Explaining the (non-) causality between energy and economic growth in the U.S.—A multivariate sectoral analysis

The rapidly growing literature on the relationship between energy consumption and economic growth has not univocally identified the causal relationship yet. We argue that bivariate models, which analyze the causality only at the macro level, are eventually misleading, especially in cases where both variables do not cover the same scope of economic activity. After discussing appropriate pairs of variables, we investigate Granger causality between energy and growth in the U.S. for the period from 1970 to 2007 for three sectors, industry, commercial sector, transport, as well as on the macro level. Using the recently developed ARDL bounds testing approach by Pesaran and Shin (1999) and Pesaran et al. (2001), we find evidence for unidirectional long-run Granger causality in the commercial sector from growth to energy, as well as evidence for bi-directional long-run Granger causality in the transport sector. The dependence of causality on the level of aggregation is interpreted as evidence for ‘Simpsons' Paradox’. The choice of control variables is based on findings from the Environmental Kuznets Curve literature: we find that controlling for the increasing energy productivity of production as well as trade significantly improves the fit of the bivariate model.