In Search of New Economic Metaphors for Biology
A review of Eric D. Beinhocker, The Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics, Harvard Business School Press, 2006.
What if biologists were to go back and reread economics? This is the question I want to foreground.
It is well-known that Charles Darwin’s theory of natural selection was inspired in part by his reading of the Scottish economist Thomas Robert Malthus. In his 1798 book The Principle of Population, Malthus argued that the pattern of exponential growth in human population due to high birthrates would quickly overwhelm agricultural production (Malthus 1798). Malthus predicted a population collapse in Europe due to famine, disease, and war by the mid-19th century. Darwin read Malthus in 1838 and drew from him the concepts of geometric increase of populations in nature resulting in a universal struggle for existence. In the Origin of Species, Darwin credits Malthus directly:
It is the doctrine of Malthus applied with manifold force to the whole animal and vegetable kingdoms; for in this case there can be no artificial increase of food, and no prudential restraint from marriage. Although some species may be now increasing, more or less rapidly, in numbers, all cannot do so, for the world would not hold them. (Darwin 1859)
There can be no doubt that Darwin was also influenced by Adam Smith theory of laissez faire economics, though there is no clear paper trail in Darwin’s own writings. While Darwin cites Smith’s moral philosophy (Smith 1759) in his book The Descent of Man(Darwin 1871), it is only to ground Darwin’s own understanding of moral instinct in our social species. Darwin was surely also familiar with The Wealth of Nations, but there are no direct citations of that work by Darwin of which I am aware (Smith 1776). In Adam Smith’s understanding of economics, Darwin must have seen an example of complexity emerging from a differentiated population of actors in an economy, as they specialized and pursued the rational maximization of self-interest in the exchange of goods and services. Darwin thought that nature was like a laissez faire economic market. He frequently refers to nature as an economy – the economy of nature. Thus, at the very foundations of evolutionary theory lie powerful analogies to economics.
Robert Malthus got it wrong. Mass famines in Europe and around the world have been largely avoided through dramatic increases in agricultural production. To this we must add improved sanitation, vaccinations, new medical treatments, the exponential increase in fossil fuel consumption, dramatic new technologies and other gains in efficiency, all of which have staved off mass disease, famine, death, and to some extent also warfare – all predicted by Malthus’s dark prognostications. Since the publishing of Malthus’s essay in 1798, the population of the world has increased six fold from approximately 1 billion people to now over 7 billion.
Adam Smith, on the other hand, got it largely right. There is something profoundly creative about laissez faire economics. Increasing specialization, the division of labor, and free trade have been powerful engines for economic growth over the last two centuries. That being said, economic theory and evolutionary theory have largely gone separate ways since Darwin. It is not until the last few decades that bridges between economics and biology have begun to be rebuilt, though largely on the side of the economists, who now talk about bionomics and import many evolutionary concepts into their latest theories. It is my suggestion in this review that the biologists also have a lot to re-learn in a new encounter with economics, and that this encounter may yield new insights for evolutionary theory.
Reading Malthus and Smith, however, would not be the best place for the contemporary theorists of biology to start rethinking key economic metaphors. If biologists were to figuratively wander across campus to the economics department, what book should they pick up to enter into the contemporary debates in that field. Eric Beinhocker’s The Origin of Wealth would be a great place to start. Beinhocker’s book explores the differently evolved science of economics and offers new and exciting metaphors for rethinking Darwinism and evolutionary theory.
Eric Beinhocker is a Senior Fellow at the McKinsey Global Institute, a private economics research group within McKinsey & Company. He was previously a partner at McKinsey. He has worked as a software CEO, a venture capitalist, executive director, and consultant. Beinhocker has also held research appointments at the Harvard Business School, the MIT Sloan School, and the Santa Fe Institute. He is a graduate of Dartmouth College and the MIT Sloan School. He has written extensively on business and economic issues.
The genius of the book is Eric Beinhocker’s grand synthesis of diverse fields of research, including physics, evolutionary biology, anthropology, psychology, game theory, information theory, and economic history, all to tell the big story about why traditional neo-classical economic theory fails, and how “Complexity Economics” works. The book includes sections on how to rethink the role of governments and private sectors, as well as how Complexity Economics might impact corporate management and strategic planning.
