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date: 13 July 2020

Abstract and Keywords

This chapter looks at three schools of post-Keynesian thought, dynamic/Kaleckian, Sraffian/neo-Ricardian, and uncertainty/Davidsonian, and two schools of economic complexity theory, dynamic and computational. It argues that while the origins of complexity theory in general are mathematical, with the earliest applications often in physics or biology, the earliest applications in economics for both the dynamic and computational complexity schools have come from post-Keynesian sources, with all three schools involved. Probably the deepest and most direct link between any of these is between the dynamic/Kaleckian and dynamic complexity schools. Dynamic complexity has been defined as endogenous trajectories that do not converge to a point, a limit cycle, or a simple expansion or implosion, in short some sort of more erratic pattern that may involve catastrophic discontinuities or aperiodic chaotic dynamics, among other possibilities. The Kaleckian branch of post-Keynesian economics arguably preceded even the publication of John Maynard Keynes’s General Theory of Employment, Interest and Money (1936), initiated by Michal Kalecki (1935) himself, with a “macrodynamic” model capable of generating endogenous cycles due to a nonlinear investment function.

Keywords: dynamic/Kaleckian, Sraffian/neo-Ricardian, uncertainty/Davidsonian, economic complexity theory, dynamic complexity, computational complexity, post-Keynesian economics, John Maynard Keynes, Michal Kalecki

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