Living the good life in a non-growth world: Investigating the role of hierarchy

This is the first of two essays written for (and supported by) the Seoul Platform for Initiating Discourses on an Equitable and Resilient Society. These essays investigate the role that hierarchy plays in driving inequality and unsustainability. This piece introduces the facts of hierarchy. The second (long-form) essay will look at how these facts relate to ‘living the good life in a non-growth world’.

Sustainability or bust

For the past 200 years, humanity has conducted an unintended experiment. The (tacit) research question is this: how much of the Earth’s resources can one species consume? We have yet to find out the answer … nor do we want to.

By nearly all indicators, humanity is doing immense damage to the biosphere. We are using non-renewable resources at a feverish pace [1]. We may be causing the Earth’s sixth mass extinction [2]. And perhaps most alarmingly, we are changing the climate in a way that could put civilization at risk [3]. It is time, then, for our unintended experiment to stop. Instead of plumbing the depths of unsustainability, we must do the opposite. Humanity must become sustainable. The question is, how?

In one sense, the answer is simple. Our impact on the environment is a function of two things: (1) how many people there are; and (2) the amount of resources each person consumes [4]. Becoming sustainable is therefore easy in principle. It requires reducing the human population and reducing resource consumption per person. And yet beneath this simple formula is a web of complexity (and confusion). Here, I will ignore population reduction (which is itself controversial). I will focus on achieving sustainability by reducing per capita resource use.

Mainstream discussions of sustainability tend to focus on efficiency [5,6]. If we can use resources more efficiently, the thinking goes, we will lessen our environmental impact. The problem, though, is that there is little evidence that this is true. Our energy conversion technologies, for instance, have been getting more efficient for two centuries [7]. Yet this greater efficiency has not caused us to consume fewer energy resources. Instead, we are using more than ever. In fact, it may be that efficiency is a primary driver of resource consumption. The reason is simple: more efficient technology tends to lower costs, which then makes resources cheaper. And so we consume more of them [8].

Outside the mainstream, more emphasis is put on directly reducing resource use by consuming less. This thinking goes by many names, but here I will refer to it as ‘degrowth’. The idea is that instead of pursuing economic growth, we should learn how to live with less. We should voluntarily ‘degrow’ the economy [9,10].

My view is that degrowth is the only sound option for becoming sustainable. I will leave aside the question of how much we need to degrow. Instead, I will focus on how we can consume less while creating a society that is equitable and just.

The human need for equity

A sustainable future need not be equitable. That is because our impact on the Earth is a function of the average resource use per person. To the Earth, it doesn’t matter if we use resources equitably, or if one person consumes almost everything and the rest of us starve. It does, however, matter to humans.

There is little that is so toxic to human welfare as rampant inequality. When inequality increases, human well-being gets worse [1113]. This is perhaps one of the most robust findings of the last few decades of social science. In the landscape of neoliberal politics, it is a finding that is surprising. But in the landscape of human evolution, it is not. Humans are a social species. As such, our welfare is inseparable from our relations with others. If these relations are unequal, those at the bottom do worse — regardless of their absolute standard of living. This is not a quirk, but rather a feature we share with other primates [14]. Among social animals, relationships matter.

Assuming we want an equitable society, how can we achieve it while consuming less? Because voluntary degrowth remains largely untested, there are no definitive answers. But I think there are hints. What I will explore, in this essay, is how resource use and equity both relate to hierarchy.

Hierarchy — the ranking of individuals — is part of most social species [1419]. Humans, however, take this form of organization to a new level. We are unique among animals in having developed an explicit chain of command in which power flows from superior to subordinates. This chain of command allows large human groups to function cohesively in a way that no animal group can [20]. But hierarchical organization comes at a cost. Hierarchy concentrates power, and that leads to despotism and inequality. Less intuitively, hierarchy also appears to be energy intensive. As we organize in larger hierarchies, we tend to consume more energy.

In this introductory essay, I will focus on the facts of hierarchy. I will show how hierarchy relates to energy use and to inequality. In the long-form essay to follow, I will explore how these facts pertain to ‘living the good life in a non-growth world’.

