PARADIGM SHIFT IN MAIN MACROECONOMIC VARIABLES’ ANALYSIS - ALEMHO J. E; ADENOMON M. O. (BIMA JOURNAL OF SCIENCE AND TECHNOLOGY (2536-6041), 2021)
Bayesian Vector Autoregressive (BVAR) models are mostly used in computational analysis of macroeconomic variables of a nation. Certain issues had led to imprecise estimation by BVAR Model. Recently, it has been discovered that BVAR exhibit some statistical imprecision and inaccuracy in evaluating and forecasting macroeconomic variables. Because of this inconsistency with VAR models, the focus has gradually shifted to models that can account for the comovement among macroeconomic variables. This shift is occasioned by the limitations associated with BVAR and its inability to elucidate information relating to the integration and cointegration among the macroeconomic variables. Also, the predictive accuracy of BVAR model has some blemish owing to the fact that it lacks the estimation capacity to elucidate vital information about the co-movement among macroeconomic variables of a developing economy like Nigeria. The research utilizes secondary data of the selected macroeconomic variables which was obtained from the statistical bulletin of the Central Bank of Nigeria (CBN) ranging from 1986 to 2019. Bayesian Vector Error Correction Model (BVECM) was used in the analysis of the macroeconomic variables. It was discovered among others that BVECM has more analytical features than BVAR. Therefore, in forecasting and evaluating main macroeconomic variables of a nation, BVECM should be considered because it possesses a better predictive ability than the BVAR model since it predicts the direction of change in the chosen macroeconomic variables.