Dr Brian Levyis a Public Sector Governance Advisor at the World Bank, andused to head up the unit responsible implementing the Bank’s governance and anti-corruption strategy.
In this guest post, cross-posted from here, he explores the relevance of complexity theory insights for South Africa. A fascinating read.
The edge of chaos is the balance point where the components of a system never quite lock into place, and yet never quite dissolve into turbulence, either…The edge of chaos is the constantly shifting battle zone between stagnation and anarchy, the one place where a complex system can be spontaneous, adaptive and alive…”
M. Mitchell Waldrop, Complexity.
We human beings do not like uncertainty. We seek to understand what events portend, taking comfort in coming up with an answer. So whenever something new in South Africa makes headlines – and that’s been happening quite often recently, the news not always happy – people ask me, “What do you think? Is the political settlement falling apart?”. And always, the expectation is for a definitive answer, one way or the other.
Yet sometimes there is more wisdom, and more comfort to be taken, in acknowledging a more humbling truth – that which of many alternative futures (including ones we cannot imagine) will come to pass is unknowable, is a product of decisions and actions that have not yet been made. This understanding of change as something ‘emergent’, evolving, which can unfold in far-reaching yet ex ante unpredictable directions, is the key insight of ‘complexity theory’ – an insight which can offer a useful dose of humility to governance prognosticators.
In a previous post, I described South Africa’s abiding tension between democracy and inequality. As that post suggested, one of the results of that tension could be a rise of patronage, personalized decision-making as to how to share the ‘spoils’ of power. Indeed, the strains on the country’s constitutional democracy are visible in the drumbeat of daily headlines, as I found when I recently spent some time in the country. Consider the following:
Over the past year, the country’s estimable Public Protector, Thuli Madonsela, investigated and made public compelling evidence of corruption on the part of two sitting cabinet ministers, and the chief of police. For many months, President Zuma did nothing – until October 24th 2011, when he unexpectedly fired the cabinet ministers, suspended the police chief, and announced the appointment of a judicial commission to re-investigate long festering allegations of corruption (including against himself) in a weapons procurement deal.
Then there’s the populist demagoguery of the leader of the ruling African National Congress’s Youth League, Julius Malema, whose political star, and polarizing influence on South Africa’s political discourse, seemed to be rising – until a disciplinary committee of the ANC announced on November 10th, 2011 that it had found Malema guilty of bringing the ANC into disrepute, and suspended him from the party for five years.
There’s the China connection. Across Africa, a context is raging between China and Africa’s erstwhile Western colonial (and post-colonial) hegemonies – for hearts, minds, natural resources, and business more generally. With its sophisticated institutions, and proud transition to constitutional democracy, it might be thought that South Africa would be unambiguously in the Western camp. So against that backdrop, the failure to grant the global human rights icon, the Dalai Lama, a visa in time to attend the October 2011 80th birthday celebration of his friend, Archbishop Desmond Tutu, is startling – and can best be explained by a desire to curry favor with the Chinese.
Finally, there’s the on-again, off-again – but then on again – Protection of Information Bill which (after numerous delays, and promises of consultation before finalization) was rushed through South Africa’s parliament on 22nd November 2011. Passage of the bill was seen as a catastrophe by many in South Africa’s civil rights community. Indeed, it signals a startling turn away from a post-apartheid commitment to openness. But no less an observer than The Economist, noting that the bill had been ‘vastly improved’ over earlier versions, suggested that some of the doomsday criticism ‘may be over the top’. And, in light of the ANC’s hitherto ironclad hold on the loyalties of its core constituencies, it is surely no small matter that the Congress of South African Trade Unions (a stalwart part of the ANC alliance) has threatened to take the bill to the Constitutional Court if it is not amended to incorporate a ‘public interest’ exception for whistleblowers.
In the face of all of these cross-currents, any claims of certainty as to where this interplay of forces will lead is surely illusory. Each of them could turn out to be a salutary example of checks and balances in action – of how democratic institutions can keep a country on track, even in the face of pressures to the contrary. But they could also be portents of a future that will become increasingly challenging for the country’s constitutional order.
