Energy is substantial for economic development. This study aims to unveil the causal relationship and long-term association between economic growth and energy consumption in Pakistan. The Granger-Causality test finds that; natural gas consumption, electricity consumption and coal consumption have uni-directional causal relationship with economic growth as (GC, EC and CC→GDP), however, GDP growth rate, natural gas consumption and coal consumption unilaterally Granger causes Inflation (GDP, GC and CC→CPI) and lastly coal consumption→natural gas consumption (GC), Electricity consumption (EC)→GC. The ARDL estimations delineate natural gas consumption and oil consumption having a positive and negative association with GDP growth rate may have significant long term impacts respectively on the the economic growth of Pakistan.

This study empirically investigates the impact (overall, regional, and seasonal) of weather and climate extremes on basic human needs by employing a new poverty index, i.e., the Human Needs Index (HNI), in the United States of America. Detecting the contemporaneous correlations between errors, we apply second-generation unit root tests on monthly statewide panel data ranging from January 2004 to December 2018. The results obtained through cross-sectional time-series feasible generalized least square (i.e., FGLS) regression suggest that human necessities statistically and significantly correlate with a positive response to the weather extremes (cold, low precipitation) and with extreme events (drought, flood). However, the response is the opposite of that in the case of high precipitation. The seasonal variations in necessities indicate that there is a significant escalation of the needs between July and December (January is taken as the reference month), but, in February, they substantially shrink. Furthermore, the regional implications imply that, with the West of the US taken as the reference region, needs are significantly augmented in the Midwest; conversely, in the east and the south, they are significantly decreased. We also observe that some interaction effects, such as high precipitation and personal income as an interaction term, significantly, but negatively, correlate with HNI, indicating a 0.025% shared effect. Contrary to these findings, high precipitation, coupled with supplements to wages and salaries, shows a positive joint association of 0.274% with HNI. Besides, low precipitation, coupled with the unemployment rate, personal income, and flooding, shows an additional positive and significant mutual effect, while low precipitation has a negative effect on basic human needs when coupled with supplements to wages and salaries. The corresponding estimated interacting coefficients are 3.77, scoring 0.053%, 0.592%, and −0.67%, respectively.