Economics

What is New Economic Thinking?

Three strands of heterodox economics that are leading the way

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By Amna Silim

The financial collapse of 2007/08 and the subsequent deep recession and sluggish recovery have left huge scars on the global economy. In the UK, the government is grappling with an unprecedented budget deficit and unemployment is over 1 million higher than it was before the recession. This is a crisis for the real economy and for economic policymakers, but it should also be seen as a crisis for the economics profession and for economic theory. Not only did mainstream neoclassical economics – which has been the overwhelmingly dominant strand in economic thinking for over a century – fail to predict the collapse and recession, its models do not even concede that such events could happen. In the future, there is bound to be more interest in economic theories that offer a better explanation of recent events; and this is where heterodox economics comes in.

Neoclassical Economics

The failure to predict or explain the financial collapse and recession has put neoclassical economic thinking in the dock, but such an interrogation is long overdue. Sharp fluctuations in economic growth are just one of the real-world phenomena that traditional economics is poor at understanding. From actual human behaviour through to constant innovation, there is much that traditional economic thinking struggles to explain.

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Neoclassical economic theories describe a world in which rational agents act as optimal decision-makers. Guided by possession of a full set of information, self-interested agents maximise utility while firms maximise profits. As a result, the economy is said to behave in a static and linear manner and the system tends towards a state of equilibrium: supply equals demand and an optimal price is set. Macroeconomic patterns are simply the sum of microeconomic properties (Blanchard 2010).

In this model, economies are not necessarily always in equilibrium; exogenous shocks, such as the development of a new technology, can disrupt them. But these disruptions will be temporary and market mechanisms will work to push the economy back to equilibrium. From a neoclassical perspective, economic development occurs through cyclical patterns of equilibrium, shocks, destabilisation and restabilisation. In each cycle the content of the economy such as the goods and services it offers might change, but its very nature essentially remains the same.

This conventional model can be challenged on four fundamental fronts: the tendency to equilibrium, exogenous shocks, individual rationality and systemic consistency. In the real world, economies are not static and geared towards equilibrium; they are dynamic and in constant flux. This dynamism is endogenous; it originates within the system, not from exogenous shocks. Consumer preferences are not formed by individuals acting solely on their own but are the result of a complex process that includes observing and interacting with other consumers. Economic agents do not have a fixed set of preferences based on rational assessment; they are subject to whims and to mimicking the behaviour of other agents. As a result, the nature of the economic system transforms over time.

In reality, the economy is a complex ecology rather than a complicated machine. It does not respond in predictable ways. It is path-dependent, with each phase building on the previous one. A greater appreciation of this reality has led to the emergence of new schools of thought that are challenging the neoclassical world view and attempting to provide a more realistic understanding of the way economies develop and change.

Complexity, evolutionary and behavioural economics

Various schools of economic thought outside the neoclassical mainstream are often placed together under the banner heading of ‘heterodox economics’. This term is used to describe any innovative way of thinking about the economy, from those that represent complete breaks from the neoclassical approach to others seeking to undermine only some of its main ideas.

In this piece, three strands of heterodox economics are discussed in some detail: complexity, evolutionary and behavioural economics. Each offers different insights into economic analysis by seeking a more accurate representation of the economy, and in so doing opens up new possibilities for policymakers. This essay summarises their basic tenets – and discusses what they might mean for public policy.

Complexity economics challenges fundamental orthodox assumptions and seeks to move beyond market transactions, static equilibrium analysis and homo economicus (the perfectly rational, self interested individuals defined in orthodox economic models). Brian Arthur, Steven Durlauf and David Lane (1997) suggest complexity has six defining characteristics.

  1.  Dispersed interaction: Developments in the economy result from the interaction of heterogeneous agents, whose actions are determined by their environment and by the predicted actions of other agents.
  2. The absence of a global controller: The economy is characterised by competition and coordination between decision-makers and no single agent is able to exploit all opportunities in the economy.
  3. A cross-cutting hierarchical organisation: The economy is comprised of many levels of organisation and there are many intertwined interactions that span across all levels.
  4. Continual adaptation: Decision-makers or agents are continually learning and adapting to their environment, emergent patterns and interactions.
  5. Perpetual novelty in the system: New niches continually emerge out of new markets, new technologies, new behaviours and new institutions.
  6.  Out-of-equilibrium dynamics: The economy is typically operating far from any equilibrium or optimal output and there is constant improvement.

An alternative definition is based on the observed tendency of the economy to produce dynamic outcomes. Richard Day (1994) argues, for example, that ‘[an] economic system is dynamically complex if its deterministic endogenous processes do not lead it asymptotically to a fixed point, a limit cycle, or an explosion’. In other words, complex systems are non-linear, dynamic and involve continuous adaptation to patterns the economic system itself creates. As a result, these systems are, in contrast to the linear systems described by neoclassical economics, unlikely to rest at a given equilibrium point.

