Age Of Empires 3 Datap Bar Download _VERIFIED_
Meryl Uphoff
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.
While wealth and the economy have been major themes of studies on empires in the Near East, ways in which the specific organisational structures and socio-economic conditions of imperial scale polities shaped wealth inequality have been less studied. The study of wealth inequality trends and the related analysis of the unequal distribution of resources and assets in a given society has attracted much attention in socio-economic studies focusing on contemporary societies. This has also stimulated a number of studies on wealth inequality in ancient societies around the globe, intended to investigate how and when wealth inequality originated in human history, how it persisted and how variations could be accounted for (Kintigh et al. 2014; Kohler et al. 2017; Kohler and Smith 2018; Milanovic et al. 2007; Scheidel 2016). In archaeology, wealth can be observed through correlations with material forms, which often translates into correlations of wealth with physical parameters such as house size, land size and the variety of portable objects owned by individuals or households (Smith 1987), with the analysis approached by means of quantitative methods, such as Gini coefficient (Ames 2008; Smith et al. 2014; Windler and Thiele 2013; Wright 2014). This is a type of wealth that derives from accessibility to resources and services that would allow someone to accumulate specific forms of physical wealth (see also below). Wealth, archaeologically, is seen as a form of accumulated goods that are ascribed to individuals or social units and made evident through material culture. Consequently, wealth in the archaeological record is not equal to income, which is used in most studies focusing on contemporary societies as a measure of wealth; in archaeology, wealth represents the product of socio-economic and political forces that shaped the material world.
Before presenting the methods and results of this work, it is worth giving a definition of the AoE and clarifying what distinguishes it from the previous historical period (pre-AoE). The study area, shown in Fig. 1, encompasses the Levant, Mesopotamia and south-west Iran. This is the area where we observe the emergence of the first urban societies in the 4th millennium BCE and their spread across the region by the Bronze Age (c. 3000 - 1200 BCE). Moreover, this is the core area of the large territorial empires that developed in the AoE.
Size (expressed in km2) of the main pre-AoE states (blue) in comparison with the AoE empires (red). The measurements refer to the maximum expansion of the states/empires. Data sources, see Altaweel and Squitieri (2018) and Scheidel (2021)
Urban scaling analysis attempts to understand how nonlinear properties found in cities, as demonstrated through infrastructure or wealth, adjust relative to urban size or population, where change in urban features develop in a sub-linear, linear or superlinear manner relative to population (Bettencourt et al. 2020). Growth and relationships between urban features and size could be irregular, but often power law relationships could be evident across wider urban systems. As explained in detail below, urban scaling offers certain advantages compared to the use of house size alone. This method is based on numerous observations conducted by urban geographers on modern cities which have allowed researchers to establish formal mathematical relationships between urban parameters such as area, population, infrastructure features and socio-economic phenomena, such as economic growth, innovation, health care and social inequality (Bettencourt et al. 2007; Bettencourt et al. 2020; Lobo et al. 2013). In fact, Bettencourt et al. (2007) demonstrate a power law, superlinear relationship between many larger cities and multiple wealth and/or income indicators; this aspect can be tested here for the pre-AoE and AoE. In the application of this method to ancient settlements in the Americas, the Mediterranean and the Near East, power law relationships between infrastructure and urban population have been demonstrated (Altaweel and Palmisano 2019; Hanson et al. 2019; Lobo et al. 2020), though more work is needed to ascertain to what extent modern and ancient cities behave similarly. Nevertheless, previous urban scaling work, with more details given below, has shown not only that a formal relationship can be expected between a city's infrastructure and the total urban area, but it has also shown that this relationship can be ultimately connected to broader socio-economic phenomena, including wealth distribution (Ortman et al. 2015; Ortman et al. 2016). Larger cities may, for instance, enable and sustain a larger number of social interactions, where these interactions grow in given measured time. The AoE empires concerned in this paper greatly affected the Near Eastern urban landscape. Some areas experienced the emergence of very large cities such as Nineveh, Babylon, Seleucia on the Tigris, while other areas became populated by relatively small sites dispersed across the landscape (Altaweel and Squitieri 2018; Lawrence et al. 2016; Wilkinson et al. 2005). By using urban or settlement scaling, we will test the expected relationship between site size and house size, and, by comparing the pre-AoE with the AoE, we will offer results that take into account changes to both house size and site size together, providing a more robust and complete picture of the changes in wealth inequality across time. Our expected relationship is that house size, as a proxy for wealth, should have a power law relationship to site size, as demonstrated for more recent societies (Bettencourt et al. 2007; Bettencourt and Lobo 2016). The use of scaling will demonstrate if house size has a relationship to the site area and what that relationship is. As this paper covers a broad area and a long period, we are mainly interested in overall statistical trends that emerge in the analysis. As mentioned above, the imperial legacy that empires in the analysis inherited and transmitted from one to another and which emerged in recurrent imperial strategies strengthens the validity of this approach.
