Tag Archives: Mariana Mazzucato

Designer economies. How much freedom do we really have when imagining believable economic systems?

In November 2023, I was asked to keynote at something called the Space Economy Camp. The organizers were a diverse mix: the Complexity Economics Lab at Arizona State University; the 100 Years Starship Initiative, with its own literary prize; the Space Prize. The idea was this: 20 writers were selected via an open call, exposed to economics lectures, and put to work in small groups to imagine “sustainable, non-exploitative economies in space”.

I was one of the economists asked to give lectures. I decided to make it as practical as I could laying out some ideas from economics that, I thought, a sci-fi author might find useful in order to build fictional worlds with credible, if fictional, economies. Those ideas – useful or not, you be the judge of that – also applies to efforts of imagining economic systems outside of science fiction writing: for example to politics, or activism, or creating businesses or communities.

This post contains the editorialized notes from that lecture, reposted from Edgeryders.

1. Introduction and lecture outline

Worldbuilding is hard, as authors well know. In this lecture, we are going to take a look at the part of worldbuilding where you give your planet, eldritch dimension, fantasyland or post-climate change polity a believable, though obviously fictional, economy. In the time-honoured tradition, I have good news and bad news. The good news is that we have considerable latitude in designing your fictional economy, just as in inventing rituals, dress codes, weapons, and other technologies. The bad news is that coming up with a good design is nontrivial. But this is also good news, since overcoming difficulties with a creative act is what authors do, and it is perhaps the most fun humans can have.

In the lecture, We are going to reflect on some basic choices that we need to make when designing an economy. To help reflection, we invoke concepts from social sciences and economics.

Concept in real life Related concept in economics
Designing credible economies Incentive compatibility
“Human nature” Value theories
Institutions Economic anthropology
Plausible histories Subgame-perfect equilibria

2. Suspension of disbelief

I am no author, just a lowly reader. But, when I read, I take pleasure from diving into an immersive, textured world that I can explore. This pleasure is enhanced by suspension of disbelief, the psychological state of someone who, willingly, suspends certain functions of critical thinking in order to enjoy the narrative. Emphasis is on “certain”. If I read The Lord of The Rings, I can allow myself to get worried about Sauron’s armies eating what’s left of the free peoples of Middle-Earth (though there is no Middle-Earth: if I look out the window, Brussels is right there). But some parts of my critical thinking are harder to switch off. If, in order to prevail in the Battle of the Pelennor Fields, Gandalf had called in a drone strike on Mordor’s siege machines, that would have broken the suspension of disbelief, at least for me, and made my reading much less pleasant.

So, worldbuilding is a balancing act: the more space the author claims for imagining things that do not exist, the higher the potential entertainment value from the exoticism and mystery. But that space needs to be highly organised to avoid inconsistencies that puncture the bubble of the reader’s suspension of disbelief.

Careless depictions of the economy of fictional words can also rupture suspension of disbelief. A favourite example of mine is the use of coins cast in precious metal as currency in J.K. Rowling Harry Potter’s saga. The book makes it clear that the coins are precious and fungible (i.e. there is an incentive to steal them). They are kept in high-security vaults, guarded by goblins with great magical powers. This, however, does not quite gel: one imagines that, if the coins were really precious, wizards would simply magick them into existence. This would quickly lead to hyperinflation (depending on the magical cost of making new coins), which would drive the real value of those coins to near zero. I cannot justify those goblins.

Of course, this is a fantasy world, and you could always salvage it by inventing exceptions: for example, the wizards can magick up all sort of stuff, but not gold coins. Additionally, that no tracer spell can be put on coins so that they “know their master”, which would make them more like balances in a bank account, valuable but impossible to simply steal. But you see how this looks a bit contrived and “just so”.

Granted, readers can sometimes ignore the nagging feeling that something is off, and concentrate on the characters and the drama instead. This is easier in some subgenres than in others: readers of high fantasy novels are unlikely to pay close attention to economics, and indeed the Harry Potter’s saga is a huge success. So is Tolkien’s, and he got away with a complete disregard for anything to do with economics: who’s feeding, clothing and arming all these standing armies? Where are the breeders and stables to produce all those horses in Rohan, and would they not create some environmental damage? How is it that in besieged Minas Tirith there is no trace of a black market, like our grandparents experienced during World War 2 in most of Europe? On the other hand, if you are writing solarpunk sci-fi or cli-fi, alternative modes of organizing society are likely to be at the center of attention.

3. Incentive compatible mechanisms as a template for credibility

I propose that a good compass for figuring out whether a fictional economy is believable or not is its incentive compatibility. It goes through the concept of mechanism, associated with the names of Eric Maskin, Leonid Hurwicz and Roger Myerson. The basics are as follows:

  1. A mechanism is a manufactured environment for agents (normally people) to interact with one another (auctions, tax systems, social media…). Within the mechanisms, agents act according to their own objectives. [Maskin 2008]
  2. Designing a mechanism is about making its rules so that people in it spontaneously take the system in the direction that the mechanism designer wants to go.
  3. A mechanism is incentive compatible when every agent’s best strategy is to follow the rules, no matter what the other agents do [Hurwicz 1960].

