After several decades of discussions, mainstream economics still does not recognize the crucial role that energy plays in the economic process. Hence, the purpose of this article is to reformulate a clear and in-depth state of knowledge provided by a thermo-evolutionary perspective of the economic system. First, definitions of essential concepts such as energy, exergy, entropy, self-organization, and dissipative structures are recalled, along with a statement of the laws of thermodynamics. The comprehension of such basics of thermodynamics allows an exploration of the meaning of thermodynamic extremal principles for the evolution of physical and biological systems. A theoretical thermo-evolutionary approach is then used to depict technological change and economic growth in relation to the capture of energy and its dissipation. This theoretical analysis is then placed in a historical context. It is shown that during the entirety of human history, energy has been central to direct the successive phases of technological change and economic development. In particular, energy is crucial to understanding the transition from foraging to farming societies on the one hand, and from farming to industrial societies on the other. Finally, the theoretical and historical insights previously described are used to discuss a possible origin of the economic slowdown of the most advanced economies for the last 40 years. The article concludes that conventional economic growth theories should finally acknowledge the central role that energy plays in the economic process.
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The birth of a coherent body of evolutionary economic thoughts is generally attributed to Nelson and Winter (1982). Nevertheless, Hodgson (1993) notes that economic evolutionary concepts can be found in the work of Marx, Veblen, Marshall, and Schumpeter; whereas van den Bergh (2007) highlights that similar evolutionary concepts are present in the work of the founding fathers of ecological economics such as Boulding and Georgescu–Roegen.
In Acemoglu (2009) and Aghion and Howitt (2009), energy is mentioned in relation to just one econometric study that investigates innovation in energy sectors. The less mathematically formalized and more historically oriented book by Weil (2013) does a slightly better job than other economic growth textbooks, it does mention energy several times, essentially in the context of the Industrial Revolution. The third edition of Jones and Vollrath (2013)’s textbook dedicates a whole chapter to exhaustible resources that was not present in previous editions.
Among more than thirty unified growth models that do not consider energy, Fröling (2011) is the only one exception.
One joule (J) is defined as the quantity of mechanical work transferred to an object by moving it a distance of one meter (m) against a force of one newton (N), i.e., 1 J = 1 Nm. One newton is the force needed to accelerate one kilogram (kg) of mass at the rate of one meter per second (s) squared in the direction of the applied force, i.e., 1 N = 1 kg m/s2 . In the context of energy transfer as heat, 1 J = 0.2389 calorie, and one calorie represents the energy needed to raise the temperature of one gram of water by one degree Celsius at a pressure of one standard atmosphere (corresponding to 101,325 Pascal).
It is important not to confuse useful energy with energy services. As put by Cullen and Allwood (2010), energy services (transport of passengers and goods, space heating, and illumination) are the outcomes of the interaction of useful energies (mechanical drive, heat, and light) with passive devices/infrastructures. Hence, all useful energy flows are measured in joules, whereas energy services take different units of measurement such as passenger-km or tonne-km for transport, and lumen for illumination.
Earlier equivalent terms to name exergy are available work, available energy (or even availability), and free energy. For the sake of completeness and clarity, “Gibbs free energy” represents exergy in a particular process performed at constant temperature and pressure, whereas “Helmholtz free energy” represents exergy in a particular process performed at constant temperature and volume.
As noted by one of the anonymous reviewers of this article, there is a tacit value judgment when using exergy instead of energy. Exergy values energy for its ability to produce mechanical work, whereas energy values the exact same flow for its ability to produce heat. There are applications in which exergy is more appropriate (manufacturing, transportation, etc.), whereas energy is more appropriate for other applications (home heating, for example).
The absolute or thermodynamic temperature uses the Kelvin (K) scale and selects the triple point of water at 273.16 K (= 0.01 °C) as the fundamental fixing point. Like the Celsius scale (but not the fahrenheit scale), the Kelvin scale is a centigrade scale so that conversions between Kelvin and Celsius scales are simple: 0 K ≡ − 273 °C, 273 K ≡ 0 °C.
For a given macrostate characterized by plainly observable average quantities of macroscopic variables such as temperature, pressure, and volume, entropy measures the degree to which the probability of the system is spread out over different possible microstates. In contrast to the macrostate, a microstate specifies all the molecular details about the system, including the position and velocity of every molecule. Hence, the higher the entropy, the higher the number of possible microscopic configurations of the individual atoms and molecules of the system (microstates) which could give rise to the observed macrostate of the system.
