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Tuesday, November 14, 2017

"An Introduction to SFC Models Using Python" Paperback Edition Published

My latest book: An Introduction to SFC Models Using Python is now available as a paperback edition. It is currently available at (some) Amazon book stores, and will show up at other online booksellers (such as Barnes and Noble) over the coming days. Many bookstores would be able to find the book via a special order.

Book Description

Stock-Flow Consistent (SFC) models are a preferred way to present economic models in the post-Keynesian tradition. This book gives an overview of the sfc_models package, which implements SFC models in Python. The approach is novel, in that the user only specifies the high-level parameters of the economic model, and the framework generates and solves the implied equations. The framework is open source, and is aimed at both researchers and those with less experience with economic models. This book explains to researchers how to extend the sfc_models framework to implement advanced models. For those who are new to SFC models, the book explains some of the basic principles behind these models, and it is possible for the reader to run example code (which is packaged with the software online) to examine the model output.

Paperback ISBN: 978-0-9947480-9-6
The book is 128 pages (excluding end matter).

The book contains some figures, and sample code. The code is available online, as the sfc_models Python package.

Recommended retail price: $11.95 (USD), GBP 8.49, EUR 10.45 (excluding VAT).

Intended Audience

This book is quite technical, as it mainly describes the Python programming framework. There are some sections describing how SFC models operate, which largely appeared in draft form already on my website. It is mainly aimed at economists who would want to start working with the sfc_models framework to build stock-flow consistent models, or programmers who are interested in learning about SFC models. More casual readers will hopefully find sections of interest, although some of the material would be too technical. It is possible to run the example programs without much programming experience, but it would require installing the software. (Since the Python installation process varies depending upon the operating system, the reader is largely directed to online resources for the exact steps.)

Ebook Editions Delayed

Unfortunately, the ebook editions have some formatting issues that I have been unable to fix right now. I thought they were ready (which is why I pulled the trigger on the paperback edition), but I discovered a fairly small (but vital) problem in the formatting of the Python code in the ebook version. I hope that I will fix the ebook edition by the weekend, but I am not making any promises. Although it is more expensive, the paperback edition has a fixed page layout which handles the code formatting relatively faithfully. For readers who are new to Python, the paperback edition is probably the preferred edition, since it gives a better idea of the layout of Python code. (Python is an unusual computer language in that the the white space -- code indentation -- matters.) Experienced Python programmers would spot the formatting issues, and know not to format their own code that way.

If I cannot resolve the issue easily, I may be forced to sell the ebook as a fixed page layout on Kindle, a format that may not be supported by older readers. For other retailers, I would need to use a PDF version (or fixed format EPUB) which is generally not supported.

I will put out a longer description of the book once I get a better handle on when the ebook editions will be ready for sale. Since the paperback edition is already for sale, I just wanted to put this announcement up.

(c) Brian Romanchuk 2017


  1. Congratulations! Found it on Amazon UK!

    1. Thanks. It was entertaining seeing a "used" copy being offered for sale in Canada on the day of publication on

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  4. Replies
    1. Sorry, I think this and another comment got held up in my spambox.

      No plans for a book on R; my SFC model work is highly object-oriented, and I am not good with object-oriented programming in R. The final models could be exported to R, but that was a project that is way back on my “TO DO” list.

      I do my time series analysis in R, but frankly, my R code is in pretty terrible shape. I might do a book on research system design, and my R code may mainly be used as an example of how not to do things...


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