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Putting the Biophysical (Back) in Economics: A Taxonomic Review of Modeling the Earth-Bound Economy

Author

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  • John Sherwood

    (Clemson University)

  • Michael Carbajales-Dale

    (Clemson University)

  • Becky Roselius Haney

    (Calvin University)

Abstract

Economists rarely model the economy as explicitly bound by earth’s ecological systems. Modeling the dynamic interactions of both human and non-human systems is admittedly a challenging task, as it requires expertise from multiple disciplines. Within the last 10 years, a wide variety of research papers have been published that include some biophysical aspects in a model of the economy. These papers all have one thing in common: the model of the economy includes physical and/or energetic exchanges, as well as monetary exchange. This theme is what defines the emerging sub-discipline of biophysical economics, BPE. BPE models of the economy originate from a variety of disciplines, and thus BPE research articles are published across a wide spectrum of academic journals. As inter-disciplinary researchers ourselves, we want to understand what BPE modeling approaches have been used so far. In this paper, we examine and classify over one hundred published articles that use biophysical models of the economy. Although BPE modeling approaches are quite varied, grouping the research by common characteristics reveals several active research areas. We highlight recent papers that are helpful examples of the most popular BPE modeling strategies. Gaps also exist. Several modeling approaches have not been used in published works yet. We identify which of those gaps could be promising avenues for future research. We conclude by suggesting which BPE modeling approach might be particularly appropriate for a variety of research questions.

Suggested Citation

  • John Sherwood & Michael Carbajales-Dale & Becky Roselius Haney, 2020. "Putting the Biophysical (Back) in Economics: A Taxonomic Review of Modeling the Earth-Bound Economy," Biophysical Economics and Resource Quality, Springer, vol. 5(1), pages 1-20, March.
    • Handle: RePEc:spr:bioerq:v:5:y:2020:i:1:d:10.1007_s41247-020-00069-0
    DOI: 10.1007/s41247-020-00069-0
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