četvrtak, 26. rujna 2013.

Peter Turchin - Cliodynamics

Kliodinamika istražuje povijest matematičkim modelima, otkrivajući obrasce koji objašnjavaju zašto se nešto dogodilo ili će se dogoditi u budućnosti. Dva primjera: nastanak velikih zajednica, gradova, država i carstava nije potaknuo razvoj zemljoradnje, kako se dosad mislilo, nego su glavni čimbenik bili ratovi. A što se tiče budućnosti, nestašica hrane uzrkovat će oko 2020. erupciju nemira, sukoba i klanja.


I’d actually recommend reading journal articles I cite before reading my article:
Dynamics of political instability in the United States, 1780–2010 by Peter Turchin

The Food Crises and Political Instability in North Africa and the Middle East by Marco Lagi, Karla Z. Bertrand and Yaneer Bar-Yam.

Data Geeks Say War, Not Agriculture, Spawned Complex Societies

By Klint Finley

Peter Turchin Photo: Peter Turchin

It seems like data is changing everything we do.
Data analysis has transformed biological research over the past decade. It has reinvented the business world by way of “big data” software platforms along the lines of Hadoop, an open source tool originally built by Yahoo and Facebook. It’s even changing historical studies, thanks to a movement called Cliodynamics.
Cliodynamics is a field of study created by Peter Turchin in the early 2000s. The idea is to use data as a means of predicting the future, but also as a way of testing theories about what happened in the past. You build a model that seeks to explain history, and then you test this model using real historical data.
The movement’s latest aim is to analyze the origins of complex societies. In a paper published today in Proceedings of the National Academy of Sciences, Turchin and a trans-disciplinary team from the University of Connecticut, University of Exeter, and the National Institute for Mathematical and Biological Synthesis attempt to overturn the long standing belief that large-scale states are the product of agriculture.
Early humans were hunter-gatherers. They had relatively simple social structures, which consisted of perhaps a few dozen people, all of whom knew each other, and they didn’t engage in complex cooperative tasks. But eventually, complex societies evolved — complete with governments, armies, agriculture, education, and other large scale, cooperative projects. With their paper, Turchin and his collaborators analyzed the spread of the social norms that allowed societies to expand across millions of people.
“You cannot have a large state without bureaucrats, but bureaucrats are expensive. You have to pay them,” he says. “So the big question is how do complex societies evolve when they are so expensive?”
The standard theory, which Turchin calls the “bottom up” theory, is that humans invented agriculture around 10,000 years ago, providing resource surpluses that freed people up for other ventures. But what Turchin and his team have found is that the bottom-up theory is wrong, or at least incomplete. “Competitions between societies, which historically took the form of warfare, drive the evolution of complex societies,” he says.
To test the two competing theories, Turchin and company designed two mathematical models for predicting the spread of complex societies. One based only on agriculture, ecology and geography. The other included those three factors, plus warfare. Then, they used data from historical atlases to determine whether these models matched up with the way the different states and empires actually evolved.
The model that included warfare predicted about 65 percent of the historical variance, while the agricultural model explained only about 16 percent, suggesting that warfare was more important in the spread of social norms that lead to complex societies.
Turchin admits that the model is far from perfect — it includes no population data, for example — but for the most part, it was able to predict the spread of large-scale states between 1,500 BC to 1,500 AD. He also notes that whether or not simple societies were warlike is hugely controversial, but says that by the time their models start, warfare was widespread. “Proximate causes for warfare are numerous: competition for resources (mainly territory), revenge and strategic consideration (attack your enemy before they are ready to attack you),” he says.
He adds, however, that agriculture is also a part of how complex societies evolve, and he and his team are already working on their next research project, which will involve crop yield data. Economic and ideological competition, he says, can help mold societies too. For example, the competition between the United States and the Soviet Union.
“Back in the 1920s in the United States, we had pretty naked capitalism. Workers were expected to get paid whatever they could get,” he says. “But then the Soviet Union came on the scene, and suggested that workers should get paid more.”
He says that during the original “Red Scare” in the 20′s, corporations — fearing a large scale shift to communism in the U.S. — voluntarily began paying higher wages and implementing more social programs, such as pensions. But a few decades later, economic competition forced Russia to allow more free trade and democracy.
But the biggest driver? War.- www.wired.com/

