Cointegration Analysis of Money Supply Effect on Economic Growth in Nigeria: An ARDL Model Approach

Abstract:

This study investigates the impact of money supply on economic growth in Nigeria using the Auto-Regressive Distributed Lag (ARDL) model and data from the National Bureau of Statistics spanning 2001 to 2021. The ARDL model was used to assess the long-term and short-term dynamics between money supply and economic growth. Stationarity tests using the Augmented Dickey-Fuller (ADF) test revealed that Total GDP was stationary both at level and first differencing (p-value: 0.01), while Money Supply M1 and M2 became stationary after first differencing (p-values < 0.05. Descriptive statistics revealed significant variability in economic indicators over the period, with Total GDP showing a mean of ₦44,032.99 billion and a standard deviation of ₦19,487.82 billion, Money Supply M1 a mean of ₦4,525.89 billion and a standard deviation of ₦4,891.06 billion, and Money Supply M2 a mean of ₦10,474.06 billion and a standard deviation of ₦12,258.55 billion. The ARDL (2,3,0) model, selected based on the Akaike Information Criterion (AIC), demonstrates significant relationships between lagged values of money supply and economic growth, with an R-squared value of 0.9987 indicating a strong fit. The Johansen Co-integration Test indicates the presence of one long-term equilibrium relationship among the variables, as confirmed by the Trace test at the 5% significance level. Vector Error Correction Model (VECM) coefficients further confirm these findings, showing that deviations from equilibrium are corrected by adjusting Money Supply M1 and M2 negatively (e.g., -0.0322 and -0.0142 units for second lags) and Total GDP positively (e.g., 0.0015 unit for its second lag), suggesting a robust long-term association between money supply and economic growth. Results also indicated that changes in money supply significantly affect Nigeria’s economic growth, with both short-term and long-term implications. Specifically, the regression coefficients reveal significant effects, such as a negative effect of M1 (-0.64, p-value: 0.003) and a positive effect of M2 (0.83, p-value: 0.001) on GDP, indicating complex dynamics.