In his Nobel lecture, Maskin asks three questions about mechanism design:

  1. When is it possible to design incentive-compatible mechanisms for attaining social goals?
  2. What form might these mechanisms take when they exist? Auctions, tax systems, elections, ritual combat, social media?
  3. When is finding such mechanisms ruled out theoretically?

They apply fairly directly to worldbuilding for science fiction authors! We can use them as a guide to imagine an economic system, for example that of a space economy. The authors can choose the system’s goals, then take on the mantle of the mechanism designer, and ask herself what form might incentive-compatible mechanisms take for those goals.

4. Incentives to do what? Introducing value theories

Incentive compatibility is about mechanisms being compatible with people’s incentives. Ok, but what are these incentives? What is it that people (be they humans, aliens, elves or robots) want? What do we value?

This is a philosophical question, and let us never forget that economics grew out of moral philosophy. Adam Smith was a professor of moral philosophy, and he authored a Theory of Moral Sentiments before The Wealth of Nations. The branch of economics dealing with it is called value theory. The most important thing to know about value theory is that it is inherently political and highly contested. Human communities in different times and places have adopted different value theories.

Consider, for example, the concept of production boundary, the imaginary line that divides activities that produce wealth to activities that merely redistribute it (I am borrowing this terminology from Mariana Mazzucato’s The Value of Everything). For example, imagine that Alice, a farmer, leases Bob’s land to grow wheat. Most economists would agree that Alice, when farming, produces wealth, whereas Bob, when collecting rent for the land, is simply redistributing to himself some of the wealth Alice has created.

Mazzucato’s point is that the production boundary has shifted over the centuries, amidst much debate and political battles. A common pattern has been that, when a class of people managed to attain some power, it fought to get legitimized as productive, declaring whatever it was doing as “production”. If what counts as value depends on who you ask, it follows that value is not some kind of universal measurable property, like mass. It’s a convention, that results from a political process.

An interesting question around value theories is this: who is supposed to be doing the valuing? The physiocrats and the classical economists disagreed about where the production boundary lay, but they agreed that value was an objective characteristic of things. Both schools believed that Alice the farmer creates value, while Bob the landlord does not. Furthermore, they believed this was just a fact, that depended on no one’s personal opinions and views. The objective nature of value implies that societies can and do make collective choices that they believe to lead to producing more value. If the value of care work (feminist economics) or nature (ecological economics) are objective, then surely we must reward their production, just as we reward the production of food and manufactured goods (you could state that value is, instead of objective, intersubjective and historically determined, and the argument would still hold).

Marginalist economics has a different idea. Starting in the second half of the 1800s, this current of economic thinking maintains that value is subjective. If anyone is willing to pay it for something, that something has value for thgat person. It posited that people wanted something called “utility”, and that different people would derive utility from different things. Its founders (Walras in France, Menger in Austria, Jevons and Marshall in the UK) had mathematical training and were keen to show that economics was “a real science” like physics. In order to make this idea of subjective preferences mathematically tractable, they assumed that, for each person, utility is an increasing function of her individual consumption of goods and services. Then, using calculus (invented in the 17th century), they could model individual choice as maximising an “utility function”, the arguments of which were individually consumed quantities of goods and services. Any collective dimension of value was discarded.

The founders of marginalism were well aware that theirs was a simplification, a thinking tool. Later, however, neoclassical economists started to think of this individualistic, subjective notion of value as true in itself. People, they thought, actually acted selfishly and in isolation: that was just human nature. Much sci-fi dystopia goes with the notion, and you can do so too. The main point of this lecture is that you don’t have to.

5. Underpinning the neoclassical theory of value: homo economicus

Neoclassical economists, then, posit that they have built a barebones model of human nature that (1) makes collective human behavior mathematically tractable and (2) despite its simplicity, captures the essence of how humans function. If both these claims hold, economists can build relatively simple models that will, nevertheless, capture the essence of human economic behavior and have explicative and predictive power. The idea of creating such a simplification for the purpose of doing economics goes all the way back to John Stuart Mill in 1836, and has later crystallized a model known as homo economicus. Looking at the conventional assumptions behind the economic theory taught in most university, homo economicus can be characterized precisely.

  • He is motivated by self-interest alone.
  • He has unlimited computational capacity (for example, computes the expected value of relevant stochastic variables).
  • This model underpins Pareto-efficient general equilibrium theory, in which the individual pursuit of self-interest by each economic agent achieves socially optimal outcomes. This is the philosophical foundation of Ayn Rand’s “Virtue of selfishness”, or Gordon Gekko’s “Greed is good”.

The history of economic thinking has seen several critiques of the homo economicus idea. Among others:

  • Most traditional societies are based on reciprocity (economic anthropology: Sahlins, Polany, Mauss…)
  • Bounded rationality (Veblen, Keynes, Simon…)
  • Inconsistent preferences for risk in investors (Tversky)
  • Unstable, poorly defined preferences (behavioral economics: Kahneman, Thaler, Knetsch…)
  • Not confirmed by experiments (experimental economics).
  • Not confirmed by experience in actual societies (Sen).

