Empires and the acceleration of wealth inequality in the pre-Islamic Near East

An Archaeological Approach

Dados Bibliográficos

ID5416624
AutoresA Squitieri (0000-0002-6746-944X, Heidelberg University), Mark Altaweel (0000-0003-1807-3737, Museum of London Archaeology, autor correspondente)
Ano2022
Volume14
Fascículo10
Data de publicação2022-10-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoArchaeological and Anthropological Sciences (JOURNAL)
Identificadores do periódicoISSN: 1866-9557 • E-ISSN: 1866-9565
EditoraSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s12520-022-01659-3
OpenAlexW4296111992
IdiomaEN
Citações recebidas9
Referências citadas50

We present an approach comparing wealth inequality between c. 3000 BCE and 224 CE in the Near East using house sizes and urban area from 1060 houses in 98 archaeological sites. We divide this dataset into two chronological phases, firstly c. 3000-800 BCE and secondly 800 BCE - 224 CE. The first phase is characterised by small, relatively weak states, while the second phase is characterised by major empires and large states, termed as the Age of Empire (AoE). For these two periods, inequality is measured using house size in relation to settlement scaling, and applying, in addition, the Gini and Atkinson indices on house sizes. Results demonstrate that pre-AoE houses have a lower scaling metric (β) that measures house size relative to site size (0.24), while for the AoE the value is higher (0.41). This indicates more rapid median house size expansion during the AoE as cities grew larger. For the pre-AoE, Gini and Atkinson inequality measures result in 0.45 and 0.16, respectively, while the AoE demonstrates 0.54 and 0.24 for the same measures, respectively. This demonstrates greater house size inequality in the AoE. Overall, we see that wealth inequality is not only greater in the AoE, but that increased wealth inequality has a likely power law relationship to increased settlement area. Alternative metrics to minimise data biases affecting results, including median house size and bootstrap sampling, are applied to strengthen these results and overall conclusions

Demographic economics · Econometrics · Economic inequality · Economics · Geography · Geometry · Gini coefficient · Inequality · Mathematical analysis · Scaling · Sociology · Statistics · Archaeology and ancient environmental studies · Archaeology and Rock Art Studies · Demography · Historical Economic and Social Studies · Mathematics