But in South Africa’s case, and surely elsewhere, too. perhaps the lack of certainty is a source of comfort. Knowing that the future is not preordained can free us from endless preoccupation with what is inherently unknowable, enabling us instead to direct energy towards action, in service of a hopeful future that we can, perhaps, yet help to create.
A continuing theme on this blog has been the issue of leadership. Many reports and studies call for it, reforms are seen as impossible without it, critical challenges will not be met without it, and we are all ready to point out the lack of it (in others, at least).
Despite the fact that leadership is one of the most researched topics in management literature (or perhaps becauseof this fact) , our understanding of leadership remains vague and ambiguous.
A blog on HBR by Duncan Watts of Yahoo’s Human Social Dynamics research group eloquently explores the concept and ideas with reference to recent social movements.
The Occupy Wall Street movement has both perplexed and frustrated observers and analysts by its persistent refusal to nominate an identifiable leadership who can in turn articulate a coherent agenda. What is the point, these critics wonder, of a movement that can’t figure out where it’s trying to go, and how can it get there without anyone to lead it?
It’s a reasonable question, but it says at least as much about what we want from our social movements as it does about the way movements actually succeed.
Typically, the way we think of social change is some variant of the “great man” theory of history: that remarkable events are driven by correspondingly remarkable individuals whose vision and leadership inspire and coordinate the actions of the many. Sometimes these individuals occupy traditional roles of leadership, like presidents, CEOs, or generals, while at other times they emerge from the rank and file; but regardless of where they come from, their presence is necessary for real social change to begin. As Margaret Meade is supposed to have said: “Never doubt that a small group of thoughtful, committed citizens can change the world. Indeed, it is the only thing that ever has.”
It’s an inspiring idea, but over 100 years ago in his early classic of social psychology, “The Crowd,” the French social critic Gustave LeBon, argued that the role of the leader was more subtle and indirect. According to LeBon, it was the crowd, not the princes and generals, that had become the driving force of social change. Leaders still mattered, but it wasn’t because they themselves put their shoulders to the wheel of history; rather it was because they were quick to recognize the forces at work and adept at placing themselves in the forefront.
Even before LeBon, no less an observer of history than Tolstoy presented an even more jaundiced view of the great man theory. In a celebrated essay on Tolstoy’s War and Peace, the philosopher Isaiah Berlin summed up Tolstoy’s central insight this way: “the higher the soldiers or statesmen are in the pyramid of authority, the farther they must be from its base, which consists of those ordinary men and women whose lives are the actual stuff of history; and, consequently, the smaller the effect of the words and acts of such remote personages, despite all their theoretical authority, upon that history.” According to Tolstoy, in other words, the accounts of historians are borderline fabrications, glossing over the vast majority of what actually happens in favor of a convenient storyline focused on the skill and leadership of the great generals.
Thinkers like Le Bon and Tolstoy and Berlin therefore lead us to a radically alternative hypothesis of social change: that successful movements succeed for reasons other than the presence of a great leader, who is as much a consequence of the movement’s success as its cause. Explanations of historically important events that focus on the actions of a special few therefore misunderstand their true causes, which are invariably complex and often depend on the actions of a great many individuals whose names are lost to history.
Interestingly, in the natural world we don’t find this sort of explanation controversial. When we hear that a raging forest fire has consumed millions of acres of California forest, we don’t assume that there was anything special about the initial spark. Quite to the contrary, we understand that in context of the large-scale environmental conditions — prolonged drought, a buildup of flammable undergrowth, strong winds, rugged terrain, and on so — that truly drive fires, the nature of the spark itself is close to irrelevant.
Yet when it comes to the social equivalent of the forest fire, we do in effect insist that there must have been something special about the spark that started it. Because our experience tells us that leadership matters in small groups such as Army platoons or start-up companies, we assume that it matters in the same way for the very largest groups as well. Thus when we witness some successful movement or organization, it seems obvious to us that whoever the leader is, his or her particular combination of personality, vision, and leadership style must have supplied the critical X factor, where the larger and more successful the movement, the more important the leader will appear.