Mathematicians Predict the Future With Data From the Past

By Klint Finley

In Isaac Asimov’s classic science fiction saga Foundation, mathematics professor Hari Seldon predicts the future using what he calls psychohistory. Drawing on mathematical models that describe what happened in the past, he anticipates what will happen next, including the fall of the Galactic Empire.
That may seem like fanciful stuff. But Peter Turchin is turning himself into a real-life Hari Seldon — and he’s not alone.
Turchin — a professor at the University of Connecticut — is the driving force behind a field called “cliodynamics,” where scientists and mathematicians analyze history in the hopes of finding patterns they can then use to predict the future. It’s named after Clio, the Greek muse of history.
These academics have the same goals as other historians — “We start with questions that historians have asked for all of history,” Turchin says. “For example: Why do civilizations collapse?” — but they seek to answer these questions quite differently. They use math rather than mere language, and according to Turchin, the prognosis isn’t that far removed from the empire-crushing predictions laid down by Hari Seldon in the Foundation saga. Unless something changes, he says, we’re due for a wave of widespread violence in about 2020, including riots and terrorism.
‘We start with questions that historians have asked for all of history. For example: Why do civilizations collapse?’
— Peter Turchin
This burgeoning field is part of a much larger effort to gain more insight into our world through the massive amounts of digital data that are now available via the internet — a movement that ranges from Google’s search engine to the data science contests run by San Francisco startup Kaggle. The difference is that cliodynamics uses data from the distant past. Turgin and his cohorts mine historical documents that have only recently come online.
Turchin didn’t begin as a historian. His original area of interest was ecosystem dynamics, but he soon decided that many of the interesting problems had already been solved. So he started looking for ways of applying mathematics to other fields. “The only way to do science is to make predictions and then testing them with data,” Turchin says. Many other social sciences — including sociology, economics, and even anthropology — had already been revolutionized by mathematics. But historians had resisted quantification.
He founded the movement in the late ’90s, and since then, many more have joined in. In 2010, this growing community of researchers started the peer-reviewed publication Cliodynamics: The Journal of Theoretical and Mathematical History.
The basic idea is nothing new. Thinkers from Georg Wilhelm Friedrich Hegel to Oswald Spengler to Leo Tolstoy tried to develop cyclic theories of history that could also predict the future. Austrian philosopher Karl Popper critiqued this notion in his The Poverty of Historicism in 1957. And the ’60s spawned a movement called cliometrics. But the approach eventually fell out of favor. “General theories of history are not accepted, in my opinion, for good reason,” says Turchin. And yet he followed cliometrics with cliodynamics. The new field, you see, has an edge that predecessors didn’t.
It’s not the mathematics. Turchin says his methods aren’t very complex. He’s using common statistical techniques like spectrum analysis — “I used much more sophisticated statistical methods in ecology,” he says. And it’s not “big data” tools. The data sets he’s using aren’t all that big. He can analyze them using ordinary statistical software. But he couldn’t have built these models even a few decades ago because historians and archivists have only recently started digitizing newspapers and public records from throughout history and putting them online. That gives cliodynamics the opportunity to quantify what has happened in the past — and make predictions based on that data.
In the simplest of terms, Turchin and his colleagues will build a mathematical model using one data set and then test that model against other historical data sets they’re unfamiliar with. That way, they can see if the model holds. This isn’t exactly the psychohistory described by Isaac Asimov. “For the most part, we don’t predict the future. It’s too far. We can’t wait 200 years to see if something’s right,” Turchin says. “I’m not a prophet.” But cliodynamics moves in that direction — and it’s not science fiction. Though traditional historians are often wary of the practice, others very much see the value.
“It’s very important to do. It should force traditional historians to respond,” says Yale historian Joseph Manning. “Most people in my field just publish documents and don’t go behind them.”

Peter Turchin’s graph describes the regular waves of violence — including riots and terrorism — that characterize U.S. history. Image: Peter Turchin

