"Not in all," he murmured with a smile.
"Time is forever dividing itself toward innumerable futures
and in one of them I am your enemy."
-Jorge Luis Borges, The Garden of Forking Path
Clouds are not spheres, mountains are not cones,
coastlines are not circles, and bark is not smooth,
nor does lightning travel in a straight line.
-Benoit Mandelbrot, The Fractal Geometry of Nature
Even after the GFC, research on business cycles still biasedly favors stochastic explanations based on RBC theory, treating shocks as driving forces and constructing microfoundations through instantaneous market clearing by omniscient agents. This ontological proposition detaches from historical time, suppresses anxieties about disappearance of markets, and eliminates the emergent process of macro patterns from network structures based on micro-interactions. Uncertainty (or volatility) is excluded, hence the economy always returns to steady state.
We need an alternative to DSGE models, one that describes the adjustment processes of macroeconomy and places the sets of feedback mechanisms at the core of macro dynamics[i]. Stability is the result of mutual conflicts between positive and negative feedbacks, thus there is no certain convergence toward equilibrium - general equilibrium is merely an ontological void, an illusion about realness. Economic path is simply the history of economy itself. The artificial construction of equilibrium should be transformed into the study of continuously alternating dynamic processes.
The non-equilibrium Tripartite Market Hierarchy allows for persistent endogenous nonlinearity and discontinuity-based ruptures, implying irreducible uncertainty and thus confirming endogenous randomness without relying on exogenous stochastic shocks. Specifically, this variant can incorporate features such as price-wage spirals around labor-capital conflicts, financial instability, and creative destruction, while ensuring the principle of effective demand and stock-flow consistency. Economic dynamics is viewed as demand-driven and profit-regulated.
Such dynamic complexity[ii]is not unknowable. A classic example of describing macro dynamics with simple ordinary differential equations is the Lorenz attractor. In heterodox economics, the Goodwin tradition exemplifies this academic endeavor, with one of its successors[iii]being the Bielefeld School centered around Peter Flaschel and Carl Chiarella. Their KMG[iv](Keynes-Metzler-Goodwin) model is a starting point to the Metzler-Goodwin-Minsky synthesis.
The affinity of this framework with the Post-Keynesian economics is evident[v]. However, the Bielefeld School fails to achieve complete Post-Keynesian closures[vi]in KMG models, especially regarding the money creation process. For private credit, while they recognize the necessity of endogenous mechanisms of money creation, they choose the wrong closure by assuming deposits create loans[vii]; for public money, they set up a budget constraint where government spending is financed by taxes and public debts, but fail to point out that this is a politically constructed constraint in history, which aims to limit the capacity of omnipotent government to strengthen security that might threaten the reproduction of social inequality.
Therefore, it is necessary to further attempt to achieve complete Post-Keynesian closures in the KMG model, which would simultaneously advance the development of Post-Keynesian nonlinear dynamic modeling. Using a metaphor of geometry, mainstream economics studies artificially smoothed triangles, while nonlinear economic dynamics seeks to understand the rough Sierpiński triangle.
[i] Chiarella, C, Flaschel, P & Semmler, W 2012, Reconstructing Keynesian Macroeconomics Volume 1: Partial perspectives 1st edn, Routledge, Oxford.
[ii] Velupillai, KV 2012, ‘NON-LINEAR DYNAMICS, COMPLEXITY AND RANDOMNESS: ALGORITHMIC FOUNDATIONS’, in Nonlinearity, Complexity and Randomness in Economics, Wiley, United Kingdom, pp. 151–171.
[iii] Flaschel, P 2015, ‘Goodwin’s MKS system: a baseline macro model’, Cambridge journal of economics, vol. 39, no. 6, pp. 1591–1605.
[iv] Chiarella, C, Flaschel, P & Semmler, W 2013, ‘Integrating Macromodels of Employment, Price and Inventory Dynamics’, in Reconstructing Keynesian Macroeconomics Volume 2, Routledge, pp. 243–274.
[v] Rosser, JB & Rosser, MV 2023, ‘The Bielefeld School of economics, Post Keynesian economics, and dynamic complexity’, Journal of economic behavior & organization, vol. 212, pp. 454–465.
[vi] Caverzasi, E & Godin, A 2015, ‘Post-Keynesian stock-flow-consistent modelling: a survey’, Cambridge journal of economics, vol. 39, no. 1, pp. 157–187.
[vii] Charpe, M, Chiarella, C, Flaschel, P & Semmler, W 2011, ‘Bankruptcy of firms, debt default and the performance of banks’, in Financial Assets, Debt and Liquidity Crises, Cambridge University Press, pp. 307–353.
