New Cliometrics for Ancient History
- Authors
- Publication Date
- Sep 22, 2023
- Source
- HAL-Descartes
- Keywords
- Language
- English
- License
- Unknown
- External links
Abstract
This thesis proposes to link formal economic analysis with the full detail of ancient historical sources, thereby extending traditional cliometrics, thanks to the recent develop- ments that have associated cliometrics and complexity. Most economic approaches into ancient history have remained in the field of analytic narratives, rather than cliometrics, because of a lack of data. We propose a new epistemological framework for cliometrics, relying on complexity: we argue they do not have to be about the economy, but can operate on primary historical sources, and could address a much broader set of periods and societies, leaning on microeconomic models. We focus on the case of ancient Greek history, and show we can frame into economic terms the massive and complex cultural material now available in electronic form. We then drill further down and concentrate on two particular aspects of ancient Greek society: the choice of names, and which gods to pray to. We first develop an economic model for the existence of names, as a way of exchanging identification information. We study the optimal choice of names in these conditions and show that the impact of strategic naming on the distribution of names works as an alteration of existing mean-field approaches to name dynamics. Confronting theoretical results with empirical data from the archaic and classical periods, we show conformist strategic naming may account for the particular shape of the name distribution in Ancient Greece. Finally, we look into the optimal choice of which god to worship as a function of the presumed strategy of the gods for returning favors to the worshippers, and relate it to a form of divine efficiency measure. Data from a large volume of epigraphic and literary sources on actual acts of worships from the ancient Greeks shows that the distributions of these acts effectively follow power laws with a high degree of regularity, as predicted by the model.
