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The Origin Of Wealth: Evolution, Complexity,…
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The Origin Of Wealth: Evolution, Complexity, and the Radical Remaking of… (edição 2007)

por Eric Beinhocker

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Over 6.4 billion people participate in a $36.5 trillion global economy, designed and overseen by no one. How did this marvel of self-organized complexity evolve? How is wealth created within this system? And how can wealth be increased for the benefit of individuals, businesses, and society? In The Origin of Wealth, Eric D. Beinhocker argues that modern science provides a radical perspective on these age-old questions, with far-reaching implications. According to Beinhocker, wealth creation is the product of a simple but profoundly powerful evolutionary formula: differentiate, select, and amplify. In this view, the economy is a "complex adaptive system" in which physical technologies, social technologies, and business designs continuously interact to create novel products, new ideas, and increasing wealth. Taking readers on an entertaining journey through economic history, from the Stone Age to modern economy, Beinhocker explores how "complexity economics" provides provocative insights on issues ranging from creating adaptive organizations to the evolutionary workings of stock markets to new perspectives on government policies. A landmark book that shatters conventional economic theory, The Origin of Wealth will rewire our thinking about how we came to be here--and where we are going.… (mais)
Membro:circulareconomy
Título:The Origin Of Wealth: Evolution, Complexity, and the Radical Remaking of Economics
Autores:Eric Beinhocker
Informação:Random House Business (2007), Paperback, 544 pages
Colecções:A sua biblioteca
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Etiquetas:economics

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Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics por Eric D. Beinhocker

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  ejmw | Aug 4, 2021 |
The text says that the graph of y= x squared is a geometric curve. An editor inserted this absurdity, or they failed to remove it. Either way I think we should boycott this publisher. ( )
  johnclaydon | Dec 17, 2018 |
I didn't have the advantage of Marx's theory when I read this book, but I enjoyed it. I might like it a lot more now! ( )
  AnupGampa | Jun 30, 2018 |
With a title echoing that of Charles Darwin’s seminal work, Eric D. Beinhocker’s “The Origin of Wealth: The Radical Remaking of Economics and What It Means for Business and Society” (2007) has a lofty aim: to provide a new foundation for the field of Economics. Beinhocker criticizes what he calls “Traditional Economics,” a view of markets that is founded on a variety of unrealistic assumptions (such as the notion that markets reach equilibrium, participants in markets are rational, all-knowing, self-serving agents, etc.). It its place, Beinhocker offers Complexity Economics, the concept that markets emerge from the behaviors of many individual, idiosyncratic agents, and the economy’s long-term growth and development is governed by evolution. In saying this, Beinhocker emphasizes that he is not making an analogy to biological evolution, but rather that evolution itself is simply a process or an algorithm, which can be instantiated in various mediums, including genes and organisms (in the biological world) or business plans and businesses (in the economic world). The last section of the book aims to provide advice on what this view of economics means for real-world companies: since it is not possible to answer questions about the economy by solving straightforward equations (as was believed to be the case under Traditional Economics), how are businesses supposed to make their decisions? Beinhocker recommends bringing the process of evolution into businesses themselves, so that instead of businesses failing or succeeding based on changing market forces, initiatives within a business can fail or succeed. If a business is sufficiently adaptable, this will help position the business for success in an uncertain economic world.

Beinhocker’s book is well-written and engaging. The author is careful to introduce the foundations of Traditional Economics, and he describes the research programs and results of a variety of studies and experiments, so that even people who have no background in Economics can appreciate the book. He begins each of the book’s eighteen chapters with a small story, which is typically fun to read and illustrates a point from that chapter.

Here, I will provide a brief summary of each chapter of Beinhocker’s book.

Chapter 1, “The Question: How is Wealth Created,” defines wealth as not just an amount of buying power, but also the availability of different products or services that can be purchased in an economy (the number of SKUs, or stock keeping units). Beinhocker points out that the growth of wealth has been highly non-linear throughout human history, with an explosion of wealth (in both buying power and in things to buy) since 1900. He also introduces the concept of Complexity Economics and the notion that the growth of wealth is driven by the process of evolution.

