Elisa Lanzi and Rob Dellink, OECD Environment Directorate
Air pollution in Delhi has been so bad this November that the Indian Medical Association declared a public health emergency. At more than 25 times the WHO recommended level, the pollution peak in India’s capital has been extraordinary. This is becoming increasingly common in Delhi and other cities around the world due to emissions from biomass burning, coal fire plants, agriculture and especially agricultural burning and diesel transport.
Dangerously high concentration levels of air pollutants, and especially of fine particles, cause an increase in asthma attacks and lung conditions. Alarmingly, air pollution is tied to longer-term chronic health problems, such as respiratory and heart diseases, premature and underweight babies, allergies and increasing incidences of cancer. All these lead to a sizable–and increasing–number of premature deaths and illnesses. According to the latest Global Burden of Disease study published in The Lancet, outdoor air pollution caused more than a million premature deaths in India in 2016, whose cost, according to OECD estimates, amounts to more than USD 800 billion. But that is not all: there is a range of other social costs associated with air pollution, such as costs related to pain and suffering, and costs to biodiversity and ecosystems.
Air pollution also exacts costs on the economy with additional health expenditures as well as lost work days, which affect labour productivity. And, agricultural productivity can also be severely affected by air pollution as high ozone concentrations and slow plant growth reduce crop yields with important economic consequences.
Strong policy action must be taken. According to projections by the OECD the population-weighted average concentrations of PM2.5–the finest, most harmful particles–are projected to increase threefold by 2060 if ambitious action is not taken. Premature deaths from being exposed to pollution are projected to increase up to five times. This is a staggering number, and represents up to a third of global projected deaths in 2060. Incidences of illness will similarly worsen. Lost working days will increase significantly, to levels equivalent to more than six million people missing work on a daily basis by 2060.
Market costs to the Indian economy are projected to increase eightfold to over USD 280 billion by 2060–this is more than 7% of India’s current GDP (in 2005 Purchasing Power Parities exchange rates). The social costs from mortality due to air pollution would increase 15 to 33 times, as both the number of premature deaths and the value per death increase.
Air pollution is a global local problem: it is a global phenomenon with local environmental and human health impacts, particularly in high-density urban areas. As such, public policies to reduce emissions must be undertaken both at the national and local levels. International co-operation on limiting concentrations and implementing the best emission reduction technologies is essential for countries to put into motion solutions and policy tools to bring down air pollution. Urban planning and transport have a central role to play here.
Air pollution is also strongly linked to another global problem: climate change. This week at the 23rd Conference of the Parties to the UNFCCC (COP23) in Bonn, policymakers face decisions on their level of commitment in combatting climate change. Taking a closer look at its link with air pollution could provide impetus for immediate policy action. It would prevent higher numbers of premature deaths, and have a positive impact on the economy too.
References and links
Safi, Michael “Delhi doctors declare pollution emergency as smog chokes city”, 7 November 2017,The Guardian. See: www.theguardian.com/world/2017/nov/07/delhi-india-declares-pollution-emergency-as-smog-chokes-city?CMP=share_btn_link
OECD (2017), “The Rising Cost of Ambient Air Pollution thus far in the 21st Century: Results from the BRIICS and the OECD Countries”, OECD Environment Working Papers, No. 124: http://dx.doi.org/10.1787/d1b2b844-en
See the latest Global Burden of Disease at http://www.thelancet.com/gbd
Gabriela Ramos, Special Counsellor to the OECD Secretary-General and Sherpa to the G20
In 2016, surprisingly for many, Oxford Dictionaries chose as their Word of the Year “post-truth”, an adjective defined as: “relating to or denoting circumstances in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief”. This runs contrary to the main tenet of the OECD, the “house of best practices” whose works and analysis depend on high quality statistics and solid empirical evidence. So how did we get here, and what does it means for our democracies?
As the OECD’s G20 Sherpa, I witnessed the evolution of what was originally a financial crisis into an economic crisis, and more recently, after eight years of low growth and very slow recovery, into a political crisis defined by the lack of trust of people in the institutions that we built over so many decades. It is also clear that the values of openness, mutual assistance, and international integration on which the OECD was founded are being questioned.
