International Journal of Political Science and Development
 

International Journal of Political Science and Development

Vol. 6(2), pp. 68–75, March, 2018. 

DOI: 10.14662/IJPSD2018.110

ISSN: 2360-784X

Research Paper

Analysis of Cocoa Yield Forecast in Nigeria: An Autoregressive Integrated Moving Average (ARIMA) Approach (2017 – 2030)

^1*Binuomote, S. O., ¹Adeleke, O. A., ¹Alao, I.B., and ¹S. O. Olumide

¹Department of Agricultural Economics, Faculty of Agricultural Sciences, Ladoke Akintola University of Technology, PMB 4000, Ogbomoso, Oyo State, Nigeria. E-mail: sobinuomote@lautech.edu.ng

Accepted 20 February 2018

Cocoa being a food-industrial and one of the most important non-oil export commodities in Nigeria has a very strong potential to play an important role in building a strong economic base for Nigeria. In the light of the importance of this crop to the Nigerian economy, the study employs the ARIMA technique to forecast the yield of cocoa in Nigeria between 2017 and 2030. Data for the study were  based on historical cocoa yield time series data sourced from the Food and Agricultural Organization of the United Nations online database (FAOSTAT), The data which covers the period of 1961 -2016 was used to forecast cocoa yield using the Autoregressive Integrated Moving Average (ARIMA). The forecast results which were evaluated using statistically estimated prediction tools to validate it, show that cocoa yield in Nigeria will peak at about 31500Kg/ha in 2030 which is lower that the 4800Kg/ha obtained in 1998. This emphasizes the need for a change of the business as usual policies and investments in order to improve the livelihoods of the cocoa growing farmers in Nigeria as well as build up a nrw revenue base in the face of failing crude oil prices in Nigeria.

Keywords: ARIMA, Forecast, Cocoa Yield, Time Series, Unit root

Cite This Article As: Binuomote, S.O., Adeleke, O.A., Alao, I.B., Olumide, S.O.(2018). Analysis of Cocoa Yield Forecast in Nigeria: An Autoregressive Integrated Moving Average (ARIMA) Approach (2017 – 2030). Int. J. Polit. Sci. Develop. 6(2) 68-75