Milk price modeling and forecasting

Abstract

Purpose. The purpose of the article is to substantiate the methodological approach to forecasting the selling price of milk, which is produced and sold by agricultural producers in the Ukrainian market of raw milk.
 Methodology / approach. The basis of the methodological approach is the construction of models describing the change in sales prices for milk and certain types of dairy products (pasteurized milk with a fat content of up to 2.5 %, sour cream with a fat content of up to 15.0 %, soft fat cheeses) during 2017–2019 and forecasting the sale price of milk for a period of 6 months. The ARIMA model was used in the forecast, taking into account the degree of correlation between changes in the price of milk and the analyzed types of dairy products. The time factor (time lag) of one month and the share of milk in the price of the finished dairy products were also considered.
 Results. The forecast results allowed us to determine milk sales prices for January–June 2020. In addition, the study showed the lack of a single direction in their change during the bias period, namely – increase in milk sales price during February–January 2020 and its reduction till June 2020. The obtained forecast values of milk selling price, considering the share of milk in the selling price of finished dairy products, were adjusted according to the time lag.
 Originality / scientific novelty. Novelty is an algorithm for using a methodical approach to forecasting the purchase price of milk, taking into account the correlation between milk prices and prices for certain types of dairy products; time lag and the share of milk prices in the sale price of finished dairy products.
 Practical value / implications. Comparison of the obtained forecast data of the price with the actual prices of milk sales indicated the existence of insignificant differences between them, proving the adequacy of the proposed methodological approach to be used in forecasting of milk prices at the enterprises.

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“…Based on the results obtained, the farms under study have the potential to increase the level of profitability and efficiency of production activities. For agricultural producers, it is vital to forecast the price of products sold on the Ukrainian market, as emphasised, for instance, by N. Shyian et al (2021). Next, the study considered the correlation and regression modelling of the dependence of milk production costs on the consumption of certain resources (Table 4) required to produce the final product.…”

Characteristic mango price forecasting using combined deep-learning optimization model

“…For example, the autoregressive integrated moving average (ARIMA) model, which extends the autoregressive moving average (ARMA) model, is widely used for agricultural econometric time-series forecasting. Tatarintsev et al [ 8 ] established an ARIMA-based price-change prediction model for sugar crops, and Shyian et al [ 9 ] did so for short-term milk price prediction. Hence, it is known to work.…”

Determinants of the Development of Economic Processes in the Dairy Market of Ukraine

“…Domestic and foreign scientists carried out scientific research on the dairy market using economic and mathematical modeling. In particular, modeling and forecasting methods were used by N. Shyian, V. Moskalenko, O. Shabinskyi, and V. Pechko [25] in forecasting milk prices; M. Chernyakov and M. Chernyakova [5] in forecasting the processes of regulation of production, processing, and sale of milk and dairy products; Yu. Bahteev, M. Bahteeva, G. Kuryaeva and A. Tuskov [1] in modeling the optimal range of dairy products.…”