Complexity economics considers the economy to be a ‘complex adaptive system’ in which constant interaction plays a significant role. A complex adaptive system allows for a wide set of interactions between individuals and recognises that an economic actor’s preferences are diverse (Beinhocker 2007). Agents do not just respond to market signals, such as price; they also interact with other agents and this influences their subsequent choices and actions (Arthur 1999). The system is adaptive because agents learn from experience, and from the experience of others, and so gain knowledge they would otherwise have lacked. (In contrast, in traditional economic theory, the economy is populated by ‘representative agents’ or identical decision-makers operating in isolation.) If we accept the existence of these complex and overlapping interactions, this requires us to rethink the equilibrium outcomes that are at the centre of neoclassical assumptions.

In complexity economics, it is accepted that interactions between different actors at the micro level will lead to particular macroeconomic outcomes. Unlike in traditional economics however, the complexity view is that micro- and macroeconomics are not separate fields and macro patterns are not the simple aggregation of the micro decisions of uniform decision-makers (Fontanta 2008). Micro level interactions mean macro patterns cannot be reduced to individual level behaviour; these patterns can only be seen as a whole (Durlauf 2011). Thus, economic growth, for example, cannot be reduced to its individual properties or elements; rather it is a result of various interactions at the micro level (Metcalfe et al 2002).

Furthermore, once a macro pattern has been established, there is nonstop adaptation that leads to a generation of new patterns – emergent phenomena – arising from within the system. This process is referred to as endogenous evolution.

In a complex system, these interactions not only influence macro patterns but also create increasingly complex networks. Economic transactions take place across a range of networks, unlike in traditional models, which assume agents interact only through auctions or oneto-one negotiation (Beinhocker 2007). If agents have the ability to learn and adapt their behaviour accordingly, and alter their preferences and decision-making in an unpredictable manner, they can no longer be seen as rational entities operating with perfect information. In this respect, complexity economics has much in common with behavioural economics, while learning and adapting is central to evolutionary economics.

Evolutionary economics is closely related to complexity economics and, as its name suggests, sees the process of evolution as central to economic developments. Evolution involves endogenous change – a process of selection, adaptation and multiplication (Metcalfe et al 2002). As a result of experience and adaptation, some economic strategies and decisions work and some fail. Those that succeed are scaled up or multiplied; those that fail are cast aside. This process of continuous knowledge gathering and adaptation is driven by feedback mechanisms and the interactions between agents and their environment (Nelson and Winter 1982).

Innovation is central to evolutionary economics and is considered a marker of the capitalist economic system (Lent and Lockwood 2010). Indeed, innovation implies experimentation with new forms of physical technology, social technology and business techniques which – as history tells us – are core drivers of increases in efficiency and productivity, economic growth and the generation of wealth (Beinhocker 2007). This process of selection, adaptation and multiplication also takes place at the firm-level, where there is continual generation and selection of new products and services. The lack of narrative around innovation is one of conventional economic theory’s greatest flaws: indeed, by assuming that economies and firms are in or close to equilibrium, neoclassical models simply overlook the role of innovation in modern capitalism.

Like complex systems theory, evolutionary economics emphasises the crucial role of history in shaping the future. Past interactions and decisions have major impacts on the economy – a characteristic known as path dependence – and any initial small changes in an economy can produce drastic downstream effects, partially driven by networks and cross-cutting hierarchical organisation. Economic outcomes are determined not only by current conditions but also by previous decisions and initial conditions (Durlauf 1997).

If adaptation and innovation are central to the evolutionary economics critique of neoclassical economics, then the psychology of human beings is central to that of the behavioural economists. In short, behavioural science is a combination of psychology and economics that has led to a debunking of the traditional economic assumption of rational, self-interested individuals. This approach explores the limits to human rationality in decision-making. It argues that human agents do not possess the flawless ability to maximise utility or profits by weighing all available alternatives presented to them and that there are flaws and imperfections associated with decision-making (Lambert 2006).

Behavioural economists believe decision-makers exhibit what they call bounded rationality, bounded self-interest and bounded willpower (Jolls et al 1998). Bounded rationality recognises the limitations agents face when it comes to decision-making. Despite any prior intentions to be rational, limited information and other constraints prevent agents from making optimal decisions. In addition, agents are not always selfish, or self-interested: their self-interest is usually bounded by a sense of fairness. And bounded willpower acknowledges that agents at times find it difficult to make decisions that will benefit them in the long term.

Agents and firms rely on decision-making methods that differ from those described in neoclassical economics. Heuristics, framing and loss aversion shape their choices (Thaler and Sunstein 2008). When making decisions, economic agents cut corners. They use rules of thumb (heuristics) rather than gather all the relevant available information (an impossible task anyway); they reach different conclusions depending on how a problem is framed to them; and they avoid taking decisions that might lead to losses (Lambert 2006).

These behaviours characterise the actions of consumers. For example in a study commissioned by the Office of Fair Trading in the UK (2010), price framing was found to heavily influence outcomes. Consumers frequently miscalculated and achieved lower value when purchasing special offers compared to those offered at a simple unit price. They simply assumed that the special offer must be the best deal. Evidence of market inefficiencies like this shows people are not always rational decision-makers in their role as consumers.