Beinhocker is a gifted storyteller and is able to call on a wide range of research to illustrate his arguments. The guiding question is what is wealth and how is it created? Curiously, Beinhocker only gets around to defining wealth in chapter fourteen, 300 pages into his 450-page text. Before he gets around to offering his definition of wealth, however, he makes it very clear that we have exponentially more wealth than our ancestors, even a few generations back.
The book opens with the contrasting of the economic life of Amazon aborigines, as a stand-in for how our hunter-gatherer forbears probably lived 15,000 years ago, with people living in the concrete jungles of New York City:
If we take a closer look at the economics of the two tribes, we see that Yannomamö employment is focused on collecting food in the forest, hunting small game, gardening a limited number of fruits and vegetables, and maintaining shelters… The average income of a Yannomamö tribesperson is approximately $90 per person per year… while the average income of a New Yorker in 2001 was around $36,000, or 400 times that of a Yannomamö…
But it is not the absolute level of income that makes New Yorkers so wealthy; it is also the incredible variety of things their wealth can buy. Imagine you had the income of a New Yorker, but you could only spend it on things in the Yanomamö economy .
Beinhocker compares the market diversity of the Yanomamö tribe to that of the New Yorker by using stock keeping units, or SKUs, those barcode numbers that retailers use in stocking their shelves and reconciling their sales, a unique code for each item sold. Total SKUs in a Yanomamö tribe are estimated to be in the hundreds, while the SKUs on the shelves of all the stores in New York City are roughly estimated at ten billion unique items (10^10). This complexification is part of the key to what Beinhocker means by wealth.
Economic complexity is dynamic. It is adaptive. It is accelerating. In the last 250 years, world GDP per person has increased 37-fold . Beinhocker writes:
To summarize 2.5 million years of economic history in brief: for a very, very, very long time not much happened; then all of a sudden, all hell broke loose .
This is the mystery of economics that Beinhocker wants to explain. The Origin of Wealth is an extended argument against traditional neoclassical economics, which is based on mathematical models of market equilibrium. The human agents in the traditional model were assumed to be selfish and rational with access to perfect information. The mathematics of Traditional Economics (TE) was mostly borrowed from 19th century physics. TE was elegant in theory, but falsified by the empirical evidence.
The miracle of economics is that 7 billion people today participate in a $83 trillion global economy which is predicted to continue to grow. No one oversees it. No one designed it. No one can control it. Economic complexity emerges from the bottom-up. How has this marvelous self-organized system evolved? What is the something new and more in economic growth and how is it created? What is the origin of wealth and how can individuals, business, and societies get more of it?
The first thing that our itinerant biologists will discover is that contemporary economists are looking back at evolutionary biology, though their reading of biology will likely seem foreign to someone schooled in transcription factors and the Krebs cycle. Nor are economists particularly concerned with Malthusian limits that so dominate Darwin’s theory of natural selection. The algorithm of natural selection is there in Beinbocker’s reading of economics – differentiation, selection, and amplification – but along side we also encounter nonlinear dynamics, thermodynamics, and the miracle of exponentially more novelty. The problem in economics that needs to be explained is how humans have been able to overcome Malthusian limits through dramatic economic growth, hence Beinhocker’s ambitious title “the Origin of Wealth”. By analogy, the hard problem that needs to be explained by evolutionary biology is not the logic of limits, not the universal struggle for survival, but the increased diversification and complexification of life.
The book begins with a review of what Beinhocker refers to as Traditional Economics (TE). This chapter will be useful to someone not familiar with the field, providing a condensed introduction to the academic discipline, starting with Adam Smith (1723-1790), Jaques Turgot (1727-1781), Jeremy Bentham (1748–1832), John Stuart Mill (1806-1873), and Alfred Marshall (1842-1924). We are then introduced to the early attempts to turn economics in a mathematical science in the works of Léon Walras (1834-1910), William Stanley Jevons (1835-1882) and Vilfredo Pareto (1848-1923). We are also introduced to a long list of influential twentieth century economists – Paul Samuelson, Kenneth Arrow, Milton Friedman, Robert Lucas – all of whom continued to build the “grand cathedral” of Traditional Economics. These chapters are dense with details, but short and easy to read.
