Measuring Regenerative Economics: 10 principles and measures undergirding systemic economic health

Fath B ORCID: https://orcid.org/0000-0001-9440-6842, Fiscus D, Goerner S, Berea A, & Ulanowicz R (2019). Measuring Regenerative Economics: 10 principles and measures undergirding systemic economic health. Global Transitions 1: 15-27. DOI:10.1016/j.glt.2019.02.002.

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Abstract

Applying network science concepts and methods to economic systems is not a new idea. In the last few decades, however, advances in non-equilibrium thermodynamics (i.e., self-organizing, open, dissipative, far-from-equilibrium systems), and nonlinear dynamics, network science, information theory, and other mathematical approaches to complex systems have produced a new set of concepts and methods, which are powerful for understanding and predicting behavior in socio-economic systems. In several previous papers, for example, we used research from the new Energy Network Science (ENS) to show how and why systemic ecological and economic health requires a balance of efficiency and resilience be maintained within a particular a “window of vitality”. The current paper outlines the logic behind 10 principles of systemic, socio-economic health and the quantitative measures that go with them. Our particular focus is on “regenerative aspects”, i.e., the self-feeding, self-renewal, and adaptive learning processes that natural systems use to nourish their capacity to thrive for long periods of time. In socio-economic systems, we demonstrate how regenerative economics requires regular investment in human, social, natural, and physical capital. Taken as a whole, we propose these 10 metrics represent a new capacity to understand, and set better policy for solving, the entangled systemic suite of social, environmental, and economic problems now faced in industrial cultures.

Item Type: Article
Uncontrolled Keywords: regenerative economics; resilience; economic networks; self-organization; autocatalysis; socio-ecological systems; network analysis
Research Programs: Advanced Systems Analysis (ASA)
Depositing User: Luke Kirwan
Date Deposited: 26 Mar 2019 09:41
Last Modified: 15 May 2019 09:12
URI: http://pure.iiasa.ac.at/15814

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