Chapter 2, “Traditional Economics: A World in Equilibrium,” is a historical review of the work of past economists. Economists covered include Adam Smith, Leon Walras, William Jervons, Vilfredo Pareto, Alfred Marshall, Paul Samuelson, Kenneth Arrow, Gerard Debreu, Joseph Schumpeter, Robert Solow, Paul Romer, and others. Beinhocker emphasizes the decision by Walras to import concepts from the field of physics to the field of economics with the goal of making it possible to use mathematics to answer economic questions.

Chapter 3, “A Critique: Chaos and Cuban Bars,” points out many flaws with Traditional Economics. Beinhocker discusses the unrealistic assumptions that are frequently made (e.g. actors have complete information, there are no transaction costs or other barriers to buying and selling, etc.). He also indicates that Traditional Economics has a poor record of being able to accurately predict aspects of the world- for example, the (incorrect) prediction that stock prices should follow a random walk. Lastly, he describes the Second Law of Thermodynamics (which states that entropy in a closed system always increases) and claims that Leon Walras and later economists mischaracterized the economy as a closed, equilibrium system rather than an open, complex, adaptive system.

Chapter 4, “The Big Picture: Sugar and Spice,” focuses on a simple, economic computer model called “Sugarscape,” developed by Joshua Epstein and Robert Axtell. By modeling independent agents who interact based on simple rules and limited information, in a greatly simplified world, an economy arises that develops some of the same traits as real-world economies, such as a range of rich and poor agents that follows a Pareto distribution. They also observe the importance of birth location in an agent’s long-term welfare and the fact that the system never reaches equilibrium.

Chapter 5, “Dynamics: The Delights of Disequilibrium,” is a discussion of various properties of nonlinear systems. Beinhocker introduces concepts such as positive and negative feedback loops, time delays, periodic and quasi-periodic limit cycles, and chaos (the mathematical concept- namely, a deterministic system whose behavior can be radically changed by a small difference in initial conditions). He highlights the work of MIT professor John Sterman, a leader in the field of system dynamics computer modeling.

Chapter 6, “Agents: Mind Games,” focuses on human psychology, and in particular, the ways people deviate from the rational behavior assumed by Traditional Economics. This includes a tendency to punish bad behavior (even at one’s own expense), framing biases, drawing conclusions from small and unrepresentative data sets, superstitious reasoning, etc. Beinhocker discusses the differences between inductive and deductive reasoning. He provides an illustration of how an agent’s mental model (the rules governing its behavior) might operate and be refined on the basis of experience, whether the agent is a frog catching flies or a stock trader in a simulated stock market.

Chapter 7, “Networks: Oh What a Tangled Web We Weave,” discusses the patterns of connections between agents within a system. Networks can be sparsely or densely connected, and connections may adopt different patterns (e.g. agents connect to their neighbors, agents are arranged in a hierarchy, etc.). As a network becomes larger and more densely connected, it becomes vulnerable to the threat of a complexity catastrophe: a situation where a positive change in one part of the network inevitably causes negative changes elsewhere in the network, so changes are resisted (even if they would improve the global fitness of the network). This helps explain why larger companies are less adaptive to changing conditions and less innovative than start-ups.

Chapter 8, “Emergence: The Puzzle of Patterns,” focuses on the large-scale behavior of economic systems. Traditional Economics holds that variance in outputs (like stock prices) are due to random, exogenous factors, but real-world economic systems do not behave this way. They include dynamics within the systems themselves that generate chaotic behavior, as illustrated by a simple simulation devised by MIT’s Jay Forrester in the 1950s called the “Beer Game.” Stock price fluctuations (like earthquake magnitudes) do not follow a bell curve but rather a power law, a probability distribution that allows for more frequent, large, sudden movements in stock price. The use of a “limit order book” is presented as an example of a mechanism by which chaotic behavior of stock prices can be an emergent property of the system.