In general, homo economicus is not a good simplification of “human nature” on which to hang a theory of value. It creates more problems than it solves.

6. Underpinning other theories of value: group selection and the evidence from ancient societies

A more plausible theory emerged in the 2000s from the work of a a school of biologists interested in cultural evolution, the interaction between evolutionary pressure, the human genome, and human cultures. The main idea is that, unlike other species, humans are subject to evolutionary pressure on two fronts: the individual level (from Darwin’s natural selection, common to all species), and the group level (from group selection) [Henrich 2016]. The fitness of a human individual depends both on the individual’s own fitness (for example his or her resistance to pathogens) and on the success of the group to which he or she is a member.

It turns out that successful groups are groups that are good at cooperation, which is intuitive and confirmed by plenty of ethnographic and archaeological evidence. So, evolution pulls humans in two opposite directions: it wants us to be more competitive, to obtain a better position within the group; but it also wants us to be more cooperative, to benefit from the success of the group with respect to other groups.

The main driver of the group’s success is the scale at which it can manage cooperation [Wilson 2012]. Given cognitive limitations, this means the successful human in a successful group must be able to cooperate with complete strangers (unlike, for example, chimps: troops of chimps that encounter a lone chimp from a different troop will typically kill the stranger on sight). This poses the additional problem of free riding: non-cooperators in a cooperative group will reduce the group’s performance, because they benefit from the “public goods” created by the group without contributing to them. For this reason, humans appeared to have evolved methods to detect and expel the strangers in their midst. Experiments on infants as young as six months – and so untouched by education and value transmission – show that they react more favorably to others who speak their own dialect (even though they themselves have not yet learned to speak!). Biologists thinks that this “primary xenophobia” is innate, hardcoded into us at birth [Henrich 2016].

The late E. O. Wilson, perhaps the most accomplished scholar of cultural evolution, sums up his idea of “human nature” like this:

Individual selection is responsible for much of what we call sin, while group selection is responsible for the greater part of virtue. Together they have created the conflict between the poorer and the better angels of our nature.

So far the theory. Is it borne out by the data? An influential 2021 book by economic anthropologist David Graeber and archaeologist David Wengrow claims it is. The Davids combine ethnographic and archaeological evidence to confute the mainstream narrative about the invention of agriculture. Such mainstream narrative is associated to scholars such as, among others, Francis Fukuyama, Steven Pinker and most recently Yuval Harari, and goes like this: for a long time, humans lived in small hunting-gathering bands. These early societies were free and equal. Women were not oppressed. But then, ten thousands years ago, agriculture was invented. Early farming societies had a decisive advantage, as they could hoard stocks in good years to weather the bad ones. But farming meant inventing and enforcing property rights, which meant top-down management and therefore hierarchies. Stratified classes appeared, themselves allowing cooperation on a larger scale and giving farmers further advantages over hunters-gatherers. Patriarchy also ensued.

According to the Davids, this story is largely a fantasy, originated (much like Hardin’s tragedy of the commons story) by deductive thinking from philosophical premises originated in the Enlightenment. We have evidence of socially stratified hunting-gathering societies; egalitarian farming ones; societies taking up, then abandoning farming; even societies that farmed in the summer, and hunted-gathered in the winter, changing their leadership structure and political order with the season. The Davids refer back to Marcel Mauss’s 1903 studies of Inuit societies, which indeed changed their societal arrangements in sync with the season (hierarchical and patriarchal in the summers, egalitarian and free-love practicing in the winters). Given the harshness of living conditions in the Arctic regions, Mauss expected that these variations could be explained by the material advantages they brought, but he had to conclude that they could not. In the words of the Davids:

“Yet even in sub-Arctic conditions, Mauss calculated, physical considerations – availability of game, building materials and the like – explained at best 40 per cent of the picture […] To a large extent, he concluded, Inuit lived the way they did because they felt that’s how humans ought to live.”

7. Implications for authors of economic science fiction

So, where does this leave us? In a fascinating place. Powered by group selection, all kinds of societal and economic arrangements seem to be possible. In fact, very many are certainly possible, and we know that because we have tried them before. Remember Maskin’s definition of mechanism, “a manufactured environment for agents to make decisions”? That definition also describes a society. A society is a mechanism, because it is manufactured – via a political process – by its members. This gives authors a license to use their imagination to design new and fascinating economies we, the readers, can try on for size. It also gives them a library of arrangements that have been (or are still being) tried, to take inspiration from.

To conclude this lecture, I want to briefly point to some historical and contemporary examples.

Monastic economies

In the 6th century, St. Benedict of Nursia codified in his Rule the “protocol” overseeing the interactions among monks in a monastery (6th century). He did not found an order, but the Rule went viral and was adopted by the nascent monastic movement. People who used it were more likely to run a successful monastery than people who did not; and so, by the time of Charlemagne all Europe was infrastructured with successful monasteries running on the Rule.

