Univariate and Vector Autocorrelation Time Series Models for Some Sectors in Nigeria (Global Journal of Science Frontier Research, 2020)
This work on univariate and Vector Autocorrelation (VAR) time series model for the sectors in Nigeria, aims at providing an in-depth quantitative analysis of the variables (Agriculture, Industry, Building & Construction, Wholesale & Retail trade and Services). The study made use of secondary data, of all the variables investigated in the model, collected from the National Bureau of Statistics ' Statistical Bulletin (2018). The sample covers quarterly data from 1981 to 2018. Univariate and Multivariate time series estimation techniques -Autoregressive Integrated Moving Average (ARIMA) and Vector Autoregressive (VAR) were employed. Plots of the five sectors indicate that they all have Quadratic trend with appreciation and depreciation. Correlation analysis of the data set show that there exists a strong relationship among each variable. Each of the economic variables ARIMA model was built using Minitab 18 statistical software.
Keywords: gross domestic product (GDP); vector autoregressive (VAR) model; ARIMA; forecast accuracy measure; model selection criteria