Application of Bayesian Vector Autoregressive Model to some Macroeconomic Variables in Nigeria and Global Factors

• Author(s): Vincent Nchedo Chukwukelo; Isaac Didi Essi; Emeka Amos; Godwin Lebari Tuaneh
• Paper ID: 1712563
• Page: 316-339
• Published Date: 05-12-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 6 December-2025

Abstract

Understanding the dynamic interplay between macroeconomic variables and external shocks is central to effective policy formulation especially in emerging economies such as Nigeria. Given Nigeria’s heavy reliance on oil exports and increasing exposure to international trade, it becomes imperative to examine how fluctuations in commodity prices such as oil, copper and maize alongside broader global factors influence domestic macroeconomic indicators. These relationships are inherently complex and interdependent, requiring an empirical approach capable of capturing their dynamic interactions. This study applied a Bayesian vector autoregressive model (BVAR) approach which is the advance version of vector autoregressive model (VAR) to examine the dynamic interrelationships between some key Nigerian macroeconomic variables and Global factor, specifically commodity prices – copper, maize, and oil – along with the Common Commodity Price Factor (CCPF) and global factors (GF). The BVAR framework was chosen because of its robustness for handling multivariate systems with limited samples and its ability to incorporate prior information, improving predictive accuracy and structural interpretation. Monthly time series data from April 1971 to July 2024 were obtained from the Central Bank of Nigeria (www.cbn.org.ng). The results reveal strong autoregressive patterns, particularly in the CCPF, copper, oil prices, and global indices, indicating high price persistence and systemic inertia in Nigeria's macroeconomic environment. Granger causality tests highlight significant bidirectional links, particularly between the CCPF and both maize and global factors, as well as the central role of copper prices as a transmission channel influencing maize prices and the global factors.” Impulse “response capabilities and model diagnostics confirm the reliability of the model with stable dynamics and superior forecast performance compared to traditional VAR models. Residual normality test shows deviations such as excessive kurtosis and skewness, validating the appropriateness of Bayesian techniques, which are not limited by classical distribution assumptions. The findings concluded and validated that Nigeria's economy is vulnerable to external shocks and the influence of global commodity trends on domestic economic indicators. The work in its conclusion recommended that government should build a fiscal buffers, adopt BVAR-based forecasts in macroeconomic planning, and diversify strategies to reduce commodity dependency, with particular emphasis on global factor and oil prices as early warning indicators of economic instability.”

Keywords

Bayesian-VAR, Macroeconomic, Variables, Stationary, Multivariate, Time Series, Common Commodity Price Factor, Global Factor.

Citations

IRE Journals:
Vincent Nchedo Chukwukelo, Isaac Didi Essi, Emeka Amos, Godwin Lebari Tuaneh "Application of Bayesian Vector Autoregressive Model to some Macroeconomic Variables in Nigeria and Global Factors" Iconic Research And Engineering Journals Volume 9 Issue 6 2025 Page 316-339 https://doi.org/10.64388/IREV9I6-1712563

IEEE:
Vincent Nchedo Chukwukelo, Isaac Didi Essi, Emeka Amos, Godwin Lebari Tuaneh "Application of Bayesian Vector Autoregressive Model to some Macroeconomic Variables in Nigeria and Global Factors" Iconic Research And Engineering Journals, 9(6) https://doi.org/10.64388/IREV9I6-1712563