By refusing to name a leader, Occupy Wall Street presents a challenge to this view. With no one figure to credit or blame, with no face to put on a sprawling inchoate movement, and with no hierarchy of power, we simply don’t know how to process what “it” is, and therefore how to think about it. And because this absence of a familiar personality-centric narrative makes us uncomfortable, we are tempted to reject the whole thing as somehow not real. Or instead, we insist that in order to be taken seriously, the movement must first change to reflect what we expect from serious organizations — namely a charismatic leader to whom we can attribute everything.
In the case of Occupy Wall Street, we will probably get our wish, for two reasons. First, if OWS grows large enough to deliver any lasting social change, some hierarchy will become necessary in order to coordinate its increasingly diverse activities; and a hierarchy by nature requires a leader. And second, precisely because the outside world wants a leader — to negotiate with, to hold responsible, and ultimately to lionize — the temptation to be that person will eventually prove irresistible.
Leaders, in other words, are necessary, but not because they are the source of social change. Rather their real function is to occupy the role that allows the rest of us to make sense of what is happening — just as Tolstoy suspected. For better and worse, telling stories is how we make sense of the world, and it’s hard to tell a story without focal actors around which to center the action.
But as we witness a succession of popular movements, from the Arab Spring to Occupy Wall Street, we can at least pause to appreciate the real story, which is the remarkable phenomenon of a great many ordinary individuals coming together to change the world.
The challenges of achieving global public policy consensus aside, new research is highlighting a range of other pressing concerns that need urgent attention.
Last week saw the launch of the summary of the IPCC special report on ‘Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation’ (SREX). This was the result of a two-and-a-half year long global collaboration between 220 scientists (full disclosure: I was one of the 220 & wrote sections of chapter 6 on managing climate risks at a national level).
One of the key messages of the IPCC report is that existing risk management and adaptation measures need to be improved dramatically. Many countries were found to be poorly adapted to current extremes and risks – let alone those projected for the future.
As recent Stockholm Resilience Centre research shows, this is more than just a technical issue. In fact, the study suggests the time is ripe for a serious rethink of the way resilience and adaptation measures are being designed and implemented.
Resilience is popular. Over the last year, I have being doing an increasing amount work on this ‘big new idea’ in international affairs – for DFID, ODI and others.
While it’s clear that there is a lot of value in this area for development and humanitarian efforts, there are some conceptual and operational challenges that need to be addressed. One widespread issue that I’ve noticed is that while aid agencies are embracing resilience, they are also tending to put the underlying theoretical framework of complex systems to one side as ‘too complicated’.
The study from experts at the Stockholm Resilience Centre shows that such conceptual simplifications of resilience can have considerable downsides – in the extreme, they can lead to interventions that actually diminish resilience.
There are now hundreds (if not thousands) of major public sector initiatives that have been developed in response to climate change, in high, middle and low income countries alike. Adaptation strategies include adjusting economic activities, changing land and energy use practices, and reforms to the design and implementation of infrastructure.
The study authors evaluated nine adaptation policy responses to assess how much they were affecting the resilience of various social-ecological systems. The findings were sobering: ‘Out of the nine initiatives analysed, only three had elements that could enhance resilience as much as reducing it. The other six had effects that predominantly reduced the resilience of a system.’
The reason? Many of the policy approaches to climate risks focused too much on short-term benefits and sought simple technological fixes to problems that were more complex. Such responses, designed with a focus on one single risk factor, can inadvertently undermine the capacity to address other stresses. As the authors put it:
There is growing evidence that current policy approaches… fail to significantly address multiple and interacting factors which affect system resilience and the needs of vulnerable populations.
Such over-simplistic efforts ‘create bizarre distortions in public policy’ precisely because climate vulnerabilities are created through multiple stresses, and not single factors. The problems went beyond how risks were defined – issues of governance, feedback and learning were also identified as critical. As the authors put it:
[In those] situations in which system stresses were defined as narrow, technical problems with short-term horizons… governance structures were top-down, did little to link actors at different scales, masked system feedbacks, and did not provide incentive or structure to promote learning…. In contrast, in the two examples where the issue was framed in a broader manner, policy implementation tended to enhance characteristics that supported the ability to manage resilience, including flexibility and learning.