One reason for this is that while we have told “the truth and nothing but the truth”, we have not told “the whole truth”. Like people gradually enclosing themselves in media silos and social networks that only give them news and views they are comfortable with, we have been happy to rely on economic models that work with comfortingly quantitative facts on GDP, income per capita, trade flows, resource allocation, productivity, and the like. These standard economic models did not anticipate the level of discontent that was created by the skewed outcomes that they were delivering, and that have prevailed for so many years.
Our “truths” did not capture very relevant dimensions that inform people’s decisions (including recent political decisions), and particularly those that are intangible or non- measurable concepts. This is why such important issues as justice, trust or social cohesion were just ignored in the models. Indeed, neoliberal economics taught us that people are rational, and that they will always take the best decisions according to the information they have to maximize utility. And that accumulation of rational decisions will deliver the best outcome on the aggregates. In this model there is no room for emotions or for concepts like fairness or resentment.
Populism, the backlash against globalisation, call it what you will, recognises these emotions. We should do so too, especially since we actually have the data and facts that gave rise to these feelings in the first place. I am referring to the increased inequalities of income and outcomes that almost all the OECD economies experienced even before the crisis and that the crisis made worse.
If we go beyond averages and GDP per capita and look at the distributional impact of our economic decisions for instance, the picture is devastating. Up to 40 percent of people in the lowest tenth of the income distribution in OECD countries (and 60% in my own country, Mexico) have not seen their situation improve in the last decades. On top of that, lower income groups accumulate disadvantages, as their initial condition does not allow them to access quality education and health care or fulfilling jobs, while their children are facing a sombre future with less chance of improving their lot. At the OECD we have confirmed this. Our data show that if you are born into a family whose parents did not reach higher education, you have four times less chance of reaching middle school. You may encounter more health problems, and have less fulfilling jobs and lower wages. You are trapped in a vicious circle of deprivation.
Even the loosely-defined middle classes in OECD countries are fearful for their future and that of their children. They too feel betrayed and are angry that despite working hard, saving and doing everything else that was supposed to guarantee a good life, they see the fruits of success being captured by a tiny elite while they are left behind. No wonder they are attracted to solutions that resonate with their emotions and seem to give them some hope.
What should an organisation like the OECD, committed to evidence-based policy advice, do in this context? First, we must speak out when there is a deliberate misrepresentation of the facts and realities. Even if the people delivering these lies are not aware of it, it does not discharge them from the responsibility to check the evidence. Presenting a view that is based on lies by omission or on purpose should be recognised as such and not go unchallenged in the “post-truth” environment.
Second, instead of defending our selection of facts, recognise that they were also biased, and that in many instances they represented preconceived notions of how the economy functions that have been proven wrong. To rebuild trust in the facts we produce to explain social and economic phenomena, we must ensure that they really represent the whole reality and provide workable solutions. We may need to start, as the Chief Statistician of the OECD has said, “to measure what we treasure and not treasure what we measure”.
Most of all we need to understand that economic challenges are not just economic. That is why the OECD’s New Approaches to Economic Challenges (NAEC) initiative promotes a multi-dimensional view of people’s well- being, with tangible and intangible elements (including emotions and perceptions) all worthy of consideration. The NAEC agenda is ambitious, calling for a new growth narrative that recognises the complexity of human behaviour and institutions, and calls on sociology, psychology, biology, history, and other disciplines to help write this narrative and build better models to inform economic decisions.
We thought there was only one truth, and we promoted it without considering that it may have had faults. We defined reality in certain ways and ignored critics to the models. We strongly, and mistakenly, believed markets were the whole answer.
I think that as economists and policymakers, we should remember that in The Wealth of Nations, Adam Smith was drawing conclusions from not just the methodology, but also the ethics and psychology he explored in The Theory of Moral Sentiments. We may need to enrich our models to ensure that the outcomes respond to people expectations, and help us to recover the most important ingredient in our societies, which is trust.
French daily Le Figaro recently included Gabriela Ramos in a feature on “The New Untouchables”, four women leading the fight against corruption and for democracy (in French)
Agent-based models to help economics do a better job
Richard Bookstaber, University of California
Economics has not done a very good job of dealing with crises. I think this is because there are four characteristics of human experience that manifest themselves in crises and that cannot be addressed well by the methods of traditional economics.
