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title: Macroeconomics of the Credit Commons

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# Macroeconomics of the Credit Commons

[This paper](https://eprints.soton.ac.uk/36569/1/KK_97_Disaggregated_Credit.pdf) equates the money supply with bank credit, and disaggregrating that issued for 'real' economic activity from that issued for 'financial' economic activity finds that modifying the associated metrics from the quantity of money theory accordingly results in a good fit to empirical data from various episodes in the Japanese economy that had previously been considered anomalies. In other words, the [equation of exchange](https://en.wikipedia.org/wiki/Equation_of_exchange) holds in each of these domains but only when their measures of price, money supply etc. are separated, and the [credit creation theory of money](https://www.sciencedirect.com/science/article/pii/S1057521915001477#bbb0820) is used. Assuming a mutual credit economy will be dominated by real activity comprising goods and services rather than financial shenanigans (or at least that they would be easy to distinguish), this offers reason to believe that certain tools from traditional macroeconomics will have some validity in this context.

See also [here](https://www.nbp.pl/badania/seminaria/28ix2018-5.pdf). If a reliable macroeconomics of the Credit Commons can be developed, it will clearly have consequences for governance; to take one example from page 12: 'The  central  banks  of  Japan,  Taiwan,  Korea  and  China  all  adopted  policies  of  bank  credit  guidance  during  their  high  growth  phases,  whereby  the central bank limited or banned bank credit creation for consumption (which would tend to produce consumer price inflation) and bank credit for  non-GDP  (financial)  transactions  (which  would  produce  asset  price  inflation  and  financial  instability),  while  directing  credit  to  productive  purposes (investment in the production of goods and services and the im-plementation  of  new  technologies  and  productivity-enhancement  measures).' This implies that starting with business-to-business trade is eminently sensible if we want to see rapid growth of the credit commons, but also that governance agreements (corresponding in part to the roel of central banks?) may also include clauses banning the use of mutual credit for complex finance or consumption, at least in the initial stages. The German system of small, local co-operative banks (Sparkasse) is also held up (page 26) as providing resilience against financial crises - anyone want to mine German banking law for governance inspiration? There is also a brief discussion of mutual credit on page 16.

[Blog post](https://economicsfromthetopdown.com/2019/05/15/the-growth-of-hierarchy-and-the-death-of-the-free-market/) on how hierarchies and management grow with increasing per capita energy use. See also [here](https://economicsfromthetopdown.com/2019/05/07/energy-and-the-size-distribution-of-firms/).


[Lietaer (2009)](https://www.researchgate.net/publication/222401950_Quantifying_sustainability_Resilience_efficiency_and_the_return_of_information_theory): Quantifying sustainability: Resilience, efficiency and the return of information theory

## Articles about WIR Bank and IRTA

* [Stodder (2000)](https://www.complementarycurrency.org/ccLibrary/reciprocal_exchange_networks-Stodder.pdf): Reciprocal exchange networks: implications for macroeconomic stability
* [Stodder (2009)](http://jimstodder.com/BE/WIR_Update.pdf): Complementary Credit Networks and Macro-Economic Stability: Switzerland’s Wirtschaftsring
* [Stodder (2016)](https://www.researchgate.net/publication/305336318_The_Macro-Stability_of_Swiss_WIR-Bank_Credits_Balance_Velocity_and_Leverage): The Macro-Stability of Swiss WIR-Bank Spending: Balance, Velocity and Leverage
* [Healey (1996)](https://www.researchgate.net/publication/248441147_Why_is_corporate_barter): Why is Corporate Barter?

