Modeling and Forecasting of Production an Agricultural Product

Abstract

Purpose: The purpose of the research is to analyze the dynamics of agricultural production, to determine the effect of different parameters on the result of production with the help of an econometric model, and to enforce production forecasting. Methods: The data of the Statistical Committee of the Azerbaijan Republic for the last 15 years were used in the research. According to the obtained data, using the EXSEL software package, the dependence between the production of agricultural products and affecting factors was determined with the help of economic-mathematical methods, and the expected change tendency of production was defined with the help of programming methods. Results: Increasing the production of agricultural products is currently maintaining its relevance both in terms of meeting the necessary raw material needs of the country, as well as solving the food problem and eliminating dependence on imports. Possible prospects for solving these problems require the application of innovative agricultural technologies to production, effective use of fertilizers, land, human resources and investments, taking into account the factors affecting production. Optimizing the mentioned factors leads to the achievement of high productivity, which is the basis of production growth, ensuring the most complete use of resource potential in agriculture. From this point of view, the modeling of production through economic-mathematical methods is possible to determine the quantitative relationship between product production and the factors affecting it, to optimize and predict the use of resources based on the obtained production function. Conclusion: It gives an opportunity to evaluate the effect of those factors on the dynamics of production in quantitative terms by comprehensively investigating the factors affecting production in agriculture, which is considered quite a risky field. At the same time, the methodology utilized provides a foundation for figuring out more effective methods of using production resources, allowing for the prediction of future changes that might take place in production.