The first of these is computational irreducibility. You may be able to reduce the behaviour of a simple system to a mathematical description that provides a shortcut to predicting its future behaviour, the way a map shows that following a road gets you to a town without having to physically travel the road first. Unfortunately, for many systems, as Stephen Wolfram argues, you only know what is going to happen by faithfully reproducing the path the system takes to its end point, through simulation and observation, with no chance of getting to the final state before the system itself. It’s a bit like the map Borges describes in On Rigor in Science, where “the Map of the Empire had the size of the Empire itself and coincided with it point by point”. Not being able to reduce the economy to a computation means you can’t predict it using analytical methods, but economics requires that you can.
The second characteristic property is emergence. Emergent phenomena occur when the overall effect of individuals’ actions is qualitatively different from what each of the individuals are doing. You cannot anticipate the outcome for the whole system on the basis of the actions of its individual members because the large system will show properties its individual members do not have. For example, some people pushing others in a crowd may lead to nothing or it may lead to a stampede with people getting crushed, despite nobody wanting this or acting intentionally to produce it. Likewise no one decides to precipitate a financial crisis, and indeed at the level of the individual firms, decisions generally are made to take prudent action to avoid the costly effects of a crisis. But what is locally stable can become globally unstable.
The name for the third characteristic, non-ergodicity, comes from the German physicist Ludwig Boltzmann who defined as “ergodic” a concept in statistical mechanics whereby a single trajectory, continued long enough at constant energy, would be representative of an isolated system as a whole, from the Greek ergon energy, and odos path. The mechanical processes that drive of our physical world are ergodic, as are many biological processes. We can predict how a ball will move when struck without knowing how it got into its present position – past doesn’t matter. But the past matters in social processes and you cannot simply extrapolate it to know the future. The dynamics of a financial crisis are not reflected in the pre-crisis period for instance because financial markets are constantly innovating, so the future may look nothing like the past.
Radical uncertainty completes our quartet. It describes surprises—outcomes or events that are unanticipated, that cannot be put into a probability distribution because they are outside our list of things that might occur. Electric power, the atomic bomb, or the internet are examples from the past, and of course by definition we don’t know what the future will be. As Keynes put it, “There is no scientific basis to form any calculable probability whatever. We simply do not know.” Economists also talk about “Knightian uncertainty”, after Frank Knight, who distinguished between risk, for example gambling in a casino where we don’t know the outcome but can calculate the odds; and what he called “true uncertainty” where we can’t know everything that would be needed to calculate the odds. This in fact is the human condition. We don’t know where we are going, and we don’t know who we will be when we get there. The reality of humanity means that a mechanistic approach to economics will fail.
So is there any hope of understanding what’s happening in our irreducible, emergent, non-ergodic, radically uncertain economy? Yes, if we use methods that are more robust, that are not embedded in the standard rational expectations, optimisation mode of economics. To deal with crises, we need methods that deal with computational irreducibility; recognise emergence; allow for the fact that not even the present is reflected in the past, never mind the future; and that can deal with radical uncertainty. Agent-based modelling could be a step in the right direction.
Agent-based models (ABM) use a dynamic system of interacting, autonomous agents to allow macroscopic behaviour to emerge from microscopic rules. The models specify rules that dictate how agents will act based on various inputs. Each agent individually assesses its situation and makes decisions on the basis of its rules. Starlings swirling in the sky (a “murmuration”) is a good illustration. The birds appear to operate as a system, yet the flight is based on the decisions of the individual birds. Building a macro, top-down model will miss the reality of the situation, because at the macro level the movements of the flock are complex, non-linear, yet are not based on any system-wide programme. But you can model the murmuration based on simple rules as to how a bird reacts to the distance, speed and direction of the other birds, and heads for the perceived centre of the flock in its immediate neighbourhood.
Click to see ABM in motion. Original file on Reddit
Likewise, the agent-based approach recognises that individuals interact and in interacting change the environment, leading to the next course of interaction. It operates without the fiction of a representative consumer or investor who is as unerringly right as a mathematical model can dream. It allows for construction of a narrative—unique to the particular circumstances in the real world—in which the system may jump the tracks and careen down the mountainside. This narrative gives us a shot at pulling the system back safely.
In short, agent-based economics arrives ready to face the real world, the world that is amplified and distorted during times of crisis. This is a new paradigm rooted in pragmatism and in the complexities of being human.
