Forecasting Fish Production in Nigeria Using Univariate Arima Models

Abstract

Estimation and forecasting of fish production are crucial in supporting policy decisions regarding food security and development issues. The present study examines the current status of fish production in Nigeria. Univariate time series modeling using ARIMA model was developed for forecasting fish production. Box and Jenkins linear time series model, which involves autoregression, moving average,and integration, also known as ARIMA (p, d, q) model was applied. The annual production series of fish from 1971 to 2015 exhibited an increasing trend while prediction of fish production for 2016-2020 showed anincreasing trend. The study has shown that the best-fitted model for fish production series is ARMA (1, 1, 1). Themodel revealed a good performance in terms of explainingvariability and forecasting power.

Authors and Affiliations

Ogunbadejo . , Hussain Kehinde, Alliu . , Kehinde Adewale

Keywords

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  • EP ID EP383227
  • DOI 10.9790/2380-1105022228.
  • Views 140
  • Downloads 0

How To Cite

Ogunbadejo . , Hussain Kehinde, Alliu . , Kehinde Adewale (2018). Forecasting Fish Production in Nigeria Using Univariate Arima Models. IOSR Journal of Agriculture and Veterinary Science (IOSR-JAVS), 11(5), 22-28. https://europub.co.uk/articles/-A-383227