Acknowledging the psychology of individuals in decision-making has led to more accurate representations of agents in economic models, thanks in part to behavioural science. These findings are shared by other heterodox economic schools. In models derived from a complexity or an evolutionary economics perspective, therefore, people are not assumed to be rational agents: they factor in the ability of agents to learn and adapt based on past experience and allow for trial and error and flexible behaviour (Nelson and Winter 1982).

To summarise then, complexity, evolutionary and behavioural thinking puts strong emphasis on dynamics, adaptation, psychology, disequilibrium and innovation. Modern economies are complex adaptive systems, rarely tending towards a steady state equilibrium in which supply equals demand and markets clear. Most change occurs endogenously, rather than as a result of exogenous shocks. Economies operate with constant fluctuation and multiple equilibria.

Policymakers operate in a neoclassical framework for the most part. They tend to evaluate various policy interventions by estimating the impact a given policy change might have on the economy and comparing this to what would happen in the absence of that policy being pursued.

Complexity economics on the other hand suggests that since the economy is a complex, adaptive and dynamic system, it is inherently difficult to predict outcomes and responses to particular policy changes (Ormerod 2010a). This presents immediate challenges for policymakers. Predicting future trends is problematic if markets and economies do not return to equilibrium, when agents are not always rational and when uncertainty is in-built into the system.

A deeper understanding of the relationship between macro outcomes and individual decisions is therefore needed for policy formulation. Solutions under complexity tend not to be based on deductive analysis or top-down approaches, but explore interaction and behaviour using a bottom-up approach. This inductive method makes use of empirical analyses such as agent-based modelling (Holt et al 2010) and tends to do away with conventional modelling techniques.

Indeed complexity economists believe emergent phenomena are better understood through computer simulations than through mathematical theorems (Rosser 1999). Computer simulations allow researchers to explore a wide range of possible outcomes (Arthur et al 1997) while agent-based modelling allows us to capture the key features of complex economic systems, in particular the interactions and networks between agents.

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Given the above, Eric Beinhocker (2007) argues that the role of government should start from the premise of seeking to ‘shape the fitness environment’. This would allow free markets to assume their natural role of differentiating, selecting and amplifying successful economic behaviour. But by analysing and monitoring evolutionary processes within the market, policymakers can attempt to influence them so as to better respond to society’s needs. The aim of policymakers should, therefore, be to shape the environment in which plans or projects are more or less likely to succeed or fail according to their ability to meet society’s needs.

An example is the use of carbon taxes. One of the main purposes of a carbon tax is to shift the fitness landscape so that projects and technologies with low emissions have a better chance of succeeding. Here the market is still allowed to differentiate, select and amplify successful plans – but the environment in which the market operates is shaped by government. However, while they can be important in influencing behaviour and market outcomes, carbon taxes and other pricing instruments have their limitations. As Jim Watson argues, carbon pricing assumes that consumers and businesses will react rationally to the price signal. Since complexity economics suggests that this will not always be the case, additional measures may be needed to drive forward the low-carbon transition at a sufficient rate – particularly if the carbon price is set too low.

Policy can also draw from evolutionary economics, for example, by focusing on how selection mechanisms create desirable and socially optimal outcomes. Evolutionary economics sheds light on problems of long-term economic growth (Nelson 2005), environmental change (Faber and Frenken 2009) and regional policy (Boschma and Lambooy 1999), as well as new innovations and technologies, and the effects of technological and social change (Lent and Lockwood 2010).

In particular, evolutionary economics argues that the way to thrive in an evolving and changing economy is to innovate. Perhaps because neoclassical models overlook its role, innovation has rarely featured at the centre of economic policymaking in the UK. Historically, innovation has been patchily applied in the UK as part of growth strategies, and businesses and policymakers have been slow to respond to rapid business transformations. The evolutionary approach, however, suggests innovative business activity should be actively encouraged. Indeed, as Adam Lent and Matthew Lockwood (2010) argue, the UK’s growth strategy would greatly benefit from placing innovation at its core.

Methods from evolutionary economics have also been used to inform approaches to international development. Richard Nelson (2005) suggests moving away from the overly rigid neoclassical prescriptions of simply increasing investment in human and physical capital in developing countries and towards greater learning and innovation. This would involve learning how other countries have advanced their economy and gaining the knowledge of how modern technology can be used most effectively in achieving desired economic outcomes (Reinert 2006). In an earlier article with Sydney Winter (1982) Nelson argued that ‘flexibility, experimentation, and ability to change direction as a result of what is learned are placed high on the list of desiderata for proposed institutional regimes’.

Crucially, policymaking from an evolutionary economics perspective recognises that the state is limited by the same factors facing agents: it is not, and cannot be, in possession of a full set of information. Therefore, the state must be willing to learn from experience and adapt its approaches. Policymaking needs to be more flexible and willing to break with organisational routines.

While complexity and evolutionary economics have struggled to get a foothold in policymaking to date, many governments have begun to reflect on the analysis of behavioural economists when exploring policy interventions. In the UK, for example, the government set up in July 2010 a dedicated Behavioural Insights Team (also known as the ‘Nudge Unit’), tasked with assessing potential policy interventions through the lens of behavioural thinking. In particular, it is seeking to use what is referred to as ‘choice architecture’ to evaluate the impact that framing details in different ways can have on how people make decisions. Choice architecture has already been applied and proved to be effective across a number of areas, including savings for pensions. While most people understand that pensions offer substantial rewards in the future for a relatively modest sacrifice made in the present, enrollment in voluntary schemes tends to be at a low level. Changing the rules so that workers must ‘opt out’ rather than ‘opt in’ to pension schemes has been found to significantly increase participation.

