Tag Archives: Roman Empire

Rise to Power and the Distribution of Rule Duration of Roman Emperors

Having gotten stuck in the project that I am working on at the moment, I decided to pass the time and heal my frustrations by playing a little bit with Roman Empire Data.

What I did was to match data for the duration of the Roman Empire with a few dummy variables on how each emperor rose to power. The data being what it is, what I found is purely descriptive. It does not really add anything that is particularly new, but at least it does not contradict common sense. Moreover, it is possible that by narrowing things down a little, it may hint at those things that matter most among those things we think matter.

It turns out that a lobbying mother, inheritance and practice make for longer rules while getting to power through the support of some general makes for shorter rules.

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Correcting the Probability of Roman Emperors – Data, Empirical CDF, Exponentional Functions, Kolmogorov-Smirnov Test, Confidence Levels and Critical Values

The idea that we can use distributions to describe political systems really stuck with me. Sure, it’s not the only one way to do so, but it seems to offer a particularly interesting and unbiased approach to measuring the survival of political systems. Unfortunately, when I discussed this fact with an example of the Roman Empire, I got it wrong. Not the general conclusion. Just the detail. The way I did it was wrong… which is embarrassing. But there you go, now there’s going to be a record of how I did it wrong and how you do it right, which was kind of what I wanted to do with this blog in the first place.

The rest of this post is organised under the following headings:

  • How did I figure I was wrong?
  • I counted duration in approximate (integer) years not in days
  • I made a mistake calculating the Kolmogorov-Smirnov Test
  • Getting accurate data
  • My Final Say – Data, Procedure and Results

 If you are just interested on how it gets done, scroll through to the end, where I’ve actually posted the excel file with the correct solution to the problem.  I hope this helps and somewhat redeems my mistake.

Continue reading Correcting the Probability of Roman Emperors – Data, Empirical CDF, Exponentional Functions, Kolmogorov-Smirnov Test, Confidence Levels and Critical Values

Roman Empire Roads, New Trade Theory and the history of Europe’s Economic Core

In preparing some tutorial notes on trade and geography, I was trying to convey some of the interesting agglomeration insights of New Trade Theory and got stuck on whether I should mention the Roman Empire and its network of roads and the effect it may have had on establishing Europe’s economic core. Ultimately, I decided against it because I thought it would confuse students and because I didn’t find any reference that said that is a cause of Europe’s core. Also, this is a group of people of whom I cannot assume any prior knowledge of the Roman Empire and I might just end up confusing them. So for practicality’s sake I’ll stick to the typical examples about financial services in the City and in Wall Street and about Silicon Valley.

However, and mostly for my own sake I wanted to highlight the following two maps:

The first is a map of the EU with shades of GDP/capita by subnational economic (NUTS) regions. Notice the axis running from Flanders to northern Italy.

The second is a map of Roman Empire Roads.Notice how the darker region in the EU NUTS map coincides with the region in the northern European part of the Roman Empire that had a lot of roads, mainly connection border garrisons protecting the Rhine frontier.


Clearly, the relationship is not linear. If roads were all there was to it, Italy would have been the most developed region in Europe. I am not suggesting we ignore the remaining and very substantial developments of European economic history that took place in the intervening 15 centuries after the fall of the Western Roman Empire. Clearly, the trade integration of northern Europe, human capital development, the right policies and industrialisation conspired to make that axis even richer.

But I like to think about the Roman Empire and I would venture the guess that the overlap described above is not without its merits, tiny though they might be. One interesting thing would be to test the pervasiveness of that Flanders to Northern Italy axis throughout history. May be Angus Madison has relevant data.. ?

Oh and if you are unhappy with the amateurish nature of the map of Roman roads, or if you are just interested in such things, I would point you to the “ORBIS” project of Stanford University which has very detailed road data for the Roman Empire.

The Probability of Roman Emperors

In my previous post I discussed how I came to be interested in probabilities, after having spent about a decade (which refers to a period of time of 10 years, and is not in any way associated with decadence… O_O (12’20”) ) making use of tools that assumed or did some calculations with probabilities. I mentioned it because it was interesting for me to realise what had made me care about it and seek out to learn more and because it might be interesting for other people. Who knows, may be you are struggling to find the motivation or interest in the topic necessary to really dig down into it, like I did. In that case may be going through those same things will help you find the focus you need.

If you’ve been one of the 150 or so people who make daily visits to my other website, Place du Luxembourg, you’ll also  have heard me go on about the Roman Empire. You’ll have noticed that I posted something about the evolution of the Roman Republic towards the Empire. You may have also read in other posts that I have not been writing because I’m trying to figure out some things about the fall of the Roman Empire. I’m still working (sporadically) on a final draft of that post, which after this much time cannot possibly measure up to my expectations, but anyway, I digress…

Nevertheless, I came across some interesting facts about autocrats and their regime. As it turns out it’s a pretty accidental lifestyle, characterised by an exponential distribution. But more importantly: Why and to what effect?

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