This work has presented an investigation of wealth inequality during the period spanning 3000 BCE to 224 CE by applying an urban scaling method as well as the Gini and Atkinson inequality indices. The goal was to compare the pre-AoE (c. 3000 - c. 800 BCE) with the AoE (c. 800 BCE - 224 CE) in order to observe the effects of large and long-lasting empires on house size in relation to site size, with the former being used as a proxy for accumulated material wealth across society. The urban scaling analysis has yielded β values of 0.28, 0.24 and 0.41 for the entire dataset, the pre-AoE and the AoE, respectively, with a higher variation for the AoE than pre-AoE. One clear result is that the obtained β values are below 1, which indicates a sub-linear relationship between house size and urban area, with values oscillating near \(^1\!\left/ \!_3\right.\). Although we use area rather than population directly, interestingly comparable values have been observed in previous studies focusing on the ratio of power law growth for urban infrastructures to urban area or population, with previous studies comparing roads, gates and squares (Altaweel et al. 2021; Hanson et al. 2019; Hanson 2020). This suggests that certain physical infrastructures within cities, including gates or roads, change at a comparable, general level relative to urban size in a manner that is also similar to house size that was measured in this work. One possible interpretation is that population growth, and consequently urban area growth, could be having a comparable effect on the growth of a variety of infrastructural features, with that growth somewhat regular in some periods and regions. In the case of houses, a variety of factors are possible, including efficiency in house size growth relative to population or limitations to house size growth as the urban area grows due to limited resource, crowding or social constraints. While the above results are worth further investigating, it is not the primary focus of the present paper.
Overall, our work has demonstrated that not only did wealth inequality increase during the AoE, relative to the pre-AoE and likely due to the effects of large empires, but wealth increases somewhat comparably to modern societies in that wealth growth has a power law relationship to urbanism. It is, therefore, worth asking how empires considered here transformed wealth inequality trends as observed in this study. As stated, one of the main characteristics of the AoE is long-term and persistent imperial control over vast portions of the Near East, in striking contrast with the more politically fragmented landscape of the pre-AoE. A durable control over vast territories conferred to empires the ability to tap into wealth-generating resources to a level that was not possible for pre-AoE states. The strategies of population migration and management that empires implemented via deportation and large resettlement programmes gave them the possibility of increasing labour supply in key sectors of their economies, such as agriculture. In addition to this, volunteer movement of private individuals was also generally evident in the AoE, facilitating labour and wealth flows to cities (Zaccagnini 1983). Agricultural productivity was also favoured by extensive irrigation programmes that, although they can be traced back to the pre-AoE and even earlier, became increasingly important and intensive during the AoE (Wilkinson and Rayne 2010). Increasing agricultural productivity meant increasing the possibility for empires to expand their expenditures via tax revenues. AoE cities could afford growing larger as they could be supplied with high quantities of agricultural products being produced by populations, often deportees or descendants thereof, working in small farm sites surrounding the cities themselves. Examples of this are the large Neo-Assyrian citadels in Assyria (northern Iraq), fed by vast irrigation infrastructures, and Babylonia (southern Mesopotamia), which experienced incremental increases in urbanisation and cultivation during most of the AoE (Jursa 2014; Van Der Spek 2007). This increasing intensity in agriculture suggests a larger population to feed, which is further supported by broader survey settlement data indicating increased population (Adams 1981).
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