As the title of Richard Thaler and Cass Sunstein’s influential book (2008) implies, small changes of this sort can ‘nudge’ people to make better decisions about their health and financial wellbeing. Libertarian paternalism has the potential to create better outcomes, while retaining people’s right to choose. What is more, change can often be brought about at little to no cost; simply paying more attention to framing a particular choice may have a greater chance of achieving the desired outcome. As a result, behavioural concepts are being progressively incorporated into policies in many areas including environmental change, finance, international development, healthcare and competition policy. But, as Paul Ormerod has argued elsewhere (2010b), successful ‘nudges’ must also be grounded in an awareness of the network effects that influence an individual’s choices and behaviour and how this can change over time: without this understanding, nudges may fail in the same way as conventional command and control policies.

The neoclassical economic model is based on a series of simplifying assumptions that result in a poor representation of the real world. New schools of economic thought are emerging built on a more accurate analysis of the way economic agents behave and the way decisions are really made. These heterodox schools of economic thought dismiss notions of rational economic agents and profit-maximising firms in favour of a greater focus on psychology, interactions and history.

Complexity economics emphasises the power of networks, feedback mechanisms and the heterogeneity of individuals. Evolutionary economics is centred on the ideas of continuous adaptation and the creation of novelty; it recognises the key roles of innovation, selection and replication in the economy. And behavioural economics seeks to understand how and why individuals behave as they do, rather than assuming that they act like the robotic homo economicus of the neoclassical textbook.

Already these approaches are beginning to help us understand some of the economic anomalies that orthodox economics cannot explain. As they develop in the future and the appetite for new economic thought grows, our understanding of the economy – and our economic policymaking – can only be improved.

Excerpt from Complex New World: Translating new economic thinking into public policy, published by the Institute for Public Policy Research (IPPR).

References

Arthur B (1999) ‘Complexity and the Economy’, Science, 284: 107–109

Arthur B, Durlauf S and Lane D (eds) (1997) The Economy as an Evolving Complex System II, Redwood: Addison Wesley

Beinhocker E (2007) The Origin of Wealth: Evolution, Complexity and the Radical Remaking of Economics, London: Random House

Blanchard O (2010) Macroeconomics, Harlow: Prentice Hall

Boschma R and Lambooy J (1999) ‘Evolutionary economics and economic geography’, Journal of Evolutionary Economics, 9: 411-429

Day R (1994) Complex Economic Dynamics, Volume I: An Introduction to Dynamical Systems and Market Mechanisms, Cambridge, MA: MIT Press

Dosi G and Nelson R (1994) ‘An Introduction to Evolutionary Theories in Economics’ Journal of Evolutionary Economics, 4: 153–172

Durlauf S (2011) ‘Complexity, Economics, and Public Policy’, working paper, Madison: University of Wisconsin

Durlauf S (1997) ‘What should policymakers know about economic complexity?’ The Washington Quarterly, 21: 157–165

Fontana M (2008) The Complexity Approach to Economics: a Paradigm Shift, Turin: Dipartimento di Economia, University of Turin

Faber A and Frenken K (2009) ‘Models in evolutionary economics and environmental policy: towards an evolutionary environmental economics’, Technological Forecasting and Change, 76: 462–470

Holt J, Rosser B and Colander D (2010) ‘The Complexity Era in Economics’, Middlebury College Economics discussion paper no 10-01, Middlebury: Middlebury College

Jolls C, Sunstein C and Thaler R (1998) ‘A Behavioral Approach to Law and Economics’, Christine Stanford Law Review, 50: 1471

Lambert C (2006) ‘The Marketplace of Perceptions’, Harvard Magazine, March–April 2006

Lent A and Lockwood M (2010) Creative Destruction: Placing Innovation at the Heart of Progressive Economics, London: IPPR

Metcalfe J, Fonseca M and Ramlogan R (2002) ‘Innovation, Competition and Growth: Evolving Complexity or Complexity Evolution’, Revista Brasileira de Inovação, 1: 85–122

Nelson R (2005) ‘Where Are We Now on an Evolutionary Theory of Economic Growth, and Where Should We Be Going?’ CCS working paper no 3, New York: Columbia University

Nelson R and Winter S (1982) An Evolutionary Theory of Economic Change, Cambridge: Harvard University Press

Nelson R and Winter S (2010) ‘Evolutionary Theorizing in Economics’, Journal of Economic Perspectives, 16: 23–46

Office of Fair Trading (2010) The impact of price frames on consumer decision making, London: Office of Fair Trading

Ormerod P (2010a) ‘Economics, management, and complex systems’ in Peter A, Maguire S and McKelvey B (eds), The Sage Handbook of Complexity and Management, London: Sage Publications Ltd