Benedictine monasteries were units of production, because, in order to be effective places of devotion, they needed to be autonomous from the secular world. Benedict was aware of this, and his Rule contains some economic prescriptions:

  • Monks must price a little lower than seculars – doing otherwise would be avarice, a sin.
  • Everything monks do must be high quality. It is work, and work is dedicated to God and leads to Him.
  • Any profit you can make within these constraints is good, and you can use it to fund work that does not generate revenue.

This could not be more different from the neoclassical theory of labor supply, where a self-interested worker trades leisure for income; as well as from the theory of the profit-maximizing form. And yet, it worked extremely well. Monks made and ran inns; farmed the land; built water mills; created schools; copied and preserved manuscripts. At its peak, the famous Cluny Abbey served 10,000 warm meals a day to people in need. Also, this model is very stable, having been around (and prosperous) for 15 centuries straight. Even now, as a Benedictine superior told me, “we tend to to get prosperous, because monks work hard”.

Seasonal economies

These were described above in reference to the Inuit. The Davids again:

“In the summer […] property was possessively marked and patriarchs exercised coercive, sometimes even tyrannical power over their kin. But in the long winter months […] Inuit gathered together to build great meeting houses of wood, whale rib and stone; within these houses, virtues of equality, altruism and collective life prevailed.” [Graeber and Wengrow 2021]

Another traditional society with a similar arrangement are the Nambikwara in Northwest Brazil, studied by Lévi-Strauss in 1994.

Systems of cooperatives

Most economists, and most of the rest of us, think of the for-profit corporation as the “natural” form to organize economic activity. And yet, cooperatives are widespread all over the world. It is estimated that there are at least 280 million cooperators worldwide, and cooperatives have at least 27 million employees. Cooperatives lend themselves to self-organizing into “layers” to solve the problem of “make or buy”: a typical example is a group of farmers who grow grapes who join forces to commission a facility that will process the grapes of all of them into wine. This way, farmers can appropriate the added value of the transformation of their primary produce. One level above, you can find that the wine-making cooperatives of the same region can create a second-level coop to organize the distribution and marketing of the wine produced by all of them, and so on.

Europe has entire regions where most of the economy is cooperative. The most famous one is the Mondragon valley in Northern Spain, where an entire cooperative ecosystem of automotive manufacturing has come into being; several northern Italian regions are characterized by the prevalence of cooperatives in industries as diverse as agriculture, construction, insurance and banking.

Commons-based peer production

These are arrangements whereby non-hierarchical communities can maintain common resources (forests, fisheries, irrigation system) over time. They are very well documented: Elinor Ostrom won a Nobel for a 1990 book, Governing the Commons, where she not only looks in depth at case studies from Spain to Japan; she also comes up with 8 principles for designing the governance of a common resource. Principle 1 is “clearly define the group’s boundaries”, which goes back to Wilson and Henrich’s point about groups in competition needing to expel free riders. If you want to imagine a space economy, you could do worse than starting from here.

Notice that Ostrom’s book proves conclusively that “tragedies of the commons” do not always occur. Indeed, the 1968 paper by ecologist Garrett Hardin which introduced the “tragedy” concept was based not on evidence, but on deductive thinking: if homo economicus is a good model for human behavior, then tragedies of the commons should occur. Historically, the English commons (common lands) were eliminated not by “tragedies” of overconsumption, but by violent evictions and enclosures. Hardin himself was a white supremacist who cultivated a “lifeboat” vision of society.

War economies

A war economy is an economy the purpose of which is exogenous to the economy itself. Typically, this purpose is winning a war: the enemy is at the gate, and all economic efforts are directed to defeating them. War economies are field tested, and have proven to work extremely well: the most famous example is that of Germany during World War 1. Germany’s technocrat-in-chief, Walther Rathenau, pivoted the Empire’s economy in a matter of weeks as the war started [Scott 1998]. The state became the master planner, and, for many businesses, the main client and a sort of uber-CEO, with entire conglomerates strongarmed into pivoting overnight into new products.

This move was very successful in keeping the German army in the field and equipped, well after external observers had predicted its dissolution. And it was widely copied, which is why Rolls-Royce makes airplane engines as well as luxury cars.

Red plenty

This is more conjectural: the idea is that, as computing becomes cheaper and more powerful, central planning might emulate the efficiency of markets, while overcoming the latter’s blindness to externalities such as pollution or care work. We do know that the Soviet Union attempted cybernized central planning using linear programming techniques [Kantorovich 1939]. The centerpiece of the effort was the idea to use something called shadow prices (the marginal advantage of releasing a constraint) to simulate market prices. This fascinating story is told in a very strange (history? Fiction?) book by Francis Spufford, Red plenty.

8. Thinking up a fictional economy with subgame-perfect equilibria

In an attempt to grapple systematically with these ideas, a few years ago I was part of a group of people that were interested in the intersection between science fiction and economics, and called ourselves, cheekily, the Science Fiction Economics Lab. We started turning these things around in our heads, and came up with the idea of an open source world where we could explore these thoughts. We were doing worldbuilding, rather than writing actual sci-fi (though eventually some sci-fi stories set in our imaginary world did appear).

