A Mathematical Model for Estimating the Retail Price Movements of Basic Meat Commodities Using a Time Series Analysis

Abstract

The prices of meat commodities in the market is a significant concern for the entire populace in a region or country. They directly affect the consumers, farmers, traders, entrepreneurs, and even the government and policymakers. Developing a mathematical model concerning the retail price movements of these essential commodities could help every concerned individual about economic matters as well as in planning the future. Specifically, the study included the essential meat commodities such as lean beef meat, lean pork meat, and fully dressed chicken. The data were obtained from the Philippine Statistics Authority (PSA) in coverage of ten (10) years, from 2009 –2018 in the National Capital Region markets of the Philippines. The data in each commodity was subdivided into training and test sets by which they were subjected to time series procedures using ARIMA, SARIMA, and ARIMAx. The data was analyzed using R-program package in developing the models. After employing forecasting analysis and accuracy tests, the researchers identified the best mathematical model to estimate the retail prices of each meat commodity. After undertaking proper procedures and processes in developing the model, it was found that each of the meat commodities investigated in the study showed an increasing trend of monthly prices for a ten-year period (2009-2018). As regards the meat commodities, SARIMA (1,1,2) (0,1,1)12 was found to be the utmost model to estimate the monthly prices of lean beef meat, ARIMA (2,2,2) for lean pork meat and ARIMA (2,2,2)for fully dressed chicken accordingly.