Ormerod P (2010b) ‘N-squared: Public policy and the power of networks’. http://www.thersa.org/ data/assets/pdffile/0003/330258/RSAPamphlet-publicpolicy.pdf

Reinert E (2006) ‘Evolutionary Economics, Classical Development Economics, and the History of Economic Policy: A Plea for Theorizing by Inclusion’, working papers in Technology Governance and Economic Dynamics 01, Tallin: TUT Institute of Public Administration

Rosser J (1999) ‘On the Complexities of Complex Economic Dynamics’, Journal of Economic Perspectives, 13(4): 169–192

Thaler R and Sunstein C (2008) Nudge: Improving Decisions About Health, Wealth, and Happiness, London: Yale University Press

2016 August 19


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  • Peter Barnes

    This is the best summary I’ve ever seen of the behavioral, evolutionary and complexity critiques of mainstream economic theory. Congratulations to Amna Silim.

    My comment has to do with what’s missing from all of these heterodox strains, and my feeling that no one of them, nor even all of them together, comes fully to grips with the failures of mainstream economics. This is obviously a huge subject, so let me just plant a seed.

    What is the primary purpose of economics? Is it to predict the future so we can make better business and policy decisions? To help maximize production and consumption of monetized goods and services? To help fix deep systemic problems?

    I tend to think it’s the third. But as I understand them, all of the aforementioned heterodox strains are primarily driven by a desire for greater predictive accuracy. If we get human psychology right, and add in feedback effects and endogenous innovation, then our models will predict the future more accurately, and a few of us will win Nobels.

    My point is, this doesn’t move me. I’m all for more accurate predictive models, but what I really care about is fixing the three tragic flaws of our current economic operating system: ever-widening wealth concentration, accelerating destabilization of nature, and rising economic insecurity at all but the highest levels of wealth. What I would like to see is a school of heterodox economics that directly addresses those deep systemic problems.

    Such a school should incorporate many of the insights of behavioral, evolutionary and complexity economics, but it should also integrate key insights of ecological and institutional economics, as well as some heterodox theories of property rights, inheritance and rent.

    I’ll stop here and invite further comments.

    • Institutional economics (old version a la Peirce and Thorstein Veblen) and evolutionary economics are related in mind and substance: Veblen’s essay can be read as discussion of limits to innovation: traditions, norms that shape economc decisions conservatively as well as a critique of the ‘neoclassical’ psychological model of self-interested maximization. These points resurface in Simon, Drucker, Hayek and not least Nelson and Winter.

  • I like the general line of argumentation in here. The three streams of complexity (and systems science), behavioral economics (and psychology), evolutionary economics need to be more integrated! The big question to me is how? They can be integrated e.g. based on the monist, evolutionary-adaptive worldview of Ernst Mach, the Viennese physicist investigating sense perceptions and dealing with the foundational philosophical requirements for such an approach. In this he covered foundations of (still today largely missing theoretical) psychology, triggered the development of an evolutionary, adaptive gestalt psychology and jumped across, or rather integrated, the metaphysical rifts between Kantian, idealist Hegelian and Marxist (later Leninist) materialist approaches.

    In the social sciences, Ernst Mach incidentally influenced a number of scientists in the fields of economics / politics / management from Samuelson to Schumpeter to Hayek and Popper (and thus also Soros) and to Simon and Drucker. One can understand the questions, topics and arguments of these researchers much better, if one realizes that they are (sometimes indirectly) influenced by his genetic-adaptive, experimental worldview and a lot of their research programs can be seen as continuation of questions and approaches Mach put in in modern fashion on the scientific agenda.

    Mach himself is influenced by the Austrian Leibniz-Wolff-Bolzano ‘school’ and a ‘heretic’, liberal, innovative, experimentalist tradition of natural philosophy (in contrast to scholastic and purely logical, ‘platonic’ approach to philosophy and science – which are similarly criticized by Taleb on the basis of Sextus Empiricus experimental natural philosophy as well).

    Mach thus can point to an integration of the three streams and to ways to make progress on new, better psychological, evolutionary economic thinking and acting.

  • Thank you, Peter, for your comment. Thank you, Amna for the analysis. Thank you to Evonomics for printing this. It is a terrific article that allowed me clearer insights into the educated mind that works “hands-off” with economics as a system. Economics as discussed seems to be an intellectual game that is deeply flawed in its impacts.

    This is not the fault of the author. The flaws are part of the system…the embedded presumptions of the entrained intellectual mind that is divorced or disconnected from the inherent nature of life itself. In striving to be an “analysis” tool, economics loses its relevance in a way. People are subjective, and the game as described strives to be objective…and it cannot be. It is quantum.

    It reminds me of reading an article written by the head of the World Bank. As I recall the article, this person was talking about making certain changes in the international economic world to “balance the economic scale” or something like that. (So that the world economy would not collapse).

    From a logic standpoint (sitting inside the non-human numbers) she made sense mathematically. Her objective was to make the numbers on the page balance. But from a human impact perspective it was not logical at all and she seemingly had absolutely no emotional cognition of it. The impact of this “balancing of the books” by these actions of hers, then meant that millions of people would die as a result. Ironically, the reality of that was not even included in the subsequent discussion by the elitists involved. It was a math problem, not a global human problem.

