Energetic Limits to Economic Growth

Brown, James H.; Burnside, William; Davidson, Ana D.; DeLong, John P.; Dunn, William C.; Hamilton, Marcus J.; Mercado‐Silva, Norman; Nekola, Jeffrey C.; Okie, Jordan G.; Woodruff, William H.; Zuo, Wenyun

doi:10.1525/bio.2011.61.1.7

Cited by 201 publications

(177 citation statements)

References 37 publications

Supporting

Mentioning

167

Contrasting

Unclassified

Order By: Relevance

“…The scaling of white and grey matter [54] and communication modularity [14] in the brain, of flow through river networks that minimize transportation costs [55], of energy use and GDP in countries [56], and the pace of life and population in cities [45] are all additional examples that a unifying scaling theory might explain. Because cost and performance, i.e.…”

Section: (B) Implications For Evolutionary Transitionsmentioning

confidence: 99%

Energy and time determine scaling in biological and computer designs

Moses

Bezerra

Edwards³

et al. 2016

Phil. Trans. R. Soc. B

View full text Add to dashboard Cite

One contribution of 13 to a theme issue 'The major synthetic evolutionary transitions'. Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy-time minimization principle may govern the design of many complex systems that process energy, materials and information.This article is part of the themed issue 'The major synthetic evolutionary transitions'.

show abstract

Section: (B) Implications For Evolutionary Transitionsmentioning

confidence: 99%

Energy and time determine scaling in biological and computer designs

Moses

Bezerra

Edwards³

et al. 2016

Phil. Trans. R. Soc. B

View full text Add to dashboard Cite

show abstract

“…Nuclear fuel cost estimated to be 0.02% of GDP in 2011, latest year for which data are available; too small a portion to show in chart fossil fuels began to come into wide use, the correlation between energy use and economic activity has been high [8][9][10]. More generally, economists have argued that because the cost of energy is only 3%-4% of the economy it is not important.…”

Section: Coalmentioning

confidence: 99%

Does a Change in Price of Fuel Affect GDP Growth? An Examination of the U.S. Data from 1950–2013

Aucott

Hall²,

Stern³

2014

Energies

View full text Add to dashboard Cite

Abstract:We examined data on fuel consumption and costs for the years 1950 through 2013, along with economic and population data, to determine the percent of U.S. gross domestic product (GDP) spent each year on fuels, including fossil fuels and nuclear ore, and the growth of the economy. We found that these variables are inversely correlated. This suggests that the availability and cost of energy is a significant determinant of economic performance. We believe this relation is consistent with analyses based on the energy return on investment (EROI) concept in that increasingly scarce, and hence expensive, fuels are a drag on economic growth. The best-fitting linear equation relating the percent of GDP (energy cost share) and year-over-year (YoY) GDP change variables suggests that a threshold exists in the vicinity of 4%; if the percent of GDP spent on fuels is greater than this, poorer economic performance has been likely. Currently, about 5% of GDP is spent on fuels; most of this is for liquids. Continued weak economic performance appears likely unless improvements in energy efficiency, on the order of a factor of 3 for liquid fuels, and/or a more rapid adoption of renewable or nuclear energy sources can be achieved, provided that the EROI of these new sources proves to be sufficiently high.

show abstract

“…There are, of course, numerous studies projecting or searching for the signs of stagnation in growth or maturing of our society or economy, which is an expectation from a systems/ecosystems point of view that considers the finite nature of the Earth as a fundamental constraint (for some studies, see 1947 1958 1963 1967 1972 1977 1982 1987 1992 1997 2002 2007 2012 26 28 26 26 28 26 26 28 28 29 29 28 28 28 30 28 28 30 28 28 30 30 30 30 30 30 30 31 30 30 31 30 30 31 31 31 31 31 31 32 32 32 32 32 32 32 32 32 32 32 32 32 The numbers indicate which of the 37 sectors made the total purchases (including from its own sector). The food sectors (numbers italicized in table) are 1 (Farms) and 18 (Food products, Stores, and Services), and the energy sectors (numbers bold in table) are 3 (Oil and gas extraction), 5 (Utilities), and 23 (Petroleum and coal products) Meadows et al (1972), Brown et al (2011), Turchin and Nefedov (2009), Brown et al (2014, DeLong and Burger (2015) and Matutinovií et al (2016)). Another way of summarizing these conclusions on the trends is that the U.S. economy transitioned from a relatively low metabolic (small low-consuming population) and resource-rich state (Phase 1) to one that has high metabolism (large high-consuming population) and is relatively resource-limited (Phase 3) in that it no longer can make energy and food cheaper.…”

Section: Interpretation Of Trendsmentioning

confidence: 99%

Information Theory to Assess Relations Between Energy and Structure of the U.S. Economy Over Time

King

2016

Biophys Econ Resour Qual

View full text Add to dashboard Cite

This paper describes the changing structure of the United States' (U.S.) domestic economy by applying information theory-based metrics to the U.S. input-output (I-O) tables from 1947 to 2012. Here the I-O tables are an economic network where the sectors are the nodes. The value of these metrics is that they describe the balance or trade-off between efficiency and redundancy of network flows as well as equality and hierarchy of flows through nodes in a network. I relate these metrics to the U.S. gross power consumption and annual intermediate spending by the food and energy sectors, the latter being a proxy for the inverse of the net power ratio (or net energy) of the economy, to test hypotheses of energy-economy structural linkages. The results of this paper show that increasing gross power consumption, as well as a decreasing share of intermediate expenditures of the food and energy sectors, correlates with increased distribution of money among economic sectors, and vice versa. The information theory metrics indicate two time periods at which major structural shifts occurred. The first was between 1967 and 1972, and the second was around the turn of the twenty-first century when food and energy expenditures no longer continued to decrease after 2002. In response to the latter, it is clear that the U.S. economy did trade off structural reserves (e.g., decreasing metrics of conditional entropy, redundancy, and equality) for structural efficiency (e.g., increasing metrics of efficiency, mutual constraint, and hierarchy) after food and energy expenditures increased post-2002. I also test the structural trends with increasingly simpler (e.g., fewer sectors) representations of the I-O tables, and the results are more consistent for I-O representations that account for inputs and outputs (e.g., value added and gross domestic product) rather than only the intermediate transactions among sectors. The findings of this paper have important implications for economic modeling in at least two ways. First, the paper helps explain how fundamental shifts in resources costs relate to economic structure and economic growth. Second, the paper shows that the number of sectors used to represent economic transactions influences the systemic metrics themselves.

show abstract

Energetic Limits to Economic Growth

Cited by 201 publications

References 37 publications

Energy and time determine scaling in biological and computer designs

Energy and time determine scaling in biological and computer designs

Does a Change in Price of Fuel Affect GDP Growth? An Examination of the U.S. Data from 1950–2013

Information Theory to Assess Relations Between Energy and Structure of the U.S. Economy Over Time

Contact Info

Product

Resources

About