In October, the US National Science Foundation put out a Grand Challenge asking economists and social scientists to draw up “grand challenge questions that are both foundational and transformative”. Respondents to the 2020 challenge were asked to look forward 10-20 years, explain the challenges ahead and propose a strategy for addressing them.

The wording of the Challenge was as follows:

At the end of the first decade of the 21st century, the social, behavioral, and economic sciences face extraordinary opportunities to address next-generation research challenges. The landscape is vast and complex, stretching across temporal and spatial dimensions and multiple levels of analysis — from studying the human brain to implications of decision-making in a dynamic and fragmented yet interconnected world. As we look forward 10 or even 20 years, [we] seek to frame innovative research for the year 2020 and beyond that enhances fundamental knowledge and benefits society in many ways.

The Challenge has been covered by various media outlets and blogs. One of the most interesting has been a Newsweek series which argues that the scope for truly groundbreaking responses is worryingly limited because of the prejudices that plague economics. As a whole, the economics profession is seen as having become:

…much more intolerant of divergence from orthodoxy… The range in which dissent happens is so narrow. In a sense they still cannot imagine the system can operate to undermine itself. That is not a position that is allowed anywhere in the economics profession. The field got rid of methodological self-criticism…

The piece goes on, echoing a previous Aid on the Edge post:

Indeed, the joke on economists… is that they create simplistic models that depend on people behaving as rational actors motivated by self-interest, yet “they have a blind spot regarding themselves.” The way they squabble mulishly to defend now-indefensible positions is itself evidence of how flawed those rational-actor models are…

However, there may be some hope for the 2020 Grand Challenge yet. One specific proposal has had an extraordinary show of support – over 50 signatories including Elinor Ostrom, Yaneer Bar-Yam, Eric Beinhocker, Paul Ehrlich, Jonathan Haidt, Simon Levin and many others. The proposal, entitled The Relevance of Evolutionary Science For Economic Theory and Policy is a submission by evolutionary biologist David Sloan Wilson and economist John Gowdy (and can be downloaded here). Wilson, Gowdy and their supporters suggest that evolutionary science provides an “exceptionally useful set of theoretical and empirical tools for integrating the many disciplines…  required to formulate economic theory and public policy for the 21st century.”
The table below illustrates the differences between the evolutionary / complexity perspective on economics and the more traditional neo-classical thinking, drawing on work by Eric Beinhocker and W. Brian Arthur:

Complexity / Evolutionary Economics Traditional Economics
Dynamic – Open, dynamic, non-linear systems, far from equilibrium – Closed, static, linear systems in equilibrium
Agents  

– Modelled individually; use inductive rules of thumb to make decisions; have incomplete information; are subject to errors and biases; learn to adapt over time; heterogeneous agents

– Modelled collectively; 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), mostly homogeneous agents
Networks  

– Explicitly model bi-lateral interactions between individual agents; networks of relationships change over time

– Assume agents only interact indirectly through market mechanisms (e.g. auctions)
Emergence  

– No distinction between micro/macro economics; macro patterns are emergent result of micro level behaviours and interactions.

– Micro-and macroeconomics remain separate disciplines
Evolution  

– The evolutionary process of differentiation, selection and amplification provides the system with novelty and is responsible for its growth in order and complexity

– No mechanism for endogenously creating novelty, or growth in order and complexity
Technology – Technology fluid, endogenous to the system – Technology as given or selected on economic basis
 

Preferences

 

– Formulation of preferences becomes central; individuals not necessarily selfish

– Preferences given; Individuals selfish
 


Origins from Physical Sciences

– Based on Biology (structure, pattern, self-organized, life cycle) – Based on 19th-century physics (equilibrium, stability, deterministic dynamics)
Elements – Patterns and Possibilities  

– Price and Quantity


Perhaps the most serious challenge to the traditional orthodoxy on the right hand side of the table has been the recent financial crisis:

it was largely because the field of economics came to be dominated by “neoclassical” thought—or the idea that markets are rational and can reach “equilibrium” on their own—that so-called financial innovation on Wall Street was allowed to run amok in recent decades. That led directly to the crisis of 2007–09. No matter how crazy or complex the products got, the theory was that, with little government oversight, the inherent stability of markets would keep things from getting too out of hand.