Richard Bookstaber video contribution, OECD New Approaches to Economic Challenges (NAEC)
Richard Bookstaber will be giving a conference within the framework of the OECD NAEC initiative in Paris in June 2017. His latest book, discussing the ideas outlined above, has just been published by Princeton University Press: The End of Theory: Financial Crises, the Failure of Economics, and the Sweep of Human Interaction
The OECD organised a Workshop on Complexity and Policy, 29-30 September 2016, at OECD HQ, Paris, along with the European Commission and INET. Watch the webcast: 29/09 morning; 29/09 afternoon; 30/09 morning
Andy Haldane, Chief Economist and Executive Director, Monetary Analysis & Statistics, Bank of England
It would be easy to become very depressed at the state of economics in the current environment. Many experts, including economics experts, are simply being ignored. But the economic challenges facing us could not be greater: slowing growth, slowing productivity, the retreat of trade, the retreat of globalisation, high and rising levels of inequality. These are deep and diverse problems facing our societies and we will need deep and diverse frameworks to help understand them and to set policy in response to them. In the pre-crisis environment when things were relatively stable and stationary, our existing frameworks in macroeconomics did a pretty good job of making sense of things.
But the world these days is characterised by features such as discontinuities, tipping points, multiple equilibria, and radical uncertainty. So if we are to make economics interesting and the response to the challenges adequate, we need new frameworks that can capture the complexities of modern societies.
We are seeing increased interest in using complexity theory to make sense of the dynamics of economic and financial systems. For example, epidemiological models have been used to understand and calibrate regulatory capital standards for the largest, most interconnected banks, the so-called “super-spreaders”. Less attention has been placed on using complexity theory to understand the overall architecture of public policy – how the various pieces of the policy jigsaw fit together as a whole in relation to modern economic and financial systems. These systems can be characterised as a complex, adaptive “system of systems”, a nested set of sub-systems, each one itself a complex web. The architecture of a complex system of systems means that policies with varying degrees of magnification are necessary to understand and to moderate fluctuations. It also means that taking account of interactions between these layers is important when gauging risk.
Although there is no generally-accepted definition of complexity, that proposed by Herbert Simon in The Architecture of Complexity – “one made up of a large number of parts that interact in a non-simple way” – captures well its everyday essence. The whole behaves very differently than the sum of its parts. The properties of complex systems typically give rise to irregular, and often highly non-normal, statistical distributions for these systems over time. This manifests itself as much fatter tails than a normal distribution would suggest. In other words, system-wide interactions and feedbacks generate a much higher probability of catastrophic events than Gaussian distributions would imply.
For evolutionary reasons of survival of the fittest, Simon posited that “decomposable” networks were more resilient and hence more likely to proliferate. By decomposable networks, he meant organisational structures which could be partitioned such that the resilience of the system as a whole was not reliant on any one sub-element. This may be a reasonable long-run description of some real-world complex systems, but less suitable as a description of the evolution of socio-economic systems. The efficiency of many of today’s networks relies on their hyper-connectivity. There are, in the language of economics, significantly increasing returns to scale and scope in a network industry. Think of the benefits of global supply chains and global interbank networks for trade and financial risk-sharing. This provides a powerful secular incentive for non-decomposable socio-economic systems.
Moreover, if these hyper-connected networks do face systemic threat, they are often able to adapt in ways which avoid extinction. For example, the risk of social, economic or financial disorder will typically lead to an adaptation of policies to prevent systemic collapse. These adaptive policy responses may preserve otherwise-fragile socio-economic topologies. They may even further encourage the growth of connectivity and complexity of these networks. Policies to support “super-spreader” banks in a crisis for instance may encourage them to become larger and more complex. The combination of network economies and policy responses to failure means socio-economic systems may be less Darwinian, and hence decomposable, than natural and biological systems.
Andy Haldane addresses OECD New Approaches to Economic Challenges (NAEC) Roundtable
What public policy implications follow from this complex system of systems perspective? First, it underscores the importance of accurate data and timely mapping of each layer in the system. This is especially important when these layers are themselves complex. Granular data is needed to capture the interactions within and between these complex sub-systems.
Second, modelling of each of these layers, and their interaction with other layers, is likely to be important, both for understanding system risks and dynamics and for calibrating potential policy responses to them.