The overarching concept was that of a floating megacity, adrift in the oceans of a vaguely post-climate change Earth. We called it Witness. Witness had launched as a unitarian project, inspired by the floating city concept of UN Habitat, but then it had fractured along ideological lines. It was large enough to sustain several splinters, called Distrikts, each of them with its own economic system. We structured the work on Witness as a wiki (Witnesspedia), with major entries for the most important Distrikts: Libria, a hypercapitalist economy with minimal state intervention, reminiscent of much cyberpunk dystopias and, well, us. The Assembly, a cooperativist society with super-strong anti-monopoly culture. Hygge, a Nordic social-democracy on steroids; the Covenant, characterized by the presence of many monasteries and other religious institutions, with a strong manufacturing vocation (pun unintended).

This all is fun, but quite hard to take it down one level, to imagining institutions like markets, central banking, antitrust enforcement institutions, and indicators of economic performance (because, come on, what kind of self-respecting sci-fi piece of work would still be mentioning GDP? seriously). The incentive compatibility constrain kicks in. Perhaps the hardest nut to crack is the presence of trade across different systems: if Libria can trade freely with Hygge, will not its products – made with alienated labour – outcompete the fairer ones in Hygge? If not, why not? You find yourself designing policies that reproduce the economic systems you want – which is more or less what Graeber and Wengrow tell us real societies do.

In trying to make these imaginary economies credible, we felt the need to come up with an origin story. If these systems are in our future (which makes them more relatable) there should be an incentive-compatible path from here to there. So, maybe a Distrikt in Witness has robust trustbusting policies. Problem with monopolists is that they tend to capture their regulators, because they typically have more money and woman- or manpower than them. So, a society with strong anti-trust policies that never had any large monopoly is in equilibrium, because no firm becomes big enough to capture the regulators. But a society that starts with incumbent monopolies (like we do), and then somehow introduces antitrust policies, is not, because monopolists have the power to prevent effective regulation. To be credible at all, an imagined future needs to be connected to the present by an unbroken series of changes, each of these is incentive compatible. Game theory has a formalization of this concept, called a subgame-perfect equilibrium [Selten 1988].

Subgame-perfection is a test for the believability of the origin story of an economic system. To pass the test, the story needs to respect the incentive-compatibility constrain at each step of the way.

9. Coda: the role of science fiction in developing economic thinking

For the first time since I am intellectually active, late-stage capitalism is being seriously contested; and neoclassical economics with it. The battering ram of these contestations, alas, is not the economics profession, but climate change. But the profession is stirring, flexing muscles that had not been used for almost 100 years. New concepts are afoot: degrowth. Commons-based peer production. Universal basic services. Modern monetary theory. And some old concepts, like mutualism, and cooperativism, are making a comeback. They can inspire you as you build fictional economies in your head, and I hope you have as much fun as I did.

It is fun, but it also is important work. Like Cory Doctorow says, science fiction stories can function as architects renderings, making these models come alive, showing us what our lives would be like, if we lived in these systems. What would our jobs look like on a planet (in a galaxy far far away) that embraced degrowth? Our schools? Our romantic life? I am convinced that we need science fiction to inspire democratic debate on the urgent economic reforms that await. So, let’s get to it.

Essential bibliography

  1. D. Graeber and D. Wengrow, 2021. The dawn of everything: a new history of humanity. London: Allen Lane.
  2. J. P. Henrich, 2016. The secret of our success: how culture is driving human evolution, domesticating our species, and making us smarter. Princeton: Princeton University Press.
  3. L. Hurwicz, “Optimality and informational efficiency in resource allocation processes,” in Mathematical methods in the social sciences, K. Arrow, S. Karlin, and P. Suppes, Eds., Stanford: Stanford University Press.
  4. E. S. Maskin, 2008. “Mechanism Design: How to Implement Social Goals,” American Economic Review, vol. 98, no. 3, pp. 567–576, May 2008, doi: 10.1257/aer.98.3.567.
  5. M. Mazzucato, 2018. The value of everything: making and taking in the global economy. London, UK: Allen Lane, an imprint of Penguin Books.|
  6. E. Ostrom. Governing the Commons: The Evolution of Institutions for Collective Action, 1st ed. Cambridge University Press, 2015. doi: 10.1017/CBO9781316423936.|
  7. R. Selten, 1988. “Reexamination of the Perfectness Concept for Equilibrium Points in Extensive Games,” in Models of Strategic Rationality, vol. 2, in Theory and Decision Library C, vol. 2. , Dordrecht: Springer Netherlands, pp. 1–31. doi: 10.1007/978-94-015-7774-8_1.|
  8. E. O. Wilson, 2012. The social conquest of earth, 1st ed. New York: Liveright Pub. Corporation.|
Hidalgo and Hausmann's product space.

Policy making as risk management under complexity: five economists for the next ten years

Author’s note: this is not an academic essay. It’s more of a long, wonkish blog post, that borrows some characteristics from academic essays. If you think it should be published elsewhere, get in touch. If you want an Italian translation, ask for one. 

