combines advantages of dynamic stochastic general equilibrium models and dynamic input-output models applied in the CAISI system. The paper describes theoretical foundations of the SRNES system, whose latest versions are premised on the general equilibrium and cooperative games theories. Then, we characterised the most developed elements of the complex model CSNES, which has the CSNES-TEK subsystem used in forecasting developments in the fuel and energy industry of Russia’s territories and SIBARP (balance calculation system for the future). The conclusion outlines directions for further research on improving the methods of macro-economic, inter-regional, and inter-sectoral forecasting based on harmonisation of analytical and forecast calculations performed using the CAISI, SRNES and CSNES systems. The results of forecast calculations using the two-level system of macro-level models can be applied in the complex models SRNES and CSNES to ensure coordination between the forecasts of socio-economic development of the Asian part of Russia and projected dynamics of macro-indicators.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.