SFC models in Python

Here is a letter from Kenn Tamara, who developed the models in Godley-Lavoie using Python:

I was reading “Monetary Economics” by Godley and Lavoie and came across the sfc-models.net website. I have taken your eViews models and reimplemented them using Python (running the experiments and generating the figures).

Everything is open-source and is written with a package that I developed to help specify and solve the models. The models are implemented as iPython notebooks for easier viewing and can be found at:

Information on the pysolve package used to specify and solve the models can be found at:

(A little warning, the code for pysolve is still under development and there isn’t that much documentation yet)

I hope that the python implementation is useful and would like to contribute it to sfc-models.net.

Thank you,
Kenn Takara

Interactive SFC models

I recently discovered that Kevin W. Capehart has written a piece of code in Mathematica from one of my Eviews files for the Godley – Lavoie Monetary economics book, and turned it into a CDF, to illustrate the paradox of thrift

To run the simulation you need to install the free Wolfram reader, and activate it.

This little tool is potentially very useful in exploring stock-flow models, which are tipically non linear, and therefore difficult to solve analitically. Creating a nice interface which allows the user to check model responses to different values of parameters and exogenous variables could help find the range of parameter values for which the model is producing stable (or unstable etc) solutions.

New papers using the SFC approach

Ayoze Alfageme kindly offered to update our references database on publications adopting the stock-flow-consistent approach.
The following is a preliminary list of recent papers, that will soon be included in our database:

Applied Macro-modelling: Fully Scalable models

Winter School on Agent Based and Stock Flow Consistent modelling.

Limerick, January 30th – February 7th

If you are a highly motivated student of economics at masters or Ph.D. level, or you are working with a research center or a public institution and want to spend one week studying, researching, discussing, and exchanging experiences in the nice atmosphere of an Irish University campus nurtured by international experts and fellow students from all around the world, our winter school offers you 7 working days of lectures, seminars, and labs on Stock-Flow Consistent and Agent Based approaches. For more information, see http://s120.ul.ie/drupal/winterSchool and Applied Macro-modelling – Call For Application.

SFC models discussed in Berlin

The annual conference of the Research Network Macroeconomic and Macroeconomic Policies in Berlin had two sessions dedicated to stock-flow models, plus other papers using this approach in other sessions.
The program is available here

Flow of funds at the ECB

This article, “Flow-of-funds analysis at the ECB”, provides an excellent technical description of the European system for flow-of-fund statistics, and some good examples of how they are used at the ECB.
I would recommend it for anyone interesed in anyone doing SFC empirical modeling. It is a pity that the authors have not discovered yet the work of Godley and the book Monetary economics, which is well known at the Bank of England.

Report of the Dijon Workshop

by Antoine Godin and Mauro Napoletano

A wide variety of approaches, methodologies and topics were presented during the first workshop, allowing for interesting discussions and exchanges. Clearly, the complementarities of the Stock-Flow Consistent and Agent-Based approaches emerged, even if some were skeptical at first. The influence of finance, fiscal austerity and the construction of the euro zone are at the heart of applied work from both approaches. Furthermore, the topics and issues addressed by papers from both methodologies are similar. On the methodology side, SFC and ABM practitioners share issues regarding estimation or the role of expectations.  On the first issue, the workshop has featured some presentations about methods that could be used to improve the matching between theory and data in both SFC and ABMs. An open issue there, and that could be developed in future workshop, is how far to go in the model calibration and estimation exercises. Indeed, both types of exercises impose strong restrictions on models (e.g. about the ergodicity of the dynamics) which could be limiting in terms of the ability of the model to catch salient features of the reality or that could be hard to detect into some models. Furthermore, the ABM literature has developed robustness checks and stability analysis that need to be further developed in SFC models. This highlights the interest of confronting the two approaches.

This workshop also showed us the importance of getting together and confronting our analysis and results. In particular, the workshop has highlighted the strong complementarities existing between ABM and SFC models. On one hand, SFC models have so far been developed as general aggregative models, i.e. as systems of stock-flow consistent equations describing the laws of motion of the economy at the aggregate level. On the other hand, ABMs provide explicit micro-foundations to macroeconomic relations that, in ABMs, are emergent properties of the disequilibrium interactions occurring among heterogeneous agents. However, the use of the stock-flow consistent approach in ABMs has so far been limited (few exceptions to this are represented by the models of Kinsella et al., 2012 and by Seppecher and Salle, 2012, Raberto et al. 2012). The use of the stock-flow consistent approach in ABMs could thus contribute to improve the rigor of the micro-foundations provided by these models. However, it could also help to micro-found many of the Keynesian dynamics emphasized by SFC models. This is important also because, as it was pointed out in the workshop, SFC models are particularly suitable to study the effects of imbalances at the aggregate level. However, by construction, they cannot study the factors underlying the emergence of those imbalances, such as for example the factors leading to bubble-and-burst dynamics in asset markets. Finally, we should mention the possibility of having some kind of mixed models where some sectors are agent based and others aggregated. Combining ABM and SFC allows thus to offer a wide variety of models with more or less complexity and different levels of aggregation, depending of the subject under scrutiny.


–       Stephen Kinsella & Matthias Greiff & Edward J Nell, 2011. “Income Distribution in a Stock-Flow Consistent Model with Education and Technological Change,” Eastern Economic Journal, Palgrave Macmillan, vol. 37(1), pages 134-149.

–       Raberto, Marco & Teglio, Andrea & Cincotti, Silvano, 2012. “Debt, deleveraging and business cycles: An agent-based perspective,” Economics – The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 6(27), pages 1-49.

–       Seppecher, Pascal & Isabelle Salle, 2012. “A Two-Sector Agent-Based Model: Empirical Validation and Prospects” Unpublished.