Is there any explanation for this widespread focus on single risk factors? There are numerous reasons cited in the study. These include:
a desire for readily observable metrics
existing political structures and incentives
entrenched institutional cultures, and
long histories of dealing with social and ecological problems in narrow and limited ways
All these factors have been identified as systemic problems in international aid agencies, both on this blog and elsewhere. Indeed, some of the most troubling manifestations of the push for simplification were to be found in developing country case studies. For example, fisheries management in Uganda and drought responses in Kenya both highlighted the importance of local sources of resilience based knowledge of local ecosystems and social networks. But in both cases, the local sources of potential resilience were diminished by actors and forces operating at wider level.
Given this important new evidence, we are left with what seems like an obvious choice. To paraphrase the study authors, do we want efficient and effective adaptation measures, narrowly and technologically defined? Or do we want strategies that are more open-ended and innovative and seek to build resilience by understanding and strengthening local capacities?
The answer may seem obvious, but as global climate policy debates have repeatedly highlighted, in this realm the obvious choices are often the hardest agree upon. Politics and special interests clearly play a major role, and can all too often inhibit the space for evidence-based considerations.
One would hope that the adaptation issue is less entrenched than the battle that continues to be being waged around mitigation. At the very least, policy makers and practitioners alike need to become more aware of, and work with the key finding of the study – namely that:
dealing with specific risks without full accounting of the nature of system resilience leads to responses that can potentially undermine long–term resilience…”
The eurozone, like the rest of the world economy, is a complex networked system. That gives it properties economists rarely consider but which could help us understand the current crisis. This New Scientist ‘Science in Society’ Briefing examines the issues.
What is a complex network?
Complex networks have many interconnected components which influence each other’s behaviour. These changes then feed back on each other. A famous example is the numbers of predators and prey in a given environment, which vary in a complex interdependent way. The eurozone – the 17 countries that share a common currency, the euro – is similarly interdependent, with similar feedback mechanisms.
All complex networks are governed by a balance between negative feedback, such as interest rates, which is stabilising, and positive feedback, such as the self-reinforcing erosion of trust in markets, which is destabilising, says physicist Len Fisher at the University of Bristol, author of Crashes, Crises and Calamities: How we can use science to read the early-warning signs.
How does that help us understand economic crises?
In certain circumstances, one type of feedback can end up dominating the system, causing it to change so dramatically that it flips to another state. Examples include the way animal populations can suddenly collapse or the way economies can slip into recession.
These tipping points tend to be highly unpredictable. Even so, Fisher says computer models of the system can still show how the system can change. Yet leading economics journals, he says, do not accept computer-modelling studies. “Mainstream economists have not considered these non-linear effects,” agrees Oonsie Biggs of Stockholm University’s Stockholm Resilience Center in Sweden.
Can we understand complex systems well enough to control them?
Maybe. The diversity of a network’s components and the density and strength of its connections – called its connectivity – affect the system’s resilience, or resistance to change. More connections make a system more resilient: if one component fails others can fill in. But only up to a point. Go past a certain threshold and more connectivity makes the system less resilient because a single failure can cascade to every other component.
The trick is to get the balance right. “Cascades of failure may be controlled by changing the nature and strength of the links between various parts of the networks,” says Fisher. Much current research in complex systems focuses on assessing connectivity correctly to enable that. Other work aims to detect behaviour that indicates an imminent collapse.
So turning 17 separate currencies into one eurozone was a cascading failure waiting to happen?
Yes. That is why Greek debt is a crisis, even though Greece accounts for only 2.5 per cent of the eurozone’s GDP. News of its debts caused the trust that markets placed in Greek government bonds to plummet. Its creditors are mainly in the eurozone, so a Greek default is causing markets to lose confidence in other members, such as Italy – which is too big to bail out.
Could the crisis have been avoided?
Complexity theory shows what went wrong. Yaneer Bar Yam of the New England Complex Systems Institute in Cambridge, Massachusetts, says his still-unpublished studies show that investors profited by driving down the value of Greek government bonds, triggering the crisis. If instead of national bonds issued by sometimes weak economies, the eurozone had one common bond backed by powerhouses such as Germany, such an attack could not have happened.
