Revisiting energy consumption and GDP causality: Importance of a priori hypothesis testing, disaggregated data, and heterogeneous panels

This paper disaggregates energy consumption and GDP data according to end-use to analyze a broad number of developed and developing countries grouped in panels by similar characteristics. Panel long-run causality is assessed with a relatively under-utilized approach recommend by Canning and Pedroni (2008) [1]. We examine (i) reduced form production function models for both the industry and service/commercial sectors, where aggregate energy consumption is expected to cause aggregate output; and (ii) reduced form demand models, where income is expected to cause (separately) per capita residential electricity consumption and per capita gasoline consumption. We uncover for 12 different panels a set of super-consistent causality findings across two demand models that income “Granger-causes” per capita consumption. By contrast, the results from the production function models suggest that a different modeling framework is required to glean new, useful insights.