Estimating the dynamic relationship between Energy Use, Economic activity and CO2 emission by using a Panel ARDL Model on a few SADC country member

Abstract

This paper investigates both the dynamic and long-run relationships between CO₂ emissions, energy consumption, and economic activity using a Panel Autoregressive Distributed Lag (ARDL) model, in which CO₂ emissions are specified as the dependent variable. To examine the direction of causality among the variables, the Granger causality test is employed. The estimation is conducted using the Pooled Mean Group (PMG) method on panel data comprising eight Southern African Development Community (SADC) countries over the period 1990–2014.

The empirical results reveal a significant causal relationship running from economic activity and energy consumption to CO₂ emissions during the study period. The long-run coefficients are all statistically significant at the 1% level, indicating the existence of a cointegration relationship among the variables. Since the variables are expressed in logarithmic form, the estimated coefficients can be interpreted as elasticities. Notably, CO₂ emissions respond negatively to GDP, suggesting environmental deterioration associated with increased economic activity.

Furthermore, the error correction term is negative and statistically significant, as expected. The estimated speed of adjustment indicates that approximately 73% of any deviation from the long-run equilibrium is corrected within each period