Chapter 9, “Evolution: It’s a Jungle Out There,” describes the workings of evolution as an algorithm for finding and propagating the most successful designs for a given environment, or “fitness function.” Examples include digital creatures of blocks that walk or swim effectively, lego toys that are most appealing to a particular child, and biological evolution. An environment with limited resources defines the fitness function, providing the determinant of which designs are successful (and will be widely replicated) and which designs are unsuccessful (and will be seldom replicated or will vanish). The design space of possible traits of an interactor (the thing that exists in the environment- an organism, in the case of biological evolution) can be envisioned as a “fitness landscape,” where each unique combination of possible traits results in a different level of fitness for a given fitness function. This fitness landscape is rough-correlated, which means that highly fit designs tend to cluster together. Since the real world is constantly changing, the fitness function is constantly changing, which causes the fitness landscape (the peaks and valleys in design space) to continually shift. The optimum algorithm for finding the highest fitness “peaks” in design space involves mostly exploring parts of the landscape near to oneself, preferring higher ground, but occasionally making, long, random “jumps” to other parts of the landscape, seeking out high fitness peaks that may be separated from one’s current peak by a lower-fitness valley. Evolution is a highly effective algorithm for finding and exploiting high-fitness peaks in a rough-correlated fitness landscape.

Chapter 10, “Design Spaces: From Games to Economies,” discusses a computer model by Kristian Lindgren that involves agents with various, evolving strategies playing a game that combines the Repeated Prisoners’ Dilemma and mathematician John Conway’s Game of Life. Beinhocker also introduces the design space for business plans as a part of an imaginary, enormous library that contains books with every possible combination of characters printed on their pages.

Chapter 11, “Physical Technology: From Tools to Spacecraft,” illustrates how evolution has driven the development of physical technologies (from Neolithic stone tools to modern computers), increasing the number of SKUs in the economy. Unlike biological evolution, changes to physical technologies do not arise randomly, but through a process of deductive tinkering. A technology’s performance often follows an S-curve path, where improvement starts slow, becomes rapid as expertise is gained, and levels off as a technology approaches maturity. S-curves arise from the process of traversing a “fitness landscape” for physical technologies.

Chapter 12, “Social Technology: From Hunter-Gatherers to Multi-Nationals,” discusses the development of mechanisms for organizing groups of people (bands of hunter-gatherers, modern nation-states, corporations, etc.). Like physical technologies, social technologies are developed through the process of evolution. The most successful organizations of people have social technologies that enable cooperation, facilitate the division of labor and processing of information, help people through periods of bad luck, and identify and punish free riders and defectors. One of the most successful social technologies is the “Big Man” organizational structure, where a single leader holds near-absolute power and orchestrates how things are done, often with sub-bosses arranged in a hierarchy below. This structure appears in everything from hunter-gatherer tribes to bowling leagues to modern corporations.

Chapter 13, “Economic Evolution: From Big Men to Markets,” points out that just as biological evolution operates at the level of genes (pieces of DNA), economic evolution operates on the level of “modules,” or components of business plans. There are two known mechanisms for defining the selection pressures that operate on modules: Big Men and markets. Business plans with good modules will be more successful at pleasing the Big Man (in a Big Man economy) or will be more popular in the market (in a market economy), and therefore they will be replicated, as the business grows and competitors take note and adopt those modules. While markets have failings and do not achieve perfectly efficient allocations of resources, they are superior to Big Men at driving innovation and achieving positive outcomes.

Chapter 14, “A New Definition of Wealth: Fit Order,” aims to connect the concept of wealth to the Second Law of Thermodynamics (which concerns entropy). Economic value is created by an action that is thermodynamically irreversible, reduces local entropy while increasing global entropy, and produces an artifact or action fit for human purposes. Beinhocker describes Maslow’s hierarchy and how humans’ economic preferences arise out of our biological evolutionary heritage. Beinhocker claims that “wealth” is effectively “fit order,” or a good or service that is needed and/or desired by people. Since such goods and services embody large amounts of information, “fit order” or “wealth” can also be thought of as “knowledge.”