For example, Shannon (1948) uses the term entropy to describe his measure of statistical uncertainty associated with the efficiency with which a message is communicated from a sender to a receiver. Hence, Shannon’s entropy bears no direct relationship with the original energetic concept of entropy.
There are a total of four laws of thermodynamics, but only the first and second are useful to understanding the economic process. The zeroth law of thermodynamics states that if two systems are in thermal equilibrium with a third system, they are in thermal equilibrium with each other. This law helps to define the notion of temperature. The third law of thermodynamics states that the entropy of a system approaches a constant value as the temperature approaches absolute zero, and with the exception of non-crystalline solids (glasses), the entropy of a system at absolute zero is typically close to zero.
Yen et al. (2014) provide a review of all thermodynamic extremal principles developed in the context of ecological systems. Apart from maximum entropy, alternatives include the maximum exergy storage of Jorgensen and Svirezhev (2004), the maximum ascendency of Ulanowicz (2003), the maximum ‘E intensity’ of Milewski and Mills (2010), and the maximum rate of cycling of Morowitz (1979). Furthermore, Yen et al. (2014) show that all these thermodynamic extremal principles are consistent with the maximum entropy production principle, including the maximum power principle of Odum and Pinkerton (1955), and the maximum rate of gradient degradation of Schneider and Kay (1994).
Weber et al. (1989) and Depew and Weber (1995) also provide comprehensive discussions on the interplay of Darwinian natural selection, self-organization, and the thermodynamic laws. In particular, they argued that a thermodynamic approach of living systems released Darwinism from its deterministic Newtonian anchoring because dissipative structures are characterized by tendencies towards spontaneous self-organization and non-deterministic bifurcations.
The Constructal law, which is supposed to be an encompassing formulation of all thermodynamics concepts and ideas, including the maximum entropy production principle, was intentionally not discussed in "Methods: Basics of Thermodynamics and the Evolution of Natural Systems" section. Bejan (1997) formulates his Constructal law as follows: “For a finite-size flow system to persist in time (to live), its configuration must evolve in such a way that provides greater and greater access to the currents that flow through it.” This supra-law is supposed to explain the dynamics of all physical, biological, or economic/cultural systems. However, when dealing with the economic process as in Bejan and Lorente (2011), the Constructal law seems to not bring anything new and to not be very useful. Basically, it says that energy is important for economic growth and that things happen the way they happen because it is the most logical/easiest way they can happen given existing constraints. The Constructal law gives the impression of being the modern reformulation of an old idea rather than a new path-breaking theory as claimed by its author. Hence, Spencer (1897, p. 249) already stated that “when we contemplate a society as an organism, and observe the direction of its growth, we find this direction to be that in which the average of opposing forces is the least. Its units have energies to be expended in self-maintenance and reproduction.”
For instance, the price of gasoline is constituted of capital interest, labor payment, and various taxes that are required to extract and refine the crude oil provided free-of-charge by nature.
Besides, Ayres et al. (2013) argue that there are also some soft constraints—corresponding to social, financial, organizational, or legal restrictions—that determine additional limits to substitution possibilities between inputs over time.
The co-evolution between genetic and cultural elements has been intensively explored since the 1980s, recent references include Richerson and Boyd (2005) and Jablonka and Lamb (2014). See also Vermeij (2009) on the fact that intentionality, preferences, and purposive utility are surely better developed in humans than in other living beings but are not unique to the former.
Accordingly, if the aggregate production function is to match the historical GDP pattern more closely, a time-dependent multiplier (generally noted A) representing TFP must be added to take into account the technological progress of the economy. Moreover, in empirical growth studies, TFP contains desired components such as the effect of technical and institutional innovations, but it also includes unwanted elements such as measurement errors, omitted variables, aggregation bias, and model specifications.
This issue is the subject of an important debate among evolutionary economists. ‘General Darwinism’ supported by Hodgson (2002) and Knudsen (2002) is a core set of Darwinian principles that, along with auxiliary explanations specific to each scientific domain, is considered applicable to a wide range of phenomena. Hence, proponents of this theory argue that evolutionary aspects of the biological and the cultural spheres both involve the general Darwinian principles of variation, selection, and replication. On the contrary, the ‘continuity hypothesis’ of Witt (2003) and Cordes (2006) rejects the application of abstract principles derived from Darwinism to socio-economic evolution. According to this perspective, at some point in time Darwinian evolutionary theory lost its power to explain human behavior. This means that after a period of co-evolution with natural evolution, cultural evolution eventually allowed forms of human behavior to emerge that entailed a strong relative reproductive success, reducing selection pressure significantly and increasing behavioral variety. In particular, the ‘continuity hypothesis’ argues that human goal-directed behavior renders the functioning of the three mechanisms of selection, variation, and replication interdependent rather than independent as in the biological world. Moreover, purposeful human action, the deliberate choosing of certain entities, gives rise to ‘directional’ change in cultural evolution. By contrast, Darwinian natural selection is not carried out by intelligent agents who purposefully choose among design possibilities. As a result, the processes and criteria of economic/cultural selection are very different from natural Darwinian selection affecting biological organisms (Cordes 2006, p. 538). ‘Generalized Darwinism’ is surely a framework of higher-level abstraction than the ‘continuity hypothesis,’ but rather than their opposition, future work will probably show the complementarity of these theories.
