The use of Multifactor Regression Models in Forecasting in the Agricultural Sector of Yakutia

Abstract

Under the constantly changing economic conditions of management, ensuring food security in the country, as well as in the regions becomes especially relevant. Agriculture is the only industry that is able to bring countries into a state of complete self-sufficiency, which is clearly indicated in the Doctrine of Food Security of Russia. With this in mind, the intensification of agricultural sectors, through the introduction of new technologies and improving the quality of land use is a particularly topical challenge. In this regard, the state faces the issues of the development of the industry and scientific forecast of its main indicators, taking into account the existing factors and conditions. This article provides a detailed methodology for developing a forecast for the agricultural sector using multivariate regression models. The main factors influencing the indicators of agriculture are considered, the main ones are highlighted and a multifactorial regression model is developed to forecast the indicator of gross agricultural output for the next five years. Recommendations are given for improving the application of this method in relation to the region under consideration.