Waves of Violence
What Turchin and his colleagues have found is a pattern of social instability. It applies to all agrarian states for which records are available, including Ancient Rome, Dynastic China, Medieval England, France, Russia, and, yes, the United States. Basically, the data shows 100 year waves of instability, and superimposed on each wave — which Turchin calls the “Secular Cycle” — there’s typically an additional 50-year cycle of widespread political violence. The 50-year cycles aren’t universal — they don’t appear in China, for instance. But they do appear in the United States.
The 100-year Secular Cycles, Turchin believes, are caused by longer-term demographic trends. They occur when a population grows beyond its capacity to be productive, resulting in falling wages, a disproportionately large number of young people in the population, and increased state spending deficits. But there’s a more important factor, one that better predicts instability than population growth. Turchin calls it “elite overproduction.” This refers to a growing class of elites who are competing for a limited number of elite positions, such as political appointments. These conflicts, Turchin says, can destabilize the state.
Many of these issues persist in industrial societies. Although population growth is no longer likely to result in mass starvation, it can push the supply of labor beyond demand, leading to increased unemployment.
Turchin takes pains to emphasize that the cycles are not the result of iron-clad rules of history, but of feedback loops — just like in ecology
Then you have the 50-year cycles of violence. Turchin describes these as the building up and then the release of pressure. Each time, social inequality creeps up over the decades, then reaches a breaking point. Reforms are made, but over time, those reforms are reversed, leading back to a state of increasing social inequality. The graph above shows how regular these spikes are — though there’s one missing in the early 19th century, which Turchin attributes to the relative prosperity that characterized the time.
He also notes that the severity of the spikes can vary depending on how governments respond to the problem. Turchin says that the United States was in a pre-revolutionary state in the 1910s, but there was a steep drop-off in violence after the 1920s because of the progressive era. The governing class made decisions to reign in corporations and allowed workers to air grievances. These policies reduced the pressure, he says, and prevented revolution. The United Kingdom was also able to avoid revolution through reforms in the 19th century, according to Turchin. But the most common way for these things to resolve themselves is through violence.
Turchin takes pains to emphasize that the cycles are not the result of iron-clad rules of history, but of feedback loops — just like in ecology. “In a predator-prey cycle, such as mice and weasels or hares and lynx, the reason why populations go through periodic booms and busts has nothing to do with any external clocks,” he writes. “As mice become abundant, weasels breed like crazy and multiply. Then they eat down most of the mice and starve to death themselves, at which point the few surviving mice begin breeding like crazy and the cycle repeats.”
There are competing theories as well. A group of researchers at the New England Complex Systems Institute — who practice a discipline called econophysics — have built their own model of political violence and concluded that one simple variable is sufficient to predict instability: food prices. In a paper titled “The Food Crises and Political Instability in North Africa and the Middle East,” they explain that although many other grievances may be aired once the violence begins, the cost of food is the primary trigger. They make a similarly grim prediction: large-scale riots over food, beginning around October of this year.
Into the Dark Archives
Much has been made of machine learning algorithms and software such as Hadoop and how they’re used to mine the enormous amounts of data generated by the average internet user, but cliodynamics shows that we can find just as much value in “dark archives” — the mounds of non-digitized records that we don’t realize contain useful data. Quantitative biologist Samuel Arbesman calls this “long data,” and he urges the world to take a closer look.
Arbesman says that many traditional historians are beginning to embrace Turchin’s practices, opening up opportunities for academics in the humanities to collaborate with mathematicians and economists. But he adds that academics aren’t the only ones who can benefit from dark archives brought online. Even businesses, he says, can mine such data.
Some businesses, explains says, have been around for hundreds of years, changing with the times. IBM was founded in 1911 and originally sold tabulating machines. Nintendo started out in 1889 as as a playing card company. The construction company Kongō Gumi existed for over 1,400 years.
Their future, he says, can benefit from their past.- www.wired.com/

Turchin's blog:

Can Math Explain History? 

One of the greatest puzzles of social science is how human societies evolved from small groups of relatives and friends to the huge, anonymous and complex societies of today.
demonstrationA peace demonstration. Today we live in huge societies of strangers, who nevertheless are capable of coming together for cooperative purposes
Ten thousand years ago everybody lived in a village. Strangers were rare, and most of them were enemies. Then the first hierarchically organized societies appeared – chiefdoms, simple and complex. Around 5,000 years ago the first states evolved and 2,500 years ago they transformed themselves into huge multiethnic empires, governing tens of millions of people.
How can we explain the rise of such large-scale societies? Archaeologists, sociologists, and political scientists proposed a multitude of theories. But the vast majority of them can be boiled down to just two general mechanisms.
Most anthropologists and archaeologists think that the driving force has been the invention of agriculture. It made possible high population densities as well as surpluses that could be appropriated by newly emerging ruling elites. In a way, this theory suggests that once agriculture created sufficient resources for the evolution of complex societies, such societies inevitably evolved.
A different theoretical perspective, one based on cultural evolution and multilevel selection theory, disagrees. Yes, intensive agriculture is a necessary condition for the evolution of complex societies. But it is not enough. Institutions of complex societies, such as bureaucracies, organized religion, and constraints on the ruling elites, which induce them to promote common good, are all costly. How can they evolve in spite of such costs? The theory of cultural multilevel selection says that this evolution is only possible when societies compete against each other, so that those that do not have the right institutions fail. Costly institutions of complex societies are spread because societies that have them destroy societies without them.
This may sound quite abstract, but it is actually possible to take this general theory and build a specific and detailed model that predicts where and when complex large-scale societies should arise, and how they spread during the Ancient and Medieval eras of human history. This is what we have done in a paper that was published today in the prestigious journal, Proceedings of the National Academy of Science.
The trick is to focus on factors that intensify intersocietal competition, which until very recently meant military competition.
In other words, warfare.
And between 1500 BC and 1500 AD the intensity of military competition in the Old World maps extremely well on the spread of military technologies based on warhorses. So we built a model around this factor, and it did an incredibly good job of predicting when and where large empires arose in Eurasia and Africa.
Here’s a press release that explains our model, written by Catherine Crawley of the National Institute for Mathematical and Biological Synthesis.
Math explains history: Simulation accurately captures the evolution of ancient complex societies
The question of how human societies evolve from small groups to the huge, anonymous and complex societies of today has been answered mathematically, accurately matching the historical record on the emergence of complex states in the ancient world.
Intense warfare is the evolutionary driver of large complex societies, according to new research from a trans-disciplinary team at the University of Connecticut, University of Exeter, and the National Institute for Mathematical and Biological Synthesis (NIMBioS) that appears this week as an open-access article in the journal Proceedings of the National Academy of Sciences.
The study’s cultural evolutionary model predicts where and when the largest-scale complex societies arose in human history.
Simulated within a realistic landscape of the Afro-Eurasian landmass during 1,500 BC to 1,500 AD, the mathematical model was tested against the historical record. During the time period, horse-related military innovations, such as chariots and cavalry, dominated warfare within Afro-Eurasia. Geography also mattered, as nomads living in the Eurasian Steppe influenced nearby agrarian societies, thereby spreading intense forms of offensive warfare out from the steppe belt. On the other hand, rugged terrain inhibited offensive warfare.
The study focuses on the interaction of ecology and geography as well as the spread of military innovations and predicts that selection for ultra-social institutions that allow for cooperation in huge groups of genetically unrelated individuals and prevent large-scale complex states from splitting apart, is greater where warfare is more intense.
While existing theories on why there is so much variation in the ability of different human populations to construct viable states are usually formulated verbally, by contrast, the authors’ work leads to sharply defined quantitative predictions, which can be tested empirically.
The model-predicted spread of large-scale societies was very similar to the observed one; the model was able to explain two-thirds of the variation in determining the rise of large-scale societies.
“What’s so exciting about this area of research is that instead of just telling stories or describing what occurred, we can now explain general historical patterns with quantitative accuracy. Explaining historical events helps us better understand the present, and ultimately may help us  predict the future,” said the study’s co-author Sergey Gavrilets, NIMBioS director for scientific activities.
Citation: Turchin P, Currie T, Turner E, Gavrilets S. 2013. War, space, and the evolution of Old World complex societies. PNAS.