For Kauffman (1993) an entity becomes individual-like, and therefore subject to selection and adaptation, when the rate of change among its components is less than the rate of sorting among like entities, that is, when the whole is intact long enough not to dissolve into chaos. According to Vermeij (2009), the criteria for entities as units of evolution are the ability to multiply, inheritance of traits, and variation in these traits among individuals. Accordingly, organisms qualify as evolutionary units but larger and more intangible entities such as coalitions, species, coherent societies, languages, cultures, and even some ecosystems can also be understood as evolutionary units. In such circumstance, units of selection are diverse and change over the course of evolution, which complicate the overall analysis of this phenomenon. The definition of the unit of selection in the evolutionary economic process that I choose here as ‘a module of routine’ is so general that it circumvents this issue.
It is interesting to note that Beinhocker (2006, p. 294) advocates market economies, not because they are the best method for allocating financial resources in a way that optimizes social welfare under conditions of equilibrium as neoclassical economics supposes it, but because they offer an evolutionary search mechanism that incentivizes deductive-tinkering leading to differentiation (of routines’ module) and then provides a fitness function upon which economic selection can act.
1 gigajoule (GJ) \(\equiv\) \(10^9\) J.
Sahlins also adds that by foraging only for their immediate needs among plentiful resources, hunter-gatherers are able to increase the amount of leisure time available to them. So for Sahlins (1972, p. 2), the original affluent society is that of the hunter-gatherers, and not the Western modern one where “man’s wants are great, not to say infinite, whereas his means are limited, although improvable” by productivity increases. Several criticisms have been developed against Sahlins’ ideas, see Kaplan (2000) for a summary.
The idea of a ceiling imposed by the organic energy supply on the capacity of development of pre-modern economies should be clarified in two ways. First, this limit was not determined at a fixed value as it could move upward (respectively downward) in the case of physical and social technological progress (respect. regress). Second, changing climatic and disease conditions implied a fluctuation of both the energy supply and standards of living per capita in the pre-modern world. Accordingly, medium-term oscillations around decreasing or increasing long-term trends characterized pre-modern economies, whereas a smoother upward long-term trend is more representative of the modern fossil regime.
It is important to understand that all these scholars do not denigrate the many scientific breakthroughs that episodically originated in China and Islamic countries. They rather highlight the earliness of Britain in creating a scientific culture able to transpose useful knowledge into technological change thanks to a favorable institutional environment. Similarly, Lipsey et al. (2005, pp. 225–289) argued that Islam is an occasionalist doctrine in which the state of the world at any one moment in time is contingent on the particular will of God. On the contrary, the doctrine of Christian naturalism posits that God created the world according to natural laws and then endowed humans with free will to determine their own affairs. For Lipsey et al. (2005, pp. 225–289), this difference was decisive to see the apparition of science in early modern Europe, whereas Islam developed hostility against free inquiry and mechanistic science. Moreover, according to the same authors, the incapacity of China to develop an original version of modern science on its own has more to do with the absence of institutions that would save and organize cumulative knowledge, whereas on the contrary Europe elaborated an early institutionalization of scientific research through universities and scientific societies.
Ayres and Warr (2009, pp. 52–53) highlight that modern technological change at the macro level is ultimately defined by the limiting efficiency of all metallurgical, chemical, and electronic processes at micro levels, which in turn depend essentially on the properties of structural materials. Indeed, some technologies, such as prime movers and many metallurgical reduction and synthesis processes, depend on the temperatures, and in some cases, pressures, achievable in a confined space. These are limited by the strength and corrosion resistance (chemical inertness) of structural materials at elevated temperatures. In the same way, turbines’ efficiencies also depend on the precision with which blades, piston rings, gears, and bearings can be manufactured, which depends in turn on the properties of materials being shaped and the properties of the ultra-hard materials used in the cutting and shaping of tools.
In France, it is even remembered with nostalgia as the ‘Glorious Thirty.’
