Kitova, Olga and Dyakonova, Ludmila and Savinova, Victoria and Fomin, Kiril (2023): Forecasting the main economic indicators for industry in the analytical system "Horizon".
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Abstract
Industrial development is of great strategic importance for ensuring sustainable economic growth in Russia and solving social problems. Therefore, the development of approaches and methods for comprehensive analysis and forecasting of industrial indicators at the national and regional level is of particular importance, which will facilitate the adoption of scientifically based decisions in the field of industrial planning and management. What is needed is a system of indicator models that will allow for a comprehensive analysis of industrial development, identification of the main influencing factors, as well as the development of forecasting models and methods and their application to the indicators under study. The hybrid forecasting system “Horizon”, developed by the authors of the study, implements regression and intelligent models for most groups of indicators of the Russian economy. At the same time, most researchers rely in their studies on autoregressive time series models based on ARIMA. The authors have developed a new module of the Horizon ARIMA system, which can be used when forecasting individual indicators. These forecasts can be considered as baseline when conducting comparative analysis with hybrid models. This study is devoted to forecasting a group of main economic indicators of Russian industry using ARIMA time series models.
Item Type: | MPRA Paper |
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Original Title: | Forecasting the main economic indicators for industry in the analytical system "Horizon" |
English Title: | Forecasting the main economic indicators for industry in the analytical system "Horizon" |
Language: | English |
Keywords: | socio-economic indicators of the Russian Federation, industry indicators, forecasting, time series, hybrid information and analytical system |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C45 - Neural Networks and Related Topics |
Item ID: | 118887 |
Depositing User: | Olga Kitova |
Date Deposited: | 26 Oct 2023 04:52 |
Last Modified: | 26 Oct 2023 04:52 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/118887 |