Third, in controlling these risks, something akin to the Tinbergen Rule is likely to apply: there is likely to be a need for at least as many policy instruments as there are complex sub-components of a system of systems if risk is to be monitored and managed effectively. Put differently, an under-identified complex system of systems is likely to result in a loss of control, both system-wide and for each of the layers.
In the meantime, there is a crisis in economics. For some, it is a threat. For others it is an opportunity to make a great leap forward, as Keynes did in the 1930s. But seizing this opportunity requires first a re-examination of the contours of economics and an exploration of some new pathways. Second, it is important to look at economic systems through a cross-disciplinary lens. Drawing on insights from a range of disciplines, natural as well as social sciences, can provide a different perspective on individual behaviour and system-wide dynamics.
The NAEC initiative does so, and the OECD’s willingness to consider a complexity approach puts the Organisation at the forefront of bringing economic analysis and policy-making into the 21st century.
This article draws on contributions to the OECD NAEC Roundtable on 14 December 2016; The GLS Shackle Biennial Memorial Lecture on 10 November 2016; and “On microscopes and telescopes”, at the Lorentz centre, Leiden, workshop on socio-economic complexity on 27 March 2015.
Paul B. Hartzog, Futurist
This article looks at three crucial insights for the future of economics: Complex adaptive systems; how technologies of cooperation enable commons-based peer-to-peer networks; and why we need complex adaptive systems to understand new economies
COMPLEX ADAPTIVE SYSTEMS
The Edge of Chaos
Complex adaptive systems has enjoyed considerable attention in recent decades. Chaos theory reveals that out of turbulence and nonlinear dynamics, complex systems emerge: order from chaos.
We learned that complex systems are poised on the “edge of chaos” and generate “order for free” (Stuart Kauffman). They are composed of many parts connected into a flexible network. As matter and energy flow through, they spontaneously self-organize into increasingly complex structures. These systems, continuously in flux, operate “far from equilibrium” (Ilya Prigogine). Beyond critical thresholds, differences in degree become differences in kind. “More is different.” (Phil Anderson)
Complexity science reveals the difference between prediction and attraction. We can know that a marble in a bowl will reach the bottom even though we cannot predict its exact path because of sensitivity to initial conditions. Deterministic chaos means path dependence, where future states are highly influenced by small changes in previous states. A typical economic example is the lock-in of the now-standard “QWERTY” keyboard.
We see network effects: adding another node to a network increases the value of all other nodes exponentially, because many new connections are possible, economically “increasing returns to scale” (Brian Arthur). Reed’s Law goes even farther, because new groups can be formed, exhibiting a much greater geometric growth. We know about “small-world,” or “scale-free,” networks, so called because there is no statistic at any scale that is representative of the network as a whole, e.g. no bell-curve average, but instead a “long tail,” mathematically a logarithmic “power law.” Some networks are robust to random failures but vulnerable to selective damage, i.e. network attacks that target nodes with a higher centrality. Furthermore, “centrality” means different things inside different network topologies. Network structure affects the frequency and magnitude of cascades. Like avalanches in sand piles, power laws create “self-organized criticality” (Per Bak).
Complex systems constitute “fitness landscapes,” exhibit cycles of growth and decline, are punctuated by explosions of diversity and periods of stasis, and show waves of ebb and flow, seen in traffic patterns. On fitness landscapes, algorithms that pursue merely maximization, without the ability to observe remote information from the landscape, freeze in local optima. Without system diversity, there is no improvement. Swarms escape because they not only read information from the landscape but also write to it, creating shared information environments.
Landscapes and occupants impart selection pressures on each other. Good employees and good jobs both outperform bad ones. Agents and strategies evolve. Adaptation can become maladaptation when selection pressures change.
Dynamics and Time
When we study the spread of disease through a forest we see a slow progression of infected trees. However, when we study the spread of fire, we see the same pattern enacted much faster.
Complex systems and their dynamics are not new. What is new is that human systems have accelerated to the point where political, economic, and social changes now occur rapidly enough to appear within the threshold of human perception. We change from slow social movement to an era of “smart mobs.” Consequently, while it may be true that we did not need the tools of complex systems in the past, because economic change was slow and did not require a dynamical viewpoint, the current speed of economic change demands this new lens.