Differences lie in (i) the fact that Brockway et al. (2014) only take into account the above-basal-need food intake needed for heavy labor, while Warr et al. (2010) consider the entire food intake of people; (ii) a higher assumption for food conversion efficiency into muscle work in Brockway et al. (2014) compared to Warr et al. (2010); (iii) a higher mechanical drive efficiency in Brockway et al. (2014) compared to that from Warr et al. (2010) (e.g., 11% vs. 8%, respectively in 1960); and (iv) a higher heat efficiency in Brockway et al. (2014) as more heat is allocated to Low Temperature Heat end-use in Warr et al.’s (2010) analysis (e.g., 12% vs. 7%, respectively, in 1960).
As noted by one of the anonymous reviewers of this article, power plants could operate at a higher efficiency, but in doing so they would produce less power and would consequently generate less revenue. So the stagnation of the average US thermal power generation efficiency around 33% shown in Fig. 6a is not strictly due to thermodynamic limits. Rather, the emergence of this optimal efficiency is caused by the interaction of thermodynamic and economic constraints.
As noticed by Malanima (2016, pp. 95–99), usual social savings calculations based on relative costs of old and alternative technologies appear quite impossible here because it would require to compute counter-factual wood prices and labor wages in a theoretical British economy where coal would have been absent.
kWh refers to kilowatt hour, a derived unit of energy equal to 3.6 MJ, and 1 megajoule (MJ) \(\equiv\) \(10^6\)J.
Bloch (1935) questions the direction of causality between technological improvements related to energy capture (e.g., water mill, horse collar) and the progressive status change of European slaves into serfs from the Early (fifth to tenth centuries) and High Middle Ages (eleventh to thirteenth centuries). He does not use the word ‘co-evolution’ but his description of the process is in line with this concept.
Various explanations can be suggested for these mixed results, including the period under study, the countries in question (the level of development affecting the results), the level of disaggregation of the data (GDP or sectorial levels), the type of energy investigated (total energy, oil, renewable, nuclear, primary, final or useful energy, energy vs. exergy), the econometric method applied (OLS, cointegration framework, VAR, VECM, time series, panel, or cross-sectional analysis), the type of causality tests (Granger, Sims, Toda and Yamamoto, or Pedroni tests), and the number of variables included in the model (uni-, bi-, or multivariate model). As proposed by one of the anonymous reviewers of this article, another possible explanation for the inconclusiveness of causality studies could come from their sensitivity to changing constraints. If that is true, and if economies oscillate among energy, materials, capital, and labor being the binding constraint over the period studied, causality test will be inconclusive. No one factor will appear to drive growth, because each is the dominant constraint at different times.
There are many causality tests based on different definitions of causality. The main idea of the Granger causality test is to verify that adding past data of variable X to past data of variable Y enhances the prediction of the present value of variable Y. If the residuals generated from a model with variable Y and its past only, are significantly different from another model with the past of variable Y and the past of variable X, we can reject the assumption of non-causality from X to Y and accept the assumption of a causality running from X to Y.
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This work benefited from the support of the Chair Energy & Prosperity. I thank Adrien Nguyen-Huu and David Le Bris for their helpful comments on earlier versions of this article. I am also grateful to two anonymous referees for their fruitful comments and suggestions. All remaining errors are mine.
Conflict of interest
The author declares that he has no conflict of interest.
Appendix 1: Labor- and Land-Savings Thanks to Coal Use
To quantify the importance of coal as a source of both heat and mechanical power in the transition from limited to sustained economic growth, Malanima (2016, pp. 95–99) follows the seminal contribution of Wrigley (1962) in order to estimate land- and labor-savings due to coal use in England and Wales on the period 1560–1913.Footnote 31 The results presented in Fig. 7 exhibit two distinct historical phases. During the first one, that lasted from the end of the sixteenth century until about 1830, the use of coal was mainly land-saving. It is only during the second phase (from 1830 to 1900) that coal was really both land and labor-saving. Covering both phases from 1800 to 1900, the land-related (resp. labor-related) social savings grew from 1 to 14 times the extent of the entire country, that is 15 million hectares (resp. from 1 million to almost 300 million workers when the English population was 32 million and the labor force 13–14 million in 1900). These estimates strongly support Wrigley’s (2016, pp. 2–4) claim that “the energy required to produce, say, iron and steel on a large scale or to construct and operate a railway system implied that it was idle to expect that it could be secured from the annual flow of energy derived from plant photosynthesis” (italic emphasis in original). As a corollary, “an Industrial Revolution could not be accomplished as long as mechanical energy continued to be provided principally by human and animal muscle.”
