ABSTRACT

The objective of this study was to assess behavior patterns in Brazilian farm milk prices. We employed a structural time series techniques model, the Unobserved Component Model (UCM), which is part of the family of State Space models, to assess the trend, seasonality, cyclical behavior, and impacts of exogenous regressors on aggregated farm milk price behavior in Brazil from January 2005 to December 2019. We tested five alternative models with different regressors using the monthly national average prices of milk paid to farmers. The fit of the models was assessed with Akaike information criterion and Bayesian information criterion. Predictions were assessed by the root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). All models demonstrated a high degree of accuracy. Trends, seasonality, and two cycles were statistically significant, with the trend and long-period cycle contributing the most to price variation. Exogenous factors such as feed cost and international dairy product prices also had significant positive effects on the level of Brazil’s farm milk prices. All models demonstrated a high degree of accuracy, which may indicate their usefulness for price forecasting and policy formulation.

Brazil; dairy; price cycles; time series