Energizing hierarchy1

That humans organize in hierarchy is a fact that should surprise no one. Our working lives are dominated by taking and giving orders [22]. What many people do not know, however, is that hierarchy has a direction — towards more of it.

This trend is recent. Only in the last two centuries has hierarchy grown significantly. While the exact reasons for this growth remain poorly understood, what we can say (with reasonable certainty) is that hierarchy is connected to energy.

I will make the case for this energy-hierarchy connection using indirect evidence. (I do so because direct data for the growth of hierarchy does not yet exist.) The first strand of evidence comes from institution size. As energy use increases, institutions tend to become larger. Figure 1 shows the trend for business firms. In the main panel, each dot represents a country. I have plotted the country’s average firm size (measured in terms of the number of employees) on the vertical axis, and energy use per capita on the horizontal axis. The trend is clear: as countries use more energy, firms tend to get larger.

Figure 1: As countries use more energy, firms get larger. The main panel shows how average firm size (within countries) changes with energy use per capita. Color indicates a country’s energy quartile. I have labelled countries using alpha-3 codes. The inset plot shows the firm size distribution within each respective energy quartile. [Sources and methods].

What we cannot tell, by looking at averages, is how this firm growth happens. It could be that the average grows because most firms get slightly larger. It turns out, however, that this is not what happens. As energy use increases, most firms remain small. Instead, average firm size grows because a few large firms get larger still.

We can see this trend in the inset panel in Figure 1. Here I plot the size distribution of firms across countries, grouped by energy quartile. (In the main plot, I have used color to indicate each quartile.) The horizontal axis shows firms size, while the vertical axis shows the portion of firms that are the corresponding size. What is important here are two things. First, most firms are small — and this remains so regardless of energy use. Second, what changes with energy is the number of large firms. More energy means more large firms. It is a rich-get-richer dynamic. Most firms stay small, but a few large ones grow larger still.

Similar trends hold for government. As countries use more energy, government tends to grow larger. For a thorough review of the energy-institution-size evidence, see [23].

The firm-size evidence hints that hierarchy grows with energy use. Here is the reasoning. From our working lives, we know that firms are hierarchically organized. Therefore, as firms grow larger, it follows that hierarchy increases. This, I believe, is sound logic. But is there evidence that it is true?

Figure 2 shows one strand of evidence that confirms our reasoning. Here, I look at the how the managers’ share of employment relates to energy use. The idea is that the relative number of managers provides a window into the amount of hierarchy in a society. The reason is simple: a manager’s job is to command others. It is a job that, without hierarchy, could not exist. So the growth of managers is indirect evidence for the growth of hierarchy.

Figure 2: As countries use more energy, the relative number of managers increases. Each line represents the path through time of a country. The black line is the smoothed trend across all countries. I have labelled select countries with their alpha-3 codes. [Sources and methods].

What Figure 2 shows is that the relative number of managers tends to grow with energy use. Note, however, that the energy-manager trend is nonlinear. As energy use increases, the relative number of managers grows rapidly at first, but then plateaus.

This non-linear trend, it turns out, is exactly what we expect if hierarchy grows with energy use. The reason has to do with a basic feature of hierarchical organization. In a hierarchy, the number of ranks tends to grow with the logarithm of group size [24]. When a hierarchy is small, adding more members quickly adds more ranks, and hence, more managers. But as the group continues to grow, new ranks are added less rapidly. So the growth of managers slows. Eventually, the hierarchy becomes so large that the portion of people in top ranks becomes constant. The relative number of managers stops growing.

When we formalize this model, it produces the trend shown in Figure 3. Here, black points are the empirical data (the same as in Fig. 2). The rainbow is the model prediction, where color indicates the span of control (how many subordinates each superior controls in a hierarchy). The inset panel shows how the best-fit model compares to the empirical trend. The fit is excellent. The model therefore suggests that managers become more common (as energy use increases) because hierarchy is growing. (See [25] for details about the model.)