Watch the movie by co-author Tom Currie showing model-predicted dynamics and actual historical data side by side.

Sticking My Neck Out

Posted on August 31, 2013 by

When 15 years ago I started working within the scientific discipline that eventually became Cliodynamics, my initial plan was to concentrate entirely on past societies. Of course, history doesn’t end in, say, 1800. But there are dangers in pushing a historical analysis all the way to the present day. First, we are too close to the societies we live in. It’s hard to imagine, for example, that the American empire might collapse tomorrow. I am not saying it will, but I imagine ancient Romans also did not think that the Roman Empire would collapse around their ears. Yet it did. In any case, it is hard to be a dispassionate analyst when you are analyzing something that will have a huge effect on your personal life.
The second danger is politics. Few people really care about why the Roman Empire collapsed. But any conclusions you reach about our own society are certain to tick off either conservatives, or liberals (and sometimes both).
So for many years I went happily refining my ideas, models, and empirical analyses of pre-industrial societies. But when I started giving talks about the decline and collapse of historical empires, I would almost invariably be asked, “so where are we?”
Eventually, I broke down and started a project on the cliodynamics of the American republic, beginning with its inception around 1780 and to the present day.
This project took more years than I thought. Partly it was for a good reason – there are much, much more data on America, even for the earlier historical periods than I was used to when I worked on long-term cycles (‘secular cycles’) in pre-industrial England, France, Russia, and Rome.
But also I have been mindful of how the results would be interpreted, so I wanted to make sure that I’d do the best job I can. I am not near that point, by any means, but the project has reached the stage where I need feedback to move forward.
Yesterday I posted on my Cliodynamics site a draft which will eventually be developed into a book describing the results. I welcome comments and suggestions on all aspects of it.
A fair warning: it’s not going to be a popular book. On the contrary, the text is very dense and there are lots of graphs and tables (and equations). This draft also needs a lot of work. But even after the book is finished, it will not be intended for most readers of this blog. Think of it as the foundations on which I will later base more popular articles or, perhaps, a book.
sticking-my-neck-out-illustration-by-baggelboy-360x540Illustration by Baggelboy. Source
Actually, I am planning to blog about some of the most striking findings in near future, so stay tuned.
But let me talk briefly about one general result right away. Things are changing in America, and there is a lot of discussion of various trends. Some commentators talk about the growing inequality and the hollowing out of the middle class. Others wonder why political polarization is reaching extreme levels and why the national government is becoming increasingly dysfunctional. Yet others debate the causes of waning social capital and cooperation.
Usually all these, and many other trends (why fewer young adults marry? Why is the distribution of law school graduates’ salaries bimodal – yes, it is!) are discussed in isolation from each other. Or, perhaps, some of them are connected, but in a cursory way. This will sound hubristic, but the structural-demographic model (the theoretical engine driving the American project) says these trends are not developing separately from each other. They are, rather, all parts of the dynamical system that is our society. There are deep, subterranean processes that explain these trends. They also explain why the trends all date from roughly the 1970s. Much of the book is devoted to tracing out these deep interconnections.
But enough of this introduction, and I am looking forward to exploring some of these interconnections in future blogs.
Again, all comments and suggestions are welcome (this is why I am posting this unfinished product, after all). You can leave comments here on the SEF or send me an e-mail.
PDF of the book draft here
Notes on the Margin: I will be off the grid for several days, because my wife and I are moving to Denmark where I took a visiting professorship at Aarhus University. So there will be a short break from blogging while we are making the transition and getting set up there.

