Fitting Dynamic Regression Models to Seshat Data

Peter Turchin

21 citations0/0 files storedCliodynamics The Journal of Quantitative History and Cultural Evolution

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Language and cultural evolution Spatial and Panel Data Analysis Culture, Economy, and Development Studies

Abstract

This article presents a general statistical approach suitable for the analysis of time-resolved (time-series) cross-cultural data. The goal is to test theories about the evolutionary processes that generate cultural change. This approach allows us to investigate the effects of predictor variables (proxying for theory-suggested mechanisms), while controlling for spatial diffusion and autocorrelations due to shared cultural history (known as Galton’s Problem). It also fits autoregressive terms to account for serial correlations in the data and tests for nonlinear effects. I illustrate these ideas and methods with an analysis of processes that may influence the evolution of one component of social complexity, information systems, using the Seshat: Global History Databank . Editor's note: the link to the R scripts in the footnote on p.1 of the Supplemental Materials is now broken. Please use the following link instead: https://datadryad.org/stash/dataset/doi:10.17916/P6159W.

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References

1969Investigating Causal Relations by Econometric Models and Cross-spectral Methods 1926Elements of Physical Biology.2022The World Atlas of Language Structures Online 1986The Logic of Writing and the Organization of Society 2011The origins of political order: from prehuman times to the French Revolution 1950The Urban Revolution 1969Standard Cross-Cultural Sample 2012How Deep Are the Roots of Economic Development?

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2020An Introduction to Seshat 2024Investigating environmental effects on phonology using diachronic models 2020The two types of society: Computationally revealing recurrent social formations and their evolutionary trajectories

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