Appendix 2: The ‘Energy Slave’ Concept and its Quantification
Focusing on the ‘energy slave’ concept, Kümmel (2011, p. 16) delivers a vivid analysis of the fundamental role that fossil fuels played in the transition towards modernity. He asserts that the human rights, as proclaimed by the United States Declaration of Independence in 1776, and market economics, as established the same year by The Wealth of Nations of Smith (1776), would not have become ruling principles of societies aspiring to freedom, had not the steam engines and more advanced heat engines provided the services that created the preconditions for toil relief. A sobering way to understand these assertions is to calculate the number of energy slaves in an economy. “This number is given by the average amount of energy fed per day into the energy conversion devices of the economy divided by the human daily work-calorie requirement of 2500 kcal (equivalent to 2.9 kWh or 10.5 MJ)Footnote 32 for a very heavy workload. In this sense, an energy slave, via an energy-conversion device, does physical work that is numerically equivalent to that of a hard-laboring human. Dividing the number of energy slaves by the number of people in the economy yields the number of energy slaves per capita.” Broadly speaking, the number of energy slaves at the service of a person has increased from one throughout the Paleolithic, to roughly ten in medieval Western Europe, to between 40 and 100 in modern Europe and North America. “And, of course, modern energy slaves work much more efficiently than medieval ones. It is also interesting that Jefferson’s original draft of the Declaration of Independence included a denunciation of the slave trade, which was later edited out by Congress. Only after industrialization had provided enough energy slaves could the noble words of the Declaration of Independence be finally put into practice—albeit not without the sufferings of the Civil War,” followed by decades of segregation and bigotry.Footnote 33 Mouhot (2011) extends the above analysis by arguing that both slave societies and developed countries externalize(d) labor and both slaves and modern machines free(d) their owners from daily chores. Consequently, modern societies are as dependent on fossil fuels as slave societies were dependent on bonded labor. Mouhot (2011) also suggests that, in different ways, suffering resulting (directly) from slavery and (indirectly) from the excessive burning of fossil fuels are now morally comparable.
Appendix 3: Econometrics of the En/Exergy-Growth Nexus
The crucial role of en/exergy in modern economies is supported by different econometric studies well summarized by Stern (2011). In addition to the work of Kümmel et al. (2002, 2010) on the controversial Linex production function (that shall not be further discussed here for the sake of brevity), Santos et al. (2018) have recently provided a new perspective on the question of the relative importance of production factors in an attempt to reconcile the ecological and neo-Keynesian approaches. Focusing on the particular case of Portugal over the last one hundred years, they find that production functions estimated from models where energy is absent from the cointegration space provide the worst fits. On the other hand, the best-estimated fit to past economic trends (and lowest total factor productivity component in growth accounting) is a two-input Cobb–Douglas function with quality-adjusted labor and capital, but with capital being a reconstructed variable as a function of useful exergy and labor and not the historical estimates retrieved from conventional data. In such a case, useful exergy is primordial to defining the actual utilization of capital in production, and estimated values of constant output elasticities for capital and labor are very similar to the average values for historically observed cost shares associated with these factors.
Finally, a word is needed on econometric studies that try to assess the direction of causality between energy and economic growth. Four assumptions are possible: (i) a relation of cause-and-effect running from energy consumption to economic growth, (ii) a causal relation running in the other direction from economic growth to energy consumption, (iii) a feedback relation between energy consumption and economic growth, and (iv) the absence of any causal relationship between energy consumption and economic growth. Unfortunately, after more than 40 years of research, and despite the increasing sophistication of econometric studies, this area of study has not led so far to a general methodological agreement or a preference for any of the four assumptions. More specifically, three independent literature reviews (Chen et al. 2012; Kalimeris et al. 2014; Omri 2014), covering respectively 39, 48, and 158 studies, have shown that no particular consensus has emerged from this empirical literature, and that the share of each assumption ranges from 20 to 30% of the total.Footnote 34 Nevertheless, both Stern (2011) and Santos et al. (2018) seem to indicate that when misspecification of early studies are avoided (e.g., choosing multivariate models instead of bi-variate) and if a quality-adjusted energy index is employed (e.g., based on exergy), energy is found to Granger cause GDP.Footnote 35
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Court, V. Energy Capture, Technological Change, and Economic Growth: An Evolutionary Perspective. Biophys Econ Resour Qual 3, 12 (2018). https://doi.org/10.1007/s41247-018-0046-3
- Energy capture
- Technological change
- Economic growth