Ibn Khaldun on the Rise and Decline of Corporate Empires

Posted on August 26, 2013 by

Paul Krugman has written two blogs about Ibn Khaldun this weekend (and also said some kind words about my research). Readers of this blog know that I hold Ibn Khaldun in great esteem (see this blog, for example).
Ibn Khaldun’s greatest contribution is the development of a theory of collective solidarity/social cooperation, for which he uses the Arabic term `asabiyyah (which I usually simplify to asabiya). In this he is very different from such great European thinkers as Machiavelli, Hobbs, Hume, and Adam Smith, whose great contributions eventually led to the Rational Choice Theory (and the dead end of homo economicus in its most primitive form). Yes, I know that those political philosophers were much more subtle than they are often given credit for; yet the fact is that by the second half of the twentieth century a very flawed model of human nature reigned supreme in economics. Economists and many other social scientists seemingly took to heart David Hume’s famous pronouncement:
Political writers established it as a maxim, that, in contriving any system of government … every man ought to be supposed to be a knave and to have no other end, in all his actions, than his private interest.
This is very wrong. It is, in fact, impossible to build a working society if all its members are selfish rational agents (or “knaves” in Hume’s wonderful characterization). Selfish agents will not cohere in a functional society – this I believe can be elevated to the First Law of Sociology.
Ibn Khaldun knew this and he devoted his book to developing a theory of the origins of social cooperation/asabiya, and mechanisms responsible for its loss. I won’t repeat myself here, because I devoted a big chunk of my popular book War and Peace and War to discussing Ibn Khaldun’s theory. In other writings I have modeled the dynamics of asabiya waxing and waning, loosely based on the ideas of Ibn Khaldun.
My models were focused on understanding the rise and fall of states and empires. What is interesting is that a very similar kind of model can be developed for the rise and fall of business firms. (In particular, Rob Axtell, with whom I have periodically interacted in Santa Fe and elsewhere, developed such models that are very similar in spirit to my models on political cycles). In fact, I believe Paul Krugman is completely right in bringing up Ibn Khaldun when thinking about the decline of Microsoft. However, I would develop this idea a bit further.
Both states and corporations are, at some fundamental level, cooperative enterprises. Yes, political elites and corporate managers are motivated by personal gain, power, status, and prestige. And that even can be the majority of their motivations. But in addition there has to be something else, at least some of these elites (whether political or economic) some of the time must behave in a cooperative prosocial manner, that is, putting the common interest of their state or corporation above their private interests. When they stop doing that, states crumble and corporations go bankrupt.
So here is a simple model that I have in mind for explaining the rise and fall of mighty corporations, which is heavily influenced by the ideas of Ibn Khaldun, Rob Axtell, and Pete Richerson (on institutions) and mine own on the empires. (Also, Rob’s model, which he has published, is well worth checking out).
In the beginning we start with small groups of entrepreneurs randomly thrown together by chance. The vast majority of these incipient firms fail. Most of these groups will contain uncooperative selfish knaves. All such groups will fail with 100% probability; only groups consisting entirely of cooperators have a chance. However, the majority of such potentially cooperative groups will still fail because they will be unable to hit upon the right combination of social norms and institutions to enable them to cooperate effectively. As an example, people coming from different ethnic backgrounds often find it difficult to concert a cooperative action, simply because different cultures evolved different ways of cooperating, and these may not work well when thrown together.
In the next step, the majority of even those groups that consist of cooperators and have acquired effective cooperative institutions will fail – because they don’t have the right product, or perhaps because they are simply unlucky. But at least they have a chance, whereas groups with knaves and lacking the right institutions have no chance at all.
This is a typical cultural evolution scenario. At this stage we have a lot of variation, with all kinds of incipient firms churned out, and a selection mechanism that weeds the ones that don’t cut the mustard. This is completely analogous to the Ibn Khaldun situation of the stateless ‘desert’ where groups that can’t cooperate together in defense (and predation on other groups!) are rapidly eliminated.
Only those Bedouin groups that wield a lot of asabiya survive and thrive in the competitive desert. Analogously, only those start-ups that have a lot of – well, asabiya – survive and thrive in the competitive markets.
So that’s how high asabiya firms are generated. What happens next? Next they need to expand without losing asabiya. That means that they need to be very picky about accepting new members (keep those knaves out) and have another set of institutions that would allow them to assimilate newbies to the firm’s social norms of cooperation. If they surmount this challenge, they will expand and become a huge corporation.
But eventually the rot sets in. More and more knaves weasel their way in. The institutions that sustained cooperation begin to be undermined by the selfish behavior of freeriders. Moralistic cooperators, in response, withdraw their cooperation, because they don’t want to be taken advantage of. Prosocial founders and early joiners leave the company and join more cooperative ones, or start new businesses.
Eventually knaves reign and the company is really moribund. However, it’s big and has a lot of inertia and so it survives – for a while. Then, however, a particularly greedy set of executives, or a market downturn, exposes its inherent weakness and the corporation goes under. You can substitute ‘executives’ with the ‘elites’ and ‘corporation’ with ‘empire’ and you have the gist of my theory of why empires collapse (however, the time scale on which firms rise and fall is much faster than that for empires).
And that’s how I see the fall and decline of imperial corporations, when looked though the lens of Ibn Khaldun’s theory. I won’t name names, but I am sure we all can think of a number of examples of such moribund corporations.