Chapter 15, “Strategy: Racing the Red Queen,” points out that value-creating actions often involve commitments that may be costly or difficult to undo. Small, random events called “frozen accidents” sometimes have a tremendous impact on the course of the future, but their significance cannot be known at the time they happen. Due to the changing fitness landscape of the economy, competitive advantage for any particular business is ephemeral, most businesses do not survive many decades, and those that do overwhelmingly tend to underperform the market average over that timeframe. The key to building a long-lasting, successful company is to bring evolution inside the company’s four walls, developing a variety of different business plans, selecting for and amplifying the ones that do well and scaling down or eliminating the ones that do poorly. This is hard for most companies to achieve because the timeframes involved are long and pressure to make operations more efficient and cut costs will tend to cause a company to shut down their experiments and redirect those resources before evolution has had time to operate. It also leaves the company without slack capacity to use to amplify business plans that are becoming successful.

Chapter 16, “Organization: A Society of Minds,” indicates that businesses are complex, adaptive systems. There is debate over the purpose of a company- to provide shareholder value, to serve society and its employees, to endure and grow, etc. Organizations are often better at exploiting current high-fitness peaks than exploring and finding new peaks, due to challenges such as over-optimism, not perceiving a need for change, and an aversion to loss (greater than an attraction to gain). Managerial styles can be either rigid or flexible- rigid styles optimized for a given environment work best in periods when the fitness landscape is stable, but flexible styles work best when change is frequent. The culture of an organization has a tremendous impact on its success, and Beinhocker identifies the ten elements of corporate cultures that make businesses successful.

Chapter 17, “Finance: Ecosystems of Expectations,” describes why stock prices were once believed to follow a random walk (with a positive overall trend), but in fact their movements are non-random. However, useful “signals” for predicting prices are constantly arising and going away as the market changes, and it may take years to gather enough data to determine that there is a “signal” amid the noise, making these signals hard to exploit. J. D. Farmer’s computer model of a stock market illustrated that a stock’s price could differ greatly from its true value, sometimes for years, and emergent behavior of the traders in the market results in chaotic price movements, even in the absence of changes in stock value. A firm’s cost of capital as determined with Traditional Finance methods is not meaningful, but Complexity Economics does not yet offer a replacement metric. The goal of a corporation should be to endure and to grow, so management should take a long-term view and not make decisions primarily driven by a desire to improve next quarter’s financial results or to improve stock price.

Chapter 18, “Politics and Policy: The End of Left Versus Right,” points out that humans favor strong reciprocity: cooperate with those who cooperate, punish those who defect. Complexity Economics has a critique of left (socialist) economies: the world is too complex for a centrally-planned (e.g. Big Man) economy to be well-managed. It also has a critique of right (free market) economies: markets operate far from theoretical efficiency, and in various cases, government involvement and regulation improves services and economic outcomes. Government also provides mechanisms for enforcing social norms, enabling higher levels of cooperation between agents. Complexity Economics’ view is that it is government’s role to shape the fitness function that defines evolutionary success in the economy, and the government should consider not just wealth creation but also other social priorities (such as avoidance of environmental damages) when crafting a fitness function. The culture of a country has a strong impact on its economic performance- countries where people have a higher level of trust for government, businesses, and other people tend to have higher per capita GDPs. In recent decades, these levels of trust in the United States have declined, raising concern over the possibility of negative economic impacts in the future. Culture is also an important explanatory factor in why there is often not a great deal of mobility between social classes within a country.

The Epilogue points out that evolution in no way guarantees “progress,” and just as there have been mass extinctions in biological history, there are dangers of collapse and of causing global catastrophe through irresponsible use of the technologies we have developed. Society is a partnership, and it is up to all of us to define a fitness function that requires our governments, businesses, and scientific institutions to take a long-term view and address society’s needs in a sustainable way.

