Forecasting of direct material costs in the national economy using the RAS method based on data extrapolation

https://doi.org/10.55214/25768484.v9i4.6287

Authors

  • V.J. Akhundov Research Laboratory of Intelligent Control and Decision Making Systems in Industry and Economics, Azerbaijan State Oil and Industry University, 20 Azadlig Avenue, AZ1010 Baku, Azerbaijan. https://orcid.org/0000-0001-7529-7142
  • I.S. Rustamov Faculty of Economics and Management, Azerbaijan State Oil and Industry University, 20 Azadlig Avenue, AZ1010 Baku, Azerbaijan. https://orcid.org/0000-0002-7300-9458

Stabilization and growth of the real sector of the economy require increased attention to the system of forecasting the development prospects of the country's economic sectors. In recent years, there has been an increase in interest in forecasting projects and methods related to forecasting industry, inter-industry, and interregional relations. In this direction, the solution to the problem of forecasting direct material costs of economic sectors is relevant. To solve this problem, the article conducts a study on the application of the RAS method. RAS is a widely used methodology for evaluating, balancing, or updating matrices. This method is the process of obtaining a final matrix from an initial general matrix, given specified sums for the rows and columns. The article analyzes the inter-industry balance of the economy of Azerbaijan, aggregated in the 14x14 dimension, for 2006-2016. At the next stage, based on the results of this period, a forecast matrix of intermediate products of this size for 2021 was calculated using the RAS method. The compiled balance sheet indicators were compared with the actual indicators for 2021. The obtained results confirmed the expediency of using the proposed method in drawing up comprehensive plans and forecasts for the country.

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How to Cite

Akhundov, V. ., & Rustamov, I. . (2025). Forecasting of direct material costs in the national economy using the RAS method based on data extrapolation. Edelweiss Applied Science and Technology, 9(4), 1377–1385. https://doi.org/10.55214/25768484.v9i4.6287

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Published

2025-04-16