Related teams & projects

Complexity: a new framework to interpret  ancient economic proxy data

Book project and conference: Sagalassos, Sept. 11-12th 2015

Organizers and editors: Jeroen Poblome (KULeuven) (), Koen Verboven (UGent) ()

No one today doubts anymore the value of archaeological data to ancient economic history. They reflect human behaviour and choice, acting out within the dimensions of landscape, natural resources, ecology and climate. However, the ‘translation’ of these data into economic indicators (such as GDP or Gini-co-efficients) remains  a huge challenge. Rather than focus on quantitative changes, increases or decreases in recorded (or recordable) data, we wish to study whether and how the data show processes that reveal the dynamics of economic systems in the Roman world.

As part of the project we will organize an open authors’ meeting in Sagalassos (Turkey), 11-12 September 2015, where we will discuss chapter drafts shared beforehand amongst the authors. 

We aim for a publication with a top academic publisher, preferably in the series Oxford Studies on the Roman Economy (Oxford University Press).


Since the early 1990’s interdisciplinary approaches within the sciences of the past have produced a variety of exciting new data on or with ramifications for our understanding of ancient economies. Ice-core samples showing air-pollution caused by mining activities, skeletal remains showing disease burdens and diets, formerly enigmatic remains now identified as mechanical parts of hydraulic and other installations or river sediment budgets revealing methods of agricultural exploitation. In addition, the incorporation of digital research strategies and tools led to the creation of Big Data collection, exploitation platforms and modelling.

Integrating these data in economic history research has profoundly changed our thinking about ancient economies. But, as usual, the data do not speak for themselves. A sherd is a sherd; add millions of them up—they still won’t talk. We can establish a diachronic shift from wheat to barley, but what does that actually mean? Exercises as these become meaningful only when the data and numbers provide a reliable proxy to measure or express levels of production, consumption, distribution, investments, changes in supply and demand, societal constellations, and/or economic organization.

So far, attempts to convert physical proxy-data from the material record into core economic data (GDP, growth rates and collapse, interdependency and integration, money-supply, consumption levels and patterns, life-expectancy and quality…) has proven frustratingly difficult. The results that have been made are either too local to allow generalization or provide only a low resolution picture, depending heavily on theoretical assumptions and comparative evidence. State of the art statistical analyses of cross-regional data, aimed to identify causality and correlation, have only just begun.

Most theoretical assumptions used so far have been derived, directly or indirectly, from mainstream economics: neo-classical, neo-institutional, and neo-malthusian models have been particularly popular. All of these to some extent rely on the assumption that economic systems spontaneously tend towards equilibrium states. Which equilibrium is ultimately achieved depends on exogenous factors, such as particular climates favouring specific crops, particular property regimes supporting private or public investment, particular demographic regimes or cultural preferences shaping demand…. All equilibria are of course vulnerable to exogenous shocks; crop failure, pandemics, war … But the conviction that the drive towards equilibrium determines how economic systems play out has been at the heart of mainstream economics since the 19th century.

This template has scored successes in explaining economic development in stable situations, when exogenous shocks are absent or mild enough to be absorbed by the system. Using the template to explain economic history, however, has proven more controversial. Part of the difficulty is that history is a succession of stochastic shocks, making it unlikely that equilibrium is ever achieved. This (damn!) reality is usually dealt with by identifying the shocks and how they affected equilibrium. For instance text-book wisdom predicts that pandemics increase the price of labour (now scarce) and decrease the price of land (now abundant). We assume that long-term strong and stable polities (such as the Roman Empire) support and are supported by resilient economic systems, capable of absorbing minor local shocks (such as crop failures) and returning to a viable equilibrium after major shocks (such as the Antonine Plague or the 3rd c. political crisis).

But, may we really assume this? Are text-book economics a reliable guide? Claiming that economic systems ‘tend’ towards equilibrium is an article of faith derived from mathematical theory, not empiry. Equilibrium models are static. Social reality is dynamic. Empirical data from real life economic systems strongly suggest that they too, like all other social systems, are dynamic. If this is true, economic systems themselves are inherently unstable. Equilibrium is not the natural (end) state of an economic system. It is a short-lived exception; a passing phase. Change itself is a prevalent structural determinant for economic and social constellations. Accordingly, the sciences of the past should turn their rationale on its head: accept change as the normal state of affairs and explain stability against that particular background.

Complexity economics is an attempt to address this gap between a model premised on irrefutable mathematical logic colliding with a reality that seems to beg for a different kind of maths. According to complexity economics, economic systems are inherently dynamic and unstable, but they are nevertheless systemic, i.e. not chaotic. They are ‘complex adaptive systems’, consisting of independent agents that interact which each other by constantly adapting themselves.

No matter which way we look at the Roman economy, complexity is arguably the word which characterizes it best. Analytical and conceptual frameworks, therefore, should be geared towards complexity. In operational terms, research projects engaging with this period should be based on collaboration and interdisciplinarity. In fact, we need an Interdisciplinarity 2.0, which no longer focuses only on specific regional or material case-studies, but which aims at developing and applying more universal tools, such as based on modelling, in order to feed higher-level synthesis. The collaboration should be as wide as possible, deepening the dialogue between history, archaeology, social sciences, and geo/bio/eco-scientific disciplines

With complexity economics, our approach of the Roman economy has the ambition to venture into the unfamiliar. In contrast to other (complex) systems, complex adaptive systems or panarchies are open and adapt to new challenges and problems. Such systems are non-linear in trajectory, not predictable in behaviour, yet self-organized in the sense that they enhance co-evolution between entities in the system, improving their performance and strengthening complexity within as well as in connection with other such systems. The properties and behaviours of complex systems cannot be attributed to any particular part, but only to the system as a whole; they are emergent. The focus on sustainability and resilience in the study of social-ecological systems and panarchies is most compatible with interdisciplinary approaches of past societal and economic development.

Presenting a selection of case-studies and conceptual studies, this volume proposes a new footing for the study of the Roman economy. It reflects an ambitious program to break new interdisciplinary ground for approaching pre-industrial societies and economies of the past. It aims to testify to the remarkable progress of the sciences of the past and claim its relevance to wider contemporary debates on sustainability and development, demonstrating the need for an improved consciousness of the importance of studying deep-time patterns of complexity and change.




Food: production and distribution

Population structures

Change, sustainability and crisis


(coming soon)


Location: Sagalassos Lodge and Spa,

Please contact  if you would like to join us.