Germany rejects eurobonds. But, says Bar Yam, complex systems such as multicellular organisms show that “if you are going to accept common risk, you have to invest in defences that extend to the weakest member”. Either that or make sure an attack on a weak member cannot spread, a technique that ant colonies have perfected: the death of a single ant has little effect on the colony as a whole. “Biology has solved this problem several ways,” says Bar Yam.
If connectivity is a risk, why create the euro?
Connectivity is also profitable as it makes economic production much more efficient. And it can adapt to problems: connectivity allows other eurozone countries to help Greece, and to build better common defences.
Trade-offs between efficiency and resilience may mean we need to develop ways to make systems more stable, such as pruning connectivity or paying for defence measures. “We now have the quantitative, analytical tools to do that,” says Bar Yam. Such models may also show when short-term costs that reduce a system’s efficiency may be warranted because of the long-term benefits of increased system resilience.
Some connectivity problems could be hard to prune, though. Biggs says close coupling between major global hubs, such as the eurozone and the US, is a big source of instability that which may threaten strong contributors in future, like France and Germany.
Why don’t economists know this?
They are starting to. Some economic theorists have drawn parallels between financial networks where bank failures are prevented, and forests where small fires are always put out. Such forests accumulate deadwood fuel and lose patchiness, increasing connectivity. When a fire eventually breaks out, it becomes huge. That’s why forest managers now encourage regular, small burns. Similarly, banking networks may need low-level failures to prune connectivity and risk.
Systems-based thinking has even reached the Bank for International Settlements in Basel, Switzerland, which sets global rules for the capital a bank must hold to back loans. It announced this month that the risks posed by banks depend on their “size, interconnectedness, complexity and global scope”. So from 2016, “global systemically important banks” – initially 29 of them – will be required to keep more capital on hand per dollar loaned than less vital banks. This is partly to “discourage banks from becoming even more systemically important” – in other worlds, too big to fail.
This recognition of the importance of complexity has been largely confined to banking, however. The eurozone is a network of governments. It is not clear how eagerly they will adopt a way of thinking that truly puts collective interests first.
Ricardo Hausmann of Harvard and Cesar Hidalgo of MIT (whose work I have blogged about previously here) have just published the deeply impressive Atlas of Economic Complexity. It is built around an innovative, network-based methodology for understanding economies and their potential for growth. It represents perhaps the most systematic and in-depth application of the ideas and methods of complexity research to issues of development to date. Readers can download the Atlas and experiment with a powerful interactive visualiser here.
Following an interview with Cesar Hidalgo last week, this extended post explores the implications of this important new work.
I. What is the premise of the Atlas?
The basic idea underpinning the Atlas of Economic Complexity is straightforward. As Hausmann notes:
The fundamental proposition… is that the wealth of nations is driven by productive knowledge. Individuals are limited in the things they can effectively know and use in production so the only way a society can hold more knowledge is by distributing different chunks of knowledge to different people. To use the knowledge, these chunks need to be re-aggregated by connecting people through organizations and markets. The complex web of products and markets is the other side of the coin of the accumulating productive knowledge. [emphasis added]
The secret to modernity is that we collectively use large volumes of knowledge, while each one of us holds only a few bits of it. Society functions because its members form webs that allow them to specialize and share their knowledge with others.”
At the heart of the Atlas is the attempt to measure the amount of productive knowledge that each country holds by applying network analysis techniques to this complex web.
Much standard development – and economic – thinking doesn’t engage very well with the idea of webs and networks. As Hidalgo told me, such ideas run counter to much standard thinking, which seeks to identify differences between individuals and groups based on their inherent qualities – demographic criteria and suchlike. Experts then puzzle over why, for example, communities with the same criteria, or countries with very similar starting points end up with very different development pathways and social and wealth outcomes. It turns out that in many cases, their relationships and networks prove to be a key differentiating factor. If the data is available, it is possible to develop very precise and rigorous analysis of these differences.
