Subject. The article discusses possible lines for improving the methodological framework of the long-term economic forecast of gold production in the Russian Federation, relying upon the mathematical apparatus of econometric models. Objectives. We devise an economic-mathematical model for predicting the gold production with respect to the specifics of the economic development in Russia’s gold mining industry. Methods. The study is based in the correlation and regression methods for analyzing publicly available statistical data on the gold market. The least square method is taken as the methodological approach to designing the economic-mathematical model for forecasting. Results. Each gold deposit is found to be distinctive, having its own qualities, which seriously differ from those of other gold deposit. As a result of the analysis, we discovered key factors, which significantly influence the gold production, such as demand and price for gold, the amount and quality of geological reserves of gold, the amount of investment to be made in geological prospecting, national exchange rate and key rate of the Bank of Russia. We substantiated the use of the linear three-factor model, which involves gold production volumes in Russia, demand for gold, national exchange rate and price for gold as regressors. According to our estimates, in the Russian Federation, gold production will have reached 370–380 tons by 2025. Conclusions. Based on the least square method, the structural forecast apparatus does not account for geological and geographic-economic distinctions of gold deposits due to their unique nature. Therefore, determining regressors for the model, we predominantly focuses on open access data.
Keywords: long-term forecasting, econometric models, demand and production of gold, correlation and regression analysis
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