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Non-equilibrium economics

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Non-equilibrium economics or out-of-equilibrium economics is a branch of economic theory that examines the behavior of economic agents and markets in situations where traditional approaches of economic equilibrium do not hold.

Overview

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Economic models in the tradition of partial or general equilibrium theory rely on the notion of economic equilibrium: because of quick price adaptation to an equilibrium price, supply equals demand and markets clear. Equilibrium theory goes back to the contributions by Léon Walras in 1874 and constitutes the core of dynamic stochastic general equilibrium models (DSGE), the current predominant framework of macroeconomic analysis. The goal to study the dynamics that may or may not lead to an equilibrium was already formulated by the developers of general equilibrium models such as Vilfredo Pareto, but despite some efforts, they were unable to describe the adaptive processes that were thought to converge to the states analyzed in static theory.[1][2][3][4][5] Research in the tradition of Disequilibrium macroeconomics which was influential in the 1970s departed from some equilibrium assumptions such as market clearing and quick price adaption, studying markets with fixed prices, leading to models of “non-Walrasian” equilibrium with rationing, but not to a genuine out-of-equilibrium dynamic analysis.[6][7][8]

In contrast, non-equilibrium economics focuses on the dynamics of economic systems in states of flux, where imbalances, frictions, and external shocks can lead to persistent deviations from equilibrium or to multiple equilibria. This approach is used to study phenomena such as market crashes, economic crises, and the effects of policy interventions. By using approaches from complex systems, behavioral economics, and non-linear dynamics, out-of-equilibrium economics emphasizes the importance of time, uncertainty, bounded rationality and the role of institutions in shaping economic outcomes. It was developed starting in the 1980s with the spread of computational economics and is used in the fields of evolutionary and institutional economics, Post Keynesian economics, Austrian economics, Ecological economics, development and growth economics.[7][9]

Model approaches

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Agent-based computational economics

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Agent-based computational economics studies economic processes as dynamic systems of interacting, bounded rational agents that usually follow some discrete decision sequence. Falling in the paradigms of complex adaptive systems and complexity economics, it analyzes the emergence of either a (statistical) equilibrium, but also discontinuities, tipping points, lock-ins or path dependencies. Different coordinating mechanisms such as price adaptation, auctions, matching or quantity rationing are implemented.[9][10][11][12]

Circular Cumulative Causation

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Circular cumulative causation is an economic concept developed by Gunnar Myrdal that describes a self-reinforcing process where initial changes in economic variables lead to further changes, creating a feedback loop that can amplify economic trends. By emphasizing the interconnectedness of economic activities, it tries to gains insights into issues like regional development, inequality, and the persistence of economic disparities.[13][14]

Constrained Dynamics

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Edgeworth box model with slow tatonnement, converging to a stationary state that differs from the usual equilibrium value because of false trading[2]

Constrained dynamics models the economy as interacting, bounded rational agents that try to adjust the economic variables to improve their situation (hill climbing as opposed to utility maximization). Economic constraints such as the budget constraints or accounting identities are guaranteed by concepts similar to constraints in Lagrangian mechanics.[2][5][15]

Evolutionary Game Theory

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Evolutionary game theory studies the strategic interactions of boundedly rational players, focusing both on the dynamic paths to reach equilibrium and the evolutionary stable equilibrium. Modeling concepts include differential equations, stochastic processes, graphs and evolutionary algorithms.[16][17][18]

Stock-Flow Consistent models

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A stability analysis shows the parameter ranges in which an SFC model is stable or unstable.[19]

Stock-flow consistent models (SFC) models are a class of economic models that ensure coherence between stocks and flows in an economy, emphasizing the relationships between different sectors and their balance sheets, while maintaining consistency in accounting identities. Rejecting the classical dichotomy, they model the dynamic adaptation processes of real and financial variables for studying macroeconomic phenomena such as the effects of fiscal policy, financial instability, and the interactions between different economic agents.[20][21][22][23]

Statistical Mechanics

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The use of statistical mechanics in economics involves applying concepts and methods from physics to analyze and model complex economic systems, particularly those characterized by a large number of interacting agents. This approach allows economists to study emergent phenomena, such as market behavior and collective decision-making, by treating economic agents as particles in a statistical ensemble, thereby uncovering patterns, networks and distributions that arise from individual actions.[24][25][26]