Figure 3: A model of the growth of managers. Black points are empirical observations for energy use and the relative number of managers (the same data as in Figure 2). Colored points represent the model results. Color indicates the span of control in the model — the number subordinates controlled by each superior. The inset panel shows how the best-fit model relates to the empirical trend across all countries. [Sources and methods].

To summarize, there is strong (but indirect) evidence that as energy use increases, hierarchy grows. This fact has many implications for sustainability, which I will discuss in the long-form version of this essay. But for now, let’s move on to another feature of hierarchy — its role in driving inequality.

Hierarchical inequality

The fact that humans organize in hierarchies is, in some ways, unsurprising. The social scientist Herbert Simon thought that hierarchy was a fundamental part of all complex systems [26]. Here was his reasoning.

Hierarchy, Simon noted, allows a complex system to be built from simpler components. Cells, for instance, are built from organelles. And multi-cellular organisms, in turn, are built from cells. This hierarchical organization, Simon thought, is how blind evolution can build complex systems. It does so from the bottom up using trial and error.

Hierarchy is also important, Simon proposed, because it centralizes control. The human body, for instance, is not composed of a mass of autonomous cells. Instead, cells surrender their autonomy to the central nervous system — the body’s command center. The advantage is that this hierarchical organization allows complicated behavior like running — something that would be unthinkable if each cell in the body acted independently. But there is one big disadvantage to this concentration of power — despotism.

True, we do not usually think of cells as being despotic. But that is because multicellular organisms have evolved ways to suppress the selfish tendencies of individual cells [27,28]. So unless there is pathology, we never see brain cells using their control over the body for selfish gain.

Among humans, things are different. Like the cells of the body, humans use hierarchy to organize. But unlike our cells, individual humans retain a healthy dose of selfishness. And so when given the chance, individuals inevitably use their hierarchical power to enrich themselves. The result is that hierarchy is a double-edged sword. It is a potent tool for organization. But it is also a pathological tool for despotism and inequality [29].

The evidence for hierarchical inequality is quite straightforward. Within hierarchies, access to resources (i.e. income) tends to grow with control over subordinates. The more subordinates you have, the greater your relative income. Figure 4 shows the evidence. I plot here relative income in a hierarchy against something I call ‘hierarchical power’ — a shorthand for control over subordinates. I define hierarchical power as:

hierarchical power = number of subordinates + 1

The idea here is that everyone starts with a hierarchical power of 1, indicating that they have control over themselves. As you accumulate subordinates, your hierarchical power increases. And, as Figure 4 indicates, so does your income.

Figure 4: Inside hierarchies, relative income grows with hierarchical power. I plot here the relation between relative income (within a hierarchy) and hierarchical power (the number of subordinates + 1). In case-study firms and the US military, I measure income relative to the lowest hierarchical rank. For CEOs, I measure income relative to the firm average. [Sources and methods].

In Figure 4, I plot three different sources of data. Red points come from six case studies of firm hierarchy [30]. Blue points represent the US military (over the last decade). For both the military and case-study firms, each point represents the average income and hierarchical power of a given rank. Green points represent a sample of US CEOs. Each point is an individual CEO [31].

Across a variety of different institutions, it seems that relative income grows with hierarchical power. This suggests that hierarchy is a key driver of inequality [32]. Exactly how hierarchy creates inequality, however, remains poorly understood. In the long-form essay to follow, I will speculate about some of the mechanisms at work.

The sustainable good life

A common thread among degrowth thinkers is that sustainability requires an end to corporate globalism and a transition to community localism. The evidence reviewed here lends credence to this view. The growth of large corporations seems to go hand in hand with using more energy. It makes sense, then, that a reversal towards smaller institutions would help us consume less energy. It is not clear, however, which causes which. Would degrowth energy policy automatically lead to smaller institutions? Or should we focus on making smaller institutions, with energy reduction coming as a side effect? I will investigate these questions in the long-form essay to follow.

