Econometric modeling of peasant (farm) production

The article shows that econometric methods are effective in describing and forecasting real economic data. We have built various forecasting models: linear regressions, a linear paired regression model (for analyzing data relationships), exponential smoothing and mixed models, and neural network models. The results of their modeling testify to the individual advantages and disadvantages of each type of model. For the study, we have used the software product MS Excel. The results obtained indicate a further increase in the production of peasant farms. The models presented in the article are informative, widely applicable and universal, and can later be used to model various socio-economic data. In practice, it is advisable to use the results obtained when planning effective strategies for the development of agriculture, and they may be a guide for econometricians who want to study various approaches to econometric modeling using efficient tools.