Development of econometric models to forecast indicators of the livestock industry

Abstract

The article discusses the importance of animal husbandry in ensuring food security and maintaining a high quality of life. In the current study, statistical monthly data on animal husbandry in the Udmurt Republic from 2018 to 2023 is analyzed to create models for forecasting key indicators: the average daily milk yield, the number of cows, and the total volume of milk production. The model of the average daily milk yield takes into account seasonal fluctuations, temperature, and time trends, with an average relative error of just 1.55%. The autoregressive model for predicting the number of cattle with a lag of 12 months has shown high accuracy with an average relative approximation error of 0.19%. The econometric model of total milk production takes into account the average daily milk yield and other factors, demonstrating high accuracy in its forecasts. These results are important to support decision-making on the development of animal husbandry and the agricultural sector in general.