The economic and geographic environments of cities

Just like plants and animals, cities compete with each other and attempt to take advantage of the local environment in which they find themselves. Some cities are founded on oceans or rivers, others on plains, mountains, deserts or at the crossroads of trade networks. Yet, just like any organism that may find begin itself in an advantageous environment one day and find its environment transformed the next, the fundamental geographic advantages of cities can shift.

Guy Michaels and Ferdinand Rauch examined the shifting fortunes of cities in Europe as Empires ebbed and flowed:

Around the dawn of the first millennium Rome conquered and subsequently urbanised areas, including those that make up present-day France and Britain (as far north as Hadrian’s Wall). Under the Romans, towns in France and Britain developed similarly in terms of their institutions, organisation, and size. Around the middle of the fourth century, however, their fates diverged.

Roman Britain suffered invasions, usurpations, and reprisals against its elite. Around 410CE, when Rome itself was first sacked, Roman Britain’s last remaining legions, which had maintained order and security, departed permanently. Consequently, Roman Britain’s political, social, and economic order collapsed. From 450-600CE, its towns no longer functioned. The Roman towns in France also suffered when the western Roman Empire fell, but many of them survived and were taken over by the Franks.

…Medieval towns in France were much more likely to be located near Roman towns than their British counterparts (Figure 1). These differences in persistence are still visible today: only three of the 20 largest cities in Britain are located near the site of Roman towns, compared to 16 in France.

Cities exhibit a ‘path dependence’, where their fortune is linked to the experience of their specific history. Of course, they can impact their own environment in ways that can manifest physically – such as through the building of canals – or the establishment of trade networks and specialization. They can even spawn the growth of nearby towns to create their own trading microenvironments.

How trade develops: thinking in terms of “we”

This is an absolutely fantastic classroom experiment by Bart Wilson:

In the traditional market experiment, the experimenters explain to the participants how to trade. For this experiment that seemed more than a little heavy handed if the question is, what is the process by which exchange “gives occasion,” as Adam Smith says, to discovering the “division of labour”? …Thus the first requirement in building the design was that participants would have to discover specialization and exchange…

The participants choose how much of their daily production time they would like to allocate to producing red and blue items in their field. They are then told, deliberately in the passive voice, that “you earn cash based upon the number of red and blue items that have been moved to your house.” What they have to discover is that not only can they move items to their own house, but that they can move items to other people’s houses…

At one extreme, the economy achieves 88% of the possible wealth above self-sufficiency by the last day[.] And at the other extreme, only 6% of the possible wealth above autarky is realized[…] Why the disparity? These students are immediately engaging their counterparts as part of an inclusive “we”. The same is not true in group 4 [which achieved less wealth].

He then goes into detail on the words and mode of thinking that different groups used to develop the idea of trade and markets. The conclusion is that the development of trade and specialization arises from considering the group and not the individual. And this is in a capitalist society! It is not to say that the only way for trade and specialization to develop is a kind of group-consciousness, and it is not to say that it wouldn’t have developed anyway. But it’s a bit of evidence that it can foster the conditions that make mutually beneficial trade networks increasingly likely.

As a second experiment, I would be interested in how quickly students familiar with the idea and the mathematics would find the optimal solution, and how it would evolve in a ‘noisy’ environment. I’d really like to see more advanced analyses of the text as well, the communication networks that evolve, and how they coordinate the development of the intellectual idea. Is there a tipping point? Is it a steady accumulation towards the optimum? Are there ‘laggards’ that are unconvinced?

But this is a great experiment and a great teacher.