Panel Vector Autoregressive Modeling of Macroeconomic Interaction in Nigeria, Ghana and Cameroon

Aims: The aim of this study is to apply Panel VAR (Vector Autoregressive) modeling and estimation to analyze the macroeconomic interaction and interdependence within the context of Nigeria, Ghana, and Cameroon. The study aims to understand the trends of key macroeconomic variables, namely gross domestic product (GDP), exchange rate, and foreign reserves.

Methodology: The study adopted three macroeconomic variables—GDP, exchange rate, and foreign reserve—and utilized annual secondary data from the World Bank spanning from 1960 to 2022. Pretests, including unit root and cointegration tests, were conducted on the variables. The panel unit root tests (Levin, Lin, and Chu t, Augmented Dickey-Fuller Fisher Chi-Square, and Phillips-Perron Fisher Chi-Square) indicated that the series had unit roots at levels but were stationary at first difference, implying integration of order one. The absence of co-integration in the panel co-integration test established the necessary conditions for estimating a panel vector autoregressive model.

Results: The trend analysis revealed that the variables were relatively low in the 1960s and 1970s but exhibited an increasing and fluctuating pattern afterward. Descriptive statistics showed variations among the countries, with Cameroon having higher GDP per capita and greater standard deviation, indicating more significant fluctuations. Ghana, in contrast, displayed lower per capita income with a lower standard deviation. The foreign exchange rate varied, with Cameroon having the highest and Ghana the lowest mean rates.
Conclusion: The fixed effect model was estimated after the Hausman Test rejected the random effect model. The results indicated that foreign exchange rates had joint significance on GDP per capita, while foreign reserves did not. The study concludes that the economies of Nigeria, Ghana, and Cameroon are responsive to GDP per capita, foreign exchange rates, and foreign reserves. The policy implication is that economic practitioners in these countries should closely monitor these variables to anticipate changes in economic indicators. Therefore, the study recommends active monitoring of the economic variables used in this research to facilitate informed decision-making.