Price Forecasting of Feed Raw Materials Used in Dairy Farming: A Methodological Comparison

Merve Kılınç Yılmaz, Yusuf Şahin and Kenan Oğuzhan Oruç

Alphanumeric Journal, 2024, vol. 12, issue 3, 249-280

Abstract: Milk is a product of strategic importance for countries due to its nutritional value and its status as a priority foodstuff. Feed raw materials represent a critical input item within the dairy cattle sector. It is of great importance for producers to maintain their activities and profitability so that they ensure the balance of milk/feed parity. In countries such as Turkey, where inflationary effects are observed, the prices of feed raw materials are not stable. In an environment characterized by high price volatility, the ability to forecast feed raw material prices is of paramount importance for producers engaged in future planning. In this study, the price forecasting of 43 feed raw materials, which are extensively utilized in the ration preparation process within the dairy cattle sector, was conducted. The efficacy of 11 methods based on time series, statistics and grey system theory was evaluated. Following the assessment of model success criteria, it was determined that the DGM (1,1) method exhibited superior forecasting capabilities compared to exponential smoothing and regression models, as well as other grey forecasting models. Based on MAD, MSE and MAPE values, it can be posited that grey forecasting methods may serve as a viable alternative for price forecasting of feed ingredients.

Keywords: Exponential Smoothing; Grey Forecasting; Price Forecasting; Regression Analysis (search for similar items in EconPapers)
JEL-codes: C52 C53 Q00 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:anm:alpnmr:v:12:y:2024:i:3:p:249-280

DOI: 10.17093/alphanumeric.1504096

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