And what about inequality? It is tempting to think that if we pursue community localism, inequality will naturally go away. The reasoning is that smaller institutions will have less hierarchy, and hence, less inequality. Unfortunately, this reasoning turns out to be false. The problem (which I will explore in the long-form essay to follow) is that hierarchy is fundamentally non-linear. This means that shrinking large hierarchies has almost no effect on inequality … until the hierarchy has become very small. Pursuing small-scale localism, then, will likely not guarantee equity. Instead, we will need explicit policies for reigning in hierarchical despotism. I will explore these ideas more in the next instalment.


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Sources and methods

Data for average firm size (Fig. 1) comes from the Global Entrepreneurship Monitor. See the appendix in [23] for details. Data for energy use per capita comes from the World Bank, series EG.USE.PCAP.KG.OE. To these values I add an estimate for energy consumed through food (2000 kcal per day).

Data for managers’ share of employment (Fig. 2) is from ILOSTAT Table TEM_OCU, series EMPoc1P.

The energy-manager model (Fig. 3) assumes that firms grow larger with energy use, as shown in Figure 1. Second, the model assumes that firms are hierarchically organized, where each superior controls the same number of subordinates — the ‘span of control’. Third, the model assumes that managers occupy the top two hierarchical ranks. For details about the model, see [25].)

Data for relative income vs. hierarchical power (Fig. 4) are from:

  • Case-Study Firms: Data is from [3338]. For details about these studies, see the appendix in [30].
  • US CEOS: Data is from Compustat and Execucomp. For details, see [31].
  • US military: Data is from annual demographics reports (Demographics: Profile of the Military Community) between 2010 and 2019. I exclude warrant officers from the data. I calculate the pay within each rank as the average of the minimum and maximum pay by years of experience.

Note: The CEO data in Figure 4 is slightly different than the other two datasets. In case-study firms and in the US military, I have indexed income relative to the average in the lowest hierarchical rank. For CEOs, however, I have indexed CEO pay to the average in the whole firm. And I have estimated CEO’s hierarchical power from firm size. I assumed that every other employee in a firm is subordinate to the CEO. As such, in a firm with x employees, x − 1 are subordinate to the CEO. So the CEO has hierarchical power of x − 1 + 1 = x. The CEO data, then, is not strictly comparable to the other data. But to illustrate the general trend, I neglect this technicality.

References

[1] Heinberg R. Peak everything. Gabriola Island 2007.

[2] Kolbert E. The sixth extinction: An unnatural history. A&C Black; 2014.

[3] Ehrlich PR, Ehrlich AH. Can a collapse of global civilization be avoided? Proceedings of the Royal Society B: Biological Sciences 2013; 280: 20122845.

[4] Ehrlich PR, Holdren JP. Impact of population growth. Science 1971; 171: 1212–7.

[5] Weizsäcker EUv. Factor four: Doubling wealth, halving resource use: The new report to the Club of Rome. London: Earthscan Publications; 1997.

[6] Hawken P. Natural capitalism: Creating the next industrial revolution. Boston: Little; 2000.

[7] Ayres RU, Warr B. The economic growth engine: How energy and work drive material prosperity. Cheltenham, UK: Edward Elgar Publishing; 2010.

[8] Polimeni J, Mayumi K, Giampietro M, Alcott B. The Jevons paradox and the myth of resource efficiency improvements. London: Routledge; 2012.

[9] Latouche S. Degrowth economics. Le Monde Diplomatique 2004; 11: 2004.

[10] Kallis G. In defence of degrowth. Ecological Economics 2011; 70: 873–80.

[11] Wilkinson RG. Mind the gap: Hierarchies, health and human evolution. Yale University Press; 2001.

[12] Wilkinson RG, Pickett K. The spirit level: Why more equal societies almost always do better. New York: Penguin Books; 2009.

[13] Wilkinson RG. Unhealthy societies: The afflictions of inequality. Routledge; 2002.

[14] Sapolsky RM. The influence of social hierarchy on primate health. Science 2005; 308: 648–52.

[15] Barroso FG, Alados CL, Boza J. Social hierarchy in the domestic goat: Effect on food habits and production. Applied Animal Behaviour Science 2000; 69: 35–53.

