INTERVENTION AND FORECAST MODELS FOR THE PRICE PAID TO PRODUCER OF BEE (Apis mellifera L.) HONEY IN MEXICO

Abstract

Bee (Apis mellifera L) honey is one of the oldest foods that humans have used. Since ancient times, it has been used as a healthy product due to its sweetening and healing properties. In 2020, Mexico produced 54 121 tons (Mg), which ranked the country as the tenth largest producer in the world. The hypothesis was that current honey prices can be explained by previous prices and that they influence the increase in the population of hives and the production of honey in Mexico. To test this hypothesis, the objective of this research was to develop a forecast model for the annual average prices of honey in Mexico (AAPH). The data comprised the 1966 to 2019 prices and the Box-Jenkins methodology of Autoregressive Integrated Moving Average (ARIMA), with and without intervention, was used. The parameters of the models were estimated with the maximum likelihood method of the SAS® software, while the structural change was calculated with the corresponding library (strucchange) of the R software. A model based on the AAPH series was adapted for the 1966−2019 period and validated with data from 2018 and 2019. The series presents five periods of trend structural changes of AAPH: 1966−1985; 1986−1995; 1996−2003; 2004−2008; and 2009−2019. The best estimated model without intervention was ARIMA (1, 1, 1) and the best model with intervention was ARIMA (1, 1, 0), which indicates that the prices of previous years can explain the AAPH. The predictions had a mean absolute percentage error (MAPE) of 8.16 % for the model without intervention and 4.02 % for the model with intervention. Both estimated models suggested that the AAPH have an upward trend in the medium term. The ARIMA model with intervention provided a more accurate estimation of the AAPH and information to plan and make decisions for the next five years.