An Imperfect Time Machine

Posted on August 20, 2013 by

In the previous blog, I asked why some nations are wealthy, stable, and happy, and others are not. Many theories have tried to provide an answer to this question. How do we decide which of the competing theories is true? So far, economists have not done a compelling job addressing this issue.
Let’s take Why Nations Fail, one of the best recent books by economists (or, rather, by an economist Daron Acemoglu and a political scientist James Robinson) that tackles this question. In his review in Cliodynamics Tom Currie notes that there are “two problems with A&R’s analysis as it currently stands: 1) The descriptive, case study approach adopted here makes the systematic appraisal of alternative hypotheses difficult, 2) The focus on historical contingency of the development of certain types of institutions overlooks or down-plays more general patterns about where and when these institutions have tended to develop.”
I think this criticism is fair. However, it is equally true that we simply lack appropriate data to test rival theories about the deep roots of economic development. Consider another article in the current issue of Cliodynamics, “Was Wealth Really Determined in 8000 BCE, 1000 BCE, 0 CE, or Even 1500 CE?” by William Thompson and Kentaro Sakuwa.
As these authors point out, previous empirical analyses have been plagued by a variety of problems. One is the use of modern states as geographical units, even though they may have little relation to historically appropriate units of analysis. Think of the USSR, for example – a very inconvenient unit of analysis for any historical period before 1700, when the Russian Empire emerged as a Great Power.
Another problem is how to deal with time. Some authors look at what was the situation 10,000 years ago, at the dawn of agriculture. From there they jump to 1500 BC (the Bronze Age), then to 1 AD (a pretty arbitrary date), to 1500 AD (the ‘dawn of modernity’), and finally to the present. Other analyses use different time jumps.
It’s like we have a faulty time machine. Ideally we’d like to jump back in time to the beginning of things, and then trace how they developed. So, for example, we would jump to the Fertile Crescent 10,000 years ago, and then travel forward in one century leaps, recording how everything changes. It would be like Sid Meyer’s game of Civilization, except for real. “Oh, they invented Monotheism”. “Aha, now they have Bureaucracy.”
Instead of this, eminently sensible approach, we have to endure jumps of random duration that land us in periods that may not be of critical importance to the understanding of questions we want to answer. And we pass over a lot of history between the jumps (from 8,000 BC to 1500 BC? Weren’t there a lot of interesting developments in between that we’d like to see?).
OK, enough of this analogy. We don’t have a time machine, so much the worse.
Except that we do, an imperfect and, at times, an exasperating version, but it does allow us to peek back in the past. Thousands of historians and archaeologists collectively can tell us a lot about the past – not everything, but if we could somehow put all their knowledge together, it would provide a very rich historical tapestry, which, I am sure, would allow us to reject a lot of theories – and build better, new and improved ones.
This is what’s most galling – the data that we need to test theories are there. Some of it is scattered over a multitude of published and unpublished articles. But most simply resides in the brains of historians or archaeologists specializing on particular regions and epochs. The only way to make these data useful (for a systematic testing of theories, that is) is to translate/transcribe them from human brains onto electronic, computer-readable media.
Can Seshat, the Egyptian goddess of knowledge and scribing, help us to transcribe what is known about human history onto electronic media? Source
As I wrote in previous blogs (e.g., here), one of my current (and probably the most important) projects is Seshat: Global History Databank. So today I cannot answer the questions with which I started this blog. But give us a few years. Once we can trace how agricultural innovations and new ways of organizing polity, society, and economy arose and spread, we will be able to have a much better idea why some nations are rich, and others are poor.