[16] Guhl AM, Collias NE, Allee WC. Mating behavior and the social hierarchy in small flocks of white leghorns. Physiological Zoology 1945; 18: 365–90.

[17] Kondo S, Hurnik JF. Stabilization of social hierarchy in dairy cows. Applied Animal Behaviour Science 1990; 27: 287–97.

[18] Meese GB, Ewbank R. The establishment and nature of the dominance hierarchy in the domesticated pig. Animal Behaviour 1973; 21: 326–34.

[19] Uhrich J. The social hierarchy in albino mice. Journal of Comparative Psychology 1938; 25: 373.

[20] Turchin P. Ultrasociety: How 10,000 years of war made humans the greatest cooperators on Earth. Chaplin, Connecticut: Beresta Books; 2016.

[21] Bichler S, Nitzan J. Growing through sabotage: Energizing hierarchical power. Review of Capital as Power 2020; 1: 1–78.

[22] Marglin SA. What do bosses do? The origins and functions of hierarchy in capitalist production. Review of Radical Political Economics 1974; 6: 60–112.

[23] Fix B. Energy and institution size. PLOS ONE 2017; 12: e0171823.

[24] Fix B. Putting power back into growth theory. Review of Capital as Power 2015; 1: 1–37.

[25] Fix B. Economic development and the death of the free market 2020. https://doi.org/doi:10.31235/osf.io/g86am.

[26] Herbert S. The architecture of complexity. Proceedings of the American Philosophical Society 1962; 106: 467–82.

[27] Sober E, Wilson DS. Unto others: The evolution and psychology of unselfish behavior. Harvard University Press; 1999.

[28] Wilson DS. Does altruism exist? Culture, genes, and the welfare of others. Yale University Press; 2015.

[29] Fix B. An evolutionary theory of resource distribution. Real-World Economics Review 2019: 65–97.

[30] Fix B. Personal income and hierarchical power. Journal of Economic Issues 2019; 53: 928–45.

[31] Fix B. How the rich are different: Hierarchical power as the basis of income size and class. Journal of Computational Social Science 2020: 1–52.

[32] Fix B. Energy, hierarchy and the origin of inequality. Plos One 2019; 14: e0215692.

[33] Audas R, Barmby T, Treble J. Luck, effort, and reward in an organizational hierarchy. Journal of Labor Economics 2004; 22: 379–95.

[34] Baker G, Gibbs M, Holmstrom B. Hierarchies and compensation: A case study. European Economic Review 1993; 37: 366–78.

[35] Dohmen TJ, Kriechel B, Pfann GA. Monkey bars and ladders: The importance of lateral and vertical job mobility in internal labor market careers. Journal of Population Economics 2004; 17: 193–228.

[36] Lima F. Internal labor markets: A case study. FEUNL Working Paper 2000; 378.

[37] Morais F, Kakabadse NK. The corporate Gini index (cgi) determinants and advantages: Lessons from a multinational retail company case study. International Journal of Disclosure and Governance 2014; 11: 380–97.

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  1. I thank Shimshon Bichler and Jonathan Nitzan for coining the phrase ‘energizing hierarchy’ [21].

8 comments

  1. Please expand on your assertion regarding inequality that “This means that shrinking large hierarchies has almost no effect on inequality … until the hierarchy has become very small.” I thought you had presented an excellent case that increasing hierarchy meant increasing inequality (Figure 4). You also point out that “Therefore, as firms grow larger, it follows that hierarchy increases”. If so, what aspect of hierarchy creation prevents the reversal of the process (lower firm size means less hierarchy means less inequality)?