II. How does the Atlas work?
So how does the Atlas make these ideas relevant to development economics? Well, for starters, it acknowledges that accumulating productive knowledge is difficult: “For the most part, it is not available in books or on the Internet. It is embedded in brains and human networks. It is tacit and hard to transmit and acquire. It comes from years of experience more than from years of schooling. Productive knowledge, therefore, cannot be learned easily like a song or a poem. It requires structural changes. Just like learning a language requires changes in the structure of the brain, developing a new industry requires changes in the patterns of interaction inside an organization or society.”
As readers will be well aware, the social accumulation of productive knowledge has not been universal: “The enormous income gaps between rich and poor nations are an expression of the vast differences in productive knowledge amassed by different nations.”
These differences are expressed in the diversity and sophistication of the things that each nation makes. In order to put knowledge into productive use, societies need to reassemble these distributed products through teams, organisations and markets. These issues are explored in detail in the Atlas, through the concept of the ‘product space’. This is a map which captures the products made by different countries in terms of their knowledge requirements. This maps provide a way of understanding how productive knowledge is accumulated.
As Hidalgo said in interview:
Knowledge doesn’t add up like capital. There is a lot of redundancy in knowledge. Some countries may have diverse knowledge but small populations. Product space is an expression of different kinds of knowledge – and its much better than other indicators.
Cesar’s TED talk from August 2010 gives more information about this idea and how it works.
The underlying notion of this analysis is that the complexity of an economy is related to the range of useful knowledge embedded in it:
For a complex society to exist, and to sustain itself, people who know about design, marketing, finance, technology, human resource management, operations and trade law must be able to interact and combine their knowledge to make products. These same products cannot be made in societies that are missing parts of this capability set. Economic complexity, therefore, is expressed in the composition of a country’s productive output and reflects the structures that emerge to hold and combine knowledge… Increased economic complexity is necessary for a society to be able to hold and use a larger amount of productive knowledge, and we can measure it from the mix of products that countries are able to make.”
III: What does it all mean?
So what does this give us in practical terms? As a starter, representing such a huge amount of data – covering 128 countries, 99% of world trade, 97% of the world GDP and 95% of the world population – in visual form is in itself a remarkable feat. As people like Hans Rosling have powerfully demonstrated, innovations in how we visualise data can yield tremendous new insights and ideas.
Here’s an example of a product space diagram, this one for the United States. To learn more about the diagrams and how to interpret them, I would strongly recommend having a play with the visualiser, then scanning the report, then having another play.
Hausmann, Hidalgo and their team have also developed an Index of Economic Complexity to represent their data systematically. This Index tells us about the richness of the product space of a given country, and by extension, is one useful indicator of the potential to grow. It can also be used to compare economic complexity across countries, as shown in this chart showing the ranking of different countries (from 1 to 128, highest is most red).
The authors acknowledge that these ideas are not always easy to grasp, and provide a useful thought-experiment to help readers get their heads around the implications of the Index.
Think of a particular country and consider a random product. Now, ask yourself the following question: If this country cannot make this product, in how many other countries can this product be made? If the answer is many countries, then this country probably does not have a complex economy. On the other hand, if few other countries are able to make a product that this country cannot make, this would suggest that this is a complex economy.
So for example, Japan and Germany are the two countries with the highest levels of economic complexity and if a good cannot be produced there, the list of other potential countries is likely to be very short. Conversely if a product cannot be made in Mauritania or Sudan, the list of other potential countries is likely to be a long one.
One useful way of understanding the benefits of the Atlas is to think about what the analysis adds to some of the key questions in growth economics. One of the classic comparisons made in the growth literature is between African and East Asian countries – which were at comparable levels of development in the 1950s-1970s, but which are now literally worlds apart.
Hausmann and Hidalgo give their take on this by comparing the Economic Complexity Index for Ghana and Thailand. The lessons are resonant for aid agencies. Both countries had similar levels of schooling in 1970, and Ghana expanded education more vigorously than Thailand in the subsequent 40 years, supported of course by external assistance and policy recommendations.