“The Origin of Wealth” is thought-provoking and provides new insights into both economics and evolution as a substrate-independent algorithm for the creation of complexity and order without a designer or central intelligence. The biggest disappointment may be that in the brave new world of Complexity Economics, there are no longer straightforward equations to answer our economic questions; the best technique we have is to run computer simulations, and if they fail to provide the desired insights, we can try to harness the power of evolution (within one’s own business) as a means to experiment our way to success. This can be unsatisfying because of the timeframe and the resources involved: while evolution is powerful, it is not known for being fast, and human organizations do not have the money, personnel, and equipment to attempt as many different business plans as there are (for example) different organisms of a given species. This implies a need to select one’s business plans very carefully - perhaps not so carefully as if you were to make a single “bet the company” business plan, but carefully enough that one of your six or ten business plans is likely to succeed. Without the equations of Traditional Economics as a guide, your best hope may be to use insights gleaned from other successful businesses (i.e. replication of successful modules in existing business plans), insights from computer simulations (the primary source of economic knowledge that avoids the problematic assumptions of Traditional Economics), and “deductive tinkering.” If this sounds messy, inexact, and offers no guarantee of success- well, perhaps the real world is messy, inexact, and offers no guarantee of success, not even to a student of Complexity Economics. ( )
2 vote jrissman | Nov 19, 2014 |
I can’t recall having ever read an author with the clarity of exposition and the depth and breadth of erudition that is demonstrated by Dr. Beinhocker in this book. It is an impressive work.

The opening sentence of the book asserts that “the field of economics is going through its most profound change in more than a hundred years.” Since much of the book directly addresses and analyzes that change and its implications, I think the book could have more accurately been entitled The Evolution of Economic Theory.

He notes “the two fundamental questions that economists have grappled with throughout the history of their field: how wealth is created and how wealth is allocated.” Adam Smith in his The Wealth of Nations (published 1776) directly addressed both these questions and, with some elaboration by others, established the basic notions of the Classical Period of economic theory; most of these concepts are still accepted today.

Adam Smith and his peers considered themselves philosophers, not scientists, and never attempted to reduce their ideas to mathematical expression. Roughly a century later Leon Walras wanted to change that, he wanted to make economics a science and to make quantitative economic predictions possible. So Walrus set about converting economic ideas into the language of mathematics. He devised a set of equations that represented the equilibrium of cleared markets. Production—how the stuff in the markets was created—was just assumed to have happened, and omitted from the representation. He made other simplifying assumptions. “Walrus’s willingness to make trade-offs in realism for the sake of mathematical predictability would set a pattern followed by economists over the next century.”

Joseph Schumpeter, with his thinking undistorted by trying to produce numbers, brought forth an entirely different vision of how an economy functions, and emphasized the heretofore largely neglected production side of the economy. Schumpeter put entrepreneurship and technical change front and center as the primary source of productivity improvement and therefore wealth creation. He saw the economy as never in equilibrium, always in a state of dynamic change.

Schumpeter’s ideas were valid and persuasive, but his failure to put them into mathematics held them back from getting the affirmation they deserved. Most economists were still trying to describe economic phenomena in a mathematical language that was inadequate to the task, resulting in the need for simplifying but unrealistic assumptions. The three that stood out was, first, that people were always economically rational in their behavior, second, that the economic system was in equilibrium, and third, that innovation—both technical and behavioral (social) change—were not considered part of the system (considered to be exogenous variables).

Robert Solow, a Harvard-trained professor at MIT, won the 1987 Nobel Prize by producing a model of a dynamic economy driven by technical change.

[This whole history is a good illustration of “the rule of the tool”: the idea when one possesses a tool there is a strong tendency to want to use it whether or not it is really appropriate to the task at hand. The result is often that the task is modified to fit the tool. It is often illustrated by the observation that when you give a small boy a hammer is just turns out that nearly everything needs bashing.

