Forecasting of Post-Covid-19 Import Value Index in Nigeria Using Box-Jenkins Methodology

Autor:	Ogunlade Temitope Olu, Akindutire Opeyemi Roselyn, Faweya Olanrewaju, Balogun Kayode Oguntuase, Okoro Joshua Otonritse
Rok vydání:	2022
Předmět:	General Mathematics
Zdroj:	WSEAS TRANSACTIONS ON MATHEMATICS. 21:144-152
ISSN:	2224-2880 1109-2769
DOI:	10.37394/23206.2022.21.21
Popis:	This study employed the Box-Jenkins Methodology otherwise known as the Autoregressive Integrated Moving Average (ARIMA) modelling to model and forecast the series for the period of 2018 to 2030. The results indicated an upward trend with fluctuations while the series was stationary at first difference, i.e the series was I(1) . Based on the Akaike information criterion (AIC) and Bayesian Information Criteria (BIC) choice criteria, it was found that ARIMA (2, 1, 2) model was better suited to the import value index (IVI) series. Diagnosed check of the model reveals that the error was random, normally distributed and there was no serial correlation, in the same vein, thirteen years forecast was made which shows fluctuation pattern in import value index (IVI) series.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1d5c87338e5c8bd946bc1c91f1366296 https://doi.org/10.37394/23206.2022.21.21 Zobrazit plný text záznamu