Open AccessTrend Analysis and GARCH Model for COVID-19 National Weekly Confirmed Cases in Nigeria for Abuja and Lagos State
Author(s) -
O O Lawal,
Nwakuya Maureen Tobechukwu,
Biu O.E.
Publication year - 2022
Publication title -
quarterly journal of econometrics research
Language(s) - English
Resource type - Journals
eISSN - 2518-2536
pISSN - 2411-0523
DOI - 10.18488/88.v8i1.2931
Subject(s) - akaike information criterion , autoregressive conditional heteroskedasticity , statistics , bayesian information criterion , covid-19 , mathematics , econometrics , bayesian probability , pandemic , quartic function , deviance information criterion , bayesian inference , medicine , volatility (finance) , disease , pathology , infectious disease (medical specialty) , pure mathematics
The trend analysis and GARCH model for COVID-19 pandemic spread between FCT/Lagos and the National Weekly confirmed pandemic cases were carried out using the statistical software Minitab17 and Gretl. Four models trend behavior were considered, which are linear, quadratic, cubic and quartic trends with respect to R-square value, Adjusted R-square value, Analysis of Variance (ANOVA) p-value and the estimated coefficients p-values. In addition, GARCH(0,1),GARCH(1,0) and GARCH(1,1) models were built separately for both FCT/Lagos on the Nigeria National Weekly confirmed pandemic cases; to determine which model has best fit for predicting weekly confirmed cases of COVID-19 pandemic in those areas. The four common information criteria was used to selected the best model, which are the Akaike Information Criteria (AIC), Schwarz-Bayesian Information Criteria (BIC), Hannan-Quinn Information Criteria (HQC) and Likelihood Criteria (LKH).This study established the quadratic trend and GARCH(1,0) as the best model that describes the data sets for FCT. Hence, both models can be used to forecasts the weekly pandemic confirmed cases in these areas.