The transistor was invented in the 1940’s. This technological discovery made the digital computer possible, and by the latter part of the century had put an entirely new tool in the hands of analysts, largely removing much of the pressure to modify the task to fit the tool.]

The digital computer opened the door to new powers of analysis, and lessened the need for simplifying assumptions made to allow any quantitative analysis at all. The computer is capable of simulating most phenomena, providing versatility to quantitative analysis heretofore not available using conventional mathematics. Complex systems—systems in which the macro behavior emerges from the interaction of the fundament agents—could be simulated and therefore studied. The economy is a prime example of a complex, adaptive system in which the fundamental agents are people and institutions that through their behavior and interaction produce the macro behavior of the total system. For the first time the goal of deriving macroeconomic behavior as an emergent property of microeconomic activity is in sight.

Beinhocker discussed in depth the implications of these events, and provided substantially more color than this brief summary here. He discussed the properties of networks as they affect economic behavior, cognitive phenomena and the unreality of the rational man, and the dynamics of systems with feedback. He illuminated many of the ideas and implications of the economy as a complex system by describing actual computer simulations of various types. He notes that “Complexity Economics is still more of a research program than a single, synthesized theory . . .”

These first two parts of the book focused on the evolution of economic theory. He also mixes in a kind of running tutorial on the terminology and often very surprising properties of complex systems. The third part addressed how evolution creates wealth. It begins with a description and illustration of the generic evolutionary process itself, including a fairly detailed presentation of the story of our biological evolution. He makes the point that the evolution of our economic system and creation of wealth are analogous processes. It seemed to me that while it is of some gee-whiz interest that the generalized patterns were the same, the specific mechanisms were so different that the fact of algorithmic or schematic similarity added very little real understanding of the economic process itself.

He notes that economic evolution is driven by the coevolution of changes in physical technologies, social technologies—how people organize and set rules, and business plans—how people behave to exploit the technical and social innovations.

The rest of the book is devoted to the detailed description and analysis of these three elements. It is very exhaustive, but at a high level of abstraction. For example, there is little or no discussion of the actual technological innovations in our history (except that of making stone tools, which is included to make a point about the properties of invention). He examines all these phenomena from many different angles which I will make no attempt to summarize.

Beinhocker is a master of inductive reasoning, going from the detailed reality to abstract patterns. His grasp of the consilience of the many dimensions of economic behavior is impressive, and the range of his interests and knowledge is downright astounding. I will admit that my reaction on my first reading of the initial chapters was negative: I thought he was painting a negative picture of past economic thinking with the intent of resurrecting it under new labels as new thinking. I was wrong, although I think much of old thinking has held up better than he seems to sometimes imply. But this profound book leaves little doubt that digital-computer-enabled Complexity Economics has and will open the window of our understanding of the creation of wealth very much wider than it has ever been. ( )
1 vote jerry6030 | May 12, 2013 |
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Over 6.4 billion people participate in a $36.5 trillion global economy, designed and overseen by no one. How did this marvel of self-organized complexity evolve? How is wealth created within this system? And how can wealth be increased for the benefit of individuals, businesses, and society? In The Origin of Wealth, Eric D. Beinhocker argues that modern science provides a radical perspective on these age-old questions, with far-reaching implications. According to Beinhocker, wealth creation is the product of a simple but profoundly powerful evolutionary formula: differentiate, select, and amplify. In this view, the economy is a "complex adaptive system" in which physical technologies, social technologies, and business designs continuously interact to create novel products, new ideas, and increasing wealth. Taking readers on an entertaining journey through economic history, from the Stone Age to modern economy, Beinhocker explores how "complexity economics" provides provocative insights on issues ranging from creating adaptive organizations to the evolutionary workings of stock markets to new perspectives on government policies. A landmark book that shatters conventional economic theory, The Origin of Wealth will rewire our thinking about how we came to be here--and where we are going.

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