The Deep Roots of Economic Development

Posted on August 15, 2013 by
Economics lately, since the ‘Great Recession’, has been getting a lot of beating. So it’s not unusual nowadays to see titles such as “Is Economics Dead?” or “The Death of Economics.”
I am not one to join in this Economics-bashing. Yes, there are lots of problems – much sterile mathematical theory in Economics, an over-reliance on equilibrium models, and a tendency to treat people as ‘homo economicuses’ (yes, I know it should be something like homines oeconomici, but we are not purists here). On the other hand, Economics was the first social science to become thoroughly mathematized. Also, in the last decade or two Economics has been reinventing itself. One only needs to point to Behavioral Economics and to Evolutionary Economics (in fact, I am going to an Evolutionary Economics conference in September – stay tuned for a report to appear on this blog).
These developments are mostly taking place within the academic science, however, and have not yet impressed themselves on popular consciousness. For example,  Freakonomics, probably the most popular recent book about Economics, stays resolutely within the classical paradigm.
A standard approach that treats people as homines oeconomici perhaps can be useful in asking some questions, but the realm of application is a very limited one.
For example, Freakonomics promises to answer such questions as:
Which is more dangerous, a gun or a swimming pool? What do schoolteachers and sumo wrestlers have in common? Why do drug dealers still live with their moms? (from the blurb on the Amazon)
My response is, who cares? Is this really the “hidden side of everything”? Why don’t you explain to me why some nations are rich and some are poor? And, even more pressingly, why some rich nations suddenly become poorer, and vice versa? How can we get out of the economic doldrums we have been stuck in for the last few years? For that matter, how can Japan, or southern Europe (which are in much worse shape) get out from the hole they are currently in? Freakonomics does not even attempt to answer such questions – because if you are stuck with the traditional approach, you can’t.
Understanding economic growth is, of course, the Holy Grail of Economics. Except you can’t do it with a purely economic approach – this has become quite clear in the last few years. You need other social sciences and, perhaps, even biological ones (especially if some current claims that there is a genetic component to economic development are true, something I am rather skeptical of). I would argue that you need something like Cliodynamics to answer this question. In particular, because evidence accumulates that modern economic development has deep historical roots.
There is no question that today there is a staggering degree of variation in economic performance and effectiveness of governance among nations. Understanding the causes of these disparities is one of the greatest intellectual puzzles in the social sciences, and one of the most pressing problems for economic policy.
We have pretty good idea of who are the winners and who are the losers (and I am not just talking about GDP per capita; human quality of life is a much more multidimensional quantity than that). But why are some nations wealthy, happy, and politically stable, while others are poor, miserable, and in the state of constant civil war? That is very much in dispute.
In answering this question, at first economists emphasized capital accumulation and technological progress; then, personal incentives and specific policies. In more recent years, the attention has moved to the institutional framework. Daron Acemoglu and James Robinson, for example, have been arguing that economic growth can only be made possible by developing inclusive institutions enabling broad sections of the population to participate in economic and political activities (see a review of their book, Why Nations Fail, by Tom Currie in the last issue of Cliodynamics).
Others think that there is a direct effect of geography on economic growth, focusing on such mechanisms as disease burdens. For example, Jeffrey Sachs and co-authors have pointed to a striking correlation between malaria and poverty. Another ‘geographic determinist’ (unlike most, I don’t think that this is a pejorative term), Jared Diamond, thinks that biogeographic conditions affect current wealth indirectly. The more time has elapsed since the agricultural revolution in a region, the wealthier the region is likely to be.
On the other hand, economists, such as Enrico Spolaore and Romain Wacziarg, make a strong case that it is not the geographic region that is of key importance. Rather, it is the ancestral composition of current populations. An even more extreme idea is the one by Oded Galor and Quamrul Ashraf, who recently concluded that countries with intermediate levels of genetic diversity, such as the United States, have the most productive economies (see this News Feature in Nature).
So we have lots of explanations of why some nations are rich and others poor. They invoke a variety of factors: economic, sociological, geographical, and even genetic. How do we decide which of the competing theories is true?


Cliodynamics: The Journal of Theoretical and Mathematical History

‘Cliodynamics’ is a transdisciplinary area of research integrating historical macrosociology, economic history/cliometrics, mathematical modeling of long-term social processes, and the construction and analysis of historical databases. Cliodynamics: The Journal of Theoretical and Mathematical History is an international peer-reviewed web-based/free-access journal that will publish original articles advancing the state of theoretical knowledge in this discipline. ‘Theory’ in the broadest sense includes general principles that explain the functioning and dynamics of historical societies and models, usually formulated as mathematical equations or computer algorithms. It also has empirical content that deals with discovering general empirical patterns, determining empirical adequacy of key assumptions made by models, and testing theoretical predictions with the data from actual historical societies. A mature, or ‘developed theory,’ thus, integrates models with data; the main goal of Cliodynamics is to facilitate progress towards such theory in history.
Submission of both empirical and modeling articles is encouraged. We are particularly interested in articles that combine model development with empirical tests. However, the journal will also publish empirical papers that make explicit connections to general theories and modeling papers that are motivated by empirically observed patterns. Additionally, we publish databases (especially those focusing on time-series data) that can serve as testbeds for theories, methodological articles relevant to the issues described above, and critical commentaries on articles published in the journal and on general issues in theoretical and quantitative history.
Most accepted manuscripts are published as articles (12,000 words or less). In addition, we will consider shorter reports (a maximum of 3,000 words and four figures or tables). Occasionally we publish forum articles (12,000 words or less) reporting on a substantial advance in cliodynamics, which will be accompanied by several shorter commentaries/critiques (1,000 words each). All word limits are strictly enforced; however, an article can be linked to on-line Supporting Information, which is not limited in size. We solicit proposals for book reviews and meeting reviews, and proposals for special journal issues devoted to a particular topic.
Note on printing articles: Journal pages have been formatted in such a way that two of them fit precisely on a regular (either American, or European) sheet of paper. Thus, to print a hard copy (1) download the PDF, (2) drop the cover page, supplied automatically by eScholarship, and (3) instruct your printer to print the rest as two pages side by side.