THE EMERGENCE OF COMMONS-BASED PEER-TO-PEER NETWORKS
A crucial global economic phenomenon is the rise of commons-based peer-to-peer networks. “Technologies of cooperation” (Howard Rheingold) enable people to self-organize in productive ways. Open-source software was one first clue to powerful new ways of organizing labor and capital. “Commons-based peer-production” is radically cost-effective (Yochai Benkler). By “governing the commons” (Elinor Ostrom), shared resources managed by communities with polycentric horizontal rules, without reliance on either the state or the market, escape the “tragedy of the commons.” Our thinking about production, property, and even the state, must evolve to reflect the growing participatory economy of global stewardship and collectively-driven “platform cooperatives” (Michel Bauwens). New commons include food, energy, “making,” health, education, news, and even currency.
The rise of 3D printing and the Internet of Things combined with participatory practices yields new forms of value production, paralleling new forms of value accounting and exchange. We witness a “Cambrian explosion” of new currency species, like BitCoin, and innovative trust technologies to support them: the blockchain and distributed ledgers. Just as 20th century electrical infrastructure remained fragmented until standards enabled a connected network (Thomas Hughes), new infrastructure matures when separate solutions merge and the parts reinforce the stability of the whole.
THE FUTURE FATE OF ECONOMICS
Economics as a discipline can only remain relevant as long as it can provide deep engagement with contemporary reality. Overly-simplified models and problematic axioms cannot guide us forward. The world is an interwoven, heterogeneous, adaptive “panarchy.”
Harnessing complexity requires understanding the frequency, intensity, and “sync” of global connectivity. Analyzing many futures demands better tools. To analyze “big data,” first we need data. Complexity science utilizes multi-agent simulations to investigate many outcomes, sweep parameters, and identify thresholds, attractors, and system dynamics. Complexity methods provide unique metrics and representations, animated visuals rather than static graphs.
This is not just big data; it’s dynamic data. With distributed systems, it becomes peer-to-peer data: shared infrastructure. Just as ants leave trails for others, shared infrastructure bolsters interoperability through a knowledge commons. Restricting connectivity and innovation, e.g. with intellectual property rights, carries extreme costs now. Fitness impedes uncooperative agents and strategies. Fortunately new commons have novel “copyleft” licenses already, promoting fairness and equity.
Complexity science shows us not only what to do, but also how to do it: build shared infrastructure, improve information flow, enable rapid innovation, encourage participation, support diversity and citizen empowerment.
December 8, 2016: Closing date for the crowdfunding campaign for the John Maynard Keynes writings project
Professor Rod O’Donnell, University of Technology Sydney, Australia
I thank, from the bottom of my heart, all those who have backed the campaign, with donations ranging from USD5 to USD1,000. Almost everyone has said complimentary things about the proposed edition (‘great idea’, ‘wonderful project’, ‘best of luck’ etc), but far fewer have followed up with contributions.
The bottom line is this. Funds are essential if the edition is to be realised. The people undertaking the large and necessary tasks of word-processing documents and background research need to be paid. All the money raised by crowdfunding will be devoted to document preparation, not to travel for document collection.
It is now time for the many supporters of the project to get serious about whether they want also to be backers and so help make the edition a reality. Time is running out − only about 3 weeks remain before the crowdfunding campaign ends. Recent events have made understanding Keynes’s economics, politics and philosophy even more important.
If you would like to provide material support, please go, before December 8, to
This link also gives more information about the project, the campaign and the editor.
Remember the overall aim: to benefit the world by completing the publication of all of Keynes’s writings of academic significance, only about one third of which are presently available.
THANK YOU IN ADVANCE FOR YOUR BACKING OF THE JMK WRITINGS PROJECT.
Professor Rod O’Donnell, University of Technology Sydney, Australia.
Contact: [email protected]
Professor Rod O’Donnell, University of Technology Sydney, Australia
Alongside Smith and Marx, Keynes is one of the triumvirate of economists on whom more ink has been expended than on any others. And, as the most recent of the three, he speaks more directly to our times and our troubles. His multi-sidedness also makes him a fascinating figure for non-economists. But more expended ink does not more knowledge guarantee, especially if the information sources being used are seriously incomplete. It is the aim of my JMK Writings Project to remedy this situation.