Despite this, “Ghana’s economic complexity and income stagnated as it remained an exporter of cocoa, aluminium, fish and forest products. By contrast, between 1970 and 1985 Thailand underwent a massive increase in economic complexity, equivalent to a change of one standard deviation in the Economic Complexity Index. This caused a sustained economic boom in Thailand after 1985. As a consequence, the level of income per capita between Ghana and Thailand has since diverged dramatically.”
The Economic Complexity Index has been shown to be a better predictor of economic growth than a number of other existing development indicators. For example, as reported in the Economist last week, it outstrips the WEF index of competitiveness by a factor of 10 in terms of the accuracy of its predictions. It also outperforms the World Governance Indicators and the standard variable used to measure human capital as predictors of growth.
There are many other rich and varied insights from the work which cannot be covered in detail here. There is also tremendous potential to build on and extend this data and analysis in the future. One of the areas I have been working on recently is on resilience, both as a means of reducing the impact of future crises and disasters, and as a means of securing development gains. This issue is understandably at the forefront of many policymakers’ minds at the moment. The network analysis underpinning the Atlas could be used as a very useful comparative indicator of economic resilience, comparing the sustainability of growth in different countries, and help us think through growth scenarios which might enhance or diminish resilience.
There may also be scope to use this kind of thinking to bring more rigour and realism to problems of industrial reform. Take for example the ubiquitous issue of how we move to low-carbon industrial strategies. It would need more data and analysis, but the product space is clearly a powerful way to start to think about the key issues in a systematic and data driven fashion. There are numerous climate change benchmarks out there but none – as far as I know – employ the kind of network analysis used in the Atlas, and so a key aspect of how industrial economies work is missed out. By understanding better the carbon reliance of a particular countries product space, it is possible to think through the implications – the likely successes and failures – of existing adaptation policies.
IV: In conclusion
Perhaps the most important contribution of the Atlas is the analytical rigour that it brings to the complex and dynamic nature of economic growth, and the ability it gives us to ask new and challenging questions more precisely. Cesar summed it up for me as follows:
What we really want to do is to inspire a new kind of conversation. Our traditional approach to economics has retained measures developed in 1930s and 1940s to deal with the situations and crises we faced back then. We think there should be a new breed of measures – that bring much more precision and resolution, and that mean we don’t continue to build our analysis on the over-simplification of a complex system.
Let’s hope we see more of this way of thinking in development debates. While there will inevitably be a degree of resistance from the old guard, it seems to me that the underlying premise of the report is something that no one could disagree with:
Ultimately, this Atlas views economic development as a social learning process, but one that is rife with pitfalls and dangers. Countries accumulate productive knowledge by developing the capacity to make a larger variety of products of increasing complexity. This process involves trial and error. It is a risky journey in search of the possible.”
Such lessons clearly need to play a much more central role in development policy and practice. Haussman, Hidalgo and their team have done us a real service with this work.
One of the areas where complexity thinking has entered the mainstream of development policy and practice is in resilience thinking. Much of this work owes a debt to C.S. ‘Buzz’ Holling, whose work on resilience of ecologies in the 1970s provided the intellectual underpinning to much recent work. Holling was recently awarded an honorary doctorate by Simon Fraser University, in Vancouver, Canada. His acceptance speech is reproduced below.
Sixty years ago I was where you graduates are now, but graduating from the University of Toronto. By the time I got my PhD a few years later, I was well launched on a goal to understand population processes. It was the unknown that beckoned me and simple curiosity that motivated me.
The goal was to develop suites of models and experiments that could yield explanations and understanding that were simultaneously precise, realistic, holistic and general. For that time, just before computers became available, that was viewed as being unnecessarily complex. After all, one distinguished ecologist asked me, if you are interested in the time a ball takes rolling downhill, why worry about anything more than the height of the hill and its slope? General laws of physics will provide the answer.
But I was stubbornly curious about the path down the hill, the bumps and valleys that the ball might encounter and the momentary pauses as the ball encountered, or even, over several runs, created a shallow valley. That led to really delightful experimental studies of predators and prey leading to generalized models and sudden discoveries from them. The beasts used in the experiments depended on the question of the moment – Preying Mantis, deer mice, shrews, then birds, fish and stalking lions. The early computers and languages like Fortran suddenly provided the language that could use the experimental and field results. Models plus reality combined to yield broadened, generalized understanding of a small number of classes of predation.
