An Econometric Analysis of the Long-Run Relationship Among Environmental Quality, Income Inequality, and Economic Indicators in Nigeria

Abstract

Purpose – The research employs annual time series data covering several decades and applies the Autoregressive Distributed Lag (ARDL) bounds testing approach to examine cointegration among variables such as carbon emissions, Gini coefficient, GDP per capita, inflation, and energy consumption.

Methodology/approach The ARDL bounds testing approach was used due to its ability to handle I(0) and I(1) variables. Diagnostic tests such as unit root (ADF and PP), multicollinearity, and residual diagnostics ensured model robustness. Stationarity was tested to prevent biased results, with decisions based on comparing test statistics to critical values. Analyses were performed in EViews 10.

Findings – The unit root tests using ADF and Phillips-Perron methods show a mixed order of integration: some variables are stationary at level [1(0)] such as CO₂, GCE, LER, and IFMR, while others—EC, GINI, PGDP, PST, and DFT—are stationary at first difference [1(1)]. This mix validates the use of the ARDL Bounds Test. Correlation analysis reveals no serious multicollinearity issues among the variables. In the ARDL Bounds Test for Model 1, the F-statistic is (10.04213), which exceeds the upper bound at the (1%) level (3.9), confirming the presence of a long-run relationship among the variables. These findings support further model estimations. The study highlights the need for policies that promote inclusive economic growth while ensuring environmental sustainability. Targeted strategies addressing both economic inequality and environmental protection are recommended to achieve balanced development outcomes.