Abstract (TL;dr)

Public policies in the past few decades have failed on many levels. While many economists have been critic of such policies, economics as a discipline was not able to deliver a better paradigm. I examine some recent work by five authors: David Colander, Roland Kupers, Mariana Mazzucato, Eric von Hippel and Ricardo Hausmann. I argue that, taken together, their contributions herald a completely new way to think about policy making. This new paradigm is the brainchild of complex systems science. It implies that policy makers should have a new skillset, new tools, new indicators and even new goals.

1. How economics failed us

Economics has made a bad name for itself.

  • In the 1980s, the Chicago School rose to prominence with its recipe of inflation control and fiscal conservatism. It inspired the controversial reforms of the Reagan-Thatcher era, and marked the beginning of the end for the European welfare state.
  • In the 1990s, the Washington Consensus ideology pushed upon the whole world a policy toolbox of fiscal discipline, privatisation of public services and liberalisation of capital movements. These policies were responsible for the mismanagement of the financial crises of those years.
  • Then came 2008 with its Great Financial Crisis. We were plunged into a strange world. In the West, negative interest rates, quantitative easing, skyrocketing inequalities, “too big to fail”. Globally, a reduction in the number of the poorest, and the rise of China over Southern Asia and Africa.

All through this, economists have put up quite a fight. The top names in the profession have denounced the inconsistencies of the dominant doctrine. Joseph Stiglitz exposed the International Monetary Fund’s mismanagement of the crises of the 1990s. Paul Krugman explained why fiscal discipline was the wrong thing to do in the wake of 2008. The list could go on and on.

But policy makers remained unimpressed. Yes, mistakes were made. Yes, some excesses needed correcting. But in the end, no other paradigm was available. Dissenting economists had strong critiques, but weak counterproposals. In the 1930s, Keynes proposed a new paradigm. It was elegant. It was operational. It offered a new way out, and policy makers embraced it. But now? No new paradigm is in sight. Standard economics is the only game in town.

Except it is not. Over the last few years, four economists and one physicist have made groundbreaking contributions. I propose that, taken together, they form the seed of a new way to think about economic policy. In what follows, I list their main contributions. I then discuss the implications of taking them together, rather than one at a time.

2. David Colander and Roland Kupers: complex systems theory as a frame

Scholars of complex adaptive systems see the world through the lens of a process called emergence. The idea is this: simple rules of interactions between agents give rise to surprising system-level properties. These properties of the system cannot be deduced by studying its components. For example, water is a liquid at room temperature. It sloshes and shimmers and does many interesting things. A single water molecule is not a liquid: liquid-ness is not in the molecules themselves. It emerges from the interaction across billions of identical molecules.

Porting this way of thinking to policy making is difficult. The starting point is this: society and its economy are no longer seen as machines. No longer can the government push the right buttons to get them to social optima. The world of traditional economics goes down in flames. So what can the government do? There is a fundamental clash: policy is about agency, intentionality, top-down process. Emergence is the opposite of that: structure happens without designers or architects. A complex system with agency in it (for example an economy with a government) is driven by two fundamental forces, emergence and agency itself.

To navigate the dilemma, Colander and Kupers propose a government that “picks its fights”. It strives to spot emergent trends that go in the direction that it wants, then moves to reinforce them. One example they give is the trend towards physical fitness and healthy living. A complexity-oriented government would move aggressively to support it, and so save taxpayer money on health care.

This has profound implications. The main one is that the government needs a new set of core skills. Among them:

  1. It needs to be great at scanning the horizon for useful social trends. This is by no means easy: we now see fitness as a trend, but in the early 80s there was no such thing. People would see their cousins taking up aerobics or weightlifting, and shrug them off as weirdos. It took serious analytical skills to recognise it for what it was.
  2. It needs to be strong and nimble, and use strength and nimbleness as a source of moral authority. When it moves to support something, private business and the public need to know that this something is here to stay, and that support will not waver.
  3. It needs to choose, and take responsibility for its choices. No more handwaving about “leadership of the private sector”. No more bullshit about impartiality. We stand for nuclear, or against it. We stand for genetic engineering, or not. And when we choose, we stay with our choice for as long as we need to, not until the next election.

3. Mariana Mazzucato and Eric von Hippel: rethinking innovation

When we think about innovation, we think about Schumpeter’s creative destruction. Stories of innovation are stories of brave, disruptive entrepreneurs who “stay foolish” as they follow their own vision. Mazzucato shows that these stories are mostly false. Aggressive state intervention was the decisive driver in kickstarting today’s hi-tech industries: IT, biotech, nanotech, green energy. Moreover, at least for IT, the (American) state’s motives were not even economic, but related to national security.  The protagonist was the Pentagon, not Treasury. In the case of China, a similar dynamics is now playing out with green energy. The main policy driver is preventing climate change and pollution. A world-leading green energy sector emerges as a result of that policy.