## Articles about complexity economics approaches
* [Natural chaos in the markets](https://physicsoffinance.blogspot.com/2011/07/natural-chaos-in-markets.html) - 'Here we're dealing in general with systems made of people driven by thoughts and emotions and interactions with other people. We surely don't know with perfection the laws of behavior of these people -- we have a few crude rules offering guidance to how they sometimes behave or might behave. Humans being among the most complex things in the universe, we should surely expect these systems to present a much richer set of possibilities than a simple plasma. Indeed, we know that markets and other economic systems, historically, have routinely acted in surprising ways and caused crises of many different kinds. Even so, theories in economics and finance have until very recently been centered almost entirely on the study of equilibrium systems, with positive feed backs rarely being considered.'
* [Power Laws in Economics and Finance](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1257822) - 'This article surveys well-documented empirical power laws concerning income and wealth, the size of cities and firms, stock market returns, trading volume, international trade, and executive pay.'
* [Complexity economics: a different framework for economic thought](http://tuvalu.santafe.edu/~wbarthur/Papers/Comp.Econ.SFI.pdf) - 'Complexity economics holds that the economy is not necessarily in equilibrium, that computation as well as mathematics is useful in economics, that increasing as well as diminishing returns may be present in an economic situation, and that the economy is not something given and existing but forms from a constantly developing set of institutions, arrangements, and technological innovations... It is a different way of seeing the economy. It gives a different view, one where actions and strategies constantly evolve, where time becomes important, where structures constantly form and re-form, where phenomena appear that are not visible to standard equilibrium analysis, and where a meso-layerbetween the micro and the macro becomes important. This view, in other words, gives us a world closer to that of political economy than to neoclassical theory, a world that is organic, evolutionary, and historically-contingent.' Medium article [here](https://medium.com/sfi-30-foundations-frontiers/economic-complexity-a-different-way-to-look-at-the-economy-eae5fa2341cd), more papers from the same author [here](http://tuvalu.santafe.edu/~wbarthur/selectedpapers.htm) and [here](http://tuvalu.santafe.edu/~wbarthur/Papers/).
* [System Dynamics: Systems Thinking and Modeling for a Complex World](https://dspace.mit.edu/handle/1721.1/102741)
* [The Emergence of Economic Organization](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=251291) - 'A model of decentralized markets is studied, in which transactors follow simple adaptive rules. Transactions are coordinated by specialist trading firms that bear the costs of market disequilibrium. Starting from an initially autarkic situation in which none of the institutions that support exchange exist, computer simulation shows that for a wide range of parameter values a fully developed market economy will emerge spontaneously. Moreover, in virtually every case where a market economy develops, one of the commodities traded will emerge as a universal medium of exchange, being traded by every firm and changing hands in every act of exchange.'
* [Detecting Causality in Complex Ecosystems](https://science.sciencemag.org/content/338/6106/496.abstract) - 'Identifying causal networks is important for effective policy and management recommendations on climate, epidemiology, financial regulation, and much else. We introduce a method, based on nonlinear state space reconstruction, that can distinguish causality from correlation. It extends to nonseparable weakly connected dynamic systems (cases not covered by the current Granger causality paradigm). The approach is illustrated both by simple models (where, in contrast to the real world, we know the underlying equations/relations and so can check the validity of our method) and by application to real ecological systems.'
* [Econophysics: Bridges over a turbulent current](https://www.sciencedirect.com/science/article/abs/pii/S1057521911000792)
* [Complex networks in finance](https://www.nature.com/collections/grmlkvrrkj) - 'The 2008 financial crisis has highlighted major limitations in the modelling of financial and economic systems. However, an emerging field of research at the frontiers of both physics and economics aims to provide a more fundamental understanding of economic networks, as well as practical insights for policymakers. In this Nature Physics Focus, physicists and economists consider the state-of-the-art in the application of network science to finance.'
* [The physics of financial networks](https://lims.ac.uk/paper/the-physics-of-financial-networks/) - 'Complex network theory unlocks systematic understanding of financial stability and climate finance in pursuit of a more sustainable society.'
* [Publications by Guido Caldarelli](https://scholar.google.com/citations?user=RZid9X8AAAAJ&hl=en)
* Agent-based modelling approaches:
    * [Cyclic game dynamics driven by iterated reasoning](https://pubmed.ncbi.nlm.nih.gov/23441191/) - 'Recent theories from complexity science argue that complex dynamics are ubiquitous in social and economic systems. These claims emerge from the analysis of individually simple agents whose collective behavior is surprisingly complicated. However, economists have argued that iterated reasoning--what you think I think you think--will suppress complex dynamics by stabilizing or accelerating convergence to Nash equilibrium. We report stable and efficient periodic behavior in human groups playing the Mod Game, a multi-player game similar to Rock-Paper-Scissors. The game rewards subjects for thinking exactly one step ahead of others in their group. Groups that play this game exhibit cycles that are inconsistent with any fixed-point solution concept... If higher-order reasoning can be complicit in complex emergent dynamics, then cyclic and chaotic patterns may be endogenous features of real-world social and economic systems.'
    * [Macroeconomics with Intelligent Autonomous Agents](https://www.brown.edu/Departments/Economics/Faculty/Peter_Howitt/publication/Autonomous.pdf) - '...agent based computational economics is a set of tech-niques for studying a complex adaptive system involving many interacting agents with ex-ogenously given behavioral rules. The idea motivating the approach is that complex systems,like economies or anthills, can exhibit behavioral patterns beyond what any of the individualagents in the system can comprehend. So instead of modelling the system as if everyone’s ac-tions and beliefs were coordinated in advance with everyone else’s, as in rational expectationstheory, the approach assumes simple behavioral rules and allows a coordinated equilibriumto be a possibly emergent property of the system itself. The approach is used to explainsystem behavior by “growing” it in the computer. Once one has devised a computer pro-gram that mimics the desired characteristics of the system in question one can then use theprogram as a “culture dish” in which to perform experiments.'
    * [Macroeconomics in a self-organizing economy](https://www.brown.edu/Departments/Economics/Faculty/Peter_Howitt/publication/OFCE_final.pdf) - 'This paper emphasizes the importance of considering the mechanisms that coor-dinate economic transactions in a decentralized economy, namely the role played bya  self-organizing  network  of  entrepreneurial  trading  firms,  for  theories  aimed  atguiding macroeconomic policy. We review a research program that aims to unders-tand how, and how well, trading activities are coordinated in various circumstancesby employing agent-based computational (ACE) models of stylized economies wherethese activities take place in a self-organizing network of markets created and operatedby profit-seeking business firms.'
    * [Agent-based Financial Markets:  Matching Stylized Facts with Style](http://people.brandeis.edu/%7Eblebaron/wps/style.pdf) - 'Empirical facts from financial data pose some of the most difficult puzzles for equilibrium macroeco-nomic modeling. Features such as volatility, excess kurtosis, and conditional heteroscedasticity are noteasily replicated by any single representative agent model. Most agent-based financial markets are ableto match a good subset of these features quite easily. This paper will summarize some of the results froman agent-based model. It will be argued that agent-based approaches also make more sense economicallythen their representative agent competition. They will also be compared and contrasted with approachescoming from the behavioral finance perspective as well.'
    * [Foreword to The Minority Game](http://tuvalu.santafe.edu/~wbarthur/Papers/MinorityGameForeword.pdf)
    * [The Minority Game: an introductory guide](http://estebanmoro.org/post/2004-08-31-the-minority-game-an-introductory-guide/) - 'The Minority Game is a simple model for the collective behavior of agents in an idealized situation where they have to compete through adaptation for a finite resource. This review summarizes the statistical mechanics community efforts to clear up and understand the behavior of this model. Our emphasis is on trying to derive the underlying effective equations which govern the dynamics of the original Minority Game, and on making an interpretation of the results from the point of view of the statistical mechanics of disordered systems.'
    * [Anomalous fluctuations in Minority Games and related multi-agent models of financial markets](https://arxiv.org/abs/physics/0608091) - 'We review the recent approaches to modelling financial markets based on multi-agent systems. After a brief summary of the basic stylised facts observed in real-market time-series we discuss some simple agent-based systems which are currently used to model financial markets. One of the most prominent examples is here the Minority Game (MG), which we address in some more detail. After a brief discussion of its basic setup and general phenomenology we summarise the main findings of the statistical mechanics analysis and discuss the emergence of stylised facts in extensions of the MG near their phase transitions between efficient and predictable regimes. We then turn towards more realistic variants which comprise heterogeneous populations of agents, with different memory capabilities, different inclinations to trade and varying expectations on the future evolution of the market. Finally we give a short outlook on potential future work in this area.'