Volume 3, Issue 2, 2012

Editor's Column

Introducing a New Section—Databases
Turchin, Peter


Evolutionary Decomposition and the Mechanisms of Cultural Change
Beheim, Bret A; Baldini, Ryan
Endogenous Population and Resource Cycles in Historical Hunter-Gatherer Economies
Szulga, Radek Szymon


A Historical Database of Sociocultural Evolution
Turchin, Peter; Whitehouse, Harvey; Francois, Pieter; Slingerland, Edward; Collard, Mark
Seeing the Forest of Secular Cycles
Sirag, Jr., David J

Book Reviews

Multicultural vs. Post-Multicultural World History: A Review Essay
Hewson, Martin
Comparative Archaeology: The Camel’s Nose?
Kohler, Timothy A.
State Formation in Hawai’i
Smith, Michael E.

Social Evolution Forum

Networking Past and Present
Dunbar, R.I.M.; Baumard, Nicolas; Hamilton, Marcus J.; Hooper, Paul; Finkel, Daniel N.; Gintis, Herbert

Volume 3, Issue 1, 2012

Editor's Column

The Special Issue on Failed States and Nation-Building
Turchin, Peter; Coon, Carleton; Wilson, David Sloan


Processes Too Complicated to Explain
Coon, Carleton
The Evolution of War
Morris, Ian
Tribal Social Instincts and the Cultural Evolution of Institutions to Solve Collective Action Problems
Richerson, Peter; Henrich, Joe
Prosociality, Federalism, and Cultural Evolution
Bednar, Jenna
Centralization/Decentralization in the Dynamics of Afghan History
Barfield, Thomas
The Taliban's Adaptation 2002-11: a Case of Evolution?
Giustozzi, Antonio
State and Socio-Political Crises in the Process of Modernization
Grinin, Leonid
Failed States and Nation-Building: A Cultural Evolutionary Perspective
Turchin, Peter

Social Evolution Forum

The Evolution of Human Cooperation
Gintis, Herbert; Doebeli, Michael; Flack, Jessica
The Peacock’s Tale: Lessons from Evolution for Effective Signaling in International Politics
Blumstein, Daniel T.; Atran, Scott; Field, Scott; Hochberg, Michael; Johnson, Dominic; Sagarin, Raphael et al.

Volume 2, Issue 2, 2011

Editor's Column

Introducing the Social Evolution Forum
Turchin, Peter; Hochberg, Michael E


The Roman Dominate from the Perspective of Demographic-Structural Theory
Baker, David C
War Games: Simulating Collins’ Theory of Battle Victory
Fletcher, Jesse B; Apkarian, Jacob; Roberts, Anthony; Lawrence, Kirk; Chase-Dunn, Christopher; Hanneman, Robert A
A Trap At The Escape From The Trap? Demographic-Structural Factors of Political Instability in Modern Africa and West Asia
Korotayev, Andrey; Zinkina, Julia; Kobzeva, Svetlana; Bozhevolnov, Justislav; Khaltourina, Daria; Malkov, Artemy et al.

Book Reviews

How Big Should Historians Think? A Review Essay on Why the West Rules—For Now by Ian Morris
Pomerantz, Kenneth
Expansion Cycles in Competitive Systems: A Review of Expansions by Axel Kristinsson
Christian, David
Middle Range Theory: A Review of The Origins of Political Order by Francis Fukuyama
Manning, Joseph G
Science or Ideology? A Review of The Archaeology of Politics and Power by Charles Maisels
Blanton, Richard E

Social Evolution Forum

Institutional Rigidity and Evolutionary Theory: Trapped on a Local Maximum
Lustick, Ian S; Nettle, Daniel; Wilson, David Sloan; Kokko, Hanna; Thayer, Bradley A

Volume 2, Issue 1, 2011

An Inquiry into History, Big History, and Metahistory
Krakauer, David; Gaddis, John L; Pomeranz, Kenneth L


A Single Historical Continuum
Christian, David
A Paleontological Look at History
Erwin, Douglas H
War, Peace, and Everything: Thoughts on Tolstoy
Gaddis, John L
Regularities in Human Affairs
Gell-Mann, Murray
Meta-History’s Dangerous Dream
Harpham, Geoffrey G
The Star Gazer and the Flesh Eater: Elements of a Theory of Metahistory
Krakauer, David C
Homogeneity, Heterogeneity, Pigs and Pandas in Human History
McNeill, John R
Labeling and Analyzing Historical Phenomena: Some Preliminary Challenges
Pomeranz, Kenneth L
Complexity in Big History
Spier, Fred
Toward Cliodynamics – an Analytical, Predictive Science of History
Turchin, Peter
A Historical Conspiracy: Competition, Opportunity, and the Emergence of Direction in History
Vermeij, Geerat J
Can there be a Quantitative Theory for the History of Life and Society?
West, Geoffrey B

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