In these stories, private business and venture capitalists consistently show risk aversion and short-termism. They do “me too” innovation and polish. An entire chapter of Mazzucato’s book is dedicated to Apple’s iOS devices. It turns out that all the key technologies putting the “smart” in smartphones are taxpayer-funded. It’s worth listing them here: microprocessors, DRAM, micro hard drives, LCD displays, LI-ion batteries, DSP signal processing, the Internet, HTTP, HTML, cellular technology, GPS, multi-touch screens, and SIRI. Apple added technology integration and design, but did none of the innovation heavy lifting. Mazzucato concludes that the State, not private firms, is the real disruptive agent:

In sum, “finding what you love” and doing it while also being “foolish” is much easier in a country in which the State plays the pivotal serious role of taking on the development of high-risk technologies, making the early, large and high-risk investments, and then sustaining them until such time  that the later-stage private actors can appear to “play around and have fun”.

von Hippel starts at the opposite end: what he calls “free innovation”. This is innovation developed and given away by consumers (patients, tinkerers etc.).  This is by no means marginal. It is a major economic phenomenon. It involves tens of millions of individuals in just six countries surveyed (Canada, Finland, Japan, South Korea, UK, US). Estimated free innovation R&D expenditure has been estimated for three countries, and found to be on the same scale of corporate R&D. These estimates are likely to be conservative: free innovation in services, for example, has been left out of them.

Moreover, free innovation tends to lead producer innovation. There can not be a market for something that does not exist yet. For-profit corporations only service markets, so they focus on incremental innovations. But people don’t care about markets: they innovate for themselves and their friends. Some of their innovations go viral and create markets that, later, producers supply with innovations of their own. This happens across the board: 3D printers, scientific instruments, health care, whitewater kayaking.

From opposite angles, Mazzucato and von Hippel see the same reality. Business is not the sole agent of innovation. It probably is not even the main one. What’s more, the innovation that it does do is uninspiring: low-risk integration of ideas developed elsewhere. Glass beads and trinkets. Their work dispels for good Silicon Valley’s claim that “we take high risks, we deserve our high profits”. The truth is this: all the main risks are underwritten by ordinary people. As taxpayers, they underwrite risky government-funded research projects. As free innovators, they directly develop technologies and create markets for them. What’s left for the companies is to take the goodies, make a grab for the money and (all too often) siphon profits to some tax haven. Mazzucato calls this configuration “parasitic”. She is right: it socializes the risks of innovation, but privatizes its rewards.

They also show that money is not the motivator of the best innovation. States innovate to further a collective vision (“go to Mars” or “stop global warming”). People innovate to help themselves and loved ones (“I built a wearable monitor the glucose level of my diabetic child, so she can sleep over at friends”), or just for fun.

4. Ricardo Hausmann: economic well-being as a set of capabilities

Hausmann and collaborators have succeeded in redefining what it means for an economy to be healthy. This is no small achievement. GDP is broken: bad things like illnesses, car accidents and pollution all make it go up, not down. Economists have been muttering and complaining for as long as I can remember, but GDP has stayed. In 2008, The French government even tried assembling a super-high-level commission. Headed by Amartya Sen, Joseph Stiglitz and Jean-Paul Fitoussi, it could count on the cream of the crop in the economics profession, including five Nobel laureates (Arrow, Heckman, Kahneman, Sen, Stiglitz). The results were disappointing. There was handwaving about “multidimensionality of well-being” and  “pragmatic approach towards measuring sustainability”. Everybody went right on using GDP.

Hausmann takes a different path. He thinks that a healthy economy is one that can make many things. A country that can make machine tools and aircraft and nanotubes is healthier than one that can only grow bananas, or pump oil. This has got nothing to do with how much money people in the country are making. It’s got everything to do with how resilient economies are. Economies that can make a great many things can engineer their way out of many shocks. For example, if you have good solar tech you are more robust to fossil fuel shortages.

Hausmann and collaborator Cesar Hidalgo invented product space, which makes this concept operational. The main idea is that what countries make reveal what they know. They start by international trade data, and build a graph of countries and products. If a country exports one product, the two are connected in the graph. Next, they apply graph theory to derive measures of economic diversity. To a first approximation, diversity is simply the number of products a country exports. More sophisticated measures include second- and third-order effects. For example, products that are exported by few countries (like medical equipment) carry higher diversity than products that are exported by many countries (like wooden logs).

Product space analysis gives us a single number that summarizes the economic diversity of an economy in a given year. You can then compare different economies, just like you do with GDP per capita. You can also check back every year or two to see how much diversity is growing, just as with GDP. Except that diversity-as-health makes sense, whereas transactions-as-health do not. Its underlying formal principles are also more intuitive: product space descends from network math, GDP from double entry accounting. Most people with no formal training in either find networks simple, and accounting intricate.

5. Coda: policy as long-term risk management in a complex world

Where does that leave economic policy? Each of the contributions I listed has strong, direct, operational policy implications. But I propose that, taken together, they form a whole greater than the sum of its parts. They outline a new approach to economic life, and to policy enacted upon it. This new framework stems from the 35 years long love-hate affair between complex systems science and economics. What follows is a rough, tentative approach to summarize it.