    * [The El Farol Bar Problem Revisited: Reinforcement Learning in aPotential Game](https://www.research.ed.ac.uk/portal/files/20037196/The_El_Farol_Bar_Problem_Revisited.pdf) - 'We revisit the El Farol bar problem developed by Brian W. Arthur(1994) to investigate how one might best model bounded rationality ineconomics. We begin by modelling the El Farol bar problem as a marketentry game and describing its Nash equilibria. Then, assuming agents areboundedly rational in accordance with a reinforcement learning model, weanalyse long-run behaviour in the repeated game. We then state our mainresult. In a single population of individuals playing the El Farol game,learning theory predicts that the population is eventually subdivided intotwo distinct groups: those who invariably go to the bar and those whoalmost never do. In doing so we demonstrate that learning theory predictssorting in the El Farol bar problem.'
    * [Why Bounded Rationality?](http://www.academicroom.com/article/why-bounded-rationality)
    * [Complex dynamics in learning complicated games](https://arxiv.org/PS_cache/arxiv/pdf/1109/1109.4250v1.pdf) - 'Game theory is the standard tool used to model strategic interactions in evolutionary biology andsocial science. Traditional game theory studies the equilibria of simple games. But is traditional game theory applicable if the game is complicated, and if not, what is? We investigate this question here, defining a complicated game as one with many possible moves, and therefore many possible payoffs conditional on those moves. We investigate two-person games in which the players learnbased on experience. By generating games at random we show that under some circumstances the strategies of the two players converge to fixed points, but under others they follow limit cycles or chaotic attractors. The dimension of the chaotic attractors can be very high, implying that the dynamics of the strategies are effectively random. In the chaotic regime the payoffs fluctuate intermittently, showing bursts of rapid change punctuated by periods of quiescence, similar to what is observed in fluid turbulence and financial markets. Our results suggest that such intermittency is a highly generic phenomenon, and that there is a large parameter regime for which complicated strategic interactions generate inherently unpredictable behavior that is best described in the language of dynamical systems theory.'
    * [Agent-based Computational Economics (ACE)](http://www2.econ.iastate.edu/tesfatsi/ace.htm)
    * [ACE Research Area: Agent-Based Macroeconomics](http://www2.econ.iastate.edu/tesfatsi/amulmark.htm)
    * [A Real Minsky Moment in an Artificial Stock Market](http://people - 'Many authors have contributed to the idea that financial markets are dynamically unstable. Much of this line of thinking suggests that bubbles and crashes will be a generic feature of most any speculative market, and that removing them would be difficult, if not impossible. Hyman Minsky is probably the one of the earlier contributors to this area, and recently his work has been looked at with new respect. This paper shows that some of his basic thinking about risk and extreme portfolio positions hold in agent-based financial markets in a way that appears close to his thinking. The advantage of this is that it presents a fully operational computer generated model with testable Minsky like effects which can be used to connect our understanding of Minsky to more modern, and rigorous approaches to macroeconomics.'
    * [Generating Fraud: Agent Based Financial Network Modeling](https://ccl.northwestern.edu/2005/Generating_Fraud_Agent_Based_Financial_N.pdf) - '... an application of agent based modeling to create financial network data... the dataset we are trying to emulate is large and sparsely connected... it includes multiple types of entities and relationships. A system made up of multiple types of entities with various relationships is tailor made for agent based modeling... this dataset is being created as part of a larger project that is creating graph analysis tools that will work with massive, dynamic datasets. Therefore, it is important that we be able to control what the generated dataset contains so we can test various parts of our graph analysis system. An initial agent based model has been created using Netlogo. This prototype is being created iteratively as we continue to investigate the patterns and other features within the actual dataset.'
    * [NetLogo artificial financial market](http://ccl.northwestern.edu/netlogo/models/community/Artificial%20Financial%20Market) - ' This is a model of an artificial financial market with heterogeneous boundedly rational agents that are influenced by the sentiment of their most close colleagues regarding the future evolution of the market. The model is capable of generating the stylized facts of the real financial markets, specifically: excess volatility in the logarithmic returns, clustered volatility (characteristic of the well known GARCH signatures), bubbles and crashes... Our model may also be of interest to areas outside of finance, areas like, for instance, the study of social influence, opinion making and political decision.'