AN ANALYTICAL STUDY OF INTERNATIONAL TRADE AND POVERTY REDUCTION IN NIGERIA: 1980-2023

ABSTRACT This study examines the impact of international trade on poverty reduction in Nigeria using annual time series data spanning 43 years. The study specifically investigates the effects of exports, imports, trade openness, and exchange rate on the poverty rate. The Autoregressive Distributed Lag (ARDL) approach was employed to capture both short-run and long-run dynamics among the variables. Preliminary analysis using descriptive statistics revealed that the variables were moderately distributed, with exports, imports, and trade openness showing relatively stable patterns over time, while exchange rate and poverty exhibited greater variability. The unit root tests indicated a mixed order of integration, with exports stationary at level (I(0)) and the other variables stationary after first differencing (I(1)), justifying the application of the ARDL bounds testing technique. The ARDL bounds test confirmed the existence of a long-run equilibrium relationship among the variables, implying that international trade variables and exchange rate jointly influence poverty reduction over time. Long-run estimates revealed that exports have a significant negative impact on poverty, highlighting the importance of export-led growth in creating employment, stimulating production, and generating foreign exchange. Conversely, imports were found to have a positive but insignificant effect on poverty, suggesting that excessive reliance on imports may undermine domestic industries. Trade openness showed a negative but statistically insignificant effect, indicating that liberalization policies alone are insufficient to reduce poverty without complementary domestic measures. The exchange rate was negatively related to poverty, contrary to expectations, suggesting that a stronger currency may help reduce poverty. Short-run results from the Error Correction Model showed that deviations from long-run equilibrium adjust at a moderate speed of approximately 25% per period. Diagnostic and stability tests confirmed the robustness of the model.