Rice Price Forecasting Using the Arima Model

Mark Benson S. Imbat; Francis Shayne S. Gordovez; Rolando M. Solomon; Glen Edison Q. Malicdem; John Domenick P. Andrada; Easter B. Belandres, PhD

1705412 Vol 7 · Issue 7 Download Paper

Rice Price Forecasting Using the Arima Model

Mark Benson S. Imbat Francis Shayne S. Gordovez Rolando M. Solomon Glen Edison Q. Malicdem John Domenick P. Andrada Easter B. Belandres, PhD

Subject area: Agriculture and Veterinary Sciences · Area of research: Agriculture

Abstract

In the Philippines, paddy is the primary source of income for Filipino farmers; however, a problem was pointed out along with the rice price. To monitor the price of rice, an autoregressive integrated moving average is employed (ARIMA). In the context of the price of rice for farmers, ARIMA can be applied to analyze historical price data and make predictions about future prices. Consequently, some factors affect the price of rice, and these factors should be identified to be able to develop a reliable forecast of the retail price in Eastern Pangasinan for the next 5 years, from 2024 to 2028. Descriptive statistics were used to analyze the factors that can affect the increase in the price of rice and the factors that greatly affect the increase in the price of rice. As a result, the increase in rice prices was affected by these factors: fertilizer, fuel, machinery, and insects. In 2024, the price of regular well-milled rice per kilogram has increased to 0.46% every month compared to the 2023 forecasted price of regular well-milled rice. Then, the price of regular well-milled rice will increase by 5.68% every year starting in 2025?2028.

Keywords

Farmers, Filipino, Paddy, Price, Well-Milled Rice

References

[1] Alcuitas, A. B., & Petralba, J. (2023). The Sectoral Impact of the Rice Tariffication Law on Filipino Rice Supply: A Time-Series Analysis. Recoletos Multidisciplinary Research Journal, 11(2), 85-95.

[2] Balilla, J., Bondoc, M., Castro, K. A., Ebrada, A., & Padua, A. A 6-Year Forecast Of Egg, Rice, And Onion Retail Prices In The Philippines: An Application Of Arima And Sarima Models.

[3] Bin Rahman, A. R., & Zhang, J. (2023). Trends in rice research: 2030 and beyond. Food and Energy Security, 12(2), e390.

[4] Durand-Morat, A., Bairagi, S., & Mulimbi, W. (2023). International Rice Outlook: International Rice Baseline Projections 2022-2032.

[5] Ibarra, J. A. M., Sumo, C. K. P., & Valdra, P. C. (2023). Forecasting Monthly Prices of Selected Fish Commodities in National Capital Region in The Philippines Through ARIMA Modeling.

[6] Jane-Atilano-Sabalberino, A. (2023). Forecasting value of production of palay and retail price of rice in the Philippines using ARIMA modelling. World Journal of Advanced Research and Reviews, 17(3), 035-054.

[7] Parreño, S. J. E. (2023). Forecasting Quarterly Rice And Corn Production In The Philippines: A Comparative Study Of Seasonal Arima And Holtwinters Models. ICTACT Journal on Soft Computing, 14(2).

[8] Timmer, C. P. (2023). Back in the Soup: Now What?. Asian Journal of Agriculture and Development, 20(2), 1-6.

How to cite this paper

Mark Benson S. Imbat, Francis Shayne S. Gordovez, Rolando M. Solomon, Glen Edison Q. Malicdem, John Domenick P. Andrada; Easter B. Belandres, PhD "Rice Price Forecasting Using the Arima Model" Iconic Research And Engineering Journals Volume 7 Issue 7 2024 Page 333-338

Mark Benson S. Imbat, Francis Shayne S. Gordovez, Rolando M. Solomon, Glen Edison Q. Malicdem, John Domenick P. Andrada; Easter B. Belandres, PhD "Rice Price Forecasting Using the Arima Model" Iconic Research And Engineering Journals, vol. 7, no. 7, Jan. 2024

Mark Benson S. Imbat, Francis Shayne S. Gordovez, Rolando M. Solomon, Glen Edison Q. Malicdem, John Domenick P. Andrada; Easter B. Belandres, PhD (2024). Rice Price Forecasting Using the Arima Model. Iconic Research And Engineering Journals, 7(7).

Mark Benson S. Imbat, Francis Shayne S. Gordovez, Rolando M. Solomon, Glen Edison Q. Malicdem, John Domenick P. Andrada; Easter B. Belandres, PhD "Rice Price Forecasting Using the Arima Model" Iconic Research And Engineering Journals, vol. 7, no. 7, Jan. 2024.

@article{1705412,
      author = {Mark Benson S. Imbat, Francis Shayne S. Gordovez, Rolando M. Solomon, Glen Edison Q. Malicdem, John Domenick P. Andrada; Easter B. Belandres, PhD},
      title = {Rice Price Forecasting Using the Arima Model},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {7},
      number = {7},
      pages = {333-338},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1705412.pdf},
      abstract = {In the Philippines, paddy is the primary source of income for Filipino farmers; however, a problem was pointed out along with the rice price. To monitor the price of rice, an autoregressive integrated moving average is employed (ARIMA). In the context of the price of rice for farmers, ARIMA can be applied to analyze historical price data and make predictions about future prices. Consequently, some factors affect the price of rice, and these factors should be identified to be able to develop a reliable forecast of the retail price in Eastern Pangasinan for the next 5 years, from 2024 to 2028. Descriptive statistics were used to analyze the factors that can affect the increase in the price of rice and the factors that greatly affect the increase in the price of rice. As a result, the increase in rice prices was affected by these factors: fertilizer, fuel, machinery, and insects. In 2024, the price of regular well-milled rice per kilogram has increased to 0.46% every month compared to the 2023 forecasted price of regular well-milled rice. Then, the price of regular well-milled rice will increase by 5.68% every year starting in 2025?2028.},
      keywords = {Farmers, Filipino, Paddy, Price, Well-Milled Rice},
      month = {January},
  }