Determining the factors affecting the consumer price of milk in Turkey by using regularization (elastic net) linear regression analysis

Understanding price interactions is critical for decision-making in uncertain conditions. The increasing volatility in the global prices of milk in recent years has increased the need for research on the factors affecting the price of milk. Identifying pr ice interactions is a prerequisite for understanding consumer prices of animal products, which is essential for producers, governments, and livestock-based industries. This study aims to reveal the structure of the basic and economic indicators that affect the consumer price of milk in Turkey. In this study, the time series of the monthly data for the 2010–2020 period was analyzed to examine the factors affecting the consumer price of milk in Turkey. We explained how the dependent variable of the consumer price of milk is affected by the independent variables of the producer price of milk; the price of dairy feed, corn, barley, wheat, soybean, sunflower seed meal, and dried distillers grains with solubles; dollar exchange rate; producer price index (PPI), and agricultural PPI. The regularization linear regression algorithm, a machine learning method, revealed that the parameters explained 97.8% of the variations in the consumer price of milk. According to the results obtained using the regularization linear regression algorithm, the consumer price of milk has the lowest positive correlation with sunflower seed meal (r = 0.917) and the highest positive correlation with PPI (r = 0.983). If Turkey wants to avoid excessive volatility in the consumer price of milk due to caused by macro variables, it must build an efficient price control system, which can only be accomplished by developing and implementing policies aimed at lowering prices of inputs and production expenses.