The fatal error of the discipline was in adopting the mathematics of nineteenth century physics. The use of equilibrium models from physics led economics down a dead end:
The models of Walras, Jevons, and Pareto began with the assumptions that an economy already exists, producers have resources, and consumers own various commodities. The models thus view the problem as how to allocate the existing finite wealth of the economy in a way that provides the maximum benefits for everyone. An important reason for this focus on allocation of finite resources was that the mathematical equations of equilibrium imported from physics were ideal for answering the allocation question, but it was more difficult to apply them to growth. Equilibrium systems by definition are in a state of rest, while growth implies change and dynamism. 
The guiding assumptions about humans in Traditional Economics were also wrong. Traditional Economics assumes that humans are rational actors with access to perfect information as they engaged in frictionless auction-like economic transactions all with the purpose of maximizing their self-interest. This, of course, is not the case. Beinhocker favorably quotes the UCLA Economist Axel Leijonhufvud, who remarks that TE models assumes “incredibly smart people in unbelievably simple situations,” while the real world involves “believably simple people [coping] with incredibly complex situations” .
Traditional Economics thus gets it mostly wrong. It fails to predict or explain. Layers of economic theory have been built upon these false assumptions progressively disconnected from the empirical data. Beinhocker cites a long list of contemporary economists, including many of the recent Nobel laureates in the field, who have gradually dislodged the old paradigms. Beinhocker proposes to use the term “Complexity Economics” to describe the new paradigm that he hopes will transform and guide the field. He offers the following chart to outline the differences between the old and the new:
Table 4-1 Five “Big Ideas” That Distinguish Complexity Economics from Traditional Economics
Complexity Economics: Dynamics — Open, dynamic, nonlinear systems, far from equilibrium
Complexity Economics: Agents — Modeled individuality; use inductive rules of thumb to make decisions; have incomplete information; are subject to errors and biases; learn and adapt over time
Complexity Economics: Networks — Explicitly model interactions between individual agents; networks of relationships change over time
Complexity Economics: Emergence — No distinction between micro- and macroeconomics; macro patterns are emergent result of micro-level behaviors and interactions
Complexity Economics: Evolution — The evolutionary process of differentiation, selection, and amplification provides the system with novelty and is responsible for its growth in order and complexity
Traditional Economics: Dynamics — Closed, static, linear systems in equilibrium
Traditional Economics: Agents — Modeled collectivity; use complex deductive calculations to make decisions; have complete information; make no errors and have no biases; have no need for learning or adaptation (are already perfect)
Traditional Economics: Networks — Assume agents only interact indirectly through market mechanisms (e.g. auctions)
Traditional Economics: Emergence — Micro- and macroeconomics remain separate disciplines
Traditional Economics: Evolution — No mechanism for endogenously creating novelty, or growth in order and complexity
Chapters then follow on each element – Dynamics, Agents, Networks, Emergence, and Evolution. In these chapters, we are introduced to nonlinear systems, feedback loops, time delays, phase transitions, Boolean networks, oscillations, punctuated equilibrium, power laws, keystone innovations, bid-ask spread, price priority, time priority, “news-less volatility” in stocks, artificial life, computer simulated economics, fitness landscape, forced moves, path dependence, design space, schema, schema reader, modules, environments, and fitness function.
Some of these concepts will be familiar to the biologist and evolutionary theorists, but others will be quite new. All of this will be in a different context and offers a vantage point to look back at theoretical biology, because my hunch is that empirical biology has evolved, while theoretical biology is largely stuck with an inadequate, though elegantly simple paradigm (Wesson 1991) (Depew 1996). Alfred North Whitehead suggests that the goal of science should be to “seek simplicity – and distrust it.” I distrust the simplicity of the Darwinian paradigm and this is in part my motivation to re-read economics, hopefully in conversation with my colleagues in biology.
Beinhocker’s chapter on evolution adopts the language of Darwinism as interpreted by Daniel Dennett and Richard Dawkins. In this sense, Beinhocker appears to be ultra-orthodox in his reading of Natural Selection. He uses the terms “differentiate, select, and amplify” to describe the evolutionary learning algorithm and applies this to developing a new theory of economics. He notes, of course, that the selectionist paradigm applied to human economic activity is going to be vastly different than biological evolution. In the human context, economic evolution is guided in part by our “deductive-tinkering”, our motivations and intentions, and our inductive hunches, while in the biological context, evolution is “random and blind”. The random-and-blind nomenclature is pernicious and misleading in the biological context. These terms are ideologically load metaphors that have little to do with molecular or cell biology. In any case, we are re-reading economics not to re-read Dennett and Dawkins, but to seek new guiding metaphors for understanding evolutionary theory. The hard question in biological evolution is not survival and reproduction, nor whether selection operates on the backdrop of randomness. The hard problem is complexification over the eons. The hard question in economics is not equilibrium, but the exponential growth of wealth.
