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Application of SARIMAX model to forecast weekly Irish potato retail prices: a case study of Kitui County, Kenya

Author

Listed:
  • Arthanus Mutuku

    (South Eastern Kenya University)

  • Peter Murage

    (South Eastern Kenya University)

  • Stanley Sewe

    (South Eastern Kenya University)

Abstract

The prices of Irish potatoes fluctuate with the seasons due to the influence of demand, supply, and macroeconomic variables such as inflation and interest rates. To effectively handle these variations, incorporating all the significant factors is crucial for Irish potato price forecasting. This study analyzed and forecasted weekly average Irish potato retail prices in major markets within Kitui County, Kenya via a seasonal autoregressive integrated moving average model incorporating inflation rates and interest rates as the exogenous variables. The study used time series data from the Kenya National Bureau of Statistics for weekly Irish potato prices, inflation rates, and interest rates from January 2014 to December 2022. We established that the SARIMAX model (1, 1, 2)(2, 1, 0)[52], with lagged inflation rates and lagged interest rates as the exogenous variable, provided the best fit for Irish potato prices. The reduced MAE, MSE, and RMSE proved that including external factors improved the forecasting accuracy of the SARIMAX model. The SARIMAX model in-sample predicted Irish potato prices were off the actual Irish potato prices by a mean price of Ksh.10.59, and better than the SARIMA model (1, 1, 2)(2, 1, 0)[52] predicted Irish potato prices by a mean price of Ksh.0.92.The SARIMAX model (1, 1, 1)(2, 1, 0)[52] was used to forecast future mean Irish potato retail prices for the next year.The insights drawn from this study would help farmers, consumers, and policymakers in this subsector make data-driven decisions in production investment and marketing, consumption and policymaking, respectively.

Suggested Citation

  • Arthanus Mutuku & Peter Murage & Stanley Sewe, 2024. "Application of SARIMAX model to forecast weekly Irish potato retail prices: a case study of Kitui County, Kenya," SN Business & Economics, Springer, vol. 4(11), pages 1-28, November.
    • Handle: RePEc:spr:snbeco:v:4:y:2024:i:11:d:10.1007_s43546-024-00746-y
    DOI: 10.1007/s43546-024-00746-y
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    References listed on IDEAS

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    1. Matei Demetrescu, 2010. "On the Dickey–Fuller test with White standard errors," Statistical Papers, Springer, vol. 51(1), pages 11-25, January.
    2. Springer, William L, 1977. "Consumer Spending and the Rate of Inflation," The Review of Economics and Statistics, MIT Press, vol. 59(3), pages 299-306, August.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    4. Nari Sivanandam Arunraj & Diane Ahrens & Michael Fernandes, 2016. "Application of SARIMAX Model to Forecast Daily Sales in Food Retail Industry," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 7(2), pages 1-21, April.
    5. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    6. Feihu Sun & Xianyong Meng & Yan Zhang & Yan Wang & Hongtao Jiang & Pingzeng Liu, 2023. "Agricultural Product Price Forecasting Methods: A Review," Agriculture, MDPI, vol. 13(9), pages 1-20, August.
    7. shamsudin, mad nasir & Ann, Chew Tek & Rosdi, Mat, 1992. "An Econometric Analysis of Cocoa Prices: A Structural Approach," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 25(June), pages 3-17.
    8. Bourke, I.J., 1979. "Comparing the Box-Jenkins and Econometric Techniques for Forecasting Beef Prices," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 47(02), pages 1-12, August.
    9. Hassani, Hossein & Yeganegi, Mohammad Reza, 2020. "Selecting optimal lag order in Ljung–Box test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    Full references (including those not matched with items on IDEAS)

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