Modelling of Post-COVID–19 Food Production Index in Nigeria using Box-Jenkins Methodology


  • Mohammed Kabir Garba Department of Statistics, University of Ilorin
  • Saheed Busayo Akanni Department of Statistics, University of Ilorin, Ilorin, Nigeria
  • Kola Yusuff Kareem Department of Agricultural & Biosystems Engineering, University of Ilorin, Ilorin, Nigeria
  • Ahmed Ayobami Yusuf Department of Statistics, University of Ilorin, Ilorin, Nigeria
  • Saheed Olalekan Jabaru Department of Physical Sciences (Statistics Option), Al-Hikmah University, Ilorin, Nigeria
  • John Seyi Abolarin Department of Civil Engineering, University of Ilorin, Ilorin, Nigeria
  • Femi Emmanuel Amoyedo Department of Statistics, University of Ilorin, Ilorin, Nigeria
  • Samuel Oluwaseun Ekundayo Department of Finance, University of Ilorin, Ilorin, Nigeria


Food Production Index, Correlogram, Selection Criteria, ARIMA, COVID-19


Before the COVID-19 pandemic, global food security has been known to be a major threat for developed and developing countries of the world. However, during the COVID-19 pandemic, global food security was expected to be at a very high risk due to lockdown across the globe. Consequently, the developing countries, most especially, were expected to experience food shortage challenges. One important way to measure the amount of food production of any country in the world is through the use of a macroeconomic variable known as Food Production Index (FPI). Therefore, this study seeks to examine the post-COVID-19 behavior of the Nigeria’s FPI using the Box-Jenkins methodology for modeling univariate time series.


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