This paper expands on the panel GDP–energy cointegration modeling literature; it does so by using data disaggregated along sectoral lines and adjusting energy consumption for the quality of the energy source (e.g., electricity is of higher quality than oil, which is of higher quality than coal) in order to examine the role of energy quality in the five most energy intensive manufacturing sectors (iron and steel, non-ferrous metals, non-metallic minerals, chemicals, and pulp and paper). The database was constructed by combing energy consumption (and energy price data to construct the energy quality index) from the IEA with economic data (value added, labor employed, and physical capital) from the OECD's Structural Analysis Database. In addition to finding the variables analyzed are panel I(1) and cointegrated for each sector-based panel, the long-run elasticity estimates (from panel FMOLS) indicate the importance of energy quality – primarily the shift toward the use of high quality electricity – in these energy-intensive manufacturing sectors. In each case, the elasticity for energy quality is greater than that for conventionally measured energy consumption—sometimes orders of magnitude greater. Indeed, the elasticity of conventionally measured energy consumption is insignificant to very small for three of the five sectors. Also, when using the energy quality measure, the importance of energy consumption relative to the other production factors stands out. Such results are useful for both energy–GDP cointegration/causality modelers and CGE modelers, who may need to estimate elasticities.