Procedural Models of Political Order: Technical Background
Algorithm design, code and replication information for building your own ancient societies
In an earlier piece, The Monopoly of Legitimate Benevolence, we put forward certain hypotheses about the way the political systems are structured. The present article presents the models we subsequently constructed to test these hypotheses. It provides only information regarding the algorithm design process, coding and replication details, with analysis of the implications being left for a separate article here. You do not need to have read the other relevant pieces to understand this one, as the key details are recapitulated here:
In Western political philosophy, the principal threat to human life comes from other humans. The development of political order is an attempt to mitigate this threat. Under such a system, the roles of leader and follower are defined by means of a simple utilitarian calculus: each individual identifies the person that constitutes the greatest threat to him and associates himself with whoever seems able to provide the most effective protection against this threat. Thus, unaffiliated weaker individuals will tend to follow the second most powerful individual in the system at any given time, as a way of hedging against the most powerful actor. The result is continual turnover at the leadership level: an aspiring leader promises protection from the greatest present threat, attracts followers, achieves dominance, gradually comes to be seen as a threat himself, and is replaced in his turn.
Because the ideas described above are so prevalent and so efficient in describing political thought in the Anglo-European sphere, it can be tempting to see in them a universal model.
In fact, this Chinese system is not merely older, but has historically enjoyed far greater prevalence. It is not unreasonable to regard the Chinese model as the default pattern of political organisation, and the Western version merely an intriguing alternative. In regions traditionally influenced by Chinese political thought, theories concerning the nature of power and the origins of the state have traditionally been based upon Spring and Autumn and Warring States era ideas of human development, which differ significantly from their Western counterparts. Rather than focusing on human threats, the earliest Chinese narratives of state formation emphasise natural risks, notably floods and famines. In these stories, the first states grew out of the incorporation of communities around individuals who had succeeded in developing new techniques in agriculture and flood defence and were willing to share their knowledge. The earliest sovereigns were innovators in farming and hydrology, whose political legitimacy was based on these skills, rather than upon their ability to protect partisans from human threats. They were described as having attracted followers through their technical inventions, with the followers submitting to their rule in exchange for the better livelihood that proximity offered. Just as in the Western model, the decision to sacrifice independence in order to be part of a community that provides significant quality-of-life benefits was a simple, utilitarian calculation.
Under such a system, a leader is the individual who can render the greatest number of people dependent upon the advantages that he can provide, and threats to his power come not from rival offers of protection, but from redistribution networks that escape his control. Thus, the defining quality of statehood is not the monopoly of legitimate violence, but the monopoly of legitimate benevolence.
While the foundations of legitimacy in Anglo-European politics have been analysed extensively via electoral studies, the Asian side of things has been studied less intensively (and where research has been conducted, such as on voting behaviour in Japan, it has generally not been tied back into any overarching political theory). The article linked above runs through some of the existing evidence for the predominance of economic legitimacy in Chinese-influenced political systems, and we have also conducted opinion polls aimed at testing the hypothesis (see here and here), however, these constitute only circumstantial evidence in favour of the idea. In order to prove it to our entire satisfaction, the only way would be to build our own simulation (or rather two, one for each system).
The idea behind this is simple: if we can model the interaction of the variables that we posit to be essential to creating the systems under consideration, the output should display the same characteristics as the real-world systems. If it does, our argument that the variables referenced are necessary and sufficient for the creation of these systems can be assumed correct. If not, we will need to begin again.
Because the Chinese system possesses a lower degree of algorithmic complexity than the Anglo-European one, we began there. Descriptions of the precise way in which this system functions varies depending on the text you consult (notably, concerning the criteria according to which resources should be distributed, something that will be covered later), but all describe the same basic set of relationships. For design purposes, we relied primarily upon the Guanzi, simply because its descriptions of of redistribution networks are among the most extensive and the most specific, but it reflects ideas that were shared by all the authors cited above, merely inflected slightly according to the political preferences of each. (For more details, see the original article.)
The idea was originally posted to Stack Exchange to solicit comments. The essential components are replicated here:
A large section of the book is about how governments should work to extract a surplus from the economy which they can redistribute to ensure the loyalty of existing followers and gain new ones. Under this system, whoever can redistribute the most wealth becomes the overall leader. However, he also has to out-compete the other individuals in the system: they are all busy trying to establish their own redistribution networks.
The result is a series of pyramid-shaped redistribution networks, both independent and nested.
These are dynamic across time and space. Gaining resources lets you acquire more followers, which in turn gives you access to more resources. There is also a random component involved: a bad harvest or a war may wipe out your resources. If one leader runs out of resources (whether as a result of a disaster or because he redistributed them too generously among his followers), he will either be supplanted by a follower or his network will collapse and its members leave to join other networks.
Modeled algorithmically, this would produce something along the following lines:
We can assume that willingness to share resources is innate.
Generosity = propensity score
An individual acquires followers as a function of both the surplus resources he possesses and his willingness to share them.
Followers[tn] = Surplus[t-1] * Generosity
It is worth noting that growth is endogenous in this model. It is a product of whatever economic growth coefficient is deemed realistic given technology and natural resources (a), as well as of the previous cycle’s surplus and the number of followers an individual has, on the basis that these constitute factors of production. (Note: I’m not interested in getting actual monetary values out of this, just modelling the relationships. I understand that if you plugged real numbers into it people would end up redistributing more than they own.)
Growth = a (Surplus[t-1] * Followers[t-1])
At T=0 the surplus enjoyed by each individual in the system must be generated randomly.
Surplus[t0] = randomly generated number
Followers generate additional resources for their leader, but they also need to be remunerated, meaning that they simultaneously deplete their leader’s resources, proportional to his generosity propensity score. A random component must also be included, as mentioned above, to account for famines, bumper crops, wars etc.
Surplus[tn] = Random Component (Surplus[t-1] + Growth) — (Followers[t-1] * Generosity)
Once these relationships have been defined, then the algorithm is relatively simple:
T1: Each individual checks the Surplus*Generosity score of the nearest individual who is not already following him. If Individual A’s SG > Individual B’s SG, then Individual B moves closer to Individual A and becomes his follower. (Note: If individual B has followers of his own, he carries them with him. Also: Followers automatically re-check their leader’s SG in every round, since he is the closest individual to them. They will leave his network to become free agents once more if his SG drops below their own.)
Otherwise, he does nothing.
T2 : Each individual’s stats (Followers, Surplus) are recalculated based on the new situation. Step 1 is repeated.
T3 : Repeat previous step
The Anglo-European model is broadly similar, with the functions that describe financial redistribution in the Chinese model standing in equally well for protection in the Anglo-European context. The major difference is that unaffiliated individuals do not search for the individual with the highest SG score, but rather the one with the second highest, on the basis that he is best equipped to protect him from the inevitable slide towards oppressive behaviour of the actor with the highest SG score.
The models are now online and can be copied/tested here:
Explore and run machine learning code with Kaggle Notebooks | Using data from europe-chinese
Explore and run machine learning code with Kaggle Notebooks | Using data from europe-chinese
 This model was covered in less detail in the original article, which focused on Chinese visions of political order. It it worth noting here, therefore, that it was inspired principally by the relationships described in Chapter IX of The Prince, which — as far as we are aware — still provides the most economical description of the phenomena available, parsimony being one of the key qualities of a good model.