Forecasting carcass meat prices with box-jenkins models: A case study on tokat province

In the livestock sector, future red meat prices are of great importance to both producers and consumers. Particularly in Turkey, factors such as market uncertainty for animal products, inflationary pressures, and import competition are the main contributors to the increasing need for accurate price predictions. Forecasting future prices can meet this need, and econometric methods like time series analysis can be employed for this purpose. This study aims to forecast future carcass meat prices in Tokat province using econometric methods. Specifically, the Box-Jenkins forecasting methods, a subset of econometric analysis techniques, will be utilized. The objective is to analyze the carcass prices from 2018 to 2024 in Tokat province through time series analysis and to predict these prices for 2025. The study will use data obtained from the Market Monitoring System, including monthly prices of calves, cows, heifers, and heifers slaughtered between 2018 and 2024. Descriptive statistics will be calculated, and price estimation will be conducted by identifying the model parameters with the highest goodness of fit from the Box-Jenkins models. Time series analyses will be performed using the SPSS 25 software package. As a result of the time series analysis, the most suitable models for calf, heifer, cow and calf carcass prices are ARIMA (1,1,0) (0,0,0), ARIMA (3,1,0) (0,0,0) respectively. , has been determined as ARIMA (3,1,0) (0,0,0) and ARIMA (0,1,0) (1,1,0) model. In line with the determined ARIMA models, carcass prices have been estimated until May 2025. According to the estimation results, it is estimated that the calf carcass will reach 378.57 TL/kg, the cow carcass will reach 397.69 TL/kg, the heifer carcass will reach 352.61 TL/kg and the heifer carcass will reach 550.37 TL/kg in May 2025 in Turkey. As a result, it was concluded that time series analysis can be used to predict calf, heifer, cow and bull carcass prices for the future, but the predictions should be updated over time and can contribute to the future planning of both producers and consumers.