That is when I discovered multi-stable states – population systems were not driven only by attraction to a single equilibrium state but, instead, there were several equilibrium states that determined their existence. And the goal for understanding and managing living resources and their physical world, was not sustainability but simple persistence. I learned, for example, that we could have detected and averted a collapse of cod populations off Newfoundland, avoiding the social and economic upheaval that in fact occurred. Or, we could have anticipated and avoided a western sub-continental outbreak of bark beetles that are now destroying stands of lodge pole pine throughout British Columbia and Alberta. Both of these examples were dominantly caused by the slow consequence of earlier development and exploitation, by the ingenious, but myopic foraging of fishers and harvesters, and by decades long fire protection policies.
Those slowly and invisibly led to reduced resilience, poising the systems on the edge of an instability state which began to unravel in a stutter of local spatial collapses and outbreaks, each stutter hidden by fast and innovative fishers and tree harvesters, until the whole system followed the stutters and collapsed at all scales.
That has forced a new paradigm that led to theories of resilience, to adaptive complex systems, to integration across scales from fast and small to very slow and big– from the needles of trees over months, to the boreal forest over millennia, That new resilience paradigm led to management of resources that was adaptive, where the unknown was large, alternatives could be proposed and monitoring was essential.
That is all part of complex adaptive system theory. It reflects humanity’s partial knowledge, fast inventions for dealing with surprises, and persistent learning.
It applies to the present turbulence in the world now. Slow economic processes have led us to the big surprises now appearing on a global scale. Financial collapse, debts threatening nations, European deep instability, and climate change.
Since the Berlin Wall fell, and the Soviet Union collapsed, corporations began to focus on fast economic variables and on globalization. That led to an emphasis on expanding efficiency but also to the emergence of slowly increasing debt, and hidden forces caused by diversified, subdivided and fragmented investments. No one knew where they were, or what they cost. That eventually triggered a collapse that exposed the reality that slow, invisible changes had decreased the resilience of the world economy. Globalization spread the collapse. What was presumed to be efficient began to be realized as being myopic.
At this turbulent time of crises, you and I have a real purpose. We need to help minimize and slow the spread of the collapses in the face of resistance from lobbies and from accumulated wealth. Banks and investment firms need regulation and a richer paradigm, but that need is opposed by the entrenched powers of corporations and banks that are caught in a rigidity trap. Nations of the European Union, and the Euro, need an integrated, multi-scalar inter-relationship, but one that now encounters the loss of resilience that comes in part from the inability to devalue a single nation’s currency and little control on debt inflamed growth. Carbon dioxide emissions need to be inhibited, but that encounters the opposition from the fossil fuel corporations- particularly oil.
Our aboriginal cultures and small communities here on the west coast are discovering and protecting treasured histories and traditions of local cultures. They now need to also add and create novel new ways to see and act beyond their traditional scales at the mouths of rivers and to connect to others across scales. Does fear stop them? Could their traditional theory (and myths) combine with adaptive resilience theory (and myths) as an emerging synthesis?
The answer is to keep trying, keep talking, keep communicating, but recognize it is a frustratingly slow process. Understand the traps- poverty traps like Haiti, rigidity traps like Fascism, lock-in traps of mega agriculture, and gilded traps from external subsidies.
And here is a program specifically for you. Encourage and support experiments, a multiplicity of experiments that search for and deepen new paradigms. Be entrepreneurs, alone and cooperatively together. And make the experiments global and cross scale. The internet and its novel ways of helping people to interact lets us reach or create groups of participants independent of where they live, ones from multiple patches and multiple time senses.
Many experiments will fail, but make them safe in their failure. Look for rare synergisms between a few successes. When enough people and experiences have accumulated, then protest publicly, non-violently and simultaneously against the defenders of the old paradigm that created the crash, the flip.
is a Public Sector Governance Advisor at the World Bank, andused to head up the unit responsible implementing the Bank’s governance and anti-corruption strategy.