In this respect, I am most intrigued by Beinhocker’s discussion of Physical Technologies and Social Technologies. “Physical Technologies (PTs)” writes Beinhocker, “are methods and designs for transforming matter, energy, and information from one state into another in pursuit of a goal or goals” . Scientific and technological innovations are often self-reinforcing processes that unfold exponentially in economic development. PTs are purposeful adaptations driven by deductive tinkering. Beinhocker understands the Scientific Revolution to be in effect a way of “Reprogramming Evolution”. Much of the exponential economic growth in the last 250 years is the result of new Physical Technologies. He offers numerous examples. I wonder what the biological analogues are to Physical Technologies and am reminded of Kevin Kelly’s motto that “life is the ultimate technology” (Kelly 1994).
“Social Technologies (STs)”, writes Beinhocker, “are methods and designs for organizing people in pursuit of a goal or goals” . In the history of economics, STs include the use of money, property rights, double-entry accounting, limited liability joint stock corporations, the rule of law, effective banking systems, economic transparency, lack of corruption, family networks, social capital, trust, and reputation. All of these play a profound role in determining economic outcomes in communities and nations. Social Technologies are necessary for unleashing the non-zero sum dynamics through which new wealth is created to the mutual advantage of the community. Here too, I wonder whether we might see a biological analogue, perhaps at the level of biochemical cascades, developmental biology, behavioral biology, or ecological networks.
The unit of selection in Beinhocker’s understanding of economic evolution is what he calls the Business Plan. This is what lives and dies within the substrate of economic evolution. Business Plans are distinct from businesses or firms; rather they are strategies, formally articulated or not. A Business Plan is a strategy for how to make a profit providing goods or services to the market. A single firm might have multiple Business Plans nested as modules within a larger strategy. A business could be a single person or a corporation with hundreds of thousands of employees. The Business Plans are the instructions for creating a business, for harnessing both Physical and Social Technologies in order to seek profits. The successful modules are rewarded with more resources. Unsuccessful Business Plans go extinct, sometimes taking the business down with it.
Beinhocker seems to suggest that the Social Technologies involved in creating wealth are much more difficult than the Physical Technologies. Prior to the evolution of market economies, economic activity was based on and limited to what he refers to as the Big Man system, here drawing on the work of Robert Wright and others. And the Big Man system still troubles many underdeveloped nations in the world, even as it troubles the internal workings of many multi-national corporations. The Big Man system is governed by sex, money, and status. Beinhocker writes:
In a Big Man system, the fitness function maximized is the wealth and power of the Big Man (and his cronies) rather than the overall economic wealth of the society. Thus, the creative, entrepreneurial, and deductive-tinkering energies of the population are directed toward pleasing the Big Man… The only alternative selection system to Big Men that humans have thus far devised is markets… In a market-based economy, a business lives or dies by whether its customers like and are willing to pay for its products and services 
Beinhocker advocates market economies, “not because they are the best method for allocating resources in a way that optimizes social welfare under conditions of equilibrium, but because they offer an evolutionary search mechanism that incentivizes deductive-tinkering leading to differentiation and then provides a fitness function on which economic selection can than act…”. So Complexity Economics is not such a revolution after-all, rather it is a reframing and re-description of business-as-usual as we have come to know it in the United States.
So what is wealth? It is not until chapter fourteen that Beinhocker offers a formal definition of economic wealth. He defines wealth in terms of the Second Law of Thermodynamics, drawing in part on the work of Friedrich Hayek (1899-1992) but especially Nicholas Georgescu-Roegen (1906-1994). Economic value is created by 1) thermodynamically irreversible processes that 2) reduce entropy locally while increasing it globally 3) in reference to some human purpose . Beinhocker never uses the word “negentropy”, but that is what wealth is, low-entropy (i.e., high-ordered complexity) that serves some human purpose. Economics, like evolution, obeys the letter of the law – the Second Law of Thermodynamics – but everywhere seems to violate the spirit of the law – with historical examples and patterns of run away complexiification, creativity, and novelty. Beinhocker writes:
Economic wealth and biological wealth are thermodynamically the same sort of phenomena, and not just metaphorically. Both are systems of locally low entropy, patterns of order that evolved over time under the constraint of fitness functions. Both are forms of fit order. 
