How Should We Study Prehistoric Economy?


TÓTH Peter

Year of publication 2019
Type Appeared in Conference without Proceedings
MU Faculty or unit

Faculty of Arts

Description According to Ian Hodder (1982) there are three basic approaches in analyses of human economic behavior in the past: substantivism, formalism, and social exchange. The substantivists tends to focus on relationships between people and on the different types of exchange mechanisms such as reciprocity, redistribution, and market systems. The formalism focuses on analytical techniques that would allow particular modes of distribution to be identified (e.g. regression analyses), assuming that universal concepts of economic theory- scarcity, maximization, surplus- are applicable in economic anthropology. Finally, social exchange studies, mixing a both of both formalism and substativism, involves social strategies, and functional interrelationships, such as the availability of resources, and control over production. Formal mathematical approaches to the study of prehistoric exchange are of value in that they allow a better description of functional relationships. In this presentation, I discuss spatiotemporal modeling as a method of choice able to interconnect social and economic processes of larger territories. Spatial-temporal modelling relates to problems where we want to analyze and predict how something varies over space and/or time. Such problems can exist in widely different spatial and temporal scales. It is based on a gradual transformation of relative dating of archaeological sites into a temporal scale. As a result, each site has assigned a temporal uncertainty in a predefined temporal block. The transformed datasets can be used for more advanced analysis, such as an investigation of cultural, social and economic processes as well as a comparison of settlement dynamics by interpolation of temporal uncertainty. This background can be also used in subsequent agent-based modeling. For archaeologists, the combination of spatiotemporal modeling and agent-based modeling can be very useful, because we can simulate and observe human behavior in changing social, economic, environmental and cultural conditions across space and time.
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