LAUSR

Abstract Planning process focusing on Energy-Environment-Economy nexus heavily relies upon the results of causality studies for policy and decision guidance. These studies are mostly aimed to determine the true direction of the causal-path among key variables such as energy consumption, economic growth and GHGs emissions. However, there are some weak points attached to already available methods and their variants such as Granger type causality tests and Peter and Clark (PC) algorithms based on Graph theoretic approach. Swanson and Granger (1997) [89] used the vector autoregressive (VAR) residuals in the PC algorithms to find the causal ordering in time series. However, these residuals carry only contemporaneous information about cross-variable effect and remove the past information. This study modified the original PC algorithms based on modified R-residuals test to analyze the causal relationship between energy consumption, economic growth and GHGs emissions in Pakistan. The results reveal that, unidirectional causality is running from economic growth towards CO2 emissions. However, no causality is running from energy consumption towards economic growth and vice-versa. This is due to the fact that, a significant portion of energy is consumed in residential and transportation sectors, both of which does not contribute to economic growth in long-run.