Forecasting Economic Performance of Industries in Conditions of Shocks: A Case Study of Russian Data

The aim of the research is to modify the input–output balance methodology taking into account the specifics of Russian data by introducing partial demand functions for the products of the sectors. The article proposes an iterative algorithm for achieving the current economic and price equilibrium based on statistical data, which consists in selecting the parameters of demand functions for each industry and in calculating equilibrium prices until the convergence of model indicators with actual data is obtained. Model experiments were conducted using Rosstat data for 2020 under two scenarios, i.e., an increase in demand for construction and a rise in the exchange rate. Stimulating the construction industry leads to an increase in production in related sectors and their reorientation towards intermediate demand. The rise in US dollar exchange rate critically affects the production indicators of automobiles, textiles, electrical machinery, electronic and computer equipment, pharmaceuticals, furniture, and other most import-dependent industries causing prices in them to rise, while service industries remain stable. The analysis made it possible to identify industries with different price elasticity of demand. The most resilient to price shocks turned out to be services: social, education, healthcare, and public administration.