    To me, it was like reading an article from inside the twilight zone. This person was absolutely so isolated from the “real world” of people living in the streets that she did not even relate her solution to human ripple effects. To her it was a simple moving of numbers from one side of the page to a different spot. It was about reactive measuring or directing the flow from a dissociated or disembodied state.

    This is disconnected from what the numbers actually represent.

    Numbers have meaning…they reflect the movement of energy between people, organizations, and structures…and this movement of numbers affects life itself. It effects the future of food, the forests, the trees, the earth.

    Economics perhaps could be compared to the medical model. Doctors are taught that the human body is a machine to be cut, spliced and chemically manipulated. While this is valuable, it is limited in scope. Often, they forget that the human body grew by itself, heals itself and is alive and makes its own choices on a cellular level. In reality, a complex human soul is living in that body they are messing with, and that soul feels and is part of the equation.

    To me, most discussion of economics misses the whole point that money, markets, and systems are about people who are alive and living. Economics misses the point that the money and numbers are reflections of life force in motion and are inspirable, creative, inform and pre-pave the future.

    I have come to this conclusion over years in business from coaching free enterprise people. And then I have applied this knowledge to study the mass incarceration driven economy. The relevance of prisons and war are so far removed from consequences…it has become self-destructive, addictive and is hemoraghing our society entirely. And the economics guys in charge of the numbers (profiteering) seem to have absolutely no idea of the ripple effects.

    Therein lies the opportunity in new economics. In the past, none of this conversation addresses humanity and the nature of humans as the major moving part of this very sterile conversation.

    In fact, we humans are the very life force that these numbers attempt to measure. The nature of humanity is a critical part of the potential that is untapped. Humans have a desire to provide, protect and nurture. We propell economies…and that element is not part of the conversation. Until it is, economics will continue to miss the mark.

    This new perspective could transform the conversation from hands-off theory into hands-on practices that address the nature of leadership, vision and potential. Living economics is beyond using economics as a measuring tool after the fact – it is about embodying the true dynamic nature of humanity at work globally.

    If you want to learn about a model of restorative economics (designed to help human leaders transform the mass incarceration economy through real innovation), you are invited to read the booklet “Stop Punishing Taxpayers, Start Rebuilding Community” at RestorativeCommunity .com This is a replacement economic model that inspires humans, rather than manipulating them.

    • The needs of Humans on spaceship Earth should be the primary focus of any organizational structure. Here’s an idea: let’s free people to volunteer/contract for work wherever they want, and pay them directly in their own private account. No person or group can pay anyone to do anything! You and I are allowed to go out and earn money however we and our community deem desirable or necessary. And for this ‘work’ we get paid, not by a person, not by a Corporation, not by a Government, but simply get paid, money gets deposited into our account. When we buy something, the money from our account is simply subtracted for the cost of that item, but not transferred to any person or group or government. The people who do the work, earn money. The people who create new inventions, or discoveries, or anything good for the local community or world could be rewarded bonuses as incentive. Groups of people working together to produce the best, most efficient and economical products are rewarded with pay for their work. The groups now compete to produce the best for people and planet rather than for profit. There is no profit necessary. The idea that 1 man or group of men should own the means of production to extract $ from the labor of other men is as ridiculous to our current world as monarchy was hundreds of years ago. $ is the new monarchy. It’s time to evolve.

      • Joy Gilfilen

        Do you have an idea for how we could implement such a structure that would be able to manage this…without it being taken off into power grabbing? Are you thinking something like a cryptocurrency or something?

        • Blockchain tech could be setup to create a secure ledger for each person, it already exists as BitCoin. check out http://www.Copiosis.com for more specifics on how each individual contributes to system of work for pay. In this way, each person could also be given an universal basic income to provide for at least the basic needs, while opening up unlimited opportunity to earn more based on contribution and expertise. all this within democratically run groups, small and large, with no need for profit. also see http://www.thenextsystem.org . There’s also a unique solution to providing every person on earth with a home and ability to move and travel as free citizens of the world, because with the security of a home, a person earning UBI and open opportunity to contribute to society for more reward, would be a safer and happier world for sure. The challenge is to present the combination of these ideas along with how to implement them all within the stride of the current global production is among the next problems to be solved. peace.

        • here’s the Introduction to our Plan: EarthVote.org/common-planet.html

  • Patrick cardiff

    I think we are getting off-topic here with respect to the utility of Economics itself. The main problem I see is the difference between the use of Economics to try to compare large aggregates and “social changes” versus the use of positive Economics to understand homo economicus. Scale is one thing – and macro has lost the quality debate – in part because it has not produced compelling, USABLE answers – what would we do with such answers if we had them? The Cambridge Capital Controversy went something like that – there’s new, and then there’s rational.

    The effect and response on social behaviors of measured policies, for example, are NOT predictive. Even with supercomputers the weather is not predictive, and there are arguably fewer factors involved in predicting the weather. When one takes heterogeneous individual behavior and – for whatever reason – aggregates bottom up, there MAY be some validities attached to these estimates, such as construct information, or even predictive validity depending on the samples used. But even bottom-up aggregation fails to represent the content of “society.” It is usually only a secondary goal to aggregate individual consumers anyway. But few will deny that “bottom up” is better than “allocate down.” All one need do is to consider whether we are effectively measuring “growth” in this country to realize how little control we have over macro estimation. There has never been a macro-econometric model of the US ever actually used.