Or as Alan Greenspan put it, rather more succinctly:

[Our] whole intellectual edifice has collapsed.”

Despite the apparent failure of existing thinking and the potential benefits of evolution and complexity-inspired approaches, the experience of evolutionary economists has not been an easy one. J Doyne Farmer is a physicist at the Santa Fe Institute who is trying to bring the idea of complexity and evolution into economics by making use of advanced computing power to map human economic behavior the way weather or climate change is analysed. However, Farmer’s programme for studying systemic risks in markets was only approved after a sympathetic case officer overruled negative assessments by “neoclassical economists who reject any model that doesn’t tend toward general equilibrium”. As Farmer puts it:

The established view just holds this stuff back. One of the dangerous cultural patterns that economics has fallen into is an excessive emphasis on theorem proof for its own sake rather than what gives you scientific results.”

The Newsweek article concludes on a note that somehow manages to be both visionary and pessimistic:

Should there not be a new economics that develops fresh concepts? Economics progresses one funeral at a time… In other words, it was necessary for the old lions to pass on before new seminal thinking took hold. But we may not have time to wait upon funerals. Policy is driving relentlessly ahead, and the economics profession and other sciences may get left far behind.
PS For more on how evolutionary thinking might help in development  policy and practice, do check out Owen Barder’s fantastic presentation from last month.

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Join the conversation! 1 Comment

  1. Ben

    Thanks for this very interesting post. The Wilson and Goady paper is very interesting.

    But I don’t recognise your caricature of “traditional economics”. The items on the right hand side of your table are the high-school economics story of perfect competition – a simplistic model designed to teach some of the basic principles, but no more believed to be an accurate model of the world than the simplistic, frictionless world of Newtonian mechanics that we all learned at the same age.

    When I first joined the British Treasury, in the 1980s, I was partly responsible for economic modelling of the impact of policy measures (such as raising tax rates). We used a highly non-linear economic model, which could be tilted into chaos with some judicious tweaking of key parameters. We routinely ran model simulations making alternative assumptions about imperfect information and learning. Depending on the assumptions we made, the model could be stable and converge, or it could explode (that was generally regarded as a bad sign). It just isn’t true that economists think the world is linear, or that everyone has perfect information, or that there is no connection between micro and macro policy.

    Look at the list of the winners of the Nobel prize for Economics:
    http://en.wikipedia.org/wiki/List_of_Nobel_laureates_in_Economics

    Almost all of them are for work about the implications of real-world phenomena such as information asymmetries, search costs, bargaining processes, bounded human rationality, non-market behaviour, drivers of innovation and growth – indeed, all the things on the left hand side of your table. And these Nobel laureates are the tip of a very large iceberg of economists working on these questions, and others, all of which exemplify the many ways in which the world is not like the simplistic model of perfect competition.

    Non-economists often complain that their economist colleagues make highly simplistic assumptions about the world – such as that systems are linear, or that everyone has perfect information. But this is a lazy dismissal of the modern science economics which reflects a complete lack of understanding of the state of the discipline.

    If people who stopped studying physics in high school dismissed physics on the basis that it is all founded on Newtonian mechanics, and that this is clearly simplistic and wrong, we would tell them to find out a little more about the current state of the science. Economists too are entitled to a little more respect than pretending that they believe the simple model you attribute to them.

    Kind regards
    Owen

    Reply

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About Ben Ramalingam

I am a researcher and writer specialising on international development and humanitarian issues. I am currently working on a number of consulting and advisory assignments for international agencies. I am also writing a book on complexity sciences and international aid which will be published by Oxford University Press. I hold Senior Research Associate and Visiting Fellow positions at the Institute of Development Studies, the Overseas Development Institute, and the London School of Economics.

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Biology, Economics, Evolution, Innovation, Public Policy, Reports and Studies