  1. We don’t have control. The world is big, complex and in constant flux. We are nowhere near to understanding it in full, let alone dominate it. The idea of computing and achieving social optima is nonsense.
  2. Focus on the “how” questions. The above looks like harmless common sense, but is has profound consequences. The main one is this: we can no longer assume markets will find the social optimum by themselves. This is not because of market failures: general equilibrium theory is discarded altogether. Markets become mere tools to allocate specific resources. This, in turn, means that economics gives up on answering the “what” question (as in “what should we do?”). It is up to humans find out, in their own messy way, what a desirable outcome looks like. Economics goes back to focusing on the “how” question (as in “how shall we get there?”), consistently with its origins as a spinoff of moral philosophy. I am grateful to Fabrizio Barca for this observation.
  3. Policy is about society-wide risk management. The policy maker’s job is to manage risk. This involves scanning the horizon for trouble (frequent) and opportunities (rare). Risk is a constant in the journey of human societies: all we can do is manage it, weighing potential gains against potential losses. Uncertainty will always be high. Companies and households, of course, do the same. The difference is that policy makers can and should do this for society as a whole, making the hard choices that individual actors won’t do, and allocating risks and rewards across society. The allocation has to be long-term sustainable. Mazzucato, for example, points out that US innovation policy is not sustainable, because its risks are borne by taxpayers and its rewards are reaped by shareholders and executives. Over the long run, this will result in political backlashes and instability, which in turn will kill the State’s ability to invest.
  4. It’s all about the skills. Upskilling your economy is the best risk management tool. The more things you can make, the greater and more diverse shocks you can withstand. Hausmann has a great quote: “don’t add value to your raw materials, add capabilities to your capabilities”.
  5. Corporations are just a tool, and not always the most effective one. Mainstream economics fetishizes companies and profit for many reasons, theoretical and otherwise. But when you think in terms of risk management, you start to see things in a new light. Suppose you, as a policy maker, believe climate change could badly hurt our societies. Suppose you plot a transition to a deep green, low-emission economy. People from business come to you and protest “this is going to hurt out bottom line, we won’t cooperate”. If you believe GDP embodies human happiness and it is your duty to maximise it, you will listen carefully. If you a risk manager, you are more likely to brush them off. Your duty is not towards shareholder value, but towards deflecting large risks. If companies won’t collaborate in building the new infrastrure you want, you will work with different tools (public sector agencies, for example).
  6. Arbitrariness is inevitable. Risk management should be evidence-based. But any risk manager will tell you that, at the end of the day, you will have to make calls. Many of these will be in terms of uncertain gains versus certain costs. Should we bail out this bank? It might save us from contagion and systemic crisis in the future, but it sure will cost us taxpayer money now. Are Arctic glaciers worth the demise of the oil industry? You get the idea. This is the core of the trade of policy making. There is no such thing as sitting back and letting social optima emerge from market equilibria. Policy makers just have to make hard calls. Which means they will sometimes (often, even) fail. There is no way to avoid this. Colander and Kuper insist on the government needing “moral strength” to do its job.

This is a high-level description. But the theory of policy making in a complexity framework is mature enough to have produced tools, practices, indicators. And boy, do they look different from what we are used to. I already mentioned product space. Both Mazzucato and (especially) von Hippel have built solid empirical methodologies to inform innovation policy. Hausmann even wrote a convincing critique of randomized control trials, the gold standard of empirical research in economics. His tool-of-choice is “crawling the design space” of policies in a decentralized fashion. Money quote:

As opposed to the two or three designs that get tested slowly by RCTs (like putting tablets or flipcharts in schools), most social interventions have millions of design possibilities and outcomes depend on complex combinations between them. This leads to what the complexity scientist Stuart Kauffman calls a “rugged fitness landscape.”

That’s what evolution does, and this is no coincidence. Hausmann is a complexity scientist himself, and thinks more like a biologist than like a neoclassical economist. The Kauffman quoted is a theoretical biologist, not an economist. Everything changes. It’s a whole new paradigm.

Conclusion. A new paradigm for policy making is warming up in the background. A lot of the foundational work has been laid out. Much work remains, but that’s no excuse not to start deploying this way of thinking right now. All we are missing is a few forward thinking national or regional governments willing to be early adopters. I think I will see such adoption in my lifetime. This is good news for everyone, but great for us economists. After decades of deadlock and frustration, it appears we, once again, have a large contribution to make. I want to end with my all-time favourite public policy quote. It is attributed to the very first complexity economist, Brian Arthur.

If you think that you are a steam boat and you can go up the river, you are kidding yourself. Actually, you are the captain of a paper boat drifting down the river. If you try to resist, you are not going to get anywhere. on the other hand, if you quietly observe the flow, realising you are part of it […], then every so often you can stick an oar into the river and punt yourself from one eddy to another.


Reading list

  • Colander, David, and Roland Kupers. Complexity and the art of public policy: Solving society’s problems from the bottom up. Princeton University Press, 2014.
  • Hausmann, Ricardo, et al. The atlas of economic complexity: Mapping paths to prosperity. MIT Press, 2014.
  • Mazzucato, Mariana. The entrepreneurial state: Debunking public vs. private sector myths. Anthem Press, 2015.
  • von Hippel, Eric. Free Innovation. MIT Press, 2016.