International Journal of Economic and Business Management
 

 Vol. 6(3), pp. 43-56, October, 2018.

ISSN: 2384-6151

DOI: 10.14662/IJEBM2018.080

Full Length Research

Modelling Annual Yield of Coffee in Nigeria Using ARIMA Time Series Model (2018 – 2050)

^1*Binuomote, S. O.  ²Lukman, A. F.,  ¹S. O. Olumide and ¹O. A. Adeleke

¹Department of Agricultural Economics, Faculty of Agricultural Sciences, Ladoke Akintola University of Technology,

PMB 4000, Ogbomoso, Oyo State, Nigeria. Corresponding author’s E-mail: sobinuomote@lautech.edu.ng

²Department of Mathematics, Landmark University, P.M.B. 1001, Omu-Aran, Nigeria.

E-mail: adewale.folaranmi@lmu.edu.ng

Accepted 18 October 2018

Coffee represents the world’s most valuable tropical agricultural commodity in the international commodity trade and it comes next to crude oil. A large proportion of growers in the major coffee - producing countries in Sub-Saharan Africa which accounts for about 12 percent of world coffee   depends on coffee for their living. The paper employed the Autoregressive Integrated Moving Average (ARIMA) time series model to analse the behavior of Nigeria’s annual coffee yield as well as make forecasts unto the year 2050. Annual coffee yield data from 1961 to 2016 was obtained from the online statistical database of the Food and Agricultural Organization of the United Nations (FAOSTAT) and analyzed using ARIMA. The results showed that coffee yield in Nigeria follow an upward and downward movement from 1961 to 2016. ARIMA (0, 1, 1) was selected as the best model for the forecast of cocoa yield in Nigeria after various diagnostics selection and evaluation criteria. In the end, the forecast figures base on Box- Jenkins forecast technique showed that Nigeria’s annual coffee yield will increase continuously in the next thirty-four (34) years.

Keywords: Coffee, Yield, ARIMA, Box –Jenkins, Forecast, Time Series, Autocorrelation.

Cite This Article As: Binuomote, S.O.  Lukman, A.F.,  Olumide, S.O., Adeleke O.A (2018). Modelling Annual Yield of Coffee in Nigeria Using ARIMA Time Series Model (2018 – 2050). Inter. J. Econ. Bus. Manage. 6(3): 43-56