Abstract:
The article presents a methodology for determining the latent parameters of a multi-level multifactor regression model and ways of using the model using the example of forecasting the dynamics of indicators reflecting the functioning of agricultural production: grain crop yield and feed wheat consumption. The relevance of the model is due to the possibility of using it for forecasting the main output indicator (the first level of the model) and its intermediate components (subsequent levels of the model). The article processes statistical data, applies the method of regression analysis of information, and plots the results of modeling using MS Excel and the Python programming language development environment. The model is built on the basis of a hierarchical dependence of the first and subsequent levels, in which the input data of the output indicator are grouped as individual or common parameters of linear dependencies of intermediate variables. As a result of testing the model, data on grain crop yields were obtained depending on the type of fertilizer application and the corresponding shares of areas according to the Russian Federation as a whole and the Rostov Region, in particular, a yield forecast for three years was made, and a comparison with the results of applying factor analysis was given. In determining the consumption of feed wheat, data on the volume of net wheat consumption and the volume of wheat processed into compound feed were obtained.
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