    Empirical economics at the micro-level is applied. I use evidence from macro-theory to form prior beliefs about a local-data model, to increase the precision of these beliefs. Macro-information might allow a sign, or trend, but forget about trusting a level and so, forget relatives. Even averages from large samples are of questionable quality sometimes given the many non-sampling errors you see in surveying nowadays. It is silly to use an aggregate total comprised of hundred of variables to refer to a detailed category.

    So for the last 25 years I have been the thorn in the side of aggregators. I have dealt mainly with household-level data. I am so tired of people saying “well, that’s all we have, may as well make the most of it…” My thing has always been “Show me the evidence! If you show me your standard errors, I’ll make my own decisions about your methods and estimates.” Science requires that we test, not rest on, assumptions. Faced with an macro result, I always question what function produced that estimate, and I have never received a satisfactory answer. Macro people really do make assumption that Statisticians never would make.

    People who call themselves Macro-economists and who do not provide their public with proper, REPRESENTATIVE numeric data, you might as well be talking with Joe at the pub. They’re hiding something! That’s why the Economic discipline needs an Statement of ETHICAL Standards.You would only sign if you were transparent about your hypothesis and estimates. “You’ve got a experiment you want to run; what real-world conditions best exemplify that experiment?”

    Macro has have given Economics a bad name because of a repeated pandering to an ignorant public willing to accept the pronouncements of an Emperor. Yet look, the Emperor has no clothes! Much is a veneer from the Ivory Tower. There needs to be a period of reflection before we come to terms with the damage done.

  • Codanonymous

    What really surprises me of Evonomics is the absolute absense of any mention to a hetherodox school that has much more to say and much more fundamental than the behavioral, evolutionary or complexity ones, with much more history on it and marginalized, that is, ecological economics and its thermodynamical implications for the economy, which Georgescu Roegen described in the most important economic book (to me) of the 20th and so far 21st century, the entropy law and the economic process. I think it’s because evonomics is targeting a certain type of audience not ready to explore the implications of what ecology, biology and physics has to say in the context of economics.

  • Well done Amna – your critique is great as far as it goes.

    I agree with most of what Peter Barnes said, and even Peter doesn’t take the paradigm of evolution deep enough to see what needs to be seen.

    In 1978 Edward Lupinski famously quipped to Milton Friedman that socialism can only work if everyone has two servants, including the servants. Technology is rapidly approaching the point at which that will become a practical reality.
    The problem is not the technology, that is on a very stable double exponential trend.

    The real problem is our understanding of understanding itself, what we are, how we got here, and what we are capable of being.
    The cosmology is now fairly stable, that our planet has been here for about 4.5 billion years, and life started in very simple forms about 4 billion years ago, and multicellular life started about 1 billion years ago, and human beings that could walk and make tools about 2 million years ago, and around 100,000 years ago the complexity of our societies significantly expanded, then about 15 thousand years ago, another big expansion in our ways of being, 100 years ago atoms, quantum mechanics and relativity, 50 years ago molecular genetics and plate tectonics and that process has continued its exponential expansion into generalised computational and paradigm spaces and Artificial Intelligence.

    Now it seems that there are a few ideas around that served our ancestors well, that are no longer serving us nearly as well.

    One of those ideas is the idea of money, of using markets and exchange to value things.
    When most things were genuinely scarce, that made a lot of sense, and served many useful functions beyond the simple function of exchange, in terms of expanding human networks of trust and information flow, extended distributed coordination functions, etc. These were valuable functions, that served to increase the security of most people most of the time.

    And now there is a fundamental change.
    Now we are developing tools and technologies to automate processes, and we are doing so at an exponentially expanding rate. Most such processes have been in the realm of information processing to date, and they are moving ever deeper into the realms of manufacturing and design. We are seeing the 1st generations of 3D printing. As that trend matures into full blown molecular level manufacturing, then nothing need be scarce.

    Even right now, we have the capacity to produce enough goods and services to meet the reasonable needs of every human being alive today, to do whatever they responsibly choose (where responsibility has both a social and an ecological context to it).

    The big issue is, that money and markets can only ever value any universal abundance at zero.
    If we deliver universal abundance, we break the money system.
    That is too radical a mind shift for many at present.
    It is logical, and inevitable (if we are to survive at all as a species) – but at present dogmatically held beliefs (in all their forms, religious, economic, political, cultural, scientific, strategic, algorithmic, paradigmatic etc) prevent most people from considering such things.

    Many people would much rather die than question “truths” they hold sacred. I have seen that over and over again, in the last 6 years since curing my own “terminal” cancer, after being ejected from the medical system as “incurable” and sent home “palliative care only”, through changes in diet (and publishing all my details including my medical records on my blog site).
    Doing that required that I be prepared to examine all the evidence available, and be willing to try anything that had evidence that it might work.

