John P. Maxwell

We translate between energetic and economic metrics that characterize the role of energy in the economy. Specifically, we estimate monetary expenditures for the primary energy and net external power ratio (NEPR direct ; NEPR, net external power ratio), a power return ratio of annual energy production divided by annual direct energy inputs within the energy industry. We estimate these on an annualized basis for forty-four countries from 1978 to 2010. Expressed as a fraction of gross domestic product (GDP), f e , GDP , the forty-four country aggregate (composing >90% world GDP) worldwide expenditures on energy decreased from a maximum of 10.3% in 1979 to a minimum of 3.0% in 1998 before increasing to a second peak of 8.1% in 2008. While the global f e , GDP fluctuates significantly, global NEPR direct declined from a value of 34 in 1980 to 17 in 1986 before staying in a range between 14 and 16 from 1991 to 2010. In comparing both of these metrics as ratios of power output over power input, one economic ( f e , GDP - 1 ) and one biophysical (NEPR direct ), we see that when the former divided by the latter is below unity, the world was in a low-growth or recessionary state.

We translate between biophysical and economic metrics that characterize the role of energy in the economy. Specifically, using data from the International Energy Agency, we estimate the energy intensity ratio (EIR), a price-based proxy for a power return ratio (PRR ∼ P out / P invested ). The EIR is a useful metric, because for most countries and energy commodities, it can indicate the biophysical trends of net energy when data are too scarce to perform an original net energy analysis. We calculate EIR for natural gas, coal, petroleum and electricity for forty-four countries from 1978 to 2010. Global EIR values generally rise from 1978 to 1998, decline from 1998 to 2008 and then slightly rebound. These trends indicate one interpretation of the net energy of the world economy. To add perspective to our recent, but short, time series, we perform the same calculations for historical England and United Kingdom energy prices to demonstrate that a given energy price translates to different PRRs (EIR in this case) depending on the structure of the economy and technology. We review the formulation of PRRs and energy return ratios (ERR ∼ E out / E invested ) to indicate why PRRs translate to (the inverse of) energy prices and ERRs translate to (the inverse of) energy costs. We show why for any given value of an ERR or PRR, there is not a single corresponding energy cost or price, and vice versa. These principles in turn provide the basis to perform better modeling of future energy scenarios (e.g., low-carbon transition) by considering the relationship between economic metrics (cost and price) and biophysical metrics (energy and power return ratios) based on energy, material and power flows.