    Like

  2. Hi Blair, been reading your blog for a while, great work. I was wondering if you have ever heard of or read the book “The Great Leveler” by Stanford historian Walter Scheidel? He makes a convincing case, at least to me, that throughout all of recorded history, only catastrophically violent events (severe pandemics, world wars, bloody revolutions, and wholesale collapses) have significantly stopped or reversed overall inequality. His thesis is that as long as economic surplus and hereditary wealth transfer exist, rising inequality is the natural order of things until checked by a violent “leveler.” The violent part is heavily stressed. Without that, he posits, there is no significant reduction in inequality. For example, he directly credits the modern welfare states of Europe to the carnage of the world wars. Any thoughts on this?
    Thanks

    Like

    • Hi vanitas,

      I have not read Scheidel’s book. I’ll put it on my list. His thesis seems plausible, but so do many hypotheses about human history. The harder part is tested these hypotheses rigorously. That’s something Peter Turchin is trying to do with his SESHAT project.

      A counterpoint here is that there are significant inequality differences between countries. I’m skeptical that the “Great Leveler” can explain all of these differences. But it does seem true that significant reductions in inequality tend to come with crises.

      Like

  3. Hi Blair, Its really great to see you move your sharp analytical focus to the possibility of achieving Degrowth. I feel that your interest in hierarchy (and its effects) and now in Degrowth will be well served by consideration of the cooperative model as offering a potential solution to both. For example I have just found this paper from 2012 ‘Cooperative governance: One pathway to a stable-state economy’ (https://www.researchgate.net/publication/232909324_Cooperative_governance_One_pathway_to_a_stable-state_economy). Regards.

    Like

  4. Quite dissappointed you took a population approach here. You’ve likely seen the stat that 100 companies are responsible for 70% of global emissions so why take people as your unit of analysis? Here’s a link as a refresher. https://www.theguardian.com/sustainable-business/2017/jul/10/100-fossil-fuel-companies-investors-responsible-71-global-emissions-cdp-study-climate-change

    Another way to cut it is that cities are responsible for 70% of emissions as well. 56% of people live in cities today and these structures require an enourmous amount of energy to build, but also maintain. The GTA is built around the automobile, the structure itself cannot be sustained without a flow of traffic and petrol. Friends coming from the suburbs and collecting in downtown Toronto have an hour commute.The very shape of our cities consumes more energy.

    These cities do not produce their own food either. It needs to be trucked in from afar and often internationally with poorer regions servicing wealthy urban areas. The hierarchial shape you may want to look at isn’t just companies, but human geography.

    Abolishing the city sounds far less reasonable than “degrowth” though and placing responsiblility on individual actions. There’s a long lost tradition of socialist literature that focussed on urban planning, indeed the feild of urban planning was socialist from the beginning.

    Focusing on degrowth may not be the best approach either. When you’re trying to quit one habit you should form a new one to replace it. John Ruskin said “there is no wealth but life” and since we are in a mass exinction right now, we are arguably already poor and de-growing. Perhaps its best to try and shepard biodiversity back to health.

    As always I look forward to your next peice. I know this is just an article and entire libraries can be dedicated to the topic but I figured I would leave you with a few interesting notes. I plan to write a book about the socialist history of human space in the future.

    Like

  5. Hey Blair!

    I think your research on energy and hierarchy could benefit from a more explicit consideration of information technologies as an important mediator between energy use and social structure.

    If we think of the brain as a technology, this is already implicit in your consideration of Dunbar’s number. However to understand the role of hierarchy today requires determining how exosomatic information storage and processing modifies human organizational capabilities.

    Some articles:
    Shin et al. (2020) “Scale and information-processing thresholds in Holocene social evolution”
    Dunbar (2016) “Do online social media cut through the constraints that limit the size of offline social networks?”
    Dunbar et al (2015) “The structure of online social networks mirrors those in the offline world”

    My hypotheses:
    1) Development and diffusion of new information technologies create transitional periods of relative or absolute decoupling of energy use from hierarchy; and mathematical relationship between energy use and hierarchy changes between different “socio-technical regimes”.

    ^simple test: use historical data to construct time periods for different ICT “regimes” and “transitions”; test how relationship between energy and hierarchy change between regimes and during major transitions.

    2) Modern information technologies do not fundamentally alter biological constraints on the number of interactions (Dunbar’s number) but instead remove the geographic constraints on interactions.

    Like

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