References

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  1. ^ McLure, Michael; Samuels, Warren J. (2001). Pareto, economics and society the mechanical analogy. London: Routledge.
  2. ^ a b c Glötzl, Erhard; Glötzl, Florentin; Richters, Oliver (2019). "From constrained optimization to constrained dynamics: extending analogies between economics and mechanics". Journal of Economic Interaction and Coordination. 14: 623–642. doi:10.1007/s11403-019-00252-7. hdl:10419/171974.
  3. ^ Donzelli, Franco (1997). "Pareto's Mechanical Dream". History of Economic Ideas. 5 (3): 127–178. JSTOR 23722580.
  4. ^ Leijonhufvud, Axel (2006). "Episodes in a century of macroeconomics". In Colander, David C. (ed.). Post Walrasian Macroeconomics: Beyond the Dynamic Stochastic General Equilibrium Model. Cambridge University Press. pp. 27–45. doi:10.1017/CBO9780511617751.003.
  5. ^ a b Richters, Oliver (2021). "Modeling the out-of-equilibrium dynamics of bounded rationality and economic constraints". Journal of Economic Behavior and Organization. 188: 846–866. arXiv:2106.00483. doi:10.1016/j.jebo.2021.06.005.
  6. ^ Backhouse, Roger; Boianovsky, Mauro (2012). Transforming modern macroeconomics : exploring disequilibrium microfoundations, 1956–2003. New York: Cambridge University Press. ISBN 978-1-107-02319-2.
  7. ^ a b Katzner, Donald W. (2003). "Equilibrium and Non-equilibrium". In King, J.E. (ed.). The Elgar Companion to Post Keynesian Economics. Cheltenham, UK: Edward Elgar. pp. 126–131.
  8. ^ Dixon, Huw (1990). "Equilibrium and explanation". In Creedy, John (ed.). Foundations of economic thought. Oxford: Basil Blackwell. pp. 356–394.
  9. ^ a b Arther, W. Brian (2006). "Out-of-Equilibrium Economics and Agent-Based Modeling". Handbook of Computational Economics. Vol. 2. pp. 1551–1564.
  10. ^ Ballot, G.; Mandel, A.; Vignes, A. (2015). "Agent-based modeling and economic theory: where do we stand?". Journal of Economic Interaction and Coordination. 10: 1–23. doi:10.1007/s11403-014-0132-6.
  11. ^ Kirman, Alan (2010). "The economic crisis is a crisis for economic theory". CESifo Economic Studies. 56 (4): 498–535. doi:10.1093/cesifo/ifq017.
  12. ^ Arthur, W. Brian (2010). "Complexity, the Santa Fe Approach, and Non-Equilibrium Economics". History of economic ideas. XVIII (2).
  13. ^ Berger, Sebastian (2009). The Foundations of Non-Equilibrium Economics: The Principle of Circular Cumulative Causation. Routledge.
  14. ^ O'Hara, Phillip Anthony (2008). "Principle of circular and cumulative causation: fusing Myrdalian and Kaldorian growth and development dynamics". Journal of Economic Issues. 42: 375–387. doi:10.1080/00213624.2008.11507146. hdl:20.500.11937/30137.
  15. ^ Estola, Matti (2017). Newtonian Microeconomics. A Dynamic Extension to Neoclassical Micro Theory. Cham: Palgrave Macmillan. doi:10.1007/978-3-319-46879-2.
  16. ^ Michihiro, Kandori (1997). "Evolutionary game theory in economics". In Kreps, David M.; Wallis, Kenneth F. (eds.). Advances in Economics and Econometrics : Theory and Applications. Vol. 1. Cambridge University Press. pp. 243–277. ISBN 0-521-58983-5.
  17. ^ Hofbauer, J.; Sigmund, K. (1998). Evolution games and population dynamics. Cambridge: Cambridge University Press.
  18. ^ Safarzyńska, Karolina; van den Bergh, Jeroen C. J. M. (2010). "Evolutionary models in economics: a survey of methods and building blocks". Journal of Evolutionary Economics. 20: 329–373. doi:10.1007/s00191-009-0153-9.
  19. ^ Berg, Matthew; Hartley, Brian; Richters, Oliver (2015). "A Stock-Flow Consistent Input-Output Model with Applications to Energy Price Shocks, Interest Rates, and Heat Emissions". New Journal of Physics. 17 (1): 015011. doi:10.1088/1367-2630/17/1/015011.
  20. ^ Godley, Wynne; Lavoie, Marc (2012). Monetary Economics. An Integrated Approach to Credit, Money, Income, Production and Wealth. New York: Palgrave Macmillan. ISBN 978-0-230-30184-9.
  21. ^ Richters, Oliver; Glötzl, Erhard (2020). "Modeling economic forces, power relations, and stock-flow consistency: a general constrained dynamics approach". Journal of Post Keynesian Economics. 43 (2). doi:10.1080/01603477.2020.1713008. hdl:10419/178651..
  22. ^ Caverzasi, Eugenio; Godin, Antoine (2015). "Post-Keynesian stock-flow-consistent modelling: a survey". Cambridge Journal of Economics. 39 (1): 157–187. doi:10.1093/cje/beu021.
  23. ^ Carnevali, Emilio; Deleidi, Matteo; Pariboni, Riccardo; Veronese Passarella, Marco (2019). "Stock-Flow Consistent Dynamic Models: Features, Limitations and Developments". In Arestis, Philip; Sawyer, Malcolm (eds.). Frontiers of Heterodox Macroeconomics. Cham: Palgrave Macmillan. pp. 223–276. doi:10.1007/978-3-030-23929-9_6.
  24. ^ Kusmartsev, F. V. (2011). "Statistical mechanics of economics I". Physics Letters A. 375 (6): 966–973. doi:10.1016/j.physleta.2011.01.003.
  25. ^ De Martino, Andrea; Marsili, Matteo (2006). "Statistical mechanics of socio-economic systems with heterogeneous agents". Journal of Physics A. 39 (43). arXiv:physics/0606107. doi:10.1088/0305-4470/39/43/R01.
  26. ^ Scharfenaker, Ellis. "Statistical Equilibrium methods in analytical political economy". Journal of Economic Surveys. 36 (2): 276–309. doi:10.1111/joes.12403. hdl:10419/261019.
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