If wealth is indeed fit order, then we can use another more familiar word to describe it. In physics, order is the same thing as information, and thus we can also think of wealth as fit information; in other words, knowledge… The origin of wealth is knowledge. Yet rather than treating knowledge as an assumption, an exogenous input, a mysterious process outside the bounds of economics, the Complexity-based view I have outlined puts the creation of knowledge at the endogenous heart of the economy. 
Whether we call it order, information, or knowledge, that which is now endogenous to the system is still mysterious. The traditional meta-scientific paradigm knows what to do with matter-energy and space-time, but information is neither. Information is something immaterial that must be “read,” “incarnated,” and “replicated” through material processes, but which is still something else altogether other. Or not? Information also costs energy, though not all energy is information.
On that issue rests the $83 trillion Malthusian question. Wealth has grown exponentially through a fantastically creative global economy, but if the Second Law of Thermodynamics has the last word, then our human-dominated ecosystem is headed for a collapse, if not in this century than in the next. The best we can do is minimize entropy and maximize creativity, thus forestalling disaster, but in the end we still lose to death and taxes, so to speak.
If, on the other hand, order, information, and knowledge, are something more, something that can grow independent of matter-energy, then the future is wide open, particularly if humans can deductively tinker our way into minimizing entropy while maximizing creativity, thereby partially dematerializing economic growth. That, in and of itself, is no guarantee of future growth, because complex systems can suddenly collapse simply based on their own internal, nonlinear dynamics, even without Malthusian-Thermodynamic limits ever being reached.
How we interpret this meta-economic question should also guide how we understand biological evolution. If life is also a story of evolving “physical technologies” and “social technologies,” then we might want to down-grade the role of the universal struggle for survival and reproduction in our evolutionary story, as I believe we should down-grade the role of supposed randomness. Exponential growth in complexification works. “Biological value” is limited only by the prodigious solar energy received from the Sun and potential chemical-nuclear energy embedded in the planet itself. Hypothetically humans, or post-humans as the case may soon be, and life could continue to complexify for a long-time to come, perhaps even with compounded interest. Sometimes survival and reproduction is everything, so life looks more like a Darwinian jungle. Sometimes, however, life looks more like a White Elephant Sale with all manner of tinkerings and novelties thrown together. I think perhaps of the trillions of chemical reactions that occur in a single cell every second. They are certainly not random, nor are they driven by survival and reproduction. The biochemical cascades that under gird cell biology come and go in a fantastically complex, indeed elegant manner. Perhaps it is a kind of category mistake, when we expect the Second Law of Thermodynamics and Natural Selection to do too much work in explaining emergent complex phenomena. Here, professional biologists must step-in to the discussion, seeing what new guiding metaphors might be productively lifted out of economics in the service of re-conceptualizing evolutionary theory. Again, I distrust the simplicity of the Darwinian paradigm, because it “explains” too much and makes it possible to ignore the empirical biology.
In any case, we treat humans as epiphenomenal to evolutionary theory at our own risk. Humans are an increasingly important part of the evolutionary story given our growing capacity to affect the entire planet, selective pressures in all ecosystems, and indeed, even the direct engineering of genomes. This book is an invitation to begin that synthesis, though it was certainly not written with that intention.
Beinhocker seems to favor the exponential growth paradigm and the dematerialization of economics, though he never says so explicitly. In his Epilogue, he does express some doubts, noting that we are conducting a real-time global experiment on the environment, whose results we do not know and cannot predict. He warns of the propensity of complex dynamic systems to reach “tipping points” that then lead to rapid changes. A whole system can collapse unpredictably, if certain minor variable are amplified by feedback loops. Earthquakes, economic markets, and perhaps also global environmental changes follow power laws and not Gaussian distributions.
Beinhocker also worries that the exponential growth in Physical Technologies in the last few centuries far exceeds the growth in Social Technologies. Indeed, the latter may be declining, if we include cultural dimensions as part of the economic stage. Culture matters in economics, as Beinhocker discusses at length in latter chapters. Cultures are also transformed by economics, technology, and globalization. The evolution of human culture, at least that is my bet, will be the real wild card in the twentieth century economics.