    Since then, many people with a similar diagnosis have visited me.
    Few have been willing to do what it takes to change old habits and beliefs.

    The evidence is clear, that most people would rather die than make a persistent conscious effort to challenge and change accepted habits or beliefs.

    In one sense, I see it happening, and know it is so.

    In another sense, I can’t understand it.

    I guess I have had the habit, for over 55 years, of challenging authority and proving it wrong.

    I don’t know what reality is, and I am very confident about many aspects of what it isn’t.

    My world doesn’t have certainty, it only has useful levels of confidence in particular sets of circumstances.

    And I am clear, beyond any shadow of reasonable doubt, that the combination of the idea of “Truth” and the idea that markets deliver a useful measure of value, now combine to deliver the greatest source of existential risk to our species.

    Human beings can be cooperative, or they can compete – we have both natures, and which one gets to express is very much a function of the context we perceive.

    The scientific reality is, that we have sufficient abundance of energy and mass and technology to meet the reasonable needs of everyone, and in such an environment, cooperative behaviour (at all levels), delivers better outcomes that competitive behaviour. And to be stable, cooperation requires effective attendant strategies to detect and remove cheating strategies.

    Markets are fundamentally based in scarcity, and as such tend to promote competitive behaviour from humans.
    In any technological realm that has available technologies for mass destruction, competitive behaviour poses fundamental existential risks to all of us.

    Using this logic alone, it must be clear to anyone prepared to look, that markets have passed the point of maximal utility in the story of human evolution, and have now moved into the realm of posing serious existential risk.

    So the question now is not if we evolve beyond markets, but rather how and how quickly we evolve beyond markets (or go extinct).

    And complexity theory would seem to suggest that we try as many different ways as possible, to find security in both distributed redundancy and diversity.

    And as an initial step towards supporting such a move away from markets, and an exploration of a diversity of alternative strategies, some sort of high Universal (global type universal – not just national) Basic Income would seem to be a reasonable intermediary strategy.

  • disqus_QZX8ENhLyb

    It appears to me that Evonomics is in the process of “rediscovering” laissez-faire, free market, anarcho-capitalism and sneaking up on the concepts of “natural law.” Do the names Schumpeter, Menger, Boehm-Bawerk, Mises, Whateley, Reisman, Rothbard strike a note anywhere? How about the terms “praxeology” and “catallactics”? Ever hear of those? Seems to me a visit to URL: https://mises.org/ is in order. You will find it all there, free for the asking. The idea of individual subjectivity is not new .

    By the way, who said: “In this present crisis, government is not the solution to our problem, government IS the problem.” It was Reagan on January 20th

    • The notion “There is nothing new under the sun, just the desire and will to see things differently” is very common, and thoroughly debunked.

      Wolfram’s NKS clearly demonstrates that even the simplest of possible systems (a linear array of cells with only two possible states) can generate complex and unpredictable behaviour infinitely.

      The evidence is now clear beyond any shadow of reasonable doubt that human beings are capable of creating and exploring novelty at potentially infinitely new dimensions and domains.

      Novelty is in a very real sense what we as a species are all about.

      In the sense that government was an experession of the idea that the problems of human social systems can be resolved by any set of fixed rules or processes, then Reagan was right ( “In this present crisis, government is not the solution to our problem, government IS the problem.”).

      In the sense that social systems can survive and prosper without systems to detect, and remove all benefit received from the use of, cheating strategies on the cooperative that is human society, then he could not have been more wrong.

      Human beings are very complex social organisms.
      We require a cooperative society to survive. Cooperatives require secondary strategies to effectively prevent destruction of the cooperative by cheating strategies.
      We also require individual security and freedom.

      Effective social systems have to acknowledge both of those realities.

      Human beings are creative.
      We all have our habitual aspects, and we all have our creative sides.

      Part of what we all do is explore novelty in some dimensions that interest us.

      We have these very complex social, cultural, technological, philosophical and economic systems that have evolved around us.

      We are now moving into domains of complexity where many of the old systems that can arguably be said to have served our ancestors well no longer work for us.

      Chief amongst those systems is the very idea of exchange, of markets, of money and capital. These ideas, these ways of conceptualising and interpeting our reality are now in direct conflict with the notions of individual life and individual liberty that many of us claim to value so highly.

      If the vaues of individual life and individual liberty are to have any real meaning, they must be applied universally.

      In an age of exponentially increasing technological capacity, capable of fully automating the production and delivery of an exponentially expanding set of goods and services, using a notion of value based in scarcity (exchange value, market value, money, capital) becomes the single greatest threat to the security of all of us.

      Yet most people are so habituated to using that frame of thinking, that it is almost impossible to think outside it, except when they think about things like love, like how they feel when they hold someone they care for, or see something of great beauty, but they are taught that those are something unrelated.

      We all know what it is to value things outside of markets, and there are entire industries devoted to trying to convince us otherwise. Arguably, that applies to neoclassical economics as a whole.

      • disqus_QZX8ENhLyb

        I HAVE INTERSPERSED MY COMMENTS WITHIN YOUR APPLICABLE TEXT IN BLUE.

        • Not sure where your comments are – but they’re not here.