A grave misapprehension pervades the discussion of Keynes’s many contributions. It is widely believed that the Royal Economic Society edition, The Collected Writings of John Maynard Keynes, in its 30 volumes, contains everything that Keynes wrote that is important in understanding his thought and activities.
This, however, is far from the truth. Although that edition was enormously valuable in promoting Keynes scholarship, it only made accessible a relatively small proportion of the total amount of his unpublished writings as a result of its narrow terms of reference, limited budget and largely single-archive focus. Only about 40% of the edition (11-12 volumes) contained new material, the rest being reproductions of already published output. The terms of reference, “Keynes as an economist and public figure”, for example, excluded vast domains in his writings, including all his unpublished philosophical output and most of his huge private correspondences. And the focus on only one primary archive, that at King’s College Cambridge (albeit supplemented by some selections from the UK National Archives) meant that vast swathes of documents held elsewhere in the UK and other countries were excluded.
Discoveries by a small band of hardy Keynes archive explorers over recent decades have revealed that huge amounts of Keynes’s academically significant writings remain unpublished. In the UK, large portions of even the Keynes Papers at King’s College Cambridge languish unpublished, not to mention the extensive holdings of other archives, both large (the National Archives and the British Library), and small (various university archives). Outside the UK, at least four countries have important holdings. The US has many medium to small collections, followed by Japan with a smaller number of key holdings resulting from its purchases of Harrod’s Papers. (Why portions of Keynes’s writings finished up in Harrod’s personal papers is a story for another day, but their existence remained entirely unknown until the latter’s international auction in the early 1990s). Australia has five archival holdings, Canada has at least one, and there may be one or two holdings in France and Germany. My current estimate is that approximately 60 archives world-wide have valuable unpublished collections.
The object of my JMK Writings Project is to make publicly accessible the treasure trove of information presently tucked away in his scattered unpublished writings. The Further Collected Writings of John Maynard Keynes, as the supplementary edition will be called, is estimated to run to around 20 to 25 volumes, although the number cannot be accurately predicted. No global catalogue of his writings has been compiled, so that nobody in the world knows their full extent.
Why crowdfunding? Sadly, official sources of funding for scholarly editorial research concerning the writings of a brilliant mind with non-orthodox views, a more discursive style of theorising, and much practical policy wisdom, have dried up due to the heavy influences of orthodox economic thinking, mathematical formalisation and econometric technique. To obtain the resources needed for the project, I have turned to the less conventional avenue of crowdfunding. The campaign launched on 11 October 2016 on the Indiegogo website, and may be located using the URL: https://www.indiegogo.com/projects/jmk-writings-project-stage-1–2#/
Much more information about the edition, its structure and planned expenditure may be gained via the above link. Donations of any size are welcome, but it may be of interest for readers to know that for each USD100,000 raised (in the aggregate or by single donation), it is planned, with publisher co-operation, to provide a university in a developing country with free online access to the edition.
Organised largely on chronological lines, the supplementary edition starts with Eton and early Cambridge before proceeding through the succeeding stages of Keynes’s crowded life. The volumes will be produced in batches of roughly 3 to 6, with future crowdfunding campaigns being run as required for the later batches. The present campaign is for the first batch, these covering Keynes’s Eton years (both early and late) and his initial Cambridge years. It may surprise readers to learn − as it surprised me, being the first thorough investigator of Eton’s records concerning Keynes – that his Eton years contain much unknown exciting and insightful material. The conventional view of Eton, as but a stepping stone to Cambridge where his real intellectual foundations were laid, will need to be completely revised.
Naturally, preparing the edition is a huge task. To expedite execution, I am seeking to build teams of scholars in different countries interested in taking responsibilities for particular volumes, or parts thereof, in a voluntary capacity. Please contact me via [email protected] if you have questions about participating in this way.
Keynes’s writings are also relevant to philosophers, political scientists, historians (economic and social), and everyone seeking to improve our struggling economies, politics and societies. This is the time to give the world access to the full range of wisdom in all his writings. Motivated and dedicated people are available now, but if we postpone these labours into the future, the chances are that the bounty will never arrive, and that would be a great loss to the world’s knowledge.
On 24 October, Georgios Krimpas, Greek Ambassador to the OECD, will be giving a talk on “Keynes: The General Theory in Three Acts – Employment, Interest and Money”. You can watch the webcast here