It would seem that humans have cheated the Malthusian Logic of Limits through Physical Technology, Social Technologies, and economic markets. Whether we can continue to do so and how long depends in part on a meta-scientific and metaphysical bet about the nature of information and the extent to which economic growth can be dematerialized. Curiously, Beinhocker never cites the Rev. Robert Thomas Malthus, but I shall:
The power of population is so superior to the power of the earth to produce subsistence for man, that premature death must in some shape or other visit the human race. The vices of mankind are active and able ministers of depopulation. They are the precursors in the great army of destruction, and often finish the dreadful work themselves. But should they fail in this war of extermination, sickly seasons, epidemics, pestilence, and plague advance in terrific array, and sweep off their thousands and tens of thousands. Should success be still incomplete, gigantic inevitable famine stalks in the rear, and with one mighty blow levels the population with the food of the world (Malthus 1798).
This is a dark vision indeed. No wonder Darwin was depressed much of his life. No wonder that economists, businesses, and politicians largely ignores Malthus today. We have two hundred years of growth, which seems to disprove Malthus. We have two hundred years of technological and scientific progress, which would dumbfounded Malthus or any of his contemporaries. We don’t know whether we can extrapolate this for another two hundred or two thousand years, but curiously even our attitudes and expectations about the future, as Complexity Economics shows, are causally significant as we tinker and muddle our way into that future. Evolutionary progress, both the human and non-human varieties, may be a myth, but it is a very useful myth and partially a self-fulfilling prophecy. Spiritual and moral progress would appear to be an absolute necessity in the twenty-first century, if our Social Technologies are ever to catch-up with our Physical Technologies. The problem is that we are not the least bit clear what spiritual or moral progress is or how to get more of it.
I am reminded that fifty percent of the United States does not accept evolution on religious grounds, so there is a lot of work getting religion, spirituality, and morality up to speed on these issues. And less you think that any of this discussion should be construed as an apologia for Intelligent Design Theory, I would only quote Beinhocker: “Your shirt was not designed; it was evolved” . Even in the domain of human artifacts, it seems evolution is a better metaphor than architecture or engineering.
There is much to commend in this book to diverse audiences. In the last four chapters, Beinhocker explores the implications of Complexity Economics for Strategy, Organizations, Finance, Politics and Policy, for instance in what he calls “the End of the Left versus Right” in contemporary politics. These chapters would make useful reading for citizens and scholars alike, as well as entrepreneurs and activists, or for that matter university administrators and biology department chairs. These chapters would also make useful reading to our presidential hopefuls. Finally, I would also recommend this book to philosophers, theologians, and religious thinkers, who are also part of a complex adaptive system trying to understand and shape human values in ways that cannot always be represented as money and accounted for, but which, as Beinhocker makes clear, are very much part of the dynamics.
I began this review by seeking new metaphors from economics for evolutionary biology, noting the central role that this played in Darwin’s own thinking. I have hardly succeeded, but hopefully have provoked some further conversations and cross-disciplinary “gene splicing”. I end with the quote that Eric Beinhocker uses to open the book. He cites Jorge Luis Borges from his book Labyrinths: “It may be that universal history is the history of a handful of metaphors” .
Beinhocker, Eric D. (2006). The Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics. Cambridge Harvard Business Press.
Darwin, Charles (1859). The Origin of Species, Online.
Darwin, Charles (1871). The Descent of Man. Online.
Depew, David and Bruce Weber (1996). Darwinism Evolving: Systems Dynamics and the Genealogy of Natural Selection. Cambridge, MA, MIT Press.
Kelly, Kevin (1994). Out of Control: The New Biology of Machines, Social Systems, and the Economic World. New York, Addison-Wesley.
Malthus, Thomas Robert (1766-1834) (1798). An Essay on the Principle of Population. London, J. Johnson.
Smith, Adam (1723-1790) (1759). The Theory of Moral Sentiments. London, A. Millar.
Smith, Adam (1723-1790) (1776). An Inquiry into the Nature and Causes of the Wealth of Nations. London, Methuen and Co.
Wesson, Robert (1991). Beyond Natural Selection. Cambridge, MA, MIT Press.