Human wealth evolution is an accelerating expansion underpinned by a decelerating optimization process
Paolo Sibani, Steen Rasmussen, Per Lyngs Hansen

TL;DR
This paper analyzes 8 centuries of European GDP data, revealing that wealth evolution, when measured by human interaction intensity, follows a decelerating pattern characterized by two logarithmic regimes and a crossover linked to technological revolutions.
Contribution
It introduces a novel approach replacing time with human interaction intensity to study wealth evolution, uncovering decelerating growth patterns and connecting them to technological and societal changes.
Findings
GDP growth shows two decelerating logarithmic regimes
A power-law crossover period links the regimes
Technological revolutions mark the transition points
Abstract
Optimization and expansion are two modes of staged evolution of complex systems where macroscopic observables change at a decreasing, respectively increasing, rate. A prime example of evolutionary expansion, Gross Domestic Product (GDP) time series gauge economic activities in changing societal structures,} and the accelerating trend of their growth probably reflects a manyfold increase of the human interactions that drive change. We show how optimization and expansion can coexist by replacing `wall clock time' as independent variable with a measure of human interactions intensity . Our analysis of eight centuries of yearly GDP data from three regions of Western Europe is carried out in two steps. First, a Monte Carlo algorithm is used to fit the GDP data to a piecewise continuous function comprising a sequence of exponentials with different exponents. In a second step,…
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Taxonomy
TopicsComplex Systems and Time Series Analysis
