Introducing nonlinear and non-equilibrium perspectives into ecological economics

from Ping Chen and RWER issue 107

Economic Complexity vs. Neoclassical Simplicity

Complexity science originated from astrophysics when Henri Poincaré discovered the three-body problem had no analytical solution in 1899. The discovery and development of deterministic chaos in the 1960s to 1990s found wide evidence that nonlinear deterministic systems only have limited predictability. Ilya Prigogine further recognized the important role of irreversibility in biological evolution since time’s arrow and history inherent to biological evolution works against thermodynamics equilibrium. In reality, non-stationarity is dominant in time series economics but absent in controlled experiments in physics and biology. In this sense economic complexity is more complex than physics and biology. In any case, the study of economic complexity reveals the fundamental flaws of neoclassical simplicity in three ways (Chen 2019, 2024).

First, the three-body problem is radically different from a one-body, two-body, and infinite-body problem. Three and many-body problems are more complex and often without analytical solutions, while in economics the representative agent model, the two-player model in game theory and international finance, and the mean-field model in statistics are all equivalent and deficient as an equilibrium framework. For example, a two-country exchange model can calculate the exchange rate and interest rate parity, but this is not so for three or more major currencies. This is also why the option-pricing model has a fundamental flaw since it is based on a single-particle model of Brownian motion without collective behavior.

Second, nonlinear stochastic processes may have a multi-peak distribution such that high moments cannot be ignored during phase transition, and this is the root of financial crises (a point that will make more sense to readers conversant in finance). The polarized presidential election in the U.S. shows a typical polarization with dual-peak distribution, which is a sign of bifurcation at the cross-point of coming crise.

Third, nonlinear trends in macro and financial indexes are the main difficulty in macro econometrics. So-called “market expectations” can be measured by macro trends separated by medium business cycles by the HP filter (Chen 1996). Yet macro management is better aimed at frequency rather than amplitude observation, and this is often used in medical diagnosis. Furthermore, the study of economic color chaos revives Schumpeter’s view of business cycles as heartbeats.

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Basic assumptions in the linear-equilibrium formulation of neoclassical economics are essentially utopian theories based on perpetual motion machines (Chen 2024). Ecological dynamics introduces nonlinear and non-equilibrium perspectives into ecological economics. Complexity sciences develop new tools for evolutionary economics and institutional economics with structural changes and diversified development. We need a new (Popperian) philosophy of science to understand the evolutionary tree of human knowledge. For example, the neoclassical model of efficient market is a special case of calm market while financial crise is the special regime of turbulent market in the phase-transition model based on birth-death process (Tang and Chen 2015). I contend that existing mainstream and heterodox economics can be better understood as special cases in different branches of the general evolutionary tree of human history.